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Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

The embedding of digital technology and the fuzzy organizational boundary have changed the operation of platform innovation ecosystem (PIE). Specifically, as an important energy of PIE, the internal logic of knowledge flow needs to be reconsidered in the context of digital age, which will be helpful to select the cultivation and governance strategy of PIE.

A dual case-analysis is applied to open the “black box” of knowledge flow in the PIE from the perspective of enabled by digital technology, by taking the intellectual property (IP) operation platform as cases.

The research findings are as follow: (1) The knowledge flow mechanism of PIE is mainly demonstrated through the processes of knowledge acquisition, knowledge integration and knowledge spillover. During this process, connectivity empowerment and scenario empowerment realize the digital empowerment of the platform. (2) Connectivity empowerment provides a channel of knowledge acquisition for the digital connection between participants in PIE. In the process of knowledge integration, scenario empowerment improves the opportunities for accurate matching and collaborative innovation between knowledge supplier and demander, and enhance the value of knowledge. The dual effect of connectivity empowerment and scenario empowerment has accelerated the knowledge spillover in PIE. Particularly, connectivity empowerment expands the range of knowledge spillover, and scenario empowerment affects the generativity of the platform, resulting in the enhancement of platform’s capability to embed and expand its value network. (3) Participants have been benefitted from the PIE enabled by digital technology through three key modules (knowledge acquisition, knowledge integration and knowledge spillover), as the result of knowledge flow.

This study focuses on the knowledge flow mechanism of PIE enabled by digital technology, which enriches the PIE theory, and has enlightenments for the cultivation of digital platform ecosystem.

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

Digital service innovation (DSI) is a type of technological innovation that is recognized in practice in the innovation structure of companies. Given the breadth of digital technologies that enable digital services and the variety of these services, analysis is needed to discern the nature of these services, as well as the process that culminates in co-innovation. The literature on DSI is fragmented and spread across multiple research areas. This fragmentation impedes conceptualization of the elements that constitute DSI. This paper describes the nature of DSI through the process and elements of initiation, adoption and routinization of DSI in the context of digital service platforms (DSPs).

This paper presents a single exploratory case study of a provider of a leading digital solution in customer relations. The data analysis is based on abductive reasoning.

The paper conceptualizes the nature of DSI and describes the process and elements of DSI (phases, actors, functions and interactions). It contributes to building a common language for DSI research in service management. The analysis shows that DSI in DSPs is synonymous with co-innovation. This paper offers insight into how co-innovation occurs, using hybrid agile methodologies with the coordination of multiple actors and multilateral interactions.

The originality and value of the study reside in its conceptualization and analysis of what is meant by DSI. The components of the service and the technological requirements for not only provision but also ideation and development appear to be inseparable. The study unveils the mechanisms that turn a digital service solution into a co-innovative proposal. This knowledge can facilitate scalability in digital services.

Quite often than not, a new industry can be created, thanks to the countless entrepreneurs and innovative activities across the globe. Smart city (SC) is one such industry and a living lab using the key roles of the digital platform that enable a seamless flow of information and knowledge for innovation within the SC. The purpose of this paper is to illustrate how SC can be a new regional industry engine through an “open collective innovation system” as its new concept. In particular, SC provides efficient transaction costs and knowledge flows. Eventually, SC can be an innovation hub for entrepreneurship through openness.

To frame the research goals, the authors used qualitative research methodologies based on grounded theory. In particular, the author used inductive reasoning to generate arguments and conclusions about the future of an SC as a new growth engine in the era of the fourth industrial revolution. Numerous documents and prior literature were used for the preliminary conceptualization of an SC. Interview data were then coded for reasoning in an open collective innovation system based on “openness”.

SC maximizes efficiency in practicing innovation. In the perspective of innovation costs, SC can minimize transaction costs, specifically the information processing costs, through data openness. In this context, transaction costs can be considered an economic equivalent of friction in a physical system. So, as the friction is low, some movements of an object on the surface are likely to be easy. SC is optimized for innovation activities through an “open collective innovation system”. In terms of innovation networks, an SC results in an innovation efficiency derived from both the network and the spatial agglomerations in physical and cyberspace. The efficiency-based SC itself overlaps knowledge creation, dissemination and absorption, providing an open innovation (OI) ecosystem.

This paper remarkably extends that SC can be an “open collective innovation system model” and a new conceptualization. Eventually, SC will play a crucial role in developing regional industries as a new growth engine. To operate as a new growth engine fully-fledged, the SC is needed to accumulate innovative assets such as the critical mass of residents, numerous firms, etc. However, this study has some limitations. First, difficulties in any analytic approach to SC resulted from their many interdependent facets, such as social, economic, infrastructural and spatial complex systems, which exist in similar but changing forms over a huge range of scales. Also, this research is at a quite an early stage. Thus, its theoretical stability is weak. So, this paper used the qualitative methodology with a grounded theory. Another limitation is in the research methodology. The limitation of using grounded theory adapted by this work is that the results of this study may not be generalizable beyond the context of this study. This non-generalizability occurs because ours is an inductive approach to research, meaning that the findings are based on data collected and analyzed. As such, the results of this study may not be applicable to other contexts or situations. In addition, the analysis of data in the grounded theory is based on researcher’s subjective interpretations. This means that the researcher’s own biases, preferences and assumptions may influence the results of the study. The quality of the data collected is another potential limitation. If the data is incomplete or of poor quality, it can cause researcher’s own subjective interpretations.

Findings of this study have some practical implications for enterprises, practitioners and governors. First, firms should use value networks instead of value chains. Notably, the firms that pursue new products or services or startups that try to find a new venture business should take full advantage of SC. This taking advantage is possible because SC not only adapts state-of-the-art information technology (e.g. sensor devices, open data analytics, IoT and fiber optic networks) but also facilitates knowledge flow (e.g. between universities, research centers, knowledge-based partner firms and public agencies). More importantly, with globalized market competition in recent years, sustainability for firms is a challenging issue. In this respect, managers can take the benefits of SC into consideration for strategic decisions for sustainability. Specifically, industrial practitioners who engage in innovation activities have capabilities of network-related technologies (e.g. data analysis, AI, IoT and sensor networks). By using these technologies in an SC, enterprises can keep existing customers as well as attract potential customers. Lastly, the findings of this study contribute to policy implementation in many aspects. At first, for SC to become a growth engine at regional or natural levels, strong policy implementation is crucial because SC is widely regarded as a means of entrepreneurship and an innovation plaza (Kraus et al., 2015). To facilitate entrepreneurship, maker spaces used for making the prototypes to support entrepreneurial process were setup within universities. The reason for establishing maker spaces in universities is to expand networking between entrepreneurs and experts and lead to innovation through a value network. One of the policy instruments that can be adapted is the “Data Basic Income Scheme” suggested by this research to boost the usage of data, providing content and information for doing business. Also, a governor in SC as an intermediator for the process of the knowledge flow should initiate soft configuration for SC.

This work makes two theoretical contributions to OI aspects: (1) it explores dynamic model archetypes; and (2) it articulates and highlights how SC with digital technology (i.e. in the AI, IoT and big data context) can be used to create collective knowledge flow efficiently. First, the findings of this study shed light on the OI dynamic model. It reveals important archetypes of new sub-clustering creation, namely, a system that underpins the holistic process of innovation by categorization in amongst the participating value network (Aguilar-Gallegos et al., 2015). In innovation studies, scholars have particularly paid attention to a cluster’s evolution model. In the process of innovation, the “open innovation dynamic model” suggested by this study illustrates sub-clustering that happens in value networks by taking the benefits of SC. Eventually, the evolution or development of sub-clusters can bring in a new system, namely, an OI system. Second, the findings of this study contribute to the understanding of the role of digital technologies in promoting knowledge flow. The usage and deployment of digital technologies in SC may enormously and positively influence innovative activities for participants. Furthermore, the rising of digital economy, in the so-called platform business, may occur depending on advanced technologies and OI. In doing so, the findings can further tow innovation research through juxtaposition between SC and innovation research (Mehra et al., 2021).

This paper shows that the function of an SC not only improves the quality of life but also acts as an engine of new industry through an open collective innovation setting using dynamic and ecological models.

This article investigates the practical implementation of the ecosystem approach in different branches of public management within an urban context. It explores how ecosystem thinking is introduced, disseminated and applied in a local government organization.

We utilize a qualitative case study methodology, relying on official documents and expert interviews. Our study focuses on the city of Espoo, Finland, which has actively embraced ecosystem thinking as a fundamental framework for its organizational development for almost a decade.

The case of Espoo highlights elements that have not been commonly attributed to the ecosystem approach in the public sector. These elements include (1) the significance of complementary services, (2) the existence of both collaborative and competitive relationships among actors in public service ecosystems and (3) the utilization of digital platforms for resource orchestration. Our study also emphasizes the need for an incremental adoption of ecosystem thinking in organizational contexts to enable its successful implementation.

The study provides valuable insights into the introduction and dissemination of ecosystem thinking in public management. It also further develops previously developed hypotheses regarding public service ecosystems.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.

A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.

While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.

The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.

The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.