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While existing research has explored the association between supervisor support and turnover intention among construction workers, there is a notable gap in the literature concerning the potential mediating role of work engagement in elucidating this relationship, warranting further investigation. The paper, hence, aims to examine the mediating role of work engagement in the relationship between supervisor support and turnover intention among construction workers.

Based on the quantitative research method, the hypothesis was tested. The data were collected from 144 construction professionals using a structured questionnaire. Observed variables were tested using confirmatory factor analysis, and the mediating role relationship was validated using hierarchical regression.

The outcome of this study shows a significant positive impact of work engagement and supervisor support on employee turnover intention. The study further showed that work engagement plays a mediating role in the connection between supervisory support and the intention to turnover and improve project and business performance. Turnover intention, on the other hand, negatively affects project and organizational performance.

By enhancing employee work engagement and perceptions of supervisor support, the findings of this study may aid construction organizations in making better judgments regarding the likelihood of employee turnover. The effectiveness of the project and the organization will likely be greatly impacted.

The results of this study provide supporting evidence and advance efforts at reducing employee turnover intention through work engagement and supervisor support in improving project and organizational performance.

This study aims to unravel a potential determinant of employee engagement in family firms. In particular, we focus on the role of the CEO by studying the influence of CEO transformational leadership on employee engagement. Moreover, we look into the potential mediating psychological safety might play in this relationship.

Based on an extensive literature review, we propose that there will be a significant positive relationship between family firm CEOs’ transformational leadership and the level of employee engagement. We argue that psychological safety will serve as an underlying mechanism explaining this positive relationship. We empirically tested our research model using quantitative data collected through a questionnaire, completed by 508 employees from Belgian family firms.

The results confirm the positive relationship between CEOs’ transformational leadership and employee engagement. Moreover, these results show that the degree of psychological safety mediates this relationship.

This study forms a significant contribution to family firm literature. Until now, even though existing studies on employee engagement in general are numerous, we had little to no knowledge of the factors influencing employee engagement taking into account the unique context of family firms. With this study, we take an important step in this matter. In addition, this study also contributes to the general literature on employee engagement, since previous studies on the impact of leadership on employee engagement tended to focus on the role of the immediate supervisors and not the CEO.

What does special education mean for general education teachers of students with disabilities? In this chapter, we share our approach to advancing values in the classroom placement of special education students in the general education setting. We will take the reader on a journey through time with “Jessie,” a special education student, as we examine the historical exclusion of students with disabilities to their inclusion in general education schools, environments and finally, general education classrooms. In doing so, we will examine the evolution of the general education teacher's role and how the historical perspective impacts current practices. Then, we will elucidate the benefits of inclusion, not only for the special education student but for the nondisabled peers as well. We will recommend values that should be maintained and practices that should be examined. This chapter will conclude with a connection between the values and recommendations of best practices for inclusive instruction.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Enhanced risk governance could reduce RAs, influencing banking policy.

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the right people to drive the implementation of these technologies and attaining strategic organisational goals is essential. While most studies have focused on the use of emerging technologies in the construction industry, less attention has been given to the ‘people’ dimension. Therefore, this study aims to assess the people-related features needed for construction digitalisation.

The study adopted pragmatic thinking using a mixed-method approach. A Delphi was used to achieve the qualitative aspect of the research, while a questionnaire survey conducted among 222 construction professionals was used to achieve the quantitative aspect. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H test, exploratory factor analysis and confirmatory factor analysis.

Based on acceptable reliability, validity and model fit indices, the study found that the people-related factors needed for construction digitalisation can be grouped into technical capability of personnel, attracting and retaining digital talent and organisation’s digital culture.

The findings offer valuable benefits to construction organisations as understanding these identified people features can help lead to better deployment of digital tools and the attainment of the digital transformation.

This study attempts to fill the gap in the shortage of literature exploring the people dimension of construction digitalisation. The study offers an excellent theoretical backdrop for future works on digital talent for construction digitalisation, which has gained less attention in the current construction digitalisation discourse.