Towards a Multivariate Asymmetry Theory of Structural Contingency Misfits

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1 Page 1 of 17 ANZAM 2012 Towards a Multivariate Asymmetry Theory of Structural Contingency Misfits Dr Ben Nanfeng Luo School of Management, Australian School of Business, University of New South Wales, Sydney, NSW 2052, Australia nanfeng.luo@unsw.edu.au Prof Lex Donaldson School of Management, Australian School of Business, University of New South Wales, Sydney, NSW 2052, Australia lexd@agsm.edu.au

2 ANZAM 2012 Page 2 of 17 Towards a Multivariate Asymmetry Theory of Structural Contingency Misfits in Organizational Design ABSTRACT This paper advances a multivariate asymmetry theory of structural contingency misfits, by theoretically extending the recently developed bivariate asymmetry theory to the context of multiple misfits in organizational design. Our analysis indicates that in multiple asymmetrical misfits, an overfit can compensate for an underfit, thereby reducing the total misfit. The reason for this inheres in information-processing being a higher level factor that rules across different contingencies and structural variables involved in asymmetrical misfits. This paper offers the prescription to organizational design that instead of eliminating all the fits, organizations sometimes should maintain or even create overfit. INTRODUCTION Organizational structure has long been an important topic in management and organization research (e.g., Burns & Stalker, 1961; Doty, Glick, & Huber, 1993; Donaldson, 1987; Lawrence & Lorsch, 1967; Meyer & Rowan, 1977; Perrow, 1967) and still enjoys popularity in the recent literature (e.g., Burton, DeSanctis, & Obel, 2006; Birkinshaw, Nobel, & Ridderstrale, 2002; Gulati & Puranam, 2009; Siggelkow, 2002; Siggelkow & Rivkin, 2005; Turner & Makhija, 2012; Wasserman, 2008). One predominant approach to organizational structure design is the structural contingency theory (Donaldson, 2001). The core idea of this theory is that, to design a high-performing organization, organizational structure needs to fit its situational factors or contingencies (e.g., environmental uncertainty, task interdependence, diversification, and size)), while the misfits between structure and its contingencies lead to performance loss. Two types of misfits are overfit and underfit, where the structures have too much and too little structure, respectively, relative to the fitting level as determined by the contingency (Klaas, Lauridsen, & Hakonsson, 2006; Naman & Slevin, 1993). The effects on performance of overfit and underfit were implicitly held in the field of structural contingency theory to be symmetrical, in that these two misfits 1

3 Page 3 of 17 ANZAM 2012 have equally negative effect on performance (Klaas, Lauridsen, & Hakonsson, 2006). However, the recent developments in this area begin to recognize the asymmetry of misfits, i.e., the effects on performance of overfit and underfit are asymmetrical. Specifically, overfit has less negative effect on performance than underfit (Klaas, Lauridsen, & Hakonsson, 2006; Klaas & Donaldson, 2009). Nevertheless, the current asymmetry theory of structural contingency misfits is bivariate, in that it has considered only the misfit of a single structural variable to a single contingency, called here bivariate asymmetry theory. Therefore, only the overfit vs. underfit for one single type of structural contingency misfit is accounted for. This is unsatisfactory because often more than one structural variable is contingent upon a contingency. Therefore, we need to consider the simultaneous misfits of more than one structural variable to a contingency and thus multiple misfits (Burton, Lauridsen, & Obel, 2002, 2003; Donaldson, 2001; Gresov, 1989). For instance, formalization, decentralization, and complexity may all misfit the environmental uncertainty contingency (Donaldson, 2001; Hage, 1980). It is thus of importance to examine whether bivariate asymmetry theory remains sound in the circumstances of multiple misfits. By extending the asymmetry idea to the context of multiple misfits, we are able to explore the potential interaction between multiple misfits and thus move towards a multivariate asymmetry theory of structural contingency misfits. Recognizing the interaction between multiple misfits will also offer critical implications to organizational design practice. As a step towards this goal, in this paper we analyse the multivariate asymmetry theory of the misfits of two structural variables to a contingency. Our analysis indicates that multivariate asymmetrical misfits do not have the same effect on performance as would be given by considering them to be multiple instances of bivariate asymmetrical misfits. This is because that in multiple asymmetrical misfits, an overfit can compensate for an underfit, thereby reducing the total misfit. The reason for this inheres in information-processing being a higher level factor that rules across different contingencies and structural variables involved in asymmetrical misfits. In addition, we also posit that multivariate asymmetry theory may not turn over the hard of structural contingency theory, in that the idea of fit having a higher performance than misfit is still held, i.e., the combination of two fits still perform better the combination of one overfit and one underfit. 2

4 ANZAM 2012 Page 4 of 17 The remainder of this paper is organized as follows. We firstly review the symmetry tradition of structural contingency theory. Then we present the recently developed bivariate asymmetry theory in the literature. After that, we advance a multivariate asymmetry theory of structural contingency misfits by extending the asymmetry theory to the contexts of multiple misfits. We then continue to discuss the theoretical and practical implications of multivariate asymmetry theory, concluding by a summary of the main ideas of this paper. STRUCTURAL CONTINGENCY THEORY AND BIVARIATE ASYMMETRY THEORY Structural contingency theory posits that for the organizational structure to be high-performing, it needs to fit its contingencies (Donaldson, 2001). The major contingency of structure can be environmental uncertainty (Burns & Stalker, 1961; Lawrence & Lorsch, 1967) and technology (Perrow, 1967). For instance, in a rapidly changing environment, organizational structure needs to be organic to gain flexibility, while in a stable environment, organizational structure should be mechanistic to ensure efficiency (Burns & Stalker, 1961). Misfit occurs when the actual structural level is different from the fitting structural level which is determined by the contingency level. There are two types of misfits: overfit and underfit (Klaas & Donaldson, 2009; Klaas, Lauridsen, & Hakonsson, 2005, 2006; Naman & Slevin, 1993). Overfit occurs when a structural level is larger than the ideal amount required by the level of the contingency, while underfit occurs when a structural level is lower than the ideal amount required by the level of the contingency. Traditionally, structural contingency theory holds that the effects on performance of overfit and underfit are symmetrical. More specifically, symmetry means that overfit and underfit have equally negative effects on performance (Klaas & Donaldson, 2009; Klaas et al., 2006). In addition, the symmetry notion is also well reflected in the measurement of misfit as an absolute difference score or a square term between contingency and structural variables, or some variations of these, in the empirical studies of structural contingency theory (e.g., Alexander & Randolph, 1985; Drazin & Van de Ven, 1985; Gresov, 1990; Keller, 1994; Miller, 1992; Naman & Slevin, 1993). These 3

5 Page 5 of 17 ANZAM 2012 measurements of misfit account for the degree of misfits, yet do not consider the signs of misfits (i.e., overfit and underfit). Recently, Klaas and Donaldson (2009) and Klaas et al. (2005, 2006) developed an asymmetry theory of structural contingency misfits, which proposes that overfit and underfit have different negative effects on performance. Specifically, underfit has a stronger negative effect on performance than overfit, i.e., underfit is worse than overfit. Therefore, the effects of misfits on performance are asymmetrical, rather than symmetrical. For instance, facing a moderate level of environmental uncertainty, an organization that has a too centralized structure would be in underfit, whereas another organization that has a too decentralized structure would be in overfit. While both the underfit and overfit are both misfits and thus perform worse than fit, the organization with an overly centralized structure (i.e., in underfit) will perform even worse than the one with an overly decentralized structure (i.e., in overfit). Because this asymmetry theory focuses on the asymmetry of the misfit between one contingency and one structural variable, it is called bivariate asymmetry theory in this paper. The bivariate asymmetry theory is based on the information-processing theory (Galbraith, 1974, 1977; Tushman & Nadler, 1978; see Klaas et al., 2005, 2006; Klaas & Donaldson, 2009). Contingencies, including environmental elements, are treated as the information-processing requirement, while structure is viewed as the information-processing capacity. When informationprocessing capacity matches the information-processing requirement, there is a fit. Otherwise, if information-processing capacity is not equal to information processing requirement, there is a misfit. Underfit occurs when information-processing capacity is lower than information-processing demand. In contrast, overfit happens when information-processing capacity exceeds the information processing requirement. The overfit is able to complete the information-processing task and thus achieve the organisational goal, but with extra information-processing capacity as a waste (Tushman & Nadler, 1978). Thus, it is effective but inefficient (Klaas et al., 2005, 2006). On the contrary, the underfit has insufficient information-processing capacity to process the required amount of information processing, but with low cost (Tushman & Nadler, 1978). Thus, underfit is efficient but ineffective (Klaas et al., 4

6 ANZAM 2012 Page 6 of ). Because effectiveness is more important than efficiency (Hofer & Schendel, 1978), overfit is considered better for performance than underfit (Klaas et al., 2005, 2006). Furthermore, Klaas and Donaldson (2009) addressed the underlying mechanisms of asymmetrical effects. They begin with assessing the effects of overfit and underfit on benefit and cost separately, and suggest that the growth rate of the benefit in underfit is predicted to be more than two times that of the cost, in order to ensure that underfit is more detrimental to performance than overfit. THEORETICAL HOLISM AND MULTIVARIATE ASYMMETRY THEORY The current asymmetry theory of structural contingency misfits is a bivariate theory, in that it focuses on the misfit of one structural variable to one contingency (Klaas et al. 2005, 2006; Klaas and Donaldson 2009). However, a contingency usually requires multiple, rather than only one, structural variables to fit it. For instance, organisational size is the contingency of formalization, decentralization, and functional specialisation (Blau, 1970; Child, 1975; Donaldson, 2001). In addition, task uncertainty requires formalization, participation, and occupational specialisation to fit it (Burns and Stalker, 1961; Donaldson, 2001; Hage, 1980). On the other hand, a structural variable usually has to fit multiple contingencies. For instance, formalization should fit both size and task uncertainty, as shown above. Hence, it is a context of multiple contingencies and multiple structural variables. Therefore, multiple structural contingency misfits exist. The question is whether the bivariate asymmetry theory can be directly applied to contexts of multiple structural contingency misfits. In other words, can knowledge gained on the asymmetrical effects of individual misfit be aggregated to understand cases of multiple structural contingency misfits? To be theoretically holistic and to explore the complexity in contexts of multiple structural contingency misfits, this paper extends the analysis of asymmetry theory to multivariate cases with two misfits/fits. The multivariate asymmetry theory takes an information-processing perspective of organisation (Galbraith, 1974, 1977; Stinchcombe, 1990; Tushman & Nadler, 1978), as the bivariate asymmetry theory. For a long time the information-processing theory has served as a theoretical foundation of organisational design (Burton & Obel, 1998, 2004; Egelhoff, 1982, 1988, 1991; Turner 5

7 Page 7 of 17 ANZAM 2012 & Makhija, 2012; Wolf & Egelhoff, 2002; See Grandori & Furnari, 2008). It is particularly useful in the identification of the fit and misfit relationship between contingency and structure, where contingency and structure are treated as the information-processing requirement and supply, respectively (e.g., Burton et al., 2006; Burton et al., 2002, 2003; Burton and Obel, 1998, 2004; Egelhoff, 1982, 1988, 1991; Keller, 1994; Tushman & Nadler, 1978; Wolf & Egelhoff, 2002). As presented above, the bivariate asymmetry theory also employed information-processing theory as the umbrella theory (Klaas et al., 2006; Klass & Donaldson, 2009). Therefore, the development of multivariate asymmetry theory follows this intellectual tradition. Overall Classification of Combinations of Two Misfits If the structural variables are in misfit, they can be in either overfit or underfit. Considering two structural variables, structural variable A and B (for instance, formalization and centralization), there are four possible combinations of the misfits of these structural variables to the contingency: both structural variables in overfit, both structural variables in underfit, structural variable A in overfit and structural variable B in underfit, and structural variable A in underfit and structural variable B in overfit. To simplify the discussion, we assume that these misfits are at the same level, for example, all being of one unit. When examining the performance of each combination, this paper follows the method of Klaas and Donaldson (2009); that is, decomposing the performance into cost and benefit, and then investigating the cost and benefit of structural variables, respectively, for a given level of contingency. We assume the costs of multiple structural variables to be additive. Then the overall cost of the combination of two misfits is simply the sum of the costs of the individual structural variables, which is in turn determined by the level of the structural variable (Klaas & Donaldson, 2009). This logic is applicable to all the combinations above. Therefore, for each of the four combinations above, its overall cost is the sum of the costs of two structural variables. In this sense, the cost calculation for multiple misfits is consistent with bivariate asymmetry theory. In contrast, for the overall benefit of the combinations of multiple structural variables, it can be separated into two situations, only one of which the bivariate asymmetry theory can apply to. On the one hand, for combinations in which two misfits are of the same types, two overfits or two 6

8 ANZAM 2012 Page 8 of 17 underfits, the overall benefit is simply the sum of the benefits of individual structural variables, which are specified in bivariate asymmetry theory. On the other hand, for combinations in which two misfits are of different types, i.e., one overfit and one underfit, the overall benefit cannot be directly derived from the bivariate asymmetry theory. We will show the latter in details below. The Combination of One Overfit and One Underfit This section show that, due to the supplement of information-processing capacity from overfit to underfit, the combination of one overfit and one underfit has more benefit than the sum of the benefits of these two individual misfits as identified in bivariate asymmetry theory. Given that the combination has the same level of overall cost as the sum of these two misfits in the bivariate manner, the combination of one overfit and one underfit actually yields more overall performance than the simple sum of the performance of individual misfits. Thus, due to differences in the treatment of benefits, multivariate asymmetry theory leads to a different view than does bivariate asymmetry theory. There are two combinations that consist of one overfit and one underfit. For the sake of simplicity, this paper focuses on the one in which structural variable A (e.g., formalization) is in overfit and structural variable B (e.g., centralization) is in underfit. In addition, both structural variables are assumed to be in one unit of misfit. Take, for example, where contingency is at level 3 (thus fitting level of structure is at level 3 as well), the overfit is at level 4 of structure and the underfit is at level 2. The Relative Performance of the Combination of One Overfit and One Underfit in Multivariate Asymmetry Theory: The Supplement from Overfit to Underfit In bivariate asymmetry theory, structural variables are considered separately. As discussed above, while an overfit does not gain more benefit than its fitting level, it has more information-processing capacity than fit (Klaas & Donaldson 2009). The extra capacity of overfit is wasted (Klaas & Donaldson 2009). Therefore, overfit can only attain the same benefit as fit. In this way, the overall benefit of one overfit and one underfit is equal to the sum of the benefits of one overfit and one underfit. 7

9 Page 9 of 17 ANZAM 2012 In the multivariate context, however, we would like to argue that, the overall benefit of the combination of one overfit and one underfit is greater than the sum of the benefits of one overfit and one underfit, because of the supplement from overfit to underfit. The information-processing capacities of misfits work together as a repertoire of information-processing mechanisms of the organisation. According to Galbraith (1977), the information-processing mechanisms and their capacities are added to the organisation s repertoire (p. 53). In this sense, the structural variables tend to satisfy the information-processing requirement of the contingency collectively, rather than separately. Hence, the information-processing capacities of multiple structural variables as a whole should be considered together as to their fit to the information-processing requirement of the contingency. In the current case, overfit of one structural variable and underfit of another should be taken into account jointly in terms of information-processing capacity. The overfit has more than enough information-processing capacity, which opens the door for the transfer of information-processing capacity from overfit. However, this can only occur when there is an underfit that has insufficient information-processing capacity to be in a position to use the extra information-processing capacity of the overfit. That is, when another structural variable is in underfit, the extra information-processing capacity of the overfit can be functional and beneficial. If one structural variable is in underfit, then this structural variable has insufficient information-processing capacity and thus is unable to meet the information-processing requirement of the contingency. In this case, the idle information-processing capacities of the overfit can be utilised as a supplement to this structural variable in underfit. The extra capacity of the overfit is no longer a waste as in the bivariate situation. Instead, it tends to increase the benefit of the structural variable in underfit and thus the overall benefit of the combination. For instance, task uncertainty (as the contingency) imposes certain information-processing requirements on both decentralization and occupational specialisation (as two structural variables) (Hage, 1965, 1980). Assume that decentralization is in underfit to task uncertainty and occupational specialisation is the same degree of overfit. That is, the organisation is over centralized into the higher levels of the hierarchy. The top managers tend to make too many decisions relative to their limited expertise, so decentralized structure in this circumstance has insufficient information-processing 8

10 ANZAM 2012 Page 10 of 17 capacity. However, if the level of occupational specialisation is in overfit, being higher than the level that fits the level of task uncertainty, then these organisational members have more than necessary knowledge and capacities, i.e., having more than enough information-processing capacity. This enables the organisation to make correct decisions in a relatively short timeframe. Organisational members who are experts can make recommendations to top managers, who, by relying on those experts, can make sound decisions. In this way, the overload on top managers that is due to an overcentralized structure can be reduced. Hence, occupational specialisation in overfit has extra information-processing capacities that can make up for the deficiency of the information-processing capacity from the lack of decentralization, that is, the underfit. Thus, the overall benefit of the combination of one overfit and one underfit is greater than the sum of the benefits of these two misfits assessed in the bivariate pattern. However, as stated above, for the cost, two misfits being considered simultaneously will not affect the identification of their overall cost. The overfit of structural variable A incurs more cost, yet the underfit of structural variable B saves certain amount of cost. The overall, net cost is the difference between these two costs, like the sum of the individual costs specified in the bivariate manner. Therefore, compared with the performance of one overfit and one underfit in the bivariate pattern, the overall performance of the combination of one overfit and one underfit in the multivariate manner is greater, due to the benefit increase from the supplementary effect. Hence, when one structural variable is in overfit and the other is in underfit, the performance of the combination of these two misfits is greater than the sum of their individual performance identified in the bivariate manner. In other words, in the multivariate approach, the whole is greater than the sum of its parts. Is multivariate asymmetry theory compatible with Structural Contingency Theory? The combination of one overfit and one underfit versus the combination of two fits The core idea of structural contingency theory is that fit produces more performance than misfit (Donaldson, 2001). In the context of two misfits, this fundamental concept can be expressed as that the combination of two fits has superior performance than any other combination of two fits/misfits. 9

11 Page 11 of 17 ANZAM 2012 As discussed above, the combination of one overfit and one underfit and that of two fits achieve the same level of benefits. Therefore, the relative difference between their performances relies on their respective costs. As we take the performance of fits as the reference, the performance difference is reflected in the overall relative cost of the combination of one overfit and one underfit,. It can be transformed into the question of whether the additional cost caused by the overfit is greater than the cost saved by the underfit. We would like to argue here that, the cost of the structural variable with extra information-processing capacity is usually higher than that of the structural variable with insufficient information-processing capacity. Part of the evidence for structural contingency theory pertains to the relationship between routine and nonroutine information-processing mechanisms (Egelhoff, 1991). The substitution between routine and nonroutine information-processing capacities is a one-way, rather than two-way, path. On the one hand, nonroutine information-processing mechanisms are also capable of processing routine information, yet at a higher level of expense (Egelhoff, 1991). For example, an autonomous team, a nonroutine information-processing mechanism, is also able to perform ordinary, standardised work, but it is not economical because of the typically higher pay of the multi-skilled workers and time spent in group discussions about routine operations that could readily be pre-programmed. Therefore, when this nonroutine information-processing mechanism (i.e., the autonomous team) is in overfit, part of it can be used to process codified information about routine operations, when there is insufficient processing capacity for routine information. Then the overfitting nonroutine informationprocessing mechanism can provide compensatory information-processing capacity to the underfitting routine information-processing mechanism. On the other hand, routine information-processing mechanisms are not able to process nonroutine information, so routine mechanisms cannot substitute nonroutine mechanisms (Egelhoff, 1991). For example, standard operating procedures are not flexible enough to deal with exceptional events. Hence, the overfit of routine information-processing mechanisms cannot provide extra information-processing capacity to the underfit of nonroutine information-processing mechanisms. Moreover, the one-way substitution also applies to the relationship between sequential and reciprocal information-processing mechanisms (Egelhoff, 1991). Specifically, reciprocal information- 10

12 ANZAM 2012 Page 12 of 17 processing mechanisms are able to provide sequential information-processing capacities at a higher cost. For instance, mutual adjustment (Thompson, 1967), where information flows back and forth, is a reciprocal information-processing mechanism. It can also provide top-down planning (Thompson, 1967) by processing the information in a sequential time order, and thus function as a sequential information-processing mechanism. However, in this instance the mutual communication is wasted. However, sequential information-processing mechanisms are not capable of transferring their capacity to satisfy the reciprocal information-processing demand. For instance, top-down planning cannot make organisational members mutually adjust with each other. In sum, the direction of the transfer of information-processing capacity can only be from nonroutine (or reciprocal) to routine (or sequential) information-processing mechanisms. Moreover, this transfer has higher cost compared with processing routine (sequential) information using a routine (sequential) information-processing mechanism. The extra information-processing capacities of overfitting nonroutine (or reciprocal) information-processing mechanisms can provide routine (sequential) information-processing capacities as a supplement to an insufficient level of routine (sequential) information-processing mechanisms. However, this supplement, while achieving the same benefit as two fits, incurs higher cost. The total cost of one overfit and one underfit is greater than that of two fits. Therefore, the performance of the combination of one overfit and one underfit is less than the performance of the combination of two fits. This result is compatible with structural contingency theory, because a fit produces maximum performance. DISCUSSION This paper develops a multivariate asymmetry theory of structural contingency misfits in organizational design, by extending the theoretical discussion of asymmetry theory from a bivariate relationship to a multivariate relationship. Even though it still needs extensive empirical testing, this theory has several theoretical implications. First, it has revealed some unique aspects of multivariate asymmetry theory, especially the supplement of information-processing capacity from overfit to underfit. The extra information-processing capacity of the structural variable in overfit can supplement the structural variable in underfit. This supplementary effect increases the overall benefit 11

13 Page 13 of 17 ANZAM 2012 of the combination of one overfit and one underfit, which in turn increases their total performance. Hence, the overall benefit of the combination of two structural variables should be assessed by taking the information-processing capacities of the two factors together, rather than separately, as in bivariate asymmetry theory. In this sense, multivariate asymmetry theory offers a qualification to bivariate asymmetry theory. Second, the supplementary effect of overfit on underfit in multivariate asymmetry theory is in line with the recent academic interests in the interaction between organisational design elements and its effect on performance (Rivkin & Siggelkow, 2003; Siggelkow, 2002; Van de Ven et al., 2012). Multivariate asymmetry theory indicates that the effects of the structural elements are not independent from each other. A compensatory effect exists between overfit and underfit. Future research should continue exploring the interdependence between design elements in their effects on organizational performance. In terms of practical implications, multivariate asymmetry theory suggests that overfit can serve as an organisational slack. Therefore, instead of eliminating overfit as the common knowledge, organisational designers should actually maintain or even create overfit. The extra informationprocessing capacity of overfit plays a role similar to organisational slack (Child, 1972; Tang & Peng, 2003). Specifically, overfit can supplement underfit has organisational design implications different from those of traditional contingency theory. Different from the prescription derived from traditional structural contingency theory to eliminate or at least reduce all the misfits including the overfits, multivariate asymmetry theory suggests that organisations should intentionally create the combination of overfit and underfit by setting up one or more overfits when the organisation is growing. The creation and maintenance of the overfit of one structural variable is to proactively prepare for the assistance of the possible underfits of other structural variables when the organization is growing (Donaldson, 1987). Organisations can then overcome the structural liability of growing organisations; in this way, organisations are able to reduce their overall degree of misfits and thus lose less performance in the long term. The less performance loss compared with other companies may in turn support organisational growth and help the organisation gain competitive advantage. 12

14 ANZAM 2012 Page 14 of 17 CONCLUSIONS This paper sought to develop a multivariate asymmetry theory of structural contingency misfits in organizational design. By focusing on situations with two structural contingency misfits, it found that multivariate asymmetry theory has unique properties, different from those of bivariate asymmetry theory. Whereas the performance of most of the combinations of two misfits/fits can be readily derived from bivariate asymmetry theory, the combination of one structural variable in overfit and another structural variable in underfit is a special case. According to multivariate asymmetry theory, the combination of one overfit and one underfit performs better than the performance predicted by bivariate asymmetry theory, due to the supplement of information-processing capacity from overfit to underfit. Nevertheless, multivariate asymmetry theory is likely to be compatible with the structural contingency theory, in that combination of the overfit and underfit performs still worse than the combination of the fits (the hard core of contingency theory). It offers the surprising prescriptions to organisational designers that in some contexts organisational designers should maintain or even create overfit, instead of eliminating it. 13

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