dis 635 week 4

Review

Performance measures and metrics in outsourcing decisions: A review for research and applications

Angappa Gunasekaran a,n, Zahir Irani b, King-Lun Choy c, Lionel Filippi d, Thanos Papadopoulos e

a Department of Decision and Information Sciences, Charlton College of Business, University of Massachusetts – Dartmouth, 285 Old Westport Road, North Dartmouth, MA 02747-2300, USA b Brunel Business School, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom c Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China d Center for Studies and Research in Management (CERAG), University of Grenoble, UMR CNRS 5820-UPMF, 150 rue de la Chimie, 38000 Grenoble, France e Department of Business and Management, University of Sussex, Sussex House, Falmer, Brighton BN1 9RH, United Kingdom

a r t i c l e i n f o

Article history: Received 25 August 2012 Accepted 17 December 2014 Available online 25 December 2014

Keywords: Outsourcing Concepts Theory and practice Literature review Research taxonomy Future research

a b s t r a c t

Outsourcing, an operations strategy that influences the performance of a supply chain, has become an important component of global operations management. An effective global sourcing strategy helps companies to manage the flow of parts and finished products in meeting the needs of overseas and domestic markets. Outsourcing reduces the cost of assets, facilitates core competencies to reduce production costs, leads to strategic flexibility and reduces administrative and overhead costs. Some of the reasons why companies are against outsourcing include integration challenges, sacrificing their competitive base, opportunistic behaviour, rising transaction and coordination costs, limited innovation, and higher procurement costs. Despite these shortcomings, outsourcing will continue to play an important role in enhancing organizational competitiveness. Therefore, an attempt has been made to review the literature on outsourcing with particular reference to Performance Measures and Metrics (PMMs) used in arriving at outsourcing decisions. The main objective of this paper is to present a taxonomy (classification) of PMMs in outsourcing decisions at the pre-outsourcing, during-outsourcing, and post-outsourcing stages. Also, based on the literature review and analysis, an attempt is made to determine a list of specific tools and techniques for PMMs in outsourcing. Finally, the limitations of the paper and future research directions are presented.

& 2014 Elsevier B.V. All rights reserved.

Contents

1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 2. Classification criteria used for the review of literature on outsourcing PMMs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

2.1. Choice of framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 2.2. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

3. Review of the literature on PMMs in outsourcing decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 3.1. Strategic outsourcing engagement decisions and relevant PMMs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

3.1.1. Pre-outsourcing stage decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 3.1.2. During-outsourcing stage decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 3.1.3. Post-outsourcing stage decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

3.2. Tactical engagement outsourcing decisions and relevant PMMs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 3.2.1. Pre-outsourcing stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 3.2.2. During-outsourcing stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 3.2.3. Post-outsourcing stage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

Contents lists available at ScienceDirect

journal homepage: www.elsevier.com/locate/ijpe

Int. J. Production Economics

http://dx.doi.org/10.1016/j.ijpe.2014.12.021 0925-5273/& 2014 Elsevier B.V. All rights reserved.

n Corresponding author. Tel.: þ1 508 999 9187; fax: þ1 508 999 8646. E-mail addresses: [email protected] (A. Gunasekaran), [email protected] (Z. Irani), [email protected] (K.-L. Choy),

[email protected] (L. Filippi), [email protected] (T. Papadopoulos).

Int. J. Production Economics 161 (2015) 153–166

4. Tools and techniques for performance measures and metrics in outsourcing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 5. Managerial implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 6. Limitations and future research directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 7. Concluding remarks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

1. Introduction

The market has become global and therefore enterprises need to adapt their operations accordingly. Today, dealing with the global market and coping with global operations have become an integral part of the strategy of many organizations. Companies competing in this market have to perform well across a range of competitive performance objectives including flexibility, respon- siveness, price, quality and dependability. The question then arises as to how companies achieve these objectives? For example, success can be achieved by decentralizing enterprise operations so that companies can focus on their core competencies. Out- sourcing has become one of the most popular operations strategies in recent years that allows companies to focus on their strengths and reduce capital costs, while at the same time being more responsive to changing market or customer requirements in the global marketplace (Kakabadse and Kakabadse, 2005), and increasing their performance (Bustinza et al., 2010).

Outsourcing refers to contracting a particular process or function in an organization to an external firm (Kotabe and Zhao, 2002). Ellram and Billington (2001) define outsourcing as the transfer of activities and processes previously conducted internally to an exter- nal party, whereas Hätönen and Eriksson (2009) suggest that the meaning of outsourcing has changed over years. Outsourcing was initiated in the 1950s but became viable in the 1980s, when organizations used outsourcing as a means of reducing costs related to service-oriented operations (Lacity and Hirschheim, 1993) which were normally non-core business processes. In the 1990s, organiza- tions, influenced by the benefits of outsourcing on cost reduction, started to outsource functions in which they did not have expertise. The seminal article by Hamel and Prahalad (1990) on core compe- tencies and the work of Porter (1996) clearly demonstrate the shift towards the strategic use of outsourcing to allow focus on core competencies and building closer relationships with other companies to acquire external skills, competences and knowledge. Thus by the 2000s, outsourcing shifted from a competitive differentiator to a norm. Low communication costs and improved technology provided organizations with the opportunity to restructure based on out- sourcing; Hätönen and Eriksson (2009) characterize this period as one of “Transformational outsourcing”, which is related to the emergence of new business models based on outsourcing that can generate sustainable competitive advantage. Therefore, outsourcing has shifted from “traditional” in the 1980s to “strategic” in the 1990s and “transformational” in the 2000s; this does not merely assist in streamlining internal processes, but transforms organizations which are now embedded in loosely coupled networks (ibid) to enable them to survive and prosper in a constantly changing landscape.

Firms outsource operations ranging from Information Technol- ogy (IT) management to entire functions, such as logistics. Out- sourcing has moved from a non-core business activity to more critical business activities such as design, manufacturing, market- ing, human resources management and logistics. Most of the papers reviewed on outsourcing deal with issues in IT/IS (Lacity et al., 1996; Lacity and Willcocks, 1998; Gunasekaran and Ngai, 2004; Graf and Mudambi, 2005; Gonzalez et al., 2006; Hsu and Wu, 2006; Bapna et al., 2010; Dibbern et al., 2004; Lacity et al.,

2009; Weiner et al., 2010). According to Yang et al. (2007), the potential determinants of outsourcing include cost savings, a focus on strengths and flexibility, information security, loss of manage- ment control, labor unions and morale problems, vendor's service quality, market maturity and other firms' outsourcing decisions. These issues demonstrate the significance of suitable PMMs in planning, coordinating and controlling outsourcing not only in IT/ IS, but also in manufacturing and some service industries.

Even though outsourcing has become a key strategy in manu- facturing and some service industries, very few journal articles focus on the PMMs in outsourcing in these industries. Therefore, our focus is broad-based and includes both manufacturing and service industries. PMMs are the basic managerial tools for decision-making in any organizational environment, including outsourcing. More accurate and reflective PMMs will eventually lead to the selection of suitable strategies, tactics, and operations in outsourcing that, in turn, should lead to increased benefits and the avoidance or reduction of any negative impact on perfor- mance. Many companies have experienced difficulties with avail- ability of high-quality products and services on time and at minimum cost because they do not have appropriate performance measures and metrics (incorporating tangibles, intangibles, finan- cial and non-financial) for outsourcing decisions.

The main contribution of this paper is to present a classification of appropriate PMMs in outsourcing in both manufacturing and service industries, which would apply to offshore, near shore and onshore outsourcing (Bunyaratavej et al., 2007; Doh, 2005; Hahn et al., 2011; Hätönen and Eriksson, 2009; Schmeisser, 2013), as well as pre-, during-, and post-outsourcing decisions. This would need to incorporate outsourcing performance measures and metrics that include PMMs. Most of the extant frameworks (e.g. Jiang and Qureshi, 2006; Jiang et al., 2006; Mantel et al., 2006; Kremic et al., 2006; Vining and Globerman, 1999; Neely et al., 2000; Marshall et al., 2007; Javalgi et al., 2009) tend to focus on the selection phase (or pre-outsourcing stage) of the decision- making process (Westphal and Sohal, 2013).

In this paper we use the framework on outsourcing decisions by Sanders et al. (2007), who classify outsourcing decisions based on different categories of outsourcing engagements. In particular, the classification is based on the scope of the function assigned to an outside party, as well as the criticality of the task to the activities of the client. Outsourcing engagements are classified, hence, in (ibid): out-tasking, where the responsibility for a task is assigned to an outside supplier; co-managed services, where a larger task or function is assigned, but remains under the control of the client; managed services, where the scope is larger (the client abdicates the responsibility of designing, implementing, and managing to the supplier); and full-outsourcing, where the supplier takes full responsibility for the design, implementation, management and strategic direction of the function, operation, or process. Out- tasking and co-managed services refer to tactical outsourcing engagements, whereas managed services and full-outsourcing refer to strategic outsourcing engagements (Sanders et al., 2007). In each of these categories, tangibles, intangibles, financial and non-financial performance measures and metrics need to be

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166154

considered. However, the framework needs adapting before apply- ing it to specific industrial environments.

Now the question is: what performance measures and metrics should be employed at each strategic and tactical engagement outsourcing decision? In view of the importance of outsourcing in global competition, an attempt has been made in this paper to review the literature available (mostly published after 2000) with the objective of determining key PMMs in outsourcing in manu- facturing and service industries. The objectives of this paper are thus to: (i) understand the scope of PMMs in outsourcing deci- sions; (ii) identify a suitable framework for classifying the litera- ture on PMMs in outsourcing; (iii) briefly review the literature available on PMMs incorporating modelling and analysis of deci- sions in outsourcing; (iv) synthesize the findings of the literature review; (v) present a classification of the PMMs in outsourcing, and (vi) identify some future research directions.

2. Classification criteria used for the review of literature on outsourcing PMMs

2.1. Choice of framework

Scholars have attempted to classify outsourcing decisions from different perspectives (e.g., Jiang and Qureshi, 2006; Jiang et al., 2006; Mantel et al., 2006; Sanders et al., 2007; Vining and Globerman, 1999). However, existing studies focus mostly on the selection phase (or pre-outsourcing stage) of the decision-making process (Westphal and Sohal, 2013). Han et al. (2008) present a theoretical framework for outsourcing decisions that include the firm's capability (technical and managerial capability, organiza- tional relationship capability, and vendor arrangement capability), interaction processes (information sharing, communication qual- ity, collaborative participation), relationship intensity (trust and commitment) and performance (outsourcing success). They study the effect of a company's resource capabilities and interaction processes on the success of IT outsourcing. PMMs can be devel- oped to cover these areas so that companies can evaluate the total cost and total benefit of outsourcing both in the short- and long-term. Jiang and Qureshi (2006) provide a comprehensive review of the literature on outsourcing results. They highlight the importance of considering intangibles and the strategic impact while making decisions about insourcing and outsourcing, similar to make-or-buy decisions, but with a different scope and broader objectives. However, their main focus is on the pre-outsourcing stage.

In this paper, the available literature on PMMs in outsourcing has been classified using the framework of Sanders et al. (2007) (Fig. 1).

The framework is based on research conducted with 19 senior executives who are experienced in outsourcing, as well as a thorough synthesis of available research. Outsourcing decisions are classified based on the scope of the outsourcing engagement – defined as the responsibility assigned to the supplier – and the criticality of the outsourced task for the activities of the client organization. Four different outsourcing categories are therefore suggested, namely, out- tasking, co-managed services, managed services, and full-outsourcing. At one extreme, out-tasking involves assigning responsibility of a tactical task or function, but not a strategic function; the task is, hence, of low risk for the client organization. On the other side of the spectrum, full- outsourcing means that the outsourced task is critical to the client organization and therefore the risks entailed in such decisions are high. Sanders et al. (2007) suggest that out-tasking and co-managed services are related to tactical-level outsourcing. At the tactical level, outsourcing could be intended to address financial cost issues and meet financial objectives, deal with difficulties related to capital needed for asset acquisitions, or acquire a non-core capability. Out- tasking could also be used when broadening geographic reach, to reduce costs and improve time to market. To this end, tactical outsourcing engagements shift from financial to resource objectives, but these engagements also reduce costs and time needed to deploy new capabilities. Strategic outsourcing engagements that focus on strategic objectives include managed services and full outsourcing. They do not focus necessarily on short-term financial benefits, but on long- term strategic positioning. To achieve a strategic goal through mana- ged services and full outsourcing engagements, it may be necessary for the client organization to commit funds to achieve profitability at a later stage. The framework and our paper reflect the focus of the extant literature on the strategic and tactical levels of outsourcing decisions (Holcomb and Hitt, 2007; Quelin and Duhamel, 2003; Sanders et al., 2007). Outsourcing decisions are not a concern at the operational level since at this level decisions have to do with how different parts of an organization manage resources, processes, and people to deliver decisions made at strategic and tactical levels (Johnson et al., 2014). Tactical outsourcing is concerned mainly with cost reduction and comparison, and ‘make or buy’ decisions (Kedia and Lahiri, 2007). Strategic outsourcing focuses on achieving compe- titive advantage through outsourcing. The focus is on those resources and competencies that enable the achievement of sustainable compe- titive advantage, whereas firms should outsource all other non-core activities to other firms (Hamel and Prahalad, 1990; Kedia and Lahiri, 2007). Companies focusing on strategic and tactical outsourcing decisions are better able to seize opportunities and gain performance benefits (e.g., Ekanayaka et al., 2003; Kroes and Gosh, 2010; Lindner, 2005; McIvor, 2008; Sia et al., 2008; Tjader et al., 2014).

In this paper we adapt the framework by Sanders et al. (2007) to include the appropriate measures and metrics, so that strategic and tactical decisions can be aligned with goals at the pre-, during- and post-outsourcing stage in both manufacturing and services. Under each major classification (strategic and tactical engage- ments) there is a sub-classification of literature covering financial and non-financial performance measures and metrics, and each sub-classification is further classified based on tangibles and intangibles. Since most of the papers deal with a mix of perfor- mance measures and metrics (financial, non-financial, tangible, intangibles), we have identified PMMs in outsourcing decisions at these two levels, but not classified the references under each of the sub-classifications to avoid duplication of citations while reviewing the literature on PMMs in outsourcing. This is also due to the fact that many papers consider more than one level of performance measures and metrics, and come under more than one classification criterion. The PMMs presented in each category are not necessarily mutually exclusive. But the PMMs from each article have been carefully reviewed to identify the tools and techniques related to these PMMs as presented in Section 4.

Fig. 1. The framework (Sanders et al., 2007: p. 10).

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166 155

Similar PMMs can be employable for offshore, nearshore and onshore decisions, although some measures and metrics (based on enablers) are very specific to each of these situations. In particular, “location” (i.e. geographical proximation) has been highlighted in the extant literature as a differentiator between onshoring, near- shoring, and offshoring (Bunyaratavej et al., 2007; Doh, 2005; Hahn et al., 2011; Hätönen and Eriksson, 2009; Schmeisser, 2013), since where to outsource has further implications in terms of the risk of operating in an “unknown” environment (financial risks, Intellectual Property risks, governmental roles, knowledge skills), and also it relates to the timing of outsourcing. However, Hahn et al. (2011) suggest that nearshoring is important in manufactur- ing since nearby locations have an impact on transportation costs and turnaround times – thus they highlight the importance of location. However, they postulate that, given the low cost of electronic communications, many services can be transmitted electronically and therefore the advantage of nearshoring as opposed to offshoring to geographically proximate locations “appears to be much less salient in the case of services.” (p. 358). What is common across the extant literature is that scholars highlight the importance of considering the impact of the choices made in all areas of organizational performance including short-, medium- and long-term outcomes while making decisions about outsourcing options (e.g., Jiang et al., 2007; Kotabe et al., 2008; Manning et al., 2011).

2.2. Methodology

We conducted the literature review following the general guide- lines by Rowley and Slack (2004) that have been used in a recent review by Chen et al. (2014). We: (a) collected the material based on searches for scientific/academic articles on PMMs in outsourcing decisions: (i) ScienceDirect; (ii) Emerald Insight; (iii) Inderscience; and (iv)Taylor & Francis. The reason for choosing these databases is that together they comprise comprehensive coverage of scientific journals, including many highly ranked journals. We used the follo- wing keywords: ‘performance measures’, ‘outsourcing’, ‘metrics’, ‘supplier selection’, and ‘supplier performance evaluation’. Since out- sourcing is becoming a more mature operations strategy, the litera- ture spans the years from 2000 to 2013.

This enabled us to: (b) made notes on these articles; (c) structure the literature review; (d) build the bibliography and classifications; and (e) write the literature review. The measures and metrics that we discovered based on the literature review indicate that they can be generalized, while undergoing minor adaptation to specific situations in both manufacturing and services. Such a perspective has been followed in Denk et al. (2012) and Beske et al. (2014), while Lee and Baskerville (2003) also suggest that it is possible to formu- late theory (and in our case PMMs for outsourcing) “based on the synthesis of ideas from a literature review” (p. 238).

The authors collaborated and interacted on all aspects of the literature review and classifications (Chen et al., 2014). We acted as reviewers for the articles identified, and in cases where there was disagreement as to whether specific articles should be included, further discussions took place until agreement was reached. Our analysis followed the argument that the intellectual core and identity construction of the discipline can be revealed by “aggre- gating individual research papers at a higher semantic level” (Sidorova et al., 2008: p. 470). We controlled for a higher level of quality by limiting the search process to peer-reviewed articles, following Esposito and Evangelista (2014). The final sample con- sisted of 41 usable articles. Full bibliographic details are given in the reference section in order to make our research processes transparent (ibid). The articles were studied in-depth and the results are discussed in the following sections.

In the next section, we follow the classification of Sanders et al. (2007), in reviewing and classifying the extant literature on outsourcing decisions and relating it to PMMs.

3. Review of the literature on PMMs in outsourcing decisions

3.1. Strategic outsourcing engagement decisions and relevant PMMs

Strategic outsourcing engagement decisions are related to the design, implementation, management, and strategic direction of functions, operations or processes that are highly critical and risky, since the client organization assigns either total or large-scale responsibility to the supplier. Such decisions may involve, for instance, sourcing decision-making, which is multi-dimensional and entails both contractual and locational implications (Kotabe et al., 2008). While making strategic outsourcing decisions, com- panies should consider, for instance, manufacturing costs, the cost of resources, and exchange rate fluctuations, availability of infra- structure, industrial and cultural environments, and ease of work- ing with foreign host governments.

Financial performance measures have been widely used to evaluate the performance of strategic outsourcing outcomes. Top management is responsible for strategic decisions and therefore particularly interested in financial outcomes, such as sales, rev- enue and profit. But these outcomes need to relate more to long- term financial gains. Competitive advantage may “require an initial outlay of funds before profitability is realised” (Sanders et al., 2007: p. 10). While tangible performance measures can be easily traced and measured, intangible financial performance is focused on subjective financial performance measures such as financial viability, strength, investment in knowledge and research and development. Non-financial performance measures at the strate- gic level have gained attention over the past 10 years given that they are equally important as financial performance measures and need be factored into PMMs in outsourcing decisions.

In this section, we review the literature on strategic level PMMs in outsourcing decisions under the classification of financial and non-financial and then for tangibles and intangibles, focusing on the pre-outsourcing, during-outsourcing, and post-outsourcing stages (Table 1).

3.1.1. Pre-outsourcing stage decisions Decision-making at this stage is usually based on whether

outsourcing, being a major strategic decision, will permit organi- zations to develop and leverage the capabilities required to compete in today's global business environment. McIvor (2008) presented a practical framework that managers can use in the pre- outsourcing phase to identify suitable outsourcing strategies for their processes. The framework provides a number of important insights for managers who want to develop and implement out- sourcing strategies in their business processes: (i) see beyond the indicators of poor process performance; (ii) analyze the processes and interdependencies; (iii) understand the potential prior to outsourcing the process; and (iv) use the contract and relationship strategy as complementary. The sourcing strategies presented considering two influential theories, viz., transaction cost econom- ics (TCE) and the resource-based view (RBV) in four quadrants are both useful for developing analytical models for optimization of outsourcing activities.

Since companies are increasingly opting to outsource, supplier selection has become a major strategic decision (Kannan and Tan, 2003; Huang and Keskar, 2007). The following performance mea- sures have been suggested for supplier selection: product-related measures (reliability, responsiveness and flexibility), supplier-related measures (cost and financial status, assets and infrastructure) and

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166156

society-related measures (safety and environmental). Also, at the integration level, it is necessary to look at the level of integration that exists between the original equipment manufacturer (OEM) and suppliers, to look at operational integration and to examine strategic partnerships. Metters (2008) presented a comprehensive typology to apply to offshore outsourcing decisions. He claims that while offshoring is a possible option, a certain proportion of service processes will remain in high-wage countries. Li et al. (2009)

developed a dynamic model to select contract suppliers under conditions of price and demand uncertainties.

Other studies have used game theory for pre-outsourcing deci- sions. For instance, Li et al. (2009) developed two dynamic three-game models based on production costs and scope economics to study the multi-client outsourcing (MCO) phenomenon that is one vendor vs. multiple clients. They applied the concept of sub-game perfect equi- librium to analyze the three-game models by backward induction and

Table 1 Summary of strategic outsourcing engagement decisions and relevant PMMs.

Strategic outsourcing engagement decisions and PMMs Pre-outsourcing stage

Type of PMMs Tangibles Intangibles References

Financial Total supply chain management cost, sales, return on asset, return on equity, return on sales, return on investment, client and supplier investments, transaction costs, supplier related costs, profitability, productivity, IT productivity, cost of sharing and cost of running, market volatility.

Financial strength, research and development. Nam et al. (1995), Alvarez and Stenbacka (2007), Dube et al. (2007), Araz et al. (2007), Araz and Ozkarahan (2007), Jiang et al. (2007), Huang and Keskar (2007), Holcomb and Hitt (2007), Isklar et al. (2007), Li et al. (2009), Lim and Tan (2010)

Non-Financial Production facility, procurement facility, location, commonality of products, market uncertainty, requirements' uncertainty, customer service level, productivity, quality, reliability, speed to market, access to outside skills and experience, degree of expertise, responsiveness, flexibility, safety and environment, time to design and produce new products, customer satisfaction, environmental stability, value difference to quantity, risk of losing organizational competencies, alliances' risk perspectives, extent of substitution, firm size.

Brand, industrial and cultural environment, goodwill, opportunistic behaviour, intellectual property law, inter-organizational relationships, loss of local and tacit knowledge, innovativeness, social exchange, competitor orientation, organizational ability, opportunities, alignment of capacity and needs, morale problems, loss of management control, knowledge capital, knowledge acquisition, efficient governance, strategic alliance, core competencies, cultural conflict, reputation, degree of control and trust.

Nam et al. (1995), Bhattacharya et al. (2003), Elmuti (2003), Huang and Keskar (2007), Paisittanand and Olson (2006), Huang and Keskar (2007), Kshetri (2007), Li et al. (2009), Holcomb and Hitt (2007), Xiao et al. (2007), Yang et al. (2007), McIvor (2008), Metters (2008), Li et al. (2009), McIvor (2009), Tjader et al. (2010), Feng et al. (2011).

During-outsourcing stage Financial Profitability, higher transaction costs, supplier-related

costs, sales growth, cost reduction. Financial strength. Arya et al. (2008), Bahli and Rivard (2005),

Gottfredson et al. (2005), Barthelemy (2003), Ellram and Billington (2001), Ellram et al. (2008), Falk and Wolfmayr (2008), Lim and Tan (2010), O'Toole and Donaldson (2002), Sinkovics and Roath (2004).

Non-Financial IT infrastructure, rate of sales of new products, service performance, inventory turns, number of new products launched, long-term partnership contracts, access to outside skills and experience, alliances’ risk perspectives, commitment, quality of service.

Environmental dynamism, knowledge and know-how, contract control, environmental heterogeneity, inter- organizational relationship, innovation, social exchange, ease of working, market conditions, competitor orientation, cultural conflict, trust, knowledge management and acquisition.

Abdel-Malek et al. (2005), Aksin and Masini (2008), Araz and Ozkarahan (2007), Arya et al. (2008), Bahli and Rivard (2005), Barthelemy (2003), Barthelemy (2003), Buehler and Haucap (2006); Conklin (2005), Ellram et al. (2007), Elmuti (2003), Goo et al. (2007), Hoecht and Trott (2006), Kotabe et al. (2008), Li et al. (2008), McDermott and Handfield (2000), Osei-Bryson and Ngwenyama (2006), O'Toole and Donaldson (2002), Raiborn et al. (2009), Tomiura (2007), Walden and Hoffman (2007).

Post-outsourcing stage Financial Cost efficiency, profitability, productivity, switching

costs, adaptation costs. Complexity of governance structures.

Barthelemy and Quelin (2006), Jiang et al. (2006, 2007).

Non-Financial Reliability, responsiveness, infrastructure, flexibility, market share, difficulty in vendor change, risk, loss of control over outsourcing process, loss of control over quality, loss of the ability to protect product confidentiality.

Skills and knowledge, vendor support, familiarity with outsourcing strategy, utilization of outsourcing strategy, trust, reputation, value of the outsourcing relationship, organizational communication, employee morale, political issues.

Barthelemy and Quelin (2006), Elmuti (2003), Weidenbaum (2005).

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the criterion used is the vendor's profit maximization. Tjader et al. (2010) present a multi-criteria decision-making methodology using Analytical Network Process (ANP) to develop an evaluation framework from the perspective of decision-makers, stakeholders, and influential groups. They evaluated four policy options with respect to approxi- mately 50 economic, political, technological and other factors. Araz et al. (2007) developed a fuzzy goal programming model for a textile company that could be used as an external vendor evaluation and management system. This is based on a well-known methodology called PROMETHEE (Multi-Criteria Decision aid Method and Fuzzy Goal Programming). They classified supplier selection methods into five categories: categorical approaches, artificial intelligence (AI), rating/linear weighting models, mathematical programming models, and integrated approaches.

Liou et al. (2011) proposed a hybrid multiple-criteria, decision- making model (MCDM) for selecting an outsourcing service provi- der combining decision-making trial and evaluation laboratory (DEMATEL), to establish the relations-structure model in evaluation problem, with fuzzy preference programming (to decide upon the pairwise comparisons from imprecise judgement), and ANP (to determine criteria weights with dependence and feedback) meth- ods. Feng et al. (2011) developed a decision method for selecting a pool of suppliers for the provision of different service process/ product elements. It employed collaborative utility between partner firms for supplier selection. Multi-objective 0-1 programming was used to select desired suppliers. They proved that the model was NP-hard and developed a multi-objective algorithm based on Tabu search to solve the problem. Isklar et al. (2007) proposed an integrated intelligent decision support model for effective supplier selection problems. This model combines different techniques in order to take advantage of the reasoning power of these techniques.

Bhattacharya et al. (2003) suggest a risk management perspec- tive for IT/IS outsourcing research. Business process outsourcing may appear to be just IT/IS outsourcing, but in practice it represents a global phenomenon. Some of the major criteria used in the selection of ERP suppliers are: interfaces with other systems, price, market position, corporate image and international orientation. They also included some additional criteria, namely: customer service, relia- bility, availability, scalability, integration, financial factors, security and service-level management.

At the pre-outsourcing stage, scholars have used TCE and RBV to explain outsourcing complexities. But, according to McIvor (2009), “neither TCE nor the resource-based view (RBV) alone can fully explain the complexities of outsourcing”. Instead, he proposed a prescriptive framework for evaluating outsourcing, integrating TCE and RBV. Transaction costs are the costs of activities after the product and service are ready to be exchanged between suppliers and clients or customers. This focuses on how much effort and cost is required for the buyer and seller to complete an economic exchange or transaction (Coase, 1937; Williamson, 1975, 2008; Oliva and Watson, 2011). According to Grover and Malhotra (2003), the three most important factors that influence the outcome of TCE are asset specificity, uncertainty and governance mechanisms. Uncertainty is related to performance evaluation, information asymmetry problems, the envir- onment, technology and demand volume and variety. The governance mechanisms depend upon the hierarchies within firms, cooperative behaviour in the buyer-supplier relationship, and increased frequency of communication and control. The RBV includes the firm's assets, organizational processes, and information technology and knowledge (Barney, 1991). Also, the importance of operations management concepts such as performance management, operations strategy, business improvement and process redesign for the study of out- sourcing is highlighted. Espino-Rodriguez and Padron-Robaina (2006) reviewed the literature on RBV and outsourcing, and illustrate the differences between TCE and RBV in that although both contribute to the definition of organizational boundaries (that is, outsourcing vs.

internalization), they differ in that: (i) TCE suggests that when activities based on specific resources are outsourced, the performance of the firm can be negatively affected, because of the increased risk stemming from opportunistic behaviour. However, from a RBV perspective, the decision to outsource depends on the “extent to which activities permit the exploitation of different knowledge, capabilities and routines within the organization” (p. 55); (ii) TCE does not recognize the importance for a firm to focus on its core competencies and safeguard its strategic resources (Prahalad and Hamel, 1990). Therefore, it does not focus on analyzing the capabil- ities of the organization, and its potential partners or suppliers during decision-making. However, Espino-Rodriguez and Padron-Robaina (2006) suggest that RBV and TCE are not opposed, but are comple- mentary in analyzing outsourcing strategies.

Finally, a variety of mathematical models have been reported for modelling strategic decision-making, including a game-theoretic approach. For example, Xiao et al. (2007) studied production and outsourcing decisions made by two manufacturers that produced partially substitutable products; and they played a strategic game involving quality competition. Both manufacturers outsourced key components to the same upstream supplier. As a result, their pro- ducts became more substitutable due to the increased availability of the products.

The PMMs for the during-outsourcing stage are discussed in the next section.

3.1.2. During-outsourcing stage decisions Outsourcing performance in this stage depends, inter alia, upon

the sharing of knowledge and resources, on the collaboration between the outsourcee and outsourcer, and on the extent to which these two partnering firms work together in a trusting and mutually supportive environment. The role of communication is vital in this effort. Aksin and Masini (2008) suggest that the effectiveness of a shared-services project depends on the degree of complementarity that exists between the needs of a company and the specific capa- bilities developed to address these needs. The following factors have been considered to influence shared services: (i) environmental factors (environmental dynamism, environmental heterogeneity, IT infrastructure and firm size); and (ii) managerial decisions (off- shoring, outward orientation, outsourcing, Shared Service Organiza- tion (SSO) concentration, commitment, and the type of service monitoring mechanisms that are used). This indicates that structural and cultural alignment between client and supplier firms are essential for success in outsourcing. To achieve this, suitable perfor- mance measures and metrics need to be considered.

As in the pre-outsourcing stage, game theory and programming could be used. Lim and Tan (2010) devised a dynamic game- theoretic model for identifying conditions under which firms could alleviate supplier opportunism in the outsourcing paradox. They suggest that outsourcing can be a viable option for a company; however, it is critical that the buyer fully understands and mitigates the long-term cost of outsourcing in terms of the threat of downstream market competition from the supplier as a result of its outsourcing experience. Ellram and Stanley (2008) discuss various performance measures in strategic cost manage- ment which include cost reduction, time to market on new products/services, meeting customer needs, product/service per- formance, new product/service launches, cost savings/increased profitability, responsive supply chain, working capital and manu- facturing reliability. It should be noted that some of these measures can be strategic as well as tactical.

There are many intangibles and non-financial performance mea- sures that should be also considered. For example, Li et al. (2008) developed a model for outsourcing decisions incorporating knowledge management, socialization, and alliance risk, and discuss the motives

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for acquiring partners' tacit knowledge through offshore outsourcing to influence innovation. A convergent reliability of the measurement models along with knowledge acquisition though offshore outsour- cing, formal control, social control, incremental innovation and radical innovation, and performance indicators can be modelled as a perfor- mance measurement tool in outsourcing decisions.

The costs and benefits of IT sourcing have been widely discussed in the literature. IT outsourcing does not involve much in the way of logistical costs and/or challenges as it does in the manufacturing of goods. Barthelemy (2003) indicates that we have to measure the hard side of outsourcing (precision of the contract) and also the soft side of outsourcing (trust, relationships). Conklin (2005) deals with the risks and rewards associated with HR business process outsourcing. Outsourcing decisions and corre- sponding implications can vary according to the position of a particular product in its life cycle. Outsourcing new product manufacturing requires a different set of PMMs. McDermott and Handfield (2000) analyze the processes associated with the development of new products and subsequently present a com- prehensive decision tree that includes a decision matrix with insourcing and outsourcing for both product development and manufacturing.

IT outsourcing has been at the forefront of outsourcing strategy due to the high cost of labor for maintaining in-house IT specialists, and the ease of exchange of products and services such as those available at call centres. A multi-theoretical approach (MTA) has been widely employed in outsourcing decisions. However, this creates more challenges and acts as a hurdle to the implementation of a user-friendly PMMs system. Goo et al. (2007) considered an MTA to study the factors that influence the duration of IT relationships between vendor and client firms in outsourcing. Some of the factors considered include: knowledge acquisition, strategic importance of IT activity, relationship-specific investment, requirement uncertainty, extent of substitution, opportunistic behaviour and satisfaction with output quality. The control variables include the organization size and the type of outsourced IT activity.

A variety of mathematical models have been reported for modelling strategic decision-making, including a game-theoretic approach. Buehler and Haucap (2006) analyzed a sequential game where firms decide about outsourcing the production of a non- specific input good to an imperfectly competitive input market. They applied a taxonomy of business strategies to characterize the different equilibria and found that outsourcing generally softens competition in the final product market. Considering the numer- ous possible uncertainties and different scenarios, game theore- tical models should be useful. However, making optimal decisions while considering all the realistic variables and constraints would be a challenge. Game theoretic models are suitable for outsourcing decisions with limited real-life considerations.

Financial and econometric models have been used for model- ling and for analysis of strategic decisions in outsourcing. For example, Arya et al. (2008) claim that duopoly competition can be reversed when the key production inputs are outsourced to a vertically integrated retail competitor with upstream market power. Using this outsourcing strategy, competition can produce higher prices, higher industry profit, lower consumer surplus and lower total surplus than competitors. Tomiura (2007) envisioned how productivity would vary with globalization, based on a firm- level data set covering all manufacturing industries in Japan.

Osei-Bryson and Ngwenyama (2006) proposed a method and mathematical models for analyzing risks and incentive contracts for IT/IS outsourcing. Contracts are an important part of the analysis of outsourcing decisions as they provide an effective mechanism for managing the outsourcing relationship. Ellram et al. (2008) utilize the framework of transaction cost economics (TCE) to develop an understanding of how firms manage the costs

and risks of offshore outsourcing of professional services. Some of the risks involved with outsourcing include market volatility, incomplete specifications, inability to measure performance and so on. Other determinants of outsourcing comprise: degree of control over processes, level of trust required, strategic importance of task and level of investment in assets by a client firm.

Falk and Wolfmayr (2008) discuss the effect of international outsourcing of services to low-wage countries on employment using a sample of manufacturing and non-manufacturing indus- tries in five EU countries. In the non-manufacturing sector, the total value of internationally purchased services from low-wage countries was statistically significant, but these purchased services had a small negative impact on employment.

Bahli and Rivard (2005) discuss the various risk factors in outsourcing IT operations. These include strategic and tactical level risks such as the client's loss of investment, the supplier's loss of investment, unsuitable human resources, an inappropriate degree of expertise with IT operations, therefore, these risks must be taken into account in outsourcing decisions. Raiborn et al. (2009) discuss the following risks with reference to outsourcing: loss of control, loss of innovation, loss of organizational trust and higher transaction costs. They offer some suggestions for dealing with support service outsourcing risks.

The PMMs for the post-outsourcing stage are discussed next.

3.1.3. Post-outsourcing stage decisions According to Jiang et al. (2006, 2007), outsourcing requires a

firm to incur the costs of negotiating, monitoring, and supervising external contractual parties. These factors need to be considered at the post-outsourcing stage, where the client organization would have to evaluate whether the outsourcing contract and supplier chosen was the appropriate one, whether, for example, the level of risk with the particular contract was low or high, and whether they would have to renegotiate the contract or select another supplier. Jiang et al. argue that the theory of transaction cost analysis explains the determinants of outsourcing decisions. They also maintain that signalling theory establishes a relationship between market value and outsourcing parameters. Risk is a major factor in outsourcing decision-making. There are different types of risks involved with outsourcing and these include: loss of control over the process, loss of control over quality and loss of the ability to protect product confidentiality and so on. A multi-criteria sorting method based on the PROMETHEE is also introduced.

Elmuti (2003) studied the perceived impact of outsourcing on organizational performance. In this study, factors such as out- sourcing familiarity, the duration of an existing program, vendor trust, the extent of interest in establishing a new program, improvement of an ongoing program or discontinuation of the present outsourcing strategy are considered. They classify the factors associated with success or failure of outsourcing to increase performance into two categories, namely, factors for successful and unsuccessful contracts. For the former, factors such as clear objectives and expectations of the outsourcing activities, adequate skills to renegotiate a contract, planning, organizational commu- nication, top management support, infrastructure, high employee morale, and flexibility in anticipating change are noted. For the latter, fear of change, inadequate planning, lack of infrastructure, cross-functional political problems, poor communication, hidden risks and costs, lack of control and flexibility were found.

Barthelemy and Quelin (2006) used TCE and RBV to study outsourcing agreements. In particular, they provide a model to analyze the complexity of outsourcing contracts and the link between exchange hazards (i.e. specificity and environmental uncertainty), the contractual aspects of outsourcing (control, incentives, penalties, price and flexibility clauses) and the level

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of ex-post (post-outsourcing) transaction costs. Such costs are high because of the high expenditure involved in: (i) ensuring that the vendor has fulfilled all contractual obligations (monitoring costs); and (ii) enforcing contractual clauses (enforcement costs). They propose three variables for evaluating the strategic importance of an outsourced activity: proximity to the core business; switching costs and adaptation costs. They suggest that the more complex an outsourcing contract is, the higher the ex-post transaction costs would be. They advise practitioners that to avoid vendor oppor- tunism, the client should ensure that contracts contain incentives and penalties, as well as pricing and monitoring clauses.

Strategic outsourcing decisions play a major role in organizational performance and competitiveness. Following Sanders et al. (2007), it is confirmed that at the strategic outsourcing stage firms are willing to include more strategic-oriented than short-term financial PMMs. Though tactical decisions are important, it is the strategic decisions that will have the greatest long-term impact on organizational performance. Strategic outsourcing also takes into account the big picture of the organization's vision, scope and objectives. Even a minor change in strategic level decisions will be amplified to a great extent along the downstream side of supply chain operations.

In the next section, tactical engagement outsourcing decisions and relevant PMMs are discussed.

3.2. Tactical engagement outsourcing decisions and relevant PMMs

Tactical engagement decisions concern less risky outsourcing engagements (Sanders et al., 2007). They can be related to, for example, processes at the aggregate production planning levels, data management, IT/IS for supply chain integration and selection of outsourcees (Table 2).

In tactical level outsourcing decisions, both financial and non- financial performance (tangible and intangible) measures are used. The financial intangibles in tactical level sourcing decisions include all the hidden costs and benefits. This is very important as most companies miss the hidden costs and benefits that may have a significant impact on organizational performance and competitive- ness. However, the major challenge is how to evaluate intangible financial implications while making outsourcing decisions. Further- more, our review suggests that companies in the early stages of outsourcing consider mostly tactical, but not strategic outsourcing engagements, decisions, and PMMs. However, these strategic and tactical engagement decisions are closely related to each other. We have made an attempt to address this issue through the results presented in Tables 1 and 2.

3.2.1. Pre-outsourcing stage In the pre-outsourcing stage, many financial and non-financial

metrics are used. For instance, Huang and Keskar (2007) suggest the following product related measures: reliability, responsive- ness and flexibility. At the integration level, it is necessary to look at operational integration. They discuss whether any integration exists between OEM and suppliers, operational integration and strategic partnership. Operational integration (tactics) is equally as important as strategic and tactical integration between buyer and supplier firms in outsourcing. Furthermore, product-related issues (reliability, responsiveness, flexibility), supplier-related issues (cost and assets and infrastructure) and social issues (safety and environmental) are incorporated in supplier selection metrics.

Araz and Ozkarahan (2007) employ the following performance measures to select suppliers: communication effectiveness, delivery reliability, cost reduction, financial strength, support in process design and engineering, design time, prototyping time and level of technology. In a more recent study, Lee and Choi (2011) model a

two-stage production scheduling problem in which each activity requires two operations to be processed at stages 1 and 2, respec- tively. The objective was to minimize the weighted sum of the makespan and the total outsourcing cost. This paper presents an approximate algorithm for one NP-hard case. Furthermore, using discrete-event simulation, Liston et al. (2007) developed tools to support outsourcing companies to estimate the cost of a contract. Anthony (1965) discussed a detailed framework and analysis for planning and control systems. The type of systems will assist the outsourcing decisions.

Lamminmaki (2008) discusses the role of management account- ing in hotel outsourcing. A decision about whether outsourcing decisions are based on long-term strategic goals depends on vari- ables affecting both the nature of accounting involvement and the degree of accounting sophistication in hotel outsourcing manage- ment. Lamminmaki (2011) examined the perspective of TCE theory in a hotel management context and presents 20 important factors that can influence the decision to outsource in a hotel.

Finally, Gooroochurn and Hanley (2007) studied the relative importance of property rights, and transaction cost factors, in driving the decision of firms to outsource innovation. According to them, property rights factors usually take precedence over trans- action cost factors. Transaction costs are more important for process innovation, while property rights factors are more sig- nificant for firms involved in product innovation.

3.2.2. During-outsourcing stage Logistics and inventory management, distance, nationalism, a

lack of working knowledge about foreign business practices, among others should be considered as problems during the out- sourcing stage (Doerr et al., 2005; Kotabe et al., 2008). Bengtsson and Berggren (2008) explored the dynamics of outsourcing and production strategies in the telecoms equipment industry. One of the critical aspects they identified is the interaction between product development and production. They analyze issues such as component standardization, differentiation and technological integration and their impact on integration capabilities for cost reduction.

Inventory models have generally been used for optimal sche- duling and production control. Now the question arises as to whether the same models can be used for outsourced environ- ments where the production control rests with outsourcee firms. Abdel-Malek et al. (2005) presented a framework for comparing outsourcing strategies in multi-layered supply chains. In order to estimate the required level of safety stock, the supply chain is modelled as a set of tandem queues and the lead-times are computed by using both Markovian closed-form expressions and simulation experiments. It is an interesting paper in which the optimal safety stock in a multi-layered supply chain is determined. Furthermore, Wang and Chen (2009) developed a model for capacity planning and resource allocation in two profit-centered factories. They proposed an ant colony algorithm for solving a set of non-linear mixed integer programming models of the problem being addressed, involving the different economic objectives and constraints of the negotiating parties.

Resource-based PMMs in outsourcing have been widely em- ployed in decision-making. Though it has worked out well for standard products and services, quality and long-term performance presents a challenge. Lahiri and Kedia (2009) focus on the resources and capabilities that are utilized by the providers in fulfilling their clients' sourcing needs. Using the resource-based view and social exchange as theoretical foundations, they claim that the provider's human capital, organizational capital, management capability, and partnership quality are crucial assets. Zhang and Du (2010) deal with a multi-product newsboy problem with limited capacity and

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outsourcing in which they consider two outsourcing strategies: (i) zero lead-time outsourcing and (ii) non-zero lead time out- sourcing. They develop structural properties and solution procedures for profit maximization via non-linear programming models.

Barthelemy (2003) suggests measuring the hard side of out- sourcing, while O'Toole and Donaldson (2002) propose that shar- ing information, the soft side, is one of the PMMs in outsourcing.

Aron et al. (2008) investigate the implications of recent advances in IT and telecommunications on the real-time monitoring of processes at the site of the provider by a buyer located across the globe. They develop a game-theoretic model of the dynamics of the buyer-supplier interaction in the presence of moral hazards and incomplete contracting. They argue that complex production processes lead to more errors.

Table 2 Summary of tactical outsourcing engagement decisions and PMMs.

Tactical outsourcing engagement/decisions and PMMs Pre-outsourcing stage

Type of PMMs Tangibles Intangibles References

Financial Manufacturing costs, distribution costs, costs of negotiation, costs of monitoring and supervising external contractual parties, cost of performance reduction, client investment, supplier investment, profitability of bought volume, cost adherence, transaction costs, price, productivity, distribution cost, inventory cost, set-up cost, cost of defective parts, shortage cost, material handling cost.

Cost of process and production innovation. Chen et al. (2001), Kakabadse and Kakabadse (2005), Araz and Ozkarahan (2007), Gooroochurn and Hanley (2007), Huang and Keskar (2007), Liston et al. (2007), Olson (2007), Paisittanand and Olson (2006), Lim and Tan (2010), Lee and Choi (2011)

Non-Financial Rate of stock-outs, fill rate, order fulfilment time, information accuracy, information timeliness, delivery performance, design revision time, prototyping time and level of technology, support in process design and engineering, project quality, precision of the contract, involvement in design, volume of jobs to be outsourced, production plan, property rights, number of contracts, partnership quality, security issues, product functionality, market leadership, customer service level, commitment, customer satisfaction, scalability.

Core competencies, manufacturer-3PL relationships, market opportunities, collaboration, employment effect, trust, information technical capability, sharing, communication quality, process/product innovation, sharing knowledge, teamwork, cooperation, intellectual capital, vendor/ client trust, degree of expertise, goal setting and cultural blending, outsourcing effectiveness, formalizing sourcing process, information sharing, technical and managerial capability, access to new technology/skills, grow in-house expertise, responsiveness, enhance position in value chain, vendor selection capability, motivation of employees on the shop floor, loss of control.

Kakabadse and Kakabadse (2005), Jiang et al. (2007), Araz and Ozkarahan (2007), Gooroochurn and Hanley (2007), Huang and Keskar (2007), Kshetri (2007), Liston et al. (2007), Olson (2007), Wadhwa and Ravindran (2007), Yang et al. (2007), Han et al. (2008), Lamminmaki (2008, 2011), Cruijssen et al. (2010), Tjader et al. (2010), Lee and Choi (2011)

During-outsourcing stage Financial Cost of monitoring and supervising external

contractual parties, cost of poor scheduling and control, cost of poor quality components and parts, cost of defective parts, shortage or products cost, productivity, material handling cost.

Cost and benefit of employee motivation and teamwork, cost and benefit of employee morale, cost and benefit of poor training and motivation, hidden idle-time cost of employees, lost capacity.

O'Toole and Donaldson (2002), Barthelemy (2003), Sinkovics and Roath (2004), Bhali and Rivard (2005), Bengtsson and Berggren (2008), Falk and Wolfmayr (2008), Mao et al. (2008), Tate and van der Valk (2008), Raiborn et al. (2009), Lahiri and Kedia (2009), Wang and Chen (2009), Li and Wang (2010), Lim and Tan (2010), Zhang and Du (2010)

Non-financial Rate of stock-outs, safety stock level, capacity planning and resource allocation, lead-time, cycle time, handling of exceptions, scheduling flexibility, component standardization, differentiation, real-time monitoring, production process control, customer satisfaction, human capital, project quality, partnership quality.

Collaboration, employment effect, trust, information technical capability, information sharing, communication quality, process/product innovation, sharing knowledge, technological integration capability, buyer-supplier interaction, team work, cooperation, motivation of employees on the shop floor, relationship with supplier, intellectual value, management capability, skills shared.

Momme (2002), Momme and Hvolby (2002), Bandyopadhyay and Pathak (2007), O'Toole and Donaldson (2002), Barthelemy (2003), Abdel-Malek et al. (2005), Bhali and Rivard (2005), Conklin (2005), Tomiura (2007), Weidenbaum (2005), Tolio and Urgo (2007), Aron et al. (2008), Kotabe et al. (2008), Currie et al. (2008), Mao et al. (2008), Tate and van der Valk (2008), Lahiri and Kedia (2009), Wang and Chen (2009), Chen et al. (2014)

Post-outsourcing stage Financial Cost efficiency, profitability, productivity,

switching costs, adaptation costs, transaction costs, ROI.

Client's control over the vendor, service performance.

Jiang et al. (2007), Mao et al. (2008), Tate and van der Valk (2008)

Non-financial Customer satisfaction, infrastructure, project quality, quality improvements (process and service delivery).

Information sharing, inter-firm adaptation, goal setting, learning experience, communication quality, cultural blending, operational integration, employee morale, employee motivation, teamwork, shared effort for operational improvement.

Han et al. (2008), Jiang et al. (2007), Mao et al. (2008), Tate and van der Valk (2008), Tarakci et al. (2009)

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Tolio and Urgo (2007) developed a two-stage stochastic program- ming model to plan production and outsourcing resources in an Engineer-to-Order manufacturing environment producing complex items. They analyze the problem of negotiation and planning of external resource usage in a manufacturing system affected by un- certainty and the need of resources is considered uncertain and it is modelled through scenario formulation. O'Toole and Donaldson (2002) studied the implications of financial and non-financial dimensions of performance. Some of the non-financial performance dimensions include productivity, quality, speed of response, satisfac- tion, stability, flexibility, joint value projects, and involvement in design. The financial dimensions include switching, interdependence, confidence abuse, sharing of information, prices, ROI, profitability, bought volume, cost sharing and running costs. Finally, Li and Wang (2010) developed a two-stage newsvendor optimization problem to study the impact of uncertainties in the exchange rate and/or demand on the choice of a domestic and an offshore supplier. This study can be extended to multiple suppliers in order to represent a more realistic outsourcing situation.

In terms of non-financial PMM types, both tangibles and intangibles play a major role. For example, the kind and level of relationship between outsourcer and outsourcee influence the outcome. Currie et al. (2008) claim that Knowledge Process Out- sourcing (KPO) vendors are gradually moving along the value chain offering more complex intellectual value, activity-based products and services to clients. On a slightly different tack, Bandyopadhyay and Pathak (2007) modelled the interaction between employees of the “host” firm and the outsourcing firm, who have to share their knowledge and skill sets in order to work effectively as a team. The analysis of the model shows that if top management reinforces cooperation between employees of both firms, better payoffs can be achieved. In these situations, the

involvement of top management extends far beyond negotiating the contract to make the outsourcing successful.

3.2.3. Post-outsourcing stage Our review of the literature indicates that compared to the

other stages, there are less PMMs used in the post-outsourcing stage. In terms of financial PMMs, cost efficiency, profitability, productivity, switching costs, adaptation costs, transaction costs, ROI tends to be used (Jiang et al., 2007; Mao et al., 2008; Tate and van der Valk, 2008).

In terms of non-financial PMMs, Tarakci et al. (2009) studied the learning effects (experience and investment based) on main- tenance outsourcing. They assume that learning occurs when the contractor performs preventive maintenance that results in reduc- tion in time and costs. They develop a basic model to introduce a short-term contract assuming no learning occurs in maintenance operations and then incorporated learning effects in preventive maintenance operations.

Mao et al. (2008) found that trust had a significant effect on project quality, but little on cost adherence. In addition, informa- tion sharing, communication quality, and inter-firm adaptation emerged as three significant contributors to the vendor's trust in the client. Goal setting and cultural blending influence the client's control over the vendor. Cai et al. (2009) presented a systematic approach for improving supply chain performance management through an iterative accomplishment of key performance indica- tors. Furthermore, Tate and van der Valk (2008) show that quality improvements in both process and service delivery lead to decreased costs and this will enhance customer satisfaction and improve the company's buying performance. The current trend for outsourced business processes is based on efficiency

Table 3 Tools and techniques used for PMMs in outsourcing.

Level of engagement

Financial/ non- financial

Tools/techniques used in outsourcing performance measurement

Pre During Post References

Strategic Financial Game-theoretic models, risk assessment, real options approach, multi-criteria decision techniques, transaction cost economics, agency theory, mixed- integer model for bidding, fuzzy goal programming, stochastic and econometric models, DSS.

Game-theoretic models, multi- criteria decision techniques, transaction cost economics, financial and econometric models, DSS, risk assessment.

Multi-criteria decision techniques, transaction cost economics, DSS.

Nam et al. (1995), Araz et al. (2007), Dube et al. (2007), Ni et al. (2009), Lim and Tan (2010), Arya et al. (2008), Alvarez and Stenbacka (2007), Jiang et al. (2007), Bhali and Rivard (2005), Liou et al. (2011), Li et al. (2009)

Non- financial

Game-theoretic models, fuzzy logic and expert systems, multi-criteria decision techniques, mixed-integer model for bidding, Analytical Network Process (ANP), TCE, DSS, multi-objective 0-1 programming, multi-attribute utility theory, stochastic dynamic programming.

Game-theoretic models, risk assessment, multi-criteria decision techniques, DSS.

Multi-criteria decision techniques, transaction cost economics, DSS.

Nam et al. (1995), Otto and Kotzab (2003), Kotabe et al. (2008), Dube et al. (2007), Tjader et al. (2010), Araz et al. (2007), Goo et al. (2007), Xiao et al. (2007); Buehler and Haucap (2006), Alvarez and Stenbacka (2007), Bhali and Rivard (2005), Liou et al. (2011), Feng et al. (2011), Osei-Bryson and Ngwenyama (2006)

Tactical Financial Stochastic programming, goal programming, optimization problem, simulation, game theoretic modelling, TCE scheduling problem, non-linear mixed integer programming models, multi-criteria decision making models (AHP).

Game theoretic modelling, multi- criteria decision-making models, real options, Ant algorithm, non- linear programming (newsboy vendor problem).

Game theoretic modelling, multi- criteria decision- making models.

Li and Wang (2010), Cruijssen et al. (2010), Huang and Keskar (2007), Lamminmaki (2011), Liston et al. (2007), Currie et al. (2008), Tate and van der Valk (2008), Sinkovics and Roath (2004), Araz and Ozkarahan (2007), Wang and Chen (2009), Lee and Choi (2011)

Non- Financial

Game theoretic models, scheduling problem, stochastic programming model, simulation, non-linear programming model, capacity planning models, inventory models, simulation models.

Nash equilibrium models, game theoretic models, stochastic programming, TCE, Ant algorithms.

Game theoretic modelling, stochastic programming, multi- criteria decision- making models.

Tolio and Urgo (2007), Aron et al. (2008), Zhang and Du (2010), Huang and Keskar (2007), Kotabe et al. (2008), Araz and Ozkarahan (2007), Abdel-Malek et al. (2005), Wang and Chen (2009), Lee and Choi (2011)

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166162

improvements and cost savings. However, this research shows that this type of focus actually decreases customer satisfaction and increases costs.

4. Tools and techniques for performance measures and metrics in outsourcing

Based on the literature review and analysis in Section 3, an attempt is also made to determine a list of specific tools and techniques for PMMs in outsourcing (Table 3). It may be that measures and metrics overlap in strategic and tactical outsourcing engagement decisions. This taxonomy must be empirically tested either wholly or in part.

Hence, we propose that the tools and techniques in Table 3 require further research and this could be one of the most promising future research directions for operations researchers.

5. Managerial implications

The literature review demonstrates the diversity of PMMs related to strategic and tactical decisions to be made (Sanders et al., 2007), at the pre-, during- and out-sourcing stages, based on both financial and non-financial aspects, as well as tangibles and intangibles.

We stress the importance for managers to attend not only to the diverse PMMs related to outsourcing decisions, but also to the challenges related to deploying PMMs to their own decisions. We acknowledge that the business objectives, risks, stakeholder agendas and requirements, as well as costs in measuring the PMMs play a vital role in the selection of PMMs for outsourcing decision-making in these three stages. Managers need to consider these factors and adapt the PMMs suggested in this paper in order to make an informed decision on their choice of PMMs and outsourcing. During the selection and deployment of appropriate PMMs for particular orga- nizations, attention should be paid not only to the scope of out- sourcing and the criticality of the task to the clients' activities, but also, to whether the organization belongs to the manufacturing or service industry, to the organizational goals and objectives, the type of business, the nature of the market, and the technological competence of the organization (Gunasekaran and Kobu, 2007). Furthermore, in order to use these PMMs effectively, organizations will have to: (i) rely on robust data collection and analysis, and this is a major task in monitoring performance; (ii) fund a major investment in terms of infrastructure (e.g. computerized systems for efficient, accurate, and meaningful data collection and analysis) and human resources (e.g. data analysts who will have knowledge of the PMMs set out in Tables 1 and 2 and the techniques and tools in Table 3 and be able to adapt them to organizational needs). Auditing of such systems would need to be conducted regularly to ensure that the appropriate data is collected and analyzed, and the systems required are working appropriately or need to be updated. The use of systems will also reduce the time lag between outsourcing PMMs and applying corrective action, if needed.

It is also necessary to constantly update these PMMs in order to facilitate continuous improvement within organizations. Although many managers believe that, once determined, PMMs are permanent, the business strategy always needs to reflect customer requirements and therefore changes and evolves. Hence, the strategic and tactical decisions as well as their PMMs need to be updated accordingly. Another challenge relates to the influence of behavioral issues while selecting and deploying these PMMs and, in particular, the politics and culture of the organization, which play a significant role in determining and deploying PMMs. To address these issues, it is suggested that all appropriate stakeholders and senior executives

participate in determining the PMMs, so that the importance of achieving particular overall organizational outsourcing objectives is highlighted and the need to align targets at all levels is commu- nicated. In this regard, it would be of great help to establish frequent meetings between appropriate stakeholders and executives, as well as using transparent communication systems.

We believe that our classification and review could inform managers about the existence of different PMMs which can be then adapted, explored and exploited by managers in their strategic and tactical outsourcing decisions. Furthermore, our focus on the pre-, during-, and post-outsourcing stages demon- strates that focusing solely on supplier selection (pre-outsourcing stage) is not sufficient for achieving outsourcing benefits; the during- and post-outsourcing decisions are also important, and relevant PMMs should be used, as mentioned above, based on their specific organizational context.

6. Limitations and future research directions

This paper has a number of limitations:

1. The findings of the literature review are based on data collected from academic journals. We excluded practitioners' literature due to accessibility limitations (Eksoz et al., 2014). Future research could be worthwhile to extend the body of literature on PMMs in outsourcing decisions including heuristic literature from practitioners.

2. Our review spanned 13 years (2000–2013) and we believe it is representative of the literature on PMMs in outsourcing deci- sions. The list may not be exhaustive, but we believe that it is comprehensive, since it includes a comprehensive coverage of scientific journals, including many highly ranked journals.

3. The findings were based on the authors being guided by particular keywords, a technique already used in Eksoz et al. (2014), Ngai et al. (2008) and Chen et al. (2014). The authors have interacted on all aspects of the literature review and classifications (Chen et al., 2014) and solved any disagreements on the inclusion of particular articles or keywords through discussion. We also controlled for quality focusing on peer- reviewed articles (Esposito and Evangelista, 2014).

4. The framework of Sanders et al. (2007) is not the only framework that can be used. There are many other frameworks in the literature. However, our choice was based on the fact that it reflects the recent views of scholars who classify outsourcing decisions at strategic and tactical levels (Holcomb and Hitt, 2007; Kedia and Lahiri, 2007; Quelin and Duhamel, 2003; Sanders et al., 2007) and that it is the outcome of research conducted with 19 senior executives who are experienced in outsourcing, as well as a thorough synthesis of available research.

Notwithstanding the aforementioned limitations, we have identified some future research directions on outsourcing PMMs based on the literature review and our own experience in working in the area for more than 20 years. We believe that encouragement for further testing of our knowledge in this context has the potential to build robust theories (Corley and Gioia, 2011).

The following are some of the future research directions on PMMs in outsourcing:

1. Based on the classification of outsourcing decisions provided in this paper, researchers could develop a business model for the management of outsourcing at both strategic and tactical levels of engagement. The model could include both input and output such as business infrastructure and organizational performance.

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166 163

Suitable empirical validation could be conducted by collecting data from both outsourcer and outsourcee companies.

2. Our review and analysis suggests that intangible/non-financial measures are equally important as financial/tangible measures. More research needs to be carried out on intangibles and non- financial PMMs and their relationship with tangibles (financial and non-financial). We believe that the suggested classification is a first step to this end.

3. We classify the literature on outsourcing decisions and PMMs using the framework by Sanders et al., (2007), which we extend for pre-, during-, and post-outsourcing decisions. This classifi- cation could be developed and validated further for a network of firms in a virtual enterprise environment wherein sourcing and supplier development plays a major role in organizational performance. The process would need to be designed in order to include: (i) the identification of appropriate functional areas such as marketing, production, research and development, human resources, accounting and finance; (ii) the choice and adaptation of PMMs for this context; and (iii) the application of PMMs to these contexts and the inclusion of a feedback mechanism to inform the future application of PMMs. Inspired by Wisner and Fawcett (1991), we suggest the following possible validation process: (i) develop an understanding of the functional areas in achieving organizational objectives; (ii) communicate possible relevant measures to top management and relevant stakeholders and establish more specific measures; (iii) assure consistency of the PMMs with the strategic objectives of the firm; (iv) apply the PMMs to the selected function(s), and periodically re-evaluate the appropriateness of the PMMs in view of the competitive environment.

4. Suitable mathematical and simulation models (based on tools/ techniques provided in Table 3) could be developed for model- ling and analysis of outsourcing decisions, along with suitable criteria for optimizing outsourcing decisions. Such models can enable scholars and practitioners to build priority scales of variables (financial, non-financial, tangibles and intangibles) across strategic and tactical engagement levels from the per- spective of outsourced and outsourcers. They could also enable the study of the degree of fit between the levels to discover their particular combination for the formulation and imple- mentation of successful outsourcing strategies.

5. Resilience and sustainability of outsourcing demand decisions could also offer scope for PMMs to be used in defining resilience and sustainability. To this end, analytical and empiri- cal studies need to be conducted.

6. There is a lack of research on suitable organizational structures for outsourcing business processes. This requires: (i) a careful assessment of needs in terms of organizational structure, beha- viour and culture to determine an organizational structure with suitable authority and responsibility for outsourcing, and (ii) a definition of the outsourcing business model in terms of input and output through system parameters and PMMs for optimal decisions.

7. The proposed taxonomy could be further developed through interviewing practitioners to understand how different the metrics they use are from the ones revealed in this literature review. The classification we present could, therefore, be further enhanced and inform both academia and practice.

7. Concluding remarks

In this paper, an attempt has been made to review the literature on outsourcing decisions with the objective of providing a classification of PMMs at the pre-, during- and post-outsourcing

stages of strategic and tactical engagement decisions. The sug- gested classifications could be used to inform managers about PMMs in strategic and tactical engagement outsourcing decisions. Managers need to attend to both the diverse PMMs related to outsourcing decisions and the way they could deploy PMMs to their own decisions, considering their adaptation to their organi- zational context and stakeholder needs and wants. As mentioned earlier, the importance of more accurate PMMs in outsourcing and their impact on organizational performance and competitiveness through effective management is evident from both an academic and practitioner perspective. Outsourcing is becoming critical in assisting companies to effectively manage their operations in a physically distributed enterprise and virtual environment. But a careful evaluation of the outsourcing decisions by managers is necessary in order for companies to achieve their objectives.

Acknowledgments

The authors would like to express their sincere thanks and gratitude to three anonymous reviewers for their extremely constructive and helpful comments, which helped to improve the presentation of the manuscript considerably. Thanks to Pro- fessor Peter Kelle, Editor of IJPE for the opportunity to revise and resubmit the paper for publication.

References

Abdel-Malek, L., Kullpattaranirun, T., Nanthavanij, S., 2005. A Framework for comparing outsourcing strategies in multi-layered supply chains. Int. J. Prod. Econ. 97, 318–328.

Aksin, O.Z., Masini, A., 2008. Effective strategies for internal outsourcing and offshoring of business services: an empirical investigation. J. Oper. Manag. 26, 239–256.

Alvarez, L.H.R., Stenbacka, R., 2007. Partial outsourcing: a real options perspective. Int. J. Ind. Organ. 25, 91–102.

Anthony, R., 1965. Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business Administration, Cambridge, USA.

Araz, C., Ozfirat, P.M., Ozkaranhan, I., 2007. An integrated multi-criteria decision- making methodology for outsourcing management. Comput. Oper. Res. 34, 3738–3756.

Araz, C., Ozkarahan, I., 2007. Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. Int. J. Prod. Econ. 106, 585–606.

Aron, R., Bandyopadhyay, S., Jayanty, S., Pathak, P., 2008. Monitoring process quality in off-shore outsourcing: a model and findings from multi-country survey. J. Oper. Manag. 26 (2), 303–321.

Arya, A., Mittendorf, B., Sappoington, D.E.M., 2008. Outsourcing, vertical integra- tion, and vs. quantity competition. Int. J. Ind. Organ. 26, 1–16.

Bapna, R., Barua, A., Mani, D., Mehra, A., 2010. Cooperation, coordination, and governance in multisourcing: an agenda for analytical and empirical research. Inf. Syst. Res. 21 (4), 785–795.

Bahli, B., Rivard, S., 2005. Validating measures of information technology out- sourcing risk factors. Omega 3, 175–187.

Bandyopadhyay, S., Pathak, P., 2007. Knowledge sharing and cooperation in outsourcing projects – a game theoretic analysis. Decis. Support Syst. 43, 349–358.

Barney, J.B., 1991. Firm resources and sustained competitive advantage. J. Manag. 17 (1), 99–120.

Barthelemy, J., 2003. The hard and soft sides of IT outsourcing management. Eur. Manag. J. 21 (5), 539–548.

Barthélemy, J., Quelin, B., 2006. Complexity of outsourcing contracts and ex post transaction costs: an empirical investigation. J. Manag. Stud. 43 (8), 1776–1797.

Bhali, B., Rivard, S., 2005. Validating measures of information technology out- sourcing risk factors. OMEGA 33 (2), 175–187.

Bhattacharya, S., Behara, R.S., Gundersen, D.E., 2003. Business risk perspectives on information systems outsourcing. Int. J. Account. Inf. Syst. 4, 75–93.

Bengtsson, L., Berggren, C., 2008. The Integrator's new advantage – the assessment of outsourcing and production competence in a global telecom firm. Eur. School Manag. 26, 314–324.

Beske, P., Land, A., Seuring, S., 2014. Sustainable supply chain management practices and dynamic capabilities in the food industry: a critical analysis of the literature. Int. J. Prod. Econ. 152, 131–143.

Buehler, S., Haucap, J., 2006. Strategic outsourcing revisited. J. Econ. Behav. Organ. 61, 325–338.

Bunyaratavej, K., Hahn, E., Doh, J., 2007. International offshoring of services: a parity study. J. Int. Manag. 13 (1), 7–21.

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166164

Bustinza-Sanchez, O.F, Arias-Aranda, D., Gutuerrez-Gutierezz, L., 2010. Outsourcing, competitive capabilities and performance: an empirical study in service firms. Int. J. Prod. Econ. 126 (2), 276–288.

Cai, J., Liu, X., Xiao, Z., Liu, J., 2009. Improving supply chain performance manage- ment: a systematic approach to analyzing iterative KPI accomplishment. Decis. Support Syst. 46, 512–521.

Chen, L., Olhanger, J., Tang, O., 2014. Manufacturing facility location and sustain- ability: a literature review and research agenda. Int. J. Prod. Econ. 149, 154–163.

Chen, F.Y., Hum, S.H., Sun, J., 2001. Analysis of third-party warehousing contracts with commitments. Eur. J. Oper. Res. 131, 603–610.

Coase, R.H., 1937. The nature of the firm. Economica 4, 386–405. Conklin, D.W., 2005. Risks and rewards in HR business process outsourcing. Long

Range Plann. 38, 579–598. Corley, K., Gioia, D., 2011. Building theory about theory building: what constitutes a

theoretical contribution. Acad. Manag. Rev. 36 (1), 12–32. Cruijssen, F., Borm, P., Fleuren, H., Hamers, H., 2010. Supplier-initiated outsourcing: a

methodology to exploit synergy in transportation. Eur. J. Oper. Res. 207, 763–774. Currie, W.L., Michell, V., Abanishe, O., 2008. Knowledge process outsourcing in

financial services: the vendor perspective. Eur. J. Manag. 26, 94–104. Denk, N., Kaufmann, L., Carter, C., 2012. Increasing the rigor of grounded theory

research – a review of the SCM literature. Int. J. Phys. Distrib. Logist. Manag. 42 (8/9), 742–763.

Dibbern, J., Goles, T., Hirschheim, R., Jayatilaka, B., 2004. Information systems outsourcing: a survey and analysis of the literature. DATA BASE Adv. Inf. Syst. 35 (4), 6–102.

Doerr, K., Lewis, I., Eaton, D.R., 2005. Measurement issues in performance-based logistics. J. Public Procure. 5 (2), 164–186.

Doh, J., 2005. Offshore outsourcing: implications for international business and strategic management theory and practice. J. Manag. Stud. 42 (3), 695–704.

Dube, P., Liu, Z., Wynter, L., Xia, C., 2007. Competitive equilibrium in e-commerce: pricing and outsourcing. Comput. Oper. Res. 34, 3541–3559.

Ekanayaka, Y., Currie, W.L., Seltsikas, P., 2003. Evaluating application service providers. Benchmarking: Int. J. 10 (4), 343–354.

Eksoz, C., Mansouri, A., Bourlakis, M., 2014. Collaborative forecasting in the food supply chain: a conceptual framework. Int. J. Prod. Econ. 158, 120–135.

Ellram, L.M., Tate, W.L., Billington, C., 2007. Services supply chain management: the next frontier for improved organizational performance. Cali. Manag. Rev. 49 (4), 44–66.

Ellram, L.M., Tate, W.L., Billington, C., 2008. Offshore outsourcing of professional services: a transaction cost economics perspective. J. Oper. Manag. 26 (2), 148–163.

Ellram, L.M., Stanley, L.L., 2008. Integrating strategic cost management with a 3DCE environment: strategies, practices and benefits. J. Purch. Supply Manag. 14, 180–191.

Ellram, L., Billington, C., 2001. Purchasing leverage considerations in the out- sourcing decision. Eur. J. Purch. Supply Manag. 7 (1), 15–27.

Elmuti, D, 2003. The perceived impact of outsourcing on organizational perfor- mance. Mid-Am. J. Bus. 18 (2), 33–41.

Espino-Rodriguez, T., Padron-Robaina, V., 2006. A review of outsourcing from the resource-based view of the firm. Int. J. Manag. Rev. 8 (1), 49–70.

Esposito, E., Evangelista, P., 2014. Investigating virtual enterprise models: literature review and empirical findings. Int. J. Prod. Econ. 148, 145–167.

Falk, M., Wolfmayr, Y., 2008. Services and materials outsourcing to low-wage countries and employment: empirical evidence from EU countries. Struct. Change Econ. Dyn. 19, 38–52.

Feng, B., Fan, Z.-P., Li, Y., 2011. “A decision method for supplier selection in multi- service outsourcing”. Int. J. Prod. Econ. 132, 240–250.

Gonzalez, R., Gasco, J., Liopis, J., 2006. Information systems outsourcing. Inf. Manag. 43, 821–834.

Goo, J., Kishore, R., Nam, K., Rao, H.R., Song, 2007. An investigation of factors that influence the duration of IT outsourcing relationships. Decis. Support Syst. 42, 2107–2125.

Gooroochurn, N., Hanley, A., 2007. A take of tow literatures: transaction costs and property rights in innovation outsourcing. Res. Policy 36, 1483–1495.

Gottfredson, M., Puryear, R., Philips, S., 2005. Strategic outsourcing: from periphery to the core. Harv. Bus. Rev. 83 (2), 132–139.

Graf, M., Mudambi, S.M., 2005. The outsourcing of IT-enabled business processes: a conceptual model of the location decision. J. Int. Manag. 11, 253–268.

Grover, V., Malhotra, V.K., 2003. A transaction cost framework in operations and supply chain management research: theory and measurement. J. Oper. Manag. 21, 457–473.

Gunasekaran, A., Ngai, E.W.T., 2004. “Information systems in supply chain integra- tion and management”. Eur. J. Oper. Res. 159 (2), 269–295.

Gunasekaran, A., Kobu, B., 2007. Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications. Int. J. Prod. Res. 45 (12), 2819–2840.

Hahn, E., Bunyaratavej, K., Doh, J., 2011. Impacts of risk and service type on nearshore and offshore investment location decisions. Manag. Int. Rev. 51 (3), 357–380.

Hamel, G., Prahalad, C.K., 1990. The core competence of the corporation. Harv. Bus. Rev. 68 (3), 79–91.

Han, H.-S., Lee, J.-N., Seo, Y.-W., 2008. Analyzing the impact of a firm's capability on outsourcing success: a process perspective. Inf. Manag. 45, 31–42.

Hätönen, J., Eriksson, T., 2009. 30þ years of research and practice of outsourcing – exploring the past and anticipating the future. J. Int. Manag. 15, 142–155.

Holcomb, T.R., Hitt, M.A., 2007. Toward a model of strategic outsourcing. J. Oper. Manag. 25 (2), 464–481.

Hoecht, A., Trott, P., 2006. The innovation risks of strategic outsourcing. Technova- tion 26, 672–681.

Hsu, C.-C., Wu, C.-H., 2006. The evaluation of the outsourcing of information systems: a survey of large enterprises. Int. J. Manag. 23 (4), 817–830.

Huang, S.H., Keskar, H., 2007. Comprehensive and configurable metrics for supplier selection. Int. J. Prod. Econ. 105, 510–523.

Javalgi, R., Dixit, A., Scherer, R.F., 2009. Outsourcing to emerging markets: theoretical perspectives and policy implications. J. Int. Manag. 15, 156–168.

Jiang, B., Belohlav, J.A., Young, S.T., 2007. Outsourcing impact on manufacturing firms' value: evidence from Japan. J. Oper. Manag. 25, 885–900.

Jiang, B., Frazier, G.V., Prater, E.L., 2006. Outsourcing effects on firms' operational performance: an empirical study. Int. J. Oper. Prod. Manag. 26 (12), 1280–1300.

Jiang, B., Qureshi, A., 2006. “Research on outsourcing results” current literature and future opportunities. Manag. Dec. 44 (1), 44–55.

Johnson, G., Whittington, R., Scholes, K., Angwin, D., 2014. Exploring Strategy: Text and Cases, 10th ed.. Pearson Education, Harlow.

Kakabadse, A., Kakabadse, N., 2005. Outsourcing: current and future trends. Thunderbird Int. Bus. Rev. 47 (2), 183–204.

Kannan, V.R., Tan, K.C., 2003. Attitudes of US and European Managers to supplier selection and assessment and implications for business performance. Bench- marking: Int. J. 10 (5), 472–489.

Kedia, B.L., Lahiri, S., 2007. International outsourcing of services: expanding the research agenda. J. Int. Manag. 13, 22–37.

Kotabe, M., Zhao, H., 2002. A taxonomy of sourcing strategic types for MNCs operating in China. Asia-Pac. J. Manag. 19, 11–27.

Kotabe, Masaaki, Mol, Michael J., Murray, Janet Y., 2008. Outsourcing, performance, and the role of e-commerce: a dynamic perspective. Ind. Market. Manag. 37 (1), 37–45.

Kremic, T., Tukel, O.I., Rom, W.O., 2006. Outsourcing decision support: a survey of benefits, risks, and decision factors. Supply Chain Manag.: Int. J. 11 (6), 467–482.

Kroes, J.R., Ghosh, S., 2010. Outsourcing congruence with competitive priorities: impact on supply chain and firm performance. J. Oper. Manag. 28, 124–143.

Kshetri, N., 2007. Institutional factors affecting offshore business process and information technology outsourcing. J. Int. Manag. 13, 38–56.

Isklar, G., Alptekin, E., Buyukozkan, G., 2007. Application of a hybrid decision support model in logistics outsourcing. Comput. Oper. Res. 34, 3701–3714.

Lacity, M., Hirschheim, R., 1993. Information Systems Outsourcing; Myths, Meta- phors, and Realities. John Wiley & Sons, Inc., New York, NY.

Lacity, M., Willcocks, L., Feeny, D. 1996. The value of selective IT sourcing. Sloan Manag. Rev. vol. 37 (3) pp. 13–25.

Lacity, M., Willcocks, L., 1998. An empirical investigation of information technology sourcing practices: lessons from experience. MIS Q. 22 (3), 363–408.

Lacity, M., Khan, S., Willcocks, L., 2009. A review of the IT outsourcing literature: insights for practice 18, 130–146.

Lahiri, S., Kedia, B.L., 2009. The effects of internal resources and partnership quality on firm performance: an examination of Indian BPO providers. J. Int. Manag. 15, 209–224.

Lamminmaki, D., 2008. Accounting and the management of outsourcing: an empirical study in the hotel industry. Manag. Account. Res. 19163–181

Lamminmaki, D., 2011. An examination of factors motivating hotel outsourcing. Int. J. Hosp. Manag. 30, 963–973.

Lee, A., Baskerville, R., 2003. Generalizing generalizability in information systems research. Inf. Syst. Res. 14 (3), 221–243.

Lee, K., Choi, B.-C., 2011. Two-stage production scheduling model with an out- sourcing option. Eur. J. Oper. Res. 213, 489–497.

Li, S., Wang, L., 2010. Outsourcing and capacity planning in an uncertain global environment. Eur. J. Oper. Res. 207, 131–141.

Li, S., Murat, A., Huang, W., 2009. Selection of contract suppliers under price and demand uncertainty in a dynamic market. Eur. J. Oper. Res. 198 (3), 830–847.

Li, Y., Liu, Y., Li, M., Wu, H., 2008. Transformational offshore outsourcing: empirical evidence from alliances in China. J. Oper. Manag. 26 (2), 257–274.

Lim, W.S., Tan, S.J., 2010. Outsourcing suppliers as downstream competitors: biting the hand that feeds. Eur. J. Oper. Res. 203, 360–369.

Lindner, J.C., 2005. Outsourcing integration. Harv. Bus. Rev. 83 (6), 12–43. Liou, J.J.H., Wang, H.S., Hsu, C.C., Yin, S.L., 2011. A hybrid model for selection of an

outsourcing service provider. Appl. Math. Model. 35, 5121–5123. Liston, P., Byrne, J., Byrne, P.J., Heavey, C., 2007. Contract costing in outsourcing

enterprises; exploring the benefits of discrete-event simulation. Int. J. Prod. Econ. 110, 97–114.

Manning, S., Lewin, A., Schuerch, M., 2011. The stability of offshore outsourcing relationships. Manag. Int. Rev. 51 (3), 381–406.

Mantel, S., Tatikonda, M., Liao, Y., 2006. A behavioral study of supply manager decision-making: factors influencing make versus buy evaluation. J. Oper. Manag. 24, 822–838.

Mao, J.-Y., Lee, J.-N., Deng, C.-P., 2008. Vendors' perspectives on trust and control in offshore information systems outsourcing. Inf. Manag. 45, 482–492.

Marshall, D., McIvor, R., Lamming, R., 2007. Influences and outcomes of out- sourcing: insights from the telecommunications industry. J. Purch. Supply Chain Manag. 13 (4), 245–260.

McDermott, C., Handfield, R., 2000. Concurrent development and strategic out- sourcing: do the rules change in breakthrough innovation. J. High Technol. Manag. Res. 11 (1), 35–57.

McIvor, R., 2009. How the transaction cost and resource-based theories of the firm inform outsourcing evaluation. J. Oper. Manag. 27, 45–63.

McIvor, R., 2008. What is the right outsourcing strategy for your process. Eur. Manag. J. 26, 24–34.

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166 165

Metters, R., 2008. A typology of offshoring and outsourcing in electronically transmitted services. J. Oper. Manag. 26, 198–211.

Momme, J., 2002. Framework for outsourcing manufacturing: strategic and opera- tional implications. Comput. Ind. 49, 59–75.

Momme, J., Hvolby, H.-H., 2002. An outsourcing framework: action research in the heavy industry sector. Eur. J. Purch. Supply Manag. 8, 185–196.

Nam, K., Chaudhury, A., Rao, H.R., 1995. A mixed integer model of bidding strategies for outsourcing. Eur. J. Oper. Res. 87, 257–273.

Neely, A., Platts, K., Gregory, M., Bourne, M., Kennerley, M., 2000. Performance measurement system design: developing and testing a process-based approach. Int. J. Prod. Oper. Manag. 20 (10), 1119–1145.

Ngai, E.W.T., Moon, K.K.L., Riggins, F.J., Yi, C.Y., 2008. RFID research: an academic literature review (1995–2005) and future research directions. Int. J. Prod. Econ. 112, 510–520.

Ni, D., Li, K.W., Tang, X., 2009. Production costs, scope economies, and multi-client outsourcing under quantity competition. Int. J. Prod. Econ. 121, 130–140.

Oliva, R., Watson, N., 2011. Cross-functional alignment in supply chain planning: a case study of sales and operations planning. J. Oper. Manag. 29 (5), 434–448.

Olson, D.L., 2007. Evaluation of ERP outsourcing. Comput. Oper. Res. 34, 3715–3724. Osei-Bryson, K.-M., Ngwenyama, O.K., 2006. Managing risks in information systems

outsourcing: an approach to analyzing outsourcing risks and structuring incentive contracts. Eur. J. Oper. Res. 174, 245–264.

O'Toole, T., Donaldson, B., 2002. Relationship performance dimensions of buyer– supplier exchanges. Eur. J. Purch. Supply Manag. 8 (4), 197–207.

Otto, A., Kotzab, H., 2003. Does supply chain management really pay? Six perspectives to measure the performance of managing a supply chain. Eur. J. Oper. Res. 144, 306–320.

Paisittanand, S., Olson, D.L., 2006. A simulation of IT outsourcing in the credit card business. Eur. J. Oper. Res. 175, 1248–1261.

Porter, M.E., 1996. What is strategy? Harv. Bus. Rev. 74 (6), 61–79. Quelin, B., Duhamel, S., 2003. Bringing together strategic ousourcing and corporate

strategy. Outsourcing motives and risks. Eur. Manag. J. 21 (5), 647–661. Raiborn, C.A., Butler, J.B., Massoud, M.F., 2009. Outsourcing support functions: identifying

and managing the good, the bad, and the ugly. Bus. Horiz. 52, 347–356. Rowley, J., Slack, F., 2004. Conducting a literature review. Manag. Res. News 27 (6),

31–39. Sanders, N.R., Locke, A., Moore, C., Autry, C.W., 2007. A multidimensional frame-

work for understanding outsourcing arrangements. J. Supply Chain Manag. 43 (4), 3–15.

Schmeisser, B., 2013. A systematic review of literature on offshoring of value chain activities. J. Int. Manag. 19 (4), 390–406.

Sia, S.K., Koh, C., Tan, C.X., 2008. Strategic Maneuvers for outsourcing flexibility: an empirical assessment. Decis. Sci. 39 (3), 407–443.

Sidorova, A., Evangelopoulos, N., Valacich, J.S., Ramakrishnan, T., 2008. Uncovering the intellectual core of the information systems discipline. MIS Q. 32 (3), 467–482.

Sinkovics, R.R., Roath, A.S., 2004. Strategic orientation, capabilities, and perfor- mance in manufacturer – 3PL relationships. J. Bus. Logist. 25 (2), 43–64.

Tarakci, H., Tang, K., Teyarachakul, S., 2009. Learning effects on maintenance outsourcing. Eur. J. Oper. Res. 192 (1), 138–150.

Tate, W.L., van der Valk, W., 2008. Managing the performance of outsourced customer contact centers. J. Purch. Supply Manag. 14, 160–169.

Tjader, Y.C., Shang, J.S., Vargas, L.G., 2010. Offshore outsourcing decision making: a policy-maker's perspective. Eur. J. Oper. Res. 207, 434–444.

Tjader, Y., May, J.H., Shang, J., Vargas, L.G., Gao, N., 2014. Firm-level outsourcing decision making: a balanced scorecard-based analytic network process model. Int. J. Prod. Econ. 147, 614–623.

Tomiura, E., 2007. Foreign outsourcing exporting, and FDI: a productivity compar- ison at the firm level. J. Int. Econ. 72, 113–127.

Tolio, T., Urgo, M., 2007. A rolling horizon approach to plan outsourcing in manufacturing-to-order environments affected by uncertainty. Ann. CIRP 56 (1), 487–490.

Vining, A.R., Globerman, S., 1999. A conceptual framework for understanding the outsourcing decision. Eur. Manag. J. 17 (5), 644–654.

Wadhwa, V., Ravindran, A., 2007. Vendor selection in outsourcing. Comput. Oper. Res. 34, 3725–3737.

Walden, E.A., Hoffman, J.J., 2007. Organizational form, incentives and the manage- ment of information technology: opening the black box of outsourcing. Comput. Oper. Res. 34, 3575–3591.

Wang, K.-J., Chen, M.-J., 2009. Cooperative capacity planning and resource alloca- tion by mutual outsourcing using Ant algorithm in a decentralized supply chain. Expert Syst. Appl. 36, 2831–2842.

Weidenbaum, M., 2005. “Outsourcing: Pros and Cons”. Bus. Horiz. 48, 311–315. Weiner, M., Vogel, B., Amberg, M., 2010. Information systems offshoring: a

literature review and analysis. Commun. Assoc. Inf. Syst. 27 (25), 455–492. Westphal, P., Sohal, A.S., 2013. Taxonomy of outsourcing decision models. Prod.

Plan. Cont. 24 (4-5), 347–358. Williamson, O.E., 1975. Markets and Hierarchies: analysis and antitrust implica-

tions. Free Press – McMillan, New York. Williamson, O.E., 2008. Outsourcing: transaction cost economics and supply chain

management. J. Supply Chain Manag. 44 (2), 5–16. Wisner, J.D., Fawcett, S.E., 1991. Link firm strategy to operating decisions through

performance measurement. Prod. Invent. Manag. J. 32 (3), 5–11 (third quarter). Xiao, T., Xia, Y., Zhang, G.P., 2007. Strategic outsourcing decisions for manufacturers

that produce partially substitutable products in a quantity-setting duopoly situation. Decis. Sci. 38 (1), 81–106.

Yang, D.-H., Kim, S., Nam, C., Min, J.-W., 2007. Developing a decision model for business process outsourcing. Comput. Oper. Res. 34, 3769–3778.

Zhang, B., Du, S., 2010. “Multi-product newsboy problem with limited capacity and outsourcing”. Eur. J. Oper. Res. 202, 107–113.

A. Gunasekaran et al. / Int. J. Production Economics 161 (2015) 153–166166