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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|2737||2009||26 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Accounting, Organizations and Society, Volume 34, Issues 3–4, April–May 2009, Pages 322–347
Recent theoretical and empirical work indicates that management control systems (MCS) are an important element in enhancing innovation. We extend this research thrust examining the adoption of MCS in product development, arguably one of the business processes where innovation plays a major role. Using a sample of 69 early-stage entrepreneurial companies, data are collected from questionnaires and interviews with each of the CEO, financial officer, and business development managers pertaining to product development MCS. We examine seven different systems: project milestones, reports comparing actual progress to plan, budget for development projects, project selection process, product portfolio roadmap, product concept testing process, and project team composition guidelines. We address three distinct questions: (1) What are the reasons-for-adoption of these systems? The nature of our sample allows us to trace back to the adoption point and develop a set of reasons-for-adoption from the analysis of the data. While MCS fulfill certain roles as described in the literature, these reasons-for-adoption are distinct from these roles. Results indicate that certain events lead managers to adopt these systems and address the challenges that they face. They include contracting and legitimizing the process with external parties and internal reasons-for-adoption such as managers’ background, learning by doing, need to focus the organization, or reaction to problems. (2) Are these reasons-for-adoption associated with differences across companies in the time from their founding date until these systems are adopted (time-to-adoption)? Prior research has looked at the covariance of various organizational variables with this timing; this study goes a step further by looking at the effect of different reasons-for-adoption on this timing. Our evidence finds an association between these two variables. (3) Are these reasons-for-adoption relevant to performance? We find that the reason-for-adoption is associated with the on-time dimension of product development performance.
Formal management control systems (MCS) have traditionally been associated with mechanistic organizations (Burns & Stalker, 1961). These systems support the periodic execution of the same routines with little if any changes. Their relevance to the innovation process – a process associated with uncertainty, with unknown links between inputs and outputs, with exceptions, and with outputs that are often hard to evaluate – is less clear. Ouchi (1979) used a research department to illustrate clan control where social norms substitute for formal management systems. Mintzberg’s separation of planning and managing (Mintzberg, 1976) and Quinn’s logical incrementalism (Quinn, 1978) also highlight the limitations of traditional MCS. A fundamentally different perspective is that these systems may provide important discipline to help manage uncertainty. Recent theoretical developments offer various concepts that support the need for formal management control systems (MCS) in uncertain settings.1 For instance, the distinction between coercive and enabling bureaucracies (Adler & Borys, 1996) suggests that MCS may be instrumental to innovation. Gavetti and Levinthal (2000) present a learning model where companies that jointly rely on planning and learning by doing are predicted to perform better in uncertain environments compared to alternative strategies. Thus, forward looking efforts typically associated with MCS complement fast reaction to new information to improve how organizations deal with uncertainty. Zollo and Winter (2002) argue that the essence of dynamic capabilities is adaptive routines – including information-based routines. Simons (1995) interactive systems concept can have an explicit role in sparking innovation around strategic uncertainties. For the most part, recent empirical evidence also indicates that innovation processes may gain from the presence of MCS. Abernathy and Brownell (1999) use Simons’ model to examine the use of budgets “as a dialogue, learning and idea creation machine” during episodes of strategic change. Cardinal (2001) reports an association between control and performance in both radical as well as incremental innovation projects in the pharmaceutical industry.2Ditillo (2004) describes MCS as a key element in knowledge intensive firms.3 Similarly, Chapman (1998) presents evidence consistent with the relevance of these systems in uncertain environments. Based on a sample of 69 technology-based early-stage companies, the paper examines the adoption of MCS within an organizational process where innovation has a pivotal role: the product development process.4 The focus on product development led to sampling from technology-based firms.5 Product development is a key aspect in these firms. If MCS are important to managing innovation, this sample of companies will be (on average) ahead in their use.6 Our objective of learning about the adoption of MCS led to adding the early-stage criteria. The focus on the adoption stage (rather than the evolution of existing MCS) suggested studying companies that are going through the transition from birth to early-stage when the MCS are adopted for the first time. We conceptualize MCS in our field research as formal systems particular to product development including: project milestones, budget for development projects, reports comparing actual progress to plan, project selection process, product portfolio roadmap, product concept testing process and, project team composition guidelines. Accordingly, this paper is built at the intersection of two main research thrusts. (a) The study examines the product development process – where innovation has a significant role. Building on existing theory on the relevance of MCS to innovation processes, it provides new evidence to advance our conceptual understanding of why MCS are an important aspect of innovation management. In particular, it highlights the difference between the reasons-for-adoption of MCS in innovation processes and the objectives that these systems pursue. (b) Our sample of entrepreneurial companies also speaks to the literature on the emergence of MCS; thus, the conceptual development around the adoption of MCS in product development processes can be the basis for empirical work to understand the adoption of these systems in other organizational processes in early-stage companies. The study speaks to the adoption of MCS in a process traditionally associated with innovation. Because the study is framed within early-stage entrepreneurial companies to capture the adoption event, it does not speak to the evolution of MCS in established firms. We examine three related research questions: (1) why MCS are first adopted in the product development process? In particular, we present various reasons-for-adoption of MCS, (2) what is the relationship between these reasons-for-adoption and speed of adoption? and (3) what is the relationship between reasons-for-adoption and a key product development performance measure (on-time development)? Fig. 1 illustrates these research questions. To inform these questions, the literature offers arguments on why organizations adopt MCS. These arguments have an early antecedent in Greiner (1972). The first stage of his growth model deals with the emergence of MCS. It describes the emergence of MCS as a crisis of leadership where: “increased number of employees cannot be managed exclusively through informal communication (…) and new accounting procedures are needed for financial control.” Yet this argument was not researched in depth for several decades.7Cardinal, Sitkin, and Long (2004) observe that much of the literature has “virtually ignored the origins and evolution of organizational control” (p. 411). Recent research has started to address the origins and evolution issue. The two main streams of research are: (a) case studies that describe the rise (and fall in some cases) of controls over the early years of startup companies (Cardinal et al., 2004) and (Granlund & Taipaleenmaki, 2005), and (b) large-sample based studies of the association between MCS evolution and organizational variables such as age, size, company strategy, and the presence of venture capital (Davila, 2005, Davila and Foster, 2005, Davila and Foster, 2007 and Sandino, 2007). The present study probes the reasons that led to a differential MCS adoption for 69 technology-based early-stage companies in the product development management systems area. Product development systems are especially important for high-technology companies given the pivotal role that product innovation plays in their growth. Our research design combines qualitative data from over 200 interviews and quantitative data gathered using questionnaires. It also triangulates the data using three different informants per company. Access to qualitative descriptions of why MCS were adopted allows us to develop a framework of reasons why such systems are adopted. We identify two external based reasons (labeled legitimize and contract) and four internal reasons (labeled manger’s background, need to focus8, chaos, and learning). One benefit of the structured qualitative analysis of interviews is the rich description we can report to illustrate the six different reasons-for-adoption. The second and third research questions build upon the framework of reasons-for-adoption developed in the first question. In particular, the second research question examines how the six different reasons for adoption influence the speed of adoption of product development systems. Speed of adoption is measured using time elapsed from the start of the company to the time reported for the adoption of the project milestones’ system.9 We find that the reasons-for-adoption associated with manager’s background, chaos, legitimize, need to focus, and contract are found to be significantly related with faster adoption vis-à-vis a subset of our sample of companies with higher reliance on informal product development control systems. The third research question probes whether the same six different reasons for MCS adoption influence a key product development performance measure (on-time development). Our results indicate that when MCS are adopted because of the manager’s background, product development performance is enhanced. Because our sample comprises early-stage companies, their level of MCS adoption and product development performance are likely to have significant variation. The sample selection is designed to capture these companies’ transition phase into MCS; moreover, their product development processes are still evolving – for instance, through the adoption of MCS – and thus expected to show different performance levels. This fact allows us to study the relationship between reason-for-adoption and speed of adoption and performance. The paper brings new evidence to the growing literature on the relevance of MCS to enhance the performance of firms employing organic structures (Kalagnanam & Lindsay, 1999) and in particular to innovation processes (Bisbe and Otley, 2004 and Granlund and Taipaleenmaki, 2005). The main findings include: (1) we identified six reasons for MCS adoption. Two reasons-for-adoption are externally related: legitimizing the company and contracting with external parties. This evidence highlights the role of external parties in shaping management systems internal to the firm (Pfeffer & Salancik, 1978); an influence that is typically associated with financial reporting. We also identify four internal reasons-for-adoption, two of them proactive: managers’ background, focus the attention of the organization on executing the strategy (need to focus), and two reactive: react to problems, and code learning (associated with formalizing repetitive yet non-formalized processes). Our evidence also provides qualitative data consistent with MCS roles identified in the literature including stimulating dialogue and idea creation; controlling execution through diagnostic systems; and stabilizing an environment that, by the nature of the innovation process, is already rich in opportunities. (2) Using these six new reasons for-adoption categories, the study then examines the impact of different reasons-for-adoption on the speed of adoption of MCS. We find that managers’ background is associated with the fastest time-to-adoption. (3) Finally, we find that MCS adopted to code learning or because of the managers’ background is associated with better on-time development (an important dimension of product development performance). The next section (‘Conceptual underpinnings and literature linkages’) of this paper reviews the literature on innovation and MCS. We highlight how the literature has emphasized the different roles that MCS may have; thus, what purpose do MCS fulfill in organizations. Yet, these roles are not necessarily associated with the reasons why MCS are adopted. These reasons are associated with events that do not have a one-to-one relationship with the roles that these systems play. Therefore, a particular event may trigger the adoption of a system with a particular role in a certain environment and a system with a different role in another environment. The reasons why systems are adopted are distinct from the roles that the systems ultimately play. This section also presents the evolution of the literature from an initial notion that innovation and MCS were incompatible to the new broader support for MCS having a positive role in promoting innovation. ‘Field research design’ presents the research design. The study is based on a multi-case, multi-method research design. We sent questionnaires and interviewed three managers in each of 69 high-growth technology entrepreneurial companies. This design allows for triangulation of the data and combining qualitative and quantitative data to develop a framework and use statistical generalization of the findings. The following three sections present the results to our three research questions. ‘Discussion’ relates these findings to the existing literature and discusses limitations and future research.
نتیجه گیری انگلیسی
Discussion of the main findings The events that trigger MCS adoption have received limited attention in the existing literature. Using a database that includes over 200 interviews with managers from 69 companies, we identify six different reasons-for-adoption. Two reasons arise from external factors – legitimize and contract. Financial accounting research has long stressed the role that external regulatory bodies such as the IASB or the FASB play in financial reporting method choice. Our analysis of product development systems highlights the role of two external reasons/events in MCS choice. The increasing role of multi-company agreements (such as joint-ventures and large-company reimbursement of early-stage company research) is likely to see the importance of external factors in MCS adoption increase.31 Four of the six factors we identify as prompting MCS adoption are classified as “internal.” Two factors are predominantly of a “proactive” kind – manager background and need to focus. One aspect of the manager background reason is the import-in notion. Key individuals (such as the CEO or a board member) may perceive a major capability gap in their company and then hire a manager who brings in (imports-in) a new MCS that is part of building up the internal capability. This reason is more likely with early-stage companies than established companies as the former rarely have the full set of functional capabilities from day zero. For example, companies with a long time gap between startup date and first revenues (such as biotechnology companies) may delay for considerable time the adoption of a customer relationship management system (CRM). The hiring of a senior marketing/sales executive after several years of R&D/product development may be a prompt to that new executive implementing a CRM system in the early-stage company. Two of the four internal reasons/events for MCS adoption we describe are predominantly of a “reactive” nature kind – learning and chaos. Simons (1995) earlier identified the chaos event as a trigger for MCS adoption. We find support for this event being associated with product development MCS adoption in 20% (14 companies) of our sample of 69 companies. We find much support in our research for the roles current theory and literature identify for MCS. Appendix A provides illustrative quotes from our interviews for seven MCS roles. In some cases, there is a one-to-one correspondence between the reason for adoption and a MCS role – see especially the legitimize and contract external reasons for MCS adoption. In most cases, a given reason (such as manager background or chaos) may be associated with the adoption of MCS performing different roles in individual companies. Limitations and extensions of the research An important caveat in interpreting our results is causality. The interview protocol was designed to have managers describe why systems were adopted. Thus, the analysis implies causality but only in the sense that managers perceived such a causality to exist. We cannot preclude that the perceived cause of adoption and the adoption itself is due to an omitted correlated variable that the manager and the coding of the interviews failed to unveil. Another important issue in interpreting the results is that the categories that we identify as reasons-for-adoption of MCS are based on the analysis of 207 interviews. Because the literature provides limited guidance as to why MCS emerge, the categories identified emerge from the analysis of data. We cannot rule out the possibility that other reasons-for-adoption may also exist. The sample is dominated by companies that received venture capital and are concentrated in two main industries: information technology and biotechnology. These characteristics make the findings most relevant to companies with similar profiles. Our research design used three contemporaneous interviews per company as the main source of data. We did not conduct longitudinal observation of these companies (although our interviews probed emergence over time in much detail). An extension of the research would be to conduct interviews at different points in company history to further probe the MCS emergence question. Such a study would enable us better understand the use of MCS within the web of social interactions both within the company and with outside parties. We treat the adoption of MCS as an event itself. Prior literature (Davila, 2005 and Sandino, 2007) have used a similar research design. Simplifying the adoption to an event facilitates the analysis of the results, but leaves open the rich issue of what drives (and when) future refinement of the adopted MCS. While there is some evidence on how this growth takes place (Cardinal et al., 2004 and Moores and Yuen, 2001), the phenomenon is still little understood. A consistent comment from managers we interviewed was the increase in sophistication of their MCS over time. This study has focused on product development but it is silent on other processes and functions such as marketing, sales, human resources, or finance. Exploring these different settings would extend the empirical basis to formulate a theory of emergence and growth of MCS. Our research design did not collect data on the specific design of the MCS adopted. Having this information may shed some light on the association between reasons-for-adoption and performance. For instance, a poor MCS design may explain why adoption as a response to chaos is associated with worse on-time development performance. The study can be extended to examine whether reasons similar to the ones identified for early-stage firms are also relevant for explaining the evolution of these systems in established companies. Adoption is just the first step in the lifecycle of MCS; a comparative study over this lifecycle to better understand why systems are redesigned would extend and enrich the findings reported in this study. A challenging aspect of research on early-stage companies is their higher mortality. The sample of companies we examined had survived their startup phase and developed a more established and possibly broader set of functional capabilities. Those companies that do not survive represent a fascinating but difficult to research sample. Anecdotal evidence from early-stage company failures cite factors that potentially have strong “absence” of MCS aspect, e.g. failure to anticipate cash shortages and failure to meet promised product or customer deadlines. Detailed case studies rather than larger sample research designs of the kind adopted in this study is likely a more fruitful avenue to examine this set of failed companies. Further research on the “consequences” of not adopting MCS is a useful complement to the research we report on surviving early-stage entrepreneurial companies.