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Decision Support Systems 53 (2012) 142–153
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Decision Support Systems
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Prioritization and management of inter-enterprise collaborative performance
María-José Verdecho ⁎, Juan-Jose Alfaro-Saiz, Raul Rodriguez-RodriguezResearch Centre on Production Management and Engineering (CIGIP), Department of Business Organization, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain
⁎ Corresponding author at: Department of Businesss/n, Building 7D, Universitat Politècnica de València, 46963877007— internal 76888; fax: +34 963877689.
E-mail address: [email protected] (M.-J. Verd
0167-9236/$ – see front matter © 2011 Elsevier B.V. Alldoi:10.1016/j.dss.2011.12.011
a b s t r a c t
a r t i c l e i n f oArticle history:Received 2 August 2010Received in revised form 16 September 2011Accepted 24 December 2011Available online 3 January 2012
Keywords:Performance managementCollaborationAnalytic network processCase studyRenewable energy sector
Collaboration among enterprises has gained attention in the business environment as a means to remaincompetitive. Enterprises that are collaborating look for improving their performance but, in real assessments,they often do not establish efficient frameworks to structure and manage the enterprise association/inter-en-terprise performance. This paper provides a methodology based on the Analytic Network Process (ANP) toprioritize and manage, within a performance management framework, inter-enterprise performance. In ad-dition, this approach allows managing the evolution of the performance status by introducing a model for ag-gregating actual performance data so that decision makers can evaluate the status of the collaborativerelationship and analyze the degree of achievement of the strategy. With this innovative approach, enter-prises will obtain significant information for the decision-making process regarding which are the inter-enterprise performance elements that generate a higher impact and, therefore, should be prioritized for im-proving the enterprise competitiveness. This approach has been applied to a collaborative enterprise networkbelonging to the renewable energy sector in Spain where managers of the network have validated the resultsobtained as well as the benefits of the approach in supporting the decision making process.
© 2011 Elsevier B.V. All rights reserved.
1. Introduction
Global competition, more exigent specifications of products, andfast technological changes are some of the factors that are boostingenterprises to adopt new business models to remain competitive. Inthis context, some enterprises that traditionally operated with theirsuppliers following a transactional relationship have adopted collab-orative initiatives [16]. Mentzer [28] defines supply chain collabora-tion as ‘a means by which all companies in the supply chain areactively working together towards common objectives, and is charac-terized by sharing information, knowledge, risk and profits’. This im-plies that independent firms are jointly working to align their supplychain processes with the goal of creating value to end customers andstakeholders with greater success than acting alone [39] and involvesstrategic joint decision-making about partnerships and network de-sign [26].
However, enterprises that desire to collaborate or are collaborat-ing often do not establish efficient mechanisms to manage the perfor-mance of the enterprise association, called global or inter-enterpriseperformance, which can be managed through performance measure-ment elements. In these contexts, it is important to define inter-enterprise performance measurement elements (objectives, perfor-mance indicators, etc.) in order to support the decision-making
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process of all the members towards the achievement of the common-ly agreed objectives [6,8,42]. Defining common objectives is clearly aniterative process that has to be addressed by negotiation–prioritiza-tion and reaching consensus by all the collaborative partners. Theymust assure a win-win situation if they desire to maintain collabora-tion in the long time. Otherwise the collaboration will probably notsucceed. Regarding the definition of inter-enterprise performancemeasurement elements is better done by using a structured perfor-mance measurement framework, such as the Balanced ScoreCard(BSC) by Kaplan and Norton [19].
In addition, it is suggested that all enterprises collaborating shouldadopt a business process approach as the main goal of each businessprocess is to satisfy customer requirements [20]. Developing such aperformance framework structure provides an overall picture of thedeployment of the strategy from the strategic level to the processlevel. Once this overall performance picture is established, decisionmakers usually deal with two important issues: prioritization of per-formance objectives, and performance data acquisition and aggrega-tion. Despite the importance of these activities, the BSC presentssome limitations for both issues, consolidating data from perfor-mance elements [1,21] and assigning weights to them [44]. It is im-portant to deal with these issues in order to get an adequate BSCimplementation. On the one hand, the prioritization of objectives isnecessary for allocating resources to them. On the other hand, oncethe objectives are ranked and performance data gathered from theirperformance indicators, it is useful to aggregate such data in orderto obtain a global performance evaluation that will show whetherthe status of the collaborative association is satisfactory or not. For
143M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
that purpose, after the global performance evaluation is obtained, it isnecessary to analyze further if performance is reached through thoseobjectives that have priority, as they are the ones that sustain the en-terprise competitiveness. Furthermore, performance elements withina performance measurement framework present interrelationshipsamong them that are to be considered [17,33].
The aim of this paper is to provide an approach that supportsdecision-making of the enterprises that collaborate (or desire to doit), based on the Analytic Network Process (ANP), developed bySaaty [35], to manage inter-enterprise collaborative performance bystructuring, under a performance management framework, inter-enterprise performance elements at both the strategic and the pro-cess level, considering their interrelationships in order to: 1) providean overall prioritization of their elements so that decision makers canfocus on those elements more relevant for their competitiveness; and2) generate an overall performance evaluation of the status of the col-laborative relationship, allowing to analyze whether the priority ele-ments are contributing the most to the consecution of theperformance of the collaborative association. The main contributionof this paper is to provide enterprises an structured approach thatpresent relevant information for the decision-making process sothat enterprises collaborating would be able to monitor their overallperformance as well as analyze which are the most important aspectsthat influence their competitiveness and how these aspects are in factcontributing to achieve the strategy of the collaborative enterprises.
The structure of this paper is as follows. Firstly, a literature reviewregarding the theory and application of ANP in general as well as theapplication of ANP for performance measurement is analyzed. Sec-ondly, the developed approach is described. Then, the application ofthe methodology to a case study is exposed. Finally, conclusions andresearch implications are presented.
2. Literature review
The BSC was initially developed for managing performance of en-terprises but different authors have extended its structure for inter-enterprise performance management [5,8,9,12]. In addition, thereare other performance measurement frameworks developed forinter-enterprise contexts following a non-BSC structure e.g. [10] and[14]. What is common to all of them is that their frameworks presentdifferent levels of decomposition/traceability of performance ele-ments, such as the strategic and process levels, in a low or high de-gree of detail. Then, they are useful structures for defining andmonitoring performance but they lack of mechanisms that providean overall prioritization of their elements and generate an overallperformance evaluation of the status of the enterprises. Therefore,these frameworks should be extended for covering these two issues.
From a methodological point of view, ANP is a muticriteria deci-sion analysis method that represents a decision making problem asa network of elements grouped into clusters. All the elements in thenetwork may have influences among them. Then, it is possible tomodel influences among elements belonging to the same cluster aswell as influences among elements belonging to different clusters.All the influences among elements are represented in a supermatrixthat is a two-dimensional matrix with all the elements in both rowsand columns. After some adjustment is done in the supermatrix tomake it stochastic and raising it to powers until stabilizes, it isobtained the global priorities of the elements. Those global prioritiesare ordered to show the ranking of elements (priority of the ele-ments). More details on the ANP method can be found in Saaty [35].The ANP method has been widely used in decision-making problemsof different fields such as R&D project evaluation [18], financial crisisforecasting [30], energy policies selection [15], asset appraisal [7],strategic e-business decision analysis [31], transportation-mode se-lection [41] and selection of technology acquisition [23].
Regarding performancemeasurement,multi-criteria decision analy-sis methods are useful for performancemeasurement applications [21].Specifically, ANP has been recently applied for performance manage-ment applications at both intra-enterprise and inter-enterprise con-texts. Within inter-enterprise performance measurement, some worksaim at selecting the best alternative that provide the highest supplychain performance [3,4,27,36,37]. Cheng and Lee [11] propose a modelto prioritize the collaboration factors depending on the phase of the col-laboration relationship (formation, application or reactivation). Sarkiset al. [38] define a model to select members for a virtual enterpriseaccording to their main function (design, rawmaterial supplier, manu-facturer, distributor, etc.). However, there is not yet a model developedto manage performance for inter-enterprise contexts using a perfor-mance framework such as the BSC and considering the global influencesamong their elements. This means that the works that use the BSC formanaging performance are only applied at the individual enterpriselevel (intra-enterprise level) [22,24,25,32,40,44]. In addition, theworks that use the BSC for intra-enterprisemanagement only approachit at the strategic level. Therefore, it is still necessary to connect the pro-cess level to the strategic level in order to integrate and manage bothlevels together. Furthermore, only two recently published works[43,44], developed for managing uniquely intra-enterprise perfor-mance, provide a ranking of criteria and aggregation of performancedata into a single unit in order to analyze the overall status of the enter-prise. However, the analysis of the resulting aggregated value is onlyperformed according to the single and final unit of measurement with-out analyzing further whether performance is reached by those aspectsthat had priority, the relevant ones, in order to sustain the competitive-ness of the enterprises. Thus, thesemodels lack of feedback between thefinal aggregation result and high priority performance elements inorder to provide useful information to decision makers. Then, it is pos-sible to affirm that there is not yet a model for managing inter-enterprise performance that considers both strategic and process levelsas well as their relationships and allows the analysis of whether theresulting performance is sustained by the priority areas of the enter-prises (those areas that sustain enterprises competitiveness). Forthese reasons, this paper proposes a novel approach to fill this researchgap. With this approach, enterprises collaborating will have a tool tomanage their performance by focusing their attention on the evolutionof those objectives and performance indicators that have the greatestimpact on their competitiveness.
3. The proposed methodology
The purpose of the methodology is to manage collaborative inter-enterprise performance. The proposed methodology is composed ofthe following five steps:
Step 1. Characterize the collaborative context. This step aims atobtaining a general overview of the inter-enterprise environ-ment and, specifically, the depth and width of the collabora-tion relationships among their members. It must be notedthat certain supply chains may not be suitable for collabora-tive relationships at all. Similarly, the level of suitability forcollaboration differs amongst different channels. In fact, be-cause of the level of commitment necessary, true collabora-tive relationships are anything but widespread [29]. Forthat reason, enterprises should first explore who is the part-ner most convenient to collaborate with.
Step 2. Establishment of the group of experts. The group of expertsshould include people within three types of skills: strategic,process and consultant. Strategic and process profiles are peo-ple from all the enterprises that are collaborating and have ex-pertise on strategic and process issues. The consultant can beeither internal or external to the collaborative enterprises andwill act as organizer and moderator of the meetings for
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deriving and implementing themethodology. It has to be notedthat steps 1 and 2 are interdependent and normally areaddressed iteratively or simultaneously.
Step 3. Definition of the inter-enterprise performance elements. Thisstep consists of the definition of the performance elementsfor the collaborative enterprises as well as their interdepen-dences. Fig. 1 shows the generic framework (adapted from[5]) that supports the methodology which is structured inthree dimensions: perspectives of the BSC, functional levels(interorganizational context and individual enterprises) andperformance elements. It has to be noted that both functionallevels are to be defined in coherence to provide consistentperformance measurement and the definition of the differentelements within the framework should guarantee equityamong the partners in order to achieve the sustainability ofcollaboration in the long time. The different partners have toaddress this issue carefully by reaching consensus and negoti-ating all the aspects involved. This is not an easy task but ifnot addressed in this manner, there is a high probabilitythat the collaboration relationship fails. In addition, perfor-mance elements are defined by deploying the strategic levelto the process level. Both levels are to be defined in coher-ence. Other approximations can be used such as thestrategic-tactical-operational levels used in [14].This step comprises six activities:
Activity 3.1. Define the joint mission and vision of the collabora-tive enterprises. The mission statement establishesthe collaborative relationship's purpose for both theorganizations and the public. Then, the vision is de-fined, which comprises a set of priorities or state-ments for guiding the future joint activity of thecollaborative enterprises. It reflects the expectationsof the collaborative association in the long term. Ithas to be noted that strategic aspects establishment
Fig. 1. Generic f
normally present conflicts of interest among themembers of the collaborative enterprises. Thus, thisactivity comprises a process of iterations by prioriti-zation–negotiation among the partners until consen-sus is reached. This is a highly important activity asstrategy definition will guide the business-operations of the collaborative enterprises.
Activity 3.2. Establish the performance objectives of the strategicframework. These objectives should keep coherencewith the previous elements (mission and vision).The objectives are defined for the four perspectivesof the BSC: financial, customer, process, and innova-tion and learning.
Activity 3.3. Establish the performance objectives of the processframework. Once the strategic framework isobtained, it is developed the process framework,which contains the objectives of the key inter-enterprise processes. Therefore, it is necessary thatthe group of experts identify the key processes inorder to establish the performance objectives,which will be in coherence with the strategic perfor-mance objectives and will be also set for the four per-spectives of the BSC.
Activity 3.4. Identify and represent influences among objectives.The vision statements and objectives belonging tothe four perspectives do present cause–effect rela-tionships, both within a framework as well as be-tween the strategic and the process frameworks.Thus, objectives are linked in a manner that theachievement of one objective influences the achieve-ment of the objectives that are linked to it. In order togain insight into these relationships, it has been dis-tinguished among four types of influences whichjointly represented compose the Inter-enterprise
ramework.
Fig. 3. Sub-map of the Strategic Framework Performance Objectives.
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Performance Objective Map (Fig. 2). This map isstructured into four sub-maps and each sub-maprepresents one type of influences as follows:1. Influences amongperformance objectives belonging
to the strategic framework: sub-map of the StrategicFramework Performance Objectives (Fig. 3).
2. Influences among performance objectives within aprocess (these are influences among objectives ofthe same process): sub-map of Process PerformanceObjectives.
3. Influences among performance objectives of dif-ferent processes (these are influences among ob-jectives of different processes): sub-map of theProcess Framework Performance Objectives.
4. Influences among performance objectives of thestrategic framework and process framework:sub-map of the Strategic Framework-ProcessFramework Performance Objectives.The objectives have been named according to theperspective and framework that they belong to.For example, the objective ILSO1 means that it isthe Innovation and Learning Strategic Objectivenumber 1. The direction of the arrow has a specif-ic meaning. For example, in Fig. 3, the arrow be-tween the objectives ILSO1 and ILSO2 indicatesthat the ILSO1 objective impacts on the achieve-ment of the ILSO2 objective. This criterion has
Fig. 2. Inter-enterprise Perfo
been established to be in coherence with the cri-terion used in the ANP method so that results ofphases 3 and 4 are coherent.
Activity 3.5. Verify coherence. It is verified that performance ob-jectives support the vision and, reciprocally, theachievement of the vision support the achievementof the performance objectives of both the strategicand the process framework. In addition, it is checkedthat objectives of lower perspectives support the ob-jectives of upper perspectives and that the objectivesof the process framework support the objectives ofthe strategic framework. This activity is a verificationtask that is done to assure that the performance ele-ments are consistent within the performance mea-surement framework.
rmance Objective Map.
Table 1Performance objectives of the strategic framework.
Perspective Performance objective
Finance Increase 10% turnover (FSO1)Increase 5% profitability (FSO2)
Customer Increase 15% the power installed by customer (CSO1)Increase 10% the number of new customers by recommendationof old customers (CSO2)
Process Increase 5% the performance ratio of the PV solar plant (PSO1)Reduce 20% total cycle time (PSO2)
Innovation andlearning
Include (at least) a PV module supplier in collaborativerelationship (ILSO1)Increase 10% the degree of anticipation to industry changes(legislation, technological, etc.) (ILSO2)
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Activity 3.6. Define performance indicators. In this activity, per-formance indicators are established to monitor theevolution of every performance objective.
Step 4. Obtain the priorities of the inter-enterprise performance ob-jectives. This step aims at composing, solving and analyzingthe results of the ANP model. This step is composed of the fol-lowing activities:
Activity 4.1. Build the ANP model. Following the ANP method[35], different elements within a network can bestructured into clusters. There will be one clustercontaining the statements of the vision and othercluster containing the performance objectives ofthe strategic framework. In addition, there will beone cluster containing the objectives of each processwithin the process framework. Then, interdepen-dences and feedback among all the elements definedin activity 3.5 are introduced in the model.
Activity 4.2. Complete the pairwise comparison matrices amongelements by using the fundamental scale of Saaty[34]. Pairwise comparison matrices in this case areestablished by consensus although there are othermethods that can be applied for collaborative con-texts such as aggregation of individual judgmentsor voting [2,13,34,35]. In order to facilitate the com-parison process, a questionnaire can be provided tothe experts and, afterwards, responses are translatedinto the numerical scale. Then, for each pairwisecomparison matrix, the eigenvector (priority vector)is calculated and consistency checked [35].
Activity 4.3. Compose the unweighted supermatrix with the ac-cepted priorities from activity 4.2.
Activity 4.4. Complete the pairwise comparison matrices amongclusters following the same procedure as activity4.2. Compose the cluster matrix with the prioritiesof the clusters.
Activity 4.5. Obtain the weighted supermatrix by multiplying thecells of the cluster matrix and the corresponding col-umns of the unweighted supermatrix. If the resultingmatrix is not stochastic, it has to be normalized incolumns so that it converges when raised to powers.
Activity 4.6. Calculate the limit matrix. Raising the weightedsupermatrix to powers until it remains stable yieldsthe limit matrix. Then, global or limit priorities ofthe objectives are obtained.
Step 5. Analysis of results. This step consists in three main activities:Activity 5.1. Classify performance objectives by priority. In this ac-
tivity is necessary to normalize the limit priorities forthe performance objectives obtained in step 4.
Activity 5.2. Obtain overall performance evaluation by multiply-ing the priority of every performance objective(given by the normalized priority) and the valuereached in its corresponding performance indicator.Then, data for all the performance objectives is ag-gregated into a single unit of measurement calledoverall performance.
Activity 5.3. Analyze the degree of achievement of the high prior-ity objectives.
This activity consists in verifying the degree of achievement of themost important objectives in order to get a feedback on the evolutionof the strategic guidelines of the collaborative enterprise.
4. Case study
The case study is carried out in a collaborative enterprise networkbelonging to the renewable energy sector located in Valencia, Spain.
During the last years, this sector has gained importance within theSpanish economy mainly due to government regulations and the ne-cessity to diversify the energy sources. The methodology is explainedwith the application as follows:
Step 1. The enterprise network comprises enterprises with differentfunctions: raw material suppliers, sub-assembly suppliers, anengineering enterprise, and a promoter enterprise. Most ofthem work on different business units, mainly, photovoltaic(PV) solar energy, wind energy, and thermoelectric energy.The application is performed at the PV solar energy businessunit dedicated to the design, construction, operation andmain-tenance of PV solar energy plants. This business unit is themostimportant one for the collaborative enterprise network.
Step 2. The group of experts is composed by operations, financial andproject managers of the enterprises as well as the authors ofthis paper acting as consultants.
Step 3. The mission of the PV solar business unit is to “commercializePV solar installations for private customers and enterprisesfrom the development of projects to the set-up of the installa-tions including their operation and maintenance”. In coher-ence with it, the vision was determined, which wascomposed of three main statements.The first statement is “To become national leader in numberof PV solar plants” (V1). The second statement is “To becomethe most important supplier of high efficiency PV solarplants” (V2). The third statement is “To increase customerportfolio” (V3).After that, performance objectives of the strategic frameworkare defined for the financial, customer, process and innova-tion and learning perspectives (Table 1).The three key inter-enterprise processes of the collaborativeenterprise network are: Definition and feasibility study ofthe project (P1), Project execution (P2) and Customer andother Stakeholders Relationship Management (P3). All threeinter-enterprise processes have been modeled in order to un-derstand the scope of each process previously to define pro-cess objectives. Fig. 4 shows the Business Process ModellingNotation (BPMN) diagram for the P1 process. The upperarea of the diagram shows the five entities taking part inthis process: customer, promoter, Administration, engineer-ing and construction enterprise, and supplier.Table 2 shows the performance objectives for each process ofthe process framework defined for the financial, customer,process and innovation and learning perspectives.Next, the Inter-enterprise performance objective Map is de-veloped to show the relationships among performance objec-tives. Figs. 5 and 6 show the sub-map of the strategicframework performance objectives and the sub-map of thestrategic framework-process framework performance objec-tives. As can be observed in Fig. 5, the objectives that receivethe highest number of influences are “Increase turnover” and
Fig. 4. BPMN diagram for process: definition and feasibility study of the project (P1).
Table 2Performance objectives of the process framework.
Perspective Performance objective
Process: definition and feasibility study of the project (P1)Finance Increase 5% turnover per installed m2 (FPO11)
Reduce 7% construction costs by design (FPO12)Customer Increase 20% customer service (CPO11)
Increase 30% the number of projects that include monitoringsystem by the customer (CPO12)
Process Increase 25% the number of projects that include highefficiency technologies (PPO11)Reduce 30% the time of definition and feasibility study of theproject (PPO12)
Innovation andlearning
Establish contrast meetings with PV module supplier every6 months (ILPO11)Implement a Knowledge Management System (ILPO12)
Process: project execution (P2)Finance Reduce 20% execution costs (FPO21)Customer Increase 10% customer satisfaction (CPO21)
Reduce 40% the number of customer modifications in on-goingprojects (CPO22)
Process Reduce 5% the time to obtain licenses (PPO21)Reduce 30% the time of construction (PPO22)
Innovation andlearning
Establish a standard procedure of execution process (ILPO21)
Process: customer and other stakeholders relationship management (P3)Finance Increase 5% turnover through stakeholder initiatives (FPO31)
Reduce 10% license costs (FPO32)Customer Increase 20% stakeholder satisfaction (CPO31)Process Increase 30% the supplier quality warrants (PPO31)
Increase 15% the number of approved initiatives (PPO32)Innovation andlearning
Improve Public Administration relationships (ILPO31)Build work teams with (at least) three suppliers (ILPO32)
Fig. 5. Sub-map of the Strategic Framework Performance Objectives.
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“Increase the number of new customers by recommendationof old customers”. This fact is not surprising as these are ob-jectives located on the upper perspectives which are sup-ported by the consecution of the objectives located on thelower perspectives. Fig. 6 shows that there are many objec-tives of the process framework that support the consecutionof the strategic framework. In this case, the objectives that re-ceive the highest number of influences are also “Increaseturnover”, belonging to the financial perspective and “In-crease the number of new customers by recommendation ofold customers”, belonging to the customer perspective.Table 3 shows the coherence matrix. In this matrix, the rowsrepresent the condition of dominance and the rows the condi-tion of dominated. Then, if the element eij influences on theelement ekl, the cell that intersects the row and column ofboth elements (aeij, ekl) is filled in with an X. In other case,it is filled in with a 0. It has to be verified that performanceobjectives support the vision and, reciprocally, the consecu-tion of the vision support the consecution of the performanceobjectives of the strategic and process framework. In addition,each objective of the strategic framework is supported by ob-jectives of the process framework and objectives of lower per-spectives support the achievement of the objectives located inthe upper perspectives. Therefore, it is verified that the de-fined vision statements and objectives have a high degree ofcoherence among themselves.
Step 4. Fig. 7 shows the ANP model for prioritization and manage-ment of inter-enterprise collaborative performance. The
network consists of five clusters: vision (VI), strategic objec-tives (SO), objectives of the definition and feasibility studyof the project process (P1), objectives of the execution pro-cess (P2) and objectives of the customer and other stake-holders relationship management process (P3). Arrowsshow the inner and outer dependences among their elementsestablished in step 3. Pairwise comparison matrices wereobtained from the questionnaire filled in by the expert team.
Table 4 shows the pairwise comparison matrix among the ele-ments of the strategic framework cluster with respect to the “Becomethe most important supplier of high efficiency PV solar plants” (V2)vision statement. The eigenvector indicates the importance of eachobjective, and it can be observed that the “Increase profitability”(FSO2) and “Increase turnover” (FSO1) objectives hold the highest ei-genvector weights with 0.3961 and 0.2245 respectively. In addition,the consistency ratio (CR) is 0.059, which means that the expertswere consistent when making their judgments.
Fig. 6. Sub-map of the Strategic Framework-Process Framework Performance Objectives.
148 M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
The summary of all weights from the pairwise comparison matri-ces is shown in the unweighted supermatrix (Table 5).
Next, we obtain the cluster matrix that shows the priorities amongclusters. Then, by multiplying the unweighted supermatrix and thecluster matrix, we obtain the weighted supermatrix that it is normal-ized and raised to powers until it converges, obtaining the limit
Table 3Coherence matrix.
VI SO
V1 V2 V3 FSO1 FSO2 CSO1 CSO2 PSO1 PSO2 ILSO1 IL
VI V1 0 X X X X X X X X X XV2 X 0 X X X X X X X X XV3 X X 0 X X X X X X X X
SO FSO1 X X X 0 0 0 0 0 0 0 0FSO2 X X X 0 0 0 0 0 0 0 0CSO1 X X 0 X X 0 0 0 0 0 0CSO2 X X 0 X 0 0 0 0 0 0 0PSO1 X X 0 0 0 0 X 0 0 0 0PSO2 X X 0 0 0 0 X 0 0 0 0ILSO1 X X X 0 0 0 0 0 X 0 XILSO2 X X X 0 0 X 0 X 0 0 0
P1 FPO11 X X 0 X 0 0 0 0 0 0 0FPO12 X X X 0 X 0 0 0 0 0 0CPO11 X X X 0 0 0 X 0 0 0 0CPO12 X X 0 X 0 0 X 0 0 0 0PPO11 X X 0 X X X 0 X 0 0 0PPO12 X X 0 0 X 0 X 0 X 0 0ILPO11 X X 0 0 0 0 0 X X X XILPO12 X X 0 0 0 0 X X X 0 0… … … … … … … … … … … …
supermatrix. Table 6 shows the limit priorities (LP) of vision state-ments and performance objectives.
In order to provide an overall prioritization of the performance ob-jectives, limit priorities are normalized (Table 7). Then, we obtain thenormalized limit priority (NLP) and the accumulated normalizedlimit priority (ANLP). In the table, the last column indicates the type
P1 …
SO2 FPO11 FPO12 CPO11 CPO12 PPO11 PPO12 ILPO11 ILPO12 …
X X X X X X X X …
X X X X X X X X …
X X X X X X X X …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 0 0 0 0 0 0 0 …
0 X 0 X 0 0 0 0 …
X 0 0 0 0 0 0 0 …
X 0 0 0 0 0 0 0 …
0 0 X 0 0 0 0 0 …
0 X 0 0 X 0 0 0 …
0 0 0 0 0 X 0 0 …
… … … … … … … … …
Fig. 7. The ANP model for prioritization and management of inter-enterprise collaborative performance.
149M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
of objective: critical (C), medium (M) or low (L) importance. The crit-ical objectives are those comprising around 50% of ANPL. These ele-ments are the most important for two reasons. On the one hand,those elements have the highest weights so that they are the most in-fluential ones within the network. On the other hand, those elementsaccumulate around the 50% of the global weight. The medium impor-tance objectives are those that remain between 0.5 and 0.8 of theANPL. Finally, the low importance objectives are between 0.8 and 1of ANPL. These cut-off values were established based on the expertiseof the group of experts. It has to be noted that the limit among classesis determined on the element that is closest to 0.5 and 0.8respectively.
In Table 7, it is observed that the critical objectives are: “Increase5% profitability” and “Increase 10% turnover” belonging to the finan-cial perspective, “Increase 15% the power installed by customer” and“Increase customer satisfaction” within the customer perspective,“Increase 10% the degree of anticipation to industry changes
Table 4Pairwise comparison matrix of the strategic framework objectives for the V2 element.
FSO1 FSO2 CSO1 CSO2 PSO1 PSO2 ILSO1 ILSO2 Eigenvector
FSO1 1 1/3 3 3 5 5 5 5 0.2245FSO2 3 1 5 5 7 7 7 7 0.3961CSO1 1/3 1/5 1 1 3 3 3 1/3 0.0833CSO2 1/3 1/5 1 1 1 3 3 1 0.0807PSO1 1/5 1/7 1/3 1 1 1 1 1/3 0.0423PSO2 1/5 1/7 1/3 1/3 1 1 1 1/3 0.0360ILSO1 1/5 1/7 1/3 1/3 1 1 1 0.0433ILSO2 1/5 1/7 3 1 3 3 1 1 0.0938
CR 0.059
(legislation, technological, etc.)”, “Include (at least) a PV module sup-plier in collaborative relationship” and “Establish contrast meetingswith PV module supplier every 6 months” belonging to the innova-tion and learning perspective. Therefore, the analysis shows how ob-jectives that are not belonging to the financial perspective achievehigh priority because they have a large influence on other perfor-mance objectives. In addition, 5 out of 7 critical performance objec-tives belong to the strategic framework and two critical objectivesto the process framework, specifically to the P1 and P2 processes.
After obtaining the ranking and classification of the objectives,performance data is gathered through the performance indicators as-sociated to those objectives. The frequency of evaluation is set by theexpert team to be done quarterly. Therefore, every quarter, a full per-formance report is provided and analyzed by management. Table 8shows the summary of the overall performance evaluation for thewhole 2009 year and first quarter (Q1) of 2010. In order to aggregatedata, the columns for 2009 and 2010 show the percent of achieve-ment of the performance objective as collected by the performanceindicators. Thus, as shown in 2009 year column, the objective “In-crease 5% profitability” was achieved in 60% as actually profitabilitywas increased by 3% during 2009. The overall performance status(%) is obtained by multiplying the priority of every performance ob-jective (given by the NLP) and its corresponding performanceachieved (%) and, then, adding their value for all the performance ob-jectives. The expert team has established that performance is satisfac-tory if overall performance status is at least 70%, mediumperformance if it ranges between 50 and 70% and low performanceif it is below 50%. In 2009, the overall performance is 68.8% (medium)that is the reason why this cell is yellow colored. Once the overall per-formance evaluation is obtained, the next step consists in analyzing ifthat performance is reached through those objectives that have
Table5
Unw
eigh
tedsu
perm
atrix.
VI
SOP1
…
V1
V2
V3
FSO1
FSO2
CSO1
CSO2
PSO1
PSO2
ILSO
1ILSO
2FP
O11
FPO12
CPO11
CPO12
PPO11
PPO12
ILPO
11ILPO
12…
VI
V1
0.00
000.83
330.75
000.33
330.46
000.33
330.33
330.46
000.25
830.33
330.28
080.46
000.45
450.25
830.58
420.14
290.46
000.28
080.33
33…
V2
0.25
000.00
000.25
000.33
330.31
890.33
330.33
330.31
890.63
700.33
330.58
420.31
890.45
450.63
700.28
080.42
860.31
890.58
420.33
33…
V3
0.75
000.16
670.00
000.33
330.22
110.33
330.33
330.22
110.10
470.33
330.13
500.22
110.09
090.10
470.13
500.42
860.22
110.13
500.33
33…
SOFS
O1
0.25
630.22
450.21
330.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
FSO2
0.36
690.39
610.63
390.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
CSO1
0.10
040.08
330.00
000.25
001.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
CSO2
0.12
750.08
070.00
000.75
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
PSO1
0.02
980.04
230.00
000.00
000.00
000.00
000.50
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
PSO2
0.03
760.03
600.00
000.00
000.00
000.00
000.50
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
ILSO
10.01
930.04
330.04
670.00
000.00
000.00
000.00
000.00
001.00
000.00
001.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
ILSO
20.06
220.09
380.10
620.00
000.00
001.00
000.00
001.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
P1FP
O11
0.38
110.43
550.00
000.51
900.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
FPO12
0.20
710.17
090.25
000.00
000.48
060.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
CPO11
0.16
100.09
100.75
000.00
000.00
000.00
000.57
470.00
000.00
000.00
000.00
000.00
000.12
500.00
001.00
000.00
000.00
000.00
000.00
00…
CPO12
0.03
720.05
470.00
000.17
750.00
000.00
000.17
720.00
000.00
000.00
000.00
000.16
670.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
PPO11
0.09
000.11
100.00
000.30
350.11
401.00
000.00
000.11
110.00
000.00
000.00
000.83
330.00
000.00
000.00
000.00
000.00
000.00
000.00
00…
PPO12
0.05
820.05
470.00
000.00
000.40
540.00
000.10
080.00
000.71
430.00
000.00
000.00
000.00
001.00
000.00
000.00
000.00
000.00
000.00
00…
ILPO
110.03
270.05
000.00
000.00
000.00
000.00
000.00
000.77
780.14
291.00
001.00
000.00
000.87
500.00
000.00
001.00
000.00
000.00
000.00
00…
ILPO
120.03
270.03
220.00
000.00
000.00
000.00
000.14
730.11
110.14
290.00
000.00
000.00
000.00
000.00
000.00
000.00
001.00
000.00
000.00
00…
……
……
……
……
……
……
……
……
……
……
…
Q4
150 M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
priority as they are the ones that decision makers consider most rel-evant for their competitiveness. Then, the final analysis consists inverifying the degree of achievement of the critical objectives or highpriority achievement (%). This parameter is calculated by multiplyingthe priority of every critical performance objective and its corre-sponding performance achieved (%) and, then, adding their valuefor all the critical performance objectives. The resulting value isthen divided by the percentage of the ANPL for the critical objectives.The expert team has established that performance is satisfactory ifhigh performance achievement is at least 75%, medium if it ranges be-tween 50 and 75% and low performance if it is below 50%. In 2009, thehigh priority achievement is 76.9% (satisfactory) that is the reasonwhy this cell is green colored. Regarding 2010 (Q1), it is observedthat overall performance reaches 72.7% (satisfactory). However,high priority achievement is 68.4% and, therefore, the collaborativeenterprises should focus on accomplishing the critical objectives asthe current status is medium and those objectives are key for theircompetitiveness. For that purpose, action plans are to be developedfor increasing the level of achievement of critical objectives until itsstatus is satisfactory. In addition, from the table, it is observed the dif-ferences among the performance achieved (%) by the objectives forboth periods analyzed. Then, the most critical objective “Increase 5%profitability” was accomplished in 60% during 2009 and 50% duringthe Q1 of 2010. This means that with increasing during the lastthree quarters of the year an additional 10%, the level of achievementwill be the same as the one obtained in 2009. For the rest of the crit-ical objectives, a similar situation is observed excepting the “Increase10% customer satisfaction” that has already overcome the levelachieved in 2009 (40% in 2009 and 60% in Q1 2010). Then, the analy-sis is extended to show the evolution of the performance achieved bythe different objectives that, in fact, aids to focus on the objectives tobe improved. Once the objectives that need to be improved are iden-tified, it is possible to identify those partners that have the greatestinfluence in reaching those objectives obtaining an enterprise-specific level feedback.
From the application, it can be observed that analyzing the statusof a collaborative network requires prioritizing objectives; aggregat-ing data into an overall performance and analyzing critical objectivesachievement. Decision makers of the collaborative enterprise net-work agree that the methodology is a tool to manage their perfor-mance over time as well as monitoring the degree of achievementof the common strategy. The different rounds of discussion neededto reach consensus in the definition of the common strategy as wellas in obtaining the judgments for objective prioritization have provid-ed enterprises greatest knowledge of the partners and the needs andwants of their business. This fact is considered of great value for thepartners given the extension and relevance of the aspects treated asthey affect basically strategic aspects and those aspects for improvingefficiency within the network. The expert team agrees that it is veryimportant to monitor the achievement of the performance objectives,especially those identified as critical. In addition, as the enterprise
Table 6Limit priorities.
Vision statementsV1 0.1225 V2 0.1159 V3 0.0995
Performance objectivesFSO1 0.0363 FPO11 0.0060 FPO21 0.0195 FPO31 0.0216FSO2 0.0710 FPO12 0.0074 CPO21 0.0325 FPO32 0.0125CSO1 0.0503 CPO11 0.0131 CPO22 0.0247 CPO31 0.0212CSO2 0.0252 CPO12 0.0018 PPO21 0.0162 CPO31 0.0116PSO1 0.0103 PPO11 0.0108 PPO22 0.0096 PPO32 0.0144PSO2 0.0104 PPO12 0.0129 ILPO21 0.0220 ILPO31 0.0258ILSO1 0.0453 ILPO11 0.0344 ILPO32 0.0290ILSO2 0.0561 ILPO12 0.0104
Table 7Classification of performance objectives.
Rank Performance objectives LP NLP ANLP (%) Class
1 FSO2 Increase 5% profitability 0.0710 0.1072 10.72% C2 ILSO2 Increase 10% the degree of anticipation to industry changes 0.0561 0.0848 19.20%3 CSO1 Increase 15% the power installed by customer 0.0503 0.0760 26.79%4 ILSO1 Include (at least) a PV module supplier in collaborative relationship 0.0453 0.0685 33.64%5 FSO1 Increase 10% turnover 0.0363 0.0548 39.12%6 ILPO11 Establish contrast meetings with PV module supplier each 6 months 0.0344 0.0520 44.32%7 CPO21 Increase 10% customer satisfaction 0.0325 0.0490 49.22%8 ILPO32 Build work teams with (at least) three suppliers 0.0290 0.0438 53.60% M9 ILPO31 Improve Public Administration relationships 0.0258 0.0389 57.49%10 CSO2 Increase 10% the number of new customers by recommendation of old customers 0.0252 0.0380 61.29%11 CPO22 Reduce 40% the nr of customer modifications in on-going projects 0.0247 0.0372 65.02%12 ILPO21 Establish a standard procedure of execution process 0.0220 0.0332 68.34%13 FPO31 Increase 5% turnover through stakeholder initiatives 0.0216 0.0327 71.61%14 CPO31 Increase 20% stakeholder satisfaction 0.0212 0.0320 74.80%15 FPO21 Reduce 20% execution costs 0.0195 0.0294 77.74%16 PPO21 Reduce 5% the time to obtain licenses 0.0162 0.0244 80.18%17 PPO32 Increase 15% the number of approved initiatives 0.0144 0.0217 82.35% L18 CPO11 Increase 20% customer service 0.0131 0.0198 84.34%19 PPO12 Reduce 30% the time of definition and feasibility study of the project 0.0129 0.0195 86.29%20 FPO32 Reduce 10% license costs 0.0125 0.0189 88.18%21 PPO31 Increase 30% the supplier quality warrants 0.0116 0.0176 89.93%22 PPO11 Increase 25% the nr of projects with high efficiency technologies 0.0108 0.0164 91.57%23 PSO2 Reduce 20% total cycle time 0.0104 0.0157 93.13%24 ILPO12 Implement a Knowledge Management System 0.0104 0.0156 94.70%25 PSO1 Increase 5% the performance ratio 0.0103 0.0155 96.25%26 PPO22 Reduce 30% the time of construction 0.0096 0.0146 97.70%27 FPO12 Reduce 7% construction costs by design 0.0074 0.0113 98.83%28 FPO11 Increase 5% turnover per installed m2 0.0060 0.0090 99.73%29 CPO12 Increase 30% the nr of projects with monitoring system 0.0018 0.0027 100.00%
151M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
network did not have already implemented a performance measure-ment framework and now the enterprises are in an advanced devel-opment situation, they have declared their interest in continuingthis activity.
Table 8Performance evaluation.
Performance objectives
FSO2 Increase 5% profitabilityILSO2 Increase 10% the degree of anticipation to industry changesCSO1 Increase 15% the power installed by customerILSO1 Include (at least) a PV module supplier in collaborative relationshipFSO1 Increase 10% turnoverILPO11 Establish contrast meetings with PV module supplier each 6 monthsCPO21 Increase 10% customer satisfactionILPO32 Build work teams with (at least) three suppliersILPO31 Improve Public Administration relationshipsCSO2 Increase 10% the number of new customers by recommendation of old cusCPO22 Reduce 40% the nr of customer modifications in on-going projectsILPO21 Establish a standard procedure of execution processFPO31 Increase 5% turnover through stakeholder initiativesCPO31 Increase 20% stakeholder satisfactionFPO21 Reduce 20% execution costsPPO21 Reduce 5% the time to obtain licensesPPO32 Increase 15% the number of approved initiativesCPO11 Increase 20% customer servicePPO12 Reduce 30% the time of definition and feasibility study of the projectFPO32 Reduce 10% license costsPPO31 Increase 30% the supplier quality warrantsPPO11 Increase 25% the nr of projects with high efficiency technologiesPSO2 Reduce 20% total cycle timeILPO12 Implement a Knowledge Management SystemPSO1 Increase 5% the performance ratioPPO22 Reduce 30% the time of constructionFPO12 Reduce 7% construction costs by designFPO11 Increase 5% turnover per installed m2CPO12 Increase 30% the nr of projects with monitoring systemOverall performance (%)High priority achievement (%)
5. Conclusions and research implications
This study has developed an approach for prioritizing and manag-ing inter-enterprise collaborative performance under a performance
NLP Performance % achievedyear 2009
Performance % achievedQ1 year 2010
0.1072 60 500.0848 80 600.0760 90 850.0685 100 950.0548 85 600.0520 80 750.0490 40 600.0438 60 900.0389 70 60
tomers 0.0380 60 800.0372 50 950.0332 70 900.0327 80 900.0320 60 800.0294 40 800.0244 50 600.0217 40 800.0198 80 600.0195 50 800.0189 40 900.0176 30 800.0164 80 500.0157 90 400.0156 60 600.0155 70 800.0146 75 750.0113 80 850.0090 90 600.0027 60 85
68.8 72.776.9 68.4
152 M.-J. Verdecho et al. / Decision Support Systems 53 (2012) 142–153
measurement framework considering the interrelationships amongperformance elements. From the literature review it has been statedthat there is not an approach developed that aims to manage collab-orative relationships and makes explicit this global network of influ-ences. Thus, this proposal, on the one hand, structures performanceelements under a performance framework and, on another hand, itassociates this framework to an ANP network structure that helps todeal with this issue.
The main contribution of this approach is to provide enterpriseswith a decision support tool to obtain a prioritization of the perfor-mance elements so that decision makers can focus on those elementsmore relevant for their competitiveness. From a practical point ofview, this methodology generates an overall performance evaluationof the status of the collaborative performance so that decision-makerscan analyze whether the critical performance elements are contribut-ing in a high degree to the consecution of the strategy of the collabo-rative association as well as to monitor the evolution of theperformance achievement in different periods. Additionally, collabo-rative enterprises can now know the reasons of why they are notachieving the global performance objectives and what they shouldmake at both the individual and collaborative enterprise levels toovercome this problem. The methodology is applicable to all typesof inter-enterprise associations (virtual enterprise, supply chain,etc.) taking into account that the performance elements definitionwill change depending on the specific context analyzed. Additionally,considering that some specific collaborative relationships may con-sider other performance frameworks different to the BSC, modifica-tions and adaptations should be performed on the methodology inthis case.
The information coming from this study may be used for othermanaging purposes such as resource and budget allocations depend-ing on priority of performance objectives. Other interesting researchline is to integrate the collaborative performance objectives withthe individual enterprise objectives within an overall model. In thiscase, it is necessary to take into account that global supply chain/net-work effectiveness is often overruled by a local efficiency goal of theenterprises. Collaboration initiatives should be preceded by a detailedsupply chain/network analysis that properly balances global versuslocal priorities. Then, performance measurement frameworks imple-mentation should assure the alignment the local priorities to theglobal ones.
Acknowledgments
This work has been developed within the framework of a researchproject partially funded by the Polytechnic University of Valencia, ti-tled “Design and Implementation of Performance Measurement Sys-tems within Collaborative Contexts for aiding the Decision-makingProcess”, reference PAID-06-08-3206.
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Dp
r. María-José Verdecho (Industrial Engineer, M.Sc. in Production, Logistics and Sup-ly Chain Advanced Engineering, PhD) is a lecturer in Operations Management and Op-erations Research at the Polytechnic University of Valencia. She has professionalexperience on service and manufacturing companies, especially on the textile and au-tomotive industry. She is a member of CIGIP (Research Centre on Production Manage-ment and Engineering) and has participated in several research projects about supplychain management, operations management, performance measurement systems andenterprise interoperability at the European and national level. Her research interestsinclude performance measurement systems, operations management, supply chainmanagement and business process modelling. She has published several papers inbooks, journals and conferences in these fields.
Dr. Juan-Jose Alfaro-Saiz is an assistant professor in Operations Management and Op-erations Research at the Polytechnic University of Valencia). He received his doctoraldegree in Industrial Engineering from Universidad Politécnica de Valencia in 2003.He is a member of the CIGIP (Research Centre on Production Management and Engi-neering). His research interests include performance measurement systems, integra-tion enterprise and modelling process business. He has published several papers inbooks, journals and conferences in these fields. He is member of the Association forthe Organization Engineering (ADINGOR). He works as researcher in several SpanishGovernment Projects (CICYT, GV, etc.) and European Projects.
Dr. Raul Rodriguez-Rodriguez (Industrial Management Engineer, MBA, PhD) is a lec-turer in Operations Management and Research at the Polytechnic University of Valen-cia (UPVL). He has worked in several projects about performance management,operations management, supply chain management and information systems in differ-ent activity sectors such as automotive, retail, consumer goods, ceramic or textile. Ad-ditionally, he is a full member of the CIGIP (Research Centre on ProductionManagement and Engineering) at the UPVL, having participated on several researchprojects at European level (ECOSELL, GPM-SME) as well as on national research pro-jects (INPREX, SP7). He lectures in both graduate and undergraduate courses and hisresearch preferences are on performance measurement and management, operationsmanagement and information system management. He is Certified Quality Engineerand a full member of the American Society for Quality. He has published several papersin books, journals and conferences in these fields.
