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This study evaluates the evolution from traditional to nontraditional financial intermediation (NTFI) in Chinese commercial banks from 2006 to 2021, analysing its impact on bank performance and risk.

Accounting measures are used to construct granular activity data, and factor analysis is employed to develop a financial intermediation evolution (FIE) index. The fully modified OLS (FMOLs) estimator is used for nonstationary data analysis, and difference-in-differences (DID) analysis is used for robustness check.

Chinese banks exhibit unique evolution in financial intermediation compared to developed economies, with greater inter-bank variations over time than intra-bank differences. From 2006 to 2017, three paths were identified: Investment, Fee and Repo models, with a fourth path (the Investment2 model) emerging post-2017. Only the Repo model enhances bank returns (ROA & ROE), while shifts towards NTFI increase liquidity and leverage risks across all models. The evolution of bank business models and their consequent implications on performance and risks are influenced by regulatory objectives and banks’ endeavours in regulatory arbitrage.

Major stakeholders in the banking sector can gain a better understanding of financial intermediation and associated market behaviour, performance and risks, with significant implications for banking regulations and crisis management.

This study provides the first comprehensive overview of the evolution of Chinese commercial banks’ financial intermediation activities over an extended period, uncovering the unique characteristics distinct from the developed economies.

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.

This paper aims to investigate whether managerial overconfidence has an impact on investment inefficiency beyond its influence on the use of internal financing or whether internal financing behaves as a full intermediary.

The study employed three dependent variables, namely business investment scale, overinvestment and underinvestment, and analyzed data from 282 firms across five different industries listed in 11 Middle East/North Africa (MENA) countries between 2013 and 2019 using regression analysis via least square dummy variable (LSDV).

The findings indicate that while internal financing can provide funding for investment opportunities and address capital shortages, it may also result in overinvestment, particularly in companies led by overconfident managers.

Stakeholders, including shareholders and board of directors, should pay attention to the chief executive officer (CEO)'s behavioral aspects such as overconfidence in decision-making while undertaking new investment projects. Additionally, regulators and policymakers in emerging markets like MENA should re-evaluate the corporate governance framework, devise a corporate governance index and promote boardroom gender diversity as it can significantly reduce risk.

This study adds to the limited research on the impact of managerial overconfidence on investment efficiency in the MENA region. By focusing on this region, which has unique economic, political and social characteristics, the study provides new insights into the role of behavioral biases in investment decision-making in emerging markets.

The study aims to add to the existing literature on food supply chains by specifically taking into the redesigning of the alignment of storage, packaging and distribution practices in the modern complex supply chain. The redesign of the food supply chain’s storage, distribution and packaging is a transformative endeavor ultimately aimed at enhancing efficiency, sustainability and reliability.

In order to identify, classify and prioritize the main challenges, this study conducted an extensive analysis of the literature and experts’ opinions in the areas of academia, information technology and the food supply chain (FSC) using combined compromise solution method (CoCoSo) and complex proportional assessment (COPRAS).

The top three classes of key indicators revealed in this study are dynamic route optimization and on-demand delivery pods (RD4), implementation of active packaging with nanotechnology (RP3) and collaborative last-mile (RD2). The findings reveal that dynamic route optimization and on-demand delivery pods (RD4) and collaborative last-mile (RD2) are maintaining a balance between collaborative delivery networks through route optimization which is a very discussable theme in recent literature.

The research provides fresh insights into how perishable food shelf life parameters and the use of distribution networks within the short supply chain can be taken into consideration when redesigning the storage, packaging and distribution system for food supply chains.

This study aims to examine how virtual influencers (VIs) affect purchase intentions in tourism and hospitality e-commerce live streaming (THCLS) by focusing on the roles of VIs’ source credibility, trust in products, trust in VIs, emotional engagement, parasocial relationships and influencer–product congruence.

Survey data from 416 active viewers of VIs in THCLS were analysed using partial least squares structural equation modelling.

This study highlights the importance of the VIs’ source credibility, which positively affects trust in the product, trust in VIs and emotional engagement. However, source credibility does not have a positive impact on parasocial relationships. Trust in products positively influences trust in VIs. Emotional engagement and trust in VIs significantly influence parasocial relationships, which, positively affects purchase intentions. Influencer–product congruence strengthens the link between parasocial relationships and purchase intentions but does not moderate the relationship between trust in VIs and purchase intentions. No significant gender differences were observed, although minor discrepancies were noted in the effect of trust in products on trust in VIs. The importance–performance map analysis revealed that parasocial relationships are the most important factor influencing purchase intentions, while influencer–product congruence has the highest performance, trust in products is the least important and VIs’ source credibility has the lowest performance.

This study provides actionable insights for marketers leveraging VIs in the THCLS sector, emphasizing strategies to enhance VI credibility, foster parasocial relationships, ensure influencer–product congruence and adopt gender-neutral marketing approaches to effectively influence purchase intentions.

This study offers theoretical and practical insights into the role of VIs in THCLS, illuminating their impact on consumer behaviour and purchase intentions.

Over the past decade, artificial intelligence (AI) technologies have rapidly advanced organizational management, with many organizations adopting AI-based algorithms to enhance employee management efficiency. However, there remains a lack of sufficient empirical research on the specific impacts of these algorithmic management practices on employee behavior, particularly the potential negative effects. To address this gap, this study constructs a model based on the psychological ownership theory, aiming to investigate how algorithmic management affects employees’ knowledge hiding.

This study validates the model through a situational experiment and a multi-wave field study involving full-time employees in organizations implementing algorithmic management. Various analytical methods, including analysis of variance, regression analysis and path analysis, were used to systematically test the hypotheses.

The study reveals that algorithmic management exerts a positive indirect influence on knowledge hiding through the psychological ownership of personal knowledge. This effect is particularly pronounced when employees have lower organizational identification, highlighting the critical role of organizational culture in the effectiveness of technological applications.

This study is among the first empirical investigations to explore the relationship between algorithmic management and employee knowledge hiding from an individual perception perspective. By applying psychological ownership theory, it not only addresses the current theoretical gap regarding the negative effects of algorithmic management but also provides new theoretical and empirical support for the governance and prevention of knowledge hiding within organizations in the context of AI algorithm application. The study highlights the importance of considering employee psychology (i.e. psychological ownership of personal knowledge) and organizational culture (i.e. organizational identification) under algorithmic management. This understanding aids organizations in better managing knowledge risks while maximizing technological advantages and effectively designing organizational change strategies.

A more accurate comprehension of data elements and the exploration of new laws governing contemporary data in both theoretical and practical domains constitute a significant research topic.

Based on the perspective of evolutionary economics, this paper re-examines economic history and existing literature to study the following: changes in the “connotation of production factors” in economics caused by the evolution of production factors; the economic paradoxes formed by data in the context of social production processes and business models, which traditional theoretical frameworks fail to solve; the disruptive innovation of classical theory of value by multiple theories of value determination and the conflicts between the data market monopoly as well as the resulting distribution of value and the real economic society. The research indicates that contemporary advancements in data have catalyzed transformative innovation within the field of economics.

The research indicates that contemporary advancements in data have catalyzed disruptive innovation in the field of economics.

This paper, grounded in academic research, identifies four novel issues arising from contemporary data that cannot be adequately addressed within the confines of the classical economic theoretical framework.

This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment.

A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions.

It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module.

The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.

The purpose of this paper is to explore how and when employee smart technology, artificial intelligence, robotics and algorithms (STARA) awareness affects job crafting through challenge appraisal and threat appraisal and provides positive stress mindset as a moderator.

The survey data was collected from 319 employees in four Chinese companies. The hypotheses were tested using Mplus 7.0 and regression analysis.

The results indicate that STARA awareness positively prompts approach job crafting via challenge appraisal and also positively predicts avoidance job crafting via threat appraisal. Meanwhile, positive stress mindset enhanced the mediating effect of challenge appraisal and weakened the mediating effect of threat appraisal.

Leaders should prioritize hiring high-positive-stress mindset candidates for jobs, and organizations should also cultivate employees’ positive stress mindset.

Building on the cognitive appraisal theory of stress, this study reveals the underlying mechanism and boundary conditions behind the linkage of STARA awareness and job crafting.

This study investigates the relationship between corporate social responsibility (CSR) and financial performance of the banking sector from the prospective of emerging countries.

This study obtained balance sheet and income statement data for 173 banks in 20 emerging countries from the Bankscope database from 2005–2018. The CSR-related data were taken from the Thomson Reuters ASSET4 database. Moreover, macroeconomic controls such as GDP per capita, inflation, and financial development are attained from the GFDD. The series of institutional quality indices (Political Stability, Rule of Law, Control of Corruption, Government Effectiveness, and Regulatory Quality) is obtained from the WGI. At the same time, national culture and bank regulation are attained from Hofstede Insights and Barth et al. (2013). We used the panel fixed-effects model in our baseline estimations, while 2SLS and GMM were applied to control for endogeneity.

The finding shows that CSR activities significantly improve bank performance, but the effect varies across the bank. Only environmentally friendly activities have shown a significant positive relationship with banking performance for CSR dimensions. However, the social and government dimensions did not significantly affect bank performance. Moreover, a sound institutional and regulatory environment and national norms play an important role in the nexus of CSR activities and bank performance.

This study provides empirical evidence that sheds light on CSR and bank performance in an emerging market context.