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Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

This study explores the influence of the Top Management Team (TMT) social capital on business model innovation in business ecosystems.

This study examines the impact of internal and external TMT social capital on enterprises’ business model innovation, explores the relationship between internal and external TMT social capital, and investigates how business ecosystem health moderates the relationship between external TMT social capital and enterprises’ business model innovation. These hypotheses are proposed and tested using a hierarchical regression analysis with data from 168 Chinese firms.

First, both internal and external TMT social capital exert a significantly positive influence on an enterprise’s business model innovation. Second, internal TMT social capital positively contributes to the development of external TMT social capital, affecting business model innovation. Finally, the moderating effect of business ecosystem health on the relationship between external TMT social capital and business model innovation depends on the dimensions. Specifically, the productivity of the business ecosystem negatively moderates this relationship, whereas the niche creation capability of the business ecosystem has a positive moderating effect.

These findings enrich prior research on business model innovation within the business ecosystem, thoroughly exploring the critical role of TMT social capital. This study reveals the diverse impacts of internal and external TMT social capital on business model innovation and the intricate relationship between these elements. Furthermore, it emphasizes that the success of enterprise’s business model innovation within a business ecosystem depends on the alignment and adaptation to dynamic ecosystem conditions. By presenting these insights, this study provides valuable practical implications for enterprises aiming to cultivate social capital within business ecosystem to facilitate business model innovation.

This study aims to understand their emergence and types of business models in the Internet of Things (IoT) ecosystems.

The paper builds upon a systematic literature review of IoT ecosystems and business models to construct a conceptual framework on IoT business models, and uses qualitative research methods to analyze seven industry cases.

The study identifies four types of IoT business models: value chain efficiency, industry collaboration, horizontal market and platform. Moreover, it discusses three evolutionary paths of new business model emergence: opening up the ecosystem for industry collaboration, replicating the solution in multiple services and return to closed ecosystem as technology matures.

Identifying business models in rapidly evolving fields such as the IoT based on a small number of case studies may result in biased findings compared to large-scale surveys and globally distributed samples. However, it provides more thorough interpretations.

The study provides a framework for analyzing the types and emergence of IoT business models, and forwards the concept of “value design” as an ecosystem business model.

This paper identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry, and argues that IoT business models follow an evolutionary path from closed to open, and reversely to closed ecosystems, and the value created in the networks of organizations and things will be shareable value rather than exchange value.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

This article aims to understand the dynamics between disruptive innovations and innovation ecosystems, using disruption business models as a catalyst.

This study presents an integrative literature review and a theoretical framework in order to integrate the theories of disruptions and ecosystems.

The dynamics of disruptive innovation, within an ecosystem, as an essential driver of creating new markets. The effect of creative destruction from a disruption influences business models in a coopetitive dynamic that drives the ecosystem as a whole.

Limited to theoretical research and suggested the application of the proposed model in an empirical study.

Understand the formation of new ecosystems based on the occurrence of a disruption as a way for organisations to prepare for the arrival of this new market.

The contribution of this study is based on joining the literature of disruptive innovation and innovation ecosystem, pointing to a theoretical framework and a flow of Evolution and Adaptation to the Disruptive Ecosystem that integrates this complex dynamic.

The time is right for a theory on strategic entrepreneurial ecosystems and business model innovation. Both topics have increased substantially during the past couple of years due to their strategic nature. This means they are uniquely placed to provide practical advice but also theoretical development. This chapter discusses the theory in terms of how it bridges strategic planning, innovation management, and entrepreneurship literature. Thereby propelling the field of entrepreneurial ecosystems further by suggesting it has both a strategic and business model perspective. This chapter argues the reasons for a new theory to be developed in order to maintain the relevance and practicality of the entrepreneurial ecosystem literature.

The paper provides a holistic overview of already available academic literature of mobile banking, business model innovation and ecosystem and activity system perspective of business model concepts. The purpose of this conceptual paper is to initiate a debate for future research in the agenda highlighted in this paper.

In this paper, mobile banking business ecosystem of Easypaisa is used as an illustrative case to understand mobile banking business model innovation in the context of business ecosystem and activity system perspective.

Based on Porter’s view of mobile financial service (MFS) industry, it is suggested that patterns of business model innovation can be explained through business ecosystem and activity system. The notion of business model innovation can also be explained through integrated value chain of mobile network operator and its partners in the supply chain of MFS.

This paper provides preliminary overview of the exiting academic literature on business model innovations, business ecosystem and activity system in the in the context of value network. Since this is only a literature review paper, therefore, no primary data have been collected for this case study through interviewing from the relevant people.

So far, no research has been conducted in Pakistan to address business model innovation in mobile banking sector in the context of business ecosystem and activity system perspective.

The purpose of this study is to identify and discuss the role of intelligent materials in the emergence of new business models based on the Internet of Things (IoT). The study suggests new areas for further research to better understand the influences of material intelligence on the business models in industry-wide service ecosystems.

The study uses data from an earlier study of intelligent materials in the steel industry networks. The insights are based on 34 qualitative interviews among 15 organizations in the industry. The data are reanalyzed for this study.

The observations from the steel industry show how material intelligence can be harnessed for value creation in IoT-based business ecosystems. The results suggest that not all “things” connected to the IoT need to be intelligent, if information related to the things are collected, stored and shared for collaborative value creation among the actors involved in the business ecosystem.

The study discusses how IoT deployments allow businesses to benefit from the velocity and variety of information associated with things and guides future research to study the ways in which value is created through IoT-enabled business models.

Rather than focusing on improving the efficiency of the supply network, the study presents new paths for competitive advantages in the new IoT ecosystems.

The study contributes to the mounting research on the IoT by identifying and discussing the critical aspects of how IoT can transform business models and supply networks within end-to-end ecosystems.

Fundamental changes in economic relations, instability of the market environment in which enterprises operate and increased intensity of competitive influences to obtain better business conditions emphasize the importance of the nature of interaction for all participants of business processes in the distribution channel and the success of the chosen business structure. This circumstance determines the expansion of the content of the ecosystem approach to the organization of enterprise activities and the clarification of the participants' roles in such systems. The purpose of the study is to identify the key features and differences in business models of digital ecosystem participants that are critical to shaping the value of the distribution system.

In this paper, within the framework of the theoretical component, the authors analyze conceptual and empirical articles contained in the Web of Science database and also rely on information obtained from the study of articles by Russian academicians in specialized journals, monographs and conference abstracts. Using the method of content analysis, data on enterprises were collected and generalized into cases, which made it possible to propose possible classification properties of enterprise archetypes within the digital ecosystem and to determine the general properties of the objects under study and their interrelations.

The systematization of results allows us to present a co-competitive activity model for ecosystem participants, depending on their archetype, where they are segmented according to the dominant principle of role and activity within the system. From a practical point of view, the considered classification of the archetypes of recipient enterprises and their economic relations make it possible to structurally visualize a digital ecosystem, which significantly reduces the distance between the consumer of the product/service, the manufacturer and the seller. This reduces the time of delivery and waiting as well as the time to find a suitable option making the market more perfect. The proposed conceptual framework indicates the interdependence of the development of all participants in the product distribution and proves that successful business models take part in the market expansion. Finally, the authors' systematic review of the academic literature results in identifying certain promising directions for future research based on the consideration of open ecosystems with transparent infrastructure.

The results are limited by the authors' sample data and the case study approach. The study does not show the further evolution of the digital ecosystem depending on the set and configurations of ecosystem participants. The authors introduce a possible new classification of archetypes of ecosystem participants and a co-competitive activity model for ecosystem participants depending on these archetypes.

From a practical point of view, the considered classification of the archetypes of recipient enterprises and their economic relations make it possible to structurally visualize a digital ecosystem, which significantly reduces the distance between the consumer of the product/service, the manufacturer and the seller.

From a practical point of view, the considered classification of the archetypes of recipient enterprises and their economic relations makes it possible to structurally visualize a digital ecosystem, which significantly reduces the distance between the consumer of the product or service and the manufacturer or the seller. This reduces the time of delivery and waiting as well as the time to find a suitable option making the market more perfect in this respect.

經濟關係作根本性的變化、企業營運的市場環境日趨不穩定、以及為求達致更好的經營狀況，企業不得不面對日益劇烈的競爭，這都清晰顯示了在分銷渠道內、業務過程中，所有參與者之相互作用的性質是必須重視的。同樣地，被採用的企業結構之成效也不可忽視。這情況就決定了企業在如斯的系統裏，對其經營活動的籌劃及參與者角色的闡明會擴大其生態系統方法的內容。本研究擬確定數位生態系統參與者的各商業模式之主要特點及不同之處；而這些商業模式，對分配系統價值之塑造、至關重要。

在本文中，我們在理論成分的框架裏，分析在Web of Science 資料庫內概念性和實徵性的文章。我們使用的資料，亦包括取自俄國院士在專業期刊、專著和會議摘要內發表的學術論文。研究人員透過內容分析，收集關於企業的數據，並概括為案例；這樣，研究人員就可以在數位生態系統裏提出企業原型可能的分類屬性，以及能夠判斷研究對象的一般屬性及它們之間的相互關聯。

研究結果之系統化，讓我們能夠依賴生態系統參與者的原型，為它們展示一個共同競爭活動模型，而在這模型裏，它們會根據在系統內作用和活動的主導原則而被分割。從實際的角度來看，因受援企業的原型及其經濟關係得到分類，故數位生態系統的結構可被形象化，這可大幅縮短商品或服務的消費者、製造商和銷售者三者之間的距離；這可減少交貨和等候的時間，以及尋找合適選擇所需的時間，使市場更趨完善。被提出之概念性框架顯示了在產物分佈上，所有參與者的發展是相互依賴的；同時，亦證實了成功的商業模式在市場擴展上擔當著一定的角色。最後，我們詳盡而有系統的學術文獻探討，確定了今後研究的某些合適方向，這都是建基於對擁有透明基礎設施的開放生態系統之研究。

研究結果因樣本數據以及採用了個案研究法而有其局限，研究沒有顯示數位生態系統如何依賴生態系統參與者的設置和配置而進一步進化。我們引進一個生態系統參與者原型的可能新分類，以及仗賴這些原型，為生態系統參與者介紹一個共同競爭活動模型。

從實際的角度來看，因受援企業的原型及其經濟關係得到分類，故數位生態系統的結構可被形象化，這可大幅縮短商品或服務的消費者、製造商和銷售者三者之間的距離。

從實際的角度來看，因受援企業的原型及其經濟關係得到分類，故數位生態系統的結構可被形象化，這可大幅縮短商品或服務的消費者、製造商和銷售者三者之間的距離；這可減少交貨和等候的時間，以及尋找合適選擇所需的時間，使市場就此而言更趨完善。

There is a knowledge gap regarding the determinants of open innovation processes and outcomes in a joint value creation context, as well as what role artificial intelligence (AI) and data management play in facilitating open innovation processes. One strategy to better understand joint value creation through open innovation, supported by AI and data management, is to conduct studies on the digital business ecosystem (DBE). The purpose of this paper is to improve our current knowledge of this urgent issue in contemporary management through the lens of an ecosystem-based theory by conducting an empirical study on two DBEs (called ecosystem micro-communities (EMCs)), developed by Haier, as well as multiple literature reviews on the key concepts “Haier EMC” and “digital business ecosystem”.

By building on multiple literature reviews and empirical data from a multi-year and ongoing research program driven by Haier, this study examines Haier’s EMC model for AI-driven DBEs. Secondary data were collected through iterative literature reviews on DBEs, the EMC concept and the two selected EMC cases. The empirical data were collected through a qualitative study of two Haier EMCs in China.

Haier's ecosystem micro-community concept represents a radical shift towards a more flexible, responsive and innovative cross-industry organizational structure, offering valuable lessons for business leaders and scholars. Haier’s ecosystem micro-community model, part of their RenDanHeYi philosophy and here viewed as a DBE, is a pioneering management concept that not only redefines the management of the firm and the traditional corporate structure, but also the traditional view on innovation management, business strategy, human resource management and marketing (customer centricity). The concept has therefore an important and big impact on traditional management. For scholars, the gap in understanding innovation processes in open business ecosystems is addressed by the concept. However, the concept also opens new areas for academic research, particularly in innovation management, business strategy, human resource management and marketing. The concepts further encourage more interdisciplinary research.

The DBE is a relatively new research area that will need more research. While the EMC model is promising as an effective version of a DBE, its effectiveness across different industries and organizational cultures needs to be explored further. Future research should investigate its applicability and impact in diverse business environments. To understand the EMC’s long-term impact, longitudinal studies are needed. These should focus on the sustained competitive advantages, potential market disruptions and the evolution of customer value propositions over time. Finally, considering increasing concerns about data privacy and security, future research should also explore how DBEs solve the issue of data protection and IP while promoting open innovation and value sharing.

For managers and practitioners, the EMC concept could inspire leaders to learn how to foster innovation by creating smaller, autonomous teams that can respond quickly to market changes in the form of a DBE. The concepts exemplify how value creation and capture could be enhanced for any company and even could be a new strategy in the company’s digital transformation and repositioning into a more competitive, high-end player on the market. The concept also emphasizes employee empowerment and ownership, which can lead to higher job satisfaction and retention rates. The concept can further improve companies’ adaptability and resilience by decentralizing decision-making. Finally, the micro-communities allow businesses to be more customer-centric, developing products and services that better meet specific customer needs.

The social implications could be positive, as complex social problems commonly need an ecosystem approach to develop and deliver impactful solutions. In addition, Haier’s ecosystem micro-community model seems inherently scalable and culturally adaptable.

Haier’s EMC model is well-known in the research literature and is a novel approach to DBEs, which has been proven successful and replicable in different countries and industries. Providing insights from multiple literature reviews and two unique Haier EMC cases will contribute to a better understanding of highly effective data- and AI-driven business ecosystems, as well as of determinants of open innovation processes and outcomes in a joint value creation context, as well as what role AI and data management play in facilitating open innovation processes.