4. Research method
4.1. Sample selection
A survey was administered to 140 manufacturing firms selected from the Business Review Weekly list of Australia’s largest companies. These firms were either “strategic business units” (divisions of larger corporations) or independent companies. To develop an accurate mailing list, each company was telephoned and the names and addresses of business units were identified, as well as the name of the most suitable person within each business unit to complete the survey. These were typically the financial controller, senior management accountant or chief executive. In most cases the particular manager was spoken to, and the purpose of the research explained. These steps were considered important to increase the accuracy of survey responses. Addressing surveys to inappropriate individuals has been a source of inaccurate responses in prior management accounting research using survey methods ( Skinner, 1993).
The sample selected was not random, being drawn from the country’s largest manufacturing companies. Therefore, the findings of this study should not be interpreted as relating to the general population of manufacturing companies. In as much as size is associated with the availability of resources to experiment with a range of management and accounting practices, it is likely that the sample included a greater proportion of companies employing “advanced practices” than the total population of manufacturers. Demographic data related to the respondents’ organizational positions, organizational size and industry are detailed in Table 2.
Table 2.
Demographic data
Industry classification
Food and beverages 13
Wood and paper products 7
Chemical products 7
Metal industry 7
Machinery and equipment 21
Textiles, printing 4
Non-metallic, minerals 3
General construction 3
Other manufacturing 13
Total sample 78
Position of respondent
Chief accountant/group controller 67
Administration manager 4
General manager 3
Other 4
Total sample 78
Size of organizations
No. of employees
0–200 16
201–500 18
501–1000 16
1001–2500 14
2500+ 14
Total sample 78
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4.2. Survey development
Given the potential for poor responses that can arise from lengthy and complex surveys, considerable attention was given to refining the visual appearance of the survey. The design was modelled on the manufacturing futures survey developed by De Meyer et al. (1989)which has been tested extensively (Miller et al., 1992). The survey was pilot tested with groups of managers and management accountants, to refine the design and focus the content.
To reduce any misunderstanding that can rise from unfamiliar terminology or ambiguities, the survey asked individuals to consult with others in their organization when this would result in more informed responses. Additionally, respondents were asked to indicate if they did not understand the meaning of any questions in the survey, and to include any additional comments of relevance in their responses. There was no evidence to indicate misunderstanding of the survey items.
The survey was designed to preserve the anonymity of respondents. Surveys were not prenumbered for identification, and respondents were not required to identify themselves or their company. The mailed survey package included an introductory letter explaining the purpose of the research, a copy of the survey, and two postage-paid envelopes—one for returning the survey anonymously, and the second to allow respondents to request a copy of the survey results. A reminder letter was posted three weeks after the initial mail-out. Two months after posting the follow-up letters, preliminary results were sent to all people who requested them.
The two mailings resulted in 78 usable responses, or a response rate of 56%. Eight firms returned the surveys unanswered indicating that it was company policy not to respond to voluntary surveys. To examine for non-response bias, the responses from the first 20% of returns and those from the last 20% (which would have included mainly respondents to the second mailing) were compared, to test if responses differed between the two groups. Levels of significance were determined for each item using t-tests. No differences were identified, providing some support for the absence of a non-response bias.
The possibility exists that respondents’ functional background may introduce bias. Table 2 reports that 86% of respondents were from accounting and 14% were non-accounting. An examination of the mean responses, between these groups, for variables listed inTable 3, did not reveal any significant differences.
Table 3.
Descriptive statistics
Variables Mean S.D.
Strategic priorities
S1—Customer service 5.52 1.00
S2—Low price 3.50 0.99
S3—Flexibility 4.64 1.10
Management techniques
M1—Human resource management policies 4.61 1.30
M2—Integrating systems 3.58 1.45
M3—Team-based structures 3.91 1.75
M4—Manufacturing systems innovations 3.55 1.41
M5—Quality systems 3.69 1.82
M6—Improving existing processes 3.82 1.77
Management accounting practices
A1—Traditional accounting techniques 4.72 1.17
A2—Benchmarking 3.57 1.64
A3—Activity-based techniques 2.24 1.64
A4—Employee-based measures 3.41 1.62
A5—Strategic planning techniques 3.30 1.53
A6—Balanced performance measures 3.81 1.74
Organizational performance 3.54 0.95
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5. Measurement of constructs
Data were collected to measure variables specified within the hypotheses: strategic priorities, management techniques, management accounting practices and organizational performance.
First, respondents were asked to indicate the degree of emphasis that their firm had given to a range of strategic priorities over the past three years. The scale ranged from no emphasis (scored one) to high emphasis (scored seven). Next, respondents were asked to indicate whether their businesses had adopted particular management techniques, and for those who had adopted each technique, to assess the benefits gained over the past three years. This was measured on a scale anchored at no benefit (scored one) to high benefit (scored seven). The same structure was used to assess the benefits firms had obtained from a range of management accounting practices. The questionnaire items related to management techniques and strategic priorities were derived from relevant items used in the manufacturing futures survey (Miller et al., 1992). The management accounting practices were derived from prior surveys of management accounting practices (see, for example, Joye & Blayney, 1990Innes & Mitchell, 1995) and additional items recommended in recent management accounting literature.Appendix Acontains a list of these survey items.
Finally, organizational performance was measured using an instrument developed byGovindarajan (1988)and Govindarajan and Fisher (1990). This measure asked respondents to assess their business’ performance relative to competitors over the last three years, across 10 dimensions, using a scale that ranged from unsatisfactory (scored one) to outstanding performance (scored seven). Also, respondents ranked each dimension to reflect its relative importance to their business. Scores for each dimension were determined by multiplying the respective “performance” and “importance” scores. A final single performance score for each firm was calculated by taking an average of all items.
While care was taken to include relevant questionnaire items, it was necessary, given the exploratory nature of the research, to examine the extent to which these items were measuring the constructs of concern to the study. As a first step, items were factor analyzed. Oblique rotation was selected to generate the factors. Oblique rotation is recommended as providing substantially more meaningful factors when it is believed that the underlying influences are correlated (Harman, 1967). In the current study, it was expected that companies would be deriving benefits from combinations of techniques. Following Harman (1967), the rule for controlling the extent of obliqueness of delta equals zero was used. Those items that loaded >0.50 on single factors were retained in the analysis. A second factor analysis was undertaken using these items. This analysis generated three constructs for strategic priorities, and six constructs for both management techniques and management accounting practices.3 Details of the items included in each factor and the factor loadings are provided in Appendix B. These constructs met acceptable reliability levels for exploratory research, with Cronbach alphas between 0.60 and 0.88. Table 3 contains descriptive statistics for these factors.
The factor analysis provided measures for all independent variables identified in Hypotheses 1 and 2. To assist in discussing the results of this study, titles for each factor were drawn from those proposed in the hypotheses, except for strategic priorities where three factors were identified. The factors for strategic priorities were customer service (S1), low price (S2) and flexibility (S3). S1 and S3 are concerned, primarily, with aspects of product differentiation. S2 is more related to strategies that focus on undifferentiated products where low price is the competitive priority.4 The items for management techniques loaded on the factors of human resource management policies (M1), integrating systems (M2), team-based structures (M3), manufacturing systems innovations (M4), quality systems (M5) and improving existing processes (M6). Factors for management accounting practices were traditional accounting techniques (A1), benchmarking (A2), activity-based techniques (A3), employee-based measures (A4), strategic planning techniques (A5) and balanced performance measures (A6).