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Researchers continue to seek understanding of industrialization as a state managed process. How to create and implement new industries based on advanced knowledge is on the policy agenda of many advanced nations. Measures that promote these developments include national capacity building in science and technology, the formation of technology transfer systems, and the establishment of industrial clusters. What these templates often overlook is an analysis of use. This chapter aims to increase the understanding of the processes that embed new solutions in structures from an industrial network perspective. The chapter describes an empirical study of high-technology industrialization in Taiwan that the researcher conducts to this end. The study shows that the Taiwanese industrial model is oversimplified and omits several important factors in the development of new industries. This study bases its findings on the notions that resource combination occurs in different time and space, the new always builds on existing resource structures, and the users are important as active participants in development processes.

This study attempts to explore how a cultural and creative firm's competitive advantages can be maintained through the accumulation of intellectual capital and entrepreneurial orientation. Another goal of this study is to identify the different mechanisms of network ties to explore the interrelationships between organizational capital and competitive advantage in the context of Taiwan and China.

Study 1 and study 2 settings are applied, and 786 samples (i.e., 418 samples from Taiwan and 368 samples from China) are used to examine the proposed model.

Study 1 reveals that entrepreneurial orientation may influence the organization capital through human capital and social capital, which discloses the mutual relationships of intellectual capital. Further, the results of study 2 confirm the mediating role of intellectual capital that links the relationships between entrepreneurial orientation and competitive advantage. Specifically, this study also discovered that firms with more network or political ties (e.g. the Chinese samples) and business ties (e.g. the Taiwanese samples) tend to amplify the effects of organizational capital on competitive advantage.

According to our empirical results, cultural and creative managers should build a learning mechanism to encourage and develop entrepreneurial orientation and intellectual capital capacities and to provide means of understanding of customers' changing expectations. Hence, in enhancing entrepreneurial orientation and intellectual capital cultural and creative firms can develop a competitive advantage over competitors. Our findings also offer new insight to support further studies of the benefits of managerial ties for firms operating in Guanxi cultural settings in Chinese contexts.

Most previous studies on tourism strategies have disregarded the impacts and different roles of government (e.g. political ties) and business (e.g. business ties) forces on cultural and creative firms' competitive advantages, suggesting a need to address social network issues in response to dynamic tourism environments. Therefore, this study examines differences in network ties and the differences observed between China and Taiwan in the context of Chinese cultural and creative firms.

In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.

This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.

Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.

This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.

The purpose of this paper is to investigate the role of intrinsic motivation and self-construal in explaining the relationship between work-related identity discrepancy and employee innovation behavior.

Based on a survey of 637 respondents from 15 organizations in southern China, this study examines four hypotheses with regard to the relationship between work-related identity discrepancy and employee innovation behavior through hierarchical regression analysis.

The research results indicate that work-related identity discrepancy is negatively related to employee innovation behavior, but intrinsic motivation mediates their negative relationship, and self-construal moderates this mediating effect further. Specifically, the results demonstrate that perceiving work-related identity discrepancy can lower intrinsic motivation among employees with interdependent self-construal and subsequently reduce their innovation behavior.

Drawn on social cognitive theory, this study reveals the negative effect of work-related identity discrepancy on employee innovation behavior and the moderated mediation effect of intrinsic motivation and self-construal on the negative relationship. The finding expands existing literature on work-related identity discrepancy and employee innovation behavior.

Despite an emerging interest in constructive deviance, the exploration of its antecedents is still limited, particularly from an ethical perspective. This study aims to uses moral disengagement theory to investigate how team identification, moral justification and team environmental instability interact to affect employee constructive deviance.

With survey data collected in two waves from 315 employees of 49 work teams in five service companies in China, this study develops four hypotheses and tests them through hierarchical linear model.

The survey results support the complete mediating effect of moral justification on the positive impact of team identification on constructive deviance. They also confirm the moderating effect of environmental instability on the relationship between team identification, moral justification and constructive deviance.

This study explores the sources of constructive deviance at team level from the ethical decision-making perspective and reveals the mechanism and contingency factors in the relationship between identity and constructive deviance. In practice, the study findings imply that managers should encourage their employees to cultivate their identification with their team and align their moral justification with the team’s norms especially when the team faces turbulent environment.

While the impact of artificial intelligence (AI) on organizational innovation is increasingly acknowledged, empirical investigations exploring its effect on product innovation efficiency, particularly through the lens of knowledge innovation at various modes, remain scarce. This study aims to address this gap by empirically examining the influence of AI application on product innovation efficiency within firms. It further investigates the mediating role of knowledge innovation within the SECI model and the moderating effect of technological perception characteristics.

Data were collected through a questionnaire survey administered to managers in intelligent manufacturing enterprises across China. The proposed hypotheses were tested using the PROCESS macro for SPSS, employing the bootstrapping method to assess mediation and moderation effects.

Enterprise application of AI significantly influences both knowledge innovation within the SECI model and product innovation efficiency. Knowledge innovation occurring in the socialization and combination modes of the SECI model mediates the relationship between AI application and product innovation efficiency. Perceived ease of use of AI exhibits a contrasting moderating effect on AI-related relationships, while perceived usefulness does not demonstrate a significant moderating effect.

This study contributes to the existing literature by empirically examining the influence of AI application on product innovation efficiency, mediated by knowledge innovation within the SECI model. Additionally, it explores the nuanced moderating role of AI perception characteristics, highlighting the potential duality of AI technology in driving innovation outcomes. These findings offer valuable insights for managers seeking to leverage AI for enhancing product innovation and knowledge management practices.

More people share their tourism experiences on social media today than in the past, and as a result, more people follow these posts in their trip planning. However, studies into tourists' intention to follow such posts are scarce. Therefore, this study investigates the antecedents influencing social media users' intentions to follow tourism-related posts (TRPs) when planning their trips.

Questionnaires were collected from 402 social media users who had followed TRPs for their trip planning. Data were then analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural networks.

The authors found that blogger–user fit and users' involvement with TRPs influenced behavior components (attitudes toward TRPs and intention to follow TRPs) via assessment components (bloggers' credibility and content quality), and the authors developed a framework to explain this relationship.

The findings advance prior studies by investigating (1) the antecedents of intention to follow TRPs when trip planning, (2) the two main social media elements – bloggers and posts – to understanding the role of social media on travel behavior and (3) involvement with TRPs and their impacts on travel behavior. This study contributes to the research on social media and tourism marketing and proposes practical indications for bloggers, social media platforms and destination marketing organizations.

The practice of artificial intelligence (AI) is increasingly being promoted by technology developers. However, its adoption rate is still reported as low in the construction industry due to a lack of expertise and the limited reliable applications for AI technology. Hence, this paper aims to present the detailed outcome of experimentations evaluating the applicability and the performance of AI object detection algorithms for construction modular object detection.

This paper provides a thorough evaluation of two deep learning algorithms for object detection, including the faster region-based convolutional neural network (faster RCNN) and single shot multi-box detector (SSD). Two types of metrics are also presented; first, the average recall and mean average precision by image pixels; second, the recall and precision by counting. To conduct the experiments using the selected algorithms, four infrastructure and building construction sites are chosen to collect the required data, including a total of 990 images of three different but common modular objects, including modular panels, safety barricades and site fences.

The results of the comprehensive evaluation of the algorithms show that the performance of faster RCNN and SSD depends on the context that detection occurs. Indeed, surrounding objects and the backgrounds of the objects affect the level of accuracy obtained from the AI analysis and may particularly effect precision and recall. The analysis of loss lines shows that the loss lines for selected objects depend on both their geometry and the image background. The results on selected objects show that faster RCNN offers higher accuracy than SSD for detection of selected objects.

The results show that modular object detection is crucial in construction for the achievement of the required information for project quality and safety objectives. The detection process can significantly improve monitoring object installation progress in an accurate and machine-based manner avoiding human errors. The results of this paper are limited to three construction sites, but future investigations can cover more tasks or objects from different construction sites in a fully automated manner.

This paper’s originality lies in offering new AI applications in modular construction, using a large first-hand data set collected from three construction sites. Furthermore, the paper presents the scientific evaluation results of implementing recent object detection algorithms across a set of extended metrics using the original training and validation data sets to improve the generalisability of the experimentation. This paper also provides the practitioners and scholars with a workflow on AI applications in the modular context and the first-hand referencing data.

The purpose of this paper is to examine ethnocentrism and animosity in a special context of two societies that share cultural, historical, ethnic and geographical characteristics. In particular, it first investigates the relationships between Chinese ethnocentrism and animosity toward Taiwan, and then it examines the impact of these two factors on the Chinese perception of Taiwanese brand quality and their purchase intent.

Based on a sample of 605 respondents from China, data were analyzed by structural equation modeling.

The results show that although Chinese animosity toward Taiwan is moderate, it is significantly driven by ethnocentrism, which has a significant and negative effect on willingness to buy, but not on the perception of Taiwanese brand quality. The Chinese animosity toward Taiwan, however, has negative and significant effects on their perception of Taiwanese brand quality and their intention of purchasing Taiwanese brands.

The immense size of the country has impeded the representativeness of the authors’ sample and the generalizability of the results. Also, the study covers only one type of product.

Forming partnerships with local Chinese businesses and developing strong ties with local communities could be considered as a solution to minimize or circumvent the effect of animosity and might help foreign companies appear more “local.”

In contrast to past studies that investigated ethnocentrism and animosity in the context of countries presenting several differences (e.g. China vs USA), this study investigates the effect of ethnocentrism and animosity in the context of two countries (China and Taiwan) that share cultural, historical, ethnic and geographic characteristics. Despite the strong ties between the two countries, the Chinese have a certain animosity, though moderate, toward Taiwan and consequently are less inclined to buy Taiwanese brands. This implies that Chinese animosity toward a country may be toned down or pronounced, depending on whether they have strong or weak ties with that country.

Chinese multinational enterprises’ (MNEs) unprecedented, aggressive cross-border mergers and acquisitions (CBMAs) have led to several studies examining Chinese CBMAs, which importantly has also led to some degree of “theorising”. This study aims to undertake a “non-theoretical” fact-finding exercise before any theorising and empirical “causal” examination for a better understanding of the phenomenon (the rise of Chinese CBMAs).

This study uses a “stylised facts” approach which documents “empirical regularities” concerning Chinese CBMAs and thus guides new research questions.

Several facts are documented. Firstly, both the value and frequency of Chinese CBMAs are catching up to greenfield investments, with CBMA deals being larger in scale but lower in frequency. Secondly, Chinese CBMAs show a global reach away from the regional orientation of their early years. Thirdly, Chinese MNEs are possibly transforming their value chain with industrial upgrading as an aim. Fourthly, Chinese “full” acquisitions of targets have surged, especially in OECD countries, suggestive of Chinese MNEs’ “radical” acquisition approaches.

The gathered facts lend support to the view of the need for such fact-finding exercises to explicate and shed “new” light on the phenomenon (beyond our “current” views/beliefs). An understanding of the underlying trends beyond bare facts can also identify new knowledge, which can in turn provide new directions for research.