مطالعه اکتشافی بر روی ظهور سیستم های کنترل مدیریت: رسمیت منابع انسانی در شرکت های در حال رشد کوچک

The adoption of management control systems (MCS) is a key element in managing the tension that growth imposes on young growing firms. Despite its importance to a large number of organizations, only recently has the empirical literature devoted attention to the evolution of these systems over the lifecycle of firms [Moores and Yuen, Account. Organizat. Soc. 26 (2001) 351]. This paper builds upon existing management control theory, mostly focused on established organizations, and existing predictions based on extended field observations to explore how these systems are adopted within growing firms. To advance theory, the paper also draws from the entrepreneurship and life cycle literatures. It identifies several variables as drivers of the emergence of management control systems including the size of the organization, its age, the replacement of the founder as CEO, and the existence of outside investors. The empirical evidence, from a database on the adoption of human resource management systems, is consistent with these variables being associated with the adoption of MCS. The paper also provides initial results on how the emergence of various types of management control systems depends on which systems the organization has already adopted.

Existing research taking an organizational view of management control systems (MCS) focuses mostly on the population of medium and large firms where formal systems have long been established and play a major role in structuring the organization and implementing strategy (Langfield-Smith, 1997; Luft & Shields, 2003). Moreover, the typical research design approaches the study of MCS from a cross-sectional perspective rather than taking a longitudinal view.1 Over time, this literature has developed a rich set of variables to explain the cross-sectional variation among different types of MCS as well as among the characteristics of these systems (Hartmann, 2000; Shields & Shields, 1998). The theoretical underpinning, rooted in contingency (Chapman, 1997; Chenhall, 2003) and agency theories (Baiman, 1982) has emphasized a static, cross-sectional view of organizations. However, an important transition point in the life of organizations that is receiving increasing attention is the emergence of MCS (Sandino, 2004). Lack of professional management tools such as MCS has been argued to restrain growth and even to cause the failure of firms (Greiner, 1972 and Greiner, 1998). MCS are important to organizational growth (Flamholtz & Randle, 2000); they liberate top managers' attention from processes that can be controlled by exception and provide them with information when their informal network is overloaded. Thus, understanding how this transition happens is an important research and managerial question. This transition point, when companies move from an informal management approach to the need for formal management tools, is most visible in the population of small growing firms.2 Growing companies are faced quickly with the tensions associated with informal processes and the challenge of successfully mastering the transition into formal control systems. At this point, the dynamic process of transitioning from an informal management to the development of MCS becomes critical to the success of these organizations. So far, our understanding of how these systems emerge in growing firms is captured through experience-based models (Flamholtz & Randle, 2000; Greiner, 1972 and Greiner, 1998; Simons, 2000). Based on life cycle models (Kazanjian & Drazin, 1989; Miller & Friesen, 1984) of the firm, recent research (Moores & Yuen, 2001) empirically identifies the growth phase in the life cycle of an organization as the phase when MCS become important to management. The objective of this paper is to extend current theory and examine empirically variables that are predicted to be associated with the emergence of MCS.3 This exploratory study focuses on those systems associated with human resource management in high-technology firms. Managing human resources is likely to be one of the most challenging tasks that small growing firms face and where MCS may have an earlier role. While not exhaustive of all management control systems in an organization (therefore, the results cannot be generalized to any MCS), systems that are used to manage organizational culture, evaluate and reward employees, and code organizational processes capture a significant and important part of MCS in small growing firms. Moreover, focusing on a subset of MCS allows triangulating the data among different respondents knowledgeable of these systems, in particular CEOs and people knowledgeable about human resource practices. This triangulation has the objective of increasing the reliability of the data at the expense of reducing the scope of MCS that could have been examined, given the knowledge of the managers interviewed. Because firms typically face similar challenges in managing human resources, focusing on these systems allows cross-sectional comparability. While focusing on a subset of MCS limits extrapolation of the results beyond theoretical generalizability (Yin, 1989), previous work has taken this approach given of the benefits associated with it (Abernethy & Lillis, 1995; Gerdin, forthcoming). Because the study relies on the experience of respondents regarding the adoption of MCS, the sample criteria include achieving a certain size over a relatively short period of time. Moreover, given the field nature of the research project a geographical criterion was also imposed. Most of the firms that meet these three criteria are in the high-technology industry, an industry that because of the dynamism associated with it has been an important research field (Burgelman, 2002), and the sample was gathered within this industry to control for potential omitted variables at the expense of limited generalizability of results (Yin, 1989). The rest of the paper is organized as follows. The second section develops the theory behind this exploratory study. Predictions are grounded on existing knowledge in the management control systems and entrepreneurship literatures and variables that existing models of the emergence of MCS have identified (Flamholtz & Randle, 2000; Greiner, 1972 and Greiner, 1998; Simons, 2000). The third section presents the research design. The study is based on a rich database (Baron et al., 1996 and Baron et al., 1999) that includes survey as well as interview information on the human resource practices of a large sample of young, high-technology firms. The fourth section presents the results. The results indicate that both size and age affect the emergence of MCS for human resource management. However, the impact of age decreases with firm size. The evidence is also consistent with the presence of venture capital and the replacement of the founder by a new CEO affecting the emergence of these systems. Further evidence indicates that the replacement of the founder is mostly significant for smaller firms. Finally, the paper provides evidence on how existing control systems affect the adoption of new ones, and which particular systems are adopted earlier. The fifth section suggests future research and concludes.

Understanding the emergence of formal MCS is important to managing growing firms (Moores & Yuen, 2001). An informal approach to the coordination and control of organizational activities becomes harder (and costlier) as the organization grows and formalizing these management activities becomes vital for future growth. The paper identifies an empirical association consistent with the predictions advanced in the theoretical literature. In the early stages of the growth of an organization, size is consistently presented as a key driver of the emergence of control systems. Consistent with this prediction, the results provide evidence on the relevance of size as an explanatory variable. An interesting and unexplained pattern is the association between the percentage of MCS adopted and size. This percentage increases for firms up to a size of 34 people, then it flattens and only starts increasing again when the size of the organization reaches around 75 people. The evidence is also consistent with age being a relevant variable in explaining the emergence of MCS. Age is argued to be relevant through its impact on the variation, selection, and retention processes where the experimentation and learning of an organization is codified over time into formal management systems. The findings are also consistent with arguments suggesting that the replacement of the original founder by a new CEO has a positive impact on the emergence of MCS. Further analysis indicates that this effect is only significant for smaller firms. In other words, the replacement of the founder is linked to the emergence of MCS only for companies that are more likely to need these systems. Founders in these companies may not be able to manage the transition into a more structured organization and a new CEO needs to be brought in to manage the transition. A similar effect is empirically unveiled for the presence of venture capital; this result suggests that these investors may transfer their management experience to the companies they invest in, and perceive the early adoption of management control systems as useful to the growth of the firm. Finally, industry––potentially proxying for environment or production process––and strategy are relevant to the phenomenon. Interestingly, the pattern of behavior across personnel, action, and results control systems is very similar. All the explanatory variables affect the adoption of these systems except for the effect of the replacement of the founder on action control's adoption and venture capital upon personnel control. Such consistency suggests that similar forces affect the adoption of all management control systems. However, the research design did not allow discriminating among these different forces––for instance, the relevance of learning versus the relevance of complexity. This study provides preliminary evidence on the emergence of management control systems, and future research can fruitfully expand these results. First, the study is limited to management control systems to manage human resources and high technology firms; it is not informative about the evolution in non-tech firms, or in other parts of the company, in particular at the top management level. A follow-up study could take a broader perspective and investigate the emergence of MCS to fulfill the planning and monitoring needs of the company or, more broadly, their role in the formulation and implementation of strategy. Planning in these companies has proven to be relevant to pace their evolution (Gersick, 1994), but both theory and empirical evidence are scant on this issue. Furthermore, the study focuses on particular systems; an alternative approach that has been previously used in the literature (Chenhall & Morris, 1986) is to abstract from particular systems and focus on the characteristics of these systems. For example, Moores and Yuen (2001) study how the mix of information, the aggregation and integration of the information, its scope and its timeliness change across life-cycle stages; but they do not address what variables drive these changes. Second, the study documents the relevance of size as well as age and suggests why these variables are relevant; however, it fails to identify how these variables act in organizations. For example, how do growing firms identify their need to adopt MCS? Is it due to process breakdowns? Is it through managers' past experience? Do customers or partners require them? Is it prompted by the need to prepare for an event like an IPO? It is possible that more experienced entrepreneurs or entrepreneurs with large company experience are more likely to adopt MCS faster. Another alternative to develop these systems is to hire a person––such as an HR manager or a CFO––that knows about them and implements them. Furthermore, external influences, not only venture capitalists, but also partners or customers may affect the emergence of MCS. Also the particular circumstances of the organization may require earlier adoption of these systems––for instance, organizations facing cash constraints or evolving business models may rely on structured systems that facilitate the processing of information. The study also fails to identify where the knowledge to design MCS comes from. Does it come from managers' experience? From the board of directors? Or from trial and error? These questions are important to advancing our knowledge, and the current study is silent about them. Extending the current study to non-technology firms also adds to the research agenda. Field study research could be used to answer these questions and potentially build a new theory that conceptualizes the process of MCS emergence. Third, as companies grow, the theory indicates that organizational structure becomes a key variable to explain the emergence of new management control systems. Existing literature has looked mostly at the role of organizational structure in cross-sectional models but not from a longitudinal perspective. Finally, the study ignores performance––a traditional variable in contingency research. Including this variable can be informative in evaluating whether formalization of the coordination and control processes is appropriate and, if so, at which stage is it most appropriate.