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Heikkilä,J.:Fromsupplytodemandchainmanagement:efficiencyandcustomersatisfaction.J.Oper.Manage.20,747-767

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Journal of Operations Management 20 (2002) 747–767

From supply to demand chain management:efficiency and customer satisfaction

Jussi Heikkilä∗Helsinki University of Technology, P.O. Box 9555, FIN-02015 Hut, Finland

Abstract

How do companies in the fast-growing industries achieve good customer satisfaction together with efficiency in supplychain management (SCM)? This inductive case study of six customer cases of Nokia Networks, one of the leading providersof mobile telecommunication technology, led to propositions exploring that question. Good relationship between the customerand the supplier contributes to reliable information flows, and reliable demand information flows in turn contribute to highefficiency—these are well-researched issues also in other industry environments. But in a fast-growing systems business suchas mobile telecommunications industry, the supplier needs to be able to adapt its offering to a wide variety of customer situationsand needs. Understanding the customer’s situation and need together with the right offering contributes to good co-operationin improving the joint demand chain, which further leads to superior demand chain efficiency and high customer satisfaction.© 2002 Elsevier Science B.V. All rights reserved.

Keywords:Marketing/operations interface; Logistics/distribution; Time-based competition; Case study research

1. Introduction

One of the main challenges of today’s manufac-turing is to be both efficient and contribute to higheffectiveness, i.e. customer satisfaction. Informationis increasingly available through e-business, customerrelationship management (CRM) and supply chainmanagement (SCM) solutions, making it—at least intheory—possible to serve customers individually withcustomized bundles of goods and services. However,going too far in customization would ruin efficiency.On the other hand, too rigid an approach to SCMwould risk customer satisfaction.

How to find a good balance between good cus-tomer satisfaction and supply chain efficiency? Ouranswer is to start from understanding the situationand need in distinct customer segments—which is not

∗ Tel.: +358-50-376-1090; fax:+358-9-451-3665.E-mail address:jussi.heikkila@hut.fi (J. Heikkilä).

normally the starting point for operations managersto begin their improvement efforts. The next step is todevelop manageable number of alternative modularservice offerings to be adapted to individual cus-tomer situations and needs. The final step is to takethe relationship characteristics into consideration anddevelop a joint improvement agenda together withthe customer to develop optimum operative efficiencywithin the constraints set by the objectives importantfor the customer; and if the joint improvement agendais implemented in good co-operation, high customersatisfaction will follow.

Nokia Networks, one of the leading technologyvendors for mobile telecommunications networks, hasrecently experienced all this. The background of thispaper is a business situation in which Nokia Networksimplemented a demand chain efficiency improvementproject with several of their customers. The companydelivers equipment for their customers’ mobile cellulartelecommunications networks. The cellular network

0272-6963/02/$ – see front matter © 2002 Elsevier Science B.V. All rights reserved.PII: S0272-6963(02)00038-4

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consists of switches, base station controllers and basetransceiver stations (BTS) (more commonly known asbase stations). Base stations are delivered in thousandsto a telecommunications operator’s network. Thereare some hundreds of telecommunications operatorsas customers for all technology vendors globally.

Nokia Networks implemented a demand chain im-provement program called Handshake with severalcustomers. The central elements of the Handshakeprogram were funnel forecasting with the expectationthat the customer could systematically improve itsplanning accuracy over time, removing inventoriesbetween the base station manufacturing plant and thecustomer’s network building operation, and assem-bling the final base station configurations in the plantfor direct delivery to final destinations. The globalsupply chain performance targets set by Nokia Net-works in 1997 (in relative terms for confidentialityreasons) are given inTable 1.

The results of the efficiency improvement projectsinitiated by Nokia were mixed: success in some ofthem and failure in others. The following quotesillustrate the difference in customers’ reactions toNokia’s proposed Handshake program. A successfulAlpha case as described by Alpha’s Section Managerresponsible for their network building with Nokia:

The initial reaction for Nokia’s proposal was a greatsurprise. Nokia had always been very strict aboutthe fixed 4 months lead-time for units. We were likehit by a log when (Nokia’s new Head of Logistics)came and said that the lead-time could be shortenedfrom 4 months to 10 days and configurations de-fined only in the call-off. The flexibility has grownconsiderably. Earlier we were suffering from lackof material and had to live with that. Now the prob-lem has disappeared. Removal of our warehouse has

Table 1Nokia Networks’ global supply chain performance improvementtargets set in 1997 (in relative terms)

Targets 1997 Reductionin 1998 (%)

Reductionin 1999 (%)

Inventory reduction 100 16 34Order fulfillment

lead-time100 79 82

Non-perfect orderfulfillment

100 33 64

also been a big achievement. The right material isdirectly moved to the right destination, there are nomore problems of having wrong materials in ware-houses. On the other hand, we have to do more workin forecasting and planning the configurations.

A less successful Beta case as described by Nokia’sQuality and Processes Manager for Beta:

In our first discussion with Beta Contract Managerconcerning the Handshake project he felt that wewere just trying to save our own costs by takingdown the country warehouse. He asked how muchprice reduction would he get?. . . When Nokiastarted piloting the Handshake project with Beta, thelead-time was reduced from 9 to 4 weeks. Severalmeetings were organized to explain the new modeland the advantages that it would give to Beta, andalso to get Beta’s acceptance to the model. Nokia’scountry organization and Beta set up joint devel-opment work-groups. The work-groups visited bothcompanies, and they met monthly for 1.5 years.However, it took months before the work-groupsstarted really working.. . . Beta did not change itspractice of ordering. They demanded immediate re-duction of lead-time without starting forecasting.

Handshake was a perfect fit for some of the cus-tomers, whereas in other cases there was a seriousmisfit between the support that the customer neededfrom their supplier partner and the improvement pro-gram elements. The resultant question for Nokia washow to tailor their demand chain improvement pro-gram according to the distinct needs and characteris-tics of specific customer segments. The demand chainarchitecture must be robust—in order to apply differ-ent demand chains in different customer situations.

1.1. Objective, research question and unit of analysis

The objective of our research was to increase un-derstanding of factors contributing to well-performingdemand chains in the mobile cellular networks indus-try. The aim was through case study research to findnew perspectives for the demand chain structure andfor the industrial customer–supplier relationships, andhow they influence the demand chain performance ina young, fast-growing industry. The research questionwas as follows:

J. Heikkilä / Journal of Operations Management 20 (2002) 747–767 749

What is the architecture of a well-performing de-mand chain in a young, fast-growing industry, sell-ing systems with varying hardware and softwarecontent to industrial customers?

The main research question was further dividedinto questions of information and material flows,customer–supplier relationships, and demand chainperformance. The unit of analysis was a demandchain for building cellular networks, consisting ofa customer (telecommunications operator), the tech-nology supplier’s organizational units responsible forserving the customer in network building, and thefactory assembling and delivering base stations to thecustomer’s network.

1.2. Supply/demand chain management

The SCM concept extends the view of operationsfrom a single business unit or a company to the wholesupply chain. Essentially, SCM is a set of practicesaimed at managing and co-ordinating the supply chainfrom raw material suppliers to the ultimate customer.The objective of SCM is to improve the entire processrather than focusing on local optimization of particularbusiness units.

A number of researchers suggest that better per-formance can be achieved by consolidating customerand supplier bases, removing unnecessary steps in thechain, speeding up information and material flows,and creating long-term partnerships with major cus-tomers and suppliers to leverage the capabilities ofseveral companies in the chain. Previous manage-ment theory in the area of SCM can be broadlydivided into two main categories. The first cate-gory is studies of primarily the chain structure (e.g.Forrester, 1958, 1961; Burbidge, 1961; Sharman,1984; Sterman, 1989; Towill et al., 1992; Lee andBillington, 1992; Lee et al., 1997a,b; Holmström,1994, 1995; Fisher, 1997). The second group is pri-marily about industrial networks and the relationshipsbetween organizations in the chain (e.g.Williamson,1985; Heide and John, 1990; Mohr and Spekman,1994; Hakansson and Snehota, 1995; Kumar et al.,1995; Dyer, 1996a,b,c, 1997; Monczka et al., 1998).

Some scholars suggest using the termdemand chainmanagementinstead of SCM (Vollmann et al., 1995,1997, 2000; Vollmann and Cordon, 1998). This puts

emphasis on the needs of the marketplace and design-ing the chain to satisfy these needs, instead of startingwith the supplier/manufacturer and working forward.In this research, the emphasis on the customer needs isadopted as the starting point for supply/demand chainmanagement.

1.3. Mobile cellular networks demand chain

The mobile telecommunications industry in 1990swas a fast-growing global industry. New technolo-gies were constantly developed for cellular networksand liberalized markets were growing at rates over50% annually during the latter half of the 1990s.The traditional division of companies in the demandchain—telecommunications operators, suppliers oftelecommunications equipment and systems, andsuppliers of components and modules—changed rad-ically. Deregulation of telecommunications marketsforced operators to focus sharply on competitiveend-user services by increasing the variety of ser-vices. New operators transferred parts of operators’traditional activities to technology suppliers, such asnetwork planning and building, and even operation oftelecommunications networks. At the same time, thesuppliers were also moving up in the value chain. Spe-cialized contract manufacturers developed increasingcapability of offering manufacturing services to al-low telecommunications technology vendors—amongthem Alcatel, Ericsson, Lucent, Motorola, Nokia,Nortel, and Siemens—to concentrate on meeting thechanging needs of the telecommunications operators.

Throughout the 1990s, the leading companies pro-viding technology for the cellular networks industryenjoyed strong growth and good profitability. Compa-nies offering new technologies entered a large numberof fast-growing new markets all over the world. Newsupply chains were quickly built to serve a wide vari-ety of customers.

Building a cellular network engages the customerand the supplier in a business relationship that lastsfor several years. The cellular network consists ofswitches, base station controllers and BTS. The stan-dardization of the technology is not completely open.It is possible to combine switches of one supplier tobase station subsystems (base station controller+BTS)from another supplier, but it is not possible to mixBTSs from several vendors within one base station

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subsystem. This means high switching costs whenchanging from one supplier to another in a geographicarea. However, it happens that the technology vendoris changed during the several years of building and ex-panding a mobile telecommunications network, mean-ing replacement of the old vendor’s technology withthat of the new one.

In our research, we concentrated on the demandchain of BTSs, the most numerous network elementin a cellular network. The process of building a BTSsite starts from network planning. Network planninggives the approximate locations of the BTS sites as abasis for site acquisition and/or provides a list of thesites readily available. Further, network planning de-fines how sites will be connected and related to thebase station controllers. Site acquisition locates threealternative sites for further technical review. One is se-lected, resulting in negotiations for a lease agreementwith the site owner and applying for necessary permitsto build the BTS site. When the lease agreement issigned and the necessary permits granted, constructionworks would start to build the necessary foundations,antenna masts and power supplies. After the construc-tion work is finished, the site is ready for installationof the BTS, antennas and other auxiliary equipment.Either a line in a fixed network or a radio link connectsthe site to base station controller. Finally, the BTS isintegrated operatively into the network.

Many of the steps in the BTS site building and in-stallation process have high uncertainty. It is not al-ways sure that the owner of a site will agree to lease it.It is also uncertain if all the necessary permits will begranted for a site, or, even if the permits are granted,there are questions as to when. Construction and in-stallation times also raise uncertainty. If the network isbuilt using leased lines from the owner of the fixed net-work, receiving the leased lines can also be delayed.For these reasons, network building can be iterative innature. Configuration of an individual site depends onthe neighboring sites. If, for some reason, a plannedsite cannot be used, it can influence the configurationof other sites around it.

The above described complexity, combined withvery rapid and unpredictable growth in the demandfor mobile communication services makes effectiveSCM a challenging task for both the customer and thesupplier. Success in network building requires closeco-operation between the two parties at several stages

of the building process. The supplier needs to be readyto take on varying roles to deal with the customer de-pending on the customer’s objectives, own resources,skills and capabilities.

2. Literature review

2.1. Supply/demand chain structure

Time-based managementand the relationship be-tweenspeedof operations andefficiencyhas been oneof the key issues in operations management literatureduring the 1980s and 1990s (e.g.Stalk, 1988; Stalkand Holt, 1990; Womack et al., 1991; The ToyotaProduction System, 1995). Stalk (1988)describes howtime has become one of the most important sourcesof competitive advantage in manufacturing indus-tries. He describes the background for “Japan’s secretweapon” (Womack et al., 1991) or “lean thinking”(Womack and Jones, 1996) by illustrating how thecompetitive advantage of Japanese manufacturingindustry evolved from low labor costs—throughscale-based strategy, focused factory and flexiblemanufacturing—to time-based competitive advantage.

Stalk describes companies as systems and says thatcompetitive advantage can be achieved by breakingthe “debilitating loop strangling traditional manufac-turing planning”. This means that traditional manu-facturing requires long lead-times to resolve conflictsbetween various jobs or activities that require thesame resources. The long lead-times require salesforecasts to guide planning. Long lead-times make theaccuracy of sales forecasts decline. Forecasting errorsincrease inventories and the need for safety stocks atall levels. Errors in forecasts mean more unscheduledjobs in the production line, increasing the lead-timesfor the scheduled jobs. The planning loop expands,drives up costs, increases delays, and creates systeminefficiencies.

Holmström (1994, 1995)has empirically studiedthe efficiency potential of speed in operations. Hismain results are empirical indications of a strongpositive correlation between speed and efficiency inmanufacturing and that a focus on speed of opera-tions helps expose and remove self-induced sourcesof uncertainty. He claims that the main contributor touncertainty in slow operations is distorted communi-cation in the activity system. Based on his findings of

J. Heikkilä / Journal of Operations Management 20 (2002) 747–767 751

a “speed threshold” he suggests that inventory com-mitment needs to be reduced to a point where demanddistortion is diminished and a synchronization of pro-duction with demand is possible in order to improveperformance by speeding up operations.

One of the main system issues in supply chains isindustrial dynamicsand management of thebullwhip(or Forrester or whiplash or whipsaw) effect. Thisrefers to the phenomenon where orders to the suppliertend to have larger variance than sales to the buyingorganization (i.e. demand distortion), and the distor-tion propagates upstream in an amplified form (i.e.variance amplification). This phenomenon is related tothe information flows among the members in the sup-ply chain. Information flows in terms of orders have adirect impact on the production scheduling, inventorycontrol and delivery plans of individual members inthe supply chain.

Information-feedback systems owe their behaviorto three characteristics—structure, delays and amplifi-cation (Forrester, 1961; Sterman, 1989). The structureof a system tells how the parts are related to one an-other. Delays exist in the availability of information,in making decisions based on the information, and intaking action on the decisions. Amplification usuallyexists throughout systems and it is observed when anaction is more forceful than might seem to be impliedby the information inputs to the system.

Lee et al. (1997b)claim that the bullwhip effectis an outcome of the strategic interactions amongrational supply chain members who are optimizing.They suggest the following sources of the bullwhipeffect: demand signal processing, rationing game, or-der batching and price variations. In the existence ofany of these four sources, bullwhip is caused by ra-tional behavior of the members in the chain. Lack ofinter-company communication combined with largetime lags between receipt and transmittal of informa-tion are at the root of the problem (Metters, 1997).Consequently, solutions to the problem often involveincreasing the abilities of companies to co-ordinateactivity and cut lead-times.

Uncertainty and the nature of the forecasting prob-lem have a considerable impact on the supply chainstructure. According toFisher (1997), the first stepin devising an effective supply chain is to considerthe nature of the demand for the products. If productsare classified on the basis of their demand patterns,

they fall into one of two categories: primarily func-tional or primarily innovative. Each category requiresa distinctly different kind of supply chain. Fisher ar-gues that with their high profit margins and volatiledemand, innovative products require a fundamentallydifferent supply chain than stable, low-margin func-tional products. Two distinct types of functions per-formed by a supply chain should be recognized: aphysical function and a market mediation function. Asupply chain’s physical function is readily apparentand includes converting raw materials into parts, com-ponents, and eventually finished goods, and transport-ing all of them from one point in the supply chain tothe next. Less visible but equally important is marketmediation (demand knowledge), the purpose of whichis to ensure that the variety of products reaching themarketplace matches what consumers need.

Most important in the environment for innovativeproducts is reading market signals correctly and beingable to react quickly during the product’s short lifecycle. The crucial flow of information occurs fromthe marketplace to the chain. The critical decisionsabout capacity and inventory are not about minimiz-ing costs but where in the chain to position inventoryand available production capacity in order to hedgeagainst uncertain demand. Suppliers should be chosenfor their speed and flexibility, not for their low cost(Fisher, 1997).

The first step in designing a responsive supply chainis to accept that uncertainty is inherent in innova-tive products. Uncertainty can be avoided by cuttinglead-times and increasing the supply chain’s flexibil-ity so that it can produce to order or at least assemblethe product at a time closer to when demand material-izes and can be accurately forecast. The company canhedge against the remaining uncertainty with buffersof inventory or excess capacity (Fisher, 1997).

Many recent texts emphasize that the product,manufacturing process and supply chain structureneed to be considered together to create a capabilityfor mass customization (Pine et al., 1993; Lampeland Minzberg, 1996; Feitzinger and Lee, 1997; Fine,1998; Duray et al., 2000). Different industries requiredifferent approaches for customization. The BTS con-figuration and delivery belongs to “menu industries”in the categorization ofLampel and Minzberg (1996).In a menu industry, buyers have a menu of choicesfrom which to select features of the final product.

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Customized standardization tends to be the preferredcustomization strategy in this type of industry. Trans-actions between the buyer and the supplier involvenegotiations and reciprocal relationships betweenbuyers and sellers. Once the configuration has beendecided, the production function assembles prefabri-cated components into finished products.

2.2. Industrial customer–supplier relationships

Texts on supply chain structure typically suggestthat great benefits could be achieved by co-operationbetween the customer and the supplier and giving thesupplier access to the customer’s real demand data.However, asLee et al. (1997b)state, a different prob-lem is under what conditions the customer would bewilling to co-operate with the supplier, to give accessto real demand data and to co-ordinate its orderingpolicies for the benefit of the supplier.

Economists have recognized that ‘resource own-ers increase productivity through co-operativespecialization’ (Dyer, 1997; further Alchian andDemsetz, 1972). Indeed, the supply chains are char-acterized by inter-firm specialization such that indi-vidual firms engage in a narrow range of activitiesthat are embedded in a complex chain of input–outputrelations with other firms. Productivity gains in thesupply chains are possible when firms are willingto make transaction or relation-specific investments(Williamson, 1985; Perry, 1989). Recent empiricalwork confirms that investments in relation-specificassets are often correlated with better performancecompared to more arms-length relationships (Parkhe,1993; Dyer, 1996a).

Recent SCM and relationship marketing researchhas attempted to increase understanding of the condi-tions for win–win partnerships, i.e. customer–supplierrelationships in which close long-term co-operationsimultaneously increases the value produced by thedemand chain and decreases the overall cost of thechain. Several researchers have come to the conclusionthat companies need to divide their customer–supplierrelationships into classes along the continuum from‘arms-length’ relationships to true partnerships(Moody, 1993; Vollmann et al., 1995; Lambert et al.,1996; Cooper et al., 1997; Friis Olsen and Ellram,1997; Bensaou, 1999). While true strategic partner-ships create new value, they are costly to develop,

nurture and maintain. Also, they are risky given thespecialized investments they require (Cooper et al.,1997; Bensaou, 1999). The number of real partner-ships a company can build and maintain is limited.Therefore, partnership type of relationships cannot beexpected to be built with a large number of customersor suppliers, and focusing the resources on buildingthe right relationships requires careful planning anddecision-making.

Commitment refers to the willingness of buyersand suppliers to exert effort on behalf of the relation-ship. Commitment to a relationship is most frequentlydemonstrated by committing resources to the relation-ship, which may occur in the form of an organization’stime, money, facilities, etc. These types of resourcesare often referred to as ‘asset-specific’ resources, inthat they are directed specifically towards the otherparty (Dyer, 1997). Several other studies have alsofound a relationship between resource commitmentand the joint action or continuity between partieswithin inter-organizational relationships (Heide andJohn, 1990; Yoshino and Rangan, 1995). These re-sults suggest that successful partnerships result whenboth buyers and suppliers demonstrate a willingnessto commit a variety of assets to a set of future trans-actions.

Two aspects of communication behavior that ad-dress the extent to which the information exchanged iseffective in a partnership include information sharing,and the level of information quality and participation(Monczka et al., 1998). Both of these aspects of in-formation sharing (quantity and quality) are requiredto successfully develop supplier partnerships. Infor-mation sharing refers to the extent to which criticaland proprietary information is communicated to one’ssupply chain partner (Mohr and Spekman, 1994).Suppliers and customers can form joint developmentteams to improve various aspects in the supply chainor suppliers can suggest changes that may lead toquality or cost improvements (Clark, 1989). Infor-mation quality includes such aspects as the accuracy,timeliness, adequacy, and credibility of informa-tion exchanged (Huber and Daft, 1987). Informationparticipation refers to the extent to which partnersengage jointly in planning and goal setting (Mohrand Spekman, 1994). These information attributes areclosely related and critical in enabling members of apartnership to co-ordinate their activities. The earlier

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mentioned works suggest that successful supplier al-liances are associated with high levels of informationsharing and information quality and participation.

Interdependence exists when one actor does notentirely control all of the conditions necessary forachievement of an action or a desired outcome. Re-source dependence has been explored in empiricalstudies, which investigate the relationship betweendependence and control in buyer–supplier relation-ships (Handfield, 1993). For instance, dealers areless opportunistic when they depend on a primarysupplier, whereas suppliers with control over dealer’sdecisions exhibit greater opportunism (Provan andSkinner, 1989). Resource dependence can also influ-ence supplier just-in-time (JIT) delivery performance(Handfield, 1993). The above literature suggests thatsuccessful partnerships are expected to be character-ized by higher levels of interdependence.

Trust encompasses two essential elements (Kumaret al., 1995): (1) trust in the partner’s reliability, thatis the belief that the partner stands by its word, fulfillspromised role obligations, and is sincere, and (2) trustin the partner’s benevolence, that is the belief that thepartner is interested in the firm’s welfare and will nottake unexpected actions that will negatively affect thefirm. Trust, therefore, exists when a firm believes itspartner is reliable and benevolent. Conflict is behav-ior that impedes, blocks, or frustrates another firm’sgoal pursuit (Kumar et al., 1995). Perceived conflict isthe magnitude of present conflict acknowledged andperceived by the firm.

3. Research method and data collection

Theory building from inductive case research waschosen as an appropriate research approach for thisstudy. The objective is increased understanding of thephenomenon. The research is directed toward devel-opment of testable hypotheses that are generalizablein various application environments. This researchapproach is a suitable method to describe and ex-plore new phenomena (Handfield and Melnyk, 1998;Eisenhardt, 1989) or to build new operations manage-ment theories (Meredith, 1998). This type of theorybuilding relies on direct observations of the objects orparticipants in the theory and its development (Glaserand Strauss, 1967; Yin, 1989). The research approach

is inductive, and utilizes both qualitative and quan-titative data. The case study allows the investigationto retain the holistic and meaningful characteristic ofcomplex real life events (Yin, 1989).

Research constructs direct attention to what shouldbe studied in order to answer the research questions(Yin, 1989). In this research, there are three main con-structs to be operationalized:information and mate-rial flows together forming thestructurein a demandchain, therelationshipbetween an industrial customerand the supplier, and theperformanceof a demandchain. Operationalization of these research constructsis shown inTable 2.

3.1. Case selection and data collection

Six supply chains of Nokia Networks were studiedwith a different customer in each case in a differentEuropean country. These six cases were selected usingthe following criteria:

• The first two cases (customers Alpha and Beta,the names used here to identify the firms arepseudonyms) represented two extremes in supplychain performance in Nokia. The higher perform-ing supply chain (Alpha) represented an indus-trial customer–supplier relationship in which thetwo organizations had co-operated for a relativelylong time, the two organizations had jointly car-ried out a Handshake supply chain improvementproject successfully, and the supply chain perfor-mance was considered good by Nokia’s managers.The lower-performing case (Beta) represented arelationship in which the two organizations hadco-operated for a few years and implementing SCMimprovement was perceived as difficult.

• Another high performing (Delta) and another lowperforming (Theta) case were selected for study af-ter the first two cases were analyzed. The objectivewas to either reinforce or reject patterns emergingfrom the first two cases related to success or failurein supply chain relationships.

• The two other cases (Gamma and Epsilon) that wereselected after the analysis of the first two cases rep-resented relationships that were just recently estab-lished and the customers’ cellular network was notyet fully opened for traffic. Right from the beginningof the relationship, Nokia was trying to implement

754 J. Heikkilä / Journal of Operations Management 20 (2002) 747–767

Table 2Operationalization of the research constructs: data collection protocol for each of the issues

Issues in the research constructs Data collection protocol

Demand chain structureMembers of the demand chain Process description from the interviewsInformation and material flows (delays)

between the membersThe database of order-to-delivery cycles

Sources of delays and distortions in the information flowsDemand signaling Forecasting practice from the interviewsRationing game Forecasting accuracy from the forecasting data and interviewsOrder batching Frequency of ordering from the interviews

Customer–supplier relationshipCommitment to future interaction Duration of the relationship from the interviews

CommunicationAmount of information sharing, information

qualityInformation sharing (both quantity and quality of information) from the survey

Participation Communication patterns from the interviews

Trust Reliability, benevolence and perceived conflict from the survey

Demand chain performanceCustomer satisfaction (effectiveness) Customer respondents’ perception of the support received from the supplier to

achieve customer’s demand chain management objectives—from the surveyEfficiency Delivery lead-times from the database of order-to-delivery cycles

Inventory commitment in terms of days-of-supply from the database oforder-to-delivery cycles and from the interviews. Share of order changes from thedatabase of order-to-delivery cycles and from the interviews

the same lean SCM practices (such as funnel fore-casting, low inventories and assemble-to-order de-liveries of BTSs) as in the Handshake improvementprojects with the customers in the other cases. Inone (Epsilon) of these two new customer relation-ships, Nokia delivered a full turnkey cellular net-work to the customer.

Theory-building research typically combines mul-tiple data collection methods. This triangulationprovides stronger substantiation of constructs andhypotheses (Jick, 1979). Combination of data typesshould be highly synergistic. Quantitative evidencecan indicate relationships, which may not be salientfrom pure qualitative data. Qualitative data is usefulfor understanding the rationale of the underlying re-lationships. In our research, data collection consistedof the following three parts in each of the six cases:

• Quantitative data was collected of the informationand material flows and supply chain performance.(forecasting and delivery data of the BTS volumes, adatabase of 605 order-to-delivery cycles, inventory

commitment in all the supply chains, data of orderchanges in all the six cases).

• Interviewing the supplier and customer rep-resentatives provided qualitative data of thecustomer–supplier relationship (35 informants,out of which 27 were representatives of Nokiacountry organizations and eight represented thecustomers).

• Based on the results of the qualitative interviews,a survey questionnaire was developed and sent torespondents in the customer and supplier organiza-tions in order to collect quantified perceptions of therelationship and co-operation in the network build-ing process (46 responses received for 63 question-naires mailed, 73% response rate).

3.2. Data analysis

Data collection, data analysis and theory buildingwere closely linked in this research, and togetherformed an iterative process. The research processstarted by definition of the research questions and

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selection of initial research constructs based on thepreliminary practical and theoretical understanding ofthe phenomenon studied.

There were three levels of analysis in each of thedata analysis steps of the research process:

• within-case analysis;• cross-case analysis;• expert analysis: presentation and discussion of the

results with the research project steering group con-sisting of industry experts and research advisors.

Within-case analysis of each case involved detailedcase study write-ups for each case. These write-upswere descriptions structured according to the con-structs used in the data collection. They were centralin the generation of the insight into each case, becausethey helped to cope with the analysis process of thelarge volume of data (Eisenhardt, 1989). The writtencase descriptions were essential for the reliability ofthe research. They also enabled the informants toreview the case analysis of each case, thereby im-proving the construct validity. This process allowedthe unique patterns of each case to emerge beforegeneralized patterns across the cases were created.

The three types of data collected—quantitative data,interview responses and survey results—were com-bined in the case study write-ups. All three types ofdata were used as important sources of evidence whendeveloping an understanding of demand chain man-agement in each case; no single type of data was al-lowed to dominate. Descriptive statistical measures(arithmetic mean, S.D., and skew) were calculated forinterpretation of survey results and quantitative data.Because of the research approach used and the rela-tively small sample sizes this was considered as anappropriate way to analyze the quantitative data.

The second level in the case analysis was thesearch for cross-case patterns. In the analysis of thefirst two cases this meant looking at the potentialreasons for differences in the supply chain perfor-mance. This helped to sharpen the research constructsand to focus the data collection in the further stepsof the research. Cross-case analysis of all the sixcases started by analyzing the three types of rela-tionships that were originally used in selecting thecases (successful, non-successful and new demandchains). Within-group similarities were sought firstcoupled with inter-group differences. The second

method used was to compare the cases across theinitial groups. Overall, the idea behind the cross-casesearching method was to force the investigation to gobeyond initial impressions (Eisenhardt, 1989). Also,cross-case searching tactics enhance the probability tocapture the novel findings that may exist in the data.

4. How to combine efficiency and customersatisfaction?

The cross-case analysis results are organized ac-cording to the background of the customer–supplierrelationship in the cases studied (Table 3), and ac-cording to the three main research constructs used toguide the research: demand chain structure (Table 4),customer–supplier relationship (Table 5), and demandchain performance (Table 6).

Refer toTable 3for the comparison of the cases interms of the background of the relationships. For fur-ther illustration, Nokia’s Project Implementation Man-ager for Epsilon and Country Logistics Manager forGamma described the planning challenge in a newdemand chain relationship as follows:

Logistics is a big mess in these projects. Theapproach is too theoretical, not practical enough.Logistics is causing our problems. Putting a com-plete site package together is in principle a goodidea, as suggested in the Handshake model. How-ever, it does not work. In the planning there is70–80% reliability for the following week, but thereis no understanding of the needs for 3 weeks out.Use of site packages is possible in an establishedproject in which the required competencies, sys-tems and planning processes are in place. In a newproject, it is better to start with a big warehouse(that can deliver materials fast).

The following conclusions are made to explain howthe background of the customer–supplier relationshipsmight be related to the demand chain efficiency in thecellular network building:

Competence of the customer, duration of the re-lationship between the customer and the supplierand experience of the employees working on thecustomer–supplier relationship increase demandchain efficiency (this proposition is based on thefinding nos. 1–3, seeTable 3).

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Table 5Relationship characteristics

Communication and trust Alpha Delta Epsilon Gamma Beta Theta Findingnumber

Communication patterns Frequent communication forums established on all levels and in allfunctions between the two organizations

13

Information sharing 14Nokia respondents 4.97 4.43 3.76 5.09 4.78 4.63Customer respondents 5.01 5.01 4.75 4.89 4.66

Reliability 15Nokia respondents 4.91 5.16 3.96 3.90 4.38 4.10Customer respondents 5.68 4.88 2.60 3.27 3.85

Benevolence 16Nokia respondents 4.20 4.12 3.32 3.80 3.93 4.20Customer respondents 5.60 5.00 3.40 3.93 4.70

Perceived conflict 17Nokia respondents 1.75 2.30 5.10 2.63 3.25 4.33Customer respondents 1.90 2.90 3.50 4.00 3.13

The numbers given are arithmetic means of responses from the indicated respondent group. The scale was a 7-point Likert scale with 7representing high and 1 representing low information sharing, reliability, benevolence, and conflict in the relationship with the other party.

The importance of efficiency as a demand chainmanagement objective increases when the networkbuilding stage matures and the growth of the net-work stabilizes. Demand chain efficiency grows be-cause of the increased attention to it (finding nos. 4and 5).

The research data on the demand chain structure inthe six cases are given inTable 4. The following con-clusions are made to explain how the demand chainstructure might be related to the demand chain effi-ciency in the cellular network building:

Lower demand chain efficiency is related tomulti-step forecasting process and consistentover-forecasting from the customer to the supplier’scountry organization and from the supplier’s coun-try organization to the factory (finding no. 6).

Lower demand chain efficiency is related to chang-ing orders, order batching or delay in the orderinginformation (finding no. 7).

The waiting time of a delivery in the target coun-try (customer-specific inventory) is a major part ofthe total inventory commitment in the chain andis related to the overall efficiency of the demand

chains. Removal of a customer-specific inventoryis a “speed threshold” that allows radical improve-ment of supply chain performance (finding no. 10).

The research data on the characteristics of thecustomer–supplier relationships in the six cases isshown in Table 5. In addition to the survey resultsin the table, the following quotes from the interviewinformants in the high-performance Alpha case andthe lower-performing Gamma case indicate consid-erable difference in how trust was perceived in thecustomer–supplier relationships:

There is a spirit of co-operation between Alpha andNokia. Both organizations are willing to do extrawork for the partner in order to help them forward.The contract between the two organizations definesprices, but otherwise it is not followed in every de-tail. An example is failure reports. Alpha wants tohave monthly Nokia’s failure reports for the net-work. This is more often than the contract defines,but we are not going to charge any extra for thisservice. (Nokia Product Manager for Alpha).

Current relationship with Nokia country organiza-tion is improving. Our biggest issue is that we donot feel they are open and honest with us. They

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continue to tell what we want to hear and deliverthe bad news at the 23rd hour. This impacts ourplanning. . . . We feel they need to improve themanagement of their subcontractors and the flow ofmaterials.. . . Their different organizational unitshave conflicting goals, for example site implemen-tation versus logistics. (Gamma Network Planningand Implementation Manager).

The following conclusions are made to explain howthe customer–supplier relationship might influence thedemand chain efficiency in the cellular network build-ing:

Good demand chain efficiency is related to goodtrust between the customer and the supplier, i.e. highreliability and benevolence and low conflict in thecustomer–supplier relationship (this proposition isbased on finding nos. 15–17 inTable 5).

High quantity of information sharing is a necessarybut not always sufficient condition for good qual-ity of information sharing and high demand chainefficiency (finding nos. 13 and 14).

Low perceived reliability of the supplier is inter-preted as low quality of information sharing. Lowerquality of information sharing in the relationship isrelated to lower demand chain efficiency (findingno. 15).

The research data on the demand chain performanceis given in Table 6. The following conclusions aresuggested to explain how the various demand chainperformance issues are related in the cellular networkbuilding:

High demand chain efficiency is not sufficient toexplain the overall customer satisfaction in the cel-lular network building. For example, technologyand its perceived quality might contribute more tothe overall customer satisfaction than demand chainefficiency (finding nos. 21–23).

Radical demand chain improvement requires goodco-operation from the customer. The customer’sclear perceived gain from co-operation is relatedto good success in demand chain improvement(removing customer’s central warehouse is a suf-ficient incentive for the customer to co-operate in

radical improvement; incremental reduction of thesupplier’s demand chain cost is not) (finding nos.24 and 25).

4.1. Cross-case analysis results accordingto effectiveness and efficiency

The cross-case analysis results are summarized inFig. 1. Each of the six cases is positioned in a ma-trix according to the demand chain effectiveness (i.e.the match between the customer need and the demandchain structure) and the demand chain efficiency (i.e.the total inventory commitment from BTS assemblystart until integration to the telecommunications net-work).

The direct BTS delivery Handshake model imple-mented in the Alpha and Delta cases matched wellwith the customers’ situation and need, making thedemand chain structure effective. The following rea-sons contributed to the successful implementation ofthe direct delivery Handshake model:

• There was an established relationship between thecustomers and Nokia. The customers had goodcompetence of working in their industry and market.Organizations and communication mechanismswere well established.

• The network building was in an advanced stage,with stabilized growth, focusing on optimizing thenetwork and building new end-customer features inthe network.

• High information sharing and trust made it possi-ble to work together to improve the demand chainperformance. High gain perceived by the customerof the demand chain improvement project increasedthe motivation of the customers to co-operate.

• The customers had good planning capabilities andthey took responsibility for the planning informa-tion provided by them.

• Because of the good co-operation it was possibleto remove the customer-specific inventory, resultingin major demand chain efficiency improvement andgood customer satisfaction.

Comparison of cases in the same effectivenessgroup results in explanations for efficiency differencesbetween cases. Delta has longer total lead-time, higherinventory commitment and more order changes thanAlpha, even if they operate with the same demand

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Fig. 1. Summary of the cross-case analysis.

chain structure in a comparable customer situationand relationship. Similar findings are made whencomparing the Epsilon, Gamma and Beta cases. Ep-silon demand chain has higher efficiency than theother two demand chains because there is no gamingin the forecasts, there are no delays and no batchingin the ordering process. Beta has lowest efficiency ofthese three cases. It also has the highest consistentbias in forecasting and longest delays in the orderingprocess. For this type of customer, a highly reactivechain is the only possibility, as also demanded byBeta’s Contract and Negotiations Manager:

Flexibility of deliveries is the most important fac-tor influencing the performance of our chain, fol-lowed by on-time delivery and quality. Flexibilitymeans having the possibility to make changes inthe content of the delivery if needed during theagreed lead-time. Sometimes a shorter than agreedlead-time is needed.. . . Lead-time could be reducedif BTS configuration could be made in our coun-try. International transportation takes too long time.Site acquisition and preparation make the site pro-cess uncertain.

Theta forms a special case among the cases stud-ied. In principle, the country warehouse model withBTS modules in the warehouse would be an effectivemodel to support fast network building with high flex-ibility. However, having all elements of low efficiencyin place ruined the effectiveness of the model. Therewas gaming in forecasts, long delays in the orderingprocess and monthly batches in ordering, resulting invery high total inventory commitment, total lead-timeand share of order changes.

5. Toward a model of demand chain management

This case research of the six customer relation-ships in cellular network building indicates thatthere are a variety of customer relationships that thesupplier needs to adapt to. Therefore, the crucialquestion for a supplier is how to design the demandchain architecture according to the needs and char-acteristics of distinct customer needs and situations.Demand chain architecture means understandingthe nature of demand and developing a modular

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demand chain structure—including decisions of theorder-penetration point, inventory buffer locations andsizes, and assembly capacity. The above describedresearch results are next positioned to the existingtheoretical literature of demand chain management.

Stalk (1988)suggests demand chain efficiency canbe improved by reducing the time delays in the flowof information and materials throughout the chain.Holmström (1995)suggests that inventory commit-ment needs to be reduced to a point where demanddistortion is diminished and synchronization of pro-duction with demand is possible in order to improveperformance by speeding up operations. There is noreason to disagree with these overall objectives to im-prove demand chain efficiency. But the research find-ings indicate that reduction of inventory commitmentmight be challenging with a large number of customerseven if it brings radical improvements with some. In-ventory reduction and an effort to speed-up operationscan fail with non-co-operative customers, and resultin lowered trust in the relationship, and further in dis-torted demand information and lowered efficiency.

The research findings comply with those ofForrester (1958, 1961)and Sterman (1989)showingthat the basic structure of a demand chain and de-lays and distortions in the information flows causeinefficiencies in the chain. Also, the findings supportthe results ofLee et al. (1997b)that demand signal-ing, rationing game and order batching are sourcesof distorted information flows and result in chaininefficiencies.

The research findings on the customer–supplier re-lationship comply with the results ofHeide and John(1990) and Mohr and Spekman (1994)that the his-torical length of the relationship increases the conti-nuity expectations, which in turn increase the level ofco-operation (joint action); and that co-operation interms of co-ordination, participation, and joint prob-lem solving (alsoMonczka et al., 1998) are goodpredictors for the success of a partnership.Dyer(1997)also sees continuity as an important factor for asuccessful partnership, through repeated transactionswith a small set of suppliers.

The research results are also consistent with theearlier research in finding high trust between the part-ners being related to good demand chain efficiency.Mohr and Spekman (1994), Dyer (1997), andMonczka et al. (1998)all found trust an important

factor contributing to partnership success. There is adifference between the results of some of the earlierresearch and our findings in the information sharingbetween customer and supplier in industrial relation-ships. Dyer (1997) found that extensive inter-firminformation sharing reduces asymmetric informationand results in lower transaction costs.Monczka et al.(1998) found that bilateral communication behaviorplayed a significant role in determining partnershipsuccess.

No major differences could be observed in thisresearch in the quantity of information sharing be-tween high and low efficiency relationships. It seemsthat information sharing is perceived as open in allcustomer–supplier relationships in cellular networkbuilding, as far as it can be concluded by studying sixrelationships of one supplier in the industry. However,there were differences in how the supplier’s reliabilitywas perceived. Reliability was perceived as higher inthe high efficiency relationships than in the low effi-ciency relationships. A conclusion is drawn here thateven if the quantity of information sharing might bea necessary precondition for well-performing supplychain relationships, it is not always sufficient. Infor-mation sharing quality comes into focus, particularlyin an industry with a large number of new companies,new markets, new employees, and new relationships.

Cellular network systems clearly fall in the cate-gory of “innovative products” in the typology ofFisher(1997). The highly uncertain receptiveness of the mar-ket increases the risk of shortages or excess supplies.The cost of shortages is that the customer loses salesin an emerging (sometimes exponentially growing)market. The high number of final product configura-tions increases the risk of obsolescence and the costof excess supplies.

According to Fisher (1997), the most importantfactor when designing global delivery chains is to un-derstand the behavior of demand in a particular indus-try and organize the chain to serve it accordingly. Insuch an environment, the crucial flow of informationoccurs from the marketplace to the chain. It is impor-tant to cut lead-times to produce the product close tothe time when demand materializes. The critical de-cisions about inventory and capacity are where in thechain to position inventory and available productionand assembly capacity in order to have maximumflexibility to deal with the highly fluctuating demand.

J. Heikkilä / Journal of Operations Management 20 (2002) 747–767 763

Fisher suggests that selection of demand chain struc-ture primarily depends on the industry characteristics.We feel that this is too simple an approach. Based onthe findings of this study, it is suggested that severaldifferent chains are needed within a single industryto meet various customer needs and situations.

This oversimplification by Fisher makes us suggestthat strategic SCM needs to be well integrated with themarket segmentation ideas in marketing. In operationsmanagement,Hill (1994) has earlier talked about thisintegration in the context of manufacturing strategy.Companies require a strategy not based solely on mar-keting, manufacturing, logistics, or any other function,but one that embraces the interface between marketsand functions. The link between functional strategiescomes from the markets the business serves.

SCM must choose its processes and design its in-frastructure in ways that help a company’s bundlesof goods and services to win orders, and that choiceand design must be adaptable to changing businessneeds. Thus, the company as a whole needs to agreeon the markets and segments within these markets inwhich it decides to compete. In no way can these crit-ical decisions be the responsibility of a single func-tion. As a function, marketing will have an importantand essential (but not the only) view. An essential per-spective of a firm’s markets has to come from oper-ations. This perspective is established by determiningthe order-qualifiers and order-winners that operationsneeds to provide (compare toHill, 1994).

Order-qualifiers are the criteria that a firm mustmeet for a customer to even consider it as a possiblesupplier. Order-winners are those criteria that win theorders. In the cellular network building—as in mostother project businesses as well—order-qualifiersare related to the customer’s perception of thesupplier’s capability to fulfill the contract require-ments. Order-winners for new relationships in thistype of high-technology industry are probably of-ten related to technological matters. But essentialorder-winners for continuous business are developedduring the co-operation between the customer and thesupplier when building the network.

For a new operator striving for launching their ser-vices to market, and thereafter aggressively competingfor the market share with the established telecommu-nications operators, speed and support from an expe-rienced technology vendor are above all other criteria.

Efficiency that is perceived to slow down the networkbuilding and expansion is not acceptable. Establishedoperators in an advanced stage of network optimiza-tion are more willing to appreciate the cost advan-tage of a lean supply chain. The technology vendorneeds to understand the differing customer needs andsituations, implement best demand chain structure inco-operation with the customer, and through improvedcustomer satisfaction contribute to better relationshipand co-operation.

The research findings are summarized in the de-mand chain management model presented inFig. 2.The model consists of the following five propositions,emerging from the research of the six cases in the mo-bile telecommunication industry:

Proposition 1. Good relationship characteristicscontribute to reliable information flows.

Proposition 2. Reliable information flows contributeto high efficiency.

Proposition 3. Understanding the customer situa-tion and need and good relationship characteristicscontribute to co-operation between the customer andsupplier.

Proposition 4. Good co-operation in implementingdemand chain improvement contributes to high effi-ciency and high customer satisfaction.

Proposition 5. High customer satisfaction contributesto good relationship characteristics.

The first two propositions state the already well-known relationships in industrial supply chains thatgood customer–supplier relationships contribute toreliable information flows, that in turn result in highsupply chain efficiency. However, this well-knownequation needs stratification for fast-growing systembusinesses, where the high growth results in a largenumber of different types of customers with differentsituations and needs. A technology vendor that wantsto achieve overall good customer satisfaction, needs tounderstand the individual customers’ needs and objec-tives and to be able to support the customer in meetingtheir objectives. Good understanding of the customerneeds builds a good basis for fruitful co-operation

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Fig. 2. The model of demand chain management.

between the customer and the supplier, increasing thedemand chain efficiency and customer satisfaction.

6. Managerial implications

The main argument resulting from this research isthat several demand chain structures are necessary toadapt to varying customer needs and situations. The

Fig. 3. The three alternative demand chain structures suggested to serve different customers in the mobile network business.

following priority order of decision-making criteriawas proposed to design alternative modular demandchain processes:

1. Supporting the customer’s network building pro-cess by sufficiently fast deliveries.

2. Building a product structure to enable decisionson the order-penetration point for a base stationaccording to the customer need.

J. Heikkilä / Journal of Operations Management 20 (2002) 747–767 765

3. Flexibility in the assembly capacity to meet themarket uncertainty.

4. Inventory optimization within the constraintsresulting from the above criteria.

Three demand chain processes as variations ofgeneric demand chain architecture were proposedto serve the different customer needs of Nokia Net-works in the cellular networks industry (Fig. 3). Animportant aspect was to see the alternative processesas modular, supporting a consistent move of particu-lar customer–supplier relationships from one demandchain process to a more advanced one when therelationship characteristics allow.

Increased rate of returns in implementing demandchain management was experienced at Nokia when thepositive feedback of good customer satisfaction feed-ing into the relationship characteristics started takingeffect (Proposition 5in the model, see alsoSterman,2000; Senge and Sterman, 1994; Senge, 1990for mod-eling organizational learning). The original Handshakemodel of Nokia Networks was developed into a newprogram called breakthrough inventory rotation days(BIRD). The BIRD program aimed at improving cus-tomer satisfaction and implementing efficient demandchains for a large number of Nokia Networks’ cus-tomers. By the end of the year 2000, during 1.5 yearsof the BIRD program implementation, about 40% av-erage reduction in inventory levels was reached de-spite of substantial growth in sales. BIRD focused onNokia Networks’ European customers. The new pro-cesses were implemented for customer projects in 17different European countries by the end of year 2000(Tissari and Heikkilä, 2001).

7. Conclusions

Companies in the fast-growing industries need tobe constantly developing their supply chain efficiency.At the same time, they are all the time facing a vari-ety of new customers, with new situations and needs.Our study of six customer cases of Nokia Networksexplored how to combine high supply chain efficiencywith good customer satisfaction. We propose that sup-ply chain improvement should start from the customerend, and the concept of SCM should be changed intodemand chain management.

Demand chain management understands the needfor good customer–supplier relationships and reliableinformation flows as contributors to high efficiency.But in a fast-growing systems business such as mo-bile telecommunications industry, the supplier alsoneeds to be able to adapt its offering to a wide vari-ety of customers. Understanding the customer’s needtogether with the right demand chain structure resultsin good co-operation in improving the joint demandchain, which further leads to superior demand chainefficiency and customer satisfaction.

The current article addresses the process ofdemand chain improvement in the fast-growing,high-technology environment of the mobile telecom-munications industry. This industry is admittedly aspecial case, an environment placing an extraordinaryemphasis on continuous and rapid changes in themode of operations to remain ahead of the competi-tion. However, the ideas here are offered for furtherempirical testing. If they survive these tests, theyprovide learning for all organizations wishing to staycompetitive in this ever-changing world.

References

Alchian, A.A., Demsetz, H., 1972. Production, information costs,and economic organization. American Economic Association62 (5), 777–795.

Bensaou, M., 1999. Portfolios of buyer–supplier relationships.Sloan Management Review 40 (3), 35–44.

Burbidge, J.L., 1961. The new approach to production. TheProduction Engineer 40 (12), 769–784.

Clark, K., 1989. Project scope and project performance: theeffect of parts strategy and supplier involvement on productdevelopment. Management Science 35 (10), 1247–1263.

Cooper, M.C., Ellram, L.M., Gardner, J.T., Hanks, A.M., 1997.Meshing multiple alliances. Journal of Business Logistics18 (1), 67–89.

Duray, R., Ward, P.T., Milligan, G.W., Berry, W.L., 2000.Approaches to mass customization: configurations and empiricalvalidation. Journal of Operations Management 18 (6), 605–625.

Dyer, J.H., 1996a. Specialized supplier networks as a sourceof competitive advantage: evidence from the auto industry.Strategic Management Journal 17 (4), 271–291.

Dyer, J.H., 1996b. Does governance matter? Keiretsu alliances andasset specificity as sources of Japanese competitive advantage.Organization Science 7 (6), 649–666.

Dyer, J.H., 1996c. How Chrysler created an American Keiretsu.Harvard Business Review 74 (4), 42–56.

Dyer, J.H., 1997. Effective inter-firm collaboration: how firmsminimize transaction costs and maximize transaction value.Strategic Management Journal 18 (7), 535–556.

766 J. Heikkilä / Journal of Operations Management 20 (2002) 747–767

Eisenhardt, K.M., 1989. Building theories from case studyresearch. Academy of Management Review 14 (4), 532–550.

Feitzinger, E., Lee, H.L., 1997. Mass customization atHewlett-Packard: the power of postponement. Harvard BusinessReview 75 (1), 116–121.

Fine, C.H., 1998. Clockspeed: Winning Industry Control in theAge of Temporary Advantage. Perseus Books, Reading.

Fisher, M.L., 1997. What is the right supply chain for your product?Harvard Business Review 75 (2), 105–116.

Forrester, J.W., 1958. Industrial dynamics: a major breakthroughfor decision makers. Harvard Business Review 36 (4), 37–66.

Forrester, J.W., 1961. Industrial Dynamics. MIT Press, NY.Friis Olsen, R., Ellram, L.M., 1997. A portfolio approach to

supplier relationships. International Marketing Management26 (2), 101–113.

Glaser, B., Strauss, A., 1967. The Discovery of Grounded Theory:Strategies for Qualitative Research. Aldine, Chicago.

Hakansson, H., Snehota, I., 1995. Developing Relationships inBusiness Networks. Routledge, London.

Handfield, R.B., 1993. A resource dependence perspective ofjust-in-time purchasing. Journal of Operations Management11 (3), 289–311.

Handfield, R.B., Melnyk, S.A., 1998. The scientific theory-buildingprocess: a primer using the case of TQM. Journal of OperationsManagement 16 (4), 321–339.

Heide, J.B., John, G., 1990. Alliances in industrial purchasing:the determinants of joint action in buyer–supplier relationships.Journal of Marketing Research 27 (1), 24–36.

Hill, T., 1994. Manufacturing Strategy: Text and Cases. RichardD. Irwin, Boston.

Holmström, J., 1994. The relationship between speed andproductivity in industry networks: a study of industrial statistics.International Journal of Production Economics 34 (1), 91–98.

Holmström, J., 1995. Speed and efficiency—a statistical enquiryof manufacturing industries. International Journal of ProductionEconomics 39 (3), 185–191.

Huber, T., Daft, R., 1987. The information environment oforganizations. In: Jablin, F., et al. (Eds.), Handbook ofOrganizational Communication. Sage Publications, NewburyPark.

Jick, T.D., 1979. Mixing qualitative and quantitative methods:triangulation in action. Administrative Science Quarterly 24 (4),602–611.

Kumar, N., Scheer, L.K., Steenkamp, J.-B.E.M., 1995. The effectsof perceived interdependence on dealer attitudes. Journal ofMarketing Research 32 (3), 348–356.

Lambert, D.M., Emmelhainz, M.A., Gardner, J.T., 1996. So youthink you want a partner? Marketing Management 5 (2), 24–33.

Lampel, D., Minzberg, H., 1996. Customizing customization. SloanManagement Review 38 (1), 21–30.

Lee, H.L., Billington, C., 1992. Managing supply chain inventory:pitfalls and opportunities. Sloan Management Review 33 (3),65–73.

Lee, H.L., Padmanabhan, V., Whang, S., 1997a. The bullwhipeffect in supply chains. Sloan Management Review 38 (3),93–102.

Lee, H.L., Padmanabhan, V., Whang, S., 1997b. Informationdistortion in a supply chain: the bullwhip effect. ManagementScience 43 (4), 546–558.

Meredith, J., 1998. Building operation management theory throughcase and field research. Journal of Operations Management16 (4), 441–454.

Metters, R., 1997. Quantifying the bullwhip effect in supply chains.Journal of Operations Management 15 (2), 89–100.

Mohr, J., Spekman, R., 1994. Characteristics of partnershipsuccess: partnership attributes, communication behavior, andconflict resolution techniques. Strategic Management Journal15 (2), 135–152.

Monczka, R.M., Petersen, K.J., Handfield, R.B., Ragatz, G.L.,1998. Success factors in strategic supplier alliances: the buyingcompany perspective. Decision Sciences 29 (3), 553–573.

Moody, P.E., 1993. Breakthrough Partnering: Creating a CollectiveEnterprise Advantage. Omneo, Essex Junction, UK.

Parkhe, A., 1993. Strategic alliance structuring: a game theoreticand transaction cost examination of inter-firm co-operation.Academy of Management Journal 36 (4), 794–829.

Perry, M.K., 1989. Vertical integration. In: Schmalensee, R., Willig,R. (Eds.), Handbook of Industrial Organization. North-Holland,Amsterdam, pp. 185–255.

Pine III, B.J., Victor, B., Boynton, A.C., 1993. Making masscustomization work. Harvard Business Review 71 (4), 108–119.

Provan, K., Skinner, S., 1989. Inter-organizational dependenceand control as predictors of opportunism in dealer–supplierrelations. Academy of Management Journal 32 (1), 202–212.

Senge P.M., 1990. The Fifth Discipline: The Art and Practice ofthe Learning Organization. Currency Doubleday, NY.

Senge, P.M., Sterman, J.D., 1994. Systems thinking andorganizational learning: acting locally and thinking globally inthe organization of the future. In: Morecroft, J.D.W., Sterman,J.D. (Eds.), Modeling for Learning Organizations. ProductivityPress, Portland, pp. 195–216.

Sharman, G., 1984. The rediscovery of logistics. Harvard BusinessReview 62 (5), 65–77.

Stalk, G., 1988. Time: the next strategic advantage. HarvardBusiness Review 66 (4), 41–51.

Stalk, G., Holt, T.M., 1990. Competing against time, Free Press,NY.

Sterman, J.D., 1989. Modeling managerial behavior: misperce-ptions of feedback in a dynamic decision-making experiment.Management Science 35 (3), 321–339.

Sterman, J.D., 2000. Business Dynamics: Systems Thinking andModeling for a Complex World. McGraw-Hill, Boston.

Tissari, T., Heikkilä, J., 2001. Successful re-engineering: learningby doing. International Journal of Logistics: Research andApplications 4 (3), 229–344.

Towill, D.R., Naim, M.M., Wikner, J., 1992. Industrial dynamicssimulation models in the design of supply chains. InternationalJournal of Physical Distribution and Logistics Management22 (5), 3–13.

Toyota Motor Co., Int. Public Affairs Division. OperationsManagement Consulting Division, 1995. The Toyota ProductionSystem, Toyota City.

J. Heikkilä / Journal of Operations Management 20 (2002) 747–767 767

Vollmann, T.E., Cordon, C., Raabe, H., 1995. From supply chainmanagement to demand chain management. IMD Perspectivesfor Managers. November.

Vollmann, T.E., Berry, W.L., Whybark, D.C., 1997. ManufacturingPlanning and Control Systems, McGraw-Hill, NY.

Vollmann, T.E., Cordon, C., 1998. Building successful customer–supplier alliances. Long Range Planning 31 (5), 684–694.

Vollmann, T.E., Cordon, C., Heikkilä, J., 2000. Teaching supplychain management to business executives. Production andOperations Management Journal 9 (1), 81–90.

Williamson, O.E., 1985. The Economic Institutions of Capitalism.Free Press, NY.

Womack, J.P., Jones, D.T., 1996. Lean Thinking: Banish Wasteand Create Wealth in Your Corporation. Simon & Schuster,NY.

Womack, J.P., Jones, D.T., Roos, D., 1991. The Machinethat Changed the World: The Story of Lean Production.HarperPerennial, NY.

Yin, R.K., 1989. Case Study Research: Design and Methods. SagePublications, Newbury Park.

Yoshino, M., Rangan, S., 1995. Strategic Alliances: AnEntrepreneurial Approach to Globalization. Harvard BusinessSchool Press, Boston.