Journal of Applied Economic Research
ISSN 2712-7435
A Fuzzy Model for Personnel Risk Analysis: Case of Russian-Finnish Export-Import Operations of Small and Medium Enterprises
Tatiana Yu. Kudryavtseva, Angi E. Skhvediani, Maiia S. Leukhina, Alexandra O. Schneider
Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia
Abstract
Small and medium enterprises (SMEs) have limited resources for balancing risks which occur during international activities. The main hypothesis tested in this research is that the qualification of employees is the main area of personnel risks in cross–border cooperation. The fuzzy-logic model for personnel risks analysis was developed for quantification of the risks related to international activities. First, different risk factors and their elements were identified and formulated as linguistic variables. Second, with the use of experts’ judgments, a fuzzy logic-based system was constructed and evaluated. Risk level was calculated using MATLAB fuzzy logic toolbox and its factors were ranked accordingly. This model was applied to survey data from SMEs on Russia-Finland import-export operations during the 2020 – 2021 period. The personnel risk related to export-import Russia - Finland operations belonged to the above-average risk levels. Based on a more detailed analysis of risk elements, such elements as personnel development and training had the greatest coefficient and is an obvious high-risk area. The second highest value of the risk coefficient belonged to the element associated with personnel management. The lowest value belonged to elements related to motivation and recruitment processes. Therefore, theoretical contribution of the article is a model which allows us to quantify and identify micro-level personnel related risks in cross-border cooperation and present linguistic interpretation of these risks. This model can be use in practice by managers of specific SMEs or policy makers for obtaining broader and more representative results on risks related to international activities.
Keywords
personnel risk; risk analysis; risk evaluation; fuzzy logic; small and medium sized enterprises.
JEL classification
F23References
1. Munteanu, D.R., Vanderstraeten, J., van Witteloostuijn, A., Cambré, B. (2022). A systematic literature review on SME internationalization: a personality lens. Management Review Quarterly, 1–62. doi.org/10.1007/s11301-022-00279-4
2. Joshi, S., Sharma, M. (2022). Impact of sustainable supply chain management on performance of SMEs amidst COVID-19 pandemic: an Indian perspective. International Journal of Logistics Economics and Globalisation, Vol. 9, No. 3, 248–276. doi.org/10.1504/IJLEG.2022.120811
3. Mardones, C. (2023). Economic effects of isolating Russia from international trade due to its ‘special military operation’ in Ukraine. European Planning Studies, Vol. 31, Issue 4, 663–678. doi.org/10.1080/09654313.2022.2079074
4. Abu Hatab, A., Lagerkvist, C.J., Esmat, A. (2021). Risk perception and determinants in small-and medium-sized agri-food enterprises amidst the COVID-19 pandemic: Evidence from Egypt. Agribusiness, Vol. 37, Issue 1, 187–212. doi.org/10.1002/agr.21676
5. Crovini, C., Ossola, G., Britzelmaier, B. (2021). How to reconsider risk management in SMEs? An advanced, reasoned and organised literature review. European Management Journal, Vol. 39, Issue 1, 118–134. doi.org/10.1016/j.emj.2020.11.002
6. Kotaskova, A., Belás, J., Bilan, Y., Khan, K.A. (2020). Significant aspects of managing personnel risk in the SME sector. Management & Marketing. Challenges for the Knowledge Society, Vol. 15, No. 2, 203–218. doi.org/10.2478/mmcks-2020-0013
7. Yuliatti, M.M.E., Hardi Purba, H. (2021). Construction project risk analysis based on fuzzy analytical hierarchy process (F-AHP): A Literature Review. Advance Researches in Civil Engineering, Vol. 3, Issue 3, 1–20. doi.org/10.30469/arce.2021.139735
8. Gallab, M., Bouloiz, H., Alaoui, Y.L., Tkiouat, M. (2019). Risk assessment of maintenance activities using fuzzy logic. Procedia Computer Science, Vol. 148, 226–235. doi.org/10.1016/j.procs.2019.01.065
9. Ratnayake, R.C., Antosz, K. (2017). Development of a risk matrix and extending the risk-based maintenance analysis with fuzzy logic. Procedia Engineering, Vol. 182, 602–610. doi.org/10.1016/j.proeng.2017.03.163
10. Agostini, L., Nosella, A., Venturini, K. (2019). Toward increasing affective commitment in SME strategic networks. Business Process Management Journal, Vol. 25, No. 7, 1822–1840. doi.org/10.1108/BPMJ-02-2018-0035
11. Khan, K.A., Dankiewicz, R., Kliuchnikava, Y., Oláh, J. (2020). How do entrepreneurs feel bankruptcy? International Journal of Entrepreneurial Knowledge, Vol. 8, No. 1, 89–101. doi.org/10.37335/ijek.v8i1.103
12. Metzker, Z., Streimikis, J. (2020). CSR activities in the Czech SME segment. International Journal of Entrepreneurial Knowledge, Vol. 8, No. 1, 49–64. doi.org/10.37335/ijek.v8i2.101
13. Hudáková, M., Masár, M. (2018). The assessment of key business risks for SMEs in Slovakia and their comparison with other EU countries. Entrepreneurial Business and Economics Review, Vol. 6, No. 4, 145–160. dx.doi.org/10.15678/EBER.2018.060408
14. Cepel, M., Gavurova, B., Dvorský, J., Belas, J. (2020). The impact of the COVID-19 crisis on the perception of business risk in the SME segment. Journal of International Studies, Vol. 13, No. 3, 248–263. doi.org/10.14254/2071-8330.2020/13-3/16
15. Juergensen, J., Guimón, J., Narula, R. (2020). European SMEs amidst the COVID-19 crisis: assessing impact and policy responses. Journal of Industrial and Business Economics, Vol. 47, Issue 3. 99–510. doi.org/10.1007/s40812-020-00169-4
16. Caligiuri, P., De Cieri, H., Minbaeva, D., Verbeke, A., Zimmermann, A. (2020). International HRM insights for navigating the COVID-19 pandemic: Implications for future research and practice. Journal of International Business Studies, Vol. 51, Issue 5, 697–713. doi.org/10.1057/s41267-020-00335-9
17. Tselyutina, T.V., Timokhina, O.A., Vlasova, T., Maslova, Y.V. (2019). Development of the personnel risks assessment and supply chain strategy as a basis of the risk management system of modern organizations. International Journal of Supply Chain Management, Vol. 8, No. 5, 1030–1038. doi.org/10.59160/ijscm.v8i5.3912
18. Lundén, T. (2018). Border regions and cross-border cooperation in Europe. A theoretical and historical approach. In: European Territorial Cooperation. The Urban Book Series. Edited by E. Medeiros. Springer Cham, 97–113. doi.org/10.1007/978-3-319-74887-0_14
19. Makarychev, A., Romashko, T. (2023). Conflictual Rebordering: The Russia Policies of Finland and Estonia. Central European Journal of International and Security Studies, Vol. 17, Issue 2, 44–79. doi.org/10.51870/OJFQ7520
20. Ivan, G., Tatyana, K., Lidiya, O. (2016). Local border traffic as an efficient tool for developing cross-border cooperation. Baltic Region, Vol. 8, No. 1, 67–82. doi.org/10.5922/2079-8555-2016-1-6
21. Catanzaro, A., Teyssier, C. (2021). Export promotion programs, export capabilities, and risk management practices of internationalized SMEs. Small Business Economics, Vol. 57, Issue 3, 1479–1503. doi.org/10.1007/s11187-020-00358-4
22. Zhang, H., Tian, M., Hung, T. K. (2020). Cultural distance and cross-border diffusion of innovation: a literature review. Academia Revista Latinoamericana de Administración, Vol. 33, No. 2, 241–260. doi.org/10.1108/ARLA-10-2018-0239
23. Tian, M., Deng, P., Wu, B. (2021). Culture and innovation in the international context: a literature overview. Innovation: The European Journal of Social Science Research, Vol. 34, Issue 4, 426–453. doi.org/10.1080/13511610.2020.1783644
24. Caldara, D., Iacoviello, M., Molligo, P., Prestipino, A., Raffo, A. (2020). The economic effects of trade policy uncertainty. Journal of Monetary Economics, Vol. 109, 38–59. doi.org/10.1016/j.jmoneco.2019.11.002
25. Crowley, M., Meng, N., Song, H. (2018). Tariff scares: Trade policy uncertainty and foreign market entry by Chinese firms. Journal of International Economics, Vol. 114, 96–115. doi.org/10.1016/j.jinteco.2018.05.003
26. Gebre Borojo, D., Yushi, J., Miao, M., Liu, Y. (2023). The impacts of trade policy uncertainty on trade flow of emerging economies and low-income developing countries. Economic Research – Ekonomska Istraživanja, Vol. 36, Issue 1, 1055–1075. doi.org/10.1080/1331677X.2022.2081235
27. Becker, K., Smidt, M. (2016). A risk perspective on human resource management: A review and directions for future research. Human Resource Management Review, Vol. 26, Issue 2, 149–165. doi.org/10.1016/j.hrmr.2015.12.001
28. Cooke, F. L., Lin, Z. (2012). Chinese firms in Vietnam: Investment motives, institutional environment and human resource challenges. Asia Pacific Journal of Human Resources, Vol. 50, Issue 2, 205–226. doi.org/10.1111/j.1744-7941.2011.00013.x
29. Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, Vol. 253, Issue 1, 1–13. doi.org/10.1016/j.ejor.2015.12.023
30. Tikhonov, A. (2020). Modern approaches to the integrated assessment of personnel risks of an industrial enterprise. Research in World Economy, Vol. 11, No. 3, 99–107. doi.org/10.5430/rwe.v11n3p99
31. Djenadic, S., Tanasijevic, M., Jovancic, P., Ignjatovic, D., Petrovic, D., & Bugaric, U. (2022). Risk evaluation: brief review and innovation model based on fuzzy logic and MCDM. Mathematics, Vol. 10, Issue 5, 811. doi.org/10.3390/math10050811
32. Uzhga-Rebrov, O., Grabusts, P. (2021). Cumulative prospect theory version with fuzzy values of outcome estimates. Risks, Vol. 9, Issue 4, 72. doi.org/10.3390/risks9040072
33. Jimbo Santana, P., Lanzarini, L., Bariviera, A. F. (2019). Variations of particle swarm optimization for obtaining classification rules applied to credit risk in financial institutions of Ecuador. Risks, Vol. 8, Issue 1, 2. doi.org/10.3390/risks8010002
34. Sardasht, M.S., Rashedi, E. (2018). Identifying influencing factors of audit risk model: A combined fuzzy ANP-DEMATEL approach. International Journal of Digital Accounting Research, Vol. 18, 69–117. doi.org/10.4192/1577-8517-v18_4
35. Luo, N., Yu, H., You, Z., Li, Y., Zhou, T., Jiao, Y., Han, N., Liu, C., Jiang, Z., Qiao, S. (2023). Fuzzy logic and neural network-based risk assessment model for import and export enterprises: A review. Journal of Data Science and Intelligent Systems, Vol. 1, No. 1, 2–11. doi.org/10.47852/bonviewJDSIS32021078
36. Wulan, M., Petrovic, D. (2012). A fuzzy logic-based system for risk analysis and evaluation within enterprise collaborations. Computers in Industry, Vol. 63, No. 8, 739–748. doi.org/10.1016/j.compind.2012.08.012
37. Afzal, F., Yunfei, S., Junaid, D., Hanif, M.S. (2020). Cost-risk contingency framework for managing cost overrun in metropolitan projects: Using fuzzy-AHP and simulation. International Journal of Managing Projects in Business, Vol. 13, Issue 5, 1121–1139. doi.org/10.1108/IJMPB-07-2019-0175
38. Hugo, F.D., Pretorius, L., Benade, S.J. (2018). Some aspects of the use and usefulness of quantitative risk analysis tools in project management. South African Journal of Industrial Engineering, Vol. 29, No. 4, 116–128. doi.org/10.7166/29-4-1821
39. Albadán, J., Gaona, P., Montenegro, C., González-Crespo, R., Herrera-Viedma, E. (2018). Fuzzy logic models for non-programmed decision-making in personnel selection processes based on gamification. Informatica, Vol. 29, Issue 1, 1–20. https://doi.org/10.15388/Informatica.2018.155
40. Izquierdo, N.V., Lezama, O.B.P., Dorta, R.G., Viloria, A., Deras, I., Hernández-Fernández, L. (2018). Fuzzy logic applied to the performance evaluation. Honduran coffee sector case. Proceedings of Advances in Swarm Intelligence: 9th International Conference, ICSI 2018, Part II. Edited by Y. Tan, Y. Shi, Q. Tang. Springer Cham, 164–173. doi.org/10.1007/978-3-319-93818-9_16
41. Osei-Kyei, R., Chan, A.P., Javed, A.A., Ameyaw, E.E. (2017). Critical success criteria for public-private partnership projects: international experts’ opinion. International Journal of Strategic Property Management, Vol. 21, No. 1, 87–100. doi.org/10.3846/1648715X.2016.1246388
42. Hsieh, M.Y., Hsu, Y.C., Lin, C.T. (2018). Risk assessment in new software development projects at the front end: a fuzzy logic approach. Journal of Ambient Intelligence and Humanized Computing, Vol. 9, 295–305. doi.org/10.1007/s12652-016-0372-5
43. Mastrocinque, E., Lamberti, E., Ramirez, F.J., Petrovic, D. (2022). Measuring open innovation under uncertainty: A fuzzy logic approach. Journal of Engineering and Technology Management, Vol. 63, 101673. doi.org/10.1016/j.jengtecman.2022.101673
44. Rajak, S., Vinodh, S. (2015). Application of fuzzy logic for social sustainability performance evaluation: A case study of an Indian automotive component manufacturing organization. Journal of Cleaner Production, Vol. 108, Part A, 1184–1192. doi.org/10.1016/j.jclepro.2015.05.070
45. Zadeh, L.A. (1965). Fuzzy sets. Information and Control, Vol. 8, Issue 3, 338–353. doi.org/10.1016/S0019-9958(65)90241-X
46. Zadeh, L.A. (1983). The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems, Vol. 11, Issue 1-3, 199–227. doi.org/10.1016/S0165-0114(83)80081-5
47. Dombi, J. (1990). Membership function as an evaluation. Fuzzy Sets and Systems, Vol. 35, Issue 1, 1–21. doi.org/10.1016/0165-0114(90)90014-W
48. Mayne, A.J. (1990). Fuzzy sets, uncertainty, and information. Journal of the Operational Research Society, Vol. 41, Issue 9, 884–886. doi.org/10.1057/jors.1990.130
49. Kreinovich, V., Kosheleva, O., Shahbazova, S.N. (2020). Why triangular and trapezoid membership functions: A simple explanation. In: Recent Developments in Fuzzy Logic and Fuzzy Sets. Edited by S.N. Shahbazova, M. Sugeno, J. Kacprzyk. Springer Cham, 25–31. doi.org/10.1007/978-3-030-38893-5_2
50. Critchfield, T.S., Epting, L.K. (1998). The Trouble with Babies and the Value of Bathwater: Complexities in the Use of Verbal Reports as Data. Analysis of Verbal Behavior, Vol. 15, 65–74. doi.org/10.1007/BF03392924
51. Oh, I.S., Han, J.H. (2021). Will investments in human resources during the COVID-19 pandemic crisis pay off after the crisis? Industrial and Organizational Psychology, Vol. 14, Issue 1-2, 98–100. doi.org/10.1017/iop.2021.13
52. Rudolph, C.W., Allan, B., Clark, M., Hertel, G., Hirschi, A., Kunze, F., Shockley, K., Shoss, M., Sonnentag, S., Zacher, H. (2021). Pandemics: Implications for research and practice in industrial and organizational psychology. Industrial and Organizational Psychology, Vol. 14, Issue 1-2, 1–35. doi.org/10.1017/iop.2020.48
53. Asgary, A., Ozdemir, A.I., Özyürek, H. (2020). Small and medium enterprises and global risks: Evidence from manufacturing SMEs in Turkey. International Journal of Disaster Risk Science, Vol. 11, 59–73. doi.org/10.1007/s13753-020-00247-0
54. Andersen, T.J., Garvey, M., Roggi, O. (2014). Value Based Enterprise Risk Management Practices. In: Managing Risk and Opportunity: The Governance of Strategic Risk-Taking. Oxford University Press, 68–100. doi.org/10.1093/acprof:oso/9780199687855.003.0004
55. Sobocka-Szczapa, H. (2021). Recruitment of employees – assumptions of the risk model. Risks, Vol. 9, Issue 3, 55. doi.org/10.3390/risks9030055
56. Oberholzner, T., Dorr, A. (2017). Employment and job creation in born global enterprises in Austria. In: European Born Globals. Edited by I. Mandl, V. Patrini. London, Routledge, 63–85. doi.org/10.4324/9781315231136
57. Stokes, P., Liu, Y., Smith, S., Leidner, S., Moore, N., Rowland, C. (2016). Managing talent across advanced and emerging economies: HR issues and challenges in a Sino-German strategic collaboration. International Journal of Human Resource Management, Vol. 27, Issue 20, 2310–2338. doi.org/10.1080/09585192.2015.1074090
58. Kimseng, T., Javed, A., Jeenanunta, C., Kohda, Y. (2020). Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity, Vol. 6, Issue 2, 38. doi.org/10.3390/joitmc6020038
59. Benbrahim, C.F., Sefiani, N., Meddaoui, A., Reklaoui, K. (2016). Assessment of human resource competence and performance indicator. International Journal of Process Management and Benchmarking, Vol. 7, No. 1, 20–37. doi.org/10.1504/IJPMB.2017.080937
60. Karatop, B., Kubat, C., Uygun, Ö. (2015). Talent management in manufacturing system using fuzzy logic approach. Computers & Industrial Engineering, Vol. 86, 127–136. doi.org/10.1016/j.cie.2014.09.015
61. Shahhosseini, V., Sebt, M.H. (2011). Competency-based selection and assignment of human resources to construction projects. Scientia Iranica, Vol. 18, Issue 2, 163–180. doi.org/10.1016/j.scient.2011.03.026
62. Wu, Y., Wang, Z., Wang, S. (2021). Human resource allocation based on fuzzy data mining algorithm. Complexity, Vol. 2021, 9489114. doi.org/10.1155/2021/9489114
Acknowledgements
This research was financed as part of the project «Development of a methodology for instrumental base formation for analysis and modeling of the spatial socio-economic development of systems based on internal reserves in the context of digitalization» (FSEG-2023-0008).
About Authors
Tatiana Yurievna Kudryavtseva
Doctor of Economics, Professor, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia (194064, Saint-Petersburg, Polytechnic street, 29); ORCID orcid.org0000-0003-1403-3447 e-mail: kudryavtseva_tyu@spbstu.ru
Angi Erastievich Skhvediani
Candidate of Economic Sciences, Associate Professor, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia (194064, Saint-Petersburg, Polytechnic street, 29); ORCID orcid.org0000-0001-7171-7357 e-mail: shvediani_ae@spbstu.ru
Maiia Sergeevna Leukhina
Master Student, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia (194064, Saint-Petersburg, Polytechnic street, 29); ORCID orcid.org0009-0003-1303-8235 e-mail: maya.leuhina@mail.ru
Alexandra Olegovna Schneider
Master Student, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia (194064, Saint-Petersburg, Polytechnic street, 29); ORCID orcid.org0009-0007-6039-5672 e-mail: shnejder.ao@edu.spbstu.ru
For citation
Kudryavtseva, T.Yu, Skhvediani A.E., Leukhina, M.S., Schneider, A.O. (2023). A Fuzzy Model for Personnel Risk Analysis: Case of Russian-Finnish Export-Import Operations of Small and Medium Enterprises. Journal of Applied Economic Research, Vol. 22, No. 3, 683-709. doi.org/10.15826/vestnik.2023.22.3.028
DOI: https://doi.org/10.15826/vestnik.2023.22.3.028
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