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Purpose: The purpose has multiple purposes. Hence, this study has been conducted not only to shed light on the factors associated with place attachment but also to make people understand the two-way association between firm performance and CSR activities of small-scale tourism companies.

Significance and Scope: This chapter is specifically written in association with the tourism industry to make readers understand the implication of place attachment with CSR activities. This chapter also has a role in theoretical optimization as it highlights possible two-way associations between firm performance and CSR.

Research Gap: The lack of studies associated with this point is the major cause of concern. Therefore, this study has been conducted specifically to understand the importance of place attachment for CSR activities of small-scale tourism companies. Moreover, almost all of the studies conducted in this vein highlighted only the reasons for place attachment and their association with the CSR of the small-scale tourism industry. None of the studies are inclined toward model extension and enhancement.

Data Collection: Data have been collected through published material to develop postulates and models authentically.

Findings: After the compilation of data, it has been presumed that place attachment is one of the important elements in CSR activities of small-scale tourism businesses. However, the model can be reassessed in two-way association as a decline in the company's performance may also cause a decline in CSR activities and also in place attachment.

The industrial revolution 4.0 (IR4.0) signifies technological advancements and digitalization. The fragmented and labour-intensive nature of the construction industry inherently possesses difficulties for IR4.0 adoption compared to other industries. This paper aims to investigate the perspectives of quantity surveying students on the challenges of IR4.0 implementation in the construction industry.

A questionnaire survey were distributed to a population of 191 quantity surveying students, with 96 valid responses returned. Descriptive statistics and factor analysis were employed to analyse the collected data.

Factor analysis revealed eight components as the key challenges for IR4.0 implementation, which revolved around resistance to change, data security issues, etc.

The findings could provide a guideline to higher education institutions on certain IR4.0-related areas to be incorporated into the syllabus, in ensuring that the students are equipped with such skills and knowledge, in meeting market demands. The construction stakeholders' could look into the identified challenges for strategizing the organizations in moving towards IR4.0 adoption.

To the best of the authors’ knowledge, this is the first study to investigate quantity surveying students' perspectives on the challenges of IR4.0 implementation in the construction industry by employing factor analysis method. The findings contribute to the body of knowledge in relation to the opinions of a younger generation who has more exposure towards technology on the hindrance of IR4.0 adoption.

This study aims to explore how training influences employee proactive behaviours in entrepreneurial ventures. Specifically, the study develops and tests a model in which organisational identification (OID) mediates the relationship between perceptions of training and two employee proactive behaviours: taking charge and creative behaviour.

Data was collected from 136 employee-supervisor dyads from 24 entrepreneurial ventures in Malaysia’s high technology industry. Smart–partial least square structural equations modelling was used to test our proposed hypothesis.

The findings suggest that entrepreneurial ventures can use training to strengthen employees’ identification with the ventures, which in turn encourages proactive behaviours.

This study shows how HRD practices found in larger firms can work in different ways to influence desirable behaviours among employees of entrepreneurial firms. Specifically, by demonstrating how the relationship between training and employee proactive behaviours occurs through OID in the context of entrepreneurial ventures, the authors provide a complementary explanation of how HRD practices in entrepreneurial ventures can influence employee positive behaviours.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

This study aims to explore the effects of responsible international investment in a least developed country (LDC) on ethics and corruption in the local industry. While investment growth in least developed countries (LDCs) is essential to meet the United Nations Sustainable Development Goals, international investment in LDCs poses challenges, including corruption. The authors explore perspectives from relevant stakeholders on the influence, if any, on an LDC’s banking sector, of investment in the LDC by a multinational bank with an environmental, social and governance focus – using a case study of Standard Chartered Bank (SCB) in Nepal.

The authors conducted thematic analysis on: focus groups with current and former SCB Nepal management; semi-structured interviews with Nepal banking regulator representatives; senior staff from SCB global divisions; and management of other commercial banks in Nepal.

Knowledge transfer, organisational enablers and constructive international competition contributed to the dissemination of best practices within the Nepal banking sector, supporting the notion of beneficial spill-over effects of multinationals on LDC host countries.

Practical insights will aid LDC governments, international businesses, investment funds and donor organisations seeking to invest in/assist LDCs with economic development.

To the best of the authors’ knowledge, this may be the first case study on ethics and anti-corruption practices of a multinational bank in a LDC. Through a practice-driven focus, the authors provide “on-the-ground” insights to better understand the complex nature of corruption.

The purpose of this study is to investigate the effects of high-temperature oxidation tests and gas thermal shock tests on IC10 simulated components with thermal barrier coatings under different temperatures and oxidation times.

In the high-temperature oxidation test, specimens were oxidized at three different temperatures of 850, 980, and 1,100 °C for durations of 10, 20, 50, 100, 200, and 300 h, respectively. In the gas thermal shock test, specimens were pre-oxidized for 10, 20, 50, and 100 h, followed by a high-temperature gas thermal shock test at 1,100 °C.

In the high-temperature oxidation tests, with increasing oxidation time, the oxidation layer thickened, and the air-film holes diameter decreased. The microstructure of the bond coat transitioned from strip-like to block-like, and internal cracks transformed from numerous and short to larger and deeper. Below the bond coat, a noticeable disappearance layer of strengthening phase appeared, with increasing thickness. The strengthening phase in the substrate transitioned from regular square shapes to circles as temperature increased. In gas thermal shock tests at 1,100 °C, the oxidation weight gain ratio increased with longer pre-oxidation times, whereas the erosion weight loss ratio gradually decreased.

The originality and significance of this study lie in its departure from the typical subjects of high-temperature oxidation and thermal shock tests. Unlike common research targets, this study focuses on IC10 simulative specimens with thermal barrier coatings and air-film holes. Furthermore, it investigates the effects of varying temperatures and oxidation durations.

Purpose: The COVID-19 pandemic has been a good example of a Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) world. Higher educational institutions (HEIs) have faced a massive hit because the jobs in this industry have become unexpected. Considering the most valuable assets ‘Teachers’ crunched in the VUCA crisis, the study intends to determine if personal harmony (PH) and organisational citizenship behaviour (OCB) would enhance teachers’ job satisfaction (JS).

Design/methodology/approach: Data are collected from the teachers of Indian HEIs and teachers who have experienced the impact of the COVID-19 catastrophe (VUCA). Considering the pandemic restrictions, data have been collected through an online survey (N = 364).

Practical Implications: PH is an individual’s internal quality and attribute that cannot be developed on force or situational need. Even in an uncertain situation, teachers have tried their best to contribute through professional service. Hence, people who possess PH contribute their best even though unsatisfied with their jobs.

Originality/value: This study has focused on finding the relationship between two different variables, PH and OCB (which has not been explored in Asian countries, majorly in India, where it has a vast cultural diversity and structure influencing the educational policies) that hinders the factors influencing JS, where these two variables are highly influenced by hygiene factors such as values, culture, ethical standards, personal belief, leadership styles, and fair treatment showcased by the organisations/institutions.

This paper aims to understand the current development situation of scientific data management policy in China, analyze the content structure of the policy and provide a theoretical basis for the improvement and optimization of the policy system.

China's scientific data management policies were obtained through various channels such as searching government websites and policy and legal database, and 209 policies were finally identified as the sample for analysis after being screened and integrated. A three-dimensional framework was constructed based on the perspective of policy tools, combining stakeholder and lifecycle theories. And the content of policy texts was coded and quantitatively analyzed according to this framework.

China's scientific data management policies can be divided into four stages according to the time sequence: infancy, preliminary exploration, comprehensive promotion and key implementation. The policies use a combination of three types of policy tools: supply-side, environmental-side and demand-side, involving multiple stakeholders and covering all stages of the lifecycle. But policy tools and their application to stakeholders and lifecycle stages are imbalanced. The development of future scientific data management policy should strengthen the balance of policy tools, promote the participation of multiple subjects and focus on the supervision of the whole lifecycle.

This paper constructs a three-dimensional analytical framework and uses content analysis to quantitatively analyze scientific data management policy texts, extending the research perspective and research content in the field of scientific data management. The study identifies policy focuses and proposes several strategies that will help optimize the scientific data management policy.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs include data on vehicles with and without intended driving behavior changes, they do not explicitly demonstrate a type of data on vehicles that intend to change their driving behavior but do not execute the behaviors because of safety, efficiency, or other factors. This missing data is essential for autonomous driving decisions. This study aims to extract the driving data with implicit intentions to support the development of decision-making models.

According to Bayesian inference, drivers who have the same intended changes likely share similar influencing factors and states. Building on this principle, this study proposes an approach to extract data on vehicles that intended to execute specific behaviors but failed to do so. This is achieved by computing driving similarities between the candidate vehicles and benchmark vehicles with incorporation of the standard similarity metrics, which takes into account information on the surrounding vehicles' location topology and individual vehicle motion states. By doing so, the method enables a more comprehensive analysis of driving behavior and intention.

The proposed method is verified on the Next Generation SIMulation dataset (NGSim), which confirms its ability to reveal similarities between vehicles executing similar behaviors during the decision-making process in nature. The approach is also validated using simulated data, achieving an accuracy of 96.3 per cent in recognizing vehicles with specific driving behavior intentions that are not executed.

This study provides an innovative approach to extract driving data with implicit intentions and offers strong support to develop data-driven decision-making models for autonomous driving. With the support of this approach, the development of autonomous vehicles can capture more real driving experience from human drivers moving towards a safer and more efficient future.