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This paper aims to explain the causal complexity between ecosystems of doing business and living standards based on the theoretical model of the ecosystem of doing business proposed by Li (2019) and Du et al. (2020). By integrating ecological theory, transaction cost theory and institutional logics theory, this study explored effective ecosystems of doing business that achieve high living standards and explained the interpretive mechanisms behind different ecosystems of doing business. Moreover, this study also analyzed whether there were any necessary elements that lead to high living standards and discussed how the interactions between these elements influence carrying capacity and transaction costs from government logic and market logic, thus affecting living standards.

In this study, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) were combined to analyze the data from the 2020 China City Statistical Yearbook, covering the main socioeconomic statistical data of cities at all levels in 2019.

This study found that no individual factor of the ecosystems of doing business was necessary to achieve high living standards, but the high level of human capital, innovation capacity, financial access and market demand play a significant role in achieving high living standards. Furthermore, two effective types of ecosystems of doing business lead to high living standards, namely, market dominance (government’s “invisible hand” or “nudging hand”) and government–market logic mutualism/symbiosis (government’s “helping hand”).

First, this work found that individual elements were not a necessary condition for high living standards, not only in kind but also in degree, complementing fsQCA with NCA, which indicates that environmental elements can be substituted by others. Second, this study considered the complex effects and explained the mechanisms behind different ecosystems of doing business, drawing on ecological theory, transaction cost theory and institutional logics theory from a configurational perspective. This study deepened the theories’ applications in the field of living standards and further discussed the elements interactions. Third, this study introduced configurational perspective and QCA into living standards research and adopted a mixed method that combines fsQCA and NCA to analyze the causal complexity between ecosystems of doing business and people’s living standards.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

Addressing the significant differences between referral programs and traditional promotional marketing, this paper aims to investigate and examine the impact of how reward-related information is presented within referral programs and how it interacts with reward size and reward allocation.

This study adopts framing effect and equity theory to build the relationship between reward presentation, reward size and reward allocation. Then, two scenario-based experimental studies are designed and conducted on Amazon Mechanical Turk.

The results show that there is no direct impact of reward presentation on referral likelihood, while the effect relies on reward size. As the levels of reward size increase, the referral likelihood gradually shifts from percentage form to dollar form as perceived size mediates the interaction effect on referral likelihood. Further, adding information about reward allocation also indicate the different impacts of equity and inequity on influencing the above findings.

The study contributes to the literature by introducing reward presentation and emphasizes its impact on individual’s behavior decisions in the context of referral programs. This study extends and broadens the scope and effectiveness of the framing effect on traditional promotional marketing strategies, while also bridging the gap in the literature by examining the combined role of information about rewards.

The purpose of this paper is to propose a new grey prediction model, GOFHGM (1,1), which combines generalised fractal derivative and particle swarm optimisation algorithms. The aim is to address the limitations of traditional grey prediction models in order selection and improve prediction accuracy.

The paper introduces the concept of generalised fractal derivative and applies it to the order optimisation of grey prediction models. The particle swarm optimisation algorithm is also adopted to find the optimal combination of orders. Three cases are empirically studied to compare the performance of GOFHGM(1,1) with traditional grey prediction models.

The study finds that the GOFHGM(1,1) model outperforms traditional grey prediction models in terms of prediction accuracy. Evaluation indexes such as mean squared error (MSE) and mean absolute error (MAE) are used to evaluate the model.

The research study may have limitations in terms of the scope and generalisability of the findings. Further research is needed to explore the applicability of GOFHGM(1,1) in different fields and to improve the model’s performance.

The study contributes to the field by introducing a new grey prediction model that combines generalised fractal derivative and particle swarm optimisation algorithms. This integration enhances the accuracy and reliability of grey predictions and strengthens their applicability in various predictive applications.

This study explores the impact of green supply chain integration (GSCI) on enterprise performance (EP) from an organizational capability perspective. Additionally, this study investigated the mediating effect of ambidextrous green innovation (AMGI) and the moderating effect of green legitimacy (GL).

This study followed a five-step systematic review of the literature to ensure the auditability and repeatability of the concept development process: (1) formulation of the question, (2) research area orientation, (3) selection and evaluation of research literature, (4) data analysis and synthesis and (5) reporting and application of results.

This study clarified the concepts and dimensions of four relevant variables and, based on the organizational capability theory (OCT), ambidextrous innovation theory (AIT) and new institutional theory (NIT), explained the interactions among these variables and proposed a conceptual framework. In addition, an agenda for future research has been suggested.

This study provides a new direction for future GSCI research and practice in emerging economies. Enterprises should focus on developing GSCI capabilities to promote its positive impact on enterprise performance through AMGI adoption. Moreover, they must emphasize the acquisition of GL, which provides a certain degree of security, to realize the benefits of AMGI.

This study aims to find that entrepreneurial activities can spur entrepreneurial firms' superior performance, but this effect is contingent on the different levels of government innovation subsidies. Extending the institutional perspective explanation and entrepreneurship perspective explanation, this study examines how a firm's entrepreneurial orientation (EO) affects its superior performance when it receives innovation subsidies.

Entrepreneurial firms in China, an emerging economy, are taken as the context for empirical evidence. A large-scale questionnaire survey is used for firm data collection. Ordinary least squares (OLS) regression is employed to test the hypothesized model using a sample of 287 entrepreneurial firms.

The results show a curvilinear, inverse U-shaped moderating effect in the relationship between EO and firm performance. This relationship is strongest at intermediate levels of innovation subsidies but is comparatively weaker when innovation subsidies are low or high.

The study contributes to entrepreneurship research by examining the nonlinear moderating effect of innovation subsidies on entrepreneurial firms' performance. The study also contributes to entrepreneurship theory by elaborating on the innovation subsidy scheme and how it facilitates the development of entrepreneurial activity.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.

The construction industry is one of the most stressful industries. Thus, quantity surveyors (QSs) who work at sites frequently experience high levels of occupational stress. The gender of a QS also has a significant impact on his/her occupational stress. Hence, this study aims to investigate the management of occupational stress in QSs working at sites for contractors (hereinafter referred to as CQSs).

The study adopted a mixed approach using semi-structured interviews and a questionnaire survey for female and male CQSs to identify, validate and rank the stressors and symptoms of occupational stress in CQSs and the strategies of managing that stress based on their significance levels. Manual content analysis and the mean weighted rating were used to analyse the data collected.

Heavy workload was the most significant occupational stressor of CQSs, whereas sleeping disorders were their primary symptom of occupational stress. Establishing a proper work programme was identified as the most effective stress management strategy for male and female CQSs. This study shows that many site QSs are stressed owing to their heavy workloads and work obligations and that their stress-related attributes significantly depend on their genders.

This study is significant because no previous studies have been conducted on managing occupational stress in CQSs in male and female CQSs. The study findings can be used to identify the stressors and symptoms of occupational stress in CQSs early and use appropriate management strategies to enhance the work satisfaction and productivity of CQSs suffering from occupational stress.

This study aims to reconstruct how smallholder farmers implement livelihood adaptation strategies to survive and escape poverty, thereby mitigating or eliminating potential livelihood risks by utilizing their available assets.

This research employed a qualitative approach. For the collection of primary data, the researcher conducted observations and in-depth interviews and engaged with the lives of smallholder farmers during the data collection period.

Among the various livelihood adaptation strategies, only migration and profit-sharing strategies enable smallholder farmers to escape poverty. However, migration is an unsustainable adaptation strategy. When farmers move to new locations, they often resort to slash-and-burn methods for clearing land, which can lead to forest degradation and deforestation. Profit sharing is a sustainable livelihood adaptation strategy that falls into a different category. This approach can lift farmers out of poverty, increase their income and have no negative environmental impact. Other adaptation strategies include adjustments to traditional agriculture, both on and off-farm diversification, involving the family in income generation, reducing farming costs, practicing frugality in post-harvest processes, converting land from coffee cultivation to other crops and borrowing money and selling owned assets. Smallholder farmers implement these strategies to survive the existing economic conditions.

The profit-sharing strategy was a novel livelihood adaptation approach that previous studies had yet to uncover at the research site. In this strategy, farmers assume the roles of both managers and laborers simultaneously during farming, while toke (the capital owners) play the role of farming funders. The generated profit is then shared between farmers and toke based on the agreement established at the outset of their collaboration.

This study aims to investigate the factors influencing the social responsibility performance of Belt and Road Initiative (BRI) megaprojects. Specifically, it examines the role of isomorphic pressures and the joint influence of perceived benefits and top management support on megaproject social responsibility performance (MSRP).

Drawing from institutional theory, social exchange theory, and top management literature, this study established a conceptual model featuring eleven hypotheses. Subsequently, a questionnaire survey was administered to collect data from 238 actively engaged participants in BRI megaprojects. Structural Equation Modelling was utilised to analyse the data.

The empirical findings indicate that mimetic and coercive pressures positively influence MSRP. Perceived benefits and top management support significantly enhance MSRP. Moreover, perceived benefits and top management support partially mediate the effects of coercive and mimetic pressures. However, when it comes to normative pressures, their impact on MSRP is solely channelled through the support of top management.

This study is one of the early endeavours to explore the factors influencing the social responsibility performance of BRI megaprojects. It sheds light on the interplay between external pressures and internal factors in shaping social responsibility efforts in these projects. These findings are of particular significance for BRI actors and stakeholders, offering guidance for enhancing social responsibility strategies within the context of BRI megaprojects.