Felt responsibility for change in public organizations: general and sector-specific paths

ABSTRACT

Employees may be a source of performance-enhancing innovation or an obstacle to its implementation. This article develops a model of felt responsibility for change that integrates general and public sector-specific components. Structural equation modelling using survey data collected from Korean government employees suggests that both transformational leadership and performance-based incentives influence change attitudes by strengthening an organization’s climate for innovation. The analysis also suggests that transformational leadership wields influence through reinforcing public service motivation. It is argued that this path is uniquely relevant to the implementation of reform in the public sector.

KEYWORDS:

• Reform
• innovation
• motivation
• incentives
• leadership

Disclosure statement

No potential conflict of interest was reported by the author.​​

Notes

1. Chi-square values, which are reported in the tables, are significant for all models. This significance suggests poor model fit. However, due to the highly sample-size dependent nature of this statistic, a statistically significant chi-square value is not conventionally treated as cause for model rejection when other indices collectively suggest good model fit (Wright, Moynihan, and Pandey 2012), such as is the case in the present study.

2. Note that in both the hypothesized and trimmed model, the relationship between the exogenous variables is unconstrained.

3. While the chi-square statistic is nominally higher in the hypothesized than in the trimmed model (though, again, the difference is not statistically significant), the RMSEA and NNFI, both of which take into account parametric complexity, are equivalent (in the case of RMSEA) or higher (in the case of NNFI) for model 2. This suggests that, even though two unconstrained parameters were removed from the trimmed model, little information has been lost.

Additional information

Funding

​​This work was supported by the National Research Foundation of Korea: [NRF-2014S1A3A2044898].