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Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

Industry 4.0 is recognised as a competitive strategy that helps implementers optimise their value chain. However, its adoption poses several challenges. This study investigates and ranks the drivers and barriers to implementing Industry 4.0 in the Thai sugar industry, the world's second-largest sugar exporter. It also evaluates the industry's readiness for Industry 4.0.

The drivers and impediments were identified based on a systematic literature review (SLR) and further investigated using a questionnaire, expert interviews, Pearson's correlation and nonparametric statistical analyses. The IMPULS model was used to assess the industry's readiness.

Most companies expect to minimise costs, develop employees and improve various elements of operational performance and data tracking capability. Thai sugar producers are still at a low readiness level to deploy Industry 4.0. High investment is the major challenge. Small businesses struggle to hire competent employees, collaborate with a highly credible technology provider and adapt to new solutions.

The findings can serve as a benchmark or guide for sugar manufacturers and companies in other sectors, where Industry 4.0 technologies are not yet widely utilised, to overcome existing roadblocks and make strategic decisions. They can also assist governments in developing policies that foster digital transformation and increase national competitiveness.

There is a scarcity of research on Industry 4.0 execution in the sugar industry. This study addresses this gap by investigating the reasons for the hesitancy of sugar producers to pursue Industry 4.0 and proposing solutions.

Since the implementation of the regulatory inquiry system, research on its impact on information disclosure in the capital market has been increasing. This article focuses on a specific area of study using Chinese annual report inquiry letters as the basis. From a text mining perspective, we explore whether the textual information contained in these inquiry letters can help predict financial restatement behavior of the inquired companies.

Python was used to process the data, nonparametric tests were conducted for hypothesis testing and indicator selection, and six machine learning models were employed to predict financial restatements.

Some text feature indicators in the models that exhibit significant differences are useful for predicting financial restatements, particularly the proportion of formal positive words and stopwords, readability, total word count and certain textual topics. Securities regulatory authorities are increasingly focusing on the accounting and financial aspects of companies' annual reports.

This study explores the textual information in annual report inquiry letters, which can provide insights for other scholars into research methods and content. Besides, it can assist with decision making for participants in the capital market.

We use information technology to study the textual information in annual report inquiry letters and apply it to forecast financial restatements, which enriches the research in the field of regulatory inquiries.

This study aims to comprehensively analyse the implementation and effectiveness of corporate social responsibility (CSR) policies within the context of the Indian coal mining sector. Furthermore, it investigates the alignment between CSR initiatives and the unique challenges faced by the coal mining sector and examines the outcomes and impacts of these initiatives on the employees of the sector and their perspective on the situation.

This study adopts a comprehensive qualitative research method, including a review of the literature, case studies and stakeholder interviews. This study seeks to deconstruct the application of CSR policies.

The analysis developed a deeper understanding of the complexities surrounding CSR policies in the Indian coal mining sector, offering insights into strategies for enhancing the effectiveness and relevance of these initiatives while fostering sustainable development.

This study reveals a rich tapestry of theoretical implications and how they connect to important organisational and societal paradigms. The results of this qualitative analysis can work as a foundation for creating scales to measure the level of efficiency of CSR policies implemented by different companies. Furthermore, this study goes beyond theoretical knowledge and gives companies, regulators and communities information they can use. By looking at how CSR policies work in the real world, a road map for responsible resource extraction and community growth can be made.

The findings are unique in exploring the CSR initiatives and the unique challenges faced by the coal mining sector. This study offers insight on the employees of the sector and their perspectives on the situation and delves into the multifaceted dimensions of CSR practices.

This paper aims at assessing the impact of a number of behavioral interventions on the willingness of informal businesses, in the Egyptian informal sector, to join the formal sector.

This paper uses an experimental methodology to examine the impact of behavioral interventions on the formalization of the Egyptian informal sector. Specifically, it conducts a survey experiment on a total of 240 informal businesses, operating in the Egyptian informal sector. The primary data collected from the survey experiment is then analyzed using a binary logistic regression to assess the impact of the behavioral primes on the probability of joining the formal market.

The empirical findings of the survey experiment indicate that the biggest obstacle facing informal businesses is finding a formal source of finance that could help them in penetrating the market. Providing informal businesses with information on funding opportunities offered by the ministry of micro, small and medium enterprises (MSME) significantly increased the probability of joining the formal sector to benefit from this opportunity.

This paper is the first to apply behavioral primes, in the form of informational cues, to the Egyptian case of informal business owners. Previous research on the use of behavioral nudges and primes has focused mainly on the western economies.

We expect to provide a complete theoretical framework and large sample evidence on the impact of corporate social responsibility (CSR) on the efficiency of labor investment. We also hope to provide micro-evidence based on labor investment behavior for the two-sided impact of corporate CSR behavior.

This paper measures labor investment efficiency by estimating the difference between actual and expected net hiring of enterprises. CSR is measured on the basis of the CSR score of Chinese listed companies published by Hexun.com. A regression model is constructed to analyze the relationship between CSR and labor investment efficiency. Possible endogeneity problems are controlled by lagging independent variables, propensity score matching method and difference-in-difference method.

Results show that CSR can improve labor investment efficiency by reducing over-hiring and under-hiring in emerging markets. The existence of the mediating effect of agency cost, information disclosure quality and employment fluctuation confirms that CSR improves labor investment efficiency through two mechanisms of corporate governance and labor market friction. The improvement effect of CSR on labor investment efficiency is more significant in non-state-owned, high CEO shareholding ratio and high-average urban wage enterprises.

In conclusion, our study is an important supplement to the existing research on the factors affecting labor investment efficiency. Our research conclusions will be helpful for enterprises in developing countries or enterprises in labor-intensive industries to improve labor investment inefficiency. The conclusion of the mechanism analysis in this paper provides more complete and reliable microscopic evidence for accurately identifying the specific path of CSR's impact on labor investment efficiency. This paper verifies the positive impact of CSR from the perspective of labor investment efficiency in the context of a developing country, which provides evidence for the theoretical conflicts related to CSR based on the effectiveness of enterprise labor investment decisions.

This study explores the influence of the Top Management Team (TMT) social capital on business model innovation in business ecosystems.

This study examines the impact of internal and external TMT social capital on enterprises’ business model innovation, explores the relationship between internal and external TMT social capital, and investigates how business ecosystem health moderates the relationship between external TMT social capital and enterprises’ business model innovation. These hypotheses are proposed and tested using a hierarchical regression analysis with data from 168 Chinese firms.

First, both internal and external TMT social capital exert a significantly positive influence on an enterprise’s business model innovation. Second, internal TMT social capital positively contributes to the development of external TMT social capital, affecting business model innovation. Finally, the moderating effect of business ecosystem health on the relationship between external TMT social capital and business model innovation depends on the dimensions. Specifically, the productivity of the business ecosystem negatively moderates this relationship, whereas the niche creation capability of the business ecosystem has a positive moderating effect.

These findings enrich prior research on business model innovation within the business ecosystem, thoroughly exploring the critical role of TMT social capital. This study reveals the diverse impacts of internal and external TMT social capital on business model innovation and the intricate relationship between these elements. Furthermore, it emphasizes that the success of enterprise’s business model innovation within a business ecosystem depends on the alignment and adaptation to dynamic ecosystem conditions. By presenting these insights, this study provides valuable practical implications for enterprises aiming to cultivate social capital within business ecosystem to facilitate business model innovation.

The purpose of this paper is to discuss how enterprises can effectively perceive and use the digital opportunities brought about by digital technologies and dynamic environments and how they can enhance their capabilities to realize digital transformation and adapt to the development of the digital economy era.

Based on the windows of opportunity theory and strategic cognition theory, this paper conducts an empirical analysis of the questionnaire data of 268 enterprises and discusses the influence of external windows of opportunity and internal windows of opportunity on the digital transformation of enterprises, as well as the action mechanism of strategic cognition and entrepreneurship.

The results show that both the external windows of opportunity and the internal windows of opportunity have significant positive effects on the digital transformation of enterprises. Strategic cognition plays a partial mediating role in the external windows of opportunity and the internal windows of opportunity influencing the enterprise digital transformation process. Entrepreneurship plays a positive regulatory role in the process of external windows of opportunity and internal windows of opportunity influencing strategic cognition.

This paper deepens the relationship between internal and external windows of opportunity and enterprise digital transformation and contributes a new theoretical cognition. This paper integrates the strategic cognition theory to clarify the complex process mechanism of digital transformation using external situational opportunities and internal capabilities. This paper introduces entrepreneurship into the path mechanism of digital transformation and expands the characteristics of the study of digital transformation antecedents to the individual level within the enterprise.

The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.

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.