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The importance of humans to the successful delivery of construction projects has led to the emergence of research attention on construction workforce management. As such, this chapter uncovers emotional intelligence (EI) and the external environment as critical aspects of workforce management practices that have not gained substantial attention in past workforce management studies. While some theories and models (existing outside the construction domain) have considered the external environment, none of these models is specific to the construction industry. Furthermore, EI has received less attention within existing workforce management models. Through a review of related studies and theories, this chapter noted that the EI of construction workers and their senior management is crucial to the performance of these workers and the ultimate performance of their organisations. In the same vein, since construction organisations do not operate in silos, the external environment significantly influences the operations of organisations in the construction industry. The environment exact pressures that can influence workforce management practices and technological innovations construction organisations adopt.

Corporate social responsibility (CSR) is viewed as a differentiating strategy that wins over stakeholders’ confidence. Due to the potential strategic and positive effects on businesses, the study of CSR and its relationship to competitiveness has gained relevance. While studies have examined the impact of CSR activities on firm competitiveness, the findings so far remain contradictory. Further research on the underlying processes/mechanisms that explain how CSR contributes to competitiveness remains scarce. Accordingly, this study aims to look into the link between CSR and competitiveness with a focus on Asian business and management studies.

By using a bibliometric approach, this paper aims to provide a review of the state-of-the-art research on the linkage between CSR and competitiveness in Asian context. The sample for this research included all 538 studies from the period of 2001–2023 in the Scopus database. A bibliometric study included both co-occurrence and co-citation analysis.

The study’s findings made significant contributions by identifying seven distinct clusters of co-occurrences. Using co-citation, three journals-based co-citation clusters and another three authors-based co-citation clusters are identified. The findings show how processes/mechanisms such as – accountability, multi-stakeholder dialogue/engagement, resource generation, emphasizing sustainable development goals and emerging markets, redefining strategy, cultivating value/vision and CSR leadership – are increasing in importance.

Overall, the authors argue that CSR-led competitiveness is indeed one of the key drivers for improved sustainability performance of a firm.

Based on findings, a conceptual framework has been proposed highlighting different processes and mechanisms that influence the CSR-led competitiveness – outcomes relationship.

Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

Proposing a strengths-based perspective for innovative work behaviour (IWB), the purpose of this paper is to explore character strengths (CS) as antecedents to IWB. Extending the literature and operating in the framework of positive organisational behaviour, this paper considers creative self-efficacy a crucial link between CS and IWB. The role of growth mindset and learning organisation in facilitating IWB, presented as a conceptual model, contributes to the theory in this field, aiding in developing an overarching theory to understand IWB.

A narrative literature review was performed on the CS, IWB and positive organisational behaviour literature to adapt theories and develop propositions for the conceptual model.

This paper develops a conceptual framework proposing direct relationships between CS and IWB. This study posits creative self-efficacy (CSE) as the mediator between this relationship and growth mindset, learning organisation as the moderators for the link between CS and CSE and CSE and IWB.

The paper presents a conceptual framework focusing on the positive personality traits of employees, precisely their CS. This study explores how leveraging these strengths can enhance their capacity for IWB. The suggested model also prompts additional research in understanding IWB.

To the best of the authors’ knowledge, the conceptual framework proposed is the first to explore the diverse individual differences factors and the role of contextual facilitation in enhancing employees’ IWB. This study contributes to the growing field of positive organisational behaviour and assists HR managers in tapping into employees’ internal resources. This paper’s theoretical and practical discourse can inspire future research and encourage a strengths-based view of workplace processes.

Sustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.

A sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.

Findings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.

The organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.

The originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.

The study aims to estimate the impact of the vigilant board independence (BIND) dimension that potentially neutralises the unfair influence of chief executive officer duality (CEODU) on Indian public banks' performance.

The study takes into account the fixed-effects model to investigate the potential moderating effect of BIND in the relationship between CEODU and Indian bank performance. The econometric model is also robust against heteroscedasticity, serial correlation and cross-section dependence issues to ensure that the model is free from such biases. The study also addresses the major issue of endogeneity via vector autoregression and performs the analysis by considering one period lag of the explanatory variables.

The findings demonstrate that CEODU does not always lead to a negative outcome on the performance until or unless the board is monitored by the effective presence of outside directors.

The regulatory bodies consider the results to strengthen board capital where CEODU can benefit a business entity if vigilance BIND is present at or above a threshold point.

The study evaluated an under-researched role of BIND as a moderator that undermines the negative influence of CEODU on the performance of Indian banks. The study also establishes that the CEO's contribution to performance increases when the number of outside directors is at or above a certain threshold.

This study aims to investigate the influence of corporate social responsibility (CSR) on corporate sustainable performance (CSP) of small- and medium-sized enterprises (SMEs) by looking into the significance of mediating factors, namely, brand image (BI) and brand loyalty (BL), within the context of an emerging economy.

The authors conduct an extensive literature study on the subjects of CSR, BI and BL to assess their influence on the sustainable performance of SMEs in an emerging market. The study adopts a quantitative methodology. A total of 438 answers were obtained from a sample size of 513. The data of the SMEs in Vietnam was analyzed using the smart partial least squares structural equation modeling software, specifically version 3.3.2.

The results of the authors demonstrate notable and favorable correlations between CSR and CSP, CSR and BI and CSR and BL. Importantly, the findings contribute to existing knowledge by looking into the mediating influence of BI and BL in the relationship between CSR and CSP.

According to the authors’ understanding, a number of research have investigated the correlation between CSR and CSP within the realm of SMEs. Nevertheless, there is a scarcity of scholarly research examining the mediating function of BI and BL in this association. The study’s findings have important implications for entrepreneurs and senior management in effectively guiding their enterprises and improving their business strategies with an emphasis on sustainability in emerging markets. The outcome of this study has the potential to significantly contribute to SMEs in Vietnam as well as other emerging countries.

Ohmic heating generates temperature with the help of electrical current and resists the flow of electricity. Also, it generates heat rapidly and uniformly in the liquid matrix. Electrically conducting biofluid flows with Ohmic heating have many biomedical and industrial applications. The purpose of this study is to provide the significance of the effects of Ohmic heating and viscous dissipation on electrically conducting Casson nanofluid flow driven by peristaltic pumping through a vertical porous channel.

In this analysis, the non-Newtonian properties of fluid will be characterized by the Casson fluid model. The long wavelength approach reduces the complexity of the governing system of coupled partial differential equations with non-linear components. Using a regular perturbation approach, the solutions for the flow quantities are established. The fascinating and essential characteristics of flow parameters such as the thermal Grashof number, nanoparticle Grashof number, magnetic parameter, Brinkmann number, permeability parameter, Reynolds number, Casson fluid parameter, thermophoresis parameter and Brownian movement parameter on the convective peristaltic pumping are presented and thoroughly addressed. Furthermore, the phenomenon of trapping is illustrated visually.

The findings indicate that intensifying the permeability and Casson fluid parameters boosts the temperature distribution. It is observed that the velocity profile is elevated by enhancing the thermal Grashof number and perturbation parameter, whereas it reduces as a function of the magnetic parameter and Reynolds number. Moreover, trapped bolus size upsurges for greater values of nanoparticle Grashof number and magnetic parameter.

There are some interesting studies in the literature to explain the nature of the peristaltic flow of non-Newtonian nanofluids under various assumptions. It is observed that there is no study in the literature as investigated in this paper.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.