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This study investigates the possible curvilinear relationship between operational interdependency and supply chain performance as well as the contingency effect of supply chain disruptions, in terms of disruption orientation and disruption impact.

Path analysis was employed to test the hypotheses using the data collected from Chinese manufacturers.

The results confirm an inverted U-shape effect of operational interdependency. As level of buyer-supplier operational dependency increase, the supply chain performance is enhanced. However, the benefits of operational interdependency diminish beyond a certain point. Additionally, the findings of this study show the disruption orientations positively moderate the relationship between interdependency and performance, whereas the effect of disruption impact is not significant.

The findings of this study provide an explanation to the theoretical gap about the equivocal results of the effect of dependency, which provide new insights into the literature regarding buyer-supplier relationships. Furthermore, this paper identifies the moderating role of supply chain disruption in the relationship between operational interdependency and supply chain performance, which provide further explanation about the mixed results of the effect of dependency. The results confirmed that supply chain disruption orientation positively moderate the relationship between operational interdependency and supply chain performance.

The demand for power has surged in recent times and continues to increase yearly. In comparison to developed countries, the power industry’s risks, especially in piblic–private partnership (PPP) projects, are more complex and essential in developing countries. Appreciating the inter relationship among these risk factors is crucial. However, there exist no studies developing quantitative models to explain how various PPP power risk factors influence each other, especially in developing countries like Ghana. This study aims to investigate and model the relationship, the probability of occurrence and severity of impact of PPP power risk factors in Ghana.

Data were collected through ranking type questionnaire in a two-round Delphi survey with 48 respondents using purposive and snowball sampling techniques. partial least squares structural equation modelling (PLS-SEM) was used for analysis of data.

A model was developed to investigate the influence the risk factors inherent in PPP power projects have on each other. Validity of the model was tested based on the data collected. PLS-SEM results indicated the various relationships and interdependencies the risk factors had on each other considering their probability and severity. Both significant and insignificant levels of relationships were found among the various risk factors.

The SEM that was developed to assess the relationships among the risk factors has great value for policy makers in the energy sector, industry practitioners, researchers and industry practitioners. Strategies can be mapped out to mitigate and effectively allocate the risks with the high interdependencies.

Regarding the quantitative impact of the interrelationship among risk factors in PPP power projects, the findings of this research are arguably the first to be presented for the construction sector and contribute to knowledge on PPP practice and further has implications toward achieving power sector risk mitigation.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.

It is critical for small and medium-scale enterprises (SMEs) to review and monitor sustainability performance indicators across three dimensions: economic, environmental and social to attain long-term competitiveness. SMEs lack a holistic perspective on sustainability; they are frequently hindered from contemplating environmentally favorable investments beyond what is legally needed. The purpose of this paper is to present a joint Decision-making trial and Evaluation Laboratory (DEMATEL) and NK methodology for developing a process model for introducing and implementing sustainable competitiveness practices for SMEs.

This study addresses the issue by adopting a sustainable competitiveness practices framework and applying a novel method that integrates DEMATEL and NK model for evaluating and developing the implementation path model for Indian manufacturing SMEs.

This paper also demonstrates that not only the relational practice itself but also the order in which the relational practices are implemented can be related to performance. According to the authors' preliminary findings, organizations in this study should first implement a social dimension, which includes sustainable leadership, knowledge sharing, etc., then an economic dimension like quality, sustainable innovations, etc., and finally environmental dimensions like green marketing, solid waste reduction, etc., with their management for competitiveness.

These findings offer some preliminary information as well as advice for managers and policymakers looking to integrate sustainable efforts.

This study asserts that not only the interdependent practice but also the sequence of implementation is important and can relate to the performance. The path result shows that the organization develops first sustainable design and product development (economic), sustainable leadership (social) and solid waste reduction (environmental) practices.

There is no such study that develops a process model for introducing and implementing sustainable competitiveness of SMEs which assesses and analyzes the interdependencies across relational behaviors, to the best of authors’ knowledge. The novelty of this work lies in integrating DEMATEL-NK model approach.

This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

Circular construction offers sustainable solutions and opportunities to disentangle a project’s life cycle, including demolition, deconstruction and repurposing of architectural, civil engineering and infrastructure projects from the extraction of natural resources and their wasteful usage. However, it introduces additional layers of novel risks and uncertainties in the delivery of projects. The purpose of this study is to review the relevant literature to discover, classify and theorize the critical risk factors for circular construction projects.

The paper conducted a systematic literature review to investigate the risks of circular construction projects. It deployed a multistage approach, including literature search and assessment, metadata extraction, citation frequency analysis, Pareto analysis and total interpretive structural modeling.

Sixty-eight critical risk factors were identified and categorized into nine broad taxonomies: material risks, organizational risks, supply chain risks, technological risks, financial risks, design risks, health and safety risks, regulatory risks and stakeholder risks. Using the Pareto analysis, a conceptual map of 47 key critical risk factors was generated for circular construction projects. A hierarchical model was further developed to hypothesize the multiple possible connections and interdependencies of the taxonomies, leading to chain reactions and push effects of the key risks impacting circular construction projects.

This study constitutes the first systematic review of the literature, consolidating and theorizing the chain reactions of the critical risk factors for circular construction projects. Thus, it provides a better understanding of risks in circular construction projects.

This study has two major objectives. First, comprehensively review the literature on transparency in supply chain management. Second, based on a critical analysis of literature, identify the attributes and sub-attributes of supply chain transparency and develop a numerical measure to quantify transparency in supply chains.

A systematic literature review (SLR) was conducted using the PRISMA approach. Utilizing SCOPUS database past eighteen-year papers search resulted in 249 papers to understand major developments in the domain of supply chain transparency. Subsequently, graph theoretic approach is applied to quantify transparency in supply chain and the proposed index is evaluated for case supply chains from pharma and dairy sectors.

It can be concluded from SLR that supply chain transparency research has evolved from merely tracking and tracing of the product towards sustainable development of the whole value chain. The research identifies four major attributes and their sub-attributes that influence transparency in supply chains, which are used to develop transparency index. The proposed index for two sectors helps to understand areas that need immediate attention to improve transparency in the case supply chains.

This paper attempts to understand the development of transparency research in supply chain using the PRISMA approach for SLR. In addition, development of mathematical model to quantify supply chain transparency is a novel attempt that would help benchmark best practices in the industry. Further, transparency index would help to understand specific areas that need attention to improve transparency in supply chains.

Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.