process of innovation essay

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The Discipline of Innovation

• Peter F. Drucker

In business, innovation rarely springs from a flash of inspiration. It arises from a cold-eyed analysis of seven kinds of opportunities.

The Idea in Brief

In the hypercompetition for breakthrough solutions, managers worry too much about characteristics and personality—“Am I smart enough? Do I have the right temperament?”—and not enough about process. A commitment to the systematic search for imaginative and useful ideas is what successful entrepreneurs share—not some special genius or trait. What’s more, entrepreneurship can occur in a business of any size or age because, at heart, it has to do with a certain kind of activity: innovation, the disciplined effort to improve a business’s potential.

Most innovations result from a conscious, purposeful search for opportunities—within the company and the industry as well as the larger social and intellectual environment. A successful innovation may come from pulling together different strands of knowledge, recognizing an underlying theme in public perception, or extracting new insights from failure.

The key is to know where to look.

The Idea in Practice

Successful entrepreneurs don’t wait for innovative ideas to strike like a lightning bolt. They go out looking for innovation opportunities in seven key areas:

1. Unexpected occurrences. These often include failures. Few people know, for instance, that the failure of the Edsel led Ford to realize that the auto market was now segmented by lifestyle instead of by income group. Ford’s response was the Mustang, and an auto legend was born.

2. Incongruities. By the 1960s, cataract removal had become high-tech, except for cutting a ligament, an “old-fashioned” step that was uncomfortable for eye surgeons. Alcon Laboratories responded by modifying an enzyme that dissolved the ligament. Surgeons immediately accepted the new product, giving Alcon a monopoly.

3. Process needs. Two process innovations developed around 1890 created “the media” as we know it today: linotype made it possible to produce newspapers quickly, and advertising made it possible to distribute news practically free of charge.

4. Industry and market changes. The brokerage firm Donaldson, Lufkin & Jenrette achieved fabulous success because its founders recognized that the emerging market for institutional investors would one day predominate in the industry.

5. Demographic changes. Why are the Japanese ahead in robotics? Around 1970, everyone knew that there was both a baby bust and an education explosion, such that the number of blue-collar manufacturing workers would decline. Everyone knew—but only the Japanese took action.

6. Changes in perception. Such changes don’t alter the facts, but can dramatically change their meaning. Americans’ health has never been better—yet we’re obsessed with preventing disease and staying fit. Innovators who understand our perception of health have launched magazines, introduced health foods, and started exercise classes.

7. New knowledge. Knowledge-based innovations require long lead times and the convergence of different kinds of knowledge. The computer required knowledge that was available by 1918, but the first operational digital computer did not appear until 1946.

Purposeful innovation begins with looking, asking, and listening. Talent and expert knowledge help, but don’t be deluded by all the stories about flashes of insight. The key task is to work out analytically what the innovation has to be in order to satisfy a particular opportunity.

Despite much discussion these days of the “entrepreneurial personality,” few of the entrepreneurs with whom I have worked during the past 30 years had such personalities. But I have known many people—salespeople, surgeons, journalists, scholars, even musicians—who did have them without being the least bit entrepreneurial. What all the successful entrepreneurs I have met have in common is not a certain kind of personality but a commitment to the systematic practice of innovation.

• PD Peter F. Drucker (November 19, 1909 – November 11, 2005) was an Austrian-born American management consultant, educator, and author whose writings contributed to the philosophical and practical foundations of the modern business corporation. He was also a leader in the development of management education, he invented the concept known as management by objectives, and he has been described as “the founder of modern management.”

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Innovation in Business: What It Is & Why It’s Important

• 08 Mar 2022

Today’s competitive landscape heavily relies on innovation. Business leaders must constantly look for new ways to innovate because you can't solve many problems with old solutions.

Innovation is critical across all industries; however, it's important to avoid using it as a buzzword and instead take time to thoroughly understand the innovation process.

Here's an overview of innovation in business, why it's important, and how you can encourage it in the workplace.

What Is Innovation?

Innovation and creativity are often used synonymously. While similar, they're not the same. Using creativity in business is important because it fosters unique ideas . This novelty is a key component of innovation.

For an idea to be innovative, it must also be useful. Creative ideas don't always lead to innovations because they don't necessarily produce viable solutions to problems.

Simply put: Innovation is a product, service, business model, or strategy that's both novel and useful. Innovations don't have to be major breakthroughs in technology or new business models; they can be as simple as upgrades to a company's customer service or features added to an existing product.

Access your free e-book today.

Types of Innovation

Innovation in business can be grouped into two categories : sustaining and disruptive.

• Sustaining innovation: Sustaining innovation enhances an organization's processes and technologies to improve its product line for an existing customer base. It's typically pursued by incumbent businesses that want to stay atop their market.
• Disruptive innovation: Disruptive innovation occurs when smaller companies challenge larger businesses. It can be classified into groups depending on the markets those businesses compete in. Low-end disruption refers to companies entering and claiming a segment at the bottom of an existing market, while new-market disruption denotes companies creating an additional market segment to serve a customer base the existing market doesn't reach.

The most successful companies incorporate both types of innovation into their business strategies. While maintaining an existing position in the market is important, pursuing growth is essential to being competitive. It also helps protect a business against other companies affecting its standing.

Learn about the differences between sustaining and disruptive innovation in the video below, and subscribe to our YouTube channel for more explainer content!

The Importance of Innovation

Unforeseen challenges are inevitable in business. Innovation can help you stay ahead of the curve and grow your company in the process. Here are three reasons innovation is crucial for your business:

• It allows adaptability: The recent COVID-19 pandemic disrupted business on a monumental scale. Routine operations were rendered obsolete over the course of a few months. Many businesses still sustain negative results from this world shift because they’ve stuck to the status quo. Innovation is often necessary for companies to adapt and overcome the challenges of change.
• It fosters growth: Stagnation can be extremely detrimental to your business. Achieving organizational and economic growth through innovation is key to staying afloat in today’s highly competitive world.
• It separates businesses from their competition: Most industries are populated with multiple competitors offering similar products or services. Innovation can distinguish your business from others.

Innovation & Design Thinking

Several tools encourage innovation in the workplace. For example, when a problem’s cause is difficult to pinpoint, you can turn to approaches like creative problem-solving . One of the best approaches to innovation is adopting a design thinking mentality.

Design thinking is a solutions-based, human-centric mindset. It's a practical way to strategize and design using insights from observations and research.

Four Phases of Innovation

Innovation's requirements for novelty and usefulness call for navigating between concrete and abstract thinking. Introducing structure to innovation can guide this process.

In the online course Design Thinking and Innovation , Harvard Business School Dean Srikant Datar teaches design thinking principles using a four-phase innovation framework : clarify, ideate, develop, and implement.

• Clarify: The first stage of the process is clarifying a problem. This involves conducting research to empathize with your target audience. The goal is to identify their key pain points and frame the problem in a way that allows you to solve it.
• Ideate: The ideation stage involves generating ideas to solve the problem identified during research. Ideation challenges assumptions and overcomes biases to produce innovative ideas.
• Develop: The development stage involves exploring solutions generated during ideation. It emphasizes rapid prototyping to answer questions about a solution's practicality and effectiveness.
• Implement: The final stage of the process is implementation. This stage involves communicating your developed idea to stakeholders to encourage its adoption.

Human-Centered Design

Innovation requires considering user needs. Design thinking promotes empathy by fostering human-centered design , which addresses explicit pain points and latent needs identified during innovation’s clarification stage.

There are three characteristics of human-centered design:

• Desirability: For a product or service to succeed, people must want it. Prosperous innovations are attractive to consumers and meet their needs.
• Feasibility: Innovative ideas won't go anywhere unless you have the resources to pursue them. You must consider whether ideas are possible given technological, economic, or regulatory barriers.
• Viability: Even if a design is desirable and feasible, it also needs to be sustainable. You must consistently produce or deliver designs over extended periods for them to be viable.

Consider these characteristics when problem-solving, as each is necessary for successful innovation.

The Operational and Innovative Worlds

Creativity and idea generation are vital to innovation, but you may encounter situations in which pursuing an idea isn't feasible. Such scenarios represent a conflict between the innovative and operational worlds.

The Operational World

The operational world reflects an organization's routine processes and procedures. Metrics and results are prioritized, and creativity isn't encouraged to the extent required for innovation. Endeavors that disrupt routine—such as risk-taking—are typically discouraged.

The Innovative World

The innovative world encourages creativity and experimentation. This side of business allows for open-endedly exploring ideas but tends to neglect the functional side.

Both worlds are necessary for innovation, as creativity must be grounded in reality. You should strive to balance them to produce human-centered solutions. Design thinking strikes this balance by guiding you between the concrete and abstract.

Learning the Ropes of Innovation

Innovation is easier said than done. It often requires you to collaborate with others, overcome resistance from stakeholders, and invest valuable time and resources into generating solutions. It can also be highly discouraging because many ideas generated during ideation may not go anywhere. But the end result can make the difference between your organization's success or failure.

The good news is that innovation can be learned. If you're interested in more effectively innovating, consider taking an online innovation course. Receiving practical guidance can increase your skills and teach you how to approach problem-solving with a human-centered mentality.

Eager to learn more about innovation? Explore Design Thinking and Innovation ,one of our online entrepreneurship and innovation courses. If you're not sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

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The Five Stages of Successful Innovation

Defining an innovation process increases companies’ future value.

• Innovation Strategy
• Developing Strategy

Serendipity is not a strategy, yet that’s the extent of most companies’ innovation planning. The importance of innovation to a company’s future is unquestionable. Then why do so few companies have a process for it? The authors of a September 2006 working paper, Crafting Organizational Innovation Processes, address that question. Their underlying research comprised semi-structured interviews conducted with senior research and development, marketing and product management executives from more than 30 U.S. and European companies in several distinct industries, supplemented with data from annual reports.

The paper identifies five discrete and essential stages of successful innovation.

Stage 1: Idea Generation and Mobilization

The generation stage is the starting line for new ideas. Successful idea generation should be fueled both by the pressure to compete and by the freedom to explore. IDEO, the product development and branding company based in Palo Alto, California, is a good example of an organization that encourages successful idea generation by finding a balance between playfulness and need.

Once a new idea is generated, it passes on to the mobilization stage, wherein the idea travels to a different physical or logical location. Since most inventors aren’t also marketers, a new idea often needs someone other than its originator to move it along. This stage is vitally important to the progression of a new idea, and skipping it can delay or even sabotage the innovation process.

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Stage 2: Advocacy and Screening

This stage is the time for weighing an idea’s pros and cons. Advocacy and screening have to take place at the same time to weed out ideas that lack potential without allowing stakeholders to reject ideas impulsively solely on the basis of their novelty. The authors found that companies had more success when the evaluation process was transparent and standardized, because employees felt more comfortable contributing when they could anticipate how their ideas would be judged. For example, one software engineer from an information technology organization said, “One of the things I have struggled with is evaluations of my ideas. Some of my ideas light up fires around here, while others are squashed. . . . Needless to say, I grow skeptical when [the executives] ask for ideas and then do not provide feedback as to why an idea was not pursued.�

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A Systems View Across Time and Space

• Open access
• Published: 25 March 2016

Conceptualizing the innovation process towards the ‘active innovation paradigm’—trends and outlook

• Dirk Meissner 1 &
• Maxim Kotsemir 1  

Journal of Innovation and Entrepreneurship volume  5 , Article number:  14 ( 2016 ) Cite this article

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This paper introduces the evolving understanding and conceptualization of innovation process models. We categorize the different approaches to understand and model innovation processes into two types. First, the so-called innovation management approach focuses on the evolution of corporate innovation management strategies in different social and economic environments. The second type is the conceptual approach which analyses the evolution of innovation models themselves as well as the models’ theoretical backgrounds and requirements. The focus in this second approach is the advantages and disadvantages of different innovation models in how far they can describe the reality of innovation processes.

The paper focuses on the advantages and disadvantages as well as the potential and limitations of the approaches. It also proposes potential future developments of innovation models as well as the analysis of the driving forces that underlie the evolution of innovation models.

The article concludes that the predominant open innovation paradigm requires rethinking and further development towards an ‘active innovation’ paradigm.

Innovation has been a phenomenon which for centuries serves the only purpose of making human beings’ lives more comfortable. Throughout history, supporting, generating and implementing innovation has been of outstanding importance not only for the well-being but sometimes the survival of individuals, entities and even for whole civilizations and nations.

Over the last few decades, our understanding of innovation and its overall impact on national welfare has changed considerably. Innovation has commonly been understood as the ‘… implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations.’ (OECD, Eurostat 2005 ). Innovation practice today shows that innovation is by nature a value-free term and comprehensively covers the whole spectrum of activities from discovery to first time practical application of new knowledge. Moreover, innovation aims to fulfil recipients’ requirements and goals in a new way; and it stresses that risk and uncertainty are inherent at all stages of innovation processes.

In light of the development of innovation concepts, models of innovation and innovation processes have evolved (for example, Carlsson et al. 2002 ; Godin 2006 ). Meanwhile, there is a broad range of models about innovation processes. All these models share a common understanding that innovation activities can broadly be described and visualized in process models. Some models describe the life cycle of innovation by an S-shaped logistic function, which consists of three separate phases reflecting the application phases of its development: emergence, growth and maturity (Howard and Guile 1992 ; Mitrova et al. 2015 ; Perani and Sirilli 2008 ). Other studies emphasize the characteristics of innovation which are defined according to innovation development stages. For example, Maidique ( 1980 ) distinguishes the recognition of the invention, development, realization and distribution as phases of innovation process. In general, linear models of innovation distinguish the discovery (invention), the definition of possible spheres of applications of the results of innovation, its development, design and use as phases of the innovation process (see for example, Niosi ( 1999 ); Godin ( 2006 ); Meissner ( 2015 ); Carayannis et al. ( 2015 )) for simplistic description of innovation processes).

The evolving understanding of innovation as a process of activities raises new challenges to innovators. Although innovation is commonly regarded the outcome of a process of activities, these are by no means always succeeding in linear shape but involve several feedback loops. Hence, typical activities and steps are common for many innovation projects but the uncertainty of achieving results and finishing an activity with the required quality force innovators to feedback between the activities in order to improve the final solution. These challenges are expressed in the increasing complexity of innovations which are in turn also determined by the complexity of the surrounding, ‘framework’ conditions. Consequently, the complexity—expressed by the number—of information sources, knowledge and application fields for innovation is rising. In this light, innovators need to analyse and process more information for the same purpose (Carayannis and Campbell 2011 ; Carayannis and Turner 2006 ; Gokhberg et al. 2010 ; Gault 2009 ; Godin 2010 ).

Furthermore, until recently, innovation was considered as a process or a sequence of activities and steps but the surrounding factors such as company culture for innovation and the meaning of human resources for innovation were only partially reflected. Therefore, the authors consider it important to review the existing academic works which analyse the understanding of the emergence of innovation from a management perspective (innovation management) and from the macro perspective. The article hence aims at the following research issues:

How did the understanding of the innovation process change?

Which features were included in the innovation process understanding?

Which issues remain open and deserve further elaboration to include in the innovation process understanding?

The article contributes to the understanding and academic and practical discussion of innovation processes by reviewing the emergence of innovation models. It discusses the potentials and limitations of the different innovation process models and derives proposals for future work on the innovation models.

The work proceeds as follows. The second section discusses how the understanding and thinking of the innovation process has evolved. In the third section, we discuss these approaches in light of the innovation management literature and a broader conceptual discussion and examine the future challenges and their impact on the innovation process model. We end with a summary and elaboration of future work.

In order to give a representative review of works, a literature search was conducted to identify influential papers. We started with the identification of leading articles that look at the models and trends of innovation processes and innovation models. The literature search covers a 50-year period based on the rationale that this is certainly long enough to describe reliable trends in innovation model and process understanding and perception.

In order to conduct a review of influential papers, a literature survey was done. First, we identified the most prominent articles that discuss innovation models and processes and their meaning for innovation management. For literature search, we used ISI Web of Science, Emerald text, Science Direct and Inderscience which we consider provide sufficient information on articles in leading scholarly journals in the area. The literature search was done using the keywords ‘innovation process’ and ‘innovation model’ which in our understanding are reasonable broad to cover the related publications. Second, we scanned articles published up to January 2013 and cited more than 200 times. Third, we narrowed the findings of the search by assessing the articles abstracts. The assessment criteria used were the article’s focus on the search term and the relevance of the search terms for the full article. Finally, from the article analysis, two groups were defined including the ‘innovation process models’ which have a clear relevance to innovation management and the ‘conceptual approaches’ which aim at explaining the emergence of innovation in conceptual sense.

Findings and Discussion - Understandings of the innovation process

Innovation is characterized by a high complexity that requires unorthodox thinking and must be socially accepted to succeed. Hence, the term innovation includes new technological, economic, organizational and social solutions which are not necessarily marketable in an economic sense with direct monetary impact but are applied and used. Therefore, knowledge and ideas are essential components of the term innovation.

The literature has devoted much attention around ‘idea driven’ innovation processes since the second half of the twentieth century. Usher describes the innovation process as the perception of an unsatisfied need, setting the stage following the primary act of insight, critical revision and development (Usher 1954 , 1955 ). Knight ( 1967 ) and Bessant and Tidd ( 2007 ) consider the first stage to be recognizing the need for innovation, followed by innovation generation, innovation adoption and the use of innovation. Based on the recognition of the invention, Maidique ( 1980 ) assumes immediate action taken for the development of new products followed by the market realization of product and the distribution of products to customers. Carlsson et al. ( 1976 )) make the process more concrete by including an application phase of research/technology after the initial discovery (need for idea) concluding with development, design and utilization activities. In Marquis’ model ( 1988 ), the process starts with the initial recognition of the technical feasibility and the assessment of potential market demands which in his view lead to idea formulation (fusion into design concept and evaluation), problem-solving (search, experimentation and calculation; readily available information), solution (solution through invention; solution through adoption), development (work out the bugs and scale up) and utilization and diffusion (implementation and use). Gallivan ( 2001 ) recognizes management objectives for change as the initial driver for innovation, complemented by the search for invention availability for technological inventions and the primary innovation adoption process embedded in a company’s mandate to adopt other influences on innovation adoption which eventually leads to a secondary innovation adoption process. Kamal ( 2006 ) has a comparable understanding by first focusing on the motivation for innovation, then the specific conception of innovation and formal proposals to the organization about innovation adoption before entering into the actual adoption decision stage. Next, the implementation is launched with the confirmation of the innovation idea, the test of user acceptance of the technology and the integration of innovative technology with other information system applications.

Other linear approaches are considered ‘invention-led’ processes (see for example, Carlsson et al. 1976 ). A more simplified linear process was postulated by Merrifield ( 1986 ) who includes the steps of invention, translation and commercialization. Niosi ( 1999 ) and Godin ( 2006 ) introduce the definition of innovation application areas after the initial discovery (invention) stage. The application definition stage is followed by innovation development, design, and use.

‘Creation-need’ process models were developed by Aiken and Hage ( 1971 ) and Pierce and Delbecq ( 1977 ) who argue that the innovation process spans the stages of generation, acceptance and implementation. Howard and Guile ( 1992 ) first showed the S-shaped logistic function of emergence, growth and maturity while Baregheh et al. ( 2009 ) distinguish creation, generation, implementation, development and adoption.

Taking the large number of models together, we find that two main process models have emerged: (1) innovation management process models and (2) conceptual process models. These are described in the following.

Innovation management process models

These simplistic approaches cannot be treated as real models of the innovation process but rather as a schematic description. Although genuine models which are more complex were developed in the scientific literature in the second half of the twentieth and the early twenty-first centuries, these models remain idealistic descriptions of innovation generation. Such process models have certain implications for the organization of innovation in companies, research institutes, and engineering companies; however, they will change each time a new innovation project is started. One can also argue that there is in fact no definite innovation project but rather overlapping activities of different kinds and intensities which form the basis for the next generation of innovation. Table  1 shows a summary of these understandings of the innovation process. It is evident that significant share of the innovation management literature describes the innovation process as somewhat linear mainly in not only the early works (Usher 1954 , 1955 ) but also in more recent papers (Kamal 2006 ; Baregheh et al. 2009 ). The full overview of innovation process models is shown in the Working Paper by Kotsemir and Meissner ( 2013 ) “Conceptualizing the innovation process—trends and outlook”.

The first-generation ‘technology push’ model postulates that new industries mostly emerge from new technological opportunities which resulted in technology-led regeneration of ‘old’ sectors requiring rapid applications of technology to enhance the productivity and quality of production. This, in turn, led to rapid employment creation, rising prosperity, and a consumer boom of ‘new products’ (consumer electronics and automobile industry). Scientific advances were perceived in favour of industrial innovation and as instruments for solving society’s greatest challenges. The logic of the ‘technology-push’ model approach was that the greater the R&D ‘input’, the more success for new products ‘as output’; this model presupposes a linear process of technological change (industrial innovation), spanning scientific discovery, technological product development and product sales. However, the process of transformation became the object of study in itself (Carter and Williams 1957 ) and this later formed the main focus for the evolutionary models of the late 1990s as well as the role of the marketplace in processes of transformation (Cook and Morrison 1961 ), upon which the innovation milieu models of the 2000s were built.

In the late 1960s, Myers and Marquis developed the ‘technology push’ idea of market-relevant aspects (second generation). They reasoned that innovation resulting from R&D activities is targeted towards satisfying customer needs: the ‘market-pull’ approach (Myers and Marquis 1969a , b ). Hence, the second generation, ‘market-pull’ models appeared in the second half of the 1960s, and early 1970s emphasized how technologies contribute to decelerated growth of new product markets and a balancing of supply and demand on new product markets, and how they assume that new products are based on existing technologies. Thus, innovation was still understood as a linear process, as in the first-generation models yet, the difference was that market needs were identified first, followed by development, manufacturing and sales. The main risks of this approach included the limited implementation of long-term R&D programmes and the danger that companies could be locked into a regime of technological incrementalism and lose the capacity to adapt to any radical market or technological changes (Hayes and Abernathy 1980 ).

Mowery and Rosenberg ( 1979 ) first described the importance of corporate functions interacting in the innovation process. Shortly afterwards, Rothwell and Zegveld ( 1985 ) extended the traditional linear approach to connect businesses with external research institutions and the market in their ‘coupling model’ (third generation, of the early 1970s and early 1980s). This third generation saw two major oil crises, high rates of inflation and demand saturation (stagflation), which resulted in an oversupply of production capacities and growing structural unemployment. In this context, science and technologies were needed to understand the basis of successful innovation which was underlined by a stream of empirical studies of innovation processes (Cooper 1980 ; Hayvaert 1973 ; Langrish et al. 1972 ; Myers and Marquis 1969a , b ; Rothwell et al. 1974 ; Rothwell 1976 ; Rubenstein 1957 ; Schock 1974 ; Szakasitz 1974 ; Utterback 1975 ). The model coupled the ‘technology-push’ and ‘market-pull’ models and was perceived as an extreme and atypical model of the innovation process. It strongly emphasized the interactions between technological capabilities and market needs, as well as the confluence of technological capabilities and market needs within the framework of the innovating firm. Rothwell and Zegveld ( 1985 ) argued that the innovation process can be functionally distinct but has interacting and interdependent stages; thus, the process itself can be logically sequential, although not necessarily continuous.

The ‘chain-linked’/integrated innovation process model (fourth generation) considered the innovation process as fundamentally a parallel process in which the corporate functions are connected through numerous backward (feedback) loops (Kline and Rosenberg 1986 ). They saw a considerable growth of generic technologies, the emergence of new generations of IT-based manufacturing equipment, and a shortening of product life cycles. During this time, firms increasingly engaged in strategic alliances (Contractor and Lorange 1988 ; Dodgson 1993 ; Hagedoorn 1990 ) and emphasized technological accumulation, core businesses and key technologies (Peters and Waterman 1982 ). These activities were accompanied by greater networking activities of small innovative firms (Docter and Stokman 1987 ; Rothwell 1991 ).

The innovation process of the ‘fifth generation’ is based on the ‘chain-linked’ model and adds a strategic component—the integration of cooperating companies, the growing importance of information and communication technologies and the use of expert systems and networks (Rothwell 1992 ). This model is characterized by integrated, parallel, flexible and interconnected innovation processes since the early 1990s. It was recognized that successful corporate innovation strategies were driven by centrally integrated and parallel development processes, strong and early vertical linkages, and the use of electronics-based design and information systems. Integrated innovation models highlight a reasonably strong presence of collaborative, pre-competitive research, joint R&D ventures and R&D-based strategic alliances. As a result, the speed and efficiency of developing innovation increased with the emergence of radical new products and developments along established design trajectories.

The ‘sixth-generation’ model emerged when Chesbrough ( 2003a , b ) postulated the open innovation paradigm, which highlights the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively. It assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as they look to advance their technology (Chesbrough 2006 ). Innovations are no longer ‘just’ seen as a process, involving various functions. Rather, it is explained by the participation of a number of different entities including suppliers, public R&D facilities and (business) external R&D facilities as well as customers with varying degrees of intensity.

Conceptual innovation process models

Marinova and Phillimore ( 2003 ) take a broader perspective in analysing the innovation process models. They find six generations of innovation models:

Black box model—first generation

Linear model—second generation

Interactive models—third generation

System model—fourth generation

Evolutionary model—fifth generation

Innovation milieu model—sixth generation

The black box model (first generation) is based on the Solow production function (Solow 1957 ) which was the first attempt to include technological progress in the economic equation. Innovation was understood as one driver of economic growth which could not be explained by changes in capital, and labour instead was assumed to be caused by technological advances. The black box term was a starting point for the innovation discussion postulating the apparent invisibility of what happens when investing in science and technology. Accordingly, the black box innovation model assumes that the innovation process itself is not important and that the only things that count are inputs and outputs, e.g., money invested in R&D (input into the black box) will generate, as a rule of thumb, new technological products (outputs). It is argued that the use of appropriate and timely adjusted management activities makes certain firms more successful than others (Rosenberg 1982 ; Mansfield 1995 ). Eventually, this understanding led to a reluctance of researchers to address the link between science, technology and industrial development, a reliance of policymakers on market mechanisms to support technological developments and a narrower understanding of innovation which was limited to R&D exclusively. Therefore, the need arose to open the black box and explore its interior.

The second-generation models in 1960s and 1970s emphasized mainly linear models which aimed at opening the black box of innovation, focusing on specific processes that generate new technologies and learning involved in technological change. It was expected that innovations open the road to formulating policies, which would stimulate R&D and consequently the development of new products and processes using a step-by-step process, e.g. a sequence of activities that lead to technologies being adopted by markets. This was reflected in three main models, the science push model in which basic science-based discoveries lead eventually to technological developments which result in a flow of new products and processes to the market place (Rothwell and Zegveld 1985 ), the technology push model emphasizing the entrepreneur as the person taking the risk and overcoming the barriers in order to extract the monopolistic benefits from the introduction of new ideas (Coombs et al. 1987 ) and the need pull (‘market-driven’) model which postulates that the causes of innovation are existing demands (Rothwell and Zegveld 1985 ). The technology push/need pull dichotomy analysed a wide range of successfully introduced new technologies and numerous cases of failure (Coombs et al. 1987 ). The linear models achieved to developing an easy and clear model of innovation and setting the direction for further research.

The interactive models in the third generation build on the main disadvantage of previous models, namely the extremely simplified picture of the generally complex interactions between science, technology and market. These models were understood to giving a deeper understanding and a more thorough description of all the aspects and actors of the innovation process and providing a new look at innovation as a process subdivided into separate stages, each of them interacting with the others. In essence, the interactive models stressed that innovation is no longer the end product of a final stage of activities but can occur at various places throughout the process and the innovation process can also be circular (iterative) rather than purely sequential (Rothwell and Zegveld 1985 ; Beije 1998 ; Kline and Rosenberg 1986 ). The interactive models eventually brought together the technology push and market pull approaches into a comprehensive model of innovation and developed a more complete and nuanced approach to the issue of the factors and players involved in innovation. However, the interactive models still did not specify the driving forces for the innovation engine, why some companies are better at doing in innovation than others, strategies of learning for organizations and the role of the company’s environment for the success of innovation.

Against these weaknesses, the system innovation model (fourth generation) emerged. The system innovation model claimed to explain and confirm the fact that complexity of innovation requires interactions not only from a wide spectrum of agents within the firm but also from cooperation amongst firms. This approach proved unique in its looking at innovation from a system perspective, which included an emphasis on interactions, inter-connectedness and synergies. It postulated that firms that do not have large resources to develop innovation in-house can benefit from establishing relationships with a network of other firms and organizations, the set of elements in the innovation system and their interconnectedness and ways of interaction are the key factors for success and functioning of this system. The most well-known system model was the national systems of innovation (Freeman 1991 ; Lundvall 1992 ; Nelson 1993 , 2000 ). The system models mainly explained the place and role of small firms in innovation, the means of surviving of small firms in the competition and from pressures from large companies, synergetic effects from innovation networks, differences between countries and the various role governments play and highlighted specific patterns of scientific, technological and industrial specialization, institutional profiles and structures as well as patterns of learning for different countries. These features were described in the concepts of innovation chains for manufacturer-distributor relationships (Marceau 1992 ; Dodgson 1993 ), innovation complexes for the integration of firms (Gann 1991 , 2000 ), strategic networks/alliances for long-term strategic contracts between companies and third parties from external environment (Jarillo 1988 ; Sako 1992 ), regional networks with a focus on geographic location of innovators (Dodgson 1993 ) and regional systems of innovation on the influence of specific regional environment on the modes of innovation processes (Cooke 1998 ). The system models have been widely used although in their original shape, they did not stress the lifetime of innovation networks, the potential of networks for promoting innovation in large firms, the meaning of trust building in the networked innovation and the ways of its achievement, mechanisms of simultaneous cooperation and competition within the innovation network and partially only the role of governments, proactive policies and regulatory environments in creating favourable conditions for such linkages and interactions.

The fifth generation evolutionary models aimed to find approaches to challenge the main disadvantage of previous models which were identified as failures in neoclassical economics to deal with dynamic qualitative changes and weak explanatory power of the mechanical metaphor adopted in orthodox economic thinking for innovation dynamics (Hodgson 1993 ; Saviotti 1996 ). The key elements of evolutionary models are the external environment (patent regimes, market structures, standards and regulations as well as natural environment) in which technologies are developed, the population perspective and variation (not only average values but also variances in the population of firms/products are in focus of analysis). Evolutionary models commonly argue that innovation by definition involves change, decisions on innovations are made not merely based on price consideration, imperfections are necessary conditions for technical change to occur in a market economy, outcomes from innovation activities are to a large degree determined by the evolutionary process (at country or firm level) and that the innovation process is as important as the results from R&D as well as that firms can be dynamic self-organized systems (Dosi and Orsenigo 1994 ; Metcalfe 1995 ; OECD 1996 ). The models are directed to explaining the ‘bounded rationality’ problem (Dosi and Egibi 1991 ) and the processes of failure of generally fit technologies and the success of ‘overlooked’ technologies (Tisdell 1995 ) as well as highlighting the value of diversity (Dowrick 1995 ). Overall, they shed light on decision-making schemes and interaction of participants’ modes in innovation processes. Related concepts to the evolutionary models are the concept of technological imperatives (Rosenberg 1976 ), innovation avenues (Sahal 1981 ), technological trajectories (Biondi and Galli 1992 ; Pavitt et al. 1989 ), technological paradigms (Dosi 1982 , 1988 ) and technoeconomic paradigms (Freeman and Perez 1988 ; Perez 1983 ) which commonly argue that a certain extent of stable regularities in innovation process and technological development are the product of ‘negotiations’ between key institutions and result of adaptation to new conditions of work. These models provided reasonable stimulus for further research, especially they stressed the need for explaining the mechanisms supporting the continuity of the old and the introduction of new equilibriums in modeled innovation processes and the need for characterization of turning points in the innovation process in the framework of evolutionary models.

Eventually, the innovation milieu concepts (sixth generation) were developed which look at theories of growth of regional clusters of innovation and high technology and the importance of geographical location for knowledge generation (Feldman 1994 ; Keeble and Wilkinson 2000 ). Whereas previously territorial organization was assumed a crucially important element for innovation process (Bramanti and Ratti 1997 ) and innovation understood as being geographically localized and innovation processes highly dependent from specific resources which are unique for each location (Longhi and Keeble 2000 ), the innovation milieu model stresses active territorial relationships, e.g. inter-firm and inter-organizational interactions fostering innovation, different territorial socio-economic actors, e.g. local private or public institutions supporting innovation, a specific culture and representation process and a dynamic local collective learning process (Camagni 1991 ). The innovation milieu approaches look at success factors of small- and medium-sized enterprises, mechanisms through which certain localities give birth to a large number of small innovative firms and provide explanation how different localities have different patterns and paths in knowledge development and transfer of high technology. This is especially apparent in the innovation clusters approach which emphasizes groups of innovative firms located in one region (OECD 1999 ), the learning regions approach (e.g. Florida 1995 ; Kirat and Lung 1999 ; Macleod 1996 ) and the collective learning concept (Keeble and Wilkinson 2000 ). The main argument of these concepts is that learning is the most important feature of any economy and that successful regions provide particular combinations of institutions and organizations to encourage knowledge development within the community and learning by local firms through conscious and unconscious mechanisms.

In general, the innovation process models developed to date are similar in that they all emphasize the key role of sources of innovation (such as sources of inspiration), which have changed considerably in innovation processes theory. Moreover, over time, the understanding of the process in which innovation is generated has deepened. On the one hand, the meaning of the sources (triggers) of innovation has changed, and on the other hand, the different phases/stages of the innovation process have been substantially redefined. Another new feature is moving away from understanding the innovation process as a linear sequence towards seeing it as made up of different, integrated phases. The individual phases overlap each other, and there are also backward loops (‘feedback loops’). In terms of transferring knowledge and technology in course of innovation development, the literature emphasizes interactive models that mutually enrich basic research and applied research and development.

All approaches distinguish between the origins of the market phase. In this understanding, the real innovation process is completed with the first economic use and the associated transition from the development cycle of a product or process to its market cycle. The market cycle of an innovation can be divided into innovation diffusion and adoption. Under diffusion, an early communication of the innovation is understood (i.e. in the model of Rogers ( 1995 )) followed by the physical diffusion of innovation in the market. Diffusion includes both the diffusion of an innovation geographically as well as within specific industries or markets (OECD, Eurostat 1997 ). Adoption of innovation by the user means actual use (Rogers 1995 ). This is not to be equated with the innovation’s general and permanent application; rather, users can disregard innovation because of unfulfilled expectations, substitution technologies or other reasons connected with further use of the technology. In the mid-twentieth century, a view predominated that innovation is entirely due to technological breakthroughs that will automatically generate demand (the technology push approach). The essential feature of these first-generation models is the assumed linear sequence of individual steps from research to market introduction.

Currently, the predominant thinking is that innovation is the result of multiple relationships of different entities and organizations in the ‘open innovation paradigm’.

Innovation models analysis: a discussion

In this paper, we compared two basic analytical approaches to the evolution of innovation process models. The first is the ‘innovation management’ approach focusing on the analysis of innovation management strategies at a firm level in different social and economic frameworks. The second is the ‘conceptual approach’, which focuses on the evolution of innovation models themselves (in a conceptual sense) as well as on the analysis of the models’ theoretical backgrounds and requirements. This approach concentrates on the advantages and disadvantages of the different models in terms of their ability to describe the reality of innovation processes. Analysing these two approaches shows a shift from a macro (meso level) to a micro level in theoretical innovation models and models of innovation management. We also illustrated the non-linear nature of the dynamics of the evolution of conceptual innovation models during the last 15–20 years. In the previous section, we showed that the understanding of innovation processes has changed considerably over the years. More recently, the two major approaches of innovation process thinking, e.g. the innovation management approach and the conceptual approach, show remarkably different features.

‘Innovation management’ approach

The models following the ‘innovation management’ approach do not focus on the development of innovation but rather on the evolution of companies’ innovation management strategies under different social, economic and political circumstances. One of the most well-known examples of such an approach is the so-called Rothwell five generations innovation model. In his seminal work, Rothwell ( 1994 ) identifies five generations of innovation management models and describes their evolutionary development as well as the respective social and economic policymaking and management strategy framework. Other major studies on the evolution of innovation management models are Niosi ( 1999 ), Verloop ( 2004 ), Cagnazzo et al. ( 2008 ), Jacobs and Snijders ( 2008 ) and Eveleens ( 2010 ). The distinctive feature of Rothwell’s model is the comprehensive analysis of innovation management models themselves and their social and economic framework and focuses on the evolutionary development of innovation strategies of companies in different economic conditions. The framework proposed by Rothwell can be considered almost universal. For example, in Jacobs and Snijders ( 2008 ), the last (fourth in a row) generation of innovation management models is treated as ‘learning and interaction’ models—in line with the fifth generation of innovation models. Moreover, according to the comprehensive review of literature on innovation management models carried out by Cagnazzo et al. ( 2008 ), all papers on the innovation management model use Rothwell’s five-generation sequence as a framework. In other words, in the nearly 20 years that have passed since the publication of Rothwell’s article in 1994, there have not been any studies proposing a sixth (or even seventh) generation of innovation management models. The reason may be that recent trends in innovation strategies such as networking, outsourcing, globalization and customer involvement can be treated as ‘flexible’, ‘parallel’, ‘interactive’ and an ‘interconnected’ process. Such logic eliminates the need for building a new generation of innovation management models.

‘Conceptual’ approach

The ‘conceptual approach’ focuses on the conceptual essence of models and analyses their theoretical backgrounds as well as their advantages and disadvantages (Marinova and Phillimore 2003 ). Analysis of the related literature shows that in most cases, the authors concentrate on the historical development of only one specific type of innovation model, i.e. the national innovation system (Bazalt and Hanush 2004 ; Sharif 2006 ; Godin 2009 ) or the regional innovation system (Iammarino 2005 ; Asheim et al. 2011 ). In contrast, Marinova and Phillimore ( 2003 ) encompass the whole sequence of innovation models from the earliest stages. The authors analysed innovation models per se, viewing the models as conceptual and theoretical constructs. Some scholars have also analysed the theoretical background and explanatory power for each generation of models, as well as the potential directions for the models’ future development.

Differences and similarities of the management and conceptual approach

Therefore, the main difference between Rothwell’s and Marinova-Phillimore’s work is the scope, namely the focus of analysis. Rothwell primarily analyses not the innovation models themselves but rather the strategies of firms’ innovation activity under different social, economic and political circumstances. Thus, Rothwell’s model is primarily for companies. Marinova and Phillimore analyse the models themselves as well as the models’ theoretical backgrounds and principal advantages and disadvantages. Therefore, in the framework of this work, innovation models are for the whole economy (Vishnevskiy et al. 2015 ; Proskuryakova et al. 2015 ; Gackstatter et al. 2014 ).

However, the similarities in the generation of models highlighted by Rothwell and Marinova and Phillimore are also very important. The evolution of innovation models starts from ‘in search’ (or simplistic) models of the first two generations, than goes to macro level (third-generation models in Rothwell’s work as well as to some extent in the fourth- and fifth-generation level models in Marinova and Phillimore’s work) and shifts to the micro level (sixth generation in Marinova and Phillimore’s work and fourth and fifth generation in Rothwell). In Marinova and Phillimore’s framework of analysis, third generation models can be described as ‘transition’ models from first ‘immature’ models to the more mature models. The first two generation models in both Rothwell and Marinova and Phillimore can be treated as meso-level models since they assume that the processes described are generally identical for all firms. Rothwell’s third-generation models cannot be treated as purely macro models; rather, they are meso-level.

Key drivers for the development of models of the third generation were the oil price shock and high inflation on the ‘economic’ side and the need for upgrading the previous two generations of models. In other words, there was a need for a model that can explain the essence of the innovation process itself. Therefore, the third-generation models were more for the economy than for companies. The fourth-generation models are ‘case study’ models. The ‘case’ here is the example of Japanese companies’ success in developing innovation strategies and penetrating the high-tech production market. These models are already micro level since their key building blocks are integration of suppliers into the product development process and integration of activities and functions between companies. Fifth-generation models are also the micro level: they emphasize the network features of the innovation process and the parallelism in the dynamics of innovation processes.

Marinova and Phillimore ( 2003 ) treat the evolution of the innovation models in generally the same way. The third-generation models (interactive models) are ‘transition models’ which ‘correct the mistakes’ of the models of the first two generations but they still lack some fundamentalism. System models (fourth generation models) are in general macro-level fundamental models. The innovation models of the last two generations gradually drift from macro to micro level. Evolutionary models are a kind of meso-level models: they analyse the behaviour of many firms in the context of the environment which is more or less common to all firms. Innovation milieu models are already purely microeconomic models focused on separate firm locations within regions.

Marinova and Phillimore ( 2003 ) offer a closer look at the history of innovation models. They show that the evolution of the model generations is non-linear. Only the first three generations of innovation models are sequential to each other. The last three generations of models are not directly sequential. In other words, the evolutionary generation can also be seen as the ‘additional fourth generation’ in innovation models development: the ‘second fourth generation’, ‘fourth generation B’, etc. The explanation is as follows. Evolutionary models as well as system models analyse the actors in the innovation process and their interactions. However, system models look more closely at the system of these relationships and at the driving factors of the system’s development. On the other hand, evolutionary models concentrate on the interactions between actors of innovation process and the diversity of these actors. The sixth generation of innovation models from a conceptual point of view can also be seen as an extension of the third-generation innovation models rather than the further development of evolutionary models. Innovation milieu models cannot be treated directly as the development of third-generation innovation models since they shift from the meso to the micro level. They also focus on the importance of firms’ geographical location rather than on the processes of firms’ interactions within or across some geographical borders.

In contrast, in Rothwell’s work, all generations of innovation management models are really in sequence. However, the changes of scope (from meso to micro level) between the third- and fourth-generation models are clear. These models follow one another.

The analysis reveals several common features in the understanding of innovation processes. Despite these commonalities, the implications for management tools and instruments vary significantly. The innovation management-centred approaches require more operational management tools to initiate, guide, steer and monitor innovation processes which eventually result in economic impact. The conceptual approach, on the other hand, is more focused on the innovation (management) framework conditions; this latter approach hence requires instruments and tools for designing framework conditions conducive to innovation at different levels (Meissner 2014 ; Khripunova et al. 2014 ; Gokhberg and Meissner 2013 ; Carayannis et al. 2011 ; Zhang et al. 2015 ).

As innovation process models have evolved over time, we have gained a greater understanding of how innovation actually occurs. Furthermore, we have learned that innovation itself is not a result but rather a process and flow of activities that aim to solve a known or unknown problem. This problem, as well as its societal implications at different levels, may or may not be widely understood. Innovation is essentially the combination of existing knowledge, the generation of new knowledge and the targeted use of existing and new knowledge to create a novel solution. Along with the rapid increase in existing knowledge and the competences to use that knowledge, new challenges arise for generating innovation.

Conclusions—revisiting innovation models towards the ‘active innovation’ paradigm

The most recent innovation models increasingly postulate external relationships of innovators in many different shapes including the acquisition and incorporation of knowledge and technology from outside the organization. Such knowledge and technologies can be either publicly accessible or privately owned by other companies, individuals or research institutions. Furthermore, external knowledge and technologies are available either in a codified or persona land published, undisclosed, form. R&D service providers and public and private research institutions and increasingly training institutions contribute much to build, develop and diffuse existing, publicly available ‘knowledge and technology pools.’ More studies are needed to examine the role of universities as employer and educator of highly skilled workers and researchers especially for R&D. These institutions also provide partners and/or service providers for external innovation-related activities (especially R&D activities). The company’s internal R&D activities—as part of the innovation process—are available in the company’s knowledge and existing technologies which are not only a prerequisite for implementing in-house innovation activities but also for the use of external sources for innovation.

The most recent generation of innovation models is not directly related to earlier ones. Examples of these models include the value chain evolution theory developed by Christensen and Raynor ( 2003 ), the strategic innovation process model proposed by Afuah ( 2002 ), the Moore ( 2005 ) ‘category-maturity life cycle model’ and the Hamel ( 2000 ) business strategy innovation model (2002). Moore’s and Hamel’s approaches show the potential to incorporate innovation process model thinking. These models cannot really be treated as descendants of sixth-generation models. They draw on some features from the system and evolutionary models. However, they do not apply system or evolutionary models at a micro level but rather develop third-generation models, with new aspects such as network infrastructure or a greater emphasis on outsourcing added. The models discussed in the article share the common feature that they all aim to explain the emergence of innovations from conceptual and process perspective but do not take account of the side resource of innovation. While the current open innovation paradigm remains dominant in innovation model thinking, we argue that even this innovation understanding and model (and thus innovation processes) needs to be extended by the human resource dimension and the meaning and impact of organizations’ innovation milieus. A company’s innovation milieu is strongly interrelated with human resources management and policies for attracting and retaining talent. Frequently, attracting talent to companies for innovation is less problematic than keeping talent on board and motivating people to perform outstandingly. This is challenging because firms lack staff who have capabilities that are directly related to not only actual innovation activities (e.g. often related to R&D) but also capabilities in management and legal affairs. Firms need these additional competences in light of the increasingly external nature of innovation. Furthermore, the economic pressure on companies leads to higher expectations by the corporate leadership from the innovation-related activities by all company units. The instruments used for monitoring and assessing innovation projects are improving considerably. Firms’ needs for innovation-related competences and corporate management’s higher expectations for innovation are very important determinants of current corporate activities, although both inherit the danger that innovation is understood a self-fulfilling prophecy. In other words, once companies invest in innovative projects, the corporate leadership expects returns on investment in ever shorter periods to meet externally imposed expectations. Accordingly, it is important to reconsider how innovation and human resource management are organized internally to prepare staff to respond to these challenges.

Equally important is the incorporation of public attitudes and perception of innovation which developed into a major driver for the acceptance of innovation by society.

Therefore, we argue that the current predominantly open innovation paradigm needs to be modified to incorporate a stronger emphasis on the human resources involved in innovation. There are signs that companies are already paying more attention to the human factor for innovation and the public perception. Consequently, we are convinced that companies will strive for an ‘active innovation’ model which builds on the open innovation paradigm. In this respect, the scientific community should develop approaches which combine the open innovation concept with the human factor and the public perception, or in other words, the ‘company innovation ecosystem’ and the product innovation ecosystem. We understand ‘product innovation ecosystem’ as a community of users of an innovation which are driven by their specific agendas which are also embedded in society. Hence, in order to accelerate the understanding the relationship between ‘company innovation ecosystems’ and ‘product innovation ecosystems’, more efforts in research are required.

Afuah, A. (2002). Innovation management: strategies, implementation, and profits (2nd ed.). New York: Oxford University Press.

Google Scholar  

Aiken, M., & Hage, J. (1971). The organic organization and innovation. Sociology, 5 (1), 63–82.

Article   Google Scholar  

Asheim, B. T., Smith, H. L., & Oughton, C. (2011). Regional innovation systems: theory, empirics and policy. Regional Studies, 45 (7), 875–891.

Baregheh, A., Rowley, J., & Sambrook, S. (2009). Towards a multidisciplinary definition of innovation. Management Decision, 47 (8), 1323–1339.

Bazalt, M., & Hanush, H. (2004). Recent trends in the research on national innovation systems. Journal of Evolutionary Economics, 14 (2), 197–210.

Beije, P. (1998). Technological change in the modern economy . Cheltenham: Edward Elgar.

Bessant, J., & Tidd, J. (2007). Innovation and entrepreneurship . Chichester: John Wiley.

Biondi, L., & Galli, R. (1992). Technological trajectories. Futures, 24 , 580–592.

Bramanti, A., & Ratti, R. (1997). The multi-faceted dimensions of local development. In R. Ratti, A. Bramanti, & R. Gordon (Eds.), The Dynamics of Innovative Regions: The GREMI Approach (pp. 3–44). Aldershot: Ashgate.

Cagnazzo, L., Botarelli, M., & Taticchi, P. (2008). Innovation management models: a literature review, a new framework, a case study. In Proceedings of the 3rd European Conference on Entrepreneurship and Innovation (pp. 55–69).

Camagni, R. (1991). “Local milieu”, uncertainty and innovation networks: towards a new dynamic theory of economic space. In R. Camagni (Ed.), Innovation Networks: Spacial Perspectives (pp. 12–143). London: Belhaven Press.

Campodall’Orto, S., & Ghiglione, B. (1997). The technology transfer process within the new innovation models. In Managing Technological Knowledge Transfer . Vol. 4.

Carayannis, E. G., & Campbell, D. F. (2011). Open innovation diplomacy and a 21st century fractal research, education and innovation (FREIE) ecosystem: building on the quadruple and quintuple helix innovation concepts and the “mode 3” knowledge production system. Journal of the Knowledge Economy, 2 (3), 327–372.

Carayannis, E. G., Meissner, D., & Edelkina, A. (2015). Targeted innovation policy and practice intelligence (TIP2E): concepts and implications for theory, policy and practice. The Journal of Technology Transfer . doi: 10.1007/s10961-015-9433-8 .

Carayannis, E. G., Provance, M., & Givens, N. (2011). Knowledge arbitrage, serendipity, and acquisition formality: their effects on sustainable entrepreneurial activity in regions. Engineering Management, IEEE Transactions on, 58 (3), 564–577.

Carayannis, E. G., & Turner, E. (2006). Innovation diffusion and technology acceptance: the case of PKI technology. Technovation, 26 (7), 847–855.

Carlsson, B., Keane, P., & Martin, J. B. (1976). R and D organizations as learning systems. Sloan Management Review, 17 (3), 1–15.

Carlsson, B., Jacobsson, S., Holmen, M., & Rickne, A. (2002). Innovation systems: analytical and methodological notes. Research Policy, 31 (2), 233–245.

Carter, C., & Williams, B. (1957). Industry and technical progress . London: Oxford University Press.

Chesbrough, H. W. (2003a). Open innovation: the new imperative for creating and profiting from technology . Boston: Harvard Business School Press.

Chesbrough, H. W. (2003b). The era of open innovation. MIT Sloan Management Review, 44 (3), 35–41.

Chesbrough, H. W. (2006). Open innovation: researching a new paradigm . New York: Oxford University Press.

Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: using good theory to solve the dilemmas of growth . Boston: Harvard Business School Press.

Contractor, F. J., & Lorange, P. (1988). Cooperative strategies in international business . Lexington: Lexington Books.

Cook, L. G., & Morrison, W. A. (1961). The origins of innovation. In Report No. 61-GP-214 . New York: General Electric Company, Research Information Section.

Cooke, P. (1998). Introduction. In H.-J. Braczyk, P. Cooke, & M. Heidenreich (Eds.), Regional Innovation Systems: The Role of Governance in a Globalised World (pp. 2–25). London: UCL Press.

Coombs, R., Saviotti, P., & Walsh, V. (1987). Economics and technological change . London: MacMillan.

Book   Google Scholar  

Cooper, R. G. (1980). Project NewProd: factors in new product success. European Journal Marketing, 14 , (5/6) pp. 277-292.

Docter, J., & Stokman, C. (1987). Innovation strategies of small industrial companies. In R. Rothwell & J. Bessant (Eds.), Innovation: Adaptation and Growth . Amsterdam: Elsevier.

Dodgson, M. (1993). Technological collaboration in industry: strategy, policy and internationalization in innovation . London: Routledge.

Dosi, G. (1982). Technological paradigms and technological trajectories: a suggested interpretation of the determinants and directions of technical change. Research Policy, 11 , 147–162.

Dosi, G. (1988). Sources, procedures, and microeconomic effects of innovation. Journal of Economic Literature, 26 , 1120–1171.

Dosi, G., & Egibi, M. (1991). Substantive and procedural uncertainty: an exploration of human behavior in changing environments. Journal of Evolutionary Economics, 1 , 145–168.

Dosi, G., & Orsenigo, L. (1994). Macrodynamics and microfoundations: an evolutionary perspective. In O. Granstrand (Ed.), Economics of Technology (pp. 91–123). Amsterdam: North-Holland.

Dowrick, S. (Ed.). (1995). Economic approaches to innovation . Aldershot: Edward Elgar.

Eveleens, C. (2010). Innovation management; a literature review of innovation process models and their implications. Science, 800 (2010), 900. 

Feldman, M. (1994). The geography of innovation . Dordrecht: Kluwer Academic Publisher.

Florida, R. (1995). Toward the learning region. Futures, 27 , 527–536.

Freeman, C. (1991). Networks of innovators: a synthesis of research issues. Research Policy, 20 , 499–514.

Freeman, C., & Perez, C. (1988). Structural crises of adjustment: business cycles and investment behavior. In G. Dosi et al. (Eds.), Technical Change and Economic Theory (pp. 38–66). London: Pinter.

Gackstatter, S., Kotsemir, M., & Meissner, D. (2014). Building an innovation-driven economy—the case of BRIC and GCC countries. Foresight, 16 (4), 293–308.

Gallivan, M. (2001). Organizational adoption and assimilation of complex technological innovations: development and application of a new framework. ACMSIGMIS Database, 32 (3), 51–85.

Gann, D. (1991). Technological change and the internationalization of construction in Europe. In C. Freeman, M. Sharp, & W. Walker (Eds.), Technology and the Future of Europe (pp. 231–244). London: Pinter.

Gann, D. (2000). Building innovation: complex constructs in a changing world . London: Thomas Telford.

Gault, F. (2009). Innovatsionnaya strategiya OESR: dostizhenie novykh tsennostey [OECD Innovation Strategy: Delivering Value]. Foresight-Russia, 3 (1), 16–28 (in Russian).

Godin, B. (2006). The linear model of innovation—the historical construction of an analytical framework. Science Technology & Human Values, 31 (6), 639–667.

Godin, B. (2009). National innovation system: the system approach in historical perspective. Science Technology and Human Values, 34 (4), 476–501.

Godin, B. (2010). Kontseptual'nye osnovy nauchnoy, tekhnologicheskoy i innovatsionnoy politiki [Conceptual Frameworks of Science, Technology and Innovation Policy]. Foresight-Russia, 4 (2), 34–43 (in Russian).

Gokhberg, L., & Meissner, D. (2013). Innovation: superpowered invention. Nature, 501 , 313–314.

Gokhberg, L., Kuznetsova, T., & Roud, V. (2010). Analiz innovatsionnykh rezhimov v rossiyskoy ekonomike: metodologicheskie podkhody i pervye rezul'taty [Analysis of Innovation Modes in the Russian Economy: Methodological Approaches and First Results]. Foresight-Russia, 4 (3), 18–30 (in Russian).

Hagedoorn, J. (1990). Organizational needs of inter-firm cooperation and technology transfer. Technovation, 10 (1), 17–30.

Hamel, G. (2000). Leading the revolution . Boston: Harvard Business School Press.

Hayes, R., & Abernathy, W. J. (1980). Managing OUR WAY TO ECONOMIC DECLINE. In Harvard Business Review (July–August) .

Hayvaert, C. H. (1973). Innovation Research and Product Policy: Clinical Research in 12 Belgian Industrial Enterprises . Belgium: Catholic University of Louvain.

Hodgson, G. (1993). Economics and evolution: putting life back into economics . Oxford: Polity Press.

Howard, W. G., & Guile, B. R. (1992). Profiting from innovation . New York: The Free Press.

Iammarino, S. (2005). An evolutionary integrated view of regional systems of innovation: concepts, measures and historical perspectives. European Planning Studies, 13 (4), 497–519.

Jacobs, D., & Snijders, H. (2008). Innovation routine: how managers can support repeated innovation. In Stichting Management Studies . Assen: Van Gorcum.

Jarillo, J. (1988). On strategic networks. Strategic Management Journal, 19 , 31–41.

Kamal, M. M. (2006). IT innovation adoption in the government sector: identifying the critical success factors. Journal of Enterprise Information Management, 19 (2), 192–222.

Keeble, D., & Wilkinson, F. (2000). SMEs, regional clustering and collective learning: an overview. In D. Keeble & F. Wilkinson (Eds.), High-Technology Clusters, Networking and Collective Learning in Europe (pp. 1–20). Aldershot: Ashgate.

Khripunova, A., Vishnevskiy, K., Karasev, O., & Meissner, D. (2014). Corporate foresight for corporate functions: impacts from purchasing functions. Strategic Change, 23 , 147–160. doi: 10.1002/jsc.1967 .

Kirat, T., & Lung, Y. (1999). Innovation and proximity: territories as loci of collective learning processes. European Urban and Regional Studies, 6 , 27–38.

Kline, S. J., & Rosenberg, N. (1986). An overview of innovation. In R. Landau & N. Rosenberg (Eds.), The Positive Sum Strategy (pp. 275–305). Washington, D.C.: National Academy Press.

Knight, K. (1967). A descriptive model of the intra-firm innovation process. The Journal of Business, 40 (4), 478–496.

Kotsemir, M. N., & Meissner, D. (2013). Conceptualizing the innovation process—trends and outlook. Working papers by NRU Higher School of Economics. Series WP BRP "Science, Technology and Innovation" . No. 10/STI/2013.

Langrish, J., Gibbons, M., Evans, W. G., & Jevons, F. R. (1972). Wealth from knowledge . London: Macmillan.

Longhi, C., & Keeble, D. (2000). High-technology clusters and evolutionary trends in the 1990s. In D. Keeble & F. Wilkinson (Eds.), High-Technology Clusters, Networking and Collective Learning in Europe (pp. 21–56). Aldershot: Ashgate.

Lundvall, B.-A. (1992). National Systems of Innovation: towards a theory of innovation and interactive learning . London: Pinter.

Macleod, G. (1996). The cult of enterprise in a networked, learning region? Governing business and skills in lowland Scotland. Regional Studies, 30 , 749–755.

Maidique, M. (1980). Entrepreneurs, champions, and technological innovation. Sloan Management Review, 21 (2), 59–76.

Mansfield, E. (1995). Contribution of R&D to economic growth in the United States. Innovation, Technology and the Economy, I , 255–273.

Marceau, J. (1992). Reworking the world: organizations, technologies and cultures in comparative perspective . Berlin: De Gruyter.

Marinova, D., & Phillimore, J. (2003). Innovation models. In L. V. Shavinina (Ed.), The International Handbook on Innovation (pp. 44–53). Oxford: Elsevier.

Chapter   Google Scholar  

Marquis, D. G. (1988). The anatomy of successful innovations. In Readings in the Management of Innovation . New York: Ballinger Publishing Company.

Meissner, D. (2014). Approaches for developing national STI strategies. STI Policy Review, 5 (1), 34–56.

Meissner, D. (2015). Public-private partnership models for science, technology, and innovation cooperation. Journal of the Knowledge Economy . doi: 10.1007/s13132-015-0310-3 .

Merrifield, B. D. (1986). Forces of change affecting high technology industries. In A speech by U.S. Assistant Secretary of Commerce .

Metcalfe, S. (1995). Technology systems and technology policy in an evolutionary framework. Cambridge Journal of Economics, 19 , 25–46.

Mitrova, T., Kulagin, V., Grushevenko, D., & Grushevenko, E. (2015). Technology innovation as a factor of demand for energy sources in automotive industry. Foresight and STI Governance, 9 (4), 18–31. doi: 10.17323/1995-459x.2015.4.18.31 .

Moore, G. A. (2005). Dealing with Darwin: how great companies innovate at every phase of their evolution . New York: Penguin Group.

Mowery, D., & Rosenberg, N. (1979). Influence of market demand upon innovation—critical-review of some recent empirical studies. Research Policy, 8 (2), 102–153.

Myers, S., & Marquis, D. G. (1969a). Successful industrial innovations: a study of factors underlying innovation in selected firms. In NSF 69–17 . Washington: National Science Foundation.

Myers, S., & Marquis, D. G. (1969b). Successful industrial innovations: a study of factors underlying innovation in selected firms. In NSF 69–17 . Washington: National Science Foundation.

Nelson, R. R. (1993). National innovation systems: a comparative analysis . New York: Oxford University Press.

Nelson, R. R. (2000). National innovation systems. In Z. Acs (Ed.), Regional Innovation, Knowledge and Global Change (pp. 11–26). London: Pinter.

Niosi, J. (1999). Fourth-generation R&D: from linear models to flexible innovation. Journal of Business Research, 45 (2), 111–117.

OECD. (1996). The OECD jobs strategy: technology, production and job creation (Vol. 2). Paris: OECD.

OECD. (1999). Managing national innovation systems . Paris: OECD.

OECD, Eurostat. (1997). Oslo manual—guidelines for collecting and interpreting innovation data. In Paris 1997 (2nd ed.).

OECD, Eurostat. (2005). Oslo manual—guidelines for collecting and interpreting innovation data. In Paris 2005, Sp 46 (3rd ed.).

Pavitt, K., Robson, M., & Townsend, J. (1989). Accumulation, diversification and organization of technological activities in U.K. companies, 1945–83. In M. Dodgson (Ed.), Technology Strategy and the Firm: Management and Public Policy (pp. 38–67). Harlow: Longman.

Perani, G., & Sirilli, S. (2008). Benchmarking innovatsionnoy deyatel'nosti evropeyskikh stran [Benchmarking Innovation in Europe ]. Foresight-Russia, 2 (1), 4–15 (in Russian).

Perez, C. (1983). Structural change and the assimilation of new technologies in the economic system. Futures, 15 , 357–375.

Peters, T. J., & Waterman, R. W. (1982). In search of excellence . New York: Harper and Row.

Pierce, J., & Delbecq, A. (1977). Organizational structure, individual attitudes and innovation. Academy of Management Review, 2 (1), 26–37.

Proskuryakova, LN, Meissner D, Rudnik, PB. (2015) The use of technology platforms as a policy tool to address research challenges and technology transfer. The Journal of Technology Transfer . Vol 41, no 5, October 2016 (in print).

Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: Free Press.

Rosenberg, N. (1976). Perspectives on technology . Cambridge: Cambridge University Press.

Rosenberg, N. (1982). Inside the black box: technology and economics . Cambridge: Cambridge University Press.

Rothwell, R. (1976). Innovation in textile machinery: some significant factors in success and failure. In Science Policy Research Unit, Occasional Paper Series, No 2, June .

Rothwell, R. (1991). External networking and innovation in small and medium-sized manufacturing firms in europe. Technovation, 11 (2), 93–112.

Rothwell, R. (1992). Industrial innovation and environmental regulation: some lessons from the past. Technovation, 12 (7), 447–458.

Rothwell, R. (1994). Towards the fifth-generation innovation process. International Marketing Review, 11 (1), 7–31.

Rothwell, R., & Zegveld, W. (1985). Reindustrialization and technology . Harlow: Longman.

Rothwell, R., Freeman, C., Horsley, A., Jervis, V. T. P., Robertson, A. B., & Townsend, J. (1974). SAPPHO updated: project SAPPHO phase II. Research Policy, 3 (3), 258–291.

Rubenstein, A. H. (1957). Looking around. Harvard Business Review, 35 (3), 133–145.

Sahal, D. (1981). Patterns of technological innovation . New York: Addison-Wesley.

Sako, M. (1992). Price, quality and trust: how Japanese and British companies manage buyer supplier relations . Cambridge: Cambridge University Press.

Saviotti, P. P. (1996). Technological evolution, variety and the economy . Cheltenham: Edward Elgar.

Schock, G. (1974). Innovation processes in Dutch industry . Apeldoorn: Policy Studies and Information Group.

Sharif, N. (2006). Emergence and development of the national innovation systems concept. Research Policy, 35 (5), 745–766.

Solow, R. M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39 , 312–320.

Szakasitz, GD. (1974). The adoption of the SAPPHO method in the Hungarian electronics industry. Research Policy , 3.

Tisdell, C. (1995). Evolutionary economics and research and development. In S. Dowrick (Ed.), Economic Approaches to Innovation (pp. 120–144). Aldershot: Edward Elgar.

Usher, A. P. (1954). A history of mechanical inventions. Revised edition . New York: McGraw Hill.

Usher, A. P. (1955). Technical change and capital formation, in national bureau of economic research, capital formation and economic growth (pp. 523–550). Princeton: Princeton University Press.

Utterback, J. M. (1975). The process of innovation in five industries in Europe and Japan . Cambridge: Centre for Policy Alternatives, MIT Press.

Verloop, J. (2004). Insight in innovation: managing innovation by understanding the laws of innovation . Exeter: Elsevier Science.

Vishnevskiy, K., Karasev, O., Meissner, D., & Part, B. (2015). Integrated roadmaps and corporate foresight as tools of innovation management: the case of Russian companies. Technological Forecasting and Social Change, 90 (Part B), 433–443.

Zhang, Y, Robinson, DK, Porter, AL, Zhu, D, Zhang, G, Lu, J. (2015). Technology roadmapping for competitive technical intelligence. Technological Forecasting and Social Change available online, doi: 10.1016/j.techfore.2015.11.029 (in print).

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Meissner, D., Kotsemir, M. Conceptualizing the innovation process towards the ‘active innovation paradigm’—trends and outlook. J Innov Entrep 5 , 14 (2016). https://doi.org/10.1186/s13731-016-0042-z

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107 Innovation Essay Topic Ideas & Examples

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Innovation is a key driver of progress and growth in any field, whether it be in science, technology, business, or the arts. As such, it is a topic that is frequently explored in essays and research papers. If you are struggling to come up with a unique and interesting topic for your innovation essay, look no further. Here are 107 innovation essay topic ideas and examples to inspire your next writing project.

The impact of artificial intelligence on innovation in the workplace

How blockchain technology is revolutionizing the financial industry

The role of innovation in addressing climate change

The future of transportation: innovations in electric vehicles

The ethical implications of gene editing technologies

How virtual reality is transforming the way we experience entertainment

The rise of telemedicine: innovations in healthcare delivery

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The impact of 3D printing on manufacturing processes

How the sharing economy is driving innovation in the service industry

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Innovations in cybersecurity: protecting data in the digital age

The role of innovation in creating sustainable cities

The impact of social media on innovation and creativity

How biotechnology is revolutionizing healthcare

The future of work: innovations in remote collaboration

The role of innovation in addressing global poverty

The impact of autonomous vehicles on transportation systems

Innovations in education technology: transforming the classroom experience

The ethical implications of artificial intelligence and machine learning

The role of innovation in disaster response and recovery

The impact of big data on innovation in business

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The future of space exploration: innovations in propulsion technology

The role of innovation in addressing mental health challenges

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The ethics of gene editing and designer babies

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Innovations in sustainable agriculture

The role of innovation in addressing income inequality

The potential of quantum computing to revolutionize technology

Innovations in personalized medicine

The impact of biometrics and facial recognition technology on privacy

The future of sustainable fashion: innovations in eco-friendly materials

The role of innovation in promoting social justice

How drones are revolutionizing industries from agriculture to delivery services

The ethics of autonomous weapons systems

Innovations in clean water technology

The impact of 5G technology on communication networks

The role of innovation in addressing mental health stigma

The potential of regenerative medicine to revolutionize healthcare

Innovations in prosthetics and assistive technologies

The impact of virtual reality on empathy and social change

The future of smart cities: innovations in urban planning

The role of innovation in addressing gender equality

How bioengineering is revolutionizing the production of food and consumer goods

The ethics of artificial intelligence and decision-making

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The impact of social media on political innovation

The role of innovation in promoting diversity and inclusion in the workplace

The potential of nanotechnology to revolutionize materials science

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The impact of biotechnology on personalized nutrition

The future of wearable technology: innovations in health monitoring

The role of innovation in addressing plastic pollution

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The impact of artificial intelligence on creative industries

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The future of smart homes: innovations in home automation

The role of innovation in promoting environmental sustainability

How bioengineering is revolutionizing the production of consumer goods

The ethics of artificial intelligence and privacy

Innovations in disaster-resistant building materials

The impact of social media on political activism

These 107 innovation essay topic ideas and examples cover a wide range of disciplines and industries, providing you with plenty of inspiration for your next writing project. Whether you are interested in exploring the ethical implications of emerging technologies, the role of innovation in addressing social challenges, or the potential of cutting-edge scientific advancements, there is sure to be a topic on this list that piques your interest. Happy writing!

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Managing Innovation Essay

Innovation can be referred to as the “incorporation of new ideas or new methods used in business with the intention of winning customer loyalty” (Klein). Innovation is an important process in any company since it helps in evaluating the performance the firm (Ettlie 74). For any company to survive in a competitive market, it must have effective strategic management policies. This can be achieved by focusing on innovation within the firm.

Managing innovation enables managers to gain the knowledge that will enable them to manage their businesses in a given business environment. The knowledge gained through effective management of innovation facilitates the development of products that meet the expectations of the clients. The level of competition in the modern market is very high (Adam 73). Thus firms should be in a position to identify and take advantage of the weaknesses of their competitors.

One of the most important factors to consider when analyzing the level of competition in the market is the level of innovation. All firms need to incorporate new ideas in their operations in order to survive in the competitive market. This is because the level of technology changes everyday and new products are brought into the market on a daily basis. Companies that intend to have the best reputation in the market must upgrade their level of innovation (Adam 82).

Innovation is a process of “thought change since its main intention is to come up with new ideas” (Adam 87) that can be implemented in the market. There are several types of innovation. However, they all focus on the development of the organization through new ideas and strategies (Adam 91). Innovation can be disruptive or sustaining (Adam 97). When analyzing the types of innovation, much emphasis is usually put on disruptive innovation since it is the most important as far as business is concerned.

Innovation is a long process that occurs in stages or phases within the organization. For example, the development of a new product begins with the thought process. This is followed by the manufacture of the product and ends with the marketing of the product. The process of innovation thus begins with the thought process. This involves developing a vision of what is to be achieved.

Innovation is therefore considered to be “the incremental or radical changes that take place in an organization” (Bessant 67). The changes relate to the manner in which decisions are made, the production of goods and services and the distribution process. The advancement in technology focuses on improving all aspects of a business in the modern economy through innovation (Klein 101). According to Pixar seminars, managing innovation is a very important process since it facilitates growth and resilience.

The second stage of managing innovation is more advanced and involves the implementation of the new ideas (Harvey 65). Thus at this stage the new ideas are “transformed into actions that are important for the survival of a firm in the competitive market” (Ranchhod 87). At the implementation stage, the management must provide the necessary resources. This is because lack of adequate resources can undermine the firm’s ability to realize its innovation objectives (Ettlie 89).

Apart from the financial resources, the firm must invest in appropriate technology that will help in the implementation of the innovation plan (Ettlie 90). This can be achieved through an assessment program that aims at identifying the technical weaknesses in the organization. Outdated technologies should therefore be replaced with new ones. Besides, there should be on-the-job training programs that aim at improving the competence of the employees.

Entrepreneurs who focus on innovation in their businesses are able to increase their rate of production in their respective industries. The increase in production is attributed to the high level of efficiency, cost saving and creativity that is associated with innovation within an organization (Bessant 103).

Managing innovation might only be possible if the managers in a given firm have the skills and knowledge that enables them to inspire their employees to be initiative. This means that the process of managing innovation is not only the responsibility of the management team. The process must bring together all members of the organization and the potential clients (Harvey 78). The perspectives of all the concerned parties should be considered.

Due to the large number of employees within an organization, the suggestions concerning the expected changes will definitely vary or even contradict each other. Thus the organization must develop an evaluation mechanism that will be used to vet the ideas presented by all individuals who are involved in the innovation process. Only the best ideas should be chosen and implemented by the organization (Bessant 114). It is not possible to implement all ideas due to lack of sufficient resources.

A company is considered to be the pioneer of innovation if it succeeds in overhauling its production and distribution processes ahead of other firms in the industry. This will enable the firm to improve its competitiveness in the industry (Ranchhod 99). Consequently, the firm’s revenue will increase as it increases its productivity and market share.

However, with time other firms in the industry will begin to restructure their operations in order to remain competitive. As firms reposition themselves in the industry, the competition in the market becomes more intense. Thus, firms will begin to focus on product differentiation with the aim of positioning themselves as the best in the market.

The most important tool in managing innovation is research and development. The decisions made at each and every stage of managing innovation must be supported by adequate and relevant research. Engaging in research at every stage of managing innovation will help in making the right decisions that will help the organization to achieve its objectives (Ettlie 100).

Reviewing research findings on particular issues concerning innovation can help in solving a dilemma. Decisions that are based on facts are likely to be more effective and will help the organization to achieve its objectives.

Works Cited

Adam, Jolly. Innovation: harnessing creativity for business growth . New York: Kogan Page, 2003. Print.

Bessant, John. Innovation and Entrepreneurship. New York: John Wiley and Sons, 2007. Print.

Ettlie, John. Managing Innovation: new technology, new products, and new services in a global economy. New York: John Wiley and Sons, 2007.Print.

Harvey, Dershin. “A framework for managing innovation.” International Journal of Business Innovation and Research 4 (2010): 598-613.

Klein, Stefan. Managing dynamic networks: organizational perspectives of technology enabled inter-firm. Frankfourt: Birkhauser Publication, 2006. Print.

Ranchhod, Ashok. Marketing Strategies: A Contemporary Approach. New York: Prince Hall, 2007.Print.

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Innovations under conditions of uncertainty- Normative model of innovation

Introduction.

Innovation is one of the most important aspects in most of the business organizations as they strive to attain their goals and objectives. It brings about changes in the traditional way of management to new and improved methods. All these methods will try to answer questions that are usually presented to managers regarding the value of the products and services offered these organizations (Davis& Scott, 2007). The need for to coming up with characteristics that can stimulate innovations is paramount to organization’s success. Furthermore there is need to provide a conducive environment where such innovators can thrive in. There is also the need for managers to come up with ways or effective methods that they use to differentiate priorities in terms of resource allocation (Gjerding, 2003). This paper will highlight and draw comparisons on different models and theories of innovation. The paper will also discuss the effects of different approaches to innovation process. Furthermore, the paper will also define concepts pertinent to innovation and use the concepts to illuminate on the effects of unintended consequences on the innovation process.

As an important point of consideration, Innovation should not be taken as a mechanical procedure that can be achieved in unplanned way. It is more of an accurate systematic approach achieved through a highly crafted adaptive system. It involves resilience, hard work and dedication. Naturally, innovation in any business is achieved as a result of interplay of three successful forces. These forces are selection, variation, and replication. The managers should be aware that when Organizing for the process of innovation. A great deal of excellent awareness regarding these three forces and their individual working is required (Galunic and Eisenhardt, 2001).

Majority of the business organizations identify their need for innovation that advises them differently. Some businesses may agree on theories that make the organization to take great risks while on the other hand accept failure. Others may follow theories that create an interesting work environment. There are also theories that encourage business networking between different organizations. This allows flexibility. The reality behind coming up with these theories cum ideas is usually the need to shift from the outdated ways of conducting business. Without proper innovations, business organizations may end up making huge losses and also loss of employees to other organizations that stand the wave of innovation (Watson & Harris, 1999).

Organizations may have unique strengths and weaknesses, with regard to planning for innovation. This calls for coming up with effective ways of resource mobilization in order to support the process of innovation. After these systems are put into place, there is need to appreciating those behind the ideas and also nurturing the idea. This will ensure the survival of the idea and also the organization is assured of continued support from those behind the idea. To organizations that are dispersed in many regions or networked organizations, their ideas spread faster to consumers than their counterparts (Garvin, 1993). Innovation is defined as the use of new ideas to the products and processes, or any o other activities that may increase value to an organization. This value is usually aimed at benefiting the organization as well as its consumers. However, innovation involves two aspects; product innovation and process innovation. Product innovation generally refers to the introduction of new products or a substantial change in the already existing products. On the other hand process innovation usually refers to coming up with a new ways in processing goods and services

Product innovations involve tangible processed goods and intangible services. It can also be a both products. Mobile phones and computers provide a good example of more recent tangible goods that have impacted heavily on the lives of people both at the working places and also at home. The combination of both the tangible and Intangible products have cannot be undermined. For example intangible products are used alongside the tangible products like computer softwares and the computers themselves. The softwares are needed for the proper working of the computer. They also help in transmission of information from one person to another (Garvin, 1993).

Synchronizing the three roles of Innovation

In all successive organizations, innovation is not taken as a solitary activity but rather handled as a detailed process. This is usually assigned to particular employees who have shown commitment to innovation. These organizations view it as the end product brought about by an effective network composed of a team of individuals who clearly understand their responsibilities. There is usually support from one another during the entire process. The organization must also chip in by supporting their ideas and also recognizing their efforts. The idea should also be nurtured from its infancy. The key individual roles in the organization are the innovator, the agent of change and the gatekeeper. With the interplay of these three roles, the success of the idea is guaranteed as a result of team work (Garvin, 1993).

Role the innovators

These are the original owners of the idea that the organization is willing to undertake .they dream big and usually convert their dreams into actions. From them the ideas are said to natural or rather unexplored. These ideas may be big or small. When these ideas are brought into the right they receive a lot of scrutiny of which most is criticism. if these ideas come to happen when an organization is facing crisis especially from the competitors, they may be accepted to bring the crisis to an end. In this regard the organization is forced to take risk in order to save itself from the crisis. It takes wise decision to give into such ideas, however if the idea saves the organization then the innovator carries the day. All these ideas brought up are for the success of the organization thus they are usually granted audience before they are thrown out. Most of these ideas however due to criticism are not granted audience and they don’t survive to see the light of the day due to negative criticism. Other innovators are not bold enough to present such ideas to the light as a result of poor or unconducive working environments in their organizations.

As a point of consideration, it should be made clear that innovators cannot come up with new ideas whenever the organization is faced with crisis. Majority of the innovations come about by mere accident rather than from point of consciousness or from deliberate responsibility (Garvin, 1993). However this is not the case in all innovations as some may arise when the organization is in dire need of them. Innovations also require good management systems from a good understanding of the key roles and functions of every part in the system. The organizations need to provide an environment where new ideas can be born and nurtured. In this environment they have a comfortable way of transferring their ideas to the gate keepers. From the networks created by the gatekeepers the innovators are made key players in the game. Innovators need to be independent and should also avoid office politics as this can influence negatively on their ideas (Butler, 1988).

The Gate Keepers

These are the transformers of the real idea into action. The gate keepers are usually the top managers or the employees who are usually networked both inside and outside the organization. These are the people who provide infrastructure and resources for the new idea for it to proper. This is because of the variations that are usually involved in the process of nurturing the idea. In the process of generating and nurturing the ideas, a lot of challenges are usually encountered and it is the role of the gate keepers to provide solutions to the challenges. They need to listen to all ideas presented by the innovators and chose the best of the ideas that can propel the organization to the desired direction. The innovators need to be informed by the gate keepers that it is only the best ideas that may be put into consideration (Butler, 1988). Gate keeping of the ideas is important in all organizations as it usually assures the innovator that their ideas are going to be nurtured and will help the organization achieve its goals and objectives. Furthermore all ideas must usually pas through this process and also it is under this process that damaging variations are eliminated.

Change Agents

In all organizations there is always a wide range of people from different cultures, religions and race. All these people have different personalities and relate differently with others. An innovator may come up with a very good idea that can change the organizations but due to strained relationships among colleagues, this idea may fail to come to be. The change agents are the people who remove such barriers in the organization and actively promote new ideas. Without the change agents, good ideas from innovators may not be considered. Through the role of change agents, innovations usually spread more rapidly and establish a competitive position in the business world. This involves changing the employees’ attitudes and perceptions in order to support the new idea. Through this entire process of replication, tremendous results are witnessed on the side of the organization (Mclean, 2005). Change agents help spur innovation in an organization. However, they also open up ways for the development of many products whose effect on the society many not be entirely quantified. For instance, the development of products that might have a negative effect on its users, whether unforeseen or otherwise may result from the efforts of change agents.

Obligatory Points of Passage

Certain processes have to be followed in the innovative process. Like in the obligatory points of passage, these processes converge at the outcome of the innovative processes. However, other outcomes that were unintended might prevail. For instance, the development of certain products using a specified process might lead to the production of toxic wastes that harm the environment. Although this was highly unintended, it is a consequence of the process of innovation. The unintended consequences need not be of a negative nature. Positive unintended consequences may also arise from the process of innovation. A good example is the processing of pork. The byproducts of the processing procedure do not all go to waste. Some of them are further processed into other products that may not have been initially intended when the process was developed.

Nurturing Innovations

Prosperous innovations often involve variation, replication and selection. In this regard, these forces can only operate in distinct organizational settings. There has been no definite answer that can be used to put into check the interplay these forces. However a little thing can be learnt from some emerging trends in the current economy. The organization only needs to know the kind of trend that fit in its shoes. The final step for the organization is to create an environment that supports the trend (Yukl, 2006).

Product and process development

In many organizations especially those that are involved in industrial processes, innovations of the product assortment coupled with innovations of the new processes that generate the products is very important.in many of the available information, the key areas of focus are usually on the product itself and the procedures involved leaving contact between the product and the process (Mclean, 2005). The product-process theory offers a valuable model by helping in the understanding the process of industrial innovation in this model the ideal relationships covering the life cycle of the product in all stages of development.

Through the virtue of identifying and splitting the process and product innovations, different stages of innovation can be used. These stages are the segmental, the systemic and uncoordinated. The current stage of product life cycle mainly determines the process innovation. The life cycle of the any given product together with its manufacturing process can be referred to the product process theory. This can result in the growth of the whole process of manufacturing the products. The theory has been shown to help a wide range of manufacturing companies (Hayes &Wheelwright, 1979). In the initial stage of innovation process is usually the uncoordinated stage. It is normally characterized by changes in the design of the product and productivity of the processes that will be involved.

At this level, performance of the product is entirely dependent on the design of the product. As a result of the slow and mostly unorganized processes in terms of technology and other organization hitches, the general improvements are low. Generally at this stage there are a numerous constraints hindering the progress of the product development thus failing to perform well. This may also result in increased costs of production as result of failure to have standardized processes (Ettlie, 1995). After the product has been fully designed, it enters the segmental stage. This is after an agreed designed of the product has been accepted. In this stage there is more coordination of the processes compared to the earlier stage. More resources will also be employed in this stage. The organization will start to source for more equipment’s to handle the new design of the product. As a result of proper condition use of more specialized equipment, the production volumes are expected to increase. The production costs are expected to reduce due to reduction in the modification of the product. Eventually the sales volume of the product will increase (Hayes &Wheelwright, 1979).

The last stage is usually the systemic stage. This involves high technological solutions which are complex and sophisticated. The organization has made all the possible changes in the entire process resulting in a more refined final product. At this point the organization aims at cutting or rather minimizing all costs that are involved in the process. It is at this stage that a tight linkage between the process and the final product is witnessed. The product and the process are interdependent at this stage. After the final touches on the standardization, further processes of innovation of both the product and process need to be stopped or decreased (Hayes &Wheelwright, 1979).

As the three stages, competitive strategies need to be adopted. These will be maximization of performance, sales and minimization of sales. This model generally provides possible explanations regarding the industrial process. As a matter of consideration, the basic ideas of the this approach into a more dynamic system taking into consideration into the technology of computer aided design in manufacturing process can greatly improve the innovation process. This allows changes in different levels of innovation. This allows monitoring of all the processes particularly if there are hitches in the process, this allows direct monitoring. This also allows product variation of high quality at later stages (Freel, 2000). Other models have also been suggested like the two dimensional model by Hayes and wheel. This is a matrix involving product- process linking the life cycle of the process and stage of the product during its life cycle. This matrix allows the interaction of both the process and product during the lifecycle. In the rows of the matrix there is the process lifecycle while in the columns there is the product life. With kind of matrix it is possible to describe the organization’s options especially with regard to its industrial function. This greatly also helps in timing of taking innovative decisions. It also shows the organization’s processing capabilities (Schein, 1992).

The idea of Hayes and Wheelwright has further been improved by Porter to give the product line complexity and process structure complexity. It incorporates performance, strategy and the use of technology in manufacturing. It allows the business to enjoy manufacturing competitiveness. This model gives high quality processing structure in processing thus lowering the complexity to product line. In this strategy the manufacturing cost is reduced as a result of very high level of mechanization (Love and roper, 2004). In the combination of these models, there is evidence of interconnection between process, product and the strategy employed in most of the manufacturing companies. All these have been employed in industrial innovation. They offer information on proper timing, decision making and level of innovation with regard to the maturity of the product life cycle. This also allows the organizations to formulate sound manufacturing strategies that may help cut cost on production or investing in a new product. It also helps the organizations to develop competitive strategies that will enable their products compete fairly in the market.

Innovations Under Uncertainty

In most of the environments where majority of the business operate, there are unseen factors that make the process of innovation to become a very difficult task. Some may assume that these factors might as well affect their competitors but they are usually wrong as most of the competitors have learnt to adapt quickly in these changing circumstances. These circumstances may be forces ranging from economic and politics. Others may issues on licensing and technology. With all these taken into consideration the organization need to either find ways of improving the existing infrastructure or keep up with the rising demand of their goods or services.

In organizations where it is difficult to obtain licenses in order to expand its services, it may seek to partner with other organizations. This will follow after signing of agreements that will indicate the scope of conducting the business. The organization can also change its services in areas that are not regulated. Furthermore the organization can come up with services that will help it camouflage its self in the market (Bijker & Law, 1997). With regard to survival most of the medium sized companies are faced by the problem of infrastructure. Lack of infrastructure is one of the great hindrances to innovation as it places them at the point of elimination by the well established companies. These are very economic and technical conditions on the part of these organizations. Because of the limited economies of scale and unfair regulatory interventions, these organizations have no capacity to influence any kind of negotiations. In this regard their existence and business survival together with their good ideas of innovation are put at stake.

Barriers Associated with Innovation

Majority of the managers are familiarizing with the creativity concepts in an effort to safeguard their business objectives. This usual brings out the need for change in order to remain relevant in the competitive business world. Coming up with innovations that can safeguard their business is an important aspect in most of the business endeavors. Certain ways need to be changed from the traditional way of conducting business.

The majority of the barriers hindering innovation may be entirely with the organization. Certain organizations may face the challenge of infrastructure, negative attitudes and perceptions from the employees. All these kind of barriers must be known to the gate keepers innovators and change agents. Size of the organization may form an advantage to the innovations however when it comes to the process of innovation it becomes a hindrance. The culture to support innovations is usually absent in many organizations. Managers must identify this culture and find a way of removing it from their organization as it can lead to their failure. This problem can be eradicated by ensuring that people work as a team and sustaining a large innovation network.

Bijker, W. E., & Law, J. (1997). Shaping technology/building society: studies in sociotechnical change. Cambridge, Mass. [u.a.], MIT Press. Butler, J.E. (1988). Theories of Technological Innovation as Useful Tools for Corporate, strategy, Strategic Management Journal, Vol. 9, 15-29. Davis, G.F. & W.R. Scott (2007), Organizations and Organizing. Rational, Natural and Open System Perspectives, Upper Saddle River, N.J.: Pearson. Ettlie, J.E., (1995). Product-Process Development Integration in Manufacturing, Management Science, Vol. 41, No. 7, 1224–1237. Freel, M. S. (2000). Strategy and structure in innovative manufacturing SMEs: The case of an English region. Small Business Economics, 15(1), 27–45. Garvin, D. A. (1993): Building a Learning Organization, Harvard Business Review, July-August, pp78-92. Gjerding, A.N. (2003), “The flexible firm: new concepts and differences between the Nordic systems of innovation”, pp.122-143. Hayes, R.H., Wheelwright, S.C. (1979). Link Manufacturing Process and Product Life Cycles, Harvard Business Review, Jan.-Feb. 1979, 133–140. Love, J. & Roper, S. (2004). The organization of innovation: collaboration, cooperation and multifunctional groups in UK and German manufacturing. Cambridge Journal of Economy, 28, 3, 379-395. McLean, L. (2005). Organizational culture’s influence on creativity and innovation: A review of the literature and implications for human resources development. Advances in Developing Human Resources, 7, 2, 226-246. Schein, E. (1992), Organizational Culture and Leadership, 2nd ed., San Francisco: Jossey- Bass. Galunic, D.C. and Eisenhardt, K.M. (2001). 'Architectural Innovation and Modular Corporate Forms'. Academy of Management Journal, 44/6: 1229-1249. Watson, T., & Harris, P. (1999). The emergent manager. London. Sage. Yukl, G. (2006), Leadership in Organizations, 6th ed., Upper Saddle River, NJ: Pearson Prentice-Hall.

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Why the Industrial Revolution Began: a Perfect Storm of Innovation and Opportunity

This essay about the origins of the Industrial Revolution explains how a combination of technological, social, economic, and cultural factors converged to trigger this transformative period, beginning in 18th-century Britain. Key technological innovations like the steam engine played a pivotal role, while the Agricultural Revolution led to a surplus labor force moving from rural to urban areas. The British Empire facilitated access to raw materials and markets, bolstering industrial growth. Additionally, economic changes such as the rise of capitalism and credit systems provided necessary investment for industrial endeavors. The Enlightenment fostered a culture that valued scientific progress and innovation, supporting technological advancements. Together, these elements created the ideal conditions for the Industrial Revolution, setting the stage for modern industrial practices and transforming global society.

How it works

The Industrial Revolution didn’t just happen overnight. It was more like a slow burn that suddenly burst into a wildfire in the 18th century. This monumental shift turned sleepy towns into bustling industrial cities and changed everyday life for generations. So, what sparked this dramatic change, especially in Britain where it all kicked off?

First up, the tech innovations were absolutely crucial. Imagine living in a world where the steam engine has just been perfected by James Watt. This wasn’t just a new gadget—it was a game changer that powered the first factories, transformed transportation, and even pumped water out of mines.

It was the kind of leap forward that made everything that followed possible.

But machines alone don’t tell the whole story. There was a lot going on socially and economically in Britain that set the stage. Take the Agricultural Revolution—this wasn’t just about better farming tools, but a whole new way to manage and produce crops. It was so effective that fewer people were needed on farms, which meant more folks were free to pack up and move to cities. And just like that, you had the perfect workforce ready and waiting just as factories began opening their doors.

Britain’s empire also played a big part. With colonies across the globe, the British had access to a staggering array of resources and a huge market for their manufactured goods. This global network was backed up by the might of the Royal Navy, keeping trade routes open and safe from pirates and rivals. It was the logistical backbone for the nation’s industrial expansion.

Then there’s the money aspect. This era saw a big shift towards what we might now call a capitalist economy. Money became something you could invest in ventures, like factories or new machinery, expecting profits that you could reinvest. Banks and the credit system started to take the shape we recognize today, providing the funds needed for large-scale industrial projects.

Culturally, Britain was riding the wave of the Enlightenment. This was a time when thinkers and tinkerers promoted reason and science. British society was primed to value innovation and improvement, with institutions like the Royal Society leading the charge in scientific exploration and application. This wasn’t just academic; it translated directly into better technology and industrial practices.

All these factors together created the perfect conditions for the Industrial Revolution. It began in Britain, thanks to this unique combination of technological prowess, available workforce, economic conditions, imperial resources, and a culture that valued progress and innovation. This wasn’t just a series of events but a confluence that reshaped the world.

Reflecting on this transformative era, it’s clear that the Industrial Revolution was fueled by much more than the desire to build and innovate. It was a complex interaction of necessity, opportunity, and ambition that changed how people lived and worked, setting the stage for the modern age. It’s a reminder of how history often hinges on a unique mix of conditions coming together at just the right moment.

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PapersOwl.com. (2024). Why the Industrial Revolution Began: A Perfect Storm of Innovation and Opportunity . [Online]. Available at: https://papersowl.com/examples/why-the-industrial-revolution-began-a-perfect-storm-of-innovation-and-opportunity/ [Accessed: 14-May-2024]

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