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The partial least squares structural equation modeling (PLS-SEM) approach for construction management (CM) scholars has become the preferred approach for its capability of assessing the complex relationship and relaxed normality and sample size assumptions. This paper systematically maps the structure of knowledge about PLS-SEM in CM using bibliometric analysis. Also, the study employs meta-analysis to explore how data and model characteristics, model evaluation and advanced modeling techniques have been utilized in the CM domain.

This study integrated two methods: bibliometric analysis on a sample of 211 articles identified using the PRISMA framework and meta-analysis on 163 articles identified based on the availability of full-length articles and relevant information.

The results revealed the leading knowledge formation entities (countries, institutions, authors, sources and documents). Also, the study employs full content analysis to identify six research themes, and meta-analysis is used to explore the use of PLS-SEM based on the following criteria: (1) reasons for using PLS-SEM in CM, (2) data characteristics, (3) model characteristics and evaluation and (4) use of advanced modeling and analysis techniques. Further, the study uses regression analysis and identifies “advanced modeling and analysis techniques” as the critical feature responsible for the publication in a journal with high scientific prestige. Finally, the study presented the comprehensive guidelines to be used by construction management scholars who wish to use PLS-SEM in their research work.

To the author’s knowledge, it is the first study of this kind to use PLS-SEM in CM research. This study provides an extensive analysis of the Scopus database and an in-depth review of the data characteristics, model characteristics and use of advanced modeling techniques in CM research.

This research aims to explore the factors influencing the adoption intention of eco-friendly smart home appliances among residents in densely populated urban areas of a developing country.

A quantitative research approach was employed to gather data from 348 respondents through purposive sampling. A comparative analysis strategy was then utilized to investigate the adoption of eco-friendly smart home appliances, combining both linear (PLS-SEM) and non-linear (fsQCA) approaches.

The results obtained from PLS-SEM highlight that performance expectancy, facilitating conditions, hedonic motivation, price value, and environmental knowledge significantly influence the adoption intention of eco-friendly smart home appliances. However, the findings suggest that effort expectancy, social influence, and habit are not significantly associated with customers' intention to adopt eco-friendly smart home appliances. On the other hand, the fsQCA results identified eight configurations of antecedents, offering valuable insights into interpreting the complex combined causal relationships among these factors that can generate (each combination) the adoption intention of eco-friendly smart home appliances among densely populated city dwellers.

This study offers crucial marketing insights for various stakeholders, including homeowners, technology developers and manufacturers, smart home service providers, real estate developers, and government entities. The findings provide guidance on how these stakeholders can effectively encourage customers to adopt eco-friendly smart home appliances, aligning with future environmental sustainability demands. The research implications underscore the significance of exploring the antecedents that influence customers' adoption intention of eco-friendly technologies, contributing to the attainment of future sustainability goals.

The environmental sustainability of smart homes, particularly in densely populated city settings in developing countries, has received limited attention in previous studies. Therefore, this study aims to address the pressing issue of global warming and make a meaningful contribution to future sustainability goals related to smart housing technologies. Therefore, this study employs a comprehensive approach, combining both PLS-SEM (linear) and fsQCA (non-linear) techniques to provide a more thorough examination of the factors influencing the adoption of environmentally sustainable smart home appliances.

The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention.

This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors.

The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors.

This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future.

This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.

The external business environment of the organization is always changing at a rapid pace. For a firm to adapt to changing client requirements, it must implement the right business procedures and strategies. To improve competitive advantage, this study investigates the roles that supply chain partnerships, cross-functional integration, responsiveness and resilience play in achieving competitive advantages in Palestine.

Industrial institutions in Palestine constitute the study population. Data are collected by distributing surveys via Google Forms linked to manufacturers in industries such as the Leather and shoe Industry, metal industries, chemical industries, construction industries, textile industries, stone and marble industries, pharmaceutical industry, veterinary industry, food industry, plastic industry, paper industry, major advantages and disadvantages. The SEM-PLS approach is used to analyze the data.

The findings demonstrate that supply chain responsiveness, resilience and cooperation are all improved by cross-functional integration in inventory data integration and immediate operation. Supply chain partnerships improve the supply chain’s responsiveness, resilience and competitive advantage by involving partners in work teams and exchanging best practices. The enhancement of supply chain resilience and competitive advantage is influenced by the company’s capacity to act promptly in response to variations in demands.

This paper faces some limitations and it can be drawn as follows: To enhance supply chain risk management, the study continues to concentrate on manufacturing organizations that have internal integration. It also emphasizes the necessity of supply chain integration, which establishes direct connections with outside partners.

The findings of this study suggest some policy implications, as follows: To provide the manufacturing sector with a competitive edge, operations supervisors must be able to track and assess processes to ensure they are meeting demand. Firms that possess the ability to adjust to novel procedures or advancements in technology gain a competitive edge by guaranteeing consistent and high-quality delivery of products.

By implementing IT integration, this study theoretically and practically advances the understanding of the resource-based view of competitive advantages. This study focuses on providing insights into the nature of the relationship between supply chain partnership, cross-functional integration, responsiveness and flexibility and competitive advantages in the manufacturing sector in the Palestinian market.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

This study examines and estimates the relationship among identified factors or determinants for the adoption of water ionizers by customers.

To this end, the questionnaire is prepared to have the preferences of customers based on the factors or enablers identified for the analysis of customers' perceptions toward the adoption of water ionizers. Recipients are identified to collect their preferences for the factors responsible for the adoption. The convenience sampling method is used in administering the questionnaire for the study. The structural equation modeling (SEM) technique is used to construct the model for defining the relationship between measured and latent variables using the lavaan, haven, psych and semPlot libraries in R software.

The study reveals that product features, which include pH value, oxidation-reduction potential (ORP) and micro-clustering (MC), are influenced by environmental sustainability (ES), and as a result, product features and product outcomes (brand value (BV), customer recommendation (CR) and perceived usefulness (PU)) together influence the adoption of water ionizers by customers.

Water ionizers have appeared as consumer electronic appliances designed to alter the pH and ORP of water through an electrolysis process. There are proven benefits to improved water quality across different pHs for its health benefits (HB) and other commercial and household uses. The study recommends that potential HB perceived through water ionizers and product features, which are supported by ES, and helps customers decide on the adoption of water ionizers.

The study supports comprehending the relationships between consumer behavior, sustainable practices and innovative technologies like water ionizers as society places a greater emphasis on environmentally conscious living and sustainable living. This study aims to clarify the elements affecting the adoption and perception of water ionizers from a sustainability perspective through an extensive assessment of the literature and empirical analysis.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

This paper presents a pioneering investigation into the barriers impeding the adoption of reverse logistics (RL) in the Iranian construction industry, addressing a significant gap in the current literature within the country.

Through a meticulous examination of the literature, complemented by 19 in-depth interviews, a battery of barriers to RL implementation was initially identified, distilled into a final set of 30 barriers, which served as the basis for the design of a structured survey questionnaire. Employing Partial Least Squares–Structural Equation Modeling (PLS-SEM), an analysis was conducted on a dataset that comprised of 80 responses. Subsequently, the barriers approved through the PLS- SEM were subjected to prioritization through the application of Fuzzy TOPSIS.

Findings reveal the critical inadequacy of contemporary technology and infrastructure, a foundation essential for the efficacious enactment of RL. This shortfall manifests in procurement and logistics processes plagued by inefficiency and ineffectiveness, as consequences of an immature information and technology ecosystem. Furthermore, the study underscores the dominance of traditional markets where the adoption of secondary materials/products remains sporadic, signaling a crucial area for further research and intervention.

This study offers original insights into the significant hurdles that hinder the adoption and integration of RL practices within the Iranian construction industry, an under-explored area within the RL research domain. For industry practitioners, findings point to recommendations for overcoming these barriers in the specific Iranian context while also offering broader insights and lessons that may be relevant to other countries and similar contexts.