PurposeThe restaurant network is reforming rapidly due to the advancements encountered so far in the restaurant–third party logistics (3PL) collaborations. These collaborations resulting from a strategical partnership between the restaurant and the 3PLs play a significant role in getting a good handle on the web, logistics activities, online business and many more services. Despite the collaborations, 3PL in the restaurant supply chain is associated with many risks that may hamper the supply chain's profitability. In this study, several risks related to 3PL are investigated and analysed.Design/methodology/approachDeciding the relative importance of different risks is an intricate errand. The predominance of one risk over the others changes from individual to individual and ?rm to ?rm. Therefore, to catch the changeability in choice, the fuzzy analytical hierarchy process (AHP) is an extremely valuable tool used in this research. In addition to this, fuzzy AHP is incorporated with fuzzy TOPSIS for preference ranking of 3PL risks in the restaurant supply chain and obtain risk index value, which provides an excellent approach to rank the risks. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.FindingsResults indicate that “macro-level risks” (i.e. the risks associated with 3PL in the restaurant supply chain due to political agitation in the district, cataclysmic events, ailments like COVID-19, bird influenza, etc.) is the most relevant first-level risk with high-risk index as well as high relative weight. As per the analysis of second-level risks, the occurrence of cataclysmic events holds the most elevated risk index value.Practical implicationsThis research provides the restaurant industry and the 3PL with a generalized framework with set parameters that can be used to attain a successful 3PL in the restaurant supply chain of any developing nation.Originality/valueThis research proposes an evaluation framework for the risk assessment of third-party logistics in the restaurant supply chain. This paper explores risks for efficient implementation of 3PL in the restaurant supply chain. From a managerial perspective, the rank table is also provided with the goal that mitigation of the risks can be done quickly.
The outbreak of COVID-19 has prompted a substantial shrinkage in various businesses worldwide, the perishable food sector being one of the worst hits. Henceforth, this manuscript intends to analyse the impact of COVID-19 on perishable food supply chains (PFSCs) of developed and developing countries. For this, the study presents the analysis in two steps. In the first step, the study illuminates the particular factors that frame unique sorts of supply chain (SC) disturbances in PFSC. Secondly, the study proposes a unique interval-valued intuitionistic fuzzy set (IVIFS)-based graph theory and matrix approach (GTMA) to analyse the COVID-19 impact index value. In addition to this, the PERMAN algorithm is used to calculate the permanent function. The study has revealed that developing nations should focus more on their technological and infrastructural factors to improve the condition of PFSC during the pandemic. This study’s results can be deployed by decision-makers to forestall the operative and long-haul consequences of COVID-19, or any other disruptions to the PFSC, and make plans to overcome the impact. The significance of this manuscript is that the prominent factors degrading the performance of PFSC amidst the pandemic have been highlighted, with their respective impact on developed and developing nations compared. Moreover, a neoteric comprehensive integration of IVIFS-GTMA technique along with the PERMAN algorithm has been utilised in this manuscript. This particular study is inimitable as it supplements existing literature by providing analytical support to the relationship among various factors impacting the PFSC amidst the pandemic.
PurposeThe purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence of these risks on the critical success factors of the coffee supply chain.Design/methodology/approachThe risks have been identified through a comprehensive literature review and validation by industry experts. The paper utilises an interpretive structural modelling (ISM) methodology for developing a hierarchical relationship among the CSFs. Furthermore, fuzzy MICMAC analysis is carried out to categorise these CSFs based on their driving power and dependence value. The fuzzy technique for order preferences by the similarity of an ideal solution (fuzzy-TOPSIS) approach has been applied to prioritise the risks associated with 3PL based on their ability to influence the CSFs of the coffee SC. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.FindingsThis study illustrates ten risks associated with 3PL and five CSFs in the coffee supply chain. The analysis revealed that coffee enterprises need to develop a balanced pricing strategy to ensure a sustainable competitive advantage, whereas the lack of direct customer communication is the most dominant 3PL risk affecting the CSFs.Practical implicationsThis research provides coffee enterprises with a generalised framework with set parameters that can be used to attain a successful coffee supply chain in any developing nation.Originality/valueThe study contributes to the literature by being the first kind of study, which has used fuzzy ISM-MICMAC to analyse the CSFs of the coffee supply chain and fuzzy-TOPSIS for analysing the impact of various risks associated with the 3PL in the coffee supply chain. Thus, this work can be considered a benchmark for future research and advancement in the coffee business field.
After the sudden advent of COVID-19, the amount of medical waste has escalated to a great extent. The incremented medical waste amidst the pandemic exposes the improper waste management system of various developing countries. India, being one of the prominent developing countries, produces the largest waste in the world. Nonetheless, the Indian waste management system is not able to manage the massive amount of waste generated. Henceforth, this research study approaches to reveal the prominent factors which are causing failure in the system of medical waste management in India. This manuscript mainly focuses on two aspects. Firstly, this paper illuminates the factors which are hindering medical waste management by third-party logistics (3PL). Secondly, this study discusses a unique interval-value intuitionistic fuzzy set (IVIFS) based on Decision Making Trial and Evaluation Laboratory (DEMATEL) to depict graphical causal interrelationships among the factors. In addition, the analytic network process (ANP) is utilized to estimate the influence ranking of each factor. The results of this research anticipate that the transportation and disposal-related constraining factors require more attention from 3PL managers. The current study is unique as it enriches the various hindering factors on 3PL BMW management by discussing the ranking and relationship among factors.
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