سیستم های مدیریت حسابداری و پیکربندی سازمانی: دیدگاه چرخه زندگی

This study adopts a configurational approach that captures possible variables (strategy, structure, leadership and decision-making styles) and their relationships with management accounting systems (MAS) from an organizational life-cycle perspective. Using Miller and Friesen's life-cycle model Miller & Friesen, 1983 and Miller & Friesen, 1984, a set of hypotheses were tested with data from mail survey and field studies of firms in the clothing and footwear industry. Results indicated that MAS formality changed to complement organizational characteristics across life-cycle stages. In uncovering how and why MAS formality changed during organizational development, our results indicate that it is growth firms that pay particular attention to increasing the formality of their MAS. Furthermore, between stages, it is the selection of management accounting tools that dominates the presentation of information in explaining the different MAS life-cycle stage designs. While based on cross-sectional data, the homogeneity of organizational configurations at each life-cycle stage does suggest that these results imply a longitudinal development of MAS.

Over the last 20 years, researchers have attempted to explain observed variations in management accounting systems (MAS)1 in terms of a range of contextual factors.2Gordon and Miller (1976) was among the first to encourage this line of contingency-based inquiry when it posited that MAS are associated with environmental, organizational and decision-making style factors. Subsequent researchers have investigated these factors as individual and interactive variables to explain variations in MAS with mixed results (Moores & Chenhall, 1994, Otley, 1980 and Otley & Wilkinson, 1988). It is notable that most MAS researchers have overlooked the second part of Gordon and Miller's (1976) suggestion that many of the contextual variables would cluster together as “commonly occurring configurations” or “archetypes”. Accordingly, they recommended that rather than analyzing an “unmanageable” number of permutations of variables, MAS researchers need only to focus on a few select variables from which a host of peripheral factors generally follow. Miller (1981) also highlighted not only the systemic nature but also the internal consistency of configurational approaches. He found that most changes in any one variable, such as controls, would be dysfunctional unless accompanied by changes in other variables such as centralization or technology. Miller (1981) emphasized that a complementary alignment among organizational variables, as a configuration, is an important determinant of performance. The aim of this paper is to return to Gordon and Miller's (1976) suggestion by exploring whether one such configuration, based on organizational life cycles, is systematically associated with observed variations in MAS. Thus far, life-cycle configurations have been found to manifest as different patterns of strategies, structural characteristics, leadership and decision-making styles at various stages of organizational development (Miller & Friesen, 1984). Accordingly, the objective of this paper is to explore whether different life-cycle configurations help in explaining variations in MAS. This exploratory study addresses the following questions:

The aim of this study was to explore whether MAS differ across stages of organizational life cycle, and if so, is there a pattern of differences in the levels of MAS formality. Using Miller and Miller & Friesen, 1983 and Miller & Friesen, 1984 five-stage life-cycle model (namely birth, growth, maturity, revival, and decline), a research framework was proposed. This framework incorporated key variables that have been evidenced in the literature as related to MAS design. Rather than analyzing the four key variables (strategy, structure, leadership and decision-making styles) in a piecemeal approach, this study adopted a configurational approach to examine them systematically. Two main hypotheses were derived from the literature review, suggesting an expected pattern of MAS formality across stages and the nature of different attributes based on the life-cycle configurations at each stage. Findings from both the cross-sectional data and field studies offer some support for the hypotheses, in particular, the overall theme. In summary, the results suggested that MAS attributes differed as firms transit from one stage to the next. In particular, growth dominates other stages in creating needs for formal MAS design. Furthermore, the selection of management accounting tools is far more important than presentation of information in varying levels of MAS formality at each life-cycle stage. MAS formality increases from birth to growth and from maturity to revival, but the decreases in MAS formality are more significant when firms transit from growth to maturity and from revival to decline. While based on cross-sectional data the homogeneity of organizational configurations at each life-cycle stage does suggest that these results imply a longitudinal development of MAS. Are these MAS changes part of a necessary organizational response to external competitive forces or are they driven by a necessity to maintain an internal equilibrium? Or perhaps the changes arise from the need to balance these internal and external imperatives. The approach adopted in this study is more in keeping with the latter. As such we do not seek to answer the question of whether one factor, such as competitive forces or origins, in terms of say predisposition to MAS, might be driving the changes. The results implied MAS were able to facilitate firms pursuing their respective strategies while exercising necessary controls as required at different stages. Firms at the Birth stage were able to rely less on formal systems due to a homogeneous product/market and simple structure. As firms enter Growth stages, the level of administrative tasks far exceeded the capacity of the existing MAS. Consequently, firms formalized their MAS in order to deal with the more diverse and complex structures than those prevailing at the birth stage. Well-established Mature firms built up their own intelligence systems over time, but with increasing levels of stability they were able to reduce the formality of their systems. If stability was superseded by poor performance, then firms needed to revive. To achieve the turnaround, Revival firms resolved the crises by increasing their reliance on formal systems. As firms' activities became stagnant with limited resources at the Decline stage, their MAS accordingly became less formal. Not only do the results from this study suggest practical prescriptions for MAS design at each life-cycle stage, they also provide evidence of how firms adapted to their growth and development. Further analysis of field study data revealed why and how firms formalize their MAS across life-cycle stages. Firms tended to formalize their MAS as they changed their strategies in gaining or maintaining their competitive advantages; or when their activities and structures became so complex such that their existing systems were insufficient. Most of the firms formalized their MAS by changing from manual to computerized systems. This enabled them to integrate all facets of operations within and outside the business. To accommodate for increased formality of MAS, firms tended to rely on professionalism in management or external consultation. Despite the fact that the findings support the general theme as conveyed by the hypotheses, there are some limitations that warrant acknowledgment. With the limited sample size due to a low response rate, the results from the statistical analyses have to be interpreted with care. Also, generalization of findings beyond the sample industry might be difficult due to a limited sample size, and in particular, the number of sample firms that fell into some of the life-cycle stages was low. While cluster analysis may be superior to CEO's self-categorizations of life-cycle stages due to its statistical properties, certain procedures involved in this technique rely on subjective and intuitive judgements. These include determination of which algorithm to be employed, which distance measures to be used, and the number of clusters to be extracted, together with labeling the clusters. This study adopted the widely used and recommended hierarchical agglomerative technique with Ward's method for distance measures as these have been found to outperform most other clustering techniques (Aldenderfer & Blashfield, 1984). Furthermore, the subjectivity involved in determining the number and labeling of clusters was minimized by adoption of theory-based guidelines. These guidelines were drawn from the Miller & Friesen, 1983 and Miller & Friesen, 1984 five-stage life-cycle model. Limitations also arise where the data obtained were mainly from CEOs' self-reported measures of all the constructs. As the majority of the firms which participated in this study were not large in size, CEOs of these firms have a relatively complete understanding of the various aspects of the organizational characteristics and MAS attributes. They also had the ability to influence the life-cycle configurations and MAS attributes across stages. The significant contribution of this study is the reinforcement of the benefits of applying the configurational approach to examining MAS attributes. The configurational approach has provided a parsimonious and precise research framework for identifying the inter-relationships among organizational characteristics and MAS. By incorporating the life-cycle theory to the research framework, this study explored the dynamic perspective of MAS and provided results indicating how and why MAS changed during organizational development. Future direction for MAS research may consider advancing the configurational approach by incorporating different types of taxonomies, such as Gordon and Miller's (1976) organizational configurations. While the environmental construct has been partially controlled by selecting a particular industry, future research can select other industries to examine whether different patterns of MAS exist. Instead of examining specific MAS attributes, future research could extend Simons, 1995 and Simons, 1999 works by examining the timing of control techniques employed by management in order to alter or maintain patterns of organizational activities across life-cycle stages. In particular, how do managers use different control systems (diagnostically or integratively) during their growth and development, would be a worthwhile future research question.