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This study investigated the influence of teachers on undergraduate students’ development of research aspirations and the mechanisms behind this process.

Employing social cognitive career theory, the study gathered data from 232 undergraduates, developed a structural equation model via the maximum likelihood method and executed empirical testing.

The findings reveal that neither direct nor emotional mentoring independently satisfies students’ needs for self-efficacy and aspiration in research nor significantly influences research interest. Specifically, the study demonstrates that (1) research self-efficacy, outcome expectations and research interest significantly shape research aspirations; (2) an overemphasis on direct mentoring might impede research aspiration development and (3) a focus on emotional mentoring, while overlooking direct mentoring, could result in diminished research self-efficacy.

This research pioneers a comprehensive analysis of the role of teachers in shaping undergraduate research aspirations through the lens of social cognitive career theory. It underscores the critical need to both balance mentoring approaches and foster intrinsic research motivation.

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.

In the accounting field, sustainability accounting (SA) has evolved as a valuable tool that links improvements in environmental, social and governance issues to financial performance. This study aims to examine the structure and evolution of SA research, map the state of knowledge and analyse the literature trends and gaps.

The study adopts a bibliometric review technique with data sourced from the Scopus database. A total of 7,049 extant literature spanning from 1982 to 2022 was analysed using the VOSviewer software.

The authors find a significant growth in the number of publications on SA research, primarily driven by collaboration among researchers from Europe and America. The analysis highlights emerging themes, structure and discusses in detail the changing phases of SA research over the past four decades while highlighting key events that have impacted the development of SA research. Furthermore, the dominant theories used by extant studies are discussed and potential avenues for future research are provided. The authors draw the attention of the research community to the dominant authors, the most cited articles, prominent publication outlets and countries advancing research in this field.

This study advances knowledge on SA research by providing a retrospective assessment of the state of knowledge in the field while highlighting avenues for future research.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

This paper investigates the dual interactive effects of manufacturer encroachment on the supply chain and retailer provision of retail services.

Consider a supply chain dominated by manufacturers, retailers, and e-commerce platforms, with the manufacturers selling the same product online and offline. Utilizing Stackelberg’s game theory, examples of wholesale and retail prices and profits of participants in the supply chain under different channels are analyzed. An effective encroachment strategy for manufacturers facing different retail service investment strategies of traditional retailers is given.

When traditional retailers do not invest in retail services, they will lose more profit due to competition with the manufacturer. At this time, the retailer does not want the manufacturer to encroach. The traditional retailer’s investment in retail services will enhance its and the manufacturer’s profits, incentivizing the manufacturer to pursue an aggressive expansion strategy.

(1) Considers a situation where the selling efficiency of the manufacturer is lower than that of the traditional retailer. (2) The interaction between traditional retailers’ retail service investment strategies and manufacturers’ encroachment strategies is investigated where the manufacturer is the dominant player. The three modes of online direct sales, resale, and third-party platform agency are compared to provide a basis for decision-making on different types of manufacturers’ encroachment. (3) Offline retail services not only directly increase sales in the offline market but also indirectly have a negative effect on the online market.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

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.

The purpose of this study is to investigate the relationship between sustainable leadership and sustainable project performance. Specifically, the study aims to examine the mediating role of knowledge integration, examining how knowledge integration within an organization influences project outcomes. In addition, the study seeks to explore the moderating role of top management knowledge values, examining how the values and beliefs of top management influence the relationship between sustainable leadership and project performance.

A three-wave survey of 392 employees working in construction sector projects in Pakistan used both hierarchical regression analysis and Hayes’ PROCESS macro method to evaluate the hypotheses.

The study results show that sustainable leadership positively relates to sustainable project performance and knowledge integration mediating this relationship. In addition, the top management knowledge value moderates the indirect effect of sustainable leadership on sustainable project performance via knowledge integration.

Although the model was tested using three-wave data, it is important to note that the data were obtained from a single source. Therefore, it is possible that common method bias may have influenced the results, and this cannot be disregarded.

Organizations seek to prioritize sustainability and integrate sustainability considerations into their project management processes. Organizations can achieve improved sustainable project performance by investing in sustainable leadership development, fostering a culture of knowledge sharing and learning, prioritizing top management support for sustainable performance and integrating sustainable considerations into project management processes.

The study’s grounding on organizational learning theory adds an original and valuable perspective to the relationship between sustainable leadership and sustainable project performance. This investigation is original, as it combines sustainable leadership, knowledge integration and the moderating role of top management knowledge value to understand their impact on sustainable project performance. This unique approach contributes to the literature by providing new insights into these relationships and mechanisms in the construction industry.

This study aims to explore the spatial impact of an increase in the minimum wage on the labor productivity of star-rated hotels in China.

The impact is analyzed by using the dynamic spatial Durbin model.

The authors find a U-shaped link between the increase in minimum wage and labor productivity of star-rated hotels. The long-term impact of a minimum wage increase has a greater influence on labor productivity than its short-term effects. While there is no notable spatial spillover impact observed in the sample of 31 provinces in China, the authors do identify a spatial spillover effect of the minimum wage rises on the labor productivity of star-rated hotels in the central area. Furthermore, they observe heterogeneity across China. The eastern and western regions exhibit a U-shaped relationship, whereas the central region exhibits an inverted U-shaped relationship.

The findings of this study allow government agencies to get a more comprehensive comprehension of the actual consequences of minimum wage hikes on the tourism and hospitality sector, thereby establishing a solid basis for them to develop appropriate policies. Moreover, it offers a variety of suggestions aimed at enhancing the quality and efficiency of hotel management.

Research on the effects of minimum wage standards is scant in the hospitality industry. Based on human capital investment theory, this study examines the effect of the minimum wage standard hikes on labor productivity of star-rated hotels from the spatial perspective, filling the existing research gap.