دانلود رایگان مقاله انگلیسی اثربخشی مدیریت کنترل و استراتژی - نشریه الزویر

abstract

This study examines management control (MC) combinations that are effective in different strategic contexts through two related approaches e MC as a package and MC as a system. First, this study identifies how a set of MC practices combine (i.e. MC packages) to achieve effective control outcomes for firms operating in defender and prospector strategic contexts by applying fuzzy set qualitative comparative analysis (fsQCA). Using data from a survey of top managers the analysis reveals that there are multiple ways by which firms can effectively combine MC practices in a given strategic context. Furthermore, the analysis shows that not all MC practices found to be relevant in isolation are relevant when examined simultaneously as a package. Second, based on a comparison of effective MC packages this study examines interdependencies between MC practices (i.e. MC systems). Results show that in defender firms a diagnostic control use of accounting and mechanistic structural controls act as complements, while mechanistic structural controls and measure diversity act as substitutes. In prospector firms an interactive control use of accounting and organic structural controls are found to have complementary effects. These results indicate that the effectiveness of accounting control and structural control choices are determined not only by their fit with strategic context but also by how they fit with each other. This study also demonstrates how an understanding of MC packages can provide guidance for theory development and empirical analysis of MC systems.

Appendix B. Overview of QCA

Qualitative comparative analysis (QCA) refers to a range of analytical methods grounded in set theory. One distinguishing characteristics is that QCA is not a statistical method but one that is based on logical relations between sets. As Rihoux and Marx (2013 p. 168) explain: “A set theoretic approach starts from the idea that attributes of cases are best described in set relations and not in terms of variables. Variables aim to capture a dimension of variation across cases and distribute cases on this variation. A set assesses whether, or to what degree, a case is a member of a set and then analyses the intersection between sets.” As an illustration, consider an example with two MC practices (A and B) hypothesized to have an association with MC effectiveness (Y) (Bedford & Sandelin, 2015). Assuming that each MC practice can take only one of two values, either 1 or 0 to indicate high and low use, then there are a total of four possible combinations (i.e. sets) to which a firm can be a member. Using set-theoretic notation, where “~” refers to the logical operator not and “” denotes the logical operator and, the possible sets in this example are AB, A~B, ~AB, and ~A~B (e.g. the second set refers to the combination of A and not B, which corresponds to a high use of practice A and a low use of practice B). Firms in each set may have either the outcome of high MC effectiveness present (Y) or absent (~Y). The analysis proceeds by examining the overlap between firm membership in the sets of MC practices and the outcome. These relations are displayed graphically in Fig. 1. In this example the set of firms that combine a high use of A with a high use of B have the greatest overlap with the set set of firms with high MC effectiveness (Y). This suggests that firms with the combination AB consistently achieve the outcome while firms with other combinations do not.