Evaluating supply chain performance measurement system (SCPMS) lifecycle during unexpected events

ABSTRACT

Supply chain management is recognized as a crucial element in boosting organizational performance and competitiveness. However, the COVID-19 crisis has demonstrated that many corporations were unprepared and lacked a recovery strategy, which led to significant supply chain disruptions. Hence, the purpose of this study is to evaluate the Supply Chain Performance Measurement System (SCPMS) lifetime under unforeseen situations, particularly in developing nations like Egypt, and its relevance during the pandemic and post-pandemic periods. A systematic questionnaire was used to gather data from 100 manufacturing firms (supply chain and retailers) with large business volume who provided a total of 562 questionnaires. The findings indicated that there were four main measurement systems: SCPMS Design, SCPMS Implementation, SCPMS Use, and SCPMS Review. The results of the AHP method found that the SCPMS implementation was the most important system, while the least important was SCPMS design.

KEYWORDS:

• COVID-19
• Egypt
• post pandemic
• performance measurement system
• supply chain

1. Introduction

The concept of supply chain management (SCM) is growing in popularity as competition shifts from enterprises to supply chains (Duong et al., 2019). SCM seeks to enhance the sourcing of raw materials, production, and distribution of goods and services for consumers (Frankel et al., 2014). Consequently, implementing the SCM practices successfully offers chances to enhance organizational performance (OP) throughout the supply chain (Wolf, 2014). The improvement of OP and competitiveness in today’s economic environment is significantly influenced by SCM (Karamouz et al., 2021).

Various SCM studies have been carried out in a variety of industries, including the automotive (Blos et al., 2009; Zhu et al., 2007), pharmaceutical (Papalexi et al., 2016), toy (Wong et al., 2005), apparel/textile (Abylaev et al., 2014), chemical (Foerstl et al., 2010), telecommunication (Reyes et al., 2002), agriculture/food (Dani & Deep, 2010), aerospace (Sinha et al., 2004), electronics (Blos et al., 2009), construction (Saad et al., 2002), facilities management services (Noor & Pitt, 2009), healthcare (I. Ali & Kannan, 2022), food industry (Mastos & Gotzamani, 2022), etc. Lately, digitalized supply chains, including Internet of Things (IoT), cloud computing, and information system integration, have recently been developed in response to industry 4.0 (I4.0) requirements to improve end-to-end supply chain operations (Bigliardi et al., 2022; Chauhan et al., 2023; Hofmann et al., 2019; Khourshed et al., 2023; Pournader et al., 2021; Yalcin et al., 2020).

Like how studies of different aspects of SCM are frequently centered with developed countries and the interactions with the developing economies as sources of supplies and applied also to some developing countries like China (Zhu et al., 2007), Brazil (Blos et al., 2009; Diniz & Fabbe-Costes, 2007), Taiwan (W. S. Chow et al., 2008), and Egypt (Attia, 2023; Hanna et al., 2021).

Manufacturing organizations are therefore under tremendous pressure to pursue operational excellence and to improve their performances to reduce their costs and provide products of higher quality in the shortest lead times as the modern market becomes more and more competitive on a global scale (Belekoukias et al., 2014). This is because of the complexity of supply chains, trading of goods and services between different countries, and the number of participating companies increase supply risks (Junior et al., 2021). Members of the supply network must not only ensure that risk is visible but also include the obtained data in their risk management strategies as the capacity to recognize and manage risks rises with supply chain transparency and visibility in making decisions in management (Chaudhuri et al., 2020). Supply chain risk management calls for coordinated and cooperative efforts of all supply chain stakeholders to reduce vulnerability, increase robustness and resilience, and maintain profitability and continuity (Baryannis et al., 2019). At the same time, Bathaee et al. (2023) demonstrate that the design costs of the entire supply chain network rise as the environmental effects decrease, and the social effects rise.

Supply chain researchers who have voiced worries about the hazards of pandemics have long warned about the fragility of the global supply chain system, which are oblivious of the ubiquitous sorts of risks that exist in supply chains (SCs) and are hidden from most observers (Nascimento et al., 2021). The coronavirus disease 2019 (COVID-19) crisis has severely hampered global supply chains, restricting access to markets and decreasing the availability of materials. World trade has been severely impacted since February 2020 (WTO, 2020). Stakeholders must now manage their SCs more skillfully due to new regulations, altering consumer preferences, and labor limits (Cohen, 2020). Handfield et al. (2020), also noticed that the corona virus is having an impact on both upstream and downstream flows of material in the supply chain. Junior et al. (2021) found that COVID-19 did not have a significant impact on SCs, but in a matter of days, the effects of COVID-19 were felt throughout the supply except for a few countries like New Zealand, Taiwan, South Korea, Australia, Germany, Finland, Norway, and Singapore that kept strategic stockpiles to deal with health emergency circumstances to fight the epidemic (Wang et al., 2020).

The COVID-19 is a specific type of disruption that has significantly changed the living conditions and preferences of consumers. The entire SC sourcing, procurement, production, and delivery processes have been changed in addition to the effects on consumers. Therefore, companies must implement several strategies to successfully meet stakeholders’ needs and demands throughout the pandemic and prepare them for post-pandemic conditions (Sharma et al., 2021). According to existing research, businesses have adopted a variety of tactics for handling interruptions, including stockpiling, diversification, crediting backup providers, emergency sourcing, buffer stock, reserve capacity, flexibility, and cooperative tactics (Chowdhury et al., 2020).

The organizations are using reactive methods to survive and carry on throughout the outbreak, but these methods won’t last in the long run. A profitable company must re-evaluate its network, dependencies, and SC structure to prepare for the unexpected and uncertain world that lies ahead (Sharma et al., 2021). Ivanov (2020) emphasizes the influence of pandemic outbreak SCs by producing protracted delays that leave businesses with many uncertainties. The consequences of the pandemic have had a considerable influence on supply networks (Frederico, 2021; Maharjan & Kato, 2023). The primary issues making dealing with pandemic disruption challenging have been poor information management and SCs with many intermediaries (Sharma et al., 2021). International firms were not prepared for such an occurrence and lacked any recovery planning, as the pandemic has shown (Sarkis et al., 2020). Maharjan and Kato (2023) added that despite having a specific amount of preparedness, organizations with different attributes, such as industry type and organization size, have varying levels of resilience preparedness, response, and future plans. Hence, to restore supply chains’ performance in the wake of the COVID-19 pandemic, the new strategy, which calls for a thorough understanding of the environment and the establishment of clear strategic objectives across the various perspectives that must be considered in the scope of the supply chain, is crucial (Frederico, 2021).

The lines above affirmed the idea that there is a field to research SC during unforeseen events like COVID-19, particularly in underdeveloped countries such as Egypt. Egypt’s interest in SCM research has increased significantly in recent years because of growing worries regarding the increase in population and the disruptions that can happen at many points of the SC. Egypt, a nation with a sizable population and a diverse economy, has unique characteristics that necessitate research into and evaluation of the SCPMS lifecycle during unplanned events. This will allow the manufacturing sector to better understand the challenges the nation’s SC faces and develop strategies to increase resilience, reduce risks, and improve overall performance. As well, Egypt’s SC network and economy is extensive and intricate because to its population of over 100 million people. The SC includes several industries, including manufacturing, transportation, tourism, agriculture, and retail. Disruptions can happen at many points of the SC during unforeseen occurrences, like as the COVID-19 pandemic, which can have an impact on performance and effectiveness overall.

Therefore, the purpose of this study is to evaluate the Supply Chain Performance Measurement System (SCPMS) lifetime under unforeseen situations like COVID-19, to determine whether it was useful during the pandemic in terms of providing a framework for survivors to function and survive as well as to be ready for post-pandemic conditions. The author is specially interested with the manufacturing companies of supply chain and retailers with large business volume in the Egyptian context.

2. Literature review

An earlier study showed SCM as a significant factor impacting company performance (Kannan and Tan, 2005). SCM is considered as a management tool that supports organisational stability, expansion, and profitability (Ou et al., 2010). The impact of SCM on company performance in the manufacturing sector has been extensively studied over the past 20 years (Li et al., 2006); in which, Financial and non-financial variables must both be considered when evaluating performance (C. W. Chow & Van Der Stede, 2006; Karamouz et al., 2021). Customer satisfaction and company performance are predicted to increase because of stronger ties between upstream suppliers and downstream clients after a successful SCM deployment (Ou et al., 2010). However, Liu and Liu (2021) showed that all of warehouses are still built near to suppliers; even though the organization is expanding facilities to reach more international consumers.

According to Hassangaviar et al. (2022), SCM is regarded as a crucial indicator to invest significant resources in supply acquisition, production, and goods distribution to survive in the market and be capable of responding to their customers’ needs as quickly and effectively as possible because of growing innovation and competitiveness in global markets of products. Where, Asree et al. (2018), examined the effectiveness of innovation in relation to SC responsiveness and strategic SC collaboration, as well, the impact of strategic cooperation as a mediating construct between SC responsiveness and innovation performance. They found that SC responsiveness and SC collaboration; both directly and affect innovation performance, and SC collaboration that serves as a mediator, has a greater impact on innovation performance.

A performance measurement system (PMS) is defined as ‘a system for tracking performance metrics’ (Neely et al., 1995). And it is essential to the implementation of a corporation; as it helps to translate strategy into actions and desired results, track progress, provide feedback, and encourage workers through rewards and penalties (C. W. Chow & Van Der Stede, 2006; Karamouz et al., 2021). Moreover, the measuring system must be based on the organizational strategy, assist in putting the plan into action, and provide feedback on whether the organization is ‘on track’ or whether adjustments in course are required, organizations also require a balanced selection of measurements (Hulthén et al., 2016). The European Foundation for Quality Management (EFQM), Balanced Scorecard (BSC) (Bhagwat & Sharma, 2007; Brewer & Speh, 2000; Frederico, 2021; Reefke et al., 2013), Activity Based Costing (ABC), and Supply Chain Operation are just a few of the models that are available for measuring performance (Karamouz et al., 2021).

Furthermore, reference is made to the Framework for Logistics Research (FLR), the Global Supply Chain Forum (GSCF), the Strategic Audit Supply Chain (SASC), the French Logistics Association (ASLOG), the Resource Output Flexibility (Beamon, 1999), and the process based SCPMSs (Chan et al., 2003). Additionally, maturity models for SCs have been produced (Frederico, 2017); maturity models have been created to evaluate a particular domain of the company based on a set of criteria. Later, in a study by Reddy et al. (2019), it was determined that the SCOR model and BSC were the most utilized PMS frameworks to gauge supply chain performance (SCP). Also, Tansakul et al. (2022), created an adaptive SCP measuring model since the performance of suppliers has a significant impact on the entire SCP.

Systems for measuring the performance of multi-business supply networks and simplifying supply chain planning are known as supply chain performance measurement systems (SCPMS) (Gunasekaran et al., 2004; Hald & Ellegaard, 2011; Maestrini et al., 2018; Neely, 2005). The literature has published a few PMS for supply chains, including those by R. I. Van Hoek (1998), Beamon (1999), and Holmberg (2000). From the standpoint of the life cycle, Maestrini et al. (2017) provided a theory-testing method for the other understudied components of SCPMSs as well as an exploratory/theory-building strategy for the supplier PMSs (i.e. customer PMSs, multi-tier SCPMSs and many-to-many SCPMSs). Later, Maestrini et al. (2018) established a conceptual framework of SCPMS lifecycle (highlighting important activities of the design, implementation, usage, and review phases) and looked at how various SCPMS players see the system as a whole. Contrary to most of the empirical research, this one focused on the standpoint of a single firm in the SC and disregarded the perspective of other entities. The SCPMS should assist in implementing the SC strategy, and the scope of the analysis could include SC relationships, SC procedures, and status information about SC partners (Giannakis, 2007; Koh et al., 2016). OP will be influenced by a single SC practice in a specific way. However, because it is integrated into a system where several other practices are carried out, it will interact with other practices (Duong et al., 2019).

Moreover, Fatemi et al. (2022) drew attention to the fact that SC managers constantly search for the best way to respond to the volume and type of communication across different SCM levels due to some constraints, like production capacity and storage capacity, and objectives, like cost reduction and increasing profits. As well, according to Jamalnia et al. (2023), focal firms that fail to act in response to stakeholder pressure to ensure sub-supplier sustainability compliance run the risk of experiencing both immediate and long-term consequences. Finally, Govindan et al. (2022), stated that SC can benefit from I4.0 technologies and concepts that can improve certain SC performance measures. Hence, Govindan et al. (2022), presented a framework for the usage of I4.0 technologies to identify the potential SCPM that includes the dimensions of Procurement 4.0, Manufacturing 4.0, Logistics 4.0, and Warehousing 4.0. Also, Alamsjah and Yunus (2022) explored the key determinants of SC4.0 maturity in the context of a developing country (Indonesia) and found that SC ambidexterity emphasizing on innovation positively influences the companies’ agility and SC4.0 maturity levels, and SC agility partially mediates SC ambidexterity. As well, Mashayekhy et al. (2022) declared that upgrading a supply chain into an integrated supply chain 4.0 is beneficial. Hangl et al. (2022), added that algorithms and the Internet of Things (IoT) are the two key areas of AI in SCM. Change management, current technology constraints, and human acceptance of these methods are the key obstacles to AI adoption in SCM. The primary motivations for AI in SCM are cost savings, efficiency gains, and the reduction of time and resources. Human-robot collaboration is the primary social component. As a result, fewer workers will be needed in the future, which will influence many current Occupations, particularly in low-income areas.

Therefore, to compete in the current unpredictable environment, manufacturing businesses need to change their settings (M. Ali et al., 2021; Napoleone & Prataviera, 2020). The attempts undertaken by academics to comprehend SCMPs in certain industrial and national contexts are collectively shown in a few research. Despite this, little research has been done on SCM in relation to the measures manufacturing businesses in developing nations must take to make their supply chains a reliable competitive vehicle for their development. Therefore, due to the country’s unique economic, political, and geographic characteristics as well as its current situation of expanding the manufacturing sector, Egypt’s supply chains differ from all others previously evaluated. Supply networks are starting to demonstrate how the chain’s structure affects how much information its participants disclose about their internal practices and performance (Gualandris et al., 2021). Due to its expanding economy, Egypt has a unique setting that demands more study. It is justified to investigate the SCMPs of the Egyptian manufacturing sector separately for the SCM theory to be able to comprehend its distinctive features and thereby contribute to its application.

Hence, according to the studies described above, the SCPMS reveals certain criticalities while also offering some benefits. Improvements in SC processes and SCM procedures, better information overload avoidance, and SC strategy control and communication have allegedly been among the benefits (Bhagwat & Sharma, 2007; Gunasekaran et al., 2004). However, as the outcomes of SCPMS are either considered theoretically or in an academic setting, there is not much concrete proof of the benefits and drawbacks of this method (e.g. Beamon, 1999; Brewer & Speh, 2000; Maestrini et al., 2018; R. I. Van Hoek, 1998). The body of existing research still has a limited amount to say about how to make SCPMS adoption effective. The development and deployment of novel research during the COVID-19 context have been highlighted by certain researchers (De Sousa Jabbour et al., 2020; R. Van Hoek, 2020). Additionally, Maestrini et al. (2018) advise discussing each stage of the SCPMS lifespan in equal detail. Considering this and having all dimensions discussed in previous studies, the author modified the SCPMS to include design, implementations, use, and review.

Accordingly, the dimensions in each of the assigned factors are reviewed in literature. As a result, the goal of this study is to evaluate the usefulness of SCPMS during unpredictable events like COVID-19 and in developing countries like Egypt (As shown in Table 1). Due of this, Junior et al. (2021) verified that one should consider the realities of each company, market, and nation due to the risks and repercussions would depend on how developed each company’s supply chain is as the complexity of the surroundings they are immersed into, both; inside and outside.

Table 1. SCMPS in the Egyptian context.

SCPMS design: SCPMS lifecycle information

(1) The system is well designed by considering the following metric sets (performance measures, targets, consequences)

(2) There are metric sets such as (performance measures, targets, consequences)

(3) All the company functions are all involved in designing the system

(4) The external factors are involved in designing the system

(5) The contractual arrangements are related to SCPMS and are in place

(6) The system is very well implemented

(7) The company calculates all the metrics

(8) The company reported the measured metrics

(9) There is an information system architecture that implements the SCPMS

(10) There are feedbacks on the performances that are achieved

(11) There are incentives and disincentives

(12) There is a debate on the performances that are reported

(13) The system is being constantly reviewed

(14) Targets are constantly controlled and reviewed

SCPMS Implementation: The role of the SCPMS within the organization

(15) SCPMS are beneficial

(16) The general perception of SCPMS in the organization is acknowledged

(17) SCPMS is used

(18) SCPMS supports planning operations

(19) The type of performance reported is satisfactory

(20) The way of the system that is implemented is satisfactory

SCPMS use: Relationship specific attributes

(21) There is commitment towards the relationships with the specific SC partner

(22) There is a higher level of mutual trust in the relationships with the specific SC partner

(23) There is collaboration in common issues with the specific SC partner

(24) For Suppliers only: There is good relationship with a Retailer before SCPMS adoption

(25) For Suppliers only: There is better relationship with a Retailer after SCPMS adoption

(26) For Suppliers only: The SCPMS adoption influences Suppliers’ opinion towards the retailer

(27) For Retailer only: There is a very good relationship with suppliers such as (logistics providers and goods manufacturers before SCPMS adoption

(28) For Retailer only: There is better relationship with suppliers after SCPMS adoption

(29) For Retailer only: The SCPMS adoption influences Retailer’s opinions towards the suppliers

SCPMS review: benefits and criticalities

(30) The SCPMS improved the operational performance

(31) The SCPMS affects the relationships with external partners

(32) There are achievable benefits from the SCPMS adoption

(33) There is perceived usefulness of the information shared

(34) There are criticalities or disadvantages adopting the SCPMS

(35) For suppliers: Suppliers are satisfied with the SCPMS used from the retailer

Source: Maestrini et al. (2018), modified by author.

One of the case studies applied for SCPMS is that of AA leather SME in Indonesia, where supply chain performance was enhanced through the design measured using the SCOR model (Kusrini et al., 2019).

3. Research methodology

To review the literature review, this study reviewed articles, survey reports, books, and doctoral theses from multiple data sources (Tranfield et al., 2003), including Emerald Insight and Science Direct from publication date 2000 to 2023, using the following keywords: COVID-19; framework; post pandemic; performance measurement system; supply chain. This research could be classed as exploratory and deductive because its goal is to evaluate the SCPMS lifetime under unforeseen situations like COVID-19 particularly in developing nations like Egypt, to determine whether it was useful during the pandemic in terms of providing a framework to function and survive as well as to be ready for post-pandemic conditions. The analyzes’ experimental unit is AHP technique, this method integrates the procedures of assessing alternatives and aggregating them to locate the most pertinent ones. The method is used to rank a set of alternatives or to choose the best option from a set of alternatives (Golden et al., 1989). It utilizes a questionnaire to help the decision makers to take the appropriate decision based on the importance of SCPMS lifetime. It also helps assessing the different dimensions of each factor, where a guide could be given to the decision makers and managers as to how build up their policies and procedures to enhance SCPMS (Zhou et al., 2019).

In order to support the internal validity, interviews with 10 practitioners were conducted then deleted unsuitable questions, and meeting notes were forwarded to the interviewees for confirmation to strengthen the accuracy of the acquired empirical data (Yin, 2015). Then, data was collected from 30 experts from Egyptian manufacturing organizations to test the reliability and validity of the questionnaire. Finally, survey data was chosen for analytical validation, a systematic questionnaire was used to gather the data from 100 industrial companies in Egypt, and it was sent by email and Google Forms. By including several informants from each firm, the validity of the research’s conclusions has been improved. The supply chain and retailers provided a total of 562 questionnaires (two or three for each of the 100 organizations that participated in the study).

A retailer serving as the focal company and funding the SCPMS provided data through a questionnaire at some point between December 2021 and April 2022. (First-tier). These players typically work with several different product manufacturers, managing a wide range of logistics tasks (from transportation to warehouse management and delivery planning); they are classified as second-tier SC players.

As the study took place and data was collected in the period of pandemic, the responses were highly influenced with the event while responding to the SCPMS statements. This means that the responses could have been varying if they were collected before that period.

Logistics providers serve as an intermediary between product manufacturers and retailers. Two sections make up this questionnaire: Among the demographic information requested in the first section are participant name (optional), Gender, age, and the kind of organization. The second section of the survey aims to gauge how much the company considers and adopts the SCPMS lifecycle milestones during COVID, the relationship among different partners, the benefits related to the SCPMS adoption, and the criticalities that are related to SCPMS adoption; using the following scales (1) strongly disagree and (5) strongly agree. Table 2 lists the methodological approach steps in along with their respective goals, data sources, and results.

Table 2. The different steps in the methodological approach.

Steps	Literature review	Interview	Pilot study	Questionnaire
Purpose	In order to create a framework for surviving and functioning during the pandemic and be ready for post-pandemic situations, it is important to examine the SCPMS lifecycle during unforeseen events like COVID-19, particularly in developing nations like Egypt.	To discuss the SCPMS lifetime under unforeseen situations like COVID-19 particularly in developing nations like Egypt, in order to determine whether it was useful during the pandemic in terms of providing a framework for survivors to function and survive as well as to be ready for post-pandemic conditions.	To test the reliability and validity of the questionnaire.	To assess the degree to which the SCPMS lifecycle steps are considered and implemented in the organization during COVID, as well as the relationships between the various partners, the advantages of SCPMS adoption, and the criticality of SCPMS adoption.
Data Source	Literature review on relevant literature to SC in various industries especially the manufacturing industry.	Semi-structured interviews with 10 practitioners were conducted to support the internal validity.	The data was collected from 30 experts from Egyptian manufacturing organizations.	A total of 562 questionnaires (two or three for each of the 100 Egyptian manufacturing organizations that participated in the study).
Outcome	This research adopted the Maestrini et al. (2018) Framework to analyse the SCPMS lifespan during unexpected events like COVID-19 in Egypt.	Inappropriate and unsuitable questions were eliminated, and only those that were pertinent to the study’s goal were asked.	Finding that the questionnaire is reliable and valid so distributed to the rest of the companies.	Finding that the supply chain performance measurement system implementation was the most important system as it takes the first rank, while, the second rank went to supply chain performance measurement system use, the third rank in importance was supply chain performance measurement system review, and the final one was supply chain performance measurement system design.

4. Results and findings

4.1. Descriptive statistics of responses

Table 3 provides some insight of the respondents, where most respondents have Years of Experience greater than 10 years (n = 73.1%). In addition, most respondents are in the first line of management (n = 70%), while they are almost equal in Gender, where the number of male respondents (n = 50.5%) is approximately equal to the number of female respondents (n = 49.5%).

Table 3. Descriptive statistics for respondents.

	Frequency	Percent %	Total
Gender
Male	284	50.5%	562
Female	278	49.5%
Years of experience
Less than 5	66	11.8%	562
5 – Less than 10	85	15.1%
10 and more	411	73.1%
Occupation
First Line of Management	393	70.0%	562
Middle Management	115	20.4%
Top Management	54	9.6%

Table 4 shows the mean values computed, where only 12 dimensions out of the 14 dimensions were selected from SCPMS Design for the next stage of the analysis, as two factors were excluded because their mean was below average. In addition, all six dimensions of SCPMS Implementation were selected. Moreover, only six dimensions out of the nine dimensions from SCPMS Use were selected, as three factors were excluded because their mean value was below average. Finally, only three dimensions out of the six dimensions from the SCPMS Review were selected, as three factors were excluded because their mean value was below average. After filtering the main important dimensions for the criteria are further analyzed using the AHP method for analysis.

Table 4. Descriptive statistics for the SCPMS lifecycle.

	Mean	Std. Deviation
SCPMS design: SCPMS lifecycle information
D1	4.0711	0.65450
D2	4.0680	0.67348
D3	4.0185	0.65338
D4	4.0046	0.66884
D5	3.9722	0.68768
D6	4.0031	0.67918
D7	3.9629	0.69620
D8	3.9104	0.66863
D9	3.8995	0.68200
D10	3.8640	0.69500
D11	3.7960	0.68268
D12	3.7218	0.65827
D13	2.1932	0.63545
D14	2.1097	0.71604
SCPMS Implementation: The role of the SCPMS within the organization
Im1	4.6754	0.63421
Im2	4.6631	0.65192
Im3	4.6692	0.65034
Im4	4.6012	0.71160
Im5	4.6121	0.69231
Im6	4.6399	0.66896
SCPMS use: Relationship-specific attributes
Use1	4.4420	0.57229
Use2	4.4328	0.61057
Use3	4.4977	0.51562
Use4	4.3462	0.59467
Use5	4.4467	0.57274
Use6	4.4544	0.57431
Use7	1.9815	0.53337
Use8	1.9675	0.53992
Use9	1.9753	0.54176
SCPMS review: Benefits and criticalities
R1	4.3338	0.52180
R2	4.0386	0.64414
R3	4.2133	0.46647
R4	1.9985	0.52048
R5	1.9907	0.51891
R6	2.0649	0.76015

4.2. Application of AHP to assess the SCPMS lifecycle during unexpected events

This section shows how to apply AHP to assess the SCPMS lifecycle during unexpected events like COVID-19 as following:

4.2.1. Selection of SCPMS

Four main measurement systems will be considered together with their factors. The four main Supply Chain Performance Measurement Systems (SCPMS) are:

• SCPMS Design: SCPMS Lifecycle Information.

• SCPMS Implementation: The Role of the SCPMS within the Organization.

• SCPMS Use: Relationship-Specific Attributes.

• SCPMS Review: Benefits and Criticalities.

On the other hand, the 35-supply chain performance measurement systems included in the main four measurement systems are listed in Table 5. Then, according to the equation, the entries of the decision matrix ‘dij’ along with the weights of the criteria ‘wi’ are used to calculate the relative significance or preference of each element using the relative importance of each choice.

(1) $\mathit{P}=\mathit{D}.\mathit{W}.\mathit{or}{P}_j=\sum _{\mathit{j}=1}^n{d}_{\mathit{ij}}{w}_j\mathit{i}=1,2,3\dots ,\mathit{m}$(1)

Table 5. Supply chain performance measurement systems included in the analysis.

Measurement Systems	Code	Factors
SCPMS Design: SCPMS Lifecycle Information	D1	The system is well designed by considering the following metric sets (performance measures, targets, consequences).
	D2	There are metric sets such as (performance measures, targets, and consequences).
	D3	All the company functions are involved in designing the system.
	D4	The external factors are involved in designing the system.
	D5	The contractual arrangements are related to SCPMS and are in place.
	D6	The system is very well implemented.
	D7	The company calculates all the metrics.
	D8	The company reported the measured metrics.
	D9	There is an information system architecture that implements the SCPMS.
	D10	There is feedback on the performances that are achieved.
	D11	There are incentives and disincentives.
	D12	There is a debate on the performances that are reported.
SCPMS Implementation: The Role of the SCPMS Within the Organization	Imp1	SCPMS are beneficial.
	Imp2	The general perception of SCPMS in the organization is acknowledged.
	Imp3	SCPMS is used.
	Imp4	SCPMS supports planning operations.
	Imp5	The type of performance reported is satisfactory.
	Imp6	The way the system is implemented is satisfactory.
SCPMS Use: Relationship-Specific Attributes	Use1	There is a commitment toward the relationships with the specific SC partner.
	Use2	There is a higher level of mutual trust in the relationships with the specific SC partner.
	Use3	There is collaboration on common issues with the specific SC partner.
	Use4	For Suppliers only: There is a good relationship with a Retailer before SCPMS adoption.
	Use5	For Suppliers only: There is a better relationship with a Retailer after SCPMS adoption.
	Use6	For Suppliers only: The SCPMS adoption influences Suppliers’ opinions towards the Retailer.
SCPMS Review: Benefits and Criticalities	R1	The SCPMS improved operational performance.
	R2	The SCPMS affects the relationships with external partners.
	R3	There are achievable benefits from the SCPMS adoption.

The alternative with the highest weight value should be taken as the best alternative.

Table 6 displays an accepted pairwise comparison matrix of measurement systems provided by one of the experts included in the analysis. According to this expert, SCPMS Implementation is given the most weight measurement system, followed by systems SCPMS Use, SCPMS Review, and finally, SCPMS Design.

Table 6. A pairwise comparison matrix for main four measurement systems.

Criterion	SCPMS (D)	SCPMS (Im)	SCPMS (Use)	SCPMS (R)	GM	W
SCPMS (D)	1	¼	2/7	2/5	0.414872	0.092758
SCPMS (Im)	3 8/9	1	1	1 ½	1.558073	0.348359
SCPMS (Use)	3 1/3	1	1	1	1.36014	0.304105
SCPMS (R)	2 5/8	2/3	1	1	1.139521	0.254778
Sum	10.85	2.92	3.28	3.92	4.472606	1.000

After that ℷmax, the Consistency Index (CI), Consistency Ratio (CR), and Random Consistency value (RC) must be calculated through the summation of multiplying the total value of the pairwise comparison with each one of the weights of the system.

(2) $\mathit{\lambda max}=4.016610619,\mathit{CI}=\frac{4.016610619-4}{4-1}=0.005536873,=0.90\mathit{for}\mathit{n}=4,\mathit{CR}=\frac{0.005536873}{0.90}=0.006152081$(2)

With this CR value, the determination of pairwise is declared valid with a CR value < 0.1. Since CR is less than 0.1, the values in Table 7 are acceptably consistent. After checking the consistency for the pairwise compression matrix, the decision matrix is obtained. It could be observed that the second system is considered the most important one as it ranks #1 through the above computation, then the third one, after that the fourth system, and finally the first one takes the last place in the ranking.

Table 7. Decision matrix for main four measurement systems.

Criterion	CR	Rank
SCPMS (D)	0.092758	4
SCPMS (Im)	0.348359	1
SCPMS (Use)	0.304105	2
SCPMS (R)	0.254778	3

Figure 1 illustrates the weight of each individual system and demonstrates that the SCPMS Implementation system is at the top of the list, while the SCPMS Use system comes in second place, the third one is SCPMS Review system, and finally, SCPMS Design is the last system in the rank.

Figure 1. Weight of main four measurement systems (according to Table 4).

Table 8 displays an accepted pairwise comparison matrix of SCPMS Design System Dimensions provided by one of the experts included in the analysis. The weight of the individual system. According to this expert, D3 is given the most weight, followed by D1, D4, D10, D7, D11, D8, D9, D2, D5, D6, and finally, D12.

Table 8. A pairwise comparison matrix for SCPMS design.

Dim	D1	D2	D3	D4	D5	D6	D7	D8	D9	D10	D11	D12	GM	W
D1	1.00	4.85	1.00	1.39	4.98	5.33	1.96	2.76	3.28	1.91	2.31	7.24	2.6123	0.177
D2	0.21	1.00	0.21	0.30	1.00	1.12	0.44	0.54	0.66	0.44	0.52	1.41	0.5473	0.037
D3	1.00	4.85	1.00	1.39	4.98	5.33	1.96	2.76	3.28	3.28	2.35	7.24	2.7363	0.186
D4	0.72	3.33	0.72	1.00	3.79	3.97	1.41	2.14	2.45	1.35	1.75	5.28	1.9148	0.130
D5	0.20	1.00	0.20	0.26	1.00	1.02	0.45	0.50	0.68	0.43	0.52	1.29	0.5289	0.036
D6	0.19	0.89	0.19	0.25	0.98	1.00	0.38	0.50	0.55	0.38	0.47	1.18	0.4855	0.033
D7	0.51	2.27	0.51	0.71	2.23	2.61	1.00	1.59	1.79	0.95	1.19	3.85	1.3292	0.090
D8	0.36	1.85	0.36	0.47	2.00	2.00	0.63	1.00	1.11	0.57	0.74	2.64	0.9164	0.062
D9	0.31	1.52	0.31	0.41	1.48	1.82	0.56	0.90	1.00	0.49	0.65	2.23	0.7861	0.053
D10	0.52	2.29	0.52	0.74	2.32	2.62	1.05	1.76	2.04	1.00	1.29	4.05	1.3978	0.095
D11	0.43	1.93	0.42	0.57	1.91	2.12	0.84	1.35	1.53	0.78	1.00	3.17	1.1099	0.075
D12	0.14	0.71	0.14	0.19	0.78	0.85	0.26	0.38	0.45	0.25	0.32	1.00	0.3660	0.025
SUM	5.59	26.47	5.58	7.67	27.44	29.80	10.94	16.18	18.81	11.82	13.12	40.59	14.7305	1.000

After that ℷmax, the Consistency Index (CI), Consistency Ratio (CR), and Random Consistency value (RC) must be calculated through the summation by multiplying the total value of the pairwise comparison with each one of the weights of the system.

(3) $\mathit{\lambda max}=12.08369,\mathit{CI}=\frac{12.08369-12}{12-1}=0.007608,\mathit{\hspace{0.17em}}=1.54\mathit{for}\mathit{n}=12,\mathit{CR}=\frac{0.007608}{1.54}=0.004941$(3)

With this CR value, the determination of pairwise is declared valid with a CR value <0.1. Since CR is less than 0.1, the values in Table 9 are acceptably consistent. After checking the consistency for the pairwise compression matrix, the decision matrix is obtained. It could be observed that the third dimension is considered the most important one as it comes in the first rank through the above computation, then the first dimension, after that the fourth dimension, then the tenth dimension, the seventh dimension, the eleventh dimension, the eighth dimension, the ninth dimension, the second dimension, the fifth dimension, the sixth dimension, and finally the twelfth dimension takes the last place in the ranking.

Table 9. Decision matrix for SCPMS design.

Criterion	CR	Rank
D1	0.177	2
D2	0.037	9
D3	0.186	1
D4	0.130	3
D5	0.036	10
D6	0.033	11
D7	0.090	5
D8	0.062	7
D9	0.053	8
D10	0.095	4
D11	0.075	6
D12	0.025	12

Figure 2 illustrates the weight of each one of SCPMS Design system and demonstrates that the ‘D3’ is at the top of the list, while the ‘D1’ comes in second place, the third one is ‘D4’, followed by ‘D10’, ‘D7’, ‘D11’, ‘D8’, ‘D9’, ‘D2’, ‘D5’, ‘D6’, and finally, ‘D12’ is the last system in the rank.

Figure 2. Weight of SCPMS design system (according to Table 9).

Table 10 displays a pairwise comparison matrix of SCPMS Implementation System Dimensions provided by one of the experts included in the analysis. According to this expert, ‘Imp2’ is given the most weight, followed by ‘Imp3’, ‘Imp4’, ‘Imp5’, and finally, ‘Imp1’ and ‘Imp6’.

Table 10. A pairwise comparison matrix for SCPMS implementation.

Dimensions	Imp1	Imp2	Imp3	Imp4	Imp5	Imp6	GM	W
Imp1	1.00	0.15	0.20	0.27	0.43	1.00	0.390489	0.051046
Imp2	6.55	1.00	1.00	1.82	2.95	6.55	2.477417	0.323858
Imp3	5.07	1.00	1.00	1.00	2.41	5.07	1.989667	0.260097
Imp4	3.66	0.55	1.00	1.00	1.78	3.66	1.534758	0.200630
Imp5	2.32	0.34	0.41	0.56	1.00	2.32	0.866888	0.113323
Imp6	1.00	0.15	0.20	0.27	0.43	1.00	0.390489	0.051046
Sum	19.603	3.192	3.809	4.932	9.008	19.603	7.649709	1

After that ℷmax, the Consistency Index (CI), Consistency Ratio (CR), and Random Consistency value (RC) must be calculated through the summation of multiplying the total value of the pairwise comparison with each one of the weights of the system.

(4) $\mathit{\lambda max}=6.027381,\mathit{CI}=\frac{6.027381-6}{6-1}=0.005476,\mathit{\hspace{0.17em}}=1.24\mathit{for}\mathit{n}=6,\mathit{CR}=\frac{0.005476}{1.24}=0.004416$(4)

With this CR value, the determination of pairwise is declared valid with a CR value <0.1. Since CR is less than 0.1, the values in Table 11 are acceptably consistent. After checking the consistency for the pairwise compression matrix, the decision matrix is obtained. It could be observed that the second dimension is regarded as being the most significant because it appears in the first rank through the above computation, then the third one, after that the fourth dimension, then the fifth dimension, and finally the first one and sixth one takes the last place in the ranking.

Table 11. Decision matrix for SCPMS implementation.

Criterion	CR	Rank
Imp1	0.051046	5
Imp2	0.323858	1
Imp3	0.260097	2
Imp4	0.200630	3
Imp5	0.113323	4
Imp6	0.051046	5

Figure 3 illustrates the weight of each one of SCPMS Implementation system and demonstrates that the ‘Imp2’ is at the top of the list, while the ‘Imp3’ comes in second place, the third one is ‘Imp4’, followed by Imp5 in the fourth place, and finally, ‘Imp1’ and ‘Imp6’ are the last system in the rank.

Figure 3. Weight of SCPMS Implementation system (according to Table 11)

Table 12 displays an accepted pairwise comparison matrix of SCPMS Use System Dimensions provided by one of the experts included in the analysis. According to this expert, Use2 is given the most weight, followed by ‘Use3’, ‘Use4’, ‘Use5’, and finally, ‘Use1’ and ‘Use6’.

Table 12. A pairwise comparison matrix for SCPMS use.

Dimensions	Use1	Use2	Use3	Use4	Use5	Use6	GM	W
Use1	1.00	0.15	0.19	0.26	0.44	1.00	0.38472	0.049967
Use2	6.67	1.00	1.00	1.82	2.95	6.63	2.489398	0.323319
Use3	5.26	1.00	1.00	1.00	2.41	5.26	2.013998	0.261575
Use4	3.89	0.55	1.00	1.00	1.78	3.89	1.567237	0.20355
Use5	2.26	0.34	0.41	0.56	1.00	2.26	0.859112	0.11158
Use6	1.00	0.15	0.19	0.26	0.44	1.00	0.38505	0.05001
Sum	20.079	3.188	3.795	4.898	9.032	20.045	7.699515	1

After that ℷmax, the Consistency Index (CI), Consistency Ratio (CR), and Random Consistency value (RC) must be calculated through the summation of multiplying the total value of the pairwise comparison with each one of the weights of the system.

(5) $\mathit{\lambda max}=6.023444,\mathit{CI}=\frac{6.023444-6}{6-1}=0.004689,\mathit{\hspace{0.17em}}=1.24\mathit{for}\mathit{n}=6,\mathit{CR}=\frac{0.004689}{1.24}=0.003781$(5)

With this CR value, the determination of pairwise is declared valid with a CR value <0.1. Since CR is less than 0.1, the values in Table 13 are acceptably consistent. After checking the consistency for the pairwise compression matrix, the decision matrix is obtained. It could be observed that the second dimension is deemed to be the significant one as it comes in the first rank through the above computation, then the third one, after that the fourth dimension, then the fifth one, the sixth dimension, and finally the first one takes the last place in the ranking.

Table 13. Decision matrix for SCPMS use.

Criterion	CR	Rank
Use1	0.049967	6
Use2	0.323319	1
Use3	0.261575	2
Use4	0.20355	3
Use5	0.11158	4
Use6	0.05001	5

Figure 4 illustrates the weight of each one of SCPMS Use system and demonstrates that the ‘Use2’ is at the top of the list, while the ‘Use3’ comes in second place, the third one is ‘Use4’, followed by ‘Use5’ in the fourth place, and ‘Use6’ in the fifth place, and finally, ‘Use1’ is the last system in the rank.

Figure 4. Weight of SCPMS use system (according to Table 13).

Table 14 displays an accepted pairwise comparison matrix of SCPMS Review System Dimensions provided by one of the experts included in the analysis. According to this expert, R1 is given the most weight, followed by R2, and finally, R3.

Table 14. A pairwise comparison matrix for SCPMS review.

Dimensions	R1	R2	R3	GM	W
R1	1.00	1.55	3.43	1.745253	0.51779
R2	0.64	1.00	2.11	1.108363	0.328835
R3	0.29	0.47	1.00	0.516963	0.153375
Sum	1.94	3.02	6.54	3.370579	1

After that ℷmax, the Consistency Index (CI), Consistency Ratio (CR), and Random Consistency value (RC) must be calculated through the summation of multiplying the total value of the pairwise comparison with each one of the weights of the system.

(6) $\mathit{\lambda max}=3.00283,\mathit{CI}=\frac{3.00283-3}{3-1}=0.000142,\mathit{\hspace{0.17em}}=0.58\mathit{for}\mathit{n}=3,\mathit{CR}=\frac{0.000142}{0.58}=0.000244$(6)

With this CR value, the determination of pairwise is declared valid with a CR value <0.1. Since CR is less than 0.1, the values in Table 15 are acceptably consistent. After checking the consistency for the pairwise compression matrix, the decision matrix is obtained. It could be observed that the first dimension is considered the major one because it is found in first rank through the above computation, then the second one, and finally the third one takes the last place in the ranking.

Table 15. Decision matrix for SCPMS review.

Criterion	CR	Rank
R1	0.51779	1
R2	0.328835	2
R3	0.153375	3

Figure 5 illustrates the weight of each one of SCPMS Review system and demonstrates that the R1 is at the top of the list, while the R2 comes in second place, and finally, R3 is the last system in the rank.

Figure 5. Weight of SCPMS review system (according to Table 15).

5. Discussion

Comparing with Maestrini et al. (2018), both studies ranked the implementation of a SCPMS as the most important system. However, there were some differences in the ranking of the other three systems. In this study, SCPMS use was ranked second, SCPMS review was ranked third, and SCPMS design was ranked fourth. In the article of Maestrini et al. (2018), SCPMS design was ranked second, SCPMS review was ranked third, and SCPMS use was ranked fourth. The differences in ranking may be due to the different methodologies used in the two studies. This study used the AHP method, while the article of Maestrini et al. (2018) used a case study approach. The AHP method is a quantitative method that uses pairwise comparisons to rank items. The case study approach is a qualitative method that examines a specific instance of a phenomenon. Despite the differences in ranking, both studies agree that the implementation of a SCPMS is the most important factor in ensuring the success of the system.

This is because implementation ensures that the system is used, and that the data collected is accurate and reliable. It also helps to build buy-in and support for the system among stakeholders. The article of Maestrini et al. (2018) also identifies four key phases in the lifecycle of a SCPMS. Overall, the results of this study are consistent with the results of the article of Maestrini et al. (2018). Both studies highlight the importance of implementing a SCPMS and the need to consider the lifecycle of the system when designing and implementing it.

6. Conclusion and recommendations

This research works on evaluating the SCPMS lifetime under unforeseen situations like COVID-19 particularly in developing nations like Egypt, to determine whether it was useful during the pandemic in terms of providing a framework for survivors to function and survive as well as being ready for post-pandemic conditions. In order to create a kind of framework for being ready for post-pandemic settings, this research adopted a previous framework to analyze the SCPMS lifespan during unexpected events like COVID-19 in Egypt. A questionnaire was given to participants in this study, which used quantitative research techniques. The findings indicated that there were four main measurement systems that will be considered together with their factors to achieve the main purpose of this paper. These four main measurement systems are SCPMS Design, SCPMS Implementation, SCPMS Use, and SCPMS Review, including the 35-supply chain performance measurement systems included in the main four measurement systems. The results of the AHP method found that the SCPMS implementation was the most important system as it takes the first rank, while, the second rank went to SCPMS use, the third rank in importance was SCPMS review, and the final one was SCPMS design.

Therefore, this research provides some recommendations for the decision makers as follows; provide to decision makers and companies owners and managers regarding improving the operation of the supply chain.

The researcher suggests working on developing overall supply chain performance measurement systems. The company should check the quantity of the company-owned inventory and keep exactly the needed quantity without storing more than that because the holding and storing inventory costs are quite high. Provide the decision makers with all possible ways to use supply chain performance measurement systems in the most appropriate way to be useful during the pandemic in terms of providing a framework for survivors to function and survive as well as being ready for post-pandemic conditions.

7. Limitations and future work

Any scientific research has a limitation that can prevent the generalization of the results. This research faces some limitations regarding the country of implementation, as this research was only implemented in Egypt. Hence, future research could compare the results of the AHP within other countries. Although most manufacturing firms could benefit from this research more studies are required to corroborate the results for a wider range of manufacturing businesses. Additionally, supply chain professionals may use this research to discover strategies for surviving and operating during this pandemic and prepare for future post-pandemic situations.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Appendix:

Survey used in the analysis

Gender

Male

Female

Years of Experience

Less than 5 Years

5 – 10 years

10 years and more

Occupation

First Line Management

Middle Management

Top Management

Please answer the following questions, where 1 means not important at all, while 5 means extremely important.

Table

	Likely of Importance
	1	2	3	4	5
SCPMS design: SCPMS lifecycle information
(1) The system is well designed by considering the following metric sets (performance measures, targets, consequences)
(2) There are metric sets such as (performance measures, targets, consequences)
(3) All the company functions are all involved in designing the system
(4) The external factors are involved in designing the system
(5) The contractual arrangements are related to SCPMS and are in place
(6) The system is very well implemented
(7) The company calculates all the metrics
(8) The company reported the measured metrics
(9) There is an information system architecture that implements the SCPMS
(10) There are feedbacks on the performances that are achieved
(11) There are incentives and disincentives
(12) There is a debate on the performances that are reported
(13) The system is being constantly reviewed
(14) Targets are constantly controlled and reviewed
SCPMS Implementation: The role of the SCPMS within the organization
(15) SCPMS are beneficial
(16) The general perception of SCPMS in the organization is acknowledged
(17) SCPMS is used
(18) SCPMS supports planning operations
(19) The type of performance reported is satisfactory
(20) The way of the system that is implemented is satisfactory
SCPMS use: Relationship specific attributes
(21) There is commitment towards the relationships with the specific SC partner
(22) There is a higher level of mutual trust in the relationships with the specific SC partner
(23) There is collaboration in common issues with the specific SC partner
(24) For Suppliers only: There is good relationship with a Retailer before SCPMS adoption
(25) For Suppliers only: There is better relationship with a Retailer after SCPMS adoption
(26) For Suppliers only: The SCPMS adoption influences Suppliers’ opinion towards the retailer
(27) For Retailer only: There is a very good relationship with suppliers such as (logistics providers and goods manufacturers before SCPMS adoption
(28) For Retailer only: There is better relationship with suppliers after SCPMS adoption
(29) For Retailer only: The SCPMS adoption influences Retailer’s opinions towards the suppliers
SCPMS review: Benefits and criticalities
(30) The SCPMS improved the operational performance
(31) The SCPMS affects the relationships with external partners
(32) There are achievable benefits from the SCPMS adoption
(33) There is perceived usefulness of the information shared
(34) There are criticalities or disadvantages adopting the SCPMS
(35) For suppliers: Suppliers are satisfied with the SCPMS used from the retailer