Journal of Product Innovation Management最新文献

The avalanche of available unstructured text data makes it ever more challenging for innovation practitioners (and academics) to extract meaningful insights from such data. Topic modeling can support these efforts and help spur innovation. The current study reviewed 1099 innovation management articles to identify and compare the most frequently used probabilistic topic modeling approaches for innovation. In an effort to contextualize the suitability of these approaches, we develop a framework to organize existing topic modeling applications along the different innovation stages (i.e., idea generation, development, and commercialization) and innovation research in general. By zooming in on the three innovation stages, the authors showcase how topic modeling can spur innovation within each stage and highlight the future potential of the specific approaches. To further assist in capturing the various dynamics in complex unstructured text datasets, we illustratively apply a tailored topic modeling configuration to 1444 Journal of Product Innovation Management articles (1984–2023) to identify emerging, stable, and mature topics, as well as looking at their respective impact. This demonstration could serve as a starting point or blueprint for innovation practitioners and researchers seeking to combine the advantages of several topic modeling approaches. We conclude by offering a future outlook, including a forward-looking research agenda. Taken together, our study offers guidance to and equips innovation practitioners and academics to design distinctive topic modeling procedures to best serve their intended purposes. If deployed appropriately, topic modeling helps users extract a wealth of unique, unprecedented insights from a continuously expanding source of data.

We investigate the interaction design preferences of solution seekers and problem solvers on open innovation (crowdsourcing) platforms. Drawing on social exchange theory (SET), we hypothesize that seekers and solvers have different preferences for the configuration of four central interaction design features of a crowdsourcing platform: communication channels, collaboration options, selection of winning submissions, and feedback mechanisms. Based on a conjoint study with 842 respondents, we show conflicting preferences for the configuration of these features, but also find a surprisingly consistent “best” configuration that can balance the individual preferences of both seekers and solvers. In addition, we identify social trust, risk aversion, and the need for cognition as three personal characteristics of individuals in seeker organizations and solvers that influence their preferred configuration of platform design. Our findings help intermediaries operating a crowdsourcing platform to offer nuanced platform interactions that align how individuals in seeker organizations (e.g., project managers) and individual solvers create and capture value in crowdsourcing. Furthermore, we contribute to the micro-foundations of open innovation by proposing SET as a novel perspective to examine how the expectations and value drivers of all parties involved in a crowdsourcing project can be balanced.

Many launch strategies for new products now aim at building pre-release consumer buzz (PRCB), defined as consumers' collective expressions of anticipation for an upcoming product. While a positive association of PRCB with innovation success has been established, little is known about how, under what conditions, and to what extent PRCB influences consumers' adoption decisions. This research sheds light on these issues by investigating PRCB's contagious nature as one of the concept's defining characteristics. Drawing on herding theory, the authors develop a conceptual framework and provide comprehensive experimental evidence that consumers' exposure to PRCB for a new product triggers distinct psychological mechanisms that influence their own adoption decisions: PRCB-observing consumers exhibit both greater social attraction to the “buzz movement” (group-related evaluation) as well as more curiosity and higher quality expectations about the new product (product-related evaluation). Furthermore, these effects are particularly strong for consumers who are highly susceptible to social influence and for products with low popular appeal. The authors complement their consumer-level analysis with an illustrative market-level what-if analysis that approximates the financial consequences of PRCB's contagious effects. Results suggest that the financial impact of PRCB can be substantial but differs significantly across scenarios, depending on product type and consumer segment. These findings have important implications for the management of innovations before launch.

Recent advancements in artificial intelligence (AI) have ushered in a wave of AI innovations in the form of embodied conversational agents. These stakeholders offer new ways to engage customers in the co-creation of services but still face significant customer skepticism. To address this challenge, we frame interactions between customers and embodied conversational agents through the lens of stakeholder engagement and apply the concept of proxy agency from social cognitive theory. This framework allows us to identify two primary stakeholder roles for embodied conversational agents: partner and servant. We conceptualize how these roles inform optimal design for embodied conversational agents and shape a two-stage value-by-proxy process, comprising proxy efficacy and outcome expectancy. Additionally, we uncover tensions within this process due to over-reliance on AI, as well as significant outcomes that extend beyond the immediate interaction. Our study, using a custom-developed embodied conversational agent with a sample of 596 U.S.-based respondents, reveals that positioning an embodied conversational agent in a partner role, combined with a human (vs. robot) appearance and emotional (vs. functional) conversation style, has the strongest positive impact on perceived value-by-proxy, usage and advice implementation intentions, and willingness to pay. We also observe an inverted U-shaped moderation by reliance in the relationship between proxy efficacy and outcome expectancy, signaling the potential risks of over-reliance on AI. Furthermore, we provide qualitative insights into why some customers avoid engaging with embodied conversational agents. Overall, we offer a nuanced perspective on embodied conversational agents as active stakeholders within organizational systems, advancing both theoretical understanding and practical applications of this rapidly evolving technology.

Realizing its overarching potential in achieving digital transformation, leading organizations, such as Air New Zealand, have recently employed blockchain technology to manage 3D printing innovation. Despite the potential benefits, including the key role of blockchain as a supporting technology in Industry 5.0, these applications of blockchain technology in 3D printing are still at a nascent stage in practice and mostly limited to producer innovation. Additionally, 3D printing and blockchain technologies are often independently revolutionizing value capture and value creation, whereas the theoretical implications of their combined impacts on innovation management remain an underexplored domain. Limited digital transformation efforts have been made to employ blockchain technology to create a synergy between producer innovation and community innovation in relation to 3D printing innovation. To solve these issues, we introduce a novel concept, distributed ledger innovation platform (DLIP), which refers to a network of firms and individuals that create and capture value on a blockchain through digital transformation efforts. In this research, we draw upon transaction cost and social production theories to investigate the potential benefits of blockchain to solve the digital transformation challenges associated with 3D printing innovation. We utilize these perspectives to propose the concept of DLIP as a new governance structure for managing digital transformation activities with blockchain. Additionally, we examine illustrative digital transformation efforts via 3D printing innovation and applications of blockchain technology. Then, we present future research directions for innovation management scholars to investigate the benefits of DLIP in digital transformation efforts via 3D printing. We conclude by discussing the potential applications of DLIP to manage other enabling technologies of digital transformation, including big data, artificial intelligence, and the metaverse.

Crowdsourcing has become an increasingly popular way for marketers to conceive of and design new products. Promoting these with “designed by consumers” claims has proven highly effective in boosting innovation appeal and market success. However, beyond the appeal of the perceived similarity between co-contributors and customers (Dahl et al., 2015), little is known about the effectiveness of different communication strategies for crowdsourced products. Central to the current investigation is the crucial creative strategy decision about whether to show the co-contributor in the advertisements and the persuasive role of the co-contributor's level of physical attractiveness. The use of attractive sources is highly prevalent in standard advertisements and is known to have reliable positive effects in persuading consumers (Mello et al., 2020). In contrast, our research suggests that showing attractive co-contributors in advertisements for crowdsourced products undermines their unique appeal and can even backfire. Through a series of qualitative and experimental studies, we found that this effect results from two mechanisms: (1) negative persuasion knowledge, where consumers question whether the attractive source is the genuine co-contributor, and (2) disruption of the similarity appeal that typically makes crowdsourced products well-received. These findings not only advance our understanding of the effectiveness of “designed by consumers” claims but also contribute significantly to the broader communication and persuasion literature. Importantly, our findings provide managers with actionable strategies for maximizing the commercial success of crowdsourced products.

This article explores the microfoundational aspects of business model innovation (BMI) under conditions of rapid change caused by technological and regulatory disruptions. Based on empirical analysis of relevant industry incumbents, we address the following research question: How do key microfoundational elements, notably individual behaviors and organizational processes and design, interact to drive business model innovation? Despite its importance, little is known about this question. We explore the microfoundations of BMI via a multiple-case study method. We specifically investigate the interplay between microfoundational components at varying levels (individual, process, interaction, and organizational design) in three incumbent companies in Finland's power electricity sector. Theoretically, this article's contributions lie in examining the interaction mechanisms that drive the interplay between microfoundational elements at macro and micro levels during the different BMI stages. These mechanisms are critical for shaping interaction processes in BMI and supporting value creation and appropriation. For managers, our research provides a microfoundational framework for guiding BMI, including guidelines for critical tasks such as promoting a creative culture, enhancing cross-functional collaboration, balancing innovation with operational stability, aligning with industry trends, and preparing the organization for continuous innovation.

While today's society tends to prioritize problem solving and idea management, framing the problem is often more important than solving it. Problem framing is not a linear process; rather, it requires creativity and the ability to explore multiple dimensions of the problem. Scholars and practitioners increasingly recognize the value of “building the right things” and addressing the right problem, rather than “building things right” and addressing the wrong problem. In this context, understanding the process of problem framing and the role of creativity—characterized by the ability to navigate uncertainty and explore unconventional perspectives—has garnered attention across disciplines. Management, psychology, and the social sciences are among the fields in which researchers have examined the role of creativity in problem framing from three interrelated perspectives: business and organizational, cognitive, and social or relational. To gain a holistic understanding of these contributions, we conducted an integrative review of 188 academic papers, synthesizing the synergies and differences between the management, psychology, and social science communities of practice on problem framing and creativity. Our review identifies and integrates key concepts of the creative process of problem framing from these communities and organizes them into four constituents: (i) problem representations, (ii) activated knowledge, (iii) influencing stimuli, and (iv) creative logics. This integration forms the basis of the framework we present, which synthesizes insights across disciplines to redirect the innovation management debate. In addition to outlining a research agenda to guide future investigation and theorizing, our research provides practical insights into the temporal interactions of the constituents of the creative process of problem framing. These insights can help innovation managers not only navigate the dynamics and complexities of this process, but also foster more effective innovation.