Wellbeing of Citizens and Employees as Indicator of Good Local Governance
Date |
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2021 |
Background: In the past decades, local governance has transformed all over the world (Barnett, 2020; Teng-Calleja et al., 2017; Swianiewicz, 2014). The emerging perspective reflects a shift from merely implementing bureaucratic controls and processes towards meeting citizens' needs. However, there is a debate over the question on "measuring what matters" in local government. Evaluation models of local government, which operates with the aim to ensure wellbeing of citizens, are based mainly on performance evaluation (Andrews et al., 2008). However, some authors refer to “community indicators”, including quality of life levels in municipalities (Ryan & Hastings, 2015). Next, ensuring the right of citizens to good administration in local government depends on the work efficiency of local governance employees, and research indicates that work efficiency depends not only on process management but also on employees’ well-being (Xerri et al., 2016). Methodology: This presentation introduces two studies which were conducted in Lithuania. In study 1, a representative sample of 1979 participants were interviewed (47.2% of males, 52.8% of females). The study applied the Satisfaction with Life Scale (SWLS) of E. Diener and colleagues (1985) with the goal to evaluate the levels of life satisfaction across municipalities. In study 2, a simple random sample consisted of 245 employees: 138 (57,5 percent) employees worked in the public sector, and 102 (42,5 percent) employees worked in the private sector. The study applied the Stress Overload Scale (Amirkhan, 2018) and the Basic Psychological Needs Satisfaction and Frustration Scale (Chen et al., 2015) with the goal to compare stress overload and needs satisfaction/frustration of public and private sector employees. Results: Some previous research suggested the possible impact of rural and urban factors on satisfaction with life, thus, in study 1, we have compared satisfaction with life scores based on the particular living area (Table 1).