Portfolio Of Controls In Global Component Outsourcing Relationships
Nukhet Harmancioglu
Department of Marketing and Supply Chain Management
Michigan State University
The Eli Broad College of Business
East Lansing, MI 48824-1122
Phone: 517-432-5535 ext.290
Fax: 517-433-1112
E-mail: [email protected]
ABSTRACT
In the contemporary business environment characterized by increasing globalization and
technological discontinuities, firms strive to develop capabilities and flexibilities through the use of
outsourcing and adopting modular systems. However, these strategies constitute risks of opportunistic
expropriation of tacit knowledge and costs related to monitoring sourcing partners due to geographical
and cultural distances. This study aims to provide a conceptual framework that explicates the ways in
which firms manage their component outsourcing relationships in global technology-intensive
markets.
Key words: global component outsourcing, joint product development, modularity, technology
intensive markets, portfolio of controls
INTRODUCTION
Technological advances and increasing globalization characterize the current business milieu and
have radically transformed the competitive landscape. Consequently, firms increasingly strive to
develop capabilities and achieve strategic flexibility through making use of outsourcing and adopting
modular systems (Garud & Kumaraswamy, 1995; Schilling, 2000). The phenomenon of downstream
buyers cooperating with upstream suppliers to introduce new products and/or improve the quality of
existing product lines is prevalent across a spectrum of industries including consumer-electronics,
computer software, textiles, automobiles, steel and pharmaceuticals (Clark, 1989; Clark and Fujimoto,
1991; Bettis, et al., 1992; Choudhury and Sabherwal, 2003). The study of technology-intensive (TI)
markets has attracted significant attention as a research area in the marketing, management and
engineering literature (Buzzell, 1999; John, et al., 1999; Teece, 1988; Dutta and Weiss, 1997). In the
extant literature, the term ‘high technology’ has been typically used to define markets characterized
by a rapid pace of technological change (Bourgeois and Eisenhardt, 1988). Based on this, as John, et
al. (1999) suggests, “technology-intensive markets are characterized by products that are based on
significant amounts of scientific and technical know-how” (p 79). Thus, an understanding of TI
markets, thus, requires a focus on the presence and transfer of know-how and the difficulties related to
transactions for know-how (Glazer, 1991; Teece 1988; Kogut and Zander, 1992). Due to rapid pace of
technological change that creates the risk of obsolesce of knowledge and capabilities, such markets
may force buyers to engage in supplier relationships (Harrigan, 1985; Swan and Allred, 2003; Weiss
and Heide, 1993). However, these relationships bring about additional threats such as potential
leakage of tacit know-how and (over)reliance on suppliers’ resources and capabilities (Heide and
Weiss, 1995; Wasti and Liker, 1997; Dutta and Weiss, 1997).
Another important feature of such technology-intensive markets is the increasing utilization of
modular product architectures as the basis for new product designs and development (Sanchez, 1995,
1999; Katz and Shapiro, 1994; Schilling, 2000; Stremersch, and et al., 2003). Modularity is created
within an architecture by standardizing the interfaces between functional components and specifying
to allow for greater reusability and commonality sharing of components among product families
(Sanchez and Mahoney, 1996; Wilson, et al., 1990). The benefits of such architectures include their
ability to increase the product variety an organization can offer to markets, decrease the time and
resources required to bring new products to market, speed up the introduction of technologically
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improved products, and reduce the costs of new product development (John, et al., 1990; Garud and
Kumaraswamy 1995; Prahalad and Bettis, 1986). More importantly, modular systems enable the
coordination of a loosely coupled organization structure linking geographically dispersed component
developers (Kogut and Kulatilaka, 1994) making global component outsourcing possible (Mikkola,
2003).
Previous research consist of conceptual studies and empirical work that have addressed the notion
of modularity, standardization and network externalities in such markets, drawing upon neoclassical
(i.e., production-cost perspective) and institutional economics (i.e., a transaction-cost perspective)
(Walker and Weber, 1984; Swan and Allred, 2003; Schilling and Steensma, 2000; Wilson and et al.,
1990). Previous research on buyer behavior in high technology markets has focused on specific
outcomes as opposed to buyers’ underlying processes (Weiss and Heide, 1993). Accordingly, there is
lack of research on the formal and informal controls the buyers exert on their suppliers in their
outsourced projects to prevent risks, such as technological know-how leakage and diffusion to
competitors. Buyers generally strive to minimize the likelihood of opportunistic expropriation of tacit
technological knowledge, eliminate the difficulties related to monitoring their partners due to
geographical or cultural distance and avoid switching costs tied to their suppliers, especially high in
the case of a high degree of external linkages and dependencies (Tidd, 1995; Pisano, 1990).
Therefore, it is also critical to gain an understanding of how firms manage their component
outsourcing relationships in the global TI markets. This argument corresponds to streams of research
such as organizational control, agency and resource dependence theories (Ouchi, 1979; Jaworski,
1988; Pfeffer and Salancik, 1978; Eisenhardt, 1985).
The focus of this paper is also on the unique consequences of modular systems, which enable the
coordination of loosely coupled and flexible organizational structures linking geographically
dispersed component developers via standardized interface specifications and feasible division of
tasks in functional specification (Mikkola, 2003; Schilling, 2000; Wilson, et al., 1990). Such interface
management systems should lead firms to adopt different control portfolios in managing their
component outsourcing than they would do with traditional interface systems (Sanchez, 1999). Thus,
referring to marketing, management, and international business literatures, the primary contribution of
this paper to provide a conceptual framework that explicates the factors that influence the
combinations of control buyers exert to their suppliers in technology intensive markets. Overall, the
discussion in this study can be summarized as follows: (1) what mechanisms constitute the portfolios
of control buyers exert to their suppliers in outsourced projects in technology intensive markets (with
modular architectures)? (2) what are the antecedents of the combinations of control utilized in these
outsourcing relationships? and (3) how does degree of modularity impact the relationships between
the control mechanisms and their determinants? We commence with providing our definition of the
control and different types of control mechanisms buyers choose to employ. We proceed by
explaining the theoretical foundations that we refer to and depicting our framework for global
component outsourcing relationships.
CONTROL AND TYPES OF CONTROL MECHANISMS
Definition of Control
This paper views control in a behavioral sense, that is, ‘attempting to ensure individuals or teams
act in a manner that is consistent with achieving desired goals’ (Ouchi, 1979; Eisenhardt 1985;
Jaworski, et al., 1993; Anderson, 1995; Kraft, 1999). The behavioral view of control implies that the
principal uses certain devices, or control mechanisms, to promote desired behavior by the agent.
These control mechanisms may broadly be divided into formal and informal controls (Jaworski 1988;
Jaworski et al., 1993). Formal controls rely on written mechanisms that influence the agent’s behavior
through performance evaluation and rewards. An example for a formal contract in the outsourcing
context may include target implementation dates. On the other hand, informal control mechanisms
such as social norms, peer pressure, shared beliefs and experiences, constitute modes that utilize
social strategies to reduce goal differences between the principal and agent.
Though the two classes of control are distinct in the actions or the approach required for their
execution, controllers often use control modes in combination, creating a portfolio of controls
(Jaworski 1988; Oliver and Anderson, 1994). Formal contracts involve control through performance
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evaluation, which emphasizes the information aspects of control, whereas informal contracts via
minimizing the divergence of preferences between the partners (Eisenhardt, 1985). In past literature,
most control researchers have examined one type of control in isolation (e.g., Ouchi 1979; Thompson
1967). However, Jaworski and et al. (1993) advocated that to fully capture the impact of management
controls one must focus on the simultaneous use of multiple controls. Though Ouchi (1979)’s original
conceptual work focused on each control independently of the others, they acknowledged that the
“problem of organization design is to discover that balance of socialization and measurement which
most efficiently permits a particular organization to achieve cooperation among its members” (p 846).
Controls combine synergistically to influence the achievement of a given objective that they are most
effective when the formal and informal techniques are bundled. These broad categories of control
mechanisms have also been further classified on certain criteria, i.e., the degree, the objectivity and
the timing of intervention for formal controls and the level (i.e., social versus individual) of
aggregation for informal mechanisms (Jaworski, 1988). Therefore, proceeding sections include
explanations of subcategories of these control mechanisms and their distinguishing characteristics.
We subsequently discuss the unique notions of implementing control in the context of outsourcing
relationships and modular systems.
Types of Formal Controls
Two types of formal controls, i.e., outcome and behavior controls, differ based on the degree of
supervision, objectivity of the evaluation procedures, and the extent of time perspective (Oliver and
Anderson, 1994). Outcome control is typified by the principal (i.e., buyer)’s focus on the outputs of
the project. Buyers that employ such mechanisms evaluate their suppliers based on desired project
goals or outcomes and reward them for meeting those goals (e.g., functional specifications, target
implementation date and performance of the component). In behavior control, on the other hand, the
buyers seek to influence the process, or the means to goal achievement. By explicitly prescribing
specific rules and procedures and closely observing the supplier’s behaviors, they reward their
suppliers based on the extent to which they follow stated procedures (Jaworski and MacInnis, 1989)
(e.g., development methodology, placing buyer personnel on supplier premises, weekly progress
reports, or conference calls) (Eisenhardt, 1985). Therefore, due to their emphasis on process behaviors
over outcome results, behavior-oriented controls involve greater supervision and contact, more
subjective evaluation methods and tend to have a longer time perspective.
Types of Informal Controls
In the literature, informal controls have been distinguished based on whether it is implemented by
or exerts an influence on a social group or an individual. Clan control is implemented through
mechanisms that minimize the differences between a principal’s and an agent’s preferences
(Eisenhardt 1985) by transmitting common values, beliefs, and philosophy within a clan (Ouchi 1979)
(e.g., structuring the relationship so that it is strategic to both parties, and socialization of buyer and
supplier executives through regular joint meetings). Self-control also relies on the supplier engaging
in behavior consistent with the best interests of the controller without formal controls. The supplier
determines both the goals and the actions through which they should be achieved as in self-regulated
teams. Mechanisms to implement self-control in the outsourced context are initiated and implemented
internally by the supplier. For instance, members of the supplier team may determine the specific
process through which the system is to be developed, or a specific timeline for system delivery, and
then monitor their compliance with the self-prescribed behaviors and/or outcomes.
THEORETICAL FOUNDATIONS AND MODEL OVERVIEW
Past research has suggested that the problems that exist in high-technology markets are of two
different kinds from a buyer’s perspective. Firstly, these markets are characterized by considerable
uncertainty due to heterogeneous and rapidly changing technologies, and to the fact that buyers
frequently lack relevant prior experience (Glazer 1991; Teece 1988; von Hippel, 1986). Thus, they
choose to outsource their product development activities and engage in partnerships with their
suppliers in order to combine suppliers’ resources and capabilities with their knowledge base. They
aim to enhance their flexibility and productivity and to lower transaction and production costs.
Secondly, these outsourcing relationships lead the buyers to face switching costs, as a result of earlier
commitments to particular product technologies or suppliers (Heide and Weiss, 1995). As a result,
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even though these relationships constitute avenues for inter-firm learning and increase firms’
adaptability, they create a certain degree of supplier-buyer interdependence. Overall, the costs and
consequences of outsourcing for the buyer firms include external dependence, functional mismatches,
and coordination difficulties, along with the gradual loss of internal design, manufacturing, and other
knowledge-based capabilities (Mikkola, 2003; Swan and Allred, 2003; Appleyard, 2003; Schilling,
2000; Wilson et al., 1990). Moreover, the most important risk associated with these linkages that can
lead to loss in competitive power is likely leakage through suppliers of both technical and marketing
know-how to competitor firms (especially at the design stage). These notions all together indicate that
buyers are faced with the necessity to implement certain control mechanisms to govern the risks and
dependencies in their relationships with their suppliers, which they initiate due to the external threats
and dependencies. Accordingly, organizational control, agency and resource dependence theories
should most adequately serve to explain the antecedents (i.e., factors both internal and external to the
relationship) and outcomes of the buyers’ choice of combinations of controls.
Organizational Control and Agency Theory
The focus of the organizational control framework and agency theory is on determining the most
efficient control(s) to govern a particular relationship from the principal’s point of view, given the
characteristics of the parties involved and the degree of environmental uncertainty, the task
complexity and the costs of obtaining information for the monitoring of the agent (Ouchi, 1979;
Eisenhardt, 1985, 1989; Anderson, 1995; Kraft, 1999). The primary assumptions of organizational
control and agency theory are information asymmetry (i.e., the principal lacks complete information
as to what the behavior of the agent will be), self-interest seeking and divergent goals of principals
and agents and uncertainty relating to the outcome of the agents’ behavior. Studies drawing upon
agency theory have employed the metaphor of a contract to describe relationships in which party
delegates responsibility to another. Hence, a buyer-supplier collaboration constitutes an agency
relationship as the buyer, i.e., the principal attempts to gain accurate product or component
information and desired benefits from a supplier, i.e., the agent (Bergen, et al. 1992). Overall, control
is viewed as an important aspect of organizational and interorganizational design (Ouchi, 1979;
Bergen et al., 1992).
Generally, agent and principal risks occur due to discrepancies between the objectives, knowledge
and capabilities of the buyer firm versus those of the supplier firm (Gurbaxani and Whang, 1991).
Due to such asymmetries, agents may be tempted to exhibit opportunistic behavior in the forms of
moral hazard, adverse selection and/ or imperfect commitment (Ouchi, 1979; Bergen et al., 1992). In
the case of technological outsourcing relationship, such intentions may be detrimental particularly in
instances where certain factors, such as non-modular (i.e., tightly integrated) systems and high
supplier involvement increase know-how leakage.
On the whole, in the control literature, behavior controls have been viewed as efficient means
when the environmental uncertainty, difficulty in measuring outcomes, and risk aversion of the agents
are all high, and when the costs of measuring behavior are low. They may be implemented as
interdependence and uncertainty increase, as are controls aimed to encourage and enable clan and
self-control. Behavior control requires task programmability, i.e., behaviors are explicitly defined,
which may be possible higher supplier involvement and interaction in the development process
(Thompson, 1967; Ouchi, 1979). Similarly, clan controls can be used in only two of the cases - when
the buyer and supplier had shared goals, and when frequent interactions can lead to shared values.
Moreover, in the organizational control and agency literature, the two control strategies, i.e., formal
and informal, have been viewed to be interrelated. Ouchi (1979) advocated that the choice between
the two is driven by the ease of performance evaluation. An organization can tolerate a workforce
with highly diverse goals if a precise evaluation system exists. In contrast, a lack of precision in
performance evaluation can be tolerated when goal incompatibility is minor (Ouchi, 1979; Eisenhardt,
1985; Lawless and Price, 1992). If the task is neither programmed nor has a measurable outcome, then
alternative control strategy of minimizing divergence of preferences such as clan control is
appropriate.
Resource Dependency Theory
Resource dependency theory views interfirm governance as a strategic response to conditions of
uncertainty and dependence (Pfeffer and Salancik 1978; Heide, 1994; Anderson and Narus, 1990).
The basic assumptions are that the lack of sufficient resources and/or capabilities to complete a task
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creates dependence on the parties from whom the resources are obtained and introduces uncertainty
into a firm’s decision making (Heide, 1994; Ganesan, 1994; Heide and John, 1992).This uncertainty
occurs to the extent that the resource flows are not subject to the firm’s control, and may not be
predicted accurately. This notion is applicable to technology outsourcing relationships that are usually
initiated due to the buyer’s need to control key technologies in the value chain and manage the
technological turbulence they face in their operating environment.
The main premise of the theory is that firms will seek to reduce uncertainty and manage
dependence by structuring their relationships by means of establishing formal and/or ‘semi’formal
links with other firms (Heide, 1994; Ganesan, 1994; Heide and John, 1992). These links with
suppliers can help reduce the cost of components through specialization and the sharing of
information on costs, but can also be a source of technology when a firm does not have the
competence to develop a critical component in-house (Tidd, 1995). However, according to the theory,
principal (buyer)’s risks occur due to the principal’s lack of experience and expertise and the agent
(supplier)’s capabilities with the activity to be outsourced (Aubert et al., 1998). Buyer firms that lack
the knowledge and experience necessary to evaluate the quality of the outsourcing service provided
may encounter problems since they make themselves vulnerable to the agent’s opportunistic behavior.
Overview of the Conceptual Model
FIGURE I. CONCEPTUAL FRAMEWORK
TASK CHARACTERISTICS
(1) Strategic Importance of
the Development Project
P1 (a:+) (b:-) (c:+) (d:-)
CONTROL MECHANISMS
P2 (a:-) (b:+) (c:-) (d:+)
FORMAL CONTROLS
(2) Geographic Dispersion
(3) Cultural Proximity
(4) Lack of Project-related
Buyer Knowledge
(a) Behavior Control
(b) Output Control
P3 (a:-) (b:+) (c:-) (d:+)
P4 (a:-) (b:+) (c:+) (d:+)
INFORMAL CONTROLS
(c) Clan Control
(d) Self Control
ENVIRONMENTAL
UNCERTAINTY
(5) Technological
Heterogeneity
P5 (a:+) (b:-) (c:+) (d:+)
P6 (a:+) (b:-) (c:+) (d:+)
(6) Technological
P8-10
Discontinuity
P7 (a:+) (b:-) (c:-) (d:-)
MODERATOR:
(10) Degree of
Modularity
P8 (a:+) (b:-) (c:+) (d:+)
SWITCHING COSTS
Component
P9(7)
(a:-)
(b:+) (c Purchase Concentration
(Single versus Multiple)
(8) Degree of Supplier Involvement
(Extent of Interdependency)
(9) Supplier Capabilities
A control situation/ agency relationship typically involves an individual principal evaluating and
influencing an individual agent. The principal and the agent constitute the members (i.e., team of
individuals) of different organizations in the case of outsourced projects. In this study, the principal
refers to the buyer organization responsible for designing and implementing interorganizational
controls, while agent refers to the supplier organization responsible for executing the project. The
most appropriate solution is influenced by the kinds of tasks the agent is expected to perform, the
level of environmental uncertainty and the characteristics of the two parties. i.e., particularly their
goals and risk preferences. The framework provided in this study, which focuses on the determinants
of the formal (i.e., behavior and output) and informal (i.e., clan and self) control mechanisms buyers
employ, is depicted in Figure I. Considering the influencing factors identified in these studies and
taking into account characteristics of outsourcing relationships, we have classified the determinants of
control mechanisms proposed in our framework into three broad categories (Bergen et al., 1992;
Heide and Weiss, 1995; Eisenhardt, 1985; Lawless and Price, 1992; Pisano, 1990). We propose that
buyers determine their control portfolios based on (1) task characteristics, i.e., strategic importance of
the development project (P1), geographic dispersion (P2), cultural proximity (P3) and project-related
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knowledge of the buyer (P4); (2) environmental uncertainty, i.e., technological heterogeneity (P5)
and discontinuity (P6) and finally, (3) switching costs, i.e., component purchase concentration (P7),
degree of supplier involvement (P8) and supplier capabilities (P9). Finally, these linkages are
moderated in part by the extent to which shared standardized interfaces are employed for the
collaboration: degree of modularity will affect the strength of these paths (P10).
ANTECEDENTS TO CONTROL MECHANISMS
(1) Task Characteristics
Task characteristics studied in the control literature are broadly included in two categories,
such as behavior observability (i.e., ability to gather information about agent behavior) and outcome
measurability (i.e., ability to specify and track desired outcomes) (Eisenhardt, 1985; Jaworski, 1989;
Oliver and Anderson, 1994; Lawless and Price, 1992). Prior research generally suggests that high
behavior observability facilitates behavior control and outcome measurability has consistently been
found to facilitate outcome control (Eisenhardt, 1985; Jaworski, 1989; Oliver and Anderson, 1994;
Lawless and Price, 1992). Informal controls (clan and/or self) are generally accepted to be used when
behavior observability and outcome measurability are both low (Eisenhardt, 1989; Bergen et al.,
1992). The extent to which the principal is knowledgeable about the task has been cited to have an
impact on the ability to monitor agents’ behavior (Choudhury and Sabherwal, 2003).
Correspondingly, this study incorporates variables that may have an impact on monitoring ability in
global technology outsourcing relationships, such as strategic importance of the component,
geographical dispersion and cultural proximity of relationship partners and finally, project-related
know-how of the buyer.
Strategic importance of the component: This construct represents the impact of the
development or acquisition of the component on organizational productivity for providing advantages
over its incumbent technology and building competitive advantage (Weiss and Heide, 1995;
Robertson and Gatignon 1986). The closer a particular activity of a firm comes to its technological
core, the higher its asset specificity, bringing about reluctance to relinguish control over the activity
and/or the necessity for safeguarding and control mechanisms (Wasti and Liker, 1997; Sanchez and
Mahoney, 1996). As Pfeffer and Salancik (1978) suggest “asymmetry is the true source of power, a
result of unequal concentration of resources or unequal perception of the importance of the exchange”
(p 52). Moreover, the higher the importance of the component or project, the more likely the buyers
will be inclined to protect their tacit technological knowledge against threats of opportunism (Dutta
and Weiss, 1997). This can be achieved by close monitoring (i.e., behavioral control) and/or
consensus building (i.e. clan control), for which output and self control may not suffice. Thus:
P1.a. The greater the strategic importance of the component, the greater the use of behavior control.
b. The greater the strategic importance of the component, the lower the use of output control.
c. The greater the strategic importance of the component, the greater the use of clan control.
d. The greater the strategic importance of the component, the lower the use of self control.
Geographical dispersion: This construct refers to the location of a firm’s operations and
linkages throughout the world. Communication is hindered as spatial separation increase between
partners. A dispersed configuration of a buyer’s supplier relationships across the world may increase
the difficulty and the cost of coordinating and integrating the development, manufacturing, and
promotion of a product (Swan and Allred, 2003). Moreover, socialization, shared experiences, beliefs,
and common goals may be more difficult to achieve between the members of a buyer firm and a
supplier firm, particularly if the supplier is remotely located. Consequently, geographical distances
may hinder the implementation of behavioral and clan control, and thus, may lead the buyer firms to
employ output and self control mechanisms. Therefore:
P2.a. The greater the geographical dispersion of the relationship, the lower the use of behavior
control.
b. The greater the geographical dispersion of the relationship, the greater the use of output control.
c. The greater the geographical dispersion of the relationship, the lower the use of clan control.
d. The greater geographical dispersion of the relationship, the greater the use of self control.
Cultural Proximity: Cultural proximity identifies the distance that exists between the national
cultures of the partners of the alliance (Shenkar, 2001; Kogut and Singh, 1988). A crucial assumption
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of agency theory is that rational managers are expected to act in their own self-interest. This
assumption, i.e., self-interest in the presence of diverging goals between the individual and the
collective, will tend to be emphasized in individualistic countries (Hofstede, 1981; Sharp and Salter,
1997). Moreover, cultural proximity may also facilitate goal congruence between partners, relaxing
the ‘divergence of preferences’ assumption of agency theory (i.e., people are assumed to have
preferences for their own actions which do not necessarily coalign with those of other organization
members or partners) and reducing the need for behavior and clan control. Thus:
P3. a. The greater the cultural proximity of the partner, the lower the use of behavior control.
b. The greater the cultural proximity of the partner, the greater the use of output control.
c. The greater the cultural proximity of the partner, the lower the use of clan control.
d. The greater the cultural proximity of the partner, the greater the use of self control.
Project-related knowledge of the buyer: A knowledgeable buyer will be apt to possess a greater
degree of confidence as well as inclination to specify the exact process the supplier should follow.
Thus, a buyer’s project-related knowledge should facilitate behavior control (Eisenhardt 1985,
Jaworski and MacInnis 1989). On the other hand, a less knowledgeable buyer may rely on the
supplier’s abilities and knowledge, which may reduce the incentive to implement behavior control and
increase the use of outcome control or self-control. However, this lack of knowledge may lead to
vulnerability on the part of the buyer, referred to as information asymmetry in the literature.
Information asymmetry is typical in principal-agent relationships, in which the distribution of
information is likely to be skewed. In the case when buyers have less information with which to
evaluate the supplier’s performance, they incur monitoring costs and face performance ambiguity.
This will reduce the buyer’s ability to assess the supplier’s performance and value of the technology
(Ouchi, 1979). Additionally, if the skills and other characteristics of the supplier cannot be obtained
through substitutes, they may appear irreplaceable in the eyes of the buyers. Since behavior control is
difficult to implement, the buyer may resort to relationship and consensus building with the supplier,
attempting to implement clan control. Hence:
P4. a. The greater the lack of project-related knowledge of the buyer, the lower the use of behavior
control.
b. The greater the lack of project-related knowledge of the buyer, the greater the use of output
control.
c. The greater the lack of project-related knowledge of the buyer, the greater the use of clan control.
d. The greater the lack of project-related knowledge of the buyer, the greater the use of self control.
(2) Environmental Uncertainty
An important determinant of buyer decision making is environmental uncertainty because
particular market conditions impose demands on a buyers’ information processing capacity, are
difficult to predict, and are beyond the control of either principal or agent (Achrol and Stem 1988;
Weiss and Heide 1993). In a general sense, perceived uncertainty in the environment leads to
uncertainty related to a task, i.e., the difference between the amount of know-how required to
complete a task and the amount already possessed. In the context of TI markets, technological
heterogeneity and discontinuity create uncertainty regarding developing the component due to
changes in component specifications, as individuals struggle to understand new and incompletely
specified processes or products (Burkhardt and Brass, 1990; Tushman and Anderson, 1986).
Technological heterogeneity refers to a lack of a common technological standard (Garud &
Kumaraswamy, 1995; Sanchez & Mahoney, 1996). One defining feature of high-technology markets
is the presence of multiple, frequently discrepant product standards and lack of a single dominant
design (Tushman and Anderson, 1986; Teece, 1988; Bourgeois and Eisenhardt 1988). Organizations
may have a higher preference for close monitoring and relationships (that is, behavioral and clan
control) with their suppliers under conditions of high technological heterogeneity, because they want
to minimize the information they need to process to cope with complexity. On the other hand, hightechnology markets also represent considerable uncertainty for buyers due to technological
discontinuity, which represent increasing speed and magnitude of technological change. As stated by
Von Hippel (1986), a buyer’s prior technologies, experiences and capabilities are often ‘rendered
obsolete’ in such markets (p 796). According to Tushman and Anderson (1996), high-technology
markets tend to be ‘competence destroying’ (Weiss and Heide, 1993; Pisano, 1990), which constitute
a shift in the locus of technical expertise from industry incumbents to new entrants. The introduction
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of fundamentally different technologies or competence-destroying discontinuities leads to major
changes in the distribution and power and control. Because of resource limitations, firms turn to and
eventually become reliant on external sources in developing new product and/or process technology
(Kotabe and Murray 1990; Swan and Allred, 2003).
Environmental uncertainty, on the whole, involves not only lack of knowledge of precise cost and
outcomes of different alternatives, but often also lack of knowledge of what alternatives are. This
would increase the specificity of the supplier and the buyer’s dependence, and therefore, the buyer
firm may prefer behavior control (Wasti and Liker, 1997; Wilson et al., 1990). However, in such
conditions, evaluation based on both behavior and outcomes may become ambiguous, leading to use
of informal controls (Lawless and Price, 1992). Thus:
P5. a. The greater the technological heterogeneity, the greater the use of behavior control.
b. The greater the technological heterogeneity, the lower the use of output control.
c. The greater the technological heterogeneity, the greater the use of clan control.
d. The greater the technological heterogeneity, the greater the use of self control.
P6. a. The greater the technological continuity, the greater the use of behavior control.
b. The greater the technological continuity, the lower the use of output control.
c. The greater the technological continuity, the greater the use of clan control.
d. The greater the technological continuity, the greater the use of self control.
(3) Switching Costs
Buyer switching costs may arise as a result of prior commitments (1) to a technology
(transaction specific assets) and (2) to a particular supplier (relationship specific assets). Asset
specificity means the buyer firm has specialized knowledge or tools with little or no use outside the
transaction. Moreover, as a result of the prior transactions and investments, buyers may have invested
in assets that are incompatible with new products. In addition to compatibility problems, buyers may
face switching costs because of established relationships with particular suppliers. The general effect
of both types of switching costs for a buyer is a disincentive to explore new suppliers (Heide and
Weiss, 1995; Swan and Allred, 2003). Consequently, buyers will be motivated to stay in existing
relationships to economize on switching costs. Essentially, switching costs constitute a form of
dependence, which is described by the extent of the replaceability of the exchange partner (Heide and
John 1988; Heide, 1994). Agency theory predicts that the purchase of products or services that cannot
be closely monitored will lead to shirking by suppliers (Wasti and Liker, 1997). As a general rule, the
buyer firm would try to detect opportunistic behavior by the suppliers through heavy monitoring via
behavior control. Knowing that it is being monitored would make the supplier less likely to shirk.
This can also be achieved by building closer ties and socialization through clan control. In the
outsourcing context, three variables, i.e., component purchase concentration, the degree of supplier
involvement and supplier capabilities are proposed to represent the switching costs perceived by the
buyer firm and the extent of irreplaceability of the supplier firm.
Component Purchase Concentration: The presence of open standards for the interfaces
between the various components allows the system components to be sold by multiple suppliers. The
buyer firms need not buy all system components from the same supplies, regardless of whether they
outsource the integration function; instead they may mix and match components from different
manufacturers, reducing their dependence on a single supplier. As a result, the buyer firms’ decision
involves whether to purchase all system components from a single supplier (high concentration) or
from multiple suppliers (low concentration) (Stremersch, and et al., 2003; Tidd, 1995; Wilson, et al.,
1990). The buyer’s position is strengthened as the number of alternate sources of supply is higher and
the transaction costs involved in switching to another supplier are less. Thus, in such conditions, the
necessity of behavior control may diminish and the use of output and self control may suffice
(Eisenhardt, 1985; Pfeffer and Salancik, 1978). Moreover, buyers may also resort to developing closer
ties and implement clan control that foster interdependence with their suppliers and reduce the threat
of opportunism. Hence:
P7. a. The lower the component purchase concentration, the lower the use of behavior control.
b. The lower the component purchase concentration, the greater the use of output control.
c. The lower the component purchase concentration, the greater the use of clan control.
d. The lower the component purchase concentration, the greater the use of self control.
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Degree of Supplier Involvement: Supplier involvement in NPD may be determined by the
extent to which the supplier influences decision-making during the early stages of product
development, the amount of control the buyer retains over the activities; and the frequency of
communication between the buyer and the supplier (Wasti and Liker, 1997). As supplier involvement
increases to earlier stage (i.e., activities concerned with product conceptualization and evaluation) in
the NPD such as idea generation, concept development, design and planning) as opposed to later stage
activities (that is, production, product testing and commercialization), the intangible nature of the
tasks and the diffusion risk of tacit know-how and core technologies increase. Critical information
that leaks out to competitors at the idea generation, design and planning stages through suppliers
utilizing the same or similar designs for different customers can constitute a serious detriment to the
buyer’s competitive power. Consequently, buyers may be concerned about multi-client suppliers’
transmitting such information to their potential competitors and may opt to close monitoring (i.e.,
behavioral control) and building of relational ties (i.e., clan control). In most cases, despite legal
agreements, buyer will have to rely on the supplier’s moral integrity (i.e., self control) not to divulge
both technical and commercial secrets. Therefore:
P8. a. The higher the degree of supplier involvement, the greater the use of behavior control.
b. The higher the degree of supplier involvement, the lower the use of output control.
c. The higher the degree of supplier involvement, the greater the use of clan control.
d. The higher the degree of supplier involvement, the greater the use of self control.
Supplier Capabilities: A supplier’s successful performance history (i.e., reputation) gives the
buyer an indication of the behavioral tendencies of the supplier, reduces the need for behavioral
monitoring and allows the buyer to utilize outcome-based contracts to a greater extent (Wasti and
Liker, 1997). However, factors such as supplier’s development cost advantages, ability and funding to
conduct R&D, skill and competitiveness in product development, number of patents and other
facilities may lead to certain asymmetries in the exchange relationship, thus escalates dependence at
the buyer’s expense (Clark and Fujimoto, 1989; Wasti and Liker, 1997). This will lead the buyers to
resort to building intimate and reciprocal relationships, that is, rely on clan control rather on suppliers’
self control. Thus:
P9. a. The higher the supplier capabilities, the lower the use of behavior control.
b. The higher the supplier capabilities, the greater the use of output control.
c. The higher the supplier capabilities, the greater the use of clan control.
d. The higher the supplier capabilities, the lower the use of self control.
MODERATING RELATIONSHIPS
Degree of modularity: Schilling (2000) defines modularity as “a continuum describing the
degree to which a system’s components can be separated and recombined and the extent to which the
system architecture enable the mixing and matching of components” (p 312). Systems are said to have
a high degree of modularity when their components can be disaggregated and recombined into new
configurations with little loss of functionality (Schilling, 2000; Schilling and Steensma, 2001;
Mikkola, 2003). The components of such systems are relatively independent of one another; however,
require compatibility with the overall system architecture to be easily recombined with one another
(Garud & Kumaraswamy, 1995; Sanchez, 1995; John, et al., 1999).
The degree of modularity
reduces the likelihood of functional mismatches, the buyer firm’s switching costs and its external
dependence. Organizational systems become increasingly modular when firms begin to substitute
loosely coupled forms for traditional tightly integrated systems or structures. Traditional systems
employ constrained optimization methods ‘to obtain the highest level of product performance within a
cost constraint’ (Sanchez and Mahoney 1996, p. 65). Integrated component designs are tightly
coupled in the sense that a change in the design of one component within an integrated assembly of
components will require compensating changes in the designs of other components in the assembly,
making these product architectures difficult, costly, and time-consuming to modify (Orton and Weick
1990; Sanchez and Mahoney 1996).
Modular systems also involve less disclosure of information about data and design plans within
the firm. Modularity, in other words, provides a structure that coordinates the loosely coupled
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activities of component developers, reducing the risk of technology know-how leakage and the need
for close monitoring of agents’ behavior (Sanchez and Mahoney, 1996). Hence, the loose coupling of
components facilitates greater specialization in particular activities, and thus, autonomous
development of components and control of the outputs of suppliers (Orton and Weick, 1990). The
standardized component interfaces in modular product architectures reduce system specificity, that is,
their components can be disaggregated and recombined into new configurations with little loss of
functionality (Baldwin and Clark, 2000; Garud and Kumaraswamy, 1995; Sanchez, 1995). Shared
standards present a form of embedded control that reduces monitoring and enforcement difficulties
and allow outcome measurability (e.g., the assessment of the performance of the components)
(Sanchez and Mahoney, 1996). As a result, in outsourced development projects, modularity provides
a medium that supports the implementation of control portfolios dominated by evaluations based on
project outcomes and/ or the suppliers’ self assessment (Orton and Weick, 1990; Sanchez and
Mahoney 1996). Such systems and structures reduce the necessity to exert managerial authority (i.e.,
behavioral control) to achieve coordination of development processes through enabling the evaluation
of the required outputs (i.e., output control) and the autonomous development of components (i.e., self
control) (Orton and Weick, 1990; Sanchez, 1999). Meanwhile, a buyer may not prefer to outsource a
product or component that is highly customized for that supplier since changes sources for that
product may create high switching costs for the buyer. They may invest in relationship-building (i.e.,
clan control), which bind the supplier and buyer by making them highly interdependent and thus by
increasing the ease of implementation of clan control. Hence, modularity may increase the extent to
which task characteristics, environmental uncertainty and switching costs lead to output, clan and self
control, but decrease the degree to which they enable behavior control. More formally stated:
P10.a. The degree to which task characteristics, environmental uncertainty and switching costs are
associated with the use of behavior control should be significantly weaker as degree of modularity
increases.
b. The degree to which task characteristics, environmental uncertainty and switching costs are
associated with the use of output control should be significantly stronger as degree of modularity
increases.
c. The degree to which task characteristics, environmental uncertainty and switching costs are
associated with the use of clan control should be significantly stronger as degree of modularity
increases.
d. The degree to which task characteristics, environmental uncertainty and switching costs are
associated with the use of self control should be significantly stronger as degree of modularity
increases.
CONCLUSION
Global manufacturing firms have increasingly been engaging in component outsourcing
relationships due to rapid technological developments increasing technological complexity and
amplified international competition leading to high environmental hostility. Their motivation is to
gain adaptability, responsiveness and competitive advantages against their rivals. Another important
trend that has been dominating TI markets is modularization, i.e., use of loosely coupled
organizational structures and standardized product architectures that allow organizational components
to be flexibly recombined into a variety of multiple end-product configurations. The ability to
assemble loosely interconnected organizational components link geographically dispersed component
developers and bring about important leverage in global ventures. Despite these benefits, such
relationships constitute certain costs and threats for the buyer firm. These relationships may lead to
asymmetries in dependence, especially, from the buyer’s perspective, due to task specific qualities
(including knowledge and experience of the partners regarding the task and the costs of obtaining
information related to other party’s behavior), switching costs (including sources of dependencies and
the characteristics of the parties involved) and the perceived dynamics of the technological
environment. These notions entail certain monitoring and coordination mechanisms against
opportunistic behavior of the suppliers and the expropriation of technology know-how and
commercial secrets of the buyers. Meanwhile, the standardized component interfaces in modular
product architectures provide a form of embedded coordination that greatly diminishes switching
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227
costs and dependencies and reduces the need for mechanisms for monitoring and coordination of
development processes. The buyer firm can easily switch between different manufacturers that
perform independent functions, since standard interfaces allow autonomous development of
independent and non-specific components.
Given these qualifications, global component outsourcing with modular systems constitutes a
unique case, thus has been the focus of this study. This paper represents an attempt to gain an
understanding of how firms manage their outsourcing relationships in the technology context drawing
upon organizational control, agency and resource dependency theory. The contribution of this
theoretical examination is to examine the antecedents of the control portfolios, i.e., both formal and
informal control mechanisms buyer firms employ to monitor their suppliers and safeguard themselves
against the mentioned risks. A conceptual framework has been presented, which requires empirical
analysis for further research. Researchers aspiring to empirically test the framework should take into
consideration other possible influential factors, such as the time duration of the relationship since the
asymmetric dependence or the interdependence in the relationship may develop due to the relationspecific investments the parties make over time. Moreover, since the topic proposed in this paper is
novel and has not been widely studied, it is well suited to a qualitative approach, such as field
interviews and case studies.
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