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Additive Manufacturing Technology  

Christina Öberg

Additive manufacturing, or three-dimensional (3D) printing, refers to a layer-based production technology. A product is created through layers that are melted together. The layer-based manufacturing means that new surfaces can be shaped with complex forms created and combined in a single manufacturing process. It leads to components or entire products being printed locally. As a technology, it infers extensive changes for (a) product and production design, (b) supply chain options, and (c) business models. It does so because additive manufacturing opens opportunities not only for new product designs but also for firm operations and offerings. More specifically, additive manufacturing enables advanced organic designs manufactured as one piece, local on-demand printing of spare parts, and the printing of full-scaled prototypes to fit and test with final solutions. Movable parts can be printed as one single product and through one single production process. The local manufacturing reduces the need for transportations and subsuppliers. New business models include firms specializing in additive manufacturing for others, such as fab labs and printing houses. Through these changes, additive manufacturing challenges manufacturers of tools and parts as well as demand for logistics solutions. Customization, higher product precision, and increased sustainability are positive consequences of additive manufacturing. Meanwhile, additive manufacturing raises concerns about who owns the product design and who carries responsibilities for the product. Additive manufacturing affects product and production design, supply chains, and business models, and businesses face several ethical dilemmas regarding this new technology. Examples are provided to illustrate additive manufacturing practices.

Article

Crowdsourcing Innovation  

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

Design Thinking in Business and Management: Research History, Themes, and Opportunities  

Jarryd Daymond and Eric Knight

Design thinking is a human-centered, innovation-focused problem-solving approach that employs various tools and methods for creative purposes. It is a dynamic process and often prioritizes the needs and experiences of people while considering both technical and economic aspects of a solution. The prominence of design thinking in practice has seen its use move beyond product development teams to take a more central role in shaping how organizations approach problems, develop strategies, build capabilities, and drive cultural change. It is common for organizations to employ executives with a specific focus on design, and traditionally “nondesign” organizations increasingly build, buy, or borrow design capabilities. The utility of design thinking stretches beyond organizational outcomes, with educators and employers recognizing that understanding and proficiency in design thinking is a valuable and transferrable skill. A rich scholarly tradition in design sciences and engineering underpins design thinking. These traditions provide the foundational understandings of problem definition and need-finding, information gathering and analysis, and creative expression and ideation, from which design thinking gained prominence. Although not often acknowledged in contemporary scholarship, design thinking research builds on these traditions and offers unique perspectives on the practice of design thinking and its theoretical underpinnings: The cognitive perspective focuses on how unique ways of thinking shape the practice of design thinking; the instrumental perspective attends to how design thinking is done, including the methods or tools used in design thinking; and the organizational-level perspective concerns the implementation of design thinking in organizations and its influence on organizational culture and capabilities. While the various research traditions preceding design thinking are receiving greater attention in contemporary research, rich insights from these established fields offer deep theoretical knowledge to develop several promising research areas. These avenues for future research include how design thinking can inform the redevelopment of services and customer experiences, tackle societal challenges, and build capabilities to benefit communities and society more generally.

Article

Governance in Digital Open Innovation Platforms  

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

Strategic Planning in the Public Sector  

John Bryson and Lauren Hamilton Edwards

Strategic planning has become a fairly routine and common practice at all levels of government in the United States and elsewhere. It can be part of the broader practice of strategic management that links planning with implementation. Strategic planning can be applied to organizations, collaborations, functions (e.g., transportation or health), and to places ranging from local to national to transnational. Research results are somewhat mixed, but they generally show a positive relationship between strategic planning and improved organizational performance. Much has been learned about public-sector strategic planning over the past several decades but there is much that is not known. There are a variety of approaches to strategic planning. Some are comprehensive process-oriented approaches (i.e., public-sector variants of the Harvard Policy Model, logical incrementalism, stakeholder management, and strategic management systems). Others are more narrowly focused process approaches that are in effect strategies (i.e., strategic negotiations, strategic issues management, and strategic planning as a framework for innovation). Finally, there are content-oriented approaches (i.e., portfolio analyses and competitive forces analysis). The research on public-sector strategic planning has pursued a number of themes. The first concerns what strategic planning “is” theoretically and practically. The approaches mentioned above may be thought of as generic—their ostensive aspect—but they must be applied contingently and sensitively in practice—their performative aspect. Scholars vary in whether they conceptualize strategic planning in a generic or performative way. A second theme concerns attempts to understand whether and how strategic planning “works.” Not surprisingly, how strategic planning is conceptualized and operationalized affects the answers. A third theme focuses on outcomes of strategic planning. The outcomes studied typically have been performance-related, such as efficiency and effectiveness, but some studies focus on intermediate outcomes, such as participation and learning, and a small number focus on a broader range of public values, such as transparency or equity. A final theme looks at what contributes to strategic planning success. Factors related to success include effective leadership, organizational capacity and resources, and participation, among others. A substantial research agenda remains. Public-sector strategic planning is not a single thing, but many things, and can be conceptualized in a variety of ways. Useful findings have come from each of these different conceptualizations through use of a variety of methodologies. This more open approach to research should continue. Given the increasing ubiquity of strategic planning across the globe, the additional insights this research approach can yield into exactly what works best, in which situations, and why, is likely to be helpful for advancing public purposes.

Article

User Innovation  

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.