The purpose of this paper is to explore the relationships between variations in management accounting systems (MAS) and organizational life cycles. The authors use a configuration approach based on the idea that contextual variables (e.g., environments, technologies, strategies, cultures and processes) cluster together into configurations of archetypes at different stages of a company's life cycle. More specifically, they address whether management accounting systems (MAS) differ at different life cycle stages and whether these differences reveal a pattern of change.

Organizational Configurations, Life Cycles and MAS

The framework is based on Miller and Friesen's five stage life cycle model* illustrated in the table above along with the organizational characteristics expected for the various life cycle stages.

The research framework includes the organizational life cycle for three reasons: 
    The life cycle concept:
    1. may provide a better framework than the contingency framework, 
    2. may provide prescriptions for MAS design, and 
    3. it may help in analyzing the relationships between MAS and the firms' internal 
       characteristics that provide implications for organizational effectiveness.

Research Framework

The research framework is illustrated in the graphic below and is based on the idea that strategies, structures and management styles vary across life-cycle stages, and that changes in MAS need to be made at different stages to maintain internal consistency.

Hypotheses

The hypotheses are based on the expectation that each life-cycle stage is associated with a different management accounting system.

More specifically, birth stage firms rely on informal control while growth stage firms rely on formal rules and procedures, diagnostic controls, participative budgeting, responsibility accounting, cash flow statements and capital budgeting. Mature firms are expected to rely on a more narrow range of tools than growth stage firms. Revival stage firms become highly decentralized with more flexible decision-making styles, use less data and use a more narrow range of tools for generating information. Decline stage firms control from the top down and also use a narrow range of MAS tools.

Birth stage firms are expected to use the least aggregated and integrated information. Growth stage firms will use more aggregated and integrated information. Mature firms are expected to use less aggregated and less integrated information as they become more centralized and adopt a more intuitive decision-making style. Revival stage firms are similar to growth stage firms in terms of using aggregated and integrated information. Firms in the decline stage are expected to use less aggregated and integrated information.

Method

The research involved survey and field studies in the Australian clothing and footwear industry. Questions related to the extent management control tools were used, how information was presented in terms of aggregation, integration, scope and timeliness, and self reported measures of organizational effectiveness.

Data Analysis

There were 49 usable responses representing a 14.5% response rate to the survey. Factor analysis was conducted to reduce the variables to a manageable size, followed by cluster analysis (the hierarchical agglomerative technique) to classify firms into life cycle stages. The factor analysis produced four factors for strategy, and two each for structure, leadership and decision-style. The cluster analysis produced five clusters.

Descriptive statistics are provided in a rather involved Table 2, not included here. The clusters were labeled, with some difficulty, by comparing the characteristics of each cluster with a priori theory. This information is presented below in an adaptation of Table 3. The clusters were labeled birth (Cluster 5, 2 firms), growth (Cluster 1, 1 firm), maturity (Cluster 3, 29 firms), revival (Cluster 4, 5 firms) and decline (Cluster 2, 9 firms).

Kruskal-Wallis and Man-Witney U-tests revealed significant differences in MAS across stages. This data is presented in Tables 4 and 5, not included here.

The authors used the data-triangulation approach on interview discussion in the field studies to deduce the MAS attributes of the case firms.

Discussion and Integration of Findings

The results showed distinctive patterns of firms characteristics and MAS formality across life-cycle stages and offers support for H1 as illustrated in the graphic below.

The findings provide reasonable support for H2 (a). Firms at the birth stage and maturity stage rely less on formal MA tools than firms at the growth stage. More formal MAS are used at the revival stage than at the maturity stage. Significant between-stage differences were found in performance evaluation, cash-flow statements, reliance on capital budgeting and long term planning.

The findings also support H2 (b). Firms at the growth and revival stages rely more on higher levels of aggregation and integration as well as more timely information. Birth firms show a more narrow scope of information use. But timely information appears to be important at all life cycle stages.

Conclusions and Limitations

The findings provide some support for the hypotheses and suggest practical prescriptions for MAS design. Limitations include a limited sample size, low response rate, judgments required in cluster analysis and the CEO's self reported measures. According to the authors, the study provides a significant contribution in that it reinforces the benefits of applying the configuration approach to examine MAS.

* Miller, D. and P. H. Friesen. 1980. Archetypes of organizational transition. Administrative Science Quarterly (25): 268-299.

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