Innovation Management Research Research Articles

Analytic Hierarchy Process Optimization of Strategic Resource Management for Sustainable Development: Enhancing International Economic and Commercial Relations through Circular Economy Factors in Open Socio-Economic Systems

This article explores how the Analytic Hierarchy Process (AHP) can optimize strategic resource management for sustainable development, emphasizing circular economy factors in open socio-economic systems. A thorough literature review links existing research in financial security, innovation, and risk management to illustrate the significance of integrating environmental considerations into long-term resource allocation. The proposed AHP framework decomposes complex decision-making into a hierarchical structure that includes both quantitative metrics, such as financial stability and waste reduction, and qualitative concerns, like stakeholder engagement and regulatory compliance. Expert evaluations highlight the primacy of environmental and circular economy factors in resource management, closely followed by financial and risk considerations. Waste reduction, resource reuse, and supply chain resilience emerge as top-ranked sub-criteria, underscoring the importance of balancing ecological imperatives with economic viability. The study further highlights digital transformation as an essential enabler of real-time analysis and adaptive resource allocation. Integrating these insights within a broader policy and managerial context offers a roadmap for enhancing international economic and commercial relations, especially in turbulence-prone global markets. The findings suggest that holistic, multi-criteria decision-making—supported by AHP—provides a robust pathway toward sustainable development, promoting resilience and competitiveness in open socio-economic systems.

Sustainable innovations through project partnerships at higher education institutions: challenges and implications for stakeholder engagement

PurposeThe purpose of this study is to identify challenges and derive options for stakeholder engagement of project partnerships for sustainable innovations in higher education institutions (HEIs).Design/methodology/approachGuided by Donabedian’s structure-process-outcome (SPO) model, our conceptual exploration focuses on understanding stakeholder experience and identifying stakeholder engagement options in different project phases. This research includes empirical data on sustainability expectations towards HEIs collected from 239 business students from the USA and Germany. The Kano method and factor analysis were used for data analysis.FindingsThis research suggests that balancing differences in stakeholder types and priorities, identifying and fulfilling key stakeholder expectations and addressing their resource limitations play a crucial role in the partnership’s structure stage. Adjustments for timing and forms of engagement, based on the stakeholder types and their expectations, are necessary during the process stage. Attaining stakeholder consensus on goal achievement and fostering trust and long-term commitment for sustainability are vital tasks in the outcome stage.Practical implicationsHEIs are advised to identify and assess stakeholders according to their anticipated inputs and contributions to the expected project outputs. They should consider adopting minimal thresholds of involvement and actively engaging key stakeholders, students, by demonstrating direct sustainability impacts.Originality/valueThis conceptual study adds value by enhancing the understanding of sustainable project partnerships in HEIs through the adoption of concepts from open innovation, service management and relationship management research. It illuminates the significance of stakeholder engagement and experience, including the management of expectations, thereby supporting HEIs in effectively implementing sustainability initiatives.

Fueling innovation management research: Future directions and five forward‐looking paths

AbstractResearch about innovation management explores how the future is created—who is creating it (organizations, collaborations, etc.), for what aims (customer satisfaction, market performance, etc.), and with what broader effects (social, environmental, etc.). With this extended essay, we explore the potential futures of innovation management research in three ways. First, we briefly review the history of past research agendas and priorities published in the Journal of Product Innovation Management (JPIM), highlighting three broad topic areas (technological, social/environmental, and organizational) that have emerged over time and their potential disruptive implications for innovation management research. Second, we describe the outcome of a gathering of leading scholars in innovation management tasked with the challenge of identifying critical research paths for our field. This collaboration resulted in five “deep dive” essays into areas ripe for innovation management research in the years ahead: liquid innovation, artificial intelligence in innovation, business model innovation, public value innovation, and responsible innovation. Third, we reflect on this expansive effort and offer a discussion of implications (tensions, challenges, and opportunities) for future innovation management scholarship.

Commentary: Company Innovativeness: A Radically New Perspective on an Old Concept

The article highlights misconceptions around the concept of innovativeness and argues for a broader understanding that encompasses both inward and outward-looking perspectives. It emphasizes the importance of perceived innovativeness as influenced by marketing, innovation culture, leadership, and emotional connection with customers. This customer-centric viewpoint not only offers a fresh lens through which to evaluate firm innovativeness but also underscores its significant implications for innovation management and future research directions.

Open innovation at the digital frontier: unraveling the paradoxes and roadmaps for SMEs' successful digital transformation

PurposeThe purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?Design/methodology/approachUsing Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.FindingsThe findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.Originality/valueThis paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

Data-push innovation beyond serendipity: The case of a digital platform making Earth Observation data fit into multiple use contexts

The potential of data to circulate across organizations and sectors and stimulate innovation in multiple contexts has been largely acknowledged by practitioners and researchers. This has given rise to a specific form of innovation strategy, “data-push innovation”, which consists of stimulating the use of existing data by third-party actors. However, how to manage such a strategy remains challenging. The paper explores this question by examining the longitudinal case study of an actor that has successfully stimulated the use of Earth observation data by multiple actors over the last 40 years. The paper offers several contributions to research in information systems and innovation management. First, the paper shows that data-push innovation can be fostered through the intentional design of a so-called “fit system” allowing data to be used in multiple contexts. Such a fit system can be built as a generic system, following similar “generification” strategies as those supporting platform or software development but with original patterns to adapt to the specificities of data-push innovation. Second, the paper characterizes the types of “boundary resources” needed to support this process. These boundary resources especially have a two-way resourcing function: they help third-party actors contribute to the fit system development, but they also allow the fit system owner to identify the knowledge boundaries preventing data from gaining meaning in new contexts. Third, the paper reveals an intriguing form of localized and nondominant platform leadership, focusing on gaining generative power rather than controlling power over the platform ecosystem.

Preface: 2023 International Conference on Innovation Management, Psychology, Education and Sociology (IMPES 2023)

The 2023 International Conference on Innovation Management, Psychology, Education and Sociology (IMPES 2023) was held during December 09-10, 2023 in Sapporo, Japan. The main objectives of the conference are to promote research and development activities in innovation management, social psychology, educational technology, cultural studies, social policy, and sociology. Another goal is to promote the exchange of scientific information among researchers, developers, students, and practitioners around the world. IMPES 2023 can be a scientific forum to accommodate fruitful discussion among international researchers in various fields. We would like to thank all speakers, invited guests, and also other parties and donors for their continuous support to the success of this event. Hopefully, this event provides many benefits for us all.
 Conference Organizing Chair
 Sapporo, Japan

An Exploration of Hackathons as Time Intense and Collaborative Forms of Crowdsourcing

Crowdsourcing has attracted increasing attention as an open innovation tool that enables firms to access the ideas and solutions of external crowds of participants. Among various crowdsourcing formats, hackathons have emerged as a form of collaborative crowdsourcing that emphasizes team-based collaboration among participants to co-create solutions to firms’ challenges under intense time pressures. Despite their increasing popularity, limited focus has been placed on understanding how hackathons should be organized and managed and the challenges that these time-intense collaborative events generate for both firms and participants. Based on a qualitative, multiple case study of six on-site hackathons, we identify and discuss four key design practices that shape these collaborative crowdsourcing forms, namely 1) problem formulation; 2) participant attraction and team composition; 3) developing the evaluation system; and 4) facilitating idea development. We show that these design practices are interrelated, with decisions about one design practice having important implications for the others, and discuss key challenges that arise from their combination. Overall, our findings highlight how organizing and managing hackathons is a complex matter that requires firms to adopt a more holistic and complementary approach. Implications for innovation management research and practice are discussed.

A Machine Learning-Based Approach to Identifying Key Innovation Determinants for Industrial Firms: The Case of the Pharmaceutical Industry in China

With abundant resources consumed by innovation practices, it is of strategic importance for industrial firms to identify key determinants of innovation performance from both internal and external environments for better and effective innovation management. To this end, this article develops a new machine learning-based approach to examine a variety of factors influencing innovation performance. In particular, a two-process modeling approach is developed to build machine learning models efficiently for identifying key internal and external innovation factors. With extensive experiments using data collected from China's pharmaceutical industry, the approach identifies a set of key internal and external innovation factors and their best configurations in terms of two commonly used innovation performance measures. The findings enable pharmaceutical firms and local governments in China to manage innovation efforts and formulate management strategies for promoting industrial innovation. The article contributes to innovation management research by providing an objective and data-oriented approach for comprehensively exploring internal and external innovation factors and establishing their relationships with expected innovation performance. Although the approach is exemplified by China's pharmaceutical industry and the results cannot be generalized, it has general applicability to other industries or countries.

The Triple Helix Model and Working with Loet Leyesdorff

Abstract This article is a reflection on the enormous debt that I owe Loet for his kindness, generosity and intellectual mentorship. This is over a period of some twenty years. Loet also became part of the Centre for Innovation Management Research (CIMR) at Birkbeck, University of London. In one of our final articles together, Loet drew the different stands of his work together by exploring synergies in scholarship of members of CIMR.

Places and spaces of collaborative R&D and innovation: navigating the role of physical and virtual contexts

The context in which collaborative R&D and innovation activities take place is a critical driver of success and failure. However, innovation management research tends to often abstract the context away, leaving the crucial contingency factors unaddressed. This special issue explores multifaceted collaborative R&D and innovation contexts across physical and virtual domains. An array of ten articles dissect various contexts, including cross‐sector partnerships, innovation hubs, living labs, makerspaces, and virtual collaboration spaces and communities, highlighting their impact on innovation processes and outcomes. In this editorial, we develop a ‘Collaborative Innovation Space Matrix’ to firstly integrate the insights from the special issue focusing on collaboration dynamics and type of spaces and, secondly, to propose a call for action for innovation researchers to better understand the crucial role of context in collaborative R&D and innovation.

Examining the Mechanism of Political Knowledge on Radical Innovation Performance

Advancing fundamental innovation is among the most popular topics in innovation management research in China in recent years; however, previous research has paid limited attention to the impact of political connections on radical innovation, particularly lacking proper explorations regarding the influence of political knowledge on radical innovation. Exploring the influence of political knowledge on breakthrough innovation from a strategy selection perspective, this study examines the mechanisms of influence, determining that two factors of strategic choice have a partial mediating role. This study presents a novel approach to further explore radical innovation from the perspective of new political knowledge.

The AI‐augmented crowd: How human crowdvoters adopt AI (or not)

AbstractTo date, innovation management research on idea evaluation has focused on human experts and crowd evaluators. With recent advances in artificial intelligence (AI), idea evaluation and selection processes need to keep up. As a result, the potential role of AI‐enabled systems in idea evaluation has become an important topic in innovation management research and practice. While AI can help overcome human capacity constraints and biases, prior research has identified also aversive behaviors of humans toward AI. However, research has also shown lay people's appreciation of AI. This study focuses on human crowdvoters’ AI adoption behavior. More precisely, we focus on gig workers, who despite often lacking expert knowledge are frequently engaged in crowdvoting. To investigate crowdvoters' AI adoption behavior, we conducted a behavioral experimental study (n = 629) with incentive‐compatible rewards in a human‐AI augmentation scenario. The participants had to predict the success or failure of crowd‐generated ideas. In multiple rounds, participants could opt to delegate their decisions to an AI‐enabled system or to make their own evaluations. Our findings contribute to the innovation management literature on open innovation, more specifically crowdvoting, by observing how human crowdvoters engage with AI. In addition to showing that the lay status of gig workers does not lead to an appreciation of AI, we identify factors that foster AI adoption in this specific innovation context. We hereby find mixed support for influencing factors previously identified in other contexts, including financial incentives, social incentives, and the provision of information about AI‐enabled system's functionality. A second novel contribution of our empirical study is, however, the fading of crowdvoters’ aversive behavior over time.

An Innovation Ecosystem Game Study: The Role of Noncontractual Mechanisms

Innovation ecosystem management is now a new paradigm in innovation management research. Innovation ecosystems are dynamic innovation alliances based on noncontractual governance. In this paper, a traditional cooperative innovation game model and a cooperative innovation game model with noncontractual mechanism are developed and compared. The results show that the cooperation formed only by contractual mechanisms’ model is unstable and the system is likely to collapse. The noncontractual mechanism can be used as a supplement to the contractual mechanism to make the game develop towards a stable “cooperation-cooperation” state. The research conclusion of this paper will make the core companies in the innovation ecosystem realize the important role of noncontractual mechanism and help them make decisions.

Preface: 2nd International Conference on Art Design, E-Education and Innovation Management (ADEIM 2023)

The 2023 2nd International Conference on Art Design, E-Education and Innovation Management (ADEIM 2023) was resoundingly held at Canberra, Australia from September 16 to 17, 2023. It highlights recent and significant advances in research and development in art design, e-education, educational reform, humanities, innovation management, and social sciences.
 With participation of a large number of young researchers, ADEIM 2023 can be a platform for new collaborative ventures and strategic alliances to gain better insights into research and innovation, to harness the strength and synergies, and to bring further prosperity to the nations. As the future becomes more competitive and challenging, it is important to remain relevant and maintain the performance for continuous improvement in research & education. It will also serve to facilitate the exchange of information between researchers and professionals to discuss the latest issues and advancement in these areas.
 ADEIM 2023 brought together experts from different organizations to initiate discussions on topics that are of interest to the conference attendees. This conference encourages young researcher from multi-discipline background to share their new and innovative ideas and findings is the aim of the conference.
 ADEIM Organizing Committee
 Canberra, Australia

Business model innovation: Integrative review, framework, and agenda for future innovation management research

AbstractThe business model innovation (BMI) concept has become a well‐established phenomenon of current academic research. While Foss and Saebi's (Journal of Management, 2017, 43, 200–227) seminal literature review on BMI revealed 349 articles on BMI published between 1972 and 2015, an additional number of 1727 articles on the topic have been published since 2016. In contrast to this overall interest in the BMI phenomenon, innovation‐focused journals include only a limited number of publications on BMI. Further, besides the valuable insights and fruitful research directions of extant literature reviews, they tend also to overlook the linkages between traditional innovation management and the majority of BMI research. Given this underrepresentation of BMI research in the innovation management literature, we conduct an integrative literature review to bring the disconnected literature closer together and offer directions for future research. Our literature review applies the review strategy of blending and merging the literature across domains. First, we blend the knowledge base of the BMI domain by applying the Product Development and Management Association (PDMA) Body of Knowledge categories. Second, we merge the literature across domains by developing an integrative framework. As recent BMI literature increasingly converged to two lines of research, our framework differentiates between the relatedness of the BMI and BMI openness. Thereby, we offer new avenues for future research that can enrich the dialogue on BMI research in the innovation management community. These results demonstrate how the BMI domain covers aspects that fit, contribute to, and extend classical innovation‐focused research, how both research domains can be merged to enrich each other, and how future research can foster the dialogue across disconnected domains.

Green Innovation Culture: Traceability Path, Current Research and Future Prospects

One of the most important topics in international innovation management research in recent years has been the new technological breakthroughs that many organizations are using to solve the technical challenges of "green performance". However, the existing studies have been focusing on green, ecological, product and technology perspectives to explore sustainable green strategies and build up core competencies globally, but they have always neglected the efficient path of innovation from the spiritual level to help green, which in turn has led to the failure of green innovation culture to be implemented and effectively guide the practice. In view of this, this paper analyzes the current research status of green innovation culture based on literature review and reveals the tracing path of green innovation culture. Finally, this paper makes a prospective view to provide important theoretical and practical guidance for promoting the in-depth study of green innovation culture.

Organizational knowledge heterogeneity: Between conceptual nuances and the quest for a measure

AbstractThis paper is a survey of relevant empirical literature pertaining to knowledge heterogeneity. Its purpose focuses on highlighting issues surrounding its definition and measurement. First, it shows that knowledge heterogeneity is definitionally close to several other concepts, each measured in a certain way. Second, the same measures have been used indiscriminately for several of these concepts. Third, different measures have been used for the same concepts. The point being made is that comparable empirical results cannot be achieved if the same measures are used for different concepts. Research in knowledge management and innovation management centered around knowledge heterogeneity could be impeded if different emphases are put on different words while studying a concept that is defined similarly across studies yet measured differently, or that is measured similarly despite being defined differently. Results in future research are more likely to converge if knowledge heterogeneity is defined separately from similar concepts such as knowledge sharing and knowledge overlap, for example.

From the Editors: Engaging with generative artificial intelligence technologies in innovation management research—Some answers and more questions

Journal of Product Innovation ManagementEarly View EDITORIAL From the Editors: Engaging with generative artificial intelligence technologies in innovation management research—Some answers and more questions Jelena Spanjol, Corresponding Author Jelena Spanjol [email protected] Institute for Innovation Management, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany Correspondence Jelena Spanjol, Institute for Innovation Management, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany. Email: [email protected]Search for more papers by this authorCharles H. Noble, Charles H. Noble Department of Marketing, University of Tennessee Knoxville, Knoxville, Tennessee, USASearch for more papers by this author Jelena Spanjol, Corresponding Author Jelena Spanjol [email protected] Institute for Innovation Management, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany Correspondence Jelena Spanjol, Institute for Innovation Management, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany. Email: [email protected]Search for more papers by this authorCharles H. Noble, Charles H. Noble Department of Marketing, University of Tennessee Knoxville, Knoxville, Tennessee, USASearch for more papers by this author First published: 20 June 2023 https://doi.org/10.1111/jpim.12689Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL REFERENCES Bouschery, S. G., V. Blazevic, and F. T. Piller. 2023. “Augmenting Human Innovation Teams with Artificial Intelligence: Exploring Transformer-Based Language Models.” Journal of Product Innovation Management 40(2): 139– 53. COPE (Committee on Publication Ethics). 2023. “Guest Editorial: The Challenge of AI Chatbots for Journal Editors.” February 23, 2023 https://publicationethics.org/news/challenge-ai-chatbots-journal-editors Kasneci, E., K. Seßler, S. Küchemann, M. Bannert, D. Dementieva, F. Fischer, Urs Gasser, et al. 2023. “ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education.” Learning and Individual Differences 103: 102274. Korneeva, E., T. O. Salge, T. Teubner, and D. Antons. 2023. “Tracing the Legitimacy of Artificial Intelligence: A Longitudinal Analysis of Media Discourse.” Technological Forecasting and Social Change 192: 122467. Noble, Charles H., and Jelena Spanjol. 2019. “Opening Thoughts from the New Editors.” Journal of Product Innovation Management 36(1): 2– 4. Peres, R., M. Schreier, D. Schweidel, and A. Sorescu. 2023. “On ChatGPT and beyond: How Generative Artificial Intelligence May Affect Research, Teaching, and Practice.” International Journal of Research in Marketing 40(2): 269–75. Roose, Kevin. 2023. “A.I. Poses ‘Risk of Extinction,’ Industry Leaders Warn.” The New York Times, May 30 2023 https://www.nytimes.com/2023/05/30/technology/ai-threat-warning.html Staiman, Avi. 2023. Academic Publishers Are Missing the Point on ChatGPT https://scholarlykitchen.sspnet.org/2023/03/31/guest-post-academic-publishers-are-missing-the-point-on-chatgpt/ Štiglic, Gregor, and Roger Watson. 2023. Guest editorial: the challenge of AI chatbots for journal editors https://publicationethics.org/news/challenge-ai-chatbots-journal-editors The Editors. 2023. “Editorial: Tools Such as ChatGPT Threaten Transparent Science; Here Are our Ground Rules for their Use.” Nature 613: 612. Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation

TECH TO MARKET. FINDING AND DESIGNING SUITABLE TECHNOLOGY APPLICATIONS WITH DESIGN THINKING

AbstractAlthough it's human centered focus, design thinking has proven to be effective also in technology-driven projects, both in education and business. Yet, scant research has investigated whether and how design thinking might be leveraged to find new opportunities based on emerging technologies and design new innovation concepts accordingly. To address this gap, we employed an Action Innovation Management Research framework and co-designed a program called Tech to Market with Oper.Space, the design factory for Open Innovation of the University of Bologna. We ran 5 iterations of the program from October 2018 to December 2022, in which we conducted 52 interviews, observed 10 presentations, and held 10 meetings with the main stakeholders involved. Our results show how to apply design thinking to find and design a suitable application for a given technology, contributing to the ongoing conversation about the implementation of design thinking in technology-driven projects.