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The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.

About 70% of all aircraft accidents are caused by human–machine interaction, thus identifying and quantifying performance shaping factors is a significant challenge in the study of human reliability. An information flow field model of human–machine interaction is put forward to help better pinpoint the factors influencing performance and to make up for the lack of a model of information flow and feedback processes in the aircraft cockpit. To enhance the efficacy of the human–machine interaction, this paper aims to examine the important coupling factors in the system using the findings of the simulation.

The performance-shaping factors were retrieved from the model, which was created to thoroughly describe the information flow. The coupling degree between the performance shaping factors was calculated, and simulation and sensitivity analysis are based on system dynamics.

The results show that the efficacy of human–computer interaction is significantly influenced by individual important factors and coupling factors. To decrease the frequency of accidents after seven hours, attention should be paid to these factors.

The novelty of this work lies in proposing a theoretical model of cockpit information flow and using system dynamics to analyse the effect of the factors in the human–machine loop on human–machine efficacy.

Researchers have tried analysing how the organizations’ practices of doing good can help improve their employees’ satisfaction over the past couple of decades. Employee satisfaction has a complicated relationship with a company’s corporate social responsibility (CSR) activities. Subsequently, the purpose of this paper is to conduct a bibliometric analysis and a literature review to trace the links between CSR and employee satisfaction, summarize and analyse the advances in this field, the knowledge gaps, publishing trends and further directions for future research.

The authors conducted a bibliometric analysis followed by a literature review of papers indexed in the Scopus database and published between 2000 and 2022. A total of 233 papers were identified, while 152 of them met the inclusion criteria for the analysis.

The subsequent analysis sheds light on the overlaps and connections between the two phenomena in human resource management (HRM). The authors outline potential avenues for future research and practical insight into how to leverage CSR activities for increasing work satisfaction.

By detailing the different ways CSR and employee satisfaction impact one another, analysing their relations and other supporting constructs, the authors contribute to the academic discourse by synthesizing prevailing literature and introducing practical guides for human resource (HR) professionals, managers and executives to manage turbulent surroundings more effectively, considering the major disruptions post-COVID-19 and the adoption of advanced technologies.

This study aims to address the noted gap in comprehensive overviews detailing the developmental trajectory of Islamic finance (IF) as an interdisciplinary academic field.

The study introduces a unique approach using the combined methodologies of co-word analysis and main path analysis (MPA) by examining a broad collection of IF research articles.

The investigation identifies dominant themes and foundational works that have influenced the IF discipline. The data reveals prominent areas such as Shariah governance, financial resilience, ethical dimensions and customer-centric frameworks. The MPA offers detailed insights, narrating a journey from the foundational principles of IF to its current challenges and opportunities. This journey covers harmonizing religious beliefs with contemporary financial models, changes in regulatory landscapes and the continuous effort to align with broader socioeconomic aspirations. Emerging areas of interest include using new technologies in IF, standardizing global Islamic banking and assessing its socioeconomic effects on broader populations.

This study represents a pioneering effort to map out and deepen the understanding of the IF field, highlighting its dynamic evolution and suggesting potential avenues for future academic exploration.

This study investigates how the initiatives and controversies related to environmental, social and governance (ESG) explain firm efficiency.

Firstly, this study applies data envelopment analysis with the epsilon-based measure to estimate the firm efficiency of 80 companies in the Chinese energy sector in 2022. This approach accounts for the diversity and relative importance of inputs and outputs from a multidimensional perspective. Secondly, this study regresses the variables of ESG initiatives and controversies on the estimated firm efficiency scores through a generalised additive model, which can capture nonlinear patterns.

This study finds that a) the samples have i) about 49% room for improvement in efficiently optimising their resources and business outcomes and ii) the highest scores in governance initiatives, followed by social initiative. b) 69% of them have controversy scores that are greater than the average value. c) A cluster analysis indicates that companies with higher social initiatives have higher firm efficiency than their counterparts. d) ESG initiatives and controversies are nonlinearly related to firm efficiency.

The findings have practical implications for policy makers and managers who prioritise ESG, particularly regarding (i) the need to examine firm performance from a multidimensional perspective, that is, to measure multiple inputs and outputs simultaneously, (ii) the nonlinearity of the nexus between ESG and efficiency in graphical forms, and (iii) the need to balance ESG initiatives and address ESG controversies.

This study integrates statistical approaches in examining and ensuring sustainable growth and efficiency within the Chinese energy sector and beyond.

This study aims to examine the historical development, present state and potential future directions of the integration between building information modeling (BIM) and life cycle assessment (LCA) in the field of construction. Additionally, this paper identifies current problems while offering insight into worldwide BIM research trends.

This study uses text mining on unstructured abstracts, a novel approach not previously documented in BIM research. By conducting a comprehensive systematic assessment of academic literature, this work uses advanced bibliometric approaches to examine the developmental trajectory of the integration of BIM and LCA. The research incorporates co-citation and keyword co-occurrence mapping, providing a complex visual depiction of the interconnectedness of information across different periods.

The results of this analysis reveal the historical development of the integration of BIM and LCA, including its roots and the initial research that established the foundation for further investigations. The aforementioned seminal works signify the inception of the discipline, serving as a source of inspiration for current scholarly investigations. Currently, there is a complex network of interdisciplinary cooperation that can be observed, combining knowledge and perspectives from the fields of design, engineering, construction and sustainability.

This research contributes novelty to the scholarly discourse by offering a holistic and up-to-date panorama of the dynamic BIM and LCA research landscape. It identifies emerging trends, influential contributors and uncharted territories, thus providing a foundation for scholars to contribute meaningfully to the advancement of knowledge in sustainable construction practices.

The purpose of this study was to investigate work-related adaptive performance from a longitudinal process perspective. This paper clustered specific behavioral patterns following the introduction of a change and related them to retentivity as an individual cognitive ability. In addition, this paper investigated whether the occurrence of adaptation errors varied depending on the type of change content.

Data from 35 participants collected in the simulated manufacturing environment of a Research and Application Center Industry 4.0 (RACI) were analyzed. The participants were required to learn and train a manufacturing process in the RACI and through an online training program. At a second measurement point in the RACI, specific manufacturing steps were subject to change and participants had to adapt their task execution. Adaptive performance was evaluated by counting the adaptation errors.

The participants showed one of the following behavioral patterns: (1) no adaptation errors, (2) few adaptation errors, (3) repeated adaptation errors regarding the same actions, or (4) many adaptation errors distributed over many different actions. The latter ones had a very low retentivity compared to the other groups. Most of the adaptation errors were made when new actions were added to the manufacturing process.

Our study adds empirical research on adaptive performance and its underlying processes. It contributes to a detailed understanding of different behaviors in change situations and derives implications for organizational change management.

Research on solar energy adoption offers a multidimensional scope and warrants exploration from multiple perspectives, including political, economic, management, behavioral, policy and innovation aspects. The aim of this paper is to comprehensively consolidate major research findings on the premise of solar energy adoption and to disclose gaps in the existing literature.

A bibliometric analysis of the vast literature is conducted on 1,009 meticulously shortlisted articles following the semi-systematic literature review methodology. A text analytics tool named BibExcel is used for synthesizing the literature, and the results are visualized using Gephi, Pajek and a spreadsheet application.

This paper reports the evolution of research in the selected domain. It is noted that research in this domain was primarily concentrated on four broad themes, namely, peer effects and spatial patterns, public perceptions, policies and economics and technological evolution. The analysis further reveals the merging of two of these themes as a result of transdisciplinary research and also projects future research trends emphasizing political interventions in technological evolution and diffusion.

Research trends and future research scope are identified and discussed in detail. The information revealed from the analysis, along with the research implications, will assist policymakers in noting the flaws in the current doctrines and practices, entrepreneurs in understanding potential enablers and barriers influencing solar energy adoption and budding scholars in comprehending the current research status and framing promising research objectives to close the existing research gaps.

Due to the extremely complicated and unpredictable outside world, using and unlocking the potential of learning agility (LA) has become a key part of making businesses more competitive, and there is a lot of new research being produced on this topic very quickly. Thus, this study aims to carry out a bibliometric analysis to systematically analyse the existing literature on LA and propose an integrated framework depicting various predictors, mediators and outcome variables covered in the LA research. Moreover, this study lays out a rich and detailed agenda for future research and enhances understanding of LA by suggesting future research questions.

This study applied bibliometric analysis using the Scopus database. This study applied bibliometric analysis and cluster analysis to examine the contributions of research constituents (authors, institutions, countries and journals) and their structural and thematic relationships (co-citation network and thematic trends). The most important insights were used to propose an integrated conceptual model.

Based on the results of the performance analysis, this study discovered that the USA is the most productive country in this research field, followed by Belgium, Australia, Korea and India. In addition, the findings highlight the most prominent journals, authors and countries contributing to LA, document citations and theories contributing to the field of LA. This study identifies four emerging future research themes (clarity of construct, identification of variables to be studied with LA, strategies enhancing LA and context of study) and proposes subsequent research questions using science mapping analysis.

A review of existing literature on LA provides a clear understanding of the current and future state of research on this topic. And, from a practical standpoint, this study highlights emergent clusters that will help practitioners build LA as a tactical reaction to the current volatile, uncertain, complex and ambiguous environment.

This study is relevant as it aims to systematically review articles on LA and proposes an integrated conceptual framework based on existing literature that will serve as a guide for existing and future research in this area.

The paper aims to reveal the intellectual structure of studies on artificial intelligence (AI) in the fields of tourism and hospitality. Evaluations regarding the intellectual structure have been made based on co-author, co-word and citation.

The study is exploratory in nature. The study, using bibliometric analysis, provides a Web of Sciences (WOS) overview. The data has been obtained from the WOS database by coding as “artificial intelligence” and “tourism” and “hospitality.” VOSviewer program has been used to obtain and analyze the data.

The findings of the research show that studies on the use of AI in tourism and hospitality have become very popular, especially in the last 4 years. The authors of the study are working in the tourism and hospitality fields and have a high h-index. Generally, in current AI studies in tourism, topics such as robot, automation, ChatGPT, technology adoption and mechanical learning are studied. It has also been determined that topics related to the future of destinations and literature reviews are also discussed.

Although this paper examines all studies identified as a result of filtering, the analysis is limited to 195 studies. However, due to the widespread use of AI in tourism-related studies recently, bibliometric analysis has been made with extensive filtering. As studies on the subject become more widespread in the coming years, it would be useful to repeat similar studies by filtering with more specific quotas.

There are a few similar studies on the subject in the field. However, these studies need to be repeated at certain periods. This paper contributes to monitoring the literature of AI studies, which are new to use in tourism and hospitality, and to the formation of a theoretical framework on the subject.