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This study aims to evaluate the drivers influencing the integration of distributed ledger technologies (DLTs) in the Nigerian construction industry to provide a comprehensive analysis of the factors that shape the adoption and utilization of this transformative technology within the sector.

This objective was achieved through a quantitative research approach, utilizing a structured questionnaire to systematically gather data from various stakeholders in the Nigerian construction sector. Data obtained were analyzed using descriptive statistics, alongside inferential statistical techniques like the Kruskal-Wallis H-test, the Shapiro-Wilk test and exploratory factor analysis.

The most highly ranked drivers for DLT within the construction industry are security and fraud resistance, traceability and transparency, government support, compliance and reporting and trust building. Further analysis unveiled five distinct factors of application areas, namely: technological and operational drivers, economic and financial drivers, regulatory and government drivers, collaborative and stakeholder drivers and environmental and sustainability drivers.

The practical implications emphasize the need for construction industry stakeholders to focus on security, transparency and trust-building when considering DLT adoption. This study also offers valuable insights for investors and technology providers seeking opportunities in the Nigerian construction sector.

This study sheds light on the factors most critical for DLT adoption in the Nigerian construction sector. Unlike previous research, this study pinpoints security and fraud resistance, along with traceability and transparency, as the most influential drivers. This highlights the Nigerian construction industry’s particular vulnerability to fraud and its emphasis on clear audit trails.

The main objective of this study is to evaluate the driving forces behind the adoption of indoor environmental quality (IEQ) principles in building designs from the perspectives of Nigerian quantity surveying firms.

A quantitative approach was used which involved administering a well-structured questionnaire to a sample of 114 quantity surveyors. The collected data were analyzed using various statistical methods, including frequencies, percentages, mean item scores, Kruskal–Wallis test and exploratory factor analysis.

The top five ranked drivers were climate change mitigation, conservation of natural resources, reduction of waste and pollution, use of sustainable building materials and development of new materials and building systems. Based on the factor analysis, the study identified five clusters of drivers: (1) health and well-being drivers (2) economic drivers (3) environmental drivers (4) innovation and technology drivers and (5) regulatory drivers.

The findings from this study suggest that to effectively integrate IEQ principles, quantity surveying firms should consider developing comprehensive guidelines and checklists that align with the identified drivers and clustered categories. These resources can serve as practical tools for project teams, facilitating a structured and holistic approach to the incorporation of IEQ factors throughout the project lifecycle.

The study’s identification of the top drivers and the subsequent clustering of these drivers into five distinct categories contributes to the existing body of knowledge on IEQ. This approach provides a structured framework for comprehensively understanding the factors influencing IEQ adoption, offering a valuable tool for researchers, policymakers and industry practitioners.

The slow adoption of unmanned aerial vehicles (UAVs) in the construction industry, particularly in developing countries like Nigeria, underscores the need for a deeper understanding of the critical factors influencing their adoption. This study aims to identify these factors using the Technology-Organization-Environment (TOE) framework and address uncertainties in their prioritization through Fuzzy Synthetic Evaluation (FSE). The utility of this approach lies in its ability to provide construction organizations with actionable insights to enhance operational efficiency and competitiveness through effective UAV adoption.

A post-positivist philosophical stance was adopted, wherein quantitative data were gathered from construction professionals in Nigeria via a questionnaire survey. The collected data were analyzed using the Cronbach alpha test as a measure of internal consistency and the FSE test to synthesize critical drivers for the adoption of UAVs.

The study found that drivers related to technology and organization are the most critical drivers. This implies that variables related to technology and organization warrant a higher level of focus if UAVs are to continue gaining popularity within the construction industry. Additionally, this study identified that logistic management, construction monitoring and site surveying represent the most critical areas of UAV application within the construction industry.

The emphasis on technology and organizational drivers as critical factors suggests that construction companies should prioritize investments in technology infrastructure and cultivate an organizational culture that embraces innovation. This may involve providing training to construction professionals to enhance their technological skills and fostering a leadership culture that champions technology adoption.

This study introduces novelty by applying the TOE framework, which has received limited attention in UAV adoption studies within construction. Additionally, the use of FSE addresses uncertainties in prioritizing critical drivers, particularly relevant in developing countries facing unique technological challenges. By assigning priority to these factors, this research lays the groundwork for a more informed and strategic approach to UAV adoption.

This study aims to investigate the drivers influencing the implementation of circular economy principles in the Nigerian architecture, engineering, construction and operation (AECO) industry across diverse regions of Nigeria.

A quantitative research approach was adopted, using a structured questionnaire distributed to AECO professionals across four selected regions (North Central, North West, South-South and South West) in Nigeria. The data were analysed using Kruskal–Wallis test and structural equation modelling (SEM).

The study findings show a robust consensus of opinions among the respondents across regions and professions. The SEM analysis establishes the significant influence of the hypothesized drivers, regulatory and institutional, supply chain collaboration, technological advancements, organizational support and business strategies on the successful implementation of circular economy principles in the Nigerian AECO industry.

The study is limited to specific regions and professions within Nigeria. Further limitation is the quantitative orientation of this study, which collects data using only a questionnaire.

The findings imply that stakeholders can adopt a unified approach to promote circular economy principles in the AECO industry. By recognizing the common understanding of circular economy drivers, collaborative efforts can be streamlined to advance sustainability, resource efficiency and circularity in the industry.

This study contributes to the nascent field of circular economy implementation in the Nigerian AECO industry. It offers a unique perspective by exploring variations in stakeholder opinions, providing insights into the nuanced understanding of circular economy drivers.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.

In the ever-evolving digital landscape, this study aims to explore which specific personality traits contribute to the innovativeness of startups, with a particular emphasis on understanding how technology adoption mediates this relationship. By doing so, the authors strive to unveil the nuanced dynamics of personality, technology adoption and startup innovativeness in the digital era.

The authors conduct a quantitative empirical analysis using a sample of 1,314 German startups. This study utilizes a mediation analysis to examine the effects of personality traits on the innovativeness of startups, taking technology adoption as a mediator into account.

The empirical results show certain personality traits have direct effects on innovativeness. Also, the results show that technology adoption is a driver of startup innovativeness. In addition, these traits are (partially) mediated by technology adoption.

The results shed new light on the interplay of entrepreneurs' personality and technology adoption in relation to startup innovativeness and therefore underline the importance of technology in this triangular relationship. The authors employ secondary data from startups in Germany, which complicates generalization of the results to other geographical and cultural contexts.

This study contributes to the scientific debate on the role of personality traits in entrepreneurship by providing empirical evidence on the mediating effect of technology adoption in the relationship between personality traits and startup innovativeness. The findings offer valuable insights for researchers, entrepreneurs and policymakers interested in understanding and promoting innovativeness in the context of startups.

This study aims to investigate the relation between corporate social responsibility (CSR) and disclosure transparency by examining over 12,000 disclosures of financial statements extending over 20 years. The purpose is to understand how CSR ratings relate to the level of disaggregation in financial statement line items. The study considers additional factors, such as firm size and governance, that can accentuate or moderate this relation.

This study applies regression analysis, including interactions, to test the magnitude of the relation between CSR ratings and disclosure transparency. CSR is measured as a composite score that ranks firms on their reputation over numerous indicators compiled by Morgan Stanley Capital International. Disclosure transparency is measured as the level of disaggregation in financial statement line items.

The study reveals evidence consistent with the notion that firms which are more CSR conscious are also more transparent with financial statements. Evidence shows that the level of transparency is more sensitive to changes in CSR for firms less CSR conscious. Firm size is found to moderate this relation, whereas enhanced governance accentuates it.

There is limited research on the relation between CSR ratings and disclosure transparency. To the best of the authors’ knowledge, this is the first empirical evidence on the relation between CSR ratings and the disaggregation of financial statement line items. Results from this study help us understand the drivers of disclosure transparency, which can aid regulators, investors and other stakeholders in knowing how such drivers impact managerial decisions on the disaggregation of financial statements. Accountants play a central role in producing transparent and disaggregated accounting disclosures, and their role is pivotal in effectively integrating CSR into accounting and reporting models.

The COVID-19 pandemic has contributed to making workers more uncompromising with respect to issues such as quality of workplace relations and work-life balance. Hence, motivation and leadership style assume a key relevance for keeping the workforce engaged. We hypothesize that individuals may exhibit different preferences for motivational drivers and for leadership style, and that these two sets of preferences might be correlated with each other and with employees’ personality traits.

Here, we empirically investigate the relationship between leadership style and motivation, by also hypothesizing the possible contribution of personality traits. An online survey was developed and distributed to 150 employees or interns/trainees to collect measures related to their preference for leadership, their motivational drivers, as well as their personality traits. The data were analyzed by means of mediation and moderation analyses to disentangle the three-level relationship existing between these constructs.

Our results suggest that indeed there exists a relationship between preferences for leadership style and motivational drivers. Furthermore, one of these relationships appears to be critically mediated by specific personality traits.

This work is the first, to our knowledge, empirically testing the existence of a three-level relationship between leadership preferences, motivation and personality traits of employees and to contribute to disentangle their reciprocal influences.