Economic Development, Technological Change and Growth
Abstract
Lots of tourism data vary over time for that reason the quality processing techniques are
demanded to relate such a series. This study concerns the covariance, resp. variance analysis of
arrivals to regions of the Czech Republic using static multivariate methods of partial least squares
(PLS), resp. principal component analysis (PCA). In addition, an analysis based on eigenvalue
decomposition of Euclidean similarity matrix is employed. The relation of profiles and the direction
of processes using linear trends in annual data are studied between arrivals of non-residents and
residents. The results are attempted to connect them with some economic parameters and global
events.
References
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Retrieved 11.8.2013.
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Corrochano, E. (Ed.). Handbook of Geometric Computing: Applications in Pattern Recognition,
Computer Vision, Neural Computing, and Robotics (pp. 1-39). Springer-Verlag, Heidelberg.
Elmore, K.L. & Richman, R. (2001). Euclidean distance as a similarity metric for principal
component analysis. Monthly Weather Review, 129(3): 540-9.
Exploring historical towns of Bohemia, Moravia and Silesia. The Association of Historical
Settlements in Bohemia, Moravia and Silesia, EU project. URL:
http://www.shscms.cz/en/eu-project-uexploring-historical-towns-of-bohemia-moravia-and-silesiau-
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Gardiner, S., King, C. & Grace, D. (2013). Travel decision making: An empirical examination of
generational values, attitudes, and intentions. Journal of Travel Research, 52(3): 310-24.
Griffith, D.A. & Amrhein, C.G. (1997). Multivariate statistical analysis for geographers. NJ: Prentice
Hall.
Harville, D.A. (1997). Matrix algebra from a statistician’s perspective. NY: Springer-Verlag.
Hasan, M.A. (2004). Information criteria for reduced rank canonical correlation analysis. In
Proceedings of the IEEE International Joint Conference on Neural Networks. Vol 3 (pp. 2215-20).
Piscataway, NJ.
International recommendations for tourism statistics (New York/ Madrid, 2008). Series M No 83/ Rev
1. URL:
http://unstats.un.org/unsd/trade/IRTS/IRTS%202008%20unedited.pdf. Retrieved 11.8.2013.
International tourism challenged by deteriorating global economy. UNWTO World Tourism
Barometer (World Tourism Organization). January 2009.
Krzanowski, W.J. (2000). Principles of multivariate analysis: A user’s perspective (2nd ed.). Oxford:
University Press.
Kuhn, H.W. & Tucker, A.W. (1951). Nonlinear programming. In Neyman, J. (Ed.). Proceedings of
the Second Berkeley Symposium on Mathematical Statistics and Probability (pp. 481-92). Berkeley:
University of California Press.
Lee, M.H. (2007). Continuum direction vectors in high dimensional low sample size data. Ph.D.
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http://www.czso.cz/eng/redakce.nsf/i/tsa_main_indicators_of_the_national_economy_and_tourism_in
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the 56th Session of the International Statistical Institute. Lisboa, Portugal.
Regulation (EU) No. 692/2011 of the European Parliament and of the Council of 6 July 2011
concerning European statistics on tourism and repealing Council Directive 95/57/EC. URL:
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:192:0017:0032:EN:PDF.
Retrieved 11.8.2013.
Tourism employment module, Czech Statistical Office. URL:
http://www.czso.cz/eng/redakce.nsf/i/tourism_employment_module. Retrieved 9.8.2013.
Vajčerová, I., Šácha, J. & Ryglová, K. (2012). Using principal component analysis for evaluating the
quality of a tourist destination. Acta Universitatis Agriculturae et Silviculturae Mendelianae
Brunensis. 60(2): 449-58.
Vinod, H.D. (1976). Canonical ridge and econometrics of joint production. Journal of Econometrics.
4(2): 147-66.
Wegelin, J.A. (2000). A survey of partial least squares (PLS) methods, with emphasis on two-block
case. Technical Report. Seattle, US: University of Washington.
Wold, H. (1975). Path models with latent variables: The NIPALS approach. In Blalock, H.M. et al.
(Eds.). Quantitative Sociology: International Perspectives on Mathematical and Statistical Model
Building (pp. 307-57). NY: Academic.
World Tourism Barometer interior update, UNWTO World Tourism Barometer (World Tourism
Organization). August 2010.
Yuksel, F. & Yuksel, A. (2008). Perceived clientelism: Effects on residents’ evaluation of municipal
services and their intentions for participation in tourism development projects. Journal of Hospitality
& Tourism Research. 32(2): 187-208.
models: Application to the post-consumption behavior in tourism. In Vinzi, V.E., Chin, W.W.,
Henseler, J. & Wang, H. (Eds). Handbook of Partial Least Squares: Concepts, Methods, and
Applications (pp. 141-69). Springer, Berlin.
Assaker, G., Hallak, R., Vinzi, V.E. & O'Connor, P (in press). An empirical operationalization of
countries’ destination competitiveness using partial least squares modelling. Journal of Travel
Research.
Bender, O., Schumacher, K.P. & Stein, D. (2005). Measuring seasonality in Central Europe’s tourism
– how and for what?. In Schrenk, M. (Ed.). CORP 2005 & Geomultimedia05, 10th International
Conference on Information & Communication Technologies (ICT) in Urban Planning and Spatial
Development and Impacts of ICT on Physical Space (pp. 303-9). Wien.
Borga, M., Landelius, T. & Knutsson, H. (1997). A unified approach to PCA, PLS, MLR and CCA.
Report LiTH-ISY-R-1992, ISY, SE-581 83. Sweden, Linkoping.
Council Directive 95/57/EC of 23 November 1995 on the collection of statistical information in the
field of tourism. URL:
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:1995L0057:20081211:EN:PDF.
Retrieved 11.8.2013.
CSO database. URL:
http://www.czso.cz/eng/redakce.nsf/i/cru_ts. Retrieved 9.8.2013.
De Bie, T., Cristianini, N. & Rosipal, R. (2005). Eigenproblems in pattern recognition. In Bayro-
Corrochano, E. (Ed.). Handbook of Geometric Computing: Applications in Pattern Recognition,
Computer Vision, Neural Computing, and Robotics (pp. 1-39). Springer-Verlag, Heidelberg.
Elmore, K.L. & Richman, R. (2001). Euclidean distance as a similarity metric for principal
component analysis. Monthly Weather Review, 129(3): 540-9.
Exploring historical towns of Bohemia, Moravia and Silesia. The Association of Historical
Settlements in Bohemia, Moravia and Silesia, EU project. URL:
http://www.shscms.cz/en/eu-project-uexploring-historical-towns-of-bohemia-moravia-and-silesiau-
2232.html. Retrieved 17.8.2013.
Franke, A. (2012). Statistiky cestovního ruchu. Praha: Wolters Kluwer.
Gardiner, S., King, C. & Grace, D. (2013). Travel decision making: An empirical examination of
generational values, attitudes, and intentions. Journal of Travel Research, 52(3): 310-24.
Griffith, D.A. & Amrhein, C.G. (1997). Multivariate statistical analysis for geographers. NJ: Prentice
Hall.
Harville, D.A. (1997). Matrix algebra from a statistician’s perspective. NY: Springer-Verlag.
Hasan, M.A. (2004). Information criteria for reduced rank canonical correlation analysis. In
Proceedings of the IEEE International Joint Conference on Neural Networks. Vol 3 (pp. 2215-20).
Piscataway, NJ.
International recommendations for tourism statistics (New York/ Madrid, 2008). Series M No 83/ Rev
1. URL:
http://unstats.un.org/unsd/trade/IRTS/IRTS%202008%20unedited.pdf. Retrieved 11.8.2013.
International tourism challenged by deteriorating global economy. UNWTO World Tourism
Barometer (World Tourism Organization). January 2009.
Krzanowski, W.J. (2000). Principles of multivariate analysis: A user’s perspective (2nd ed.). Oxford:
University Press.
Kuhn, H.W. & Tucker, A.W. (1951). Nonlinear programming. In Neyman, J. (Ed.). Proceedings of
the Second Berkeley Symposium on Mathematical Statistics and Probability (pp. 481-92). Berkeley:
University of California Press.
Lee, M.H. (2007). Continuum direction vectors in high dimensional low sample size data. Ph.D.
thesis. Chapel Hill, US: University of North Carolina.
Main indicators of the national economy and tourism in the Czech Republic. Czech Statistical Office.
URL:
http://www.czso.cz/eng/redakce.nsf/i/tsa_main_indicators_of_the_national_economy_and_tourism_in
_the_czech_republic. Retrieved 9.8.2013.
Methodological manual for tourism statistics (Version 1.2). EUROSTAT Methodologies and
Working Papers. URL:
http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-11-021/EN/KS-RA-11-021-EN.PDF.
Retrieved 17.8.2013.
Methodology of Czech Statistical Office. URL:
http://www.czso.cz/eng/redakce.nsf/i/methodology_time_series_tourism. Retrieved 9.8.2013.
Pinto da Costa, J., Silva, I. & Silva, M.E. (2007). Time dependent clustering of time series. Bulletin of
the 56th Session of the International Statistical Institute. Lisboa, Portugal.
Regulation (EU) No. 692/2011 of the European Parliament and of the Council of 6 July 2011
concerning European statistics on tourism and repealing Council Directive 95/57/EC. URL:
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:192:0017:0032:EN:PDF.
Retrieved 11.8.2013.
Tourism employment module, Czech Statistical Office. URL:
http://www.czso.cz/eng/redakce.nsf/i/tourism_employment_module. Retrieved 9.8.2013.
Vajčerová, I., Šácha, J. & Ryglová, K. (2012). Using principal component analysis for evaluating the
quality of a tourist destination. Acta Universitatis Agriculturae et Silviculturae Mendelianae
Brunensis. 60(2): 449-58.
Vinod, H.D. (1976). Canonical ridge and econometrics of joint production. Journal of Econometrics.
4(2): 147-66.
Wegelin, J.A. (2000). A survey of partial least squares (PLS) methods, with emphasis on two-block
case. Technical Report. Seattle, US: University of Washington.
Wold, H. (1975). Path models with latent variables: The NIPALS approach. In Blalock, H.M. et al.
(Eds.). Quantitative Sociology: International Perspectives on Mathematical and Statistical Model
Building (pp. 307-57). NY: Academic.
World Tourism Barometer interior update, UNWTO World Tourism Barometer (World Tourism
Organization). August 2010.
Yuksel, F. & Yuksel, A. (2008). Perceived clientelism: Effects on residents’ evaluation of municipal
services and their intentions for participation in tourism development projects. Journal of Hospitality
& Tourism Research. 32(2): 187-208.
Published
2021-05-27
How to Cite
Collective Authors. (2021). Economic Development, Technological Change and Growth: Array. Acta Universitatis Danubius. Œconomica, 10(2). Retrieved from https://dj.univ-danubius.ro/index.php/AUDOE/article/view/1082
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