The volatility of bank stock prices and macroeconomic fundamentals in the Pakistani context: an application of GARCH and EGARCH models

Authors

DOI:

https://doi.org/10.24136/oc.2020.025

Keywords:

bank stock return, OLS-HAC, GARCH, EGARCH

Abstract

Research Background: The banking sector plays a crucial role in the world?s economic development. This research paper evaluates the volatility spillover, symmetric, and asymmetric effects between the macroeconomic fundamentals, i.e., market risks, interest rates, exchange rates, and bank stock returns, for the listed banks of Pakistan.

Purpose of the article: The main purpose of this study is to examine the volatility of Pakistani banking stock returns due to the influence of market risk, interest rates, and exchange rates. Pakistan is selected for the study because the volatility of its banking stock returns is strongly influential in achieving sustainable economic development.

Methods: By applying the OLS with the Heteroskedasticity and Autocorrelation Consistent (HAC) covariance matrix, the GARCH (1, 2), and the EGARCH (1, 1), analysis is conducted for the period from January 1, 2009 to December 31, 2019 using samples of 13 listed banks.

Findings & Value added: The ARCH parameter is significant in the OLS with the HAC covariance matrix estimation, which is a clear indication of the existence of heteroskedasticity in the squared residuals and the inaccuracy of the OLS with the HAC covariance matrix. The results of the OLS with the HAC covariance matrix suggest using the GARCH model family to accurately measure the volatility of bank stock prices. The results of the mean equation in the GARCH (1, 2) and EGARCH (1, 1) indicate the positive significance of market risk and the low significance of interest and exchange rates, confirming that market returns strongly affect the sensitivity of bank stock returns compared to interest and exchange rates. It should be noted that the ARCH (?) and GARCH (?) parameters of the variance equation fulfill the non-negative conditions of the GARCH model. Furthermore, the leverage parameter (?) is found to be positively significant for all banks, and volatility is found to be influenced by positive shocks compared to negative shocks. Conclusively, it can be stated that market returns determine the dynamics of the conditional returns of bank stocks. Nevertheless, the interest and exchange rate volatilities determine the conditional bank stock returns? volatility.

Downloads

Download data is not yet available.

References

Ahmad, F., Draz, M. U., & Yang, S. C. (2019). China's economic development: does the exchange rate and FDI nexus matter? Asian?Pacific Economic Literature, 33(2), 81-93. doi: 10.1111/apel.12268.

Adler, M., & Dumas, B. (1983). International portfolio choice and corporation finance: a synthesis. Journal of Finance, 38(3), 925-984. doi: 10.1111/j.1540-6261. 1983.tb02511.x.

Bae, S. (1990). Interest rate changes and common stock returns of financial institutions: revisited. Journal of Financial Research, 13(1), 71-79. doi: 10.111 1/j.1475-6803.1990.tb00537.x.

Booth, J. R., & Officer, D. T. (1985). Expectations, interest rates, and commercial bank stocks. Journal of Financial Research, 8(1), 51-58. doi: 10.1111/j.1475-6803.1985.tb00425.x.

Chance, D. M., & Lane, W. R. (1980). A re-examination of interest rate sensitivity in the common stocks of financial institutions. Journal of Financial Research, 3(1), 49-56. doi: 10.1111/j.1475-6803.1980.tb00036.x.

Chand, S., Kamal, S., & Ali, I. (2012). Modeling and volatility analysis of share prices using ARCH and GARCH models. World Applied Sciences Journal, 19(1), 77-82. doi: 10.5829/idosi.wasj.2012.19.01.793.

Chen, C., & Chan, A. (1989). Interest rate sensitivity, asymmetry, and the stock returns of financial institutions. Financial Review, 24(3), 457-473. doi: 10.1111/j.1540-6288.1989.tb00352.x.

Choi, J. J., Elyasiani, E., & Kopecky, K. J. (1992). The sensitivity of bank stock returns to market, interest, and exchange rate risks. Journal of Banking and Finance, 16(5), 983-1004. doi: 10.1016/0378-4266(92)90036-Y.

Choi, S., Salam, M. A., & Lee, K. D. (2019). The nature of exchange rate movements and exchange rate exposure: the Bangladesh case. Journal of South Asian Development, 14(2), 180-222. doi: 10.1177/0973174119853446.

Chamberlain, S., Howe, J., & Popper, H. (1997). The exchange rate exposure of U.S. and Japanese banking institutions. Journal of Banking & Finance, 21, 871-892. doi: 10.1016/S0378-4266(97)00002-2.

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431. doi: 10.1080/01621459.1979.10482531.

Ekinci, A. (2016). The effect of credit and market risk on bank performance: evidence from Turkey. International Journal of Economics and Financial Issues, 6(2), 427-434.

Elyasiani, E., & Mansur, I. (2003). International spillover of risk and return among major banking institutions: a bivariate GARCH model. Journal of Accounting, Auditing & Finance, 18(2), 303-330. doi: 10.1177/0148558X0301800207.

Fama, E. F., & Schwert, G. W. (1977). Asset returns and inflation. Journal of Financial Economics, 5(2), 115-146. doi: 10.1016/0304-405X(77)90014-9.

Ferson, W. (1989). Changes in expected security returns, risk, and the level of interest rates. Journal of Finance, 44(5), 1191-1217. doi: 10.1111/j.1540-6261. 1989.tb02650.x.

Flannery, M., & James, C. (1984). The effect of interest rate changes on the common stock returns of financial institutions. Journal of Finance, 39(4), 1141-1153.

Flannery, M. (1981). Market interest rates and commercial bank profitability: an empirical investigation. Journal of Finance, 36(6), 1085-1101. doi: 10.1111/j. 1540-6261.1984.tb03898.x.

Foster, J. (1976 ). The redistributive effects of inflation-questions and answers. Scottish Journal of Political Econorny, 23(1), 73-98. doi: 10.1111/j.1467-9485.1976.tb01196.x.

Gilkeson, J. H., & Smith, S. D. (1992). The convexity trap: pitfalls in financing mortgage portfolios and related securities. Economic Review-Federal Reserve Bank of Atlanta, 77(6).

Hahm, J.-H. (2004). Interest rate and exchange rate exposures of banking institutions in pre-crisis Korea. Applied Economics, 36(13), 1409-1419. doi: 10.1080/0003684042000206979.

Hamilton, J. D. (2008). Macroeconomics and ARCH. NBER Working Paper, 14151.

Hooy, C. W., Tan, H. B., & Nassir, A. M. (2004). Risk sensitivity of bank stocks in Malaysia: empirical evidence across the Asian financial crisis. Asian Economic Journal, 18(3), 261-276. doi: 10.1111/j.1467-8381.2004.00192.x.

Hussain, F., Hamid, K., Imdad Akash, R. S., & Imdad Khan, M. (2011). Day of the week effect and stock returns: (evidence from Karachi stock exchange-Pakistan). Far East Journal of Psychology and Business, 3(1).

Jiménez?Rodríguez, R., & Sánchez, M. (2012). Oil price shocks and Japanese macroeconomic developments. Asian?Pacific Economic Literature, 26(1), 69-83. doi: 10.1111/j.1467-8411.2012.01336.x.

Kasman, S., Vardar, G., & Tunç, G. (2011). The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: evidence from Turkey. Economic Modelling, 28(3), 1328-1334. doi: 10.1016/j.econmod.2011. 01.015.

Kane, E., & Unal, H. (1988). Change in market assessments of deposit-institution riskiness. Journal Of Financial Services Research., 1, 207-229. doi: 10.1007/B F00114851.

Merton, R. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867-887. doi: 10.2307/1913811.

Newey, W., & West, K. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55, 703-708.

Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: a new approach. Econometrica: Journal of the Econometric Society, 59(2), 347-370. doi: 10.2307/2938260.

Nelson, D., & Foster, D. (1995). Filtering and forecasting with misspecified ARCH models II making the right forecast with the wrong model. Journal of Econometrics, 67(2), 303-335. doi: 10.1016/0304-4076(94)01635-D.

Nor, M. I., Masron, T. A., & Alabdullah, T. T. Y. (2020). Macroeconomic fundamentals and the exchange rate volatility: empirical evidence from Somalia. SAGE Open, 10(1). doi: 10.1177/2158244019898841.

Olbryś, J. (2018). The non-trading problem in assessing commonality in liquidity on emerging stock markets. Dynamic Econometric Models, 18, 67-79. doi: 10.12775/DEM.2018.004.

Olbryś, J. (2019). Intra-market commonality in liquidity: new evidence from the Polish stock exchange. Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(2), 251-275. doi: 10.24136/eq.2019.012.

Olbryś, J. (2020). No commonality in liquidity on small emerging markets? Evidence from the Central and Eastern European stock exchanges. Comparative Economic Research. Central and Eastern Europe, 23(3), 91-109.

Olbryś, J., & Majewska, E. (2017). Asymmetry effects in volatility on the major European stock markets: the EGARCH based approach. Quantitative Finance and Economics, 1(4), 411-427. doi: 10.3934/QFE.2017.4.411.

Patnaik, I., & Shah, A. (2004). Interest rate volatility and risk in Indian banking. International Monetary Fund Working Paper, 1-28.

Salamat, S., Lixia, N., Naseem, S., Mohsin, M., Zia-ur-Rehman, M., & Baig, SA (2020). Modeling cryptocurrencies volatility using GARCH models: a comparison based on normal and Student's T-error distribution. Entrepreneurship and Sustainability Issues, 7(3), 1580-1596. doi: 10.9770/jesi.2019.7.3(11).

Saunders, A., & Yourougou, P. (1990). Are banks special? The separation of banking from commerce and interest rate risk. Journal of Economics and Business, 42(2), 171-182. doi: 10.1016/0148-6195(90)90033-9.

Shanken, J. (1990). Intertemporal asset pricing an empirical investigation. Journal of Econometrics, 2, 99-120. doi: 10.1016/0304-4076(90)90095-B.

Sukcharoensin, P. (2013). Time-varying market, interest rate and exchange rate risks of Thai commercial banks. Asian Academy of Management Journal of Accounting and Finance, 9(1), 25?45.

Scott, W., & Peterson, R. (1986). Interest rate risk and equity values of hedged and unhedged financial intermediaries. Journal of Financial Research, 9(4), 325-329. doi: 10.1111/j.1475-6803.1986.tb00465.x.

Shah, S. Z., Baharumshah, A. Z., & Habibullah, M. S. (2019). Dynamic linkages and volatility transmissions between macroeconomic uncertainty and performance: evidence from South Asian countries. Journal of South Asian Development, 14(3), 281-313. doi: 10.1177/0973174119874184.

Stone, B. (1974). Systematic interest-rate risk in a two-index model of returns. Journal of Financial and Quantitative Analysis, 9(5), 709-721. doi: 10.2307/ 2329656.

Sweeney, R., & Warga, A. (1986). The pricing of interest-rate risk: evidence from the stock market. Journal of Finance, 12(2), 393-410. doi: 10.2307/2328443.

Verma, P. (2016). The impact of exchange rates and interest rates on bank stock returns evidence from U.S. banks. Studies in Business and Economics, 11(1), 124-139. doi: 10.1515/sbe-2016-0011.

Yourougou, P. (1990). Interest-rate risk and the pricing of depository financial intermediary common stock. Journal of Banking And Finance, 14(4), 803-820. doi: 10.1016/0378-4266(90)90077-F.

Tsay, R. S. (2010). Analysis of financial time series. New York: John wiley & sons.

Markowicz, I., & Baran, P. (2020). A new method for calculating mirror data asymmetry in international trade. Oeconomia Copernicana, 11(4), 637?656. doi: 10.24136/oc.2020.026

Contact to corresponding author: iwona.markowicz@usz.edu.pl; University of Szczecin, ul. Mickiewicza 64, 71-101 Szczecin, Poland

Iwona Markowicz

University of Szczecin, Poland

orcid.org/0000-0003-1119-0789

Paweł Baran

University of Szczecin, Poland

orcid.org/0000-0002-7687-4041

A new method for calculating mirror data asymmetry in international trade

JEL Classification: F14; C10; C82

Keywords: international trade; intra-community trade; mirror data; COMEXT

Abstract

Research background: Some statistics are of a bilateral nature. This is how foreign trade data is organized. They are recorded both in the supplier and recipient countries, hence they are called mirror data. The data recorded at both trading partner countries are not the same for different reasons. Such differences between data on the same groups of transactions are often referred to as the asymmetry of mirror data. The information about the value of the flows of goods are of great importance in economic analyses and therefore their quality is particularly important.

Purpose of the article: The aim of this paper is to present a new measure of data asymmetry ? the aggregated quantity index with value-based weights.

Methods: The proposed measure combines the quantity and the value of turn-over in individual trade relations. Such a measure makes it possible to eliminate basic deficiencies in value-based measures, while considering the specificity of trade in individual countries. The proposed measure of data asymmetry was confronted with several measures present in the literature and previously used by the Authors. The numerical example uses Comext data on intra-Community trade in 2017 provided by Eurostat.

Findings & Value added: The proposed measure performs better than all the previously used data asymmetry indices. It is to some extent immune to exchange rate differences and inconsistencies resulting from the inclusion of transport and insurance costs in the value of goods. In addition, it gives lower weights to unimportant trade directions than other data asymmetry indices. Since the new index has proved to be better than the measures previously used, it is worth applying to those trade relations where the data are not de-rived from customs documents, but from declarations made by businesses, as in the case of intra-Community trade.

References

Bahmani-Oskooee, M., Usman, A., & Ullah, S. (2020). Asymmetric J-curve in the commodity trade between Pakistan and United States: evidence from 41 industries. Eurasian Economic Review, 10, 163-188. doi: 10.1007/s40822-019-00137-x.

Baran, P., & Markowicz, I. (2018). Analysis of intra-community supply of goods shipped from Poland. Socio-Economic Modelling and Forecasting, 1, 12-21.

Carr?re, C., & Grigoriou, Ch. (2014). Can mirror data help to capture informal international trade? Policy issues in international trade and commodities research study series No. 65. New York: UNCTAD.

Cate ten, A. (2007). Modelling the reporting discrepancies in bilateral data. CPB Netherlands Bureau for Economic Policy Analysis Memorandum, 179.

Cate ten, A. (2014). The identification of reporting accuracies from mirror data. Jahrbücher für Nationalökonomie und Statistik, 234(1), 70-84. doi: 10.1515/ jbnst-2014-0106.

Eurostat (2017). National requirements for the Intrastat system. Luxembourg: Publications Office of the European Union.

Federico, G., & Tena, A. (1991). On the accuracy of foreign trade statistics (1909?1935). Morgenstern revisited. Explorations in Economic History, 28(3), 259?273. doi: 10.1016/0014-4983(91)90007-6.

Ferrantino, M. J., Liu, X., & Wang, Z. (2012). Evasion behaviors of exporters and importers: evidence from the U.S.?China trade data discrepancy. Journal of International Economics, 86(1), 147-157. doi: 10.1016/j.jinteco.2011.08.006.

Ferrantino, M. J., & Wang, Z. (2008). Accounting for discrepancies in bilateral trade: the case of China, Hong Kong, and the United States. China Economic Review, 19(3), 502-520. doi: 10.1016/j.chieco.2008.02.002.

Fisman, R., & Wei, S-J. (2004). Tax rates and tax evasion: evidence from ?missing imports? in China. Journal of Political Economy, 112(2), 471-496. doi: 10.1086 /381476.

Guo, D. (2010). Mirror statistics of international trade in manufacturing goods: the case of China. UNIDO, Research and Statistics Branch Working Paper, 19/2009.

Hamanaka, S. (2012). Whose trade statistics are correct? Multiple mirror comparison techniques: a test of Cambodia. Journal of Economic Policy Reform, 15(1), 33-56. doi: 10.1080/17487870.2012.657827.

HMRC Trade Statistics (2014). A reconciliation of asymmetries in trade-in-goods statistics published by the UK and other European Union member states. Southend-on-Sea.

Hummels, D. L., & Lugovskyy, V. (2006) Are matched partner trade statistics a usable measure of transportation costs? Review of International Economics 14(1), 69-86. doi: 10.1111/j.1467-9396.2006.00561.x.

Javorcik, B. S., & Narciso, G. (2008). Differentiated products and evasion of import tariffs. Journal of International Economics, 76(2), 208-222.

LeSage, J. P., & Llano-Verduras, C. (2014). Forecasting spatially dependent origin and destination commodity flows. Empirical Economics, 47, 1543-1562. doi: 10.1007/s00181-013-0786-2.

Markowicz, I., & Baran, P. (2019a). ICA and ICS-based rankings of EU countries according to quality of mirror data on intra-Community trade in goods in the years 2014?2017. Oeconomia Copernicana, 10(1), 55-68. doi: 10.24136/oc. 2019.003.

Markowicz, I., & Baran, P. (2019b). Quality of intrastat data. Comparison between ?old? and ?new? EU member states. Acta Universitatis Lodziensis. Folia Oeconomica, 2(341), 69?80. doi: 10.15611/eada.2020.1.01.

Markowicz I., & Baran P. (2020a). Discrepancies between mirror data on intra-community trade: the case of Poland. Econometrics. Ekonometria, 24(1), 1-11. doi: 10.15611/eada.2020.1.01.

Markowicz, I., & Baran, P. (2020b). Identification of EU countries due to the quality of data on intra-community supplies of goods shipped from Poland in the years 2005?2017. In K. Nermend & M. Łatuszyńska (Eds.). Experimental and quantitative methods in contemporary economics: computational methods in experimental economics (CMEE) 2018 Conference. Cham: Springer International Publishing. doi: 10.1007/978-3-030-30251-1_22.

Morgenstern, O. (1963). On the accuracy of economic observations. New Jersey: Princeton University Press.

Parniczky, G. (1980). On the inconsistency of world trade statistics. International Statistical Review, 48(1), 43-48. doi: 10.2307/1402404.

Rasoulinezhad, E. (2018). A new evidence from the effects of Russia?s WTO accession on its foreign trade. Eurasian Economic Review, 8, 73-92. doi: 10.1007/ s40822-017-0081-1.

Splunk (2019). The state of dark data. Industry leaders reveal the gap between AI?s potential and today?s data reality.

Tsigas, M. E., Hertel, T. W., & Binkley, J. K. (1992). Estimates of systematic reporting biases in trade statistics. Economic Systems Research, 4(4), 297-310. doi: 10.1080/09535319200000028.

Roszko-Wójtowicz, E., Grzelak, M.M., Laskowska, I., (2019). The impact of research and development activity on the TFP level in manufacturing in Poland. Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(4), 711-737. doi: 10.24136/eq.2019.033.

Yurik, S., Pushkin, N., Yurik, V., Halík, J., & Smutka, L., (2020). Analysis of Czech agricultural exports to Russia using mirror statistics. Entrepreneurial Business and Economics Review, 8(2), 27-46. doi: 10.15678/EBER.2020.080 202.

Roszko-Wójtowicz, E., & Grzelak, M. M. (2020). Macroeconomic stability and the level of competitiveness in EU member states: a comparative dynamic approach. Oeconomia Copernicana, 11(4), 657?688. doi: 10.24136/oc.2020.027

Contact to corresponding author: elzbieta.roszko@uni.lodz.pl; University of Lodz, Department of Economic and Social Statistics, ul. Rewolucji 1905 r. 41, 90-214 Lodz

Elżbieta Roszko-Wójtowicz

University of Lodz, Poland

orcid.org/0000-0001-9337-7218

Maria M. Grzelak

University of Lodz, Poland

orcid.org/0000-0003-4353-9893

Macroeconomic stability and the level of competitiveness in EU member states: a comparative dynamic approach

JEL Classification: C30; E01

Keywords: macroecnomic stabilisation pentagon; competitiveness; competitive position; competitive capacity; Hellwig's method; linear ordering; European Union

Abstract

Research background: The choice of the issue of international competitive-ness of economies as the research problem addressed in this paper has been mainly dictated by the changes observed in the nature of the development of EU economies and the need to assess the competitiveness of the Polish economy. It is time to evaluate and learn from the largest enlargement in the history of the EU which took place in May 2004. An assessment of changes in the state of EU economies, including the Polish economy, is in the centre of research interest of many scientists. National competitiveness is the subject of a great deal of research and economic studies. Integration and globalisation processes in the world economy are the main reasons for the popularity of this topic. The efficient use of sources and factors determining the competitiveness of economies, sectors and enterprises is associated with prosperity over the long term. One of the methods based on the observation of selected basic indicators of economic competitiveness is the method of analysis called the macroeconomic stabilisation pentagon. The method illustrates the extent to which the government achieves five macroeconomic objectives. It is very difficult, if not impossible, to meet all these objectives at the same time. The difficulty of meeting all these goals concurrently is due to the fact that they are more or less competitive rather than complementary. The proposed assessment of competitiveness based on the developed model of macroeconomic stabilisation pentagon is a unique approach in terms of discussion of country?s competitiveness. This approach significantly distinguishes the current study in comparison with standard international reports on competitiveness such as the Global Competitiveness Index or the EU Regional Competitiveness Index.

Purpose of the article: The main aim of the paper is to assess the competitiveness of EU economies in the years 2005?2018, based on a selected set of diagnostic variables referring to the concept of macroeconomic stabilisation pentagon. The paper also formulates a detailed list of four research hypotheses.

Methods: In order to characterise the competitiveness of the European Union economies, including the EU?15 and EU?13 groups, as well as the Visegrad group, six diagnostic variables affecting the economic situation of individual EU countries were analysed. The variables for analysis were chosen so as to reliably describe the competitive position of a given country, at the same time referring in a substantive sense to the concept of macroeconomic stabilisation pentagon. The linear ordering of objects was made using the reference Hellwig method. The selected method enabled the development of competitiveness rankings of EU Member States in the years 2005, 2009, and 2018.

Findings & Value added: The comparative analysis of the main macroeconomic indicators conducted in the paper forms the basis for assessing the cur-rent state of the EU economy in relation to other countries. In the paper, the authors depart from the standard elaboration of ?magic pentagon.? Instead, they apply the variables used in the macroeconomic stabilisation pentagon analysis to develop competitiveness rankings of EU Member States. The con-ducted empirical study has confirmed that the 15th anniversary of EU member-ship had a decidedly positive impact on the level of economic development of the EU?13 countries.

References

Ahangari, A., Arman, A., & Saki, A. (2014). The estimation of Iran?s macroeconomics instability index. Management Science Letters, 4(5), 871-882. doi: 10.5267/j.msl.2014.4.003.

Aiginger, K. (1998). A framework for evaluating the dynamic competitiveness of countries. Structural Change and Economic Dynamics, 9(2), 159-188. doi: 10.1016/S0954-349X(97)00026-X.

Aiginger, K. (2000). Europe?s position in quality competition. Background report for European Competitiveness Report. Brussels: European Commission.

Aiginger, K., & Landesmann M. (2002). Competitive economic performance: the European view. WIFO Working Papers, 179.

Altomonte, C., & Ottaviano, G.I.P. (2011). The role of international production sharing in EU productivity and competitiveness. European Investment Bank Papers, 16(1), 62-89.

Altomonte, C., Aquilante, T., & Ottaviano, G. (2012). The triggers of competitiveness: the EFIGE cross-country report. Brussels: Bruegel.

Annoni, P., Dijkstra, L., & Gargano, N. (2017). The EU regional competitiveness index 2016. European Commission Working Paper, WP 02/2017. doi: 10.2776 /94425.

Balcerzak, A. P. (2016). Multiple-criteria evaluation of quality of human capital in the European Union countries. Economics and Sociology, 9(2), 11-26. doi: 10.14254/2071-789X.2016/9-2/1.

Balcerzak, A. P. (2020). Quality of institutions in the European Union countries. Application of TOPSIS based on entropy measure for objective weighting. Acta Polytechnica Hungarica, 17(1), 101-122. doi: 10.12700/APH.17.1.2020.1.6.

Balcerzak, A. P., & Pietrzak, M. B. (2017a). Digital economy in Visegrad countries. Multiple-criteria decision analysis at regional level in the years 2012 and 2015. Journal of Competitiveness, 9(2), 5-18. doi: 10.7441/joc.2017.02.01.

Balcerzak, A. P., & Pietrzak, M. B. (2017b). TOPSIS with Generalized Distance Measure GDM in assessing poverty and social exclusion at regional level in Visegrad countries. In P. Pražák (Ed.). 35th international conference mathematical methods in economics MME 2017 conference proceedings. Hradec Králové: University of Hradec Králové, 18-23.

Bąk, A. (2016). Linear ordering of objects using Hellwig and TOPSIS methods - a comparative analysis. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 426, 22-31.

Berger, I. (2011). An overview and analysis on indices of regional competitiveness. Review of Economics and Finance, 1, 17-33.

Berger, T. (2008). Concepts on national competitiveness. Journal of International Business and Economy, 9(1), 3-17.

Blanchard, O., & Giavazzi, F. (2002). Current account deficits in the Euro area: the end of the Feldstein-Harioka puzzle? Brookings Papers on Economic Activity, 33(2), 142-210.

Blanchard, O., & Milesi-Feretti, G. M. (2011). (Why) should current account balances be reduced? IMF Staff Discussion Note, SDN/11/03.

Borowski, J. (2015). International competitiveness: theoretical concepts. Optimum. Studia Ekonomiczne, 4(76), 25-42. doi: 10.15290/ose.2015.04.76.02.

Burda, M. C., & Dluhosch, B. (2002). Cost competition, fragmentation, and globalization. Review of International Economics, 10(3), 424-441. doi: 10.1111/14 67-9396.00341.

Burda, M. C., & Severgnini, B. (2009). TFP growth in old and new Europe. SFB 649, Discussion Paper, Humboldt University, 2009-033.

Castellani, D., Piva, M., Schubert, T., & Vivarelli, M. (2018). Can European productivity make progress? Intereconomics: Review of European Economic Policy, 53(2), 75­78. doi: 10.1007/s10272­018­0725­8.

Castellani, D., Piva, M., Schubert, T., & Vivarelli, M. (2016). The productivity impact of R&D investment: a comparison between the EU and the US. Institute for the Study of Labor (IZA) Discussion Papers, 9937.

Castles, I., & Henderson, D. (2005). International comparisons of GDP: issues of theory and practice. World Economics, 6(1), 55-66. doi: 10.22459/mpw.04. 2014.16.

Cheba, K., & Szopik-Depczyńska, K. (2017). Multidimensional comparative analysis of the competitive capacity of the European Union countries and geographical regions. Oeconomia Copernicana, 8(4), 487-504. doi: 10.24136/oc.v8 i4.30.

Chen, Y., Kersten, G., Vetschera, R., & Xu, H. (Eds.). (2018). Group decision and negotiation in an uncertain world. GDN 2018, 18th International Conference Proceedings. Nanjing, China.

Chikan, A. (2008). National and firm competitiveness: a general research model. Competitiveness Review, 18(1), 20-28. doi: 10.1108/10595420810874583.

Cho, D. S., & Moon, H. C. (2013). From Adam Smith to Michael Porter: evolution of competitiveness theory. Singapore: World Scientific Publishing Company. doi: 10.1142/8451.

Cho, D., & Hwy-Chang, M. (2000). From Adam Smith to Michael Porter: evaluation of competitiveness theory. Singapore: World Scientific Publishing.

Cho, D. S., Moon, H. C., & Kim, M. Y. (2009). Does one size fit all? A dual double diamond approach to country-specific advantages. Asian Business and Management, 8(1), 83-102. doi: 10.1057/abm.2008.27.

Clyde, V., & Prestowitz, J. (1994). Playing to win. Foreign Affairs, 73(4), 186-189, doi: 10.2307/20046815.

Cohen, S. (1994). Speaking freely. Foreign Affairs, 73(4), 194-197. doi: 10.2307 /20046818.

Daszkiewicz, N. (Ed.). (2008). Konkurencyjność. Poziom makro, mezo i mikro. Warszawa: Wydawnictwo Naukowe PWN.

Dia, M., & Abdelaziz, F. (2011). A hierarchical methodology for performance evaluation based on Data Envelopment Analysis: the case of companies? competitiveness in an economy. American Journal of Operations Research, 1(3), 134-146. doi: 10.4236/ajor.2011.13015.

Dunning, J. H. (Ed.). (2000). Globalization, regions, and the knowledge-based economy. Oxford: Oxford University Press.

Delgado, M., Ketels, C., Porter, M. E., & Stern, S. (2012). The determinants of national competitiveness. NBER Working Paper, 18249. doi: 10.3386/w1824.

DiRienzo, C., Das, J., & Burbridge, J. (2007). Does diversity impact competitiveness? A cross country analysis. Competitiveness Review, 17(3), 135-152.

Dresch, A., Collatto, D. C., & Lacerda, D. P. (2018). Theoretical understanding between competitiveness and productivity: firm level. Industrial Engineering, 20(2), 69-86. doi: 10.25100/iyc.v20i2.5897.

Eichengreen, B. (2006). Global imbalances: the new economy, the dark matter, the savvy investor, and the standard analysis. Journal of Policy Modeling, 28(6), 645-652. doi: 10.1016/j.jpolmod.2006.06.001.

Esty, D. C., & Porter M. E. (2002). Ranking national environmental regulation and performance: a leading indicator of future competitiveness? In M. E. Porter, J. D. Sachs, P. K. Cornelius, J. W. McArthur & K. Schwab (Eds). The global competitiveness report 2001?2002. Oxford: Oxford University Press, 78-101.

European Commission (2019). Alert mechanism report 2020. Report from the Commission to the European Parliament, the Council, the European Central Bank and the European Economic and Social Committee, COM(2019)651 final. Strasbourg: European Commission.

Fagerberg, J. (2002). Technology, growth and competitiveness. Selected Essays. Cheltenham, UK: Edward Elgar Publishing.

Frieden, J., & Rogowski R. (1996). The impact of the international economy on national policies: an analytical overview. In R. O. Keohane & H. V. Milner (Eds.). Internationalization and domestic politics. Cambridge University Press. doi: 10.1017/CBO9780511664168.003.

Gardiner, B., Martin, R., & Tyler, P. (2006). Competitiveness, productivity and economic growth across the European regions. In R. Martin, M. Kitson, & P. Tyler (Eds.). Regional competitiveness. London: Routledge. doi: 10.4324/9780 203607046.

Gorynia, M. (2019). Competition and globalisation in economic sciences. Selected aspects. Economics and Business Review, 5/19(3), 118-133. doi: 10.18559/ebr. 2019.3.7.

Gruber, J. W., & Kamin, S. B. (2007). Explaining the global pattern of current account imbalances. Journal of International Money and Finance, 26(4), 500-522. doi: 10.2139/ssrn.854224.

Grabiński, T., Wydymus, S., & Zeliaś, A. (1989). Metody taksonomii numerycznej w modelowaniu zjawisk społeczno-gospodarczych. Warszawa: PWN.

Grabiński, T., Wydymus, S., & Zeliaś, A. (1982). Metody doboru zmiennych w modelach ekonometrycznych. Warszawa: Państwowe Wydawnictwo Naukowe, 1982.

Hämäläinen, T. J. (2003). National competitiveness and economic growth, the changing determinants of economic performance in the world economy. Cheltenham, UK: Edward Elgar Publishing.

Huggins, R., Izushi, H., & Thompson, P. (2013). Regional competitiveness: theories and methodologies for empirical analysis. Journal of CENTRUM Cathedra (JCC): The Business and Economics Research Journal, 6(2), 155-172. doi: 10.7835/jcc-berj-2013-0086.

Hurduzeu, G., & Lazar, M. I. (2015). An assessment of economic stability under the new European economic governance. Management Dynamics in the Knowledge Economy, 3(2).

IMD (2020). The IMD World Competitivenss Yearbook 2020. Switzerland: IMD.

Ketels, C. (2016). Review of competitiveness frameworks: an analysis conducted for the Irish National Competitiveness Council. Retrieved from http://www.hbs.edu/faculty/Publication%20Files/Review%20of%20Competitiveness%20Frameworks%20_3905ca5fc5e6-419b-8915-5770a2494381.pdf. (1.02.2020).

Kim, K. M., & Kwon, H.-K. (2017). The state?s role in globalization: Korea?s experience from a comparative perspective. Politics & Society, 45(4), 505-531. doi: 10.1177/0032329217715614.

Kołodko, G. W. (1994). The Vishegrad economies in transition: the comparative perspective of the macroeconomic stabilization pentagon. In H. Herr, S. Tober, & A. Westphal (Eds.). Macroeconomic problems of transformation. Stabilization policies and economic restructuring. Aldershot: Edward Elgar, 115-123.

Krugman, P. (1996). Making sense of the competitiveness debate. Oxford Review of Economic Policy, 12(3), 17-25. doi: 10.1093/oxrep/12.3.17.

Krugman, P. (1994). Competitiveness: a dangerous obsession. Foreign Affairs, 73(2), 28-44.

Lanoie, P., Laurent-Lucchetti, J., Johnstone, N., & Ambec, S. (2011). Environmental policy, innovation and performance: new insights on the Porter hypothesis. Journal of Economics and Management Strategy, 20(3), 803-842. doi: 10.1111/j.1530-9134.2011.00301.x.

Liu, C. (2017). International competitiveness and the fourth industrial revolution. Entrepreneurial Business and Economics Review, 5(4), 111-133. doi: 10.1567 8/EBER.2017.050405.

Lyulyov, O., & Shvindina, H. (2017). Stabilization pentagon model: application in the management at macro- and micro-levels. Problems and Perspectives in Management, 15(3), 42-52. doi: 10.21511/ppm.15(3).2017.04.

Machek, O., & Hnilica, J. (2012). Total factor productivity approach in competitive and regulated world. Procedia ? Social and Behavioral Sciences, 57, 223-230. doi: 10.1016/j.sbspro.2012.09.1178.

Marsh, K., Goetghebeur, M., Thokala, P., & Baltussen, R. (Eds.). (2017). Multi-criteria decision analysis to support healthcare decisions. Berlin, Germany: Springer International Publishing AG. doi: 10.1007/978-3-319-47540-0_5.

Martin, R., Kitson, M., & Tyler, P. (2006). Regional competitiveness: an elusive yet key concept? In R. Martin, M. Kitson & P. Tyler (Eds.). Regional competitiveness. London: Routledge. doi: 10.4324/9780203607046.

Martínez, V., & Sanchez-Robles, R.B. (2012). Macroeconomic stability and growth in Eastern Europe. In G. Erreygers & W. Meeusen (Eds.). Macroeconomics and beyond: essays in honour of Wim Meeusen. Garant: Antwerpen.

Matkowski, Z., Rapacki, R., & Próchniak, M. (2016). Porównanie wyników gospodarczych Polska na tle Unii Europejskiej. In M. A. Weresa (Ed.). Polska. Raport o konkurencyjności 2016. Warszawa: Szkoła Główna Handlowa ? Oficyna Wydawnicza.

Misala, J. (2011). Międzynarodowa konkurencyjność gospodarki narodowej. Warszawa: Polskie Wydawnictwo Ekonomiczne.

Młodak, A. (2006). Analiza taksonomiczna w statystyce regionalnej. Warszawa: Wydawnictwo Difin.

Momaya, K. S. (2019). The past and the future of competitiveness research: a review in an emerging context of innovation and EMNEs. International Journal of Global Business and Competitiveness, 14, 1-10. doi: 10.1007/s42943-019-00002-3.

Montiel, P., & Servén L. (2006). Macroeconomic stability in developing countries: how much is enough? World Bank Research Observer, 21(2), 151-178. doi: 10.1093/wbro/lkl005.

Moon, H. C., & Cho, D. S. (2000). National competitiveness: a nine factor approach and its empirical application. Journal of International Business and Economy, Fall, 17-38.

Mróz, J. (2016). Determinanty i miary międzynarodowej konkurencyjności gospodarki. In P. Urbanek & E. Walińska (Eds). Ekonomia i nauki o zarządzaniu w warunkach integracji europejskiej. Ekonomia i Zarządzanie w Teorii i Praktyce, Tom 9. Łódź: Wydawnictwo Uniwersytetu Łódzkiego, 15-29.

Nehme, G. N. (2014). Ensuring effectiveness of economic and monetary policies through considering economic schools of thought: Lebanon 1990-2010. Open Journal of Social Sciences, 2(4), 197-205. doi: 10.4236/jss.2014.24020.

Nehme, G. N., & Nehme, E. (2014) Competitive advantage of nations and multilateral trade system: how can Lebanon benefit from trade liberalization without enhancing its strategic industries? Open Journal of Social Sciences, 2, 217-231. doi: 10.4236/jss.2014.24023.

Obstfeld, M., & Taylor, A. M. (2002). Globalization and capital market. NBER, Working Paper, 8846.

Panek, T. (2009) Statystyczne metody wielowymiarowej analizy porównawczej. Warszawa: Szkoła Główna Handlowa w Warszawie.

Perenyi, Á. (2016). Diagnosing cluster competitiveness using firm level data in the profit-growth nexus framework. Acta Oeconomica, 66(3), 469-463. doi: 10.1556/032.2016.66.3.4.

Petricevic, O., & Teece, D.J. (2019). The structural reshaping of globalization: implications for strategic sectors, profiting from innovation, and the multinational enterprise. Journal of International Business Studies, 50, 1487-1512. doi: 10.1057/s41267-019-00269-x.

Pieloch-Babierz, A., Misztal, A., & Kowalska M. (2020). An impact of macroeconomic stabilization on the sustainable development of manufacturing enterprises: the case of Central and Eastern European Countries. Environment, Development and Sustainability, Advance online publication. doi: 10.1007/s10668-020-00988-4.

Porter, M., Stern, S., & Green, M. (2016). Social progress index 2016. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/mx/Documents/about-deloitte/Social-Progress-Index-2016-Report.pdf. (11.06.2020).

Porter, M. E. (2003). The economic performance of regions. Regional Studies, 37(6/7), 549-578. doi: 10.1080/0034340032000108688.

Porter, M. E. (2001). Porter o konkurencji. Warszawa: PWE.

Porter, M. E. (1998). The competitive advantage of nations. New York: Free Press.

Porter, M. E. (1990). The competitive advantage of nations. Harvard Business Review, 68, 73-93.

Rogalska, E. (2018a). Cluster analysis of entrepreneurial environment in Polish regions. In M. Reiff & P. Gezik (Eds.). Proceedings of the international scientific conference quantitative methods in economics multiple criteria decision making XIX. Trenčianske Teplice: Letra Edu, 305-312.

Rogalska, E. (2018b). Measurement of entrepreneurship conditions in Polish regions. In T. Loster & T. Pavelka (Eds.). The 11th international days of statistics and economics. Conference proceedings. September 6-8, 2018. Prague: Libuse Macakova, Melandrium, 1479-1487.

Rogalska, E. (2018c). Taxonomic measure of development with entropy weights in assessment of entrepreneurial conditions in Poland. In 36th international conference mathematical methods in economics MME 2018 conference proceedings. Prague: MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University, 463-469.

Roszko-Wójtowicz, E., Grzelak, M. M., & Laskowska, I. (2019). The impact of research and development activity on the TFP level in manufacturing in Poland. Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(4), 711-737. doi: 10.24136/eq.2019.033.

Roszko-Wójtowicz, E., & Białek J. (2019). Measurement of the average innovativeness change overtime in the EU member states. Journal of Business Economics and Management, 20(2), 268-293, doi: 10.3846/jbem.2019.8337.

Rugman, A. M., & D'Cruz, J. R. (1993). The ?Double diamond? model of international competitiveness: the Canadian experience. Management International Review, 33(2), 17-39.

Rugman, A. M., & Verbeke, A. (1993). How to operationalize porter's diamond of international competitiveness. International Executive, 35(4), 283-299. doi: 10.1002/tie.5060350403

Rusu, V. D., & Roman, A. (2018) An empirical analysis of factors affecting competitiveness of C.E.E. countries. Economic Research-Ekonomska Istraživanja, 31(1), 2044-2059. doi: 10.1080/1331677X.2018.1480969.

Santos, A. D., Ribeiro, S., Castela, G., & da Silva N. T. (2017). The dynamics between economic growth and living standards in EU countries: a STATICO approach for the period 2006?2014. Estudios de economía aplicada, 35(3), 629-652.

Schwab, K. (Ed.). (2019). The global competitiveness report 2019. Switzerland: World Economic Forum.

Schwab, K., & Sala-i-Martin, X. (2013). The global competitiveness report 2013?2014. Geneva: World Economic Forum.

Su, W., Zhang, D., Zhang, C., Abrhám, J., Simionescu, M., Yaroshevich, N., & Guseva, V. (2018). Determinants of foreign direct investment in the Visegrad group countries after the EU enlargement. Technological and Economic Devel-opment of Economy, 24(5). doi: 10.3846/tede.2018.5487.

Walesiak, M. (2011). Uogólniona miara odległości GDM w statystycznej analizie wielowymiarowej z wykorzystaniem programu R, Wrocław: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu.

Walesiak, M. (2004). Metody porządkowania liniowego. In E. Gatnar, M. Walesiak (Eds.). Metody statystycznej analizy wielowymiarowej w badaniach marketingowych. Wrocław: Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu.

Weresa, M. A. (Ed.). (2016). Poland: competitiveness report 2016. The role of economic policy and institutions. Warsaw: Warsaw School of Economics Press. Retrieved from https://ssl-kolegia.sgh.waw.pl/pl/KGS/struktura/IGS-KGS/publi kacje/Documents/Raport_POLAND2016.pdf. (18.10.2019).

Weresa, M. A. (2008). Definicja, determinanty oraz sposoby pomiaru konkurencyjności krajów. In W. Bieńkowski & M. A. Weresa (Eds.). Czynniki i miary międzynarodowej konkurencyjności gospodarek w kontekście globalizacji. Warszawa: Szkoła Główna Handlowa.

Vachris, M. A. (1999). International price comparisons based on purchasing power parity. Monthly Labor Review, October.

Zanakis, S. H., & Becerra-Fernandez, I. (2005). Competitiveness of nations, a knowledge discovery examination. European Journal of Operational Research, 166(1), 185-211. doi: 10.1016/j.ejor.2004.03.028.

Zeliaś, A. (2004). Taksonomiczna analiza przestrzennego zróżnicowania poziomu życia w Polsce w ujęciu dynamicznym. Kraków: Akademia Ekonomiczna.

Żuchowska, D. (2013). Assessment of the Central and Eastern Europe economies in the years 2007-2010 based on the model of the macroeconomic stabilization pentagon. Equilibrium. Quarterly Journal of Economics and Economic Policy, 8(4), 49-64. doi: 10.12775/EQUIL.2013.026.

Gavurova, B., Belas, J., Bilan, Y., & Horak, J. (2020). Study of legislative and administrative obstacles to SMEs business in the Czech Republic and Slovakia. Oeconomia Copernicana, 11(4), 689?719. doi: 10.24136/oc.2020.028

Contact to corresponding author: beata.gavurova@tuke.sk; Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical university of Košice, Komenského 1096/19, 040 01 Košice, Slovak Republic

Beata Gavurova

Technical university of Košice, Slovakia

orcid.org/0000-0002-0606-879X

Jaroslav Belas

Tomas Bata University in Zlín, Czech Republic

orcid.org/0000-0002-5900-997X

Yuriy Bilan

Rzeszów University of Technology, Poland

orcid.org/0000-0003-0268-009X

Jakub Horak

Institute of Technology and Business in Ceske Budejovice, Czech Republic

orcid.org/0000-0001-6364-9745

Study of legislative and administrative obstacles to SMEs business in the Czech Republic and Slovakia

JEL Classification: L26; O16

Keywords: small and medium-sized enterprises; SMEs; legislative obstacles; administrative obstacles; business environment; stability of business environment

Abstract

Research background: SMEs represent an integral part of the economy environment in a majority of the countries all over the world. They signify the most efficient, progressive, and important part of the advanced economies. The long-term effort of the EU countries, as well as other advanced economies is to create quality and stable conditions for their development in order to be able to respond to all the possible changes in the business environment that is being changed to more and more comprehensive in the recent time.

Purpose of the article: The objective of the contribution is to examine administrative and legislative obstacles to SMEs business in the Czech Republic and Slovakia and the quantification of the differences in perceiving legislative and administrative obstacles to business by entrepreneurs in both countries.

Methods: A questionnaire survey was conducted within SMEs in the Czech Republic and Slovakia in 2019. The research sample included 641 SMEs, 312 from the Czech Republic and 329 from Slovakia. We focused on 5 dimensions related to legislative and administrative obstacles to SMEs business within which selected statements were examined. Contingency tables were used to analyze the ratios of the examined variables.

Findings & Value added: The differences detected in both countries in the respondents´ perception and assessment are evidence of the changes in the business environment of both countries, giving rise to the questions about the extent to which the legislative and administrative obstacles, as well as the obstacles related to law enforcement and bureaucracy are acceptable and by which groups of entrepreneurs. The results of the research provide valuable findings for the creators of regional and national policies, and represent a valuable basis for the creation of the concepts focused on the SMEs´ development in both countries. The results of the study also support the implementation of follow-up research in this area that will reveal other determinants affecting the development of SMEs. They also create a valuable platform for the construction of national and international benchmarking indicators in this area and the implementation of comparative analyses. This will also support the methodological area necessary for a creation of high-quality concepts and strategies.

References

Abrham, J., Strielkowski, W., Vošta, M., & Šlajs, J. (2015). Factors that influence the competitiveness of Czech rural small and medium enterprises. Agricultural Economics ? Czech, 61(10). doi: 10.17221/63/2015-AGRICECON.

Anand, B. (2015). Reverse globalization by internationalization of SME's: opportunities and challenges ahead. Procedia - Social and Behavioral Sciences, 195. doi: 10.1016/j.sbspro.2015.06.359.

Ariel, E., & Rocha, G. (2012). The impact of the business environment on the size of the micro, small and medium enterprise sector; preliminary findings from a cross-country comparison. Procedia Economics and Finance, 4. doi: 10.1016/ S2212-5671(12)00348-6.

Balcerzak, A. P. (2020). Quality of institutions in the European Union countries. Application of TOPSIS based on entropy measure for objective weighting. Acta Polytechnica Hungarica, 17(1), 101-122. doi: 10.12700/APH.17.1.2020.1.6.

Bileviciute, E., Draksas, R., Nevera, A., & Vainiute, M. (2019). Competitiveness in higher education: the case of university management. Journal of Competitiveness, 11(4). doi: 10.7441/joc.2019.04.01.

Buno, M., Nadanyiova, M., & Hraskova, D. (2015). The comparison of the quality of business environment in the countries of Visegrad group. Procedia Economics and Finance, 26. doi: 10.1016/S2212-5671(15)00826-6.

Čepel, M. (2019). Social and cultural factors and their impact on the quality of business environment in the SME segment. International Journal of Entrepreneurial Knowledge, 7(1). doi: 10.2478/ijek-2019-0005.

DiPietro, F., Palacin-Sanchez, M. J., & Roldan, J. L. (2017). Regional development and capital structure of SMEs. Cuadernos de Gestion, 18(1), 1-24. doi: 10.5295 /cdg.150530fd.

Dvorský, J., Petráková, Z., & Polách, J. (2019). Assessing the market, financial, and economic risk sources by Czech and Slovak SMEs. International Journal of Entrepreneurial Knowledge, 7(2). doi: 10.12345-0008.

Gavurova, B., Kubak, M., Huculova, E., Popadakova, D., & Bilan, S. (2019). Financial literacy and rationality of youth in Slovakia. Transformations in Business &Economics, 18(3).

Gavurova, B., Huculova, E., Kubak, M., & Cepel, M. (2017). The state of student?s financial literacy in selected Slovak universities and its relationship with active pension savings. Economics & Sociology, 10(3). doi: 10.14254/2071-789x.201 7/10-3/15.

Kot, S., Onyusheva, I., & Grondys, K. (2018). Supply chain management in SMEs: evidence from Poland and Kazakhstan. Engineering Management in Production and Services, 10(3). doi: 10.2478/emj-2018-0014.

Kraśnicka, T., & Głód, W. (2016). Management innovation and its measurement. Journal of Business, Management and Innovation, 12(2).

Ključnikov, A., Kozubíková, L., & Sopková, G. (2017). The payment discipline of small and medium-sized enterprises. Journal of Competitiveness, 9(2). doi: 10.7441/joc.2017.02.04.

Lisowska, R. (2016). The potential of business environment institutions and the support for the development of small and medium-sized enterprises. Entrepreneurial Business and Economics Review, 4(3). doi: 10.15678/EBER.2016.04 0307.

Matijová, M., Onuferová, E., Rigelský, E., & Stanko, V. (2019). Impact of selected indicators of tourism capacity and performance in the context of the unemployment rate in Slovakia. Journal of Tourism and Services, 10. doi: 10.29036/ jots.v10i19.95.

Michalski, G. (2014). Value maximizing corporate current assets and cash management in relation to risk sensitivity: Polish firms case. Economic Computation and Economic Cybernetics Studies and Research, 48(1).

Michalski, G. (2013). Financial consequences linked with investments in current assets: Polish firms case. In European financial systems 2013, Brno: Masaryk University, 213-220.

Mura, L., & Kajzar, P. (2019). Small businesses in cultural tourism in a Central European country. Journal of Tourism and Services, 10(19). doi: 10.29036/jots .v10i19.110.

Nguyen, T. A. N., & Rozsa, Z. (2019). Financial literacy and financial advice seeking for retirement investment choice. Journal of Competitiveness, 11(1). doi: 10.7441/joc.2019.01.05.

Onuferová, E., & Čabinová, V. (2018). Enterprise performance analysis of the selected service sector by applying modern methods with an emphasis on the creation and application of the modified creditworthy model. Journal of Tourism and Services, 9(17). doi: 10.29036/jots.v9i17.74.

Perez-Gomez, P., Arbelo-Perez, M., & Arbelo, A. (2018). Profit efficiency and its determinants in small and medium-sized enterprises in Spain. BRQ Business Research Quarterly, 21(4). doi 10.1016/j.brq.2018.08.003.

Psárska, M., Vochozka, M., & Machová, V. (2019). Performance management in small and medium-sized manufacturing enterprises operating in automotive in the context of future changes and challenges in SR. Ad Alta: Journal of Interdisciplinary Research, 9(2).

Rahman, A., Rahman, M. T., & Belas, J. (2017). Determinants of SME finance: evidence from three central European countries. Review of Economic Perspectives, 17(3).

Wang, Y. (2016). What are the biggest obstacles to growth of SMEs in developing countries? ? An empirical evidence from an enterprise survey. Borsa Istanbul Review, 16(3). doi: 10.1016/j.bir.2016.06.001.

Stefko, R., Fedorko, R., Bacik, R., Rigelsky, M., & Olearova, M. (2020). Effect of service quality assessment on perception of TOP hotels in terms of sentiment polarity in the Visegrad group countries. Oeconomia Copernicana, 11(4), 721?742. doi: 10.24136/oc.2020.029

Contact to corresponding author: richard.fedorko@unipo.sk; University of Prešov in Prešov, Faculty of Management, Konštantínová 16, 080 01 Prešov, Slovakia

Robert Stefko

University of Prešov in Prešov, Slovakia

orcid.org/0000-0002-0650-7780

Richard Fedorko

University of Prešov in Prešov, Slovakia

orcid.org/0000-0003-3520-1921

Radovan Bacik

University of Prešov in Prešov, Slovakia

orcid.org/0000-0002-5780-3838

Martin Rigelsky

University of Prešov in Prešov, Slovakia

orcid.org/0000-0003-1427-4689

Maria Olearova

University of Prešov in Prešov, Slovakia

orcid.org/0000-0001-9086-7975

Effect of service quality assessment on perception of TOP hotels in terms of sentiment polarity in the Visegrad group countries

JEL Classification: M31; L83; D12

Keywords: sentiment polarity; customer satisfaction; hotel; Visegrad group

Abstract

Research background: In the developed countries, the services sector, which also includes the accommodation services, is a significant source of the gross national product. Tourism can be perceived as an important determinant of countries' economies, so attention paid to the needs of clients is at least necessary and beneficial.

Purpose of the article: The aim of the study is to assess the quality of services provided and the perception of the hotel from the point of view of the accommodated clients. This objective was fulfilled by determining the effect of selected indicators of perception of the quality of provided services (location, personnel evaluation, cleanliness, equipment, comfort, price/quality ratio of provided services, free Wi-Fi connection) on the indicator determining the perception of the hotel (polarity of sentiment).

Methods: In the analysis of the above, 22,000 text-reviews of 117 five-star hotels of the Visegrad Group countries were evaluated. The hotel reviews were obtained from Tripadvisor.com and indicator rankings from Booking.com. The analysis made use of the regression analysis methods ? influence (regulatory models ? Ridge, Lasso, Elastic net, and multiple linear regression ? OLS).

Findings & Value added: It has been found out that hotel equipment and cleanliness have the greatest effect on the polarity of sentiment. As could be expected, the trend has an upward tendency ? that is, as quality increases, so does the sentiment polarity ? the perception of hotel facilities. Overall, the analysed sentiment variables can be considered positive, as was confirmed by the positive coefficients of the coherence analysis (Spearman-?; Pearson-r), as well as the upward trend in the predictions under the regression analysis. Hotels should be strategically customer-oriented and, as the analyses show, pay the greatest attention to equipment and cleanliness. The services of accommodation facilities are dominant in terms of satisfaction with the destination in general, so in the long run, they should be given due attention. These findings are particularly beneficial for hotel services provided in the Visegrad Group countries, as no research studies have yet been carried out on customer evaluation of the quality of accommodation facilities using the presented methods.

References

Albayrak, T., & Caber, M. (2015). Prioritisation of the hotel attributes according to their influence on satisfaction: a comparison of two techniques. Tourism Management, 46. doi: 10.1016/j.tourman.2014.06.009.

Assaf, A. G., & Magnini, V. (2012). Accounting for customer satisfaction in measuring hotel efficiency: evidence from the US hotel industry. International Journal of Hospitality Management, 31. doi: 10.1016/j.ijhm.2011.08.008.

Banerjee, S., & Chua, A. Y. (2016). In search of patterns among travellers' hotel ratings in TripAdvisor. Tourism Management, 53. doi: 10.1016/j.tourman.2015 .09.020.

Barreda, A., & Bilgihan, A. (2013). An analysis of user?generated content for hotel experiences. Journal of Hospitality and Tourism Technology, 4(3). doi: 10.1108/JHTT-01-2013-0001.

Berezina, E., & Cobanoglu, C. (2010). Importance-performance analysis of in-room technology amenities in hotels. In U. Gretzel, R. Law, & M. Fuchs (Eds.) Information and communication technologies in tourism. Vienna: Springer. doi: 10.1007/978-3-211-99407-8.

Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding satisfied and dissatisfied hotel customers: text mining of online hotel reviews. Journal of Hospitality Marketing & Management, 25(1). doi: 10.1080/1936862 3.2015.983631.

Bhandari, M., & Rodgers, S. (2018). What does the brand say? Effects of brand feedback to negative eWOM on brand trust and purchase intentions. Inter-national Journal of Advertising, 37(1). doi: 10.1080/02650487.2017.1349030.

Booking (2019). Booking. Retrieved from https://www.booking.com/ (25.06.2019).

Bulchand-Gidumal, J., Melián-González, S., & Lopez-Valcarcel, B. G. (2013). A social media analysis of the contribution of destinations to client satisfaction with hotels. International Journal of Hospitality Management, 35. doi: 10.1016 /j.ijhm.2013.05.003.

Bulut, M., Demirbas, M., & Ferhatosmanoglu, H.(2015). LineKing: coffee shop wait-time monitoring using smartphones. IEEE Transactions on Mobile Computing, 14(10). doi: 10.1109/TMC.2014.2384032.

Callan, R. J., & Kyndt, G. (2001). Business travellers? perception of service quality: a prefatory study of two european city centre hotels. International Journal of Tourism Research, 3. doi: 10.1002/jtr.333.

Carneiro, M. J., & Costa, C. (2000). The influence of service quality on the positioning of five star hotels?the case of the Lisbon area. Journal of Quality Assurance in Hospitality & Tourism, 1(4). doi: 10.1300/J162v01n0401.

Chaves, M. S., Gomes, R., & Pedron, C. (2012). Analysing reviews in the Web 2.0: small and medium hotels in Portugal. Tourism Management, 33(5). doi: 10.1016/j.tourman.2011.11.007.

Choi, T. Y., & Chu, R. (2001). Determinants of hotel guests? satisfaction and repeat patronage in the Hong Kong hotel industry. International Journal of Hospitality Management, 20(3). doi: 10.1016/S0278-4319(01)00006-8.

Crick, A., & Spencer, A. (2011). Hospitality quality: new directions and new challenges. International Journal of Contemporary Hospitality Management, 23(4). doi: 10.1108/09596111111129986.

Deng, W. J., Yeh, M. L., & Sung, M. L. (2013). A customer satisfaction index model for international tourist hotels: integrating consumption emotions into the American customer satisfaction index. International Journal of Hospitality Management, 35. doi: 10.1016/j.ijhm.2013.05.010.

Ekiz E., Khoo-Lattimore, C., & Memarzadeh, F. (2012). Air the anger: investigating online complaints on luxury hotels. Journal of Hospitality and Tourism Technology, 3(2). doi: 10.1108/17579881211248817.

Emir, O. (2016). A study of the relationship between service atmosphere and customer loyalty with specific reference to structural equation modelling. Economic Research, 29(1). doi: 10.1080/1331677X.2016.1195276.

Gretzel, U., & Yoo, K. H. (2008). Use and impact of online travel reviews. In P. O?Connor, W. Höpken, & U. Gretzel (Eds). Information and communication technologies in tourism 2008. Vienna: Springer. doi: 10.1007/978-3-211-77280-5_4.

Hasegawa, H. (2014). Customer satisfaction and online hotel review evaluation. Tourismos, 9(1).

Hemsley-Brown, J., & Alnawas, I. (2016). Service quality and brand loyalty. International Journal of Contemporary Hospitality Management, 28(12). doi: 10.1108/IJCHM-09-2015-0466.

Heung, V. C. S. (2000). Satisfaction levels of mainland Chinese travelers with Hong Kong hotel services. International Journal of Contemporary Hospitality Management, 12(5). doi: 10.1108/09596110010339689.

Hui, T. K., Wan, D., & Ho, A. (2007). Tourists? satisfaction, recommendation and revisiting Singapore. Tourism Management, 28(4). doi: 10.1016/j.tourman.2006 .08.008.

Kim, W. G., Ng, C. Y. N., & Kim, Y. S. (2009). Influence of institutional DINESERV on customer satisfaction, return intention, and word-of-mouth. International Journal of Hospitality Management, 28(1). doi: 10.1016/j.ijhm.2008. 03.005.

Kim, B., Kim, S., & Heo, C. Y. (2016). Analysis of satisfiers and dissatisfiers in online hotel reviews on social media. International Journal of Contemporary Hospitality Management, 28(9). doi: 10.1108/IJCHM-04-2015-0177.

Kucukusta, D. (2017). Chinese travelers? preferences for hotel amenities. International Journal of Contemporary Hospitality Management, 29(7). doi: 10.1108/ IJCHM-09-2016-0511.

Lai, I. K. W., & Hitchcock, M. (2017). Sources of satisfaction with luxury hotels for new, repeat, and frequent travelers: a PLS impact-asymmetry analysis. Tourism Management, 60. doi: 10.1016/j.tourman.2016.11.011.

Lee, C. C., & Hu, C. (2004). Analyzing hotel customers? e-complaints from an internet complaint forum. Journal of Travel & Tourism Marketing, 17(2?3). doi: 10.1300/J073v17n02_13.

Lee, G., & Tussyadiah, P. (2010). The influence of wi-fi service on hotel customer satisfaction. In Proceedings of the 9th Asia pacific forum for graduate students? research in tourism. Kyushu: Beppu.

Lewis, B. R., & McCann, P. (2004). Service failure and recovery: evidence from the hotel industry. International Journal of Contemporary Hospitality Management, 16(1). doi: 10.1108/09596110410516516.

Li, M., Huang, L., Tan, C.-H. & Wei, K.-K. (2013). Helpfulness of online product reviews as seen by consumers: source and content features. International Journal of Electronic Commerce, 17(4). doi: 10.2753/JEC1086-4415170404.

Li, X., & Hitt, L. M. (2008). Self-selection and information role of online product reviews. Information Systems Research, 19(4). doi: 10.1287/isre.1070.0154.

Limberger, P., Anjos, F., Meira, J., & Anjos, S. (2014). Satisfaction in hospitality on TripAdvisor.com: an analysis of the correlation between evaluation criteria and overall satisfaction. Tourism & Management Studies, 10(1).

Lin, C. N., Tsai, L. F., Wang, P. W., Su., W. J., & Shaw, J. C.. (2011). Using the expected importance and perceived satisfaction of tourists to construct indicators for improvement of resort hotel service quality. International Journal of Computer Science and Network Security, 11(4).

Lockyer, T. (2003). Hotel cleanliness?how do guests view it? Let us get specific: a New Zealand study. International Journal of Hospitality Management, 22. doi: 10.1016/S0278-4319(03)00024-0.

Lopes, R., Abrantes, J., & Kastenholz, E. (2014). Innovation, tourism and social networks. Revista Turismo e Desenvolvimento, 21(22).

Mohsin, A., & Lockyer, T. (2010). Customer perceptions of service quality in luxury hotels in New Delhi, India: an exploratory study. International Journal of Contemporary Hospitality Management, 22(2). doi: 10.1108/09596111011 018160.

Ortiz-Rendón, P. A., Sanchez Torres, W. C., & Zu?iga-Collazos, A. (2018). Hotel ethical behavior and tourist origin as determinants of satisfaction. Journal of Environmental Management and Tourism, 8(8). doi: 10.14505/jemt.v8.8(24) .01.

Papathanassis, A., & Knolle, F. (2011). Exploring the adoption and processing of online holiday reviews: a grounded theory approach. Tourism Management, 32(2). doi: 10.1016/j.tourman.2009.12.005.

Poon, W., & Low, K. L. (2005). Are travellers satisfied with Malaysian hotels? International Journal of Contemporary Hospitality Management, 17(3). doi: 10.1108/09596110510591909.

Radojevic, T., Stanisic, N., & Stanic, N. (2015). Solo travellers assign higher ratings than families: examining customer satisfaction by demographic group. Tourism Management Perspectives, 16. doi: 10.1016/j.tmp.2015.08.004.

Rajaguru, R., & Rajesh, G. (2016). Value for money and service quality in customer satisfaction. Social Sciences, 11(19). doi: 10.36478/sscience.2016.461 3.4616.

Rauch, D. A., Collins, M. D., Nale, R. D., & Barr, P. B. (2015). Measuring service quality in mid-scale hotels. International Journal of Contemporary Hospitality Management, 27(1). doi: 10.1108/IJCHM-06-2013-0254.

Shankar, V., Urban, G. L., & Sultan, F. (2002). Online trust: a stakeholder perspective, concepts, implications, and future directions. Journal of Strategic Information Systems, 11(3). doi: 10.1016/S0963-8687(02)00022-7.

Sim, J., Mak, B., & Jones, D. (2006). A model of customer satisfaction and retention for hotels. Journal of Quality Assurance in Hospitality & Tourism, 7(3). doi: 10.1300/J162v07n03_01.

Sparks, B. A., & Browning, V. (2010). Complaining in cyberspace: the motives and forms of hotel guests? complaints online. Journal of Hospitality Marketing & Management, 19(7). doi: 10.1080/19368623.2010.508010.

Sun, K. A., & Kim, D. Y. (2013). Does customer satisfaction increase firm performance? An application of American Customer Satisfaction Index (ACSI). International Journal of Hospitality Management, 35. doi: 10.1016/j.ijhm.2013. 05.008.

Štefko, R., Fedorko, I., Bačík, R., & Fedorko, R. (2015). An analysis of perceived topicality of website content influence in terms of reputation management. Polish Journal of Management Studies, 12(1).

Štefko, R., Fedorko, R., Bačík, R. (2016). Website content quality in terms of perceived image of higher education institution. Polish Journal of Management Studies, 13(2). doi: 10.17512/pjms.2016.13.2.15.

Stringam, B. B., & Gerdes, J. (2010). An analysis of word-of-mouse ratings and guest comments of online hotel distribution sites. Journal of Hospitality Marketing & Management, 19(7). doi: 10.1080/19368623.2010.508009.

Tripadvisor (2019). Tripadvisor. Retrieved from https://www.tripadvisor.com/ (25.05.2019).

Va´squez, C. (2011). Complaints online: the case of TripAdvisor. Journal of Pragmatics, Postcolonial Pragmatics, 43(6). doi: 10.1016/j.pragma.2010.11. 007.

Victorino, L., Verma, R. Plaschka, G., & Dev, C. (2005). Service innovation and customer choices in the hospitality industry. Managing Service Quality, 15(6). doi: 10.1108/09604520510634023.

Wang, S., & Hung, K. (2015). Customer perceptions of critical success factors for guest houses. International Journal of Hospitality Management, 48. doi: 10.1016/j.ijhm.2015.05.002.

Xiang, Z., & Krawczyk, M. (2016). What does hotel location mean for the online consumer? Text analytics using online reviews. In Information and communication technologies in tourism 2016). Proceedings of the international conference. Bilbao. doi: 10.1007/978-3-319-28231-2_28.

Xie, K. L., Zhang, Z., & Zhang, Z. (2014). The business value of online consumer reviews and management response to hotel performance. International Journal of Hospitality Management, 43. doi: 10.1016/j.ijhm.2014.07.007.

Xu, X., & Li, Y. (2016). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: a text mining approach. International Journal of Hospitality Management, 55. doi: 10.1016/j.ijhm.2016.03.003.

Yang, J., & Mai, E. (2010). Experiential goods with network externalities effects: An empirical study of online rating system. Journal of Business Research, 63(9-10). doi: 10.1016/j.jbusres.2009.04.029.

Ye, Q., Law, R., & Gu, B. (2009). The impact of online user reviews on hotel room sales. International Journal of Hospitality Management, 28. doi: 10.1016/j. ijhm.2008.06.011.

Ye, Q., Law, R., Li, S., & Li, Y. (2011). Feature extraction of travel destinations from online Chinese-language customer reviews. International Journal of Services Technology and Management, 15(1). doi: 10.1504/IJSTM.2011.038665.

Yoon, Y., & Uysal, M. (2005). An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26. doi: 10.1016/j.tourman.2003.08.016.

Zhang, Z, Ye, Q., & Law, R. (2011). Determinants of hotel room price. International Journal of Contemporary Hospitality Management, 23(7). doi: 10.1108/ 09596111111167551.

Zhou, L., Yea, S., Pearce, P. L., Wua, M. Y. (2014). Refreshing hotel satisfaction studies by reconfiguring customer review data. International Journal of Hospitality Management, 38. doi: 10.1016/j.ijhm.2013.12.004.

Vveinhardt, J., & Sroka, W. (2020). Mobbing and corporate social responsibility: does the status of the organis

Downloads

Published

2020-12-30

How to Cite

Mohsin, M., Naiwen, L., Zia-UR-Rehman, M., Naseem, S., & Baig, S. A. (2020). The volatility of bank stock prices and macroeconomic fundamentals in the Pakistani context: an application of GARCH and EGARCH models. Oeconomia Copernicana, 11(4), 609-636. https://doi.org/10.24136/oc.2020.025

Issue

Section

Articles