IDEAS home Printed from https://ideas.repec.org/p/hig/wpaper/09-psp-2017.html

Innovative Behavior and Prosocial Motivation of Russian Civil Servants

Author

Listed:
  • Tim Jaekel

    (National Research University Higher School of Economics)

Abstract

The motivation of civil servants has a considerable impact on their decision-making and thus the performance of a bureaucratic agency. This paper studies how innovative and error-correcting behavior of Russian public civil servants correlates with three types of motivation: public service motivation (PSM), power motivation (PM) and security motivation (SM). Civil servants with a higher level of PSM are expected to correct existing errors in standard operating procedures (SOP) and to introduce “new ways of doing things” (Fernandez and Moldogaziev 2013); and so to improve their organizations’ performance and citizens’ well-being by enhancing organizational learning. For empirical analysis the paper uses a new unique dataset with some 1,600 responses from a survey questionnaire among local civil servants in the Russian region of Leningrad. The results from regression analyses demonstrate that prosocial motivation (seven item scale, Cronbach’s alpha =0.72), power motivation (nine-item scale, Cronbach’s alpha=0.78), employee encouragement, empowerment practices, and citizens orientation are positively correlated with innovative and error-correcting. In contrast the level of security motivation and job satisfaction fail to achieve statistical significance throughout all models

Suggested Citation

  • Tim Jaekel, 2017. "Innovative Behavior and Prosocial Motivation of Russian Civil Servants," HSE Working papers WP BRP 09/PSP/2017, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:09/psp/2017
    as

    Download full text from publisher

    File URL: https://wp.hse.ru/data/2017/05/15/1171307252/09PSP2017.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    2. Walker, Jack L., 1969. "The Diffusion of Innovations among the American States," American Political Science Review, Cambridge University Press, vol. 63(3), pages 880-899, November.
    3. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    4. Wesley Eddings & Yulia Marchenko, 2012. "Diagnostics for multiple imputation in Stata," Stata Journal, StataCorp LLC, vol. 12(3), pages 353-367, September.
    5. Manuel P. Teodoro, 2009. "Bureaucratic Job Mobility and The Diffusion of Innovations," American Journal of Political Science, John Wiley & Sons, vol. 53(1), pages 175-189, January.
    6. Ivan Shulga & Anna Sukhova & Gagik Khachatryan, 2014. "Empowering Communities : The Local Initiatives Support Program in Russia," World Bank Publications - Reports 18932, The World Bank Group.
    7. Walker, Jack L., 1969. "The Diffusion of Innovations among the American States," American Political Science Review, Cambridge University Press, vol. 63(3), pages 880-899, November.
    8. Berry, Frances Stokes & Berry, William D., 1990. "State Lottery Adoptions as Policy Innovations: An Event History Analysis," American Political Science Review, Cambridge University Press, vol. 84(2), pages 395-415, June.
    9. Tim Jaekel & Georgiy Borshchevskiy, 2017. "Occupational Intention of Public Administration Undergraduates," HSE Working papers WP BRP 07/PSP/2017, National Research University Higher School of Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Biao Huang & Jiebing Wu & Li Ye, 2023. "Fiscal decentralization, intergovernmental mobility, and the innovativeness of local governments' policy response in COVID‐19: Evidence from China," Public Administration & Development, Blackwell Publishing, vol. 43(2), pages 196-206, May.
    2. Jäkel Tim, 2019. "Performance Gaps, Peer Effects, and Comparative Behaviour: Empirical Evidence from Swedish Local Government," Statistics, Politics and Policy, De Gruyter, vol. 10(1), pages 27-53, June.
    3. Amy Y. Li, 2017. "Covet Thy Neighbor or “Reverse Policy Diffusion”? State Adoption of Performance Funding 2.0," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(7), pages 746-771, November.
    4. Fonseca, Camila & Jiang, Haiyue & Zeerak, Raihana & Zhao, Jerry Zhirong, 2024. "Explaining the adoption of electric vehicle fees across the United States," Transport Policy, Elsevier, vol. 149(C), pages 139-149.
    5. Felix Strebel & Thomas Widmer, 2012. "Visibility and facticity in policy diffusion: going beyond the prevailing binarity," Policy Sciences, Springer;Society of Policy Sciences, vol. 45(4), pages 385-398, December.
    6. Xiaohan Li & Yang Lv & Md Nazirul Islam Sarker & Xun Zeng, 2022. "Assessment of Critical Diffusion Factors of Public–Private Partnership and Social Policy: Evidence from Mainland Prefecture-Level Cities in China," Land, MDPI, vol. 11(3), pages 1-15, February.
    7. Weixing Liu & Hongtao Yi, 2020. "What Affects the Diffusion of New Energy Vehicles Financial Subsidy Policy? Evidence from Chinese Cities," IJERPH, MDPI, vol. 17(3), pages 1-15, January.
    8. Saatvika Rai, 2020. "Policy Adoption and Policy Intensity: Emergence of Climate Adaptation Planning in U.S. States," Review of Policy Research, Policy Studies Organization, vol. 37(4), pages 444-463, July.
    9. Bernecker, Andreas, 2016. "Divided we reform? Evidence from US welfare policies," Journal of Public Economics, Elsevier, vol. 142(C), pages 24-38.
    10. Youlang Zhang & Hongshan Yang, 2023. "Bureaucratic politics, innovation compatibility, and the dynamic diffusion of subnational decentralization reforms in China," Review of Policy Research, Policy Studies Organization, vol. 40(4), pages 553-572, July.
    11. Chandler, Jess, 2009. "Trendy solutions: Why do states adopt Sustainable Energy Portfolio Standards?," Energy Policy, Elsevier, vol. 37(8), pages 3274-3281, August.
    12. Fabrizio Gilardi, 2010. "Who Learns from What in Policy Diffusion Processes?," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 650-666, July.
    13. Anderson, John E. & Giertz, Seth H. & Shimul, Shafiun N., 2022. "Reducing property taxes for agriculture: Diffusion of use-value assessment policy across the United States," Land Use Policy, Elsevier, vol. 120(C).
    14. Jolley, G. Jason, 2023. "The Political Economy of Local Government Enterprise Zone Designation," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 53(2), September.
    15. Zhang, Kaiwen & Tan, Rong, 2024. "Land policy making in a complex system: The innovation and diffusion logic of China's retained land policy reform," Land Use Policy, Elsevier, vol. 144(C).
    16. Kseniya M. Khovanova, 2009. "How Does Variation in City Fiscal Health Affect Its Degree of Innovation?," Croatian Economic Survey, The Institute of Economics, Zagreb, vol. 11(1), pages 43-72, April.
    17. Pranpreya Sriwannawit & Ulf Sandström, 2015. "Large-scale bibliometric review of diffusion research," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1615-1645, February.
    18. Lee, Donghyun & Kim, Minki & Lee, Jungyoun, 2016. "Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries," Energy Policy, Elsevier, vol. 90(C), pages 187-201.
    19. Lanahan, Lauren & Feldman, Maryann P., 2015. "Multilevel innovation policy mix: A closer look at state policies that augment the federal SBIR program," Research Policy, Elsevier, vol. 44(7), pages 1387-1402.
    20. David Lazer, 2005. "Regulatory Capitalism as a Networked Order: The International System as an Informational Network," The ANNALS of the American Academy of Political and Social Science, , vol. 598(1), pages 52-66, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • H83 - Public Economics - - Miscellaneous Issues - - - Public Administration

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hig:wpaper:09/psp/2017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shamil Abdulaev or Shamil Abdulaev (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.