The use of management accounting information, learning and organizational performance

learning and organizational performance

European Business School Working Papers on Management

Accounting & Control, No. 11 (Revised Version)

Utz Schäffer/Daniel Steiners*

Chair of Management Accounting & Control

European Business School (ebs)

Oestrich-Winkel, May 2004

The use of management accounting information, learning

and organizational performance

by Utz Schäffer / Daniel Steiners

Abstract

This paper analyses the relationship between the use of management accounting information by CEOs of German manufacturing companies, individual learning and organizational per-formance.

Several hypotheses concerning the relationship between the use of management accounting information, individual learning and organizational performance are developed. It is argued that different types of information use (decision-making, monitoring and scanning) influence whether learning takes the form of mental model maintenance and/or mental model building. It is further proposed that the use of management accounting information has a positive im-pact on organizational performance both directly and indirectly via the afore mentioned learn-ing processes.

The proposed relationships are tested using structural equation modeling (LISREL). The data is derived from an empirical survey among CEOs of German manufacturing companies (sam-ple size of 449 responses). The results indicate that different types of management accounting information use have different effects on mental model maintenance and mental model build-ing of CEOs as well as on organizational performance.

1. Introduction

Most industries undergo substantial change, either driven by customers, competitors, or tech-nology suppliers (Achrol 1991; Williams 1992). This change creates continuous pressure for companies to adapt products and services to the changing needs of their customers as no com-petitive advantage is save from being overhauled by competitors (Bhide 1986; Ghemawat 1986; Williams 1992). Thus, it is no surprise that executives and scholars alike see continuous learning as a necessary prerequisite for lasting organizational performance (Choe 2002; de Geuss 1988; Kloot 1997).

A necessary precondition for learning is the perception and interpretation of information (Lovell 1980; Huber 1991). The importance of information for managers has been docu-mented extensively (Macintosh 1994; Mintzberg 1973; Tushman & Nadler 1978; Walsh 1995). While managers can choose from a wide range of internal or external information sources, one of the main sources within organizations is the management accounting system (Auster & Choo 1993; Macintosh 1994; Mintzberg 1973).

The use of management accounting information by chief executive officers (CEOs) is particu-larly important as they perceive and interpret information for the entire company and take action based on this information (Daft & Weick 1984; Hambrick & Mason 1984). Due to their position they have the greatest capacity to affect their company’s behavior and thus, perform-ance (Tripsas & Gavetti 2000; Vandenbosch & Higgins 1996).

Although learning has been associated with the use of management accounting information (e.g. Simons 1990; Bailey & McIntyre 1992; Kloot 1997; Abernethy & Brownell 1999), a model of the relationship between management accounting information use by CEOs, indi-vidual learning and organizational performance has not been fully developed yet. Our objec-tive in this paper is to develop such a model. More specifically, we investigate the following research questions:

• How does the use of management accounting information influence learning of CEOs in German manufacturing companies?

• How do the use of management accounting information and learning of CEOs in German manufacturing companies influence organizational performance?

In a study on executive support systems Vandenbosch (1993) analyzed the relationship be-tween the use of executive support systems, learning of senior executives and organizational performance in Canadian and US-companies (see also Vandenbosch & Higgins 1995, 1996; Vandenbosch & Huff 1997). Her model describes the process by which executive support systems lead to different types of learning and increased organizational performance. It also proposes that the type of information use determines the type of learning that is possible. While we base our analysis in large parts on Vandenbosch’s research model, it is important to keep in mind that her field of research were executive support systems which are different from management accounting systems in at least two respects: a) executive support systems are computer-based tools, b) executive support systems usually comprise more types of in-formation than the management accounting systems we are looking at. In addition, the cul-tural context of senior executives in Canadian and US-companies eleven years ago might be considerably different from the context of German CEOs today. So care has to be taken when comparing the results of the two studies. Furthermore, we propose two extensions of Vanden-bosch’s research model that aim at making it more suitable for our field of research.

The remainder of the paper describes our research and its results. It is divided into three sec-tions. In the first part, we commence by describing different types of information use and dividual learning. We then develop our hypotheses concerning the relationship between in-formation use, learning and organizational performance. The second section of our paper de-scribes the empirical methods used and the results. Finally, the last section discusses our re-search findings and the limitations of the study.

2. Research

model

2.1 Individual learning

Cognitive theories of learning form the theoretical basis of our investigation. From this per-spective, learning emerges from the interaction of a stimulus and the mind of the recipient, and results in a change of the recipient’s mental model (Piaget 1974; Tolman 1948; Wessels 1994). This construct found its way into management from psychology and clinical neurology (Bartlett 1932; Craik 1943; Tolman 1948). Since human beings are boundedly rational, they form mental models as simplified representations of their environment based on prior experi-ence in order to process information more efficiently (Daft & Weick 1984; Kiesler & Sproull

1982; Simon 1955). As a result, mental models are “the images, assumptions, and stories which we carry in our minds of ourselves, other people, institutions, and every aspect of the world. Like a pane of glass framing and subtly distorting our vision, mental models determine what we see” (Senge 1990, p. 235f.). They direct the gathering and interpretation of informa-tion and this informainforma-tion, in turn, helps to reinforce or change mental models. Based on the works of Piaget (1974), Maier (1945), and Norman (1982), Vandenbosch (1993) distinguishes two distinct types of learning:

• In mental model maintenance, existing mental models are (believed to be) appropriate to a given situation. New information fits into them and confirms existing assumptions, atti-tudes and beliefs.

• Mental model building refers to the process of rearranging, redefining or developing men-tal models to interpret and incorporate new or contradictory information that puts existing assumptions, attitudes and beliefs into question.

From a cognitive perspective, every time a piece of information is used by a manager, one of the two types of learning occurs. Either the information is integrated into the existing mental model or the model has to be changed. Similar descriptions of learning types are proposed by a number of authors. For example, Argyris and Schön (1978) distinguish between single-loop and double-loop learning, Fiol and Lyles (1985) between lower-level- and higher-level- learn-ing, Hedberg (1981) between adjustment and turnover learning and Senge (1990) between adaptive and generative learning.

As information is a necessary precondition for learning, the next section deals with the use of management accounting information as one of the main information sources for managers.

2.2 Management accounting information use

Following Horngren, Sundem and Stratton (2000) we define management accounting systems as “formal mechanisms for gathering, organizing, and communicating information about an organization’s activities” (p. 6). While more traditional management accounting systems used to focus on financial and historic information about events within the organization, modern management accounting systems also provide external, non-financial and future-oriented in-formation (Atkinson et al. 2000; Chenhall & Morris 1986; Mia & Chenhall 1994).

As learning requires the perception and interpretation of information, management accounting information has to be used by managers to trigger learning. Vandenbosch (1993) argues that

information can be used in two fundamental ways: Scanning and focused search. Scanning is the behavior executives exhibit when they browse through information without a particular question to answer or problem to solve (e.g. to understand trends or sharpen their general un-derstanding of the business), while focused search occurs when executives actively search for information, often in response to actual or suspected problems or opportunities (e.g. to verify performance results or to look up a specific piece of information).

Based on Huber (1991) und extending Vandenbosch’s model we find it useful to distinguish between two sub-types of focused use. If a manager actively searches for information to choose between possible courses of action, to set goals or to determine an adequate level and mix of resources to achieve those goals, he is using information for decision-making (Simon et al. 1954; Simons 2000). The manger can also actively search for information after a deci-sion has been implemented. In that case he uses information to benchmark actual against planned results to ensure that input, processes, and output are aligned to achieve organiza-tional goals (Simon et al. 1954; Simons 2000). We call this type of focused information use monitoring. The distinction between the two types of focused use enables us to take into ac-count specific performance effects of monitoring use that were neglected in the study of Van-denbosch (1993) (see section 2.5). In the next section we turn to the relationship between the three types of information use and learning of CEOs.

2.3 Information use and learning

Management accounting systems can be interpreted as rule sets (Roberts & Scapens 1996; Simons 1987). From this perspective, they are similar to the mental models held by individu-als. Like mental models they provide a simplified world view. They contain assumptions about what information is important and which characteristics of the environment are essen-tial. As they cannot include all information, the representation is partial, an interpretation through a particular framing of reality (Dent 1991; Hedberg & Jonsson 1978). A necessary consequence is that management accounting systems often only represent the status quo and do not contain enough and/or relevant information that indicates environmental changes: “Current information – and accounting – systems do more to stabilize organizations than to destabilize them. They filter away conflicts, ambiguities, overlaps, uncertainty, etc. and they suppress many relevant change signals and kill initiatives to act on early warnings” (Hedberg

& Jonsson 1978, p. 47; see also Argyris 1977). This point of view would lead to the conclu-sion that management accounting information use leads to mental model maintenance.

Some authors argue differently. They propose that management accounting systems can also signal the need for mental model building: “Information gathered by the management control system may be used to question the existing rationales for action and if the current strategies and structures are appropriate in a new environment” (Kloot 1997, p. 55). Hedberg and Jons-son (1978) note that management accounting information can stimulate curiosity, enable dia-lectical decision processes and help the organization to cope with environmental variety. Simons (1995) argues that the interactive use of management accounting information can question existing operating paradigms. From this perspective, management accounting infor-mation use can also lead to mental model building.

As CEOs search for information to make a specific decision or monitor certain results, they will seldom encounter information that puts their existing assumptions and beliefs into ques-tion: “When executives are engaged in focused search, in most instances, they will see what they expect to see. Unless the information is widely different from their expectations, mental model maintenance is most probable” (Vandenbosch & Higgins 1996, p. 203). For example, in the decision-making process CEOs may use management accounting information to ana-lyze the impact of a change in the mix and level of resources on the cost structure and produc-tivity of the organization while the underlying assumptions and policies are not questioned (Simons 2000). Similarly, in the monitoring process, the CEO may realize that actual results differ significantly from planned results. He may then try to analyze the reasons for that and take remedial action. However, if the underlying assumptions and policies are not questioned and the information is used to solve operating problems in a given context, monitoring use of management accounting information will lead to mental model maintenance (Flamholtz, Das & Tsui 1985; Kloot 1997; Ouksel, Mihavics & Chalos 1997; Schäffer 2001). Even scanning (as unfocused information use) leads to mental model maintenance if there is no new man-agement accounting information that arises during the scanning process or if a CEO is not receptive to new and unusual information (Day 1994; Vandenbosch & Higgins 1996).

Our argument is also supported by the findings of Vandenbosch (1993) who shows that fo-cused use of executive support systems and scanning both lead to mental model maintenance. Therefore we suggest:

• H1a: Management accounting information use for decision-making by CEOs is positively related to mental model maintenance.

• H1b: Management accounting information use for monitoring by CEOs is positively related to mental model maintenance.

• H1c: Management accounting information use for scanning by CEOs is positively related to mental model maintenance.

Decision-making, monitoring and scanning can also lead to mental model building if CEOs encounter information that puts existing assumptions, attitudes and beliefs into question: For instance, the decision to add a new production line may depend on an analysis of accounting data that provides insight into the economics and profitability of the business (Simons 2000). In this case management accounting information can signal that existing assumptions and beliefs regarding the profitability of the product portfolio are no longer appropriate and that existing mental models need to be changed.

If expectations are not met during monitoring activities managers may also question their ex-isting mental models (Hedberg 1981; Siegwart & Menzl 1978). For example, management accounting information can indicate that expectations regarding the profitability of a product in a certain market are not met. An analysis of the variance between actual and planned results could lead to the insight that the product does not meet the customer's needs in that specific market. Managers have to change their existing mental model regarding the product and the market as it does not correspond to reality any more. As a consequence of that insight the company might adapt its product to the customer needs or withdraw from the market (Sieg-wart & Menzl 1978).

Several authors argue that particularly scanning helps to identify blind spots, foster the user's creativity and therefore contributes to mental model building. For example, in a study investi-gating the change of mental models of MBA students El Sawy and Pauchant (1988) find a positive impact of scanning on mental model building. In a study investigating the decision-making of CEOs, Eisenhardt (1989) draws the conclusion that managers who use information for scanning accelerate their cognitive processing which speeds decision-making. Daft, Sor-munen and Parks (1988) show that CEOs in successful companies scan broader and more often than senior managers in less successful companies. They argue that scanning may be proactive in finding opportunities and detecting problems and therefore enables the organiza-tion to achieve a better strategic fit. In an investigaorganiza-tion of budget informaorganiza-tion use by managers

Macintosh and Williams (1992) observe that some managers scan through their budget infor-mation to pick up relevant changes in their environment early on. Thomas, Clark and Gioia (1993) found that CEOs who use high levels of information during scanning tend to interpret strategic issues as positive for the organization and feel they have more control over them. Finally, Vandenbosch (1993) also shows a positive impact of scanning on mental model building of senior executives.

In view of these findings we assume that management accounting information can also lead to mental model building when it is used for scanning and – extending Vandenbosch’s model – for decision-making and monitoring. Hence, we propose:

• H2a: Management accounting information use for decision-making by CEOs is positively related to mental model building.

• H2b: Management accounting information use for monitoring by CEOs is positively related to mental model building.

• H2c: Management accounting information use for scanning by CEOs is positively related to mental model building.

In the next section we turn to the impact of learning on organizational performance.

2.4 Learning and organizational performance

The CEO of an organization usually represents the most knowledgeable person regarding an organization’s strategy and is the one most responsible for action intended to align an organi-zation’s strategy, structure, processes, and environment (Daft & Macintosh 1981; Thomas, Clark & Gioia 1993; Zajac & Shortell 1989). CEOs perceive and interpret information for the entire organization and take action based on this information (Hambrick & Mason 1984). It is therefore widely accepted that CEOs have significant impact on organizational performance (e.g. Burke & Steensma 1998; Fritz 1995).

The perception and interpretation of information by CEOs is influenced by their mental mod-els. Negative consequences of selective perception and incorrect interpretation of environ-mental stimuli by CEOs and other senior executives on organizational performance have been documented extensively (Burgelman 1991; Ghemawat 1991; Mintzberg 1978; Rindova & Fombrun 1999; Starbuck 1983; Starbuck & Milliken 1988).

For instance, Tripsas and Gavetti (2000) show in their study of the Polaroid Corporation how existing mental models of top executives can prevent a company from adapting to a changing

environment. Tripsas and Gavetti describe that two central beliefs were deeply engraved in the mental models of Polaroid's top management. The first one was the belief in Polaroid’s technical competency as the company's main competitive advantage. The second belief was the management's conviction that the financial performance of Polaroid depends on the sales of consumables (films) and not on the sales of hardware (cameras). As the upcoming digital imaging did not have consumables (and therefore did not fit into the existing razor/blade business model), Polaroid’s top-management decided to stop its investments in digital imag-ing and focus on instant photography. The existimag-ing business model was so deeply engraved in the management's mental models that other possible business models were ignored and the market change towards digital photography was not realized until it was too late. Of particular importance in this case study is the fact that while subordinate managers realized the changing environment early enough and urged their top executives to change their strategy, top execu-tives decided to follow the old business model and therefore kept the company from adapting to the changing customer needs.

In a case study of two railroads Barr, Stimpert and Huff (1992) also show the impact of men-tal models on organizational performance. The authors observed that the senior management of the more successful company changed its mental models quite often and incrementally dur-ing the period of the study. In the less successful company there was only one fundamental change of the senior management's mental model. Changes in action and beliefs were not evi-dent until the company was near bankruptcy. From their observation Barr, Stimpert and Huff draw the conclusion that the reason for the different behaviors may have been the result of the different mental models of the CEOs of the organizations. During a difficult time in the rail-road industry, the more successful firm was lead by a CEO with no previous railrail-road experi-ence, and therefore no railroad-specific mental model, while the less successful company was led by a succession of railroad-experienced CEOs with deeply ingrained models of the busi-ness that were no longer appropriate in the changed environment.

Therefore, the change of mental models is regarded as a necessary precondition for sustain-able organizational performance. Without mental model building stagnation commences and the organization ultimately fails (Hall 1984; Vandenbosch 1993). However, mental model building alone is not sufficient to influence organizational performance. The change of mental models has to be reflected in the CEO’s action and other individuals in the company (Daft & Weick 1984; Thomas, Clark & Goia 1993).

Managerial action is evaluated by judging whether it is effective (“doing the right things”) or efficient (“doing things right”) (Otley 1978; Ruekert, Orville & Roering 1985; Reed 1991). As the two cases show, mental model building is closely related to the effectiveness of mana-gerial action, i.e. whether the right action is taken or not. Mental model maintenance on the other hand aims at detecting and correcting errors within existing structures. As mental mod-els make it unnecessary to construct understanding from scratch each time similar information is encountered, stable mental models improve productivity, speed decision-making and are consequently related to improvements in efficiency.

Therefore, mental model building is a necessary condition for improvements in effectiveness and mental model maintenance is necessary for improvements in efficiency. The empirical findings of Vandenbosch (1993) support this argument in the context of executive support systems. Her results indicate that mental model building is indeed positively related to effec-tiveness while mental model maintenance is positively related to efficiency. In the face of these findings we propose a positive impact of mental model maintenance on efficiency and of mental model building on effectiveness. Hence:

• H3: Mental model maintenance is positively related to efficiency. • H4: Mental model building is positively related to effectiveness.

Effectiveness and efficiency of organizational action are both seen as necessary preconditions for organizational performance: “… highly efficient firms that are not effective in producing the goods and services demanded by customers do not survive. Equally, firms that are highly effective in the production of the requisite goods and services but have overly high costs, and thus are not efficient, do not survive. They are overtaken and replaced by firms with better cost structures” (Reed 1991, p. 60; see also March 1991; Vandenbosch 1993). Since effi-ciency means low employment of resources (e.g. time and money) to achieve organizational goals it should have a positive impact on financial performance. This argument is also sup-ported by Vandenbosch (1993) who shows that efficiency is weakly but significantly related to organizational performance. Hence, we propose:

• H5: Efficiency is positively related to financial performance.

In the dynamic environment facing most organizations, effective action in the form of new products and services (Miles 1982) is expected to enable competitive advantage (Thomas, Clark & Gioia 1993). Empirical evidence from several studies supports this argument. In a study of U.S. domestic airlines Smith et al. (1991) come to the conclusion that successful

air-lines realize competitive actions sooner than less successful airair-lines and also take appropriate responses immediately. Shortell, Morrison, and Friedman (1990) show that successful hospi-tal managers recognized and responded to changing needs of their patient bases rapidly. Simi-larly, Thomas, Clark and Gioia (1993) come to the conclusion that hospitals that are charac-terized by growth in their product and service offerings exhibit higher performance than hos-pitals characterized by little or no growth. Finally, Kuratko, Ireland and Hornsby (2001) show in a longitudinal study of an insurance company that adapting to changing environments and developing new products were two of the main reasons for the successful development of the company. The results of these studies lead to the conclusion that improvements in effective-ness due to mental model building should enable companies to adapt to new market condi-tions adequately and rapidly. This argument is supported by Schäffer and Willauer (2003) who show that the effectiveness of the strategic planning process is positively related to or-ganizational adaptiveness. In the view of these findings we assume:

• H6: Effectiveness is positively related to adaptiveness.

Schreyögg and Steinmann (1985) note that the potential strategic advantage of quick re-sponses to environmental turbulence needs to be weighed with the risk of maladaptions. If the benefits of increased adaptiveness outweigh the costs, adaptiveness should positively influ-ence the financial performance of the company. This argument is supported by several studies that show that adaptiveness is positively related to market performance and financial perform-ance (Dehler 2001; Schäffer & Willauer 2003; Smith et al. 1991). These findings lead to the following hypothesis:

• H7: Adaptiveness is positively related to financial performance.

So far we have argued that management accounting information use influences organizational performance indirectly via learning by CEOs. In the next section we address the immediate impact of management accounting information use on organizational performance.

2.5 Information use and organizational performance

The distinction of monitoring and decision-making as two types of focused information use enables us to take account not only of the indirect but also of the direct impact of monitoring activities on organizational performance. While all three types of information use indirectly influence organizational performance via the afore mentioned types of learning, monitoring also influences performance directly. This is due to the fact that monitoring by a supervisor

can influence the behavior of subordinates. If a subordinate realizes that his work is monitored by a supervisor he will usually put more effort into achieving planned results (Merchant 1985; Schäffer 2003; Treuz 1974).

The classic Hawthorne studies show that the mere presence of observers is sufficient to influ-ence the performance of groups, even if nothing in the work environment is changed (Roeth-lisberger and Dickson 1939). Blau (1955) found that the evaluation of subordinates on the basis of quantitative performance indices influenced their behavior. Subordinates increased their productivity due to the monitoring of their supervisors: „The supervisor wanted to know the number of interviews completed by each subordinate only in order to take corrective ac-tion in case any of them worked too slowly. The fact that the very counting of interviews had induced them to work faster facilitated operations by making such corrective steps superflu-ous. The use of statistical records not only provided superiors with information which enabled them to rectify poor performance but often obviated the need for doing so“ (p. 35). In a series of studies Churchill and Cooper (1961; 1964; 1966) also show, that monitoring, the an-nouncement of monitoring activities or the existence of a monitoring authority influences the behavior of people in an organization.

This leads to the proposition that the use of management accounting information by CEOs influences the behavior of subordinate managers and increases their individual performance (e.g. by ensuring that the right goals are pursued and that all goals are achieved with a mini-mum level of resources). This increase in individual performance should finally lead to an increase in organizational effectiveness and efficiency. Extending the model of Vandenbosch we therefore propose:

• H8: Management accounting information use for monitoring by CEOs is positively related to efficiency.

• H8: Management accounting information use for monitoring by CEOs is positively related to effectiveness.

The next section describes the methods used to test the proposed hypotheses.

3. Methods

A self-administered questionnaire was sent to the CEOs of 3.500 German manufacturing companies with 100 to 2.000 employees. A total of 449 usable responses (12.8%) was re-ceived. The sample was tested for non-response bias by splitting it in three equally large parts according to the return date of the questionnaires (Armstrong & Overton 1977). The mean responses for 79 variables in the three groups were compared with each other. Only three sig-nificant differences were identified, providing some support for the absence of a non-response bias.

The questionnaire was pre-tested by a group of academics and managers, prior to postage. This resulted in changes to some of the wording and the presentation of the questionnaire. The survey instrument consists of demographic data, including sales revenue and employee num-bers, and questions that measure the variables of interest. As far as possible all scales were adapted from prior research. New scales were developed only if no prior research existed. All variables were measured on a five-point scale.

In our survey we rely on self-reported and perceptual measures. The CEO’s perception was considered appropriate in this situation, compared to the use of more objective measures for several reasons. First, it is difficult (if not impossible) to measure objectively variables such as the different types of information use and the types of learning. Secondly, self-reported measures are the easiest and most efficient way to gather data from a large number of CEOs. Finally, several studies show that self-reported and objective measures are highly correlated (Cagwin & Bouwan 2002; Dess & Robinson 1984; Robinson & Pearce 1988; Shortell & Za-jac 1990). However, as dependent and independent variable data are collected from a single informant, common method bias can still be a potential problem (Podsakoff & Organ 1986). What follows is a brief description of the measurement instruments (for details see appendix): Decision-making describes the extent to which management accounting information is used for supporting a specific decision respectively solving a particular problem. It was measured based on a scale used by Karlshaus (2000), Hunold (2003) and Sandt (2003).

Monitoring describes the extent to which management accounting information is used to compare actual against planned results and to supervise activities in their respective areas of responsibility. The measurement instrument was developed for this study.

Scanning describes the extent to which management accounting information is used without having a particular decision to make or problem to solve. It aims at increasing the user’s

knowledge base to improve future decision-making and monitoring. The measurement in-strument was developed for this study.

Mental model maintenance and mental model building were measured using measurement instruments developed by Vandenbosch (1993) in her investigation of the relationship be-tween the use of executive support systems and learning of senior executives. Mental model maintenance measures in how far management accounting information confirms existing as-sumptions, attitudes and beliefs and can be integrated into existing mental models. Mental model building measures in how far management accounting information has the potential to put existing assumptions, attitudes and beliefs into question, foster the user’s creativity, in-crease the user’s scope and hence may lead to the creation of new mental models.

Efficiency and effectiveness of organizational action was measured using measurement in-struments developed by Vandenbosch (1993). Efficiency was measured by asking CEOs in how far the management accounting system improves productivity, speeds decision-making and increases efficiency. Effectiveness was measured by asking in how far the management accounting systems facilitates innovation, determines which products and services to market, makes the organization more flexible and improves the organization’s effectiveness.

Although the importance of the performance concept is widely recognized, its conceptualiza-tion in research settings is one of the thorniest issues confronting researchers. The narrowest concept centers on the use of simple out-come-based financial indicators that are assumed to reflect the fulfillment of the economic objectives of the company. Typically, the researcher chooses indicators such as sales growth, return on investment, return on sales, and return on equity. In addition, reflecting the popular view that market or value-based measurements are more appropriate than are accounting-based measures, some studies have used measures such as market-to-book value or stock-market returns. A broader conceptualization of organiza-tional performance also includes indicators of operaorganiza-tional performance such as market-share, new product introduction, product quality, manufacturing value-added, and other measures of technological efficiency within the domain of organizational performance.

For this study we consider two dimensions of organizational performance: adaptiveness and financial performance (Schäffer & Willauer 2003). Adaptiveness reflects the company’s abil-ity to adapt to changes in its environment (e.g. by adapting the product portfolio to changing customer needs, exploitation of new opportunities in the market) (Ruekert, Walker & Roering 1985; Krohmer 1999). It was measured using a scale developed by Dehler (2001). Financial

performance was measured using sales on return and increase in company value. Sales on return has been used in several empirical investigations as a measure for financial perform-ance (Dehler 2001; Dess, Ireland & Hitt 1990; Hatten, Schendel & Cooper 1978). In addition, reflecting the view that market or value-based measurements are more appropriate than are accounting based measures, we include increase in company value as a second indicator (Günther 1997).

To provide an appropriate frame of reference, the CEOs were asked to rate their company’s adaptiveness and financial performance in relation to that of competitors. The comparison with similar firms provides a form of control for differences in performance that may be due to industry and strategic group effects. But as both dimensions are again subjective assess-ments of CEOs, biased responses cannot be excluded.

3.2 Models

Structural Equation Modeling (SEM) was used to analyze the proposed hypotheses as this technique has several advantages compared to the more commonly used regression analysis in management accounting. Firstly, SEM takes into account error variances associated with multi-item constructs. Secondly, it allows to consider many relationships within a single analysis. Finally, it makes it possible to determine several measures of fit (Baines & Lang-field-Smith 2003; Homburg 1992).

As recommended by Schumacker and Lomax (1996) a two-stage process was used. In the first stage, each latent variable was modeled as a separate measurement model. A measure-ment model relates observed variables to their latent variable. In this case the latent variables were decision-making, monitoring, scanning, mental model maintenance, mental model build-ing, efficiency, effectiveness, adaptiveness and financial performance. The second stage in-volved constructing the structural model by specifying the relationships between the latent variables.

Formulating measurement models for the variables involved using LISREL to conduct con-firmatory factor analysis for each set of items. Covariance were included between error terms in each measurement model where suggested by LISREL, but only where such covariance were justified theoretically. A number of items were deleted to improve the quality of the measurement models (Baines & Langfield-Smith 2003).

Model fit was measured by using an adequate selection of fit indices as suggested by Scher-melleh-Engel, Moosbrugger and Müller (2003):

• The χ2

-test was used to test the significance of the proposed model. Due to the sensitivity of the χ2_{-test to sample size, the relative χ}2 _{(ratio of χ}2

and the degrees of freedom) was used. It should be 3 (2) or less for an acceptable (good) model.

• The Rooted Mean Square Error of Approximation (RMSEA) and the Standardized Root Mean Square Residual (SRMR) were considered as descriptive measures of overall model fit. Both measures indicate to which extent a structural equation model corresponds to the empirical data. Both values should be below 0.1 for an acceptable and 0.05 for a good model fit.

• The Nonnormed Fit Index (NNFI), the Comparative Fit Index (CFI) and the Adjusted Goodness of Fit Index (AGFI) were used as descriptive measures based on model compari-sons. Comparison indices measure whether or not the model of interest is an improvement relative to an independent model. Values above 0.95 (0.97) for NNFI and CFI indicate an acceptable (good) model fit. The corresponding values for AGFI are 0,85 (0,90).

In addition to these fit measures, Cronbach’s α was computed for all measurement models as it is one of the most often used measures for construct reliability (Carmines & Zeller 1979; Cronbach 1951). Values above 0.6 (0.7) indicate an acceptable (good) model fit (Malhorta 1993; Nunnally 1978). When evaluating model fit it has to be considered that not all fit indi-ces have to be above the required levels for acceptable model fit. It is always possible that a model may fit although one or more fit indices may suggest bad fit (Homburg & Baumgartner 1998; Schermelleh-Engel, Moosbrugger & Müller 2003).

Table 1 provides details of the model fit for all measurement models.

Variable α χ2

/ df RMSEA SRMR NNFI CFI AGFI Decision-making 0,67 5,66 0,10 0,03 0,91 0,99 0,94

Monitoring 0,79 0,98 0,0 0,01 1,0 1,0 0,99 Scanning 0,63 0,21 0,0 0,01 1,0 1,0 1,0 Mental model maintenance 0,81 −* −* −* −* −* −*

Mental model building 0,88 3,11 0,07 0,01 0,99 1,0 0,97 Efficiency 0,81 −* −* −* −* −* −*

Effectiveness 0,78 2,24 0,05 0,02 0,99 1,0 0,98 Adaptiveness 0,81 −* −* −* −* −* −*

Financial performance 0,78 −* −* −* −* −* −* *: As variables have two or three items only, the measurement models have 0 degrees of freedom.

A computation of these fit indices is therefore not meaningful.

Table 1: Model fit for measurement models

As Table 1 shows, almost all fit measures indicate a good or acceptable model fit for each measurement model. Only “decision-making” has two indices (χ²/df, NNFI) below the re-quired minimum for an acceptable model fit.

In the second stage of our analysis the structural model was constructed by specifying the relationships between the latent variables in line with the hypotheses. As can be seen from Table 2 all fit indices indicate a good (χ²/df, RMSEA, NNFI, CFI) or acceptable (SRMR, AGFI) model fit.

Fit indice Value

χ² 678,81 df 408 χ²/df 1,66 RMSEA 0,038 NNFI 0,97 SRMR 0,07 CFI 0,97

AGFI 0,89

Table 2: Fit of structural model Figure 1 shows the structural model.

Decision-making Monitoring Scanning + 0,31 **** + 0,11 ** + 0,15 *** Mental Model Maintenance Mental Model Building Efficiency Effectiveness + 0,20 **** + 0,38 **** + 0,24 **** + 0,18 **** + 0,12 ** Financial Performance Adaptiveness + 0,35 **** + 0,36 **** + 0,05 ns + 0,28 **** + 0,34 ****

Level of significance: * 10% ** 5% *** 1% **** 0,1% ns not significant

Figure 1: Structural model

3.3 Results

The results from the structural model were used to test the hypothesized research model. Hy-potheses 1a to c proposed that decision-making, monitoring and scanning have a positive im-pact on mental model maintenance. These hypotheses are supported by the model. The paths from decision-making and scanning to mental model maintenance are positive and significant at p ≤ 0.01, the path from monitoring to mental model maintenance is also positive and sig-nificant at p ≤ 0.05.

In hypotheses 2a to c it was assumed that decision-making, monitoring and scanning are posi-tively related to mental model building. These hypotheses are also supported. The paths from

decision-making and scanning to mental model building are positive and significant at p ≤ 0.01 and the path from monitoring to mental model building is positive at p ≤ 0.05.

Hypotheses 3 and 4 proposed that mental model maintenance is positively related to im-provements in efficiency while mental model building is positively related to imim-provements in effectiveness. Both hypotheses are supported. The path coefficients from mental model maintenance to efficiency and from mental model building to effectiveness are positive and significant at p ≤ 0.01.

Hypothesis 5 predicted a positive impact of efficiency on financial performance. As the path coefficient from efficiency to financial performance is not significant the hypothesis is not supported.

In hypotheses 6 and 7 it was assumed that mental model building has a positive impact on organizational adaptiveness and adaptiveness is positively related to financial performance. Both hypotheses are supported as the path coefficients are positive and statistically significant at p ≤ 0.01.

Finally hypotheses 8 and 9 proposed that monitoring is positively related to efficiency and effectiveness. These hypotheses are also supported as the paths from monitoring to efficiency and effectiveness are positive and significant at p ≤ 0.01.

A summary of the findings relating to the hypotheses is shown in Table 3.

Hypothesis Support/ reject Level of sig-nificance

H1a Management accounting information use for decision-making by CEOs is positively related to mental model maintenance.

supported 1%

H1b Management accounting information use for monitoring by CEOs is positively related to mental model maintenance.

supported 5%

H1c Management accounting information use for scanning by CEOs is positively related to mental model maintenance.

supported 1%

H2a Management accounting information use for decision-making by CEOs is positively related to mental model building.

supported 1%

H2b Management accounting information use for monitoring by CEOs is positively related to mental model building.

supported 5%

positively related to mental model building.

H3 Mental model maintenance is positively related to efficiency. supported 1% H4 Mental model building is positively related to effectiveness. supported 1% H5 Efficiency is positively related to financial performance. rejected

H6 Effectiveness is positively related to adaptiveness. supported 1% H7 Adaptiveness is positively related to financial performance. supported 1% H8 Management accounting information use for monitoring by CEOs is

positively related to efficiency.

supported 1%

H9 Management accounting information use for monitoring by CEOs is positively related to effectiveness.

supported 1%

Table 3: Summary of hypotheses testing

4. Discussion

The survey provides strong support for our research model on the relationship between man-agement accounting information use, learning by CEOs and organizational performance. First of all, the results indicate that the use of management accounting information for decision-making, monitoring and scanning does not only support mental model maintenance but also helps to build new models by questioning existing assumptions, attitudes and beliefs. These findings support our first extension of Vandenbosch’s (1993) model: we show that decision-making and monitoring do not only lead to mental model maintenance but can also lead to mental model building.

The relationship between information use for decision-making and mental model maintenance is stronger than the relationship between decision-making and mental model building. This provides some evidence for Vandenbosch’s (1993) argument that focused search primarily leads to the verification of existing assumptions, attitudes and beliefs. However, monitoring is only weakly related to the two types of learning. We could imagine that monitoring very often does not directly lead to the learning of CEOs but that the results of monitoring activities are used as input in following decision-making processes.

The relationship between scanning and mental model building is stronger than the relationship between scanning and mental model maintenance. That could indicate that if management accounting information is used for scanning, mental model building is more likely to happen than mental model maintenance. Therefore an increase in scanning would help CEOs to chal-lenge their existing assumptions, attitudes and beliefs. Since a broad scope of management accounting information and flexible access are necessary prerequisites for scanning, CEOs have to make sure that they do not only get reports with aggregated pieces of information but that they also have access to detailed information (e.g. by implementing computerized man-agement information systems).

As in Vandenbosch’s (1993) model our research model shows that mental model maintenance is positively related to efficiency while mental model building is positively related to effec-tiveness. The results of our survey further indicate that effectiveness is positively related to organizational adaptiveness and that organizational adaptiveness is positively related to finan-cial performance. Efficiency, however, is not positively related to finanfinan-cial performance. Hence, it appears that although executives value improvements in both efficiency and effec-tiveness, they believe that improvements in financial performance are principally the result of effectiveness and adaptiveness. A possible explanation for the missing link between effi-ciency and financial performance is based on the fact that our sample consists of German manufacturing companies. Due to intense competition most of those companies have already increased their efficiency to such an extent that from the CEOs' point of view a further in-crease in efficiency may not contribute significantly to financial performance. This matches the findings of Vandenbosch (1993) who shows a significant but weak link between effi-ciency and organizational performance. She concludes that effieffi-ciency does not have a sub-stantive impact on organizational performance.

All three types of information use influence organizational performance indirectly via the afore mentioned learning processes. In a second extension of Vandenbosch’s model we argue that monitoring also influences organizational performance directly. Our survey provides evi-dence that monitoring use of management accounting information by CEOs has a direct im-pact on efficiency and effectiveness of organizational action. The relationship between moni-toring and efficiency is stronger than the relationship between monimoni-toring and effectiveness. This corresponds to the prevailing opinion that management accounting information is pri-marily intended to increase organizational efficiency.

As always there are limitations to this study that provide important challenges for future re-search:

• Although the data supports all the hypotheses except for H5, a limitation of the study is that some of the standardized path coefficients are rather small (especially from monitoring and scanning to mental model maintenance and mental model building). This means that although they are statistically significant they do not have high predictive power (Chin 1998). This could mean that the impact of management accounting information use on maintaining or changing mental models is not as strong as we expected. As suggested in the literature it may be that other information sources (e.g. personal contacts) are more im-portant for CEOs (Daft, Sormunen & Parks 1988; Mintzberg 1973) and that the use of in-formation from these sources has a stronger impact on the learning of CEOs. Therefore, fu-ture research should also investigate the relationships between information use, learning and organizational performance by considering additional information sources.

• The sample for the study was selected from German manufacturing companies. Generaliz-ing the results to other industries (such as retail or service industries) or countries should be done cautiously. Therefore, future studies should also consider possible culture-specific differences in the use of management accounting information.

• Our research relies on user perceptions and self-reported measures. The collection of de-pendent and indede-pendent variables from a single informant may lead to common method bias. Particularly, the use of self-rating scales to measure organizational performance is likely to result in higher mean values (higher leniency error) and a restricted range (lower variability error) of scores (Chong & Chong 1997). It also seems likely that companies that are dissatisfied with their management accounting system would be less prone to answer-ing our questionnaire. Hence, the sample might contain a larger proportion of “good” man-agement accounting systems than it is the case in the population of all manman-agement ac-counting systems. Unfortunately, the information use and mental model constructs would have been difficult to obtain for large numbers of respondents in any other way.

• The study assumes unidirectional relationships between variables. It is possible, however, that some relationships are in the opposite direction, or even reciprocal. Also causal effects of learning on performance may be subject to time-lag and thus may not necessarily be captured to their full extent as the survey research methodology allows for examination of

statistical associations at one point in time only. Therefore, longitudinal analyses could be employed to systematically investigate the causal relationships proposed in our study. • SEM does not imply causal relationships between the variables under investigation

(Nachtigall et al. 2003). It only means that if the fit of the model is acceptable, the assumed relationships between the various latent variables are regarded as being supported by the data. Strictly speaking, the assumed model is not rejected.

• Another limitation of structural equation modeling is that the relationships between the variables are assumed to be linear. However it may be that they are not linear at all or that the relationships exhibit linearity only within a limited relevant range. These types of rela-tionships could be evaluated with a case study approach.

• This study focused on three particular types of management accounting information use (decision-making, monitoring and scanning). As other types of information use (e.g. power-oriented information use) are mentioned in the literature (e.g. Vandenbosch 1999; Karlshaus 2000; Schäffer & Steiners 2003), further research is needed to investigate the impact of those types of information use on learning and organizational performance. • A final limitation is related to construct development. A single data collection was used to

purify the measures and test the structural model in the survey data analysis. A second data collection would have been better to improve the psychometric properties of the measure-ment instrumeasure-ments. However, a sample of CEOs is difficult and expensive to collect. It was felt that changes to the measurement model were not sufficiently substantive to warrant the use of the resources required for a second data collection.

In spite of all limitations the results of this research should help CEOs to gain a better under-standing of the potential management accounting systems have for improving organizational performance. Since mental model building influences organizational effectiveness and – indi-rectly – adaptiveness and financial performance, CEOs should make sure that they use their management accounting system not only for focused search (i.e. decision-making and moni-toring) but also for scanning. In addition, imformation use for monitoring can influence or-ganizational performance not only indirectly via the learning of CEOs but also directly due to the fact that monitoring by the CEO stimulates learning of subordinate managers and influ-ences their behavior accordingly. These learning effects can help CEOs to adapt their organi-zation’s products and services to the changing customer needs and to ensure lasting organiza-tional performance.

Appendix: Measurement instruments

Without management accounting information my decisions would be different. I use management accounting information directly for making decisions.

The management accounting information direct my attention to aspects of my decision that I would not have taken into consideration otherwise.

I hardly use management accounting information for decision-making. (R) (R): Reverse coded item

Learning ex post (monitoring)

Management accounting information helps me to monitor activities in my area of responsibility. Management accounting information helps me to realize deviations from plans.

I use management accounting information to monitor key performance indicators (e.g. gross margins, costs).

Management accounting information helps me to supervise the implementation of my decisions.

Scanning

I use management accounting without having to make a specific decision or having to solve a particular problem.

I use management accounting information to improve my understanding of the business. I browse through management accounting information without having specific questions to an-swer.

I use management accounting information to get a “big picture perspective” on my business.

Mental model maintenance

Management accounting information helps me to verify my assumptions. Management accounting information helps me to maintain my perspectives. Management accounting information helps me to support my actions.

Mental model building

Management accounting information fosters my creativity.

Management accounting information helps me to reorient my thinking. Management accounting information helps me to broaden my outlook.

Management accounting information helps me to question my preconceptions.

Efficiency

The management accounting systems improves productivity. The management accounting systems speeds decision-making. The management accounting system improves our efficiency.

Effectiveness

The management accounting system improves the organization’s effectiveness. The management accounting system facilitates innovation.

The management accounting system enables us to determine which products and services to market.

The management accounting system makes us more flexible.

Adaptiveness

Adpation of products/services to new customer needs. Fast reaction to changes in the market.

Fast exploitation of new opportunities in the market.

Financial Performance Return on sales.

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