The metaverse ecosystem empowers the development of strategic emerging and future industries with a new model of high-quality productivity. This research introduces the complex adaptation theory, selects five metaverse related listed companies in China to carry out a logical analysis of value co-prosperity, and compares and analyzes the logical chain of the evolution of enterprise value co-enrichment in different case companies. On the basis of case analyses, this paper systematically summarizes an evolutionary logic of value co-enrichment in the metaverse ecosystem. The research concludes that the metaverse ecosystem experiences a dynamic evolutionary logic of “resource → value capital → value product → value wealth → value co-enrichment”. The research on value co-enrichment can provide a new perspective and practical direction for the future development of metaverse.

Based on the theoretical perspective of synergism, the study takes Hisense Group’s three-stage R&D collaboration evolution as a vertical case to explore the evolution path and driving mechanism of the R&D collaboration in an enterprise group. It is found that the R&D collaboration of the enterprise groups follow the three-stage evolutionary path of “collaborative preliminary — collaborative exploration — collaborative stabilization”, which is a combination of independent innovation and technology accumulation. Driven by the competitive environment and collaborative strategy, it promotes the dynamic integration of resources, information and technology of collaborative entities, and helps enterprise groups to optimize resource allocation and technological innovation, thereby stimulating the group’s deep-seated innovation capability. The conclusion of the study is conducive to promoting China’s enterprise groups to realize the transformation from industry technology breakthroughs to domestic technology leadership and then to international technology leadership.

Digital transformation is widely accepted among Chinese family businesses, however, they face a substantial digital divide, with limited research on this topic. From the perspective of dynamic tension between digital strategy and organizational change, this article conducts an exploratory case analysis of New Hope Liuhe, examines the mechanism of “external change tension → internal intergenerational tension → digital strategy implementation” in family businesses’ digital transformation. The study reveals that: (1) external change tension, arising from scarce technical talent, creates significant challenges for digital transformation, exacerbating internal power shift and influencing intergenerational tension; (2) internal intergenerational tension, driven by generational conflicts, exposes the organization to risks of rigidity and loss of control during transformation, thus exerting a counter-effect on external change tension; (3) the interaction of internal and external tensions accelerates generational power shift. Contrary to expectations, while this shift boosts digital transformation by enhancing the organization’s digital readiness and capabilities, the new executives’ limited cross-cycle management experience weakens risk management, potentially hindering transformation. This study unveils the tension mechanism between digital strategy and organizational change in family businesses, provides insights into organizational change and transformation of family businesses in the digital age.

The high-quality development of creative enterprises and the efficient transformation from creativity to innovation are garnering increasing attention from both academia and industry. Grounded on the case of Betop which exhibits both conventional and unique attributes in the creative industry, this article employs the “intention-behavior-result” framework to uncover the unique value of trial-and-error learning in the efficient transformation from creativity to innovation. The research demonstrates that: (1) the efficient transformation from creativity to innovation is a dynamic, complex, and continuously knowledge-creating trial-and-error learning process. Moreover, this process exhibits a continuous “ripple effect” and revolves around three stages of transformation in creative practices, that is, first forming the “incremental-radical- ambidexterity” creativity from the current knowledge base, then through “parallel-sequential- interactive” trial-and-error learning, knowledge creation is superimposed to form a continuous driving force, which enhances the efficiency of the transformation from creativity to innovation, and finally achieves multi-dimensional innovation of “product-market-ecosystem”. (2) the iterative process of trial-and-error, which transforms from creativity to effective innovation, reveals a cyclical mechanism of knowledge and action unity. This underscores the substantial value of knowledge practice within the realm of innovative endeavors. (3) the fundamental reason for the transformation from creativity to innovation lies in the conversion of subjective knowledge into objective knowledge. Trial-and-error learning alters the essence of knowledge in both creativity and innovation by employing the mechanism of knowledge and action unity.

Under the background of the wave of artificial intelligence (AI) sweeping the world, how to unlock the full potential of AI in the innovation process to achieve corporate innovation goals has become a hot issue in both academia and the industry. However, research related to AI in the context of existing innovation is still in the early stages of exploration, with issues such as fragmentation and an unclear knowledge context. These problems seriously affected the knowledge and application of AI in the process of enterprise innovation in the theory and the industry. Through a systematic quantitative literature review, relevant domestic and international literatures from 1997 to 2023 has been summarized, and a theoretical framework of artificial intelligence in the context of innovation has been formulated with the core of “antecedents—application process—supporting factors—outcomes”. Specifically, the specific embodiment of the core functions of artificial intelligence in the various innovation segments is highlighted and clarified. On this basis, the main directions and issues of future research are put forward, aiming at providing support for the development of artificial intelligence industrial digital intellectualization.

With the advent of the digital era, an innovation ecosystem based on digital technology has gradually emerged. Based on the theory of resource orchestration, this paper adopts the method of longitudinal case study, analyzes the establishment process of digital innovation ecosystem of Weichai Group in detail, and actively explores the evolution model of digital innovation ecosystem of manufacturing enterprises. The findings are as follows: (1) the digital innovation ecosystem goes through three stages of generation stage, advanced stage and complete stage, and the development program of the system is started through the combination of different endogenous and exogenous causes. (2) the generation of digital innovation ecosystem follows the dynamic evolution characteristics of “growth effect—platform integration effect—digital ecological effect”. (3) in the digital context, manufacturing enterprises realize the application of digital technology and the rapid evolution of digital innovation ecosystem through the resource process of “digital resource structuring → digital resource capability → digital resource utilization”. Based on digital technology, digital innovation ecosystem promotes the continuous expansion and iteration of innovation ecosystem through digital products, gradually expands the system boundary and forms the digital innovation ecosystem. This study expands the theory of digital innovation ecosystem in manufacturing enterprises, bridges the theory of resource orchestration with the theory of digital innovation ecosystem, enriches the theoretical content, and provides certain practical guidance for the construction of digital innovation ecosystem in enterprises.

This article takes Ping An as an example to explore the causes and consequences of targeted poverty alleviation in private listed companies, attempting to reveal whether profit-driven private enterprises can achieve the righteousness and benefit through targeted poverty alleviation. The study finds that: (1) Ping An’s poverty alleviation model covers industrial, medical and educational poverty alleviation. Its participation in poverty alleviation is driven by altruistic factors such as responding to national policies and improving the image of the insurance industry, but more importantly, it is driven by self-interest factors such as obtaining tax dividends, maintaining the relationship with government, improving the ESG system and laying out financial and medical technology strategies. (2) while achieving the altruistic act of poverty alleviation, Ping An has also realized positive self-interest consequences. Firstly, it has accumulated reputation capital, including winning poverty alleviation awards, improving ESG ratings and attracting international capital. Secondly, obtain political resources, increase government subsidies after poverty alleviation, deepen cooperation between government and enterprises, and lowering the level of tax burden. The third is to promote the improvement of industrial layout and enhance the performance of the core platforms for poverty alleviation. This article enriches the research on the causes and consequences of targeted poverty alleviation in private listed companies from the perspectives of self-interest and altruism. This can provide reference for enterprises to organically combine targeted poverty alleviation with corporate strategies and establish a long-term mechanism for targeted poverty alleviation.

Digital transformation has become an inevitable move for the survival and long-term development of global manufacturing enterprises. Although current studies have pointed out the strategic direction of digital transformation, there is still a lack of holistic research on its dynamic process. Based on the perspective of resource action theories, this paper takes Audi AG as the case study object to describe the evolution trajectory and transformation mechanism of the digital transformation of manufacturing industry. The results indicate that enterprise digital transformation follows the stage evolution logic of “exploration - growth - deepening”, at different stages of enterprise digital transformation, affected by resource scenario constraints and strategic orientation, the enterprise resource action mode shows an evolutionary trend from “resource bricolage” to “resource configuration” and then to “resource orchestration”. The evolution of enterprise resource action makes enterprise business model realize the iteration from “supplier business model” to “digital platform business model” and then to “digital ecosystem business model”. The research conclusion is expected to provide theoretical support and practical guidance for digital transformation of manufacturing enterprises.

Science and technology projects are one of the main forms of innovation policy in China. To clarify the mechanism through which government’s science and technology projects affect enterprise innovation is the premise to respond to the controversy of “innovation policy effectiveness”. Based on the perspective of regional innovation system theory, this paper makes a case study on the practice of promoting enterprise innovation through science and technology projects in County J, and refines the innovation system construction mechanism. The grassroots government, guided by the requirement of declaring science and technology projects, mobilizes innovation subjects such as research institutions, financial institutions, intermediaries and the government to provide various innovation resources to enterprises, which actually forms a multi-subject collaborative innovation system with science and technology projects as the carrier to promote enterprise innovation. This mechanism is not the initial goal of policy formulation, but a “non-proactive” policy effect promoted by the grassroots government under the incentive mechanism. The results show that attaching great importance to the key role of grassroots government in the implementation of innovation policy and strengthening the construction of relevant incentive mechanism are the keys to improve the effectiveness of innovation policy.