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Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and centrality in influencing tourists’ intention in the context of developing countries such as Tanzania remains largely unaddressed. This study, therefore, examined the relationship between celebrity involvement and domestic tourists' intentions to visit tourist attractions, attitude being the mediating variable.

A questionnaire was self-administered on a convenient sample of 279 domestic tourists in the Tanzania’s four largest regions, namely, Dar es Salaam, Mbeya, Arusha and Mwanza. Employing a quantitative research approach, structural equation modelling was performed to test the cause-and-effect relationships between celebrity involvement and tourists’ intentions before testing the mediating role of attitude in such a relationship. Confirmatory factor analysis was also performed to test the measurement models.

Attraction emerged to be the main determinant of the celebrity dimension that significantly influenced domestic tourists’ travel intentions, whereas attitude partially mediates such a relationship. Moreover, Bongo Fleva musicians, particularly Diamond Platnumz, one of the leading celebrities in this genre, were found to influence most of the respondents’ travel intentions – he posted a picture on his Instagram account of him touring the Serengeti National Park.

The study focused on domestic tourists residing in four of the Mainland Tanzania’s largest regions, hence excluding those residing on the islands of Unguja and Pemba. Due to cultural differences, including the islands not only could unleash new perspectives on celebrity involvement dimensions but also could have introduced new determinants of travel intentions.

This study offers guidance to tourism businesses on designing their marketing campaigns that they should harness celebrity’s attractive qualities effectively. The focus should be directed not only towards linking destinations with celebrities but also on stimulating positive perception of those destinations, aligning with the attitudes of their followers.

The study has set out a new perspective for researchers, practitioners and tourism businesses to refine their promotional strategies and for academicians to gain a deeper understanding of visitor behavioural intention dynamics.

This study has proposed and verified that attraction is a dominant determinant compared to self-expression and centrality in explaining tourists’ travel intentions and attitudes, which play a significant role in explaining such a relationship. Although the study employed a modified theory of planned behaviour in a celebrity involvement study, the findings have broadened the understanding and its applicability in the context of a developing country.

This study highlights the influence of non-financial sustainability reporting and firm reputation (FR) on the China Stock Exchange. The study is based on the components of sustainability reporting that influence FR.

A simple ordinary least squares (OLS) regression model is initially run to test the hypotheses. Advanced econometric methods are used to detect the presence of heteroskedasticity. The study utilizes fixed-effect, two-stage least squares (2SLS) and two-step generalized method of moments (GMM) regression models to address endogeneity issues.

Findings suggest that NFSR has a negative influence on FR. Conversely, environmental, social and governance (ESG) sustainability reporting exhibited positive associations with a FR in fixed-effect, 2SLS and GMM results.

This study has limitations, and data collection is restricted to the period from January 2018 to June 2023, limiting the scope of findings due to data constraints. Brand equity measurement is considered only one aspect of a company's activities, and other methods can also be considered for measuring brand equity. Another limitation is a standardized method for measuring NFSR. While this study used the Arianpoor and Salehi (2021) model to measure sustainability reporting in the Chinese market, future research could explore different methods.

The findings of this study have important practical implications for corporate management, highlighting reputation challenges and the strategic importance of sustainability. Managers are encouraged to use NFSR strategically to enhance their reputation and corporate strategy.

The social implications highlight ownership and regulatory structures, promoting enhanced sustainability reporting in China's business culture. This insight informs policymakers, businesses and stakeholders regarding the importance of sustainability reporting, guiding decisions on corporate reputation and sustainability regulations.

The research indicates the importance of context-specific sustainability reporting for enhancing reputation. It provides insights into sustainability's impact on a company's reputation, promoting responsible practices for a sustainable global economy. To the best of the authors' knowledge, this is the first research that utilizes the NFSR frameworks and a sample of firms in China to discuss sustainability reporting with different guidelines.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

This paper aims to study the influence of cylindrical texture parameters on the lubrication performance of static and dynamic pressure thrust bearings (hereinafter referred to as thrust bearings) and to optimize their lubrication performance using multiobjective optimization.

The influence of texture parameters on the lubrication performance of thrust bearings was studied based on the modified Reynolds equation. The objective functions are predicted through the BP neural network, and the texture parameters were optimized using the improved multiobjective ant lion algorithm (MOALA).

Compared with smooth surface, the introduction of texture can improve the lubrication properties. Under the optimization of the improved algorithm, when the texture diameter, depth, spacing and number are approximately 0.2 mm, 0.5 mm, 5 mm and 34, respectively, the loading capacity is increased by around 27.7% and the temperature is reduced by around 1.55°C.

This paper studies the effect of texture parameters on the lubrication properties of thrust bearings based on the modified Reynolds equation and performs multiobjective optimization through an improved MOALA.

Cultivating loyal customers is a pressing concern for streamers. The present study investigates how to build interpersonal relationships with streamers and whether different interpersonal relationship factors lead to repurchase intention and WOM intention in live streaming commerce. The moderating effect of gender is also examined.

A self-administered questionnaire was completed by 429 live streaming commerce users in mainland China. Partial least squares structural equation modeling was used to test the research hypotheses.

The results indicate that all four streamer attributes (expertise, authenticity, attractiveness, and homophily) have a positive influence on swift guanxi, and swift guanxi is effective in predicting both calculative commitment and affective commitment. In addition, all interpersonal relationship factors (swift guanxi, calculative commitment, and affective commitment) significantly affect repurchase intentions, with only affective commitment being linked to WOM intention. Also, the moderating role of gender was confirmed in expertise – swift guanxi, attractiveness – swift guanxi, cognitive commitment – repurchase intention and affective commitment – repurchase intention linkages.

This paper contributes to the live streaming commerce literature by integrating swift guanxi, calculative commitment, and affective commitment to understand the repurchase intention and WOM intention from the relationship-building process perspective. In addition, this paper enriches the source credibility and source attractiveness models by identifying gender boundaries on the effectiveness of these models in predicting swift guanxi.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

This study intends to investigate the determinants of learners' continuance intention to use massive open online courses (MOOCs) for personal or professional development.

This study employed quantitative research design. The respondents were individual learners from six selected universities in China who used MOOCs for continuous learning. A purposive sampling technique was employed to obtain 270 valid samples. Data were analyzed and analytical outputs were produced using the techniques of Partial Least Squares Structural Equation Modeling and Importance-Performance Matrix.

Expectation confirmation was found to have a positive relationship with perceived usefulness, flow experience, learning self-efficacy and satisfaction with MOOCs. Perceived usefulness, flow experience and leaning self-efficacy were also found to have a positive relationship with MOOC satisfaction. In addition, perceived usefulness, flow experience, learning self-efficacy and MOOC satisfaction had a positive impact on continuance usage intention.

The outcomes of the study can serve as a practical reference for MOOC providers and decision-makers to develop relevant strategies to increase the course completion rates.

We investigate the extended service strategy choices of competing manufacturers and examine their impact on the retail platform.

We construct a supply chain model with a retail platform as the leader and manufacturers as the followers. Manufacturers face differential consumer preferences on the same agency retail platform, and they can sell a bundled extended service product and sell a separate product without any extended service.

The sale of extended warranty services on the retail platform leads to lower pricing of the manufacturers' products and changes in the product market structure in response to differences in consumer preferences. The retailing platform tends to provide an extended warranty conditionally. The sale of extended warranty services on a retail platform would be detrimental to the interests of the manufacturer who sells products with extended warranty services and in favor of the manufacturer who sells products without them.

The equilibrium results of the retail platform’s non-sales and sales of extended warranty services for the no-extended warranty product under the same commission rate and differential commission rate models are discussed, and the product structure of the market is investigated, respectively.

This paper aims to study the preferences of the supply chain (SC) members on various power structures under demand information asymmetry considering competing retailers.

A two-level SC with one manufacturer and two retailers is designed. The retailers are in Bertrand competition. The manufacturer who holds the confidential demand information chooses the appropriate information sharing (IS) format. Three IS formats are provided, i.e. no IS (the manufacturer never shares with the retailers), partial IS (the manufacturer shares with one retailer), full IS (the manufacturer shares with all retailers). In addition, the authors model two power structures based on the decision sequences in the SC, i.e. retailers or manufacturer-dominant SC. The authors characterize the equilibrium solutions and payoffs and then investigate the members’ preferences for IS formats.

It is shown that in retailers (manufacturer)-dominant SC, the retailers prefer full (no) IS, but the manufacturer prefers no (full) IS. Moreover, the authors analyze the members’ preferences on power structures under demand information asymmetry, which has a relationship with the degrees of demand uncertainty and competition intensity.

The analysis regarding the preferences of the SC members on power structure under demand information asymmetry provides valuable managerial insights to enhance cooperation and achieve a win-win result.