extant literature in research

Alvita Nathaniel 1 *

AM J QUALITATIVE RES, Volume 6, Issue 3, pp. 45-59

https://doi.org/10.29333/ajqr/12441

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Glaser and Strauss (1967) sprinkled suggestions about the use of the literature throughout their seminal work as did Glaser in subsequent years. They, however, did not lay out a clear and structured overview of how to use the literature. The aim of this paper is to weave together the recommendations from classic grounded theory originators and to describe how, why, and when to review the literature and which literature to review. The paper includes a section debunking the no literature myth followed by descriptions of the three phases of the classic grounded theory literature review—the introduction phase, the integration phase, and the disposition phase. The three phases work together to substantiate, confirm, and enhance an emerging grounded theory and situate it within the existing body of knowledge.

Keywords: literature review, extant literature, grounded theory, classic grounded theory.

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Using scoping literature reviews as a means of understanding and interpreting existing literature

Affiliation.

• 1 College of Education, Health, and Human Services, Kent State University, Kent, OH 44242-0001, USA. [email protected]
• PMID: 20364059
• DOI: 10.3233/WOR-2010-0998

Objective: This article compares and contrasts scoping literature reviews with other established methods for understanding and interpreting extant research literature.

Methods: Descriptions of the key principles and applications of scoping reviews are illustrated with examples from contemporary publications.

Conclusions: Scoping reviews are presented as an efficient way of identifying themes and trends in high-volume areas of scientific inquiry.

• Databases, Bibliographic
• Research Design*
• Review Literature as Topic*

• Open Access
• Submissions
• Barney Glaser – In Memoriam

When and How to Use Extant Literature in Classic Grounded Theory

Alvita K. Nathaniel, PhD, APRN, BC, FAANP

Professor Emerita, West Virginia University

Glaser and Strauss (1967) sprinkled suggestions about the use of the literature throughout their seminal work as did Glaser in subsequent years. They, however, did not lay out a clear and structured overview of how to use the literature. The aim of this paper is to weave together the recommendations from classic grounded theory originators and to describe how, why, and when to review the literature and which literature to review. The paper includes a section debunking the no literature myth followed by descriptions of the three phases of the classic grounded theory literature review—the introduction phase, the integration phase, and the disposition phase. The three phases work together to substantiate, confirm, and enhance an emerging grounded theory and situate it within the existing body of knowledge.

Keywords:  literature review, extant literature, grounded theory, classic grounded theory.

Introduction

This paper lays out a systematic approach to the literature review that is consistent with the classic grounded theory method as established by Glaser and Strauss (1967) and further by Glaser in subsequent publications. Their ideas about the pre-investigation literature review adhere to the foundational assumptions of the classic grounded theory method including discovery, emergence, and a foundation based upon participants’ perspectives. Through sentences and short paragraphs, Glaser and Strauss sprinkled suggestions about the use of the literature throughout their seminal work, The Discovery of Grounded Theory: Strategies for Qualitative Research (1967) , as did Glaser in subsequent years. They, however, did not articulate a complete and structured overview of how to use the literature. Much has been written in intervening years, mostly focusing on misunderstandings. Few have attempted to piece together Glaser and Strauss’ advice into a cohesive whole. Even the most adamant proponents of classic grounded theory have struggled to rectify Glaser and Strauss’s (1967) suggestions about the literature review with the exigencies of authoritarian social structures that have strict rules for reviewing the literature. This paper explains how a classic grounded theory literature review can be accomplished, even within strict institutional standards. The aim of this paper is to weave together the classic grounded theory originators’ advice and describe what, how, why, and when to review the literature. Recommendations in this paper derive from original sources of classic grounded theory and other proponents of the method but also interweave complementary, sometimes surprising, views expressed by authors of remodeled versions of grounded theory and also advice from general research methods literature.

The grounded theory literature review is defined for this paper as the systematic selection, interpretation, and review of published and unpublished material on a particular topic. The literature may include empirical data, research findings, ideas, theories, recordings, and other collections and may include the work of researchers, scholars, and theorists along with other historic and current grounded sources. A literature review can also include conceptual and opinion pieces that provide insight into others’ thinking about a topic (Creswell & Creswell, 2018). As you read further, you will see that the appropriate grounded theory literature review is intended to be focused, deliberate, and useful.

The preliminary grounded theory literature review does not focus on concepts from a fixed research question, as is customary in quantitative research, because grounded theory research questions begin very broad and evolve as data are collected and analyzed. As Creswell and Creswell (2018) suggest, this can be uncomfortable for researchers since it challenges the accepted approaches of some faculty, ethics committees, and funding sources whose background in research is often quantitative and deductive. This paper proposes strategies to avoid these conflicts and demonstrates that an institutionally required pre-investigation literature review is sometimes acceptable, even to classic grounded theory purists, as a strategy to move forward with research. The paper includes a section debunking the “no literature review” myth followed by descriptions of the three phases of the classic grounded theory literature review—the introduction phase, the integration phase, and the disposition phase.

The No Literature Review Myth

What do classic grounded theory sources have to say about the literature review? Contrary to what some critics have put forth, the originators of grounded theory, Glaser and Strauss (Glaser, 1978, 1992, 1998, 2001; Glaser & Holton, 2004; Glaser & Strauss, 1967) call for an extensive review of the literature, both within the area of study and in other fields. Andrews (2006), an experienced classic grounded theorist, agrees that a preliminary review of the literature is “entirely consistent” with the established principles of grounded theory. The issue of when to, rather than whether to perform the literature review sets classic grounded theory apart from other research methods. Glaser and Strauss established the ideal method of researching the extant literature, while recognizing the practical issues that can arise. They propose arguments in favor of avoiding a pre-investigation literature review but acknowledge that one might be needed.

Since qualitative studies are generally exploratory, with little written about the topic, Creswell and Creswell (2018) agree that researchers must use the literature as a complement to participant-focused inquiry, rather than as a springboard for preconceived questions. In the Discovery of Grounded Theory , Glaser and Strauss (1967) suggest that delaying the empirical and theoretical literature within the area under study is one effective strategy to assure that categories in the evolving theory will not be contaminated by received ideas less suitable to the research focus. Glaser suggested that the researcher should choose areas for the initial literature review that will not pre-conceptually contaminate the emerging theory but will enhance theoretical sensitivity (Glaser, 1998). Dey (2007), who argues in favor of a pre-investigation literature review, nevertheless recognized that Glaser and Strauss did not advise investigators to completely abstain from reviewing the literature, but rather to engage broadly and with literature from other academic and non-academic fields.

Glaser and Strauss’s suggestion to read the literature of different disciplines at the beginning of the research process is consistent with Abraham Kaplan’s position. Kaplan, who believed that a discipline can remain autonomous even though sharing and borrowing the science of others, wrote,

For the domain of truth has no fixed boundaries within it. In the one world of ideas there are no barriers to trade or to travel. Each discipline may take from others techniques, concepts, laws, data, models, theories, or explanations—in short, whatever it finds useful in its own inquiries. (Kaplan, 2011/1998, p. 4)

As Glaser and Strauss suggested, then, reading widely from other disciplines broadens the researcher’s knowledge and sensitivity to a realm of theoretical codes that might not be present in other disciplines’ literature. Dey (2007) and Hallberg (2010) agree that working with a wide range of interdisciplinary ideas, including Glaser’s coding families, sharpens theoretical sensitivity, avoiding “the blinkered vision of an established theoretical framework” (Dey, 2007, p. 75). In addition to reading widely from the research of other disciplines, students of Glaser and Strauss were encouraged to read good theoretical studies (Stern & Covan, 2001) in order to become familiar with the structure of the theory.

Glaser (1998) initially reiterated that the researcher should avoid a phenomenon-specific pre-investigation literature review in the substantive area, but should review the literature when the grounded theory is nearly completed. Reacting to practical exigencies, however, Glaser later acknowledged that the investigator must fulfill the basic institutional requirements of the university or funding source because, without it, the research would not be possible. He wrote,

If the regulations state that any Ph.D. research proposal must be accompanied by a literature review, then do a literature [review]. If the regulations state that a literature review must become the first paper of the Ph.D., then again, give them a literature review. (Glaser, 2011, p. 56)

Guthrie and Lowe (2011) agreed with Glaser when they advised that, when faced with institutional requirements the researcher should “fully comply with the university regulations, and write a logically plausible (but quite irrelevant) literature review” (p. 61). Glaser (2011) and Guthrie and Lowe (2011) agree that novice grounded theorists should be assured that they can discover a classic grounded theory even if required to perform extensive pre-investigation literature reviews.

The reasons for avoiding an extensive pre-investigation literature review, however, are integral to the assumptions of the method—that is, a pre-investigation literature review threatens to derail emergence and diminish the focus on the participants’ perspectives. Glaser points out that the results of an early literature review are inimical to generating grounded theory. As suggested by Glaser and Strauss (1967) and Glaser (1998), there are a number of interrelated reasons to avoid a pre-investigation literature review.

First, the investigator may become enthralled, or “grabbed,” by received concepts that neither fit nor or are relevant (Glaser, 1998). Although it is possible that some concepts can be borrowed from extant theory if they fit the data (Glaser & Strauss, 1967), other concepts in the literature may be fascinating to the investigator but wildly unrelated to the processes occurring in the study participants’ lives or simply unimportant to the participants. Dunne (2011) is correct that this is a pragmatic view because it can save time and energy by guiding the researcher away from avenues that may be of little ultimate importance.

Second, the investigator may derail a potential emergent theory through a preconceived academic or discipline-specific problem of no relevance to the substantive area of the research (Glaser, 1998). Dey (2007) labeled that “ploughing ahead along an established theoretical furrow regardless of the diversity and richness of the data” (p. 175). This often happens when the novice researcher joins a supervisor’s ongoing study. The investigator may find that merely selecting data for a received concept hinders the generation of new categories because the major effort is data selection, rather than discovery or emergence (Glaser & Strauss, 1967). For example, for a PhD thesis, Amélia Didier was asked to join an ongoing faculty study about interdisciplinary health care teams. Didier (2019) chose to use classic grounded theory to learn about hospitalized patients’ perspectives on interdisciplinary teams. She quickly learned that patients had no knowledge of nor interest in interdisciplinary teams. The patients were focused on seeking aufgehobenheit, a German term which encompasses the concepts of safety, dignity, humanity and respect (Didier, 2019, p. iv). In other words, patients main concern was to feel in safe hands, well cared for. Fortunately, Didier was allowed to proceed with the grounded theory, focus on the patients’ main concern, and develop the rich and useful theory of aufgenhobenheit.

Although Didier (2019) was successful in re-directing her research focus, Kaplan agreed with Glaser and Strauss’s concern, proposing that

officers of the professional associations, honored elders, editors of journals, reviewers, faculties, committees on grants, fellowship and prizes—all exert a steady pressure of conformity to professional standards. . . . The innate conservatism, or at least inertia, of professional standards has from time to time stood in the way of scientific progress . (Kaplan, 2011/1998, p. 4)

Guthrie and Lowe (2011) go so far as to propose that those who demand to be in control cannot let go of their pre-understanding—they are likely “experts in their fields” who think they know the answers already.

Third, the investigator may become imbued with speculative, non-scientifically related interpretations and theoretical connections, likely through a review of deductive, pre-conceived theories (Glaser, 1998). Every discipline has popular speculative theories, philosophical frameworks, or conceptual models written in the jargon of the profession. Use of these interpretations and theoretical connections can hijack inductive concept emergence if they are not relevant or do not fit the data. Suddaby (2006) suggests that this will force the researcher into testing hypotheses, rather than directly observing. Thornberg and Dunne (2020), on the other hand, warn that when researchers view an extant theory as correct or superior, they will become “data resistant, disregarding or overlooking data that do not support that particular theory, and their theory will act as a self-fulfilling prophecy” (p. 207).

Fourth, the investigator may become awed by famous or celebrated scholars, theorists, or researchers, thus detracting from the investigators’ own self-valuation. Glaser (1978) proposed that being doctrinaire or revering ‘great scholars’ interferes both with sensitivity to the data and with generating ideas that fit and work best since the investigator may configure the data to fit the doctrine. He also wrote that pre-conceived or ungrounded theory “derives from any combination of several sources; whims and wisdoms of usually deceased great men, conjecture and assumptions about the “oughts” of life, and other extant speculative theory” (Glaser, 1978, p. 143), and thus is unsuited to use in grounded theories. Strauss and Corbin (1998) agreed with this concern proposing that it is not unusual for students to become enamored with a previous study to the point that they are nearly paralyzed.

Fifth, the investigator may become what Glaser terms “rhetoricalized,” relying on rhetorical jargon that is in vogue at the time, rather than allowing theory to emerge. Rhetoricalized jargon is a discipline’s authoritarian method of control. It does not pass the test of time well and may fail to cross disciplinary boundaries, limiting the scope and power of emerging theories.

Sixth, the investigator can completely miss the focus of a (yet to emerge) theory. Since classic grounded theory relies on emergence, a purely speculative pre-investigation literature review wastes valuable time and energy and can send the researcher off on useless tangents.

The researcher must understand why a preliminary review of the literature is not recommended. Equally important are guidelines on the timing and the phases of the literature review, the types of literature to be reviewed, and the importance of the literature when situating the new theory among extant works. The following discussion focuses on these issues and offers a three-phase literature review process.

Phases of the Classic Grounded Theory Literature Review

The classic grounded theory literature review is neither performed nor presented in the traditional hypothetical-deductive manner. The discursive literature review, which is traditional with other research methods, is structured around specific concepts articulated in the research question, conducted before the investigation is initiated, and presented in writing preceding the research findings. This is an immediate problem for grounded theories in which research questions are broad, and specific concepts are unknown at the beginning of the study. Creswell and Creswell (2018) acknowledge that the literature review in qualitative studies may be conducted and presented in a manner that is congruent with the assumptions of the method. The qualitative literature review may be conducted in a serial fashion and presented in a separate section, included in the introduction, or woven into the study as is generally the case with classic grounded theory. Creswell and Creswell also acknowledge that the literature is used less often to set the stage for grounded theory studies, though the eventual breadth will be comparable.

The eventual scope of the grounded theory literature review is both broad and specific—at different points in the research process. Most classic grounded theorists perform the literature review in three phases, with one caveat: they read widely in other fields throughout the research process in order to increase theoretical sensitivity. The three phases include the introduction phase , which makes the case for the study; the integration phase , in which the extant literature is identified, synthesized, and integrated into the theory; and the disposition phase , which situates the new theory in relation to the extant theoretical and empirical literature.

Introduction Phase of the Literature Review

The introduction phase prepares the researcher and builds the case for the research study. The multi-faceted literature review during this phase sets the course for the research. For the reader, it makes the case for the study, which is especially important when institutional and funding entities require a pre-investigation literature review for the research to proceed. The introduction phase of the literature review gives a general overview of the substantive area and indicates gaps in the knowledge base if those are known. It demonstrates the investigator’s familiarity with the substantive area, describes the method of investigation, describes the study population, and often gives clues as to the investigator’s worldview or philosophic stance.

Review of Literature in the Substantive Area.

As noted previously, the ideal review of literature in the substantive area should be delayed until the integration phase, which is not to suggest that the classic grounded theorist enters a study “empty-headed” as some would suggest. McCallin (2006) reminded us that students and others tend to misunderstand that each research study is about something in the beginning, even though the specific problem is unknown in the early stages. Hallberg (2010) is right that any researcher has acquired years of academic and professional knowledge in their disciplines. Although they moved away from many of the original classic grounded theory tenets, Strauss and Corbin (1998) also made the assumption that most professionals are familiar with the literature in their field. Glaser often reminded Ph.D. candidates in his seminars that they (Ph.D. students) are the institutionally and self-selected elite. Investigators generally begin studies with a depth and breadth of knowledge and a sense of curiosity—something they are interested in. Many will have identified a gap in knowledge early in their academic program or professional career. As a supervisor to Ph.D. students, Andrews (2006) discovered that some will enter the field with a clear question in mind. Since the classic grounded theory is an inductive method of discovery, investigators will begin by asking themselves. “What is going on” with this group of people in this situation?

Ideally, then, the classic grounded theorist who already has a depth of knowledge would not need to perform an extensive pre-investigation literature review in the substantive area. However, as most classic grounded theorists acknowledge, a literature review in the substantive area may be necessary to verify the investigator’s questions, withstand public scrutiny, establish a defensible rationale for a given project, and fulfill institutional requirements (Andrews, 2006; Ekstrom, 2006; Glaser, 2011; Martin, 2006; McCallin, 2006; Nathaniel, 2006b; Thornberg & Dunne, 2020; Thulesius, 2006). McCallin (2006) wrote,

While the beginner researcher receives that [no literature review] interpretation happily, supervisors and institutional review committees are rather more nervous of such a simplistic approach. Those responsible for student researchers seek some reassurance that the student knows what they are doing, has a general focus, and is at least safe to enter the field. (p. 12).

Creswell and Creswell (2018) admitted that satisfying the reader is more important than the length of the literature review. The researcher must convince the reader that the study was or will be possible in a practical sense, necessary, and potentially significant.

Holton and Walsh (2017) and McCallin (2006) agree that a common strategy to fulfill institutional requirements and satisfy readers is for the investigator to perform a pre-investigation review of the literature that is broad in scope in the substantive area, setting the stage for an exploratory study, while avoiding specific concepts or phenomena. McCallin suggests that the “mental wrestle” for investigators is for the literature review to remain general, avoiding the main interest as much as possible, yet focused enough to meet institutional requirements.

What facets of the literature are reviewed in the introduction phase? In addition to reviewing the general literature around the substantive area, the investigator will review the literature for descriptions of the population of interest, the research method, and often the researcher’s worldview. The researcher may also need to become familiar with population-specific terminology that may be encountered during data gathering.

Review of the Literature Describing the Population. 

Descriptions of the population of interest should include enough information to give readers a glimpse of the context and to grab their interest. The investigator will review the literature for demographics of the study population and other statistics, which may also include a historical review (Rhoades, 2011) of the population. For example, to study the homeless female population in Denver, Colorado, the researcher would review the literature from established sources for the statistics and demographics of the national, state, and city homeless population. Information on weather trends that affect the homeless, crimes committed by or against homeless people, the progression of homelessness, causes of homelessness, special concerns of homeless women, and available resources might also be helpful. If the researcher wants to further limit the study to those who are addicted to methamphetamine, another search of the literature would add information about the prevalence of methamphetamine addiction in the general population versus the homeless population, the risk factors associated with addiction, and the life expectancy of this population. For an exploratory study asking, “what is going on with this population,” this type of literature review may satisfy an institution’s literature review requirement.

Review of the Grounded Theory Methodology/Method Literature

In addition to general literature surrounding the substantive area and the population of interest, the investigator should review the literature about the classic grounded theory method. Although Glaser stipulated that grounded theory is a general method that can be used with both qualitative and quantitative data, it is found to be the most frequently used qualitative method. Yet, paradoxically, many researchers, thesis/dissertation supervisors, ethics committees, and readers are poorly versed in the classic grounded theory methodology, therefore misinterpretations abound. Thulesius (2006) advised the researcher to begin a classic grounded theory study to educate readers on the method’s background, language, procedures, and the rationale for choosing grounded theory. Further, Thulesius proposes that reading the appropriate grounded theory method books repeatedly throughout the research process is the most important facet of reading the literature. The most often cited primary sources of information on the method are The Discovery of Grounded Theory: Strategies for Qualitative Research by Glaser and Strauss (1967), Theoretical Sensitivity: Advances in the Methodology of Grounded Theory (Glaser, 1978), and Doing Grounded Theory: Issues and Discussion (Glaser, 1998). All of Glaser’s subsequent publications are also excellent primary sources for classic grounded theory as well as Grounded Theory: The Philosophy, Method, and Work of Barney Glaser (Martin & Gynnild, 2012), Classic Grounded Theory: Applications with Qualitative and Quantitative Data (Holton & Walsh, 2017), and Experiencing Grounded Theory: A Comprehensive Guide to Learning, Doing, Mentoring, Teaching, and Applying Grounded Theory (Simmons, 2022) Since all peer reviewers are experienced classic grounded theorists, methodological papers published in the Grounded Theory Review are also good sources for classic grounded theory methodology and original theories published there can serve as exemplars for novice researchers.

Because classic grounded theory is vastly different from other methods, a review of the methodological literature should be comprehensive, descriptive, and explanatory. A meticulous review of the method literature can forestall questions and objections from Ph.D. supervisors, ethics committees, and funding sources. The researcher should review the literature on the use of grounded theory’s inductive approach as contrasted with the hypothetical-deductive approach used in many other methods. The review of methods literature should also include the method’s dependence upon participants’ perceptions, conceptualization, category development, and theoretical relationships. Procedures, processes, and language of classic grounded theory that should be covered in the literature review include sampling; data sources; data collection methods; data recording methods (generally field notes); emergence; constant comparison; open, selective, and theoretical coding; memoing; memo sorting; identification of the core category; unique criteria for rigor in grounded theory; and standard ways of writing and presenting grounded theories. A description of the method’s procedures also serves as a primer for grounded theory language. It is always helpful when research supervisors unfamiliar with grounded theory also read the method literature.

Although Glaser and Strauss wrote the seminal work from which all grounded theory has developed, Strauss and others went on to modify the method and write about grounded theory’s perspectives and procedures in significantly remodeled ways—adding procedures, philosophic foundations, new language, and adapted understandings. So, subsequent publications by Strauss and Corbin (Corbin & Strauss, 1997, 2015; Strauss & Corbin, 1998), Charmaz (Bryant & Charmaz, 2016; Charmaz, 2000, 2006), Clarke (Clarke, 2005; Clarke et al., 2016, 2018), Birks and Mills (Burks & Mills, 2015), and others, although easy to find in the literature, cannot be used to describe the classic grounded theory.

Review of Extant Theory Literature in the Introduction Phase

Except when modifying an existing grounded theory or developing a formal grounded theory, a review of extant theories should not be performed in the introduction phase of the grounded theory literature review. The goal of classic grounded theory is to use inductive reasoning with a particular type of data from which concepts, categories, and theoretical relationships emerge. As noted previously, reviewing extant theories before gathering data puts the investigator at risk of consciously or unconsciously adopting speculative pre-conceived concepts and finding ways to configure data to conform to them. There are two main exceptions to this tenet. First, extant grounded theories must be reviewed during the introduction phase if the purpose of the research is to modify the existing theory. For example, data from front-line nurses’ experiences during the Covid-19 pandemic might easily modify Nathaniel’s (2006a) theory of Moral Reckoning in Nursing or Andrews’ (2003) theory of Making Credible: A Grounded Theory of How Nurses Detect and Report Physiological Deterioration in Acutely Ill Patients, both of which were developed in the early 21 st century prior to the pandemic. The extremely difficult context of health care during height of the pandemic vastly affected patients,’ physicians,’ and nurses’ relationships; the structure of health care delivery; and previously rigid ethical parameters, which shifted with each new crippling wave of the pandemic. New, more current studies could modify these two theories to fit real-world circumstances and therefore become more explanatory, predictive, and useful for nurses who might face similar situations during future pandemics or other catastrophic events.

Second, grounded theory researchers must review the theory literature when developing formal grounded theory. Up to this point, the discussion has focused solely on substantive theory, or theory of the middle range that focuses on real-life issues in specific contexts. Formal theory, on the other hand, raises the level of abstraction and expands the context. Glaser defined formal grounded theory as an overarching theory of a “substantive grounded theory core category’s general implications [broader than the initial context] generated from, as wide as possible, other data and studies in the same substantive and in other substantive areas” (Glaser, 2007b, p. 4). Thus, the investigator preparing to develop a formal grounded theory must review theoretical literature in the introduction phase. The literature review, in this case, is restricted to empirical research and theories, often from disparate disciplines, that apply directly to the core category and concepts of the original substantive theory. But, to reiterate, unless the investigator intends to modify an existing theory or develop a formal grounded theory, extant theories should not be reviewed during the introduction phase.

Philosophical Foundations Literature

Many universities require Ph.D. students to review the literature surrounding the philosophical foundations of the research method used in a study. Creswell and Creswell (2018) agree with Annells (1996) that the researcher should include philosophical assumptions or worldviews of qualitative research in the literature review. However, the philosophical foundations of classic grounded theory are as controversial as the literature review itself since Glaser and Strauss (1967) did not articulate a philosophical foundation for the method. In fact, Glaser stated emphatically that grounded theory is not based upon a particular philosophy (personal communication). So, what philosophical literature does the investigator review when the method has no established philosophical foundation?

If a review of the philosophical foundations of the grounded theory method is institutionally required, there are three options, each of which includes an acknowledgment that the method has no philosophical foundation. The first option is to present the researcher’s own worldview as the foundation of the research study. For example, Holton and Walsh (2017) acknowledge that they hold the critical realist perspective. Thus, their research investigations and analyses are conducted through the critical realist lens. A literature review of critical realism with its implications for the research processes would be appropriate for the introduction phase of the literature review. A second option is to adopt a formal theory of science that includes inductive logic, such as that of Charles Sanders Peirce (1901/1992), as a philosophical foundation for the method. If the investigator chooses to use a philosophy of science as the philosophical foundation, the literature review should include primary source ontology and epistemology elements that logically fit with the classic grounded theory method. The third option is to select symbolic interactionism as the philosophical foundation of the method. Even though Glaser denied a specific foundation of the method, he recognized that symbolic interactionism could serve as a sensitizing agent for grounded theory research (personal communication). That is, symbolic interactionism is not the foundation of the method but can be used as a lens through which to conduct and analyze grounded data. If a researcher chooses to propose symbolic interactionism as the foundation of a research study, the literature review should use primary sources to describe the elements that affect the research process.

Population-Specific Terminology

Sometimes, researchers seeking to closely follow the procedures of classic grounded theory worry that any review of any literature, including sources that will help them to understand the study population, will violate the method’s precepts. For example, a researcher studying problems encountered by those interested in cryptocurrency found that new terms and unfamiliar language surrounding virtual currency had developed. For example, terms such as ashraked, atomic swap, and blockchain, are not part of common language. Understanding the language or terminology is critical in collecting and analyzing data. The researchers could not pierce the language barrier without familiarizing themselves with these and other critical terms. For that reason, familiarizing oneself with population-specific language is preparatory to a study and is not considered part of the review of literature.

Integration Phase of the Literature Review

The integration phase of the literature review occurs during the data collection and analysis stages of the research process. Finally! A focused literature review of the substantive area is an essential element at this point in grounded theory development. Classic grounded theorists use extant literature in a systematic, yet entirely different manner from quantitative and most qualitative methods. The purpose and process of the literature review in classic grounded theory is unique and the type of literature to be reviewed can be vast—unrestricted by conventional rules. According to Glaser and Strauss (1967) theorizing begs for comparative analysis, creating what Creswell and Creswell (2018) labeled, a reciprocal relationship between theory and data. Once the analysis is well underway, the grounded theorist compares the literature to the emerging theory and uses the literature to support, corroborate, and illustrate the emerging theory. Glaser (1978) believed that well done grounded theories can transcend previous works while integrating them into the new theory, thus providing a theory of greater scope. Martin (2006) contends that grounded theory can help researchers to cross disciplinary boundaries and use existing literature to develop more potent theories. Strübing (2007) points out that the secret lies in how to properly use previous knowledge. Following is a discussion of the process of the literature review in the integration phase and the types of literature to be considered.

Process of Literature Integration

Since grounded theory is an inductive method and the problem is not known beforehand, the focused literature review cannot occur until data collection is underway and analysis has begun. Glaser (1998) proposed that the literature review in the substantive area should be done when the theory is nearly completed, during the sorting and writing the theory. Specifically, Holton and Walsh (2017) and Glaser and Strauss (1967) suggested that similarities and convergences with the literature can begin to be reviewed once the analytic core of categories emerges. At that time the literature can be used as additional data to be constantly compared with the emergent concepts, elaborating emerging concepts and directing further theoretical sampling (Holton & Walsh, 2017).

Grounded theory analysis occurs quickly and each new hypothesis directs the researcher to new sources of library material and exceptionally revealing comparison groups (Glaser & Strauss, 1967). To be clear, as concepts emerge from the data, literature searches are conducted for those specific concepts or others that are closely related. For example, Ekstrom (2006) was led to papers about how women experienced menopause and papers about status passages, since these were the concepts emerging from her data. Stern turned to the literature on fathering and family dynamics (Stern & Covan, 2001). Once the concepts and categories emerge from the data and it is time for a literature search, the researcher must carefully choose sources of data and search terms.

Library databases serve as invaluable tools for locating existing literature in the electronic age. However, Boell and Cecez-Kecmanovic (2010) warn that databases are limited in their coverage since single databases only cover a subset of academic journals. Further, some databases do not include all papers included in each journal. For that reason, Boell and Cecez-Kecmanovic propose that researchers conduct searches of multiple databases. But what are the best search terms? Glaser and Strauss (1967) instructed their students to cultivate several functional synonyms in order to fully explore relevant literature. For example, when searching the literature for moral reckoning, literature on moral distress, moral outrage, moral agony, moral uncertainty, and other possible synonyms was searched. Boell and Cecez-Kecmanovic recognize that specific topics can be described using an almost indefinite number of words. One strategy to overcome this problem is to scour books such as a thesaurus or Rodale’s (1978) Synonym Finder using a snowball technique by moving from one term to another in an attempt to gather many possible common language search terms. Glaser and Strauss focused on library literature and methods to search a brick-and-mortar library, but in the electronic age researchers have almost unlimited access to many types of literature.

Types of Literature to Integrate

In grounded theory, there is no clear distinction between data and literature since existing theoretical and empirical literature can be integrated into an emerging theory. Simmons (2022) states that one unique feature of classic grounded theory is that literature is often treated as if it were data. In fact, Glaser (2007a) proposed that “all is data,” blurring the line between data and empiric literature. Glaser and Strauss (1967) stressed that the decision about what sources of data to use is crucial to the outcome of the study. So, what types of literature-cum-data will the researcher use?

Many sources of library material are available for comparison and integration. In fact, Glaser and Strauss (1967) proposed that a researcher should use any relevant material bearing on the substantive area. One of the best sources of literature is existing behavioral research, which offers data, categories, theoretical relationships, and illustrations. Most types of qualitative research are grounded in the data but should be carefully evaluated before being integrated into or compared with the emerging theory. Once the emerging theory has shape, extant themes, ideas, hypotheses, and concepts can be analyzed, compared, and integrated if they are found to be relevant and if they fit and work. The researcher must be careful, though, because words used in existing literature may not have the same meaning or relevance as the emerging theory. Other sources of library data include letters, diaries, newspaper accounts, government documents, speeches, sermons, annual reports, and company files (Glaser and Strauss, 1967). For example, Glaser and Strauss found a collection of interviews with very poor New Yorkers in the early 20 th century, which offered a vivid picture of poverty during that era (1967). These types of documents tend to be used almost exclusively for verification of the emerging theory or for illustration. In today’s age of information technology, there are many sources of data. Blogs, for instance, can offer rich information that can be useful in grounded theory studies.

Formal grounded theory, especially, makes use of empiric literature and existing theories. Glaser (2011) suggested that a major source of data for generating a formal grounded theory includes a secondary analysis of data collected for other reasons. Caches of secondary analysis include those of interviews, speeches, collections of letters, journals, and so forth. Glaser wrote, “But it amazes me how many data sources just bursting for use in a formal grounded theory such as readers, journals, documents, researched newspaper articles, or areas of much literature coverage with arrays of articles” (Glaser, 2011, p. 262). When the analysis is complete, the literature review has been fully integrated, and the theory has been written the researcher is ready to present a disposition of the newly emerged theory.

Disposition Phase

The disposition phase occurs after the theory is written. During this phase, the researcher prepares the discussion section of the research study, often chapter five of a traditional thesis or dissertation. Creswell and Creswell (2018) agree that this is appropriate for a grounded theory study. The ongoing development of knowledge is the incessant interaction between induction and deduction between empirical and theoretical realms (de Groot, 1969) in which hypotheses link the two worlds together (van de Wijngaert et al., 2014). Therefore, the literature reviewed at this point should not be an exhaustive (and exhausting) review of all literature, but rather a carefully analytic meaningful review of related extant empiric and theory literature. Stern and Covan (2001) wrote,

Without reverence to existing knowledge, even grounded theories remain sterile: a researcher is unable to add to the body of knowledge expected in a research enterprise. In other words, without this step of comparing and coordinating the work of other scholars, a researcher may not develop his or her theory completely and others may not be able to develop a theory further in the future. (p. 25)

In this section of the written research study, the researcher provides a scholarly discussion about the position and contribution of the new theory in relation to extant literature. During the disposition phase, the order and relative position of the new theory is established in terms of the discipline’s knowledge base, placing the theory among other researchers’ work on the same ideas. The discussion in this phase of the literature review can add a new dimension to existing work (Stern & Covan, 2001) or extend the theory of others. The new theory will usually, if not invariably, “transcend diverse previous works while integrating them into a new theory of greater scope than extant ones” (Glaser, 1978, p. 10). The fully emerged theory becomes a powerful instrument that can clarify, synthesize, and organize prior grounded theories and refute flawed theories, thus contributing to the knowledge base of a discipline. Thus, each work adds to or corrects those before it, moving closer to knowledge that is true and correct—what Peirce called moving humankind toward the final opinion (Houser & Kloesel, 1992) . 

The approach to the literature review during the disposition phase is important. Glaser advised his students to measure extant literature against the newly emerged theory, rather than the other way around. He warned researchers to avoid an attitude of reverence for extant works or to search for their own best ideas in previous works in order to legitimate the new theories—“as if they could not be allowed to generate on their own” (Glaser, 1978, p. 137). Nor should there be an implication that the current theory was derived from a previous work merely to legitimize the new theory. Idolization, Glaser proposed, should be replaced with the thought that “he too was working on these ideas” (p. 138). In other words, the researcher should not give older works precedence over the newly generated theory. However, Glaser (1978) also advised that the researcher should not attempt to debunk old theories since a vigorous justification of the new theory, beyond its normal justification, would not be useful, and the good aspects of the extant theory could be lost in the bargain. The secret is to compare and contrast the new theory with existing works while maintaining the power of the new theory and respecting the old.

The literature review of a classic grounded theory study is an integral piece of a newly emerged theory, which enhances both the new and old, adds to the knowledge base, and positions the new theory in relation to extant works. Consistent with the classic grounded theory method, this paper lays out a rigorous and systematic three-phase approach to the literature review. It also refutes common misunderstandings of critics that claim the timing and procedures of the grounded theory literature review are inadequate. The paper offers strategies to avoid conflicts and demonstrates that an institutionally required pre-investigation literature review is sometimes accepted as a strategy to move forward with research, even to classic theory purists. The paper gathers together Glaser and Strauss’s recommendations and establishes a clear roadmap for conducting a literature review for a classic grounded theory study.

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Declaration of Conflicting Interests: The author declares no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Knowledge transfer in university–industry research partnerships: a review

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• Volume 44 , pages 1236–1255, ( 2019 )

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• Esther de Wit-de Vries   ORCID: orcid.org/0000-0002-9182-5176 1 ,
• Wilfred A. Dolfsma   ORCID: orcid.org/0000-0002-5636-3391 2 ,
• Henny J. van der Windt 1 &
• M. P. Gerkema 1  

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This paper identifies practices that can facilitate knowledge transfer in university–industry (U–I) research partnerships by systematically reviewing extant literature. We aim to contribute to the theoretical development in the field of academic engagement and propose that knowledge transfer provides a valuable perspective. We started our review with identifying barriers and facilitators of knowledge transfer. Extant literature identified knowledge differences and differences in goals resulting from different institutional cultures as important barriers to knowledge transfer. They result in ambiguity, problems with knowledge absorption and difficulties with the application of knowledge. Trust, communication, the use of intermediaries and experience are found as facilitators for knowledge transfer that help to resolve the identified barriers. Our analysis offers practical advice for the management of academic engagement. Finally, we identified questions for future research based on inconsistencies in extant research and open questions we encountered during our analysis.

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1 Introduction

1.1 knowledge transfer practices in u–i collaborations.

Knowledge transfer between academia and industry is considered an important driver of innovation and economic growth as it eases the commercialization of new scientific knowledge within firms (Bercovitz and Feldmann 2006 ; Mowery and Nelson 2004 ). Researchers benefit from the interaction with industry as well, as it can inspire new research directions and provides additional funding (D’Este and Perkmann 2011 ). Over the past decades, research into academic engagement increased. Most of this research studied academic entrepreneurship (Agrawal 2001 ; Shane 2005 ), which includes patenting, licensing, joint ventures, spin-offs and so forth. However, there are other ways for academics to ensure application of their knowledge these practices focus predominantly on knowledge exchange (Salter and Martin 2001 ; Alexander and Childe 2013 ). These forms of interaction have been referred to as academic engagement or academic partnership (Perkmann et al. 2013 ). In this paper we focus on these kinds of academic engagement which we define as research partnerships based on “high relational involvement in situations where individuals and teams from academic and industrial contexts work together on specific projects and produce common outputs” (Perkmann and Walsh 2007 , p. 263). This means that we will focus on research partnerships, collaborative research, contract research and consulting while collaborations with limited interaction or that require little or no new research are excluded.

Although university income from academic engagement outranks income derived from selling intellectual property (IP) (Perkmann et al. 2011 ) and is valued higher by industry (Cohen 2002 ), researchers into university–industry interactions have ignored these forms of collaborations for a long time. Since 2006 research into academic engagement is increasing (Perkmann et al. 2013 ). Up till now, the field is still behind in the development of theoretical perspectives. We propose that research into academic engagement can build on theory on knowledge transfer to fill this gap. Academic engagement, after all, aims to develop novel knowledge that benefits the academic and industrial partner. This requires bidirectional knowledge sharing to identify relevant problems, share and develop new insights, and the transfer and implementation of knowledge or technology.

In this paper we aim to map extant knowledge and perspectives on knowledge transfer in academic engagement through a systematic literature review. Additionally, we identify open questions for future research. Besides our aim to develop a theoretical perspective to study academic engagement our focus on knowledge transfer adds to previous reviews on academic engagement. As those have focussed on characteristics of researchers and institutions (Perkmann et al. 2013 ), factors that affect collaboration but did not focus on academic engagement, its management or knowledge transfer (Ankrah and AL-Tabbaa 2015 ; Agrawal 2001 ), tried to define academic engagement (Perkmann and Walsh 2007 ) or discussed policies (Hagedoorn 2002 ; Hagedoorn et al. 2000 ).

In this review we discuss which theoretical frames could deepen our understanding of university–industry (U–I) knowledge transfer, identify barriers and facilitators of knowledge transfer and use a ‘practices perspective’ to identify ways to deal with these barriers. This allows us to emphasize social interactions, managerial aspects and concrete activities that enhance knowledge transfer. The term “practice” can refer to a broad range of activities. We use the term to refer to institutionalized daily events at a workplace (Nicolini 2009 ). The abstraction level we use is such that it can be translated into managerial implications. In adopting this focus we follow a developing interest in organization science that seeks a detailed understanding of ‘what is actually done’, or “the micro-level”, and how to make sense of those activities (Nicolini 2009 ).

To define knowledge transfer we used the definition by Bloedon and Stokes ( 1994 , p. 44) who defined this as ‘the process by which knowledge concerning the making or doing of useful things contained within one organized setting is brought into use within another organizational context’. Knowledge transfer practices are then defined as the activities that facilitate what is needed to bring knowledge into use in another organization’s context, such as, teaching, the management of interactions and sharing data and technology.

This paper continues with a methodological section that describes our review process. The third section outlines our analysis of the literature resulting from our review. In that section we provide an overview of theoretical perspectives and activities that have been described in previous research. We aim to realize generalization and accumulation of knowledge and to identify issues which are inconclusive or have been ignored in the extant literature and provide practices that facilitate the management of academic engagement in practice. The paper concludes with translating these insights into an analytical framework and research agenda.

1.2 Methodology

Following previous research in the field of U–I research (for example Perkmann et al. ( 2013 ) and Ankrah and AL-Tabbaa ( 2015 ) we used the principles and process of a systematic literature review (Tranfield et al. 2003 ). While conducting our review we encountered some problems in our search process. The main problem was that there is little consistency in the terminology used to describe research partnerships/academic engagement and knowledge transfer. Secondly, the literature that focusses on knowledge transfer and management of such collaborations is scarce. As a result, combining key words such as academic engagement or research partnerships with knowledge transfer or knowledge management provided limited results. We developed a methodology that overall followed the analytical process of a systematic review but differs from other systematic reviews when it comes to searching and identifying relevant literature. Therefore, the following section describes our method in detail.

Previous reviews by Agrawal ( 2001 ), Hagedoorn et al. ( 2000 ) and Hagedoorn ( 2002 ) concluded that there was a lack of research into transfer channels other than commercialization. Also Perkmann et al. ( 2013 ) found that literature on academic engagement was mainly published after 2006. Therefore, we did not expect to find many papers on knowledge transfer before 2002 and selected the period 2002–2016 for our review. We also searched the period 1997–2001 to verify the findings by Perkmann et al. ( 2013 ), but we did not find relevant papers in this period. We only searched within English peer reviewed journal articles. Instead of limiting our search to a list of prominent journals we decided to include a wide range of economic and managerial literature. This was necessary as literature on research partnerships is widespread. We used the following academic databases: Emerald, Web of Knowledge and Business Source Premier. In the end we identified relevant papers in 26 different journals. There were only six journals in which we found more than 1 paper, three of those had published two papers and three published three papers.

1.4 Search protocol

The initial search strategy was to find papers discussing “research partnership*”, “academic engagement” or papers that combined “scienc*, academi* or university” with “industry* or business”, in combination with “knowledge management”, “knowledge transfer” or “technology transfer”. This, however, did not provide many useful results. Therefore, we changed the search strategy to an approach in which we used broad Boolean search strings to identify papers on academic engagement from which we manually selected the ones that discuss research partnerships in relation to knowledge transfer. We searched in: titles, keywords and abstracts using the terms: ‘University–business’, ‘university–industry’ “academic engagement” and “research partnership” (other terms for university such as ‘Academ*’ and ‘Higher Education’ ‘science’ did not yield additional results), combined with one of the terms ‘collaborat*’, ‘cooperation*’, ‘partnership*’, ‘engage*’, ‘relation* ‘research’ ‘alliance*’. The term ‘research’ generated results for a broad range of terms used to indicate collaborations such as joint research, collaborative research, contract research and so on. Our search terms were based on previous reviews by Ankrah and AL-Tabbaa ( 2015 ) and Perkmann et al. ( 2013 ). The results from the Boolean search from the three literature databases were combined in Rayyan (Ouzzani et al. 2016 ). In total we found about 890 unique papers.

From these results we selected papers that could help us answer the following research questions: What is known about knowledge transfer in academic engagement according to the extant literature. How can failure and success of knowledge transfer be explained? And what practices facilitate the transfer of knowledge in academic engagement? We used the following steps and criteria (see Fig.  1 ). First, we excluded papers that focus solely on entrepreneurial activities like patenting, liaison offices, science-hubs and other intermediary organisations. Second, we excluded papers that were not related to knowledge transfer. Third, we only included papers that gave theoretical explanations relating to effectiveness of knowledge transfer, papers that identified factors that influence knowledge transfer and papers that describe knowledge transfer practices and management practices that influence knowledge transfer. If the abstract was unclear about the content, the decision to include a paper was made after scanning the whole paper.

Selection criteria

There are not many papers that focus explicitly on knowledge transfer in academic engagement (Bruneel et al. 2010 ). To find literature that discusses knowledge transfer we first identified the factors that affect knowledge transfer in inter-organizational collaboration. This can be justified when we follow the logic that academic engagement is a specific form of inter-organizational collaboration or alliance (see for example Galan-Muros and Plewa 2016 ). Additionally, we looked for research that confirmed the relevance of the factors we identified for academic engagement. To identify the inter-organizational factors we used a paper by Van Wijk et al. ( 2008 ). This study combined results from 75 papers on knowledge transfer to re-evaluate previous quantitative findings from inter- and intra-organizational studies. We only used the factors that were relevant for inter-organizational collaborations, absorptive capacity, ambiguity, cultural differences, differences in goals, trust and tie-strength (Fig.  2 ).

Publications per year

These factors and their definitions (see below) were used to decide which of the papers on academic engagement in our results discussed topics that could be related to knowledge transfer. Van Wijk et al. ( 2008 ) identified “absorptive capacity” and “ambiguity” as important factors. Given that these factors relate to differences in knowledge background and the complexity of knowledge we included all research that discussed differences in knowledge background and knowledge characteristics. “Cultural differences” and “differences in goals” were also identified by van Wijk et al. ( 2008 ) and literature that discussed such differences was therefore included. “Trust” and “tie-strength” were identified as important facilitators. We therefore included literature that discussed these factors, but also other forms of relational capital. We found 35 papers that discussed relevant insights into knowledge transfer after applying the inclusion and exclusion criteria (for an overview of the papers see Table  1 ).

1.5 Data analysis process

The next step was to analyse the papers we selected. First, we prepared a table which summarized the research questions and answers. Second, we identified the information that related to knowledge transfer and included this in our table. Third, we organized our literature in line with three themes—cognitive difference, institutional differences and social capital in a summarizing document that formed the basis for the analysis.

2 Factors influencing knowledge transfer

Before turning to the analysis of the selected papers we will discuss the definitions of and relations between the factors identified by Van Wijk et al. ( 2008 ) and relate them to literature on academic engagement. The factors relating to cognitive differences are ambiguity and absorptive capacity. They relate to differences in knowledge background between the firm and the academics. Similarity in knowledge backgrounds makes it easier to understand and absorb new knowledge that results from the collaboration. Knowledge ambiguity refers to a situation where dissimilarities in knowledge result in “inherent and irreducible uncertainty regarding what the underlying knowledge components and sources are precisely, and how they interact” (van Wijk et al. 2008 ). It is an aggregated term for various knowledge characteristics of which the tacit nature (Polanyi 1966 ), complexity and the limited possibilities for specification (Simonin 1999 ) are the most important. Knowledge that has these characteristics is hard to identify, understand and transfer (ibid.). Hence, ambiguity is negatively related to knowledge transfer and hard to resolve without on the job training (Van Wijk et al. 2008 ).

Absorptive capacity refers to the ability to recognize, assimilate and apply new external knowledge (Cohen and Levinthal 1990 ). The capability of firms to absorb new knowledge depends on the shared knowledge base of the academics and the firm employees. It has a strong relationship with causal ambiguity, as it also strongly depends on a shared knowledge base (Cohen and Levinthal 1990 ).

The relevance of ambiguity and absorptive capacity in the context of U–I collaboration was confirmed by Santoro and Bierly ( 2006 ). They showed that technological relatedness and technological capability (which increases absorptive capacity) were the most important facilitators of knowledge transfer in U–I collaborations. In the same study, tacitness and explicitness (related to knowledge ambiguity) moderated knowledge transfer negatively.

Institutional factors are cultural differences and shared goals. The term cultural differences is used to indicate a lack of shared meaning and social conventions (Tsai and Ghoshal 1998 ). This complicates collaboration because different languages, opinions, social behaviours, norms and beliefs make the interpretation of behaviour and knowledge more difficult (Lane and Lubatkin 1998 ; Mowery and Shane 2002 ; Simonin 1999 ).

Different goals relate to the different ways in which business and academia benefit from knowledge. Shared goals are needed to reach a common understanding of the desired output and the interpretation of results (Tsai and Ghoshal 1998 ). When shared goals are lacking it becomes more difficult to understand the implications and cause effect relations of the knowledge developed, which causes ambiguity (Partha and David 1994 ). Different goals are also seen as an obstacle to build trust (Davenport et al. 1998 ). The relevance of cultural differences for U–I collaborations is confirmed by research from Bruneel et al. ( 2010 ), Cyert and Goodman ( 1997 ), Liyanage and Mitchell ( 1994 ), Partha and David ( 1994 ), Galan-Muros and Plewa ( 2016 ) and Ghauri and Rosendo-Rios ( 2016 ).

Social capital in the form of tie strength and trust reflects the closeness of a relationship and positively influences knowledge transfer (Bloedon and Stokes 1994 ; Bruneel et al. 2010 ; Davenport et al. 1998 ; Santoro and Gopalakrishnan 2001 ). Tie strength is a measure for the frequency of interactions and communication. While trust is used to express the reliability of a partner (Hansen 1999 ). Tie strength influences trust positively. Additionally, trust and tie strength are associated with the commitment to help a partner to understand new knowledge (Hansen 1999 ; Inkpen 2000 ). Sherwood and Covin ( 2008 ) found that trust is positively associated with tacit knowledge transfer, as trust increases open communication and the willingness to share knowledge. The importance of social capital (trust and tie strength) has been confirmed for academic engagement (Amabile et al. 2001 ; Philbin 2008 ; Plewa et al. 2013a ; Schartinger et al. 2002 ).

As can be seen from the previous text, the factors that influence knowledge transfer are interrelated. Trust is positively influenced by tie strength and shared goals, and negatively by ambiguity and organizational differences. Tie strength improves absorptive capacity, as more interaction provides more opportunities to exchange knowledge. Ambiguity can be reduced by tie strength as well. Reduced ambiguity in return improves absorptive capacity and the understanding of the goals and needs of the partner. When there are large differences between organizational cultures, it is more likely that organizations have different research goals and possibly also different knowledge backgrounds. This can result in more ambiguity and less trust in that the partner will do what is right for you.

In the following part we will discuss the findings from the literature we reviewed. For each of the three topics we identified we will discuss the theoretical insights, their implications and the associated practices for successful knowledge transfer.

3.1 Cognitive differences

We start with a general discussion on knowledge flows in academic engagement. After this, we turn to theoretical insights about how knowledge differences and characteristics influence the effectiveness of knowledge exchange and absorptive capacity. Finally, we discuss how different practices of knowledge exchange are influenced by these factors and which practices help to improve knowledge transfer from a cognitive differences perspective.

Looking at the papers in our review, the overall picture is that the extant literature pays little attention to the knowledge contribution of industrial partners. The majority of the papers focuses on development and transfer of knowledge by the academic partner. The knowledge contribution from the industrial partner is reduced to formulating interesting research problems (D’Este and Perkmann 2011 ; McCabe et al. 2016 ) and providing data and insight in the application context (Barnes et al. 2002 ; Gertner et al. 2011 ; Hadjimanolis 2006 ; McCabe et al. 2016 ; Wang and Lu 2007 ).

Ulhøi et al. ( 2012 ) focus specifically at the knowledge contribution of the industrial partner. They sketch a much more dynamic exchange process, in which the industrial application of research outcomes directly influences academic research. This discrepancy is partly explained by McCabe et al. ( 2016 ) who discusses three levels of collaboration, low, high and deep, and links them to different knowledge exchange practices. In collaborations with low engagement the firm is seen as data source, while all research activities are controlled and conducted by the academic partner. In high collaborations the firm contributes through the identification of research problems, grounding the design and data collection in the application context and by assisting academics in making decisions. In ideal circumstances during deep collaboration the industrial partner would take a more equal role as the academics and contribute to the identification of research problems, help with the selection of methods and is engaged in data gathering and analysis. In practice, the role of the industrial partner in data analysis and theory development is limited, even in deep collaborations. Because industrial partners lack the time to dive into the data and feel unequipped to participate truly in the academic debate (McCabe et al. 2016 ). Also, academics hardly use data that is produced by the industrial partner due to a lack of quality signals of industrial data that is required for academic publication (Canhoto et al. 2016 ). Additionally, academic knowledge and expertise is valued higher than industrial knowledge. This makes industrial partners reluctant to take part in the research and the academic debate (McCabe et al. 2016 ).

The ease with which knowledge is transferred depends on the characteristics of knowledge, similarities in knowledge background and knowledge management capabilities. We will discuss each of these aspects in the following paragraphs.

The most important characteristic of knowledge is its explicitness (Santoro and Bierly 2006 ). Knowledge that can be made explicit can be transferred through prototypes, formulas or manuals. Such knowledge is often transferred through contractual agreements, like patents (Alexander and Childe 2013 ; Sandberg et al. 2015 ). In that case the successful use of the knowledge depends on whether it can be appropriated to the application contexts (Alexander and Childe 2013 ; Sandberg et al. 2015 ; Wang and Lu 2007 ). Tacit knowledge transfer requires interaction to develop competence (Johnson and Johnston 2004 ) and more direct collaboration (Alexander and Childe 2013 ; Azevedo Ferreira and Rezende Ramos 2015 ; Daghfous 2004 ; Gertner et al. 2011 ; Steinmo 2015 ; Wang and Lu 2007 ) and interactional expertise (Canhoto et al. 2016 ; Sandberg et al. 2015 ). Therefore, tacit knowledge is best transferred through academic engagement, instead of patenting or licensing, as it includes more personal interaction.

Nonaka ( 1994 ) developed the knowledge creation circle to explain tacit knowledge transfer. Which shows that tacit knowledge is transferred in four steps; (1) through creating shared experiences (socialization), after which knowledge is (2) externalized, (3) recombined and (4) internalized. Johnson and Johnston ( 2004 ) explored how the knowledge creation cycle affects knowledge transfer in academic engagement. They found that all four steps of the knowledge creation cycle (socialization, externalization, combination and internalization) were needed in the initiation phase, to formulate relevant research questions and goals, and in the knowledge transfer phase, to absorb tacit knowledge. The need to go through the whole knowledge cycle in both phases distinguishes collaborative research from other learning processes.

The second important factor that influences knowledge absorption, is differences in knowledge background, referred to as cognitive and epistemic difference. They result in differences in ‘language’ and different logics regarding what methods should be used. Therefore, relatedness of prior knowledge and technological competence help to understand and integrate new knowledge (Daghfous 2004 ; Santoro and Bierly 2006 ) and reduces ambiguity.

Although cognitive distance does not diminish the propensity to collaborate, it does limit interaction during the collaboration. Resultantly, tacit knowledge transfer which requires interaction is limited. But is might also be problematic for forms of engagement that require interaction relating to the use of methods and technology, like joint research or sharing facilities (Sandberg et al. 2015 ).

Studies on prior knowledge have asked how prior technological knowledge and management capabilities are related. There seems to be agreement on the importance of general collaboration experience, organizational capabilities, and experience with the particular partners for overall collaboration success (Buganza et al. 2014 ; Bjerregaard 2009 ; Canhoto et al. 2016 ; Daghfous 2004 ; Sandberg et al. 2015 ). Studies that particularly studied cognitive difference in relation to knowledge transfer are contradictory about the effect of experience. Daghfous’s ( 2004 ) and Muscio and Pozzali ( 2013 ) found that cognitive differences are not diminished by experience. To which Daghfous’s ( 2004 ) adds that systematic learning in relation to management skills does not significantly increase learning capabilities. Steinmo ( 2015 ), on the other hand, found that cognitive capital can be developed over time at the organizational level. While research by (Corley et al. 2006 ) indicates that epistemic differences can be reduced by strong organizational routines. Therefore, the role of experience to mitigate knowledge differences remains unclear. If experience or management capabilities do not reduce cognitive differences, identifying suitable partners with matching knowledge backgrounds is an important success factor (Galan-Muros and Plewa 2016 ). Finding the right partners is especially difficult for SME (small and medium size enterprises) as they have smaller networks (Buganza et al. 2014 ).

The relevance of technical and organizational uncertainties in relation to learning activities is unclear as well. A study by Daghfous ( 2004 ) indicated that prior knowledge was only significant in case of high uncertainty about the organizational aspects for the implementation of the new knowledge. His hypotheses is that in the case of radically new technologies knowledge is so different from existing knowledge that knowing how to organize the implementation of new technologies becomes more relevant. This needs to be confirmed by future research.

We now turn to practices that can improve knowledge transfer. Communication is an important facilitator to improve absorptive capacity. The channels for communication during engagement are diverse and differ in their ability to transfer tacit knowledge and to deal with differences in knowledge backgrounds (Alexander and Childe 2013 ). Knowledge transfer through rich, or interactive, media is preferred over indirect communication through reports, presentations, patents and so forth, as the latter are unable to transfer tacit knowledge (Alexander and Childe 2013 ; Sandberg et al. 2015 ).

We noticed that three reoccurring practices are important for rich communication practices: boundary spanners (Al-Tabbaa and Ankrah 2016 ; Barnes et al. 2002 ; Gertner et al. 2011 , Hadjimanolis 2006 ; Wallin et al. 2014 ), training (Alexander and Childe 2013 ; Azevedo Ferreira and Rezende Ramos 2015 ; Daghfous 2004 ; Gertner et al. 2011 ; Wallin et al. 2014 ; Wang and Lu 2007 ) and the use of tools or objects (Buganza et al. 2014 ; Wallin et al. 2014 ). We will continue with discussing how each of these practices can be used effectively to transfer knowledge according to the literature.

Boundary spanners are often personnel that is exchanged between academia and industry during the course of the collaboration. For instance, the outplacement of personnel from the firm, secondment and employment of graduates (Galan-Muros and Plewa 2016 ; Gertner et al. 2011 ; Harryson et al. 2007 ; Hadjimanolis 2006 ; Pinheiro et al. 2015 ; Ulhøi et al. 2012 ; Wang and Lu 2007 ) or (Ph.D.) students that do part of their research at the firm (Gertner et al. 2011 ; Galan-Muros and Plewa 2016 ; Hadjimanolis 2006 ; Harryson et al. 2007 ; Wang and Lu 2007 ). Such mobility can be limited by organizational differences (Galan-Muros and Plewa 2016 ).

If partners mainly interact through periodical meetings instead of personnel exchange the identification of suitable recipients within the firm, who have the right knowledge background is essential. This requires time and commitment (Mesny and Mailhot 2007 ; Plewa et al. 2013a ).

Boundary spanners are effective because they facilitate the knowledge conversion and translation of academics results to the context of the firm and vice versa (Azevedo Ferreira and Rezende Ramos 2015 ; Gertner et al. 2011 ). This requires the investment of time to develop a shared language and discourse (Al-Tabbaa and Ankrah 2016 ; Canhoto et al. 2016 ). Over time and through close collaboration the boundary spanner gets a better understanding of the partner’s needs and knowledge background. This enables him to translate results which facilitate application and implementation (Gertner et al. 2011 ; Hadjimanolis 2006 ; Wang and Lu 2007 ). Firm employees who interact frequently with researchers and follow the debate at academic meetings gain a deeper understanding of the working methods and knowledge produced by the researchers. This helps to integrate the results of the research (McCabe et al. 2016 ).

Training and workshops help to transfer tacit, complex knowledge and build skills (Azevedo Ferreira and Rezende Ramos 2015 ; Daghfous 2004 ). They provide a space for deliberation and feedback which increases the comprehension of results (McCabe et al. 2016 ). It is important to have the right people, with the right level of expertise, involved in these meetings (Azevedo Ferreira and Rezende Ramos 2015 ). The open and interactive mode of communication in this kind of meetings gives industrial partners the possibility to engage more and feel more comfortable about giving input (McCabe et al. 2016 ). Creating creative chaos in interactive sessions provides a way to learn autonomic and recombine the new insights with previous knowledge, which facilitates absorption (Johnson and Johnston 2004 ).

The use of prototypes and working in the facilities of the industrial partner helps to integrate knowledge and learn about implementation challenges (Daghfous 2004 ; Gertner et al. 2011 ; Hadjimanolis 2006 ; Wallin et al. 2014 ; Wang and Lu 2007 ). Mostly because it helps to see connections between different aspects of knowledge and this is an important way to reduce ambiguity. Close interaction is also the most important way for researchers to identify interesting questions for future research (Perkmann and Walsh 2007 ; Ulhøi et al. 2012 ; Wang and Lu 2007 ).

3.2 Institutional differences

Differences in organizational goals and culture are a frequently mentioned, but not well defined barrier to academic engagement. The literature we reviewed uses the term cultural differences to indicate differences in project goals, expected outcomes, visions on required research activities, the allocation of time and resources, management styles, social conducts, cognitive differences, different ‘language’ and time perception (Bjerregaard 2010 ; Galan-Muros and Plewa 2016 ; Ghauri and Rosendo-Rios 2016 ; Harryson et al. 2007 ). In spite of that, they are frequently mentioned as barrier, they are not well researched. It is therefore much welcomed, that since 2013 more research has been conducted into how institutional differences influence knowledge transfer and collaboration success.

There remains discussion about the extent to which cultural differences actually affect collaboration in practice. On the one hand, it has been shown that increasing academic convergence between companies and industry reduce the differences (Bjerregaard 2010 ). On the other hand, the limited statistical research on cultural differences indicates that cultural differences do affect collaboration success (Galan-Muros and Plewa 2016 ; Ghauri and Rosendo-Rios 2016 ). Ghauri and Rosendo-Rios ( 2016 ) found that especially market and time orientation affect collaboration success.

Differences in goals originate from differences in market orientation (Ghauri and Rosendo-Rios 2016 ), priorities in norms (Al-Tabbaa and Ankrah 2016 ; Mesny and Mailhot 2007 ), and different logics for the sharing of knowledge (Steinmo 2015 ). Differences in goals are best managed by improved communication (Bjerregaard 2009 ; Plewa et al. 2013b ). Goals and outcomes should be established early in the project. The use of project plans that outline goals and outcomes could facilitate this (Canhoto et al. 2016 ; Morandi 2013 ). Project management tools can be helpful in the communication of progress and the relation between goals and outcomes (Wallin et al. 2014 ). A complicating factor here is that differences in goals are often not recognized in the early, ‘honeymoon’, stage of a collaboration, they become clear during the engagement phase (Estrada et al. 2016 ; Plewa et al. 2013a ). In this phase the selection of actual research questions, methods and resource allocation might provide problems, even if these matters seemed clear at the beginning (Estrada et al. 2016 ; Mesny and Mailhot 2007 ; Plewa et al. 2013a ).

Researchers are expected to put sufficient effort into understanding the needs of the industrial partner; this becomes especially important during the engagement phase (Canhoto et al. 2016 ; Ghauri and Rosendo-Rios 2016 ; Plewa et al. 2013a ). Expectation management about what can be achieved in the available time and when results can be expected is also important to keep industrial partners satisfied (Azevedo Ferreira and Rezende Ramos 2015 ; Barnes et al. 2002 ; Bjerregaard 2009 ; Sandberg et al. 2015 ; Steinmo 2015 ; Wallin et al. 2014 ).

Frequent meetings and deliberation are key to recognize and solve differences (Morandi 2013 ; Plewa et al. 2013b ; Steinmo 2015 ). The possibility for interactive discussion for the coordination of goals is important to keep industrial and academic expectations aligned (Johnson and Johnston 2004 ). Experience with the collaboration partner has been found to mitigate problems relating to differences in goals, because it leads to more realistic expectations and better insight in the partner’s needs (Azevedo Ferreira and Rezende Ramos 2015 ; Steinmo 2015 ; Wallin et al. 2014 ). Finally, looking for a higher common good can help to re-unite goals if there seems to be no common ground (Mesny and Mailhot 2007 ).

A highly valued academic norm is academic freedom, the autonomy to follow interesting directions and choose one’s own research problems and methods. This may conflict with making strict project plans and specifying deliverables that align with industrial needs. A good understanding of a partner’s needs helps to take these needs into account, also when novel directions are pursued, while open communication raises understanding. Zhu and Hawk ( 2015 ) show how academics at Stanford University and MIT (Michigan Institute for Technology) managed to maintain their academic freedom. They focus on fundamental research, but use market developments to inspire their research. This way they manage to secure industrial funding. At the same time strict conflict of interest policies are in place to prevent conflicts of interests.

Cultural differences that are referred to as institutional norms or organizational routines relate to differences in project management and time orientation. Time orientation relates to differences in what is considered an acceptable period to reach goals, punctuality in meeting deadlines and the continuity of personnel (Barnes et al. 2002 ; Ghauri and Rosendo-Rios 2016 ). The industrial partner’s aversion to long term orientation of academics and the fundamental nature of research can be managed by open communication and good project management. This requires clarifying communication channels, providing and updating project plans and punctuality from academics (Barnes et al. 2002 ; Ghauri and Rosendo-Rios 2016 ; Morandi 2013 ; Wallin et al. 2014 ). Estrada et al. ( 2016 ) found that such ‘routine’ based differences, meaning dissimilarities in working methods, could only be resolved when orientation based differences, meaning dissimilarities in goals, were settled.

Cultural differences relating to the application of knowledge and willingness to share knowledge relates to the academic habit to publish results, while industrial partners rather keep knowledge secret. These differences can be handled through publication management and upfront arrangement of IP (intellectual property) rights (Azevedo Ferreira and Rezende Ramos 2015 ). However, arranging IP too early in the collaboration might negatively influence trust between partners (Canhoto et al. 2016 ). Publication management includes arrangements regarding what data can be published and allows the industrial partner to authorize publication, this ensure academics do not publish sensitive knowledge (Azevedo Ferreira and Rezende Ramos 2015 ). Also, providing the industrial partner the possibility to delay the publication to arrange IP rights reduces this barrier (Hadjimanolis 2006 ).

3.3 Social capital

Trust has been shown to influence knowledge transfer in research partnerships (Bruneel et al. 2010 ; Plewa et al. 2013b ; Ulhøi et al. 2012 ). Mostly, because it reduces fear of opportunistic behaviour and, resultantly, increases the willingness to share information (Plewa et al. 2013b ; Philbin 2008 ; Sherwood and Covin 2008 ; Steinmo 2015 ). Trust increases with frequent communication. Therefore, tie strength improves trust (Al-Tabbaa and Ankrah 2016 ; Plewa et al. 2013b ).

Trust in U–I collaboration is affected by two things. First, industrial partners fear that the academic partner is not working on the same goals, due to institutional differences, and that academics use the industrial partner as money cow (Al-Tabbaa and Ankrah 2016 ; Pinheiro et al. 2015 ; Ulhøi et al. 2012 ). Second, there is a fear that academic partners, unintentionally, share sensitive knowledge with other companies, due to a lack of experience with handling sensitive knowledge (Ulhøi et al. 2012 ). The latter can be prevented by providing secrecy training and using a split management strategy. Meaning that academics who work for different companies should not be mixed in research projects (Ulhøi et al. 2012 ). Fear for a lack of common interests is reduced by building social capital, which includes, tie-strength, and collaboration experience with the particular partner (Pinheiro et al. 2015 ; Sandberg et al. 2015 ). Frequent meetings in the initiation stage also help to merge goals, keep them aligned and increase trust (Plewa et al. 2013b ).

What is needed to build trust also depends on the collaboration stage. In the initiation stage trust is mainly based on the reputation of and previous experiences with the partner (Plewa et al. 2013b ). Resultantly, academic reputation and previous personal ties are important drivers for establishing collaborations (Pinheiro et al. 2015 ; Sandberg et al. 2015 ). While Muscio and Pozzali ( 2013 ) found that research quality is less important for establishing the collaboration than the applicability, in the sense of ‘readiness to use’, of the knowledge that will be produced.

During the collaboration the quality of communication is important. Social capital is built through frequent face-to-face communication and workshops that facilitate interaction (Al-Tabbaa and Ankrah 2016 ; Plewa et al. 2013b ). This kind of communication improves insight in the partner’s goals. Spontaneously sharing interesting knowledge that is not directly related to the specific project, experience and successful previous collaborations make partners feel that the other is genuinely interested in what is needed and improves insight in the partner’s needs (Al-Tabbaa and Ankrah 2016 ; Pinheiro et al. 2015 ). Therefore, it is often recommended to start with small projects, like student projects, and build to more complex collaborations and more fundamental questions from there (Buganza et al. 2014 ; Pinheiro et al. 2015 ). This way managerial capabilities can be developed and academic work can be aligned with business challenges (Buganza et al. 2014 ; Plewa et al. 2013a ; Pinheiro et al. 2015 ).

Trust also influences the contractual and organizational management of the collaboration. Trust results in less formal contractual agreements (Chin et al. 2011 ; Morandi 2013 ; Ulhøi et al. 2012 ). When there are no IP-rights expected the collaboration is often formed by memoires of understanding (MoU) or standard documents from the technology transfer office (TTO) instead of legal contracts (ibid). Additionally, trust is reflected in the absence of formal control mechanisms. Coordination is often effected informally between project managers from both sides (Barnes et al. 2002 ; Chin et al. 2011 ; Morandi 2013 ). This can lead to confusion when university partners have several senior researchers, and it is unclear who is in control (Barnes et al. 2002 ). Appointing a single person from both organizations as a liaison has therefore been recommended (Morandi 2013 ).

Furthermore, trust influences the formalization of communication. Regular contact during the collaboration is important to ensure that goals remain aligned (Buganza et al. 2014 ; Plewa et al. 2013a ). To align goals, projects often start with a project plan, which allocates tasks and responsibilities and milestones in detail (Barnes et al. 2002 ; Morandi 2013 ). These plans are rarely updated as the work develops and they soon become obsolete. The risk in this kind of work is that projects deviate from original plans, or that changes in plans are not well administrated and lead to discussion later on. Collaborations involving mutually dependent research form an exceptions, these plans are more likely to be updated to coordinate activities (Morandi 2013 ).

Although partners expect to be informed, reports play a minor role in this and are usually only compiled at the end of each phase and perceived as archiving material (Chin et al. 2011 ; Morandi 2013 ). Preferably, results are discussed in informal settings and regular progress meetings, or informally by email (discussions) and telephone (Chin et al. 2011 ; Morandi 2013 ; Ulhøi et al. 2012 ).

4 Conclusion

This review aimed to explore the relevance of knowledge transfer as a concept for theory development regarding academic engagement and to give an overview of literature that addresses knowledge transfer in academic engagement. We found that research into knowledge transfer in academic engagement is dispersed. This could be due to incoherence in terminology at all levels; from terminology to indicate the form of engagement to the factors and theoretical frames that are used to discuss knowledge transfer.

Nevertheless, knowledge transfer seems an interesting perspective for theory development for research into academic engagement. Our framework and the factors found by van Wijk et al. ( 2008 ) provided an interesting starting point for a more focused analysis, and integration of concepts. We also found that especially qualitative research can benefit from a better theoretical bedding for its analysis in order to provide better funded insights in the mechanisms behind success and fail factors of academic engagement. And makes it easier to build on previous research.

Bringing together this literature on knowledge transfer enabled us to develop a stylised model that shows how different characteristics of knowledge transfer relate in the context of academic engagement (Fig.  3 ). We could also compare previous research outcomes and draw new conclusions by connecting empirical results with theoretical explanations and by identifying dissimilarities that require more research. In the remainder of this paper we present the stylised model and the implications of our analysis for future research and management.

Analytical framework of knowledge transfer success in academic engagement

We found two promising lines of research. The first, deals with the cognitive differences and the adsorption of knowledge. The second, with differences in goals and the applicability of knowledge. We also identified the most relevant factors and practices for the mitigation of these differences. Trust and communication help to overcome both, cognitive differences and differences in goals. Intermediaries mainly help to reduce cognitive differences, and experience primarily helps to resolve differences is goals.

In relation to cognitive differences there seems to be agreement that secondment, employee exchange and hiring graduates are important ways to (bi-directionally) transfer the tacit aspects of knowledge and that Master and PhD students can play a particularly important role in this (Gertner et al. 2011 ; Harryson et al. 2007 ; Thune 2009 ). Because similarity in knowledge background is so important for absorptive capacity, we recommend that this is taken into account in partner selection. The use of prototypes and models helps to resolve ambiguity and to connect new and extant knowledge. For absorptive capacity, trust is foremost a mediating factor, because it increases the willingness to share knowledge. Communication practices on the other hand are very important for the quality of knowledge sharing. Communication should be open, interactive and bidirectional, for instance in the form of workshops, to recognize and resolve cognitive differences. When tacit knowledge needs to be transferred this requires on the job training or the hiring of graduates who worked on the project. The use of prototypes to show underlying relations can help to manage ambiguity. The role of experience to mitigate differences in knowledge background remains unclear. We believe that experience can help overcome minor differences through learning activities, but does not resolve fundamental differences in epistemic background or knowledge background without extensive learning. For example, an ICT-professional will not learn fundamental physics through collaboration experience; this requires extensive training.

The second line of research, applicability of knowledge, is highly dependent on goal similarity of the partners. Industrial partners often feel (or fear) that differences in knowledge application requirements might go at the costs of industrial needs if there is too much focus on academic relevance and publication requirements. While the need to publish might be at odds with the need to protect sensitive company knowledge and hamper trust. Communication to determine goals and to discuss what information can be published is the most important way to deal with these differences. Drawing up project plans that include milestones and the use of management tools can improve trust in the willingness of the academic to take into account industrial needs. Furthermore, experience with academic engagement in general and the specific partner in particular will build understanding for the needs of industry and the particular partner more specifically. Collaboration experience with the specific partner also increases trust in that the partner will handle sensitive information carefully.

4.1 Future research agenda

We can identify a number of avenues for future research into knowledge transfer related to academic engagement. These suggestions are based on open questions we encountered during our analysis and inconsistencies between the results in the papers discussed here.

Absorptive capacity, ambiguity and cognitive distance seem to be the most difficult barriers to be resolved. There remains uncertainty over the relevance of experience and management capabilities to solve transfer problems related to knowledge differences. This requires more research. Also, there seems to be agreement that secondment, employee exchange and hiring graduates are important ways to transfer the tacit aspects of knowledge in both directions. However, there is a need for more insight into the firms’ perspective on the involvement of students and Ph.D.’s in research partnerships (Thune 2009 ), as most research discusses the academic perspective only.

We noticed that “cultural differences” is used as an aggregated term for different goals, organizational and managerial differences and epistemic norms. This is problematic as it makes it hard to understand the cause-effect relations of the individual aspects of cultural differences on knowledge transfer. Research that differentiates between cognitive or goal related differences and routine based differences indicates that these factors affect collaborations differently (Corley et al. 2006 ; Estrada et al. 2016 ). A more structured approach is required which distinguishes between the effects of single attributes of cultural differences and their effect on collaboration success and knowledge transfer.

The extent to which cultural differences affect academic engagement is unclear, even as the role of experience to reduce this barrier. Bjerregaard ( 2010 ) and Bruneel et al. ( 2010 ) found that experience and academic convergence reduces differences. While Muscio and Pozzali ( 2013 ) and Morandi ( 2013 ) found that more experience in interaction with firms does not change the perception of cognitive distance. Firms indicated that different logics remained problematic for the development of useful interaction with universities, but that this disadvantage was outweighed by the benefits of the collaboration (Morandi 2013 ). There seems to be a need for future research to improve our understanding of how cultural differences are managed.

The relation between trust and knowledge transfer and the specific threats perceived in U–I collaborations requires greater attention in future studies (Plewa et al. 2013a , b ). We noticed that trust issues for research partnerships differ from those for business-to-business collaborations. Yet the trust scales used most frequently in the papers we reviewed are the ones intended for analysing business-to-business relations, developed by Saparito et al. ( 2004 ). Therefore, these do not fully reflect the trust related concerns we encountered in our analysis. Secondly, trust is mainly researched in quantitative research in relation to general collaboration success. Little attention has been paid to the practices required to build trust or the effect of trust on knowledge transfer specifically.

From the papers we studied, it seems that U–I research partnerships are managed informally (e.g. MoU instead of formal contract, informal reporting), or as Powell et al. ( 1996 ) call it, irrational. This is in contrast with the findings of Ankrah and AL-Tabbaa ( 2015 ), who argue that U–I collaborations are managed as rational process: focusing on planned resource and knowledge transfer. This could be due to a difference in focus, as Ankrah and AL-Tabbaa ( 2015 ) focus on negotiations in the pre-collaboration phase and their data included many results related to academic entrepreneurship, while the papers we analysed focus on the execution of the project and research partnerships. Yet, we believe this difference taps into a broader debate, on the governance of university knowledge transfer, presented by Geuna and Muscio ( 2009 ), who argue that U–I collaborations have a more informal irrational management style than is often assumed. This is also confirmed by the papers in our review, which show a very informal management style, based on high levels of trust. In our view, an increased understanding of when informal or formal management mechanisms are used is needed.

We also found that the current literature is focussed on the responsibilities and perception of the academic partner, with very limited attention for the role of the industrial partner. While knowledge transfer is a bidirectional process. This could lead to an underestimation of the importance of the firm’s efforts to absorb knowledge and communicate its needs to the researcher. More attention for how firms manage research partnerships is therefore needed. On the other hand, it would be interesting to gain greater insight into what knowledge academics require from firms, to enables them to provide relevant results and manage the knowledge needs of the firm. Also, the literature mainly focuses on problems in the implementation phase. There is room left for research into problem management during the initiation and collaboration phase.

Closing the gap between qualitative and quantitative research is another way to bring the field forward. Qualitative and quantitative research has both identified factors which influence knowledge transfer, but have not integrated their results. Such integration would increase the understanding of the underlying mechanisms. Qualitative research in this field is often very descriptive and does not refer to theoretical concepts.

Researchers who consider using results from this paper should be aware of the fact, that the qualitative nature of most research papers we used in this review, the small samples in both case study and quantitative studies we reviewed, and the sample bias of the selected cases in these studies (discussing only one sector, one university or a single research collaboration) might influence the validity of results we discussed. Resultantly, the conclusions we draw about the relation between different factors require more research. We therefore invite scholars to conduct more research into the relationships we proposed in our model.

4.2 Managerial implications

In our analysis we identified a number of barriers to successful knowledge transfer in academic engagement. We also identified the practices that could help to overcome those barriers. We found that cognitive differences are hard to overcome without the presences of boundary spanners or intermediaries. Therefore, we recommend to carefully select knowledge partners and the persons who represent the company. During the collaboration knowledge is best transferred through rich, meaningful, direct and bilateral interaction, especially when tacit knowledge is involved. Attributing sufficient time for interaction is important to reap the fruits of the partnership. Workplace mobility of employees during and after the collaboration seems the best way to transfer and implement (tacit) knowledge, while these employees also act as intermediaries to align goals.

Collaboration experience with a specific partner and learning how to deal with differences seems the best way to overcome differences in logic and goals. It can be wise to start with smaller projects, such as student internships or thesis research, to gain collaboration experience and to learn about the capabilities of a partner. Drawing up project plans and the use of management tools can help to make differences in goals visible over the course of the project. If they are regularly updated they help to keep goals and research work aligned.

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de Wit-de Vries, E., Dolfsma, W.A., van der Windt, H.J. et al. Knowledge transfer in university–industry research partnerships: a review. J Technol Transf 44 , 1236–1255 (2019). https://doi.org/10.1007/s10961-018-9660-x

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Limited by our limitations

Paula t. ross.

Medical School, University of Michigan, Ann Arbor, MI USA

Nikki L. Bibler Zaidi

Study limitations represent weaknesses within a research design that may influence outcomes and conclusions of the research. Researchers have an obligation to the academic community to present complete and honest limitations of a presented study. Too often, authors use generic descriptions to describe study limitations. Including redundant or irrelevant limitations is an ineffective use of the already limited word count. A meaningful presentation of study limitations should describe the potential limitation, explain the implication of the limitation, provide possible alternative approaches, and describe steps taken to mitigate the limitation. This includes placing research findings within their proper context to ensure readers do not overemphasize or minimize findings. A more complete presentation will enrich the readers’ understanding of the study’s limitations and support future investigation.

Introduction

Regardless of the format scholarship assumes, from qualitative research to clinical trials, all studies have limitations. Limitations represent weaknesses within the study that may influence outcomes and conclusions of the research. The goal of presenting limitations is to provide meaningful information to the reader; however, too often, limitations in medical education articles are overlooked or reduced to simplistic and minimally relevant themes (e.g., single institution study, use of self-reported data, or small sample size) [ 1 ]. This issue is prominent in other fields of inquiry in medicine as well. For example, despite the clinical implications, medical studies often fail to discuss how limitations could have affected the study findings and interpretations [ 2 ]. Further, observational research often fails to remind readers of the fundamental limitation inherent in the study design, which is the inability to attribute causation [ 3 ]. By reporting generic limitations or omitting them altogether, researchers miss opportunities to fully communicate the relevance of their work, illustrate how their work advances a larger field under study, and suggest potential areas for further investigation.

Goals of presenting limitations

Medical education scholarship should provide empirical evidence that deepens our knowledge and understanding of education [ 4 , 5 ], informs educational practice and process, [ 6 , 7 ] and serves as a forum for educating other researchers [ 8 ]. Providing study limitations is indeed an important part of this scholarly process. Without them, research consumers are pressed to fully grasp the potential exclusion areas or other biases that may affect the results and conclusions provided [ 9 ]. Study limitations should leave the reader thinking about opportunities to engage in prospective improvements [ 9 – 11 ] by presenting gaps in the current research and extant literature, thereby cultivating other researchers’ curiosity and interest in expanding the line of scholarly inquiry [ 9 ].

Presenting study limitations is also an ethical element of scientific inquiry [ 12 ]. It ensures transparency of both the research and the researchers [ 10 , 13 , 14 ], as well as provides transferability [ 15 ] and reproducibility of methods. Presenting limitations also supports proper interpretation and validity of the findings [ 16 ]. A study’s limitations should place research findings within their proper context to ensure readers are fully able to discern the credibility of a study’s conclusion, and can generalize findings appropriately [ 16 ].

Why some authors may fail to present limitations

As Price and Murnan [ 8 ] note, there may be overriding reasons why researchers do not sufficiently report the limitations of their study. For example, authors may not fully understand the importance and implications of their study’s limitations or assume that not discussing them may increase the likelihood of publication. Word limits imposed by journals may also prevent authors from providing thorough descriptions of their study’s limitations [ 17 ]. Still another possible reason for excluding limitations is a diffusion of responsibility in which some authors may incorrectly assume that the journal editor is responsible for identifying limitations. Regardless of reason or intent, researchers have an obligation to the academic community to present complete and honest study limitations.

A guide to presenting limitations

The presentation of limitations should describe the potential limitations, explain the implication of the limitations, provide possible alternative approaches, and describe steps taken to mitigate the limitations. Too often, authors only list the potential limitations, without including these other important elements.

Describe the limitations

When describing limitations authors should identify the limitation type to clearly introduce the limitation and specify the origin of the limitation. This helps to ensure readers are able to interpret and generalize findings appropriately. Here we outline various limitation types that can occur at different stages of the research process.

Study design

Some study limitations originate from conscious choices made by the researcher (also known as delimitations) to narrow the scope of the study [ 1 , 8 , 18 ]. For example, the researcher may have designed the study for a particular age group, sex, race, ethnicity, geographically defined region, or some other attribute that would limit to whom the findings can be generalized. Such delimitations involve conscious exclusionary and inclusionary decisions made during the development of the study plan, which may represent a systematic bias intentionally introduced into the study design or instrument by the researcher [ 8 ]. The clear description and delineation of delimitations and limitations will assist editors and reviewers in understanding any methodological issues.

Data collection

Study limitations can also be introduced during data collection. An unintentional consequence of human subjects research is the potential of the researcher to influence how participants respond to their questions. Even when appropriate methods for sampling have been employed, some studies remain limited by the use of data collected only from participants who decided to enrol in the study (self-selection bias) [ 11 , 19 ]. In some cases, participants may provide biased input by responding to questions they believe are favourable to the researcher rather than their authentic response (social desirability bias) [ 20 – 22 ]. Participants may influence the data collected by changing their behaviour when they are knowingly being observed (Hawthorne effect) [ 23 ]. Researchers—in their role as an observer—may also bias the data they collect by allowing a first impression of the participant to be influenced by a single characteristic or impression of another characteristic either unfavourably (horns effect) or favourably (halo effort) [ 24 ].

Data analysis

Study limitations may arise as a consequence of the type of statistical analysis performed. Some studies may not follow the basic tenets of inferential statistical analyses when they use convenience sampling (i.e. non-probability sampling) rather than employing probability sampling from a target population [ 19 ]. Another limitation that can arise during statistical analyses occurs when studies employ unplanned post-hoc data analyses that were not specified before the initial analysis [ 25 ]. Unplanned post-hoc analysis may lead to statistical relationships that suggest associations but are no more than coincidental findings [ 23 ]. Therefore, when unplanned post-hoc analyses are conducted, this should be clearly stated to allow the reader to make proper interpretation and conclusions—especially when only a subset of the original sample is investigated [ 23 ].

Study results

The limitations of any research study will be rooted in the validity of its results—specifically threats to internal or external validity [ 8 ]. Internal validity refers to reliability or accuracy of the study results [ 26 ], while external validity pertains to the generalizability of results from the study’s sample to the larger, target population [ 8 ].

Examples of threats to internal validity include: effects of events external to the study (history), changes in participants due to time instead of the studied effect (maturation), systematic reduction in participants related to a feature of the study (attrition), changes in participant responses due to repeatedly measuring participants (testing effect), modifications to the instrument (instrumentality) and selecting participants based on extreme scores that will regress towards the mean in repeat tests (regression to the mean) [ 27 ].

Threats to external validity include factors that might inhibit generalizability of results from the study’s sample to the larger, target population [ 8 , 27 ]. External validity is challenged when results from a study cannot be generalized to its larger population or to similar populations in terms of the context, setting, participants and time [ 18 ]. Therefore, limitations should be made transparent in the results to inform research consumers of any known or potentially hidden biases that may have affected the study and prevent generalization beyond the study parameters.

Explain the implication(s) of each limitation

Authors should include the potential impact of the limitations (e.g., likelihood, magnitude) [ 13 ] as well as address specific validity implications of the results and subsequent conclusions [ 16 , 28 ]. For example, self-reported data may lead to inaccuracies (e.g. due to social desirability bias) which threatens internal validity [ 19 ]. Even a researcher’s inappropriate attribution to a characteristic or outcome (e.g., stereotyping) can overemphasize (either positively or negatively) unrelated characteristics or outcomes (halo or horns effect) and impact the internal validity [ 24 ]. Participants’ awareness that they are part of a research study can also influence outcomes (Hawthorne effect) and limit external validity of findings [ 23 ]. External validity may also be threatened should the respondents’ propensity for participation be correlated with the substantive topic of study, as data will be biased and not represent the population of interest (self-selection bias) [ 29 ]. Having this explanation helps readers interpret the results and generalize the applicability of the results for their own setting.

Provide potential alternative approaches and explanations

Often, researchers use other studies’ limitations as the first step in formulating new research questions and shaping the next phase of research. Therefore, it is important for readers to understand why potential alternative approaches (e.g. approaches taken by others exploring similar topics) were not taken. In addition to alternative approaches, authors can also present alternative explanations for their own study’s findings [ 13 ]. This information is valuable coming from the researcher because of the direct, relevant experience and insight gained as they conducted the study. The presentation of alternative approaches represents a major contribution to the scholarly community.

Describe steps taken to minimize each limitation

No research design is perfect and free from explicit and implicit biases; however various methods can be employed to minimize the impact of study limitations. Some suggested steps to mitigate or minimize the limitations mentioned above include using neutral questions, randomized response technique, force choice items, or self-administered questionnaires to reduce respondents’ discomfort when answering sensitive questions (social desirability bias) [ 21 ]; using unobtrusive data collection measures (e.g., use of secondary data) that do not require the researcher to be present (Hawthorne effect) [ 11 , 30 ]; using standardized rubrics and objective assessment forms with clearly defined scoring instructions to minimize researcher bias, or making rater adjustments to assessment scores to account for rater tendencies (halo or horns effect) [ 24 ]; or using existing data or control groups (self-selection bias) [ 11 , 30 ]. When appropriate, researchers should provide sufficient evidence that demonstrates the steps taken to mitigate limitations as part of their study design [ 13 ].

In conclusion, authors may be limiting the impact of their research by neglecting or providing abbreviated and generic limitations. We present several examples of limitations to consider; however, this should not be considered an exhaustive list nor should these examples be added to the growing list of generic and overused limitations. Instead, careful thought should go into presenting limitations after research has concluded and the major findings have been described. Limitations help focus the reader on key findings, therefore it is important to only address the most salient limitations of the study [ 17 , 28 ] related to the specific research problem, not general limitations of most studies [ 1 ]. It is important not to minimize the limitations of study design or results. Rather, results, including their limitations, must help readers draw connections between current research and the extant literature.

The quality and rigor of our research is largely defined by our limitations [ 31 ]. In fact, one of the top reasons reviewers report recommending acceptance of medical education research manuscripts involves limitations—specifically how the study’s interpretation accounts for its limitations [ 32 ]. Therefore, it is not only best for authors to acknowledge their study’s limitations rather than to have them identified by an editor or reviewer, but proper framing and presentation of limitations can actually increase the likelihood of acceptance. Perhaps, these issues could be ameliorated if academic and research organizations adopted policies and/or expectations to guide authors in proper description of limitations.

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Quantitative Research Designs, a Review of Extant Literature

• Riungu Festus Kinyua 1
• 1. Thika Technical Training Institute

Description

Most students find it difficult to identify appropriate research design as they undertake their research. The objective of this study was to review extant literature by defining quantitative and qualitative research designs and then focusing on quantitative research starting with general definitions of quantitative research design, delineating the generic quantitative designs including survey, experimental and ex post facto designs. It furthers looks at the subgroups in detailing their definitions and characteristics. The Methodology adopted by the paper is extant literature review which permits review of existing literature on the topic in question. This paper will help researchers and scholars to make the right choices of research design depending on different parameters which are of interest to the researcher. The review found out that survey   design is the friendliest because of its ability to handle large samples from the population with ease of generalizing the findings. Those with limited time should opt for cross sectional studies which would save on time and cost. For panel, cohort and retrospective studies, as much as they are quantitative in nature they would fit more in a qualitative type of study because at one point in time, there would be a lot of reflection and emotional involvement. Finally, the review of this literature leads to the recommendation that experimental, quasi experimental and ex post factor studies would be useful in the social sciences context but more useful in the medical and other scientific disciplines which rely much on laboratories settings.

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Studies in Economics and Finance

ISSN : 1086-7376

Article publication date: 7 November 2019

Issue publication date: 24 February 2020

This paper aims to undertake a thematic review of academic papers on financial technology (FinTech) to identify three broad categories for the purpose of classifying extant literature. The paper summarizes the research and findings in this emerging field. Thereafter, it identifies the gaps and provides directions for further research. Simultaneously, the paper collates technical terms related to FinTech that appear repeatedly in each category and explains them. Finally, the study highlights the lessons that growing FinTech firms and their regulators can learn from the experiences of their counterparts across the globe.

Design/methodology/approach

A systematic review of literature consisting of 130 studies (social science research network [SSRN]-29 papers, Scopus-81, other sources-20) on FinTech is carried out in this thematic paper.

This thematic paper divides FinTech into three themes, i.e. financial industry, innovation/technology and law/regulation. The paper suggests that a thorough impact of FinTech on various stakeholders can be understood using three dimensions, namely, consumers, market players and regulatory front. It is noted that FinTech is in its nascent phase and is undergoing continuous development and implementation through product and process innovation, disruption and transformation.

Research limitations/implications

The paper reports that FinTech promises huge potential for further study by various stakeholders in the FinTech industry – from academia to practitioners to regulators.

Practical implications

The paper summarizes lessons that could be of significance for FinTech users, producers, entrepreneurs, investors, policy designers and regulators.

Originality/value

The paper is believed to add value to the understanding of FinTech in light of the emerging threats and opportunities for its various stakeholders.

• Crowdfunding
• Shadow banking
• P2P lending
• Entrepreneurial finance
• Regulatory sandbox
• Cryptocurrency

Sangwan, V. , , H. , Prakash, P. and Singh, S. (2020), "Financial technology: a review of extant literature", Studies in Economics and Finance , Vol. 37 No. 1, pp. 71-88. https://doi.org/10.1108/SEF-07-2019-0270

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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