Power Distribution
In Information Systems
Outsourcing Relationships
Final Version
22 February 2009
Author: Christian Moens Student Number: 1462121
Supervisor: Professor H. Van Ees Rijksuniversiteit Groningen
Table of Contents 1. INTRODUCTION ... 3 2. THEORETICAL FRAMEWORK ... 6 2.1 TRANSACTIONS ... 6 Discrete Exchange ... 6 Non-discrete exchange ... 7 Cost of transactions ... 7 2.2 RELATIONAL EXCHANGE ... 9
The Role of Relational Norms in Relational Exchange ... 10
The Role of Power in Relational Exchange ... 11
2.3 OUTSOURCING RELATIONSHIPS ... 14
The Role of Power in Outsourcing Relationships ... 14
The Role of Relational Norms in Outsourcing Relationships... 17
2.4 INFORMATION SYSTEMS OUTSOURCING ... 20
2.5 RESEARCH GAP ... 20 3. RESEARCH METHODOLOGY... 21 3.1 SAMPLING DESIGN ... 21 3.2 DESCRIPTION OF VARIABLES ... 21 OUTSOURCING SUCCESS ... 21 POWER DISTRIBUTION ... 21
Kraljic Portfolio Model ... 22
RELATIONAL NORMS ... 28 SERVICE QUALITY ... 29 CULTURAL COMPATIBILITY ... 29 4. RESULTS ... 30 4.1 GENERAL APPROACH ... 30 4.2 MODEL 1 ... 30
4.2.1 Test for Equality of Means for Outsourcing Success ... 30
4.2.2 Model 1 structure ... 31
4.2.3 Results of OLS Regression ... 32
4.3 MODEL 2 ... 33
4.3.1 Exploratory Factor Analysis ... 34
4.3.2 Test for Equality of Means of Relational Norms ... 35
4.3.3 Model 2 Structure ... 36
4.3.4 Results of OLS Regression Model 2 ... 36
5. CONCLUSIONS ... 38
1.
Introduction
Information Systems (IS) Outsourcing is the practice of turning over part or all of an
organization’s IS functions to external service provider(s) (Grover, Cheon and Teng, 1996). The IS outsourcing phenomenon is considered to be about 15 years old, dating back to the first major contract announcement between Eastman Kodak and IBM in 1989 (Dibbern et al.,
2004).The strong growth of the market for IS Outsourcing reveals managers nowadays consider outsourcing to be major option (Henderson, 1990). However, managers’ expectations of the outsourcing relationship are often not realised and in many cases contracts are not renewed or even prematurely terminated, in fact the reported success rate is as low as 56% (Lacity and Wilcocks, 1996).
Despite the vast literature on outsourcing, there has been no integrated view to provide an in-depth analysis of the outsourcing relationship (Lee and Kim, 1999). Most outsourcing research is focused on the decision to outsource, but this thesis is concerned with the post contract
signing period. Moreover, although most outsourcing related research is based on economic
theories, this thesis broadens the theoretical perspective by incorporating social exchange theory. The social aspect is relevant because outsourcing can be considered to be a type of transaction which involves ‘relational exchange’ processes. Moreover, an exclusively economic view falls far short of a comprehensive understanding of an outsourcing relationship because it views the actor as not interacting with another actor but rather directly with the market and thus does not include the perspective of exchanges between individual actors (Kern and Wilcocks, 2000).
(Lee and Hsieh, 2003). Instead, this thesis presents an analysis of the effect of a series of objective power attributes concerning both parties in 1300 individual outsourcing relationships. Another relevant element of relational exchange is the set of values which comprise relational
norms in an outsourcing relationship. These norms serve to protect the relationship specific
investments of both parties (Heide and John, 1992). Moreover, they reduce the potential for opportunism (Williamson, 1985). The relational norms evaluated in this thesis are flexibility, risk
sharing, innovation and partnership quality. The latter element of relational norms is considered
to be particularly relevant in outsourcing relationships (Lee and Kim, 1999).
In summary, this thesis is an attempt to investigate the role of power distribution as a
determinant of success in information systems (IS) outsourcing relationships, and as a variable affecting the quality of relational norms.
The following research questions comprise the basis of this study:
- To what extent does the relative power distribution between buyers and service providers in IS outsourcing relationships influence outsourcing success?
- Can the quality of relational norms be explained by the relative power distribution? - Can the formation of partnerships between buyers and service providers contribute to
outsourcing success?
To address these questions, Transaction Cost theory and Social Exchange theory are
discussed, along with their (partly conflicting) assumptions, to determine what the direction of the relationships presented in the research questions should be from a theoretical perspective. The hypotheses derived from the theoretical perspective will be tested using a database with outsourcing client satisfaction in the Netherlands, Belgium and Nordics, in combination with firm level financial data to establish the power distribution using Kraljic Portfolio Model (Kraljic, 1983), for each of the 1300 IS Outsourcing relationships under study. The purpose of this model is to assess the complexity of market supply / demand, together with the strategic / financial impact of the relationship on the buyer / service provider. This assessment in turn can be used to determine whether the relative power distribution can be classified as either ‘Independence’, ‘Buyer Dominance’, ‘Service Provider Dominance’ or ‘Interdependence’.
The outcomes of this thesis indicate a) Outsourcing Success is highest when the relative power distribution is characterized by Interdependence (tested using ANOVA) and b) relative to
linear regression with the use of subsamples). Furthermore, the state of Buyer Dominance positively affects Relational Norms, while this relationship is significantly negative in case of
Service Provider Dominance. One of these norms – partnership quality – has a general positive
effect on Outsourcing Success.
This thesis contributes to the literature on outsourcing relationships, because it is based on a theoretical framework which takes into account both economic (transaction costs) and social (relational norms) considerations. Moreover, the findings are highly representative, because they are based on a relatively large sample of outsourcing contracts.
Figure 1: Structure of the Theoretical Framework
The structure of this thesis is as follows. The first section consists of the theoretical framework, which is shaped along the structure of the ‘inverted pyramid’ presented in figure 1 (from
‘general’ to ‘specific’). The top layer of this pyramid is titled ‘Transactions’, representing a
general discussion of transactions, including transaction cost economics. Next, a specific type of transactions (Relational Exchange) and its distinctive characteristics is discussed. The third layer is ‘Outsourcing’, which is considered to be a unique type of relational exchange. Here, the
Power Matrix is presented, which forms the basis for the first set of hypotheses, related to the
effect of the distribution of power. Following is a presentation of the characteristics of
2.
Theoretical Framework
2.1 Transactions
In order to be able to investigate the research questions as presented in the Introduction, the outsourcing relationship should first be placed in the broader perspective of transactions. This should provide a framework in which a particular type of transactions (outsourcing) can be investigated. Transactions are exchanges of goods, services or currency between people or organizations. In the modern society, goods and services are usually paid for by currency. In addition to the volume of these transactions, the three critical dimensions for characterizing transactions are (1) uncertainty, (2) the frequency with which transactions recur, and (3) the degree to which durable transaction-specific investments are incurred (Williamson, 1979). These dimensions are further described below.
Uncertainty refers to the predictability of the environment in which the transaction takes place. Obviously, in the real world, there is always some degree of uncertainty regarding the future. According to the theoretical argument of Williamson (1979), the frequency with which
transactions recur can be considered to be either: one-time, occasional, or recurrent. Following the same logic, the degree to which durable transaction-specific investments (which are only valuable in the context of a particular buyer-seller relationship) are incurred can be considered to be either high or low.
The three critical dimensions of transactions together facilitate the distinction of two types of transactions: discrete and non-discrete exchanges.
Discrete Exchange
Discreteness is the separating of a transaction from all else between the participants at the
same time and before and after. Its [pure form], never achieved in life, occurs when there is nothing else between the parties, never has been, and never will be (MacNeil, 1980).
focus on) is limited to the extent that the power of parties is based upon the sanctions they can evoke in case either the buyer fails to pay or the seller fails to deliver (MacNeil, 1978, 1980).
Non-discrete exchange
Non-discrete exchange has intermediate or high degrees of uncertainty, which is why they differ from discrete transactions with respect to contract incompleteness. Long-term contracts
executed under conditions of uncertainty are always incomplete to some extent. This is because not all future contingencies for which adaptations are required can be anticipated at the outset. Moreover, the appropriate adaptations of the contract will not be evident for many contingencies until the circumstances (such as technological improvements) are in place (Williamson, 1985). According to Macneil (1978), two common characteristics of long-term contracts are the existence of gaps in their planning (i.e. contractual incompleteness) and “the presence of a range of processes and techniques used by both parties to create flexibility in lieu of either leaving gaps or trying to plan rigidly”. In the context of this thesis, these processes and
techniques are labeled relational norms, which will be discussed in the corresponding section.
Cost of transactions
When people or organisations exchange goods or services in return for currency, they incur costs related to the transaction itself. According to transaction cost economics, these costs are of critical importance for the ‘make or buy’ decision faced by organizations. Four conditions give rise to the costs of transactions: uncertainty and complexity of future environmental states, bounded rationality, small numbers bargaining, and opportunism (Provan and Skinner, 1989). Uncertainty and the bounded rationality of decision makers combine to create situations in which contracts based on transactions between two organizations cannot specify all possible contingencies. In these cases, complete contracting is often impossible, and incomplete
contracts give rise to subsequent renegotiations (Williamson, 1979). Any increase in uncertainty provides an incentive for opportunistic behavior when contract clauses need to be amended (Williamson, 1985). In general, most markets are characterized by relatively small numbers of possible transaction partners, some of which behave opportunistically. Other firms cannot easily avoid opportunistic organizations because of the small numbers condition (Provan and Skinner, 1989).
inhouse. The costs of buying include operational costs (e.g., search costs, inventory holding costs), as well as contractual costs (e.g., cost of writing and enforcing a contract). The costs of producing inhouse include coordination costs. Transaction cost theory is based on two
behavioural assumptions: bounded rationality and opportunism (Williamson, 1985). Bounded rationality refers to how the cognitive limitations of the human mind rule out a complete evaluation of the consequences of all possible decisions. The impact of bounded rationality depends in part on the level of uncertainty, but also on the knowledge and skills the buyer has in specifying requirements, selecting suppliers and managing the relationship. The second
assumption; opportunism (the critical assumption in the context of this thesis), implies people do not only act in self-interest, but that they also act with guile (cunning). In Williamson’s (1985) words, opportunism refers to “self-interest seeking with guile . . . [which] includes but is scarcely limited to more blatant forms, such as lying, stealing, and cheating . . . [Opportunism] involves subtle forms of deceit.’’ Opportunistic behavior is distinguishable from self-interested behavior in that whereas a party behaving in the latter manner makes their intentions and objectives clear to their partner, an opportunistic party strives to keep their intentions and objectives unclear to their partner (Joshi and Arnold, 1997).
Prior research has documented the detrimental impact of opportunism on both qualitative and quantitative outcomes (Joshi and Arnold, 1997). Opportunism has been shown to reduce system performance, and reduce satisfaction (Gassenheimer et al., 1996), trust and commitment (Morgan & Hunt, 1994).
However, as briefly discussed in the Introduction, relational norms can reduce the potential for opportunism (Williamson, 1985). This is because high relationship specific investments have to be made to develop these norms, which include trust and commitment. Opportunistic behaviour would damage the relational norms and thus the outcome of the relationship specific
2.2 Relational Exchange
This section is dedicated to the principals of Relational Exchange, which is the type of non-discrete transaction which involves relatively high uncertainty, high frequency of exchanges and high transaction-specific investments.
Relative to other types of transactions, Relational Exchange takes on the properties of "a mini-society with a vast array of relational norms beyond those centered on the exchange and its immediate processes" (Williamson, 1979). In addition to the actual exchange of a product or service for financial compensation, relational exchange participants may experience personal, non-economic satisfactions and engage in social exchange (Dwyer, Schurr, and Oh, 1987). In contrast to those exchanges in which the reference point for effecting adaptations remains the original agreement, the reference point under a truly relational approach is the "entire relation as it has developed through time” (Williamson, 1979).
Contracts outline roles to be played by each party involved. However, when uncertainty exists and the contract length considerable, there will be a degree of contract incompleteness. Thus, social (extralegal) mechanisms based on mutual awareness and understanding, become relevant (Clark et al., 1995). According to (Macneil, 1974), these relational norms lead to expectations that future behavior will continue along the lines of current behavior, in effect “projecting a pattern of exchanges into the future”, independent of the contract. This expected pattern of behavior and exchanges is what bounds and shapes the Relational Exchange. A strong relationship is the manifestation of the “underlying philosophy of the contract”. It includes both formal and informal governance mechanisms, and forms a basis upon which a range of future activities, behaviors, needs, and exchanges take place (Shepherd, 1999).
Social Exchange theorists argue economic approaches, such as Transaction Cost theory, neglect aspects of interorganizational relationships that go beyond the traditional ‘make or buy’ decision, and how to structure the contract. The social perspective is differentiated from the economic perspective by its underlying assumption that there are shared relational norms and also harmony of interests between the parties that influence their interaction, leading to
considerations of trust, equity, and cooperation (Goles and Chin, 2005). Social Exchange theory sees the relationship as a dynamic process through specific sequential interactions in which two participants carry out activities with one another and exchange valuable resources (Lee, 2001). This assumes that processes evolve over time as the actors mutually and sequentially
Social Exchange theory is built around the relational aspect and can therefore offer
supplementary insights regarding success in a particular type of outsourcing relationship. This theory is built upon the following assumptions: a) social behaviour is a series of exchanges, b) individuals attempt to maximize their rewards and minimize their costs, and c) when individuals receive rewards from others, they feel obliged to reciprocate (LaGaipa, 1977; Nye, 1979). The latter assumption is fundamental to Social Exchange theory (Dibbern, 2004). In order to discharge this obligation the second must deliver benefits to the first in return. Blau (1964) defines Social Exchange as: “voluntary actions of individuals that are motivated by the returns they are expected to bring and typically do in fact bring from others”. Social exchange can be viewed as an ongoing reciprocal process in which actions are contingent on rewarding reactions from others (Das and Teng, 2002).
The Role of Relational Norms in Relational Exchange
Social Exchange theory is based on the notion that parties to an exchange are in mutual agreement that the resulting outcomes of the exchange are greater than those that could be attained through other forms of exchange, or from exchange with a different partner (Goles and Chin, 2005). This motivates the exchange partners to consider the relationship important in and of itself, and to dedicate resources towards preserving and enhancing it (Anderson & Narus, 1984; Dwyer et al., 1987). Because of contract incompleteness, exchanges between parties to a relationship are shaped and administered by a set of relational norms, or expectations about behavior that are shared between exchange partners, and that are intended to strengthen the relationship as a whole (Heide & John, 1992). Thus, Relational Exchange is characterized by the presence of relational norms associated with the creation, preservation, and harmonization of the relationship between exchange partners (Macneil, 1980).
The Role of Power in Relational Exchange
According to Emerson (1972), power – “the level of cost one actor can induce over the other” - is one of the most important attributes in Relational Exchange. That is why the role of power is elaborated upon here. This section provides an overview of the most influential and relevant research on dependency and power. The ultimate goal is to develop a categorical framework of relative power distribution.
Power and dependence are two constructs which are derived from founding research on Social Exchange theory. Emerson (1962) argues A depends on B if he aspires to goals or gratifications whose achievement is facilitated by appropriate actions on B’s part. Therefore, each party has the power to deny or hinder the other’s gratification. This is how power resides in mutual dependency. Dependence is high when A’s motivational investment in goals mediated by B is high, when the availability of goals outside the A-B relation is low and the associated switching costs are high.
In studies of power between organizations (see below), dependencies have traditionally been used to determine the existence of a power relationship and the extent to which one
organization is likely to influence another. The basic idea is that highly dependent organizations will be subject to the influence attempts of those organizations that control critical contingencies (Provan and Gassenheimer, 1994).
French and Raven (1959) made an effort to identify the major types of power bases (sources). These include:
- Reward power, i.e. power based on the belief that the other party has the ability to mediate rewards for him, e.g. factory workers who get paid per unit they produce; - Coercive power, i.e. power based on the anticipation of possible punishment by the
other party, e.g. the ability of a factory boss to fire one of his workers;
- Legitimate power, i.e. power originating from internalized values which dictate that one party has a legitimate right to influence the other party, e.g. judges have the right to levy fines;
- Referent power, i.e. power based on the identification of one party with the other, where identification means a feeling of oneness or a desire for such an identity;
Hunt and Nevin (1974) tested the French-Raven framework of power sources in a franchisor-franchisee channel setting (the fast-food industry). They distinguish between coercive and noncoercive power sources (the latter includes reward, legitimate, referent and expert power). They found franchisors rely primarily on coercive sources to achieve power over their
franchisees. Moreover, they found franchisee satisfaction is improved if franchisors would rely more on noncoercive sources instead. Thus, the findings indicate that the consequences of exercising power depend on the sources of power exercised.
Gaski and Nevin (1985) contributed to research by testing the particular effects of exercised power, as opposed to power which remains unexercised. With regard to coercive power, harsh sanctions on channel members seem certain to cause dissatisfaction and conflict. Contrary, the
dormant presence of the potential to take such action could be regarded by buyers as
‘benevolent restraint’ (supported by their results). Interestingly, they also note it is possible that the greater the sources of power are, the less they need to be exercised (also supported). Based on their conclusions regarding noncoercive (reward) power, the authors conclude that the potential for reward might be virtually as satisfying to buyers as the realization of that potential1.
El-Ansary and Stern (1972) considered dependence (giving each party the power to deny or hinder the other’s gratification) to be a function of the importance of:
- The percentage of the channel member's business contracted with the other firm; - The size of the contribution that business makes to the firm's profits
- The commitment of a channel member to another member in terms of the contribution of the latter's marketing policies to its business;
- The difficulty in effort and cost faced by a channel member in attempting to replace the other as a source of supply or as a customer.
Heide and John (1992) applied measures of a) buyer concentration and b) the degree to which buyers produce the relevant service internally (versus externally), to approximate the power on the side of the buyer. Their results suggest dominant firms in terms of power are able to extract safeguards for protecting their transaction specific assets.
1
Recently, the concept of dependence has been elevated to the dyadic level—relative
dependence—with the recognition that a firm's power over another firm is relative to the other
firm's power (Buchanan 1992; Kumar, Scheer, and Steenkamp 1995). It is this relative power that determines the extent to which a firm will have influence (i.e. power) over, and be
influenced by, its partner (Anderson and Narus, 1990).
Cox (2001) used power attributes (among which those identified by El-Ansary and Stern, 1972) as a basis to distinguish four distinct relationship types in terms of relative power distribution, as presented in the ‘Power Matrix’ (see figure 1), along two dimensions: relative Buyer power (vertical axis) and relative Service provider power (horizontal axis).
Figure 2. The Power Matrix (Kumar, Scheer and Steenkamp, 1994; Cox, 2001)
2.3 Outsourcing Relationships
Outsourcing refers to the use of external agents to perform one or more organizational activities (e.g., purchasing of a good or service) (Dibbern, 2004). It is a special form of Relational
Exchange. Outsourcing contracts are often incomplete because the parties are rationally bounded and cannot foresee all eventualities. These eventualities comprise uncertainty regarding environmental volatility, technological discontinuity (technologies might become obsolete during the contract period) and the nature of outsourced activities, of which it might be hard to describe with exactitude the outputs it should produce (Aubert et al., 1998). Outsourcing often involves fairly long-term relationships during which time the perception of the relationship takes on increasing weight in influencing satisfaction with the outsourcing arrangement (Whitten and Leidner, 2006). The earlier described role of power and relational norms in Relational Exchange will be discussed in the narrower context of Outsourcing in this section. Furthermore, the hypotheses regarding power and relational norms will be presented subsequently.
The Role of Power in Outsourcing Relationships
As illustrated in figure 2, the distribution of power between two parties can be either symmetric (balanced) or asymmetric (unbalanced). Moreover, in relationships with symmetric power distributions, the degree of mutual dependence is either low (i.e. ‘Independence’) or high (i.e. ‘Interdependence’). In general, based on Williamson’s (1979) argument, it is assumed that the presence of relational norms can reduce the potential for opportunistic behaviour. According to Social Exchange theory, these relational norms are most developed when the power distribution is a) symmetrical and b) highly mutual dependent (i.e. in ‘Interdependence’ type relationships). This argument is set out below.
The management of a powerful party will behave opportunistically in relations with its partner (buyer / service provider) because it can readily exploit the weak party and thus gain further advantage. On the other hand, relatively weak parties also behave opportunistically. Lacking more traditional bases of power (e.g. reward and coercive power), the management of these organizations may view opportunism as the only viable way of ensuring that their needs are adequately met in relations with a powerful supplier (Provan and Skinner, 1989).
of the expected long-term benefits. Trust and commitment in a relationship allow firms to view potentially high-risk actions (i.e., using a single-source supplier) as being prudent because of the belief that their partners will not act opportunistically (Morgan and Hunt, 1994). Moreover, relationships with a power imbalance are characterized by less cooperation and greater conflict (Anderson and Weitz, 1989)2. Summing up, asymmetric power distribution leads to unproductive relationships, because the position of the weaker party will be eroded too much in the long term (McDonald, 1999).
The relatively more dependent (less powerful) firm has, by definition, relatively greater interest in sustaining the relationship. This can only be achieved by becoming more receptive to requests and amenable to changes suggested by its partner firm. In contrast, the firm with lesser relative dependence can use its ‘superior position’ to request changes of its partner. With these changes, it can improve the outcome of the relationship either to the benefit of both parties, or strictly to its own benefit (Anderson and Narus, 1990). Assuming opportunism is present, the powerful party will opt for the latter type of action, which is detrimental to the overall success of the outsourcing relationship. The reasoning behind this argument is that the use of power to one party’s own benefit will generate conflict, which is known to lead to lower
satisfaction (Anderson and Narus, 1990).
According to the findings of Burgess and Huston (1983), relationships with symmetric power distribution are more stable than asymmetrical relationships. In addition, high mutual
dependence (as in ‘Interdependence’) discourages the development and expression of conflict3, because the partners have equivalent- and high stakes in the relationship (Kumar, Scheer, and Steenkamp, 1995). These high stakes create vulnerability, because the impact of the contract on both organizations is high.
The state of ‘Interdependence’, as presented in the Power Matrix, is one in which both the Buyer and its Service Provider are highly dependent on each other. Contrary, the state of ‘Independence’ implies the degree of mutual dependency is very low. Emerson (1972) referred to the level of mutual dependence (contrasting ‘Independence’ to ‘Interdependence’) as an assessment of relational cohesion, which is the intensity of a relationship. Buchanan (1992) found that increasing mutual dependence in symmetric relationships enhances performance.
2
However, according to Frazier and Antia (1995), in case of obvious asymmetrical interdependence, effective coordination of the exchange relationship might arise and it can become legitimated over time, with both parties expecting and valuing a certain pattern of influence.
3
This finding can be explained by the following arguments, related to the degree with which the potential for opportunistic behavior can be reduced.
- ‘Independence’ may well lead to high levels of opportunism among parties; if caught applying guile (cunning), these parties can shift to other buyers / service providers without large impact on their business (Provan and Skinner, 1989). Given that the devoted resources are limited, parties with low mutual dependence are unlikely to make the necessary investments to develop norms such as trust and commitment since they may see few potential benefits from doing so (Joshi and Arnold, 1997). Conversely, expected termination costs (associated with high dependence) lead to an ongoing relationship being viewed as important, thus generating commitment to the relationship. - A state of ‘Interdependence’ is an indicator for a strong, co-operative long-term
relationship in which both parties have invested, resulting in little need for opportunism. The Buyer and its Service Provider will have a certain loyalty or commitment4 towards each other and have the accompanying desire to continue the relationship. Moreover, when both parties know that the other party possesses much power, it is not likely that either side is going to use it. The risk of retaliation is often considered as being too high (Ramsay, 1996).
- The development of relational norms in outsourcing relationships requires significant investments of time, energy, and resources by both parties (Anderson and Weitz 1989; 1992). In relationships with high mutual dependence (i.e. in ‘Interdependence’), as Dwyer, Schurr, and Oh (1987) argue, bilateral governance or a true partnership emerges as both parties take responsibility for managing what is an important or strategic
relationship for them. Such bilateral governance should result in the partners being more responsive to each other’s needs, and consequently, relationships with high mutual dependence should elicit higher levels of trust and commitment than either asymmetric or ‘Independence’ type relationships (Kumar, Scheer and Steenkamp, 1994).
According to Kanter (1994), for a relationship to be successful, it should comply with a number of success factors, including interdependence. When either party does not feel dependent on the other, it is likely the relationship and its underlying norms will not receive sufficient attention.
4
In short, the assumed presence of well developed relational norms, reducing the potential for opportunistic behavior, in ‘Interdependence’ type relationships permits the development of favorable affective reactions (Kumar, Scheer, and Steenkamp, 1995).
Contrary, conflict and exploitation are expected to be present in other type of relationships, stemming from the lack of well developed relational norms, which can reduce the potential for opportunistic behaviour. In ‘Interdependence’, conflict and exploitation are less likely to be present. The expected relative impact of these relationship characteristics on outsourcing success is formally stated in Hypotheses H1a-c:
H1a: Relative to ‘Interdependence’ type relationships, ‘Buyer Dominance’ has a negative influence on the level of Outsourcing Success
H1b: Relative to ‘Interdependence’ type relationships, ‘Service Provider Dominance’ has a negative influence on the level of Outsourcing Success
H1c: Relative to ‘Interdependence’ type relationships, ‘Independence’ has a negative influence on the level of Outsourcing Success
The Role of Relational Norms in Outsourcing Relationships
Lee and Kim (1999) have constructed a framework which distinguishes the components of relational norms from the variables that influence it. Moreover, they apply Social Exchange theory to examine the relationship between relational norms and outsourcing success. The results of the study indicate a strong positive relationship between relational norms and outsourcing success. With regard to the components of relational norms; trust, risk sharing, commitment and business understanding (about behaviour, goals and policies) appeared to be positively related to at least one of the outsourcing success indicators (overall success,
business- and user perspective).
Heide and John (1992) argue, with respect to the influence of relational norms, that the
dependent Buyer would not be able to acquire power in the absence of the supportive relational norms. Instead, the Buyer would lose power because of its dependence. Service Providers might voluntarily decide to relinquish power, based on strategic and efficiency considerations. However, they will not do so unless there is some insurance that the relinquished power will not be abused by the Buyer (Heide and John, 1992). This insurance is in place by means of
relational norms.
relationship. Furthermore, in relationships with high mutual dependence (i.e. in
‘Interdependence’), a true partnership emerges, as both parties take responsibility for managing what is an important or strategic relationship for them (Dwyer, Schurr, and Oh, 1987).
H2. ‘Interdependence’ has a positive influence on Relational Norms, relative to other relationship types
Outsourcing involves business relationships which are partnerships, rather than simple recurring transactions between customer and service provider (Grover, Cheon and Teng, 1996). A
transaction style relationship develops through a formal contract in which the expected service is well specified and failure to deliver on commitments is resolved through penalty clauses (Lee and Kim, 1999). In contrast, a partnership style relationship has been defined as “an agreement between buyer and supplier that involves a commitment over an extended time period, and includes the sharing of information along with a sharing of the risks and rewards of the relationship” (Ellram, 1995).
Anderson and Narus (1990) define partnership quality as “the extent to which there is mutual recognition and understanding that success of each firm is in part dependent upon the other firm''. Mohr and Spekman (1994) define it as “purposive strategic relationships between independent firms who share compatible goals, strive for mutual benefit, and acknowledge a high level of mutual interdependency''.There are several possible causes for the reliance on
partnerships in outsourcing. First, under conditions of high uncertainty, parties are generally not
able to sign complete contracts, therefore flexibility and close collaboration is necessary. Second, the relationship specific investments taking place at the beginning of the relationship should be protected, and bonding as partners is a mechanism to do so. Third, when the needs met through outsourcing are ongoing and best met through a long-term relationship, a
(Grouping Variables) Relational Norms Outsourcing Success Power Distribution Four Relationship Types: Buyer Dominance Service Provider Dominance Independence Interdependence Flexibility H2 H1a H1b H1c Risk Sharing Innovation H3 Partnership Quality
2.4 Information Systems Outsourcing
The hypotheses will be tested in the context of Information Systems (IS) Outsourcing, a popular type of Outsourcing, with specific characteristics, which are outlined below (and in Appendix B). Information Systems (IS) Outsourcing is the practice of turning over part or all of an
organization’s IS functions to external service provider(s) (Grover, Cheon and Teng, 1996). According to Grover, Cheon and Teng (1996), IS outsourcing success can be assessed in terms of benefits. They identify three types of benefits from IS outsourcing:
- Strategic benefits, which refer to the ability of a firm to focus on its core business activities and on the strategic uses of IT;
- Economic benefits, which refer to the ability to utilize expertise and economies of scale in human and technological resources of the service provider;
- Technological benefits, which refer to a) the ability to gain access to leading-edge IT and b) the avoidance of the risk of technological obsolescence, resulting from dynamic changes in IT.
As an illustration of opportunism in IS Outsourcing, service providers may overstate their capabilities or use their knowledge advantage to sell IT resources to clients who have little experience and/or knowledge about their needs or market prices (Bahli and Rivard, 2003).
2.5 Research Gap
Although many academics have performed research on success in (IS) Outsourcing, only limited attention has been paid to the effect of power distribution between Buyer and Service Provider on Outsourcing Success. Although previous studies find that a higher magnitude of
interdependence leads to more positive outcomes (Kumar, Scheer, and Steenkamp 1995), this
information does not describe the combination of Buyer dependence and Service Provider dependence that will result in the highest level of positive outcomes. Similarly, asymmetry of power has been found to cause more negative outcomes, but it is unclear whether this asymmetry is due to a Buyer’s or a Service Provider's dependence (Lee and Hsieh, 2003). Moreover, power has mostly been estimated only from the buyer’s point of view, and by using subjective measures (interviews). Contrary, this research applies objective and dyadic
3.
Research Methodology
3.1 Sampling Design
The sample was obtained by means of the Outsourcing Performance study, as carried out by EquaTerra (multinational consultancy firm) and Giarte (Dutch research agency). The
respondents were decision-makers who influence the extension of contracts for Information Systems (IS) services and/or expansion of the “share of IS wallet”. The study was performed in the Netherlands, Belgium and the Nordic countries, among firms active in multiple industries. The respondents were asked to complete a questionnaire (see Appendix A) regarding their Information Systems Service Providers. By 2007, a total of 1300 responses were received. This database was accessible by the author as he is employed at EquaTerra.
3.2 Description of Variables
Outsourcing Success
The dependent variable (Outsourcing Success) is adapted from Grover, Cheon and Teng (1996). It is defined as the satisfaction with benefits from outsourcing gained by an organization.
Satisfaction has been defined as "a positive affective state resulting from the appraisal of all
aspects of a firm's working relationship with another firm" (Anderson and Narus 1984). Satisfaction is perceived to be the best surrogate for capturing both cognitive and affective components of human actions (Ives, Olson and Baroudi, 1983). Anderson and Narus (1990) contended that satisfaction, by its nature, is not only a close proxy for concepts such as perceived effectiveness, but also may be more predictive of future actions by partner firm managers. Further, satisfaction has been found to lead to the long-term continuation of relationships (Gladstein, 1984). The satisfaction score reflects to what extent the achieved strategic, economic and technological benefits satisfy the buyer of the IS services (Grover, Cheon and Teng, 1996). This measure offers a broader insight into the outcome of the relationship than traditional Transaction Cost theory-based studies, which solely focus on the achievement of economic benefits (such as cost savings).
Power Distribution
identifies and measures the major dimensions of power: magnitude and asymmetry (dimensional approach) (Kumar, Scheer, and Steenkamp 1995; Brown et al., 1995).
The categorical approach keeps supplier dependence and distributor dependence separate and categorizes each as low or high, thereby creating a 2 x 2 power matrix. Two methods have been used to develop the matrix. The direct method applies a questionnaire for respondents to
classify their relationship directly into one of the four cells (Buchanan 1992). In the indirect method, researchers perform a mean-split of the dependence scores (Kumar, Scheer, and Steenkamp 1994). The categorical approach uses analysis of variance (Kumar, Scheer, and Steenkamp 1994) or ordinary least squares regression (Buchanan 1992) to analyze the impact of interdependence.
The categorical approach shows the relative contribution of Service Provider power and Buyer Power on Outsourcing Success. However, the categorical approach has some limitations. First, it reduces a multipoint scale to a two-point scale (because of the use of dummies), which has adverse effects on the statistical power. Accordingly, it can only handle the direction (i.e., low or high), not the degree, of relative power distribution. Moreover, it depends on the researcher's judgment in categorizing the extent of replaceability and importance (which indicate the level of dependence) in constructing the matrix (Lee and Hsieh, 2003).
Despite of its limitations, the categorical approach (facilitated by Kraljic Portfolio Model) is adopted in this research to measure Power Distribution. This is because the alternative – the dimensional approach – requires a) the availability of data regarding magnitude and asymmetry and b) the construction of a measure for these ill-defined constructs. These requirements cannot be met in this research.
Kraljic Portfolio Model
The Kraljic (1983) Portfolio Model provides a tool to assess the power distribution in a
relationship between a particular Buyer and Service Provider. The relationship types associated with the power distribution are identified in two steps. First, the power attributes determine how both parties view the particular outsourcing relationship in terms of their dependence on the other party. Dependence varies with the value received (i.e., importance) from a partner and inversely with the availability of alternative trading partners (Cook and Emerson, 1975). Power is a primary consequence of dependence (Emerson, 1962). Second, the viewpoints of the two parties are contrasted to determine the relationship type.
investments), which determine the relative power distribution. The incorporated power attributes are5:
a) The buyer’s switching cost is approximated by the size of the contract. A high contract value implies high relationship specific investments, high complexity of the provided service and therefore high switching costs. Moreover, in anticipating contract renewal, a buyer will take into account the costs of not renewing the contract and instead selecting a new service provider for the required IT services. Depending on the size of the deal, it will be costly to write a Request for Proposal (see Appendix B) and evaluate Service Provider’s proposals (Whitten and Wakefield, 2006).
The value of each outsourcing contract has been indicated by the respondents of the Outsourcing Performance questionnaire (see Appendix A). In order to be able to compare contracts with different durations, the values represent annual costs of the delivered services.
b) The measure of contract value / Buyer’s budget shows how crucial the outsourced service is to the business of the buyer. However, this research involves only Information Technology services, which makes this measure not applicable because the impact of these particular services on the business is unique for each buyer. The role of IT is different in each company. Alternatively, the Strategic Impact can be approximated by a ratio of the contract value to total corporate IT Budget (El-Ansary and Stern, 1972). This ratio shows how important the outsourced IS function is, in relation to the size of a company’s total IT spending. This is consistent with Heide and John (1992), who argue that buyers who partly maintain in-house manufacturing in addition to outsourcing have higher levels of control, relative to their suppliers. However, the total level of the IT budget could be relatively low, which would imply IT is relatively unimportant to the firm. Therefore, the relative importance of IT is assumed to be fixed.
c) The cost of attracting new Buyers depends in part on whether the service provider in question is a market leader or not. Market leaders are visible to (future) buyers and can offer a wide variety of products and services (Provan and Gassenheimer, 1994). These characteristics make it less hard for them to attract new buyers. Specifically, because of their popularity, market leaders are more likely to be included on buyers’ shortlists than other service providers. Buyers served by these dominant suppliers have few equivalent
5
alternatives, and thus, tend to be highly dependent (Emerson, 1962). In this research, market leaders are defined as the top 10% of service providers in terms of number of clients served6.
To determine whether a service provider is a market leader or not, the service providers were ordered by the number of cases in the database they represented. The database includes a total of 82 individual service providers, of which the top 8 was labelled as ‘market leader’. The database is thus assumed to represent the market for IS services in the relevant countries. This assumption has been made because no figures related to markets shares in these markets could be obtained.
d) The contract value / service provider’s revenue (Dickson, 1983) is an assessment of how important the buyer is to the service provider, i.e. how much worse off the service provider would be in case of termination of the contract. In this respect, Heide and John (1992) argue that buyers who account for larger proportions of a supplier’s revenue may acquire more control because of their influence and prominence.
To compose this measure, the contract value was divided by the revenue of the service provider in the year 2006. The revenue data were collected from annual reports
available on company websites. When the value was in a currency different from euro, it was converted to the average exchange rate in the year 2006.
The contract value was divided by the corporate IT Budget of the Buyer, as indicated by the respondents (see Appendix A). The budget is a proxy for the total size of the buyer’s organization. The advantage of using this proxy is that it implicitly controls for the
importance of Information Technology for the organization.
The four power attributes together give an indication of relative dependence, because they measure a) how important the other party is to the buyer / service provider and b) how easily they can replace their partner. Based on the level of mutual dependency, each party has the
relative power to deny or hinder the other’s gratification (Emerson, 1962). The labels in the cells
in the tables below refer to how the buyer / service provider would classify the types of (IT) services they demand or deliver. These classifications are associated with strategies firms should apply to become relatively less dependent on their service provider7.
6
The market leaders in this database together serve 45.5% of the Buyers. 7
Table 1. Kraljic Matrix (1983): Buyer’s Perspective
Below, each of the contract types is shortly described:
- ‘Routine’ contracts have a small value relative to the total IT Budget and switching costs are low. Therefore, the Service Provider is relatively unimportant to the Buyer and easily replaceable.
- ‘Leverage’ contracts have a high value relative to the total IT Budget, but switching costs are low. Therefore, the Service Provider is relatively important to the Buyer, but at the same time it is easily replaceable.
- ‘Bottleneck’ contracts have a low value relative to the total IT Budget, but the associated switching costs are high. Therefore, the Service Provider is relatively unimportant to the Buyer, but it is hard to replace.
- ‘Strategic’ contracts have a high value relative to the total IT Budget and also high switching costs. Therefore, the Service Provider is important to the Buyer and also hard to replace.
Table 2. Kraljic Matrix (1983): Service Provider’s Perspective
- ‘Routine’ contracts provide the service provider with relatively low revenue, but the cost of attracting new Buyers is low. Therefore, the Buyer is relatively unimportant to the Service Provider and also easily replaceable. When the contract is also viewed as ‘Routine’ from the Buyer’s point of view, it means both parties are Independent, as they are unimportant to each other and also easily replaceable.
- ‘Get rid of’ contracts represent a low value and the cost of attracting new Buyers is high. Therefore, the Buyer is relatively unimportant to the Service Provider, but at the same time it is hard to replace. In this case, the Service Provider is always the dominant party, because, according to Kraljic (1983), Service Provider’s strategy in this case is to get rid of these contracts and focus on more important clients which are more easily
replaceable, which would limit the need for relationship specific investments. - ‘Potential’ contracts represent a high value relative to the Service Provider’s total
revenue and the cost of attracting new Buyers is high. Therefore, the Buyer is important to the Service Provider and it is also hard to replace. When this type of contracts is viewed as ‘Strategic’ from the Buyer’s point of view, it means both parties are
Interdependent, as they are important to each other and also hard to replace.
By linking these two Kraljic matrices, the distribution of relative power distribution follows from the combination of each party’s relative dependence. The matrix below shows which
combinations of buyer- and service provider viewpoints are associated with which relationship types. This distribution of relationship types is based upon the assumption that a party is
Table 3. Combined Kraljic Matrix (Faas and Hendriks, 2005)
It follows from this matrix that the Service Provider is assumed to be dominant in half of the combinations. According to social exchange theory, this is because a characteristic of Relational Exchange is that contracts have a length of several years, during which the Service Provider’s income is guaranteed. From the Buyer’s point of view, its business is dependent on the provided services on a day-by-day basis. Thus, although Buyers are usually viewed as dominant in the process of selecting a new Service Provider, the Service Provider is often dominant once the contract is signed (Kern, Willcocks, and van Heck, 2002). According to theory, parties will invest in relational norms when they are dependent on each other (when importance is high and the degree of replaceability is low), these norms reduce the potential for opportunism. Therefore, in
Interdependence type relationships we expect to find a higher degree of outsourcing success.
Each case (contract) was assigned a value of 1 for one of the relationship types. These values were assigned on the basis of the combined Kraljic matrix (see Table 3. Combined Kraljic Matrix (Faas and Hendriks, 2005). This was done on the basis of observing the operational measures being:
- Above or below the median value of: Contract Value / Service Provider’s Revenue (VALRE);
- Above or below the median value of: Contract Value (VAL);
- Above or below the top 10% cut-off number for market leadership (CLI).
Cluster Analysis has been carried out in order to investigate the distribution of the operational measures in the sample (See Appendix E). The results show how the outsourcing contracts in the database fit into the Kraljic Matrix. Five out of the 16 cells were identified as clusters, which represented each of the four relationship types. This means that not all of the groups of
outsourcing contracts as represented by the cells in the Kraljic Matrix are so unique that they can be classified as clusters. Considering this outcome of the cluster analysis, it can be
concluded the Kraljic Matrix might not be the optimal model to determine the power distribution in Information Systems Outsourcing relationships. Perhaps these relationships lack the variety of general buyer-supplier relationships in procurement, for which the model has been designed.
Relational Norms
‘Relational Norms’ is a higher order construct (Heide and John, 1992; Lee and Kim, 1999) consisting of the dimensions Flexibility, Risk sharing, Innovation and Partnership Quality. Each item is measured on a 6 Likert scale.
In this thesis, Risk Sharing, Flexibility, Innovation and Partnership Quality are used as measures for a factor representing Relational Norms. Risk sharing is at the heart of an outsourcing
relationship (Ellram, 1995) and was found to be a component of relational norms by Lee and Kim (1999). Flexibility is the bilateral expectation of willingness to make adaptations as circumstances change (Heide and John, 1992). Flexibility is fundamental to any outsourcing relationship, since these involve long-term contracts and dynamic, unpredictable environments. Participants in outsourcing relationships need the freedom and spontaneity to respond to
changing circumstances (Goles and Chin, 2005). Therefore, according to research by Fitzgerald & Wilcocks (1994), flexibility is a critical element of outsourcing relationships. Innovation signals whether the flexibility incorporated in the contract is actually used by the Service Provider to actively implement innovative solutions.
Partnership Quality refers to the intensity of the relationship, which will be further described
Exploratory Factor Analysis will be performed on these variables so as to construct one
‘summary variable’. The data regarding the Partnership Quality (OP, Question 4) is available for all countries. However, the data for Flexibility, Risk sharing, Innovation (OP, Question 7, 8 and 9) are only available for Belgium and Nordics. Therefore, these three variables are not included in the first model, but included in the second model (testing H2) as part of a ‘summary variable’, Relational Norms.
Service Quality
The quality of the service provided is critical to the success of IT outsourcing and can be assumed to be independent of the outsourcing decision (Williamson, 1991). Service quality is the conformance to customer requirements in the delivery of a service. It is a perceived judgment resulting from a comparison of client expectations with the actual level of service customers perceive to have received from the outsourcing vendor. Service quality results in significant benefits, such as profit-level increases, cost savings, and increased market share, to both entities involved in a transaction (Whitten and Leidner, 2006). Since service quality is not an element of the actual relationship between the two parties, it is not in scope of this research. Rather, the satisfaction of buyers regarding quality is added as a control variable.
Cultural Compatibility
Cultural Compatibility is the extent to which both parties can coexist with each other’s beliefs about what values, behaviours, goals and policies are important and appropriate, and which are not (Morgan and Hunt, 1994). In case cultures are incompatible, this can be a major stumbling block for the parties involved in an outsourcing relationship (Klepper and Jones, 1998).
Moreover, minimizing cultural differences allows both parties to make greater progress in achieving compatible objectives (Kanter 1994; Kern, 1997). Although evidence exists of the positive influence of cultural compatibility on outsourcing success (Henderson, 1990; Morgan and Hunt, 1994), others found no relationship (Lee and Kim, 1999). Cultures might be
4.
Results
Cross section analysis is used to carry out the main analysis. This is because the observations from the population subset are non-recurrent (i.e. they are observations from a single point in time). The cross section units are the individual relationships (contracts) in the database. The data related to these units are based upon financial data (used to measure power distribution) and the buyer’s perception of the relationship (used to measure Relational Norms and
Outsourcing Success).
4.1 General Approach
Because the formulated hypotheses include two different dependent variables (Outsourcing Success and Relational Norms), two distinct multiple regression models are constructed. The first model serves to test hypothesis 1a-d and 3. It includes data from all countries, but data on
Flexibility, Risk Sharing and Innovation is excluded, because it is not available for all countries.
Contrary, the second model serves to test hypothesis 2. It includes the variables Flexibility, Risk
Sharing and Innovation, but excludes the data related to outsourcing relationships in the
Netherlands.
4.2 Model 1
4.2.1 Test for Equality of Means for Outsourcing Success
In order to check whether outcomes are significantly different, the mean values for Satisfaction (SAT) are compared among the relationship types using Analysis of variance (ANOVA). The statistical package Eviews 6 facilitates this analysis (as well as the multiple regression analysis). The ANOVA test returns the two-tailed probability that the means in either subset of data are not significantly different. The probability of 0.0137 indicates (with p-value ≤ 0.05) that the means for SAT - the measure of Outsourcing Success - are significantly different among the relationship types. The highest mean level of Outsourcing Success (a satisfaction level of 4.288) is observed in ‘Interdependence’ type relationships. Contrary, the lowest mean level of Outsourcing Success (3.978) can be observed in ‘Service Provider Dominance’ type relationships. The next step concerns the construction and execution of an OLS regression, to find evidence in support of Hypothesis 1a-d, and also to test Hypothesis 3.
Categorized by values of POWER Sample: 1 874
Method df Value Probability
Anova F-test (3, 869) 3.574617 0.0137
Welch F-test* (3, 306.308) 3.531248 0.0152
*Test allows for unequal cell variances
Analysis of Variance
Source of Variation df Sum of Sq. Mean Sq.
Between 3 13.66539 4.555130
Within 869 1107.366 1.274299
Total 872 1121.031 1.285586
Category Statistics
Std. Err.
POWER Count Mean Std. Dev. of Mean
BDOM 180 4.166667 1.101041 0.082067 SPDOM 417 3.978417 1.138071 0.055732 IND 92 4.043478 1.128191 0.117622 INT 184 4.288043 1.134972 0.083671 All 873 4.089347 1.133837 0.038375 Table 4 4.2.2 Model 1 structure
IND SPDOM BDOM Independence 1 0 0 Service Provider Dominance 0 1 0 Buyer Dominance 0 0 1 Interdependence 0 0 0 Table 5
The regression to be estimated is:
(1) SAT = b0 + b1IND + b2SPDOM + b3BDOM + b4SQUAL + b5PQUAL + b6CUL + ε
4.2.3 Results of OLS Regression
Dependent Variable: SAT Method: Least Squares Sample: 1 874
Included observations: 847
Coefficient Std. Error t-Statistic Prob.
C 0.516292 0.128310 4.023780 0.0001 IND -0.153780 0.096864 -1.587587 0.1128 BDOM 0.119649 0.080422 1.487761 0.1372 SPDOM -0.032061 0.067741 -0.473283 0.6361 SQUAL 0.604426 0.028544 21.17493 0.0000 PQUAL 0.283761 0.025964 10.92915 0.0000 CUL -0.012790 0.052871 -0.241909 0.8089
R-squared 0.569617 Mean dependent var 4.082645
Adjusted R-squared 0.566543 S.D. dependent var 1.136237
S.E. of regression 0.748069 Akaike info criterion 2.265588
Sum squared resid 470.0705 Schwarz criterion 2.304776
Log likelihood -952.4765 Hannan-Quinn criter. 2.280601
F-statistic 185.2918 Durbin-Watson stat 1.869931
Prob(F-statistic) 0.000000
In general, the coefficients in a regression measure the marginal contribution of the independent variable to the dependent variable, holding all other variables fixed. These can be interpreted as the slope of the relation between the corresponding independent variable and the dependent variable. However, as the independent variables in this regression are dummies, they cannot be directly interpreted as the slope of the relation. In this regression, the PQUAL and SQUAL variables are regressed against the SAT variable in three subsets: IND, BDOM and SPDOM. Formally, for each of the subsets, the regression should be interpreted as:
(2) SAT = b0 + b1PQUAL + b2SQUAL + b2CUL + ε
The results of Ordinary Least Squares (OLS) regression indicate that the b0 value is negative for IND and SPDOM. This means that these relationship types have a lower level of Outsourcing Success, relative to ‘Interdependence’ relationship types. Contrary, the b0 is positive for the BDOM subset, which indicates this type of relationship has a relatively higher level of
Outsourcing Success. In conclusion, evidence has been found in support of H1b and H1c, but not for H1a. However, none of the relationship types show a significant relationship with the dependent variable.
Moreover, the outcome indicates the relationship between Partnership Quality and Outsourcing Success is significant and positive, supporting H3.
With regard to the control variables, it can be concluded that Service Quality is significant and positive, which is in line with previous research in this field. Contrary, the level of Cultural Similarity in outsourcing relationships has an insignificant effect.
4.3 Model 2
Model 2 includes only data regarding relationships in Belgium and Nordics, because Dutch data concerning Risk Sharing, Flexibility and Innovation is lacking. The correlation matrix below shows correlations higher than 0.5, which indicates exploratory factor analysis is feasible for the listed variables.
PQUAL RISK FLEX INNO
PQUAL 1.000
RISK 0.544 1.000
FLEX 0.630 0.510 1.000
Table 7. Correlation matrix for Partnership Quality, Risk Sharing, Flexibility and Innovation 4.3.1 Exploratory Factor Analysis
Exploratory Factor Analysis is used to identify if the underlying variables explain the pattern of correlations within the set of observed variables related to the higher order construct ‘RN’ (Relational Norms). This procedure is used to reduce the number of variables in a data set and explore the underlying structure of the variables. Factor analysis shows how the variables relate to each other in terms of ‘communality’ and ‘uniqueness’. The level of communality of each variable is the estimated squared correlation with its own common portion - that is, the proportion of variance in that variable that is explained by the common factors. Contrary, the level of uniqueness shows to what extent the factors are totally uncorrelated. The results
indicate Flexibility is the component which shows the lowest of communality and highest degree of uniqueness, meaning the common factor explains a relatively low amount of its variation. However, none of the four components has a very low level of communality, which means the components explain the Relational Norms variable well. This is confirmed by the Bartlett probability8 of less than 0.05, which indicates the components are highly related.
Loadings RN Communality Uniqueness PQUAL 0.827528 0.684802 0.315192 RISK 0.731895 0.535670 0.464334 FLEX 0.672940 0.452848 0.547153 INNO 0.856941 0.734347 0.265651 Model Independence Discrepancy 0.018246 1.799384 Chi-square statistic 8.958730 883.4978 Chi-square prob. 0.0113 0.0000 Bartlett chi-square 8.907033 879.5991 Bartlett probability 0.0116 0.0000 8
Parameters 8 4 Degrees-of-freedom 2 6
Table 8
The factor loadings for ‘RN’ (Relational Norms) are the basis on which the ‘summary variable’ is constructed, which is used in the ANOVA and multiple regression analysis.
4.3.2 Test for Equality of Means of Relational Norms
The equality of means of the created Relational Norms variable is tested because it will indicate whether the values differ significantly in terms of relative power distribution. If the outcome shows significant differences, the multiple regression analysis will show the exact relationship between relative power distribution and Relational Norms.
Categorized by values of POWER Sample: 1 534
Included observations: 492
Method df Value Probability
Anova F-test (3, 488) 3.052576 0.0282
Welch F-test* (3, 200.566) 3.013716 0.0311
*Test allows for unequal cell variances
Category Statistics
Std. Err.
POWER Count Mean Std. Dev. of Mean
BDOM 80 0.165924 0.899935 0.100616 SPDOM 226 -0.096054 0.916727 0.060980 IND 81 -0.105111 0.936933 0.104104 INT 105 0.161412 0.973946 0.095047 All 492 -2.02E-16 0.935676 0.042184 Table 9
we can observe ‘Interdependence’ and ‘Buyer Dominance’ have positive values, contrary to the other two relationship types.
4.3.3 Model 2 Structure
Hypothesis 2 states ‘Interdependence’ has a positive influence on Relational Norms, relative to other relationship types. In the OLS regressions conducted to test Hypothesis 2, an intercept (C) is included to catch the ‘overall’ effect of factors outside the model. This means one of the dummy variables should be dropped from the regression, to avoid the dummy trap, which occurs when all the dummy variables are included (summing up to 1, which stands for the variable X0 to the constant term B0), resulting in perfect multicollinearity. The structure of the
dummies is presented below. It should be noted that ‘Buyer Dominance’ is selected as the base category, against which the other relationship types are contrasted.
(3) RN = b0 + b1IND + b2INT + b3SPDOM + b4SQUAL + ε
IND SPDOM INT Independent 1 0 0 Service Provider Dominance 0 1 0 Buyer Dominance 0 0 0 Interdependence 0 0 1 Table 10
4.3.4 Results of OLS Regression Model 2
Dependent Variable: RN Method: Least Squares Sample: 1 534
Included observations: 488
Coefficient Std. Error t-Statistic Prob.
C -2.314113 0.174812 -13.23770 0.0000
IND -0.171988 0.119121 -1.443810 0.1494
INT -0.105900 0.112529 -0.941086 0.3471
SPDOM -0.243593 0.098472 -2.473717 0.0137
SQUAL 0.552608 0.034228 16.14512 0.0000
Adjusted R-squared 0.356722 S.D. dependent var 0.938267 S.E. of regression 0.752534 Akaike info criterion 2.279452
Sum squared resid 273.5264 Schwarz criterion 2.322385
Log likelihood -551.1862 Hannan-Quinn criter. 2.296316
F-statistic 68.51489 Durbin-Watson stat 1.894066
Prob(F-statistic) 0.000000
Table 11
According to the OLS Regression outcome of this model, there is a significantly (p<0.05)
negative association between ‘Service Provider Dominance’ and Relational Norms. This means Relational Norms are at a relatively low level when the Service Provider is the dominant party in outsourcing relationships. The effects associated with other relationship types are not
5.
Conclusions
The general purpose of this thesis has been to gain further insight into the role of power distribution in outsourcing relationships. Specifically, it has provided answers to three research questions, of which the findings are discussed in turn. First, I will discuss the findings regarding the influence of the type of power distribution on outsourcing success. Based on contract theory, transaction cost economics and social exchange theory, four distinct relationship types and their characteristics have been identified: Buyer Dominance, Service Provider Dominance,
Independence and Interdependence. The outsourcing relationships in this study were assigned one of these classifications on the basis of the the value received (i.e., importance) from a partner and the availability of alternative trading partners. In ‘Interdependence’ type
relationships, both parties view the other as both important and hard to replace. In that case, social exchange theory predicts they will invest in the relationship, leading to highly developed relational norms (such as trust and commitment). These norms in turn reduce the potential for opportunism, which is detrimental to the success of the outsourcing relationship, as predicted by transaction cost economics.
The hypothesized difference between Interdependence and other relationship types, with regard to the level of Outsourcing Success, was partially identified. Independence and Service Provider
Dominance relationship types showed relatively lower level of Outsourcing Success, as
hypothesized. However, the sign of the corresponding coefficient related to Buyer Dominance was positive, indicating an effect similar to that of Interdependence type relationships.
Therefore, we can conclude Outsourcing Success is facilitated when the distribution of power is such that the buyer is dominant in the relationship with its service provider. A possible
explanation might be that success in outsourcing relationships depends on the extent to which the buyer is able to govern the relationship. Alternatively, despite the lack of well developed relational norms, the negative consequences of opportunism (e.g. exploitation), might not occur when the buyer is the powerful party; the buyer might not have the incentives to exploit the service provider. Moreover, firms that perceive that they are "calling the shots" in a relationship will experience greater satisfaction (Anderson and Narus, 1990).
The second research question addressed in this thesis was: are ‘Interdependence’ type
