Abstract
Efforts to “reinvent” government have emphasized the importance of performance measurement and management (PMM) systems to improve government operations. Although it seems clear why organizations adopt PMM systems, less is known about their actual consequences. This study, using a survey to Japanese local government departments, explores whether different uses of PMM and their interaction with the context (predictability and bureaucratic culture) can affect the impact of PMM on organizational performance. Results show that using PMM, not only having it, is not enough to generate performance improvements. It is shown that the fitness of use to the local government context is the way to foster performance. A strong bureaucratic culture shows a positive relation with performance in the Japanese setting.
Notes
1 See Moynihan (2009) for an extended explanation of mediating variables creating first-order and second-order effects over performance management implementation.
2 See Kobayashi et al (2016), Suzuki and Han (Suzuki & Han, Citation2019), Suzuki and Avellaneda (Suzuki & Avellaneda, Citation2018), Suzuki and Sakuwa (2016), Miyazaki (2014) and Council of Local Authorities for International Relations (2013) for a detailed explanation of the Japanese system.
3 Cities were selected as the ratio of PMM implementation is 84.9%, Towns and villages were discarded as the implementation ration is much lower (38.9%) (MIC, 2017). The departments analyzed were Disaster Recovery Support and Risk Management; Culture and Sports Affairs; Industrial and Labor Affairs; Child affairs; Regional Cooperation and Community support; Urban Development and Construction; Environment, Public Cleaning and Health and Welfare
4 Results of this analysis have not been included due to the length of the paper but can be provided by the authors on demand.
5 To validate the graphs of the figure Johnson–Neyman technique has been use as recommended by Bauer and Curran (2005).
6 It should be noticed that predictability is the sum of uncertainty, ambiguity and complexity. Thus, high values represent low levels of predictability. The variable is measuring the absence of predictability. The analysis will be done considering this fact.
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Notes on contributors
Ana Yetano
Ana Yetano (PhD) is an associate professor in the Department of Accounting and Finance at the School of Economics and Business of the University of Zaragoza (Spain). She has published in leading international journals such as Administration & Society, Public Administration, European Accounting Review, Public Administration Review and Public Performance.
Takami Matsuo
Takami Matsuo (PhD) is a professor at the Graduate School of Business Administration of Kobe University. His fields of expertise are Management Control and Public sector Accounting. He is actually leading a research project on New Governance of Kobe University Center for Social Systems Innovation. He has published articles in journals such as International Journal of Public Administration and the China-USA Business Review.
Keisuke Oura
Keisuke Oura (PhD) is an accounting professor of the College of Business Administration at the Ritsumeikan University. His field of expertise is Management Control.