Designing a Performance Measurement System for ...

Post print version Citation: Pekkola, S., & Ukko, J. (2016). Designing a performance measurement system for collaborative network. International Journal of Operations & Production Management, 36(11), 1410-1434. Publisher: Emerald Group Publishing Publisher's version can be downloaded at http://www.emeraldinsight.com/doi/pdfplus/10.1108/IJOPM-10-2013-0469

Designing Performance Measurement System for Collaborative Network Pekkola, Sanna; Ukko, Juhani Purpose The study aims to examine how performance measurement system (PMS) can be designed for collaborative network and to identify which factors affect such design. Design/methodology/approach This is single-case study of collaborative network. The data has been collected from semi-structured interviews conducted during 2008 to 2009 and after the design process in 2010 and 2012, respectively. Findings The research results present five-step process model for designing PMS for collaborative network. The findings show that participatory development style that enhances socialisation, the positive development of network culture, and an outside facilitator all have beneficial effects on the design process. Practical implications The practical contribution of this study is related to knowledge about the PMS design process for collaborative network to support its measurement-related development projects. This knowledge involves the phases of such process as well as the various factors supporting or hindering it. Originality/value The study presents PMS design process for the case network, which can be utilised in other collaborative networks in similar context. It also highlights the most essential practical experiences related to this process. Keywords: Performance management, performance measurement system, collaborative network, collaboration

Introduction In the modern world, companies operate in globalised, turbulent and complex markets (Cocca and Alberti, 2010; Barrows and Neely, 2011; Nudurupati et al. 2011; Pekkola, 2013). It is commonly accepted that in order to survive in such competitive environment, companies have to collaborate with one another, focusing on meeting customers’ needs more effectively and efficiently (Bititci et al. 2007, 2012). If companies therefore aim to create and sustain competitive advantage through collaboration, their network structures should be fully understood and managed; otherwise, the objectives will not be achieved and the network will fail (Verdecho et al. 2009). Therefore, network-level performance measurement system (PMS) is needed by collaborating organisations. Unfortunately, only limited empirical research has been conducted on PMSs and their design in small and medium-sized enterprise networks (Yin et al. 2011; Bititci et al. 2012). It is important to apply system-level control mechanisms and performance measurement (PM) tools to network when attempting to manage it. network itself has no intrinsic value; rather, it is tool for organising operations amongst companies. Therefore, recently the networks’ ability to succeed in their tasks has been receiving considerable attention (Bititci et al. 2007; Varamäki et al. 2008; Laihonen et al., 2014). Companies in collaborative network are interested in the benefits and costs of networking, investors are keen on the revenue opportunities involved, and customers in the value chain are concerned with the network’s ability to manage production tasks as well as or better than single, integrated company. This situation leads to the following question: How are networks considered in measurement systems? Previous literature offers frameworks for the overall PM of networks (Beamon, 1999; Leseure et al. 2001; Busi and Bititci, 2006; Varamäki et al. 2008; Laihonen et al., 2014) as well as presenting some models for supply chain PM (Brewer and Speh, 2000; Gunasekaran et al. 2004; Schmitz and Platts, 2004; Bititci et al. 2005; Saiz et al. 2007) and individual measures for customer-supplier boundaries (Ellram, 1995; Beamon, 1999). However, thus far, the need for structured methodology for PMS design for the network environment has not been addressed (Link et al., 2002; Busi and Bititci, 2006; Yin et al. 2011). Link et al. (2002) and Kulmala and Lönnqvist (2006) revealed that many organisations acknowledge the importance of business networks and inter-organisational co-operation. The PMSs often include issues related to customer relationships (e.g. customer satisfaction), supplier relationships (e.g. supplier’s delivery accuracy) and other stakeholders (e.g. stakeholder communication). Strengthening interorganisational relationships creates need for managing such relationships. For example, networklevel PMS could be used to manage business processes and guide actors in the pursuance of the network’s common targets (Cohen and Lee, 1988; Beamon, 1999; Leseure et al. 2001; Busi and Bititci, 2006; Kulmala and Lönnqvist, 2006; Laihonen et al., 2014). Furthermore, information on network-level PM is required for decision making, for example to avoid organisation-level sub-optimisation. Generally speaking, the question regarding collaboration is no longer concerned with whether or not to collaborate, but with the need to understand and select suitable options (Pisano and Verganti, 2008; Bititci et al. 2012). According to Bititci et al. (2012), the PM literature recognises the trend towards inter-organisational work and so warrants the study of PM in collaborative organisations. The measurement of collaborative networks is challenging due to the complex environments of such networks (Lambert and Pohlen, 2001; Bititci et al. 2005; Busi and Bititci, 2006). There are different levels of information needs and various opinions concerning the importance of diverse information (e.g. Lönnqvist and Laihonen, 2012). The boundaries and relationships amongst network partners also influence the network-level PM. Moreover, lack of trust and commitment has been considered key reason for the failure of the design process. The results presented in previous literature (Busi and Bititci, 2006) indicate the need for developing deeper understanding of how and what to measure in collaborative networks. Furthermore, Busi and Bititci (2006) presented the need for research to develop structured methodology for designing PMS for collaborative networks. Based on this identified gap, the present paper addresses the following two research questions: 1) How can performance measurement system for collaborative network be designed?

2) What factors influence the design of network?

performance measurement system for

collaborative

This paper presents case study that uses interviews and participatory research approach to empirically investigate conceptual framework for developing PMS design process in collaborative network. The factors affecting the design are also empirically examined. The study highlights the most essential practical experiences related to this process. The paper concludes by illustrating how the stated goals can be achieved.

Literature review 2.1 Classification of networks Collaboration is concept that describes the closest relationship amongst partners (Parung and Bititci, 2006). Nowadays, it is common for several companies to collaborate in network by sharing data, information, systems, risks and benefits. Although collaboration can be defined in many ways, it generally means working together for mutual benefits (Wernerfelt, 1984; Huxham, 1996; Parung and Bititci, 2006; Camarinha-Matos et al. 2009). The concept is typically used when organisations work together towards common goal. Other terms often used to describe the phenomenon are ‘relationship’, ‘partnership’ and ‘alliance’. Collaboration has been presented as way forward for an organisation when working alone is insufficient to achieve its desired ends (Huxham, 1996). Bititci et al. (2003) listed the following characteristics of collaboration: 1) It is positive form of working in association with others for some form of mutual benefits. 2) It implies positive and purposeful relationship amongst organisations that retain autonomy, integrity and distinct identities, and thus the potential to withdraw from the relationship. 3) It is performed by number of companies that create and support service or product. 4) It focuses on joint planning, coordination and process integration amongst suppliers, customers and other partners in network. It also involves strategic, joint decision making about partnership and network design. 5) It is process in which organisations exchange information, alter activities, share resources and enhance one another’s capacity for mutual benefits and to achieve common purpose by sharing risks, responsibilities and rewards. Collaboration can be classified in more detail regarding what individual participants bring to and share during collaboration, the intensiveness of collaboration, and different actors’ roles in collaboration. Based on these factors, the relevant literature presents different classifications for networking, which are collected and presented in Table 1. For example, in Table 1, supply chains are networks that interlink suppliers, manufacturers and distributors in different processes and activities that produce value in the form of products and services delivered to the end consumers. In this end-to-end process, all channels in the supply chain can bring or share data, information and resources with their partners in order to achieve their objectives. However, it is not common to share risks and benefits amongst the participants in the supply chain (Christopher, 1992). Extended enterprises are conceptual business units or systems that consist of purchasing company and supplier that collaborate closely to maximise the returns for each partner. The extended enterprise is an approach whereby the partners strategically combine their core competencies and capabilities to create unique competency. Additionally, people across number of organisations participate in the decision-making process. The mutual benefits are the sharing of data, information, resources and risks (Childe, 1998). Based on these different classifications, it is important to understand what is involved at different levels of networking in order to support and manage the process better. Although each of these concepts forms an important component of collaboration, they are neither of equal value nor equivalent to each other. For example, collaboration can involve communication and exchange of information for mutual benefits.

The value of networking comes from the exchange of information and sharing of experiences amongst the participants; however, there may be no common goal (Camarinha-Matos et al. 2009). Alternatively, collaboration can be more structured and mature, so that the entities share information, resources and responsibilities to jointly plan, implement and evaluate programme of activities to achieve common goal, thereby generating value. Collaboration involves the participants’ mutual engagement to resolve problem, which implies mutual trust and takes time, effort and dedication (Camarinha-Matos et al. 2009). Table 1. Different classifications of networking Classifications Collaborative network Social, bureaucratic, proprietary networks Development circle, loose cooperative circle, project group, joint venture, joint unit Supply network, joint venture, regional industrial system Strategic network, virtual enterprise, regional network, operative network Collaborative network: supply chain, extended enterprise, virtual enterprise, cluster 11 different categories of collaborative networks

Author(s) (year) Wernerfelt (1984); Bititci et al. (2003); Camarinha-Matos et al. (2009) Grandori and Soda (1995) Varamäki and Vesalainen (2003) Nassimbeni (1998) Pfohl and Buse (2000) Christopher (1992); Childe (1998); Parung and Bititci (2006) Camarinha-Matos et al. (2009)

The case network in this study can be defined as collaborative network (cf. Camarinha-Matos et al., 2009). The studied network meets the different criteria of collaborative network (Figure 1), such as joint process, information sharing, and the resources and responsibilities to plan, implement and evaluate activities in order to achieve common goal of the network (cf. Camarinha-Matos et al. 2009).

Figure 1. Interaction maturity levels (modified from Camarinha-Matos et al. 2009, p. 3).

Camarinha-Matos et al. (2009) presented the following four categories of networking (which are illustrated in Figure 1). First, network involves communication and the exchange of information for mutual benefits. The value of networking comes from the exchange of information and the sharing of experiences amongst the participants; however, there may not be any common goal or structure influencing the form and timing of individual contributions. Second, in addition to communication and information exchange, a coordinated network involves aligning/altering activities so as to achieve more efficient results. Coordination, which is an act of working harmoniously in concerted manner, is one of the basic building blocks of collaboration. Third, a cooperative network involves not only communication, information exchange and the adjustment of activities, but also resource sharing for achieving compatible goals. Cooperation is achieved through the division of some labour (though not an extensive division of labour) among the participants. Fourth, collaborative network is more demanding process, where the involved entities share information, resources and responsibilities to jointly plan, implement and evaluate programme of activities for achieving common goal, thereby generating value. Collaboration involves the mutual engagement of the participants to resolve the problem together, which implies mutual trust and takes time, effort and dedication. 2.2 Performance, performance measurement and performance measurement systems The literature does not extensively discuss the definitions of performance, PM, PMSs and performance management in general network environment. This could be because collaboration has many partly overlapping definitions, while network environments have general classifications. However, despite the active discussion on this research theme, the concept is not clearly defined (see, e.g. Leseure et al. 2001; Busi and Bititci, 2006; Kulmala and Lönnqvist, 2006; Cunha et al. 2008; Papakiriakopoulos and Pramatari, 2010). Busi and Bititci (2006) noted that collaborative network becomes kind of ‘virtual’ organisation by forming several organisations. Therefore, the general performance-related concept can be applied to those related to networks, albeit with some modifications. Performance is complex phenomenon with diverse meanings. Basically, the performance of an organisation is concerned with achieving its goals (Kaplan and Norton, 1996; Lebas and Euske, 2002). The performance of collaboration can be defined as meeting the collaborators’ joint strategic goals (Beamon, 1999; Parung and Bititci, 2006). Performance can be examined from different perspectives; therefore, each collaborator’s goals may vary. For example, Varamäki et al. (2008) investigated performance in the following six dimensions: network culture, network resources and competencies, network models of action, performance of internal processes, customer perspective, and financial perspective. Neely et al. (1995, p. 80) define performance measurement (PM) as ‘the process of quantifying the efficiency and effectiveness of action.’ Effectiveness refers to the extent to which customer requirements are met, whereas efficiency is measure of how economically the resources are utilised when providing given level of customer satisfaction. Parung and Bititci (2006) define collaborative network’s PM by using Neely et al.’s (1995, p. 80) definition, but from the collaborative perspective, these ‘actions’ are jointly produced. Neely et al. (1995, p. 80) define performance measurement system (PMS) as ‘a set of indicators used to quantify the efficiency or effectiveness of purposeful actions.’ They also state that PMS can be examined at the following three levels: (1) individual measures that quantify the efficiency and effectiveness of actions; (2) set of measures combined to assess the performance of an organisation as whole; and (3) supporting infrastructure that enables data to be acquired, collated, sorted, analysed, interpreted and disseminated. Based on the collaboration’s objective, the measures are delivered by monitoring both external relations and the efficiency of internal and extended processes (Busi and Bititci, 2006). Papakiriakopoulos and Pramatari (2010) described collaborative network’s PMS as set of measures used to quantify the efficiency or effectiveness of purposeful, jointly produced actions and processes. Papakiriakopoulos and Pramatari’s definition is utilised in this study. 2.3 Performance measurement in collaborative networks

2.3.1 Premise and framework Prior literature presents individual measures, some overall frameworks for network-level PM, and some specific features for supply chain PMSs (e.g. Ellram, 1995; Gunasekaran et al. 2004; Busi and Bititci, 2006; Varamäki et al. 2008; Laihonen et al. 2014). The analyses performed in these studies show that networks and their partners’ interfaces include many important features that need to be considered when designing and selecting the measures. The literature also presents some impacts that can be achieved through collaborative PM. According to Kaplan et al. (2010), network-level PM can enable networks to enhance the focus of network management from contribution and operations to joint strategy and commitment. Mahama’s study (2006) revealed that PMS facilitates cooperation and socialisation in inter-organisational relationships. Furthermore, Mahama (2006) indicated that PMS helps to ensure that performance information is distributed fairly amongst the participants, thereby facilitating learning and problem solving within the network. However, Franco-Santos et al. (2012) noted that the impact of PMS on inter-firm performance has received little attention in the existing literature. Many of the studies concerning the frameworks of network-level PMSs and the desired impacts are theoretical and utilise various research approaches without clarifying the context in which the measurement takes place. Understanding how PMS in collaborative network is developed and used requires capturing its context, process and content (Cuthbertson and Piotrowicz, 2011; cf. Pettigrew, 1985). It is important to define the conditions in which the measurement takes place. Cuthbertson and Piotrowicz (2011) presented framework for supply chain PMS that can also be applicable for other types of collaborative networks, since the definition of the context can be assumed to be relevant regardless of the nature of collaboration. Cuthbertson and Piotrowicz’s framework (2011) incorporates elements such as those shown in Figure 2.

Figure 2 Framework to analyse network PMS (revised, Cuthbertson and Piotrowicz, 2011, p. 585)

2.3.2 Context of PM in network The literature reveals various reasons why performance management and measurement are considered challenging in the network context (Lambert and Pohlen, 2001; Busi and Bititci, 2006; Kulmala and

Lönnqvist, 2006). Many of the reasons can be connected to the organisational and network contextual factors presented in Figure 2. Bititci et al. (2012) emphasised that future research should focus on 1) understanding collaboration and its mechanisms and 2) developing theories, methods and techniques to ensure that all network partners can define, manage, measure and evaluate the common goals and responsibilities. lack of understanding of the collaborative structure and dynamics is considered the main cause of the failure of collaborative initiatives (Busi and Bititci, 2006). Therefore, it is necessary to determine the key elements of collaboration as well as how they interact and can be integrated within PMS. Busi and Bititci (2006) emphasised that the difficulty in developing collaborative culture and the lack of appropriate performance measures have been identified as the major barriers to the successful implementation of network-level PMS. Busi and Bititci (2006) highlighted the lack of consensus amongst network partners as being arguably the biggest problem in implementing measures. The network must have clear vision of its roles and targets, and an understanding of and commitment to the shared objectives. Therefore, intensive discussions are required to improve understanding amongst the partners. It is important that the network determines and defines the benefits of common PMS for the entire network in general and for each partner in particular. Varamäki et al. (2008) have developed PM framework which comprises the factors that enable action, contribute to the success of processes, and ensure the productivity and profitability of activities. The factors enabling success are the network’s values and culture, resources and competencies, and models of action. According to Busi and Bititci (2006), the factors influencing performance management are enterprise collaboration, operations management, business process management/engineering, performance measurement/management and decision support, information and communication management, and organisational behaviour and knowledge management. Busi and Bititci (2006) claimed that all of these elements should be analysed to develop collaborative performance management measures. 2.3.3 Process of PM in network When the context for network-level PM is defined, it is essential to determine how the measurement is carried out. This process covers the system design, metrics selection, data capture, analysis, presentation and usage (Cuthbertson and Piotrowicz, 2011). Radnor and Barnes (2007) argued that apart from the measurement (which includes reporting and performance management), the actions taken should be considered based on the information provided. Furthermore, Busi and Bititci (2006) revealed that organisations find it challenging to share information with their partners. In network measurement, it is essential that companies share almost all of their information with the other network partners. Developing suitable communication infrastructure is necessary because information sharing amongst organisations has posed problem in defining an appropriately balanced set of measures for collaborative performance management (Busi and Bititci, 2006). Busi and Bititci (2006) and Beamon (1999) noted that networks face difficulties in evaluating and determining the unit of analysis, that is, the level of measurement. 2.3.4 Content of PM in network The important issue in network-level PM is the content, in other words, what is measured. In collaborative networks, the measurement systems should be designed to utilise balanced set of performance measures that monitor both external relationships and the efficiency of internal and extended processes, which will support proactive management based on both feedback and feedforward operations control. Furthermore, Busi and Bititci (2006) also suggested studying team performance management and developing performance measures for extended processes, collaboration and collaboration management. They presented an extended enterprise PM model that comprises series of scorecards, including enterprise, business unit, extended enterprise (or metalevel) and extended business process types. Regarding balanced set of performance measures, Parung and Bititci (2006, 2008) proposed numerous value generators (e.g. physical assets and human, organisational and relational capital) besides financial assets because the existent literature (Kald and

Nilsson, 2000; Leseure et al. 2001; Håkansson and Lind, 2004) and empirical evidence on network-level PM seem limited to financial measures. The following three kinds of measurements may influence the success of collaborative networks: (1) input to the collaboration, that is, each participant’s contribution; (2) the collaboration’s health; and (3) the collaboration’s outcome (Parung and Bititci, 2008). Measuring the input determines the participants’ resource contributions to the collaborative network. The collaborative network’s health status is established by measuring the dimensions of commitment, coordination, trust, quality of communication and participation, and by utilising the conflict resolution technique of joint problem solving (Parung and Bititci, 2006, 2008). Measuring the output identifies the benefits accrued by the key stakeholders as result of their participation in the collaborative network. According to Parung and Bititci (2006), the outcome of the organisation is usually associated with its performance, and PM is often linked to its efficiency and effectiveness in satisfying its customers (Neely, 1999). To evaluate the participants’ benefits stemming from joining collaborative networks, the output should be measured both before and after collaboration (Parung and Bititci, 2006). 2.3.5 Summary of factors affecting the design process This section summarises the prior studies on the factors affecting the PMS design process in collaborative network. broad perspective reveals that the process should be structured (Busi and Bititci, 2006; Kulmala and Lönnqvist, 2006; Franco-Santos et al., 2012) and managed (Busi and Bititci, 2006), and it should cover the context, process and context aspects (Cuthbertson and Piotrowicz, 2011) of PMS. Based on the preceding sections, Table details the factors affecting such process. Table 2. Factors affecting the PMS design in collaborative network Influencing factors Context factors Understanding collaboration, mechanisms, developing theories, methods, techniques, business model

Prior studies

Joint vision and strategy, common goals, responsibilities, roles, commitment

e.g. Busi and Bititci, 2006; Cunha et al., 2008; Kaplan et al., 2010

e.g. Lambert and Pohlan, 2001; Busi and Bititci, 2006; Bititci et al., 2012; Lönnqvist and Laihonen, 2012

Values and culture of network, resources and competencies, e.g. Busi and Bititci, 2006; Parung and Bititci, 2006, 2008; models of action Varamäki, 2008 Process factors Information, communication and knowledge sharing, communication infrastructure

e.g. Kulmala, 2003; Busi and Bititci, 2006; Mahama, 2006; Radnor and Barnes, 2007

Structured design of the PMS (methods and tools, system design, metrics selection, data capture and analysis, metrics usage)

e.g. Busi and Bititci, 2006; Kulmala and Lönnqvist, 2006; Franco-Santos et al., 2012

Unit of analysis (level of measurement)

e.g. Beamon, 1999; Busi and Bititci, 2006

Structured management to support decision making

e.g. Busi and Bititci, 2006; Camarinha-Matos et al., 2009

Participation, socialisation, learning and problem solving

e.g. Mahama, 2006; Parung and Bititci, 2006, 2008

Content factors Value generators

e.g. Parung and Bititci, 2006, 2008; Varamäki et al., 2008

Balanced set of measures Monitoring external relationships and the efficiency of internal and extended processes

e.g. Busi and Bititci, 2006; Papakiriakopoulos and Pramatari, 2010 e.g. Bititci et al., 2005; Busi and Bititci, 2006; Varamäki et al. 2008; Papakiriakopoulos and Pramatari, 2010

Regarding research question two, the factors affecting the PMS design are discussed and compared against the factors presented in this section. 2.4 Design of PMS in network The literature has presented various frameworks for designing PMS for manufacturing or service organisation (Kaplan and Norton, 1992, 1996; Simons, 2000; De Toni and Tonchia, 2001; Gooderham, 2001; Mettänen, 2005). These frameworks comprise varying number of phases and methods. However, in most cases, the design process is quite similar; the first phase elucidates the strategy and determines the critical success factors, and then the second phase defines the measures for these factors. Kaplan and Norton (1996) described typical and systematic implementation plan to develop balanced scorecard for an organisation. The process model, comprising four main steps, aims to encourage commitment to the scorecard amongst senior and mid-level managers, which is considered prerequisite for successful implementation. Kaplan and Norton’s (1996) balanced scorecard model was created to meet the needs of large organisation. Although other process models for designing and implementing PMS exist (e.g. Gooderham, 2001), most disregard the specific nature of collaborative networks. Although many models and guidelines have been provided for PMS design, only few (e.g. Kulmala and Lönnqvist, 2006) have been intended for network. Kulmala and Lönnqvist (2006) proposed the following approach for network: In the first phase, the network’s success factors should be identified from the end customer’s perspective and can be defined in the same manner as performance measures are defined for an individual company. The success factors are likely to comprise both financial and nonfinancial components. In the second phase, network-level performance measures should be defined for these success factors. Moreover, Cunha et al. (2008) have identified set of requirements when developing PMS for production networks to satisfy the stakeholders’ information needs. First, defining indicators should be collaborative process, performed during the network set-up and redefined periodically during the operation phase. Second, the defined indicators should enable the performance evaluation of the collaborative aspects of the network. In the third phase, each network partner’s vision should be considered, and the individual PMSs should be embedded into the network’s PMS. Thus, both the network-level and partner-level performance measures should be considered. Fourth, the performance system’s technological design should provide an architecture that is flexible enough to support the entry and exit of new partners. In the fifth and final stage, methodology for defining wellstructured set of performance measures is considered an important contribution to the management activity. In practice, designing and implementing PMS does not necessarily proceed as smoothly as described in the literature. For example, according to Bourne et al. (2002), many of the factors that cause problems in the implementation of PMS can be attributed to poor design process. In summary, there is need to study and develop structured methodology for designing PMS and structured management process for using measures to support decision making in collaborative network (e.g. Busi and Bititci, 2006). Only few studies have focused on collaborative design, especially from the design process perspective (Yin et al. 2011). Rey-Marston and Neely (2010) also suggested that future research should focus on the scope of the current PMSs beyond organisational boundaries. Based on the cited literature, both academic and managerial sectors are perceived as necessary in studying the design process of network-level PMS, considering the characteristics (context, content and process) and challenges of the network environment. 2.5 Conceptual framework for developing PMS design process in network As discussed in the previous sections, understanding how PMS in collaborative network is developed and used requires capturing its context, process and content (Cuthbertson and Piotrowicz, 2011; cf. Pettigrew, 1985). The need to develop structured methodology to design PMS and structured management process for using measures to support decision making in collaborative network has also been presented in previous studies (e.g. Busi and Bititci, 2006). Hence, in constructing conceptual framework for developing robust design process, detailed steps and phases should be followed. The following five-step procedure has been proposed: (1) analysing the network’s state; (2) clarifying the

network’s strategy; (3) defining the network’s success factors; (4) defining and evaluating the measures for the network; and (5) defining the network’s reporting principles and data sources. The design process is based on combining the existing literature and empirical studies on the PMS design process for single organisations (Kaplan and Norton, 1996; Simons, 2000; De Toni and Tonchia, 2001; Gooderham, 2001) and networks (Kulmala and Lönnqvist, 2006; Cunha et al., 2008). The context, content and process perspectives should be involved in the design process in order to clarify the structure and phases. Table presents the conceptual framework and detailed procedure for developing PMS design process in network. Table 3. Phases of PMS design process Perspective Context

Phase Target Initial interviews - What are the current network-level measures? What kinds of information needs does the network have? What kinds of development challenges does the network face? What kinds of structures and processes does the network have? What are the success factors of the network’s business?

Output - Detailed understanding of network structures, processes, current measures and information needs. Revealing the key network-level success factors.

Step 1, 2, 3

Content

1st development session

- What kinds of measures would be beneficial for network-level performance management? What kinds of measures would be beneficial for network-level operations? What measures are beneficial for single-partner company?

- Selecting the number of measures important for network management and single-network partner performance.

4

Content, process

2nd development session

Critical evaluation of selected measures: Are the selected measures appropriate for network management? Is the required data available for the measures? Who is responsible for data gathering? How is the data reported?

- Producing the final version of 4 selected measures and principles for data collection, reporting and dissemination.

Process

3rd development session

- How can the effective use of the information from the network-level performance measurement (PM) be ensured?

- Presentation and training in the use 5 of the reporting tool that was developed when the measures were designed. Implementation by the development group.

Content, process

Feedback session - How does the PM system work in practice? What are the key development needs? What kinds of impacts and benefits does the PM system have?

- Identifying the key development 5 needs. More training and guidance may be needed considering the interpretation of the PM information.

Regarding research question one, the empirical results of the design process are discussed and compared against the conceptual framework presented in this section.

Methodology 3.1 Case research The case study has consistently been one of the most powerful methods used in management research, particularly when it comes to the development of new theory (Voss et al., 2002). case study focuses

on creating an understanding of certain phenomenon (Eisenhardt, 1989). This strategy is further used in many situations to contribute to the knowledge of individual, group, organisational, social, political and other related phenomena (Yin, 2009). Voss et al (2002) cited the following three strengths of case research: 1) The phenomenon can be studied in its natural setting; meaningful and relevant theory can be generated from observing and understanding actual practice. 2) The method allows answering the why, what and how questions with relatively full understanding of the nature and complexity of the complete phenomenon. 3) The case method is useful when the variables are unknown and the phenomenon is not fully understood. Although case study is occasionally considered single research method, it should be viewed as being capable of employing various qualitative and quantitative approaches, such as analysing archives, conducting interviews or using questionnaires (Gummesson, 2000; Yin, 2009). This paper presents single-case study focusing on the PMS design process for collaborative network and its influencing factors. The empirical data has been gathered using qualitative methods, which are discussed later. single-case study is an appropriate research design under several circumstances. First, it is analogous to single experiment because many of the conditions justifying single experiment are also applicable to single-case study. One rationale concerns critical case used for testing well-formulated theory. The second rationale pertains to case representing an extreme or unique model. From the perspective of the present case, the existing literature reveals minimal practical experience of using network-level performance management and PMS. Thus, the case under study is unique because it provides new, practical information regarding the design of network-level PM. The third rationale involves the use of revelatory case (Yin, 2009); that is, an investigator has an opportunity to observe and analyse previously inaccessible phenomenon. Occasionally, for example, in extreme or polar situations, successful and unsuccessful cases are selected (Eisenhardt, 1989). The case utilised in this study involved collaborative network that operates nationwide in Finland. The case network comprised main company that primarily manufactures kitchen fitments and the resellers of such products. The main company had five trademarks; however, the empirical research was based on one trademark where the network formed the case. The case network can be described as follows: the resellers operated inside hardware store, where they had their own selling points. There were 23 resellers and 26 selling units, with each unit comprising an entrepreneur and 1-3 seller(s). Furthermore, all of the resellers were independent entrepreneurs. The resellers sold the products, while the main company billed the customers and transported the products. The case network partially used the franchising concept. franchising network refers to the methods of practising the franchisor’s business philosophy. The franchisor grants an independent operator the right to distribute its products and use its techniques and trademarks in return for percentage of the gross monthly sales and royalty fee. Usually, the franchisor provides various tangible and intangible resources, such as national or international advertising, training and other support services (Sherman, 2004). However, the case network differed from the traditional franchising concept in several ways. The franchisees sold kitchen fitments, which were very challenging to sell because the sales action was unique in each situation. Purchasing kitchen is an expensive investment; not only are there numerous variations of models and materials, but customers’ preferences and tastes also influence the selling process. Therefore, the network partners had strong and shared identity, collaborating on many issues. Compared to the traditional concept of franchisor, the franchisor’s role was more consistent with that of the franchisees. The challenging products and selling processes offered many opportunities to learn from the other network partners. The network had many common plans (e.g. action plan and marketing strategy), and its partners shared the risks that might arise from the plan implementation. Their joint information system also allowed them to participate in the design process. Their common target was to maximise the entire network’s turnover. Based on Camarinha-Matos et al.’s (2009)

definition, this case study can be viewed as collaborative network, which is mature form of networking (see section 2.1. Classification of networks). Franchising networks can also be treated as strategic networks (Sydow, 1998). The case was selected due to the researchers’ access to its network and its sufficient maturity for this kind of research setting. 3.2 Data collection The data collection for the study comprised the following three elements: 1) developing preliminary understanding of the state of the case network and its PM; 2) building network-level PM design process; and 3) gaining better understanding of the factors that played an important role in this process. As the network’s state and strategy were fairly clearly defined at the beginning of the research project, the study mainly focused on steps 3, and (see Table 3). The data was gathered by conducting 1) initial interviews prior to the PMS design process (2009); 2) feedback interviews after every development session and feedback session (2009); and 3) two interview studies after the PMS was implemented in the network (2010 and 2012). Eight resellers were selected for the network-level PM design process, with mix of old and new resellers being included; some resellers had better economic performance than others (see Table 4). This sample was believed to provide comprehensive picture of network activity. Moreover, the main company’s sales director, sales manager, area sales manager and financial manager participated in the design process. These participants formed the project group and were involved in the interview studies at different phases of the process. Table summarises the data collection phases, participants, and data collection methods. Table 4. Summary of data collection phases, participants, and data collection methods. Perspective Context

Phase Participants Initial interviews Sales director, main company Sales manager, main company Area sales manager, main company Financial director, main company Eight entrepreneurs, reselling network

Data collection methods Interview, recorded and transcribed

Content

1st development session

Sales director, main company Sales manager, main company Area sales manager, main company Financial director, main company Eight entrepreneurs, reselling network

Group discussion, documented

Content, process

2nd development Sales director, main company session Sales manager, main company Area sales manager, main company Seven entrepreneurs, reselling network

Group discussion, documented

Process

3rd development Sales director, main company session Sales manager, main company Area sales manager, main company Seven entrepreneurs, reselling network

Group discussion, documented

Content, process

Feedback session Sales director, main company Sales manager, main company Area sales manager, main company Seven entrepreneurs, reselling network

Group interview, documented

Content, process

Interview study (2010)

Questionnaire and group interview, recorded and transcribed

Sales director, main company Sales manager, main company Area sales manager, main company Financial director, main company Seven entrepreneurs, reselling network

Content, process

Interview study (2012)

Sales director, main company Sales manager, main company Area sales manager, main company Six entrepreneurs, reselling network

Interview (four conducted by phone), recorded and transcribed

Prior to the design process, two researchers acquired background information on the case network by conducting semi-structured interview, where the topics and issues were decided beforehand. The interviews focused on the network’s success factors; the collaboration’s health; the current measures, including their weaknesses and strengths; information requirements from the entire network’s perspective; information regarding the resellers and the main company’s sales management; and expectations for the design process. The interviews included the questions presented in Table 3. These initial interviews increased the understanding about the state of the network and its PM, as well as the partners’ expectations for the future. The collaboration’s current health status (commitment, coordination, trust and communication quality) was evaluated based on the interviewees’ perceptions. Each interview lasted approximately one and half hours. The interviews were initially analysed independently by the two researchers, using codes related to the network’s state, information needs, current measures etc.; subsequently, common view was discussed. Then, the PMS design process was carried out by utilising the development sessions (see Table 3) that focused on the following: 1) the selection of measures important for network management and singlenetwork partner performance; 2) the final version of the PMS confirmation and identification of the principles for data collection, reporting and dissemination; and 3) presentation and training in the use of the reporting tool that was developed when the measures were designed. At the end of every development session, the researchers asked the participants about their views and experiences of that specific session (Which elements promoted the design process? What were the main obstacles? Did the session focus on the right issues?). These interviews were held as group discussions, which was deemed an efficient way to capture broad view of the PMS design process. The interview results were documented in every session. Next, the feedback session utilised the group interview method, where the participants evaluated the entire design process and its effects on the network’s operations, knowledge and culture. The collaboration’s current state of health was assessed by asking the participants to analyse and describe, for example, their current level of commitment to the network. After each session, all of the researchers reviewed the documentation and formed common perspective. After the design process, all of the data (obtained through the interviews and documented observations, discussions and results) was analysed according to the study’s two research questions (see section 1). First, the researchers analysed the empirical data from the perspective of how the PMS design process was experienced. Second, they examined the factors that influence the process. To increase the validity of the empirical results and minimise interruptions, new interview study was conducted in 2010 after the design process was completed. First, the participants filled in questionnaire consisting of the same open-ended questions as those that were later asked in the group interview. The questions, based on the existent literature, were related to the design process as well as to the network-level PMS and its impact on operations and business. The interviews focused on the participants’ experiences of the design process (e.g. what was important, their successes and failures) and the impacts of using the PMS (e.g. what kinds of impacts the PMS had on network-level operations, management and systems). Research validity is concerned with whether or not the researcher is studying the phenomenon he/she purports to study (cf. Gummesson, 2000; Yin, 2009). Thus, in 2012, third round of interviews was conducted to validate the study’s previous results. The main company’s four managers were interviewed as group and four resellers were interviewed by phone. The same questions were asked during these two sets of interviews. The findings were integrated to identify the PMS design process framework for networks and the factors that affected the process. These results were linked to the timely literature on performance measurement and management. According to

Gummesson (2000), generalisations cannot be made based on case studies. However, the idea of singlecase studies is to provide an in-depth illustration of the case in specific context. As Lukka and Kasanen (1995) suggested, the main findings of case studies are often at least applicable to some organisations with similar context. In this context, our case study is explorative in an area that lacks empirical evidence because it is difficult for researchers to obtain access to or information about this type of network.

Findings 4.1 How can PMS for collaborative network be designed? The importance of network-level PMS and its benefits in enhancing the success of the network have been widely recognised by researchers and practitioners alike. However, thus far, few empirical studies have addressed the topic of the design of such system. This study therefore attempts to address these research gaps by developing PMS design process for collaborative network. The paper applied the conceptual framework presented in section 2.5 (Conceptual framework for developing PMS design process in network in order to better understand how PMS can be designed. The design process comprised the phases presented in Table 3: initial interviews, PM development sessions, and feedback session. The key empirical outputs of the study are presented in Table and the results are introduced in more detail above. The empirical results confirmed that steps 1, and of the PMS design process (related to the PM context) were emphasised. Networks can be very complex systems; hence, it is important to understand their structures and dynamics, and to ensure the network partners’ joint knowledge of the common vision and targets (cf. Lambert and Pohlen, 2001; Busi and Bititci, 2006). However, if the collaboration (cf. Camarinha-Matos et al. 2009) has not attained mature level, i.e. it lacks shared goals or responsibilities, the partners should focus on creating and clarifying these because the basis of the PMS is strategic goals (cf. Busi and Bititci, 2006; Kaplan et al., 2010). The network should evaluate the collaboration’s degree of maturity (cf. Cunha et al. 2008; Camarinha-Matos et al. 2009; Pekkola et al., 2013) before beginning the design of comprehensive, network-level PMS. In light of empirical evidence, the individual interviews with network partners before phases and were the workable tool used to understand network structures and dynamics, and to ensure that they all understood the joint goals. The result here supports Cuthbertson and Piotrowicz’s (2011) results; furthermore, the analysis of the context (network structures, processes and information needs) would be necessary to understand the success factors and priorities, including how measures are developed and used. Otherwise, the process output would just be list of measures. The results showed that the initial interviews gave the interviewees an opportunity to express their opinions and expectations, and to describe the development needs from their own perspective. The following interview excerpts illustrate these findings: was left with the feeling that all was heard, and everyone had possibility to give [his/her] opinion (Reseller). At first, thought that [the] development project’s aim was to develop control tool for [the] main company. After the interview, realised that the project is genuine co-development project (Reseller). The evidence also reveals that the interviewees were not completely familiar with the terms ‘performance measurement’ and ‘performance management’. Performance was connected to book accounting and was seen as tool used to control the financial performance of each partner company. One interviewed participant described the importance of the initial interviews as follows:

‘Performance measurement’ and ‘performance management’ were new terms for me. It was good that was able to ask questions that focused on the use of [the] PM system, its benefits, how much time the development work takes etc. (Reseller). The results confirm that it is important to define the terms that are used in the development process. Doing so helps to ensure that the development targets are understood and that everybody understands and uses the same ‘language’. This can increase commitment, trust and the willingness to share information between network partners. lack of suitable communication infrastructure and problems in information sharing amongst organisations would cause difficulties in defining an appropriate, balanced set of measures for collaborative performance management (Busi and Bititci, 2006). Table 5 The key empirical outputs Perspective Context

Phase Initial interviews

Step 1, 2, 3

Content

1st development 4 session

- Consensus regarding the PMS’ development targets and information needs First version of measurement system

Content, process

2nd development session

- The final version of selected measures Principles for data collection, reporting and dissemination

Process

3rd development session

5

- Knowledge of how to use PMS (utilisation in management and reporting tool) Jointly decided management practices at the network-level

Content, process

Feedback session

5

- The key development needs First results of the workability of the PMS End of the design process

4

Empirical output - Understanding of network structures, processes, current measures and information needs -> selection of suitable measurement method Identified success factors and ensured strategic objectives Comprehensive picture of the network’s specific needs Understanding what PMS means Commitment to process

The results revealed that step 4, related to the PM process (defining and evaluating the measures for the network), received only modest attention during the design process but is nevertheless important to ensure balanced view of the network-level performance. The reason for this can be identified from earlier steps: the clearly defined objectives and success factors, as well as information needs, help in selecting the appropriate measures for the network. From the financial perspective, the network partners had taken steps to compare the financial measures used in their respective companies. This allowed the resellers to compare their own results to the entire network’s average, thus enabling benchmarking amongst the partners. This initiative had been facilitated by an integrated measurement system in the joint information system. Moreover, based on the results of the measures, the main company could develop its own business processes (e.g. marketing and factory processes) and support the resellers’ actions and decision making: understood that if have network-level PM information in use, can compare my own firm’s results to these averages and then benchmark and develop my business, and further, the entire network’s business (Reseller). Therefore, step 5, relating to the PM content (defining the network’s reporting principles and data sources), played significant role, especially in terms of using the measurement information. In addition, the literature (see e.g. Bourne et al. 2002; Kennerly and Neely, 2002; Cunha et al. 2008; Bititci et al. 2012) shows that PMS that lacks incorporated information technology does not support the management practices as efficiently and effectively as possible. The results highlighted this point,

especially in the network context. The results show that information system integration made following and analysing the PMS results more efficient for various users. In addition, the results of the interviews indicated that jointly decided management practices (e.g. meeting practices) and their utilisation promoted the effective use of performance information and also had an important effect on the performance of the network. The empirical evidence also raises the role of the feedback session in the process. This step of the process ensures that the process had clear beginning and end. This phase also brings out the possible development needs and problems that arose during the testing of the PMS. The results revealed that the design process was successful because the network-level PMS seemed to work in practice and the outputs were applied in the network. Based on the measurement information in the system, the reclamation costs were reduced in many selling units. One reseller stated that he successfully reduced reclamation costs by 50% by following the measurement information and the network’s averages, and by developing his kitchen planning process accordingly. Overall, the reclamation costs decreased by 20% in the reseller units that began utilising the network-level PMS. Therefore, the design process utilised in the study passed the weak market test (Kasanen et al. 1993) and covered one of the research needs, as highlighted by Busi and Bititci (2006). 4.2 What factors influence the design of PMS for collaborative network? The results emphasised the factors that play an important role in the design process of network-level PMS. These factors are also recognised when launching PMSs for single organisations; however, the study stressed the significance of these elements in collaborative network environment. The results showed that the main process factors (see Table 2) facilitating PMS design for network were socialisation, participation and information sharing. Socialisation refers to the verbal and interpersonal interactions through which individuals negotiate roles and identities and associate significance to events, practices and procedures (Reichers, 1987). According to Mahama (2006), the interactions that lead to socialisation may include training, meetings, seminars and personal consultations. Meetings and seminars are arenas for participation; these interactional settings are also avenues for information sharing (Mahama, 2006). In the study, the main reason for the successful design process was that both the resellers and the main company’s key representatives were involved in the initial interviews, development sessions and feedback session. Such participation-enabling socialisation was perceived to increase trust, openness and commitment amongst the network partners. The opportunity to participate in the early stage of the process encouraged them to voice their opinions and ideas and to ask questions about PMS issues. Their participation also expedited the learning process concerning PM, target setting and managing performance in general, which was considered vital because most of the resellers lacked any kind of management or financial education. Many researchers have highlighted the following challenges regarding the performance management and measurement of collaborative networks: network complexity, relationship issues amongst partners, lack of trust and commitment, communication quality problems, and common knowledge regarding performance management (Busi and Bititci, 2006; Bititci et al. 2007). The study’s results indicated that participation during the early stages of carefully designed and structured design process (cf. Busi and Bititci, 2006) could address most of these cited concerns. This outcome is consistent with the findings of Mahama (2006), who examined the association between PMS and cooperation and performance in strategic supply relationships. His study demonstrated that using PMS stimulated the cooperation and socialisation process, which in turn facilitated information sharing, process that similarly occurred in the case study. Information sharing plays crucial intermediate role in enhancing performance, although it is not directly associated with it (Mahama, 2006). Furthermore, when focusing on the context factors of the PMS design for the network, the study indicated positive development of the network culture. On the other hand, the literature reveals that measurement can often be perceived as controlling (Simons, 2000), which may also be the case in collaborative network. However, one interviewed reseller described the development as follows:

year earlier, we were talking about the joint measurement in the network and we [participants] were not so keen to share any information. However, we decided to start this development process together, although we were still unwilling to share information. During the development sessions, we noticed the value of network-level PM information for our own business and the network-level business. Our culture has become more open (Reseller). Varamäki et al. (2008) argued that network’s values and culture describe its mental state. Mahama (2006) showed that openness is generally key issue in network-level performance management. The current study’s results indicated that actual participation (instead of nominal) would create culture of development (not culture of control). The partners were actively involved in the structured design process by increasing their understanding of the value of network-level PM information for both their own business and the network-level business. This realisation strengthened their willingness to share information and thus improved their business knowledge. The study suggests that this type of network culture is needed in the design process and can be achieved through dynamic participation. Additionally, the facilitators (i.e. the researchers) performed significant function in the design process of the network-level PMS. One important aspect was that the resellers felt that they attended development session organised by the researchers, not by the main company: The outside facilitator’s role was very important, think. She was asking the questions and challenging us to think about what we wanted, how we wanted to develop the network (Reseller). The facilitators were like referees who helped us along in situations where there were disagreements (Sales manager). All of the participants thought that the facilitators’ presence enabled the resellers and sales managers to develop mutual understanding and align their objectives. The participants’ learning process was also fostered by the facilitators, who were PM experts. Both the resellers and the sales managers viewed the facilitators not only as specialists but also as neutral operators, which motivated the partners to actively participate and so advanced the culture of development. The study thus suggests that the use of facilitators is also an essential factor in the PMS design process for network. In the study, the five-step design process and the factors affecting the PMS design have been examined. The factors affecting the PMS design process have been summarised and explained in Table 6. Table 6. Factors affecting the PMS design process Influencing factors Context factors Understanding collaboration and performance measurement

Creating culture of development in network

Description of the effect The active involvement of the network partners in the structured design process increased their understanding of the value of network-level PM information for both their own business and the network-level business. The presence of the performance measurement facilitators during the design process enabled the network partners to develop mutual understanding and align their objectives concerning the network-level PMS. The performance measurement facilitators were considered not only as specialists but also as neutral operators, which in turn motivated the partners to actively participate and so advanced the culture of development. The actual participation (instead of nominal) of the network partners in the different phases of design process will create culture of development (not culture of control). This means the possibility for interactions that lead to socialisation, for example, in different meetings.

Process factors Active participation

The successful design process necessitated that both the resellers’ and the main company’s key representatives were involved in the initial interviews, development sessions and feedback session.

Socialisation

The participation-enabling socialisation was perceived to increase trust, openness and commitment amongst the network partners. These issues are considered critical in the previous studies (e.g. Busi and Bititci, 2006; Bititci et al. 2007).

Learning process

The participation in the different phases of the design process also expedited the learning process concerning PM, target setting and managing performance in general. The learning process was also supported by the performance measurement facilitators.

Structured design of the PMS

Information sharing Content factors Balanced set of measures

The study’s results indicated that participation in the early stages of carefully designed and structured design process (cf. Busi and Bititci, 2006) could address most of the cited concerns, such as network complexity, lack of trust and commitment, and communication quality problems. The structured design of the PMS stimulated the cooperation and socialisation process, which in turn facilitated information sharing. balanced set of measures that cover the essential value generators for both the individual network partner and the entire network can be achieved through the structured design of PMS as presented in this study.

The theory (section 2) presents variety of factors that affect the network-level PMS design process. This study shows that eight factors (table 6) from the prior theory can be highlighted when utilising the five-step design process for network-level PMS. Regarding research question two, the study makes two essential contributions to the literature on performance measurement systems. First, the study highlights eight of the most important factors affecting the design process of PMS in networks. Second, the study describes how both influence and changes have been realised through these factors.

Conclusions Researchers have emphasised the need for structured design process for PMS for collaborative network (e.g. Busi and Bititci, 2006; Yin et al. 2011; Bititci et al. 2012). To address this demand, conceptual framework for developing such process was presented and empirically investigated. This paper concludes by illustrating how this goal can be achieved and its influencing factors. The study also highlights the most essential practical experiences related to this process. The study contributes to the existent literature on this subject by presenting five-step, structured framework that covers the context, process and content of network-level PMS. First, the network context (including the collaboration’s structure, mechanisms, roles and goals) is defined by conducting initial interviews with the participants. These interviews also clarify how the organisational and network contexts match. The next four steps include three development sessions and one feedback session that focus on the process and content of network-level PMS. These steps utilise the collaborative design by involving the network participants. The examined design process enables the definition of an appropriate, balanced set of measures for collaborative PM that covers all of the essential value generators. The study’s results validate that the first phase (focusing on steps 1, and 3, which relate to the PM context) is emphasised in the PMS design process. These initial interviews help guarantee the partners’ shared understanding of the network’s structures, dynamics, vision and strategy. Otherwise, they should concentrate on identifying and developing common goals and responsibilities before beginning the PMS design process. The network’s maturity has notable impact on such process. Step (focusing on the PMS content and use) is also highlighted. The results show that integration with the information system is vital in sharing performance information, thereby

enabling its effective and timely use in network environment where the partners are dispersed around the country. The study also contributes to the existent theory of performance management and performance measurement by presenting the factors that affect the network-level PMS design process. The prior studies present variety of factors and the chains of evidence affecting the design of network-level PMS. This study highlights the following eight factors that can be considered in the design process: understanding collaboration and performance measurement, creating the culture of development in network, active participation, socialisation, learning process, structured design of the PMS, information sharing, and balanced set of measures. The study shows how these factors are interlinked and describes how both influence and changes have been realised through the factors. The first managerial contribution is related to knowledge about the process of designing performance measurement system for collaborative network that can support measurement-related development projects in the network. This knowledge is related to the steps and various factors supporting and hindering the design process of performance measurement system. The case descriptions can be regarded as illustrative examples of the design process for performance measurement system for collaborative network. There are no perfect performance measurement systems, but there are many systems that satisfy the defined managerial needs reasonably well. Second, this research provides information on important factors from the perspective of successful performance measurement design process in collaborative network. By understanding and prioritising these factors, collaborative network can avoid some of the main challenges and so increase the success of the design process. The studied factors, including their interaction, as well as the discussion around the influences and changes, can be utilised by managers operating in the area of performance management in the network context. The present study is limited and context-bound to one case network that operates by utilising franchising concepts. In this context, the network partners have joint targets and networking is structured. The design process and associated features can be applicable to the type of collaborative network similar to that presented in this study. However, single-case study necessitates further research to develop and test the design process in other collaborative networks. In the future, it will also be useful to investigate whether this type of design process is applicable to other networks, for example more complex, collaborative networks. Furthermore, in-depth empirical studies regarding the implementation of collaborative PMS are needed, as are broader set of networks to expand the proposed framework and generalise the findings to an overall theory on network-level performance measurement and management. An interesting question for future research involves examining how to define the measures for different network types and how to identify the key measures in such environments. The current literature proposes that network-level PMSs should evaluate both local and business network-wide measures in order to maintain relevance and effectiveness in their specific settings (Busi and Bititci, 2006). Finally, the research should also focus on the impacts and utilisation of PMSs in network environment.

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