The complex interactions of industrial Policy, structural transformation, economic growth, and competitive strategy within regional industries are examined in this research. Using a dynamic capabilities framework, the study examines the mediating roles of organizational innovation and adaptability in the link between competitiveness and macroeconomic variables. A two-way fixed effects model is used in this study to examine the influence of structural transformation (ST) on Industrial Policy (IP). Using regional data covering the years 2010 to 2022, the research undertaken in this paper explores the dynamics of the Indonesian economy by empirically assessing the consequences of structural change on industrial Policy. In order to establish a comprehensive model that clarifies the mechanisms through which industrial policies and structural shifts impact the development of dynamic capabilities, ultimately influencing competitiveness strategies, this research draws on a large amount of empirical data and integrates insights from seminal works. Our research adds to our knowledge of strategic management in regional industries by providing detailed information on how economic development and policy interventions influence businesses’ ability to adapt and gain a competitive edge. In addition to advancing scholarly discourse, this study offers business executives and politicians valuable insights for managing the intricacies of global economic processes.

This research aims to analyze the relationship between dynamic capabilities and organizational performance, networking, and organizational performance, and to analyze the relationship between spiritual motivation variables and organizational performance. This research method is a quantitative survey. The respondent sampling technique used in this research is a purposive sampling technique, namely samples taken based on certain considerations. Responses to this study came from 567 Organization members of education. The data collection method used in this research is an online questionnaire which provides a written list of questions to respondents. The questionnaire was designed using a Likert scale of 1 to 7. In this study, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely integrated validity and reliability testing, inner model testing, and hypothesis testing. The independent variables of this research are dynamic capabilities, collaborative networks, and spiritual motivation and the dependent variable is Organization performance. The results of this research are that dynamic capabilities have a significant and positive influence on organization performance, collaboration networks have a significant and positive influence on organization performance, and motivation has a significant and positive influence on organization performance. The managerial implication of the results of this research is that to improve the performance of educational organizations, managers can apply dynamic capability variables because dynamic variables have been proven to significantly encourage increased organizational performance. Organizations could improve the performance of educational organizations, and managers bu implement collaboration network variables because collaboration networks have been proven significantly can significantly encourage the increased performance of educational organizations. To improve the performance of educational organizations, managers can apply motivation variables because motivation variables have been proven to significantly encourage increased performance of educational organizations.

Universities play a key role in university-industry-government interactions and are important in innovation ecosystem studies. Universities are also expected to engage with industries and governments and contribute to economic development. In the age of artificial intelligence (AI), governments have introduced relevant policies regarding the AI-enabled innovation ecosystem in universities. Previous studies have not focused on the provision of a dynamic capabilities perspective on such an ecosystem based on policy analysis. This research work takes China as a case and provides a framework of AI-enabled dynamic capabilities to guide how universities should manage this based on China’s AI policy analysis. Drawing on two main concepts, which are the innovation ecosystem and dynamic capabilities, we analyzed the importance of the AI-enabled innovation ecosystem in universities with governance regulations, shedding light on the theoretical framework that is simultaneously analytical and normative, practical, and policy-relevant. We conducted a text analysis of policy instruments to illustrate the specificities of the AI innovation ecosystem in China’s universities. This allowed us to address the complexity of emerging environments of innovation and draw meaningful conclusions. The results show the broad adoption of AI in a favorable context, where talents and governance are boosting the advance of such an ecosystem in China’s universities.

This study investigates the escalating complexity and unpredictability of global supply chains, with a particular emphasis on resilience in the agricultural sector of Antioquia, Colombia. The aim of the study is to identify and analyze the dynamic capabilities, specifically flexibility and adaptability that significantly enhance resilience within agri-food supply chains. Given the sector’s vulnerability to external disruptions, such as climate change and economic volatility, a thorough understanding of these capabilities is imperative for the formulation of effective risk management strategies. This research is essential to provide empirical insights that can inform stakeholders on fortifying their supply chains, thereby contributing to enhanced competitiveness and sustainability. By presenting a comprehensive framework for evaluating dynamic capabilities, this study not only addresses existing gaps in the literature but also offers practical recommendations aimed at bolstering resilience in the agricultural sector.