No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
The moderating effect of internet of things and wearable technologies on enhancing safety management in construction sites
Abstract
Purpose
This study aims to investigate the moderating effects of the internet of things (IoT) and wearable technologies (WT) on the relationship between traditional safety practices (TSP) and safety management (SM) outcomes in Shanghai’s construction sector. It examines how these technologies enhance safety performance by addressing limitations in conventional approaches.
Design/methodology/approach
A survey of 300 construction professionals, including project managers, site managers and safety officers, was conducted in Shanghai. Data analysis using partial least squares structural equation modelling (PLS-SEM) assessed the moderating effects of IoT and WT on SM outcomes.
Findings
The results indicate that WT has a stronger moderating effect ( ß = 0.21, p < 0.01) than IoT ( ß = 0.11, p = 0.07). WT offers immediate safety benefits through real-time worker monitoring, whereas IoT enhances long-term safety by enabling predictive analytics and hazard detection. The study highlights the synergy between WT and TSP in improving SM outcomes.
Practical implications
While both IoT and WT enhance SM practices, their impacts differ. WT significantly improves real-time worker safety, making it essential for high-risk zones, whereas IoT contributes to long-term risk mitigation through data-driven insights. Construction managers should prioritise WT adoption for immediate safety improvements while integrating IoT-driven predictive models for sustained hazard prevention.
Originality/value
This study provides empirical evidence on the complementary roles of IoT and WT in enhancing SM in construction. It offers valuable insights into digital transformation’s role in improving safety performance.
ResearchGate has not been able to resolve any citations for this publication.
Background
This study explores the psychosocial impact of sports-related injuries on elite basketball players and their search for psychological and counselling support.
Objective
The objective is to examine how injuries affect athletes’ mental well-being, their attitudes toward received support, and their use of psychological interventions.
Methods
A phenomenological approach, analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), was applied to data from 253 elite Turkish basketball players, including active and retired athletes. A structured questionnaire was administered to gather the data.
Results
The results show that while athletes seek individual psychological support, they often feel neglected by their clubs, leading to insecurity and helplessness. Many report dissatisfaction with the mental health services provided by their organisations.
Conclusions
The study recommends integrating sports psychologists and counsellors within clubs, promoting mental health awareness, and forming interdisciplinary teams to address this. Holistic sports education programs that foster psychological resilience and emotional regulation are also advised. Further research is needed to assess the long-term effects of interventions and the role of organizational support on athletes’ mental well-being.
Construction workers are often subjected to strenuous manual labor, poor working conditions, and prolonged separation from family, leading to psychological symptoms such as stress, depression, and anxiety. These psychological factors, combined with safety climate elements like risk perception and safety attitude, significantly influence workers’ safety behaviors, including risk-taking, safety compliance, and safety participation. To address these issues, this study investigates the interplay between psychological symptoms, safety climate, and safety behaviors among construction workers in Mainland China. Data were collected through a survey of 160 construction workers, with results analyzed using correlation and regression techniques. The findings reveal that: (1) risky behavior is primarily driven by anxiety and risk perception; (2) safety participation is influenced by safety attitudes and levels of depression; and (3) safety compliance is affected by risk perception, safety attitude, stress, and depression. Interestingly, an inverse relationship is observed between depression and both risky behavior and safety compliance. These results underscore the importance of addressing psychological well-being to improve safety outcomes. Practical implications include providing psychological counseling, stress management training, and improving social connections for workers, such as facilitating regular video calls with family members or offering travel reimbursements.
Construction sites are among the most hazardous workplaces, making safety a critical concern in the sector. This study investigates the interplay between safety leadership, employee morale, harmonious safety passion, and safety performance through the lens of the social exchange theory. This research aims to assess how safety leadership impacts safety performance directly and indirectly, with employee morale acting as a mediator while harmonious safety passion moderates these relationships. A quantitative approach was employed, with data collected through structured questionnaires administered to construction workers in Istanbul and Ankara, Turkey. A total of 438 valid responses were analyzed using the Statistical Package for the Social Sciences (version 25) and Analysis of Moment Structures (version 24) for reliability, validity, and hypothesis testing. The findings confirm that safety leadership positively influences both safety performance and employee morale. Employees with high morale directly contribute to improved safety performance and act as a mediator between safety leadership and safety performance. Additionally, harmonious safety passion moderates the relationship between employee morale and safety performance, strengthening the link for workers with higher levels of passion. However, its moderating effect on the relationship between safety leadership and safety performance was not significant. These insights offer practical implications for designing safety training programs, leadership development initiatives, and policies aimed at improving safety outcomes in construction. Future research should explore longitudinal designs and diverse contexts to further validate these findings.
Purpose-The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry. Design/methodology/approach-The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area. Findings-The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites. Originality/value-This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.
The economic viability of Internet of Things (IoT) technologies in additive and advanced manufacturing has received much attention recently. This study investigates the economic benefits and constraints of incorporating IoT into additive and advanced manufacturing. The ability to produce intricate, detailed products using additive manufacturing, often known as 3D printing, has revolutionised the business, customised items with shorter lead times and lower costs. Advanced manufacturing techniques such as robotics, automation, and data analytics have increased efficiency and flexibility even more. The incorporation of IoT technologies has several benefits. Real-time data is made possible through the Internet of Things, monitoring and data collecting across the industrial workflow, improving quality control, enabling predictive maintenance, and optimising production processes. Inventory management that is effective saves waste and material costs. Analytics enabled by IoT detects inefficiencies, allowing for continual improvement and increased production. Economic viability requires addressing challenges. The initial investment for IoT infrastructure can be prohibitively expensive for small and medium-sized enterprises (SMEs). The economic benefits of IoT in additive and advanced manufacturing, on the other hand, outweigh the hurdles. Improved efficiencies, lower prices, and higher quality contribute to increasing competitiveness. Implementing the IoT leads to the creation of novel business models, such as product-as-a-service, which results in fresh sources of income. IoT device data provides essential insights into client preferences. From the findings, the market for manufacturing IoTs was valued at USD 326.1 billion in 2021 and is anticipated to reach USD 1742.8 billion by 2030, growing at a CAGR of 20.47% from 2022 to 2030. The study also cut across the quantum computing or 6G impact IoT in manufacturing and the cost–benefit analysis model, life cycle assessment (LCA), and ethical implications of IoT in manufacturing. Finally, there is no doubt about the economic potential of IoT technology in additive and advanced manufacturing. IoT integration allows for cost savings, enhanced quality, and overall efficiency. While there are issues with data security and upfront expenditures, the benefits outweigh them. Collaboration among stakeholders is required for a safe and supportive ecosystem.
Due to their widespread misuse and inadequate waste management, single-use plastic bags represent the global plastic pollution crisis and ecosystem degradation. Comprehensive research on population knowledge, attitudes, and practices (KAP) regarding single-use plastic bags is lacking in the United Arab Emirates (UAE). This study aims to fill this gap by assessing the KAP levels among the UAE population and determining the relationships between these variables. A five-point Likert scale questionnaire from previous studies was used in a cross-sectional study, and the questionnaire was distributed via Google Forms. The UAE University Research Ethics Committee approved the study (ERSC_2024_4377). Non-probability sampling and G*power statistical analysis version 3.1.9.6 determined 385 UAE residents aged 18 years and older. The findings were verified through face-to-face interviews and Cronbach’s alpha tests. KAP variable associations were assessed using Chi-square tests, Pearson’s correlation coefficients, and a structural equation model with SPSS version 29.0. This test was chosen for robust categorical and continuous data. The study included 84.7% female, and 15.3% male participants aged 18 to 65 years, primarily aged 18 to 25 years, with most holding bachelor’s degrees (47.6%), and were students (51.4%), employed (33.1%), or unemployed (12.2%). The results indicated a favourable inclination towards sustainability, with mean ± standard deviation (SD) for seven knowledge questions (3.89 ± 0.7), seven attitude questions (3.99 ± 0.7), and five practice questions (3.42 ± 0.8) exceeding the midpoint. The correlation test showed that total knowledge was positively correlated with practice (r = 0.399; p < 0.001) indicating the increasing knowledge regarding single-use plastic bags associated with increasing sustainable practices and attitudes (r = 0.648; p < 0.001). There was also a significant correlation between the total attitude and practice (r = 0.487; p < 0.001). The findings suggest targeted educational and policy interventions to promote sustainable behaviour.
Wearable technologies have become increasingly popular in recent years, as athletes and coaches look for ways to gain a competitive edge. These devices can track a variety of metrics, including heart rate, sleep quality, and movement patterns. This information can be used to identify areas for improvement and make small, incremental changes that can lead to significant gains in performance. The purpose of this narrative review is to provide an integrative overview of the literature on the impact of wearable technologies on marginal gains in sports performance. The literature review was conducted using the Scopus, PubMed, and Web of Science databases, and a total of 55 papers were considered eligible. The results of the literature overview suggest that wearable devices can be classified into three main categories. (1) Location-based wearables (LBW) track an athlete’s location and movement, which can be used to analyze training patterns and identify potential injury risks. (2) Biometric wearables (BMW) track physiological data such as heart rate, sleep quality, and body temperature; these data can be used to monitor an athlete’s fitness levels and identify signs of overtraining. (3) Performance wearables (PMW) track performance metrics such as power output, speed, and distance; this information can be used to optimize training programs and track progress over time. For each category, this paper provides the five most important data points measured by each suggested device. Additionally, sport-specific examples are provided for each category based on the literature data. The limitations of wearable devices, such as accuracy, validity, reliability, interpretability, and cost, are also discussed. However, despite these limitations, the results of the literature review suggest that wearable technologies can be a valuable tool for athletes and coaches who are looking to improve performance. Ultimately, this technological evolution in sports science is likely to dramatically change the state of the art in athletic monitoring and sports analytics.
Top management involvement (MVV) is acknowledged to be a critical factor in enhancing firm performance. As a result, we evaluated the mediation role of supply chain integration (SCI) in the relationship between MVV and innovation performance. Again, the study evaluated the moderation role of firm experience capability (FEXCAP) in the association between MVV and SCI (internal, customer, and supplier). To this end, we conducted a quantitative empirical study in Ghana enterprise agency. Data was gathered from 685 manufacturing and service small and medium enterprises’ top managers and analyzed using the Analysis of Moment Structures (Amos) and Statistical Package for Social Sciences version 26 software. The results revealed that SCI (internal, customer, and supplier) partially mediated the relationship between MVV and innovation performance.
Additionally, FEXCAP positively moderated the association between MVV and SCI (internal, customer, and supplier). The study is critical as it endorses the significant role of MVV in improving the effectiveness of SCI and FEXCAP in firm innovation performance. We evaluated our model in a small and medium context.
Abstract
Purpose
Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.
Design/methodology/approach
In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.
Findings
We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.
Practical implications
A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.
Originality/value
By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.
This educational article explores the convergence of open science practices and traditional, complementary, and integrative medicine (TCIM), shedding light on the potential benefits and challenges of open science for the development, dissemination, and implementation of evidence-based TCIM. We emphasize the transformative shift in medical science towards open and collaborative practices, highlighting the limited application of open science in TCIM research despite its growing acceptance among patients. We define open science practices and discuss those that are applicable to TCIM, including: study registration; reporting guidelines; data, code and material sharing; preprinting; publishing open access; and reproducibility/replication studies. We explore the benefits of open science in TCIM, spanning improved research quality, increased public trust, accelerated innovation, and enhanced evidence-based decision-making. We also acknowledge challenges such as data privacy concerns, limited resources, and resistance to cultural change. We propose strategies to overcome these challenges, including ethical guidelines, education programs, funding advocacy, interdisciplinary dialogue, and patient engagement. Looking to the future, we envision the maturation of open science in TCIM, the development of TCIM-specific guidelines for open science practices, advancements in data sharing platforms, the integration of open data and artificial intelligence in TCIM research, and changes in the context of policy and regulation. We foresee a future where open science in TCIM leads to a better evidence base, informed decision-making, interdisciplinary collaboration, and transformative impacts on healthcare and research methodologies, highlighting the promising synergy between open science and TCIM for holistic, evidence-based healthcare solutions.
Purpose-The construction industry is one of the most hazardous working environments globally. Studies reveal that wearable sensing technologies (WSTs) have practical applications in construction occupational health and safety management. In the global south, the adoption of WSTs in construction has been slow with few studies investigating the critical drivers for its adoption. The purpose of this study is to investigate the factors driving WSTs adoption in Ghana where investment in such technologies can massively enhance health and safety through effective safety monitoring. Design/methodology/approach-To meet the objectives of this study, research data was drawn from 210 construction professionals. Purposive sampling technique was used to select construction professionals in Ghana and data was collected with the use of well-structured questionnaires. The study adopted the fuzzy synthetic evaluation model (FSEM) to determine the significance of the critical drivers for the adoption of WSTs. Findings-According to the findings, perceived value, technical know-how, security, top management support, competitive pressure and trading partner readiness obtained a high model index of 4.154, 4.079, 3.895, 3.953, 3.971 and 3.969, respectively, as critical drivers for WSTs adoption in Ghana. Among the three broad factors, technological factors recorded the highest index of 3.971, followed by environmental factors and organizational factors with a model index of 3.938 and 3.916, respectively. Practical implications-Theoretically, findings are consistent with studies conducted in developed countries, particularly with regard to the perceived value of WSTs as a key driver in its adoption in the construction industry. This study also contributes to the subject of WSTs adoption and, in the case of emerging countries. Practically, findings from the study can be useful to technology developers in planning strategies to promote WSTs in the global south. To enhance construction health and safety in Ghana, policymakers can draw from the findings to create conducive conditions for worker acceptance of WSTs. Originality/value-Studies investigating the driving factors for WSTs adoption have mainly centered on developed countries. This study addresses this subject in Ghana where studies on WSTs application in the construction process are uncommon. It also uniquely explores the critical drivers for WSTs adoption using the FSEM.
Working with SEM and cross-sectional data, and depending on the studied phenomenon, assuming an acyclic model may mean that we obtain only a partial view of the mechanisms that explain causal relationships between a set of theoretical constructs, given that variables are treated as antecedents and consequences. Our two-step approach allows researchers to identify and measure cyclic effects when working with cross-sectional data and a PLS modelling algorithm. Using the resources and appropriation theory and the sequential model of internet appropriation, we demonstrate the importance of considering cyclic effects. Our results show that opportunities for physical access followed by digital skills acquisition enhance internet usage (acyclic effects), but also that internet usage intensity, in reverse, reinforces both digital skills and physical access (cyclic effects), supporting Norris (Digital divide: civic engagement, information poverty, and the internet worldwide. Cambridge University Press, Cambridge, 2001) social stratification hypothesis regarding future evolution of the digital divide.
Purpose. This study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on DT outcomes for small-and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.
Methods. The study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS Multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.
Originality. This research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership, and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants, and outcomes of digitalisation.
Findings. The findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity's positive and significant moderating effect on these indirect relationships.
The incidents at Three Mile Island and Chernobyl have poignantly spotlighted the indispensable role of human factors and organisational dimensions in ensuring nuclear safety. These events illuminated that beyond the intricate technicalities of nuclear operations, lie the equally significant non-technical facets that warrant utmost attention. While human factors delve into the cognitive and ergonomic challenges faced by operators, safety culture represents the ingrained organisational ethos that promotes or impedes safety standards. While a myriad of studies has dissected the impact of these elements on nuclear safety, the quest for an encompassing methodology that holistically integrates them is still ongoing. This paper embarked on an exhaustive review that probed the symbiotic relationship between human factors, safety culture, organisational performance, and individual performance within nuclear power plants, all the while bearing the indelible imprints of the Three Mile Island and Chernobyl disasters. Beginning with an elucidation of the core tenets of human factors and safety culture and their intrinsic ties to nuclear safety, the review delved deeper into empirical research that illustrated their influence on the overarching safety climate of nuclear establishments. It shines a light on recurrent challenges like communication lapses, leadership oversights, and the ever-present spectre of human error. In its culmination, the review underscored the intertwined nature of these pivotal elements and expounds on their collective import in sculpting a resilient safety culture in nuclear setups. Recommendations for bolstering human factors and safety culture practices, gleaned from the bitter lessons of Three Mile Island and Chernobyl, are proffered. At its core, this paper advocated for an integrative paradigm that melds organisational and individual performance metrics with human factors and safety culture insights, perpetually underscored by rigorous research and evaluation, to ensure the unerring safety and dependability of nuclear power plants.
The construction sector is characterized by dynamic and perilous conditions, demanding innovative strategies to bolster worker safety. This research delves into the incorporation of cutting-edge wearable technologies as a proactive measure to tailor safety protocols for construction sites. Focused on risk mitigation and overall safety enhancement, this investigation assesses the efficacy of various advanced wearable devices. The study commences by scrutinizing the role of intelligent helmets equipped with augmented reality (AR) technology. These helmets furnish real-time data about the construction site, delivering critical information to workers, including potential hazards, emergency exits, and equipment statuses. The integration of AR heightens situational awareness, empowering workers to make well-informed decisions and respond promptly to changing conditions. Beyond smart helmets, the research explores the implementation of wearable sensors designed to monitor the physiological parameters of construction workers. Capable of measuring vital signs such as heart rate, body temperature, and fatigue levels, these sensors enable continuous assessment of worker health. The data generated can be analyzed to identify patterns and trends, facilitating the implementation of preventive measures to address health-related risks. Additionally, the study delves into the adoption of exoskeletons as wearable devices to enhance human capabilities and diminish the risk of musculoskeletal injuries. These exoskeletons provide ergonomic support, particularly during tasks involving heavy lifting or repetitive motions. By assisting workers in maintaining proper posture and reducing physical strain, exoskeletons contribute to long-term injury prevention and improved overall well-being. Integration with artificial intelligence (AI) algorithms enhances the capabilities of these sensors, providing a nuanced understanding of individual health patterns and personalized safety recommendations. The integration of smart helmets, wearable sensors, and exoskeletons presents a multifaceted approach to personalized safety, addressing both environmental and physiological factors. As the construction industry continues to evolve, the adoption of these technologies holds the potential to not only enhance safety outcomes but also redefine the future of work in hazardous environments.
Keywords: Wearable technology, Wearable devices, Construction industry, Accident prevention, Occupational risk, Wearable sensor, Construction safety.
The rapid progression of technology has paved the path for the convergence of Artificial Intelligence (AI), Internet of Things (IoT), and big data within the Architecture, Engineering, and Construction (AEC) industry. This convergence has given rise to intelligent and sustainable construction paradigms, exemplified by Construction 4.0 and Construction 5.0. This research delves into the challenges and future directions associated with seamlessly integrating these cutting-edge technologies in the AEC sector. The discussion begins with an in-depth exploration of the foundational aspects of intelligent and sustainable construction. It focuses on the crucial roles played by IoT technology, advanced computing models, and big data technology. The research then delves into the various AI models and techniques that are reshaping the landscape of Construction 4.0 and 5.0, along with the broader societal changes embodied in Society 5.0. The research underscores the significance of these AI-driven solutions in optimizing resource management, streamlining operational processes, and enhancing decision-making within the AEC field. Furthermore, the study highlights the synergistic relationship between Blockchain technology and its applications in conjunction with AI and IoT. This convergence of technologies not only enhances transparency and security in transactions but also facilitates the implementation of efficient and sustainable construction practices in alignment with societal and environmental needs. Throughout the exploration of these technological advancements, the research underscores the integration of the Sustainable Development Goals (SDGs) as a vital guiding framework for shaping future initiatives within the AEC sector. By aligning technological innovation with the pursuit of sustainable development, the AEC industry can proactively contribute to global endeavors aimed at achieving long-term socio-economic and environmental sustainability. This research serves as a roadmap for industry stakeholders, policymakers, and researchers, emphasizing the importance of strategic collaboration and innovative solutions to address challenges and unlock the full potential of AI, IoT, and big data technologies for intelligent and sustainable AEC practices.
Keywords: Artificial Intelligence, Construction 4.0, Internet of Things, Construction 5.0, Big Data, Industry 4.0, Smart construction, Sustainable construction.
Construction projects are risky environments which can increase the number of fatal and non-fatal accidents. The development of Personal Protective Equipment (PPE) is one of the beneficial endeavors to control the number of accidents. Since traditional PPEs have not reached full success in controlling occupational injuries, the collection and analysis of safety data were introduced as a vital factor in comprehensive safety management of construction sites. With the widespread use of advanced technologies in this industry, questions have arisen about impacts of the smart PPE on construction safety. This study thus reviews high-tech PPEs for the construction industry and discusses possible benefits, challenges, and structures to explore their capacity for data collection from personnel and construction sites to reduce the risks and hazards.
Cutting-edge technologies, with a special emphasis on the Internet of Things (IoT), tend to operate as game changers, generating enormous alterations in both traditional and modern enterprises. Understanding multiple uses of IoT has become vital for effective financial management, given the ever-changing nature of organizations and the technological disruptions that come with this paradigm change. IoT has proven to be a powerful tool for improving operational efficiency, decision-making processes, overall productivity, and data management. As a result of the continuously expanding data volume, there is an increasing demand for a robust IT system capable of adeptly handling all enterprise processes. Consequently, businesses must develop suitable IoT architectures that can efficiently address these continually evolving requirements. This research adopts an incremental explanatory approach, guided by the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). A rigorous examination of 84 research papers has allowed us to delve deeply into the current landscape of IoT research. This research aims to provide a complete and cohesive overview of the existing body of knowledge on IoT. This is accomplished by combining a rigorous empirical approach to categorization with ideas from specialized literature in the IoT sector. This study actively contributes to the ongoing conversation around IoT by recognizing and critically examining current difficulties. This, consequently, opens new research possibilities and promotes future developments in this ever-changing sector.
Business–IT alignment (BITA) has become crucial for effective organisational management in today’s interconnected global economy. This article investigates the relationship between BITA and corporate sustainability, exploring how businesses can leverage BITA for sustainable growth and development. The study employs a case research approach in a multinational manufacturing organisation, utilising a mixed methods research (MMR) design. In the quantitative part of the research, the PLS-SEM technique was used to examine the influence of six BITA factors on employees’ self-perceived action competence for sustainability (SPACS). This study confirmed that all six BITA factors strongly influence all three SPACS factors. In the qualitative part of the research, semi-structured interviews were used to measure the BITA maturity level of the organisation and the influence of BITA factors on corporate sustainability. Based on quantitative and qualitative research results, it can be confirmed that BITA strongly influences corporate sustainability. Results also confirm that there is no universal approach to BITA and its influence on corporate sustainability. Organisations must focus on all factors of BITA equally to achieve better levels of BITA and ensure its influence on corporate sustainability.
The Electronic Manufacturing Service (EMS) industry contributes significantly to toxic waste generation due to its fabrication processes. Notably, adherence to the Restriction of Hazardous Substances (RoHS) Directive varies amongst EMS providers, despite its aim to reduce electronic waste. This study explores the factors influencing EMS providers’ decision to adopt the RoHS directive, utilizing the technology–organization–environment (TOE) and the human–organization–technology (HOT) fit, or the TOE-HOT fit framework. We validated our framework using partial least squares structural equation modeling (PLS-SEM), based on responses from 379 questionnaires from major EMS providers. The results demonstrated that expert resources, adequate resources, perceived industrial pressure, institutional pressure, and costs were positively associated with RoHS adoption. However, innovation, relative advantage, and verification ability were identified as significant barriers. In particular, innovation in the human dimension was the key determinant for RoHS adoption. Therefore, clear policy instruments and regulations may enhance RoHS adoption by EMS providers. These findings can guide environmental policy definitions in governmental laws and strategies, encouraging EMS providers and other firms to adopt RoHS standards.
A large number of studies have been conducted to demonstrate that job stress negatively affects construction workers’ physiological safety behaviors, but there is a lack of research on the impact of psychosocial safety behaviors on construction workers, which is an important component of overall workplace safety. This study modeled the effects between three job stressors (the job itself, job insecurity, and family-work conflict) and psychosocial safety behavior sub-dimensions (psychosocial safety compliance and psychosocial safety participation), using psychological resilience as a mediating variable. Data were obtained from 304 construction workers in China. The results showed that there were positive and negative effects between the three job stressors, psychosocial safety behavior sub-dimensions, and psychological resilience. Psychological resilience was mediated differently across the three job stressors and psychosocial safety behavior sub-dimensions. This study reveals the mechanisms by which job stress affects the psychosocial safety behaviors of construction workers and provides more empirical evidence to unravel the relationships between various job stressors and psychosocial safety behavior sub-dimensions. In addition, this paper discusses measures to improve psychosocial safety behaviors based on the perspectives of job stressors and psychological resilience.
In a world driven by constant change and innovation, Higher Education Institutions (HEIs) are undergoing a rapid transformation, often driven by external factors such as emerging technologies. One of the key drivers affecting the design and development of educational delivery mechanisms in HEIs is the fast pace of educational technology development which not only impacts an institution’s technical capacity to infuse hardware and software solutions into existing learning infrastructure but also has implications for pedagogical practice, stakeholder acceptance of new technology, and HEI administrative structures. However, little is known about the implementation of contemporary educational technology in HEI environments, particularly as they relate to competing stakeholder perceptions of technology effectiveness in course delivery and knowledge acquisition. This review fills that gap by exploring the evidence and analyses of 46 empirical research studies focussing on technology implementation issues in a diverse range of institutional contexts, subject areas, technologies, and stakeholder profiles. This study found that the dynamic interplay of educational technology characteristics, stakeholder perceptions on the effectiveness of technology integration decisions, theoretical frameworks and models relevant to technology integration in pedagogical practices, and metrics to gauge post-implementation success are critical dimensions to creating viable pathways to effective educational technology implementation. To that end, this study proposes a framework to guide the development of sound implementation strategies that incorporates five dimensions: technology, stakeholder perceptions, academic discipline, success metrics, and theoretical frameworks. This study will benefit HEI decision-makers responsible for re-engineering complex course delivery systems to accommodate the infusion of new technologies and pedagogies in ways that will maximise their utility to students and faculty.
The global COVID-19 pandemic forced the construction industry to a standstill. In the wake of the pandemic, this sector must be prepared to make bold, innovative moves to prepare for the future. Over the past few years, the use of drones and robotics has expanded with many commercial uses, including in the construction industry. Drone-driven automation has an enormous impact in improving productivity and reducing cost and schedule overruns. The use of drones, along with the application of Internet of Things (IoT) and robotics, can make a significant impact on the supply chain and improve inventory accuracy, leading to faster and more cost-effective building projects. This paper will propose and statistically substantiate an optimization model for supply chain management through the accelerated use of drones and Artificial Intelligence (AI) in the post-pandemic era. The use of smart devices and IoT will allow warehouse managers to have real-time visibility of the location and inventory tracking, as well as enabling warehouse workers to access information without being physically present. Cutting-edge drone technology can quickly perform inspections to make inventory control more economical and efficient. While they are certainly not a perfect fit for every building surveillance task, drones have many advantages for probing buildings in search of leaks, performing aerial surveys, and dealing with security issues more cost-effectively than manual procedures, thereby leading to improved communication and collaboration between different stakeholders. This paper includes a real-life case study and dynamic mathematical model to demonstrate how this approach results in a project’s materials becoming visible, traceable, and easily tracked from end to end.
The Internet of Things (IoT) is playing a significant role in the transformation of traditional factories into smart factories in Industry 4.0 by using network of interconnected devices, sensors, and software to monitor and optimize the production process. Predictive maintenance using the IoT in smart factories can also be used to prevent machine failures, reduce downtime, and extend the lifespan of equipment. To monitor and optimize energy usage during part manufacturing, manufacturers can obtain real-time insights into energy consumption patterns by deploying IoT sensors in smart factories. Also, IoT can provide a more comprehensive view of the factory environment to enhance workplace safety by identifying potential hazards and alerting workers to potential dangers. Suppliers can use IoT-enabled tracking devices to monitor shipments and provide real-time updates on delivery times and locations in order to analyze and optimize the supply chain in smart factories. Moreover, IoT is a powerful technology which can optimize inventory management in smart factories to reduce costs, improve efficiency, and provide real-time visibility into inventory levels and movements. To analyze and enhance the impact of internet of thing in smart factories of industry 4.0, a review is presented. Applications of internet of things in smart factories such as predictive maintenance, asset tracking, inventory management, quality control, production process monitoring, energy efficiency and supply chain optimization are reviewed. Thus, by analyzing the application of IoT in smart factories of Industry 4.0, new ideas and advanced methodologies can be provided to improve quality control and optimize part production processes.
The Internet of Things is a comprehensive system of connected computing devices and sensors that provide extensive data sharing capability for any specific purpose. For the construction industry, the applications of the Internet of Things have been increasing over the past few years, and it is because technology can provide full support to construction projects in attaining significant efficiency. The most critical part of construction products where the internet of things can be adopted is safety management because hundreds of accidents happen every year that result in significant injuries to construction workers and even death in some cases. For small construction projects, the situation is much worse, as there are never enough resources to adopt the latest technology, such as the Internet of Things. This study is structured with the aim of identifying the critical implementation barriers of the internet of things that affect small construction projects in Malaysia specifically. A mixed methodology study design is followed in which, after identifying the implementation barriers of the internet of things from existing literature, they are filtered with expert opinion. A pilot survey was conducted on which exploratory factor analysis was applied to further identify the significant barriers relating to the Internet of Things in small construction projects in Malaysia. A main survey was conducted afterwards, on which the structural equation modelling was done to develop the model involving the final 16 barriers divided into 5 formative constructs. The most critical barriers are found to be related to databases and technology, while the least impact is created by management barriers. Positive theoretical and managerial implications are indicated for future researchers and construction workers, respectively, by which they can improve the implementation of internet of things in small construction projects in Malaysia.
Information and Communication Technology (ICT) has been acknowledged to be an enabler of small businesses, including those in the informal sector. However, determining the relationship between the perception of technology by informal service providers and the readiness to use technology is critical. By adopting a survey research design, this study investigates how the perception of a web technology portal (WTP) by informal sector service providers in the Cape Town metropolitan area in South Africa affects their readiness to use WTP to support their businesses. The study involved a sampled population of 419 informal sector service providers within the Cape Town metropolis. A conceptual framework consisting of constructs from the self-efficacy theory (SET), the unified theory of acceptance and use of technology (UTAUT) and the technology readiness index (TRI) was used as the theoretical reference for the study. We used a semi-structured questionnaire based on a five-point Likert scale to collect data, which we analyzed using partial least squares structural equation modelling (PLS-SEM). The results showed that discomfort (p = 0.330), effort expectancy (p = 0.630), innovativeness (p = 0.620), optimism (p = 0.740), insecurity (p = 0.110), facilitating conditions (p = 0.160), and internal factors (p = 0.180) all had a non-significant positive influence on e-readiness. On the other hand, self-efficacy (p < 0.001), performance expectancy (p < 0.030), social influence (p < 0.001), and external factors (p < 0.001) had a significant positive influence on e-readiness. Gender and business type, the moderating variables for respondents’ e-readiness, were found to be insignificant (p > 0.005) for e-readiness for web portal technology utilization. This study identifies the key variables that could influence the readiness of informal sector operators to utilize web portal technology. It also provides a guide for designers and developers of digital platforms and government policymakers on critical factors germane to providing technology support for the informal business sector.
Many constructs in management studies, such as perceptions, personalities, attitudes, and behavioral intentions, are not directly observable. Typically, empirical studies measure such constructs using established scales with multiple indicators. When the scales are used in a different population, the items are translated into other languages or revised to adapt to other populations, it is essential for researchers to report the quality of measurement scales before using them to test hypotheses. Researchers commonly report the quality of these measurement scales based on Cronbach’s alpha and confirmatory factor analysis results. However, these results are usually inadequate and sometimes inappropriate. Moreover, researchers rarely consider sampling errors for these psychometric quality measures. In this best practice paper, we first critically review the most frequently-used approaches in empirical studies to evaluate the quality of measurement scales when using structural equation modeling. Next, we recommend best practices in assessing reliability, convergent and discriminant validity based on multiple criteria and taking sampling errors into consideration. Then, we illustrate with numerical examples the application of a specifically-developed R package, measureQ, that provides a one-stop solution for implementing the recommended best practices and a template for reporting the results. measureQ is easy to implement, even for those new to R. Our overall aim is to provide a best-practice reference for future authors, reviewers, and editors in reporting and reviewing the quality of measurement scales in empirical management studies.
Purpose
This study aims to assess the usability of augmented reality (AR) based mobile app for excavation and earthmoving processes using a novel tool entitled Excavator Augmented Reality (EAR).
Design/methodology/approach
A mixed-methods research approach was used through conducting experimentation to collect qualitative and quantitative data collected from the Sri Lankan construction sector. EAR app was used for experimentation in outdoor areas examining how a 360° tracked hydraulic excavator can be navigated in different physical environments similar to the real prospected job.
Findings
The findings reveal that EAR could make a considerable impact on enhancing productivity, safety and training processes. However, the developed EAR App subjected to assessment demonstrated the highest satisfaction gap for the auditory aspects. Among the remaining criterion, the satisfaction met user expectations for comfortability and no-risk practice. An analysis of strengths, weaknesses, opportunities and threats (SWOT analysis) conducted revealed that visualising the excavator activities and the requirements of improved features were the highest agreed strengths and weaknesses of the EAR. Among the opportunities for improvement, the necessity of improving emergency and safety reached the highest agreement. Moreover, the study presented the challenges in introducing mobile augmented reality (MAR) to the construction sector under the political, economic, sociocultural, technological, environmental and legal (PESTEL) model along with solutions to be taken.
Originality/value
This study provides a novel approach to addressing the safety, productivity and training concerns in heavy mobile plants and machinery on construction sites which remains to be unexplored to this end.
Purpose
This study aims to explore the impact of financial management strategies on the financial performance of construction projects in Iraq, specifically investigating the moderating role of company size. The primary focus is to understand how different cost components contribute to performance and how this relationship varies between larger and smaller businesses in the construction industry.
Design/methodology/approach
Utilizing a sample of 296 participants from the construction business in Iraq, this research employed a survey questionnaire. The WarpPLS software facilitated data analysis, employing Partial Least Squares Structural Equation Modelling (PLS-SEM) with bootstrapping for model validation. Confirmatory factor analysis (CFA) with maximum likelihood estimation assessed the measurement model, ensuring a comprehensive understanding of the financial management strategies and performance relationship.
Findings
The study reveals that equipment costs show no significant relationship with performance in Iraq’s construction industry. Larger construction firms exhibit a positive influence on financial performance from material costs, labour costs and permit/licencing fees compared to smaller firms. This suggests a moderation effect of size on the relationship between these cost components and financial outcomes, highlighting the nuanced impact of financial management strategies on performance.
Research limitations/implications
While shedding light on the size-dependent nuances in the relationship between financial strategies and performance, this study is confined to the construction industry in Iraq. The findings might not be universally applicable, and contextual variations should be considered. Additionally, the reliance on survey data introduces the potential for response bias. Future research could expand the scope to different industries and regions, incorporating diverse methodological approaches for a more comprehensive understanding of the nuances in the financial management and performance relationship.
Practical implications
Construction companies in Iraq can enhance project performance by strategically allocating resources and effectively managing costs, considering the nuanced impact of company size. Larger firms, in particular, should focus on optimising material costs, labour costs and permit/licensing fees to maximise financial outcomes. This study provides actionable insights for practitioners, guiding financial management decisions and offering practical recommendations for improving project performance in the Iraqi construction industry.
Social implications
The research contributes valuable insights to the Iraqi construction industry, an area with limited prior research on management matters. By emphasising the role of size in moderating the relationship between financial strategies and performance, the study informs industry stakeholders, policymakers and professionals about the importance of tailoring financial management approaches based on company size. This knowledge can potentially lead to improved financial outcomes, positively impacting the overall economic and social landscape in Iraq.
Originality/value
This research adds to the body of knowledge by examining the impact of company size on the relationship between financial management methods and performance in Iraq’s construction projects. The study’s originality lies in uncovering the moderating effect of size on the connection between specific cost components and financial performance. The findings provide a unique perspective on financial management strategies, offering construction companies valuable insights into optimising performance based on their size. This research contributes significantly to an underexplored area, filling a gap in the existing literature and providing practical implications for financial decision-making in the construction industry.
Purpose
This paper aims to explore the impact of digitalisation on waqf activities, focussing on blockchain, crowdfunding and artificial intelligence to predict future trends in digitalisation within waqf activities.
Design/methodology/approach
The study used a quantitative approach to combine the Unified Theory of Acceptance and Use of Technology (UTAUT) and Diffusion of Innovation Theory (DIT) to comprehensively analyze the elements that affect the adoption of digital technology. SmartPLS software conducted the data analysis after collecting the data using SPSS. In this study, 310 respondents comprising Muslims who contribute to waqf were collected.
Findings
This research provides important insights into the elements influencing future behavior and can help policymakers promote and facilitate the digitalisation of waqf activities, not only in Malaysia but also in similar situations worldwide.
Research limitations/implications
Analysis indicated that four hypotheses were validated, implying that effort expectancy, compatibility, observability and trialability are significant determinants affecting intention. The findings suggest significant potential for further research. This paper delineates numerous methodological challenges and concerns while proposing recommendations for further research. Future research could use additional search phrases and engines not incorporated in this study to provide a more comprehensive overview. This study primarily concentrates on the applications of waqf development, digitalisation, blockchain, crowdfunding and artificial intelligence.
Practical implications
The four hypotheses regarding facilitating condition, performance expectation, relative advantage and social influence were not supported as they were found to have no significant impact on intention. For practitioners, based on the findings, it can give some insight into digitalisation’s influence on the intention of contributing to waqf in society. As for the researchers, there could be some ideas to study other than the factors mentioned in this study, as well as the supporting literature for their studies.
Originality/value
This paper provides useful insights on how emerging technology can potentially disrupt the traditional waqf landscape. It emphasizes the unique contributions of digitalization in improving transparency and accessibility, blockchain in ensuring security and trust, crowdfunding in mobilizing resources and artificial intelligence in optimizing decision-making processes.
Purpose
The importance of cybernetic controls (CC) in the context of accounting information systems (AIS) in increasing data accuracy (DA) and improving decision-making (DM) has attracted much attention. In this study, the paper analyses the moderating role of CC on the relationship between DA and DM in AIS, which is supposed to be a case of construction projects in Iraq.
Design/methodology/approach
Data were collected using a questionnaire-structured interview targeted at construction site managers and project managers, employing probability sampling on the 253 valid responses, which was analysed using the partial least squares structural equation modelling (PLS-SEM) method.
Findings
CC significantly reduced the role of the moderating aspect of the DA and positively influenced DM in AIS. These results provided a base for the research postulates, including integrating CC in AIS to offer an overdue solution to challenges in construction project DM.
Practical implications
Empirical outcomes of the study demonstrated that the implementation of CC in AIS can be applied successfully to the accounting of exact data and precision decisions in construction projects. Such lessons are strategically important to practitioners needing optimal AIS performance with a view to industry satisfaction.
Originality/value
The work has a breakthrough quality in the study at hand by stressing that CC moderate the link of DA to the DM approach in AIS. This area lacks exposition when construction projects in Iraq are the case. The findings of the research are aligned with the criteria of good governance in the context of the use of electronic systems to make decisions in AIS.
Exploring the transformative synergy of IoT and blockchain in biomedical and healthcare realms, this abstract delves into the pivotal role these technologies play in placing patients at the forefront of their care journey. Blockchain technology improves data security and privacy, giving patients greater control over their confidential medical data. When IoT devices are combined with blockchain technology, they facilitate the collection and transmission of real-time data, enhancing remote patient monitoring and telehealth services. In addition, blockchain technology guarantees transparency in the pharmaceutical supply chain by fighting against counterfeit drugs and verifying medication authenticity. Patients can now easily manage their electronic health records, allowing for smooth sharing between healthcare providers. Recognizing challenges such as user education and system integration underscores the significance of closing knowledge gaps and creating user-friendly interfaces. By integrating blockchain technology with IoT solutions, this approach prioritizes patients, providing secure data, personalized care, and reliable medications to improve well-being. Continuous collaboration between technology innovators, healthcare practitioners, and patients is crucial to fully harness this transformative potential.
In the history of our civilization, masonry structures date back thousands of years. Considering the different types, geometries, and arrangements of masonry components, as well as the mortar properties, defining “masonry” precisely is challenging. Construction of masonry structures relies on layering single components and binding them using mortar or crafting them with stones without mortar. Despite many advantages, masonry structures remain one of the most vulnerable construction types. Many of these structures have not been designed to withstand seismic loads. Generally, their structural systems have been designed primarily to withstand gravity loads. Consequently, moderate earthquakes can cause extensive damage and destroy entire cities. Therefore, the assessment, repair, and retrofitting of these structures is vital to society’s well-being. First, this study describes masonry structures and their mechanical and structural characteristics. Next, methods for detecting and classifying common types of damage are presented. Subsequently, a comprehensive review of assessment, repair, and retrofitting methods for masonry structures is provided. Machine learning (ML) techniques have proven to be exceptional tools for providing accurate and reliable information. In this paper, descriptions and recent advances in ML techniques for the assessment, repair, and retrofitting of masonry structures are presented. These models can be utilized for several predictive applications, such as determining possible damage scenarios in heritage buildings, assessing seismic vulnerability, detecting superficial surface damage, and selecting mortar compositions for optimal mechanical properties. Furthermore, structural health monitoring (SHM) methods applicable to masonry structures are discussed. The study concludes with case studies, and an extensive discussion of existing methods, challenges, and recommendations for future work.
In 2008, Vietnam's Prime Minister approved the construction of the ‘Hanoi Urban Railway System’, a major infrastructure project for the country's capital city. The construction of Line 2A, the first line of this 8‐line railway, took ten years to complete, and was finally inaugurated in November 2021. Spanning 13 km across the city centre, Line 2A encountered more than just construction setbacks, with its reputation tarnished by contractor choice, accidents, and public scepticism over safety and accessibility. Sowing further seeds of doubt in the minds of many Hanoi residents is the fact that two‐thirds of the original financing came from preferential loans from Vietnam's large northern neighbour, conditional on the contractor and key materials being sourced from Vietnam's large, northern neighbour. Moreover, the project is informally categorized as part of Vietnam's large northern neighbour's Belt and Road Initiative. Drawing from conceptual literature regarding infrastructural politics and mobility (in)justice, we analyse how Hanoi residents have experienced and negotiated the construction of this Chinese‐Vietnamese infrastructure project. In particular, we consider how the livelihoods of those directly affected by the railway's operations, namely motorbike taxi‐drivers, have been impacted to date.
The maturing state of partial least squares structural equation modeling (PLS-SEM) research has seen exceptional knowledge advances over the past decade. However, advances in practice among lay researchers have advanced at a slower pace. We conclude that this gap between PLS-SEM research and practice may be attributed to the sophisticated and arcane approach to detailing new methodological advances. Moreover, prediction has been a peripheral topic in PLS-SEM mediation literature to date. This chapter sits at the intersection of these two gaps. We first seek to advance understanding of the intertwining roles of prediction and mediation. We then provide practical demonstrations of two particularly occluded topics in mediation research: specific indirect effects and indirect effect sizes.
Purpose - This study evaluates the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Design/methodology/approach - Based on a structured literature review approach, we reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques, and reporting practices.
Findings - LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models, and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.
Originality/value - This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
Training deep neural networks (DNNs) typically requires massive computational power. Existing DNNs exhibit low time and storage efficiency due to the high degree of redundancy. In contrast to most existing DNNs, biological and social networks with vast numbers of connections are highly efficient and exhibit scale-free properties indicative of the power law distribution, which can be originated by preferential attachment in growing networks. In this work, we ask whether the topology of the best performing DNNs shows the power law similar to biological and social networks and how to use the power law topology to construct well-performing and compact DNNs. We first find that the connectivities of sparse DNNs can be modeled by truncated power law distribution, which is one of the variations of the power law. The comparison of different DNNs reveals that the best performing networks correlated highly with the power law distribution. We further model the preferential attachment in DNNs evolution and find that continual learning in networks with growth in tasks correlates with the process of preferential attachment. These identified power law dynamics in DNNs can lead to the construction of highly accurate and compact DNNs based on preferential attachment. Inspired by the discovered findings, two novel applications have been proposed, including evolving optimal DNNs in sparse network generation and continual learning tasks with efficient network growth using power law dynamics. Experimental results indicate that the proposed applications can speed up training, save storage, and learn with fewer samples than other well-established baselines. Our demonstration of preferential attachment and power law in well-performing DNNs offers insight into designing and constructing more efficient deep learning.
In most fast-urbanising cities there is an enormous challenge in the provision of decent housing for the urban poor. It is common for the housing for the urban poor to be sited in areas of poor transport and job accessibility. This paper hypothesizes that for those cities that have reasonable growth potentials, the priority for such housing provision should be a much greater effort in coordinating the distribution of jobs and transport infrastructure construction with housing. To examine this hypothesis, we establish a systematic and quantitative approach to evaluate the long-term impacts of alternative urban development strategies by extending a recursive spatial equilibrium model through differentiating socio-economic groups based on the Erikson-Goldthorpe-Portocarero schema. The model is tested using empirical data from Beijing, a city where the imbalance among housing, jobs and transport has become an acute issue. The model results show that the current required level of effort in the coordination is likely to be a magnitude higher than what the current policies envisage. Further decentralisation of employment coordinated with improved transport interventions and enhanced housing supply in new towns is critical in resolving the problems of increased commuting demands and low job accessibility.