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Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

This paper constructs the uncertainty analysis model of prefabricated building supply chain risk. The model is designed to study the formation path of prefabricated building supply chain risk and is expected to be used by industry stakeholders for supply chain risk management.

Based on the uncertainty circle model, construct a configuration analysis framework for supply chain risks in prefabricated buildings. The fuzzy set qualitative comparative analysis (fsQCA) is used to study the configuration influence of five uncertain factors, including environment, plan-control, demand-supply, manufacturing and assembly-transportation, on the risk of the prefabricated building supply chain.

There are three paths to promote the high-risk generation of the prefabricated building supply chain: assembly-transportation-oriented, plan-control-oriented and manufacturing-oriented. There is a specific equivalent substitution relationship among the five causal conditions. Under specific conditions, different combinations of conditions have the same effect on promoting supply chain high-risk generation through equivalent substitution.

The multiple concurrent causal relationships of risk conditions in the assembly construction supply chain are studied under the grouping perspective, which helps to expand the research perspective of assembly construction supply chain risk and provides theoretical guidance for supply chain risk management of construction enterprises.

Acknowledging, on the one hand, the increasing fragility of supply chains and the number of risks involved in supply chain operations and, on the other hand, the role of small- and medium-sized enterprises (SMEs) in supply chains and the high exposure of these firms to risks of different types, this study aims to examine the relationship between supply chain risk management (SCRM) and innovation performance in SMEs. Furthermore, the impact of technological turbulence on this relationship was studied to take into account recent technological changes.

Structural equation modelling was carried out on a sample of Turkish SMEs to test the hypotheses developed.

The findings presented allow the authors to better understand the link between SCRM and innovation performance in SMEs. More precisely, empirical evidence is provided about the impact of SCRM components such as maturity and ability on innovation performance. Furthermore, the findings show the impact of technological turbulence on both SCRM and innovation performance.

By focusing on SCRM in SMEs, this paper contributes to the body of knowledge with regard to SCRM in general and with regard to SMEs in particular; research on the latter has only started recently. Moreover, by having studied SMEs from a developing country (other than China), this paper helps to develop a broader and more diverse perspective of SCRM.

Drawing on the dynamic capability view (DCV), the current study aims to examine the mediating effects of entrepreneurial orientation (EO), in terms of innovativeness, proactiveness and risk taking, on the relationships between big data analytics (BDA) capability and sustainable supply chain performance (SSCP).

Data were collected by questionnaire survey from 300 manufacturing organizations. Structural equation modeling (SEM) was used to test the hypotheses.

The findings showed that innovativeness and proactiveness fully mediated the link between BDA capability and SSCP. However, risk taking only partially mediated the relationship between BDA capability and SSCP. There was also a negative relationship between BDA and risk taking.

Given that the current study focused on the manufacturing sector, future research is needed to compare different sectors and cultural contexts. Further exploration is also needed into the dimension of risk taking in terms of the role of risk taking in linking BDA capability with SSCP in different cultural settings.

Technology may not increase the risk taking capability. Organizations may be creative and proactive but may remain risk averse despite having access to big data. Organizations need a more balanced approach to dynamically integrate and reconfigure the organizations' BDA and EO capabilities in order to enhance SSCP.

The role of EO in mediating the relationship between BDA capability and SSCP has not been studied before. The current study aimed to address the gap and contribute to the existing debate on better understanding the factors that are needed by organizations to effectively employ technology to enhance SSCP. Untapped areas for future research are also identified.

This study aims to evaluate the adoption of four types of supplier sustainability risk management (SSRM) strategies, namely, risk avoidance (RA), risk acceptance (RAC), collaboration-based risk mitigation (CBM) and monitoring-based risk mitigation (MBM) in Sri Lankan apparel and retail industries, and to investigate their effect on supply chain performance (SCP).

This study uses the dynamic capability view (DCV) to develop its hypotheses. Data collected from 89 firms were analysed using partial least square (PLS) structural equation modelling and PLS-based multiple group analysis.

Sri Lankan apparel and retail firms adopt RA and MBM strategies relatively more than CBM and RAC strategies, whereas there is no significant difference between the two industries in terms of the use of SSRM strategies. The path analysis revealed significant effects of RA and RAC strategies on SCP of both industries. The effect of CBM strategy on SCP is moderated by industry, while MBM has no significant impact.

While managing supplier sustainability risks effectively, RA and RAC strategies provide more opportunities for managers to improve SCP. In achieving SCP, CBM strategies are proven to be more effective for retail industry compared with the apparel sector. Although MBM strategies offer sustainability advantages to firms, their contribution to improving the performance of apparel and retail supply chains is not significant. This research is limited to only two industries (apparel and retail) in Sri Lanka, where the evidence for the effects of SSRM strategies is not available for other contexts.

Either the effects of the four types of SSRM strategies on SCP or the moderating effect of industry on these effects have not been empirically confirmed in the literature. Evaluating the extent to which different strategies are implemented in Sri Lankan apparel and retail industries is another significant contribution of this research. Furthermore, this study contributes by using DCV to a sustainability-based supply chain risk management research.

The purpose of the paper is to present research trends in the food supply chain in the context of changes in food systems due to globalization, urbanization, environmental concerns, technological changes and changes in food consumption patterns in the world.

The present investigation was performed by bibliometric analysis using the VOSviewer software, visualization software developed by Nees and Waltman (2020). In this work we performed co-citation, bibliographic coupling and keyword evolution analyses.

The results show that research in the food supply chain is rapidly changing and growing. By applying co-citation analysis, The authors found that the intellectual structure of the food supply chain has evolved around six clusters, namely, (a) collaboration and integration in the supply chain (b) sustainable supply chain management, (c) food supply chain management (FSCM), (d) models for decision-making in the food supply chain, (e) risk management in the supply chain and (g) quality and food logistics in the supply chain. However, based on bibliographic coupling analysis, The authors find that new or emerging research niches are moving toward food supply market access, innovation and technology, food waste management and halal FSCM. Nevertheless, the authors found that the existing research in each of the thematic clusters is not exhaustive.

The limitation of the research is that the analysis mainly relates only to the bibliometric approach and only one database, namely, Scopus. Broader inclusion of databases and deeper application of content analysis could expand the results of this research.

There are limited studies that have examined research trends in food supply chains in both developed and developing countries using bibliometric analysis. The present investigation is novel in identifying the thematic research clusters in the food supply chain, emerging issues and likely future research directions. This is important given the dynamics, consumer demand for quality food, technological changes and environmental sustainability issues in food systems.

This study aims to uncover apple preference and consumption in Indonesia, to disclose the risk of non-halal contamination of apples and the importance of maintaining the halal integrity of apples along the supply chain and to uncover the impacts of food miles of apples along supply chain segmentation.

This study adopted mixed research methods under a fully mixed sequential dominant status design (QUAN → qual). Data were collected through a survey in some Indonesian provinces (N = 396 respondents). Samples were collected randomly from individual consumers. The qualitative data were collected through interviews with 15 apple traders in Indonesia. Data were analysed using crosstab, chi-square and descriptive analysis.

First, Muslim consumers believe in the risk of chemical treatment of apples because it can affect the halal status of apples. Second, Indonesian consumers consider the importance of halal certification of chemical-treated apples and the additives for apple treatments. Third, the insignificance of domestic apple preference contributes to longer food miles at the first- and middle-mile stages (preference for imported apples). Fourth, apple consumption and shopping distance contribute to the longer food miles problem at the last-mile stage. Fifth, longer food miles have negative impacts, such as emissions and pollution, food loss and waste, food insecurity, financial loss, slow development of the local economy and food unsafety.

This research has implications for the governments, farmers, consumers (society) and business sectors.

This study proposes a framework of food miles under a halal supply chain (halal food miles) to reduce the risk of food miles and improve halal integrity. The findings from this research have theoretical implications for the development of the food mile theory, halal food supply chain and green supply chain.

We conducted a systematic review to explore the potential for the application of blockchain technologies for supply chain resilience in a small-scale agri-food business context.

As part of the research methodology, scientific databases such as Web of Science, Google Scholar and Scopus were used to find relevant articles for this review.

The systematic review of articles (n = 57) found that the use of blockchain technology in the small-scale agri-food business sector can reduce the risk of food fraud by assuring the provenance of food products.

Only a few papers were directly from a small-scale agribusiness context. Key challenges that limit the implementation of blockchain and other distributed ledger technologies include concerns over the disclosure of proprietary information and trade secrets, incomplete or inaccurate information, economic and technical difficulties, low levels of trust in the technology, risk of human error and poor governance of process-related issues.

The application of blockchain technology ensures that the risks and costs associated with non-compliance, product recalls and product loss are reduced. Improved communication and information sharing can increase resilience and better support provenance claims and traceability. Better customer relationships can be built, increasing supply chain efficiency and resilience.

Due to the current volatile environment and fierce competition, manufacturing firms (MFs) must improve their performance to survive. In this regard, checking and monitoring the suppliers' risk should significantly improve the performance of MFs. In addition, a relation based on not being an opportunist, confidence and reliance are influential factors in reducing the supplier defaults on his/her supply obligations and improving supply chain performance (SCP). Besides, the moderator function of supplier involvement (SI) in the relationship between quality of the relationship (QoR) and supply risk mitigation (SRM) is undeniable.

Based on the survey of 148 samples from small to large-sized MFs in Jordan, Turkey and Egypt, empirical evidence has been conducted to support a majority of the authors’ hypotheses. This paper provides a theoretical review of buyer–supplier relationships and supply risk. Hypotheses were tested by using structural equation modeling (SEM)/Smart PLS-4.

According to the results, confidence and reliance have statistically significant and positive impacts on SRM, resulting in better SCP. Moreover, the findings show that SI positively affects and moderates the relationship between confidence (C) and SRM, while it has no statistically significant influence on the relationship between reliance (R) and SRM.

This study provides necessary material for managers and decision-makers in MFs to confirm the importance and understanding of the QoR in building relationships and business dealings with partners in the SC, in addition to limiting and mitigating the risks of an interruption in supply in particular. Therefore, building a high-quality relationship as a practice based on trust and reliability with suppliers positively affects the performance of the SCs of MFs.

This research paper offers empirical evidence for using QoR within SRM resources of MFs' context for enhancing their supply chain performance. This study is one of few studies that examine the QoR and SRM that contribute to enhancing SCP in MFs in developing countries, which also can serve as a reference for many SC managers and practitioners.