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We examined who is more likely to use flexible work arrangements (FWAs) to alleviate work-family conflict (WFC) and under what conditions the use of FWAs actually reduces WFC.

We tested the model using survey data collected at two time points from 217 employees.

Proactive employees are more likely to use flextime to alleviate WFC (b = −0.03; 95% biased-corrected CI: [−0.12, −0.01]) and this mediation relationship is not moderated by their level of low work-to-nonwork boundary permeability. In addition, only when proactive employees have a low work-to-nonwork boundary permeability does their use of flexplace alleviate WFC (b = −0.07, 95% bias-corrected CI: [−0.1613, −0.0093]).

We expand our understanding of who is more likely to utilize FWAs by identifying that employees with proactive personality are more likely to use flextime and flexplace. We also advance our understanding regarding the conditions whereby FWA use helps employees reduce WFC by identifying the moderating role of work-to-nonwork boundary permeability on the relationships between both flextime and flexplace use on WFC.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.

The purpose of this study is to develop a framework for the perceived intelligence of VAs and explore the mechanisms of different dimensions of the perceived intelligence of VAs on users’ exploration intention (UEI) and how these antecedents can collectively result in the highest level of UEI.

An online survey on Amazon Mechanical Turk is employed. The model is tested utilizing the structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach from the collected data of VA users (N = 244).

According to the SEM outcomes, perceptual, cognitive, emotional and social intelligence have different mechanisms on UEI. Findings from the fsQCA reinforce the SEM results and provide the configurations that enhanced UEI.

This study extends the conceptual framework of perceived intelligence and enriches the literature on anthropomorphism and users’ exploration. These findings also provide insightful suggestions for practitioners regarding the design of VA products.

Although the importance and variety of emotions have been emphasized in existing literature, studies on discrete emotions remain limited. This study aims to propose a method for more precise recognition and calculation of emotions in massive amounts of online data on attraction visitor experiences and behaviour, by using discrete emotion theory.

Using HowNet’s word similarity calculation technique, this study integrated multiple generic dictionaries, including the sentiment vocabulary ontology database of the Dalian University of Technology, the National Taiwan University Sentiment Dictionary and the Boson Dictionary. Word2vec algorithm filters emotion words unique to hospitality and tourism in 1,596,398 texts from Sogou News, Wikipedia and Ctrip reviews about attractions, and 1,765,691 reviews about attractions in China.

The discrete sentiment dictionary developed in this study outperformed the original dictionary in identifying and calculating emotions, with a total vocabulary extension of 12.07%, demonstrating its applicability to tourism.

The developed new dictionary can be used by researchers and managers alike to quickly and accurately evaluate products and services based on online visitor reviews.

To the best of the authors’ knowledge, this study is the first to construct a sentiment dictionary based on discrete emotion theory applicable to hospitality and tourism in the Chinese context. This study extended the applicability of affective psychology to hospitality and tourism using discrete emotion theory. Moreover, the study offers a methodological framework for developing a domain-specific sentiment dictionary, potentially applicable to other domains in hospitality.

This study aims to examine the present condition of blockchain technology (BT) applications in auditing by analyzing journal publications on the topic to acquire a better understanding of the field.

This study makes use of the Bibliometric Analysis method and gathered 725 papers from the Web of Science and Scopus databases in the management and accounting, business, financial, economic and social science, as well as decision sciences fields from 2017 to 2021 using the R-Package Bibliometrix Analysis “biblioshiny”.

The findings revealed that blockchain research in terms of auditing has already increased and started to spark a quick rise in popularity, but is still in its initial phases with important quality though less in quantity. Moreover, the Journal of Emerging Technologies in Accounting is the most prolific journal with 2019 as the highest publication year, with the United States and China as the most cited countries in this field. Furthermore, in this field, there are much research topics involving blockchain, audit and smart contracts; and there is less involving data analytics, governance, hyperledger, distributed ledger and financial reporting. Additionally, Sheldon (2019) and Smith and Castonguay (2020) are the most productive authors in the field in terms of the H-index.

This study has certain limitations such as the fact that it only looked at 105 papers in the domains of finance, business, economics, accounting, management as well as multidisciplinary science. Moreover, the research’s data and dates have an impact on the results dependability. As this is an original topic, fresh studies are anticipated to remain to shine a spotlight on and suggest answers to blockchain’s implications on auditing. Additionally, the period of time was limited to only the last five years, from 2017 to 2021. As a result, extensive study into the topic is required since there is currently a research deficit in the blockchain field in the setting of auditing. So, new research is required to offer new frameworks and understandings for describing the blockchain function in auditing, including processes, techniques, security, as well as timeliness. Investigations in unique circumstances and research employing innovative research methodologies for discovering the new issue would be valuable in acquiring a higher grasp of the complexities faced.

This research contributed to the field by assessing the present state of the art of research on the usage and use of BT in finding research gaps, the audit profession and, most importantly, recommending a future direction for researchers in the subject.

This study aims to solve the problems of large training sample size, low data sample quality, low efficiency of the currently used classical model, high computational complexity of the existing concern mechanism, and high graphics processing unit (GPU) occupancy in the current visualization software defect prediction, proposing a method for software defect prediction termed recurrent criss-cross attention for weighted activation functions of recurrent SE-ResNet (RCCA-WRSR). First, following code visualization, the activation functions of the SE-ResNet model are replaced with a weighted combination of Relu and Elu to enhance model convergence. Additionally, an SE module is added before it to filter feature information, eliminating low-weight features to generate an improved residual network model, WRSR. To focus more on contextual information and establish connections between a pixel and those not in the same cross-path, the visualized red as integer, green as integer, blue as integer images are inputted into a model incorporating a fused RCCA module for defect prediction.

Software defect prediction based on code visualization is a new software defect prediction technology, which mainly realizes the defect prediction of code by visualizing code as image, and then applying attention mechanism to extract the features of image. However, the challenges of current visualization software defect prediction mainly include the large training sample size and low sample quality of the data, and the classical models used today are not efficient, and the existing attention mechanisms have high computational complexity and high GPU occupancy.

Experimental evaluation using ten open-source Java data sets from PROMISE and five existing methods demonstrates that the proposed approach achieves an F-measure value of 0.637 in predicting 16 cross-version projects, representing a 6.1% improvement.

RCCA-WRSR is a new visual software defect prediction based on recurrent criss-cross attention and improved residual network. This method effectively enhances the performance of software defect prediction.

With the growing global emphasis on environmental, social and governance (ESG) criteria, it is crucial to investigate the factors that influence individuals' intentions to invest in ESG and to understand the underlying mechanisms at play. This study constructs a theoretical model, grounded in the Fogg behavioral model (FBM), and explores the mediating role of ESG investment attitudes in shaping individuals' ESG investment behaviors.

A survey was conducted among ESG investors and potential ESG investors in China, resulting in 613 valid responses regarding ESG investment. The partial least squares structural equation modeling (PLS-SEM) approach was utilized to evaluate the proposed model and test the hypotheses.

The results reveal that future orientation, ESG investment bias and perceived ESG investment performance are significant determinants of ESG investment intentions, with attitude playing a partially mediating role. Furthermore, government support moderates the relationship between perceived ESG investment performance and investment intention.

This study expands the application of the FBM to the context of ESG investment and introduces a novel conceptual framework for understanding ESG investment behavior. The findings provide valuable insights for enterprises and institutions involved in ESG investment, aiding them in identifying and targeting potential investors more effectively. Additionally, the study offers a foundation for policymakers to devise strategies that promote sustainable development.

This paper explores the Entrepreneurial Well-Being (EWB) of expatriate entrepreneurs in China. Through the analysis of their contextualised lived experience across the entrepreneurial journey, the paper proposes a novel theorisation of EWB.

This study adopts an interpretivist approach of abductive reasoning to analyse the data from 50 in-depth interviews conducted with expatriate entrepreneurs in China. Expatriate entrepreneurs are confronted with enhanced challenges in their host country, leading to particular emotional engagement with the entrepreneurial journey.

Findings show the importance of life situations, emotions and relatedness in the entrepreneurial process and the EWB of expatriate entrepreneurs. Theorising from their lived experiences, the paper presents EWB as a dynamic process. It further theorises this process as a constant, ongoing interaction and integration between the self and world, in an interplay of being and becoming. Such theorisation contributes first to advancements in the EWB literature, with a stronger emphasis on the entrepreneurial aspect. The paper also contributes to discussions on contextualised entrepreneurship by stressing the role of emotions and relatedness in the pursuit of EWB.

Entrepreneurship is a global phenomenon, which is often presented as a suitable alternative career path for migrant and expatriate individuals. However, the importance of EWB for entrepreneurs requires further attention from policy-makers, support institutions and entrepreneurs themselves. By theorising EWB as a processual journey of being and becoming and the relation between the self and world, this paper opens avenues for innovative support policies and practices aiming at developing the full potential of individuals in entrepreneurship and promoting both the happiness index and the global index of society.

This chapter specifically examines the convergence (divergence) effect of agricultural production by sector and the effect of agricultural production on environmental sustainability using West African countries as a case study. Annual time series variables covering the periods from 2000 to 2022 were empirically analysed using system dynamic panel-data estimation. Results showed significant beta-divergence in crop production, livestock production and total agricultural production, with a half-life of divergence rates of 10.71%, 13.15% and 16.91%, respectively, for crops, livestock and aggregate agricultural production. It was also found that the consumer prices index had a positive and significant effect on crop production, livestock production and total agricultural production. The findings also showed that crops and livestock production had a negative and significant effect on arable land and a positive and insignificant effect on CO₂ emissions. Also, total agricultural production had a negative and insignificant effect on arable land and a positive and insignificant effect on CO₂ emissions. It was also found that gross fixed capital formation had a negative and significant effect on arable land and a negative and insignificant effect on CO₂ emissions. The government and pertinent parties ought to promote sustainable farming practices such as conservation agriculture, rotational grazing, agroecology and reduced dependency on chemical inputs. Policies that support legislation that provide financial incentives for environmentally sustainable agricultural activities and encourage of preservation of biodiversity are suggested.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.