A central concern within the field of organizational design and configuration is the study of the relationship between structure, innovation and organizational performance (Cyert & March, 1963; Lawrence & Lorsch, 1967; Mintzberg, 1979). This concern goes back at least to the work of Burns and Stalker (1961) on mechanistic and organic forms and prior to that with Weber's (1947) consideration of corporate bureaucracy. A major driver has been the discovery of the most appropriate organizational structure to foster innovation and survival in the long run (Greenwood & Hinings, 1988; Lam, 2005). This has resulted in a number of organizational typologies (Galan et al., 2012) from the multidivisional structure (Chandler, 1962), to the adhocracy (Mintzberg, 1979), to the radical, and very unstable spaghetti organization (Foss, 2003). However, and despite the recently renewed interest in organizational design (Greenwood & Miller, 2010; Schreyogg & Sydow, 2010), the literature is, with few exceptions (see, for example, Siggelkow & Levinthal, 2003), still inconsistent in answering the question of what dimensions of the structure have the most significant impact on both innovation and performance in the long run (Badir et al., 2009).
In this pilot study we seek to expand the categories of analysis to organizational types that have been overlooked in recent simulation studies of organizational design. To address this problem, we employ an experimental design - an NK modeling technique to simulate the behavior of organizations composed of many interacting elements. This technique proposed by Kauffman (1969; 1993) for understanding mutational processes in biological systems has proven more than adequate in other contexts, including in organizational design (Levinthal, 1997; Rivkin & Siggelkow, 2007). We aim to understand how search activity in organizations is best structured to achieve performance improvements, and discuss some benefits and costs linked to mixed forms of organization not considered in previous simulation models. The model is built around two dimensions of organizational structure: the degree of centralization of decision-making and the interdependency among decisions. The degree of centralization reflects the locus of decision-making power and refers to the extent to which authority is distributed among different units in an organization (Miller & Droge, 1986). The interdependency among decisions reflects the level of complexity of the system (Kauffman, 1993; Simon, 1962) and describes the many parts and processes that a system must coordinate to achieve some measure of overall success (Kauffman & Levin, 1987).
In line with previous studies (cf. Rivkin & Siggelkow, 2007), we simulate two organizational types which have been previously studied: a "Block-Diagonal" structure (Siggelkow & Levinthal, 2003), in which decisions are made independently in two divisions; and a "fully interdependent" structure (Kauffman, 1993), which is modeled using a matrix where all decisions interact with each other in a single firm with no divisions.
We also establish a different set of relationships within a firm structure with two divisions, so as to study two new designs. One termed "semi-decentralized" struc- ture, in which each division makes proposals to their headquarters which selects the combination of decisions with the highest overall payoff for the firm (Wall, 2010). The second we refer to as an "individualistic" structure (Press, 2007), in which divisions seek to maximize their own partial fitness (utility), where the winning division forces the other to follow its lead, resulting in a potential win-lose situation, which cannibalizes the competencies of the other division. Game theory assumptions are employed to simulate the individualistic structure. This simulation design, and its concomitant results, provide an extension of previous research on organizational design.
The creation of the new ideas and innovations that support competitiveness and growth (Tripsas, 2009) rely on the ability of an organization to explore and find new opportunities, or high peaks in existing or new landscapes (March, 1991). In accordance with its ecological derivation, a landscape is an "area that is spatially heterogeneous in at least one factor of interest" (Turner et al., 2001, p. 3). The purpose of exploration; "is to find and occupy a high spot on this landscape, i.e., to select a combination of choices [i.e., decisions, activities] that, together, are highly successful." (Siggelkow & Rivkin, 2005, p. 104).
The achievement of successful exploration however poses an organizational dilemma as managers seek to unleash the power of exploration at the lower levels of an organization in order to promote innovation, while maintaining strategic focus requires managers to preserve organizational unity in decision-making to bring to fruition future developments (Siggelkow & Rivkin, 2006). Failure to strike a balance between these two agendas can lead to incompatible and internally competitive actions (Nickerson & Zenger, 2002) hampering performance (O'Reilly & Tushman, 2007). Part of this challenge is that organizational choices made to bring efficiency gains can also hinder a firm's ability to develop new knowledge (Tripsas & Gavetti, 2000).
Prior research on organizational design has shown that several elements found in more mechanistic forms of organization, including hierarchical structures, centralized decision-making and formal controls and communication channels, are likely to enhance operational efficiency but also produce risk aversion as firms avoid uncertain possibilities in favor of actions that have produced positive results in the past (Lam, 2005; Miller et al., 2006). Conversely, more organic structures include several elements that appear to foster creativity, complexity and adaptability, such as decentralized decision making, a lack of formally defined tasks and loose coupling systems, but at the cost of efficiency (Sheremata, 2000). The latter suggests that the coherence of an organizational design "is not accidental" (Greenwood & Hinings, 1988, p. 295); but that "there are several models of organization with differential efficiencies depending on the nature of the work and the types of tasks to be performed" (Litwak, 1961, p. 181).
While formal structure has been measured in a variety of dimensions (Price & Mueller, 1986), there appears to be a consensus that centralization (the distribution of authority within an organization), formalization (the degree of work standardization) and complexity (the degree of specialization, and number of hierarchical levels within an organization) are the basic dimensions of structure (Tsai, 2002; Van de Ven, 1976). Thus, we draw on the work of Van de Ven et al., making centralization and complexity the focal aspects of this paper.
Centralization refers to the concentration of authority or decision-making power (Miller & Droge, 1986), and points to whether the locus of authority and decisionmaking lies in the higher or lower levels of the organizational hierarchy (Jansen et al., 2006). In research on multidivisional organizations, centralization has focused on the dichotomous relationship between the relative degree of influence or control exercised by the corporate headquarters and the individual organizational units in relevant decision-making processes (Tsai, 2002).
The notion of centralization has long been a consideration in organizational design theorizing, from Weber's notion of bureaucracy, to the work of the Aston group (Pugh et al., 1969), and to contingency theory (Lawrence & Lorsch, 1967). Most of the work within this tradition argues that organizations must centralize to attain superior efficiency (Adler & Borys, 1996). Centralized power in the hands of a few reduces diversity in decision-making (Siggelkow & Rivkin, 2005), thereby increasing speed, and control (Sheremata, 2000).
Centralization may however constrain a firm's ability to experiment as there is less latitude for new strategic choices (Jansen et al., 2006). Centralization may also induce conformity with rules and established routines, making people "less receptive and supportive of ideas that might deviate from the status quo" (Lubatkin et al., 2006, p. 652), whereas the associated vertical decision process may reduce the felt need for interactions to solve problems collaboratively (Miller, 1987). The result may generate structural inertia (Hannan & Freeman, 1984), constraining an organization's ability to respond to new opportunities, and thereby to change, grow, and compete (Oldham & Cummings, 1996).
Decentralization, on the other hand, appears best suited to igniting creativity (Nonaka & Konno, 1998; Zammuto & O'Connor, 1992), since it eliminates organizational constraints to freedom in the conduct of work (Amabile et al., 1996). Decentralization is beneficial to promote innovation and thus adaptability to unstable and more turbulent environments (Benner & Tushman, 2003). Yet this comes at the cost of efficiency.
Accordingly, several studies have observed that extreme degrees of decentralization may have negative effects on innovation (Van Looy et al., 2005). Extreme...
Speed, coordination and individualistic behaviors: a pilot NK modeling study to investigate the moderating effects of organizational structure on performance in individual firms.
|Author:||Cornejo, Pablo E. Pinto|
|Position:||Articulo en ingles|
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