A framework for measuring the performance of service supply chain management

Computers & Industrial Engineering 62 (2012) 801–818

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Computers & Industrial Engineering

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A framework for measuring the performance of service supply chain management

Dong Won Cho, Young Hae Lee ⇑, Sung Hwa Ahn, Min Kyu HwangDepartment of Industrial and Management Engineering, Hanyang University, South Korea

a r t i c l e i n f o a b s t r a c t

Article history:Available online 26 November 2011

Keywords:Service supply chainPerformance measurementFuzzy-AHP

0360-8352/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.cie.2011.11.014

⇑ Corresponding author.E-mail addresses: [email protected] (D.W

(Y.H. Lee), [email protected] (S.H. Ah(M.K. Hwang).

Despite the increasing attention to the service supply chain management by both practitioners and aca-demics, the performance measurement of service supply chains still remains unexplored. Most servicefirms realize that, in order to evolve an efficient and effective service supply chain, service supply chainmanagement needs to be assessed for its performance. A literature review was conducted on perfor-mance measurement issues of service supply chains. This paper develops a framework of service supplychain performance measurement. Based on the strategic, tactical and operational level performance in aservice supply chain, measures and metrics are discussed. The emphasis is on performance measuresdealing with service supply chain processes such as demand management, customer relationship man-agement, supplier relationship management, capacity and resource management, service performance,information and technology management and service supply chain finance. And to prioritize service sup-ply chain performance measurement indicators to improve service supply chain performance, a method-ology based on the extent fuzzy analytic hierarchy process is stressed. The developed framework ofservice supply chain performance measurement is applied to the hotel supply chain. The results of thisstudy are useful both to practitioners in the service supply chain and to researchers carrying out furtherstudies in the field.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

In recent decades, services have become extremely important inthe world economies. The service economy has always been thedriving force of economic growth of every developed nation (Gian-nakis, 2011). Indeed, the transformation of industrialized econo-mies from a manufacturing base to a service orientation is acontinuing phenomenon (Smith, Karwan, & Markland, 2007). How-ever, despite the importance of services and the increasing serviti-zation of world economies, services lag behind in performancewhen compared to manufacturing (van Ark, Mahony, & Timmer,2008). One of the reasons is that most of successful manufacturingorganizations have an opportunity to achieve higher performancein pursuit of supply chain management (SCM), which is a commonpractice across manufacturing industries From both the practicaland academic standpoints, the emphasis in SCM is still stronglyskewed toward the manufacturing sector (Boonitt & Pongpanarat,2011). This is because effective SCM can lead to a lowering of thetotal amount of resources required to provide the necessary levelof customer service to a specific segment and improving customerservice through increased product availability and reduced order

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cycle time while reducing costs (Banomyong & Supatn, 2011).Although, it is believed that service industry can benefit applyingsome best practices from manufacturing industry, the indifferencesbetween service and manufacturing industries could create a needfor specific service supply chain performance measures reflectingservice supply chain practices. Thus, there has been little researchto date on service supply chain performance measurement. For thisreason, it is necessary for researchers to measure the service sup-ply chain processes.

The swift expansion of the service industries over the last dec-ades has enhanced the need for creative innovations and increasedservice productivity to accelerate economic growth. While diversefields of research such as service marketing, service operationsmanagement, service science and service engineering have becomeestablished, very few studies have investigated how serviceproviders manage the service supply chain that extends their orga-nizational boundaries. The inherent problems for service standard-ization, as well as the difficulties of service design and deliveryprocesses may have contributed to the dearth of research in theservice supply chain management. Services are difficult to visualizeand measure and the diversity of the services sector make it diffi-cult to develop a unifying services framework (Ellram, Tate, &Billington, 2004). To obtain objectives or ensure continuousimprovement, the performance of the processes must be mea-sured. Moreover, a process cannot be managed if its performancecannot be measured (Neely, Adams, & Kennerley, 2002). S}urie

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802 D.W. Cho et al. / Computers & Industrial Engineering 62 (2012) 801–818

and Wagner (2002) stress that performance measures have twocentral effects and work in two directions. First of all they can beused to report the current context with a better understanding ofthe past and present of the process being considered. On the otherhand, they can be used to establish performance goals. This allowsfor a focus on the future. By adjusting the target of a performancemeasure it is possible to observe the course in getting to the targetand the success in attaining the target itself. Especially, in order toidentify the quality of a fulfilled practice or a sequence of activities,results must be measured. Target vs. actual performance value datashould be analyzed. For example, input of operational data such asservice capacity are compared to service capacity forecast data. Ananalysis of the difference can reveal the cause of mismatching sup-ply with demand, high shortage costs and poor service level. Usingsuitable approaches, problems can be tackled and close monitoringand opportunities for subsequent improvements can be identified.

Thus, it is important to develop a framework of service supplychain performance measurement (SSCPM) to evaluate changesand to assess the performance of the service supply chain. SSCPMSnot only provides feedback information to show improvement,reinforce motivation and communication and identify problems,but also promotes integration and coordination among servicesupply chain members. As a result, overall customer service levelas well as competitiveness and profitability can be increased. Eventhough the literature on the importance of manufacturing supplychain performance measurement is extensive and many systemsassessing the performance of manufacturing supply chain opera-tions are available (Foggin, Mentzer, & Monroe, 2004), many ofthem are difficult to use in measuring the performance of servicesupply chain activities. As an example, since 1997, the supply chainoperations reference (SCOR) model, produced by the supply chaincouncil, has evolved into a very popular supply chain performancesystem (Giannakis, 2011). It has allowed supply chain members tomodel their supply chains, but it is yet to be applied in service sup-ply chains.

Although it is believed that service can benefit applying somebest practices from manufacturing, the differences between serviceand manufacturing businesses creates a need for specific con-structs or scales reflecting service supply chain practices (Boonitt& Pongpanarat, 2011). Thus, there has been little research to dateon SSCPM related to the development of sound measurement.For this reason, there is a need for a new system to assess servicesupply chain performance that is better suited to service enter-prises’s requirements. The objective of SSCPM is to assess keyservice supply chain activities under different performancedimensions.

Since services contain intangibility, inseparability and heteroge-neity, it becomes difficult to measure service supply chain perfor-mance. Since the evaluation results from evaluator’s view oflinguistic variables, it must be conducted in an uncertain, fuzzyenvironment. In order to overcome the issue, fuzzy set theory isincorporated into the measurement of performance. Fuzzy set the-ory aids in measuring the ambiguity of concepts that are associatedwith human being’s subjective judgment. Nowadays, fuzzy set the-ory has been applied to many fields of management science includ-ing decision making (Buyukozkan, Cifci, & Guleryuz, 2011).However, it is scarcely used in service supply chain performancemeasurement. Also, there is a need for an effective tool in identify-ing and prioritizing relevant criteria to develop a systematicservice supply chain performance measurement process. Theapproach should also develop consensus decision making. Thus,AHP (analytic hierarchy process), a MCDM (multiple criteria deci-sion making) theory proposed by Saaty (1980), is applied in theservice supply chain performance measurement process.

The aim of this paper emphasizes the need for SSCPM anddevelops a general framework to better address the unique nature

of service supply chain. In particular, the article has contributed toimportant issues of SSCPM theory and practice.

� It points out the importance of SSCPM, and the nature of theroles it needs to play.� The developed SSCPM not only helps service organizations in

faster and wider progress monitoring of their operations butcan also help them in improving their internal and externalfunctions of business such as service quality improvement, ser-vice operation management, quick response, gaining lost mar-ket shares, and proper implementation of business strategies.� The metrics selected also reflects balanced service SCM between

financial and non-financial measures, throwing light on serviceSCM. It focuses on core metrics and measures that are likely tocontribute for the successful performance measurement of ser-vice SCM.� By applying the developed SSCPM to hotel supply chain under

service SCM principles, we define a methodology to improvethe quality of prioritization of SSCPM indicators. To do so, amethodology based on the extent fuzzy analytic hierarchy pro-cess (AHP) is applied.

This paper is organized in seven sections. In Section 2, the liter-ature on SSCPM is presented and the peculiarity of service perfor-mance is analysed. Section 3 deals with the identification ofmeasures and metrics in the service supply chain processes. Sec-tion 4 explains the methodology for the framework of the SSCPM.Section 5 includes a summary of the basics of fuzzy sets and num-bers and defines the basic steps of the fuzzy-AHP method used inthe proposed framework. Section 6 proposes the application ofSSCPM to hotel supply chain performance evaluation. Finally, thepaper concludes with a discussion of the theoretical and manage-rial insights of the framework, its limitations and extension ofthe research.

2. Literature review

2.1. Supply chain performance measurement

This section summarizes research related to performance mea-surement at the supply chain, not at the individual company, level.The literature is used in providing the general structure and theneed of supply chain performance measurement.

Neely et al. (2002) define performance measurement as the pro-cess of quantifying the effectiveness and efficiency of past actions.Effectiveness is the extent to which customers’ requirements aremet and efficiency measures how economically a firm’s resourcesare utilized when providing a pre-specified level of customer satis-faction. Also, they highlight that a performance measurement sys-tem should enable informed decisions to be made and actions to betaken because it quantifies the efficiency and effectiveness of pastactions.

Lee and Billington (1992) reported that the discrete sites in sup-ply chain do not maximize efficiency if each pursues goals inde-pendently. SCM is mentioned as a tool to pursue continuousimprovement by many firms in the competitive market. However,occurrences reported in the literature on maximization of overallsupply chain profit through a coordination and integration of thechain members are rare. This is mainly because of their failure todevelop the performance measures and metrics needed to fullyintegrate their supply chain to maximize effectiveness and effi-ciency (Gunasekaran, Patel, & McGaughey, 2004). Thus, measure-ments should be shared and manipulated by all supply chainmembers. Performance studies and models should be created sothat organizational goals and achievement of those goals can be

D.W. Cho et al. / Computers & Industrial Engineering 62 (2012) 801–818 803

measured, thus allowing the effectiveness of the strategy or tech-niques employed to be accessed.

Supply chain management issues span a large spectrum of afirm’s activities, from the strategic through the tactical to the oper-ational level (Simchi-Levi, Kaminsky, & Simchi-Levi, 2008). Theyare the hierarchies in function, wherein the major difference be-tween them is the time horizon for the planning and the decisionsof different levels of management (Ballou, 2004). The strategic le-vel deals with decisions that have a long term planning effect onthe firm. This includes the top level management decisions regard-ing product design, supplier selection, and strategic partnering,very often reflecting the investigation of broad based policies, cor-porate financial plans, competitiveness and level of adherence toorganizational goals. The tactical level includes decisions that aretypically updated anywhere between once every quarter and onceevery year. These include inventory policies, resource allocationand measuring performance against targets to be met in order toachieve results specified at the strategic level. The operational levelrefers to day-to-day decisions such as scheduling, lead time androuting. Measurement at this level requires accurate data and as-sesses the results of the decisions of the low level managers. Thesupervisors and workers are set operational objectives that, ifmet, will lead to the achievement of tactical objectives. Accordingto Kaplan and Norton (1992), the balanced scorecard emphasizes abalance between the use of financial and nonfinancial measures toachieve strategic alignment. Most companies realize the impor-tance of financial and non-financial performance measures; how-ever, they fail to represent them in a balanced framework.Gunasekaran, Patel, & Tirtiroglu, 2001; Gunasekaran et al., 2004)propose a framework for measuring the strategic, tactical andoperational level performance in a supply chain. In addition, a listof key performance metrics is presented. They highlight that per-formance measures should deal with suppliers, delivery perfor-mance, customer-service, and inventory and logistics costs in aSCM.

The literature on supply chain performance measurement pro-vides useful insights to the study of SSCPM. However, these studieswere designed primarily for use in manufacturing supply chains.Therefore, there is a need to develop an appropriate performancemeasurement in the context of service supply chains. In the devel-opment to SSCPM, the metrics that are used in SSCPM should bethose that truly capture the essence of service organizational per-formance. SSCPM goals must consider the overall service supplychain goals and metrics selected should reflect a balance betweenfinancial and non-financial measures that can be related to strate-gic, tactical and operational levels of decision making and controlin the context of the most appropriate service supply chain activi-ties/processes. This being the background, the measures and met-rics are identified and discussed in service supply chains.

2.2. Application of supply chain tool of services

There is very little literature available on SSCPMS, especiallydealing with system design and measures selection. Moreover,there is a lack of investigation on understanding the service supplychain measures which relates the objectives and motivations ofvarious entities in service supply chains. In an attempt to manageservice supply chain processes, Giannakis (2011) explores the util-ity of the manufacturing biased SCOR model in services and devel-ops a reference model for use in service organizations. In hisresearch, services are considered as supply chain processes thatare balanced around the capacity of the firm through the upstreamsourcing processes. The developed model conceptualizes thecapacity of service firms as a resource inventory to build a serviceoffering. This inventory-capacity duality that describes a servicefirm’s capabilities is applicable across a wide spectrum of the ser-

vice sector. Even though the developed reference framework is aproposition of how management in service supply chains couldbe standardized, the focus on operation level seems to limit theapplication of it on strategic and tactical levels.

Boonitt and Pongpanarat (2011) apply the Q-sort technique tothe scale development process in order to address the reliabilityand validity problems caused by subjectivity of the supply chainmanagement in service. They develop a meaningful scale to mea-sure service supply chain management processes. However, fourdimensions, including demand management, capacity and re-source management, order process management, service perfor-mance management have limited numbers of qualifying scales,indicating that the scales need to be reviewed.

Studies so far focus on application of existing SCM models to themanagement of service supply chains (Arlbjørn, Freytag, & de Haas,2011; Baltacioglu, Ada, Kaplan, Yurt, & Kaplan, 2007; Ellram, Tate,& Billington, 2007; Sengupta, Heiser, & Koll, 2006). Few researchershave been interested in how traditional supply chain functions canbe defined in services (Ellram et al., 2004; Kathawala & Abdou,2003), and investigated the dyadic relationship between the ser-vice providers and the end consumer of a service (Sampson,2000). In an attempt to develop a service SCM framework, Ellramet al. (2004) defined service supply chain management as the man-agement of information, processes, capacity, service performanceand funds from the earliest supplier to the ultimate customer. Animportant message in SCM is that a differentiation of tasks shouldtake place (Arlbjørn et al., 2011). Such a differentiation can be prac-ticed through different types of relationships with customers, aswell as suppliers. According to Ellram et al. (2004), there are seventheoretical processes of service supply chains including: Informa-tion flow, capacity and skills management, demand management,customer relationship management, supplier relationship manage-ment, service delivery management, and cash flow. Like the re-search of Giannakis (2011), they view capacity management as akey to understanding the service, by considering the process ofproviding a service as the transfer of capacity for the purposes ofproviding value to the customer. Baltacioglu et al. (2007) developa new framework for the service supply chain, which is built onthe existing knowledge derived from the SCOR and Ellram’s et al.models, with an application in the healthcare industry (Table 1).

The efforts to propose conceptual models to pinpoint servicesupply chains and measure service supply chain processes for thecase of management consulting have provided useful insights tothe study of SSCPM. These works however provide only a concep-tualized service supply chain framework and performance mea-surement for a specific service sector. They do not provideSSCPM that can be used to guide service supply chain processesin each sector of the service economy such as tour, hotel, hospitaland leisure.

2.3. Service performance measures

For the development of the SSCPM framework, since the serviceperformance measures play a core role, their characteristics needto be considered. There are a number of papers on performancemeasures in manufacturing operational settings (Neely et al.,2002), However, less emphasis has been placed on performancemeasures and measurement in service operational settings (Yasin& Gomes, 2010). This is attributed to the difficulties associatedwith the intangibles aspects of different services (Doney, Barry, &Abratt, 2007). Fitzgerald, Johnston, Brignall, Silvestro, and Voss(1991) propose six dimensions of service performance (Table 2).There will be interactions and trade-offs between the six dimen-sions, the consideration of which during the process of strategyformulation should lead to better-balanced strategic plans. Para-suraman, Zeithaml, and Berry (1988) suggest five dimensions for

Table 1Definition of service supply chain processes. Source: Baltacioglu et al. (2007).

Process Definition

Demand management Managing and balancing customer demand bykeeping up-to-date demand information

Capacity and resourcemanagement

Management capacity and resources of service,these resources are organized effectively andefficiently operate at optimum capacity

Customer relationshipmanagement

Maintaining and developing long-term customerrelationships by developing customerinformation continuously and trying tounderstand what customers want

Supplier relationshipmanagement

A process where customers and suppliers developand maintain a close and long-term relationshipas partners. SRM composes of five keycomponents, including coordination, cooperation,commitment, information-sharing and feedback

Order processmanagement

Organizing response for orders processed fromcustomers. The scope of order processmanagement includes getting orders untildelivering service to customers

Service performancemanagement

Management services systems, all of whichshould be taken into account when managing,measuring, modifying and rewarding serviceperformance to improve organizationalperformance in order to achieve corporatestrategic aims and promote its mission and values

Information andtechnologymanagement

Adoption of technologies to support andcollaborate within supply chain to improveservice supply chain operations for achievingcompetitive advantage in their businesses

Table 2Six service performance dimensions, issues and type of measure. Source: Fitzgeraldet al. (1991).

Dimension Issue Type of measure

Financial Asset turn over ProfitabilityControl of labor and capital costs LiquidityProfit per serve Capital structure

Market ratios

Competitiveness Ability to win new customers Relative marketshare and position

Customer loyalty Sales growthMeasures of thecustomer base

Quality ofservice

Relationship between customer andorganization

Overall serviceindicators:

Setting of clear customer expectations ReliabilityMeasurement of customer satisfaction Responsiveness

Aesthetics/appearanceCleanliness/tidinessComfortFriendlinessCommunicationCourtesyCompetenceAccessAvailabilitySecurity

Flexibility Building volume, delivery speed andspecification flexibility into servicedesign in the long term

Specificationflexibility

Use of level capacity strategies Volume flexibilityEmployment of part-time and floatingstaff

Delivery speedflexibility

Use of price and promotion strategies tosmooth demand

Resourceutilization

Utilization of facilities, equipment andstaff

Productivity

Efficiency

Innovation Measurement of the success of theinnovation process and the innovationitself

Performance of theinnovation process

Performance ofindividualinnovations


service quality. It is conceptualized as tangibility, empathy, compe-tence, responsiveness, and reliability called SERVQUAL. Gaiardelli,Saccani, and Songini (2006) also highlight the importance ofafter-sales service in supply chains. At a strategic level theyconsider financial performance measures while at the operationallevel they focus on customer satisfaction, flexibility and productiv-ity. They distinguish the service processes into the back and frontoffice. Reliability and responsiveness are suggested to measurefront office activities, while internal lead time, waste, costs and as-set utilization are evaluated as being appropriate for back officeactivities.

By contrasting Fitzgerald’s et al. (1991), Parasuraman’s et al.(1988), and Gaiardelli’s et al. (2006) service performance dimen-sions with the existing manufacturing supply chain performancemeasures, it is evident that current manufacturing supply chainperformance measures are insufficient to assess service perfor-mance. Therefore, measures and metrics which are used in SSCPMare identified and discussed to measure service performance.

3. Performance metrics and measurement in a service supplychain

In this section, the metrics and measures area identified anddiscussed in the context of service supply chain processes sug-gested by Baltacioglu et al. (2007). Baltacioglu et al. (2007) definethe service supply chain as the network of suppliers, service pro-viders, consumers and other supporting units that performs thefunctions of transaction of resources required to produce services,transformation of these resources into supporting and core ser-vices, and the delivery of these services to customers. In the defini-tion, the ‘‘core service’’ that provides a benefit to the customer isthe ultimate product delivered to the customer. Supporting ser-vices are subsidiary ones required to deliver a core service. Thesupporting services may be produced by suppliers as well as theservice provider itself. In the service supply chain context, the coreservice and supporting services in combination are the key subjectof the transaction. In other words, this combination is the general

context that is addressed by a ‘service’. The customer perceives allservices s/he receives as one and as aiming to provide her/him theultimate benefit.

3.1. Metrics for performance evaluation of order process management

For any firm, the first activity to obtain orders is the order pro-cessing. In the service industry the orders may take many formssuch as reservations or applications. Order process managementfunction covers many sub-processes such as order preparation, or-der transmittal, order entry, order filling, and order status report-ing (Ballou, 2004) and have many intersections with otherfunctions of service SCM. The way the orders are generated andscheduled determines the performance of downstream activitiesand service capacity levels. Order processing has a great impacton customer’s perception of service and customer satisfactionwhich are decisive and shared aims of the firms in a service supplychain (Baltacioglu et al., 2007). Thus, it has great importance inservice businesses and improvements in this function are usuallyreflected in cost decreases or sales growth. The service businessesshould ensure that their order processing system is well designedand managed, and operates in cooperation with all the other sup-ply chain activities. To do this, the most important issues are the


service order-entry method, service order lead-time and path ofservice order traverse (Gunasekaran et al., 2001). The details ofthese are provided hereunder.

3.1.1. The service order entry methodThe service order entry method determines the way and extent

to which customer specifications are converted into informationexchanged along the supply chain (Gunasekaran et al., 2001).Due to the simultaneity characteristic of services, which meansthat the service production process usually takes place only whenthe service provider and the service customer are both present inthe service environment, it is mandatory that timely, accurateand used information should be passed down along the supplychain. Hence, the service order entry method can be used as a met-ric of performance measure.

3.1.2. Service order leadtimeService order leadtime refers to the time which elapses between

the receipt of the customer’s order and the delivery of a service tothe customer. Service industry forms a wide spectrum from massservice in which most of the service operation is completed beforethe customer appears and there is little contract with the cus-tomer, to professional service, which is based on the personal skillsof the people providing the service (Fitzgerald et al., 1991). Thus,each sector of service industry need to has its own set of specificchallenges to decrease service order leadtime. The reduction in ser-vice order leadtime leads to reduction in service supply chain re-sponse time, and as such is an important performance measureand source of competitive advantage (Christopher, 1992). Accord-ing to Brignall and Ballantine (1996), The topic of performancemeasurement has come increasingly to the fore in recent years,reflecting widespread dissatisfaction with traditional performancemeasurement systems, which are argued to focus on short-termmeasures of financial performance, neglecting nonfinancial aspectsof performance such as service quality or service delivery speedflexibility.

3.1.3. The customer service order pathThe customer service order path determines a series of activities

that need to deliver a service. By identifying these activities, thetime spent in different routes and non-value adding activities canbe identified, and suitable steps can be taken to eliminate them.

3.2. Supplier relationship management and related metrics

In recent years, to achieve the high levels of diverse services de-manded by customers, the buyer’s ability to link and work effec-tively and efficiently with suppliers has become the focus ofservice SCM. Therefore, the buyer–supplier relationship is becom-ing more critical for all companies in the supply chain. In this con-text, supplier relationship management, which is defined as acomprehensive approach to enhance cooperation (business rela-tionship level), coordination (process level), and communication(information systems level) between the enterprise and its suppli-ers in order to continuously improve the efficiency and efficacy ofcollaboration and concurrently enhance quality, security, and inno-vation (Mettler & Rohner, 2009), provides the interaction betweenthe focal company and the potential suppliers that are upstream inthe supply chain (Chopra & Meindl, 2004).

Supplier relationship management aims for arranging for andmanaging an organization’s interactions with the suppliers thatsupply the products and services it uses. Accordingly, this functionincludes many processes such as the purchasing strategy, supplierselection, contract management, negotiations with suppliers, sup-plier management, and procurement and control of supply chainperformance. In order for the supplier relationship management

system to perform successfully in the service industry, servicefirms and their suppliers should collaboratively create and deliverservices faster and at the lowest total cost.

According to Baltacioglu et al. (2007), supplier relationshipmanagement is unquestionably critical to service supply chainmanagement. This basically results from the characteristic of theservice delivery process, in which suppliers have a great domi-nance in the chain. In service supply chains, suppliers contributedirectly to the production of services and usually in direct contactwith customers. Thus, suppliers play an important role in cus-tomer’s perception of services and customer satisfaction. A failurein the supply side may simultaneously turn into a failure in servicedelivery performance. To avoid such an occurrence, sustainableand reliable relationships built on coordination, collaboration,responsiveness and trust should be maintained between servicefirms and the suppliers, which is the focus of supplier relationshipmanagement. To do this, the most important issues such as buyer–supplier partnership level and supplier evaluation need to be con-sidered. The other important issue is the evaluation of suppliers.Selecting the wrong suppliers could be enough to deteriorate boththe financial and non-financial performance of the whole servicesupply chain. As mentioned before, this is due to the fundamentalnature of the service delivery process, in which suppliers contrib-ute to successful service performance.

3.2.1. Buyer–supplier partnership levelBuyer–supplier partnership level mentions the extent of partner-

ship that exists between service firms and suppliers. The inter-orga-nizational partnerships and their impact on firm performance havebeen studied at length in various business literatures, with manystudies predicting that in dyadic exchange contexts strong relation-ships should lead to better performance for both parties involved(Autry & Golicic, 2010). Thus, the level of collaborative assistancein service supply chain problem solving can support buyer–supplierpartnership improvement. A number of papers (Doran, Thomas, &Caldwell, 2005; Hansen, 2009; Thakkar, Kanda, & Deshmukh,2007; Toni, Nissimbeni, & Tonchia, 1994; van der Valk, Wynstra, &Axelsson, 2009) have dealt with buyer–supplier partnership in ser-vice supply chains. These studies report a set of criteria/parametersin evaluating partnership. For example, a service firm and its suppli-ers may broaden their contact and share business or technologyinformation. Thus, suppliers may expand their roles to provide re-lated supports beyond traditional transactions, such as participatingin the service firm’s research and development activities or provid-ing technology supports and training by virtue of their areas ofexpertise. The parameters that measure the level of partnershipare summarized in Table 3. By utilizing the proposed criteria, a part-nership will result in win–win situations, leading to a more efficientand effective service supply chain.

3.2.2. Evaluation of suppliersIn a service supply chain management, the performance of po-

tential suppliers is evaluated against multiple criteria importantat the strategic, operational and tactical level. Particularly, suppli-ers in service industries need more collaboration than those inmanufacturing industries because they perform different activitiesconsecutively in a whole service process and in order to impresscustomers consistently, they have to employ compatible interfacemanagement (Feng, Fan, & Li, 2011). There is very little literatureavailable on the evaluation of suppliers in service supply chains,although various related theories and practices are addressed inthe context of manufacturing supply chains (e.g. Kim & Ellegaard,2011; Lee, Chang, & Lin, 2009; Ordoobadi & Wang, 2011). Accord-ingly, an effort is needed to draw measures for evaluating suppliersin the service supply chain with the objective of preparing steps toincrease efficiency and speed.

Table 3Partnership evaluation criteria/parameter in a service supply chain.

Partnership evaluation criteria/parameter

References

Extent of mutual understanding andcloseness for business growth –long-term perspective

Thakkar et al. (2007)

Level and degree of productive andlogistic congruency

Toni et al. (1994)

Level and degree of informationexchange

Toni et al. (1994)

Buyer–supplier risk/profit sharinginitiatives

Thakkar et al. (2007)

Extent of mutual cooperation leadingto continuous improvement

Doran et al. (2005), Hansen (2009),Thakkar et al. (2007), and van derValk et al. (2009)

Level and degree of operativeinteraction between buyer andsupplier

Toni et al. (1994)

Extent of mutual assistance inproblem solving efforts

Doran et al. (2005), and Thakkar et al.(2007)


Strategic level measures include supporting service delivery leadtime, quality of supplier’s service level, risk sharing initiatives, costsaving initiatives, and supplier pricing against market. Tactical levelmeasures include utilization of service facilities, equipment andstaff, the delivery efficiency of supporting services, booking in proce-dures, cash flow, volume and specification flexibility and qualityassurance methodology. Then, operational level measures includeability in day to day technical representation, adherence to a devel-oped schedule, and ability to avoid complaints of service delivery.

3.3. Service performance management and related metrics

Service performance management plays a key function whichmanages the necessary activities for the delivery of a service tothe customer in the service supply chain. Because of the natureof service businesses, the service delivery process requires bothcustomer and producer to be present. In addition, service deliveryand consumption occurs simultaneously (Baltacioglu et al., 2007).These have difficulty in measuring the performance of the servicedelivery process. However, the service performance must be mon-itored and compared to the contract for compliance. Performedproperly, this process should reduce uncertainty in supplier perfor-mance outcomes and reduce the likelihood of any severe contractviolation (Ellram et al., 2004).

In the light of the characteristics of service supply chains, it isnot an easy task to appreciate how a change in one of the majorelements of the service delivery process will affect the system asa whole. One of the ways to overcome this problem is to adopt atotal chain of processes that links together in order to deliver theservice to customers or end users. This has the objective of under-standing and measuring the system performance as a whole, aswell as in relation to the constituent parts of the system. For effec-tive performance measurement, service supply chain metrics mustbe linked to customer satisfaction. This measurement is needed tointegrate the customer specification in service design, to set thedimensions of service quality, for cost control, and as a feedbackfor the control of the service delivery process.

3.3.1. Service delivery performance evaluationIn order to understand the impact of service delivery on the

financial and broader business performance, Johnston and Glark(2008) propose a service performance network, which is formedby the chains of cause and effect between the service deliveryand business performance so that they know how to get the rightresponse from their limited resources. They maintain that there aredirect and strong relationships between service delivery, an orga-nization’s financial performance (such as a reduced costs and/or in-creased revenues) and broader aspects of business performance(such as improved customer satisfaction, retention and attraction).Not all the relationships will apply to every situation and to everyorganization by trying to unravel these relationships, service sup-ply chain managers can understand the direct impact of changesthey make to the service delivery on the organization’s financialand broader business performance and identify the measures foreach element or variable in the network. Silvestro and Cross(2000) provide various measures on service delivery performanceevaluation. These includes profit margin, productivity, customersatisfaction, service value, employ satisfaction, operating ratio ofactual to planned working hours, customer loyalty such as averagecustomer spend per visit per store and customer referral, and em-ployee loyalty such as employee referral, employee turnover andemployee absence.

3.3.2. Service flexibilityService flexibility is the ability of the service process to adapt to

change (Fitzgerald et al., 1991). A concern for the service manager

quickly adapts the provision of service systems to meet thechanging needs and expectations of customers. There seem to bethree different types of service flexibility: volume, delivery speedand specification flexibility. According to Fitzgerald et al. (1991),volume flexibility in services means the ability of the service pro-cess to respond to varying levels of demand. Delivery speed flexi-bility means the adaptability of the service process in meetingdifferent customer needs in terms of speed of response or customerprocessing. Specification flexibility is the degree to which the ser-vice process can be adapted to meet individual customer needs.Moreover, Hill (1985) highlights that flexibility can be a majorsource of competitive differentiation for many services and a keyorder-winning criterion. Hence, it needs to be considered in perfor-mance evaluation.

3.3.3. Range of servicesThe service performance processes may include a variety of

types of sub-processes or activities: some may be routine; othersmay be less routine but still standard activities; others may benonstandard activities that happen infrequently and can be moredifficult to predict how long or how many resources they will re-quire (Johnston & Glark, 2008). Therefore, the service performancethat includes the variety of processes needs typically to focus onproviding a capability for their customers or users, rather than apre-prepared service. But the one that limits the variety of pro-cesses should concentrate on operating as efficiently as it might.Service firms that deliver a wide range of services are likely to per-form poorly on added-value per employee, speed and delivery reli-ability. Furthermore, a company with an extensive service portfolioless frequently breeds new services of innovation. This indicatesthat ‘‘service range’’ has an impact on service supply chain perfor-mance, and so, it needs to be measured.

3.3.4. Total service delivery costA change in service delivery, resulting in an improved customer

experience and/or outcome for the customer may well represent acost to the organization and therefore have a negative impact onfinancial performance (Johnston & Glark, 2008). Improving servicedelivery process, redesigning jobs, improving service quality, forexample, are all likely to incur costs. Therefore, a thorough under-standing and a good performance evaluation of total service deliv-ery cost are essential. A profile consisting of various servicedelivery cost elements should be developed so that the appropriatetrade-offs can be applied as a basis for the planning and reassess-ment of the service delivery process, and thus, the overall costeffectiveness can be achieved.


3.3.5. The customer query timeThe customer query time refers to the time it takes for a firm to

respond to a customer inquiry with the required information (Gun-asekaran et al., 2001). On several occasions, a customer enquires orneeds to be informed about the potential problems on servicedelivery. Since the service delivery process requires both customerand producer to be present, providing such information genuinelyhelps both service providers and the customers to schedule theirrespective activities, and in addition it helps service providers toretain them as customers. Thus, providing online information forcustomers is an important element of customer service, and itcan be evaluated for improving the same. To measure customersatisfaction for the customer query time, questions ‘‘what are theresponse times’’, and ‘‘what procedures exist to inform customers’’should be considered (Gunasekaran et al., 2001).

3.3.6. Post process servicesPost process services are services that are applied after the core

service process has taken place (Bruhn & Georgi, 2006). The func-tion of a service supply chain simply does not end by providing ser-vices to the customer. The post process services play an importantrole both as part of customer satisfaction, and for valuable feed-back for further improvements in the service supply chain. Forexample, training for the customer’s employees by consultantsregarding tools using during a consulting project are often neededin order to make the service delivery result applicable. Timelytraining helps firms to provide better customer service. Apart fromthese, there are other post processing elements, such as service le-vel compared to competitors and measuring customer perceptionof service, that need to be evaluated.

3.4. Capacity and resources management and related metrics

Capacity management is the dedicated act to balance demandfrom customers and the capability of the service delivery system.This is a particularly difficult task when faced with very variabledemand, not only in terms of the size of volume but also the varietyof services required. Moreover, because of the characteristic of ser-vices that are produced and consumed simultaneously, servicebusinesses continuously face the problem of matching their capac-ity and demand.

The task of capacity management is to try to achieve a balancebetween too much and too little resource utilization, within theconstraints of the networks and facilities of the operation. Johnstonand Glark (2008) state that managers in service firms are con-cerned with ensuring that the service process has sufficient re-sources to deal with the anticipated levels of customer demandin such a way that quality of service meets pre-set targets in themost cost-effective manner. However, because of the perishabilitycharacteristic of services, in times of low demand unused capacityis lost forever. Contrary to this, during periods of excess demand,the excess business is usually also lost. This usually increases theseverity of the problem in capacity management. Service organiza-tions can respond to this situation by choosing one of three strate-gic alternatives: matching capacity exactly to demand (called aschase strategy), maintaining a capacity that serves the maximumdemand (called as level strategy) and influencing the demandprofile to smooth the load on the resources (called as demandmanagement). The typical components of capacity include humanresources, facilities, equipment, tools, time, customer participation,and alternative sources of capacity. These strategies inevitably relyon skillful use of one or more capacity components in changing theservice capacity (Haksever, Render, Russell, & Murdick, 2000). Asuccessful capacity and resources management requires that allthese resources are organized effectively and efficiently to operateat optimum capacity that meets the fluctuating demand

(Baltacioglu et al., 2007). Hence, this has an important influenceon the service supply chain performance and the suitable metricsfor it should be established.

3.4.1. Service capacityService capacity is defined as the maximum level of value-

added activity over a period of time that the service process canconsistently achieve under normal operating conditions (Johnston& Glark, 2008). It is important to note the words ‘under normaloperating conditions’ and ‘consistently’. It may be possible, in somecases, for an individual employee to exceed the throughput rate fora short period. For example, if call center employees handle 120calls over 8 h (15 calls per hour), it may be possible for them toachieve as many as 30 calls in one of these hours, but this rate isnot sustainable over any length of time. Therefore, the measureof service capacity is an inherent difficulty with the concept. More-over, a number of factors, such as service product mix, the impactof location, the extent of intangibility in the service production,and the ease of identification of resource constraints, make theassessment of service capacity difficult. Therefore, it is necessaryto develop a measure of capacity that is sufficiently detailed to givea ‘good enough’ estimate of capacity. Because services cannot beinventories, service capacity has a direct impact on the service sup-ply chain performance.

3.4.2. Capacity utilizationResource utilization is a performance criterion which evaluates

how efficiently resources are utilized in the delivery of services(Fitzgerald et al., 1991). It is clear that the role-played by resourcein determining the level of activities in a service supply chain isquite important. If a service organization can provide the same le-vel of service with fewer resources and capacities than its compet-itors, this will enable it either to operate on higher profit marginsor to reduce its price with a view to increasing market share.Hence, it should be measured in performance evaluation.

3.4.3. Effectiveness of scheduling techniquesScheduling deals with the allocation of resources to tasks over

time to perform a collection of activities. In the fiercely competitiveenvironment effective scheduling has become an indispensable es-sence for survival in the marketplace. Companies have to providethe delivery of a service according to the due date, as failure todo so may result in a significant loss of goodwill. They have toschedule activities in such a way as to use the resources availablein an efficient manner. The effectiveness of scheduling has a signif-icant impact on the performance of a service supply chain. Sched-uling can have a significant impact on capacity utilization, supplierperformance and customer satisfaction. Besides those mentionedabove, there are other performance measures including: the pro-ductivity of human resources, comparison of actual vs. plannedtime to determine the service production efficiency, capacity lev-els, and service delivery cost. Of these performance measures,capacity spans the entirety of the service supply chain, and hence,is not just confined to service production.

3.5. Customer relationship management and related metrics

Customer relationship management (CRM), which includes theprocesses that focus on the interface between the firm and itscustomers, seeks to create customer demand and facilitate theplacement and managing of orders (Chopra & Meindl, 2004).CRM attempts to integrate the many communication channels be-tween an organization’s units and its customers, for examplerecording information about customer preferences and then usingthe information to develop and strengthen the relationship and theprofitability of the customer (Johnston & Glark, 2008). Therefore,


CRM gathers data from all parts of the organization in order totrack and analyze a single customer relationship, as well as identifymore general trends.

The aim of CRM enhances both customer retention and relation-ship to enable the organization to achieve a more profitable busi-ness and some closer understanding of the needs of individualcustomers. According to Johnston and Glark (2008), retainingvaluable customers provides significant benefits for many organi-zations. One key benefit for retaining valuable customers in for-profit organizations is in capturing the customer’s revenue streamcalculated as the lifetime spending of a customer. By building long-term customer relationships, which in turns encourage customersto be loyal and helpful, managers and marketers recognize theimportance of retaining existing business rather than simplyattracting new customers. In order to be sure of successful CRMin a service supply chain, possible measures related to customerretention and relationship must be established.

3.5.1. Customer retentionThe determinants of customer retention can be divided into

alignment and bonding (Bruhn & Georgi, 2006). Alignment de-scribes a voluntary emotional connection between the customerand the service provider that can be explained by the psychologicalappreciation of the customer, such as customer satisfaction, trustor commitment. On the one hand, bonding represents not an emo-tional but a formal connection between the customer and the ser-vice provider that implements switching barriers for the customer,such as for membership-like relationships. While alignment causesa voluntary retention, bonding is often associated with so-calledlock-in effects. As a result of these effects, possible measures in or-der to manage customer retention are geared to these two catego-ries of retention causes. Alignment measures strive for customerretention by means of psychological determinants such as relation-ship quality and customer satisfaction, whereas a bonding measureset up switching barriers to achieve customer retention. Further-more, retention measures differ according to the time horizon oftheir use. Bruhn and Georgi (2006) differentiate between short-term and long-term bonding measures as well as short-term andlong-term alignment measures.

3.5.2. Customer relationshipManaging customer relationships is about establishing, main-

taining and enhancing relationships with customers for mutualbenefit (Johnston & Glark, 2008). The organization can use cus-tomer relationship lifecycle to identify customer relationshipintensity. Customer relationship lifecycle describes the customerrelationship intensity based on the time period, i.e. in dependenceof relationship duration (Bruhn & Georgi, 2006). Customer rela-tionship intensity between the service provider and the customercan be measured with both pre-economic measures – customersatisfaction and customer loyalty, and economic measures – cus-tomer profitability, customer value (Bruhn & Georgi, 2006). Thecustomer relationship lifecycle describes a typical concourse of acustomer relationship. Service providers can draw specific conclu-sions for the relationship management from this lifecycle. In theinitial phase a customer relationship begins with lower relation-ship intensity. In this phase, investments into the relationshipare necessary which are justifiable by the possibility of higher rela-tionship intensities in later phases. The growth and maturity phasesees a rapid increase in customer relationship intensity. As a result,this phase emphasizes that service providers only utilize the fullpotential of a relationship when succeeding in bringing the rela-tionship to a higher level. Also, the possible fall of relationshipintensity demonstrates that it is important to observe customerrelationships even when they are at a high intensity level. Finally,the threat, dissolution, an abstinence phase is concerned with the

termination of the relationship by the customer. This stage stressesthat the relationship could commence again because of either cus-tomer-originated reasoning or due to recovery measures under-taken by the provider.

3.6. Demand management

Demand management, which is the preliminary function of ser-vice SCM, focuses on forecasting and managing customer require-ments, with the objective of facilitating this information to shapeservice supply chain operating decisions. In other words, demandmanagement focuses on how to meet, and in many cases how togenerate, customer demand. For effective service SCM, the success-ful management of demand is essential due to a number of difficultproblems that arise from the unique characteristics of services.First, in service industries there exists a great uncertainty of de-mand patterns. With this variation, the services sector has lessflexibility to deal with uncertain demand due to the inability toinventory services. To cope, demand management process focuseson managing the impact of demand variation (Ellram et al., 2004).The service provider should understand its own capacity and pro-ductivity, current commitments, potential to absorb additionalwork through hiring and overtime, and to match these with its ef-forts to sell additional services. Those whose job it is to sell profes-sional services to potential customers need to have an excellentunderstanding of their current workloads and capacity available.According to Baltacioglu et al. (2007), there is little doubt thatthe success of all other supply chain activities depends on deter-mining demand and planning the other processes according todetermined demand. In this context, the importance of demandmanagement is also significant in service supply chains. In a ser-vice flow, the functions of demand forecasting, determinationand planning are needed prior to actual service delivery. Also,the supporting functions in the service supply chain, which are di-rectly related to the product supply chain, should also be taken intoconsideration. As an important part of service SCM, the perfor-mance of demand management needs to be measured and suitablemetrics for it should be established.

3.6.1. Forecast accuracyMost of customer demand has a random component. A good

forecasting method should capture the systematic component ofdemand but not the random component (Chopra & Meindl,2004). The random component manifests itself in the form of aforecast error. Chopra and Meindl (2004) stress that forecast errorscontain valuable information and must be analyzed carefully fortwo reasons: (1) Managers use error analysis to determine whetherthe current forecasting method is predicting the systematic com-ponent of demand accurately. (2) All contingency plans must ac-count for forecast error. These are the main reasons forecasterror must be measured.

3.7. Information and technology management

Information is critical to the performance of a supply chain be-cause it provides the basis on which supply chain managers makedecisions (Chopra & Meindl, 2004). Information technology con-sists of the tools used to gain awareness of information, analyze,this information, and execute on it to increase the performanceof the supply chain. The key drivers for information and technologymanagement can be summarized as the efforts to improve cus-tomer satisfaction through product availability, delivery accuracy,responsiveness and flexibility, improvement through feedback,and to increase sales revenue and improve efficiency of operations(Korhonen, Huttunen, & Eloranta, 1998). It is obvious that informa-tion systems benefit vastly from advances in technology, and today


management of technology is also crucial to maintain effective andefficient information systems. Management of information andtechnology is critical to service supply chains as the success ofthe key functions in the chain such as demand management,capacity and resource management, CRM, SRM and order processmanagement are dependent on an effective flow of information(Baltacioglu et al., 2007).

A successful implementation of information and technology isobvious goal of any organization that has decided to go for a supplychain project. As a SCM project multiple functional areas like de-mand management, capacity and resource management, CRM,SRM, the risk involved in such an implementation are considerable.So, some of the worst SCM projects are due to the fact that compa-nies try to implement information and technology system in awide variety of processes the same time and end up with their pro-jects being failures (Chopra & Meindl, 2004). One way to help en-sure success of the projects is to consider the level of thefunctional requirements to which an IT system deals with thefirm’s key success factors.

3.7.1. The level of functional requirements for IT systemTo reflect the plans of the existing information and technology

system to further develop their systems, the level of the functionalrequirements must be developed. For example, according to Kilger(2002), the following assessment scheme can be developed, con-sisting of five levels:

� Level 1: The functionality is not available; there is no plan todevelop this functionality.� Level 2: The functionality is not available; it is planned to

develop this functionality in the future.� Level 3: The functionality is partially available; there is no plan

to develop this functionality further.� Level 4: The functionality is partially available; it is planned to

further develop this functionality in the future.� Level 5: The functionality is currently fully available.

3.8. Service supply chain finance

Supply chain finance is related with optimizing the financialstructure and the cash-flow within the supply chain (Gomm,2010). Its objective is to optimize financing across company bordersin order to decrease the cost of capital and speed up cash-flow. Cashflow essentially entails the flow of funds between members in thesupply chain, also termed payment. In most professional servicesagreements, payments are made periodically based on performance(CAPS Research Purchasing Performance Benchmarking Study,2003). The party or parties responsible for service delivery manage-ment should determine the appropriateness of the timing and theamount of payment made, based on actual performance towardthe goal (Ellram et al., 2004). This requires that the financial perfor-mance of a service supply chain be measured such as the cost asso-ciated with service supply chain assets and total cash-flow time.

Cost associated with assets and return on investment. For pro-ducing and delivering a specific service unit, certain service re-sources, such as facilities, equipment, and tools, are necessary.Due to the direct contract between these service resources andthe customer (or their objects), which are integrated into the ser-vice process, a service provider can only deliver as many serviceunits as service capacities are available (Bruhn & Georgi, 2006).So, in a service supply chains, as the components of service capacity,mobile and immobile assets must be available. But recently it isbecoming harder for the finance department to keep a clear visibil-ity of the financial commitments of their trading partners (Kerr,2006). So, in a service supply chain, it is essential to determinehow the costs associated with each asset, combined with its

turnover, affects the total cash flow time. This can be measured asthe average number of days required to transform the cash investedin assets into the cash collected from a customer (Stewart, 1995).Once the total cash flow time is determined, it can readily be com-bined with profit with the objective of providing an insight into therate of return on investment (Gunasekaran et al., 2001). This deter-mines the performance that the top management can achieve onthe total capital invested in business. As a corollary to this, the ser-vice delivery management policies have a significant impact on re-turn on investment. For example, superior customer service leads toimproved sales and an increased profit, and subsequently, a higherreturn on investment. Likewise, other areas of organization can beexplored. By measuring ROI and the impact of the service deliverymanagement policies on it, significant insights can be gained aboutthe financial health of the service supply chain.

3.9. Hierarchical structure for service supply chain performancemeasurement

In the previous sections, a review of various issues that are cur-rently in focus for evaluating the performance of a service supplychain were presented. How these issues can be measured and whatmetrics would be suitable for them were also discussed. Alongwith this set of metrics and measures, a summary of metrics is pre-sented in Table 4. Like the classified method proposed by Gunasek-aran et al. (2001) in a framework of manufacturing supply chainperformance measurement, the metrics are classified into strate-gic, tactical and operational levels of management. This has beendone so as to assign them where they can be best dealt with bythe appropriate management level, and for fair decisions to bemade. The metrics are also distinguished as financial and non-financial so that a suitable costing method based on activity anal-ysis can be applied. In some cases, a metric is classified as bothfinancial and nonfinancial. The representation of metrics can givea clear picture of which metric should be used for the performanceassessment study, where it can be used, and who will be responsi-ble for that. Such a representation is a step closer to bridging thegap between the need for a model with which performance of aservice supply chain can be assessed, and the potential areas ofimprovement that can be identified.

In the one hand, the measures and metrics that were discussed,in fact, have a broader perspective, and therefore, it is possible tocategorize these metrics under the different dimensions of thestudy for evaluating service supply chain performance. In this re-search, based on the dimensions of performance measures classi-fied by Fitzgerald’s et al. (1991), and Parasuraman’s et al. (1988)and SCOR model, we categorize the metrics at system and subsys-tem level to develop the hierarchical structure of the aggregativeassessment (Table 5). The hierarchical structure is first categorizedinto three assessment areas: supply chain operation, customer ser-vice and corporate management. There are general criteria withineach assessment area. The hierarchy is then descended from themore general criteria in the second level to sub-criteria. To assessthe aggregative level of service supply chain performance, all crite-ria and sub-criteria associated with each attribute have to be incor-porated into the calculation. The AHP approach would address thediverse aspects associated with performance management in ser-vice supply chains and enable the decision maker to make distinc-tions in the assignation of the importance/weights of eachindividual factor.

4. Methodology

The performance evaluation in a service supply chain iscomplex and may vary even within the service sector. It involves

Table 5Metrics and metrics dimensions for service supply chain performance evaluation.

Assessment areas Criteria Definition Performance metrics

Service supply chainoperation

Responsiveness Willingness to help customers andprovide prompt service

Service delivery Customer query time

Flexibility The ability of the service process to adapt to change Flexibility (volume, delivery speed, specification)Quality of serviceEmployee loyaltySupplier risk sharing initiatives

Reliability Ability to perform the promised service dependably andaccurately

Buyer–supplier partnership level

Quality of supplier’s service levelThe service order entry methodThe customer service order pathAccuracy of forecasting techniquesSupporting service delivery lead timeService order leadtime

Customer service Tangibles Physical facilities, equipment, and appearance of personnel Range of servicesService capacity

Assurance Knowledge and courtesy of personnel and theirability to inspire trust and confidence

Customer satisfaction

Customer retention/loyaltyEmpathy Caring, individualized attention the firm provides its customer Customer relationship

Corporate management Profitability The value of a customer. Average customer spend per visit per storeCost The costs associated with operating the supply chain Total service delivery cost

Supplier pricing against marketSupplier cost saving initiatives

Asset The management of all assets: fixed and working capital Rate of return on investmentTotal cash flow time

Resourceutilization

Utilization of resource in the delivery of services Capacity utilization

Total cycle timeProductivityEffectiveness of scheduling techniquesOperating ratio of actual to planned workinghours

Table 4Metrics for service supply chain performance evaluation.

Level Performance metrics Financial Non-financial

References

Strategic Range of services j Johnston and Glark (2008)Buyer–supplier partnership level j j Doran et al. (2005), Hansen (2009), Toni et al. (1994), Thakkar et al. (2007), and van

der Valk et al. (2009)Flexibility (volume, delivery speed,specification)

j Fitzgerald et al. (1991), and Parasuraman et al. (1988)

Service delivery j j Giannakis (2011), Johnston and Glark (2008), and Silvestro and Cross (2000)Productivity j Fitzgerald et al. (1991), Giannakis (2011), and Silvestro and Cross (2000)Quality of service j Fitzgerald et al. (1991), and Parasuraman et al. (1988)Customer satisfaction j Bruhn and Georgi (2006)Customer retention/loyalty j Bruhn and Georgi (2006), and Silvestro and Cross (2000)Employee loyalty j Silvestro and Cross (2000)Customer relationship j Bruhn and Georgi (2006)Supporting service delivery lead time j Feng et al. (2011)Quality of supplier’s service level j j Feng et al. (2011), and Giannakis (2011)Service order leadtime j Giannakis (2011), and Gunasekaran et al. (2001)Total service delivery cost j Giannakis (2011), and Johnston and Glark (2008)Total cash flow time j Giannakis (2011), and Stewart (1995)Total cycle time j Stewart (1995)Rate of return on investment j Gunasekaran et al. (2001)Customer query time j Gunasekaran et al. (2001)

Tactical Service capacity j j Johnston and Glark (2008), and Haksever et al. (2000)Supplier risk sharing initiatives j Feng et al. (2011)Supplier cost saving initiatives j Feng et al. (2011)Supplier pricing against market j Feng et al. (2011)Effectiveness of scheduling techniques j Giannakis (2011), and Haksever et al. (2000)Accuracy of forecasting techniques j Chopra and Meindl (2004)

Operational The service order entry method j Gunasekaran et al. (2001)The customer service order path j Gunasekaran et al. (2001)Capacity utilization j Johnston and Glark (2008), and Haksever et al. (2000)Operating ratio of actual to plannedworking hours

j Silvestro and Cross (2000)

Average customer spend per visit perstore

j Silvestro and Cross (2000)



multiple criteria, and uncertain and qualitative factors that are dif-ficult to measure. Many techniques, including qualitative andquantitative approaches, appear in the literature in service sector(Buyukozkan et al., 2011). These selection models include statisti-cal models and decision theory models. The difficulty of the assess-ment in service sector is increased because of the ambiguity ofinnovative technology and the lack of experts. Also due to its intan-gible and multiple criteria structure, a strong method should be ap-plied that can handle this ambiguity. So MCDM, which is adiscipline aimed at supporting decision makers who are faced withmaking numerous and conflicting evaluations, is the best way forservice supply chin performance measurement.

AHP is one of the most popular and powerful MCDM method fordecision making that has been used for years in service sector(Buyukozkan et al., 2011). The AHP, first developed by Saaty(1980), is a quantitative technique that facilitates structuring acomplex multi-attribute problem, and provides an objective meth-odology for deciding among a set of solution strategies for solvingthat problem. The procedures of the AHP involve the followingessential steps (Isaai, Kanani, Tootoonchi, & Afzali, 2011): Thistechnique first separates the complex problem being studied intoa hierarchical system of elements. In the next step, pair-wise com-parisons of elements in each hierarchy are done using a nominalscale. Therefore, to represent the comparative weights among var-ious elements of a certain hierarchy the eigenvector of the matrixis extracted. Then, in order to establish a comparison matrix, com-parison results are quantified. Finally, in order to appraise the con-sistency ratio of the comparative matrix and to decide to accept orreject the information, the eigen-value is used. To generate pre-cious information about decision maker’s preference, pair-wisecomparison is usually employed. The ultimate rationale of AHP isthat one could rank and order the alternate solution strategies ontheir final score and choose the best.

AHP has several advantages as seeking consistency in judg-ments, being user friendly, etc. (Buyukozkan et al., 2011). It also al-lows users to structure complex problems in the form of ahierarchy or a set of integrated levels. AHP can also be combinedwith well-known operations research techniques to handle moredifficult problems. One of the main advantages of this method isthe relative ease with which it handles multiple criteria (Dura’nand Aguilo, 2008). In addition, AHP can handle both qualitativeand quantitative data effectively. But on the other hand, AHP isinadequate and defective in handling the ambiguity of the con-cepts that are associated with human being’s subjective judgment.The fuzzy-AHP method, which combines AHP and fuzzy logic, al-lows a more accurate description of the decision making process.

5. Fuzzy-AHP

Fuzzy-AHP methodology is designed for decision makingproblems and selecting the best of alternatives by integrating theconcept of fuzzy set theory and hierarchical structure analysis. Cer-tain characteristics of fuzzy methodology and AHP empower thedecision maker to incorporate both their knowledge, which ismainly qualitative, and quantitative information into the decisionmodel (Isaai et al., 2011). Decision makers usually feel more confi-dent to give interval judgments rather than fixed value judgments.In this approach, triangular fuzzy numbers are used for the prefer-ences of one criterion over another, and then the extent analysismethod proposed by Chang (1996) is used to calculate the syn-thetic extent value of the pair-wise comparison.

A fuzzy number is defined on the universe R as a convex andnormalized fuzzy set. A triangular fuzzy number A or simply a tri-angular number with membership function lA(x) is defined on R by

lAðxÞ ¼0; x < l or x > m

ðx� 1Þ=ðm� lÞ; l 6 x 6 m

ðx� uÞ=ðm� uÞ; m 6 x 6 u;

8><>: ð1Þ

where l 6m 6 u and l and u stand for the lower and upper values ofthe support of A respectively, and m is the mid-value of A. Whenl = m = u, it is a non-fuzzy number by convention. The main opera-tional laws for two positive triangular fuzzy numbers A = (l1, m1, u1)and B = (l2, m2, u2) are as follows:

Aþ B ¼ ðl1 þ l2;m1 þm2;u1 þ u2Þ: ð2ÞA� B ¼ ðl1 � l2;m1 �m2;u1 � u2Þ: ð3ÞA� B ¼ ðl1l2;m1m2;u1u2Þ: ð4Þk� B ¼ ðkl1; km1; ku1Þ; k > 0; k 2 R: ð5Þ

A�1 ¼ ð1=u1;1=m1;1=l1Þ: ð6Þ

In this work, Chang’s extent analysis method is preferred since thesteps of this approach are relatively easier than the other fuzzy-AHPapproaches and similar to the conventional AHP. In the following,the outlines of the extent analysis method on fuzzy-AHP are given:

Let X = (x1, x2, . . . , xn) be an object set, and U = (u1, u2, . . . ,um) bea goal set. According to extent analysis method, each object is ta-ken and Chang’s extent analysis for each goal, gi, is performed,respectively. Therefore, m extent analysis values for each objectcan be obtained, with the following signs:

M1gi;M2

gi; . . . ;Mm

gi; i ¼ 1;2; . . . ;n; ð7Þ

where all the mjg1ðj ¼ 1;2; . . . ;mÞ are triangular fuzzy numbers

whose parameters are l, m, and u. They are the least possible value,the most possible value, and the largest possible value, respectively.A triangular fuzzy number is represented as (l, m, u).

The steps of Chang’s extent analysis can be given as in thefollowing:

Step 1. The value of fuzzy synthetic extent with respect to theith object is defined as

Si ¼Xm

j¼1

Mjgi�

Xn

i¼1

Xm

j¼1

Mjgi

" #�1

: ð8Þ

To obtainPm

j¼1Mjgi

, perform the fuzzy addition operation of m extentanalysis values for a particular matrix such that

Xm

j¼1

Mjgi¼

Xm

j¼1

lij;Xm

j¼1

mij;Xm

j¼1

uij

!; i ¼ 1;2; . . . ;n; ð9Þ

and to obtainPn

i¼1

Pmj¼1Mj

gi

h i�1, perform the fuzzy addition opera-

tion of Mjgiðj ¼ 1;2; . . . ;mÞ values such that

Xn

i¼1

Xm

j¼1

Mjgi¼

Xn

i¼1

Xm

j¼1

lij;Xn

i¼1

Xm

j¼1

mij;Xn

i¼1

Xm

j¼1

uij

!; ð10Þ

and then compute the inverse of the vector in Eq. (10) such that

Xn

i¼1

Xm

j¼1

Mjgi

" #�1

¼ 1Pni¼1

Pmj¼1lij

;1Pn

i¼1

Pmj¼1mij

;1Pn

i¼1

Pmj¼1uij

!:

ð11Þ

Step 2. The degree of possibility of M2 = (l2, m2, u2) P M1 =(l1, m1, u1) defined as

VðM2 P M1Þ ¼ supyPx½minðlM1

ðxÞ;lM2ðyÞÞ�; ð12Þ

and can be equivalently expressed as follows:

Table 6Triangular fuzzy conversion scale.

Linguistic scale Fuzzy scale Fuzzy reciprocal scale

Equal (1, 1, 1) (1, 1, 1)Similar (1/2, 1, 3/2) (2/3, 1, 2)More important (1, 3/2, 2) (1/2, 2/3, 1)Important (3/2, 2, 5/2) (2/5, 1/2, 2/3)Very important (2, 5/2, 3) (1/3, 2/5, 1/2)Extremely important (5/2, 3, 7/2) (2/7, 1/3, 2/5)


VðM2 P M1Þ¼hgtðM2\M1Þ¼lM2ðdÞ¼

1; ifm2 P m1

0; if l1 P u2l1�u2

ðm2�u2Þ�ðm1�l1Þ; otherwise;

8><>:

ð13Þ

where d is the ordinate of the highest intersection point D betweenlM1

and lM2(see Fig. 1).

To compare M1 and M2, we need both the values of V(M1 P M2)and V(M2 P M1).

Step 3. The degree of possibility for a convex fuzzy number to begreater than k convex fuzzy numbers Mi(i = 1, 2, . . . , k) can bedefined by

ðM P M1;M2; . . . ;MkÞ ¼ V ½ðM P M1ÞandðM P M2Þand � � � andðM P MkÞ� ¼min VðM P MiÞ; i ¼ 1;2; . . . ; k: ð14Þ

Assume that

d0ðAiÞ ¼min VðSi P SkÞ: ð15Þ

For k = 1, 2, . . ., n; k – i. Then the weight vector is given by

W 0 ¼ ðd0ðA1Þ;d0ðA2Þ; . . . ;d0ðAnÞÞT ; ð16Þ

where Ai(i = 1, 2, . . . , n) are n elements.Step 4. Via normalization, the normalized weight vectors are

W ¼ ðdðA1Þ; dðA2Þ; dðAnÞÞT ; ð17Þ

where W is a non-fuzzy number.It is not possible to make mathematical operations directly on

linguistic values. This is why the linguistic scale must be convertedinto a fuzzy scale. In the literature about fuzzy-AHP, one can find avariety of different fuzzy scales (Kahraman, Cebeci, & Ruan, 2004).The triangular fuzzy conversion scale given in Table 6 is used in theevaluation model of this paper.

6. Application of service supply chain to the hotel industry

6.1. Hotel supply chain

The hotel industry constitutes one of the significant segments ofthe service sector. It is generally understood that SCM conceptsmay be well implemented in the hotel industry. However, the de-gree to which the hotel industry has embraced them appearsequivocal. For the hotel industry, Kothari, Hu, and Roehl (2005)argue that the SCM concepts or philosophy has been practiced tocertain extent. But despite the importance of the hotel industry,a review of literature on the adoption of SCM revealed that, unlikein other service industries, little published research exists andvirtually no academic research has been conducted to investigateSCM in the hotel industry. Thus, very little has been learned as towhere the hotel industry stands in the context of SCM. In thispaper, we propose that applying SSCPM to hotel organizations un-der service SCM principles will be beneficial in terms of increasingperformance and reducing costs.

Fig. 1. Intersection bet

From a service supply chain perspective, the core service of ahotel is lodging, and the process of realizing this service has manyother components accompanying the core service. Some examplesof these services can be listed as maintenance, hospitality, catering,cleaning and laundry. The latter forms the operational area of thesuppliers in the hotel supply chain, whereas many hotels still pro-duce these services themselves. However, this inclination to verti-cal integration is usually responsible for ineffectiveness andinefficiency of hotel organizations. The hotel industry can benefitconsiderably from partnerships and the value chain approachwhich requires the hotels to focus on their core services, and tooutsource others from their suppliers.

Ideally, a hotel supply chain is composed of suppliers offeringthe aforementioned support services, the hotel as the core serviceprovider and guests as the consumers. In such a framework, thecritical activities of service SCM are also applicable to the hotelindustry. To start with, demand management in this chain engagesin activities of identifying and forecasting the hotel demand andmatching it to the organization’s resources. In the hotel industry,demand management involves the processes for controlling de-mand and managing the flow of guests through the system. De-mand for hotel services depends on many predictable factors,such as periodic events and seasonality. These patterns can betraced and forecasted using statistical data. For example, touristgrowth due to several causes such as the summer vacation or re-gional festival follows seasonal patterns. Given such a track record,the service may increase its supply in accordance with the increasein their incidence. Similarly, during special events that directly af-fect the hotel demand (Olympiads, international conferences, etc.),logistics operations in the chain should be organized to meet in-creased demand. However, since the hotel industry provides ser-vice with fixed assets, it is especially difficult to meet thesechanges in demand. Price policy or promotions are therefore usu-ally used to even out demand. If there is excess demand from thefailure of demand management or shortage, a great loss can occur.Therefore, an effective and efficient forecasting technique is essen-tial to manage demand. A good forecasting method should capturethe systematic component of demand but not the random compo-nent. Forecast errors contain valuable information and must beanalyzed carefully. A hotel has to continually carry out retrospec-tive analyses and base its future strategies on the results of theseanalyses. Consequently, the hotel may develop guidelines to man-age guest admissions, operational and personnel scheduling, or use

ween M1 and M2.


of support services, addressing flexible strategies to suit the dy-namic nature of lodging itself and which will in turn enhance theeffectiveness and efficiency of operations.

Capacity and resources management is closely connected to de-mand management (Baltacioglu et al., 2007). Capacity can beplanned using demand forecasts, as well as information flowingfrom other primary or secondary data sources. By using this data,the organizations operating in the hotel supply chain should orga-nize and plan their available capacity and resources to meet the de-mand, and if there is shortage of resources they should seekoutsourcing alternatives. The resources of a hotel include staff(manager, chambermaid and information clerk), rooms, restau-rants and facilities and determine the type and level of hotel ser-vice offered. It should be noted that the availability andutilization level for many of these resources is to a large extentfixed. Capacity of the hotel has small flexibility and cannot bechanged easily according to predicted demand. Essential assetsfor deciding capacity are costly fixed assets such as rooms, restau-rants, and banquet halls that cannot be changed in the short time.Consequently, capacity and resource management responses arelimited to setting up labor plan, food and drink, consumable sup-plies, each material supplement based on predicted demand. Andit is difficult to manage and plan capacity in hotel institutions.Therefore, capacity planning should be done at the hotel level asthe part of strategic decision making to ensure efficiency in alldepartments.

Customer relationship management practices are relativelynew, and thus still insignificant in the hotel industry. However,CRM constitutes an important area for successful implementationof service SCM principles and is an important tool for understand-ing, managing and measuring customer profitability. CRM in hotelindustry includes obtaining information about the guests, commu-nicating relevant and timely information to them, and tracking re-sults to make message. The CRM approach is also an effective toolto improve customer relationships and loyalty. In the hotel indus-try, an effective CRM programme may only be achieved by infor-mation systems that enhance data quality and data integration.Therefore, hotel informatics systems are of critical importance forCRM applications in hotel services capes.

Supplier relationship management is also core function to hotelsupply chains. This is basically due to the nature of the servicedelivery process, in which suppliers may contribute directly to ser-vice delivery and usually come into contact with guests (custom-ers). For example, suppliers may provide food and drink,materials using in the hotel or offer supporting service such ascleaning, laundry, facility and maintenance. The hotel can ensuresuppliers who provide supporting service through outsourcing,and it is also included supplier relationship management. Sincesuppliers influence service quality and service environment, theyaffect customers service experiences. Therefore, maintaininghealthy relationships with service suppliers emerges as one ofthe critical tasks for the hotel industry. According to Baltaciogluet al. (2007), given the complex and interdependent structure ofsupplier–buyer relationships in the chain, SRM, which is responsi-ble for the selection of suppliers, collaborative service design pro-cesses, definition of optimal sourcing strategies and the actualprocurement processes, directly contributes to actual service per-formances and plays a key role in the effective management andmaintenance of the system.

Order process management in the hotel industry is responsiblefor translating guest (customer) requirements into actual ordersthat are put into the system. In the hotel sector, order process man-agement begins with the initiation of the hotel service reservation,which can be in the form of appointment or admission to the insti-tution and continues as long as the relationship with the guest ismaintained. The order process management function in the hotel

industry covers many sub-processes such as order preparation, or-der transmittal, order entry, order filling, and order status report-ing (Ballou, 2004) and is of critical importance to delivery of theservice. Consequently, this activity has a great impact on cus-tomer’s perception of hotel service delivery and satisfaction. Fail-ures in order process management may have a direct negativeimpact on the overall effectiveness of the service performance(Baltacioglu et al., 2007).

Service performance management in the hotel industry is aboutthe core service delivery to the guest. It therefore includes the de-sign of the hotel service and management of operations during ser-vice delivery. All other activities mentioned before are stronglylinked to service performance management and form the basisfor success in this activity. Service performance management isthe production function in the chain, and the actual service productsuch as reservation and guide services offered to guests, with allthe aspects surrounding the core service product, is under directresponsibility of service performance management. In hotel servicesettings, the hotel staff is of great importance, as these services re-quire constant interaction with guests. Since the attitude of hotelstaff directly faced with customers has a significant impact on cus-tomer satisfaction and experiences, education and motivation forthem are critical issues to maintain efficient and high quality cus-tomer service. Therefore, it should be noted that human resourcesmanagement contributes extensively to the success of service per-formance management.

Maximizing the profit using hotel’s assets efficiently is critical.Hotel supply chain finance consists of some divisions. First, thecapital procurement area ensures and procures needed capital.Second, the practical use area of capital includes a switch from en-sured capital in the hotel to needed goods, equipment, and facilitymaintenance. Third, the profit creation area pursues more profitsthrough consuming assets. Fourth, the asset management areaintegrates overall present condition.

Finally, information and technology is an important enabler ofeffective supply chain management, which typically spans the en-tire enterprise and beyond, encompassing suppliers on one endand customers on the other (Simchi-Levi et al., 2008). Kothariet al. (2005) argue that a major goal of a hotel’s SCM is to efficientlyapply information technology to its procurement systems. Sinceinformation and technology management can access any data inthe system from a single point of contact, it serves as the glue thatallows the other supply chain drivers to work together with thegoal of creating an integrated, coordinated hotel supply chain(Chopra & Meindl, 2004). As a result, it is the key to the successof a hotel supply chain because it enables management to makedecisions over a broad scope that crosses both functions andcompanies.

6.2. Application of fuzzy-AHP to the hotel supply chain

One among goals of this study develops a general framework ofSSCPM which can assess service supply chain performance. So,through the application of the developed SSCPM to the hotel sup-ply chain, we define a methodology to improve the quality of pri-oritization of SSCPM indicators. To build the pair-wise comparisonmatrixes for assessment areas, criteria, and performance measures,some academics and professionals are worked. A questionnaire(available upon request from authors) is provided to get the eval-uations. The results are calculated by taking the geometric meanof individual evaluations. For the first step of the analysis, thepair-wise comparison matrix for the assessment areas is built(see Table 7).

For the first level (i.e. for assessment areas), the values of fuzzysynthetic extents with respect to the assessment areas are calcu-lated as below (see Eq. (8)):

Table 7Pair-wise comparisons for assessment areas.

Service supply chainoperations

Customerservice

Corporatemanagement

Service supply chainoperations

(1, 1, 1) (2/5, 1/2, 2/3)

(1/2, 2/3, 1)

Customer service (3/2, 2, 5/2) (1, 1, 1) (1, 3/2, 2)Corporate efficiency (1, 3/2, 2) (1/2, 2/3, 1) (1, 1, 1)

Table 8Pair-wise comparison for the sub-attributes of service supply chain operations.

Service supply chain operations Responsiveness Flexibility Reliability

Responsiveness (1, 1, 1) (3/2, 2, 5/2) (1/2, 1, 3/2)Flexibility (2/5, 1/2, 2/3) (1, 1, 1) (2/5, 1/2, 2/3)Reliability (2/3, 1, 2) (3/2, 2, 5/2) (1, 1, 1)

Table 9Pair-wise comparison for the sub-attributes of customer service.

Customer service Tangibles Empathy Assurance

Tangibles (1, 1, 1) (2/5, 1/2, 2/3) (1/2, 1, 3/2)Empathy (3/2, 2, 5/2) (1, 1, 1) (3/2, 1/2, 2/3)Assurance (2/3, 1, 2) (2/5, 1/2, 2/3) (1, 1, 1)

Table 10Pair-wise comparison for the sub-attributes of corporate management.

Corporateefficiency

Cost Asset Profitability Resourceutilization

Cost (1, 1, 1) (3/2, 2, 5/2) (3/2, 2, 5/2) (1, 3/2, 2)Asset (2/5, 1/2, 2/3) (1, 1, 1) (1/2, 1, 3/2) (1/2, 2/3, 1)Profitability (2/5, 1/2, 2/3) (2/3, 1, 2) (1, 1, 1) (1/2, 2/3, 1)Resource

utilization(1/2, 2/3, 1) (1, 3/2, 2) (1, 3/2, 2) (1, 1, 1)

Table 11Pair-wise comparison for the sub-attributes of responsiveness.

Responsiveness Service delivery Customer query time

Service delivery (1, 1, 1) (1/3, 2/5, 1/2)Customer query time (2, 5/2, 3) (1, 1, 1)

Table 12Pair-wise comparison for the sub-attributes of flexibility.

Flexibility Flexibility Quality ofservice

Employeeloyalty

Supplierrisk sharinginitiatives

Flexibility(volume,delivery speed,specification)

(1, 1, 1) (3/2, 2, 5/2) (3/2, 2, 5/2) (1, 3/2, 2)

Quality of service (2/5, 1/2, 2/3) (1, 1, 1) (1/2, 1, 3/2) (1/2, 2/3, 1)Employee loyalty (2/5, 1/2, 2/3) (2/3, 1, 2) (1, 1, 1) (1/2, 2/3, 1)Supplier risk

sharinginitiatives

(1/2, 2/3, 1) (1, 3/2, 2) (1, 3/2, 2) (1, 1, 1)


M1 ¼ ð1;1;1Þ � ð2=5;1=2;2=3Þ � ð1=2;2=3;1Þ¼ ð1þ 2=5þ 1=2;1þ 1=2þ 2=3;1þ 2=3þ 1Þ¼ ð1:90;2:17;2:67Þ;

M2 ¼ ð3=2;2;5=2Þ � ð1;1;1Þ � ð1;3=2;2Þ¼ ð3=2þ 1þ 1;2þ 1þ 3=2;5=2þ 1þ 2Þ ¼ ð3:50;4:50;5:50Þ;

M3 ¼ ð1;3=2;2Þ � ð1=2;2=3;1Þ � ð1;1;1Þ¼ ð1þ 1=2þ 1;3=2þ 2=3þ 1;2þ 1þ 1Þ ¼ ð2:50;3:17;4:00Þ;

S1 ¼ ð1:90;2:17;2:67Þ � ð1=12:17;1=9:83;1=7:90Þ¼ ð0:16;0:22;0:34Þ;

S2 ¼ ð3:50;4:50;5:50Þ � ð1=12:17;1=9:83;1=7:90Þ¼ ð0:29;0:46;0:70Þ;

S3 ¼ ð2:50;3:17;4:00Þ � ð1=12:17;1=9:83;1=7:90Þ¼ ð0:21;0:32;0:51Þ:

The degrees of possibility are calculated as below (see Eq. (13)):

VðS1 P S2Þ ¼ 0:17; VðS2 P S1Þ ¼ 1;VðS1 P S3Þ ¼ 0:56; VðS3 P S1Þ ¼ 1;VðS2 P S3Þ ¼ 1; VðS3 P S2Þ ¼ 0:62:

For each pair-wise comparison, the minimum of the degrees of pos-sibility is found as below (see Eq. (15)):

min VðS1 P SkÞ ¼ 0:17;min VðS2 P SkÞ ¼ 1;min VðS3 P SkÞ ¼ 0:62:

These values yield the following weights vector:

W 0 ¼ ð0:17;1:00;0:62Þ;

via normalization, the importance weights (i.e. eigenvalues) of theassessment areas are calculated as follows:

W ¼ ð0:10;0:56;0:34Þ:

At the second level, the weights of the criteria of each assess-ment area are calculated. As can be seen from Table 5, service sup-ply chain cost has three criteria; responsiveness, flexibility andreliability. The pair-wise comparison for these three can be seenin Table 8.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to service supply chain operations are found as below:

ðResponsiveness; flexibility and reliabilityÞ ¼ ð0:79;0; 0:21Þ:

The second assessment area in the model, customer service, hasthree criteria; tangibles, empathy, assurance. The pair-wise com-parison for these three can be seen in Table 9.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to customer service are found as below:

ðTangibles; empathy; assuranceÞ ¼ ð0:24;0:38;0:38Þ:

The third assessment area in the model, corporate management,has four criteria; cost, asset, profitability and resource utilization.The pair-wise comparison for these two can be seen in Table 10.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to corporate management are found as below:

ðCost; asset;profitability and resource utilizationÞ¼ ð0:46;0:09;0:18;0:27Þ:

For the third level, the pair-wise comparisons of performancemeasures regarding to the criteria are calculated. The first criterionto be taken into account is responsiveness. Table 11 shows thecomparisons for that criterion.

Table 13Pair-wise comparison for the sub-attributes of reliability.

Reliability Buyer–supplierpartnership

Quality ofsupplier’s servicelevel

The service orderentry method

The customerservice order path

Accuracy offorecastingtechniques

Supporting servicedelivery leadtime

Serviceorderleadtime

Buyer–supplierpartnership

(1, 1, 1) (1/2, 2/3, 1) (1, 3/2, 2) (1, 3/2, 2) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3)

Quality of supplier’sservice level

(1, 3/2, 2) (1, 1, 1) (1, 3/2, 2) (1, 3/2, 2) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3)

The service orderentry method

(1/2, 2/3, 1) (1/2, 2/3, 1) (1, 1, 1) (2/3, 1, 2) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3)

The customer serviceorder path

(1/2, 2/3, 1) (1/2, 2/3, 1) (1/2, 1, 3/2) (1, 1, 1) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3)

Accuracy offorecastingtechniques

(3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (1, 1, 1) (2/5, 1/2, 2/3) (2/5, 1/2, 2/3)

Supporting servicedelivery leadtime

(3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (1, 1, 1) (2/3, 1, 2)

Service orderleadtime

(3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (3/2, 2, 5/2) (1/2, 1, 3/2) (1, 1, 1)

Table 14Pair-wise comparison for the sub-attributes of tangibles.

Tangibles Range of services Service capacity

Range of services (1, 1, 1) (2/3, 1, 2)Service capacity (1/2, 1, 3/2) (1, 1, 1)

Table 15Pair-wise comparison for the sub-attributes of assurance.

Assurance Customersatisfaction

Customer retention/loyalty

Customer satisfaction (1, 1, 1) (2/3, 1, 2)Customer retention/

loyalty(1/2, 1, 3/2) (1, 1, 1)

Table 16Pair-wise comparison for the sub-attributes of empathy.

Empathy Customer relationship

Customer relationship (1, 1, 1)

Table 17Pair-wise comparison for the sub-attributes of profitability.

Empathy Average customer spend per visit perstore

Average customer spend per visit perstore

(1, 1, 1)

Table 18Pair-wise comparison for the sub-attributes of cost.

Profitability Total servicedelivery cost

Supplier pricingagainst market

Supplier costsaving initiatives

Total servicedelivery cost

(1, 1, 1) (2/3, 2, 5/2) (3/2, 2, 5/2)

Supplier pricingagainst market

(2/5, 1/2, 2/3) (1, 1, 1) (1/2, 2/3, 1)

Supplier costsavinginitiatives

(2/5, 1/2, 2/3) (1, 3/2, 2) (1, 1, 1)

Table 19Pair-wise comparison for the sub-attributes of asset.

Asset Rate of return oninvestment

Total cash flowtime

Rate of return oninvestment

(1, 1, 1) (1, 3/2, 2)

Total cash flow time (1/2, 2/3, 1) (1, 1, 1)


The importance weights (i.e. eigenvalues) of the main attributeswith respect to responsiveness are found as below:

ðService delivery; customer query timeÞ ¼ ð0;1Þ:

The second criterion to be taken into account is flexibility. Table12 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to flexibility are found as below:

ðFlexibility;quality of service; employee loyalty;supplier risk sharing initiativesÞ ¼ ð0:18;0:47;0:35;0Þ:

The third criterion to be taken into account is reliability. Table13 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to reliability are found as below:

(Buyer–supplier partnership, quality of supplier’s service level,the service order entry method, the customer service orderpath, accuracy of forecasting techniques, supporting servicedelivery leadtime, service order leadtime) = (0.09,0.12,0.06,0.04,0.2,0.25,0.25).

The fourth criterion to be taken into account is tangibles. Table14 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to tangibles are found as below:

ðRange of services; service capacityÞ ¼ ð0:5;0:5Þ:

The fifth criterion to be taken into account is assurance. Table15 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to assurance are found as below:

ðCustomer satisfaction;Customer retention=loyaltyÞ ¼ ð0:5;0:5Þ:

Table 21The importance weights of assessment areas, criteria and performance measures.

Assessment areas Criteria Performance metrics

Service supply chain operation (0.1) Responsiveness (0.79) Service delivery (0)Customer query time (1)

Flexibility (0) Flexibility (volume, delivery speed, specification) (0.18)Quality of service (0.47)Employee loyalty (0.35)Supplier risk sharing initiatives (0)

Reliability (0.21) Buyer–supplier partnership level (0.09)Quality of supplier’s service level (0.12)The service order entry method (0.06)The customer service order path (0.04)Accuracy of forecasting techniques (0.2)Supporting service delivery lead time (0.25)Service order leadtime (0.25)

Customer service (0.56) Tangibles (0.24) Range of services (0.5)Service capacity (0.5)

Assurance (0.38) Customer satisfaction (0.5)Customer retention/loyalty (0.5)

Empathy (0.38) Customer relationship (1)

Corporate management (0.34) Profitability (0.18) Average customer spend per visit per store (1)Cost (0.46) Total service delivery cost (0.66)

Supplier pricing against market (0)Supplier cost saving initiatives (0.34)

Asset (0.09) Rate of return on investment (0.68)Total cash flow time (0.32)

Resource utilization (0.27) Capacity utilization (0.16)Total cycle time (0.21)Productivity (0.38)Effectiveness of scheduling techniques (0.1)Operating ratio of actual to planned working hours (0.14)

Table 20Pair-wise comparison for the sub-attributes of resource utilization.

Resource utilization Capacityutilization

Total cycletime

Productivity Effectiveness of schedulingtechniques

Operating ratio of actual to plannedworking hours

Capacity utilization (1, 1, 1) (1/2, 2/3, 1) (2/5, 1/2, 2/3)

(1, 3/2, 2) (1, 3/2, 2)

Total cycle time (1, 3/2, 2) (1, 1, 1) (2/5, 1/2, 2/3)

(1, 3/2, 2) (1, 3/2, 2)

Productivity (3/2, 2, 5/2) (3/2, 2, 5/2) (1, 1, 1) (3/2, 2, 5/2) (2, 5/2, 3)Effectiveness of scheduling techniques (1/2, 2/3, 1) (1/2, 2/3, 1) (2/5, 1/2, 2/

3)(1, 1, 1) (1, 3/2, 2)

Operating ratio of actual to plannedworking hours

(1/2, 2/3, 1) (1/2, 2/3, 1) (1/3, 2/5, 3) (1/2, 2/3, 1) (1, 1, 1)


The sixth criterion to be taken into account is empathy. Table 16shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to empathy are found as below:

ðCustomer relationshipÞ ¼ ð1Þ:

The seventh criterion to be taken into account is cost. Table 17shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to cost are found as below:

ðTotal service delivery cost; supplier pricing against market;supplier cost saving initiativesÞ ¼ ð0:66;0;0:34Þ:

The eighth criterion to be taken into account is asset. Table 18shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to asset are found as below:

ðRate of return on investment; total cash flow timeÞ¼ ð0:68;0:32Þ:The ninth criterion to be taken into account is profitability.

Table 19 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to profitability are found as below:

ðAverage customer spend per visit per storeÞ ¼ ð1Þ:

The tenth criterion to be taken into account is resource utiliza-tion. Table 20 shows the comparisons for that criterion.

The importance weights (i.e. eigenvalues) of the main attributeswith respect to resource utilization are found as below:

ðCapacity utilization; total cycle time;productivity;effectiveness of scheduling techniques;operating ratio of actual to planned working hoursÞ¼ ð0:16;0:21;0:38;0:10;0:14Þ:

All of the results are summarized in Table 21.

7. Conclusion and insight for practitioners

The importance of service is emphasized in current businesspractice, and there is an increasing trend in service expenditures.The research on efficient and effective service supply chain isbecoming critical for both practitioners and academics. Dissemi-


nating information on best universal practices of performancemeasurement of service supply chain could help businessesachieve their competitive advantage in the growing globaleconomy.

In this paper, the importance of the service supply chain perfor-mance measurement has been highlighted. Based on a literaturereview, measures and metrics of service supply chain performancemeasurement are discussed, and a framework is developed with anew perspective of how service supply chain processes could bemeasured. We apply the developed service supply chain perfor-mance measurement to the hotel supply chain. The hotel industrytoday is characterized by continuous growth due to globalizationand technological advancements. Therefore, implementation ofeffective service supply chain performance measurement in thehotel industry emerges as a powerful tool to cope with these chal-lenges. In this context, service supply chain performance measure-ment is undoubtedly vital for the industry.

Our research provides practitioners with managerial insights inthe following aspects.

(1) Its greatest value is that it can help service supply chainmanagers to view and assess the design and managementof service supply chain processes in a different way asopposed to the traditional management of service levelagreements.

(2) It is expected that this research will further motivateresearchers to work in this area. This service supply chainperformance measurement framework will be beneficial toresearchers and practicing managers in identification ofopportunities for improvements in service supply chain.

As further research, the validity of the framework in other ser-vice industries needs to be examined. Moreover, with both aca-demic research and practitioner-driven initiatives creative effortsare required to develop new measures and new programs for eval-uating the performance of the service supply chain as a whole aswell as the performance of each organization that is a part of theservice supply chain.

Acknowledgment

This research was supported by Basic Science Research Programthrough the National Research Foundation of Korea (NRF) fundedby the Ministry of Education, Science and Technology of Korea(2009-0076847).

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A framework for measuring the performance of service supply chain management