ECONOMETRIC STUDY OF THE EVOLUTION OF BRASOV LODGING INDUSTRY AND TOURISM MARKET. Gabriel-Iustin FLORESCU

Transcription

1 ECONOMETRIC STUDY OF THE EVOLUTION OF BRASOV LODGING INDUSTRY AND TOURISM MARKET Gabriel-Iustin FLORESCU Abstract: Given the contribution of tourism industry in the Brasov County economy, local authorities, hoteliers and all other stakeholders have to have a vast view to increase Brasov destination market share of the tourist arrivals. Therefore, this study attempts to investigate the short run demand from domestic tourists by using an econometric model. Empirical studies on tourism field for Brasov County have illustrated little attention in modelling properly the demand function for tourism and identifying the main basis for tourism flows, including the supply factors, as accommodation capacity, which might influence substantially the tourism performance, and this is the objective of this study. Keywords: tourism demand, accommodation capacity in operation, forecast, regression, econometric model. 1. Introduction Tourism is an important economic sector of Brasov County, generating a considerable amount of exports, income from fees and taxes, under the ownership of a significant proportion of the employed population. In 2013, Brasov County was visited by 835,044 tourists, of which 708,775 Romanian and 126,269 foreign. However, it should be noted that the number of visitors has dropped steeply in 2009, as direct consequence of the economic crisis. Tourist arrivals represent the starting mechanism of the Brasov hotel industry. The higher the number of tourists in Brasov County, the greater the benefits generated by the tourism activity. The objective of this study is the analysis of Brasov Tourist market after the year 2000, in order to assess its evolution and trends and to identify solutions for the sustainable development of the hotel industry in the area of Brasov. The operators of hotels need to observe the increase of the inter-regional competition and the demands of the current generations of tourists regarding the new meanings of the hotel comfort and quality services in the Internet era. 2. Working method An econometric model is proposed in the content of the article to determine the number of tourist arrivals in Brasov County according to the simultaneous influence of two main factors, acting as explanatory variables. Furthermore, the multiple regression model allows the analysis of correlations between variables, the explanatory variables significance testing, determining the validity of the multiple regression model and its use for forecasting. 3. Results and discussions Accommodation capacity has grown very rapidly in the period after 2001, even during the crisis. The tourist offer, i.e. the number of bed nights available in accommodation structures has been much higher than the tourism demand throughout the whole period analysed, and the economic crisis has boosted the excess capacity. The evolution of accommodation capacity in operation in Brasov County, compared to tourist arrivals and the number of overnight stays in , shown in Figure 1 as a chart, highlights the imbalance between the supply of rooms for accommodation and the tourism demand, as well as the intensification of this imbalance in recent years. Accordingly, the average occupancy level dropped dramatically after 2008, reaching under 19.67% in This occupancy percentage demonstrates a moment of unsustainable development of tourism in Brasov.

2 Figure 1. Market developments in Brasov County between 2001 and 2013 The operators of hotels in Brasov County responded to the crisis by reducing the rates for accommodation, in hopes of maintaining the interest of potential tourists, even if their discretionary income was reduced. However, the inelastic demand in the sector as a whole led to lower revenue of operators of tourism establishments and to substantially reduced profits or even to registering losses. This process was emphasized by the actions of nonviable long-term hotels, which have reduced rates for accommodation down to unsustainable levels, because of the overriding need to free up cash flow under any conditions. Investments in recent years were due to some passionate decisions on behalf of the investors, and not to professional analyses regarding the sector's perspective. Grants funding has supported investments in tourist accommodation capacities, but nobody pulled a wake-up call about the potential impact of the rapid increase of the accommodation capacity, of the excess offer of rooms for accommodation on the viability of recently opened or older hotel businesses and the local tourism sector in general. The situation was aggravated by the high prices of resources from the Romanian economy: energy prices 50% higher than in Bulgaria for instance, high costs of the staff because of the high level of labour taxation, loan interest rates substantially higher than in other European countries. Hotel operators have been caught in the trap of low tariffs for the services rendered, seconded by high costs. Not to forget the action of political actors interested solely in the short-term effect of the decisions made. All of these are detrimental to the general evolution of the tourism sector of Brasov. The evolution of tourist arrivals and overnight stays looks sinusoidal, with successive increases and decreases. The minimum value of arrivals is recorded in 2002, when Brasov County received thousand tourists, and the maximum level of thousand arrivals was reached in The general trend is ascending over the analysed period. The delay of almost a year of the manifested effects of the economic crisis in Romania in relation to Western States decisively influenced the evolution of demand for tourist accommodation capacity in Brasov County too, the steepest decline taking place in 2009, when the number of tourist arrivals was thousand, 22% lower than in the previous year. The dynamics of the number of overnight stays was similar, as one may see in the chart shown in Fig. 1. Unlike the tourist demand indicators taken into consideration, the accommodation capacity in operation the indicator selected to emphasize the dynamics of the tourist offer -

3 has increased continuously and quickly during the years of economic crisis too. The number of bed nights available was 82% higher in 2013, compared to the situation in 2008, as shown by the data presented in Table 1. In consequence, the indicator which characterizes the relationship between tourist demand and supply-average degree of accommodation capacity in function - was also a sine wave, but at a very low level, oscillating between 19.56% and 26.07% over the analysed period. Tabel 1. Market developments in Braşov County between 2001 and 2013 Tourism supply Tourism demand Year Number of accommodation capacities Accommodation capacity (beds) accommodation capacity in operation (thousands bednights) Tourist arrivals (thousands) Overnights (thousands) Average occupancy rate (%) ,276 3, ,528 3, ,611 3, ,380 3, ,037 4, , ,883 4, , ,634 4, , ,729 4, , ,728 5, ,742 5, , ,795 5, , ,699 7, , ,524 8, , The evolution of tourism flow is influenced by a complex of factors, some essential, others with less significant influence, many of them being unpredictable. The tourism demand forecast raises some specific problems: The emergence of the new hospitality capacities, of new forms of sales and marketing, can influence current trends; Tourism has the handicap of a lack of historical compatible data; There is a large number of social, political, economic variables, majorly affecting tourist flows; Tourism is highly vulnerable to terrorism, epidemic diseases, natural disasters and political changes. Knowing the range of future development of the tourism demand should provide sufficient information for the policy management of the Brasov County, as a tourist destination, limiting the uncertainty and limiting the risk of investments. According to Archer (quoted by Norbert Vanhove in The Economics of Tourism Destinations, 2011), the estimation of tourism demand requires both rigorous scientific analysis, and practical experience, and the accuracy of the information relating to the history of the tourist phenomenon is the starting point. Causal analysis methods of the tourism phenomenon, such as the regression analysis, seek to explain why the dependent variable changes over time, starting from the assumption that the changes involved are the effect of the influence of one or more independent variables. Tourism demand is such a complex phenomenon that, in most cases, several factors have impact simultaneously on the dependent variable. In most cases, dependent variables in regression models in tourism are: tourist arrivals, overnight stays or expenses of tourists in a certain destination. Regarding independent variables, Frechtling (quoted by N. Vanhove in The Economics of Tourism Destinations, 2011)

4 distinguishes between: (a) momentum factors, also named push factors: those home market characteristics which encourage people to go on trips, such as family income; (b) factors of attraction, the pull factors: those attracting tourists to a specific destination, such as the existence of accommodation facilities at destination and the comfort level; (c) resistance factors, such as terrorism or prices. Taking into account the particularities of the tourism demand according to the basin of 4. Forecasting the number of tourist arrivals using the multiple regression model The multiple regression analysis allows the estimation of the parameters of the econometric model to determine the number of tourist arrivals in Brasov County according to the simultaneous influence of several factors, acting as explanatory variables. Furthermore, the multiple regression model allows the analysis of correlations between variables, the explanatory variables significance testing, determining the origin of tourists (Romanians or foreigners), this work analyses the Romanian tourist flows in Brasov County, considering the following variables: Dependent variable: number of tourist arrivals; Explanatory variables: (1) number of accommodation establishments in Brasov County - attraction factor; (2) GDP volume of the national economy - push factor. validity of the multiple regression model and its use for forecasting. The data regarding the evolution of the explanatory variables and the explained variable is shown in Tabel 2. Data on the number of tourist arrivals and the number of accommodation establishments in Brasov County between 2001 and 2013 was obtained by consulting the website of the National Institute of Statistics the data on the volume of GDP was obtained by consulting the website of the World Bank Tabel 2. Multiple regression indicators dynamics Year Number of accommodation establishments GDP (Millions $) Observed number of arrivals (Thousands) , , , , , , , , , , , , , The features of the econometric model associated with the relationship between the dependent variable selected and the two independent variables are presented in Table 3:

5 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 13 Table 3. Table of regression model with two explanatory variables ANOVA df SS MS F Significance F Regression E-07 Residual Total Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept X Variable E X Variable E Quality adjustment was calculated as the ratio between the variance explained by the model and the total variance of the dependent variable. The value of the quality adjustment is R 2 = , which means that the total variance is almost entirely explained by the model; the model is well chosen. The multiple correlation ratio R = shows a very strong intensity of the simultaneous correlation between the endogenous variable "number of tourist arrivals in Brasov County" and the exogenous variables number of accommodation establishments in Brasov County" x 1, "volume of GDP in Romania" x 2. The expectations regarding positive coefficients for the explanatory variables, were confirmed: the purchase desire of the Romanians for tourist consumption in destinations in Brasov County increases in direct proportion to the number of accommodation establishments in operation (which implies comfort diversity and high competition between hoteliers to attract tourists, thus a favourable quality/price ratio), as well as to the evolution of the GDP volume (indicator giving a real picture of the performance of the Romanian economy and, finally, of the people s welfare). The regression shown in Table 3 is globally significant because the theoretical value = 4.10 is lower than the calculated value F * = , for a significance threshold of %. The analysis of the individual tests of significance of the coefficients for each explanatory variable in the model, based on Student ratios, compared to the theoretical value Student for α = 5% and 10 degrees of freedom = 2.23 leads to the following conclusions: = 7.48 > 2.23, hence 0, so variable x 1 contributes to the expanation of the variance of variable y; = 2.25 > 2.23, hence 0, so variable x 2 contributes to the explanation of the variance of variable y. The P-value, the lowest value from which the estimator coefficients are significantly different from zero, is less than 5% in the case of each explanatory variable of the selected model, with a probability of at least 95%. Also, the claim is valid for the coefficient, for which the calculated Student ratio = 2.75 is bigger than the theoretical one, and the P-value shows that the estimator

6 becomes significantly different from zero starting with a significance threshold of 2%, compared to the acceptable level of 5%. Confidence intervals for the constant estimator and for the two estimators of the explanatory variables coefficients are: IC : [ ; ] does not contain the zero value; IC : [ ; ] does not contain the zero value and has the sign + of the direct connection between the explained variable and the explanatory variable number of accommodation establishments in Brasov County ; IC : [ ; ] does not contain the zero value and has the sign + of the direct connection between the explained variable and the explanatory variable volume of GDP in Romania. The model identified is: ŷ t = * x * x 2. The theoretical values ŷ t obtained by applying the model are presented in Table 4: Table 4. The observed values of the variables, and the theoretical amount of tourist arrivals determined by the regression model Year Number of accommodation establishments GDP (Millions $) Observed number of arrivals (Thousands) Theoretical number of arrivals ŷ t (Thousands) , , , , , , , , , , , , , The evolution of the theoretical values ŷ t is presented in Figure 2, on the same chart with the values observed. One may notice that the two curves have the same shape. The distances show there are other possible explanatory variables:

7 Fig. 2. Evolution of tourist arrivals in Brasov County from 2001 to 2013 and their adjustment This statistical analysis shows that the model closely approximates the variance of the endogenous variable and, therefore, is used for the development of forecasts for 2014 and In order to forecast the number of tourist arrivals in 2014 and 2015 we need to know the prognosis of the evolution of the two explanatory variables next couple of years: the number of accommodation establishments will increase to 786 in 2014 and 821 in 2015 respectively, according to the author's estimates, based on the absolute average modification method applied to the data published by the National Institute of Statistics; gross domestic product will grow with 2.2% in 2014 and with 2.5% in 2015, according to the forecasts of the Romanian government. By substituting the explanatory variables with the estimated values for the years 2014 and 2015, we obtain the following values of the explained variable: Ŷ 2014 = thousands of Romanian tourists; Ŷ 2015 = thousands of Romanian tourists. Therefore, the forecast of the number of tourist arrivals in Brasov County seeks further growth trend, as to approach the threshold of 800 thousand arrivals of Romanian tourists by the end of 2015, which is plotted in Figure 3. The econometric model could be improved by refining the explanatory variables and by introducing dummy variables to take into account the influence of economic and political events such as the conflict of Ukraine and the running of Brasov international airport.

8 Fig. 3. Evolution of the number of tourist arrivals in Brasov County in the period , adjustment and their forecast in Conclusions The econometric model used highlights that between the number of Romanian tourist arrivals in the County of Brasov and the accommodation capacity there is a very strong relationship, in both directions. The statistical analysis proves that the tourist offer in Brasov County grew strongly in the period , while tourism demand has not kept pace despite the strategy adopted by tourism operators to diminish tariffs aggressively. At the same time, the increased dependency of the tourist activity on domestic tourism is obvious. Research shows the inelastic demand to price reductions, the hotel revenue decreasing even if the number of overnight stays increased over the period. This approach of the hoteliers has clear adverse implications on profit rates and on the viability of the local tourism business. Accordingly, the majority of accommodation establishments in Brasov County are going through serious financial difficulties. Resolving the situation by sharply increasing tourist demand, so that the current excess capacity is covered, is improbable, as shown by the above analysis. Figure 4 shows the evolution of the main indicators of tourism demand and supply, as well as the average level of occupancy in the period and the estimation for , taking into account the conclusions of this review and the following assumptions: Average length of stay will be maintained to 2.1 days; The number of arrivals of foreign tourists will increase by 2% in each of the coming years, according to the average rate of growth of the past decade.

9 Fig. 4. Evolution of the main indicators of tourism activity in Brasov County between 2001 and 2013 and their estimation in the period Whereas, it is impossible that this level of occupancy enables the support of the activity for all structures existing at this time on the Brasov market, it is expected that the phenomenon of insolvency and bankruptcy will manifest worse in the coming years in the tourism sector. The question is to what extent the local tourist offer will be affected by this phenomenon? If we start from the premise that an occupancy rate of around 40% ensures sustainability of a business in the hotel industry, it would result that in the next two years approximately 42% of the current accommodation capacity in Brasov County will become inactive, in various forms: bankruptcy, voluntary reduction in accommodation capacity, the change of the profile activity etc. The graph in Figure 5 highlights the fact that such an assumption would lead to a tourist offer similar to the one of the year 2008, the first year of the economic crisis. Fig. 5. Evolution of the average occupancy rate in Brasov County in the period , under the scenario of an accommodation capacity similar to 2008

10 On the one hand, we can estimate that the existence of the black or grey economy will make this process of adjustment of the tourist offer to the manifested demand less dramatic, and on the other hand it is necessary for the process to be followed by a forum of rationality, that could be a local Association of operators of accommodation establishments. The conclusion therefore is that the unsustainable development of Brasov tourism will continue in the following period, in the absence of active policies aimed at rebalancing the relationship between tourist demand and supply in the market, including the controlled reduction of the rate of growth of the accommodation capacity. Bibliografie selectivă Anghelache C., Anghelache G. V., Modele macroeconomice utilizate în analiza structurală a Produsului Intern Brut, Revista Română de Statistică, Nr. 6/2013, pag. 8-14; Bălăcescu A., Zaharia M., Analiza statistică a circulaţiei turistice şi a capacităţii de cazare în funcţiune în perioada în judeţul Braşov, Analele Universităţii Constantin Brâncuşi din Târgu Jiu, Seria Litere şi Ştiinţe Sociale, Nr. 3/2012, pag. 1-9; Cristureanu C., Strategii şi Tranzacţii în Turismul Internaţional, Editura C. H. Beck, Bucureşti, 2006, pag ; Duguleană L., Metode de previziune economică, Editura Universităţii Transilvania Braşov, 2011, pag ; Gruia R., (2013): Managementul activității hoteliere, note de curs, Universitatea Transilvania Braşov, Facultatea de Alimentaţie şi Turism. Vanhove N., The Economics of Tourism Destinations, Elsevier Ltd., Second edition, 2011, pag ; *** *** ***