Risk analysis and mitigation for perishable food supply chain: a case of dairy industry

Risk Prevention and Quality Control in Camel Milk Collection: Insights from Field Research

The camel milk market's rapid expansion necessitates strategies that ensure raw milk quality and safety, particularly in small-scale production. This study examines smallholder farmers in Haixi, Qinghai Province, China, where traditional practices intersect with modern standards. Analyzing 80 raw camel milk samples, the study assessed risks like adulteration, microbial contamination, and nutritional variability. DNA testing and microbial assays revealed that 66.67% of hand-milked samples were adulterated with cow milk, a significantly higher rate than mechanically processed samples (p < 0.05). Manual milking also showed higher microbial counts (up to 2.05 × 104 CFU/mL) and somatic cell levels, indicating hygiene issues. Nutritional analysis found that grazing systems yielded milk with more vitamin A, B2, and potassium, while semi-intensive systems had higher ash content. A quality evaluation framework was developed, combining pastoralist knowledge with rapid diagnostic tools, focusing on mechanization, cold-chain efficiency, and community training. This framework provides strategies to reduce adulteration, ensure nutritional consistency, and align small-scale production with international standards. The study proposes culturally adaptive quality control methods to protect consumer health, support rural livelihoods, and standardize the camel milk market.

Process ambidexterity driven by environmental uncertainty: balancing flexibility and routine

Purpose

This study aims to extend ambidexterity theory from the perspective of organisational learning and examine how process ambidexterity, which comprises operational flexibility and operational routine, responds to environmental uncertainty and ultimately reduces organisational risks.

Design/methodology/approach

This study tests the hypotheses by analysing 464 annual reports of 115 listed companies in the Chinese agricultural and food industry using content and secondary data analyses. Four case studies are also provided.

Findings

The results show that (1) environmental uncertainty has a positive effect on either operational flexibility or operational routine; (2) both operational flexibility and operational routine have negative effects on organisational risks, supporting the view that process ambidexterity mediates the relationship between environmental uncertainty and organisational risks; and (3) organisational slack plays the role of “double-edged sword” by negatively moderating the effect of environmental uncertainty on operational flexibility and positively moderating the effect of environmental uncertainty on operational routine.

Originality/value

In an uncertain environment, companies are exposed to greater risk. This study contributes to risk management in three ways: first, it extends ambidexterity theory to process management and proposes how process ambidexterity balances operational flexibility and routines. Second, it distinguishes between the different conditions under which flexibility or routines are superior. Third, it explains the mechanisms related to how organisations can resolve environmental uncertainty into risk through process ambidexterity.

Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities. We therefore conduct a bibliometric and network analysis of SCRA publications to identify research areas and underlying themes, leading to the identification of three major research clusters for which we provide interpretation and guidance for future work. In doing so we focus in particular on the variety of parameters, analytical approaches, and characteristics of multi-criteria decision-making techniques for assessing supply chain risks. This offers an invaluable synthesis of the SCRA literature, providing recommendations for future research opportunities. As such, this paper is a formidable starting point for operations researchers delving into this domain, which is expected to increase significantly also due to the current pandemic.

Modeling traceability in food supply chain

Purpose

Currently, digital technology has been proposed as a new archetype for developing an effective traceability system in the perishable food supply chain (FSC). Implementation of such a system needs significant investment and the burden lies with the members of the supply chain. The purpose of this paper is to examine the impact on the profit of the supply chain members due to the implementation of an effective traceability system with such a large investment. The study also tries to explore the impact of the implementation of such a system by coordination among the members through a cost-sharing mechanism.

Design/methodology/approach

A two-level supply chain that comprises a supplier and retailer is analyzed using a game-theoretic approach. The mathematical models are developed considering the scenario for an individual, centralized and both members invest using a cost-sharing mechanism. For each of the models, the impact of product selling price, information sensing price and quality improvement level on profit is analyzed through numerical analysis.

Findings

The study reveals that consumer involvement can be a strong motivation for the supply chain members to initiate investment in the traceability system. Further, from an investment perspective cost-sharing model is beneficial compared to the individual investment-bearing model. This mechanism can coordinate as well as benefit the FSC members. However, the model is less beneficial to the centralized model from profit and quality improvement levels.

Practical implications

Food wastage can be less from supplier and retailer perspectives. Moreover, consumers can purchase food items only after verifying their shipping conditions. Consequently the food safety scandals can be reduced remarkably.

Originality/value

Digital technology adoption in the perishable FSC is still considered emerging. The present study helps organizations to implement a traceability system in the perishable FSC through consumer involvement and a cost-sharing mechanism.

Blockchain-Enabled Supply Chain platform for Indian Dairy Industry: Safety and Traceability

Conventional food supply chains are centralized in nature and possess challenges pertaining to a single point of failure, product irregularities, quality compromises, and loss of data. Numerous cases of food fraud, contamination, and adulteration are daily reported from multiple parts of India, suggesting the absolute need for an upgraded decentralized supply chain model. A country such as India, where its biggest strength is its demographic dividend, cannot afford to malnutrition a large population of its children by allowing them to consume contaminated and adulterated dairy products. In view of the gravity of the situation, we propose a blockchain-enabled supply chain platform for the dairy industry. With respect to the supply chain platform, the dairy products of choice include milk, cheese, and butter. Blockchain is one of the fastest growing technologies having widespread acceptance across multiple industry verticals. Blockchain possesses the power to transform traditional supply chains into decentralized, robust, transparent, tamper proof, and sustainable supply chains. The proposed supply chain platform goes beyond the aspect of food traceability and focuses on maintaining the nutritional values of dairy products, identification of adulteration and contamination in dairy products, the increasing economic viability of running a dairy farm, preventing counterfeit dairy products, and enhancing the revenue of the dairy company. The paper collates the mentioned functionalities into four distinct impact dimensions: social, economic, operations, and sustainability. The proposed blockchain-enabled dairy supply chain platform combines the use of smart contracts, quick response code (QR code) technology, and IoT and has the potential to redefine the dairy supply chains on socio-economic, operational, and sustainability parameters.

Assessing Risks in Dairy Supply Chain Systems: A System Dynamics Approach

Due to the dynamic nature of the food supply chain system, food supply management could suffer because of, and be interrupted by, unforeseen events. Considering the perishable nature of fresh food products and their short life cycle, fresh food companies feel immense pressure to adopt an efficient and proactive risk management system. The risk management aspects within the food supply chains have been addressed in several studies. However, only a few studies focus on the complex interactions between the various types of risks impacting food supply chain functionality and dynamic feedback effects, which can generate a reliable risk management system. This paper strives to contribute to this evident research gap by adopting a system dynamics modelling approach to generate a systemic risk management model. The system dynamics model serves as the basis for the simulation of risk index values and can be explored in future work to further analyse the dynamic risk’s effect on the food supply chain system’s behaviour. According to a literature review of published research from 2017 to 2021, nine different risks across the food supply chain were identified as a subsection of the major risk categories: macro-level and operational risks. Following this stage, two of the risk groups identified first were integrated with a developed system dynamics model to conduct this research and to evaluate the interaction between the risks and the functionality of the three main dairy supply chain processes: production, logistics, and retailing. The key findings drawn from this paper can be beneficial for enhancing managerial discernment regarding the critical role of system dynamics models for analysing various types of risks across the food supply chain process and improving its efficiency.

Interval-valued intuitionistic fuzzy digraph-matrix approach with PERMAN algorithm for measuring COVID-19 impact on perishable food supply chain

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.

A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment

In nowadays world, firms are encountered with many challenges that can jeopardize business continuity. Recently, the coronavirus has brought some problems for supply chain networks. Remarkably, perishable product supply chain networks, such as pharmaceutical, dairy, blood, and food supply chains deal with more sophisticated situations. Generally, during pandemic outbreaks, the activities of these industries can play an influential role in society. On the one hand, products of these industries are considered to be daily necessities for living. However, on the other hand, there are many new restrictions to control the coronavirus prevalence, such as closing down all official gatherings and lessening the work hours, which subsequently affect the economic growth and gross domestic product. Therefore, risk assessment can be a useful tool to forestall side-effects of the coronavirus outbreaks on supply chain networks. To that aim, the decision-making trial and evaluation laboratory approach is used to evaluate the risks to perishable product supply chain networks during the coronavirus outbreak era. Feedback from academics was received to identify the most important risks. Then, experts in pharmaceutical, food, and dairy industries were inquired to specify the interrelations among risks. Then, Pythagorean fuzzy sets are employed in order to take the uncertainty of the experts' judgments into account. Finally, analyses demonstrated that the perishability of products, unhealthy working conditions, supply-side risks, and work-hours are highly influential risks that can easily affect other risk factors. Plus, it turned out that competitive risks are the most susceptive risk in the effect category. In other words, competition among perishable product supply chain networks has become even more fierce during the coronavirus outbreak era. The practical outcomes of this study provide a wide range of insights for managers and decision-makers in order to prevent risks to perishable product supply chain networks during the coronavirus outbreak era.

Enablers for resilience and pandemic preparedness in food supply chain

The recent COVID-19 pandemic has caused enormous disruptions to supply chain (SCs). Border restrictions forced countless businesses to close either permanently or temporarily. However, the food industry is an essential sector that needs to be operational during a pandemic. Although the food industry has proactively worked towards fulfilling human needs, the food supply chain (FSC) faced numerous challenges, forcing SC managers to rethink their business strategy to cater to consumer demands effectively. In a pandemic situation, manufacturing operations need to repurpose and adapt to produce different high-demand products. Resilience initiatives help fight disruption phases in an uncertain environment by building capacity to resist and recover to a better position. This study identifies 14 key enablers to develop a resilient FSC and reveals the most significant enablers in India. We used a hybrid Delphi-interpretive structural modeling (ISM) and Fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) methodology to achieve these goals. The Delphi technique identified essential enablers, while the ISM analyzed the interrelationship among enablers and level of importance in a hierarchical structural model. Finally, the Fuzzy-DEMATEL categorized the enablers into the cause-effect group. This study helps SC decision-makers recognize the enablers and the contextual and causal relationships to improve resilience initiatives. It also helps them repurpose their manufacturing operations and shift to other highly required and high-demand production.

In-transit interventions using real-time data in Australian berry supply chains

Purpose

The objective of this paper is to contribute to Australian berry supply chains with a relevant identification regarding the possible data driven interventions that stakeholders can take while the berries are in transit.

Design/methodology/approach

An exploratory series of semi-structured interviews was conducted through six Australian experts in the industry with more than 20 years of experience in Australian berry supply chains and the Australian perishable food industry, to identify key possible in-transit interventions that could be implemented in the Australian berry industry.

Findings

The analysis of the interviews revealed a total of 18 possible in-transit interventions. An important finding is that in-transit interventions are made possible by the use of real-time data gathered through IoT devices such as Active Radio Frequency Identification, Time and Temperature Indicators interacting with Wireless Sensor Networks. Another key finding is that Australian berry growers and retailers do possess the technologies and the resources necessary to make in-transit interventions possible, however they have yet applied these technologies to operational decision-making and interventions based on the product, rather focussing on supply chain transactions and events.

Research limitations/implications

Since the research focusses on an Australian context, its findings may or may not be applicable to other countries. The research is exploratory in nature, and its findings should be verified by future research, in particular to test whether the in-transit interventions proposed here can be implemented in a cost-efficient way.

Originality/value

To the authors' knowledge, this publication is the first known academic article to provide a clear understanding of the Australian berry industry from a supply chain and logistics perspective, and the first to explore possible data driven in-transit interventions in perishable food supply chains.

Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Purpose

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

Design/methodology/approach

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

Findings

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

Research limitations/implications

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

Practical implications

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Originality/value

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

Investigating the effects of the outbreak of COVID-19 on perishable food supply chains: an empirical study using PLS-SEM

Purpose

At the end of 2019, the first case of the Corona Virus Disease (COVID-19) was reported in Wuhan city of China. The disease was declared a pandemic without imagining the magnitude of damage currently caused in all branches of the economy. One of the most affected sectors was food and mostly perishable food (PF), which are more susceptible to environmental conditions. Thus, the research examines the effect of the COVID-19 outbreak on Ecuador's perishable food supply chains (PFSCs) during the pandemic. It contributes to new results on the special issue (SI) PFSC response to event risk and uncertainty, such as those that generated the pandemic.

Design/methodology/approach

The data used are from primary information sources, which were collected through a questionnaire. The questionnaire was applied to 298 companies belonging to the sector, and later the information was processed through partial least squares structural equation model. The convergent validity, discriminate and robustness tests provide arguments for the suitability of the model. Therefore, the findings are reliable and valid for the adequate measures to improve the PFSC due to a COVID-19 outbreak.

Findings

The results show that the perception of personal risk (PPR) produced by COVID-19 has caused the companies of the PFSC to adopt preventive policies (PO) to avoid contagion and guarantee the operation of the companies. In addition, the PPR has been responsible for the alterations in the demand and price (DP) of PF. Next, PO and DP have a significant effect on PFSC, which shows the evidence favouring the malfunction of PFSC operations due to anti-contagion PO, the mismatch of DP. On the contrary, circular economy practices contribute to the excellent performance of the PFSC. Finally, the research suggests some policy implications to consider in improving the PFSC.

Originality/value

This study is the first to be carried out in Ecuador's country on the PFSC; its contribution is unprecedented and makes it a road-map to be considered to guarantee the correct functioning of the PFSCs, and it will provide policymakers with valid elements to design efficient PFSCs that better respond to unforeseen events and uncertainties. Future research will focus on analysing the management of PF consumption in Ecuador during the pandemic.

Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry

Purpose

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study aims to develop SCR networks and determine the major risk drivers that impact the performance of the sago starch agro-industry (SSA).

Design/methodology/approach

The risk and performance variables were collected from the relevant literature and expert consultations. The Bayesian network (BN) approach was used to model the uncertain and interdependent SCRs. A hybrid method was used to develop the BN structure through the expert’s knowledge acquisitions and the learning algorithm application. Sensitivity analyses were performed to examine the significant risk driver and their related paths.

Findings

The analyses of model indicated several significant risk drivers that could affect the performance of the SSA. These SCR including both operational and disruption risks across sourcing, processing and delivery stage.

Research limitations/implications

The implementation of the methodology was only applied to the Indonesian small-medium size sago starch agro-industry. The generalization of findings is limited to industry characteristics. The modelled system is restricted to inbound, processing and outbound logistics with the risk perspective from the industry point of view.

Practical implications

The results of this study assist the related actors of the sago starch agro-industry in recognizing the major risk drivers and their related paths in impacting the performance measures.

Originality/value

This study proposes the use of a hybrid method in developing SCR networks. This study found the significant risk drivers that impact the performance of the sago starch agro-industry.

A bi-level multi objective programming approach to solve grey problems: an application to closed loop supply chain network

Purpose

This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and transportation plan for a closed loop supply chain network under an uncertain environment and different scenarios is also developed.

Design/methodology/approach

In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using GLP. Membership functions for the decision variables under the control of the leader and for the goals are created. These membership functions are then used to generate the final solutions.

Findings

This paper provides insight for fomenting the decision-making process while providing a more flexible approach in uncertain logistics problems. The deviations of the final solution from the individual best solutions of the two levels are very little. These deviations can further be reduced by adjusting the tolerances associated with the decision variables under the control of the leader.

Practical implications

The proposed approach uses the concept of membership functions of linear form, and thus, requires less computational efforts while providing effective results. Most of the organizations exhibit decentralized decision-making under the presence of uncertainties. Therefore, the present study is helpful in dealing with such scenarios.

Originality/value

This is the first time, formulation of a decentralized bi-level multi-objective model under a grey environment is carried out as per the best knowledge of the authors. A solution approach is developed for bi-level MOP under grey uncertainty.

Collaborative risk management in decentralised multi-tier global food supply chains: an exploratory study

Purpose

The aim of this paper is to explore the value of collaborative risk management in a decentralised multi-tier global fresh produce supply chain.

Design/methodology/approach

This study utilised a mixed methods approach. A qualitative field study was conducted to examine the need for collaborative risk management. The simulation experiments with industry datasets were conducted to assess whether risk-sharing contracts work in mitigating joint risks in parts of and across the supply chain.

Findings

The qualitative field study revealed risk propagation and the inefficiency of company-specific risk management strategies in value delivery. The simulation results indicated that risk-sharing contracts can incentivise various actors to absorb interrelated risks for value creation.

Research limitations/implications

The research is limited to risks relevant to supply chain processes in the Australia–China table grrape supply chain and does not consider product-related risks and the risk-taking behaviours of supply chain actors.

Practical implications

Collaborative risk management can be deployed to mitigate systematic risks that disrupt global fresh produce supply chains. The results offer evidence-based knowledge to supply chain professionals in understanding the value of collaborative risk assessment and management and provide insights on how to conduct collaborative risk management for effective risk management.

Originality/value

The results contribute to the supply chain risk management literature by new collaborative forms for effective risk management and strategic competition of “supply chain to supply chain” in multi-tier food supply chains.

Effect of information sharing in supply chains: understanding the roles of supply chain visibility, agility, collaboration on supply chain performance

Purpose

Exploring ways to acquire, sustain and improve competitive positions in supply chains through information sharing, supply chain visibility, collaboration and agility have been essential for scholars and practitioners. Basing on the relational view, resource based view and the extended resource based view, this study assesses the critical role of information sharing in supply chains through emphasizing its effect on supply chain visibility, collaboration, agility and supply chain performance. Particularly, the study proposes that information sharing, supply chain visibility, collaboration and agility collectively have crucial direct and indirect influences on supply chain performance which lead to superior gains, competitiveness and flexibility.

Design/methodology/approach

The study adopted a survey research design, a quantitative approach and partial least square structural equation modeling (PLS-SEM) in making data analysis and interpretations due to its suitability for predictive research models.

Findings

The results indicate information sharing positively and significantly influenced supply chain visibility, collaboration, agility and performance. Supply chain visibility presented significant effects on collaboration, agility and performance, while supply chain collaboration and agility had significant impact on supply chain performance. The study findings connote that information sharing is key to enhancing competitive gains and superior supply chain performance.

Originality/value

The study is among the few to probe on how information sharing as a variable interacts with supply chain visibility, collaboration, agility and performance. Although, information sharing has received a lot of attention in supply chains, this study is among the first to capture the study variables in a single model and thus, exposes the vital need for information sharing in improving supply chain performance seeing that it ensured significant and robust impacts on the study variables.

Assessment of risks associated with third-party logistics in restaurant supply chain

Purpose

The 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/approach

Deciding 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.

Findings

Results 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 implications

This 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/value

This 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.

Production planning decision of a dairy under supply disruption and demand uncertainty

Purpose

The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement.

Design/methodology/approach

A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha.

Findings

From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases.

Research limitations/implications

The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well.

Practical implications

This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant.

Originality/value

This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).

Strategies to Manage the Impacts of the COVID-19 Pandemic in the Supply Chain: Implications for Improving Economic and Social Sustainability

This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy: Bangladesh. To achieve the aims, a methodological framework is proposed through a literature review, expert inputs, and a decision-aid tool, namely the grey-based digraph-matrix method. A total of 10 types of negative impacts and 22 strategic measures to tackle the impacts were identified based on the literature review and expert inputs. Then, the grey-based digraph-matrix was applied for modeling the strategic measures based on their influence to deal with the impacts. Findings reveal that the strategies “manufacturing flexibility”, “diversify the source of supply”, and “develop backup suppliers” have significant positive consequences for managing the impacts of the COVID-19 pandemic in the RMG supply chain. The findings help industrial managers recover from supply chain disruptions by identifying and classifying the impacts and strategies required to manage the major supply chain disturbances caused by the COVID-19 pandemic. As a theoretical contribution, this study is one of few initial attempts to evaluate the impacts of the COVID-19 outbreak and the strategies to deal with the impacts in the supply chain context.

Risk Assessment and Monitoring of Green Logistics for Fresh Produce Based on a Support Vector Machine

The sustainability and profitability of fresh produce supply chains are contingent upon several risk factors. This work, therefore, examines several risk indicators that affect the quality and safety of fresh produce in transit, including technological, biological, sustainability, environmental, and emergency risks. Then, we developed a risk assessment and monitoring model that employs a machine learning algorithm, a support vector machine, based on historical monitoring data. The proposed methodology was then applied to simulation and numerical analysis to assess the risks incurred in the strawberry cold chain. After training, the algorithm predicted the risks incurred during transportation with an average accuracy of 90.4%. Therefore, the developed methodology can effectively and accurately perform a risk assessment. Furthermore, the risk assessment model can be applied to other fresh produce due to comprehensive risk indicators. Decision-makers in fresh produce logistics companies can use the developed methodology to identify and mitigate risks incurred, thus improving food safety, reducing product loss, maximizing profits, and realizing sustainable development.

Exploring the best policy scenario plan for the dairy supply chain: a DEMATEL approach

Purpose

This research primarily aims to find and analyse the interaction among success factors for improving the performance of Indonesia’s dairy milk supply chain. Further, this research aims to formulate the right policies for improving the performance of the chain based on the success factor that belongs to cause groups.

Design/methodology/approach

The paper analyses 10 success factors for improving the performance of the Indonesian dairy supply chain with the decision-making trial and evaluation laboratory (DEMATEL) method and analyses the Delphi method to formulate the right policies for improving performance.

Findings

There are four important influencing factors that directly impact the overall system, i.e. the number of dairy cattle import, national milk demand, the total number of dairy farmers and the number of dairy cattle ownership or herd size. Several alternative policies have been designed by several experts according to the influencing factors, i.e. the government assists in the procurement of imported cattle, provides financial assistance to farmers in the form of low-interest financing, improves the partnership system between farmers and dairy cooperatives, provides a reward system for the farmers and increases the level of formality of contract between the farmers and cooperatives.

Research limitations/implications

Interrelationships of each success factor and the most important influencing success factors could not be generally determined because it depends on the point of view of the experts. Future research can apply the success factors proposed by this research to the different dairy milk supply chain. Then, this research used only nine experts for formulating alternative policies. Future research may repeat this method using multiple experts to justify the validity of the research. Moreover, this research only explored 21 success factors of the increase in the performance of the Indonesian dairy supply chain. Future research should consider not only the supply side and number of dairy cattle but also several success factors from the causal relationship diagram in the broader dairy milk supply chain.

Practical implications

This research provides essential insights for policymakers, as they have to understand and evaluate the success factors before formulating several alternative policies.

Social implications

The research has revealed that the right alternative policies can be designed, as the causal factor has been known.

Originality/value

This research contributes to applying a combination of causal relationship diagram of System Dynamic and DEMATEL method as a qualitative and quantitative method in one integrated way through performance dairy supply chain analysis. As a result, this research draws a policy for the dairy supply chain referring to the success factor as a cause for the low performance of the Indonesian dairy supply chain.

A mathematical model formulation to design a traditional Indian agri-fresh food supply chain: a case study problem

Purpose

The purpose of this paper is to study and develop supply chain structure of traditional Indian agri-fresh food supply chain (AFSC). This paper proposes a mathematical model to design a traditional Indian AFSC to minimize total distribution cost and post-harvest losses in the chain.

Design/methodology/approach

This paper formulates two mathematical models to structure and represent the flow of products in the existing chain. First, a three-echelon, multi-period, multi-product, mixed-integer linear programming (MILP) model is formulated to minimize the total distribution cost incurred in the chain. Further, the developed formulation is extended by considering the perishability of products in the second model.

Findings

A real case study problem of Mandsaur district (India) is solved in LINGO 17.0 package to check the validity of the formulated models. The perishable (second) model of AFSC reports better results in terms of costs and post-harvest losses minimization. The results revealed that 92% of the total distribution cost incurred in the transportation of products from farmers to the hubs.

Research limitations/implications

This paper includes implications for redesigning an existing supply chain network by incorporating an appropriate transportation strategy from farmers to hubs to minimize transportation inefficiency and enhance the profitability of farmers.

Practical implications

The formulated AFSC model would help managers and policymakers to identify optimal locations for hubs where required infrastructure would be developed.

Originality/value

According to the author's best knowledge, this paper is the first to design traditional Indian AFSC by considering the perishability of products.

Benchmarking the relationship between supply chain risk mitigation strategies and practices: an integrated approach

Purpose

The purpose of this paper is to explore the relationship between various risk management strategies and risk management practices in order to design and hence enact a suitable supply chain risk mitigation (RM) plan. Additionally, this study proposes a hierarchical framework to explain the mutual relationship between supply chain risk management (SCRM) practices and strategies by considering the underlying dimensions between them.

Design/methodology/approach

An amalgamation of systematic literature analysis (SLA) and correspondence analysis (CA) has been performed to develop the conceptual framework. A real-life case of Indian petroleum supply chain has been considered to validate and explain the proposed model.

Findings

The results reveal three underlying dimensions, which associate the relationship between RM strategies. They are, risk adaptability of SC managers with a variance of 34.71%, followed by resource capability of the firm and the degree of sophistication of RM practices, with variances of 27.72 and 20.35%, respectively. Risk avoidance strategy comprises of practices such as supplier evaluation, technology adaption, flexible process and information security. On the other extreme, the risk sharing strategy includes revenue sharing, insurance, collaboration, public–private partnership and so on as essential RM practices.

Research limitations/implications

The study not only focuses on the distinction between RM strategies and practices, which were used interchangeably in the prior literature, but also provides an association between the same by exploring the underlying dimensions. These underlying dimensions perform a crucial role while developing a risk management plan. This study explicitly focuses on the RM step of SCRM process. Pre and post risk mitigation phases of SCRM process, such as risk assessment and risk monitoring, are beyond the scope of the current research.

Originality/value

The paper develops a framework for mapping various RM strategies with their corresponding practices by considering the Indian petroleum supply chain as a viable case study. Various theoretical and business implications are derived in the context of the developing country.

The design and planning of an integrated supply chain for perishable products under uncertainties

Purpose

This paper aims to design an optimal supply chain network and to develop a suitable distribution planning under uncertainty for perishable product's supply chain. The ultimate goal is to help in making decisions under uncertain environments.

Design/methodology/approach

In this paper, stochastic programming is used under conditions of demand, supply and process uncertainties, and a non-linear mathematical model is developed for perishable product’s supply chain. Authors’ study considers disruptions in transportation routes and also within the facilities and investigates optimal facility location and shipment decisions while minimising the total supply chain cost. A scenario-based approach is used to model these disruptions. The retailer level uncertainty due to demand-supply mismatch is handled by incorporating the newsvendor model into the last echelon of supply chain network. In this paper, two policies are proposed for making decisions under uncertain environments. In the first one, the expected cost of the supply chain is minimised. To also consider the risk behaviour of the decision maker, authors propose the second policy through a conditional value-at-risk approach.

Findings

Authors discuss the model output through various examples that are provided via a case study from the milk industry. The supply chain design and planning of the disruption-free model are different from those of the resilient model.

Practical implications

Authors’ research benefits the perishable products industries which encounter the disruption problems in their transportation routes as well as in the facilities. Authors have demonstrated the research through a real-life case in a milk industry.

Originality/value

The major contribution of authors’ work is the design of the supply chain network under disruption risks by incorporating aspects of product perishability. This work provides insight into areas such as the simultaneous consideration of demand, supply and process uncertainties. The amalgamation of newsvendor model and the approximation of the non-linearity of retailer level cost function especially in the context of supply chain under uncertainty is the first of its kind. We provide a comprehensive statistical study of uncertainties that are present in the supply chain in a unique manner.

Making dairy supply chains robust against corruption risk: a systemic exploratory study

Purpose

To improve robustness of a dairy supply chain (SC) against corruption, the purpose of this paper is to propose a systemic model of a corruption impacted dairy SC, exposing relationships among SC operations, risks and the impact of corruption.

Design/methodology/approach

Cases from the dairy industry in New Zealand (NZ) are used for thematic analysis of interview data collected from participants at senior levels of NZ dairy firms. Based on these and other inputs from literature, a systemic model is built subsequently.

Findings

Mitigating certain risks can significantly alleviate the impact of corruption, an external factor, on supply chain performance (SCP). The causal loop diagram (CLD) developed here brings out the modifying effect of corruption on dairy risks and SCP.

Practical implications

The illustration of the CLD helps business managers better understand the interactions among risk variables and explains the systemic reasons for SC vulnerability.

Originality/value

This is the first paper to construct a holistic system to comprehensively reveal the interactions of supply chain risks (SCRs) and the impact of corruption. Also, by utilizing SCR interactions, this study indicates a pathway to mitigate the negative effects of corruption through improving dairy SC robustness.

Modeling Deming’s quality principles to improve performance using interpretive structural modeling and MICMAC analysis

Purpose

The purpose of this paper is to study the 14 principles of Edwards Deming and create significant relationships between them. No research has been reported on the implementation of Total Quality Management (TQM) using Deming’s 14 principles. To fill this gap, Interpretive Structural Modeling (ISM) and MICMAC analysis have been developed to understand mutual interactions among variables and find both the dependence and driving power of these variables.

Design/methodology/approach

The research paper discusses a blend of practical applications and introduces a theoretical framework. An ISM-based methodology is used to study and examine interactions between identified variables, while MICMAC analysis is used to identify the dependence and driving power.

Findings

This research utilizes Deming’s 14 quality principles, with experts from academia and industry consulted to identify contextual relationships among variables. The result shows that the stated principles “take action to accomplish the transformation,” “institute training,” “encourage education to employees” and “institute leadership” are strategic requirements, while “drive out fear,” “break down barrier between staff areas” and “eliminate numerical quotas” are tactical requirements. “Adopt the new philosophy,” “create constancy in improvement of product and service” and “cease dependence on mass inspections” are operational requirements for TQM applications.

Originality/value

An ISM-based quality framework, dependence power and driving power of variables using MICMAC analysis have been recommended to the service and manufacturing industry as a new focus area in the implementation of TQM.

Using integrated weighted IRP-Fuzzy TISM approach towards evaluation of initiatives to harmonise Halal standards

Purpose

Multiplicity and conflicting Halal standards involve unnecessary repetition of testing for demonstrating the Halal integrity of the process and the product, thus making it difficult for the Halal commodities to get traction in international markets. The purpose of this paper is to suggest initiatives to facilitate harmonisation of Halal standards as to eliminate trade barrier of Halal and to assure the availability of Halal consumables to larger masses.

Design/methodology/approach

Ranking of the initiatives for the harmonisation of Halal standards taking in consideration the costs of accomplishment and associated benefits obtained has been done through the application of integrated Interpretive Ranking Process (IRP) and Fuzzy Total Interpretive Structural Modelling (Fuzzy TISM). This integrated methodology with the weighted criteria have refined the value of the net dominance of different variables, thereby increasing the efficacy of IRP in decision making.

Findings

Findings suggest that strengthening the strategic coordination and collaboration among competent HCBs is a significant initiative. This initiative needs to be undertaken to mitigate the conflict between HCBs. This necessitates to develop a common platform in making the collective decision for effectively controlling Halal businesses. Moreover, recognising competent HCBs will prompt the effective implementation and execution of Halal standards across the supply chain, and ease the global trading of Halal products. A framework has been conceptualised to enable harmonisation of Halal standards which intimates to develop globally agreed protocols for Halal practices.

Practical implications

The framework presented may act as a prelude to harmonise Halal standards and may positively affect the international trade of Halal commodities by phasing out the discriminatory and market-impeding standards.

Originality/value

A harmonised system may provide correct information to the stakeholders and may help in making an informed decision.

Benchmarking the risk assessment in green supply chain using fuzzy approach to FMEA

Purpose

The purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production.

Design/methodology/approach

Initially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment.

Findings

Results indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis.

Originality/value

The present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode.

Strategic action grids: a study on supply chain risk management in manufacturing industries in India

Purpose

The purpose of this paper is to provide strategic recommendations to supply chain managers of Indian manufacturing industries for a robust supply chain related to risk management by original equipment manufacturers (OEMs) and suppliers in manufacturing industries to ensure a robust supply chain risk management (SCRM).

Design/methodology/approach

Importance-performance analysis (IPA) is utilized to identify and provide strategic recommendations to manufacturing industries for improving their supply chain performance by attaching due importance to risk constructs and appropriately choosing mitigation strategies.

Findings

The investigation using the strategic action grids reveals that most of the means of risks are near the point of intersection of the grand means of the risk constructs and their impact on the supply chain, indicating that all the risks have the equal likelihood of occurrence. The mean importance of risk monitoring, risk avoidance (RA) and risk sharing surpass the mean performance for both OEMs and suppliers.

Research limitations/implications

The study is executed with following limitations: the study assumes that the manufacturing industries across different sectors perceive similar risk. The sectors considered are automotive, heavy engineering, general engineering and home appliances. The Southern States of India are considered because of the dominant presence of many industries, especially automotive industries. However, it should be noted that these States form the manufacturing hubs where the lead organizations are functioning along with their major suppliers.

Practical implications

By understanding the importance of SCRM dimensions and utilization of these dimensions, firms can mitigate the impact of risk on the supply chain. The detailed study of SCRM strategies highlights the importance attached to risk factors, mitigation strategies, and top management commitment. By the implementation of SCRM strategies, supply chain managers can improve the firm’s performance.

Originality/value

The study involves empirically validated data on SCRM dimensions. The IPA is performed on the SCRM dimensions to investigate the importance attached to the factors of the dimensions and their performance.

Food safety assessment in India: modelling enablers

Purpose

The ever-widening competitive global markets demand food business to demonstrate safe food supplies across the world. The causes of food borne illness are complex to determine and require a careful evaluation of all stages of food supply chain and food safety practices. The purpose of this paper is to systematically investigate the factors responsible for the assessment of food supply chain and evaluation of food safety system in India.

Design/methodology/approach

The study utilizes a combination of qualitative and quantitative approach by exploring expert’s opinion systematically using a semi-structured interview followed by careful grouping of responses using the grounded theory approach to build the research theme. The prioritization of the critical factors is carried out using Pareto analysis. The methodological review was carried out to identify factors and categorize them based on their impact on hierarchical logical relationship using total interpretive structural modeling approach to determine the enablers.

Findings

This paper attempts to deliver an inimitable list of seven vital factors for the effective design of evaluation system for food safety practices. The study provides a careful insight on the issue pertaining to designing of assessment system including competence building for assessor and availability of well-defined technical protocol. The recommendation for developing a robust food safety inspection system by implementing stricter regulation, enhancing competence and design initiatives is provided.

Originality/value

The study provides a unique list of factors for the assessment of food safety practices and develops the relationship. Food safety assessment is an integral part of food safety study which is systematically explored and conceptualized in this paper. The study is carried out using the opinion of Indian experts.

Modelling the factors affecting Indian medical tourism sector using interpretive structural modeling

Purpose

Medical tourism encourages the traveling of patients, expert healthcare professionals and promotes cross-border trade in healthcare services. The Indian medical tourism sector is facing new challenges as well as certain ethical and legal issues because of continuous market changes and patient’s requirements while at the same time advancements in current health services have also been observed. It is therefore very important to understand and address the issues of the medical tourists. The purpose of this paper is to evaluate the important factors which can make India an affordable medical tourism destination.

Design/methodology/approach

In this paper, the factors influencing Indian medical tourism sector have been explored by conducting literature review, they are ranked according to the results of a questionnaire-based survey and further analyzed by using the interpretive structural modeling (ISM) approach. The mutual relationships between these factors were identified to develop an ISM model so as to find out the important factors which can make India an affordable place for medical tourism.

Findings

The results of the survey and the model show that cost of medical procedures, facilitation, and care, the infrastructure of Indian hospitals, clinical excellence and the competence of doctors and staff are the top level factors.

Practical implications

It is very important to address the concerns of the patients coming to a developing country like India for availing medical services. This research has evaluated the important factors which can make India an affordable medical tourism destination.

Originality/value

This research assesses the effects of globalization on delivery of healthcare services in India by conducting critical analysis of the medical tourism industry by collecting original data from the international patients coming to India for different types of medical procedures so that a comprehensive model can be prepared which will help the hospitals and policymakers to improve the processes related to medical tourism.