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Article

Fred Gault and Luc Soete

Innovation indicators support research on innovation and the development of innovation policy. Once a policy has been implemented, innovation indicators can be used to monitor and evaluate the result, leading to policy learning. Producing innovation indicators requires an understanding of what innovation is. There are many definitions in the literature, but innovation indicators are based on statistical measurement guided by international standard definitions of innovation and of innovation activities. Policymakers are not just interested in the occurrence of innovation but in the outcome. Does it result in more jobs and economic growth? Is it expected to reduce carbon emissions, to advance renewable energy production and energy storage? How does innovation support the Sustainable Development Goals? From the innovation indicator perspective, innovation can be identified in surveys, but that only shows that there is, or there is not, innovation. To meet specific policy needs, a restriction can be imposed on the measurement of innovation. The population of innovators can be divided into those meeting the restriction, such as environmental improvements, and those that do not. In the case of innovation indicators that show a change over time, such as “inclusive innovation,” there may have to be a baseline measurement followed by a later measurement to see if inclusiveness is present, or growing, or not. This may involve social as well as institutional surveys. Once the innovation indicators are produced, they can be made available to potential users through databases, indexes, and scoreboards. Not all of these are based on the statistical measurement of innovation. Some use proxies, such as the allocation of financial and human resources to research and development, or the use of patents and academic publications. The importance of the databases, indexes, and scoreboards is that the findings may be used for the ranking of “innovation” in participating countries, influencing their behavior. While innovation indicators have always been influential, they have the potential to become more so. For decades, innovation indicators have focused on innovation in the business sector, while there have been experiments on measuring innovation in the public (general government sector and public institutions) and the household sectors. Historically, there has been no standard definition of innovation applicable in all sectors of the economy (business, public, household, and non-profit organizations serving households sectors). This changed with the Oslo Manual in 2018, which published a general definition of innovation applicable in all economic sectors. Applying a general definition of innovation has implications for innovation indicators and for the decisions that they influence. If the general definition is applied to the business sector, it includes product innovations that are made available to potential users rather than being introduced on the market. The product innovation can be made available at zero price, which has influence on innovation indicators that are used to describe the digital transformation of the economy. The general definition of innovation, the digital transformation of the economy, and the growing importance of zero price products influence innovation indicators.

Article

Nikolaus Franke and Christian Lüthje

Users of products and services, be they user firms or consumers, frequently develop innovations for their own benefit. Such user innovation is a long-existing phenomenon, but it has gained much momentum in the new millennium. The Internet has greatly facilitated connections between creative users, and at the same time cost-effective design and prototyping technologies are making it increasingly feasible for users to develop their own products and services. Users have been found to innovate mainly because they want solutions that best serve their own needs. In general, their innovation activities involve no expectations of monetary profit, being motivated rather by self-rewards (such as fun, positive feelings of altruism, signaling of competence to the community of peers). This explains why users are typically willing to share their innovations without requiring payment. A problem of user innovation is that, since the benefit that others could gain is an externality for users, they lack strong incentives to invest in the active diffusion of their innovations. The consequence of this “diffusion shortfall” is social welfare losses. There are several ways in which producers and service providers can help overcome these problems and benefit from the innovation potential of users at the same time. They can apply the lead user method to actively search for a small group of particularly highly motivated and qualified users, they can outsource product design work to their users via user design toolkits, and they can broadcast innovation challenges to an appropriate crowd of external problem solvers.

Article

Fariborz Damanpour

Innovation is a complex construct and overlaps with a few other prevalent concepts such as technology, creativity, and change. Research on innovation spans many fields of inquiry including business, economics, engineering, and public administration. Scholars have studied innovation at different levels of analysis such as individual, group, organization, industry, and economy. The term organizational innovation refers to the studies of innovation in business and public organizations. Studies of innovations in organizations are multidimensional, multilevel, and context-dependent. They investigate what external and internal conditions induce innovation, how organizations manage innovation process, and in what ways innovation changes organizational conduct and outcome. Indiscreet application of findings from one discipline or context to another, lack of distinction between generating (creating) and adopting (using) innovations, and likening organizational innovation with technological innovation have clouded the understanding of this important concept, hampering its advancement. This article organizes studies of organizational innovation to make them more accessible to interested scholars and combines insights from various strands of innovation research to help them design and conduct new studies to advance the field. The perspectives of organizational competition and performance and organizational adaptation and progression are introduced to serve as platforms to position organizational innovation in the midst of innovation concepts, elaborate differences between innovating and innovativeness, and decipher key typologies, primary sets of antecedents, and performance consequences of generating and adopting innovations. The antecedents of organizational innovation are organized into three dimensions of environmental (external, contextual), organizational (structure, culture), and managerial (leadership, human capital). A five-step heuristic based on innovation type and process is proposed to ease understanding of the existing studies and select suitable dimensions and factors for conducting new studies. The rationale for the innovation–performance relationship in strands of organizational innovation research, and the employment of types of innovation and performance indicators, is articulated by first-mover advantage and performance gap theory, in conjunction with the perspectives of competition and performance and of adaptation and progression. Differences between effects of technological and nontechnological innovation and stand-alone and synchronous innovations are discussed to articulate how and to what extent patterns of the introduction of different types of innovation could contribute to organizational performance or effectiveness. In conclusion, ideas are proposed to demystify organizational innovation to allure new researches, facilitate their learning, and provide opportunities for the development of new studies to advance the state of knowledge on organizational innovation.

Article

Jennifer Kuan

Open Innovation, published in 2003, was a ground-breaking work by Henry Chesbrough that placed technology and innovation at the center of attention for managers of large firms. The term open innovation refers to the ways in which firms can generate and commercialize innovation by engaging outside entities. The ideas have attracted the notice of scholars, spawning annual world conferences and a large literature in technology and innovation management (including numerous journal special issues) that documents diverse examples of innovations and the often novel business models needed to make the most of those innovations. The role of business models in open innovation is the focus of Open Business Models, Chesbrough’s 2006 follow-up to Open Innovation. Managers have likewise flocked to Chesbrough’s approach, as the hundreds of thousands of hits from an online search using the term open innovation can attest. Surveys show that the majority of large firms were engaging in open innovation practices in 2017, compared to only 20% in 2003 when Open Innovation was published.

Article

Erik E. Lehmann and Julian Schenkenhofer

The pursuit of economic growth stands out as one of the main imperatives within modern economies. Nevertheless, economies differ considerably in their competitiveness. Theories on the endogeneity of growth agree on the value of knowledge creation and innovativeness to determine a country’s capability to achieve a sustained performance and to adapt to the dynamics of changing environments and faster information flows. To this effect, national institutional regimes shape nation-specific contexts and embed individuals and firms. The resulting incentive structures shape the attitudes and behavior of individuals and firms alike, whose interactions contribute to the accumulation and flow of knowledge among the nodes of their networks. National systems of innovation (NSIs) therefore embody a concept that aims to analyze the national innovation performance of economies. It rests its rationale in the variation of national institutions that shape the diffusion of technologies through the process of shared knowledge creation and the development of learning routines. Both public and private institutions are thought to interact in a given nation-specific institutional context that essentially affects incentive schemes and resource allocation of the involved economic agents in creating, sharing, distributing, absorbing, and commercializing knowledge. To this effect, public policy plays a key role in the NSI through building bridges between these actors, reducing information asymmetries, and providing them with resources from others within the system. The different actors contributing to the creation and diffusion of knowledge within the system are needed to exchange information and provide the engine for sustained economic growth. Universities, research institutes, companies and the individual entrepreneur are in charge of shaping their economic system in a way that resource and skill complementarities are exploited to the mutual benefit.

Article

Alfredo De Massis, Emanuela Rondi, and Samuel Wayne Appleton

The involvement of families in firms’ ownership, management, and governance is a key driver of organizational attitudes, behaviors, and performances, especially those related to innovation. Starting from the beginning of the 21st century, the academic interest toward family firm innovation has bloomed. This body of research has mostly emerged from family firm scholars, while mainstream innovation scholars have often overlooked family variables in their studies. Indeed, innovation is one of the main areas in family firm research, integrating family and business aspects, leading to a plethora of sometimes contradictory findings. Initially, research compared innovation between family and nonfamily firms. While this approach has been beneficial to the rise of this stream of research and underlined the idiosyncratic characteristics of family firms on this matter, it soon emerged that within family firms there is a high degree of heterogeneity, especially in their attributes and the way they relate to innovation. Therefore, scholars have delved deeper into the heterogeneous influence that different types and degrees of family involvement in the firm can exert on innovation. This vast body of literature can be reconciled according to an antecedents–activities–outcomes framework allowing to attune current understanding of family firm innovation and recommend directions for future research. While most of current research has examined the antecedents of family business innovation, further examination of the activity of innovating in family firms is needed. Fostering accessibility to this literature allows students, practitioners, and scholars to grasp and digest this insightful area of family business research. It also encourages an extension of the range of perspectives adopted to examine innovation in family firms, contributing to advance current knowledge.

Article

Samer Faraj and Takumi Shimizu

Online communities (OCs) are emerging as effective spaces for knowledge collaboration and innovation. As a new form of organizing, they offer possibilities for collaboration that extend beyond what is feasible in the traditional hierarchy. OC participants generate new ideas, talk about knowledge, and remix and build on each other’s contributions on a massive scale. OCs are characterized by fluidity in the resources that they draw upon, and they need to manage these tensions in order to sustain knowledge collaboration generatively. OCs sustain knowledge collaboration by facilitating both tacit and explicit knowledge flows. Further, OCs play a key role in supporting and sustaining the knowledge collaboration process that is necessary for open and user innovation. As collective spaces of knowledge flows, OCs are mutually constituted by digital technologies and participants. The future is bright for OC research adopting the knowledge perspective and focusing on how to sustain their knowledge flow.

Article

Sanjay Sharma

At a macro level, innovation for society refers to innovation of societal institutions. At a micro level, it refers to innovations undertaken by social entrepreneurs as start-ups with a social and/or environmental mission and innovations undertaken by firms in products/services, processes, operations, technologies, and business models to address social and environmental challenges while achieving core economic objectives. The focus here is on firm-level innovations and the drivers for such innovations. Exogenous drivers include institutional-level influences such as regulations, societal norms, and industry best practices (mimetic forces) and stakeholder-level influences including shareholders, investors, customers, regulators, nongovernmental organizations, media, and others that have power, legitimacy, and urgency of their claims directly or indirectly via other stakeholders. The endogenous drivers include institutional ownership, activist shareholders, boards of directors, ownership, and competitive strategy focused on developing profitable businesses that address societal challenges. Even when the firm is motivated due to exogenous and endogenous drivers to undertake investments in innovating for society, it needs the capacity to generate and implement such innovations. Innovations for society require motivated managers, managerial capacity, and organizational capabilities that go beyond routine innovations that firms undertake to improve products and processes and enter new markets. This capacity enables firms to reconcile their performance on economic, social, and environmental metrics to address societal challenges while achieving core economic objectives. Managerial capacity requires firms to overcome cognitive biases and create opportunity frames that convert negative loss bias, where managers perceive lack of control over outcomes, to a positive opportunity bias, where managers perceive the ability to control their decisions and actions. Opportunity framing involves legitimization of innovation for society in the corporate identity, integration of sustainability metrics into performance evaluation, creation of discretionary slack, and empowerment of managers with a relevant and ongoing information flow. Innovating for society also requires major changes in a firm’s decision-making processes and investments in new organizational capabilities of engaging stakeholders and integration of external learning, processes of continuous improvement of operations, higher order or double-loop organizational learning by integrating external learning with internal knowledge, cross-functional integration, technology portfolios, and strategic proactivity, all leading to processes of continuous innovation. Knowledge about the role of firms in addressing societal challenges has grown over the past three decades as scholars in multiple disciplines have explained the motivations of firms to undertake innovations for society, processes to build organizational capabilities to adopt and implement sustainability strategies, and linkages of such strategies to financial performance. Nevertheless, such innovations and strategies are far from a universal norm.

Article

Linus Dahlander and Henning Piezunka

Crowdsourcing—a form of collaboration across organizational boundaries—provides access to knowledge beyond an organization’s local knowledge base. There are four basic steps to crowdsourcing: (a) define a problem, (b) broadcast the problem to an audience of potential solvers, (c) take actions to attract solutions, and (d) select from the set of submitted ideas. To successfully innovate via crowdsourcing, organizations must complete all these steps. Each step requires an organization to make various decisions. For example, organizations need to decide whether its selection is made internally. Organizations must take into account interdependencies among these four steps. For example, the choice between qualitative and quantitative selection mechanisms affects how widely organizations should broadcast a problem and how many solutions they should attract. Organizations must make many decisions, and they must take into account the many interdependencies in each key step.

Article

Lucy L. Gilson, Yuna S. H. Lee, and Robert C. Litchfield

Although creativity research has historically focused on individuals, with more and more employees working in teams, researchers have started to explore the construct of team creativity. Rather than a comprehensive review, this article takes an in-depth look at the most recent team creativity research. To do this, key themes and trends are discussed, which are then tied back to prior reviews, and new avenues for future research are proposed. Team creativity is a challenging construct because it can be conceptualized as both an outcome and a process, and there is no clear definition of either. When considering team creativity as an outcome, research has employed both complex mediation models as well as a more nuanced examination of moderating variables and constructs that may strengthen or attenuate the effects of relationships related to team creativity. This growing avenue of research recognizes the variability in team creativity that is possible in different circumstances and contexts, and seeks to identify what drives different outcomes. These approaches also acknowledge that team creativity is not guaranteed even when enabling conditions are in place, and that other variables may exert forces in different ways. The recognition that team creativity is unlikely to be the simple sum of members’ creative processes is becoming very apparent, with researchers examining ways of encouraging, fostering, and sustaining creativity in teams over time. Researchers have also recognized that team creativity is more likely to unfurl over time as a process, rather than a discrete point-in-time event. To this end, the key areas examined are the roles of member diversity and leadership. For diversity, racio-ethno, cultural, gender, age, political orientation, and diversity training have all been examined. For leadership, the focus has shifted away from the more traditional transformational theories and to newer constructs such as humility, ethical and shared leadership, as well as what it means to have an ideational leader who facilitates idea generation. Taken together, what the most recent research tells us is that creativity in teams remains a growing and evolving area of inquiry. While no longer unexplored, much remains to be clarified such as the barriers to effective team creativity, and practices that may help transcend these barriers. A lot of promising areas for future research are highlighted, which will become more important as workplaces pivot toward cultivating team creativity in a systematic and intentional way.

Article

Yao Sun and Ann Majchrzak

Starting from early 21st century, companies increasingly use open innovation challenges to generate creative solutions to business problems. This revolution in business models and management strategy reflects the evolution supported by new technology. Employing this new strategic model, companies seek to innovate in a wide variety of areas, such as clothes designs, photography solutions, business plans, and film production. Contrary to closed innovation through which companies develop creative ideas internally, innovation challenges are catalyzed by socioeconomic changes such as the rapid advancement of information technologies, increased labor division, as well as ever-expanding globalization. Going hand in hand are trends such as outsourcing, occurring in parallel in the management area, which makes companies more agile and flexible. Multifaceted and multidimensional, open innovation challenges consist of various activities such as inbound innovation (acquiring and sourcing), outbound innovation (selling and revealing), or a compound mix of these two forms. It also pertains to complementary assets, absorptive capacity, organizational exploration, and exploitation. In an attempt to determine how to best support such an important component of society, scholars and practitioners continue to pursue effective innovation challenge architecture (the art or practice that guides participants’ interactions and exchange) that allows open collaboration among the crowd, as well as an approach for incorporating such architecture into technological platforms in order to improve the crowd’s creativity. This issue is addressed by focusing on existing research that delineates various types of effective architecture of innovation challenges. A theory-based framework guides this examination, and work from various scholarly perspectives of innovation challenges, knowledge management, motivated knowledge sharing, and crowdsourcing are integrated into this framework.

Article

Lorenzo Massa and Christopher L. Tucci

Starting from the mid-1990s, business models have received increased attention from both academics and practitioners. At a general level, a business model refers to the core logic that a firm or other type of organization employs to achieve its goals. Thus, in general terms, the business model construct attempts to capture the way organizations “do business” or operate to create, deliver, and capture value. Business model innovation (BMI) constitutes a unique dimension of innovation, different from and complementary to other dimensions of innovation, such as product/service, process, or organizational innovation. This distinction is important in that different dimensions of innovation have different antecedents, different processes, and, eventually, different outcomes. Business models have been the subject of extensive research, giving birth to several lines of inquiry. Among them, one line focuses on business models in relation to innovation. This is a vast, somewhat fragmented, and evolving line of inquiry. Despite this limitation, it is possible to recognize that, at the core, business models are relevant to innovation in at least two main ways. First, business models can act as vehicles for the diffusion of innovation by bridging inventions, innovative technologies, and ideas to (often distant) markets and application domains. Therefore, business models speak to the phenomenon of technology transfer from the point of view of academic entrepreneurship and of corporate innovation. Thus, an important role of the business model in relation to innovation is to support the diffusion and adoption of new technologies and scientific discoveries by bridging them with the realization of economic output in markets. This is a considerable endeavor that relies on a complex process entailing the search for, and recombination of, complementary knowledge and capabilities. Second, business models are a subject of innovation that can become a source of innovation in and of themselves. For example, offerings that reinvent value to the customer—as opposed to offerings that incrementally add value to existing offerings—often involve designing novel business models. Relatedly, BMI refers to both a process (i.e., the dynamics involved in innovating business models) as well as the output of that process. In relation to BMI as a process, the literature has suggested distinguishing between business model reconfiguration (BMR; i.e., the reconfiguration of an existing business model), and business model design (BMD; i.e., the design of a new business model from scratch). This distinction allows us to identify three possible instances, namely general BMR in incumbent firms, BMD in incumbent firms, and BMD in newly formed organizations and startups. These are arguably different phenomena involving different processes as well as different moderators. BMR could be understood as an evolutionary process occurring because of changes in activities and adjustments within an existing configuration. BMD involves facing considerable uncertainty, thus putting a premium on discovery-driven approaches that emphasize experimentation and learning and a considerable degree of knowledge search and recombination.

Article

Cristina Chaminade and Bengt-Åke Lundvall

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Business and Management. Please check back later for the full article. Scientific advance and innovation are major sources of economic growth and are crucial for making social and environmental development sustainable. A critical question is if private enterprises invest sufficiently in research and development and, if not, to what degree and how governments should engage in the support of science and innovation. While neoclassical economists point to market failure as the main rationale for innovation policy, evolutionary economists point to the role of government in building stronger innovation systems and creating wider opportunities for innovation. Research shows that the transmission mechanisms between scientific advance and innovation are complex and indirect. There are other equally important sources of innovation, including experience-based learning. Innovation is increasingly seen as a systemic process where the feedback from users needs to be taken into account when designing public policy. Science and innovation policy may aim at accelerating knowledge production along well-established trajectories or at giving new direction to the production and use of knowledge. It may be focused exclusively on economic growth, or it may give attention to the impact on social inclusion and the natural environment. An emerging topic is the extent to which national perspectives continue to be relevant in a globalizing learning economy facing multiple global complex challenges, including the issue of global warming. Scholars point to a movement toward transformative innovation policy and global knowledge sharing as a response to current challenges.

Article

Likoebe Maruping and Yukun Yang

Open innovation is defined as an approach to innovation that encourages a broad range of participants to engage in the process of identifying, creating, and deploying novel products or services. It is open in the sense that there is little to no restriction on who can participate in the innovation process. Open innovation has attracted a substantial amount of research and widespread adoption by individuals and commercial, nonprofit, and government organizations. This is attributable to three main factors. First, open innovation does not restrict who can participate in the innovation process, which broadens the access to participants and expertise. Second, to realize participants’ ideas, open innovation harnesses the power of crowds who are normally users of the product or service, which enhances the quality of innovative output. Third, open innovation often leverages digital platforms as a supporting technology, which helps entities scale up their business. Recent years have witnessed a rise in the emergence of a number of digital platforms to support various open innovation activities. Some platforms achieve notable success in continuously generating innovations (e.g., InnoCentive.com, GitHub), while others fail or experience a mass exodus of participants (e.g., MyStarbucksIdea.com, Sidecar). Prior commentaries have conducted postmortems to diagnose the failures, identifying possible reasons, such as overcharging one side of the market, failing to develop trust with users, and inappropriate timing of market entry. At the root of these and other challenges that digital platforms face in open innovation is the issue of governance. In the article, governance is conceptualized as the structures determining how rigidly authority is exerted and who has authority to make decisions and craft rules for orchestrating key activities. Unfortunately, there is no comprehensive framework for understanding governance as applied to open innovation that takes place on digital platforms. A governance perspective can lend insight on the structure of how open innovation activities on digital platforms are governed in creating and capturing value from these activities, attracting and matching participants with problems or solutions, and monitoring and controlling the innovation process. To unpack the mystery of open innovation governance, we propose a framework by synthesizing and integrating accreted knowledge from the platform governance literature that has been published in prominent journals over the past 10 years. Our framework is built around four key considerations for governance in open innovation: platform model (firm-owned, market, or community), innovation output ownership (platform-owned, pass-through, or shared), innovation engagement model (transactional, collaborative, or embedded), and nature of innovation output (idea or artifact). Further, we reveal promising research avenues on the governance of digital open innovation platforms.

Article

Lukas Neumann and Oliver Gassmann

Frugal innovation as a concept was initially sparked by a groundbreaking article published in The Economist in 2010. In it, the conception and application of a handheld electrocardiogram (ECG), the Mac 400, specifically designed to serve the rural population in India, was introduced. Every aspect of this product and its ecosystem was designed to serve the customer at less than 25% of the original cost. Since this publication, a lively discussion around this concept has developed in academia as well as in the industry. As a term, “frugal innovation” refers to solutions (products or services), methods, or designs that focus on serving new customers in resource-constrained contexts at the bottom of the pyramid (BoP) and/or emerging and developing markets. This understanding has broadened somewhat as such innovations gain increasing attention and relevance throughout all customer segments across the globe. What remains consistent is that frugal innovation is based on a new type of value architecture that is specifically developed to serve customers’ needs in the respective context by utilizing as few resources as possible. This approach leads to many cases where frugal innovations are novel and disruptive to their market environment. Research shows that for firms, especially traditional “Western” ones, these innovations require significant changes in firms’ activities along the entire value chain.

Article

The strategic management of technology and innovation is an important contributor to organizational performance and competitiveness. It creates value, assists differentiation, enhances productivity, and guides creativity and initiative. In the face of uncertainty in operating environments, caused especially by rapid technological change, the strategic management of innovation configures capabilities and resources within organizations. These include the capability to search for innovations, select the most advantageous, and appropriate or capture their returns. It involves investing in sources of innovation, such as research and development (R&D) and collaboration with external partners, and using methods for effectively assessing their contributions. Unstable and turbulent operating conditions can disrupt established organizational policies and practices and make planning difficult. As a result, strategies for technology and innovation are necessarily emergent rather than prescriptive, exploratory rather than determinable. Any advantages technology and innovation create are likely to be transitory. The pressing need for greater environmental sustainability, increased focus on the social consequences of innovation, and the impact of new digital and data-rich technologies, add to the challenges of the strategic management of technology and innovation. To address these challenges, attention to physical and intellectual capital needs to be supplemented by greater concern for human, social, and natural capital, and to organizational culture and behavior. This requires the foundation of the strategic management of technology and innovation in the discipline of economics to be complemented by others, such as psychology, organizational behavior, and ethics.

Article

Donald F. Kuratko and Jeffrey G. Covin

The theoretical and empirical knowledge on corporate entrepreneurship (ce) has evolved in the research domain over the last 50 years, beginning very slowly and growing in importance in that time. Because of this evolution and expansion in CE research, the theoretical and empirical knowledge about CE and the entrepreneurial behavior on which it is based has progressed to a point where a greater understanding of the concept can be presented. Many of the elements essential to constructing a theoretically grounded understanding of the domains of CE have been identified. An examination of the field reveals that there are three research domains that have developed over the years: corporate venturing (either internal or external), strategic entrepreneurship, and entrepreneurial orientation. In examining the evolution of CE research across five decades, the focus of CE research has varied over the years. The very early research published in the 1970s focused more on how teams could establish entrepreneurial activities inside established organizations; however, this early research was sparse because CE was not widely acknowledged nor sought in existing organizations. The 1980s saw some research into entrepreneurial behavior inside established organizations that explained how such activity could simply not exist in the structure and operations of existing corporations. Opposed to that thinking, many more researchers demonstrated that the idea of corporate entrepreneurial activity could be conceived as a process of organizational renewal. In the 1990s, researchers began to develop more comprehensive examinations of CE that focused on re-energizing companies and therefore increasing its abilities to develop innovations. The first and second decades of the 21st century witnessed a more sophisticated refinement of research topics in CE. In addition to research specific to the development of the three main domains of CE (corporate venturing, entrepreneurial orientation, and strategic entrepreneurship), there has been research on more specific areas of interest in CE including the implementation of CE, management levels, the individual corporate entrepreneur, models and metrics of CE, a deeper examination of internal corporate ventures, the international domain, firm size, family firms, ethics, and corporate venture capital. These areas illustrate the developmental expansion of interest in CE across different domains. Even with the continued expansion in the research on CE, there is so much that is still not understood nor researched well enough to fully advance the theoretical and empirical knowledge on CE. With the growing climate of disruption through external antecedents such as COVID-19, the entrepreneurial behavior of individuals within organizations becomes paramount and warrants a deeper understanding. Newer research questions on CE are emerging and further theoretical exploration should be the work of ongoing scholarly efforts.

Article

Pankaj Setia, Franck Soh, and Kailing Deng

Organizations are widely building digital platforms to transform operations. Digital platforms represent a new way of organizing, as they leverage technology to interconnect providers and consumers. Using digital technologies, organizations are platformizing operations, as they open their rigid and closed boundaries by interconnecting providers and consumers through advanced application programming interfaces (APIs). Early research examined platformized development of technology products, with software development companies—such as Mozilla Foundation—leading the way. However, contemporary organizations are platformizing nontechnology offerings (e.g., ride-sharing or food delivery). With growing interest in platforms, the basic tenets underlying platformization are still not clear. This article synthesizes previous literature examining platforms, with the aim of examining what platformization is and how and why organizations platformize.

Article

Michael D. Mumford, Robert Martin, and Samantha N. Elliott

Creative thinking is the basis for innovation in firms. And the need for strategy-relevant innovations has generated a new concern with how people go about solving the kinds of problems that call for creative thought. Although many variables influence people’s ability to provide creative problem solutions, it is assumed the ways in which people work with or process knowledge provides the basis for successful creative problem-solving efforts. Additionally, there has been evidence bearing on the processing activities that contribute to creative problem solving. It is noted that at least eight distinct processing activities are involved in most incidents of creative problem solving: (1) problem definition, (2) information gathering, (3) concept selection, (4) conceptual combination, (5) idea generation, (6) idea evaluation, (7) implementation planning, and (8) adaptive monitoring. There are strategies people employ in effective execution of each of these processes, along with contextual variables that contribute to, or inhibit, effective process execution. Subsequently, there are key variables that operate in the workplace that contribute to, or inhibit, effective execution of these processing operations. These observations, of course, lead to implications for management of innovative efforts in firms.

Article

Though concern for environmental issues dates back to the 1960s, research and practice in the field of sustainability innovation gained significant attention from academia, practitioners, and NGOs in the early 1990s, and has evolved rapidly to become mainstream. Organizations are changing their business practices so as to become more sustainable, in response to pressure from internal and external stakeholders. Sustainability innovation broadly relates to the creation of products, processes, technologies, capabilities, or even whole business models that require fewer resources to produce and consume, and also support the environment and communities, while simultaneously providing value to consumers and being financially rewarding for businesses. Sustainability innovation is a way of thinking about how to sustain a firm’s growth while sustainably managing depleting natural resources like raw materials, water, and energy, as well as preventing pollution and unethical business practices wherever the firm operates. Sustainability innovation represents a very diverse and dynamic area of scholarship contributing to a wide range of disciplines, including but not limited to general management, strategy, marketing, supply chain and operations management, accounting, and financial disciplines. As addressing sustainability is a complex undertaking, sustainability innovation strategies can be varied in nature and scope depending upon the firm’s capabilities. They may range from incremental green product introductions to radical innovations leading to changes in the way business is conducted while balancing all three pillars of sustainability—economic, environmental, and social outcomes. Sustainability innovation strategies often require deep structural transformations in organizations, supply chains, industry networks, and communities. Such transformations can be hard to implement and are sometimes resisted by those affected. Importantly, as sustainability concerns continue to increase globally, innovation provides a significant approach to managing the human, social, and economic dimensions of this profound society-wide transformation. Therefore, a thorough assessment of the current state of thinking in sustainability innovation research is a necessary starting point from which to improve society’s ability to achieve triple bottom line for current and future generations.