type of research strategy

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Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

• Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
• Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

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6 Research strategy

A research strategy introduces the main components of a research project such as the research topic area and focus, the research perspective (see Sections 1 and 2), the research design, and the research methods (these are discussed below). It refers to how you propose to answer the research questions set and how you will implement the methodology.

In the first part of this course, you started to identify your research topic, to develop your research statement and you thought about possible research question(s). While you might already have clear research questions or objectives, it is possible that, at this stage, you are uncertain about the most appropriate strategy to implement in order to address those questions. This section looks briefly at a few research strategies you are likely to adopt.

Figure 5 shows the four main types of research strategy: case study, qualitative interviews, quantitative survey and action-oriented research. It is likely that you will use one of the first three; you are less likely to use action-oriented research.

Here is what each of these strategies entails:

• Case Study : This focuses on an in-depth investigation of a single case (e.g. one organisation) or a small number of cases. In case study research generally, information is sought from different sources and through the use of different types of data such as observations, survey, interviews and analysis of documents. Data can be qualitative, quantitative or a mix of both. Case study research allows a composite and multifaceted investigation of the issue or problem.
• Qualitative interviews : There are different types of qualitative interviews (e.g. structured, semi-structured, unstructured) and this is the most widely used method for gathering data. Interviews allow access to rich information. They require extensive planning concerning the development of the structure, decisions about who to interview and how, whether to conduct individual or group interviews, and how to record and analyse them. Interviewees need a wide range of skills, including good social skills, listening skills and communication skills. Interviews are also time-consuming to conduct and they are prone to problems and biases that need to be minimised during the design stage.
• Quantitative survey : This is a widely used method in business research and allows access to significantly high numbers of participants. The availability of online sites enables the wide and cheap distribution of surveys and the organisation of the responses. Although the development of questions may appear easy, to develop a meaningful questionnaire that allows the answering of research questions is difficult. Questionnaires need to appeal to respondents, cannot be too long, too intrusive or too difficult to understand. They also need to measure accurately the issue under investigation. For these reasons it is also advisable, when possible, to use questionnaires that are available on the market and have already been thoroughly validated. This is highly recommended for projects such as the one you need to carry out for this course. When using questionnaires decisions have to be made about the size of the sample and whether and when this is representative of the whole population studied. Surveys can be administered to the whole population (census), for example to all employees of a specific organisation.
• Action-oriented research : This refers to practical business research which is directed towards a change or the production of recommendations for change. Action-oriented research is a participatory process which brings together theory and practice, action and reflection. The project is often carried out by insiders. This is because it is grounded in the need to actively involve participants in order for them to develop ownership of the project. After the project, participants will have to implement the change.

Action-oriented research is not exactly action research, even though they are both grounded in the same assumptions (e.g. to produce change). Action research is a highly complex approach to research, reflection and change which is not always achievable in practice (Cameron and Price, 2009). Furthermore action researchers have to be highly skilled and it is unlikely that for this specific project you will be involved in action research. For these reasons this overview focuses on the less pure action-oriented research strategy. If you are interested in exploring this strategy and action research further, you might want to read Chapter 14 of Cameron and Price (2009).

It is possible for you to choose a strategy that includes the use of secondary data. Secondary data is data that has been collected by other people (e.g. employee surveys, market research data, census). Using secondary data for your research project needs to be justified in that it meets the requirements of the research questions. The use of secondary data has obvious benefits in terms of saving money and time. However, it is important to ascertain the quality of the data and how it was collected; for example, data collected by government agencies would be good quality but it may not necessary meet the needs of your project.

It is important to note that there should be consistency between the perspective (subjective or objective) and the methodology employed. This means that the type of strategy adopted needs to be coherent and that its various elements need to fit in with each other, whether the research is grounded on primary or secondary data.

Now watch this video clip in which Dr Rebecca Hewett, Prof Mark Saunders, Prof Gillian Symon and Prof David Guest discuss the importance of setting the right research question, what strategy they adopted to come up with specific research questions for their projects, and how they refined these initial research questions to focus their research.

Make notes on how you might apply some of these strategies to develop your own research question.

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• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Basic Research Strategies for the Social Sciences: Research Methods

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Sage Research Methods Online (SRMO)

• SAGE Research Methods Online

Sage Research Methods Online (SRMO). SRMO provides access to information about research methods compiled from a variety of Sage publications, including books/handbooks, articles, and the “Little Green Book” series, Quantitative Applications in the Social Sciences .  SRMO is searchable and browsable by author, and it includes a methods map, as well as video tutorials.  Results can be refined to focus on specific academic disciplines of interest.

Great resource for learning more about what comprises a specific research method, with a view into how that method was applied within actual published scholarly literature.

• analysis of variance (ANOVA)
• ethnography
• focus groups
• mixed methods
• narrative analysis
• qualitative research
• quantitative data analysis
• social network analysis
• structural equation modeling
• time-series analysis
• visual representations
• ... and more

Research Methodologies

There are a variety of methods you can adopt for your research strategy, depending on your subject area or the outcome of your research.  Research methodology will differ depending on whether:

• you are doing an empirical study, using quantitative data or qualitative information, or mixed methods approach
• If you are seeking very current sources, or
• historical research
• critical analysis

Your strategies will be different as will the type of information sources you will seek and find.

See some databases below that offer examples of research methods, datasets or cases:

• Sage Research Methods: Data Visualization Video, text, and datasets to teach researchers the fundamentals of data visualization and design.
• Sage Research Methods: Foundations Introductory information about research methods and design.
• SAGE Research Methods Cases Teaching cases in which a variety of research methods are used in a number of social sciences subject areas. Cases are incorporated into SAGE Research Methods Online.
• SAGE Research Methods Datasets Datasets for teaching qualitative and quantitative research methods. Datasets are incorporated into SAGE Research Methods Online, and include sample sets, with a description of the research project and instructions regarding the method.
• SAGE Research Methods Online Information about research methods and design; includes Sage Datasets and Sage Cases, and the qualitative and quantitative methods series, "Little Green Books" and “Little Blue Books.”

Research Integrity

• SU - Office of Research and Integrity The Office of Research and Integrity provides administrative services to university researchers to facilitate research and ensure regulatory compliance with applicable federal regulations, laws and University policies, including administrative support and regulatory advisement to the University’s Institutional Review Board (IRB) and Institutional Animal Care and Use Committee (IACUC).

Qualitative Data Repository

Research methods for social sciences.

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How to formulate a research strategy?

A research strategy refers to a step-by-step plan of action that gives direction to the researcher’s thought process. It enables a researcher to conduct the research systematically and on schedule. The main purpose is to introduce the principal components of the study such as the research topic, areas, major focus, research design and finally the research methods.

An appropriate strategy has to be selected on the basis of the following:

• Research questions.
• Research objectives.
• Amount of time available.
• Resources at the researcher’s disposal.
• Philosophical underpinnings of the researcher.

Types of research strategies

Research strategy helps a researcher choose the right data collection and analysis procedure. Thus, it is of utmost importance to choose the right strategy while conducting the research. The following section will focus on the different types of strategies that can be used.

• Qualitative: This strategy is generally used when to understand the underlying reasons or the opinion of the people on certain facts or a problem. It does not involve numerical data. It provides insights into the research problem and hence helps in achieving the research objectives. Various methods that can be used include interviews, observations, open-ended surveys and focus group discussions.
• Quantitative: It involves the collection of primary or secondary data which is in numerical form. Under this strategy, the researcher can collect the data by using questionnaires, polls and surveys or through secondary sources. This strategy mainly focuses on when, where, what and how often a specific phenomenon occurs.
• Descriptive: This is generally used when the researcher wants to describe a particular situation. This involves observing and describing the behaviour patterns of either an individual, community or any group. One thing that distinguishes it from other forms of research strategies is that subjects are observed in a completely unchanged environment. Under this approach surveys, observations and case studies are mainly used to collect the data and to understand the specific set of variables.
• Analytical: This involves the use of already available information. Here the researcher in an attempt to understand the complex problem set, studies and analyses the available data. It majorly concerns the cause-and-effect relationship. The scientifically based problem-solving approaches mainly use this strategy.
• Action: This strategy aims at finding solutions to an immediate problem. It is generally applied by an agency, company or by government in order to address a particular problem and find possible solutions to it. For example, finding which strategy could best work out to motivate physically challenged students.
• Basic: According to this strategy no generalizations are made in order to understand the subject in a better and more precise way. Thus, it involves investigation and the analysis of a phenomenon. Although their findings are not directly applicable in the real world, they work towards enhancing the knowledge base.  
• Critical: It works towards analyzing the claims regarding a particular society. For example, a researcher can focus on any conclusion or theory made regarding a particular society or culture and test it empirically through a survey or experiment.  
• Interpretive: this strategy is similar to the qualitative research strategy. However, rather than using hypothesis testing, interpretation is done through the sense-making process. In simple terms, this strategy uses human experience in order to understand the phenomena.
• Exploratory: It is mainly used to gain insights into the problem or regarding certain situations but does work towards providing the solution to the research problem. This research strategy is generally undertaken when there is very little or no earlier study on the research topic.
• Predictive: It deals with developing an understanding of the future of the research problem and has its foundation based on probability. This is generally very popular among companies and organizations.

Difference between the types of research strategy

How to write a research strategy.

The main components of a research strategy include the research paradigm, research design, research method and sampling strategy. It should be in a form such that your research paradigm should guide your research design. Which in turn should lead to the appropriate selection of the research methods along with the correct sampling strategy. It is applicable to different kinds of research such as exploratory, explanatory and descriptive.

Step1: Defining the research paradigm

This involves a basic set of beliefs that guides the researcher regarding the way of performing the research. There are various types of research paradigms, including positivism, post-positivism or constructivism.

Step 2: Defining the research design

The research paradigm and the type of research mainly guide the choice of research design. For example, some researches that include experiments lean quantitative research design. On the other hand, exploratory research in social sciences often uses a qualitative research design. This must be done very carefully because the research design will eventually impact the choice of research method and sampling strategy.

Step 3: Defining research methods

This step helps the researcher to explain the potential methods that can be used for carrying out the research. The choice here also depends on the research paradigm and research design selected in the above steps. For example, if a researcher followed a constructivist paradigm using a qualitative research design, then the data collection method can be interviews, observation or focus group discussions.

Step 4: Defining the sampling strategy

This step involves specifying the population, sample size and sampling type for a study. In the population, the researcher defines the profile of respondents and justifies their suitability for the study. For defining the sample size , a specific formula can be applied.  Finally, there are many sampling types for a researcher to choose from.

Things to keep in mind while writing research strategies

As there exist different types of research strategies, for the researcher, order to embark according to the study needs he or must identify the three main questions in order to write an appropriate strategy.

Is it suitable for the research aim?

As shown in the figure above the first thing that needs to be kept in mind is that the strategy should be suitable with respect to the purpose of the study i.e. it should rather support the researcher in finding the answers to the research questions which are under the consideration.

For example, a case study may be considered the right choice when investigating the social relationship in some specific setting, while it might be probably inappropriate when it comes to measuring the attitude of a large population.

Feasibility as per available sources

The second point that needs to be considered, is that it should be feasible from the practical point of view. The researcher should formulate the strategy so that he or she had complete access to data sources. Also, some of the research strategies like action research which are generally highly time-consuming, thus the researcher must consider all these aspects while preparing the strategy.

Ethical considerations

Also, another point that needs to be considered, is that the researcher should ensure that the strategy chosen must be followed in a responsible way. For example, in social science research participants of the study should be allowed to remain anonymous.

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Types of research

Primary research  involves collecting original data for subsequent analysis. This could involve building prototypes, conducting experiments, or designing and carrying out surveys, focus groups, or interviews, for example.  Secondary research  is researching the ideas and contributions – the primary research – of others, usually by reading books and journal articles (sometimes known as literature review).  Quantitative research  involves analysis using statistical techniques with numerical data, while  qualitative research  involves analysis of more word-based, subjective data. The types of research that you will do as a student will depend on your course and the stage you are at in your studies.

Starting your research

Before you begin any piece of research, make sure that you have a clear understanding of:

• The  due date  for your research
• The  size  of the research (for example, the word count, if any)
• The  research question  that you are trying to answer or the  hypothesis  that you are testing
• The  scope  of the research (for example, what time span, countries, or age groups should be included? How much detail is required?)
• The  methodology  that you are expected to use (for example, are you conducting primary or secondary research? Will you conduct a literature review or a series of experiments?)
• Key  words and terms :Referring back to these will help you to stay focused. Use brainstorming or mind mapping techniques if you find them helpful.
• Key  theorists or publications :in most areas of research, there are a few ‘giants’ or milestone contributions. Make sure to consult and to reference these.

We live in an information-rich world, and you’re probably accustomed to using sophisticated information tools (like Google) to navigate day-to-day life, as well as for educational purposes. Having access to vast amounts of information about every conceivable subject at the touch of a button or click of a mouse can both help and hinder your academic research. The sheer volume of available information can be overwhelming at times.

Doing research at university will involve building on many skills that you already have. In particular, you will learn to approach information in a critical way, and to work with new types of information sources and new tools to discover, locate, absorb and use appropriate information.

Here are five key research strategies for ensuring that your research stays focused and relevant and is completed to a high standard. 

1.  Consult a wide variety of sources

 When you begin your research, cast a wide net in order to get a feel for the range and scope of your subject area. Google and Wikipedia can be useful starting points for getting a handle on your research topic, but you must exercise caution about the quality of the information that you gather from these sources.

Websites are not enough: most serious academic research requires consulting and referencing books and specialised academic journals. The majority of academic research is published in these forms. See the section on Reading and note-making   and our top-tips for academic reading  for more on using these resources. Your gateway to research published in books (or e-books) and academic journal articles is the Library catalogue, searchable via the Library’s homepage . Check out any of the discipline- or subject-specific Library Guides for short videos on how to find books and journal articles. You can also try Google’s special tool for discovering scholarly information, called Google Scholar .

Depending on the discipline, you may also need to find information in government reports and other publications, the popular press (newspapers and magazines), or think-tanks, for example. Much of this information is also available via the library catalogue. Again, see your discipline or subject-specific Library Guide for more information on the types of sources that you might find yourself using in your area of study. Aim for a rich and varied bibliography or list of references at the end of your research.

2.  Be patient and stay focused

Research is a slow and laborious process. A ‘rookie’ mistake is to alight on the first seemingly relevant piece of information that you find and to stop your search at that point. Use it – but keep looking. The direction of your research may change a number of times before you feel confident that you are on the right track.

During this process, you may be led down all sorts of interesting pathways, not all of which will be relevant to the question that you are trying to answer. Try to stay focused on your research question. It can be tricky to know when a line of inquiry is helpful for your research, and when it is a dead end – this is where your patience may be required. Remember that all of your research, whether relevant or not, will pay off in the end: the very act of deciding what is relevant and what is not will deepen your understanding of the topic at hand.

3.  Use your critical thinking skills

This includes: being able to think in a very broad sense about the topic that you’re working on; identifying, analysing, and thinking creatively about key words, concepts and connections; and then assessing and adjusting your search results accordingly. When you find something that you think might be useful for your research, critically evaluate the information at hand. Consider the reliability of the information, and its relevance to your research question. Consider also whether you agree or disagree with any conclusions reached, and why. See the Critical thinking section of the Academic Skills Hub for more on this topic.

 4.  Be objective and keep an open mind

Academic research should strive to be as objective as possible. We all carry preconceptions, prejudices and value systems, whether we are aware of them or not, but we should try not to let these dominate the direction of our research. If you start your research with a clear idea of what you will conclude, it’s unlikely that you are conducting good research. Consider both (or more) sides of the issue, before you attempt to offer a conclusion, opinion or recommendation. Any opinion that you do set out must be based on the available evidence.

Be particularly careful not only to present research that fits your perception of a topic; you must remain open to other points of view. Be aware also of your ‘filter bubble’ – sophisticated search engines and algorithms can ‘screen out’ content that, based on your previous online activities, you are less likely to be interested in, agree with, or like. Filter bubbles are dangerous because they present a version of the world to us that is dependent on our personal preferences. See this video for more on the topic of filter bubbles:

5.  Keep track of your information sources

This is essential: keeping a record of your research will help you to save time when putting together your bibliography or references list, and to avoid issues of plagiarism. Be sure to take note of all necessary bibliographic information from any source from which you’ve taken notes and that you think you might use as a source in an assignment. See this g uide to managing your references for more.

There are a number of reference management software programmes available, such as Endnote and Mendeley; you may find it useful to start using one of these to keep track of your information sources and to save time. See the Referencing/Citation tab in this Library guide on academic integrity for more information on referencing and citation management software.

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Writing a Research Strategy

This page is focused on providing practical tips and suggestions for preparing The Research Strategy, the primary component of an application's Research Plan along with the Specific Aims. The guidance on this page is primarily geared towards an R01-style application, however, much of it is useful for other grant types as well.

Developing the Research Strategy

The primary audience for your application is your peer review group. When writing your Research Strategy, your goal is to present a well-organized, visually appealing, and readable description of your proposed project and the rationale for pursuing it. Your writing should be streamlined and organized so your reviewers can readily grasp the information. If it's a key point, repeat it, then repeat it again. Add more emphasis by putting the text in bold , or bold italics . If writing is not your forte, get help.  For more information, please visit  W riting For Reviewers .

How to Organize the Research Strategy Section

How to organize a Research Strategy is largely up to the applicant. Start by following the NIH application instructions and guidelines for formatting attachments such as the research plan section.

It is generally structured as follows:

Significance

For  Preliminary Studies (for new applications) or a Progress Report (for renewal and revision applications).

• You can either include preliminary studies or progress report information as a subsection of Approach or integrate it into any or all of the three main sections.
• If you do the latter, be sure to mark the information clearly, for example, with a bold subhead.

 Helpful tips to consider when formatting:

• Organize using bold headers or an outline or numbering system—or both—that are used consistently throughout.
• Start each section with the appropriate header: Significance, Innovation, or Approach.
• Organize the Approach section around the Specific Aims.

For most applications, you need to address Rigor ous Study Design  by describing the experimental design and methods you propose and how they will achieve robust and unbiased results. See the NIH guidance for elaboration on the 4 major areas of rigor and transparency emphasized in grant review.  These requirements apply to research grant, career development, fellowship, and training applications.

Tips for Drafting Sections of the Research Strategy

Although you will emphasize your project's significance throughout the application, the Significance section should give the most details. The farther removed your reviewers are from your field, the more information you'll need to provide on basic biology, importance of the area, research opportunities, and new findings. Reviewing the potentially relevant study section rosters may give you some ideas as to general reviewer expertise. You will also need to describe the prior and preliminary studies that provide a strong scientific rationale for pursuing the proposed studies, emphasizing the strengths and weaknesses in the rigor and transparency of these key studies.

This section gives you the chance to explain how your application is conceptually and/or technically innovative. Some examples as to how you might do this could include but not limited to:

• Demonstrate the proposed research is new and unique, e.g., explores new scientific avenues, has a novel hypothesis, will create new knowledge.
• Explain how the proposed work can refine, improve, or propose a new application of an existing concept or method.

If your proposal is paradigm-shifting or challenges commonly held beliefs, be sure that you include sufficient evidence in your preliminary data to convince reviewers, including strong rationale, data supporting the approach, and clear feasibility. Your job is to make the reviewers feel confident that the risk is worth taking.

For projects predominantly focused on innovation and outside-the-box research, investigators may wish to consider mechanisms other than R01s for example (e.g., exploratory/developmental research (R21) grants, NIH Director's Pioneer Award Program (DP1), and NIH Director's New Innovator Award Program (DP2).

The Approach section is where the experimental design is described. Expect your assigned reviewers to scrutinize your approach: they will want to know what you plan to do, how you plan to do it, and whether you can do it. NIH data show that of the peer review criteria, approach has the highest correlation with the overall impact score. Importantly, elements of rigorous study design should be addressed in this section, such as plans for minimization of bias (e.g. methods for blinding and treatment randomization) and consideration of relevant biological variables. Likewise, be sure to lay out a plan for alternative experiments and approaches in case you get uninterpretable or surprising results, and also consider limitations of the study and alternative interpretations. Point out any procedures, situations, or materials that may be hazardous to personnel and precautions to be exercised. A full discussion on the use of select agents should appear in the Select Agent Research attachment .  Consider including a timeline demonstrating anticipated completion of the Aims. 

Here are some pointers to consider when organizing your Approach section:

• Enter a bold header for each Specific Aim.
• Under each aim, describe the experiments.
• If you get result X, you will follow pathway X; if you get result Y, you will follow pathway Y.
• Consider illustrating this with a flowchart.

Preliminary Studies

If submitting a new application to a NOFO that allows preliminary data, it is strongly encouraged to include preliminary studies.  Preliminary studies demonstrate competency in the methods and interpretation. Well-designed and robust preliminary studies also serve to provide a strong scientific rationale for the proposed follow-up experiments. Reviewers also use preliminary studies together with the biosketches to assess the investigator review criterion, which reflects the competence of the research team. Provide alternative interpretations to your data to show reviewers you've thought through problems in-depth and are prepared to meet future challenges. As noted above, preliminary data can be put anywhere in the Research Strategy, but just make sure reviewers will be able to distinguish it from the proposed studies. Alternatively, it can be a separate section with its own header.

Progress Reports

If applying for a renewal or a revision (a competing supplement to an existing grant), include a progress report for reviewers.

Create a header so reviewers can easily find it and include the following information:

• Project period beginning and end dates.
• Summary of the importance and robustness of the completed findings in relation to the Specific Aims.
• Account of published and unpublished results, highlighting progress toward achieving your Specific Aims.  

Other Helpful Tips

Referencing publications.

References show breadth of knowledge of the field and provide a scientific foundation for your application. If a critical work is omitted, reviewers may assume the applicant is not aware of it or deliberately ignoring it.

Throughout the application, reference all relevant publications for the concepts underlying your research and your methods. Remember the strengths and weaknesses in the rigor of the key studies you cite for justifying your proposal will need to be discussed in the Significance and/or Approach sections.

Read more about Bibliography and References Cited at Additional Application Elements .

Graphics can illustrate complex information in a small space and add visual interest to your application. Including schematics, tables, illustrations, graphs, and other types of graphics can enhance applications. Consider adding a timetable or flowchart to illustrate your experimental plan, including decision trees with alternative experimental pathways to help your reviewers understand your plans.

Video may enhance your application beyond what graphics alone can achieve. If you plan to send one or more videos, you'll need to meet certain requirements and include key information in your Research Strategy. State in your cover letter that a video will be included in your application (don't attach your files to the application). After you apply and get assignment information from the Commons, ask your assigned Scientific Review Officer (SRO) how your business official should send the files. Your video files are due at least one month before the peer review meeting.

However, you can't count on all reviewers being able to see or hear video, so you'll want to be strategic in how you incorporate it into your application by taking the following steps:

• Caption any narration in the video.
• Include key images from the video
• Write a description of the video, so the text would make sense even without the video.

Tracking for Your Budget

As you design your experiments, keep a running tab of the following essential data:

• Who. A list of people who will help (for the Key Personnel section later).
• What. A list of equipment and supplies for the experiments
• Time. Notes on how long each step takes. Timing directly affects the budget as well as how many Specific Aims can realistically be achieved.

Jotting this information down will help when Creating a Budget  and complete other sections later.

Review and Finalize Your Research Plan

Critically review the research plan through the lens of a reviewer to identify potential questions or weak spots.

Enlist others to review your application with a fresh eye. Include people who aren't familiar with the research to make sure the proposed work is clear to someone outside the field.

When finalizing the details of the Research Strategy, revisit and revise the Specific Aims as needed. Please see Writing Specific Aims . 

comments Want to contact NINDS staff? Please visit our Find Your NINDS Program Officer page to learn more about contacting Program Officer, Grants Management Specialists, Scientific Review Officers, and Health Program Specialists.

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Research strategy sets the general direction of research. It is one of the elements of research methodology and includes the process in which research is carried out. The right research strategy must be selected based on research objectives as well as questions, the amount of resources available and time, the philosophical foundations of the researcher, and the scope of existing knowledge about the studied area (Wedawatta G., Ingirige B., Amaratunga D. 2011, p. 3-4).

• 1 Types of research strategies
• 2 Quantitative and qualitative research strategies
• 3 Criteria to choose a research strategy
• 4 Research strategy impact on limitations of the research results
• 5 References

Types of research strategies

There are different research strategies, but they are largely convergent. Therefore, it is important to choose the most favorable strategy for a particular study. Part of the research strategies used in management and business are (Wedawatta G., Ingirige B., Amaratunga D. 2011, p. 4):

• experiment,
• action research,
• case study,
• grounded theory,
• ethnography,
• cross sectional studies.

Surveys are used to obtain data that will guide research groups (from choosing samples to questions and topics). It is a successful method that helps generate a large amount of data from many people. Respondents can be selected based on a different number of features, such as: sex, age, race, sexuality, social class or demographic questions. These questions are usually placed first in the survey. Such information may be needed by a researcher who does not know which focus groups to use (homogeneous or heterogeneous) (Hesse-Biber S., Leavy P. 2011, p. 173).

The experiment is a detailed study using the general empirical method. Processes and phenomena are tested in controlled, rigorous conditions. The main principle in each experiment is to change the selected individual component in the test procedure, the remaining components are fixed - they do not change. During a given experiment, the researcher introduces a new factor to the process, modifying its rate. This factor is called an independent variable or an experimental factor. On the other hand, factors changed under the influence of an independent variable are dependent variables (Novikov A., Novikov D. 2013, p. 56-56).

Action research

Action research is systematic research that helps people solve everyday problems, looking for effective solutions. The aim of this research is to involve complex dynamics in all social contexts. Continuous cycles of designed research seek to solve problems that occur in specific situations and locations, which allows for obtaining measures that increase efficiency and effectiveness of work , in: social organizations and agencies, human and health services, companies, schools. Thanks to this, it builds knowledge that strengthens social and professional practices and increases the well-being of people who take part in it (Stringer E. 2014, p. 1).

Case study is one of the most popular research methods used by researchers in industrial marketing . The reason for this may partly be the nature of the subject. The main object of the study are relationships and organizations that have a complex structure and are difficult to access than (for example) consumer markets. The study of a single or small number of entities brings a lot of qualitative data that can be described as a case study, providing insight into their nature of phenomena (Easton G. 2010, p. 118).

Grounded theory

Grounded theory is recognized as a qualitative research method. It aims to develop a theory that is based on the systematic collection and analysis of data. From other quantitative methods, it is distinguished by a specific approach to the development of theory. Grounded theory believes that there should be a continuous relationship between two activities: collecting and analyzing data. It allows the appearance of rich and original results, closely related to data, and offers well-marked data analysis procedures. It guarantees the researchers self-confidence, because they can indicate a large number of cases in the data that are associated with the concept produced (Urquhart C., Lehmann† H., Myers M. 2010, p. 357-358)

Ethnography

Ethnography favors nuanced, contextually rich and involved nuanced examples of qualitative social research, the driving force of the produced data are daily interactions. It includes a combination of different field techniques (interviews, observations, audiovisual recording, note taking, research of autochthonous literature) inscribed in the participants' observation. It is based on the conviction and trust that data is created thanks to the deep interaction between researchers. Ethnographers often treat data as a gift from informers with all the mutual consequences that suggest the exchange of these gifts (Falzon M. 2016, p. 1).

Cross sectional studies

Cross sectional study is one of the types of observational studies. At the same time, the researcher measures the exposure and the result of the study participants in it. Participants of the study are selected according to the inclusion and exclusion criteria adopted for a given study. After selecting the participants, the researcher assesses the exposure and results following the task. Cross-sectional studies are used to assess the incidence of diseases in clinical samples and for population studies (Setia M. 2016, p. 261)

Quantitative and qualitative research strategies

Qualitative and quantitative research strategies are two different approaches to conducting research.

Quantitative research is a method of gathering and analyzing numerical data to understand patterns and trends. This approach is often used in social sciences and natural sciences to examine cause-and-effect relationships, and it relies on statistical analysis of data. Surveys, experiments, and observational studies are some examples of quantitative research methods.

On the other hand, qualitative research is a method of gathering and analyzing non-numerical data, such as words, images, and observations. It is often used in fields such as sociology, anthropology, and psychology, and it aims to understand the meaning and experiences of individuals and groups. Some examples of qualitative research methods include ethnography, case study, and grounded theory.

Both qualitative and quantitative research strategies have their own advantages and disadvantages, and the choice of which approach to use will depend on the research question and the overall goals of the study. In some cases, a mixed-methods approach, which combines both qualitative and quantitative methods, may be most appropriate.

Criteria to choose a research strategy

There are several criteria to consider when choosing a research strategy. These include:

• Relevance : The research strategy should be relevant to the research question and the purpose of the study.
• Feasibility : The research strategy should be feasible to implement within the given time and budget constraints.
• Validity : The research strategy should be able to provide valid and reliable results that can be generalized to the population of interest .
• Ethical considerations : The research strategy should take into account any ethical considerations, such as informed consent and the protection of participants' rights.
• Study design : The research strategy should be appropriate for the study design, whether it be quantitative, qualitative or mixed-methods.
• Data collection methods : The research strategy should include appropriate methods for collecting and analyzing data, such as surveys, interviews, or experiments.
• The sample size : The research strategy should consider the sample size to be able to generalize the results to the population of interest.
• The resources available : The research strategy should be compatible with the resources available to the researcher, such as time, budget, and personnel.

Ultimately, the choice of research strategy will depend on the specific research question and the overall goals of the study.

Research strategy impact on limitations of the research results

The research strategy chosen can have a significant impact on the limitations of the research results. Each approach has its own strengths and weaknesses, and the choice of strategy can influence the reliability and validity of the data, as well as the generalizability of the findings.

For example, quantitative research is often considered to be more objective and reliable than qualitative research because it relies on numerical data and statistical analysis. However, quantitative research can be limited by the specific research question and the methods used, and the results may not fully capture the complexity of social phenomena.

On the other hand, qualitative research can provide rich, in-depth data that can give a detailed understanding of a particular phenomenon. However, qualitative research can be more subjective and may be influenced by the researcher's own biases. Additionally, the sample size in qualitative research is usually small, which can limit the generalizability of the findings.

A mixed-methods approach can overcome some of the limitations of both qualitative and quantitative research by combining the strengths of both methods. However, it also requires more resources and can be more complex to implement.

In summary, the limitations of the research results are closely tied to the research strategy chosen. Therefore, it is important to consider the strengths and weaknesses of different approaches when choosing a research strategy and to be aware of the limitations of the research results.

• Easton G. (2010), Critical realism in case study research , Industrial Marketing Management, nr. 39, p. 118-128
• Falzon M. (2016), Multi-sited Ethnography: Theory, Praxis and Locality in Contemporary Research , Taylor & Francis Group, London, p. 1
• Gravetter F., Forzano L. (2017), Research Methods for the Behavioral Sciences , Cengage Learning, USA
• Hesse-Biber S., Leavy P. (2011), The Practice of Qualitative Research , SAGE Publications, USA, p. 173
• Novikov A., Novikov D. (2013), Research Methodology: From Philosophy of Science to Research Design , CRC Press, Boca Raton, p. 56-56
• Rainer A. (2011), The longitudinal, chronological case study research strategy: A definition, and an example from IBM Hursley Park , Information and Software Technology , Volume 53, Issue 7, p. 730-746
• Setia M. (2016), Methodology Series Module 3: Cross-sectional Studies , Indian J Dermatol, nr 61, p. 261-264
• Stringer E. (2014), Action Research , SAGE Publications, USA, p. 1
• Urquhart C., Lehmann† H., Myers M. (2010), Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems , Info Systems J, nr 20, p. 357-358
• Whitley B., Kite M. , Adams H. (2013), Principles of Research in Behavioral Science , Routledge, New York
• Wedawatta G., Ingirige B., Amaratunga D. (2011), Case study as a research strategy: Investigating extreme weather resilience of construction SMEs in the UK , the University of Salford, Manchester, p. 3-4

Author: Dominika Magusiak

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• J Med Libr Assoc
• v.106(4); 2018 Oct

A systematic approach to searching: an efficient and complete method to develop literature searches

Associated data.

Creating search strategies for systematic reviews, finding the best balance between sensitivity and specificity, and translating search strategies between databases is challenging. Several methods describe standards for systematic search strategies, but a consistent approach for creating an exhaustive search strategy has not yet been fully described in enough detail to be fully replicable. The authors have established a method that describes step by step the process of developing a systematic search strategy as needed in the systematic review. This method describes how single-line search strategies can be prepared in a text document by typing search syntax (such as field codes, parentheses, and Boolean operators) before copying and pasting search terms (keywords and free-text synonyms) that are found in the thesaurus. To help ensure term completeness, we developed a novel optimization technique that is mainly based on comparing the results retrieved by thesaurus terms with those retrieved by the free-text search words to identify potentially relevant candidate search terms. Macros in Microsoft Word have been developed to convert syntaxes between databases and interfaces almost automatically. This method helps information specialists in developing librarian-mediated searches for systematic reviews as well as medical and health care practitioners who are searching for evidence to answer clinical questions. The described method can be used to create complex and comprehensive search strategies for different databases and interfaces, such as those that are needed when searching for relevant references for systematic reviews, and will assist both information specialists and practitioners when they are searching the biomedical literature.

INTRODUCTION

Librarians and information specialists are often involved in the process of preparing and completing systematic reviews (SRs), where one of their main tasks is to identify relevant references to include in the review [ 1 ]. Although several recommendations for the process of searching have been published [ 2 – 6 ], none describe the development of a systematic search strategy from start to finish.

Traditional methods of SR search strategy development and execution are highly time consuming, reportedly requiring up to 100 hours or more [ 7 , 8 ]. The authors wanted to develop systematic and exhaustive search strategies more efficiently, while preserving the high sensitivity that SR search strategies necessitate. In this article, we describe the method developed at Erasmus University Medical Center (MC) and demonstrate its use through an example search. The efficiency of the search method and outcome of 73 searches that have resulted in published reviews are described in a separate article [ 9 ].

As we aimed to describe the creation of systematic searches in full detail, the method starts at a basic level with the analysis of the research question and the creation of search terms. Readers who are new to SR searching are advised to follow all steps described. More experienced searchers can consider the basic steps to be existing knowledge that will already be part of their normal workflow, although step 4 probably differs from general practice. Experienced searchers will gain the most from reading about the novelties in the method as described in steps 10–13 and comparing the examples given in the supplementary appendix to their own practice.

CREATING A SYSTEMATIC SEARCH STRATEGY

Our methodology for planning and creating a multi-database search strategy consists of the following steps:

• Determine a clear and focused question
• Describe the articles that can answer the question
• Decide which key concepts address the different elements of the question
• Decide which elements should be used for the best results
• Choose an appropriate database and interface to start with
• Document the search process in a text document
• Identify appropriate index terms in the thesaurus of the first database
• Identify synonyms in the thesaurus
• Add variations in search terms
• Use database-appropriate syntax, with parentheses, Boolean operators, and field codes
• Optimize the search
• Evaluate the initial results
• Check for errors
• Translate to other databases
• Test and reiterate

Each step in the process is reflected by an example search described in the supplementary appendix .

1. Determine a clear and focused question

A systematic search can best be applied to a well-defined and precise research or clinical question. Questions that are too broad or too vague cannot be answered easily in a systematic way and will generally result in an overwhelming number of search results. On the other hand, a question that is too specific will result into too few or even zero search results. Various papers describe this process in more detail [ 10 – 12 ].

2. Describe the articles that can answer the question

Although not all clinical or research questions can be answered in the literature, the next step is to presume that the answer can indeed be found in published studies. A good starting point for a search is hypothesizing what the research that can answer the question would look like. These hypothetical (when possible, combined with known) articles can be used as guidance for constructing the search strategy.

3. Decide which key concepts address the different elements of the question

Key concepts are the topics or components that the desired articles should address, such as diseases or conditions, actions, substances, settings, domains (e.g., therapy, diagnosis, etiology), or study types. Key concepts from the research question can be grouped to create elements in the search strategy.

Elements in a search strategy do not necessarily follow the patient, intervention, comparison, outcome (PICO) structure or any other related structure. Using the PICO or another similar framework as guidance can be helpful to consider, especially in the inclusion and exclusion review stage of the SR, but this is not necessary for good search strategy development [ 13 – 15 ]. Sometimes concepts from different parts of the PICO structure can be grouped together into one search element, such as when the desired outcome is frequently described in a certain study type.

4. Decide which elements should be used for the best results

Not all elements of a research question should necessarily be used in the search strategy. Some elements are less important than others or may unnecessarily complicate or restrict a search strategy. Adding an element to a search strategy increases the chance of missing relevant references. Therefore, the number of elements in a search strategy should remain as low as possible to optimize recall.

Using the schema in Figure 1 , elements can be ordered by their specificity and importance to determine the best search approach. Whether an element is more specific or more general can be measured objectively by the number of hits retrieved in a database when searching for a key term representing that element. Depending on the research question, certain elements are more important than others. If articles (hypothetically or known) exist that can answer the question but lack a certain element in their titles, abstracts, or keywords, that element is unimportant to the question. An element can also be unimportant because of expected bias or an overlap with another element.

Schema for determining the optimal order of elements

Bias in elements

The choice of elements in a search strategy can introduce bias through use of overly specific terminology or terms often associated with positive outcomes. For the question “does prolonged breastfeeding improve intelligence outcomes in children?,” searching specifically for the element of duration will introduce bias, as articles that find a positive effect of prolonged breastfeeding will be much more likely to mention time factors in their titles or abstracts.

Overlapping elements

Elements in a question sometimes overlap in their meaning. Sometimes certain therapies are interventions for one specific disease. The Lichtenstein technique, for example, is a repair method for inguinal hernias. There is no need to include an element of “inguinal hernias” to a search for the effectiveness of the Lichtenstein therapy. Likewise, sometimes certain diseases are only found in certain populations. Adding such an overlapping element could lead to missing relevant references.

The elements to use in a search strategy can be found in the plot of elements in Figure 1 , by following the top row from left to right. For this method, we recommend starting with the most important and specific elements. Then, continue with more general and important elements until the number of results is acceptable for screening. Determining how many results are acceptable for screening is often a matter of negotiation with the SR team.

5. Choose an appropriate database and interface to start with

Important factors for choosing databases to use are the coverage and the presence of a thesaurus. For medically oriented searches, the coverage and recall of Embase, which includes the MEDLINE database, are superior to those of MEDLINE [ 16 ]. Each of these two databases has its own thesaurus with its own unique definitions and structure. Because of the complexity of the Embase thesaurus, Emtree, which contains much more specific thesaurus terms than the MEDLINE Medical Subject Headings (MeSH) thesaurus, translation from Emtree to MeSH is easier than the other way around. Therefore, we recommend starting in Embase.

MEDLINE and Embase are available through many different vendors and interfaces. The choice of an interface and primary database is often determined by the searcher’s accessibility. For our method, an interface that allows searching with proximity operators is desirable, and full functionality of the thesaurus, including explosion of narrower terms, is crucial. We recommend developing a personal workflow that always starts with one specific database and interface.

6. Document the search process in a text document

We advise designing and creating the complete search strategies in a log document, instead of directly in the database itself, to register the steps taken and to make searches accountable and reproducible. The developed search strategies can be copied and pasted into the desired databases from the log document. This way, the searcher is in control of the whole process. Any change to the search strategy should be done in the log document, assuring that the search strategy in the log is always the most recent.

7. Identify appropriate index terms in the thesaurus of the first database

Searches should start by identifying appropriate thesaurus terms for the desired elements. The thesaurus of the database is searched for matching index terms for each key concept. We advise restricting the initial terms to the most important and most relevant terms. Later in the process, more general terms can be added in the optimization process, in which the effect on the number of hits, and thus the desirability of adding these terms, can be evaluated more easily.

Several factors can complicate the identification of thesaurus terms. Sometimes, one thesaurus term is found that exactly describes a specific element. In contrast, especially in more general elements, multiple thesaurus terms can be found to describe one element. If no relevant thesaurus terms have been found for an element, free-text terms can be used, and possible thesaurus terms found in the resulting references can be added later (step 11).

Sometimes, no distinct thesaurus term is available for a specific key concept that describes the concept in enough detail. In Emtree, one thesaurus term often combines two or more elements. The easiest solution for combining these terms for a sensitive search is to use such a thesaurus term in all elements where it is relevant. Examples are given in the supplementary appendix .

8. Identify synonyms in the thesaurus

Most thesauri offer a list of synonyms on their term details page (named Synonyms in Emtree and Entry Terms in MeSH). To create a sensitive search strategy for SRs, these terms need to be searched as free-text keywords in the title and abstract fields, in addition to searching their associated thesaurus terms.

The Emtree thesaurus contains more synonyms (300,000) than MeSH does (220,000) [ 17 ]. The difference in number of terms is even higher considering that many synonyms in MeSH are permuted terms (i.e., inversions of phrases using commas).

Thesaurus terms are ordered in a tree structure. When searching for a more general thesaurus term, the more specific (narrower) terms in the branches below that term will also be searched (this is frequently referred to as “exploding” a thesaurus term). However, to perform a sensitive search, all relevant variations of the narrower terms must be searched as free-text keywords in the title or abstract, in addition to relying on the exploded thesaurus term. Thus, all articles that describe a certain narrower topic in their titles and abstracts will already be retrieved before MeSH terms are added.

9. Add variations in search terms (e.g., truncation, spelling differences, abbreviations, opposites)

Truncation allows a searcher to search for words beginning with the same word stem. A search for therap* will, thus, retrieve therapy, therapies, therapeutic, and all other words starting with “therap.” Do not truncate a word stem that is too short. Also, limitations of interfaces should be taken into account, especially in PubMed, where the number of search term variations that can be found by truncation is limited to 600.

Databases contain references to articles using both standard British and American English spellings. Both need to be searched as free-text terms in the title and abstract. Alternatively, many interfaces offer a certain code to replace zero or one characters, allowing a search for “pediatric” or “paediatric” as “p?ediatric.” Table 1 provides a detailed description of the syntax for different interfaces.

Field codes in five most used interfaces for biomedical literature searching

Searching for abbreviations can identify extra, relevant references and retrieve more irrelevant ones. The search can be more focused by combining the abbreviation with an important word that is relevant to its meaning or by using the Boolean “NOT” to exclude frequently observed, clearly irrelevant results. We advise that searchers do not exclude all possible irrelevant meanings, as it is very time consuming to identify all the variations, it will result in unnecessarily complicated search strategies, and it may lead to erroneously narrowing the search and, thereby, reduce recall.

Searching partial abbreviations can be useful for retrieving relevant references. For example, it is very likely that an article would mention osteoarthritis (OA) early in the abstract, replacing all further occurrences of osteoarthritis with OA . Therefore, it may not contain the phrase “hip osteoarthritis” but only “hip oa.”

It is also important to search for the opposites of search terms to avoid bias. When searching for “disease recurrence,” articles about “disease free” may be relevant as well. When the desired outcome is survival , articles about mortality may be relevant.

10. Use database-appropriate syntax, with parentheses, Boolean operators, and field codes

Different interfaces require different syntaxes, the special set of rules and symbols unique to each database that define how a correctly constructed search operates. Common syntax components include the use of parentheses and Boolean operators such as “AND,” “OR,” and “NOT,” which are available in all major interfaces. An overview of different syntaxes for four major interfaces for bibliographic medical databases (PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest) is shown in Table 1 .

Creating the appropriate syntax for each database, in combination with the selected terms as described in steps 7–9, can be challenging. Following the method outlined below simplifies the process:

• Create single-line queries in a text document (not combining multiple record sets), which allows immediate checking of the relevance of retrieved references and efficient optimization.
• Type the syntax (Boolean operators, parentheses, and field codes) before adding terms, which reduces the chance that errors are made in the syntax, especially in the number of parentheses.
• Use predefined proximity structures including parentheses, such as (() ADJ3 ()) in Ovid, that can be reused in the query when necessary.
• Use thesaurus terms separately from free-text terms of each element. Start an element with all thesaurus terms (using “OR”) and follow with the free-text terms. This allows the unique optimization methods as described in step 11.
• When adding terms to an existing search strategy, pay close attention to the position of the cursor. Make sure to place it appropriately either in the thesaurus terms section, in the title/abstract section, or as an addition (broadening) to an existing proximity search.

The supplementary appendix explains the method of building a query in more detail, step by step for different interfaces: PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest. This method results in a basic search strategy designed to retrieve some relevant references upon which a more thorough search strategy can be built with optimization such as described in step 11.

11. Optimize the search

The most important question when performing a systematic search is whether all (or most) potentially relevant articles have been retrieved by the search strategy. This is also the most difficult question to answer, since it is unknown which and how many articles are relevant. It is, therefore, wise first to broaden the initial search strategy, making the search more sensitive, and then check if new relevant articles are found by comparing the set results (i.e., search for Strategy #2 NOT Strategy #1 to see the unique results).

A search strategy should be tested for completeness. Therefore, it is necessary to identify extra, possibly relevant search terms and add them to the test search in an OR relationship with the already used search terms. A good place to start, and a well-known strategy, is scanning the top retrieved articles when sorted by relevance, looking for additional relevant synonyms that could be added to the search strategy.

We have developed a unique optimization method that has not been described before in the literature. This method often adds valuable extra terms to our search strategy and, therefore, extra, relevant references to our search results. Extra synonyms can be found in articles that have been assigned a certain set of thesaurus terms but that lack synonyms in the title and/or abstract that are already present in the current search strategy. Searching for thesaurus terms NOT free-text terms will help identify missed free-text terms in the title or abstract. Searching for free-text terms NOT thesaurus terms will help identify missed thesaurus terms. If this is done repeatedly for each element, leaving the rest of the query unchanged, this method will help add numerous relevant terms to the query. These steps are explained in detail for five different search platforms in the supplementary appendix .

12. Evaluate the initial results

The results should now contain relevant references. If the interface allows relevance ranking, use that in the evaluation. If you know some relevant references that should be included in the research, search for those references specifically; for example, combine a specific (first) author name with a page number and the publication year. Check whether those references are retrieved by the search. If the known relevant references are not retrieved by the search, adapt the search so that they are. If it is unclear which element should be adapted to retrieve a certain article, combine that article with each element separately.

Different outcomes are desired for different types of research questions. For instance, in the case of clinical question answering, the researcher will not be satisfied with many references that contain a lot of irrelevant references. A clinical search should be rather specific and is allowed to miss a relevant reference. In the case of an SR, the researchers do not want to miss any relevant reference and are willing to handle many irrelevant references to do so. The search for references to include in an SR should be very sensitive: no included reference should be missed. A search that is too specific or too sensitive for the intended goal can be adapted to become more sensitive or specific. Steps to increase sensitivity or specificity of a search strategy can be found in the supplementary appendix .

13. Check for errors

Errors might not be easily detected. Sometimes clues can be found in the number of results, either when the number of results is much higher or lower than expected or when many retrieved references are not relevant. However, the number expected is often unknown, and very sensitive search strategies will always retrieve many irrelevant articles. Each query should, therefore, be checked for errors.

One of the most frequently occurring errors is missing the Boolean operator “OR.” When no “OR” is added between two search terms, many interfaces automatically add an “AND,” which unintentionally reduces the number of results and likely misses relevant references. One good strategy to identify missing “OR”s is to go to the web page containing the full search strategy, as translated by the database, and using Ctrl-F search for “AND.” Check whether the occurrences of the “AND” operator are deliberate.

Ideally, search strategies should be checked by other information specialists [ 18 ]. The Peer Review of Electronic Search Strategies (PRESS) checklist offers good guidance for this process [ 4 ]. Apart from the syntax (especially Boolean operators and field codes) of the search strategy, it is wise to have the search terms checked by the clinician or researcher familiar with the topic. At Erasmus MC, researchers and clinicians are involved during the complete process of structuring and optimizing the search strategy. Each word is added after the combined decision of the searcher and the researcher, with the possibility of directly comparing results with and without the new term.

14. Translate to other databases

To retrieve as many relevant references as possible, one has to search multiple databases. Translation of complex and exhaustive queries between different databases can be very time consuming and cumbersome. The single-line search strategy approach detailed above allows quick translations using the find and replace method in Microsoft Word (<Ctrl-H>).

At Erasmus MC, macros based on the find-and-replace method in Microsoft Word have been developed for easy and fast translation between the most used databases for biomedical and health sciences questions. The schema that is followed for the translation between databases is shown in Figure 2 . Most databases simply follow the structure set by the Embase.com search strategy. The translation from Emtree terms to MeSH terms for MEDLINE in Ovid often identifies new terms that need to be added to the Embase.com search strategy before the translation to other databases.

Schematic representation of translation between databases used at Erasmus University Medical Center

Dotted lines represent databases that are used in less than 80% of the searches.

Using five different macros, a thoroughly optimized query in Embase.com can be relatively quickly translated into eight major databases. Basic search strategies will be created to use in many, mostly smaller, databases, because such niche databases often do not have extensive thesauri or advanced syntax options. Also, there is not much need to use extensive syntax because the number of hits and, therefore, the amount of noise in these databases is generally low. In MEDLINE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCOhost), the thesaurus terms must be adapted manually, as each database has its own custom thesaurus. These macros and instructions for their installation, use, and adaptation are available at bit.ly/databasemacros.

15. Test and reiterate

Ideally, exhaustive search strategies should retrieve all references that are covered in a specific database. For SR search strategies, checking searches for their recall is advised. This can be done after included references have been determined by the authors of the systematic review. If additional papers have been identified through other non-database methods (i.e., checking references in included studies), results that were not identified by the database searches should be examined. If these results were available in the databases but not located by the search strategy, the search strategy should be adapted to try to retrieve these results, as they may contain terms that were omitted in the original search strategies. This may enable the identification of additional relevant results.

A methodology for creating exhaustive search strategies has been created that describes all steps of the search process, starting with a question and resulting in thorough search strategies in multiple databases. Many of the steps described are not new, but together, they form a strong method creating high-quality, robust searches in a relatively short time frame.

Our methodology is intended to create thoroughness for literature searches. The optimization method, as described in step 11, will identify missed synonyms or thesaurus terms, unlike any other method that largely depends on predetermined keywords and synonyms. Using this method results in a much quicker search process, compared to traditional methods, especially because of the easier translation between databases and interfaces (step 13). The method is not a guarantee for speed, since speed depends on many factors, including experience. However, by following the steps and using the tools as described above, searchers can gain confidence first and increase speed through practice.

What is new?

This method encourages searchers to start their search development process using empty syntax first and later adding the thesaurus terms and free-text synonyms. We feel this helps the searcher to focus on the search terms, instead of on the structure of the search query. The optimization method in which new terms are found in the already retrieved articles is used in some other institutes as well but has to our knowledge not been described in the literature. The macros to translate search strategies between interfaces are unique in this method.

What is different compared to common practice?

Traditionally, librarians and information specialists have focused on creating complex, multi-line (also called line-by-line) search strategies, consisting of multiple record sets, and this method is frequently advised in the literature and handbooks [ 2 , 19 – 21 ]. Our method, instead, uses single-line searches, which is critical to its success. Single-line search strategies can be easily adapted by adding or dropping a term without having to recode numbers of record sets, which would be necessary in multi-line searches. They can easily be saved in a text document and repeated by copying and pasting for search updates. Single-line search strategies also allow easy translation to other syntaxes using find-and-replace technology to update field codes and other syntax elements or using macros (step 13).

When constructing a search strategy, the searcher might experience that certain parentheses in the syntax are unnecessary, such as parentheses around all search terms in the title/abstract portion, if there is only one such term, there are double parentheses in the proximity statement, or one of the word groups exists for only one word. One might be tempted to omit those parentheses for ease of reading and management. However, during the optimization process, the searcher is likely to find extra synonyms that might consist of one word. To add those terms to the first query (with reduced parentheses) requires adding extra parentheses (meticulously placing and counting them), whereas, in the latter search, it only requires proper placement of those terms.

Many search methods highly depend on the PICO framework. Research states that often PICO or PICOS is not suitable for every question [ 22 , 23 ]. There are other acronyms than PICO—such as sample, phenomenon of interest, design, evaluation, research type (SPIDER) [ 24 ]—but each is just a variant. In our method, the most important and specific elements of a question are being analyzed for building the best search strategy.

Though it is generally recommended that searchers search both MEDLINE and Embase, most use MEDLINE as the starting point. It is considered the gold standard for biomedical searching, partially due to historical reasons, since it was the first of its kind, and more so now that it is freely available via the PubMed interface. Our method can be used with any database as a starting point, but we use Embase instead of MEDLINE or another database for a number of reasons. First, Embase provides both unique content and the complete content of MEDLINE. Therefore, searching Embase will be, by definition, more complete than searching MEDLINE only. Second, the number of terms in Emtree (the Embase thesaurus) is three times as high as that of MeSH (the MEDLINE thesaurus). It is easier to find MeSH terms after all relevant Emtree terms have been identified than to start with MeSH and translate to Emtree.

At Erasmus MC, the researchers sit next to the information specialist during most of the search strategy design process. This way, the researchers can deliver immediate feedback on the relevance of proposed search terms and retrieved references. The search team then combines knowledge about databases with knowledge about the research topic, which is an important condition to create the highest quality searches.

Limitations of the method

One disadvantage of single-line searches compared to multi-line search strategies is that errors are harder to recognize. However, with the methods for optimization as described (step 11), errors are recognized easily because missed synonyms and spelling errors will be identified during the process. Also problematic is that more parentheses are needed, making it more difficult for the searcher and others to assess the logic of the search strategy. However, as parentheses and field codes are typed before the search terms are added (step 10), errors in parentheses can be prevented.

Our methodology works best if used in an interface that allows proximity searching. It is recommended that searchers with access to an interface with proximity searching capabilities select one of those as the initial database to develop and optimize the search strategy. Because the PubMed interface does not allow proximity searches, phrases or Boolean “AND” combinations are required. Phrase searching complicates the process and is more specific, with the higher risk of missing relevant articles, and using Boolean “AND” combinations increases sensitivity but at an often high loss of specificity. Due to some searchers’ lack of access to expensive databases or interfaces, the freely available PubMed interface may be necessary to use, though it should never be the sole database used for an SR [ 2 , 16 , 25 ]. A limitation of our method is that it works best with subscription-based and licensed resources.

Another limitation is the customization of the macros to a specific institution’s resources. The macros for the translation between different database interfaces only work between the interfaces as described. To mitigate this, we recommend using the find-and-replace functionality of text editors like Microsoft Word to ease the translation of syntaxes between other databases. Depending on one’s institutional resources, custom macros can be developed using similar methods.

Results of the method

Whether this method results in exhaustive searches where no important article is missed is difficult to determine, because the number of relevant articles is unknown for any topic. A comparison of several parameters of 73 published reviews that were based on a search developed with this method to 258 reviews that acknowledged information specialists from other Dutch academic hospitals shows that the performance of the searches following our method is comparable to those performed in other institutes but that the time needed to develop the search strategies was much shorter than the time reported for the other reviews [ 9 ].

CONCLUSIONS

With the described method, searchers can gain confidence in their search strategies by finding many relevant words and creating exhaustive search strategies quickly. The approach can be used when performing SR searches or for other purposes such as answering clinical questions, with different expectations of the search’s precision and recall. This method, with practice, provides a stepwise approach that facilitates the search strategy development process from question clarification to final iteration and beyond.

SUPPLEMENTAL FILE

Acknowledgments.

We highly appreciate the work that was done by our former colleague Louis Volkers, who in his twenty years as an information specialist in Erasmus MC laid the basis for our method. We thank Professor Oscar Franco for reviewing earlier drafts of this article.

• How it works

Types of Research – Tips and Examples

Published by Carmen Troy at August 16th, 2021 , Revised On October 26, 2023

“Research is an investigation conducted to seek knowledge and find solutions to scientific and social problems.”

It includes the collection of information from various sources. New research can contribute to existing knowledge.

The types of research can be categorised from the following perspectives;

• Application of the study
• Aim of the research
• Mode of inquiry
• Research approach

Types of Research According to the Application Perspective

The different types of research, according to the application perspective, include the following.

Basic Research

Primary research is conducted to increase knowledge. It is also known as theoretical research, pure research, and fundamental research. It provides in-depth knowledge about the scientific and logical explanations and their conclusions.

The results of the primary research are used as the base of applied research. It is based on  experiments  and observation. The results of basic research are published in peer-reviewed journals.

• What is global warming?
• How did the Universe begin?
• What do humans get stress?

Applied Research

Applied research is conducted to find solutions for practical problems. It uses the outcomes of basic research as its base. The results of applied research are applied immediately. It includes case studies, experimental research.

Example: Finding the solution to control air pollution.

Descriptive Research

Descriptive research  is carried out to describe current issues, programs, and provides information about the issue through  surveys  and various fact-finding methods.

It includes co-relational and comparative methods of research. It follows the Ex post facto research, which predicts the possible reasons behind the situation that has already occurred.

A researcher cannot control its variables and can report only about the current situation and its occurring.

Example: The widespread contaminated diseases in a specific area of the town. Investigation reveals that there is no trash removal system in that area. A researcher can hypothesise the reason that the improper trash removal system leads to the widespread of contaminated disease.

Analytical Research

In analytical research, a researcher can use the existing data, facts, and knowledge and critically analyses and evaluates the sources and material. It attempts to describe why a specific situation exists.

Example: Impact of video games on teenagers.

Explanatory

Explanatory research is conducted to know why and how two or more variables are interrelated. Researchers usually conduct experiments to know the effect of specific changes among two or more variables.

Example: A study to identify the impact of a nutritious diet on pregnant women.

Exploratory

Exploratory research is conducted to understand the nature of the problem. It does not focus on finding evidence or a conclusion of the problem. It studies the problem to explore the research in-depth and covers such topics which have not been studied before.

Example:  An investigation about the growing crimes against women in India.

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Types of Research According to the Mode of Inquiry

Qualitative research.

Qualitative research  is based on quality, and it looks in-depth at non-numerical data. It enables us to understand the comprehensive details of the problem. The researcher prepares open-ended questions to gather as much information as possible.

• Stress level among men and women.
• The obesity rate among teenagers.

Quantitative Research

Quantitative research is associated with the aspects of measurement, quantity, and extent. It follows the statistical, mathematical, and computational techniques in the form of numerical data such as percentages and statistics. The research is conducted on a large group of population.

• Find out the weight of students of the fifth standard
• Studying in government schools.

Types of Research According to the Research Approach

Longitudinal research.

Researchers collect the information at multiple points in time. Usually, a specific group of participants is selected and examined numerous times at various periods.

Example: If a researcher experiments on a group of women to find out the impact of a low carb diet within six months. The women’s weight and a health check-up will be done multiple times to get the evidence of the study.

Cross-Sectional Research

Cross-sectional research  gathers and compares the information from various groups of the population at the same point. It may not provide the exact reason and relationship between the subjects but gives a broad picture to study multiple groups at the same time.

Example: If a researcher wants to know the number of students studying in a school, he will get to know about the age groups, height, weight, and gender of the students at the same time.

Conceptual Research

It is associated with the concept and theory that describes the hypothesis being studied. It is based on  the inductive  approach of reasoning. It does not follow practical experiments. Philosophers, thinkers, logicians, and theorists use such research to discover new concepts and understand the existing knowledge.

Example: discoveries of Sir Isaac Newton and Einstein.

Empirical Research

It is also known as experimental research, which depends on observation and experience. It is based on the  deductive  approach of reasoning . A researcher focuses on gathering information about the facts, their sources and investigating the existing knowledge. Example: Is intermittent fasting the healthy weight loss option for women?

The researcher can come up with the result that a certain number of women lost their weight, and it improved their health. On the other hand, a certain number of women suffering from low blood pressure and diabetes didn’t lose weight, and they faced negative impacts of intermittent fasting on their health.

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It ensures:

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Mixed Methods of Research

When you combine quantitative and qualitative methods of research, the resulting approach becomes mixed methods of research.

Over the last few decades, much of the research in the world of academia has been conducted using mixed methods. Due to its greater legitimacy, this particular technique has gained for several reasons, including the feeling that combining the two types of research can provide holistic and more dependable results.

Here is what mixed methods of research involve:

• Interpreting and investigating the information gathered through quantitative and qualitative techniques.
• There could be more than one stage of research. Depending on the topic of research, occasionally, it would be more appropriate to perform qualitative research in the first stage to figure out and investigate a problem to unveil key themes; and conduct quantitative research in stage two of the process for measuring relationships between the themes.

 Tips for Choosing the Right Type of Research

Choosing the right type of research is essential for producing relevant and actionable insights. The choice depends on your objectives, available resources, and the nature of the problem. Here are some tips to help you make the right decision:

Define your Research Objectives Clearly

• Descriptive Research: To describe the characteristics of certain phenomena.
• Exploratory Research: To explore a problem that hasn’t been studied in depth.
• Explanatory (or Causal) Research: To explain patterns of cause and effect.
• Predictive Research: To forecast future outcomes based on patterns.

Understand the Research Methods

• Quantitative Research: Employs structured data collection (e.g., surveys) to generate statistical data.
• Qualitative Research: Uses unstructured or semi-structured data collection methods (e.g., interviews, observations) to understand behaviour, motivations, etc.

Consider the Time Dimension

• Cross-sectional Studies: Capture data at a single point in time.
• Longitudinal Studies: Collect data over extended periods to observe changes.

Evaluate Available Resources

• Budget: Some research methods, like experimental research, may require more funding.
• Time: Exploratory or ethnographic studies may take longer than surveys.
• Expertise: Ensure you or your team possess the skills needed for your chosen research method.

Consider the Nature of the Problem

Complex problems may require mixed-methods research (a combination of qualitative and quantitative).

Review Existing Literature

Review existing literature before settling on a type to see what methodologies were previously employed for similar questions.

Think about Data Collection

Consider the best method to gather data: surveys, interviews, experiments, observations, etc. Your choice affects the research type.

Ethical Considerations:

Ensure your chosen method abides by ethical standards, especially when human subjects are involved.

Generalisability Vs. Depth

Quantitative methods often allow for generalizability, while qualitative methods provide depth and detail.

Pilot Testing

If unsure, run a pilot study to test your chosen method’s feasibility and utility.

Stay Open to Adaptation

Sometimes, initial research can lead to unforeseen insights or complexities. Be prepared to adjust your approach if needed.

Seek Feedback

Discuss your research approach with colleagues, mentors, or experts in the field. They might offer valuable insights or identify potential pitfalls.

Stay Updated

Research methods evolve. Stay updated with the latest techniques, tools, and best practices in your field.

Frequently Asked Questions

What is research.

Research is a systematic inquiry aimed at discovering, interpreting, and revising knowledge about specific phenomena. It involves formulating hypotheses, collecting data, and analysing results to generate new insights or validate existing theories. Conducted in various fields, research can be empirical, theoretical, or experimental and is fundamental for informed decision-making.

What are the different Types of Research?

Different types of research include:

• Descriptive: Describe and analyze phenomena.
• Experimental: Manipulate variables to establish causation.
• Correlational: Examine relationships between variables.
• Qualitative: Gather insights and understanding.
• Quantitative: Use numerical data for analysis.
• Case study, survey, ethnography, and more.

What is research design?

Research design is a structured blueprint for conducting a study, outlining how data will be collected, analysed, and interpreted. It determines the overall strategy and approach to obtain valid, accurate, and reliable results. Research design encompasses choices about type (e.g., experimental, observational), method (qualitative, quantitative), and data collection procedures.

What is survey?

A survey is a research method used to gather data from a predefined group by asking specific questions. Surveys can be conducted using various mediums, such as face-to-face interviews, phone calls, or online questionnaires. They are valuable for collecting descriptive, quantitative, or qualitative information and gauging public opinion or behaviours.

What is research method?

A research method is a systematic approach used by researchers to gather, analyse, and interpret data relevant to their study. It dictates how information is collected and evaluated to answer specific research questions. Methods can be qualitative, quantitative, or mixed and include techniques like surveys, experiments, case studies, and interviews.

What is exploratory research?

Exploratory research is an initial study designed to clarify and define the nature of a problem. It’s used when researchers have a limited understanding of the topic. Instead of seeking definitive answers, it aims to identify patterns, ideas, or hypotheses. Methods often include literature reviews, qualitative interviews, and observational studies.

What is the purpose of research?

The purpose of research is to discover, interpret, or revise knowledge on specific topics or phenomena. It seeks to answer questions, validate theories, or find solutions to problems. Research enhances understanding, informs decision-making, guides policies, drives innovation, and contributes to academic, scientific, and societal advancement. It’s fundamental for evidence-based practices.

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A variable is a characteristic that can change and have more than one value, such as age, height, and weight. But what are the different types of variables?

Thematic analysis is commonly used for qualitative data. Researchers give preference to thematic analysis when analysing audio or video transcripts.

Quantitative research is associated with measurable numerical data. Qualitative research is where a researcher collects evidence to seek answers to a question.

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• Published: 01 April 2024

Strategies to implement evidence-informed decision making at the organizational level: a rapid systematic review

• Emily C. Clark 1 ,
• Trish Burnett 1 ,
• Rebecca Blair 1 ,
• Robyn L. Traynor 1 ,
• Leah Hagerman 1 &
• Maureen Dobbins 1 , 2  

BMC Health Services Research volume  24 , Article number:  405 ( 2024 ) Cite this article

Metrics details

Achievement of evidence-informed decision making (EIDM) requires the integration of evidence into all practice decisions by identifying and synthesizing evidence, then developing and executing plans to implement and evaluate changes to practice. This rapid systematic review synthesizes evidence for strategies for the implementation of EIDM across organizations, mapping facilitators and barriers to the COM-B (capability, opportunity, motivation, behaviour) model for behaviour change. The review was conducted to support leadership at organizations delivering public health services (health promotion, communicable disease prevention) to drive change toward evidence-informed public health.

A systematic search was conducted in multiple databases and by reviewing publications of key authors. Articles that describe interventions to drive EIDM within teams, departments, or organizations were eligible for inclusion. For each included article, quality was assessed, and details of the intervention, setting, outcomes, facilitators and barriers were extracted. A convergent integrated approach was undertaken to analyze both quantitative and qualitative findings.

Thirty-seven articles are included. Studies were conducted in primary care, public health, social services, and occupational health settings. Strategies to implement EIDM included the establishment of Knowledge Broker-type roles, building the EIDM capacity of staff, and research or academic partnerships. Facilitators and barriers align with the COM-B model for behaviour change. Facilitators for capability include the development of staff knowledge and skill, establishing specialized roles, and knowledge sharing across the organization, though staff turnover and subsequent knowledge loss was a barrier to capability. For opportunity, facilitators include the development of processes or mechanisms to support new practices, forums for learning and skill development, and protected time, and barriers include competing priorities. Facilitators identified for motivation include supportive organizational culture, expectations for new practices to occur, recognition and positive reinforcement, and strong leadership support. Barriers include negative attitudes toward new practices, and lack of understanding and support from management.

This review provides a comprehensive analysis of facilitators and barriers for the implementation of EIDM in organizations for public health, mapped to the COM-B model for behaviour change. The existing literature for strategies to support EIDM in public health illustrates several facilitators and barriers linked to realizing EIDM. Knowledge of these factors will help senior leadership develop and implement EIDM strategies tailored to their organization, leading to increased likelihood of implementation success.

Review registration

PROSPERO CRD42022318994.

Peer Review reports

There exist expectations that decisions and programs that affect public and population health are informed by the best available evidence from research, local context, and political will [ 1 , 2 , 3 ]. To achieve evidence-informed public health, it is important that public health organizations engage in and support evidence-informed decision making (EIDM). For this review, “public health organizations” refers to organizations that implement public health programs, including health promotion, injury and disease prevention, population health monitoring, emergency preparedness and response, and other critical functions [ 4 ]. EIDM, at an organizational level, involves the integration of evidence into all practice decisions by identifying and synthesizing evidence, then developing and executing plans to implement and evaluate changes to practice [ 2 , 5 , 6 ]. EIDM considers research evidence along with other factors such as context, resources, experience, and patient/community input to influence decision making and program implementation [ 2 , 3 , 7 , 8 ]. When implemented, EIDM results in efficient use of scarce resources, encourages stakeholder involvement resulting in more effective programs and decisions, improves transparency and accountability of organizations, improves health outcomes, and reduces harm [ 3 , 7 , 8 ]. Therefore, it is important that EIDM is integrated into organizations serving public health.

Driving organizational change for EIDM is challenging due to the need for multifaceted interventions [ 9 ].While there are systematic reviews of the implementation of specific evidence-informed initiatives, reviews of implementation of organization-wide EIDM are lacking. For example, Mathieson et al. and Li et al. examined the barriers and facilitators to the implementation of evidence-informed interventions in community nursing and Paci et al. examined barriers in physiotherapy [ 10 , 11 , 12 ]. Li et al. found that implementation of evidence-informed practices is associated with an organizational culture for EIDM where staff at all levels value and contribute to EIDM [ 12 ]. Similarly, Mathieson et al. and Paci et al. found that organizational context plays an important role in evidence-informed practice implementation along with organizational support and resources [ 10 , 11 ]. While these reviews identify organizational context, culture and support as crucial for the implementation of a particular evidence-informed practice, they do not identify and describe sufficiently what and how an organization evolves to consistently be evidence-informed for all decisions and programs and services it delivers.

Primary studies have explored how building capacity for staff to find, interpret and synthesize evidence to develop practice and program recommendations may contribute to EIDM [ 13 , 14 , 15 , 16 ]. In 2019, Saunders et al. completed an overview of systematic reviews on primary health care professionals’ EIDM competencies and found that implementation of EIDM across studies was low [ 9 ]. Participants reported insufficient knowledge and skills to implement EIDM in daily practice despite positive EIDM beliefs and attitudes [ 9 ]. In 2014, Sadeghi-Bazargani et al. and in 2018, Barzkar et al. also explored the implementation of EIDM and found similar results, listing inadequate skills and lack of knowledge amongst the most common barriers to EIDM [ 17 , 18 ].

An underlying current in research for organizational EIDM is a focus on organizational change [ 13 , 14 , 19 , 20 ]. To achieve EIDM across an organization, significant organizational change is usually necessary, resulting in substantial impact on the entire organization, as well as for individuals working there. However, while there are reviews of individual capacity for EIDM, there is minimal synthesized evidence describing EIDM capacity at the organizational level. This review seeks to address this research gap by identifying, appraising, and synthesizing research evidence from studies seeking to understand the process of embedding EIDM across an organization, with a focus on public health organizations.

The COM-B model for behaviour change was used as a guide for contextualizing the findings across studies. By integrating causal components of behaviour change, the COM-B model supports the development of interventions that can sustain behaviour change in the long-term. While there are numerous models available to support implementation and organizational change, the COM-B model was chosen, in part, for its simple visual representation of concepts, as well as its contributions to the sustainability of behaviours [ 21 ]. This model is designed to guide organizational change initiatives and distill complex systems that influence behaviour into simpler, visual representations. Specifically, this model looks at capability (C), opportunity (O) and motivation (M) as three key influencers of behaviour (B). The capability section of the COM-B model reflects whether the intended audience possess the knowledge and skills for a new behaviour. Opportunity reflects whether there is opportunity for new behaviour to occur, while motivation reflects whether there is sufficient motivation for a new behaviour to occur. All three components interact to create behaviour and behaviours can, in turn, alter capability, motivation and opportunity [ 21 ]. Selection of the COM-B model was also driven by authors’ extensive experience supporting public health organizations in implementing EIDM, which observed enablers for EIDM that align well with the COM-B model, such as team-wide capacity-building for EIDM, integration of EIDM into processes, and support from senior leadership [ 20 , 22 , 23 ]. The COM-B model has been used to map findings from systematic reviews examining the barriers and facilitators of various health interventions including nicotine replacement, chlamydia testing and lifestyle management of polycystic ovary syndrome [ 24 , 25 , 26 ]. This review has a broader focus and maps barriers and facilitators for organization-wide EIDM to the COM-B model.

Overall, EIDM is expected to be a foundation at public health organizations to achieve optimal health of populations. However, the capacity of public health organizations to realize EIDM varies considerably from organization to organization [ 14 , 22 , 27 , 28 , 29 ]. This rapid review aims to examine the implementation of EIDM at the organizational level to inform change efforts at Canadian public health organizations. The findings of this review can be applied more broadly and will support public health organizations beyond Canada to implement change efforts to practice in an evidence-informed way.

Study design

The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; Registration CRD42022318994). The review was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for reporting systematic reviews and meta-analyses [ 30 ]. A rapid review approach was used, since the review was requested to be completed by the National Collaborating Centre for Methods and Tools’ Rapid Evidence Service within a specific timeline, in order to inform an organizational change initiative at a provincial public health organization in Canada [ 31 ]. Given the nature of the research question, a mixed methods rapid systematic review approach was taken, with guidance from the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis [ 32 ].

Information sources and search strategy

The search was conducted on March 18, 2022. The following databases were searched from 2012 onward: Medline, Embase, Emcare, Global Health Database, PsycINFO, Web of Science. Each database was searched using combinations and variations of the terms “implement*”, “knowledge broker*”, “transform*”, “organizational culture”, “change management”, “evidence-based”, “knowledge translation”, and “knowledge mobilization”. Additionally, publications by key contributors to the field were reviewed. The full search strategy is included in Appendix 1 .

Studies were screened using DistillerSR software. Titles and abstracts of retrieved studies were screened by a single reviewer. Full texts of included studies were screened by a second reviewer and reviewed by a third. Screening was not completed in duplicate, consistent with a rapid review protocol [ 31 ]. To minimize the risk of bias, a subset of 100 retrieved articles were screened in duplicate at the title and abstract stage to ensure consistency across reviewers. Of this subset, there were four articles with conflicting decisions, which were discussed amongst screeners to clarify inclusion criteria.

Eligibility criteria

English-language, published primary studies with experimental or observational designs were eligible for inclusion. Review papers, such as literature and systematic reviews, were excluded to ensure that details regarding implementation of initiatives were captured without re-interpretation or generalization by review authors. Grey literature was not included. Eligibility criteria are outlined below in terms of a PICO (Population, Intervention, Comparison, Outcome) structure [ 33 ].

Studies conducted with public sector health-related service-delivery organizations were eligible for inclusion. This included public health departments and authorities, health care settings and social services. Studies focused on departments or teams within an organization, or on entire organizations, were also eligible for inclusion. Studies conducted in private sectors or academic institutions were excluded to narrow the focus of the review.

Intervention

Interventions designed and implemented to shift teams, departments, or organizations to EIDM in all decisions were eligible for inclusion. These can include initiatives where organizations establish roles or teams to drive organizational change for EIDM, or efforts to build and apply the knowledge and skill of staff for EIDM. These are distinct from implementation strategies for evidence-informed interventions. Eligible interventions were applied to a team, department, or organization to drive change toward evidence use in decision making at all levels of the organizations.

Studies that included any comparator or no comparator were included, recognizing that literature was likely to include case reports.

Outcomes measured either quantitatively or qualitatively were considered. These included behaviour change, confidence and skills, patient-level data such as quality indicators, evidence of EIDM embedded in organizational and decision-making processes, changes in organizational culture, and changes to budget allocation. Studies that reported primarily on implementation fidelity were excluded, since studies of implementation fidelity focus on whether an intervention is delivered as intended, rather than drivers for organizational change.

Studies conducted in the 38 member countries of the Organization for Economic Co-operation and Development (OECD) were included in this review to best align with the Canadian context and to inform organizational change efforts in public health within Canada [ 34 ].

Quality assessment

The methodological rigour of included studies was evaluated using the JBI suite of critical appraisal tools [ 35 ]. Ratings of low, moderate, or high quality were assigned based on the critical appraisal results. Quality assessment was completed by one reviewer and verified by a second. Conflicts were resolved through discussion or by consulting a third reviewer.

Data extraction

Data extraction was completed by a single reviewer and reviewed by a second. Data on the study design, setting, sector (e.g., public health, primary care, etc.), participants, intervention (e.g., description of learning initiatives, implementation strategies, etc.), outcome measures, and findings were extracted. To minimize the risk of bias, a subset of three included articles underwent data extraction in duplicate to ensure consistency across reviewers. There was good agreement between duplicate extraction, with variations in the format of extracted data but consistency in content.

Data analysis

Quantitative and qualitative data were synthesized simultaneously, using a convergent integrated approach [ 32 ]. Quantitative data underwent narrative synthesis, where findings that caused benefit were compared with those that caused harm or no effect [ 36 ]. Vote counting based on the direction of effect was used to determine whether most studies found a positive or negative effect [ 36 ]. For qualitative findings, studies were grouped according to common strategies. Within these common strategies, findings were reviewed for trends in reported facilitators and barriers. These trends were deductively mapped to the COM-B model for behaviour change [ 37 ].

Due to the heterogeneity in study outcomes, the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) [ 38 ] approach was not used for this review. Overall certainty of evidence was determined based on the risk of bias of included study designs and study quality.

Database searching retrieved 7067 records. After removing duplicates, 4174 records were screened by title and abstract, resulting in 1370 reports for full text review. Of those 1370 records, 35 articles were included. Scanning the publication lists of key authors retrieved 187 records, of which eight were retrieved for full text review and two were included, for a total of 37 articles included in this review. See Fig. 1 for a PRISMA flow chart illustrating the article search and selection process.

PRISMA 2020 flow chart

Study characteristics

The overall characteristics of included studies are summarized in Table 1 . Of 37 included studies, most were conducted in primary care settings ( n  = 16) and public health settings ( n  = 16), with some in social services ( n  = 3), child and youth mental health ( n  = 1), and occupational health ( n  = 1). Most studies were conducted in the USA ( n  = 17), followed by Canada ( n  = 12), Australia ( n  = 5), and Europe ( n  = 3).

Study designs included case reports ( n  = 18), single group pre-/post-test studies ( n  = 10), qualitative studies ( n  = 7), and randomized controlled trials (RCTs) ( n  = 2). Both RCTs evaluated the implementation of organizational EIDM.

Studies reported quantitative ( n  = 11), qualitative ( n  = 20), or both quantitative and qualitative results ( n  = 6). For the studies that reported quantitative results, measures included EIDM implementation, EIDM-related beliefs and behaviours, organizational priorities for EIDM, and patient care quality indicators. Quantitative measures were heterogenous and did not allow meta-analysis. Qualitative findings were generated through formal qualitative analysis ( n  = 19) or descriptive case reports ( n  = 7). Most qualitative results included facilitators and barriers to implementation ( n  = 16).

Study quality

The critical appraisal checklist used to assess each study is indicated in Table  1 . Single group, pre-/post-test studies were evaluated according to the JBI Checklist for Quasi-experimental Studies [ 35 ].

A lack of control groups contributed to the risk of bias. Most included studies were rated Moderate or High quality according to their respective quality assessment tools. Full quality assessments for each article are included in Appendix 2 . Therefore, the overall methodological quality for this body of literature was rated as Moderate.

Strategies for implementing organization-wide EIDM

Due to the heterogeneity of study designs, interventions, and outcomes, it was not possible to determine which EIDM implementation strategies are more effective compared to others. Implementation strategies included the establishment of Knowledge Broker-type roles, building the EIDM capacity of staff, and research or academic partnerships. These strategies are listed in Table  2 .

Evaluation of strategies implemented by studies in this review was often qualitative and described facilitators and barriers, rather than quantitatively measuring effectiveness. However, it is possible to explore EIDM implementation strategies and factors that appear to contribute to or inhibit success. The most common strategy implemented in included studies was the establishment of Knowledge Broker-type roles [ 20 , 41 , 44 , 47 , 48 , 51 , 52 , 54 , 55 , 56 , 57 , 59 , 60 , 62 , 63 , 64 , 65 , 66 , 67 , 69 , 71 , 72 ]. Studies described roles differently (e.g., “Evidence-based Practice Facilitator”, “Evidence Facilitator”, “EIDM Mentor”). These roles all served to support EIDM across organizations through knowledge sharing, evidence synthesis, implementation, and other EIDM-related activities. In some studies, new staff were hired to Knowledge Broker roles, or developed among existing staff, while in others, Knowledge Brokers were contracted from external organizations. Knowledge Broker strategies were mostly implemented in parallel with other EIDM implementation strategies, such as capacity building for staff, integrating EIDM into decision-making processes and development of leadership to support EIDM. When these strategies were evaluated quantitatively for organizational capacity, culture and implementation of EIDM, most studies found positive results, such as increased scores for organizational climates supporting EIDM, improved attitudes toward EIDM, or the integration of EIDM into processes [ 44 , 52 , 54 , 62 , 66 , 67 , 71 , 72 ], although some studies found no change [ 55 , 60 ] following implementation of Knowledge Broker roles. Qualitatively, most studies described facilitators and barriers to EIDM, either through formal qualitative analysis or case report [ 14 , 20 , 39 , 40 , 41 , 42 , 43 , 45 , 47 , 48 , 52 , 55 , 57 , 59 , 60 , 61 , 64 , 65 , 68 ]. Facilitators included organizational culture with supportive leadership and staff buy-in, expectations to use evidence to inform decisions, accessible knowledge, and integration of EIDM into processes and templates. Barriers included limited time and competing priorities, staff turnover, and lack of understanding and support from management.

Ten included studies focused primarily on building EIDM capacity of existing staff at the organization, often at multiple levels (e.g., front-line service providers, managers, and leadership) [ 13 , 14 , 39 , 40 , 42 , 43 , 46 , 49 , 50 , 58 , 61 ]. Capacity building was typically done through EIDM-focused workshops, often with ongoing follow up support from workshop facilitators. While studies often measured changes in individual knowledge and skill for EIDM for workshop participants, organizational change for EIDM was reported qualitatively, either through formal qualitative analysis or through a case report. Facilitators for EIDM in these ten studies included organizational culture with supportive leadership and staff buy-in, dedicated staff roles to support EIDM, opportunities to meet and discuss EIDM (e.g., communities of practice, journal clubs), knowledge sharing across the organization, expectations to use evidence to inform decisions, accessible knowledge, and integration of EIDM into processes and templates. Barriers included limited time and competing priorities, staff turnover, and negative attitudes toward EIDM.

Research or academic partnerships and networks were the main strategy described in three case reports [ 45 , 53 , 68 ]. These involved establishing collaborations, either through universities or non-governmental health organizations, that provided direct EIDM support. These strategies were not evaluated quantitatively but described facilitators and barriers to effective cross-sector collaborations. Facilitators for EIDM included supportive leadership and management, dedicated staff roles to support EIDM, EIDM knowledge and skill development for staff, and regular communication between partners. Barriers included limited time and competing priorities, preference for experiential over research evidence, and negative attitudes toward EIDM.

Overall, studies described successes in implementing EIDM across organizations, citing several common key facilitators and barriers. To instigate behaviour change, strategies must address capability for change, which may be achieved by building staff capacity, establishing dedicated support roles, improving access to evidence, and sharing knowledge across the organization. Strategies must also enable opportunities for change, which may be supported through forums for EIDM learning and practice, protecting time for EIDM, integrating EIDM into new or existing roles, and adding EIDM to processes and templates. Behaviour change also requires motivation, which may be built through a supportive organizational culture, expectations to use EIDM, recognition and positive reinforcement, and strong support from leadership.

Key considerations for implementing EIDM

Many of the facilitators and barriers to EIDM are common across strategies explored by the studies included in this review. To conceptualize these factors, they were mapped to the COM-B model for behaviour change [ 21 ] in Fig. 2 .

COM-B Model for behaviour change with facilitators and barriers for implementation of organization-wide EIDM

Within the capability component of the COM-B model, staff knowledge and skill development were included as a facilitator. Studies included in this review demonstrated that knowledge and skill for EIDM supported the use of evidence in decision making [ 13 , 14 , 39 , 40 , 42 , 43 , 46 , 49 , 50 , 58 , 61 ]. The establishment of specialized or dedicated roles for EIDM, such as Knowledge Broker roles, was included in the capability component of the COM-B model, since Knowledge Broker roles support the capacity of organizations and their staff to use evidence-informed approaches [ 20 , 41 , 44 , 47 , 48 , 51 , 52 , 54 , 55 , 56 , 57 , 59 , 60 , 62 , 63 , 64 , 65 , 66 , 67 , 69 , 71 , 72 ]. Finally, knowledge sharing across organizations was described as a facilitator for EIDM by several of the studies that built staff capacity for EIDM or established Knowledge Broker roles [ 13 , 48 , 49 , 51 , 52 , 54 , 56 , 59 , 61 , 65 ]. Barriers to the capability for EIDM behaviours include staff turnover and subsequent knowledge loss [ 14 , 20 , 56 ]. Staff turnover is especially challenging for interventions that involve staff in dedicated Knowledge Broker roles and interventions that build the knowledge and skill for staff to engage in evidence use [ 14 , 20 , 56 ]. In some cases, individuals who are trained in the Knowledge Broker role are then promoted to new roles or management and have fewer opportunities to apply their Knowledge Broker skills [ 20 ].

The opportunity portion of the COM-B model reflects whether there is opportunity for new behaviour to occur. The development of processes and mechanisms that support new practices can act as a reminder for staff, and may include re-design of planning or decision-making templates to capture supporting evidence, or adding EIDM-related items to agendas for regular meetings [ 41 , 47 , 53 , 60 ]. Forums for learning and skill development provide staff with opportunities to gain knowledge and practice newly acquired skills in group settings, such as communities of practice or journal clubs [ 48 , 56 , 61 , 65 ]. Finally, protected time to apply EIDM was found to be a facilitator for opportunity in the COM-B model [ 20 , 47 , 57 , 59 , 65 ], while competing priorities were found to be a barrier [ 20 , 39 , 40 , 52 , 55 , 57 , 60 , 64 , 65 ].

The final influencer in the COM-B model, motivation, reflects whether there is sufficient motivation for a new behaviour to occur. Facilitators include supportive organizational culture [ 14 , 20 , 43 , 47 , 57 , 59 ], expectations for new practices to occur [ 20 , 40 ], recognition and positive reinforcement [ 52 , 59 , 60 , 65 ], and strong leadership support [ 14 , 20 , 39 , 40 , 43 , 47 , 56 , 59 , 65 , 68 ]. Barriers to motivation included a lack of understanding or support from management [ 20 ], and negative attitudes toward change [ 20 , 52 , 59 , 68 ].

Strategies to implement EIDM across organizations include establishing specialized roles, providing staff education and training, developing processes or mechanisms to support new practices, and demonstrating leadership support. Facilitators and barriers for these strategies align with the COM-B model for behaviour change, which outlines capability, opportunity, and motivation as influencers of behaviour (Fig. 2 ). The COM-B model provides a comprehensive framework for the factors that influence behaviour change and has provided a valuable structure for examining barriers and facilitators to behaviour change in public health and related fields [ 73 , 74 , 75 , 76 ].

The capability section of the COM-B model reflects whether the intended audience possess the knowledge and skill for a new behaviour. Findings from this review establish facilitators for EIDM implementation capability, including the development of staff knowledge and skill, establishing specialized roles, and knowledge sharing across the organization. The development of staff knowledge and skill for EIDM are a necessary component to ensure EIDM in practice, however, literature has found that the organization-wide impact of conducting only individual-level knowledge and skill development is limited [ 77 , 78 , 79 ]. While knowledge and skill development are a necessary component to EIDM practice, they must be supported by other components to have an impact beyond the individual. Other strategies that support the use of newly gained knowledge and skills include the establishment of specialized roles for EIDM. Another strategy to support the use of EIDM is the establishment of dedicated staff roles, such as Knowledge Brokers. Knowledge Broker roles have been used across diverse contexts and show promise in supporting organization-wide EIDM implementation [ 20 , 22 , 23 , 67 , 80 , 81 , 82 , 83 ]. One facilitator for Knowledge Broker roles was knowledge sharing across the organization. Factors that influence the success of staff in Knowledge Broker roles align with those mapped to opportunity and motivation in the COM-B model, including the integration of EIDM into processes, knowledge sharing, and supportive organizational culture [ 20 , 22 , 47 , 67 , 84 , 85 ]. Knowledge Brokers can also help facilitate knowledge sharing across the organization, which was another facilitator mapped to the capability level of the model [ 20 , 47 , 84 , 85 ]. Knowledge sharing refers to the shared learning, knowledge products and resources for EIDM. At large public health organizations, it can be challenging to facilitate knowledge sharing between teams and departments [ 86 , 87 ]. Integrating technology can help; there have been some advances driven by the COVID-19 pandemic, such as the development of knowledge sharing platforms [ 88 , 89 , 90 , 91 ]. Public health organizations seeking to implement EIDM should invest in their knowledge sharing infrastructure.

At the capability level of the COM-B model, staff turnover was a barrier to EIDM implementation. Organizations that implement these strategies should be cognizant of the potential for knowledge loss due to staff turnover when selecting staff for Knowledge Broker roles or capacity building opportunities.

Facilitators for organizational EIDM opportunity include the development of processes or mechanisms to support new practices, forums for learning and skill development, and protected time. The use of reminders for organizational behaviour change and implementation of clinical practice guidelines has been shown to be an effective strategy across many contexts [ 92 , 93 , 94 , 95 ]. Organizations seeking to implement EIDM should consider revising current templates and processes to support their initiatives. Another facilitator included forums for shared learning and skill development. Other literature shows that these forums can be effective in developing knowledge and skill and should foster an environment of learning without fear of reprisal [ 96 , 97 ]. Finally, protected time for EIDM was a facilitator and competing priorities were a barrier. In public health practice, staff are often challenged with high workloads, so that EIDM may be viewed as an additional burden rather than a means to improve practice [ 98 , 99 ]. For an EIDM approach to be practiced, staff must be provided with sufficient time to apply and practice skills. Organizations should consider involving middle management who oversee staff time allocations, rather than only senior leadership, to help ensure that staff are provided with the time they need and that expectations are adjusted accordingly [ 20 , 23 ].

At the motivation level of the COM-B model, supportive organizational culture was mapped as a facilitator. The influence of organizational culture on evidence-informed practice at health organizations has been explored in a previous systematic review by Li et al. [ 100 ]. This systematic review of organizational contextual factors that influence evidence-based practice included 37 studies conducted in healthcare-related settings. Findings align with facilitators identified above, especially leadership support, which was found to impact evidence-based practice as well as all other factors that influence evidence-based practice [ 100 ]. The review also found that monitoring and feedback contributed to implementation of evidence-based practice, which aligns with recognition and positive reinforcement in the COM-B model above [ 100 ]. Notably, another factor that was mapped to the COM-B model was the expectation for new practices to occur, which was not explicitly identified as an influence on practice [ 100 ]. While Li et al. acknowledge that leadership that neglects to hold staff accountable are detrimental to implementation of EIDM, this accountability and clear expectations for change practice were a stronger finding in this current rapid systematic review.

The need for leadership support aligns with opportunity, since it is often management that determines the allocation of staff time for EIDM [ 20 , 23 ]. Attitudes and the belief that EIDM is associated with positive outcomes is a key factor in overall competence for EIDM [ 101 ]. Efforts to address negative attitudes within staff, especially at the leadership level, may improve implementation of EIDM.

While this review provides a comprehensive overview of interventions to support EIDM in public health and related organizations, it does have some limitations. Given the heterogeneity of included studies, it was not possible to discern which implementation strategies for EIDM are more effective compared to others. Knowledge Broker roles, building capacity for EIDM, and research-academic partnerships were all shown to contribute to EIDM, but study findings do not support one strategy as superior to others. Given the highly contextual nature of these interventions, it is likely that the relative effectiveness of different interventions depends on the organization’s unique set of characteristics. Evaluation is also critical to determine if change efforts are successful or need to be adjusted. It is possible that a combination of strategies would maximize the likelihood that diverse needs of staff are met. Rigorous studies to evaluate this hypothesis are needed.

Most studies included in this review are non-randomized studies of interventions. Given the importance of context in organizational change, randomized controlled trial designs may not be well-suited to evaluate studies of EIDM implementation [ 102 ]. High-quality single-group studies, such as prospective cohort analytic studies evaluated with validated measures or qualitative descriptive analyses of case studies with thorough descriptions of interventions and context, may be more appropriate designs for designing future initiatives in this field. However, arguments have been made for the use of randomized trial designs in implementation research [ 103 ]. Foy et al. advocate for overcoming contextual barriers by using innovative trial designs, such as the multiphase optimization strategy approach, where a series of trials identify the most promising single or combined intervention components, or the sequential multiple assignment randomized trial approach, where early results inform tailoring of adaptive interventions [ 103 ]. These designs may be a promising approach to conducting trials within highly contextual settings. Another viewpoint is that perhaps it may not be essential to determine if one strategy is superior to another, but rather that strategies build a larger, multi-strategy approach to implementation [ 104 ]. There may be greater benefit to determining the conditions under which various strategies are effective [ 104 ].

A limitation in this review’s methodology is that the review was completed following a rapid review protocol to ensure timely completion. Modifications of a systematic review approach included the use of a single reviewer for screening and using an unblinded reviewer to check quality assessment and data extraction. This may have contributed to some bias within the review, due to the reviewers’ interpretations of studies. To minimize this bias, there were efforts to calibrate screening, quality assessment and data extraction using a subset of studies.

This review provides a synthesis of strategies for the organization-wide implementation of EIDM, and an in-depth analysis of their facilitators and barriers in public health organizations. Facilitators and barriers mapped to the COM-B model for behaviour change can be used by organizational leadership to drive organizational change toward EIDM.

This rapid systematic review explored the implementation of EIDM at the organizational level of public health and related organizations. Despite the similarity of these implementation challenges, studies used distinct strategies for implementation, including the establishment of dedicated roles to support EIDM, building staff capacities, research or academic partnerships, and integrating evidence into processes or mechanisms. Facilitators and barriers mapped to the COM-B model provide key guidance for driving organizational change to evidence-informed approaches for all decisions.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

Evidence-informed Decision Making

Evidence-based Practice

Evidence-informed Practice

Grading of Recommendations, Assessment, Development and Evaluations

Joanna Briggs Institute

Knowledge Translation

Randomized Controlled Trial

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Acknowledgements

The authors would like to acknowledge the NCCMT’s Rapid Evidence Service, particularly Alyssa Kostopoulos, Sophie Neumann and Selin Akaraci, for their contributions to this review.

The National Collaborating Centre for Methods and Tools is hosted by McMaster University and funded by the Public Health Agency of Canada. The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada. The funder had no role in the design of the study, collection, analysis, or interpretation of data or in writing the manuscript.

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Clark, E.C., Burnett, T., Blair, R. et al. Strategies to implement evidence-informed decision making at the organizational level: a rapid systematic review. BMC Health Serv Res 24 , 405 (2024). https://doi.org/10.1186/s12913-024-10841-3

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Creating a winning organizational culture takes a lot of time and effort — your culture must accurately reflect your values and align with your overall mission. It’s a big to-do, but don’t get discouraged: your efforts will pay off in the long run.

While any given organizational culture will evolve with time — especially as the team grows and onboards more people — you can take steps to tailor your culture to better fit your organization’s values and mission. But first, you need to understand the type of organizational culture your company has.

Related Types of Diversity in the Workplace You Need to Know

4 Types of Organizational Culture

There are four main types of organizational culture, which come from Robert E. Quinn and Kim S. Cameron of the University of Michigan, who investigated the qualities that make businesses effective. From a list of 39 attributes, the researchers identified two key polarities: (1) internal focus and integration vs. external focus and differentiation, and (2) flexibility and discretion vs. stability and control.

Types of Organizational Culture

• Clan Culture: emphasizes collaboration across teams and a horizontal structure. 
• Adhocracy Culture: allows individuals to share ideas and encourages the company to take risks. 
• Market Culture: focuses on financial success and how each employee contributes to revenue. 
• Hierarchy Culture: emphasizes career paths and provides clear managerial processes.  

These qualities are visually represented within the Competing Values Framework, which is part of the validated and widely-used Organizational Cultural Assessment Instrument . Although there are several types of organizational culture, Quinn and Cameron’s four types are generally accepted and appear to influence any variations. These four types of organizational culture are neither good nor bad, but they do provide frameworks that company leadership can lean on. 

Understanding what type of organizational culture your company has can help you identify what makes your company stand out to candidates. When you know why your organization’s culture is unique, you can highlight these attributes in your recruitment marketing materials. Recognizing the type of company culture you have can also help you write your core values and mission statement . 

Related 21 Company Culture Examples to Get You Inspired

Type 1: Clan Culture

Primary Focus: Mentorship and teamwork.

Motto: “We’re all in this together.”

About Clan Culture: A clan culture is people-focused in the sense that the company feels family-like. This is a highly collaborative work environment where every individual is valued and communication is a top priority. Clan culture is often paired with a horizontal structure, which helps to break down barriers between the C-suite and employees, and it encourages mentorship opportunities . These companies are action-oriented and embrace change, a testament to their highly flexible nature.

Clan Culture Definition

• Clan culture is a collaborative model usually paired with horizontal company structure.
• Communication is key to this type of culture. 
• Companies can implement clan culture by asking for direct feedback for employees and taking action based on their suggestions.

Advantages of Clan Culture:  Clan cultures boast high rates of employee engagement , and happy employees make for happy customers. Because of its highly adaptable environment, there’s a great possibility for market growth within a clan culture.

Disadvantages of Clan Culture:  A family-style corporate culture is difficult to maintain as the company grows. Plus, with a horizontal leadership structure, day-to-day operations can seem cluttered and lacking direction.

Where You’ll Find Clan Culture: It’s no surprise that clan cultures are often seen in startups and smaller companies. Young organizations that are just starting out put a heavy emphasis on collaboration and communication, leadership looks to employees for feedback and ideas and companies prioritize team-building. 

For companies with a large percentage of employees working remotely like HR tech provider Hireology , creating an empathetic and communicative organizational culture is key to success. “When you have a blended team, your local staff can help bridge gaps and build empathy,” Joel Schlundt, vice president of engineering at Hireology, said. The team coordinated job swaps to help employees better understand and appreciate their peers’ roles.

How to Create Clan Culture Within Your Organization: To cultivate a clan culture within your company, your first step is to turn to your employees. Communication is vital to a successful clan culture, so let your team know that you’re open to feedback. Find out what they value, what they’d like to see change, what ideas they have to help push the company further. Step two: take their thoughts into account and put them into action.

Type 2: Adhocracy Culture

Primary Focus: Risk-taking and innovation.

Motto: “Risk it to get the biscuit.”

About Adhocracy Culture: Adhocracy cultures are rooted in innovation and adaptability. These are the companies that are on the cutting-edge of their industry — they’re looking to develop the next big thing before anyone else has even started asking the right questions. To do so, they need to take risks. Adhocracy cultures value individuality in the sense that employees are encouraged to think creatively and bring their ideas to the table. Because this type of organizational culture falls within the external focus and differentiation category, new ideas need to be tied to market growth and company success.

Adhocracy Culture Definition

• Adhocracy culture puts a focus on employees adapting and innovating. 
• This culture helps companies take risks and invites individuals to share their ideas. 
• Companies can implement adhocracy culture by hosting strategy and brainstorming sessions.   

Advantages of Adhocracy Culture: An adhocracy culture contributes to high profit margins and notoriety. Employees stay motivated with the goal of breaking the mold. Plus, with a focus on creativity and new ideas, professional development opportunities are easy to justify.

Disadvantages of Adhocracy Culture: Risk is risk, so there’s always a chance that a new venture won’t pan out and may even hurt your business. Adhocracy cultures can also foster competition between employees as the pressure to come up with new ideas mounts.

Where You’ll Find Adhocracy Culture: Think of Google or Apple — these are companies that embody the external focus and risk-taking nature of adhocracy culture. They run on creative energy and doing what hasn’t been done before. Adhocracy cultures are commonplace within the ever-changing tech industry where new products are being developed and released on a regular basis.

How to Create Adhocracy Culture Within Your Organization: Depending on your industry, it may be hard to develop an authentic adhocracy culture that includes a high-risk business strategy. However, implementing strategy and brainstorming sessions provides employees with the opportunity to share big ideas that can help to propel the company further. Rewarding successful ideas encourages teams to think outside of the box, too.

Related Culture Fit: More Harm Than Good? 12 Experts Share Their Take.

Type 3: Market Culture 

Primary Focus: Competition and growth.

Motto: “We’re in it to win it.”

About Market Culture: Market culture prioritizes profitability. Everything is evaluated with the bottom line in mind; each position has an objective that aligns with the company’s larger goal, and there are often several degrees of separation between employees and leadership roles. These are results-oriented organizations that focus on external success rather than internal satisfaction. A market culture stresses the importance of meeting quotas , reaching targets and getting results. 

Market Culture Definition

• Companies with a market culture are focused on financial success and meeting goals and targets. 
• Each employee working within market culture plays a distinct part in reaching the company’s larger goals. 
• Companies can implement market culture by analyzing each role within the company and determining the ROI of each role. Rewarding top performers will motivate employees.

Advantages of Market Culture: Companies that boast market cultures are profitable and successful. Because the entire organization is externally focused, there’s a key objective employees can get behind and work toward.

Disadvantages of Market Culture: On the other hand, because there’s a number tied to every decision, project and position within the company, it can be difficult for employees to meaningfully engage with their work and live out their professional purpose. There is also risk for burnout in this aggressive and fast-paced environment.

Where You’ll Find Market Culture: The goal of a market culture company is to be the best in its industry. Because of that, these are often larger companies that are already leaders of the pack. They’re looking to compete and beat out anyone else that may compare.

For an industry leader like Bluecore , a retail marketing platform that utilizes AI technology , providing employees with clear objectives helps the team provide all-star customer service. “Our team is clear on its goals, and we are incentivized through compensation structure and recognition,” Kim Surko, vice president of customer success, said. “With that foundation, we can apply our personality and values to define how we will accomplish those goals.” 

How to Create Market Culture Within Your Organization: Because every aspect of a market culture is tied to the company’s bottom line, start by evaluating each position within your organization. Calculate the ROI of every role and ascribe reasonable benchmarks for production. Consider rewarding top performers to encourage similar work.

Type 4: Hierarchy Culture

Primary Focus: Structure and stability.

Motto: “Get it done right. ”

About Hierarchy Culture: Companies with hierarchy cultures adhere to the traditional corporate structure. These are companies focused on internal organization by way of a clear chain of command and multiple management tiers that separate employees and leadership. In addition to a rigid structure, there’s often a dress code for employees to follow. Hierarchy cultures have a set way of doing things, which makes them stable and risk-averse.

Hierarchy Culture Definition

• Companies with hierarchy culture have a clear chain of command and detailed career paths within the organization. 
• These companies tend to avoid risk and focus on internal organization. 
• Companies can implement hierarchy culture by ensuring each department and team has clear and concise processes and managerial structure.   

Advantages of Hierarchy Culture: With internal organization as a priority, hierarchy cultures have clear direction. There are well-defined processes that cater to the company’s main objectives.

Disadvantages of Hierarchy Culture: The rigidity of hierarchy cultures leaves little room for creativity, making these companies relatively slow to adapt to the changing marketplace. The company takes precedence over the individual, which doesn’t necessarily encourage employee feedback.

Where You’ll Find Hierarchy Culture: Hierarchy cultures can be found at both ends of the corporate spectrum, from old-school organizations to those of the customer service industry, such as fast food restaurants. These are companies that are hyper-focused on how day-to-day operations are carried out and aren’t interested in changing things up anytime soon.

How to Create Hierarchy Culture Within Your Organization: The first step to establishing a hierarchy culture is to button up your processes. If the chain of command has some gaps, fill them. Consider every team and department to ensure they have clear long- and short-term goals.

Learn About Recruiting 12 Recruitment Strategies and Examples to Hire Top Talent

Other Types of Organizational Culture

Outside of these four main categories of organizational culture, there are a few more worth noting. 

Purpose Culture

Purpose culture focuses on a company’s mission and core values. These aspects drive the culture. Often companies with this culture will have a mission of changing an industry or community for the better. One example of this can be seen in Patagonia ’s mission statement : “We’re in business to save our home planet.” 

Coaching Culture

In a company with a coaching culture senior leadership is responsible for mentoring their employees and ensuring that individuals advance in their careers. Various coaching techniques, such as providing assessments on specific projects or one-on-one meetings where expectations and personal goals are discussed, typically drive this style of culture. 

Related 5 Companies With Interesting Organizational Cultures

Accountability Culture

Accountability culture means that everyone within the organization, including the CEO and senior leadership, are responsible and held accountable for their own actions and performance. This can look like employees taking ownership of their mistakes and openly questioning how they can learn from them as well as recognizing colleagues when they have excelled in their role.

Learning Culture 

Companies with a learning culture put a special emphasis on learning and development opportunities . These organizations often have company-wide workshops and encourage employees to learn skills outside of what is immediately required for their role, providing stipends for various educational opportunities . 

Go Deeper 7 Leadership Lessons From Netflix CEO Reed Hastings

How to Identify Your Organizational Culture

Your organizational culture says a lot about your team and what you value, and job seekers can pick up on that almost immediately. If you’re not sure where your organization lands on this list, you’re not alone. Cameron and Quinn developed an assessment tool that helps companies identify their organizational culture. 

Once you evaluate your existing organizational culture, take stock of what truly matters to your organization: Where are you aligned? What are your areas for improvement? 

If you think a different kind of organizational culture would work better for your company and employees, take steps to shift it . While that looks different from company to company, you’ll generally want to start by defining and assessing the current culture, financial goals, company structure, mission and core values. Then continually evaluate your culture and the progress you’ve made toward your organizational culture goals.

Strategies to decode, maintain and improve company culture.

Frequently Asked Questions

What is organizational culture.

Organizational culture, or company culture, is the shared values, practices and attitudes that characterize an organization. It defines the overall personality and working environment of a company, and has a significant impact on employee behavior and satisfaction.

What are the 4 types of organizational culture?

The four main types of organizational culture include:

• Clan culture 
• Adhocracy culture
• Market culture
• Hierarchy culture

What does a good organizational culture look like?

A good or positive organizational culture is often one that fosters mutual respect, growth opportunities and shared goals amongst employees. This kind of organizational culture also reflects a company's core values and aligns with the company's overarching mission.

What are the 7 characteristics of organizational culture?

The seven characteristics of organizational culture include:

• Attention to detail 
• Emphasis on outcome and results 
• Emphasis on people and relationships
• Aggressiveness or competitive nature

Organizational cultures are comprised of all of these characteristics to some degree. However, the prioritization and value put to each characteristic will vary depending on the company and its type of culture.

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An Introduction to Design Science pp 41–75 Cite as

Research Strategies and Methods

• Paul Johannesson 3 &
• Erik Perjons 3  
• First Online: 22 July 2021

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Researchers have since centuries used research methods to support the creation of reliable knowledge based on empirical evidence and logical arguments. This chapter offers an overview of established research strategies and methods with a focus on empirical research in the social sciences. We discuss research strategies, such as experiment, survey, case study, ethnography, grounded theory, action research, and phenomenology. Research methods for data collection are also described, including questionnaires, interviews, focus groups, observations, and documents. Qualitative and quantitative methods for data analysis are discussed. Finally, the use of research strategies and methods within design science is investigated.

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Inbound Links: What Are They and How They Help

Stephan Miller - Guest Contributor

What are inbound links?

Inbound link-building tactics, tools and technologies to help you build inbound links, how to measure the quality of backlinks, other types of links, start building your inbound link strategy, learn how inbound links signal trust and authority to search engines..

As a small business leader, CMO, or marketing professional, you know the importance of SEO for driving traffic and boosting your online presence. In fact, you may have heard that inbound links are one key to boosting your search engine rankings.

But you may not know what an inbound link is or how to create an SEO strategy . This article is your roadmap to understanding and using inbound links. We'll break down the basics, explain their importance, and provide actionable strategies you can implement to attract high-quality links to your website.

By the end of this guide, you'll have a clear understanding of how to use inbound links to achieve higher rankings, increase website traffic, and build a stronger online presence for your business.

According to Gartner, inbound links are links from sources other than search engines that lead directly to a page on your website. [ 1 ] If you think of your website as a city, you can imagine inbound links are like highways connecting you to other important locations. The more links that lead to your site, the easier it is for people to find and visit it.

But these links aren't just pathways. They have more power than that. They can also significantly boost your search engine ranking. Inbound links represent a "vote of confidence" from other sources as homepages receiving many inbound links likely rank higher in search engine results pages (SERPs). [ 1 ] In other words, the more high-quality inbound links you have pointing to your site, the higher it will rank in search engines.

For SMBs, ranking in search engines can mean the difference between success and failure. The top results on Google receive most of the clicks for a given search term, while clicks significantly dwindle for lower-ranking positions. Inbound links are the key to unlocking this prime real estate and attracting qualified traffic directly to your website. By building a strong backlink profile, you'll increase your website's visibility and attract potential customers actively searching for your products or services.

Why are inbound links important?

In the competitive landscape of the internet, standing out from the crowd is important for SMBs. While many marketing channels compete for your budget, inbound links offer a powerful and cost-effective way to achieve your goals. Here are five key benefits that make inbound links your secret weapon for online success:

1. Higher search engine rankings

Imagine spending a fortune on advertising only to have potential customers miss you entirely. That's the harsh reality for businesses neglecting SEO. Inbound links act as votes of confidence for your website, influencing search engines like Google to rank you higher in relevant searches.

This translates into organic visibility, meaning potential customers discover you naturally without paying for ads , and smart CMOs know this. Search engine optimization led all digital channels as a priority for marketers in 2022, with a 45% expected investment increase, according to Gartner. [ 2 ]

2. Attract high-quality traffic

Not all website traffic is created equal. Inbound links bring qualified visitors who are already interested in what you have to offer. Unlike cold leads from paid advertising , these individuals have already clicked on a link from a trusted source, indicating a pre-existing interest in your content or industry. This translates to higher conversion rates and more customers for your business.

3. Establish brand authority and credibility

Inbound links are like being featured in a prestigious industry publication. Earning links from reputable websites signals to both search engines and users that you're a trusted source of information in your field. This builds brand authority and credibility, making you stand out from the competition and attracting more potential customers who trust your expertise.

4. Boost brand awareness and visibility

Inbound links help your website gain exposure beyond your immediate audience. When your content is linked to various sources, it reaches a wider range of potential customers, increasing brand awareness and recognition. This broader visibility builds trust and credibility, establishing you as a legitimate player in your market.

5. Cost-effective growth strategy

Compared to paid advertising, inbound links offer a sustainable and cost-effective approach to online growth. While ad campaigns require ongoing investment to maintain visibility, well-built inbound links continue to drive traffic and boost your SEO ranking over time, offering long-term value without constant financial drain.

With a handful of digital channels taking almost half of CMO's budgets (44.2%), inbound links provide a strategic advantage by offering organic growth opportunities without breaking the bank. [ 3 ]

Now you understand the power of inbound links, but how do you actually attract them? Here are some effective tactics to get you started:

1. Guest blogs

Contribute valuable content to relevant websites in your industry. Gartner's Ignition Guide to Formalizing an SEO Strategy as a Digital Marketing Leader emphasizes the effectiveness of guest posting, stating, "Guest posting and PR coverage efforts can help you get backlinks for your content. [ 4 ] " By sharing your expertise on established platforms, you gain exposure to a new audience and earn valuable links back to your website.

Remember, target high-quality pages with good domain authority and page authority for maximum impact. Focus on creating content formats like listicles, guides, surveys, infographics, and expert opinions, as they naturally attract more links due to their shareability.

2. Broken link building

You can turn the broken links on someone else's website into a link-building opportunity. Find relevant websites with broken links to pages similar to yours, then offer your high-quality content as a replacement. By fixing their broken link and providing valuable information, you earn a link and improve the user experience on their website.

3. Outreach

Direct outreach can be a powerful tool. Identify relevant websites, bloggers, and influencers in your industry and reach out with personalized messages. Offer to contribute content, collaborate on projects, or simply share your expertise. Building genuine relationships can lead to natural link opportunities as others discover the value you provide.

4. Create high-quality content

Content is king . Creating informative, engaging, and valuable content naturally attracts links. Conduct thorough research, offer unique insights, and optimize your content for search engines. The more valuable your content is, the higher the chance others will link to it as a trusted source.

5. Promote your content

Creating great content is only half of the equation. You also need to promote it actively to reach a wider audience and increase the chances of attracting backlinks. Share your content on social media , engage in online communities, and consider submitting it to relevant directories. The more visibility your content gets, the more likely it is to attract attention and valuable links.

Building a robust backlink profile takes time, effort, and the right tools. However, there are plenty of tools available that will help you streamline the process and track your progress.

Link management software will give you a bird's-eye view of all your inbound links, their source, quality, and impact. These platforms come with a variety of features allowing you to:

Discover all the inbound links pointing to your website, even those you may not be aware of.

Analyze the authority and relevance of each backlink to understand its true value.

Identify and disavow spammy or harmful backlinks that could harm your SEO.

Monitor your overall backlink profile growth and see how it impacts your search engine ranking.

Some of this software comes with a broken link discovery feature , which will:

Scan relevant websites for broken links on pages related to your niche.

Offer your high-quality content as a replacement, providing value to the website owner and potentially earning an inbound link.

Streamline the process of contacting webmasters and suggesting your content as a replacement.

Those with a link analytics feature can:

Track how often people click on links from other websites.

See which websites are sent to you the most traffic through inbound links.

Identify the inbound links driving the most traffic and engagement.

Benchmark your link profile against your competitors and identify areas you can improve.

While having a large number of links pointing to your website might seem impressive, it's important to focus on quality over quantity. High-quality inbound links from relevant and authoritative sources carry significantly more weight in the eyes of search engines. Here are key factors to consider when assessing the quality of your inbound links:

Domain authority (DA): This metric, often provided by SEO tools , indicates the overall strength and authority of a website. Links from websites with high DA carry more weight in boosting your search engine rank.

Page authority (PA): Similar to DA, PA measures the authority of a specific web page, and inbound links from pages with higher DA are more valuable.

Relevancy : A backlink for a website in your niche or industry holds more value than a link from a completely unrelated website.

Link placement: Links embedded within the content, particularly in the main body text, are generally more valuable than those placed in footers, sidebars, or comment sections.

Link type: "Do-follow" links pass on more authority, while "no-follow" links don't directly impact your SEO ranking but can still drive traffic and brand awareness.

Anchor text: The text used to link to your website should be relevant to your content and brand.

The quality of your backlink profile as a whole also matters. It should be diverse. A natural backlink profile includes links from various sources, not just a few high-authority websites.

While inbound links are the focus of this article, it's important to understand the broader landscape of links. Here are two other valuable types of links you should be aware of.

Outbound links

Understanding the difference between inbound links and outbound links is key, even though they can both be useful. Outbound links are links from your website that point to another website. Your outbound links are some other site's inbound links. Outbound links matter because they:

Improve user experience.

Demonstrate expertise.

Have SEO benefits because search engines consider sites that link to relevant sites more informative.

But be mindful of overusing outbound links because they can dilute your website's SEO value. Choose relevant, high-quality websites and use descriptive anchor text to maximize the benefits.

Internal links

Internal links connect different pages within your website. They:

Make it easier for users to find relevant content.

Spread your website's SEO value across all pages.

Keep users engaged by guiding them to related content.

Strategically using internal links helps both users and search engines understand your website structure and content hierarchy. Use relevant anchor text and prioritize linking to high-value pages to maximize the impact.

If you're looking for new strategies to enhance your business's online presence and boost traffic to your website, building inbound links could be one of the best. It attracts high-quality traffic, boosts your business's authority, and is sustainable and cost-effective.

Your next steps are:

Audit your existing backlink profile

Implement strategic link-building tactics

Create high-quality, link-worthy content

Promote your content across channels

Monitor and analyze your progress

Outsourcing this work is also an option. Here are some resources to help you find an agency that will work with you to improve your backlink profile .

Digital Marketing Agencies

SEO Companies

What Are the Different Types of SEO Services & Strategies?

Steer Clear of These Four Red Flags When Outsourcing SEO Services

Ignition Guide to Refreshing Website Homepages , Gartner

Create Customer-Centric Content for SEO , Gartner

2023 Gartner CMO Strategy and Spend Survey , Gartner

Ignition Guide to Formalizing an SEO Strategy as a Digital Marketing Leader , Gartner

Was this article helpful?

About the author.

Stephan Miller is a freelance writer and software developer specializing in software and programming. He has written two books for Packt Publishing.

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Methodology

• Sampling Methods | Types, Techniques & Examples

Sampling Methods | Types, Techniques & Examples

Published on September 19, 2019 by Shona McCombes . Revised on June 22, 2023.

When you conduct research about a group of people, it’s rarely possible to collect data from every person in that group. Instead, you select a sample . The sample is the group of individuals who will actually participate in the research.

To draw valid conclusions from your results, you have to carefully decide how you will select a sample that is representative of the group as a whole. This is called a sampling method . There are two primary types of sampling methods that you can use in your research:

• Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group.
• Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.

You should clearly explain how you selected your sample in the methodology section of your paper or thesis, as well as how you approached minimizing research bias in your work.

Table of contents

Population vs. sample, probability sampling methods, non-probability sampling methods, other interesting articles, frequently asked questions about sampling.

First, you need to understand the difference between a population and a sample , and identify the target population of your research.

• The population is the entire group that you want to draw conclusions about.
• The sample is the specific group of individuals that you will collect data from.

The population can be defined in terms of geographical location, age, income, or many other characteristics.

It is important to carefully define your target population according to the purpose and practicalities of your project.

If the population is very large, demographically mixed, and geographically dispersed, it might be difficult to gain access to a representative sample. A lack of a representative sample affects the validity of your results, and can lead to several research biases , particularly sampling bias .

Sampling frame

The sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).

Sample size

The number of individuals you should include in your sample depends on various factors, including the size and variability of the population and your research design. There are different sample size calculators and formulas depending on what you want to achieve with statistical analysis .

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Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research . If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.

There are four main types of probability sample.

1. Simple random sampling

In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population.

To conduct this type of sampling, you can use tools like random number generators or other techniques that are based entirely on chance.

2. Systematic sampling

Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.

If you use this technique, it is important to make sure that there is no hidden pattern in the list that might skew the sample. For example, if the HR database groups employees by team, and team members are listed in order of seniority, there is a risk that your interval might skip over people in junior roles, resulting in a sample that is skewed towards senior employees.

3. Stratified sampling

Stratified sampling involves dividing the population into subpopulations that may differ in important ways. It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.

To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income bracket, job role).

Based on the overall proportions of the population, you calculate how many people should be sampled from each subgroup. Then you use random or systematic sampling to select a sample from each subgroup.

4. Cluster sampling

Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.

If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above. This is called multistage sampling .

This method is good for dealing with large and dispersed populations, but there is more risk of error in the sample, as there could be substantial differences between clusters. It’s difficult to guarantee that the sampled clusters are really representative of the whole population.

In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included.

This type of sample is easier and cheaper to access, but it has a higher risk of sampling bias . That means the inferences you can make about the population are weaker than with probability samples, and your conclusions may be more limited. If you use a non-probability sample, you should still aim to make it as representative of the population as possible.

Non-probability sampling techniques are often used in exploratory and qualitative research . In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under-researched population.

1. Convenience sampling

A convenience sample simply includes the individuals who happen to be most accessible to the researcher.

This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results. Convenience samples are at risk for both sampling bias and selection bias .

2. Voluntary response sampling

Similar to a convenience sample, a voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).

Voluntary response samples are always at least somewhat biased , as some people will inherently be more likely to volunteer than others, leading to self-selection bias .

3. Purposive sampling

This type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.

It is often used in qualitative research , where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific. An effective purposive sample must have clear criteria and rationale for inclusion. Always make sure to describe your inclusion and exclusion criteria and beware of observer bias affecting your arguments.

4. Snowball sampling

If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias .

5. Quota sampling

Quota sampling relies on the non-random selection of a predetermined number or proportion of units. This is called a quota.

You first divide the population into mutually exclusive subgroups (called strata) and then recruit sample units until you reach your quota. These units share specific characteristics, determined by you prior to forming your strata. The aim of quota sampling is to control what or who makes up your sample.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

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Intelligent Investment

2024 Global Investor Intentions Survey

Investment activity expected to improve after rate cuts begin.

March 27, 2024 5 Minute Read

Executive Summary

• Our survey of investors worldwide reveals both higher purchasing and selling expectations compared with 2023 amid growing optimism that the real estate investment market will return to normalized levels of activity in the short-to medium-term.
• Although some further yield expansion is expected, this trend should start to reverse by midyear.
• While investors in most markets will remain cautious in H1 2024, expected rate cuts in mid-2024 should underpin improved commercial real estate investment activity in the second half of the year.

Methodology

CBRE surveyed investors in the U.S, Europe and Asia Pacific between November and December 2023. The surveys had 1,400 total responses from investors who shed light on their intentions, perceived challenges and preferred strategies, sectors and markets for 2024. This report combines the findings of the three regional surveys into a global view.

Investor Sentiment

While buying intentions remain weaker, global investors indicated a pickup in overall investment activity is expected.

• Following a subdued year for investment in 2023, investors across all regions indicated that they plan to increase their purchasing activity this year.
• Major reasons for increasing capital deployment in 2024 include capitalizing on opportunities to acquire distressed properties; taking advantage of opportunities in assets where prices have declined sufficiently; and improved expected total returns.

Figure 1: Purchasing and Selling Intentions by Investor Origin

Major Challenges/Opportunities by Investor Type

Private/high-net-worth investors to be most active; equity funds to see increase in buying activity.

Major Challenges for Real Estate Investment

Uncertainty on interest rate movements and mismatch between buyer and seller expectations remain biggest challenges

• Despite improved sentiment, investors indicated that higher-for-longer interest rates and a divergence between buyer and seller expectations remain significant barriers to real estate investment in 2024.
• While fears of a recession have diminished among U.S. and European investors compared with last year, investors from Asia Pacific said that this is one of their biggest challenges for 2024 due to concerns over mainland China’s recovery.
• In terms of debt financing, the greatest challenges for global investors are lower loan-to-value ratios and higher interest expenses. Banks have tightened their lending criteria, with a major focus on interest coverage ratios (ICRs).

Figure 2: Major Challenges for Real Estate Investment

Policy Interest Rates

Interest rates in most global markets are set to fall by mid-2024

• The expected easing of central bank policy rates in mid-2024 should give investors greater confidence in the months ahead.
• CBRE forecasts that both the European Central Bank (ECB) and the U.S. Federal Reserve will begin cutting rates by mid-2024.
• While mainland China continues to lower policy rates to stimulate growth and Japan ended its negative interest rate environment as of March 2024, other Asia Pacific countries are expected to begin cutting rates before the end of the year.

Figure 3: Central Policy Interest Rates (%)

Preferred Strategy

Investors keen to boost returns with value-add & opportunistic plays while utilizing core-plus strategies for stable cash flow

• Preferred strategies for real estate acquisitions diverge across the three major regions to reflect the different market dynamics (i.e., repricing and fundamentals).
• In Asia Pacific and Europe, investors indicated a preference for value-add strategies, with many seeking double-digit IRRs in markets where capital values have declined significantly.
• Most investors in the U.S. opted for opportunistic strategies, and many buyers foresee an attractive entry point in certain markets and sectors by 2024, including potential distressed assets and non-performing loans (NPLs).

Figure 4: Preferred Investment Strategy

Private Equity Dry Powder

Available capital (dry powder) for commercial real estate investment still elevated across all regions.

• Opportunistic and value-add strategies are also a focus of unallocated private equity real estate capital globally. Approximately 41% of all unallocated real estate capital globally is targeting opportunistic and value add strategies.
• While core assets in Tier I markets like New York City, London and Tokyo remain sought after, investors continue to believe asset values have not yet declined enough to match the higher cost of debt.

Figure 5: Global Private Equity Dry Powder Levels for Commercial Real Estate – by Strategy (US$bn)

Preferred Sectors

Multifamily is attracting stronger demand but interest in offices lags across all regions

• From a sector standpoint, residential property continues to gain traction in Europe and Asia Pacific, while easily still the No. 1 choice in the U.S. Investors continue to ramp-up multifamily purchases in key markets in the Nordics, U.K., Australia and Japan.
• The industrial & logistics sector remains a favorite among investors globally, placing either first or second in each region for a second consecutive year. Logistics assets are being targeted in all markets in 2024, due to healthy prime asset rent growth.
• Investor interest in office assets remains muted on the back of hybrid working arrangements in the U.S.. However, Asian and selective European investors continue to favor core assets in prime locations.

Figure 6: Preferred Commercial Real Estate Sector

Preferred Alternative Assets

Debt strategies are growing in importance amid the tight credit market; housing sector sees increased interest.

• There has been a marked increase in investors eyeing student housing and co-living assets.
• Real estate debt remains top of mind for investors, with U.S. and Asia Pacific investors ranking real estate debt as their first and second most preferred alternative asset class, respectively. While not included in the European edition of the survey, debt remains an investable asset class in this region, especially in Southern Europe, where 10-year government bonds remain elevated compared with those in other countries.
• Structural tailwinds continue in the data center sector; however adequate power supply remains a common challenge across regions.

Figure 7: Preferred Alternative Asset Class

Pricing Expectations

Office assets are expected to see further repricing in 2024, with shopping malls in select locations also under repricing pressure

• While overall real estate investment activity is expected to pick up moderately in 2024, investors foresee further repricing throughout the year.
• Investors are focused on discounts for value-add and core office acquisitions in all regions. Many buyers believe that further price erosion and increased tenant demand are needed to justify current overpricing.
• Investors anticipate less repricing pressure on the hotel and residential sectors. Hotels remain in a cyclical recovery phase, while structural tailwinds will remain for the housing sector (i.e., multifamily).

Figure 8: Pricing Expectations in 2024

Aggregated Yields Across Sectors and Regions

Significant asset repricing has been observed in the United States and Europe than in Asia Pacific.

• The last stage of the repricing cycle will end a significant expansion in cap rates over the past 24 months. U.S. and European assets have seen much greater cap rate expansion than those in Asia Pacific.

Figure 9: Aggregate Yields (%) Across Sectors

Cross-border Investment

Despite reduced cross-border capital flows , investors remain active in Tier 1 global markets.

• Industrial & logistics remained the most preferred commercial real estate sector by global investors, attracting the most cross-regional capital in 2023. Multifamily also saw strong interest, with 18% of cross-regional flows targeting the sector in H2 2023.
• London is a clear winner in terms of cross-border investment, with the current pricing and forecast returns across the residential, industrial and core office sectors attractive to global investors. Investors also looked at established markets that have seen adequate repricing and liquidity, such as New York, Toronto and Paris.
• Tokyo remains the favorite for cross-border capital deployment in Asia Pacific, as investors remain attracted to the prospect of low cost of debt and stable income streams. Sydney and Seoul are seeing investor interest as well, particularly for core assets at attractive price points.

Figure 10: Top 20 Global Cities – Cross-border Investment Activity in 2023 (US$)

Investment destinations

Chris ludeman, global president, capital markets.

" We believe that commercial real estate activity will pick up in the second half of 2024, with expectations that the Federal Reserve will begin the rate cut cycle in the middle of the year. The U.S. residential property sector continues to attract capital due to a significant housing shortage. The industrial sector also has solid fundamentals and we continue to see retail and hospitality outperforming. Where are the opportunities? We need to follow the people, the jobs and the most business friendly environments. Sun Belt and gateway markets remain top destinations for investment. We are now seeing a gradual shift back from credit solutions to equity amid a growing belief that the market has weathered the storm. While there may be some distress due to higher-for-longer interest rates, there will be opportunities for investors to transact at what we believe to be the turning point of the market."

Chris Brett, Head of Capital Markets (Europe)

"Investors are showing a greater desire to be active in the market, with inquiry levels in the first few months of the year higher than what we expected. However, these conversations need to be converted into transactions. A recovery in transactional activity will be driven by the U.K., followed by the Netherlands, Southern Europe (Spain and Italy) and Poland. Industrial assets remain a favorite for investors, with repricing for this asset class happening much faster than for other asset classes, underpinned by stronger rent growth. This is the same story in the residential sector, which continues to see strong demand and durable income streams amid material undersupply, particularly for multifamily and student accommodation. Value-add remains the preferred strategy in Europe, mostly because core product is now available at value-add pricing. This strategy will be most popular in markets where pricing has moved the most (U.K. and Netherlands) and in the Nordics, where some public companies are under pressure and may have to offload some core product at value-add pricing. Retail is the one sector in Europe that best suits the value-add story, alongside select office assets in central locations within Tier I markets.”

Greg Hyland, Head of Capital Markets (Asia Pacific)

"Investors are now underwriting that we are at the peak of the interest rate cycle and we are seeing confidence return to the investment market. Interest rate cuts later this year will stimulate investment activity. Japan continues to attract significant investor interest due to its low interest rate environment, with expectations that this will continue throughout H1 2024. Once central banks begin cutting interest rates, markets that have been weakest, such as Korea, Australia and Singapore, should see a recovery in investment activity. Structural undersupply and rent growth that is outstripping the rate of asset repricing ensures it remains the region’s most preferred sector. Residential property, particularly multifamily/build-to-rent, shares many of these traits, with undersupply and stable cash flows encouraging investors to look beyond Japan to growing markets such as Korea and Australia. While investors will consider value-add product in the short-term as the market goes through the final phase of price discovery, we anticipate many institutional investors will shift back to core strategies over the course of the year amid a clearer outlook for the debt market.”

Investment outlook

Although the high cost of debt will temper global real estate investment in H1 2024, CBRE expects activity to recover in H2 2024 in response to rate cuts. Global investment volume is forecast to increase by 7% year-over-year.

• U.S. (+5% year-over-year) Total investment volume in the U.S. is expected to increase by 5% year-over-year in 2024, stabilizing after a 45% drop in 2023. Investment activity will be directly linked to movements in the 10-year Treasury yield, which is expected to remain high for the first half of 2024 before declining in mid-2024. This will cause some distress for Class B and C office buildings and for certain assets that were highly leveraged using floating-rate debt amid ultra-low rates.
• Europe (+10% year-over-year) CBRE expects Europe to post the strongest recovery out of the three major regions this year, with total volumes projected to increase by 10% year-over-year. While price discovery continues in the region, commercial real estate valuations are catching up with the rapid change in pricing, reducing the bid-ask spread that is the biggest obstacle for investors in this region. Higher financing costs will continue to put pressure on investors, however, with assets most at risk being those acquired at the peak of the market and having required refinancing.
• Asia Pacific (+5%-10% year-over-year) Following a 26% year-over-year decline in investment volume in 2023, real estate investment activity in Asia Pacific is expected to remain muted in H1 2024. Limited cap rate expansion and high interest rates continue to result in a wide yield-to-debt spread for commercial property as well as a gulf between buyers’ and sellers’ expectations. However, H2 2024 should see a pick-up in investment activity, with most markets projected to return to positive carry by the end of the year. CBRE expects full-year investment volume in Asia Pacific to recover by 5% to 10% year-over-year in 2024.

Figure 11: Global commercial real estate investment volumes (forecast)

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2024 european investor intentions survey.

February 5, 2024

CBRE's 2024 European Investor Intentions Survey was conducted between November 6, 2023, and November 30, 2023.

2024 U.S. Investor Intentions Survey

January 26, 2024

Investors cited higher-for-longer interest rates, tight credit conditions and differing buyer and seller expectations as the biggest impediments to commercial real estate investment activity in 2024.

2024 Asia Pacific Investor Intentions Survey

January 16, 2024

CBRE’s 2024 Asia Pacific Investor Intentions Survey was conducted in November and December 2023. Over 500 responses were received from participants who were asked a range of questions related to their buying intentions, perceived challenges and preferred strategies, sectors and markets for the coming year.

Henry Chin, Ph.D.

Global Head of Investor Thought Leadership & Head of Research, Asia Pacific

• Phone +852 2820 8160

Darin Mellott

Vice President, Head of U.S. Capital Markets Research

• Phone +1 801 869 8014

Tasos Vezyridis

Executive Director, Head of Thought Leadership for Europe

Gus McConnell

Associate Director, Research, Asia Pacific

Jaeyoung Kim

Sr Research Analyst

• Phone +1 212 984 8398

Benjamin Pipernos

Senior Research Analyst, Global Investor Thought Leadership

Greg Hyland

Head of Capital Markets, Asia Pacific

• Phone +65 6224 8181
• Mobile +65 9818 1537

Christopher R. Ludeman

Global President, Capital Markets

• Phone +1 212 984 8330
• Mobile +1 310 227 6309

Chris Brett

Head of Capital Markets, Europe

• Phone +44 20 7182 2848

Kevin Aussef

Americas President of Investment Properties, CBRE

• Phone +1 949 809 3798

James Millon

U.S. President, Debt & Structured Finance

• Phone +1 212 984 8041
• Mobile +1 347 901 3644

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