An integrated framework for prioritizing risk mitigation approaches – the case of dairy supply chain

Abstract

Purpose

This paper proposes an approach for prioritizing Risk Mitigation (RMTG) approaches in perishable food Supply Chains (SCs).

Design/methodology/approach

An integrative approach has been proposed, based on the risk typology and Supply Chain RMTG (SCRMTG) approaches literature review, integrating trending Failure Modes and Effects Analysis (FMEA), Quality Function Deployment (QFD) and Quadrant Analysis (QA). Risks are prioritized using Trending FMEA. SCRMTG approaches are prioritized by considering the prioritized risks using QFD and also based on their strategic importance and ease of Benchmarking via QA. The proposed approach has been examined in a dairy-manufacturing company.

Findings

Findings indicated supplying the imported machine parts, old machines and delayed new product introduction, respectively, as the most prominent supply, process and demand risks and multiple sourcing, upgraded machinery, hiring skilled staff and training, collaboration with downstream partners as the highly prioritized SCRMTG approaches based on the strategic importance and ease of benchmarking.

Research limitations/implications

The results of this study increase the awareness of SC managers and provide the company with a framework of risk management and the insights to manage SCRs in the dairy industry more effectively and efficiently.

Originality/value

While the literature review indicates that only a few studies have been focused on prioritizing SCRMTG approaches concerning each type of SCRs, SCRMTG approaches are prioritized based on the SCRs type. Other innovations include QFD development based on the FMEA and SCRMTG approaches, considering the probability of risk occurrence, severity-impact cost and risk recovery duration in trending FMEA instead of the three risk factors in traditional FMEA.

1. Introduction

Risk management has always been a critical concept within the Supply Chain (SC). Companies implement SC Risk Management (SCRM) approaches to secure their SC, ensure the continuity of their activities and reduce their vulnerability to risks. SCRM is a multi-step process consisting of identifying the potential risk sources, defining the risk concept, identifying the risk drivers and finally, Risk Mitigation (RMTG) (Ferguson and Drake, 2021; Vishnu et al., 2019). One of the applied techniques in risk management is Failure Modes and Effects Analysis (FMEA), broadly used to identify and eliminate possible failures within a process or system before their occurrence (Shahin et al., 2020; Shaker et al., 2019). It is a structured approach to prioritize failure modes based on an indicator named Risk Priority Number (RPN), calculated by multiplying three risk factors, that is Occurrence (O), Severity (S) and Detection (D) of the failures (Cho and Chae, 2022; Shaker et al., 2022; Reda and Dvivedi, 2022; Liu, 2019; Huang et al., 2022).

Quality Function Deployment (QFD) is a customer-oriented approach to transforming customer needs and expectations into technical requirements (Cho and Chae, 2022). The House of Quality (HoQ) translates the customer requirements (WHATs) to the technical features (HOWs) to prioritize essential resources that describe how an organization meets customer requirements (Hammid et al., 2022; Reda and Dvivedi, 2022). Moreover, benchmarking is a team-based approach for continuous quality improvement and enhancing the performance and profitability of organizations. It is a systematic and continued process of identifying the best practices for products, services or processes and making improvements necessary to achieve them (Hatami-Marbini, 2019; Hutton and Zairi, 1994).

Despite its potential benefits in a wide range of situations, SC RMTG (SCRMTG) approaches have received scant attention on the subject of SCRM in the business environment (Saglam et al., 2020). Asrol et al. (2021) developed a new framework to identify SC risks and defined MTG to improve performance based on a SC Operation Reference (SCOR) and Fuzzy-Analytic Hierarchy Process (AHP). Findings showed that the upstream of the SC had to bear major risks while the downstream faced minor ones. Yu and Shahbaz et al. (2020) identified three types of risks, namely, supply, process and demand side risks and proposed a framework to investigate their effects on SC performance. Yu and Huatuco (2016) assessed and prioritized risks in a Chinese dairy company by FMEA and provided some recommendations to mitigate the high-priority risks. Wang et al. (2017) proposed an integrated framework to take account of multiple types of risks and compared and ranked alternative RMTG approaches, using the fuzzy Delphi method to extract appropriate RMTG approaches and fuzzy TOPSIS to acquire the priority ratings of identified SCRMTG approaches.

Perishable Food SCs (PFSCs) is a complex network and it is a challenging task to manage it due to the product’s short lifetime and the multitude of participating stakeholders in production, distribution and retailing (Zhu and Krikke, 2020; Zhang et al., 2017). Kumar et al. (2021) identified and analyzed RMTG approaches for PFSCs during the pandemic of COVID-19, using the fuzzy-best-worst methodology. Findings showed collaborative management, proactive business continuity planning and financial sustainability as the top-risk MTG approaches. Prakash et al. (2017a, b) identified and analyzed supply, process, demand and environmental risks in PFSCs and determined the most effective RMTG approaches using FMEA and Interpretive Structural Modeling (ISM). The impact and prioritization of the RMTG approaches were achieved by calculating RPNs and RMTG numbers.

It is apparent from the literature that there is a visible research gap in studies dealing with the interrelationships of SCRs and the appropriate MTG approaches and what MTG approaches are suitable for a specific type of risk in the SC. To fill this gap, through this paper, an extensive review of SCRs typology and MTG approaches is performed to identify and prioritize the most relevant risks and MTG approaches in PFSC. It is apparent from the literature that there is a visible research gap in studies dealing with the interrelationships of SCRs and the appropriate MTG approaches and what MTG approaches are suitable for a specific type of risk in the SC. To fill this gap, through this paper, an extensive review of SCR typology and MTG approaches is performed to identify and prioritize the most relevant risks and MTG approaches in PFSC. Although only a few studies focus on analyzing or prioritizing SCRMTG approaches concerning each type of SCR, in this study, the SCRMTG approaches are prioritized separately for every three categories of supply, process and demand risks in the dairy industry. First, SCRs are prioritized based on RPN values obtained by multiplying the probability of risk occurrence (O), severity-impact cost (S) and recovery duration (D) obtained from the three-dimensional risk trending plot developed by Ghadge et al. (2013) as the risk factors in trending FMEA instead of those in traditional FMEA. Then, HoQs are developed to prioritize the SCRMTG approaches for each risk category. Lastly, the final prioritization of the SCRMTG approaches, based on the strategic importance and the ease of benchmarking, is done through quadrant analysis (QA). So, the proposed model application can help managers identify, assess and mitigate SCRs and prioritize SCRMTG approaches, determining the most effective ones.

The paper is organized as follows. Section 2 presents the literature on SCRs typology and MTG approaches in the PFSC. Section 3 describes the proposed approach. Section 4 provides an overview of the case company and demonstrates the proposed approach to prioritize SCRs and MTG approaches in the dairy industry, followed by discussion and conclusions in Sections 5 and 6.

2. Literature review

A comprehensive literature review on SCRs typology and MTG approaches has been performed, presented in the following sections.

2.1 SCR typology

However, the literature on managing SCRs seems relatively well-developed and risk identification research is still in the early stage (Rao and Goldsby, 2009). Although several risk classifications exist, SCRs can be classified into two types (Prakash et al., 2017a, b; Ghadge et al., 2013; Samvedi et al., 2013; Waters, 2011):

1. Internal risks arise from within the SC network and appear in normal operations, like late deliveries, poor forecasts, faults in information technology (IT) systems and others, and;

2. External risks emanate from outside the SC, such as natural disasters, shortages of raw materials and price rises.

In some studies, such as Waqas et al. (2022), Ivanov (2021), Wang et al. (2017), Chen et al. (2013), Diabat et al. (2012) and Tang and Tomlin (2008), SCRs are classified into three categories, namely, supply, process and demand. Some other studies on SCR typology are summarized in Table 1.

Moreover, based on the related literature review, some factors/agents/sources of the SCRs regarding the supply, process and demand risks are proposed in Table 2.

2.2 Risks in PFSC

Food SC Risks have been described as unforeseen events that can interrupt or negatively affect the food SC (Rathore et al., 2020). Food SC risk management is an emerging concern as it inadequately handles the rising risk level. A review of prior literature over the past five years indicated a growing attention to risks in FSCs, particularly concerning perishable and dairy products (Azizsafaei et al., 2022; Rathore et al., 2017). In this study, we tried to determine significant risks in the dairy industry based on the literature review.

2.2.1 Supply risks

Supply risks involve potential deviations in the inbound supply in terms of time, quality and quantity at different levels or within the same level of the SC, that may cause order failure and potential disturbances to the flow of products and information coming out from upstream activities in the SC. Some examples of sources of supply risks are supplier quality problems, supply cost, supplier bankruptcy, the inability to supply, failure of the partnership, communication failure between different stages of the SC, delay in delivery, uncertain or variable lead time, capacity fluctuations or shortages in the supply markets (Majumdar et al., 2021; Shekarian and Mellat Parast, 2021; Truong and Hara, 2018; Rathore et al., 2017; Diabat et al., 2012).

2.2.2 Demand risks

Demand risks are internal to the chain but external to the firm and are concerned with downstream activities in the SC. They involve the potential difference between actual and forecasted demand and potential disturbances in the flow of products and information within the network or between the focal firm and the market. It means firms in the supply network are unable to forecast actual market demands, leading to a gap between supply and demand. Some sources of demand risks are demand uncertainty and fluctuation, forecasting errors, delayed or inappropriate new product introductions, changes in customer tastes, innovative competitors and insufficient or distorted information from the customers about orders or demand quantities (Majumdar et al., 2021; Shekarian and Mellat Parast, 2021; Shahbaz et al., 2020; Tarei et al., 2018; Truong and Hara, 2018; Prakash et al., 2017a, b; Samvedi et al., 2013; Diabat et al., 2012; Tang and Tomlin, 2008; Manuj and Mentzer, 2008).

2.2.3 Process risks

Process risk, as a result of an unreliable production process, has been defined as any potential source that generates a negative impact on the flow of information, goods and cash in the operations (Shekarian and Mellat Parast, 2021; Shahbaz et al., 2020; Wang et al., 2017). It results from disturbances in the product flow through different processes within a firm and involves potential deviations from producing desired quality and quantity at the right time (Shekarian and Mellat Parast, 2021; Wang et al., 2017; Samvedi et al., 2013). Some process risks sources are downtime or loss of own production capacity due to local disruption (e.g. labour strikes), technical reasons (e.g. machine failure), technology risk (can be caused by hardware, software and technology associated with communication between hardware and software), scarcity of skilled personnel and product quality problems (Majumdar et al., 2021; Shekarian and Mellat Parast, 2021; Rathore et al., 2020; Ghadge et al., 2013; Diabat et al., 2012; Manuj and Mentzer, 2008).

2.3 RMTG approaches

SCRM is a systematic identification, assessment, MTG and/or control of potential risks, within SCs or outside, to reduce their negative impact on the SC performance (Wang et al., 2017). The risk identification process includes risk taxonomy and trending, while the risk assessment contains risk modelling and sensitivity analysis.The RMTG process includes strategic planning and RMTG (Tarei et al., 2020; Ghadge et al., 2013).

The SCRMTG approaches refer to company actions to reduce the probability of risks occurrence and their negative impacts (Chang et al., 2015). Kilubi (2016) indicated eight top SCRMTG approaches deemed crucial by many researchers, including flexibility, collaboration, visibility and transparency, postponement, multiple sourcing, redundancy, flexible contracts, relationships/partnerships and joint planning and coordination. Saglam et al. (2020) summarized some key SCRMTG approaches in the literature, including collaboration, flexibility, resilience, responsiveness, acquiring multiple suppliers and agility. Some of the most frequently mentioned SCRMTG approaches are summarized in Table 3.

3. The proposed approach

Our proposed model, illustrated in Figure 1, aims to provide a framework for prioritizing PFSC RMTG approaches using trending FMEA, HoQ and QA. The proposed approach is divided into five phases described further in the text. It is worth mentioning that the model validity has been evaluated and confirmed by 20 experts from the under-studied company and five university professors.

3.1 First phase: SCRs classification

In this phase, some of the specific supply, process and demand risks are identified in the SC through a comprehensive literature review and with regard to the expert opinions in the factory.

3.2 Second phase: trending FMEA

Risk prioritization is achieved by calculating RPN via trending FMEA. The questionnaire of trending FMEA focused on the assessment of the SCRs placed into the three risk categories: supply, process and demand risks, via evaluating RPN values calculated by multiplying risk occurrence, severity-impact cost and recovery duration as three risk factors, using a 10-point Likert scale according to the guidance tables of the O, S and D (Table 4), developed by interviewing the experts in the factory. A higher RPN value means a higher priority of the considered risk.

3.3 Third phase: identifying SCRMTG approaches

Through an overview of the most frequently mentioned SCRMTG approaches in the literature (see Table 3) and interviewing the experts in the under-studied company, the appropriate SCRMTG approaches regarding the identified risks are determined.

3.4 Fourth phase: HoQ

Three HoQs are developed to prioritize SCRMTG approaches based on the prioritized SCRs. In HoQ, the prioritized risks obtained by trending FMEA are used as WHATs, and the identified SCRMTG approaches as HOWs, separately for every three types of risks in the dairy-manufacturing company. Three HoQs interrelationships matrixes, consisting of the prioritized supply, process and demand risks given from the trending FMEA and the identified SCRMTG approaches, are filled by the experts in the company using weights of 1, 3 and 9, respectively, for a weak, a medium and a strong relationship, to prioritize the SCRMTG approaches. Lastly, the importance rates of the SCRs, that is the RPN values calculated in the previous phase, are multiplied by the interrelationship weights, and the sum of the computed values for each column is used in the SCRMTG approaches prioritization.

3.5 Fifth phase: benchmarking

The decision of what to benchmark is highly subjective and also critical. Among several studies that presented various parameters and methods to select the appropriate process for benchmarking, the Hutton and Zairi (1994) research is more comprehensive. They suggested that among several factors that influence benchmarking priorities, two main parameters are particularly essential for all organizations: issues regarding the strategic importance of a process and the ease of benchmarking. So, in this final phase, the prioritized SCRMTG approaches delivered from the previous step are prioritized once more based on their strategic importance and the ease of benchmarking, using QA, to select the best choice for improvement.

4. Case example and findings

A large dairy company with 50 years of worthy experience and extensive activity in the dairy Industry, with a recognized brand name in Iran, is considered for further analysis to obtain an in-depth appreciation of the proposed integrated approach in a real-life context. The applicability of the proposed approach was examined using the data gathered from 20 well-experienced experts and decision-makers from different units in the company, such as production, purchasing/supply, marketing/sales, R&D, staff, quality assurance, engineering and management, in 2022. Based on the proposed approach in Figure 1, SCRs were classified into supply, process and demand risks, and 30 specific risks and 14 SCRMTG approaches were proposed by an extensive literature review in the PFSC and the knowledge contribution of the expert group in the studied factory (see Table 5).

Ranking the identified risks was done using trending FMEA. A total of 11 supply risks, 11 process risks and eight demand identified risks were prioritized by the RPN values, calculated using a 10-point Likert scale, in terms of Table 4, shown in Table 6. According to the findings, supplying the imported machine parts, supplying imported raw and packaging materials and suppliers reluctant to enter into a contract were recognized as the most critical supply risks. Delayed new product introduction, deficient customer relationships and changes in customer tastes were found as the most prominent demand risks. Moreover, old machines, wasting raw and packaging materials and machine failure were determined as the most crucial process risks.

In the next phase, the relevance of the supply, process and demand risks, prioritized by trending FMEA, is evaluated to the appropriate SCRMTG approaches. Three separate HoQs were developed to prioritize SCRMTG approaches based on the prioritized SCRs, using the given RPN values from the trending FMEA as the importance rates of the identified SCRMTG approaches. The interrelationship weights among the SCRs and SCRMTG approaches are provided by exploring the viewpoints of the experts, using weights of 1, 3 and 9. For this purpose, the most frequently expressed weights are entered into the matrix cells. The prioritized SCRMTG approaches concerning supply, process and demand risks are listed in Tables 7–9, respectively. If the relative weights of the bottom of the first HoQ, shown in Table 7, are summed up, then the share of multiple sourcing and flexible supply contracts would be about 65%, and therefore it is concluded that they are the most important SCRMTG approaches based on the prioritized supply risks in the dairy-manufacturing company. Similarly, the results represented that upgraded machinery, and hiring skilled staff and their training, and collaboration with downstream partners are the highest-prioritized SCRMTG approaches, respectively, for the prioritized process and demand risks in the company.

Finally, the final prioritization of the SCRMTG approaches is performed via QA, considering their strategic importance and ease of benchmarking, using the critical process benchmarking prioritization matrix (Hutton and Zairi, 1994), with the strategic importance on one axis and the ease of benchmarking on the other. The given weights of the prioritized SCRMTG approaches obtained from the HoQs were entered into this phase as strategic importance, and the provided data through the questionnaire regarding ease of benchmarking issues were used as ease of benchmarking. The questionnaire developed by Hutton and Zairi (1994) was used for data gathering regarding the ease of benchmarking issues, containing seven factors/questions described below. It was completed by consensus among the company expert team, using a 10-point Likert scale.

1. Level of TQ implementation (1 = Low/Little TQ implementation; 10 = High/Significant level of TQ implementation).

2. The generic nature of the processes (1 = Specific to your company; 10 = Highly generic).

3. Relevance to groups or only individuals (1 = Only a few individuals; 10 = Organization-wide).

4. Availability of benchmarking partners (1 = Difficult to identify partners; 10 = Partners easily identifiable).

5. Process information availability (1 = Difficult to obtain; 10 = Readily available).

6. Willingness to share information (1 = Not willing at all; 10 = Very willing to share).

7. Perception of improvement capability (1 = Difficult to improve/few opportunities; 10 = Easy to improve/Many opportunities).

The prioritization matrix provides an analytical method of assessing the prioritized SCRMTG approaches against the benchmarking priorities. Since the matrix is a relative comparison of the critical processes, the axis can range from the lowest to the highest scores of each parameter. In the case of the studied company concerning the SCRMTG approaches:

1. Strategic Importance will range from 0.1 to 0.4, and;

2. Ease of Benchmarking will range from 1 to 10.

It is worth noting that the data regarding ease of benchmarking were multiplied by a coefficient, 0.04, to be the same scale as the data regarding strategic importance for better analysis through QA. The best choices for a successful benchmarking exercise would be the SCRMTG approaches with the highest scores on both strategic importance and ease of benchmarking and thus occupy the top right sector of the matrix. Based on the obtained results from the QA, displayed in Figures 2–4, multiple sourcing, upgraded machinery, hiring skilled staff and their training and collaboration with downstream partners were the best choices in terms of the strategic importance and ease of benchmarking to implementation in the under-studied factory.

5. Discussion

It is evident from the study that among the proposed SCRMTG approaches, multiple sourcing, upgraded machinery, hiring skilled staff and their training and collaboration with downstream were addressed repeatedly twice as the highest-prioritized SCRMTG approaches, once based on the prioritized SCRs through the interrelationship weights of the middle cells of the HoQs interrelationships matrixes, and once based on their strategic importance and ease of benchmarking using QA. So, one of the advantages of the proposed approach is proposing and prioritizing appropriate mitigating approaches to deal with supply, process and demand risks in the dairy industry. For example, multiple sourcing and flexible supply contracts increase supply flexibility. On the other hand, hiring efficient and skilled staff and training them has a considerable impact on reducing risks of mismanagement and different hazard risks such as machine damage and staff injury.

Another advantage of the proposed approach, especially concerning the second phase, compared to the conventional FMEA, is taking into consideration the probability of risk occurrence, severity-impact cost and recovery duration as three risk factors, in trending FMEA, for determining risk priority instead of the usual O, S and D used in traditional FMEA. Since answers to the failure duration, rate of failures and the probable impact of disruptions is critical for today’s businesses (Altay and Green, 2006), from this point of view, our proposed approach can be helpful for managers by considering these crucial factors in determining the priority of exposed risks in the dairy industry via trending FMEA.

5.1 Theoretical contribution

Tang and Tomlin (2008) explored the role of flexibility approaches in managing supply, process and demand risks. Results showed that the company has more supply flexibility by increasing the number of suppliers, and the percentage increase in the manufacturer’s optimal expected profit increases by flexible supply contracts. Their results support the results of this study. Shekarian and Mellat Parast (2021) found that flexibility is the most important approach to cope with supply, process, demand and environmental SC disruptions. Chopra and Sodhi (2004) believed lack of coordination results in a significant loss of SC profit. Lavastre et al. (2012) also found collaboration and establishment of joint and common transverse processes with industrial partners critical for an effective SCRM. The proposed approach of this study has similar advantages too.

Yu and Huatuco (2016) presented that increasing collaboration with partners and flexibility of the system are some proposed approaches that can be adopted by the organization in risk responding. According to the AMR (Advanced Market Research) SCR survey in 2009, closer collaboration with SC partners, use of multiple sourcing strategies and redundant suppliers are the most successful methods often used for RMTG (Tummala and Schoenherr, 2011). Chen et al. (2013) examined supply, process and demand risks and understood that collaboration effectively reduces SCRs. Coordinating with suppliers also were suggested by Trenggonowati et al. (2020) as a high-priority RMTG approach. Similarly, in this study, flexibility through multiple sourcing and flexible supply contracts were the first two priority levels of the supply RMTG approaches, and collaboration with downstream partners were at the top level of demand RMTG approaches prioritization.

Mangla et al. (2018) proposed a model for benchmarking the risk assessment in a green SC using fuzzy FMEA. They assessed common risk factors like supply quality, unskilled labour and disruption in supply, but not conducted in the dairy industry, unlike this study. They also provided some suggestive measures for improvement, in which interaction with suppliers, interactive sessions with customers and training and education were similar to the proposed SCRMTG approaches in this paper.

Prakash et al. (2017a, b) found that supplier-related risks were more prominent than others, followed by market and process risks. Similar to this study, performed in the case of the dairy industry, prioritized supply, process and demand risks by RPN values and considered similar risk-enabling factors such as supply cost, uncertain demand, lead time, lack of communication and wrong information sharing. Moreover, upgraded machinery was determined as the most efficient practice for RMTG, confirming our results about the risk of using old machines and suggesting upgraded machinery to reduce process risks in the SC. However, unlike us, they didn’t consider the strategic importance and ease of benchmarking in the SCRMTG approaches prioritizations.

5.2 Managerial implications

Regarding benchmarking, it is worth mentioning that improvement should occur in uncomplicated processes so that employees can see the progress results soon, accelerating the repetition of the improvement cycle and continuous improvement activities. So, it is suggested to the managers of the studied company to pay extra attention to the most highly prioritized SCRMTG approaches proposed based on the ease of benchmarking and strategic importance. Some practical suggestions, according to the field findings of this research, are as follows:

Increasing supply flexibility is recommended by using one or more alternative suppliers and making flexible supply contracts by making different quantity orders through time, due to the highest priority of multiple sourcing and flexible supply contracts among supply risks MTG approaches, to reduce supply risks and mitigate the risk of disruption from any supply sources. Besides, since collaboration with downstream partners were identified as the highest-priority approach for mitigating demand risks, for this purpose, because of the highly significant role of information sharing in an effective SC collaboration, it is suggested to the managers of the studied company to share knowledge and expertise with downstream SC partners to reduce uncertainty. Moreover, regarding deficient customer relationships identified among the high-priority demand risks and concerning the critical role of recognizing customer needs and expectations, it sounds great to implement a Customer Relationship Management (CRM) system or improve the existing one to enhance customer satisfaction and product quality. In addition, upgraded machinery and hiring skilled staff and their training were addressed as the high-prioritized approaches for mitigating process risk. Hence, it is suggested to the decision-makers to upgrade the old equipment or replace it with a new one when is necessary, along with taking advantage of training management as well as Human Resource Management (HRM) through hiring skilled staff, arranging consistent training programs, providing motivational and incentives facilities for staff and building a monitoring team, leading to a growth in job skills and work more professionally with fewer mistakes.

6. Conclusions

In the proposed approach, QFD developed based on RMTG and FMEA methods for prioritizing SCRMTG approaches in the PFSC. Among 11 supply risks, 11 process risks and eight demand risks identified in the dairy-manufacturing company, supplying the imported machine parts and raw materials and packaging materials were placed as the highest-priority risks at the supply end, as well as delayed new product introduction and deficient customer relationships at the demand end, and old machines and wasting raw and packaging materials, among process risks. On the other hand, multiple sourcing, upgraded machinery, hiring skilled staff and their training and collaboration with downstream partners were identified as the highest-priority SCRMTG approaches based on the ease of benchmarking and strategic importance.

While the literature review indicates that just a few studies have been focused on prioritizing SCRMTG approaches concerning each type of SCR, in this study, SCRMTG approaches are assigned based on the SCR type, that is supply, process and demand risks and prioritized once by considering the SCRs priorities in each category, and once by considering strategic importance and ease of benchmarking of the SCRMTG approaches. Other innovations of this research include the development of QFD based on RMTG approaches and the FMEA method while considering the probability of risk occurrence, severity-impact cost and risk recovery duration in the trending FMEA instead of the three risk factors in the traditional FMEA. Three independent HoQs were developed to prioritize the supply, process and demand RMTG approaches in the dairy industry. The results of this study increase the awareness of SC managers and provide the company with a framework of risk management and the insights to manage SCRs in the dairy industry more effectively and efficiently. Moreover, the proposed model can lead to some social Implications, such as:

1. Employment Opportunities: Implementing strategies like hiring skilled staff and providing training can contribute to job creation and skill development in the community.

2. Environmental Sustainability: Prioritizing the SCRMTG approaches related to the risks of wasting raw and packaging materials can cause reduced environmental impact and promote sustainable practices.

3. Consumer Welfare: Enhancing customer relationships and ensuring timely product introductions can lead to improved consumer satisfaction and trust in the company’s products.

4. Economic Stability: Effective SCRMTG approaches can contribute to the stability of the dairy industry and the broader economy by reducing disruptions.

Besides, the integrated approach can facilitate public Policy Formulation, for instance:

1. Regulatory Framework: Governments may consider introducing or strengthening regulations related to SCRMTG approaches to ensure companies prioritize the safety and reliability of the SCs.

2. Training and Education Initiatives: Public policies can support initiatives aimed at providing training and education programs for workforce development, particularly in areas related to SCRM and RMTG.

3. Incentive Programs: Governments can introduce incentive programs to encourage companies to invest in upgraded machinery, sustainable practices and collaborative partnerships to mitigate SCRs.

4. Research Funding: Policymakers may allocate funding for research and development in SCRM to support innovative approaches and tools like QFD based on RMTG approaches and the FMEA method, which can benefit industries beyond the dairy sector.

6.1 Limitations and future research agenda

The SCRMTG approaches were assumed to be independent, although they may affect each other in real. So, applying simulation models such as system Dynamics methodology can be advised to consider potential interactions and identify the best combination of SCRMTG approaches. Considering other effecting factors such as budget constraints are recommended too.

On the other hand, using the fuzzy logic approach seems beneficial to decrease judgmental effects and vagueness in evaluating O, S and D in trending FMEA, determining interrelationships among the SCRs and the SCRMTG approaches in the QFD interrelationship matrixes and weighting allocation to ease of benchmarking for SCRMTG approaches. Besides, quantitative techniques such as DEMATEL may help determine the interrelationships among the SCRs and SCRMTG approaches in the QFD interrelationship matrixes. Moreover, since the validation of the proposed model was based on a single case study, implementing it in other cases or industries for further confirmation of the effectiveness and validity would be of interest.

Figure 1

The proposed approach

[Figure omitted. See PDF]

Figure 2

Final prioritization of supply risk MTG approaches using QA

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Figure 3

Final prioritization of process risk MTG approaches using QA

[Figure omitted. See PDF]

Figure 4

Final prioritization of demand risk MTG approaches using QA

[Figure omitted. See PDF]

Table 1

Summarizing some studies on SCR typology

Risk category/type	Reference
External to the network: environmental risk	Shekarian and Mellat Parast (2021)
External to the firm but internal to the SC network: supply and demand risks
Internal to the firm: process and control risks
Supply, demand, process/operations, business environment and financial risks	Majumdar et al. (2021)
Supply, operation/process, demand and environmental risks	Zhang et al. (2023)
Supply, demand, process, control and environmental risks	Andersson and Pardillo-Baez (2020)
Environment, supply, demand and process risks	Prakash et al. (2017a, b)

Source(s): The authors’ own work

Table 2

Supply, demand and process risk factors/agents/sources

Risk type	Specific risks	Reference
Supply	Supplier bankruptcy/insolvency	Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Ma and Wong (2018), Hernandez and Haddud (2018), Truong and Hara (2018), Nyamah et al. (2017), Moslemi et al. (2016), Yu and Huatuco (2016), Badurdeen et al. (2014), Samvedi et al. (2013), Diabat et al. (2012)
	Dependency on single (a few) supplier/Single sourcing	Ma and Wong (2018), Hachicha and Elmsalmi (2014), Punniyamoorthy et al. (2013), Tummala and Schoenherr (2011), Pujawan and Geraldin (2009), Blackhurst et al. (2008), Tang and Tomlin (2008)
	Dependence on suppliers	Zhang et al. (2023), Carpitella et al. (2022), Kumar et al. (2018), Truong and Hara (2018), Hallikas and Lintukangas (2016)
	Supplier failures/disruptions	Barros et al. (2021), Fagundes et al. (2021), Majumdar et al. (2021), Shahbaz et al. (2020), Tarei et al. (2018), Hallikas and Lintukangas (2016), Christopher et al. (2011), Tummala and Schoenherr (2011), Manuj and Mentzer (2008)
	Interruption or inability of supply	Fagundes et al. (2021), Rathore et al. (2017, 2020), Hachicha and Elmsalmi (2014), Chen et al. (2013), Diabat et al. (2012)
	Supplier commitment	Shekarian and Mellat Parast (2021), Fischl et al. (2014), Tang and Tomlin (2008)
	Supplier reliability	Fagundes et al. (2021), Yoon et al. (2018), Diabat et al. (2012)
	Supplier capability	Diabat et al. (2012)
	Faults or delay in delivery/Inefficient delivery	Zhang et al. (2023), Barros et al. (2021), Carpitella et al. (2022), Fagundes et al. (2021), Shahbaz et al. (2020), Er Kara and Oktay Fırat (2018), Tarei et al. (2018), Prakash et al. (2017a, b), Wang et al. (2017)
	Uncertain/variable/fluctuating lead time	Shekarian and Mellat Parast (2021), Er Kara and Oktay Fırat (2018), Hong et al. (2018), Hallikas and Lintukangas (2016), Tang (2006)
	Lack of/low supplier flexibility	Fagundes et al. (2021), Er Kara and Oktay Fırat (2018), Punniyamoorthy et al. (2013), Tummala and Schoenherr (2011)
	Supply quality	Zhang et al. (2023), Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Fagundes et al. (2021), Shahbaz et al. (2020), Er Kara and Oktay Fırat (2018), Chen (2018), Hernandez and Haddud (2018), Ma and Wong (2018), Truong and Hara (2018), Prakash et al. (2017a, b), Nyamah et al. (2017), Rathore et al. (2017, 2020), Kilubi (2016), Hallikas and Lintukangas (2016), Yu and Huatuco (2016), Hachicha and Elmsalmi (2014), Chen et al. (2013), Diabat et al. (2012), Samvedi et al. (2013), Manuj and Mentzer (2008)
	Supply cost or price escalation/uncertainty/fluctuations	Barros et al. (2021), Carpitella et al. (2022), Fagundes et al. (2021), Shekarian and Mellat Parast (2021), Shahbaz et al. (2020), Pattanayak et al. (2019), Er Kara and Oktay Fırat (2018), Truong and Hara (2018), Hallikas and Lintukangas (2016), Hachicha and Elmsalmi (2014), Fischl et al. (2014), Tang and Tomlin (2008), Manuj and Mentzer (2008)
	Inventory level problems	Majumdar et al. (2021), Tarei et al. (2018), Hallikas and Lintukangas (2016), Badurdeen et al. (2014), Tummala and Schoenherr (2011)
	Globalization	Samvedi et al. (2013)
	Outsourcing risk	Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Prakash et al. (2017a, b), Hallikas and Lintukangas (2016), Badurdeen et al. (2014), Samvedi et al. (2013)
	Supplier labor strike	Ma and Wong (2018), Vilko and Hallikas (2012)
	poor relationship with suppliers	Hernandez and Haddud (2018), Aloini et al. (2012)
	Failure of the partnership	Diabat et al. (2012)
	Communication failure	Rathore et al. (2017, 2020), Diabat et al. (2012)
	Communication and information delivery	Mirhosseini et al. (2019), Hallikas and Lintukangas (2016)
	Supplier capacity (constraints/uncertainty/fluctuations)	Fagundes et al. (2021), Shekarian and Mellat Parast (2021), Nyamah et al. (2017), Wang et al. (2017), Kilubi (2016), Tang (2006)
	Shortage in supply market/raw materials	Mouloudi and Evrard Samuel (2022), Shekarian and Mellat Parast (2021), Diabat et al. (2012)
Process/Operations	Machine/equipment/facility failure	Zhang et al. (2023), Carpitella et al. (2022), Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Ma and Wong (2018), Tarei et al. (2018), Badurdeen et al. (2014), Samvedi et al. (2013)
	Poor quality/Product quality	Shekarian and Mellat Parast (2021), Tarei et al. (2018), Prakash et al. (2017a, b), Ghadge et al. (2013), Samvedi et al. (2013), Tummala and Schoenherr (2011), Manuj and Mentzer (2008)
	Technology risk/failure	Rathore et al. (2020), Majumdar et al. (2021)
	Technology changes	Majumdar et al. (2021), Truong and Hara (2018), Samvedi et al. (2013), Manuj and Mentzer (2008)
	Lack of updated technology/Aged machines	Ma and Wong (2018), Tarei et al. (2018), Badurdeen et al. (2014), Mishra and Raja Shekhar (2012)
	Manufacturing technology	Tarei et al. (2018)
	Infrastructure failure	Majumdar et al. (2021)
	Breakdown of IT system/infrastructure	Shekarian and Mellat Parast (2021), Moslemi et al. (2016)
	Transportation issues	Majumdar et al. (2021), Prakash et al. (2017a, b)
	Scarcity of skilled personnel/staff	Ali et al. (2019), Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Ma and Wong (2018), Diabat et al. (2012), Mishra and Raja Shekhar (2012), Vilko and Hallikas (2012)
	Labour strike	Zhang et al. (2023), Azizsafaei et al. (2022), Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Ma and Wong (2018), Truong and Hara (2018), Prakash et al. (2017a, b), Badurdeen et al. (2014), Samvedi et al. (2013)
	Component/material shortages	Radivojević and Gajović (2014), Badurdeen et al. (2014)
	Production issues	Prakash et al. (2017a, b)
	Inflexible processes	Shekarian and Mellat Parast (2021)
Demand	Uncertainty/variation/fluctuation/volatility of demand	Majumdar et al. (2021), Shahbaz et al. (2020), Chen (2018), Hong et al. (2018), Truong and Hara (2018), Ma and Wong (2018), Tarei et al. (2018), Nyamah et al. (2017), Hernandez and Haddud (2018), Prakash et al. (2017a, b), Rathore et al. (2017, 2020), Kilubi (2016), Yu and Huatuco (2016), Kilubi (2016), Ho et al. (2015), Punniyamoorthy et al. (2013), Chen et al. (2013), Samvedi et al. (2013), Diabat et al. (2012), Manuj and Mentzer (2008), Pujawan and Geraldin (2009)
	Unanticipated/unpredictable demand	Shekarian and Mellat Parast (2021), Shahbaz et al. (2020)
	Changes in customer tastes	Majumdar et al. (2021), Tarei et al. (2018), Diabat et al. (2012)
	Order changes by customers	Barros et al. (2021), Tarei et al. (2018), Chen et al. (2013), Waters (2011)
	Market changes	Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Samvedi et al. (2013)
	Competition change	Majumdar et al. (2021), Shekarian and Mellat Parast (2021), Samvedi et al. (2013)
	Forecasting errors	Zhang et al. (2023), Barros et al. (2021), Majumdar et al. (2021), Shahbaz et al. (2020), Hernandez and Haddud (2018), Tarei et al. (2018), Ma and Wong (2018), Prakash et al. (2017a, b), Rathore et al. (2017), Ho et al. (2015), Samvedi et al. (2013), Punniyamoorthy et al. (2013), Tummala and Schoenherr (2011), Pujawan and Geraldin (2009), Manuj and Mentzer (2008)
	Key customer failure	Majumdar et al. (2021)
	Exchange rate fluctuation	Zhang et al. (2023), Pereira et al. (2021)
	Bullwhip effect	Majumdar et al. (2021), Hernandez and Haddud (2018), Ho et al. (2015), Chen et al. (2013)
	Short lifecycle	Hernandez and Haddud (2018), Ho et al. (2015)
	Innovative competitors	Shekarian and Mellat Parast (2021)
	Delayed new product introduction	Chen (2018), Kilubi (2016), Manuj and Mentzer (2008), Shahbaz et al. (2020)
	Failure to communicate with customers	Diabat et al. (2012)
	Insufficient or distorted information from customer orders	Shekarian and Mellat Parast (2021), Shahbaz et al. (2020)
	Order fulfillment errors	Truong and Hara (2018), Tarei et al. (2018), Ho et al. (2015), Tummala and Schoenherr (2011)

Source(s): The authors’ own work

Table 3

Overview of the most frequently mentioned SCRMTG approaches

SCRMTG approaches	Relevant studies
Flexible supply via multiple suppliers	Saglam et al. (2020), Wang et al. (2017), Kilubi (2016), Lavastre et al. (2012), Chopra and Sodhi (2004), etc.
Flexible supply via flexible supply contracts	Wang et al. (2017), Kilubi (2016), Tang and Tomlin (2008)
Flexible process via flexible manufacturing process (or resources)	Wang et al. (2017), Tang and Tomlin (2008), Zhang et al. (2003)
Flexible production or manufacturing	Zhang et al. (2003)
Flexible transportation	Tang (2006)
Visibility and transparency (e.g. information sharing, communication)	Wang et al. (2017), Kilubi (2016), Nasir et al. (2014), Lavastre et al. (2012), Wieland and Wallenburg (2012), etc.
Quality of relationships/partnerships	Shahbaz et al. (2020), Wang et al. (2017), etc.
Collaboration	Shekarian and Mellat Parast (2021), Saglam et al. (2020), Kilubi (2016), Chang et al. (2015), Chen et al. (2013), etc.
Joint planning and coordination	Kilubi (2016), Lavastre et al. (2012)
Postponement	Wang et al. (2017), Kilubi (2016), Wieland and Wallenburg (2012), Tang and Tomlin (2008), Tang (2006)
Strategic/Safety Stock	Shekarian and Mellat Parast (2021), Tarei et al. (2020), Kilubi (2016), Lavastre et al. (2012), Tang (2006)
Revenue Management	Tang (2006)
Insource/Outsource	Tarei et al. (2020), Wieland and Wallenburg (2012), Tang (2006)
Upgraded machinery/Technology adaptation	Tarei et al. (2020), Prakash et al. (2017a, b)
Human resource management (e.g. hiring skilled staff and their training)	Nasir et al. (2014)

Source(s): The authors’ own work

Table 4

Rating scale of O, S and D

Probability of occurrence (O)		Severity-impact cost (S)		Recovery duration (D)
Item	Score	Item	Score	Item	Score
More than one occurrence in one day	10	20 billion Rials	10	Several months	10
One occurrence every 3 or 4 days	9	15 billion Rials	9	6 months	9
One occurrence per week	8	10 billion Rials	8	1–2 months	8
One occurrence per month	7	5 billion Rials	7	1 month	7
One occurrence every 3 months	6	2 billion Rials	6	3 weeks	6
One occurrence every 6 months to a year	5	1 billion Rials	5	2 weeks	5
One occurrence per year	4	800 million Rials	4	1 week	4
One occurrence every up to 3 years	3	500 million Rials	3	1–2 days	3
One occurrence every 3–5 years	2	300 million Rials	2	10 h	2
One occurrence in more than 5 years	1	20 million Rials	1	1 h	1

Source(s): The authors’ own work

Table 5

PFSC risks and the SCRMTG approaches

Risk type	Risks in PFSC		SCRMTG approaches
Supply risks	Poor quality of the supplied goods	R1	Multiple sourcing	MTG1
	Supply cost/price escalation	R2	Flexible supply contracts	MTG2
	Supplier bankruptcy/financial crisis	R3	SRM	MTG3
	Inability of supply	R4	Collaboration with upstream partners	MTG4
	Supplier capacity	R5	Information sharing	MTG5
	Faults or delay in delivery	R6
	Uncertain or variable lead time	R7
	Communication and partnership failure	R8
	Supplying the imported raw and packaging materials	R9
	Supplying the imported machine parts	R10
	Suppliers reluctant to enter into a contract	R11
Process risks	Machine failure	R12	Flexible manufacturing process	MTG6
	Scarcity of skilled personnel	R13	Flexible production or manufacturing	MTG7
	Technology failure	R14	Hiring skilled staff and their training	MTG8
	Lack of updated technology	R15	Upgraded machinery	MTG9
	Labor strike	R16
	Product quality problems	R17
	Incorrect/incomplete labeled data	R18
	Washing and disinfection of the production path of equipment	R19
	Transportation issues (transportation cost, safety and hygiene)	R20
	Old machines	R21
	Wasting raw and packaging materials	R22
Demand risks	Demand uncertainty/fluctuation	R23	Postponement	MTG10
	Unanticipated demand	R24	Dynamic pricing and promotion	MTG11
	Forecasting errors	R25	Collaboration with downstream partners	MTG12
	Changes in customer tastes	R26	Flexible transportation (multi-modal transportation; multi-carrier transportation; Multiple routes)	MTG13
	Deficient customer relationships	R27	CRM	MTG14
	Insufficient/distorted information from customer orders	R28
	Delayed new product introduction	R29
	Defects in products daily distribution	R30

Source(s): The authors’ own work

Table 6

Prioritizing SCRs via trending FMEA

Supply risks						Process risks						Demand risks
Item	O	S	D	RPN	Rank	Item	O	S	D	RPN	Rank	Item	O	S	D	RPN	Rank
R1	4	2	1	32	6	R12	8	8	4	256	3	R23	2	10	8	160	4
R2	7	3	4	84	4	R13	4	7	6	168	4	R24	1	6	7	42	7
R3	1	1	1	1	11	R14	4	6	4	96	6	R25	1	6	8	48	6
R4	3	2	2	12	8	R15	3	5	9	135	5	R26	3	8	9	216	3
R5	5	1	2	10	9	R16	1	8	6	48	8	R27	7	5	7	245	2
R6	5	5	3	75	5	R17	5	8	1	40	11	R28	3	2	5	30	8
R7	4	2	3	24	7	R18	4	6	3	72	7	R29	5	7	8	280	1
R8	1	1	2	2	10	R19	3	7	2	42	10	R30	7	5	4	140	5
R9	7	6	7	294	2	R20	3	5	3	45	9
R10	7	7	8	392	1	R21	6	9	9	486	1
R11	6	4	7	168	3	R22	8	7	6	336	2

Source(s): The authors’ own work

Table 7

Prioritizing supply risk MTG approaches

SCR items	Importance	MTG1	MTG2	MTG3	MTG4	MTG5
R1	32	1	1	1	3	3
R2	84	3	3	3	3	3
R3	1	1	3	1	1	1
R4	12	1	3	3	3	3
R5	10	3	3	1	1	1
R6	75	3	3	1	1	1
R7	24	3	1	1	1	1
R8	2	3	3	3	3	3
R9	294	9	9	3	3	3
R10	392	9	9	3	3	3
R11	168	9	9	3	3	1
Total weight		8,316	8,294	2,998	3,062	2,726
Relative weight		0.3275	0.3266	0.1181	0.1206	0.1073
Priority		1	2	4	3	5

Source(s): The authors’ own work

Table 8

Prioritizing demand risk MTG approaches

SCR items	Importance	MTG10	MTG11	MTG12	MTG13	MTG14
R23	160	1	3	3	3	3
R24	42	3	9	9	3	1
R25	48	3	9	9	3	9
R26	216	1	9	9	1	9
R27	245	1	3	9	3	9
R28	30	3	9	9	1	9
R29	280	1	9	9	1	3
R30	140	1	9	9	9	9
Total weight		1,401	8,019	9,489	3,271	7,473
Relative weight		0.0472	0.2704	0.3200	0.1103	0.2546
Priority		5	2	1	4	3

Source(s): The authors’ own work

Table 9

Prioritizing process risk MTG approaches

SCR items	Importance	MTG6	MTG7	MTG8	MTG9
R12	256	3	9	9	9
R13	168	3	3	9	3
R14	96	1	1	1	9
R15	135	3	9	1	9
R16	48	1	1	3	1
R17	40	1	1	9	3
R18	72	1	1	9	1
R19	42	1	1	3	3
R20	45	1	1	3	1
R21	486	3	3	1	9
R22	336	1	1	3	3
Total weight		3,814	5,350	6,954	6,304
Relative weight		0.1381	0.1996	0.2519	0.3868
Priority		4	3	2	1

Source(s): The authors’ own work