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This paper systematically analyzes the literature on environmental, social and governance (ESG). It explores the antecedents, decisions and outcomes (ADO) influencing ESG investments; theories used in the literature; publication years, geographical locations and journals of publication of ESG-related articles; notable gaps in research on ESG investments; theoretical and managerial implications and prospective research avenues within the ESG field. All ESG components are interconnected with the United Nations’ Sustainable Development Goals (SDGs).

The PRISMA framework was employed to screen articles from the Scopus database. A total of 386 articles spanning 2011–2024 were included. The search terms used to screen the articles for inclusion were “sustainable finance,” “ESG,” “environment, social, corporate governance,” “green finance,” “green bond,” “social bond,” “blue bond,” “social finance” and “corporate social responsibility.”

The findings indicate that organizations utilize green bonds, blue bonds and green loans to mitigate environmental concerns. To address social issues, companies issue social bonds and sustainable bonds and engage in socially responsible investing. To address concerns about corporate governance, companies emphasize corporate social responsibility and intellectual capital.

The findings can be used to inform policymakers on the implementation of comprehensive regulatory frameworks in the realm of ESG. Tax benefits and subsidies should be extended to firms fostering ESG practices.

This study offers a comprehensive synthesis of the ESG literature by examining the ADO framework, which has not been systematically applied to ESG investments before. It integrates diverse components of ESG investments with the United Nations’ SDGs, providing a unique perspective on how these investments align with global sustainability objectives.

Environmental, social and governance (ESG) performance has received significant attention around the world. Could robust ESG performance become a new advantage for supporting companies’ outward foreign direct investment (OFDI) in emerging markets? Prior studies have not articulated the nexus between ESG performance and OFDI. This paper aims to conduct both theoretical and empirical work to clarify the effect, especially the mechanisms of ESG performance on companies’ OFDI.

Using the data of A-share listed companies in China from 2010 to 2020, this paper empirically tests the effect and the mechanisms of ESG performance on companies’ OFDI.

Firstly, robust ESG performance increases the likelihood of companies engaging in OFDI and also augments the scale of such investments. Within the realm of ESG, environmental performance, social performance and governance performance all play important roles in fostering OFDI. Secondly, strong ESG performance promotes OFDI by enhancing the competitive edge and alleviating financial constraints. Also, environmental performance, social performance and governance performance individually contribute to supporting competitiveness and mitigating financial constraints. Thirdly, the effect of ESG performance on OFDI is particularly pronounced for companies targeting developed countries, those operating in heavily polluting sectors and those with significant institutional investor presence.

This study advances the applicability of the stakeholder theory in the realm of firm internationalization. Moreover, the findings of this paper provide new strategies for promoting the OFDI of companies in emerging market economies.

It is widely acknowledged that the ability of a firm to develop and exploit their innovative capabilities is a critical determinant that maintains their competitive advantage. The purpose is to evaluate the research and development (R&D) inputs and outcomes on the performance of firms in different stages.

Drawing on a sample of 30 firms over 8 years (2009–2016), the results from a three-stage Bayesian stochastic frontier analysis model support were used.

Some interesting findings were discovered. First, the R&D intensity is positively associated with the number of patents granted, which is negatively associated with the number of new drug approvals (NDAs). Second, R&D inputs, including expenditures and human resources, are negatively related to the number of NDAs and firm performance. Third, state-owned firms perform better and have more patents granted than private-owned firms in China. Finally, the traditional Chinese medicine firms and non-coastal firms both gain fewer profits, but they generate more new drugs than chemical drug firms and coastal firms in terms of policy support.

It is revealed that there are no common factors among Chinese pharmaceutical firms except for ownership, and this heterogeneous behavior indicates that there is no common factor for enhancing the efficiency of all Chinese pharmaceutical firms.

In a typical problem of allocating a fixed resource across a set of decision-making units (DMUs), the decision maker will decide how much resource to allocate to each DMU. Real-world decision-making contexts frequently pose challenges in precisely assessing each DMU’s performance on distinct parameters and in ascertaining the relative importance of these parameters, since resource allocation often precedes the decision-making process. Conventional decision-making approaches fall short in effectively addressing such complexities. In this paper, the authors propose a stochastic multi-attribute acceptability analysis (SMAA)-based model that can deal with the resource allocation problem with uncertain attribute values and unknown attribute weights.

The SMAA-based model first regards the resource to be allocated as an evaluation attribute and then proposes a fair resource allocation solution that minimizes the gap between the holistic acceptability of each DMU. To address the optimization of the SMAA-based model, two heuristic strategies were devised: a modified particle swarm optimization (PSO) approach and an adaptive algorithm, both designed to yield acceptable outcomes within a constrained time frame.

The resource allocation model based on SMAA can provide an effective analytical framework for the resource allocation problem of different DMUs in uncertain environments. Meanwhile, the PSO algorithm and adjustment algorithm proposed in this paper can help decision-makers quickly find a fair resource allocation plan.

Primarily, this study introduces a novel approach rooted in SMAA for tackling resource allocation dilemmas where attribute values are uncertain and weight information is absent. Secondly, a fairness-centric strategy that minimizes the disparity in overall acceptability among various DMUs is presented. Thirdly, two heuristic algorithms, namely, PSO algorithm and adjustment algorithm, are developed to solve the problem.

This paper aims to examine the mediating role of employees’ intrinsic motivation in the relationship between perceived ambidextrous organizational culture and innovative behaviour among information technology (IT) sector employees.

The study used a quantitative research methodology, using a questionnaire to gather data from a sample of 510 employees across a range of IT organizations and various roles in the Indian IT sector. Smart partial least squares structural equation modeling Version 3 was used for the analysis and interpretation of the study.

The findings revealed a significant positive relationship between perceived ambidextrous organizational culture and employees’ innovative behaviour in the Indian IT sector. Moreover, the study established that employees’ intrinsic motivation played a significant mediating role in this relationship.

This study stands out for its exploration into how employees’ intrinsic motivation mediates the relationship between ambidextrous organizational culture and innovative behaviour. It offers valuable insights for enhancing organizational creativity by understanding the critical role of intrinsic motivation.

Under the rural revitalization, the effect of China's implementation of rural prefabricated housing is not obvious. Cost has become the biggest obstacle to its development. Therefore, it is necessary to study the factors influencing the cost of prefabricated buildings in villages and clarify the focus of cost control.

This paper focuses on the whole process of prefabricated housing construction in villages in China and uses grounded theory to identify and screen out 27 related factors that affect the construction cost of prefabricated buildings. A system dynamics model is used to dynamically analyze the influencing factors. The engineering examples in rural areas of southern Shaanxi are simulated. Finally, five key factors that influence cost are obtained. Based on this, cost control countermeasures are proposed for rural prefabricated housing in southern Shaanxi.

The results show that: the key factors affecting the cost of prefabricated buildings in villages include the selection of production methods, the degree of design standardization, the quality of construction personnel, the level of construction technology and the circulation cycle of molds. The cost of prefabricated housing in villages can be controlled through five aspects: mass production of components, design exchange and feasibility analysis, improvement of employee professionalism, strict selection of construction schemes and technologies and improvement of mold turnover rate.

The system dynamics model applied in this paper is based on the idealized state. The system boundary is narrow and has a certain subjectivity. It needs further detailed research to make it closer to the engineering practice. In addition, this paper applies the rural engineering example in southern Shaanxi to carry out a single case study, and the universality of the research results needs to be further tested. There are many village construction projects and building types, so the research results can be further enriched through large sample research.

Rural construction is an important step in the implementation of rural revitalization. Exploring the factors that affect the key costs of prefabricated buildings in villages and towns in view of the particularity of rural areas will help provide a reference for their cost control and help the rural development of prefabricated houses.

The research results of this paper can provide a reference for the development of prefabricated buildings in other rural revitalization areas.

Different from the traditional research on urban prefabricated buildings, this paper focuses on rural areas and explores the core factors affecting the cost of prefabricated buildings from the micro level. This study establishes a system dynamics model suitable for the cost control of prefabricated housing at the village level and provides methods for its cost control. Based on the identified key factors affecting costs, cost control measures were proposed for prefabricated housing tailored to the unique characteristics of villages.

This paper aims to address the gaps in current research by exploring how blockchain technology influences corporate green innovation.

This study investigates the potential of blockchain technology to stimulate the green innovation of companies using the difference-in-difference model with a panel data set of 1,803 Chinese listed companies from 2012 to 2019.

The application of blockchain significantly increases the number of green invention patents obtained by companies but has no significant impact on green utility model patents, that is, blockchain applications improve the quality rather than the quantity of green innovation. The role of blockchain in promoting green innovation is particularly pronounced in state-owned enterprises, non-heavily polluting industries and older companies. The use of blockchain technology helps reduce sales costs and boosts research and development investments, thereby encouraging green innovation. Additionally, a company’s internal control quality plays a moderating effect.

Firstly, previous research on blockchain has primarily centered on its relationship with supply chain management. This article empirically tests the impact of blockchain applications on the green innovation of companies using the DID method. Secondly, current studies mainly explore the influencing factors on green invention patents. This article examines the impact of blockchain applications on both green invention patents and green utility model patents and identifies distinct influencing effects. Finally, this article introduces the internal control mechanism of enterprises into the DID model and explores the potential impact of the quality of internal control on the relationship between blockchain and green innovation.

We examine the relationships among leader spirituality, organizational innovativeness, transformational leadership style and project success. Integrating principles of behavioral learning and social learning theories, we argue that spiritual leadership style is positively linked to project success, and this relationship is mediated by transformational leadership. Furthermore, the relationship between leader spirituality and transformational leadership is moderated by organizational innovativeness.

Data are collected from 180 individuals working in seven large project-based organizations from the telecom sector in Pakistan. The individuals comprise engineers, functional managers, dedicated project managers and individuals who have led and/or worked in project teams. Data are analyzed using variance-based structural equation modeling.

Results suggest that the relationship between spiritual leadership style and project success is positive and is partially mediated by transformational leadership. Furthermore, organizational innovativeness positively moderates the spiritual leadership and transformational leadership relationship.

Research calls for examining the relationship between leadership styles and project success. We address this call through examining the role of spiritual leadership style (which is rather ignored in project management literature) for project success. Furthermore, we take a novel evolutionary approach of integrating different leadership styles and indicating determinants as well as contingencies to leadership development.

Given the importance of chatbots in customer service in tourism, this paper aims to understand the drivers that predispose regular consumers of restaurant recommendation chatbots to continue using them.

A total of 386 regular consumers of a chatbot via WhatsApp restaurant recommender responded to an online questionnaire (inspired by scales found in the literature on technology adoption). Structural equation modeling was used to test the hypotheses.

Significant predictors of intention to continue using these chatbots included “effort expectancy (EE),” “hedonic motivation (HM),” “price value (PV)” and “habit (HT).” Specifically, HT still has a long way to go in terms of its performance, and it will be possible to work on it. Furthermore, two variables, EE and HM, act as a bottleneck when it comes to explaining this recurrent usage intention. Factors such as “performance expectancy (PE),” “facilitating conditions (FC)” and “social influence (SI)” did not influence “behavioral intention (BI).” Likewise, the moderating variables, age and gender, are not significant. Finally, the predictive capability of the model is demonstrated. The study findings will enable the development of effective strategies to foster consumer loyalty to this new technology in the restaurant industry.

This study contributes, building on the suitability of the unified theory of acceptance and use of technology 2 model, to explain users’ intention to continue using chatbot tourism services in the context of an information search for an unplanned and varied purchase decision, namely, restaurant recommendation services. To the best of the authors’ knowledge, this is the first analysis of tourist’s intention to reuse a real and fully functional chatbot via mobile instant messaging.

鉴于聊天机器人在旅游客户服务中的重要性, 本研究旨在了解驱动消费者持续使用WhatsApp餐厅推荐聊天机器人的因素。

共收集386名WhatsApp餐厅推荐聊天机器人的常规用户在线问卷数据（问卷设计参考技术采纳相关文献中的量表）。研究采用结构方程模型（SEM）验证假设。

影响用户持续使用意图的显著预测因素包括“努力期望（EE）”、“享乐动机（HM）”、“价格价值（PV）”和“习惯（HT）”。其中, “习惯（HT）”表现仍有提升空间, 而“努力期望（EE）”和“享乐动机（HM）”是解释持续使用意图的瓶颈因素。此外, “绩效期望（PE）”、“促进条件（FC）”和“社会影响（SI）”对“行为意图（BI）”无显著影响。性别和年龄等调节变量同样不显著。研究结果验证了模型的预测能力, 能够为餐厅行业制定有效策略以增强消费者对这一新技术的忠诚度提供指导。

本研究基于UTAUT2模型, 首次分析了消费者在餐厅推荐服务中持续使用移动即时通讯（MIM）聊天机器人的意图, 为探索非计划性和多样化购买决策背景下的信息搜索服务提供了新见解。

With the rapid growth of the gig economy worldwide, gig workers’ perceived algorithmic control has been proven to have a crucial impact on the service performance, well-being and mental health of gig workers. However, the literature suggests that gig workers’ perceived algorithmic control may be a double-edged sword. The purpose of this research is to explore how the perceived algorithmic control of gig workers can accelerate thriving at work.

Based on the model of proactive motivation and work design literature, a three-wave survey was employed, yielding 281 completed responses. The structural equation modeling method was used to test the theoretical hypothesis.

The results indicate that gig workers’ perceived algorithmic control has positive and indirect effects on thriving at work through the mediating role of job crafting. In addition, job autonomy can moderate the mediated relationship; specifically, when job autonomy is high, this mediated relationship will be stronger.

The health and well-being of gig workers is a concern around the world. The findings provide insights for service platform enterprises and gig workers.

Perceived algorithmic control is critical to mental health and positive work experiences during a gig worker’s service process. However, the current literature focuses more on the negative aspects of algorithmic control. This paper provides a comprehensive research agenda for how to accelerate thriving at work for gig workers.