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Use of simulation in controlling research: a systematic literature review for German-speaking countries

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Abstract

This paper provides a systematic literature review of the use of simulation in the field of “controlling”, a term synonymously used for management accounting and control in German-speaking countries. The review starts from a total of 12,102 articles published in leading, controlling-related business journals in German-speaking countries (Germany, Austria, and Switzerland) between 1980 and 2009. Thereof, 47 articles specifically refer to the use of simulation in controlling. This set of articles is analyzed along the following dimensions: development of publication volume over time, important authors, controlling tasks and instruments supported by simulation or fulfillment of minimum quality criteria concerning simulation modeling and analysis. The results indicate an increasing interest in employing simulation within controlling and its particular relevance in practice. Two areas emerge as the main application arena: planning and risk management. Despite some progress the review also shows that simulation is not yet an established branch of research on its own in controlling. A detailed analysis of the articles suggests that more transparency and standards in the application of simulations are needed to further advance this method.

Zusammenfassung

Dieser Artikel führt eine systematische Literaturanalyse der Nutzung von Simulation im Bereich Controlling durch. Von insgesamt 12.102 Artikeln, die zwischen 1980 und 2009 in führenden, für das Controlling relevanten betriebswirtschaftlichen Zeitschriften im deutschsprachigen Raum (Deutschland, Österreich und Schweiz) veröffentlicht wurden, können 47 Simulationsartikel mit Controllingbezug identifiziert werden. Diese Artikel werden hinsichtlich verschiedener Dimensionen untersucht, wie etwa die Entwicklung der Anzahl der Publikationen, wichtigste Autoren, Aufgaben und Instrumente des Controllings die mit Simulation unterstützt werden oder die Erfüllung gewisser Minimumstandards bezüglich der Anwendung von Simulation. Die Analyse zeigt ein steigendes Interesse an Simulation im Bereich Controlling, insbesondere auf Seite der Praxis. Dabei stehen vor allem die Themengebiete Planung und Risikomanagement im Vordergrund. Jedoch verdeutlichen die Ergebnisse auch, dass Simulation noch kein eigenständiger etablierter Forschungszweig innerhalb des Controllings ist. Eine Detailanalyse der Artikel zeigt Defizite in den Bereichen Transparenz und Standards bei der Anwendung von Simulationen auf.

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Notes

  1. For a more detailed discussion see Sect. 2.

  2. This description is based on Reiss (2011:245), Davis et al. (2007:481) and Evans and Olson (2002:2).

  3. The use of simulation in corporate controlling practice has been examined in Grisar and Meyer (2015).

  4. The term “German-speaking countries” refers to Germany, Austria, and Switzerland in the following. We are aware of the fact that Lichtenstein is also a German-speaking country. However, as there is no controlling-related journal originated from Lichtenstein, we refrain from further explicitly mentioning the country in our article.

  5. The journal “Management Science” sticks out with an extreme value of 23.4 %.

  6. Richiardi et al. analyzed top economic research regarding agent-based simulation and yield a share of less than 0.03 % agent-based simulation in economics (Richiardi et al. 2006:1.3).

  7. In this empirical study, cost accounting is denoted as task and instrument at the same time; however, we are abstain from this perspective and denote cost accounting only as an controlling instrument in the following.

  8. For different classifications, see Harrison et al. (2007), Davis et al. (2007) and Macy and Willer (2002).

  9. Using digital computers one can strictly speak only of “quasi-continuous” simulations.

  10. For example Deckert and Klein distinguish in their review between three categories of simulation: discrete simulation, continuous simulation and Monte Carlo simulation (Deckert and Klein 2010:93). Based on what has been described here, discrete simulation and continuous simulation should already fully describe how the change of state variables can be modeled. The last category therefore does not fit.

  11. Both Crystal Ball and @Risk are Excel-based software. The name @Risk indicates its specific application for the calculation of “at risk” figures such as Value at Risk (VaR). Crystal Ball is a registered trademark of Oracle, see Oracle (2010). @Risk is a registered trademark of Palisade, see Palisade (2012).

  12. For a comparison of different software programs, see Klein (2010) and Sugiyama (2008).

  13. For an overview of different classifications, see Schäffer and Steiners (2004).

  14. For the relevance of the conceptual use of controlling information in general, see Heine (2008).

  15. We would like to mention that simulation articles possibly relevant for Controlling may also be published in journals located in the sub-rankings Business Information Systems and Operations Research, such as the journals Wirtschaftsinformatik (WI) and OR Spectrum. To keep our study and its results comparable to the previous studies about Controlling mentioned above, we decided not to include these journals. Still, we screened these journals for possibly relevant contents and will reflect on possible biases and implications of this decision in the last section of this paper.

  16. In 2013, this journal was relaunched and appears now as “Journal of Business Economics”.

  17. In 2012, this journal obtained an English name in addition: “Business Administration Review”.

  18. In 2014, this journal was relaunched and appears now as “Management Review Quarterly”.

  19. The extended version of the ranking does not affect the selection of the journals as only some additional journals are included. The ranking position of the selected journals remains the same, see JQ2.1 (VHB 2011).

  20. In 2011, this journal was relaunched and appears now as “Journal of Management Control”.

  21. It is the only journal in the sample that is currently included in the Social Science Citation Index (Thomson Reuters 2012).

  22. In 2013, this journal was renamed again and appears now as “Controlling Management Review”.

  23. It should be noted that in a different version of the JQ2 ranking, krp has an independent index of 4.54 (VHB 2008).

  24. See Schäffer and Binder (2008:62). Their citation analysis is based on academic publications.

  25. We are aware of the fact that simulation-based controlling articles may also be published in other journals than the introduced ones. However, with our selection, we rely on those journals that have been used in other studies and that are perceived at most related to controlling.

  26. The establishment of practice journals may have triggered the rise of the share of articles in these journals compared to the share of academic articles in the 1990s. Between 1980 and 1989, the share of academic articles is 83.4 %; between 1990 and 2009, the share decreases to 69.0 %.

  27. It should be noted that this had to be done by hand for 66.8 % of the articles as they were not included in electronic databases.

  28. Throughout the paper, the sample of simulation articles in controlling is referred to as “simulation articles” or “reviewed articles”. The single term “articles” refers to all published articles within the defined journals (universe of articles).

  29. We set the number of simulation articles in controlling in relation to the overall number of articles published in each journal between 1980 and 2009.

  30. In case of joint work, the article counts for both authors.

  31. In addition, one reviewed article provided a survey on simulation in controlling but did not refer to specific tasks.

  32. In this review, the term “risk analysis” denotes every practice to model risk and to make it manageable. It abstracts from the narrow view that risk analysis itself denotes a simulation approach which is sometimes found in the literature (Hertz 1964).

  33. Heine and Kunz (2003) is a review article and has been excluded as well.

  34. We would like to remind of the problematic character of these self-descriptions discussed in Sect. 2, where we also discussed issues with the term “Monte Carlo simulation”.

  35. Maple 11 is now available in its 16th edition. It is a registered trademark of Waterloo Maple Inc., see Maplesoft (2012).

  36. For the following analysis of the simulation quality, we excluded articles that do not contain a simulation model for examination. Articles dealing with simulation in a wider sense such as the mere examination of alternatives and business games were excluded as well. Therefore, 31 out of 47 articles were included in our analysis.

  37. It is worth noting that these results may be different for journals of other disciplines, e.g., business informatics or operations research that also happen to contain simulation-based controlling articles. Due to a greater focus of simulation in these journals, the simulation quality is likely to be higher.

  38. This problem is also found and discussed in a study by Fontana who analyzed the diffusion of simulation in economics (Fontana 2006:4.8 and 5.2).

  39. Wolf identified the methodological and conceptual gap and describes in detail how to implement the simulation (Wolf 2003). A general introduction to simulation within the reviewed articles is given by Deckert and Klein (2010).

  40. For detailed information on experimental design, see (Law 2007:619–668) and Kleijnen et al. (2005).

  41. It should be mentioned, deciding what articles in these journals can be classified as controlling articles can become a quite challenging task with high differences in interrater reliability. For a good discussion of the relationships of the disciplines of the fields of controlling and operations research see Küpper (2007).

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Acknowledgments

An earlier version of the paper benefited from discussions at the EAA Annual Congress in Rome. We also would like to thank Iris Lorscheid, Klaus G. Troitzsch and the two anonymous reviewers for their helpful comments. Finally, we would like to thank Jonas Hauke for his support in screening the business informatics and operations research literature.

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  1. Institute of Management Control and Simulation, Hamburg University of Technology, Schwarzenbergstraße 95 D, 21073, Hamburg, Germany

    Cathérine Grisar & Matthias Meyer

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  1. Cathérine Grisar
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  2. Matthias Meyer
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Correspondence to Matthias Meyer.

Appendix

Appendix

See Tables 11 and 12.

Table 11 Data extraction form (part 1 of 2)
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Table 12 Data extraction form (part 2 of 2)
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Grisar, C., Meyer, M. Use of simulation in controlling research: a systematic literature review for German-speaking countries. Manag Rev Q 66, 117–157 (2016). https://doi.org/10.1007/s11301-015-0117-0

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