Ladislav Šiška

The First and the Second Generation of Statistical Methods in Management Accounting Research

Calls for more frequent application of the second-generation statistical methods such as structural equation modeling (SEM) have emerged in the field of management accounting recently. The aim of this article is to compare these statistical methods to the first-generation methods using the real-life example. Specifically, the relationship between the organizational capabilities and perceived nonfinancial performance is investigated. Firstly, the sequential combination of principal component analysis and regression analysis is deployed to the outlined case example. Secondly, partial least squares structural equation modeling (PLS-SEM) is applied to the case example. The comparison of both approaches proves SEM to be more vigilant statistical method for capturing the strength of relationship between latent constructs.

Adoption of Strategic Management Accounting Techniques in Czech and Slovak Companies

The purpose of this paper is to classify strategic management accounting (SMA) techniques. More specifically, two objectives were stated: (1) to derive a classi-fication of SMA theoretically and then (2) to verify such classification empiri-cally. To achieve these objectives, our study deploys literature review and empir-ical survey. Convenience sample of 99 profit seeking companies domiciled in the Czech Republic and Slovak Republic was analyzed by means of descriptive sta-tistics and principal component analysis. The latter method identified three broader categories of SMA techniques: Internally focused; Competitor focused; Stakeholder focused SMA techniques. Such findings only partly correspond to the theoretically derived classification that enumerates five broader categories, which were identified in SMA literature: Product accounting; Process account-ing; Customer accounting; Competitor accounting; Performance measurement. The comparison of both classifications reveals that respondents perceived inter-nally focused groups of SMA techniques similarly and did not differentiate among them. Further detailed analysis also shows influence of some control var-iables such as industry, size of the respondents company or differences between independent enterprises and subsidiaries/parent companies.