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This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

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.

The purpose of this study is to examine the dynamic relationship between intellectual capital (IC) and its components on financial performance of banks within the selected eight countries of Association of Southeast Asian Nations (ASEAN).

The study utilizes the balanced panel data of 37 publicly listed banks from eight leading ASEAN economies for the period of 2017–2021. In this sense, the authors applied the Ante Pulic's typology, i.e. value-added intellectual coefficient (VAIC™) to evaluate the efficiency of intangible and tangible assets. While, investigating the dynamic nature of relationship, the authors employed the generalized system method of moments because of its power to account for the problem of endogeneity and heteroscedasticity.

The results of the study demonstrate that banks in ASEAN countries shed a varied degree of a spotlight on VAIC™ and its components to create value. The findings revealed that structural capital efficiency is significantly associated with earning per share (EPS), return on assets (ROA) and return on equity (ROE), compared to human capital efficiency (HCE) and capital employed efficiency of ASEAN banks. These results endorse the importance of resource- and knowledge-based views of organizations to leverage the financial performance of banks. However, contrary to theoretical expectations, this study found no positive relationship between HCE with ROA and ROE. Whereas, the relationship of VAIC™ is positive and significant with EPS and ROE but it remains statistically very marginal.

There are some inherent limitations in this study that could be opportunities for future research. The current study uses the VAIC™ typology, but future researchers can use the modified value-added intellectual coefficient (MVAIC) or triangulation approach to enhance the validity and reliability of the study. Additionally, future research can investigate the similarities and differences among countries in terms of their cultural backgrounds and regulatory frameworks regarding the disclosure of intangibles. Furthermore, future research can increase the length and sample size of the study to enhance its generalizability.

The robust empirical findings extend the academic debate on IC by unveiling the dynamic nature of relationship between IC and financial performance in context of ASEAN banking sector. The findings provide plausible recommendations for policy makers (managers, regulators and stakeholders) to understand how to increase the IC efficiently, especially human capital as a source to evaluate the firms’ ability in determining value-added and financial performance. Further, findings of this study also suggest that how can policy makers get the benefit by investing more on structural capital as a valuable strategic source to guarantee the optimal performance returns.

Prior studies on IC have been country- and firm-specific, utilizing cross-sectional research designs. However, this research contributes to the limited literature by investigating the dynamic nature of the relationship between IC and financial performance of banks in the context of ASEAN countries using micro-panel data.

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.

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.

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.

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.

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.

This study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.

This study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.

Study 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.

The new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

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.