*Related content and download information correct at time ofdownload.

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Developing a model for an agilesupply chain in pharmaceutical

industryGholamhossein Mehralian

Department of Pharmacoeconomics and Pharma Management,School of Pharmacy, Shahid Beheshti University of Medical Sciences,

Tehran, Iran

Forouzandeh ZarenezhadInstitute of Management and Developing of Technology,

Tarbiat Modares University, Tehran, Iran, and

Ali Rajabzadeh GhatariDepartment of Management, Faculty of Management and Economic,

Tarbiat Modares University, Tehran, Iran

AbstractPurpose – The purpose of this study is to develop a model for an agile supply chain in the pharmaceuticalindustry. In a continuous changing global competitive environment, an organization’s supply chain agilitydirectly impacts its ability to produce and deliver novel products to its customers in a timely andcost-effective manner. While the beneficial effect of supply chain agility is generally appreciated, theliterature addressing how a pharmaceutical company can achieve supply chain agility is limited.Design/methodology/approach – This paper analyzes the three parts of pharmaceutical supplychain including supply of active pharmaceutical ingredient, manufacturing and distribution based onthe supply chain operations reference model to assess agile supply chains by using three diversequestionnaires. In addition, to prioritize critical factors, TOPSIS (technique for order preference bysimilarity to ideal solution) algorithm as a common technique of multiple attribute decision-making(MADM) model has been used.Findings – Achieving supply chain agility is dependent on other capabilities; including flexibility,responsibility, competency and quickness. Findings reveal several factors identified as critical factorsto being agile in each part of pharmaceutical supply chain.Research limitations/implications – This research was challenged with some limitations such asnovelty of the subject in this environment, and the lake of data in this area is also another constraint.Originality/value – This is an initial and pioneering study to highlight the importance of agilityconcept in the pharmaceutical industry. The present study also provides a new aspect of supply chainmanagement for such industry, and would be a good topic for further research. Finally, this studycontributes to highlight and prioritize factors involved in this area.

Keywords Agility, Supply chain management, Pharmaceutical supply chain

Paper type Research paper

The authors would like to thank Daroupkhsh Holding Company, Alborz Investment Company,Shafa Investment Company and Pars Darou holding company for providing their support inconducting this study.

The current issue and full text archive of this journal is available on Emerald Insight at:www.emeraldinsight.com/1750-6123.htm

IJPHM9,1

74

Received 12 September 2013Revised 12 September 2013Accepted 14 October 2013

International Journal ofPharmaceutical and HealthcareMarketingVol. 9 No. 1, 2015pp. 74-91© Emerald Group Publishing Limited1750-6123DOI 10.1108/IJPHM-09-2013-0050

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

1. IntroductionIn today’s extremely competition-oriented universal market, productive supply chainmanagement (SCM) plays a crucial role and is accepted as a key factor for organizationalcompetitive advantage (Schneller and Smeltzer, 2006; White and Mohdzain, 2009). Overthe last two decades, globalization has resulted in a highly competitive businessenvironment. The turbulent market condition in the twenty-first century has increasedthe need for more competitive enterprise strategies (Mehralian et al., 2013). Speed,quality, flexibility and responsiveness, which are the key elements of agile capabilities,are necessary for meeting the unique needs of customers and markets. Companies enjoysuch agile characteristics by forecasting uncertainties and allowing quick changes torespond to the requirements greatly in their business (Jackson and Johansson, 2003;Baramichai et al., 2007).

Today’s business situation is characterized by an upward level of unpredictability. Inthis unstable market, firms face an aggressive competitive environment due toglobalization, technological changes, shorter lifecycles of goods, diminished margins,economic downsized markets and more informed and well-informed customers withunique and quickly changing needs (Shabaninejad et al., 2014a; Mehralian et al., 2012b).The focus of supply chain has changed from production efficiency to customer-drivenand collaboration synchronization approaches, which need a high degree of cooperationamong all supply chain partners (Lou et al., 2005). These changing market situationsforce organizations to alter their supply chain structure and handle it to be moreresponsive to these changes. To respond to the challenges and demands of today’sbusiness environment, firms have undergone a revolution for implementing noveloperations strategies and technologies (Gunasekaran et al., 2008). Recent literature ofsupply chain has addressed this flow and proposes that the key factor for surviving inthese changing situations is agility by forming responsive supply chain (Christopher,2000). In a continuously changing global competitive environment, agility of anorganization’s supply chain directly affects its ability to produce and give inventiveproducts to its customers in a timely and cost-effective manner (Swafford et al., 2006).

The pharmaceutical section plays a significant role in the medical and healthcontinuum (Shabaninejad et al., 2014b). The pharmaceutical market is heavily regulatedin many countries because of the unique nature of supply and demand in this section (Yuet al., 2010; Mehralian et al., 2014). According to the characteristics of the competition inthe drug market, governments must balance both clinical and economic interests(Hakonsen et al., 2009; Rasekh et al., 2012). One of the targets of this supply chain is toassure a continuous flow of drugs to patients at optimal price with minimal delays, lowshortages and little room for error (HDMA, 2009). A scientific and technologicaltransformation occurs in the pharmaceutical industry that will allow drug producers toproduce new profitable medicines in situations that they cannot be treated very welltoday and in conditions which they have formerly persisted against all treatments.Several elements press pharmaceutical firms to change their old manners of conductingbusiness. One of these elements is the supply chain, which changes to a source ofcompetitive advantage (Ahmad et al., 2009). Finally, the objective of this paper is toaddress this question:

• To develop a model for an agile pharmaceutical supply chain (PSC), what criticalfactors should be considered by pharmaceutical companies?

75

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

To answer this question, there are some sub-questions which should be answeredleading us to respond to the research question:

• To be agile in supply of active pharmaceutical ingredient, what critical factorsshould be considered by pharmaceutical companies?

• To be agile in production of pharmaceutical products, what critical factors shouldbe considered by pharmaceutical companies?

• To be agile in distribution of pharmaceutical products, what critical factorsshould be considers by pharmaceutical companies?

To answer the question, this article utilizes the fuzzy TOPSIS (technique for orderpreference by similarity to ideal solution) to quantify critical factors. The remainder ofthe paper is organized as follows: Section 2 presents the literature on SCM and a reviewof pharmaceutical industry. In Sections 3 and 4, research methodology and datacollections are developed. Section 5 presents the data analysis and results and,ultimately, Sections 6 and 7 provide conclusion and implementations.

2. Literature review2.1 The agile supply chainSupply chain agility has been considered a lot recently as a way for organizations torapidly reply to changing business environment and improve their customer servicelevels. To perceive this concept, it is important to first give the definition of the agilecompanies. Agility has been proposed as a reply to the high levels of intricacy anduncertainty in advanced markets (Christopher and Juttner, 2000). According to Nayloret al. (1999), “agility means applying market knowledge and a vital corporation toexploit profitable opportunities in a rapidly changing market place”. The relationshipbetween agility and flexibility is extensively discussed in the literature (Christopher,2000; Swafford et al., 2006). It has been proposed that the origins of agility lie in flexiblemanufacturing systems (Gosling et al., 2010).

The goal of an agile enterprise is to enrich or satisfy customers and employees. A firmbasically has a set of capabilities for giving appropriate replies to changes occurring inits business environment. The business status in which a lot of companies understandthemselves is characterized by volatile and unpredictable demand. Hence, agility mightbe defined as the ability of a firm to reply rapidly to changes in the market andcustomers’ demands. To be really agile, a firm should control a number of differentiatingagility providers. Tseng and Lin (2011) have developed an agile enterprise conceptualmodel, as shown in Figure 1.

Therefore, firms need a number of distinguishing attributes to promptly deal withthe changes inside their environment. Such attributes include four main elements (Sharpet al., 1999): responsiveness, competency, flexibility/adaptability and quickness/speed.The base for agility formation is to incorporate information technologies, staff, businessprocess organization, innovation and facilities into main competitive attributes. Theinclusion of agile strategies has some benefits for firms, including quick and efficientreaction to changing market requests; the ability to customize products and servicesdelivered to customers, the capability to manufacture and deliver new products in acost-effective manner (Swafford et al., 2006), reduce production costs, enhance customer’ssatisfaction, remove non-value-added activities and increase competitiveness. Therefore,agility has been advocated as the commercial paradigm of the twenty-first century. In

IJPHM9,1

76

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

addition, agility is considered as the winning strategy for becoming a universal leader in anincreasingly competitive market of quickly changing customers’ requirements (Agarwalet al., 2006; Ismail et al., 2007).

2.2 The pharmaceutical industry environmentThe pharmaceutical industry is defined as a system of procedures, operations andorganizations involved in the discovery, development and production of drugs andmedications. The PSC represents the path through which essential pharmaceuticalproducts are distributed to the end-users with the right quality, at the right place and atthe right time (Mehralian et al., 2012a). The PSC is very complicated and greatlyresponsible for ensuring that the appropriate drug is delivered to the right people at theright time and in the right situation to fight against sickness and sufferings. This is ahighly sensitive supply chain in which everything less than 100 per cent customerservice level is unacceptable, as it directly influences health and safety. The solutionwhich many pharmaceutical industries adopt is to bear a vast inventory in the supplychain to ensure about 100 per cent of fill rate. However, it is a great challenge to ensure100 per cent of product availability at an optimum cost unless supply chain processesare streamlined toward customer requirements and demands (Chandrasekaran andKumar, 2003).

Figure 1.Components of anagile supply chain

77

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

More specifically, attributes such as marketing time, R&D productivity, drugslifecycle reduction, government regulations, decreasing exclusive patent life, productionflexibility and increase of cost are the main problems that pharmaceutical industriesface today. A manufacturer who can adjust improvement time by 19 per cent can saveup to $100 million. At the time of getting delivery of a drug to access the market, a firmmay get rid of around $1 million a day; therefore, marketing time is too important forpharmaceutical companies to gain market share (Chandrasekaran and Kumar, 2003).The pharmaceutical market is heavily regulated in many countries because of thesingular nature of supply and demand for drugs (Garattini et al., 2007). In accordancewith the feature of the competition in the drug market, governments must balance bothclinical and economic interests (Hakonsen et al., 2009). The pharmaceutical section playsa crucial role in the medical and health system. Characterized with its size of total andaging population, quickly increasing economy and increasing prevalence of chronicdiseases (like cardiovascular disease, cancer and chronic respiratory disease),pharmaceutical industry growth has increased very fast (Mehralian et al., 2012a).

2.3 PSC componentsThe PSC, like other industries, begins with sourcing of active and inactive ingredientsfor approved products. Dosages are planned and packed into different configurations.Products are delivered to company’s warehouses, wholesale distributors, retailpharmacies, medicinal organizations (hospital pharmacy) and finally to end-users. Thedata flow and funds flow start from end customer to producer through differentchannels (Chandrasekaran and Kumar, 2003). A supply chain is the arrangement oforganizations, their facilities, acts and activities which are involved in manufacturingand giving a product or service. A typical PSC consists of the following members: initialmanufacturing, secondary manufacturing, market warehouse/distribution centers,wholesalers, retails/hospitals and patients (Shah, 2004). Previously, under a centrallyorganized economy, whole pharmaceutical products were distributed by an ownedmonopoly firm (first-tier wholesaler) to some regional wholesalers (second-tierwholesalers) who would then deliver the products to local wholesalers (third-tierwholesalers) (Shao and Ji, 2006). Among PSC components, it has been argued thatdelivery of medicines has crucial effect on customers’ satisfaction (Rossetti et al., 2011).Due to changing economic system, PSC has been reformed, and Figure 2 exhibits thenew PSC.

2.4 Supply chain operations reference modelIn this study, we use the supply chain operations reference (SCOR) model according toSupply Chain Council in 2001 (Braunscheidel, 2005). The SCOR makes a cross industrystructure for estimating and improving SCM and execution (Stewart, 1997). Five mainsupply chain processes are captured by the structure of the SCOR model. The processesare plan, source, making, deliver and return. In conceptualization of supply chain agility,it is better to apprise each process separately to frame the theoretical parts of supplychain agility into a generally accepted business structure (Braunscheidel, 2005).

2.5 Fuzzy TOPSISTOPSIS solves the multi-criteria decision-making tasks that implies full andcomplete information on criteria expressed numerically. The method is very usefulfor solving real problems; it provides us with the optimal solution or the alternative

IJPHM9,1

78

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

ranking. In addition, it is not as complicated for the managers as some othermethods that require additional knowledge. The TOPSIS technique would searchfor the given alternatives and find the one that would be closest to the ideal solution,but the farthest from the anti-ideal solution at the same time. Modification of themethod aims to set a different manner of determining the ideal and anti-ideal pointby standardizing quantification of linguistic attributes and introducing fuzzynumbers for description of the attributes for the criteria expressed by linguisticvariables (Karimi et al., 2011).

3. Research methodIn this section, we presented a methodology for operationalizing the variables andfactors, acquiring the data and determining the reliability of factor grouping. Thedata used in this study were collected from a questionnaire distributed to managersin the Iranian pharmaceutical companies. The pharmaceutical industry is chosenbecause it has a heavy and complete supply chain. These types of firms have tried toimprove their supply chain performance due to increasing concerns and importanceof supply issues and also manufacturers seek to find methods for improving theirperformance.

This research is based on the SCOR model, and the scope of this paper emphasized onthe whole parts of PSC. To develop questionnaires, an extensive literature review hasprovided several important factors for each part of supply chain area at the first phase(for example: Tseng and Lin, 2011; Swafford et al., 2008; Qureshi et al., 2008;Gunasekaran et al., 2008; Baramichai et al., 2007; Agarwal et al., 2007; Antonio et al.,2007; Sharifi and Zhang, 1999). At the second phase, the initial questionnaires weredesigned based on extracted factors. At the third phase, the initial questionnaires werefurther revised by experts to customize them more specifically based on thecharacteristics of PSC. Finally, nine critical factors for each part of the supply chainconsisting of supply, manufacturing and distribution were prepared, according toTables I-III. To measure the attitude, the chosen response is scored on a scale rangingfrom 1 (strongly disagree) to 5 (strongly agree).

In addition to the above questions, information related to the basic profile of therespondents was requested at the end of the questionnaire. The main sampling targetswere senior managers, department managers and personnel who were involved in thedecision-making.

Figure 2.Pharmaceutical

supply chain

79

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

3.1 Research modelOur research model is presented in Figure III. The key dependent variable of interest isagility in the aforementioned sections which is expected to be influenced by someindependent variables. These variables have some related sub-factors and they areshown in Tables I-III, and as a result, agility can improve responsiveness, quickness,flexibility and competency of distributers.

3.2 Capabilities of agilityAgile companies require a number of distinguishing capabilities or “fitness” to deal withthe change, uncertainty and unpredictability within their business environment. Thesecapabilities consist of four principal elements (Ren et al., 2001; Giachetti et al., 2003):

(1) Responsiveness: Which is the ability to identify changes and respond quickly tothem, reactively or proactively and recover from them.

Table I.Agile supply factors

Dimensions Factors Citations

Planning and reordersegmentation

Market research and monitoringForecast of alternatives suppliers

Baramichai et al. (2007),Agarwal et al. (2007),Tseng and Lin (2011),Lin et al. (2006), Swaffordet al. (2008)

Assessment and prioritizingof suppliers for purchasing

Quality/cost standards for supplierselectionMaintaining list of prequalifiedsuppliers

Baramichai et al. (2007)

Utilizing of IT tools E-commerceElectronic bidingRFID (radio frequencyidentification)

Baramichai et al. (2007),Gunasekaran et al.(2008), Agarwal et al.(2007), Swafford (2003)

Material quantity adjustment Order consolidationVariety of suppliers

Baramichai et al. (2007)

Process integration andperformance management

Co-managed inventoryCollaborative product design anddevelopmentSynchronous supply

Agarwal et al. (2007),Christopher (2000)

Cost reduction Sourcing costInventory cost

Qureshi et al. (2008),Agarwal et al. (2007),Lin et al. (2006), Swafford(2003)

Delivery speed Responsiveness rateReliability delivery

Agarwal et al. (2007),Tseng and Lin (2011),Sharifi and Zhang (1999)

Trust development Trust-based relations withsuppliersMinimizing uncertainty

Agarwal et al. (2007),Tseng and Lin (2011),Handfield and Bechtel(2002)

Environmental pressure Political factorEconomic factorsSocial factors

Sharifi and Zhang (1999),Tseng and Lin (2011)

IJPHM9,1

80

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

(2) Competency: Which is the ability to efficiently and effectively reach the firms’aims and goals.

(3) Flexibility/adaptability: Which is the ability to process different processes andachieve different goals with the same facilities.

(4) Quickness/speed: Which is the ability to carry out activity in the shortest possibletime.

Furthermore, a methodology of integrating them into a coordinated, interdependentsystem and translating them into strategic competitive capabilities underpin these foursprinciples (Sharp et al., 1999). These must be considered if an organization carries out anagile enterprise (Tseng and Lin, 2011).

Table II.Agile manufacturing

factors

Citations Factors Dimensions

Breu et al. (2001),Gunasekaran et al. (2008)

Education and learningInnovation and creationPeople flexibility

Employee empowerment

Agarwal et al. (2007),Gunasekaran et al. (2008),Swafford et al. (2008), Tsengand Lin (2011)

Skills in IT (information technology)RFIDExchange of informationCollaboration on strategic andoperational planningE-commerce

Information technologyand systems

Christopher (2000),Agarwal et al. (2007), Lin et al.(2006), Tseng and Lin (2011)

Customer orientationMonthly feedbackRetain and grow customerrelationshipsMarket behaviors

Market sensitive

Swafford (2003),Braunscheidel, (2005),Baramichai (2007), Agarwal etal. (2007)

Fast introduction of new productsTechnological innovationApproved qualityPerformance quality

New innovativeproducts

Antonioa et al. (2007),Agarwal et al. (2007)

Product quality

Sharifi and Zhang (1999),Antonioa et al. (2007),Agarwal et al. (2007), Yeung(2008)

Timeliness of deliveryDelivery reliability

Delivery speed

Patil (2006), Agarwal et al.(2007), Antonioa et al. (2007),Tseng and Lin (2011)

Penalty costInventory costReduce setup time

Reduction costs

Swafford (2003),Braunscheidel (2005), Lin et al.(2006), Antonioa et al., (2007),Tseng and Lin (2011)

Supply flexibilityManufacture flexibility

Flexibility

Sharifi and Zhang (1999),Braunscheidel (2005), Tsengand Lin (2011)

Political factorEconomic factorsSocial factors

Environmental pressure

81

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Figure 3.Research model

Table III.Agile distributionfactors

Dimensions Factors Citations

Information technologycapability

Utilizing of IT for information sharingRFIDUtilizing of IT for distribution

Tseng and Lin (2011),Swafford et al. (2008),Qureshi et al. (2008)

Flexibility Flexibility in warehouses spaceUtilizing of flexible equipmentsSkilled employeeFlexibility in operation and delivery

Tseng et al. (2011), Swaffordet al. (2008), Qureshi et al.(2008), Baker (2008), Agarwalet al. (2007)

Quality Quality of serviceManagement quality

Qureshi et al. (2008), Lin et al.(2006), Antonio et al. (2007)

Market research andmonitoring

Sale feedbackCustomer orientationForecasting crisis capacity

Agarwal et al. (2007), Tsengand Lin (2011), Qureshi et al.(2008)

Optimum cost Inventory costTransportation and delivery costPenalty cost

Agarwal et al. (2007), Tsenget al. (2011), Qureshi et al.(2008), Patil (2006

Customer satisfaction Product reliabilityCustomer complaints

Yeung (2008), Agarwal et al.(2007)

Delivery speed Delivery speedReliability deliveryReduced production lead time

Antonio et al. (2007),Agarwal et al. (2007), Tsengand Lin (2011), Swafford etal. (2008), Qureshi et al. (2008)

Relationship Geographical distribution rangeReputationLong-term relationship

Qureshi et al. (2008)

Environmentalpressure

Political factorEconomic factorsSocial factors

Sharifi and Zhang (1999),Tseng and Lin (2011)

IJPHM9,1

82

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

3.3 Reliability and validity of the questionnaireThe internal consistency of a set of measurement items refers to the degree to whichitems in the set are homogeneous. Internal consistency can be estimated using reliabilitycoefficient such as Cronbach’s alpha (Saraph et al., 1989). In this research, Cronbach’salpha was calculated to be 0.86.

The validity of a measure refers to the extent to which it measures what should bemeasured. Content validity is not evaluated numerically, it is subjectively judged by theresearchers (Kaplan, 1987). The measurement items were based on an extensive reviewof the literature on various SCM approaches. To measure the acceptance of thequestionnaire, ten people who were qualified for SCM participated in a pilot test. Theparticipants suggested adding and omitting some parts of the questionnaire. Finally, allthe pretest participants strongly agreed on the suitability of the questionnaire. Thequestionnaire was considered to be finalized after modifying some questions and thenwas ready for delivery.

In addition to the face validity, factors of eigenvalues greater than 1 were kept usingmethod of principal components extraction. The factor analysis (i.e. Pearson’s principalcomponent analysis) was tested with and without rotation (i.e. varimax rotation withKaiser normalization). The conservative factor loadings of greater than 0.5 wereconsidered at the 95 per cent level of confidence (Hair et al., 1998).

4. Data collectionData of this study were collected using a questionnaire distributed to 21 pharmaceuticalfirms affiliated to three large holding companies. To understand the viewpoints of agilesupply chain from key sectors of the pharmaceutical industry, questionnaires were sentto the marketing, sales, information technology (IT), finance, R&D and qualityassurance and control departments. Accordingly, respondents were chosen amongmanagers who had comprehensive knowledge about company’s process, products andgeneral pharmaceutical-related issues. The number of questionnaires was different,depending on the target section in PSC. Finally, 93 questionnaires for supply sector, 156questionnaires for manufacturing sector and 118 questionnaires relating to distributionsector were returned.

5. Results and analysisData have been analyzed through statistical analysis and the multiple attributedecision-making (MADM) algorithm. In statistical analysis, Pearson correlation andfuzzy TOPSIS have been used. In this section, fuzzy TOPSIS technique as an algorithmof MADM has been used to prioritize SCM agility factors. There are many applicationsof fuzzy TOPSIS in the literature. Chen et al. (2006) presented a fuzzy TOPSIS approachto deal with the supplier selection problem in a supply chain system. Yang and Hung(2007) used TOPSIS and fuzzy TOPSIS methods for a plant layout design problem(Karimi et al., 2011).

The TOPSIS method was first proposed by Hwang and Yoon (1981). The basicconcept of this method is that the chosen alternative should have the shortest distancefrom the positive ideal solution and the farthest distance from a negative ideal solution.A positive ideal solution is a solution that maximizes the benefit criteria and minimizescost criteria (Karimi et al., 2011), whereas a negative ideal solution maximizes the costcriteria and minimizes the benefit criteria. In the classical TOPSIS method, the weights

83

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

of the criteria and the ratings of alternatives are known precisely and crisp values areused in the evaluation process. However, crisp data are inadequate to model real-lifedecision problems under many conditions. Therefore, the fuzzy TOPSIS method isproposed, in which the weights of criteria and ratings of alternatives are evaluated withlinguistic variables represented by fuzzy numbers to deal with the deficiency of thetraditional TOPSIS (Ertugrul and KarakasoGlu, 2008).

This paper extends the TOPSIS method proposed by Chen et al. (2006). The relatedalgorithm can be described as follows (Chen et al., 2006).

Step 1: A committee of the decision-makers is established. Fuzzy rating of eachdecision-maker Dk � (k � 1, 2, … k) can be represented as triangular fuzzy numberRk � (k � 1, 2, …;) with membership function �Rk

(x).Step 2: Criteria evaluation is determined.Step 3: After that, appropriate linguistic variables are chosen for evaluating criteria

and alternatives.Step 4: Then the weight of criteria is aggregated. The aggregated fuzzy rating can be

determined by:

R � (a,b,c), k � 1, 2, … k.

where, a � min�ak�, b �1k �

k�1

k

bk, c � max�ck� (1)

aij � mink

�aijk�, bij �1k �

k�1

k

bijk, cij � maxk

�cijk� (2)

Then, the aggregated fuzzy weight (wij) of each criterion is calculated by:

(wij) � (wj1, wj2, wj3) (3)

Where wj1 � mink

�wik1�, wj2 �1k �

k�1

k

wjk2, wj3 � maxk

�wjk3� (4)

Step 5: Then, the fuzzy decision matrix is constructed.Step 6: The above matrix is normalized.Step 7: Considering different weights of each criterion, the weighted normalized

decision matrix is computed by multiplying the importance weights of evaluationcriteria by the values in the normalized fuzzy decision matrix.

Step 8: The fuzzy-positive ideal solution (FPIS,A*) and fuzzy-negative ideal solution(FNIS,A*) are determine by:

A* � (V�

1*, V

�2*, …, V

�n*), (5)

A� � (V�

1�, V

�2�, …, V

�n�), (6)

Where, V�

j* � max

i�Vij3� and V

�j� � min

i�Vij1�.

IJPHM9,1

84

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

i � 1, 2, …, m; j � 1, 2, …, n

Step 9: Then, the distance of each alternative from FPIS and FNIS is calculated by:

di* � �

j�1

n

dv(V�

ij, V�

j*) i � 1, 2, …, m (7)

di� � �

j�1

n

dv(V�

ij, V�

j�) i � 1, 2, …, m (8)

Where dv(…) is the distance measurement between two fuzzy numbers.Step 10: A closeness coefficient is defined to rank all possible alternatives. The

closeness coefficient represents the distance between the FPIS (A*) and FNIS (A�)simultaneously. The closeness coefficient of each alternative is calculated by:

CCi �di

�i

di* � di

�, i � 1, 2, …, m (9)

Step 11: According to the closeness coefficient, the ranking of the alternative can bedetermined.

5.1 Correlation analysisTo test the relationships among risk factors, Pearson correlation has been used in thisstudy. It means that if there is any inter-correlation among critical factors. The resultsindicated that these factors had been generally correlated with each other in each sector.

5.2 Result of fuzzy TOPSISTo apply fuzzy TOPSIS, the language terms have been converted into fuzzy numbersaccording to Table IV.

To prioritize the factors, the fuzzy TOPSIS method has been used, and its results areshown from Tables V-VII.

Based on agile supply factors, delivery speed, planning and reordering and trustdevelopment are placed in the top ranking priorities, as shown in Table V. To associateagile manufacturing factors, as shown in Table VI, delivery speed, productsdevelopment and cost reduction should be highly considered by pharmaceuticalmanagers, until they can perform their operations efficiently. According to the agiledistribution section, as illustrated in Table VII, factors such as market research, quality,delivery speed and customer satisfaction show high concerns regarding to respondents’attitude.

Table IV.Language term for

TOPSIS method

Very low 1 (0, 0.1, 0.2)Low 2 (0.1, 0.25, 0.4)Medium 3 (0.3, 0.5, 0.7)High 4 (0.6, 0.75, 0.9)Very high 5 (0.8, 0.9, 1)

85

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

6. ConclusionToday, organizations encounter dynamic and changing environments, where productlifecycles are short and environmental pressures make a lot of uncertainties, which forcecompanies to manage risks proactively. Companies need agility to deal with thesesituations not only in the organization but also in their entire supply chain (Ismail andSharifi, 2006; Charles et al., 2010). In this study, all attempts aimed to provide an efficientand optimized model for agility of supply chain in the pharmaceutical industry. At first,attempt is made to identify factors affecting supply chain agility and these factors wereprioritized in the second phase. Generally, seven main indicators were identified as themost important factors affecting process of agility in the PSC including; delivery speed,

Table V.TOPSIS rank of agilesupplying factors

Agile supply factors Ci (rank of TOPSIS)

Delivery speed 0.339Planning and reordering 0.416Trust development 0.457Quantity adjustment 0.576Cost reduction 0.70Assessment and prioritizing 0.81Environmental pressure 1.26Process integration 1.39Utilizing of IT tools 1.78

Table VI.TOPSIS rank of agilemanufacturingfactors

Agile manufacturing factors Ci (rank of TOPSIS)

Delivery speed 0.418Products development 0.525Cost reduction 0.780Market research 0.970Product quality 1.05Environmental pressure 1.12Employee empowerment 1.19Flexibility 1.34Information technology 2.65

Table VII.TOPSIS rank of agiledistribution factors

Agile distributing factors Ci (rank of TOPSIS)

Market research 0.652Quality 0.657Delivery speed 0.719Customer satisfaction 0.773relationship 0.804Information technology 1.04Environmental pressure 1.14Optimum cost 1.57Flexibility 2.31

IJPHM9,1

86

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

cost reduction, quality, market research, flexibility, use of IT tools and environmentalpressure.

According to Sharifi and Zhang (1999), delivery speed will directly increase the speedof supply chain. Certainly, each business wants to reduce costs because it has manypositive effects. In the agile supply chain, decrease of the costs both inside theorganization and even outside the organization, which directly or indirectly affects costof the finished product is the strategic goal (Cooper and Slagmulder, 1998). According toAgarwal et al. (2007), cost reduction can promote accountability of supply chain as well.According to most definitions of agility, it can be seen that they have directly orindirectly concentrated on flexibility (Christopher, 2000). Studies (Sharifi and Zhang,1999; Swafford et al., 2006, 2008) have shown that flexibility can remarkably promotethe responsiveness of supply chain.

Quality considered as a vital factor of pharmaceutical manufacturer was recognizedas another fundamental factor in this study and closely relates to good manufacturingpractice, which has been reinforced by regulatory body to assure the quality of drugsuntil they reach end users. Furthermore, quality is generally accepted as an essentialfactor, besides efficacy and safety, almost in any country in the world, according to theNational Drug Policy, such that pharmaceutical manufacturers must consider this issueseriously along with drug supply chain (Friedli et al., 2010). Agarwal et al. (2007) believethat agile supply chain can effectively increase quality of pharmaceutical products, and,as a result, patient satisfaction could be achieved. In the present study, market researchand monitoring along with sub-indices (sale feedback, customers’ requirement andforecasting) were identified as the most and influential factors of shaping agile supplychain in pharmaceutical sector, and they are in line with several works which haveshown the ability of this case to increase responsiveness, flexibility and agility of supplychain (Sharifi and Zhang, 1999; Christopher, 2000; Gunasekaran et al., 2008). Finally, inthe obtained supply agility model, the last identified effective factor generally uses ITtools (UIT), while Breu et al. (2001) stated that information systems are integral parts ofagile supply chain and they will increase its speed and flexibility.

7. Managerial implicationsDuring the recent decades, SCM has become a popular agenda for both pharmaceuticalindustry and non-pharmaceutical industry. Factors such as globalization, outsourcing,single sourcing, just-in-time SCM and lean and agile supply chain have made PSC moresensitive to the environment. As such, to survive and make progress in the twenty-firstcentury economy, pharmaceutical companies should learn how to manage the ongoingchallenges in their environment. More specifically, pharmaceutical firms must deeplymanage their supply chain to become resilient to unexpected disruptions in theirenvironment. Finally, it should be said that firms must extensively pay attention to theirsupply chain operations due to unbelievable relationships between response toconsumer’s requirements and firm’s success (like profitability and corporate socialresponsibility).

ReferencesAgarwal, A., Shankar, R. and Tiwari, M.K. (2006), “Modeling the metrics of lean, agile and leagile

supply chain: an ANP- based approach”, European Journal of Operational Research,Vol. 173 No. 1, pp. 211-225.

87

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Agarwal, A., Shankar, R. and Tiwari, M.K. (2007), “Modeling agility of supply chain”, IndustrialMarketing Management, Vol. 36 No. 4, pp. 443-457.

Ahmad, N., Awan, M.U. and Raouf, A. (2009), “Development of a service quality scale forpharmaceutical supply chains”, International Journal of Pharmaceutical and HealthcareMarketing, Vol. 3 No. 1, pp. 26-45.

Antonio, K.W.L., Richard, C.M. and Yama, E.T. (2007), “The impacts of product modularity oncompetitive capabilities and performance: an empirical study”, International JournalProduction Economics, Vol. 105 No. 1, pp. 1-20.

Baramichai, M., Zimmers, E.W. and Marangos, C.A. (2007), “Agile supply chain transformationmatrix: a QFD- based tool for creating an agile enterprise”, The International Journal ofValue Chain Management, Vol. 3 No. 2, pp. 281-303.

Braunscheidel, M.J. (2005), “Antecedents of supply chain agility: an empirical investigation”, PhDdissertation, The State University of New York, Buffalo, NY.

Breu, K., Hemingway, C.J., Strathern, M. and Bridger, D. (2001), “Workforce agility: the newemployee strategy for the knowledge economy”, Journal of Information Technology, Vol. 17No. 1, pp. 21-31.

Chandrasekaran, N. and Kumar, S.M. (2003), “Pharmaceutical supply chain challenges and bestpractices”, Working Paper, CII – Institute of Logistics, Indian.

Charles, A., Lauras, M. and Wassenhove, L.V. (2010), “A model to define and assess the agility ofsupply chains: building on humanitarian experience”, International Journal of PhysicalDistribution and Logistics Management, Vol. 40 Nos 8/9, pp. 722-741.

Chen, C.T., Lin, C.T. and Huang, S.F. (2006), “A fuzzy approach for supplier evaluation andselection in supply chain management”, International Journal Prod Econ, Vol. 102 No. 2,pp. 289-301.

Christopher, M. (2000), “The agile supply chain: competing in volatile markets”, IndustrialMarketing Management, Vol. 29 No. 1, pp. 37-44.

Christopher, M. and Juttner, U. (2000), “Developing strategic partnerships in the supply chain: apractitioner perspective”, European Journal of Purchasing and Supply Management, Vol. 6No. 2, pp. 117-127.

Cooper, R. and Slagmulder, R. (1998), “Cost management beyond the boundaries of the firm”,Management Accounting, Vol. 79 No. 9, pp. 18-20.

Ertugrul, I. and KarakasoGlu, N. (2008), “Comparison of fuzzy AHP and fuzzy TOPSIS methodsfor facility location selection”, The International Journal of Advanced ManufacturingTechnology, Vol. 39 Nos 7/8, pp. 783-795.

Friedli, T., Goetzfried, M. and Basu, P. (2010), “Analysis of the implementation of total productivemaintenance, total quality management, and Just-In-Time in pharmaceuticalmanufacturing”, Journal of Pharmaceutical Innovation, Vol. 5 No. 4, pp. 181-192.

Garattini, L., Cornago, D. and De Compadri, P. (2007), “Pricing and reimbursement of in-patentdrugs in seven European countries: a comparative analysis”, Health Policy, Vol. 82 No. 3,pp. 330-339.

Giachetti, R.E., Martinez, L.D., Saenz, O.A. and Chen, C.S. (2003), “Analysis of the structuralmeasures of flexibility and agility using a measurement theoretical framework”,International Journal of Production Economics, Vol. 86 No. 1, pp. 47-62.

Gosling, J., Purvis, L. and Naim, M.M. (2010), “Supply chain flexibility as a determinant of supplierselection”, International Journal of Production Economics, Vol. 128 No. 1, pp. 11-21.

Gunasekaran, A., Lai, K. and Cheng, T.C.E. (2008), “Responsive supply chain: a competitivestrategy in a networked company”, Omega, Vol. 36 No. 4, p. 549.

IJPHM9,1

88

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Hair, J.F.J., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis,Prentice-Hall, Upper Saddle River, NJ.

Hakonsen, H., Horn, A.M. and Toverud, E.L. (2009), “Price control as a strategy for pharmaceuticalcost containment – what has been achieved in Norway in the period 1994 –2004?”, HealthPolicy, Vol. 90 Nos 2/3, pp. 277-285.

Handfield, R.B. and Bechtel, C. (2002), “The role of trust and relationship structure in improvingsupply chain responsiveness”, Industrial Marketing Management, Vol. 31 No. 4,pp. 367-382.

HDMA. (2009), The Role of Distributors in the Us Healthcare Industry, Healthcare DistributionManagement Association, Center for Healthcare Supply Chain Research, Arlington, VA.

Hwang, C.L. and Yoon, K. (1981), Multiple Attributes Decision Making Methods and Applications,Springer, Berlin.

Ismail, H.S. and Sharifi, H. (2006), “A balanced approach to building agile supply chains”,International Journal of Physical Distribution and Logistics Management, Vol. 36 No. 6,pp. 431-444.

Ismail, H., Raid, I., Mooney, J., Poolton, J. and Arokiam, I. (2007), “How small and mediumenterprises effectively participate in the mass customization game”, IEEE Transactions onEngineering Management, Vol. 54 No. 1, pp. 86-97.

Jackson, M. and Johansson, C. (2003), “An agility analysis from a production system perspective”,Integrated Manufacturing Systems, Vol. 14 No. 6, pp. 482-488.

Kaplan, R.M. (1987), Basic Statistics for the Behavioral Sciences, Allyn and Bacon, Boston, MA.

Karimi, A.R., Mehrdadi, N.S., Hashemian, J., Nabi-Bidhendi, G.R. and Tavakkoli-Moghaddam, R.(2011), “Using of the fuzzy TOPSIS and fuzzy AHP method for wastewater treatmentprocess selection”, International Journal of Academic Research, Vol. 3 No. 1, pp. 737-745.

Lin, T.C., Chue, H. and Chu, P.Y. (2006), “Agility index in the supply chain efficiency”,International Journal of Production Economics, Vol. 100 No. 2, pp. 285-299.

Lou, P., Zhou, Z. and Chen, Y. (2005), “Study on coordination in multi-agait- based agilemanufacturing paradigms in the total supply chain management”, Proceedings of 2005International Conference on Machine Learning and Cybernetics, Vol. 1 Nos 18/19/20/21,pp. 171-175.

Mehralian, G., Nazari, J.A., Akhavan, P. and Rasekh, H.R. (2014), “Exploring the relationshipbetween the knowledge creation process and intellectual capital in the pharmaceuticalindustry”, The Learning Organization, An International Journal, Vol. 21 No. 4,pp. 258-273.

Mehralian, G., Rasekh, H.R., Akhavan, P. and Ghatari, A.R. (2013), “Prioritization of intellectualcapital indicators in knowledge-based industries: evidence from pharmaceutical industry”,International Journal of Information Management, Vol. 33 No. 1, pp. 209-216.

Mehralian, G.H., Rajabzadeh, A., Morakabati, M. and Vatanpour, H. (2012a), “Developing asuitable model for supplier selection based on supply chain risks: an empirical study fromIranian pharmaceutical companies”, Iranian Journal of Pharmaceutical Research, Vol. 11No. 1, pp. 209-219.

Mehralian, G.H., Rajabzadeh, A., Sadeh, M.R. and Rasekh, H.R. (2012b), “Intellectual capital andcorporate performance in iranian pharmaceutical industry”, Journal of Intellectual Capital,Vol. 13 No. 1, pp. 138-158.

Patil, R.J. (2006), “Improved techniques for due date quotation in realistic productionenvironments”, PhD dissertation, University of Colorado.

89

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Qureshi, M.N., Kumar, D. and Kumar, P. (2008), “An integrated model to identify and classify thekey criteria and their role in the assessment of 3PL services providers”, Asia Pacific Journalof Marketing and Logistics, Vol. 20 No. 2, pp. 227-249.

Rasekh, H.R., Mehralian, G. and Vatankhah-Mohammadabadi, A.A. (2012), “Situation analysis ofR & D activities: an empirical study in Iranian pharmaceutical companies”, Iranian Journalof Pharmaceutical Research, Vol. 11 No. 4, pp. 1013-1025.

Ren, J., Yusuf, Y.Y. and Burns, N.D. (2001), “Organizational competitiveness identifying thecritical agile attributes using principal componentanalysis”, 16th International Conferenceon Production Research, ID 0588, 29 July–3 August, Prague, Czech Republic.

Rossetti, C.L., Handfield, R. and Dooley, K.J. (2011), “Forces, trends, and decisions inpharmaceutical supply chain management”, International Journal of Physical Distributionand Logistics Management, Vol. 41 No. 6, pp. 601-622.

Saraph, J.V., Benson, P.G. and Schroeder, R.G. (1989), “An instrument for measuring the criticalfactors of quality management”, Decision Sciences, Vol. 4, pp. 810-829.

Schneller, E.S. and Smeltzer, L.R. (2006), Strategic Management of the Health Care Supply Chain,Jossey-Bass, San Francisco, CA.

Shabaninejad, H., Mehralian, G.H., Rashidian, A., Baratimarnani, A. and Rasekh, H.R. (2014a),“Identifying and prioritizing industry-level competitiveness factors: evidence frompharmaceutical market”, DARU Journal of Pharmaceutical Sciences, Vol. 22 No. 35, pp. 1-17.

Shabaninejad, H., Mirsalehian, M.H. and Mehralian, G.H. (2014b), “Development of an integratedperformance measurement (PM) model for pharmaceutical industry”, Iranian Journal ofPharmaceutical Research, Vol. 13 No. 1, pp. 207-215.

Shah, N. (2004), “Pharmaceutical supply chains: key issues and strategies for optimization”,Computers and Chemical Engineering, Vol. 28 Nos 6/7, pp. 929-941.

Shao, X. and Ji, J. (2006), “Reconfiguration of pharmaceutical logistics operations in China: anempirical study”, Transportation Journal, Vol. 45 No. 4, pp. 52-66.

Sharifi, H. and Zhang, Z. (1999), “A methodology for achieving agility in a manufacturingorganization: an introduction”, International Journal of Production Economics, Vol. 62 Nos1/2, pp. 7-22.

Sharp, J.M., Irani, Z. and Desai, S. (1999), “Working towards agile manufacturing in the UKindustry”, International Journal of Production Economics, Vol. 62 Nos 1/2, pp. 155-169.

Stewart, G. (1997), “Supply-chain operations reference model (SCOR): the first cross industryframework for integrated supply-chain management”, Logistics Information Management,Vol. 10 No. 2, pp. 62-67.

Swafford, P. (2003), “Theoretical development and empirical investigation of supply chainagility”, PhD dissertation, The Georgia Institute of Technology, Athens, GA.

Swafford, P.M., Ghosh, S. and Murthy, N.N. (2006), “A framework for assessing value chainagility”, International Journal of Operations and Production Management, Vol. 26 No. 2,pp. 118-140.

Swafford, P.M., Ghosh, S. and Murthy, N.N. (2008), “Achieving supply chain agility through ITintegration and flexibility”, International Journal of Production Economics, Vol. 116,pp. 288-297.

Tseng, Y.H. and Lin, C.T. (2011), “Enhancing enterprise agility by deploying agile drivers,capabilities and providers”, Information Sciences, Vol. 181 No. 17, pp. 3693-3708.

White, A.D. and Mohdzain, M.B. (2009), “An innovative model of supply Chain management: asingle case study in the electronic sector”, International Journal of Information Technologyand Management, Vol. 8 No. 1, pp. 69-84.

IJPHM9,1

90

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)

Yang, T. and Hung, C.C. (2007), “Multiple-attribute decision making methods for plant layoutdesign problem”, Robotics and Computer-Integrated Manufacturing, Vol. 23 No. 1,pp. 126-137.

Yeung, A.C.L. (2008), “Strategic supply management, quality initiatives, and organizationalperformance”, Journal of Operations Management, Vol. 26 No. 4, pp. 490-502.

Yu, X., Li, C., Shi, Y. and Yu, M. (2010), “Pharmaceutical supply chain in China: current issues andimplications for health system reform”, Health Policy, Vol. 97 No. 1, pp. 8-15.

About the authorsGholamhossein Mehralian is Assistant Professor in the Pharma Management andPharmacoeconomics Department, School of Pharmacy, Shahid Beheshti University of MedicalSciences, Iran. He is Pham-D and received his PhD in Pharma Management andPharmacoeconomics from School of Pharmacy, Shahid Beheshti University of Medical Sciences,Iran. He has more than 25 papers in organizational behavior, management, drug supply chain aswell as pharmaceutical policy and practice, which published in peer-reviewed journals.Gholamhossein Mehralian is the corresponding author and can be contacted at:gmehralian@gmail.com

Forouzandeh Zarenezhad is a Researcher in Tarbiat modaress Unviersity, Tehran, Iran. She isstudent of DBA degree in Entrepreneurship in Tehran University, Tehran, Iran. She receivedMBA degree in Strategy in Science and Culture university, Tehran, Iran. Her research interests arein entrepreneurship, strategic planning, leadership and supply chain management. She haspublished five papers in ISI journals.

Ali Rajabzadeh Ghatari is associated as a Professor in Operation Management at TarbiatModares University. He has graduated in Industrial Management from Petroleum University ofTechnology for bachelor degree. His Master degree is in Business Administration and he receivedhis PhD in Operation Management from Tarbiat Modares University. He has done more than 20different research projects related to different fields in management such as operationmanagement, IT management, productivity and strategies. He has more than ten books and morethan 70 research papers in different managerial and IT fields.

For instructions on how to order reprints of this article, please visit our website:www.emeraldgrouppublishing.com/licensing/reprints.htmOr contact us for further details: permissions@emeraldinsight.com

91

Model for anagile supply

chain

Dow

nloa

ded

by U

NIV

ER

SIT

Y O

F O

TA

GO

At 0

1:37

02

Apr

il 20

15 (

PT)