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This research explores how individual factors drive early-stage strategic entrepreneurship (SE) in Vietnam and Taiwan. The authors extend SE and integrate knowledge spillover theory to gain insights into the relationship between individual factors and SE. The research highlights the importance of a dual process, which involves advantage-creating by innovation, as value creation and capture, and advantage-leveraging by growth and international expansion, as value retention and capture.

Innovation-oriented SE (ISE), growth-oriented SE (GSE) and internationalization-oriented SE (ITSE) are identified as new measures of SE. There are six hypotheses containing the effect of six personal characteristics have on SE. The authors employed logit regression to estimate the effect of independent variables on SE based on a pooled cross-sectional dataset drawn from Global Entrepreneurship Monitoring (GEM) in Vietnam and Taiwan during 2013–2018.

Opportunity sensing, education, self-funding ability, startup knowledge and skills and startup experience are crucial to the engagement of at least one type of SE in Vietnam. In contrast, education, self-funding ability and start-up knowledge and skills are key factors in Taiwan.

This study contributes to the extension of SE at the individual level in the early phase of new venturing and the integration of knowledge spillover theory. In order to drive early-stage SE further, the authors recommend to prioritize learning from spillovers within and among organizations, industries and communities, as well as through quality institutions, in addition to the individual drivers.

This paper aims to examine spillover effects of heterogenous foreign direct investment (FDI) enterprises (domestic vs. export-oriented) through horizontal and vertical linkages and absorptive capacity effect on domestic firms' total factor productivity (TFP). It clarifies the spillover effect on domestic firms in accordance with industrial zones, business size, technology sector and geographical agglomeration, respectively.

The dataset used is based on Vietnamese manufacturing firms during 2011–2014, input–output (I–O) Table 2012. This paper is conducted in two steps: (1) TFP is estimated by using a semi-parametric approach developed by Levinsohn and Petrin (2003); (2) Regression with panel data for domestic firms, applying the fixed effect method.

In terms of domestic-oriented FDI (DFDI) enterprise group: TFP spillover through horizontal linkages is found negative for domestic firms but positive for those participating in export. Additionally, backward linkages have a negative impact on TFP for most domestic enterprises, except for those operating in the high-tech sector. In terms of export-oriented FDI (EFDI) enterprise group, horizontal linkages have a negative impact on domestic firms' TFP including domestic ones participating in export whereas backward linkage is an important channel with positive effects. Absorptive capacity enables firms to improve productivity through linkages with EFDI and DFDI enterprises. Exporters located in industrial zones or regions with numerous exporters can receive better impacts through backward linkages EFDI.

Comprehensively, this is the first paper to detect FDI heterogeneity in their behavior when entering a developing country like Vietnam. The added value in this study comes from the export ability of local firms which is in line with Melitz (2003) theory that they can excel in absorping the TFP spillover from competing with DFDI competitors or from supplying to EFDI enterprises. Moreover, the role of small and medium-sized enterprises (SMEs), low technology, high technology and learning by regions affecting the impact through both horizontal and vertical linkages are included for analysis.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on tourism industry revenues in Spain.

Data were collected from the Bureau van Dijk's (BvD) Orbis global database. The data were analysed using a spatial econometric model and the Cobb–Douglas production function.

This study reveals that hotels located inside the buffer zone of points of tourist interest achieve better economic outcomes than hotels located outside the buffer. Furthermore, the results show that there is a direct and indirect spatial spillover effect in the hotel industry.

The results provide valuable information for identifying areas where the agglomeration of hotels will produce a spillover effect on hotel revenue and the area of influence of location characteristics. This information is relevant for hotels already established in a destination or when seeking a location for a new hotel.

The results of this study can help city planners in influencing the distribution of hotels to fit desired patterns and improve an area's spatial beauty.

The paper provides insights into how investment, structural characteristics, reputation and location affect hotel revenue.

This paper aims to study the role of foreign direct investment (FDI) channels in improving local firms' productivity. Two transmission channels of knowledge spillovers are empirically investigated. The study focuses on the role of high-growth firms (HGFs) that are assumed to have a higher absorptive capacity.

A threshold regression model that considers country and sector fixed effects is applied to investigate 8525 firms across 50 sectors in 12 developing countries in the East Asia and Pacific (EAP) region.

The author's findings indicate that first, larger firms with external market linkages are more productive. Second, high-growth enterprises are powerful engines of job creation; however, the firms do not outperform other firms in terms of capacity in absorbing FDI spillovers and do not have higher productivity.

The findings highlight the necessity of rethinking public policy priorities to support firm growth. Policies to maximize the gains from FDI spillovers are discussed.

This is the first study to investigate the strength of FDI spillover channels across different sectors, and the channels' impact on the productivity of local enterprises in the EAP region. This study also explores the potential role of high-growth firms (HGFs) in this interaction via job creation and improving output growth rate.

Proximity is a crucial factor influencing innovation collaboration and performance. Most existing studies have primarily focused on the organizational level and been static in nature. Therefore, a further study on how proximity affects innovation performance is needed. This paper aims to fill this gap by highlighting the organizational, cognitive and geographical proximity in China’s open regional innovation system.

This paper analyzes the data from 2010 to 2015 through path analysis.

The results reveal that geographical proximity has a direct positive effect on regional innovation performance in China’s regional innovation system. It also shows that organizational proximity exerts a negative impact on absorptive capacity, and through it adversely affects regional innovation performance. In contrast, cognitive proximity is found to have a positive effect on absorptive capacity, enhancing regional innovation performance.

Based on these findings, this paper contributes to a better understanding of the role of proximity in innovation collaboration and performance. By highlighting the importance of different proximity types, it provides insights for policymakers and practitioners seeking to foster regional innovation.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

Digital transformation (DT) is among the vital factors contributing to innovation ambidexterity, especially for advanced manufacturing firms (AMFs). However, the empirical studies on the relationship between DT and innovation ambidexterity in AMFs from the perspective of knowledge management are inadequate. Therefore, this study aims to systematically analyze the impact of DT on innovation ambidexterity and its mechanism of action.

This study selects 254 listed firms within the ten key areas of “Made in China 2025,” as they occupy a key position in China’s advanced manufacturing system. Based on the knowledge-based view (KBV) and contingency theory, it constructs a model of the influence mechanism of DT on innovation ambidexterity.

The results show that the DT of AMFs positively influence innovation ambidexterity. External pressure from environmental turbulence enhances the positive relationship between DT and innovation ambidexterity, demonstrating the “resilience effect,” external knowledge search (EKS) and broadening the knowledge base mediating roles between them, highlighting the “accumulation effect.”

By identifying this mediation mechanism of DT and innovation ambidexterity, this study provides new ideas for path research on the KBV. Moreover, this study explores the triggering effect of market environmental turbulence on the DT of firms. It reveals the boundary conditions of DT acting on innovation ambidexterity, expands the research perspective on organizational resilience and enriches the theory of power change.

This study investigates whether and how place-based industrial relocation policy affects firm innovation.

By exploiting the establishment of China's National Industrial Relocation Demonstration Zones (NIRDZs) as a quasi-natural experiment in a difference-in-differences design, the authors examine the externalities of industrial policies that support sustainable development and growth from the perspectives of firms' patenting activities.

The study consistently finds that the NIRDZs policy significantly boosts local firm innovation, translating into a 60.46% increase in the patent applications of treated firms. The estimation results remain robust to a series of alternative specifications. Moreover, heterogeneity analysis suggests that the firms that benefited most were state-owned enterprises, firms with higher productivity, or firms in non-high-tech industries. Further, the authors find that the NIRDZs policy stimulates firm innovation mainly in the form of utility model patents, followed by designs and invention patents.

The results provide suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in policy implementation.

This study provides suggestions and implications for policymakers to improve the efficiency of state-led industrial policies and avoid “government failure” in the policy implementation.

This study fills the research gap by exploiting quasi-experiments to assess the effectiveness of state-led industrial policies for emerging economies. (2) The analysis sheds empirical light on how corporate innovation is motivated and financed by selective and functional industrial policies. (3) Theoretically, the results rationalize why state-led industrial relocation fuel innovation capabilities of localities from Marshall externalities and competition crowding-out effects.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.