Search results

Ecosystem partnerships are driving a dramatic change in the nature of business as industries as diverse as banking, automotive and retail are converging in unprecedented ways–and at an unprecedented rate. To learn how leading companies are embracing innovation in ecosystems to drive both value creation and competitiveness, the IBM Institute for Business Value in collaboration with Oxford Economics surveyed 1000 top executives in 19 industries and 29 countries between August and January 2019.

The survey cohort included 250 Chief Executive Officers, 150 Chief Financial Officers, 150 Chief Innovation Officers, 150 Chief Marketing Officers, 150 Chief Operations Officer and 150 Chief Alliance/Partnership Officers.

Analysis revealed that organizations with high engagement in ecosystems generate greater revenues from innovation initiatives. Specifically, revenues tied to innovation were more than 14 percent higher for ecosystem-engaged businesses than their less ecosystem-oriented peers.

The analysis showed that organizations differentiated on four innovation-enabling dimensions are more successful than others in ecosystem innovation. Their winning practices: 10;•9;They lead with platforms for innovating in ecosystems. 10;•9;They create the structures that enable the transformation of ideas into desired customer experiences in ecosystems 10;•9;They establish effective, meaningful measurements for successful innovation in ecosystems. 10;•9;They approach innovation with a collaborative mindset and create an environment of openness that shapes innovative behavior. 10;

The study identified the best practices of the most successful companies, ecosystem innovators. They excel across four innovation dimensions. They build platforms and employ ecosystems to better orchestrate customer experiences. They establish processes to effectively measure innovation within ecosystems in which they operate. They form organizational structures that institutionalize innovation. And they create and promote environments of openness and collaboration

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

Building on the theory of resource-based view (RBV), this paper is determined to explore the key drivers that drive platform ecosystem adoption by small businesses and mediation mechanisms that facilitate the translation of these drivers into improved firm financial and nonfinancial performance.

In this study, structural equation modeling is used to analyze the data. A survey questionnaire was taken from 430 small businesses operating their businesses on various digital platform ecosystems in China to investigate the links between parameters by testing hypotheses. Digital startups operating their businesses on popular Chinese platform ecosystems, including Alibaba, Taobao, Jingdong, Maituan and HelloChe, were chosen.

The finding deciphers a nuanced interplay of the adoption drivers, with innovation capability emerging as a mediation mechanism translating these drivers into improved financial and non-financial performance.

The acknowledgment of potential drawbacks, such as the focus on specific drivers of platform ecosystem adoption, highlights the need for future research to explore additional factors that may influence adoption decisions. By examining institutional factors, market conditions or external shocks like the COVID-19 pandemic, researchers can provide a more comprehensive understanding of the complexities surrounding platform ecosystem dynamics and offer insights into adaptive strategies for businesses facing uncertainty.

The outcome benefits policymakers and ecosystem designers by creating and overseeing platform ecosystems that support the highlighted drivers. This study further serves as a roadmap for both platform owners and prospective small enterprises as they map their path toward the digital frontier.

The findings from the research indicate that small enterprises that embrace platform ecosystems can experience improved financial and non-financial performance, which in turn promotes economic development and the generation of jobs. By utilizing innovative strategies and maximizing their strategic advantages, these enterprises can not only prosper but also make significant contributions to community development and help alleviate joblessness. This highlights the significance of assisting with the incorporation of digital technology in small businesses to achieve wider societal advantages.

Research originality lies in bridging the gap between strategic inputs and measurable outcomes, stressing the vital function of a firm’s innovation in turning ecosystem-driven opportunities into enhanced performance. This means the pivotal role of this study lies in exploring platform ecosystem adoption drivers based on the theory of RBV and the way innovation capability of platform ecosystems facilitates the translation of these drivers into improved financial and nonfinancial performance.

The link between theory and practice in innovation studies still has some gaps, despite scholars’ efforts to illustrate and identify them in real-world situations. To fully understand the dynamics of the innovation ecosystem, it is crucial to consider key actors and their roles and recognize their impact on ecosystem outcomes. Therefore, this paper seeks to discuss how analytical structures of innovation ecosystems address the dynamics of actors and their contribution to the ecosystem outcomes.

A research protocol was developed to query the Web of Science database to identify analytical structures of innovation ecosystems based on pre-established criteria.

The dynamics of actors interfere with their contribution to value creation. That is, the actor changes his contribution. Therefore, depending on the ecosystem's value proposition, the activities and dynamics of the actors change over time.

It contributes to advancing the discussion of innovation ecosystems, addressing insights into the dynamics of actors in different analytical structures. The essay proposal considers innovation ecosystems' evolutionary aspects, value propositions and exchange. In addition, the importance of orchestration in the various stages of the ecosystem is highlighted.

The objective of this article is to analyze the mediating role of innovation capability—both radical and incremental—between technological turbulence and digital innovation ecosystem performance, considering the impact of cross-organizational knowledge sabotage. Despite the enthusiasm surrounding digitization, the high failure rate (80%) of digital transformation projects has received limited attention. This alarming statistic indicates a potential rise in opportunistic behaviors within organizations. We hypothesize that employees seeking to reduce the risk of being displaced by digital technologies, may not only hide knowledge, as previously observed, but also engage in knowledge sabotage by disseminating inaccurate information during the co-creation of digital innovations within the digital innovation ecosystem.

The study employed structural equation modeling to examine moderated mediation using survey data collected from 148 firms, mainly from sectors of high to medium levels of digital intensity.

The most significant finding indicates that cross-organizational knowledge sabotage considerably reduces the only mediating effect, namely that of incremental innovation capability.

Our study presents a novel perspective by investigating the phenomenon of cross-organizational knowledge sabotage. Unlike prior research, which primarily identified the existence of knowledge hiding, our findings suggest that employees are not only willing to withhold information but also to disseminate inaccurate information to external partners. Consequently, our research extends the boundaries of the existing knowledge field by demonstrating that cross-organizational knowledge sabotage has repercussions that extend beyond intra-organizational impacts, as previously recognized. It also adversely affects the outcomes of collaborative work within the digital innovation ecosystem.

This research intends to analyze the innovation ecosystem factors that play a vital role in firm performance. As a result, large-scale empirical studies on the innovation ecosystem are rare, and fewer efforts have been made to determine if and how different factors affect the ecosystem models of firms. There has yet to be a substantial empirical study on the innovation ecosystem.

Data were acquired from Pakistani IT companies. The results show that factors of the innovation ecosystem significantly contribute to business performance. The essential assumption is that resource endowment, organizational culture, knowledge and competence, and technology capability are allied to the innovation ecosystem.

The findings are crucial from a managerial view because firms must focus on changing their innovation ecosystem factors model to achieve greater performance. Radical changes in the firms will only be worthwhile if they value their resource endowments. To attain superior firm performance via influential factors of the innovation ecosystem, IT administrators need to build organizational cultural capacities to adapt to changes brought on by digitization quickly and effectively. However, this must be supplemented by improving organizational knowledge, competencies and technological capabilities to enable organizations to modify their ecosystems.

Eventually, firms can better respond to changes in their settings if they combine these variables by implementing an effective innovation ecosystem model, which leads to greater sector and superior financial performance.

With the widespread penetration of digital technologies, disruptive innovation is not developed by a single firm but is increasingly achieved by an ecosystem. However, limited research has examined the mechanisms involved in achieving disruptive innovation in the context of digitalization and ecosystems. To address this gap, we explore the impact of three dimensions of specialized complementary assets (SCAs) within the innovation ecosystem, human capital SCA (HCSCA), production SCA (PSCA) and marketing SCA (MSCA), on disruptive innovation in core firms through the mediation of digital capability, comprising digital operation capability (DOC) and digital resource collaborative capability (DRCC). Furthermore, innovation ecosystem embeddedness is examined as a moderator between digital capability and disruptive innovation.

Survey data were collected from 234 core firms in China’s high-tech industry. Hierarchical regression, AMOS, and PROCESS tools were used to examine the data.

The results reveal the following: (1) HCSCA and PSCA positively affect disruptive innovation, while MSCA is negatively correlated with disruptive innovation. (2) Digital capability mediates the relationship between HCSCA and disruptive innovation, as well as PSCA and disruptive innovation. However, it suppresses the negative impact of MSCA on disruptive innovation. (3) Innovation ecosystem embeddedness strengthens the influence of DOC on disruptive innovation, but weakens the influence of DRCC on disruptive innovation.

The findings advance the knowledge of disruptive innovation, SCAs within the innovation ecosystem, digital capability and innovation ecosystem embeddedness. They also provide practical insights into the effective implementation of disruptive innovation.

Platform, open/user innovation, and ecosystem strategies embrace and enable interactions with external entities. Firms pursuing these approaches conduct business and interact with environments differently than those pursuing traditional closed strategies. This chapter considers these strategies together highlighting similarities and differences between platform, open/user innovation, and ecosystem strategies. We focus on managerial and organizational challenges for organizations pursuing these strategies and identify four institutional logic shifts associated with these strategic transitions: (1) increasing external focus, (2) moving to greater openness, (3) focusing on enabling interactions, and (4) adopting interaction-centric metrics. As mature incumbent organizations adopt these strategies, there may be tensions and multiple conflicting institutional logics. Additionally, we consider four strategic leadership topics and how they relate to platform, open/user innovation, and ecosystem strategies: (1) executive orientation and experience, (2) top management teams, (3) board-management relations, and (4) executive compensation. We discuss theoretical implications, and consider future directions and research opportunities.

The purpose of this paper is to analyze the symbiotic evolution decisions of digital innovation enterprises, research institutes and the government in the digital innovation ecosystem.

Based on innovation ecosystem theory and an evolutionary game model, this study constructs a tripartite symbiotic evolution game model of digital innovation ecosystems with digital innovation enterprises, research institutes and the government as the main bodies and analyzes the influencing factors as well as the evolution paths of the different behavioral strategies of each subject through numerical simulation.

The research shows that the digital innovation ecosystem has the characteristic of self-organization, which requires the symbiotic cooperation of each subject. The government plays an active role in any stage of symbiotic evolution, and the system cannot enter symbiosis under a low level of subsidies and penalties. Only when the initial willingness to cooperate of digital innovation enterprises and scientific research institutes is at a medium or high level is the system likely to become symbiotic. While digital innovation enterprises are more sensitive to government subsidies and punishments, scientific research institutes are more sensitive to the distribution proportion of cooperation income.

This study includes government regulation into the research scope, expands the research mode of the digital innovation ecosystem and overcomes the difficulties of empirical research in collecting dynamic large sample data. It vividly and systematically simulates the symbiotic evolution process of the digital innovation ecosystem, which provides a theoretical and practical reference for digital innovation ecosystem governance.

This chapter adopts a problem-solving perspective to analyze the competitive dynamics of innovation ecosystems. We argue that features such as uncertainty, complexity, and ambiguity, entail different knowledge requirements which explain the varying abilities of focal firms to coordinate the ecosystem and benefit from the activities of their suppliers, complementors, and users. We develop an analytical framework to interpret various instances of coupling patterns and identify four archetypical types of innovation ecosystems.