The consolidation of Industrial Estate companies in Indonesia into a single holding company is reshaping the structure, behaviour and business models of key actors in the country’s industrial development landscape. This study examines whether there is a relationship between the efficiency levels achieved by Industrial Estate companies and their degree of involvement and strategic role in mergers, acquisitions and consolidation processes within the holding. Because this relationship may operate in different directions, both highly efficient and poorly performing parks may be targeted for integration. The issue is relevant for a wide range of stakeholders, from policy-makers and the holding’s management to investors and regulators. We measure efficiency using two Stochastic Data Envelopment Analysis (SDEA) models. Based on a hand-collected data set of 113 Indonesian Industrial Estates, belonging to 48 corporate groups over the period 2022–2024, the results indicate that consolidation and M&A decisions essentially involve parks located at both ends of the efficiency spectrum, characterised by either relatively high or relatively low efficiency levels.
Digital transformation is the inevitable trend of the survival and development of manufacturing enterprises in the era of indus-try 4.0.In recent years,Chinese enterprises have been actively exploring the road of digital transformation,especially under the im-pact of the novel coronavirus pandemic,have accelerated the process of digital transformation.However,the overall digital transforma-tion performance of Chinese enterprises is not satisfactory.According to the resource-based theory,the different competitive advanta-ges and performance of enterprises depend on how they use resources to form unique core competence,thus influencing organizational behavior to improve performance.Specifically,by analyzing and utilizing big data resources,enterprises can more comprehensively and deeply capture the market environment and the potential demand of consumers.Although big data resources provide opportunities for enterprises'digital transformation,how to use big data resources to improve the performance of digital transformation is still a challenge. Although scholars have done some research on big data resources and digital transformation,there are still some shortcomings in the current research results.First,the intermediate mechanism of the impact of the lack of big data resources on the performance of digital transformation;The second is the lack of research on the impact of organizational change in the process of digital transformation.Based on this,this study combines dynamic capability theory and organizational convention theory,and based on the practical back-ground of manufacturing enterprises'digital transformation,builds a theoretical model of"big data resource-digital dynamic capability-organizational convention renewal-digital transformation performance",carries out an empirical study on the relationship between the four,and further defines the influence mechanism of big data resources on digital transformation performance. In this study,the questionnaire Star platform was selected for investigation,the industry of the enterprise was limited to the manu-facturing industry,and the positions of the personnel were middle and senior managers.The data collection period consisted of two sta-ges:the first stage was from February 8,2022 to February 22,2022,and 302 questionnaires were collected;The second stage is from August 6 to August 20,2022.204 questionnaires were collected,and 506 questionnaires were collected in the two stages.After elimi-nating non-existent fake enterprises,short filling time and obvious similarity questionnaires,427 valid questionnaires were obtained.Mplus8.0 software was used to conduct empirical research through structural equation modeling(SEM). The study finds that:(1)Three sub-dimensions of big data resources and digital dynamic capabilities:Digital perception capa-bility,digital utilization capability,digital reconstruction capability and organizational convention update all have positive effects on the digital transformation performance.(2)Digital utilization capability,digital reconstruction capability and organizational convention up-date have mediating effects on the relationship between big data resources and digital transformation performance respectively.(3)Dig-ital dynamic capability and organizational routine updating have a chain-mediated effect on the relationship between big data resources and digital transformation performance. This study will theoretically expand the research on the chain-mediated mechanism of big data resources on the performance of digital transformation in the context of digital digitalization,promote the theoretical exploration of digital transformation from the theory of dynamic capability and organizational practice,and further supplement the case study of Jiao Hao et al.[7]on the realization of digital transformation by data-driven dynamic capability from an empirical perspective.Echoing Hanelt et al.19]'s view that digital transfor-mation is an organizational transformation,responding to Verhoef et al.[2]'s topic of how big data resources promote digital transforma-tion,opening the"black box"in the performance path from big data resources to digital transformation,and providing a new theoretical framework for the study of digital transformation;In practice,it is helpful to guide manufacturing enterprises to use big data resources in the dynamic environment,improve the digital dynamic ability,accelerate the update of organizational practices,and then realize the digital transformation.
The purpose of this paper is to consider the joint action of structural, cognitive and relational social capital, and to explore the formation mechanism of the innovation network of new energy vehicles (NEV). The research data come from China's NEV cooperative invention patent applications from 2001 to 2019. This paper uses the exponential random graph model (ERGM) to study the impact of different dimensions of social capital on the NEV industry-university-research (I-U-R) innovation network. The results show that from the perspective of structural capital, the closed network structure has a positive impact on the formation of NEV I-U-R innovation network. From the perspective of cognitive capital, the homogeneity of knowledge base has a positive effect on the formation of the NEV I-U-R innovation network, and the innovation subjects with the same knowledge base breadth and the same knowledge base depth are more inclined to form a cooperative relationship. For relational capital, institutional environment similarity and organizational structure similarity are important factors affecting the formation of NEV I-U-R innovation network to a similar extent. The findings of this study provide scientific references for promoting the sustainable development of I-U-R innovation network in NEV industry.
"十四五"时期是加快迈向创新型国家前列的开局关键期,如何提供更好的制度环境以驱动企业创新备受关注,本文立足于有为政府的监管视角,认为证监会派出监管机构与上市公司之间的地理距离能够影响上市公司创新绩效.本文以2003-2019年中国A股上市公司为研究样本,实证检验了监管距离对企业创新绩效的影响及内在机理.研究结果表明:(1)监管距离对企业创新绩效产生负向影响,即监管机构与上市公司地理距离越远,企业创新绩效越低,考虑内生性问题后本文研究结论依然成立,总体上监管机构对企业创新活动的影响呈现出"鞭长莫及"效应;(2)内在机制检验结果表明监管距离主要通过影响上市公司的盈余管理程度以及内部控制质量两种公司治理效应对企业创新绩效产生负向影响,并且盈余管理程度与内部控制质量在监管距离与企业创新之间产生部分中介效应;(3)进一步分析结果表明,监管距离对企业创新的抑制效应在高铁开通前以及制度环境更弱的区域中更显著.本文基于地理经济学与制度经济学的融合框架丰富了传统基于"制度环境—产业/行业竞争—企业高管"驱动企业创新的研究框架.
针对当前元宇宙的发展态势和理论研究,本文重新界定了元宇宙的概念内涵.元宇宙的样态本源可追溯至数字化数据,其技术源头则是各类数字化数据生成技术.根据数字样态的作用场域和虚实世界互动过程的主体跨域性等两个拓扑维度,可将元宇宙划分为四类阶段性形态:纯数字化世界、数字孪生世界、虚实互构世界和虚实协同世界.将元宇宙置于数字样态的整体演进历程中发现其四种发展形态之间的演化机理,即,纯数字化世界与传统网络空间紧密相关而成为元宇宙创新的首选之地,数字孪生世界的元宇宙侧重于工业实在世界,虚实互构世界综合了纯数字化世界和数字孪生世界的结构与功能,虚实协同世界则是人类数字化观念革新的驱使下虚实互构世界的高级形态.本文澄清了元宇宙的概念内涵、形态发展与演变机理,为后续的产业政策制定和治理体系建构提供了学理基础.
