Academic journal article Journal of Applied Management and Entrepreneurship

Performance Metric Selection Methodology for Multi-Organizational Service Network Integration

Academic journal article Journal of Applied Management and Entrepreneurship

Performance Metric Selection Methodology for Multi-Organizational Service Network Integration

Article excerpt


Many manufacturing firms have added a service dimension to their portfolio of product offerings. This "servitization" enables these manufacturing companies to enhance the value add offered to their customers and also create additional revenue streams (Baines, Lightfoot, Benedettini, & Kay, 2009). Recent literature on the servitization of manufacturing has focused on factors that are driving this movement from a manufacturing-oriented business to a servicecentric business. Other writers have focused on the relative benefits of servitization strategies based on gains or losses in revenue and market share (Chou & Chung, 2009; Johanssen & Olhager, 2006). Combining product and service product offerings for customers places an increasingly heavy reliance on networks of multiple partners to deliver newly created productservice combinations.

While previous research suggests a positive correlation between network integration and business performance (Ellinger, 2000; Fröhlich & Westbrook, 2001; Lambert & Cooper, 2000; Swink, Narasimhan, & Wang, 2007, Saccani, Gaiardelli, & Songini, 2007; Van Donk, Van der Vaart, & Giménez, 2007), network integration remains difficult to operationalize. Within highlypartnered service supply chain networks, closely coupled customer-supplier and suppliersupplier relationships have been described as multi-organizational networks (MON) (Srai, 201 1). The MON concept, represented in Figure 1, highlights the overlapping interests of suppliers and the end customer at the 'touch points' between these organizations. With the emergence of these increasingly complex multi-partner arrangements in services, there is a growing need for organizations to know how best to configure these complex interdependent networks, and how best to integrate across organizations. However, the key factors that enable effective collaboration in a service supply chain environment remain, to a large extent, poorly understood (Barrati, 2004; Nyaga, Whipple, & Lynch, 2010).

Understanding this configuration is important, as not managing the touch points has implications for the success of a servitization strategy. Customer relationship management (CRM) initiatives, for example, may fail due to a lack of organizational (and/or network) integration and customer orientation, attributed to a lack of clarity on network objectives, poor design and planning and the use of misleading metrics or improper measurement approaches (Jain, Jain, & Dhar, 2007; Foss, Stone, & Ekinci, 2008).

Previous research indicates that a selective focus on a few core processes or 'linkages' between supply chain partners may provide better solutions to network integration than attempting a detailed and comprehensive process integration (Iakovaki, Srai & Harrington, 2009). Srai (201 1) argues that companies would be more effective in integrating their supply chain networks by focusing on network enablers. These enablers are: 1) Common Goals (network relationships marked by clearly defined roles, integrated resources, joint ownership of decisions, and meaningful and cooperative relationships), 2) Shared Risk and Reward (collective responsibility for risk and sharing of network derived benefits), 3) Network Synchronization (sequencing activities and operations to maximise the performance of essential network functions), 4) Collaborative Resources (using resources in ways that complement networked organizations' routines and enhance future capabilities), and 5) Knowledge Sharing (willingness to exchange key technical, financial, operational and strategic information). These five factors enable organizations to find more productive routes to service network integration and improved business performance. They provide greater clarity on overall network objectives for all parties to the networked service supply chain (Srai, 201 1).

Although some have recognised the requirements for flexibility in strategy as a direct link to performance (Iravani, van Oyen, & Sims, 2005) and some QoS (quality of service) metrics have been proposed (Alkahtani, Woodward, & Al-Begain, 2006), there is not much written on performance measures in the multi-organizational service network. …

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