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Taiwan's semiconductor industry continues moving out to China, therefore Taiwan's semiconductor distributors must cooperate with the local distributors in China in order to survive. The purpose of this paper is to discover the key factors considered by Taiwan's semiconductor distributors when selecting partners in China.

This study summarizes the factors from the literatures and the experts' discussion, then develops a hierarchical structure. Using DEMATEL and MMDE to construct the causality of the dimensions, which are then taken as the basis for the development of the analytic network process (ANP) framework. Finally, it gets the weight values of various factors through the results of ANP, which serves as a proposal to discuss how Taiwan's professional semiconductor distributors select partners in China.

According to the weight of the ANP, results show that trust and commitment, scale, market share and corporate culture are factors that increase the possibility of collaboration.

China has become a favorite for foreign investments. Taiwan's semiconductor distributors must actively expand the China market in order to maintain their survival. This study focuses on Taiwan semiconductor distributors who want to invest and establish factories in China, and investigates the key factors that are involved in the selection of partners for Taiwan semiconductor distributors. The results can increase the chances of success among cooperative members.

The purpose of this paper is to develop a reliable and valid measurement of human resource management (HRM) practices and identify the key dimensions based on evidence of the multinational corporations (MNCs) in China. The aim of this paper is to investigate the relationship between HRM practices and knowledge transfer.

This paper involves a questionnaire survey concerning HRM practices, including employee satisfaction, hedonism, and altruism at the organizational level; training and self‐efficiency at the individual level. A quantitative analysis of the questionnaires is conducted through structural equation modeling in order to indicate the direction and relationship between those constructs.

The results show a striking effect of organizational commitment and individual attitudes on knowledge transfer performance in MNCs.

This paper suggests that organizational commitment and individual attitudes should be conceptualized as being comprised of HRM practices. Further, the results indicate that both commitment and attitudes are needed to facilitate the transfer of knowledge from other parts of the MNC.

Purpose – The net increase in China's urban population in the last 50 years equals the current total population of the European Union. The scale and speed of urbanization in China requires a sustainable solution to unprecedented energy demands and elevated carbon emissions. As low-carbon development emerges in urban China, it offers a unique vantage point to examine some fundamental theoretical questions of the environmental state. How do structural socioeconomic changes affect the environmental state? Does the rise of the environmental state offer a basis for regulatory reform on a broader scale?

Methodology/approach – Case study of five low-carbon cities in China provides the empirical evidence for the analysis. The five cities represent a continuum in their levels of postindustrialization. I compare low-carbon development strategies in postindustrial cities with those strategies in industrial cities. Evidence is collected primarily by way of interviews with planning bureau officials, urban design professionals, involved NGOs, academics, and private sector individuals familiar with the matter.

Findings – First, in cities where the level of postindustrialization is high, state resources support innovative low-carbon development strategies that attempt to achieve emission reductions in a variety of sectors. In industrial cities, however, the environmental state's regulative power is limited to one or two (sub)sectors. Second, and more importantly, a new pattern of governance is emerging in postindustrial cities. Low-carbon development in postindustrial cities is a much less centralized process, having local levels of governments as key players of low-carbon policy making. When the environmental state intersects with the postindustrial city, it gives birth to a new urbanism that has profound implications for political structuring in China.

Research limitations – The analysis in this chapter is based on evidence from a purposefully selected set of Chinese cities, which may render the results biased. Future studies should aim for a more systematic analysis of cities in order to establish more generalizable conclusions. In addition, given the increasing availability of quantitative data at the city level in China, future studies should also seek to incorporate quantitative analyses to better substantiate existing knowledge derived from qualitative sources of evidence.

Originality/value of chapter – First, this chapter challenges the Western bias in the existing literature on the environmental state. The role of the civil society is far from salient in the Chinese context, and yet the environmental state demonstrates a robust level of activity despite the weak civil society. It therefore seems that a general theory of the environmental state can be built from existing literature, but needs to be sensitive to non-Western social conditions that might falsify parts of the theoretical claims. Second, the environmental state literature can be consolidated and further developed when examined in conjunction with other literatures in the modernity tradition. I have demonstrated the connection between the environmental state and the postindustrial city. More studies are needed to examine other facets of the environmental state, as it intersects with a multitude of (post)modern conditions.

This paper aims to study whether rural collective construction land marketization (RCCLM) affects pension industry and analyze its impact mechanism.

Based on the theory of planned behavior (TPB) and social cognition theory (SCT), this paper constructs a theoretical framework for the purchase behavior of rural retirement housing with the influence of RCCLM. A mixed-methods investigation combining qualitative and quantitative study is adopted in this paper.

The research results indicate that the purchase intention of rural retirement housing has a significant positive impact on the purchase behavior. However, RCCLM has a significant negative impact on the purchase intention of rural retirement housing. A logical framework of “land system participant behavior” has been constructed from three main bodies: government, developers and elderly urban and rural residents.

This paper provides suggestions for the three entities from the perspectives of macro, medium and micro-level to improve transaction system for rural collective construction land use right (TSRCCLUR), providing references for the collective construction land marketization policy and the development of the pension industry.

This paper deepens the study of behavior intention in planned behavior, enriches TPB model in the study of rural retirement housing security and clarifies the influence mechanism of the rural retirement housing purchase intention with the theoretical and empirical test of the model.

This chapter examines the ‘embodied turn’ in the study of traditional Chinese sports and identifies issues within this area of research. It introduces new interpretative perspectives and approaches within the framework of bodily sociology to elucidate the link between locally-informed sports practices and the formation of socialized individuals. The chapter categorises the current research into three main themes: self-giving, the creation of bodily value and the construction of national identity through sports. It then integrates these themes with the findings of embodied sociology. The chapter compiles and analyzes the existing literature on traditional Chinese sports culture from both Chinese and international scholars, offering insights into the status, rationale and challenges of bodily sociological research. By contextualising the concept of the embodied turn in traditional Chinese sports culture – through concepts such as self-givenness, self-techniques, the generation of value and the creation of collective memory – the chapter discusses the impact of bodily sociology on cultural research. The chapter advocates for further bodily sociological studies of Chinese sports culture, which could enhance the understanding of Chinese studies among Western scholars and contribute to a genuine embodied turn in this field of study. Providing one of the initial explorations of embodied studies in traditional Chinese sports, the chapter reveals a transition from broad cultural interpretations and symbolic, structuralist sociology to a phenomenological approach in sports cultural studies. It posits that the bodily sociology approach is beneficial for sports studies although current research has not yet fully realized the embodied turn.

This study aims to investigate how high-speed railway (HSR) development affects urban construction investment (UCI) bond yield spreads based on China’s background.

This study constructs a quasi-natural experiment and adopts regression analyses to empirically examine the relation between HSR development and UCI bond yield spreads. The empirical analysis is based on a Chinese sample of 15,109 bond offering observations from 2008 to 2019.

The results show that HSR development reduces UCI bond yield spreads. Mechanistic analysis shows that HSR development increases land prices and the level of urbanization, which in turn lowers the UCI bond yield spreads. In addition, the impact of HSR development on UCI bond yield spreads is more significant at higher marketization levels and lower degrees of dependence on land finance cities where UCI corporations are located.

The results imply that transportation infrastructure improvement, such as HSR development, helps to enhance the credit of local governments and the solvency of UCI corporations and ultimately reduces the financing cost of UCI bonds.

This paper provides theoretical support and empirical evidence for the impact of transportation infrastructure construction on the implicit debt risks of local governments in China, which enriches the research on the “HSR economy” from a micro perspective and expands the research on the influencing factors of local governments’ debt risk.

This study examines the forecasting performance of the professional analysts participating in the Blue Chip Economic Indicators Survey using an alternative methodological research design.

This work employs two methodologies, namely a panel specification, with the cross-section being the forecast horizon (from 1-month to 18-months ahead forecasts) and the time period being the time that the forecast was made and a quantile regression technique, which evaluates the hidden nonmonotonic relations between the forecasts and the target variables being forecasted.

The empirical findings of this study show that survey-based forecasts of certain key macroeconomic variables are generally biased but still efficient predictors of target variables. In particular, we find that survey participants are more efficient in predicting long-term interest rates in the long-run and short-term interest rates in the short run, while the predictability of medium-term interest rates is the least accurate. Finally, our empirical analysis suggests that currency fluctuations are very hard to predict in the short run, while we show that survey-based forecasts are among the most accurate predictors of GDP deflator and growth.

Evaluating the accuracy of economic forecasts is critical since market participants and policymakers utilize such data (as one of several inputs) for making investment, financial and policy decisions. Therefore, the quality of a decision depends, in part, on the quality of the forecast. Our empirical results should have immediate implications for asset pricing models that use interest rates and inflation forecasts as variables.

The present study marks a methodological departure from existing empirical attempts as it proposes a simpler yet powerful approach in order to investigate the efficiency of professional forecasts. The employed empirical specifications enable market participants to investigate the information content of forecasts over different forecast horizons and the temporal evolution of forecast quality.

This paper examines the methodical and highly efficacious manner in which China deployed its comprehensive AI (artificial intelligence) strategy to significantly stymie the spread of COVID-19 across the country.

This study deploys a case-study approach, supported by the literature on existing and emerging AI and related technologies.

The onset of the COVID-19 pandemic has revealed to the world the remarkable progress China has made in AI and its accompanying ecosystem. More importantly, this outlier event demonstrates the surgical, hybridised manner in which China has utilised these emerging technologies in containing its spread (i.e. “AI Epidemiological Targeting”) and set itself on the path to unleashing their full potential (i.e. “AI Symbiosis Paradigm”). Nonetheless, China still needs to harness its rapidly advancing AI prowess in identifying COVID-19's pathogenesis and developing a proven vaccine.

This study presents a pioneering effort to analyse the deployment of AI and its ecosystem in the “war” against COVID-19.

The purpose of this study is two-fold. First, to identify and encapsulate the enablers that can facilitate technology integration in higher education and second, to understand and analyze the interplay between technology agility enablers.

The study used the Total Interpretive Structural Modeling (TISM) approach to construct a theoretical model of the technology agility enablers in higher education and MICMAC analysis for ranking and segregating the enablers based on their dependence power into four categories: Autonomous, Dependent, Linkage and Independent.

The study helped identify eight technology agility enablers, with the Covid-19 pandemic as the most significant enabler. The Covid-19 pandemic has catalyzed the diffusion of technology across the education sector in India, including tertiary higher education. The study revealed government initiatives and institutional commitment as other enablers that can promote technology agility in higher education.

The results of this study would assist the policymakers and management of universities and colleges in understanding the important enablers that can facilitate technology integration in higher education.

Research in the past on technology adoption in higher education has looked into each enabler in isolation. This research provides a comprehensive view of the enablers and has attempted to establish a multidirectional interplay between the enablers.

Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B) marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation.

Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021.

Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identifying the main trends in the literature and suggesting directions for future research.

Through the five identified domains, practitioners can assess their current use of AI and identify their future needs in the relevant domains in order to make appropriate decisions on how to invest in AI. Thus, the research enables companies to realise their digital marketing innovation strategies through AI.

The research represents one of the first large-scale reviews of relevant literature on AI in B2B marketing by (1) obtaining and comparing the most influential works based on a series of analyses; (2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation and (3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field.