The use of neural networks to determine value based drivers for SMEs operating in the rural areas of the Czech Republic

Abstract

Research background: In the past, the main objective of a company was to generate sufficient profit. Nowadays, a company must seek to achieve much broader objectives. To be successful in this pursuit, it must not only measure financial performance, but also monitor internal and external developments, increase shareholders? wealth and protect the interests of other stakeholders, i.e. to analyze and act on those factors that affect company value.

Purpose of the article: The objective of the contribution is to determine through the use of artificial neural networks the relationship between business value drivers, or value based drivers (VBD), and EVA Equity, which is economic value added (EVA), of small and medium-sized enterprises operating in the rural areas of the Czech Republic.

Methods: The data was obtained from the Bisnode´s Albertina database. The data set consists of the profit and loss accounts for 2013 to 2017 of small and medium-sized enterprises operating in rural areas of the Czech Republic. Two scenarios are analyzed. In the first, the independent variables are only the value drivers, whereas in the second, company location (region) is included. The objective is to find the dependence of EVA Equity on individual VBD and company location. A sensitivity analysis is conducted, on the basis of which the importance of individual value drivers and company location is determined.

Findings & Value added: The output is a set of value drivers, which could be used by company managers to regulate the growth of EVA Equity, i.e. value for shareholders. The findings reveal that the difference between successful and unsuccessful companies is determined by the level of involvement of human capital; companies use a large number of substitutes for factors of production, whereby the involvement of borrowed capital is likely to cause a positive financial leverage effect.

Keywords

business value drivers, value based drivers, small and medium-sized enterprises, rural area, ultimate goal, economic value added, neural networks

References

1. Akalu, M. M. (2002). Measuring and ranking value drivers. Retrieved from https://www.econstor.eu/bitstream/10419/85955/1/02043.pdf (20.01.2020).
   View in Google Scholar
2. Andrea, B., Coulson, A., Hogan, R., & Evans, J. D. (2015). Does the strategic alignment of value drivers impact earnings persistence? Sustainability Accounting, Management and Policy Journal, 6(3). doi: 10.1108/SAMPJ-11-2014-0073. DOI: https://doi.org/10.1108/SAMPJ-11-2014-0073
   View in Google Scholar
3. Brata, H. O., Estensen, L., & Ekambaram, A. (2015). Competence brokering: an efficient tool to provide R&D to SMEs in rural areas. In M. Massaro & A. Garlatti (Eds.). Proceedings of the European conference on knowledge management. Reading: Academic Conferences and Publishing International Limited.
   View in Google Scholar
4. Delgado Ferraz, F. A., & Gallardo-Vázquez, D. (2016). Measurement tool to assess the relationship between corporate social responsibility, training practices and business performance. Journal of Cleaner Production, 129. doi: 10.1016/j.jcle pro.2016.03.104. DOI: https://doi.org/10.1016/j.jclepro.2016.03.104
   View in Google Scholar
5. Di Tollo, G., Tanev, S., Davide, D. M., & Ma, Z. (2012). Neural networks to model the innovativeness perception of co-creative firms. Expert Systems with Application, 39(16). doi: 10.1016/j.eswa.2012.05.022. DOI: https://doi.org/10.1016/j.eswa.2012.05.022
   View in Google Scholar
6. Firk, S., Schrapp, S., & Wolff, M. (2013). Drivers of value creation – the role of value-based management and underlying institutions. Management Accounting Research, 33. doi: 10.1016/j.mar.2016.04.002. DOI: https://doi.org/10.1016/j.mar.2016.04.002
   View in Google Scholar
7. Hall, J. H. (2016). Industry-specific determinants of shareholder value creation. Studies in Economics and Finance, 33(2). doi: 10.1108/SEF-08-2014-0155.
   View in Google Scholar
8. Hall, J. H. (2016). Industry-specific determinants of shareholder value creation. Studies in Economics and Finance, 33(2). doi: 10.1108/SEF-08-2014-0155. DOI: https://doi.org/10.1108/SEF-08-2014-0155
   View in Google Scholar
9. Hammann, E. M., Habisch, A., & Pechlaner, H. (2008). Values that create value: socially responsible business practices in SMEs – empirical evidence from German companies. Business Ethics: A European Review, 18(1). doi: 10.1111/ j.1467-8608.2009.01547.x. DOI: https://doi.org/10.1111/j.1467-8608.2009.01547.x
   View in Google Scholar
10. Heckman, T. G., Somlai, A. M., Otto-Salaj, L., & Davantes, B. R. (1998). Health-related quality of life among people living with HIV disease in small communities and rural areas. Psychology & Health, 13(5). doi: 10.1080/08870449 808407436 DOI: https://doi.org/10.1080/08870449808407436
    View in Google Scholar
11. Cheverton, P. (2004). Key marketing skills: strategies,tools & techniquies for marketing success. London: Kogan Page.
    View in Google Scholar
12. Janda, K., Rausser, G., & Strielkowski, W. (2013). Determinants of profitability of Polish rural micro-enterprises at the time of EU accession. Eastern European Countryside, 19(1). doi: 10.2478/eec-2013-0009. DOI: https://doi.org/10.2478/eec-2013-0009
    View in Google Scholar
13. Kazlauskiene, V., & Christauskas, C. (2008). Business valuation model based on the analysis of business value drivers. Inzinerine Ekonomika-Engineering Economics, 2.
    View in Google Scholar
14. Klieštik, T., Lyakin, A. N., & Valášková, K. (2014). Stochastic calculus and modelling in economics and finance. In G. Lee (Ed.). 2nd international conference on economics and social science, information engineering research institute, advances in education research. Texas City: Information Engineering Research Institute.
    View in Google Scholar
15. Koller, T., Copeland, T. E., Goedhart, M., & Wessels, D. (2005). Valuation: measuring and managing the value of companies. New York: John Wiley & Sons.
    View in Google Scholar
16. Kuzey, C., Uyar, A., & Delen, D. (2014). The impact of multinationality on firm value: a comparative analysis of machine learning techniques. Decision Support Systems, 59. doi: 10.1016/j.dss.2013.11.001.
    View in Google Scholar
17. Kuzey, C., Uyar, A., & Delen, D. (2014). The impact of multinationality on firm value: a comparative analysis of machine learning techniques. Decision Support Systems, 59. doi: 10.1016/j.dss.2013.11.001. DOI: https://doi.org/10.1016/j.dss.2013.11.001
    View in Google Scholar
18. Lin, G. T., & Tang, J. Y. H. (2009). Appraising intangible assets from the viewpoint of value drivers. Journal of Business Ethics, 88(4). doi: 10.1007/s 10551-008-9974-y. DOI: https://doi.org/10.1007/s10551-008-9974-y
    View in Google Scholar
19. Liu, Y. C., & Yeh, I. C. (2016). Building valuation model of enterprise values for construction enterprise with quantile neural networks. Journal of Construction Engineering and Management, 142(2). doi: 10.1061/(ASCE)CO.1943-7862. 0001060. DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001060
    View in Google Scholar
20. Machová, V., & Rowland, Z. (2018). Value generators of enterprises in the processing industry. In O. Dvouletý, M. Lukeš & J. Mísař (Eds.). Proceedings of the 6th international conference innovation management, entrepreneurship and sustainability. Prague: Oeconomica Publishing House.
    View in Google Scholar
21. Machová, V., & Vrbka, J. (2018). Value generators for businesses in agriculture. In T. Löster & T. Pavelka (Eds.). 12th international days of statistics and economics. Slaný: Melandrum.
    View in Google Scholar
22. Machová, V., & Horák, J. (2020). Value generators in forestry and logging. In J. Horák, J. Vrbka, & Z. Rowland (Eds.). SHS Web of conferences: innovative economic symposium 2019 – potential of Eurasian Economic Union. Les Ulis: SHS Web of Conferences. doi: 10.1051/shsconf/20207302003. DOI: https://doi.org/10.1051/shsconf/20207302003
    View in Google Scholar
23. Miao, Q. (2010). Study on the financing difficulties of the rural SMEs and countermeasures. In R. J. Li, H. Zhang & R. M. Zhao (Eds.). 4th international conference on the development of small and medium-sized enterprises. Marrickville: Orient Academic Forum.
    View in Google Scholar
24. Miles, S. J., & Van Clieaf, M. (2017). Strategic fit: key to growing enterprise value through organizational capital. Business Horizons, 60(1). doi: 10.1016/j.bushor .2016.08.008. DOI: https://doi.org/10.1016/j.bushor.2016.08.008
    View in Google Scholar
25. Neumaierová, I., & Neumaier, I. (2008). Financial analysis of industry and construction for the year 2007. Analýzy MPO.
    View in Google Scholar
26. Olsen, M. D. (2008). Strategic management in the hospitality industry. New York: John Wiley & Sons.
    View in Google Scholar
27. Panaretou, A. (2013). Corporate risk management and firm value: evidence from the UK market. European Journal of Finance, 20(12). doi: 10.1080/1351847X. 2013.766625.
    View in Google Scholar
28. Panaretou, A. (2014). Corporate risk management and firm value: evidence from the UK market. European Journal of Finance, 20(12). doi: 10.1080/1351847X. 2013.766625. DOI: https://doi.org/10.1080/1351847X.2013.766625
    View in Google Scholar
29. Rappaport, A. (1998). Creating shareholder value: a guide for managers and investors. New York: The Free Press.
    View in Google Scholar
30. Reno, A., & Vadi, M. (2010). What factors predict the values of an organization and how? Tartu: The University of Tartu FEBA. DOI: https://doi.org/10.2139/ssrn.1635901
    View in Google Scholar
31. Scarlett, R. C. (2001). Value-based management. London: Ivey Management Services.
    View in Google Scholar
32. Serefoglu, C., & Gokkaya, E. (2017). Challenges of rural SMEs in Ankara, Turkey. In C. A. Brebbia, J. Longhurst, E. Marco & C. Booth (Eds.). 9th international conference on sustainable development and planning – sustainable development and planning IX. Southampton: WIT Press. doi: 10.2495/SDP170271. DOI: https://doi.org/10.2495/SDP170271
    View in Google Scholar
33. Stehel, V., & Vochozka, M. (2016). The analysis of the economical value added in transport. Nase More, 63(3). doi: 10.17818/NM/2016/SI20. DOI: https://doi.org/10.17818/NM/2016/SI20
    View in Google Scholar
34. Stehel, V., Horák, J., & Vochozka, M. (2019). Prediction of institutional sector development and analysis of enterprises active in agriculture. E & M Ekonomie a Management, 22(4). doi:10.15240/tul/001/2019-4-007. DOI: https://doi.org/10.15240/tul/001/2019-4-007
    View in Google Scholar
35. Strielkowski, W., Lisin, E., & Herget, J. (2015). Success factors of rural SMEs: a case study of Polish micro enterprises. In E. Pastuszková, Z. Crhová, J. Vychytilová, B. Vytvrhlíková & A. Knápková (Eds.). International scientific conference on finance and performance of firms in science, education and practice. Zlín: Tomas Bata University.
    View in Google Scholar
36. Sulistyowati, L., Pardian, P., Syamsyiah, N., & Deliana, Y. (2018). Development of small and medium business (SMES) of mango dodol processing to increase the added value (a case study in Ujungjaya Village, Indramayu District, West Java). In IOP conference series: earth and environmental science. Bristol: IOP Publishing. doi: 10.1088/1755-1315/142/1/012042. DOI: https://doi.org/10.1088/1755-1315/142/1/012042
    View in Google Scholar
37. Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2). doi: 10.1016/j.ejor.2017.02.023. DOI: https://doi.org/10.1016/j.ejor.2017.02.023
    View in Google Scholar
38. Vochozka, M., & Machová, V. (2018). Determination of value drivers for transport companies in the Czech Republic. Naše More, 65(4). doi: 10.17818/NM/2018/ 4SI.6. DOI: https://doi.org/10.17818/NM/2018/4SI.6
    View in Google Scholar
39. Vochozka, M., & Rowland, Z. (2015). The evaluation and prediction of the viability of construction enterprises. Littera Scripta, 8(1).
    View in Google Scholar
40. Vochozka, M., & Machová, V. (2017). Enterprise value generators in the building industry. In J. Váchal, M. Vochozka & J. Horák (Eds.). SHS web of conferences: innovative economic symposium 2017 – strategic partnership in international trade. Les Ulis: SHS Web of Conferences. DOI: https://doi.org/10.1051/shsconf/20173901029
    View in Google Scholar
41. Vochozka, M., Horák, J., & Šuleř, P. (2019). Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate. Journal of Risk and Financial Management, 12(2). doi: 10.3390/jrfm12020076. DOI: https://doi.org/10.3390/jrfm12020076
    View in Google Scholar
42. Wilimowska, Z., & Krzysztoszek, T. (2013). The use of artificial neural networks in company valuation process. Studies in Computational Intelligence, 457. doi: 10.1007/978-3-642-34300-1_27. DOI: https://doi.org/10.1007/978-3-642-34300-1_27
    View in Google Scholar