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This study aims to examine the role of authenticity in tourists’ destination selection, analyze the factors that influence tourists to form their initial opinions and explore how tourists construct the authenticity of traditional villages. The authors selected Chengkan village in Huizhou district, Huangshan city, as a case. In the study, the authors constructed an attribute-hardware-software research framework and analyzed tourists’ authentic emic experiences from the perspective of constructivism. The findings of this study suggest that tourists’ destination selection is influenced by authenticity. The destination culture brokers who interact with tourists play an essential role in forming authentic experiences. According to differences in how tourists construct authenticity, the study divided tourists into three types: primitive imagination, aesthetic reality and rational cognition. The results of this study provide a deeper understanding of various viewpoints about authenticity research and contribute to the academic discussion on how to understand the authenticity of unique cultural heritage sites such as traditional villages in the context of tourism development.

Despite the importance of tourism ethnocentrism in emerging tourism destinations, there is limited, but growing, research interest in this area. This study aims to respond to current calls for investigating mechanisms that can promote tourism ethnocentrism in both emerging and developed tourism destinations.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

The purpose of this study is to investigate the impact of e-service quality and e-trust on customer e-satisfaction and, subsequently, on customer e-loyalty towards a website in the online shopping environment of Pakistan.

The research employed a quantitative approach and utilised structural equation modelling to investigate the relationship between e-service quality and e-trust on consumers’ e-satisfaction and e-loyalty. The data were collected from 250 individuals who actively use online shopping websites to purchase products in Pakistan.

The findings revealed that e-service quality and e-trust offered on e-commerce websites significantly impacted customer e-loyalty. However, it was found that both e-service quality and e-trust do not have a significant impact on customer e-satisfaction. In addition, the findings showed that customer e-satisfaction positively impacts e-loyalty.

Overall, these findings emphasise the importance of e-service quality, e-trust and customer e-satisfaction and their role in cultivating customer loyalty within the context of the online shopping environment in Pakistan.

This study contributes to the existing literature on online shopping in Pakistan by exploring the factors influencing consumer behaviour in this context. The findings add to the academic understanding of consumer behaviour and provide valuable insights for e-commerce businesses in Pakistan.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

Posting and sharing about food on social media has surged in popularity amongst younger generations such as Millennials and Generation Z. This study aims to analyse and compare food-tourism sharing behaviour on social media across generations. First, this study specifically investigates the factors influencing the intention to share food experiences on social media; second, it examines the impact of sharing intention on actual behaviour and loyalty; and third, it determines whether Millennials and Generation Z differ in these relationships.

A survey was carried out of Millennial and Generation Z travellers who shared food experiences on social media. Structural equation modelling (SEM) and multi-group analysis were performed to examine the cause-and-effect relationship in both generations.

The findings reveal differences in motivation, satisfaction, sharing intention, sharing behaviour and loyalty between generations (Millennials and Generation Z).

This study contributes to the literature on the antecedents of food-sharing behaviour in online communities by indicating factors that influence the sharing of culinary experiences and brand or destination loyalty across generations. Suggestions for future research include exploring online food-sharing behaviour through cross-cultural comparisons in various regions.

As Millennials and Generation Z will expand their market share in the coming years, the findings of this study can help improve marketing strategies for culinary tourism and generate more intense food experiences for both generations.

The outcome of the research provides new insights to develop a conceptual model of food-sharing behaviour and tourism on social media by drawing comparisons across generations.

Agricultural and food systems in the Mekong Region are undergoing transformations because of increasing engagement in international trade, alongside economic growth, dietary change and urbanisation. Food systems approaches are often used to understand these kinds of transformation processes, with particular strengths in linking social, economic and environmental dimensions of food at multiple scales. We argue that while the food systems approach strives to provide a comprehensive understanding of food production, consumption and environmental drivers, it is less well equipped to shed light on the role of actors, knowledge and power in transformation processes and on the divergent impacts and outcomes of these processes for different actors. We suggest that an approach that uses food systems as heuristics but complements it with attention to actors, knowledge and power improves our understanding of transformations such as those underway in the Mekong Region. The key transformations in the region include the emergence of regional food markets and vertically integrated supply chains that control increasing share of the market, increase in contract farming particularly in the peripheries of the region, replacement of crops cultivated for human consumption with corn grown for animal feed. These transformations are increasingly marginalising small-scale farmers, while at the same time, many other farmers increasingly pursue non-agricultural livelihoods. Food consumption is also changing, with integrated supply chains controlling substantial part of the mass market. Our analysis highlights that theoretical innovations grounded in political economy, agrarian change, development studies and rural livelihoods can help to increase theoretical depth of inquiries to accommodate the increasingly global dimensions of food. As a result, we map out a future research agenda to unpack the dynamic food system interactions and to unveil the social, economic and environmental impacts of these rapid transformations. We identify policy and managerial implications coupled with sustainable pathways for change.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

The purpose of this paper is to evaluate the influence of budgeting process elements (budget participation, preparation, implementation and evaluation) on budget performance of government.

A cross-sectional survey was administered among budget officers from government agencies, departments, and units in Malaysia. Descriptive and regression analyses were used to examine the relationship between the budgeting process and budget performance.

The findings revealed the significant influence of the two predictors: (1) budget participation and (2) budget implementation and evaluation, on budget performance. Both have positive and significant impacts on budget performance. However, budget preparation appeared to have no significant relationship with budget performance, although there is positive effect.

This study provides empirical evidence on the budgeting process factors that influence budget performance. The findings hopefully are of interest to government officials, especially frontline bureaucrats, who seek to ensure that budget performance meets expectations in Malaysia and other countries.

The purpose of the present study is to investigate travel agencies' social media usage and its perceived effectiveness by small- and micro-Italian travel agencies; the pre-pandemic period is compared to the forecasts for the post-Covid-19 period and different characteristics of firms and entrepreneurs are considered. Furthermore, the study analyses the expected benefits in terms of marketing objectives, such as improving brand image and/or personalizing the offer.

The research was developed through a questionnaire administered electronically to travel agents (282 respondents). The resulting data was analyzed by applying the McNemar test, a pairwise t-test and the multivariate analysis of variance.

The results show that social media are strategically significant for travel agents, even though their adoption is influenced by different agency aims; the perceived effectiveness results are diversified according to varying agency typologies.

The two main limitations of the study are its focus on the Italian context only and the missing consideration of the consumer's point of view. The latter prevents an exhaustive assessment of future trends regarding the use of social media in the client–agency relationship.

The study, which focuses on a little debated topic concerning the relationship between social media and SMEs, organically explores various dimensions related to the adoption of social media by small agencies, also considering the impact of the Covid-19 on the perception of travel agents. As a further element of originality, the research takes into consideration the main social platforms separately rather than the set of tools as a whole.