Search results

This study aims to identify the barriers to building supply chain resilience and assess the contextual relationship between them in the Indian micro, small and medium enterprise (MSME) sector for the post COVID-19 era.

Barriers to supply chain resilience were extracted from the extant literature and were evaluated using the grey sets and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach from strategic, tactical and operational business perspectives. The responses from experts on the identified barriers were collected through a structured questionnaire. The prominence-net effect results obtained after the DEMATEL application helped identify the most prominent barriers, their net cause and effect, and their correlation with each other.

A total of 16 barriers to resilience, identified from the literature, were considered for analysis. The findings of the study revealed that the lack of flexibility is the most critical causal barrier to building a resilient supply chain. Lack of planned resource management was also found to be an influential barrier. The study also identified the supply chain design, need for collaboration and technological capability as important factors for the MSME sector to focus on.

The study is limited to assessing barriers to the supply chain resilience of MSMEs in India. More extensive research may be needed to reveal the global trend.

The study is significantly important for the MSMEs looking to establish resilient supply chains. Managers can use the findings to identify the weak links in the supply chain for strategic and tactical planning and can take corrective actions.

The study pinpoints the key linkages between barriers that impede MSMEs to make their supply chains resilient and robust to mitigate the impact of future disruptions and adversities. The work may be used by practitioners to further their attention on the significant challenges.

This study aims to identify blockchain-related innovation trends that can improve trust networks in a smart city's transport and supply chain networks. Trust networks are crucial in building and maintaining the trust of citizens in smart cities. By promoting transparency and accountability, facilitating collaboration and innovation, enhancing citizen participation and protecting privacy and security, trust networks can help to ensure that smart cities are developed and implemented in a responsible and sustainable way. A systematic literature review identifies 60 conceptual and empirical studies. This research focuses on the current problems and developing procurement and supply chain strategy and the potential benefits of using blockchain in these areas. It suggests ways for the smart city's transport and supply chain networks to utilise blockchain to improve operations and supply chain strategy and identifies innovation trends related to blockchain. The study also includes a systematic literature review and Blockchain Transformation and Influence model as the basis to enhance trust networks in the supply chain.

This study aims to investigate the influence of supply chain resilience (SCR) and supply chain capabilities (SCC) on supply chain performance (SCP) through the direct and moderating influence of the degree of SCR (DSCR), as demonstrated in UAE energy industry supply chain management (SCM) processes.

Using the partial least squares structural equation modeling (PLS-SEM), a questionnaire-survey collected 168 valid responses from UAE-based companies that operate within the energy industry. This study investigates the moderated mediation research model of the SCR, SCC and SCP with DSCR being considered as the variable having the moderation role.

SCR and SCC were found to have a significant positive affect on SCP playing a mediating role in improving performance during or after a SC disruption. However, the objective was to confirm the exitance of the moderator role in DSCR to substantiate its moderated mediating effect in the research model. There was a negative moderating effect of SCR on SCP through SCC.

This is among the pioneer study that suggests and empirically tests the moderated mediating impacts of the SCR degree on the relationships between SCR, capability within a supply chain and its performance. An additional element of originality of this study is its relevance to the UAE energy industry and recent SC disruptions.

In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.

This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.

The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.

This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.

This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.

This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.

This study investigates the quantitative aspect of the various strains of operational excellence (OE) and competitive-potential (CP) in the SME sector. It has five steps, i.e., identifying the key performance constructs of OE and their hypothesized relationship pattern from literature, validating these constructs through factor analysis, formalizing their empirical relationships by structural-equation-modeling (SEM), path analysis of performance constructs with the empirical results, and lastly proposing a framework for OE deployment in SMEs.

Data for the deployment scores of operational excellence procedures (OEPs) were collected through a structured questionnaire survey. Nine hundred participants from a stratified random sample were approached for the survey, and 473 responses were received. Sample stratification was based on Gender, Education, Experience, Position, Department and Industry. Respondents had 5–30 years of experience managing manufacturing operations, holding the manager position and above.

The path analysis of the structural model provides unique insights into OE's practical aspects in SMEs (small and medium enterprises). For example, Contractual-conformance and Process-efficiency play pivotal roles as both have a significant positive impact on CP. Supplier efficacy, Consistency and Product-excellence do not improve CP unless mediated by Contractual-conformance or Process-efficiency.

The study provides important implications for academia, policymakers and managers. The study identifies and validates the operational excellence key performance practices and proposes a framework for manufacturing organizations. SME managers can follow the framework to develop effective operational excellence strategies to help them achieve their organizational goals. Additionally, the study emphasizes the need for continuous culture in SMEs, which will help to support operational excellence deployment. Overall, the implications presented in the study will help SMEs to enhance their competitiveness and operational performance.

The study explores the empirical investigation of the operational excellence deployment in SMEs. The study uses a mixed method approach for research design, including qualitative and quantitative approaches, and uses SEM to test the proposed framework. Validation of OE's six key performance constructs and establishing their empirical relation is an attempt to advance the Operations excellence theory. Unlike large enterprises, SMEs demonstrate an incohesive response to the practices pertaining to Supplier efficacy, Consistency and Product-excellence. This unique response pattern requires special treatment, which is incorporated into the proposed framework.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

Due to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.

A combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.

The authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.

To the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.

The practice of consanguinity has been culturally preferred in most Arab countries, including Morocco. This behavior leads to an increase in genetic abnormalities, such as hypertension and diabetes. This paper examines the prevalence and determinants of first-cousin marriages and their impact on diabetes among offspring.

Data on 882 couples were collected through face-to-face interview via a pre-established questionnaire based on the variables selected within the objectives of this study. The authors used the multiple logistic regression modeling procedure in this study.

The results of the study indicate that the prevalence of first-cousin marriages were 15% among students’ parents. From the multiple logistic regression modeling, the authors found a significant effect of paternal and maternal grandparents’ first-cousins marriage on that of parents (aOR = 3.27 and aOR = 3.36, respectively). However, an 11-fold higher risk of first relative marriages among parents once the paternal and maternal grandparents were first-cousins and the father was illiterate (aOR = 11.01). Moreover, the authors reported a diabetes risk of more than 14 times when the effects of first-cousin maternal grandparents and parents and the hypertension among mother or her sibling were combined (aOR = 14.48) or when the effects of first-cousins maternal grandparents, first-cousin parents and mother’s age at marriage between 21 and 29 years were combined (aOR = 14.56).

First-cousin marriage depends on the father’s illiteracy and the consanguinity of grandparents’ factors. The cumulative effect of first-cousin marriage among grandparents, parents and a family history of hypertension among mother or her sibling increase the risk of diabetes among these mothers.