Adoption of activity management practices: a note on the extent of adoption and the influence of organizational and cultural factors

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1 Management Accounting Research 15 (2004) Adoption of activity management practices: a note on the extent of adoption and the influence of organizational and cultural factors Kevin M. Baird, Graeme L. Harrison, Robert C. Reeve Division of Economic and Financial Studies, Macquarie University, Sydney, NSW 2109, Australia Received 1 November 2003; accepted 12 July 2004 Abstract We examine the extent to which activity management practices are adopted by Australian business units at each of Gosselin s [Gosselin, M., The effect of strategy and organizational structure on the adoption and implementation of activity-based costing. Acc. Organ. Society 22 (2), ] levels of Activity Analysis, Activity Cost Analysis and Activity-based Costing. We also examine the association between extent of adoption and the organizational factors of size and decision usefulness of cost information, and the business unit culture dimensions of innovation, outcome orientation, and tight versus loose control. Data were collected by mail survey questionnaire of a random sample of business units, with questionnaire design and distribution based on Dillman s [Dillman, D.A., Mail and Internet Surveys: The Tailored Design Method. John Wiley & Sons Inc., New York] Tailored Design Method. Adoption rates are found to be higher than in prior studies, suggesting the continuing relevance of activity management practices and the advantage of using Gosselin s (1997) levels. All factors were found to be associated with all activity management practices. In particular, business unit size and all three business unit culture dimensions were found to be associated with extent of adoption of Activity Analysis (AA) and Activity Cost Analysis (ACA), while decision usefulness and the cultural dimensions of outcome orientation and tight versus loose control were associated with Activity-based Costing Elsevier Ltd. All rights reserved. Keywords: Activity management; Activity Analysis; Activity Cost Analysis; Activity-based Costing; Business unit culture; Organizational culture Corresponding author. Tel.: ; fax: address: kbaird@efs.mq.edu.au (K.M. Baird) /$ see front matter 2004 Elsevier Ltd. All rights reserved. doi: /j.mar

2 384 K.M. Baird et al. / Management Accounting Research 15 (2004) Introduction An Activity-based Costing (ABC) system is a system that focuses attention on the costs of various activities required to produce a product or service (Langfield-Smith et al., 1998, Glossary, p. 1). First developed by Cooper and Kaplan (e.g., Cooper, 1988; Cooper and Kaplan, 1988), ABC was promoted as a system that would reduce the level of arbitrary cost allocations associated with traditional costing systems and result in more accurate product costs. Since its inception, many authors have further advocated the benefits of ABC, and a number of studies have provided empirical evidence to support those benefits (e.g., Norris, 1994; Anderson, 1995; Swenson, 1995; Foster and Swenson, 1997; McGowan and Klammer, 1997). Despite the claimed benefits of ABC, studies which have examined the extent of adoption of ABC by organizations have reported considerable variation. For example, while studies in the U.K. in the early to mid-1990s reported adoption rates around 10% (Innes and Mitchell, 1991, 1995; Nicholls, 1992; Drury et al., 1993; Drury and Tayles, 1994), studies in the U.S. recorded considerably higher rates (Shim and Sudit, 1995 (27%); Green and Amenkhienan, 1992 (45%); Hrisak, 1996 (53%)). Similarly, while studies in Australia have generally recorded relatively low adoption rates (Teoh and Schoch, 1993 (17%); Clarke and Mia, 1995 (12%); Booth and Giacobbe, 1997 (12%); Warwick et al., 1997 (10%)), Chenhall and Langfield-Smith (1998) recorded a much higher adoption rate of 56%. One explanation for the low adoption rates in studies in the early to mid-1990s may have been accounting lag, i.e., the time lapse between development of theory and application in practice (Scapens, 1994). Bruggeman et al. (1996), in their study of Belgian organizations, found that while only 19.5% of organizations said they had adopted ABC, 49.5% said they planned to do so in the future. Similarly, the adoption rate found for U.K. organizations by Innes and Mitchell (1995) of 20% was treble that of their earlier (1991) study of 6%, and, in the U.S., Krumwiede (1998b) reported adoption rates had increased from 41% in 1995 to 49% in Despite these findings, recorded rates of adoption remain lower than might be expected given the advantages claimed for ABC. Additionally, there continues to be significant variation in the rates recorded across studies conducted at similar points in time, suggesting that the variation cannot be attributed solely to accounting lag, and that alternative explanations for the low and variable adoption rates are also possible. This paper suggests that part of the explanation may lie in differences in the manner in which ABC has been defined and operationalized in prior studies. First, prior studies have used a multiplicity of terms such as ABC itself, Activity-based Management (ABM) (Reeve, 1996), Activity-based Cost Management (ABCM) (Foster and Swenson, 1997), Activity Accounting (AA) (Brimson, 1991), Activity Management (AM), Activity Analysis (AA) and Activity Cost Analysis (ACA) (Gosselin, 1997). Second, the studies have rarely provided explicit definitions of the terms they have used such that it is difficult to compare results across studies and across time, and survey respondents have often been required to place their own interpretations on the terms with the potential consequence that their interpretations might have been different from those of the researcher and from other respondents in the study. Third, with few exceptions (Norris, 1994; Reeve, 1996; Gosselin, 1997; Chenhall and Langfield- Smith, 1998), prior studies have tended not to recognize, or convey to survey respondents, that ABC (or alternative terms) may be adopted at different levels, or to different degrees. Gosselin, for example, identifies ABC as just one of three hierarchical levels of Activity Management, the other two being AA and ACA. As discussed in the next section, the different levels of Activity Management serve different

3 K.M. Baird et al. / Management Accounting Research 15 (2004) purposes for organizations and, hence, organizations might choose to adopt different levels depending on their purpose. The failure to recognize, and/or convey to survey respondents, the different levels at which organizations might adopt activity management, 1 together with the use of different activity management terms across prior studies, might well contribute explanation both to the variation in the adoption rates found in those studies, and to the low levels of adoption recorded in some studies. For example, some studies have used the term ABC to refer to all levels of activity management (Anderson, 1995; Swenson, 1995), while others (Booth and Giacobbe, 1997; Gosselin, 1997) have used it to refer to one specific level. A consequence is a potential misunderstanding by respondents in these studies of the term ABC, particularly for respondents whose organizations were using activity management at the level of either AA or ACA, but who may not have reported such use because of their (mis)interpretation of the term ABC. The failure to recognize the different levels of activity management adoption might also affect the results of studies which have examined the impact of organizational factors, such as size, structure, strategy and decision usefulness of cost information, on the adoption of ABC (Drury and Tayles, 1994; Moores and Chenhall, 1994; Björnenak, 1997; Brown et al., 2000). If prior studies of extent of adoption may have been affected by differences in terminology and/or by the failure to consider different levels of adoption, so too might prior studies of the factors associated with adoption. Our study seeks to overcome some of these limitations of prior studies by examining the extent of adoption of activity management practices, and the association between selected organizational factors and the extent of adoption, at each of Gosselin s (1997) three levels of activity management. In addition, we examine the association between selected business unit cultural dimensions and the extent of adoption. The study is exploratory, particularly with respect to the affect of organizational and cultural factors on extent of adoption, as there is no developed theory to associate the factors with each of Gosselin s (1997) three levels. Consequently, we do not develop formal propositions or hypotheses; rather we use the following research objectives to guide empirical research and then interpret our empirical findings ex post. Objective 1: To examine the extent of adoption of activity management at each of Gosselin s (1997) three levels of Activity Analysis, Activity Cost Analysis and Activity-based Costing. Objective 2: To examine organizational factors previously found to be associated with adoption of activity management generally (specifically, business unit size and decision usefulness of cost information) for their association with the extent of adoption of activity management at each of Gosselin s three levels. Objective 3: To examine business unit cultural dimensions (specifically, innovation, outcome orientation, and tight versus loose control) for their association with the extent of adoption of activity management at each of Gosselin s three levels. These organizational factors and cultural dimensions are not chosen as comprehensive of the factors affecting adoption of activity management. We choose them as examples of factors that have been suggested or found to affect adoption of activity management generally, and we use them in this study as examples to test empirically the utility of Gosselin s three level approach to activity management classification. The motivation for including size and decision usefulness of cost information comes from prior studies which have found these factors to be associated with activity management generally. The motivation for 1 This paper will use the lower case term activity management to refer to activity management generally. Where specific levels of activity management are being referred to, upper case letters will be used, as in Activity Analysis (AA), Activity Cost Analysis (ACA), and Activity-based Costing (ABC).

4 386 K.M. Baird et al. / Management Accounting Research 15 (2004) including selected business unit cultural dimensions is twofold. First, culture has been proposed as a factor with significant potential to affect adoption of activity management (Foster and Swenson, 1997; Parker, 1997; Shields and Young, 1989; Langfield-Smith et al., 1998), and second, no study to date has empirically examined the association between culture and activity management adoption. 2. Levels of activity management As noted above, Gosselin (1997) identifies three levels of activity management: AA, ACA and ABC. AA consists of identifying the activities and procedures carried out to convert material, labor and other resources into outputs ; ACA progresses AA to identify the costs of each activity and the factors that cause them to vary ; while ABC progresses a further stage to trace costs to products and services through identifying overhead costs with homogeneous activity-cost pools and applying pooled costs to products and services based on measures of the activities consumed by those products and services (Gosselin, 1997, pp ). While AA does not involve the collection of cost information, such analysis is important in its own right as it provides the business unit with a better understanding of the tasks performed and the processes being used to produce outputs (Edwards, 2000, p. 6), enabling the business unit to improve the effectiveness and efficiency with which activities are performed. By going one step further and calculating the costs of performing activities and identifying cost drivers, ACA enables further improvement in effectiveness and efficiency. AA and ACA would be important to business units intent on analyzing activities and determining cost drivers with the purpose of improving processes and making cost reductions (Reeve, 1996, p. 6; Sakurai, 1996, p. 155). The third level of activity management, ABC, would be important to business units seeking to measure product/service costs with the purpose of making product/service decisions. Business units may, therefore, choose to adopt activity management at any of the three levels, depending on their situation. They may choose to adopt AA or ACA and not proceed to ABC because (a) their primary objectives from activity management are process improvement and cost reduction, and/or (b) of concerns over the utility of the cost allocations to products and services at the ABC level, and/or (c) the adoption of ABC is not seen as cost-beneficial. 3. Factors affecting extent of adoption of activity management 3.1. Business unit size Several studies have supported a link between size and the adoption of modern management accounting practices such as activity management (Drury and Tayles, 1994; Moores and Chenhall, 1994; Innes and Mitchell, 1995; Björnenak, 1997; Langfield-Smith et al., 1998). The arguments for this link include: (a) the demand for activity management information for planning, control and coordination of activities is greater in larger organizations; (b) larger organizations are more able to commit resources to the development and implementation of activity management practices; and (c) the more resources are available to activity management practices, the better those practices are likely to be and the higher their perceived benefits (Moores and Chenhall, 1994).

5 K.M. Baird et al. / Management Accounting Research 15 (2004) Decision usefulness of cost information Prior literature has suggested two ways in which the decision usefulness of cost information affects the extent of adoption of activity management practices. First, business units with a high potential for cost distortions may adopt activity management to a greater extent in order to overcome such distortions (Krumwiede, 1997, p. 2). The potential for cost distortions is reflected in the level of product and/or process diversity and the level of overhead costs relative to total costs (Cooper, 1988; Warwick et al., 1997). Business units with more diverse products and processes require more overhead cost allocations and are, therefore, more likely to have distortions in the determination of product costs. Additionally, the impact of cost distortions will be greater in business units with a higher proportion of overhead costs. The level of overhead relative to total costs has frequently been cited as the major factor influencing organizations to adopt activity management (Johnson and Kaplan, 1987; Cooper, 1988; Innes and Mitchell, 1994). Second, business units are only expected to adopt activity management if it will generate information that will be used in decision-making. Noreen (1991, p. 160) argues that while business units may have the potential for cost distortions, the information provided by the new system must be relevant for decision making. Similarly, Krumwiede (1998b, p. 33) notes that even if ABC will reduce cost distortions substantially, it probably will not be implemented unless a company can use the better cost in its decision making Business unit culture Although there are numerous definitions of organizational (here, business unit) culture, most have commonality with Gordon and DiTomaso s (1992, p. 784) pattern of shared and stable beliefs and values that are developed within a company (business unit) over time. While some approaches to business unit culture conceptualise it in aggregate, holistic terms for a particular organizational unit (such as Trompenaar s, 1994, classification of incubator, guided missile, family and Eiffel Tower cultures), most approaches to, and research on, business unit culture conceptualise and operationalize it in terms of subdimensions (O Reilly et al., 1991; Hofstede et al., 1990). These dimensions may subsequently aggregate to form a particular shared pattern for any particular business unit, but not necessarily in the classificatory patterns suggested by Trompenaars (1994), for example. As our focus is on identifying factors that may be associated with adoption of activity management practices across business units, we adopt the approach of examining specific dimensions of culture for the potential of those dimensions separately to affect extent of adoption. Three dimensions of business unit culture are examined: innovation, outcome orientation and tight versus loose control. The first two are drawn from the O Reilly et al. (1991) Organizational Culture Profile (OCP), and the third from the Hofstede et al. (1990) practices-based measure of organizational culture. Innovation represents a business unit s receptivity and adaptability to change, and its willingness to experiment (O Reilly et al., 1991, p. 505). This dimension is likely to be associated with adoption of activity management given that resistance to (innovation and) change represents one of the most profound sources of potential adoption and implementation problems for new management accounting techniques and systems such as ABC (Parker, 1997, p. 120). Business units with more innovative cultures will, therefore, be more likely to experiment with new practices, such as activity management, than units with less innovative cultures. The second cultural dimension, outcome orientation, refers to the extent to which business units emphasize action and results, have high expectations for performance, and are competitive (O Reilly

6 388 K.M. Baird et al. / Management Accounting Research 15 (2004) et al., 1991, p. 505). Business units with an outcome orientation culture are likely to be attracted to practices, such as activity management, that claim to facilitate improvements in processes and to enhance performance and competitiveness. The third dimension, tight versus loose control, relates to the emphasis on control of activities and costs. Hofstede (1998, p. 4) described units that have a tight control culture as being extremely cost conscious. Tight control is also seen as involving extensive and continuous flows of information and an extremely detailed planning, budgeting and reporting system (Merchant and Van der Stede, 2003, p. 133). These characteristics suggest that business units with tight control cultures are more likely to adopt activity management practices than those with loose control cultures. 4. Method A survey questionnaire was mailed to the financial controller (or equivalent) of a random sample (stratified by size) of 400 Australian business units chosen from the Kompass Australia (2001) directory. 2 Business units were chosen as the unit of analysis because activity management practices may differ across business units within a firm, making it difficult for respondents to complete the questionnaire at firm level. The choice of financial controllers and business units is consistent with previous research (Anderson, 1995; Gosselin, 1997; Krumwiede, 1998a). The survey was administered using the Dillman (2000) Tailored Design Method which provides guidelines in relation to the format and style of questions, techniques to personalise the survey, and distribution of the surveys. 3 This method has been shown to improve response rates to mail survey questionnaires (Dillman, 2000, p.3) Variable measurement Extent of adoption of activity management The extent of adoption of activity management was measured by responses to three statements (shown in Appendix A) designed to capture the characteristics of each level of activity management. Essentially, respondents were asked to indicate the extent to which they analyzed the various activities involved with providing services or producing goods (AA), calculated the costs of the activities for the purpose of identifying the factors which influence costs (ACA), and calculated the costs of activities for the purpose 2 The sample size of 400 was determined based on the formulae of Cohen (1988), taking account of the number of independent variables, statistical significance and power, and effect size; and on anticipated response rates both overall and of business units likely to have adopted activity management drawn from a recent survey study in this area (Chenhall and Langfield-Smith, 1998). The Kompass Australia business directory lists all businesses in Australia, such that a random sample drawn from this directory as the sampling frame is highly representative of the Australian context. Business units with less than 50 employees were excluded because activity management would rarely be relevant at this size. 3 The surveys were distributed using the Dillman (2000) four-stage approach. The initial mailing was accompanied by a postcard which respondents were asked to return separately. This allowed identification of respondents and non-respondents for follow-up purposes, yet preserved respondents anonymity. A reminder letter was sent 2 weeks later, and a second reminder letter with another copy of the questionnaire was sent after a further 2 weeks. A fourth and final letter with a single-page extract from the questionnaire was sent 3 months after the initial mail-out. This shortened version contained only questions about the extent of adoption of activity management. The purpose was to allow a test of non-response bias by comparing the extent of adoption by respondents to the single-page version (who were non-respondents to the full questionnaire) with those of respondents to the full questionnaire.

7 K.M. Baird et al. / Management Accounting Research 15 (2004) of assessing product costs (ABC). A 7-point Likert-type scale was used with anchors of 1 not at all and 7 to a great extent Business unit size Business unit size was measured by the number of equivalent full-time employees in each unit, logarithmically transformed to improve normality of the distribution Decision usefulness of cost information Decision usefulness of cost information was obtained by combining a measure of the potential for cost distortions and a measure of the extent to which the information provided was used for decision-making purposes. The potential for cost distortions was, itself, based on two components: level of overheads and product diversity. The level of overheads was measured by asking respondents to indicate the magnitude of overhead costs as a proportion of total product costs, using a 7-point Likert-type scale with anchors of 1 a very large % and 7 a very small %. Lower (higher) scores represent a higher (lower) level of overheads. Product diversity was measured using the four-item summated scale of Krumwiede (1998a) and Brown et al. (2000) (Appendix A). Each item was presented as a statement and respondents were required to indicate the extent to which they agreed with each statement on a 7-point Likert-type scale, anchored at 1 strongly agree and 7 strongly disagree. The items were worded positively for diversity, such that lower (higher) scores on this measure represent higher (lower) levels of product diversity. The potential for cost distortion was measured by summing the scores for the level of overheads item and the four product diversity items. The extent to which activity management information is used for decision-making was measured using Krumwiede s (1998a) three-item summated scale. These items (Appendix A) were again presented as statements, positively worded towards use, and with anchors of 1 strongly agree and 7 strongly disagree, such that lower (higher) scores represent higher (lower) levels of the use of activity management information in decision-making. Decision usefulness of cost information was scored as the sum of the five items for potential for cost distortion and the three for extent to which activity management information is used in decision-making Business unit culture Two of the business unit cultural dimensions, innovation and outcome orientation, were measured using the sum of the cultural value items which loaded on those dimensions following a factor analysis of the 26-item version of the Organizational Culture Profile (O Reilly et al., 1991)(Appendix A). Respondents were asked to indicate the extent to which each item was valued in their business unit. A 5-point Likerttype scale with anchors of 1 valued to a very great extent and 5 not valued at all was used and scores for each dimension were calculated as the sum of responses. Lower (higher) scores represented higher (lower) values on the dimensions. The factor structure was highly consistent with O Reilly et al. (1991), and with subsequent applications by Windsor and Ashkanasy (1996) and McKinnon et al. (2003). 4 We have used a global measure of extent of adoption. That is, we have allowed respondents to self-assess and report extent of adoption in their business unit in a broad, unconstrained manner. Thus, an assessment of used to a small extent might, for example, indicate used (uniformly) to a small extent across all parts of a business unit s operations, or used in only a small part of the unit s operations.

8 390 K.M. Baird et al. / Management Accounting Research 15 (2004) Table 1 Summary statistics for independent variables Independent variable Mean Standard deviation Minimum actual (theoretical) Maximum actual (theoretical) Business unit size a ( ) 9.62 ( ) Decision usefulness of cost information (8) 50 (56).70 Innovation (5) 23 (25).78 Outcome orientation (5) 24 (25).86 Tight vs. loose control (8) 50 (56).90 a Log transformation of number of employees. α The third business unit culture dimension, tight versus loose control, was measured with an eight-item summated scale (Appendix A) developed from Merchant (1985). Respondents were asked to indicate the extent to which they agreed that each statement in the scale reflected practices within their business unit. Each item was scored on a 7-point Likert-type scale, anchored on 1 for strongly agree and 7 for strongly disagree so that lower (higher) scores represented tighter (looser) control. Table 1 shows summary statistics for the independent variables. For the multi-item scales used to measure decision usefulness of cost information and the three dimensions of culture, the actual range was comparable with the theoretical range, and the Cronbach alpha coefficients met or exceeded the.70 threshold generally considered acceptable for scale reliability (Nunnally, 1978, p. 245). 5. Results Two hundred and forty-six responses were received for a response rate of 61.5%. These comprised 184 complete responses to the full survey questionnaire (46%) and 62 responses to a single-page extract from the questionnaire sent on the final follow-up mailing (15.5%). A further 36 respondents (9%) provided feedback that they could not complete the survey because of time or company policy constraints. Non-response bias was assessed by comparisons of business unit demographics (size, location and industry) between respondent and non-respondents, comparisons of independent and dependent variable values between early and late responders, and comparisons of responses to the single-page extract from the questionnaire between the 184 respondents who completed the full questionnaire and the 62 who completed the single-page only. No significant differences were detected in any of the comparisons Extent of adoption of activity management practices The extent of adoption for each level of activity management, AA, ACA and ABC, is shown in Table 2. The table shows the adoption status broken into four categories: non-adopters, and adopters who indicated that they adopted each level of activity management to a small extent (scored as response points 2 and 3 on the 7-point scale), to a moderate extent (4 and 5), and to a great extent (response points 6 and 7). The table shows that, of the business units that use each level to either a moderate or great extent (combining response points 4 and 5 with 6 and 7), 86.2% use AA, 82.1% use ACA and 78.1% use ABC. Only a small percentage of respondents reported that they did not adopt any level of activity management. Table 2 also

9 K.M. Baird et al. / Management Accounting Research 15 (2004) Table 2 Extent of adoption of activity management practices Activity management practice Non-adopter (1) Adopt to a small extent (2 3) Adopt to a moderate extent (4 5) Adopt to a great extent (6 7) Activity analysis (AA) 10 (4.1%) 24 (9.7%) 71 (28.9%) 141 (57.3%) Activity cost analysis (ACA) 11 (4.5%) 33 (13.4%) 80 (32.5%) 122 (49.6%) Activity-based Costing (ABC) 13 (5.3%) 41 (16.7%) 89 (36.2%) 103 (41.9%) shows that of those business units that adopt each level to a great extent, not all have adopted the highest level of ABC. Rather, 38 (141 minus 103) have remained at the lower AA and ACA levels of adoption Factors affecting extent of adoption of activity management The association between business unit size, decision usefulness of cost information, and business unit culture, and the extent of adoption of AA, ACA and ABC was initially assessed using hierarchical regression, the results of which are presented in Table 3. All models are significant (F sig =.000) and have R 2 values greater than.20. Business unit size was entered into the models in Block 1. The amount of variation in extent of adoption of activity management practices explained by business unit size was small but statistically significant, or close to statistical significance, at conventional levels. The R 2 change values and their statistical significance were.020 and.067 for AA,.025 and.041 for ACA, and.027 and.030 for ABC. Decision usefulness of cost information was entered into the models in Block 2. The additional amount of variation in extent of adoption of activity management practices explained by decision usefulness of cost information was small, but statistically significant and larger than for business unit size, and was largest in the case of ABC. The R 2 change values and their statistical significance were.038 and.010 for AA,.042 and.006 for ACA, and.068 and.000 for ABC. The three business unit culture variables were entered into the models together in Block 3. The additional amount of variation in extent of adoption of activity management practices explained by the Table 3 Hierarchical regression analysis of extent of adoption of activity management practices Block no. Independent variable Activity Analysis (AA) Activity Cost Analysis (ACA) Activity-based Costing (ABC) R 2 change F change (sig) R 2 change F change (sig) R 2 change F change (sig) 1 Business unit size (.067) (.041) (.030) 2 Decision usefulness (.010) (.006) (.000) of cost information 3 Business unit culture (.000) (.000) (.000) (innovation, outcome orientation, tight vs. loose control) Total F (F sig ) (.000) (.000) (.000) R

10 392 K.M. Baird et al. / Management Accounting Research 15 (2004) Table 4 Stepwise regression analysis of extent of adoption of activity management practices Independent variable Activity Analysis (AA) Activity Cost Analysis (ACA) Activity-based Costing (ABC) β coefficient t-statistics (t sig ) β coefficient t-statistics (t sig ) β coefficient t-statistics (t sig ) Constant (.000) (.000) (.000) Business unit size (.050) (.031) Decision usefulness of cost information (.008) Innovation (.016) (.023) Outcome orientation l (.045) l (.036) (.009) Tight vs. loose control l (.001) l (.002) (.001) F (F sig ) (.000) (.000) (.000) R Notes. (1) Positive signs for the business unit size coefficients in the AA and ACA regressions indicate larger business units adopt AA and ACA to a greater extent than smaller business units. (2) Negative signs for the decision usefulness coefficient in the ABC regression indicate business units where decision usefulness of cost information is high adopt ABC to a greater extent than business units where decision usefulness of information is lower. (3) Negative signs for the innovation coefficient in the AA and ACA regressions indicate business units with a more innovative culture adopt AA and ACA to a greater extent than those with less innovative culture. (4) Negative signs for the outcome orientation coefficient in the AA, ACA and ABC regressions indicate business units with a more outcome oriented culture adopt AA, ACA and ABC to a greater extent than those with a less outcome oriented culture. (5) Negative signs for the tight vs. loose control coefficient in the AA, ACA and ABC regressions indicate business units with a tight control culture adopt AA, ACA and ABC to a greater extent than those with a loose control culture. (6) One-tailed significance values have been used because the expected directions of the effects have been indicated in Section 3. business unit culture variables, in aggregate, was statistically significant and larger than the amount explained by business unit size and decision usefulness of cost information. The R 2 change values and their statistical significance were.148 and.000 for AA,.139 and.000 for ACA, and.112 and.000 for ABC. 5 Thereafter, stepwise regression was used to identify those independent variables that have the most significant effect on the extent of adoption of activity management at each of the three levels. The final models produced by the stepwise regression are presented in Table 4. All models are significant (F sig =.000) and have R 2 values greater than.17. The models show that four of the five variables were associated with adoption of AA and ACA (business unit size, and the three cultural dimensions of innovation, outcome orientation, and tight versus loose control), and three were associated with ABC (decision usefulness of cost information, outcome orientation, and tight versus loose control). The expected association between business unit size and adoption of activity management was found to hold at the AA (p =.050) and ACA (p =.031) levels, with larger business units adopting AA and ACA to a greater extent than smaller business units, but not at the ABC level. By contrast, the ex- 5 Although the three cultural variables were entered into the hierarchical regression in a block, the focus of the study, as noted in Section 3, is on the association between each of the separate cultural variables and extent of adoption of activity management practices. The results of the hierarchical regression indicate that the cultural variables, in aggregate, are significant in their association with extent of adoption, providing the basis to examine the individual associations in the subsequent stepwise regression.

11 K.M. Baird et al. / Management Accounting Research 15 (2004) pected association between decision usefulness of cost information and adoption of activity management was found to hold at the ABC level (p =.008), with units with higher decision usefulness adopting ABC to a greater extent than those with lower decision usefulness, but not at the AA and ACA levels. Considerable support was found for the expected association between the three business unit cultural dimensions and adoption of activity management at all three levels of AA, ACA and ABC. Innovation was associated with the first two levels of AA (p =.016) and ACA (p =.023), with more innovative business unit cultures adopting AA and ACA to a greater extent than less innovative cultures, but not with ABC. Outcome orientation was associated with extent of adoption at all three levels of AA (p =.045), ACA (p =.036) and ABC (p =.009), with business unit cultures higher in outcome orientation adopting all three levels to a greater extent than cultures lower in outcome orientation. Tight (versus loose) control was also strongly associated with greater extent of adoption at all three levels of AA (p =.001), ACA (p =.002) and ABC (p =.001) Conclusions 6.1. Discussion This study had three objectives, each related to exploring the utility of Gosselin s (1997) three levels of activity management (Activity Analysis, Activity Cost Analysis and Activity-based Costing) for research into adoption of activity management practices. The first objective was to examine the extent of adoption of activity management at each of Gosselin s three levels. Overall, our results suggest that activity management practices are widely used by Australian business units. We found adoption rates considerably higher than those in prior studies, with 86% of business units reporting they adopted activity management to a moderate or great extent in its Activity Analysis form, and 78% in the higher level Activity-based Costing form. These rates compare with the next highest rates in prior studies in Australia of 56% (Chenhall and Langfield-Smith, 1998) and the U.S. of 53% (Hrisak, 1996). The higher adoption rates we found lend support to the continuing relevance of activity management, a relevance which has been questioned in the past because of low adoption rates found in a number of studies. However, the higher rates also lend support to the use of Gosselin s (1997) approach to measure extent of adoption of activity management practices. The higher adoption rates found here compared to prior studies might be the result of the continued passage of time and more organizations adopting activity management practices. However, these practices have been in the business arena for some 15 years, suggesting that the explanation may lie less in the effluxion of time, and more in the improved measure of adoption used in this study, allowing (a) a more accurate measure of extent of adoption and (b) recognition of adoption at lower or less complex levels than prior studies might have allowed. In this latter respect, an important finding is that, while the rates of adoption (to a moderate or great extent) do not vary greatly across the three forms of activity management, the simpler forms of Activity 6 The negative sign on the coefficients results from the direction of scoring the cultural dimensions. For more detail, refer to the notes to Table 4.

12 394 K.M. Baird et al. / Management Accounting Research 15 (2004) Analysis and Activity Cost Analysis attracted greater proportionate adoption rates (86 and 82%, respectively) than the more complex Activity-based Costing (78%). Further, while 103 of the business units reported they adopted activity management to a great extent at the highest level of Activity-based Costing, a further 38 (27% or one in four business units) appeared satisfied to concentrate their adoption of activity management at the lower levels of Activity Analysis and Activity Cost Analysis. Taken together, these results lend support to those authors (Nanni et al., 1992; Norris, 1994; Reeve, 1996; Sakurai, 1996) who argue that organizations may well choose to adopt Activity Analysis and Activity Cost Analysis, but not proceed to Activity-based Costing because (a) their objectives from activity management are process improvement and cost reduction, or (b) the adoption of Activity-based Costing is not seen as cost-beneficial or as improving cost allocations. The second objective was to examine organizational factors (specifically business unit size and decision usefulness of cost information) found to be associated with activity management generally, for their association with each of Gosselin s three levels. Here, our results show that size was associated with both the Activity Analysis and Activity Cost Analysis levels of activity management, but not the Activity-based Costing level, where it was replaced by decision usefulness of cost information. The importance of size at the Activity Analysis and Activity Cost Analysis levels is consistent with previous literature and theory that larger firms have both a greater need for activity management in planning, controlling and coordinating their activities, and a greater ability to commit resources to develop and implement activity management. The disappearance of size and the appearance of decision usefulness of cost information in the stepwise regression model for Activity-based Costing suggests, however, that while size is important generally in the implementation of activity management, its importance at the Activity-based Costing level may be less than that of other factors, particularly the factor of decision usefulness of cost information. That decision usefulness supplants size in the explanatory model for Activity-based Costing is highly plausible. Decision usefulness of cost information is related theoretically to the potential for cost distortions in the determination of product or service costs, arising from the level of product or service diversity and the level of overhead costs relative to total costs. It is in these circumstances that Activity-based Costing is claimed to be more advantageous than traditional costing systems. Hence, the association we found in this study for the third of Gosselin s (1997) activity management levels provides empirical support that such advantage is perceived by organizations and business units with high potential for cost distortion in product and service costs. The third objective was to examine three dimensions of business unit culture (innovation, outcome orientation, and tight versus loose control) for their association with each of Gosselin s three levels. Although highly exploratory in this context, the results were strong and promising with respect to the importance of culture in explaining extent of adoption of activity management practices. The dimensions of outcome orientation and tight versus loose control were important in the explanatory models for all three levels of activity management while innovation was important in the first two. These results suggest that business units with a culture of outcome orientation and which emphasize action, achievement and results and have high expectations for performance and competitiveness, are likely to be attracted towards, and to adopt, analyses which promise enhanced performance through cost reduction, improved effectiveness and efficiency, and more competitively targeted product and service pricing, i.e., they are attracted to the outcomes of activity management at all levels of Activity Analysis, Activity Cost Analysis and Activity-based Costing. Similarly, business units with a culture of tight (versus loose) control and which emphasize cost control and detailed planning, budgeting and costing systems, are

13 K.M. Baird et al. / Management Accounting Research 15 (2004) also more likely to be attracted towards analyses which emphasize cost control and the detailed tracking of costs to activities and products and services, i.e., again reflective of the specific objectives of each of the three levels of activity management. The association of an innovative culture with the first two levels of Activity Analysis and Activity Cost Analysis is also plausible in explanation. The cultural dimension of innovation may well be associated with the earlier stages of adoption of activity management where activity management represents something new and experimental to the organization such that an innovative business unit culture is more likely to adopt activity management to a greater extent than a less innovative culture. However, Activitybased Costing represents a later and more advanced stage in activity management, building on, and developing from, earlier stages. Hence, it may be argued that the progression to this stage of activity management does not represent an innovation, but rather an evolutionary development from an earlier stage. Indeed, the progression to this stage suggests that the business unit has sufficient stability in its products and services that the investment in implementing the Activity-based Costing level is seen as justified Limitations and suggestions for future research As data were gathered using a mail survey questionnaire, the limitations of such a method generally apply, including the simplification of questions, the absence of opportunity to probe answers, and issues of control over who completes the survey and of ensuring adequate response rates. While the first two of these limitations cannot be overcome within the mail survey method, the use of Dillman s (2000) Tailored Design Method was successful in alleviating the latter two. To overcome the first two limitations, a different research method would be needed. For example, we have imputed motivations for adoption of different levels of activity management based on the assumption that managers will make conscious choices about the level to adopt based on the particular circumstances of their business unit, and the purpose they seek to obtain from activity management. This imputation is grounded in theory (Nanni et al., 1992; Norris, 1994). Nonetheless those motivations could be examined more deeply using other methods. Personal interviews, for example, would allow such motivations to be elaborated in richer detail and will be an important part of future research in this area. Important also will be further research into the effects of business unit culture. Our study sought to identify the potential effects of culture dimensions across business units and, hence, we examined the effects of the dimensions separately. However, the culture of any particular business unit is a combination of dimensions. Such combinations will vary and there may be combinations where one dimension (e.g., innovation) might point in a different direction with respect to extent of adoption of activity management (according to our empirical findings) than another (e.g., tight versus loose control). Alternatively, the dimensions found in our study to affect extent of adoption of activity management might not be found in common combination. Our results are not counter-intuitive in that innovation relates to the initial levels of adoption, while tight versus loose control is relevant at all three levels and, notably, at the Activity-based Costing level. Nonetheless, future research could be directed at unravelling the relative effects of different cultural combinations where the dimensions compete for their importance in combination in a particular context rather than complement each other. Whatever the focus and method of future research, such research should recognize the different levels of activity management, both in terms of researching the extent of adoption of activity management and factors affecting adoption. Gosselin s (1997) levels of Activity Analysis, Activity Cost Analysis

14 396 K.M. Baird et al. / Management Accounting Research 15 (2004) and Activity-based Costing proved informative in our study and would also support future studies. 7 Many studies may still need to rely on more succinct or generic descriptions of activity management, depending on their purpose and the importance of activity management in those studies. However, our study has shown that more detailed and finer descriptions and measures of activity management practices are required if an accurate portrayal and analysis of activity management is to be obtained. Appendix A. Variable measurement Extent of adoption of activity management Please indicate the extent to which the following statements describe current practices in your business unit. (a) Our business unit identifies and analyses the various activities involved with providing services or producing products. (b) Our business unit identifies and calculates the costs of the various activities involved with providing services or producing goods, for the purpose of identifying the factors which influence costs. (c) Our business unit identifies and calculates the costs of the various activities involved with providing services or producing goods for the purpose of enabling a more accurate assessment of product costs. Decision usefulness of cost information Level of overheads Please indicate the approximate proportion of your business unit s total product cost that is represented by overhead costs. Product diversity (Krumwiede, 1998a; Brown et al., 2000) Regarding the diversity of manufacturing/service operations within your business unit: (a) Product lines are quite diverse. (b) Most products require different processes to design, produce and distribute. (c) There are major differences in volume/output across product lines. (d) The consumption of support department (e.g., engineering, purchasing, marketing) resources varies quite substantially across product lines. Extent of information use (Krumwiede, 1998a) Regarding the use of cost data within your business unit: 7 Further, as one reviewer and the Editor pointed out, while we used Gosselin s levels of activity management, and were therefore limited to the three levels in that analysis, future studies could also include a fourth level of adoption where such a level would include activity-based budgeting, cost behaviour hierarchies and customer profitability analysis.

15 K.M. Baird et al. / Management Accounting Research 15 (2004) (a) Cost data is an important factor in pricing decisions. (b) Operating cost data is extremely important because of our cost reduction efforts. (c) Product cost data must be highly reliable to compete in our markets. Business unit culture Innovation and outcome orientation (O Reilly et al., 1991) Below is a list of values that may be used to describe the nature of the work environment in business units. For each item please indicate the extent to which it is valued in your business unit. Innovation: A willingness to experiment Not being constrained by many rules Being quick to take advantage of opportunities Being innovative Risk taking Outcome orientation: Being competitive Being achievement oriented Having high expectations for performance Being results oriented Being action oriented Tight versus loose control (Merchant, 1985) Below is a list of eight practices that may be used to describe the nature of the work environment in business units. For each item please indicate the extent to which you agree that the item represents current practices within your business unit. (a) Employee expectations are specified in detail. (b) Desired results are explicitly defined. (c) Work rules and/or specific work policies are widely used. (d) Direct supervision of employee activities takes place frequently. (e) Frequent monitoring of employee performance takes place. (f) Performance measures are precise and timely. (g) Performance reviews are detailed, comprehensive and frequent. (h) There is a strong link between the penalties imposed or rewards provided and the performance measures used. References Anderson, S.W., A framework for assessing cost management system changes: the case of activity based costing implementation at General Motors, J. Manage. Acc. Res. Fall, Björnenak, T., Diffusion and accounting: the case of ABC in Norway. Manage. Acc. Res. 8 (1), 3 17.