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The purpose of the paper is to investigate compensation and related welfare issues in the case of the expropriation of land for urban redevelopment in China.

A mixed methods quantitative and qualitative approach was selected to undertake the research. This involved a wide ranging qualitative review of the academic and policy literature to explore the relevant arguments and issues, combined with a quantitative regression analysis of survey data collected from research subjects.

The research identified the complex and changeable phenomena of urban village redevelopment in China, and the variable compensation arrangements used. The research found that monthly family income before land expropriation, monthly family expense before expropriation, the location of the housing expropriation and family unit size are important determinants for the property holders chosen methods of compensation. It also found that an increase in family size leads to a decreasing probability that the expropriated farmers choose the single monetary compensation relative to the alternative option of housing compensation. The degree of satisfaction with compensation, changes in monthly family income and expense are found to be significant determinants for changes in life satisfaction.

The research made the following four recommendations based upon the qualitative and quantitative analysis: that local governments should pay closer governance/ political attention to changes in the welfare of the farmers/ villagers whose property has been expropriated; that central and local government should aim to improve the compensation system for rural land and property expropriation, to make the compensation policy be perceived as fairer and more reasonable by citizens; that a broad National standard of compensation be used within a pragmatic locally focussed regime; that the Chinese Central, Provincial and Local governments can devise improved policy tools and make more effective policy interventions by learning from the experiences (both successes and failures) of other countries approaches to this topic. It also suggested that further research be undertaken investigating the multitude of local level policy experiments, as a way of developing better National compensation standards based upon those compensation standards that appear to be working – and have citizen support – at the local level.

The literature review identified recent developments in Chinese urban studies and originally synthesised both recent and longstanding work on the issue of urban villages in China. The research also suggested changes to the National and Local legal and policy framework for compensation cases in urban redevelopment expropriation scenarios.

In the tourism sector it is often impossible for an travel agent to answer all the specific questions about destinations in a certain area. The tourist expects an expert in front of him, but a travel agent can't know everything about all the holiday resorts. Also taking into account his lack of time due to the enormous number of tourists, the travel agent will overwhelm the client with detailed brochures. Unfortunately, this service doesn't fulfill the requirements of quality management. The travel agent needs a tool to give better advice to the tourist. At the same time this can result in a strategic differentiation from competitors. Together with the students of the special licentiate in Tourism at the Limburg University Centre, Faculty of Applied Economics, we have designed such an advice system. It should lead to an improvement in the quality of advice given to the tourist who is looking for the appropriate holiday destination. We used the technology of an expert system. The experiment was limited to the 13 seaside resorts on the Belgian Coast.

The purpose of this paper is to construct a multi-relational network for an online sharing platform in the age of the sharing economy, to identify the factors impacting users’ product adoption behavior and to predict consumers’ purchases of user-generated products on the platform.

The study conducted multi-relational network analyses of five different sub-networks in identifying influential factors for e-book adoption. Meanwhile, the study adopted machine learning methods with different classification algorithms and feature sets to predict users’ purchasing behaviors.

The authors found that an individual’s adoption of a product was correlated with his or her purchasing habits and collaboration with others on the online sharing platform. Through the inclusion of network features, the authors were able to build a predictive model that forecasted consumers’ purchases of user-generated e-books with reasonable accuracy.

The interdisciplinary approach used in the study can serve as a good reference for identifying factors impacting the product adoption behavior of users in the online sharing platform, through employing different sociological and computational methods.

The outcome of the study has provided important managerial implications, especially for the design of social commerce platform in the age of the sharing economy.

The authors verified the social influence impacting consumers’ product adoption behavior and shed light on the value of collaboration in the age of the sharing economy.

The study was the first to identify user-generated e-book adoption on an online sharing platform from a multi-relational network perspective. The idea and the approach supplied a new method of behavioral analysis in the context of a sharing economy.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

The purpose of this study is to explore the potential contribution of the metaverse to improve training and development as a function of human resource development (HRD) perspective. The authors explore the benefits and challenges of the metaverse and introduce cases of companies using the metaverse in training.

A narrative literature review was conducted to collect information on the metaverse in training. The authors reviewed peer- and non-peer-reviewed articles, book chapters, white papers, corporate websites and blogs and business magazines.

A total of 75 articles were reviewed, including 14 cases, which were summarized to demonstrate how companies are applying metaverse technology in training contexts. For a more in-depth review, three cases were selected and summarized in terms of context, process and outcomes.

The metaverse is an emergent topic in HRD. It has the potential to revolutionize the functions of training and development through the combination of advanced technologies, including virtual reality, augmented reality and mixed reality. This article is the foundational attempt to provide a comprehensive summary of existing literature and case studies that highlight the potential of the metaverse in training within the context of HRD.

This paper reviews the strategic responses of successful local Chinese banks (LCBs) in the changeable Hong Kong banking sector over the past decades. Given the mixed outlook of the industry resulting from the handover of sovereignty, financial internationalization, and regional and domestic economic developments, this paper also discusses the benefits of using strategic alliance as a means for LCBs to meet current and future challenges. Based on case reviews, the paper demonstrates the values of strategic management concepts for small banks to cope with an externally oriented and politically uncertain operating environment.

Traces the economic development of Thailand since 1945, referring to relevant research, and analyses the reasons why it was the first Southeast Asian country to collapse in the 1997 economic crisis: large current account deficits, excessive external debt, a collapse in the property sector, exchange rate mismanagement and political instability. Considers its future prospects and shows statistics on economic growth and inflation for the world as a whole and various countries and groups within it.

This paper aims to investigate the effects of descent time spent with flaps extended on fuel burn (FB) and specific range for five different flight path angles (FPAs) ranging between 2.0° and 4.0° for a commercial aircraft.

A large data set of actual flight data (n = 475) of the same type of a frequently used commercial aircraft were investigated by using statistical methods.

The result of the comparison of the highest and the lowest FBs of flight profiles for each FPAs present that the fuel saving was achieved by keeping at as a high airspeed as possible and deploying flaps as late as possible, which is in line with the objective of delayed deceleration approaches. From analyzing the flight profiles, it was proven that delaying deceleration and also descending without flaps or with flap over a shorter time resulted in less FB of 101.1, 70.9 and 94.9 kg for FPA 2.5°, FPA 3.0° and FPA 3.5°, respectively.

This study differs from prior studies because it focused on the effects of the different vertical profiles on FB. Also, the use of real flight data recorder data in the analysis presents the originality of this study.