Related Literature and Hypotheses
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There has been a considerable interest in the study of the relationship between strategy, MCS and performance. Previous research in this area can be categorized into
three main streams. First, studies that investigate the impact of strategy on MCS Quanttrone Hopper, 2005; Langfield-Smith, 1997; Abernethy Lillis, 1995;
Abernethy Guthrie, 1994; Dent, 1990; Simons 1987. This stream of research considers MCSs as strategy implementation systems. The basic argument is that MCS
should be designed to support a firm‘s chosen strategy to gain competitive advantage and superior performance. Quattrone Hopper 2005, for example, proposed that
different strategies will lead to different configurations, implementations, and usage of management control systems. Other authors suggest that prospector and defender
strategies require quite different design and use of MCA e.g., Abernethy Lillis, 1995; Abernethy Guthrie, 1994; Langfield-Smith, 1997, Simons, 1987. Miles and Snow
1978, for example, found that a particular configuration of task technology, structure, and process is adopted by firms to match their strategy. In their study, they found that
firms that adopt a defender strategy tend to adopt a functional structure with high formalization to support their capability to operate efficiently. In contrast, firms that
adopt a prospector strategy tend to adopt low formalization to support their ability to create new product and exploit market opportunities. For firms that adopt an analyzer
strategy, they tend to adopt a functional structure characterized by fluid product-market group to balance the pressure for innovation and efficiency.
A second stream of research examines the influence of MCS on strategy Chenhall Euske, 2007; Chenhall, 2005; Bisbe Otley, 2004; Marginson, 2002; Dent,
1991. This stream of research considers MCS as systems that are used by management to formulate a firm‘s strategy. Chenhall and Euske β007, for example,
investigated the role of activity based cost management ABCM in a strategic change process. Based on their study in an Australian and a US military organization, they
found that information generated from the ABCM systems is used by the organizations
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to influence the planned organizational change. Naranjo-Gil and Hartmann 2007 conducted a survey of 103 Spanish public hospitals. They found that top management
team use management accounting systems for strategic change. Based on a longitudinal study of a public sector entity spanning five years, Kober, Ng and Paul
2007 found that management control systems help to facilitate a change in strategy for their sample organizations. In a similar vein, Dent 1991 found that railway
organizations used MCS to change their strategic orientation from a government dependent to a business oriented strategy.
A third stream of research investigates the impact of aligning strategy and MCS on performance e.g., Sandino, 2007; Ittner, Larcker, Randall, 2003; Simons, 1987.
This perspective is based on the premise that strategy-MCS fit is achieved when the characteristics of a business strategy and control systems are joined together in a
particular configuration to achieve completeness in a description of a social system Van de Ven, 1979. As such, the performance effects of misfits should reflect the
simultaneous and holistic pattern of inter-linkages between strategy and control systems Venkatraman and Prescott, 1990.
Despite its intuitive appeal, previous studies investigating the effects of strategy-MCS misfits have reported weak and often contradictory results e.g, Ittner,
Larker Randall, 2003; Sandino, 2007; Simons, 1987. Several authors have suggested that the link between strategy, MCS and performance is not fully understood
Chapman, 2005; Skaerbaek Tryggestad, 2009. Ittner, Larcker Randall, 2003 investigated whether firm performance is
positively associated with the extent to which management control systems are aligned with the firm‘s strategy. Based on a survey of US financial services firms, they found
little support that deviation from the ―ideal‖ profile negatively affect performance.
Sandino 2007 used a sample of US retailer to investigate the impact of strategy-MCS fit on performance. She employed four types of MCS: basic MCS focus
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on planning, setting standards and establishing the basic operations, cost MCS emphasize on enhancing operating efficiencies and minimizing costs, revenue MCS
use to foster growth and customer responsiveness, and risk MCS focus on reducing risks and protecting assets integrity. She reported that firms that match their MCS with
their intended strategy outperform those that reveal a strategy-MCS mismatch. Based on a sample of 76 firms, Simons 1987 reported that the use of tight
budget goals and forecast data in control reports was positively related to performance for prospectors but not for defenders. However, the establishment of goals related to
outputs and close monitoring of results were positively related to performance for prospectors but negatively related to performance for defenders. He concluded that
intensive use of financial control systems is more effective for prospectors than defenders.
Some researchers have argued that the conceptual notion of strategy-MCS misfits is only understood implicitly rather than in explicit functional forms e.g.,
Venkatraman Prescott, 1990; Scherer, 1980. Venkatraman and Prescott 1990 argued that previous research has used phrases like ―matched with‖, ―contingent upon‖
or ―congruent with‖ without necessarily providing precise guidelines for translating such phrases into the operational domain of empirical research and statistical tests. As such,
there is a lack of general consensus regarding the conceptualization of misfits and its related empirical tests.
We conceptualize strate gy based on εiles and Snow‘s 1978 generic strategy
taxonomy which provides the richest portrayal of organizational arrangements associated with particular strategies Dent, 1990. This typology is unique because it
views the organization as a complete and integrated system in dynamic interaction with its environment McDaniel and Kolari, 1987. Miles and Snow 1978 argued that
prospector, defender, and analyzer are all viable strategies. The key dimension underlying this typology is the organization‘s response to changing environmental
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conditions. According to Miles and Snow, defenders have narrow product-market domains and tend not to search outside their domains for new opportunities.
Prospectors continually reach for market opportunities and tend to be creators of change in the industry. Analyzers are a mixture of both, operating in perhaps one
relatively stable and one changing product-market domain. εCS are conceptualized based on Van de Ven and Ferry‘s 1980 and Drazin
and Van de Ven‘s 1985 notion of organizational process or control. We focus on control systems that have been used in the accounting literature namely performance
evaluation, compensation, communication, conflict resolution, commitment, and product and market policy e.g., Selto, Renner and Young, 1995; Gresov, 1989.
This study uses the holistic perspective
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to determine the misfits between business strategy and MCS e.g., Van de Ven, 1979; Selto, Renner Young, 1995
and investigates the performance implications of the misfits. Ittner Larker 2001 proposed that one key element in studying strategy and MCS is to identify the specific
factors that do in fact lead to value creation. One way to identify the factors that contribute to value creation in the strategy-MCS study is to investigate the specific
control systems that contribute positively to performance given a specific type of strategy. Following Venkatraman and Prescott 1990, we obtain a profile of control
systems dimension for a set of high performing firms adopting a specific strategy. Any deviations from this profile will have negative performance implications.
The ideal profile can be derived either theoretically or empirically Van de Ven and Drazin, 1985. The test for performance implication of the misfit between strategy
and control system is provided by correlating the misfit with performance. A negative and significant negative correlation between misfit and performance will support the
proposition that misfits negatively affect performance.
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Most early studies used selections and interactions method to define misfits. These two approaches, however, have been criticized for their inability to measure the alignment of the
whole systems e.g., Selto, Renner Young, 1995; Van de Ven and Drazin, 1985.
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Following a contingency theory, we hypothesize that firms that reveal a fit between strategy and MCS is more effective than those that do not achieve such fit
Lawrence Lorsch, 1969. The more a firm deviates from the ideal profile, the lower will be its performance Drazin and Van de Ven, 1985 since fit between strategy and
control systems will reinforce competitiveness leading to superior performance McDaniel and Kolari, 1987. However, the misfit between strategy and control systems
will affect performance negatively only if the firm deviates from the ideal in terms of the critical control systems. Specifically, the following hypotheses will be tested:
H1a: A misfit between business strategy and the critical control systems will have a negative and significant impact on financial performance.
H1a: A misfit between business strategy and the critical control systems will have a negative and significant impact on non financial performance.
Venkatraman and Prescott, 1990 proposed that while the negative and significant correlation between misfits and performance support the notion that aligning
MCS with strategy positively affects performance, it only serves as a necessary but not sufficient condition to argue convincingly for the strong relationship between misfits and
performance. This is because the power of the test is unknown. To address this concern, Venkatraman and Prescott 1990 suggest developing a baseline profile using
variables that were not significantly related to performance in each type of strategy. The baseline profile reflects a model where firms use control systems that are not
critical in affecting the firms‘ performance. We expect that the relationship between the misfits in the baseline profile will not be significantly different from zero. Specifically, the
following hypotheses will be tested: H2a: A misfit between business strategy and the non critical control systems will not
have a significant impact on financial performance H2a: A misfit between business strategy and the non critical control systems will not
have a significant impact on non financial performance
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We also expect that the magnitude of the correlation between misfits and performance for critical MCS will be significantly more negative than the magnitude of
the correlation between misfits and performance for non critical MCS. Specifically, the following hypotheses will be tested:
H3a: The correlations between misfits and financial performance for critical MCS are significantly more negative than the correlations between misfits and financial
performance for non-critical MCS. H3a: The correlations between misfits and non-financial performance for critical MCS
are significantly more negative than the correlations between misfits and non-financial performance for non-critical MCS.