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.
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Additive Manufacturing Technology
Christina Öberg
Article
Behavioral Decision Making and Game Theory Methods
Georgios Christopoulos
Behavioral decision making and game theory (BDMGT) is the umbrella term for a set of methods aimed at recording the choices and eliciting the decision preferences of individuals (organizational agents like managers, employees, entrepreneurs, investors, or consumers). BDMGT comprises a set of well-defined decision problems that, in contrast to surveys or questionnaires that rely on self-assessment, evaluate actual behavioral choices with well-defined outcomes and choice parameters. Additionally, in contrast to idealized models, BDMGT focuses on actual decision-making processes. BDMGT allows for dynamic and complex decision scenarios that are nevertheless computationally tractable and have lower linguistic demands (thus making inter-group and cross-cultural comparisons easier).
BDMGT decision problems can be broadly categorized as either individual (i.e., where the agent acts against nature or luck, and all outcomes return to the agent) or social (i.e., where [at least one] another agent—“the partner”—is involved). Social decisions can be further defined as either non-strategic (i.e., where the partner makes no decisions, but some of the outcomes can be returned to them) or strategic (i.e., where the partner makes decisions that can affect the final outcomes returned to the agent). Examples of generic research questions for individual decision tasks include how risk influences decisions (i.e., measuring risk preferences) or (for social decision tasks) how agents interact with each other (i.e., how they allocate resources, what they consider fair, how they build trust, or how they coordinate to achieve common strategic goals).
The present entry focuses on the methodological aspects of BDMGT. There are major methodological considerations and common pitfalls associated with BDMGT that can bias results and their interpretation, including incentives and how participants should be paid, anonymity, double-blinding (and when this is not enough), social desirability, how the “partner” participant is explained, or what issues may arise with repeated decisions or trials. The field has also seen the introduction of newer but well-established developments in the field, such as computerized testing, decision neuroscience, and augmented and virtual reality.
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Sustainability Innovation: Drivers, Capabilities, Strategies, and Performance
Devashish Pujari and Anna Sadovnikova
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.
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Luxury Business
Pierre-Yves Donzé and Rika Fujioka
The luxury business has been one of the fastest growing industries since the late 1990s. Despite numerous publications in management and business history, it is still difficult to have a clear idea of what “luxury” is, what the characteristics of this business are, and what the dynamics of the industry are. With no consensus on the definition of luxury among scholars and authors, the concept thus requires discussion. Luxury is commonly described as the high-end market segment, but the delimitation of the lower limit of this segment and its differentiation from common consumer goods are rather ambiguous. Authors use different terminology to describe products in this grey zone (such as “accessible luxury,” “new luxury,” and “prestige brands”).
Despite the ambiguous definition of “luxury,” various companies have described their own businesses in this way, and consumers perceive them as producers of luxury goods and services. Research on luxury business has focused mostly on four topics: (1) the evolution of its industrial organization since the 1980s (the emergence of large conglomerates such as Moët Hennessy Louis Vuitton SE or LVMH, and the reorganization of small and medium-sized enterprises); (2) production systems (the introduction of European companies into global value chains, and the role of country of origin labels and counterfeiting); (3) brand management (using heritage and tradition to build luxury brands); and (4) access to consumers (customization versus standardization). Lastly, new marketing communication strategies have recently been adopted by companies, namely customer relations via social media and the creation of online communities.
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Product and Innovation Portfolio Management
Vinícius Chagas Brasil and J.P. Eggers
In competitive strategy, firms manage two primary (non-financial) portfolios—the product portfolio and the innovation portfolio. Portfolio management involves resource allocation to balance the important tradeoff of risk reduction and upside maximization, with important decisions around the evaluation, prioritization and selection of products and innovation projects. These two portfolios are interdependent in ways that create reinforcing dynamics—the innovation portfolio is the array of potential future products, while the product portfolio both informs innovation strategy and provides inputs to future innovation efforts. Additionally, portfolio management processes operate at two levels, which is reflected in the literature's structure. The first is a micro lens which focuses on management frameworks to boost portfolio performance and success through project-level selection tools. This research has its roots in financial portfolio management, relates closely to research on new product development and marketing product management, and explores the effects of portfolio management decisions on other organizational functions (e.g., operations). The second lens is a macro lens on portfolio management research, which considers the portfolio as a whole and integrates key organizational and competitive concepts such as entry timing, portfolio management resource allocation regimes (e.g., real options reasoning), organizational experience, and the culling of products and projects. This literature aims to set portfolio management as higher level organizational decision-making capability that embodies the growth strategy of the organization. The organizational ability to manage both the product and innovation portfolios connects portfolio management to key strategic organizational capabilities, including ambidexterity and dynamic capabilities, and operationalizes strategic flexibility. We therefore view portfolio management as a source of competitive advantage that supports organizational renewal.
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The Uppsala Model in the Twenty-First Century
Jan-Erik Vahlne
When it was developed in 1977, the Uppsala internationalization process model (Uppsala model for short) had three basic premises: process ontology, behavioral assumptions, and the presence of uncertainty. Multinational business enterprises (MBEs), among all actors, were in their infancy, and their future could not be known. Later on, the model was extended to cover the evolution of the MBEs, with factors such as internationalization, globalization, and the development of characteristics prompting changes and making them possible. Likewise, the knowledge concept was substituted for by capabilities, operational and dynamic, fitting well the other concepts of the model. The neoclassical view of the firm as an independent unit on the market is considered unrealistic. Instead, firms, MBEs, and small and medium enterprises are seen as embedded in networks with other cooperating and competing actors. The mechanisms of the 2017 version, though, are the same as in the original version. Hopefully, the latest version can be used as a tool within the scope of the “theory of the firm” research and as a platform for more studies on causal mechanisms, later to be applied in normative conclusions. It follows that static cross-sectional statistical methods are not fully satisfactory. Application of dynamic analytical methods requires investment in longitudinal data collection, which is costly, and has to be performed by institutions rather than individuals. A dream is that the Uppsala model can be used as a stepping stone in the construction of realistic macro-level studies of the economy.
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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.
