Increasing the enabling use of performance measures:a longitudinal quasi natural experiment
Autor: | Henrik Saabye, Thomas Borup Kristensen |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Measure (data warehouse)
Continuous improvement Process management Natural experiment Relation (database) Computer science Strategy and Management media_common.quotation_subject Enabling formalization Control (management) Context (language use) Management Science and Operations Research Management Information Systems Test (assessment) Management of Technology and Innovation Accounting Performance measurement Quality (business) Lean Performance indicator Longitudinal natural experiment media_common |
Zdroj: | Kristensen, T B & Saabye, H 2021, ' Increasing the enabling use of performance measures : a longitudinal quasi natural experiment ', Journal of Management Control, vol. 32, no. 3, pp. 401-433 . https://doi.org/10.1007/s00187-021-00322-7 |
DOI: | 10.1007/s00187-021-00322-7 |
Popis: | In this paper, we study how organizational members’ perceptions of the enabling use of performance measures is increased when the case company adopted lean principles in one of its production-support departments. The theory of enabling formalization is applied to gauge and understand the extent to which organizational members perceive performance measures, such as key performance indicators (KPIs), as enabling (i.e. as a vehicle creating continuous improvement). We empirically confirm a positive relation between changing the context of performance measures and the perceived level of enabling use of KPIs by applying a difference-in-differences test. We also show that the increase in perceptions of the enabling use of KPIs is associated with improved perceived performance (e.g. time consumption, quality). We measure the perceived enabling use using data gathered from questionnaires distributed over several rounds in both the department implementing lean principles and a non-affected control department. As such, our study involves a longitudinal, quasi-natural experiment. We confirm the statistical results through interviews, observations, and internal documents from the case company. |
Databáze: | OpenAIRE |
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