Management Control and the Decentralization of R&D
Brigitte EckerJoanneum Research
Sander van TriestUniversity of Amsterdam
Christopher WilliamsUniversity of Western Ontario
The authors investigate organizational conditions influencing the allocation of decision rights made by headquarters of multinational corporations (MNCs) to their foreign R&D subsidiaries. The authors draw on the logic of management control theory to build their conceptual model and then develop this model using arguments from the R&D and time use literatures in order to test the direct and indirect effects of advanced R&D processes within the subsidiary. They find that control theory makes correct predictions in terms of three organizational conditions, namely, research nature, information asymmetry, and interdependencies, but not in terms of social controls. In addition, the authors uncover a significant interaction between research nature and advanced R&D processes that indicates a breakdown in control logic in situations of high time pressure and intense R&D effort. Their study extends the body of literature on organizational conditions that influence how R&D decision rights are allocated in the MNC by drawing attention to the task environment in the locations where R&D is performed.
Keywords: decentralization; management control; multinational corporations; research and development
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Acknowledgments: This article was accepted under the editorship of Talya N. Bauer. We thank Paul Beamish, Jasmijn Bol, Igor Goncharov, and seminar participants at EIBA 2008 in Tallin, EIASM 2008 in Brussels, AAA 2009 in New York, and at Copenhagen Business School.
Corresponding author: Sander van Triest, Amsterdam Business School, University of Amsterdam, Plantage Muidergracht 12, 1018 TV Amsterdam, The Netherlands.
In this article, we study the control of research and development (R&D) activities in multi-national corporations (MNCs), and specifically the extent to which decision rights are allocated to subsidiaries that perform these activities.1 The process of conducting R&D is idiosyncratic, unstructured, and tacit, and it involves trial and error (Clark, 1985; Hill, Martin, & Harris, 2000; Kim, Park, & Prescott, 2003; Saviotti, 1998). Because of these characteristics, R&D activities are not straightforward to control. The received logic is that individuals are more creative when “their supervisors engage in supportive, noncontrolling behaviors [and] their work is evaluated in a developmental, nonjudgmental fashion” (Shalley, Zhou, & Oldham, 2004: 942). In a meta-analysis, Damanpour (1991) finds that innovation is negatively related to centralized decision making and to formalization. More recently, Siggelkow and Rivkin find that “studies report a positive correlation between decentralization and innovation and, in general, view the associa-tion as evidence that greater decentralization leads to greater innovation” (2006: 780). According to Merchant and van der Stede, “Many organizations operate on the belief that research scientists are highly professional and will control themselves better than the organiza-tion could by implementing formal controls” (2007: 183). This literature suggests that the allocation of decision rights to those performing R&D is an effective way of controlling R&D.
Meanwhile, internationalization of R&D activities has been occurring for decades and shows no signs of letting up (“The New Masters of Management,” 2010; OECD, 2007). According to Goldman Sachs, global R&D investment is driven mostly by the corporate sec-tor and over the past decade has grown most prolifically outside of the G7 countries (which averaged 3.2% growth per year), particularly in countries such as China (20%) and Korea (8%; Gilman, 2010). MNCs have increasingly moved their R&D operations to be closer to human capital and networks of innovation.2 This internationalization of R&D creates prob-lems for corporate managers in terms of how to influence behavior in R&D units around the world. Indeed, when placing R&D activities abroad, managers need to make a choice as to the amount of decision rights they allocate to these subsidiaries. Nobel and Birkinshaw state that the level of autonomy given to R&D units is “probably the most important aspect of control, [since] it indicates the extent to which head office managers actively influence deci-sions made in the R&D unit” (1998: 483). It is by no means a foregone conclusion, however, that all foreign R&D subsidiaries will be given decision-making autonomy to the same degree (Cheng & Bolon, 1993). As pointed out by Gerybadze and Reger, “International dispersion of [R&D] activities does not necessarily lead to greater decentralization of . . . control” (1999: 264). The level of decentralization of authority in international R&D is a control choice that varies from firm to firm (Brockhoff & Schmaul, 1996).
Our study into the question of what influences the assigning of decision rights to foreign R&D units builds on a line of research that focuses primarily on organizational rather than external conditions. Birkinshaw, Nobel, and Ridderstråle (2002) find R&D unit autonomy to be predicted by system embeddedness, that is, the extent to which knowledge in the unit is contextually embedded. Birkinshaw (2002) also shows how an R&D unit with knowledge that is low on mobility would benefit from high autonomy. Nobel and Birkinshaw (1998) show how the role of the unit influences the degree of decentralization, with local R&D adap-tors being most suited to the decentralization of decision making. Luo (2006) finds R&D autonomy to be directly related to the task performed, with development tasks more likely to
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require autonomy than pure research due to greater information-processing requirements for the former. Using resource-based and embeddedness arguments, Asakawa (2001) argues that resource accumulation through increasing centrality in local R&D networks leads to greater autonomy for the overseas R&D unit.
We extend this literature by examining the decentralization decision from the logic of management control theory (Eisenhardt, 1985; Ouchi, 1979) augmented with a time use per-spective (Bluedorn & Denhardt, 1988; Hall, 1983). According to management control logic, decentralization is a central element of an organization’s design (Brickley, Smith, & Zimmerman, 2001; Love, Priem & Lumpkin, 2002; Pavitt, 1991). While the choice to internationalize the firm’s R&D can arise for many reasons (Kuemmerle, 1999; von Zedtwitz & Gassmann, 2002), once this choice has been made the firm will have to decide how to control those activities (Anthony & Govindarajan, 2004: 1), including how much to decentralize decision making. Pavitt (1991: 45) argues that this is difficult in practice; an optimal level of decentralization in R&D is hard for corporate managers to determine.
The management control literature suggests that decentralization is a trade-off between the superior knowledge of local managers and the loss of control at firm headquarters (Acemoglu, Aghion, Lelarge, van Reenen, & Zilibotti, 2007; Christie, Joye, & Watts, 2003). The established view suggests that the nature of the research (i.e., basic vs. applied; Rockness & Shields, 1984), information asymmetry between headquarters and subsidiary (Baiman, Larcker, & Rajan, 1995), interdependencies between subsidiaries (Milgrom & Roberts, 1992), and socialization of employees (social controls; Ouchi, 1979) all influence the delegation of decision making to foreign R&D operations. We extend this logic to include advanced R&D processes undertaken within the foreign subsidiary: a variable hitherto neglected in the management control literature but nevertheless a prominent consideration for R&D managers (Gerybadze & Reger, 1999).
Using questionnaire survey data elicited from heads of 123 Austrian R&D subsidiaries of MNCs, we find a large variance in the level of R&D decentralization: Not all R&D subsidiar-ies receive the same amount of decision rights from their headquarters. This variation is explained in part by the hypothesized effects of the nature of the research activities, information asymmetry, and interdependencies. However, the result for social controls is unexpected: Our data indicate that higher decentralization is associated with less use of training, interunit travel, and rotation policies. Thus, the management control theory prediction that any loss of control at headquarters through higher decentralization is offset by increasing socialization activities does not hold for our sample. Furthermore, advanced R&D processes negatively impact decen-tralization: When subsidiaries are involved in more time-compressed and complex R&D, fewer decision rights are given to the subsidiary. We also identify a significant interaction between research nature and advanced R&D processes: For highly intensive R&D, management control logic breaks down with respect to the impact of research nature on decentralization.
Our main contribution is to extend the body of literature that examines how organizational conditions influence allocation of decision rights to geographically dispersed R&D (e.g., Luo, 2006; Nobel & Birkinshaw, 1998).3 We do this by analyzing operational conditions at the unit using management control theory. We also provide a way of extending this logic by consider-ing how activities are performed in the subsidiary (i.e., their nature and the degree to which they can be considered advanced R&D processes). The interaction between research nature
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and advanced R&D processes previously has not been considered in relation to decentraliza-tion of R&D in MNCs. Our contribution is to show how advanced R&D processes in remote R&D units amount to a special condition that dampens the effect of the nature of the research on decentralization. This angle is new and underlines the importance of time use theory in management control problems where time pressures are of concern to the organization.
Theory and Hypothesis Development
Management control theory encompasses a broad literature relating to planning, organizing, and controlling activities within the firm (Giglioni & Bedeian, 1974). The key thrust of this theory is implementation of strategy in terms of design and use of systems of organizational control (Anthony & Govindarajan, 2004; Merchant & van der Stede, 2007). Decentralization, or the allocation of decision rights to lower level managers, features prominently in this theory (Abernethy, Bouwens, & van Lent, 2004; Love et al., 2002). As benefits of decentral-ization, Brickley et al. (2001) see the effective use of local knowledge, conservation of man-agement time, and training and motivation for local managers. Costs of decentralization include incentive problems, coordination and failure costs, and less effective use of central informa-tion. The trade-off between costs and benefits means that choosing the appropriate level of decentralization is a major issue for management.
For R&D, this trade-off is complicated by the fact that science and technology research involves activities that are difficult to control through formal mechanisms, that is, mechanisms that involve rules, standard procedures, and budgetary targets (e.g., Langfield-Smith, 1997: 208). R&D is an innovative activity: The R&D process is unstructured, involving experimentation and creativity from individuals with specialized expertise (Kim et al., 2003: 331). Indeed, accord-ing to the creativity literature, innovation is associated with high levels of authority at the unit level: Formal, centralized control is viewed as impeding innovative activities that require autonomy and employees’ intrinsic motivation (Amabile, 1998; Davila, Foster & Oyon, 2009; Shalley et al., 2004). In his seminal article on management control, Ouchi (1979: 844) uses research as the example of an activity that cannot be controlled by “rational” forms of control (behavioral or output controls); instead, the organization needs to rely on social (clan) controls. Merchant and van der Stede state that “many organizations operate on the belief that research scientists are highly professional and will control themselves better than the organization could by implementing formal controls” (2007: 183). Hill et al. claim that R&D activities are “difficult to incorporate into organizational control systems” (2000: 565) , while Kim et al. (2003: 336) find that formalization and centralization are not effective in coordinating and controlling R&D. The idiosyncratic nature of R&D means that the application of results controls or action controls is difficult. Although it is not uncommon for R&D activities to be viewed as a profit center or to be outsourced, which requires formal controls (Hill et al., 2000; Howells, Gagliardi & Malik, 2008), Kerssens-van Drongelen, Pearson, and Nixon (2003: 760) find that performance measure-ment in R&D profit centers or independent R&D units is limited to items like billable hours, hit rate on project bids, or size of the forward workload. These items reflect the input (or input usage) rather than output in terms of performance, innovations, productivity, or profit contribu-tions (cf. Ulset, 1996).
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Management Control Theory and R&D Decentralization
According to management control theory, the trade-off between knowledge transfer costs and loss of control lies at the heart of explaining decentralization decisions (Acemoglu et al., 2007). The costs of knowledge transfer increase with the specificity of information (Jensen & Meckling, 1992). If the unit’s activities are difficult to measure, knowledge transfer is more costly since performance measures are not always available, nor is it clear what information should be given to the unit due to low programmability of activities (Acemoglu et al., 2007; Eisenhardt, 1985). Furthermore, if decisions require high levels of information about the environment of the unit, this increases knowledge transfer costs. If there is more local knowl-edge at the unit, local management will be better placed to both gather and interpret this knowledge (e.g., Melumad, Mookherjee, & Reichelstein, 1992). Thus, to economize on knowledge transfer costs, a firm will delegate more authority if the local activities are more difficult to measure and prescribe and if there is more information asymmetry.
The downside of delegating authority, however, is a loss of control (Acemoglu et al., 2007). Unit managers can use delegated authority to make decisions that are not in the firm’s best interest: They may not have all the relevant information to reach an optimal decision, or they may act in their own self-interest (Eisenhardt, 1985). Both the likelihood and the costs of suboptimal decision making increase with intrafirm interdependencies because unit actions will impact other organizational units more often and/or to a greater extent (Abernethy et al., 2004; Bushman, Indjejikian, & Smith, 1995). The likelihood of self-interested behavior will decrease with the extent of shared values, that is, the degree to which employees internalize organizational goals (Eisenhardt, 1985; Parsons, 1956). To reduce the expected costs of the loss of control, a firm will delegate authority to a lesser extent in case of higher interdependencies, but social controls in the form of shared values will enable delegation. Thus, the positive and negative effects of decentralization lead to four factors impacting the decentralization choice: the type of activity performed in the unit (we refer to this as research nature in our study), information asymmetries, interde-pendencies, and social controls.
Research nature. R&D can be categorized on a continuum ranging from basic research (i.e., earlier stage, more exploratory, highly uncertain) to late-stage development (more applied, much less uncertain; Luo, 2006; Nobel & Birkinshaw, 1998; Rockness & Shields, 1984). Research nature influences the applicability of management control because tight controls (detailed prescriptions, frequent monitoring, and detailed performance measure-ment) are less effective in basic research where activities are less programmable and measur-able than in late-stage development (Eisenhardt, 1985; Ouchi, 1979; Rockness & Shields, 1984). The ineffectiveness of these controls for basic research means that headquarters’ managers will assign more decision rights to the R&D unit. As applied research activities are less uncertain, the need for more decision rights at the R&D unit is reduced. Hence,
Hypothesis 1a: The more basic the R&D activities, the higher will be the decentralization of decision rights relating to R&D activities in the unit.
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Information asymmetry. Reducing the distance to markets for human capital through inter-national R&D (e.g., Sanna-Randaccio & Veugelers, 2007) has implications for how decision rights are allocated. Information asymmetry arises between headquarters and the R&D subsidiary because local managers will have specific knowledge that is not available to their superiors (Abernethy et al., 2004; Christie et al., 2003; Jensen & Meckling, 1992). Reducing information asymmetry incurs costs through information exchange and monitoring activities and also entails opportunity losses, as the unit may not be able to react quickly to local infor-mation (Brickley et al., 2001: 296). In situations of higher information asymmetry, allocating decision rights to the unit will enable better unit performance (Andersen, 2004; Birkinshaw et al., 2002). Hence,
Hypothesis 1b: The higher the information asymmetry between an R&D unit and the other units of the firm, the higher will be the decentralization of decision rights relating to R&D activities in the unit.
Interdependencies. Interdependencies refer to the extent that business units are dependent upon each other, for example, one being a supplier to another or both working on the same development project (Fisher, 1994; Thompson, 1967). When interdependencies increase, coordination becomes more important, and thus decision rights should be handed down limitedly (Abernethy et al., 2004; Fisher, 1994; Milgrom & Roberts, 1992). Doing this mitigates the risks of suboptimization: units making decisions that benefit their own perfor-mance at the cost of the organization’s overall performance. In international firms, increased centralization is associated with greater interdependencies between subsidiaries because of increased information-processing demands: Centralization helps overcome the problem of information overload (Egelhoff, 1982). Hence,
Hypothesis 1c: The higher the interdependencies between an R&D unit and other units of the firm, the lower will be the decentralization of decision rights relating to R&D activities in the unit.
Social controls. Social controls emphasize internalization of values (Parsons, 1956), strong company cultures (Deal & Kennedy, 1982), reducing opportunistic behavior (Ouchi, 1980), and understanding and internalizing organizational goals (Eisenhardt, 1985). A common set of values enables subsidiaries to use their knowledge “to pursue the interests of the MNC as a whole and not just their partisan interests” (Nohria & Ghoshal, 1994: 494). Socialization mechanisms can “build inter-personal familiarity, personal affinity, and convergence in cogni-tive maps” (Gupta & Govindarajan, 2000: 479) and allow subsidiary managers’ interests to be aligned with those of the corporation (Gupta, Govindarajan, & Malhotra, 1999: 211). Higher use of social controls allows for more decentralization because headquarters’ manag-ers are more comfortable that employees receiving decision rights share the values of the wider corporation and have knowledge and skills that are aligned to the goals of the corpora-tion (Nobel & Birkinshaw, 1998: 488). Hence,
Hypothesis 1d: The higher the use of social controls at the R&D unit, the higher will be the decen-tralization of decision rights relating to R&D activities in the unit.
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Extending Management Control Theory in the R&D Context
We now extend the logic of management control theory to incorporate the notion that how R&D work is conducted in the subsidiary influences decentralization choices. Our interest here is not the nature of R&D in the sense of basic versus applied research (see Hypothesis 1a) but, rather, how the R&D unit performs these activities. Our particular focus is on the use of advanced practices such as simultaneous engineering, parallel R&D, and/or conducting R&D on a 24-hour basis. There are two reasons for this focus. First, such practices represent an advanced set of capabilities in the R&D subsidiary. Various scholars in the international management and innovation literatures have highlighted the potential relationship between subsidiary capabilities and decentralization (Gassmann & von Zedtwitz, 1999; Ghoshal & Bartlett, 1988). Second, these practices imply a decision made by the firm to compete under time pressure. R&D-intensive industries are characterized by a high rate of technological development and change, and firms are likely to resort to time-based competition (de Meyer & Mizushima, 1989). We develop competing hypotheses for the direct and indirect effects of advanced R&D processes based on these two lines of reasoning.
Advanced R&D processes. Ghoshal and Bartlett’s (1988) groundbreaking study of the deter-minants of innovation in overseas MNC subsidiaries identifies a strong correlation between local resources and local autonomy. Although this often-cited study is potentially less relevant, as it covers a broader set of functions than R&D (de Meyer & Mizushima, 1989), the logic that the state of R&D advancement (i.e., possessing and using advanced resources and capabilities) is associated with decentralization of decision making to the unit is supported in various R&D-specific studies. For example, Gassmann and von Zedtwitz (1999) stress the importance of decentralized communication and self-coordination when advanced R&D is carried out.
Simultaneous engineering occurs in group R&D activity where a number of operational units of the organization are involved in R&D projects, working on new product and produc-tion technology at the same time (Davila & Wouters, 2004; Shenas & Derakhshan, 1994; Sohlenius, 1992). Similarly, parallel R&D refers to separate R&D teams (or units) working in parallel on a joint project, normally at an early stage of the life cycle, that are less likely to require production engineering input. The R&D literature suggests that when an R&D unit is involved in these types of activities, decentralized communication and self-coordinating become critical (Gassmann & von Zedtwitz, 1999). New developments in communication and information technology also enable continuous R&D, or “24-hour R&D” (e.g., Inkpen & Ramaswamy, 2006: 75). When an R&D unit is sophisticated enough to become involved in 24-hour R&D, it is likely to require operational decision-making authority as headquarter managers will not be available at key times. Hence,
Hypothesis 2: The more advanced the R&D processes in the unit, the higher will be the decentral-ization of decision rights relating to R&D activities in the unit.
An alternative logic drawn from the time management and time use literature (Bluedorn & Denhardt, 1988; Hall, 1983) suggests that the use of advanced practices in an R&D unit are
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associated with centralization of decision making. When the R&D unit uses advanced practices, such as 24-hour R&D and simultaneous engineering, it is effectively addressing a need to perform under time pressure (Sohlenius, 1992). Time pressure in group projects comes with certain costs. For example, Bluedorn and Denhardt (1988: 309-310) state that the quality of decision making reduces as time pressure increases. In an R&D setting, scientists usually adopt a long-term time horizon (von Zedtwitz & Gassmann, 2002), and this may be at odds with the time horizon adopted by applied engineers and R&D managers. Andrews and Farris (1972) find that the relationship between time pressure and performance in science and engineering groups is only positive up to a point: When the pressure desired by scientists is out of step with the pressure applied, performance will suffer. Thus, there are circumstances in which time pressure in R&D becomes counterproductive. These hazards are likely to encourage headquarter manag-ers to maintain centralized control over remote R&D operations in order to ensure that any decision to increase advanced R&D processes in the unit does not have an adverse outcome.
This line of argument is also reinforced in the R&D literature. De Meyer and Mizushima (1989) show that time pressure to complete R&D projects is associated with a tendency toward centralization. Gerybadze and Reger also argue that when the innovation regime in the company is dynamic and fast, centralization is more likely because of the need to “secure direct and undistorted access to the most critical resources” (1999: 264). Related to this line of thinking, Pearce and Papanastassiou argue that an overseas lab with an advanced, special-ized mandate is especially “vulnerable to external decision-making concerning the evolution of the overall networked programme” (1999: 38). Thus, the parent company maintains strong power to limit the role of the specialized R&D unit, and this becomes especially acute when the level of advancement is associated with high financial cost. In support of this, Baiman et al. (1995) suggest that relative importance is negatively related to decentraliza-tion: If a business unit is more important to the firm, headquarters will delegate less author-ity. This leads to the following alternative expectation of the relationship between advanced R&D processes and decentralization:
Hypothesis 2alt: The more advanced the R&D processes in the unit, the lower will be the decentral-ization of decision rights relating to R&D activities in the unit.
Moderating effects of advanced R&D processes. We extend our logic by considering the impact of advanced R&D processes on the relationship between the nature of R&D activities (i.e., basic research vs. applied development) and decentralization since both are character-istics at the R&D task level. Following the competing hypotheses (2 and 2alt), we also pro-pose competing hypotheses for this moderating effect.
In the first instance, we assume that advanced R&D processes in the unit amplify the effect that basic research in the unit has on the need to decentralize. As argued above, basic research is less programmable and measurable, reducing the effectiveness of centralized controls. In advanced R&D processes, such basic research not only is less programmable and measurable but also is more likely to require intense local communication and self-coordi-nation (Gassmann & von Zedtwitz, 1999). This is particularly so if the R&D projects are of the simultaneous or parallel kind (Davila & Wouters, 2004; Shenas & Derakhshan, 1994; Sohlenius, 1992). Similarly, if R&D work is conducted on a 24-hour basis, the operational
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influence of headquarter managers becomes limited. Thus, the combination of an activity that is not easily programmed or measured, along with an operational need for this activity to be coordinated locally, means a strengthening in the decentralization of decision rights. Hence,
Hypothesis 3: Advanced R&D processes positively moderate the relationship between research nature and the decentralization of decision rights relating to R&D activities in the unit.
An alternative argument is that advanced R&D processes in the unit dampen the effect that basic research in the unit has on the need to decentralize. In this logic, we draw again on the time management and time use literature (Bluedorn & Denhardt, 1988; Hall, 1983): The pres-ence of advanced R&D processes in the subsidiary represent a strategic emphasis for the unit to perform under time pressure (de Meyer & Mizushima, 1989). Because of the risk that lower quality decisions will be made by those working under time pressure (Bluedorn & Denhardt, 1988), as well as the issue that time pressure applied to scientists can become counterproductive (Andrews & Farris, 1972), the requirement to decentralize simply because the core activity in the unit is less programmable becomes muted. In addition, if we follow the logic that advanced R&D processes represent a cost that needs to be monitored closely by those making the investment (Baiman et al., 1995), the fact that the research is basic is of secondary importance. Therefore, our alternative expectation of the impact of advanced R&D processes on the relationship between research nature and decentralization is as follows:
Hypothesis 3alt: Advanced R&D processes negatively moderate the relationship between research nature and the decentralization of decision rights relating to R&D activities in the unit.
Method
Sample
An MNC develops R&D capabilities outside of its country of origin in order to seek new knowledge for product and technology development, enabling it to build and sustain competi-tive advantage on a global basis (Dunning & Narula, 1995; Kuemmerle, 1997). The question of decentralization is especially relevant for the R&D function of the MNC (Nobel & Birkinshaw, 1998). Our analysis is based on a survey of R&D subsidiaries of MNCs operating in Austria in 2002. We started by conducting 10 interviews with CEOs, R&D managers, and information technology managers of Austrian subsidiaries of foreign MNCs. These interviews were con-ducted in German. The purpose of these initial interviews was to explore R&D subsidiary roles and control issues within networks of R&D. The sample frame of all foreign MNCs with R&D activities in Austria was then constructed using data assembled via the Hoppenstedt database and the Austrian register of companies. The Hoppenstedt database includes data on the owner-ship, as well as the activities, of MNCs in Austria. Two criteria were used: (1) that the units were majority owned by a foreign MNC (i.e., the MNC had at least 50% equity share of the unit) and (2) that the subsidiary contained a dedicated R&D function. These criteria were used in order to select cases of geographically dispersed R&D units in which the responsibility for
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control choice lies with the MNC. Next, we contacted the subsidiaries by phone as a prenoti-fication aimed at increasing the likelihood of response (van der Stede, Young, & Chen, 2005).
The sample frame consisted of 272 R&D unit heads. Questionnaires in German were sent by postal mail, with a follow-up mailing after two months. In total, we received 197 responses (72%), of which 138 filled in questionnaires, for a response rate of 51%. Because of missing values on several items, we had to drop 15 further responses for the analyses reported in this article. Therefore, the final sample consists of 123 observations, for a final response rate of 45%. These R&D subsidiaries belonged to 123 different MNCs. We tested for response bias on subsidiary characteristics (number of employees, age of subsidiary, mode of establishment) and on the dependent variable (the decentralization construct, reported below) for early versus late responders and found no significant differences. The sample contained R&D units from a range of technology-intensive sectors (electronics, telecommunications, pharmaceuticals, chemicals, automotive, etc.) and 16 different home countries (i.e., headquarter locations). Among these, Germany, the United States, Switzerland, and the Netherlands were the most frequent.
Measures
Decentralization. Decentralization in the MNC refers to the extent to which authority has been delegated to units of the firm. The dependent variable is measured through six question-naire items capturing the influence of headquarter management on decisions relating to R&D activities in the subsidiary (Gates & Egelhoff, 1986; Gordon & Narayanan, 1984; Moers, 2006). The level of decentralization is established by asking the respondent about the loca-tion of six key decisions with respect to the subsidiary’s R&D activities: the appointment of the R&D unit’s manager, the formulation of standards for technical documentation at the R&D unit, the development of new products and/or processes at the R&D unit, participation in transnational projects, investments in the R&D unit, and approval of the R&D unit’s bud-get. This is done on a scale of 1 to 5 from headquarters alone (1) to subsidiary alone (5), with combined decision making in between. The six items were averaged to create the decentral-ization measure, which had a Cronbach’s alpha of .84. The actual range of 1.00 to 5.00 covers the complete theoretical range.
Nature of R&D activities. Decentralization is likely to be associated with R&D activities that are more basic (cf. Evans & Davis, 2005). We asked respondents to categorize their R&D activities. Respondents could allocate a total of 100% across four categories: basic research, development of new products and services, development of existing products and services, and customer service (Håkanson & Nobel, 1993: 395; Rockness & Shields, 1984: 169). Research nature was measured as a weighted sum of these categories, with basic research receiving a weight of 4, development of new products 3, development of existing products 2, and customer service 1, leading to a theoretical range of 1.00 to 4.00. So if a respondent indicated 10% basic research, 30% new product development, 20% existing product development, and 40% customer service, it received a research nature score of 2.10. In this way, higher scores represent more basic research. The actual range is 1.10 to 4.00.
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Information asymmetry. Direct measurement of information asymmetry is difficult since there is a theoretical possibility that information asymmetry is an endogenous variable: If the subsidiary has more decision rights, there is less need for communication (Aghion & Tirole, 1997). Following this logic, decentralization is naturally related with information asymmetry: The subsidiary is allowed to make more decisions on its own; it does not need to keep head-quarters informed of these decisions. Therefore, rather than measuring information asymme-try through communication frequency or asking who is more informed about the subsidiary’s activities (e.g., Abernethy et al., 2004), we utilize the importance of the geographic scope of the mandate. Studies of MNC subsidiary roles have highlighted increased information asym-metry in subsidiaries that have local mandates (e.g., Birkinshaw & Morrison, 1995; Roth & Morrison, 1992). In Roth and Morrison’s terms, a subsidiary with a global mandate has a worldwide responsibility for a complete set of product activities; this requires that the subsid-iary work “with headquarters to develop and implement strategy” (1992: 716). This acts to reduce information asymmetry between subsidiary and headquarters. “Local implementers,” on the other hand, arise in situations where responsiveness to national differences is important (Birkinshaw & Morrison, 1995). Gassman and von Zedtwitz (1999: 240) referred to R&D units in polycentric configurations having a strong local market sensitivity but having little incentive to share information with other units, thus increasing information asymmetry.
We capture information asymmetry by asking respondents to indicate the principal geo-graphic markets for their R&D units: local, Europe, and outside Europe. We expect informa-tion asymmetry will be higher in local mandates, since local knowledge will be more important in this case. We measure the importance of local activity as follows: If the mandate is only local, we score a 3; if the mandate is local and either Europe or outside Europe, we score a 2; and if the mandate covers all three levels, we score a 1. If the mandate does not include local, we score a 0 (this happens for 79 out of 123 respondents). In nontabulated results, we repeat our analysis using a dummy variable with any local orientation scoring a 1 and otherwise 0; the inferences remain identical.
Interdependencies. We measure interdependencies as the relative importance of intraorga-nizational flows of products and services at the subsidiary level (Nobel & Birkinshaw, 1998). Respondents were asked to indicate the share of purchases from other units of their firms and the share of sales to other units. To simplify the questionnaire, respondents were offered vari-ous ranges (0%, 1-5%, 6-10%, 11-20%, 21-40%, 41-70%, 71-100%). We took the midpoint of each range to come to a percentage score for interdependency. Since the largest range was 71-100%, the maximum theoretical score on this construct is 0.85, obtained if both intrafirm purchases and sales are in the range of 71–100%. The observed range is from 0.00 to 0.70.
Social controls. Following Nobel and Birkinshaw (1998), on a scale of 0 (does not happen) to 5 (very important), we asked for the importance of the following four items: personnel rotation programs, job training programs, personal visits by the R&D unit’s employees to other units, and personal visits from employees of other R&D units to the unit. First, Merchant and van der Stede (2007: 83, 90) note that personnel rotation and job training are important social controls. Second, we use personal visits because these are an important mechanism by
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which shared values are established within the organization (Edström & Galbraith, 1977). The four items were averaged into a construct, which had a Cronbach’s alpha of .81, with the actual range of the resulting construct covering the complete theoretical range of 0.00 to 5.00.
Advanced R&D processes. We use four items to capture advanced R&D processes: simul-taneous engineering, parallel R&D, 24-hour R&D, and participation in international projects. Simultaneous engineering refers to the degree of R&D unit involvement with other operational units of the organization in R&D projects (Davila & Wouters, 2004; Shenas & Derakhshan, 1994). Parallel R&D refers to separate R&D units working in parallel on a joint project. New developments in communication and information technology also enable continuous R&D, or 24-hour R&D (e.g., Inkpen & Ramaswamy, 2006: 75). The score on these items is averaged on a scale of 0 (does not happen) to 5 (very important), with the actual range covering the whole theoretical range of 0.00 to 5.00. The Cronbach’s alpha of .62 is acceptable for a new construct.
Control variables. We include a range of control variables that have been identified in prior research as having an influence over control choices within the firm. First, we might expect subsidiary size and age to play a role (Gates & Egelhoff, 1986). We control for this using the natural log of the total number of employees at the subsidiary, as well as the log of the num-ber of years since the establishment of the subsidiary. Second, we might expect prior perfor-mance of the R&D subsidiary to influence decentralization, as the parent company rewards good performance with additional investment (Frost, Birkinshaw, & Ensign, 2002). We account for past performance of the subsidiary by including the log of the total number of patents filed by the subsidiary in the past five years. Third, greenfield investments may offer more possibilities to structure the organization and management of unit development and integration (e.g., Barkema & Vermeulen, 1998). We capture the mode of establishment of the subsidiary using a dichotomous variable for greenfield versus acquisition. Fourth, cultural distance between home and host countries can influence managerial attitudes toward risk in host countries. We use Kogut and Singh’s (1988) cultural distance measure to account for any effects caused by differences in national culture between the Austrian unit and its foreign headquarters. Fifth, we account for industry effects by including two industry dummies for the most knowledge-intensive industries, one for electronics and telecommunications and one for pharmaceuticals and chemicals (Kuemmerle, 1999). Finally, we control for the difference in national technological capability between the home country of the MNC and Austria. For this, we use the difference in the ArCo Index (Archibugi & Coco, 2004) for the country pair. A higher score on this variable means that the MNC’s home country is more technologically advanced. We also run untabulated regressions with the World Economic Forum Technology Index as a measure of national technological capability; inferences remain similar.
There is a risk of common method bias from using the single-respondent self-reported ques-tionnaire. We checked for common method bias using Harman’s single-factor test (Podsakoff & Organ, 1986). With the scale items entered into an unrotated factor analysis, the variance for the first factor was 25% (out of 69% variance for all emerging factors having an eigenvalue greater 1). We therefore expect that common method bias will not affect the interpretation of the results.
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Table 1 presents descriptive information and bivariate correlations. Most important in this table is the variation in the measure of decentralization. As indicated in the method section, the actual range covers the complete theoretical range. This implies that there are R&D-active subsidiaries that have full control over their decisions but that there are also subsidiaries indicating that headquarter management makes all decisions. Overall, firms differ substantially in the amount of decision rights they allocate to their R&D-active subsidiaries.
The measure of the nature of the R&D activities also shows a broad range, with a minimum of 1.10 (implying 90% customer service activities and 10% existing product development) and a maximum of 4.00 (only basic research). The scores on the individual research types (untabulated) show that development is the most frequent type of research, and basic research is the least frequent. The remaining independent variables all show good variation in their standard deviations and ranges.
With respect to the bivariate correlations, we see that correlations of decentralization with research nature and interdependencies have the expected sign and are significant, while infor-mation asymmetry is positively correlated but not significant. Unexpectedly, social controls are negatively associated with decentralization. Advanced R&D processes is negatively related. Finally, all control variables show lower correlations than the main independent variables do.
Main Findings
To analyze our hypotheses, we use an ordinary least squares (OLS) regression with robust standard errors, presented in Table 2. Robust standard errors provide for more conservative (higher) standard errors (e.g., Wooldridge, 2002: 57); our statistical inferences are identical when using regular OLS standard errors. To facilitate interpretation of the interaction models, we report regression results using standardized independent variables (Jaccard, Turrisi, & Wan, 1990). In column 1, we analyze the effects of the control variables. All are insignificant and thus do not explain the decentralization decision by themselves.
The regressions testing our hypotheses (Models 2-4) have R2 values of .25 to .31 and adjusted R2 values of .17 to .20 due to the relatively high number of independent variables given the number of observations. This is comparable to the results of Moers (2006: 914) and Abernethy, Bouwens, and van Lent (2010: 12), who report adjusted R2 values of .15 to .19 for the explanatory variables in regressions analyzing decentralization. We find that for all models, the management control–based independent variables have the expected sign at a significance level of .05 or less (with research nature significant at p = .08 in Model 4), except for social controls, which is highly significant (p < .01) but in the opposite direction. Advanced R&D processes in Model 3 is significantly negative at p = .07. The interaction Model 4 leads to a significant negative direct effect of advanced R&D processes and a negative coefficient on the interaction of advanced R&D processes and R&D research nature. The maximum VIF
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in all models is 1.74, indicating that multicollinearity will not affect our interpretation of the results.
The results are as follows. First, more basic research is associated with higher decentral-ization. If research activities are less programmable, the unit gets more freedom to enable the creativity that is required. Next, interdependency limits decentralization: The extent to which the unit is integrated with other units impacts the decentralization of the R&D activ-ities. The significant positive coefficient on the importance of local activities supports the argument on information asymmetry. Contrary to our expectations, social controls are significantly negatively related with decentralization; that is, more decentralization is asso-ciated with less use of social controls. Finally, the control variables are all insignificant. This strengthens our argument that operational characteristics are more important than higher level characteristics such as size, cultural distance, or national technological capabil-ity in the decentralization decision.
Figure 1 illustrates the effect of the interaction between advanced R&D processes and research nature. This graph has been constructed using the coefficients from Model 4, with all variables taken at their mean except for the two interacted variables. The graph shows that for advanced R&D processes, the nature of the research does not impact decentralization. Advanced R&D processes appear to “override” management control logic in this respect.
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The increasing geographic dispersion of R&D activity around the world (i.e., the interna-tionalization of R&D) raises an important question for MNCs relating to how decision rights are allocated to remote R&D units once they have been set up abroad. The traditional view argues that R&D unit managers require freedom to make key decisions; R&D is idiosyncratic and difficult to control from afar. The current study provides evidence that R&D units vary in terms of how much freedom they have to make decisions and that this freedom is dependent on internal organizational factors. Thus, consistent with management control theory (Anthony & Govindarajan, 2004; Giglioni & Bedeian, 1974; Merchant & van der Stede, 2007), we find strong support for hypotheses relating to research nature, information asymmetry, and inter-dependencies. In terms of these three variables, there is nothing special about R&D. However,
Figure 1Impact of Advanced R&D Processes on the Relationship
Between Research Nature and Decentralization
2.7
2.9
3.1
3.3
3.5
3.7
3.9
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4.3
Service Basic research
Research Nature
Dec
entr
aliz
atio
n
Less advanced R&D processes
More advanced R&D processes
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in terms of social controls, on the one hand, and advanced R&D processes within the unit, on the other, our results challenge and extend management control theory. This leads us to three key discussion points.
First, the results suggest that decentralization to R&D units can be largely explained from a management control perspective, despite the idiosyncratic nature of R&D activities. If the specific R&D activities in question are more early stage and exploratory (i.e., so-called basic research), more decision rights are allocated to the managers involved. Too much centraliza-tion for this type of R&D stifles creativity and innovation and reduces the effectiveness of the exploratory science. R&D managers heading units that undertake basic research are offered the opportunity to decide for themselves how their budgets are allocated, which transnational projects to take part in, and how local processes and technical documentation are formulated. As new discoveries are made and new scientific information comes to light, the ability to readjust resource deployments locally in order to respond and exploit new knowledge is important. Similarly, our results suggest that information asymmetry is managed by placing decision rights with the R&D subsidiary. Where the unit’s mandate is purely local, integration with local actors becomes a necessity. As a consequence of this, increased levels of local information occur. Centralizing decision rights in this scenario is counterproductive and inef-ficient. There is a strong risk that differences in levels of information regarding the local environment will mean that central decision makers will make poor decisions that do not reflect the needs of the unit. In terms of interdependencies, we find interdependences to be associated with lower decentralization. Coordination among units that are highly dependent on each other requires a centralization of decision making. We conclude that as far as these variables are concerned, there is nothing special about R&D.
Second, from a management control theory perspective, the finding regarding social con-trols is unexpected. We expected social controls to be associated with higher decentralization but find the opposite. This highlights a potential limitation of management control theory within an international R&D context. Normative integration is much harder and more costly to implement in international organizations than domestic ones. Cultural and institutional differences across countries may prevent the efficient transfer of tacit knowledge that informal communications should allow (Szulanski, 1996). Our finding may also be explained by the argument that transferring and rotating staff across countries and continents has a financial cost that will encourage MNCs to look for alternative ways of communicating and sharing knowledge with a remote R&D subsidiary. Developments in information technology enable a much faster transfer of management information on current activities and performance, reducing the need for informal, social controls (Dewett & Jones, 2001).
Third, we show how aspects of R&D policy implemented at a local level (namely, research nature and advanced R&D processes) have an important implication for theorizing on the issue of control within international R&D. The most striking finding in the current study relates to the interaction between these variables: For time-compressed and advanced R&D processes, management control logic no longer applies with respect to the relationship between research nature and decentralization. Such an advanced R&D process environment in a foreign sub-sidiary has been set up for a reason: high scientific yield and performance in terms of tech-nological breakthroughs and patenting. This type of R&D operation may require substantial capital investment by the corporation, and expectations from headquarters will be high. For
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these reasons, subsidiaries that are involved in more time-compressed and sophisticated R&D stand out in terms of importance. As a result, fewer decision rights are given to the subsidiary, even if the subsidiary is performing more basic, early-stage research (cf. Argyres & Silverman, 2004). This extends the management control perspective in relation to activities performed by the unit: It is not just what the unit does that influences control choice; it is also the inter-action between what the unit does and how it does it.
Implications, Limitations, and Future Directions
One implication of our research is to reinforce the existing call to stop viewing R&D as a “monolithic” process (Davila et al., 2009): Managers incorporate the nature of R&D and other subunit organizational contingencies in their control choices. This qualifies the tendency in the creativity literature to suggest that control “kills” creativity (Amabile, 1998). In fact, the sug-gested optimal control mechanism from the literature is social controls (Kim et al., 2003; Ouchi, 1979), but we find that social controls are not used as a mechanism to counter the possibilities of divergence of interest between headquarters and subsidiaries. On the other hand, the view sometimes voiced in the management literature that R&D activities need to be centralized due to the difficulties in establishing formal controls (Hill et al., 2000) is not reflected in our findings. If anything, the implication is to focus on the observable characteristics of the R&D subsidiary.
Another implication for researchers relates to the question of whether allocating decision rights to dispersed R&D units is linked in any way to the original decision to internationalize. Our approach of disentangling internationalization and decentralization adds clarity to prior research on control of foreign R&D, which uses dispersion and decentralization as interchange-able terms (Howells, 1990). We emphasize that these are quite different phenomena. Decentralizing R&D operations may accompany an initial relocation or expansion of R&D operations abroad, but it does not have to. As capabilities in remote operations develop, organizational contingen-cies play an ever-increasing role in the need to reassess the appropriateness of the control mechanism. The lack of extant literature on this topic points to new research possibilities.
There are a number of limitations in the current research. First, the data collection was only carried out in one, relatively small, developed country. Second, firms were chosen only from technology-intensive manufacturing sectors; the service sector was not included. This sampling strategy will limit the generalizability of the findings. Third, our data collection instrument utilized self-reported measures. Fourth, we did not control for whether the outcome of the underlying R&D projects in the subsidiaries were more product oriented or process oriented. Future research could address these issues by including more sectors and countries and con-ducting detailed case studies of R&D decentralization in different empirical settings. Indeed, a useful continuation of the current research would be to identify which types of control mechanisms substitute for social controls within decentralized R&D, given our finding on social controls. Another extension would be to examine the fit between the organizational contingencies discussed here, the delegation of decision rights, and performance of overseas R&D subsidiaries. Furthermore, future research could investigate the potentially complex interactions between organizational factors that influence the trade-off between local knowl-edge and loss of control at headquarters and policy choices—such as how intense and time-compressed R&D should operate—which are ultimately implemented at a local level.
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1. We use the term decentralization to refer to the delegation of decision-making authority (or decision rights) by superiors to lower levels in the organization. Some studies refer to this as autonomy.
2. No longer are home countries of multinational corporations (MNCs) the only incubating environments for the firm’s innovation, and game-changing innovations may arise from any host country in which the MNC has access to intellectual and human capital (Florida, 2003). Therefore, the geographical proximity of innovation capa-bility to headquarters is not as important as it once was.
3. Other streams of literature have focused on strategic factors such as industry contingencies, corporate struc-ture and other parent company characteristics, entry mode, and local context characteristics (e.g., Howells, 1990; von Zedtwitz & Gassmann, 2002; Young & Tavares, 2004).
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