Managing induced tourism image : relational patterns and the life cycle

The tourism image is an element that conditions the competitiveness of tourism destinations by making them stand out in the minds of tourists. In this context, marketers of tourism destinations endeavour to create an induced image based on their identity and distinctive characteristics.A number of authors have also recognized the complexity of tourism destinations and the need for coordination and cooperation among all tourism agents, in order to supply a satisfactory tourist product and be competitive in the tourism market. Therefore, tourism agents at the destination need to develop and integrate strategic marketing plans.The aim of this paper is to determine how cities of similar cultures use their resources with the purpose of developing a distinctive induced tourism image to attract tourists and the extent of coordination and cooperation among the various tourism agents of a destination in the process of induced image creation.In order to accomplish these aims, a comparative analysis of the induced image of two cultural cities is presented, Girona (Spain) and Perpignan (France). The induced image is assessed through the content analysis of promotional brochures and the extent of cooperation with in-depth interviews of the main tourism agents of these destinations.Despite the similarities of both cities in terms of tourism resources, results show the use of different attributes to configure the induced image of each destination, as well as a different configuration of the network of tourism agents that participate in the process of induced image creation

The role of the tourism sector in economic development. Lessons from the Spanish experience

Tourism is one of the most important sectors in the global economy and is considered an efficient tool with which to promote economic growth. The case of Spain¿s economy is well known in this respect; in fact, widespread consensus exists on the part played by tourism in enhancing the industrialisation process in Spain and the part played by foreign currency receipts from tourism in financing the imports of capital goods, which made the expansion of manufacturing possible. This paper aims to assess the real role of foreign currency receipts from tourism in Spain¿s economy from 1960 to the present. The results of Spain¿s experience may well help to guide policy decisions in developing countries in similar circumstances.

The role of the tourism sector in economic development. Lessons from the Spanish experience

Tourism is one of the most important sectors in the global economy and is considered an efficient tool with which to promote economic growth. The case of Spain¿s economy is well known in this respect; in fact, widespread consensus exists on the part played by tourism in enhancing the industrialisation process in Spain and the part played by foreign currency receipts from tourism in financing the imports of capital goods, which made the expansion of manufacturing possible. This paper aims to assess the real role of foreign currency receipts from tourism in Spain¿s economy from 1960 to the present. The results of Spain¿s experience may well help to guide policy decisions in developing countries in similar circumstances.

Tourism and Exports as a means of Growth

This study expands existing research by considering both exports and tourism as potential influencing factors for economic growth. While trade of goods has been proven as a means of growth for countries, inbound tourism as non-traditional exports, has been scarcely examined in the literature. Using data for Italy and Spain over the period 1954-2000 and 1964-2000 respectively, both exports of goods and tourism exports are included in the same model. Standard cointegration and Granger causality techniques are applied. The main results reveal the significance of both exports and tourism towards longterm growth with some peculiarities for each country.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Structuration and branding of a religious tourism product: Catalonia sacra

This article aims to provide an overview of the products Catalonia has to offer in terms of religious tourism. The growing interest in this kind of tourism worldwide, and in Catalonia itself, along with the region's wealth of religious heritage (particularly connected to the Christian Church) contrast with the lack of religion-based tourism products available, which results in its absence from the region's image as a tourism destination. In view of this, the Faculty of Tourism (University of Girona), the Vic Bishopric's Albergueria-Centre for Cultural Dissemination and the Tarraconense Episcopal Conference's Interdiocese Secretariat for the Custody and Promotion of Holy Art (SICPAS) decided to address the situation with the help of funding from the Autonomous Government of Catalonia. In order to re-position Christian religious heritage in the image of Catalonia as a tourist destination, the aforementioned parties embarked upon a project to set up a series of routes throughout the region, branded under the name Catalonia Sacra

Forecasting the maximum compensation offer in the automobile BI claims negotiation process

Most motor bodily injury (BI) claims are settled by negotiation, with fewer than 5% of cases going to court. A well-defined negotiation strategy is thus very useful for insurance companies. In this paper we assume that the monetary compensation awarded in court is the upper amount to be offered by the insurer in the negotiation process. Using a real database, a log-linear model is implemented to estimate the maximal offer. Non-spherical disturbances are detected. Correlation occurs when various claims are settled in the same judicial verdict. Group wise heteroscedasticity is due to the influence of the forensic valuation on the final compensation amount. An alternative approximation based on generalized inference theory is applied to estimate confidence intervals on variance components, since classical interval estimates may be unreliable for datasets with unbalanced structures.

Otra mirada al tema del cambio de escala: los nuevos espacios de comercio, ocio y turismo = Another look at the theme of the change of scale: new spaces in commerce, leisure and tourism

The technological advances and new organisation of the economy together with a change in ideas in consumer habits andlifestyle that have happened in the last 25 years have placed us in a new state of capitalism. The spatial translation of thisnew state has been immediate and implies among other changes the overcoming of the concept of scale. Commercialspaces and those of leisure and tourism offer us an unbeatable opportunity of exemplifying these changes because they arethe most effected by the new postmodern tendencies

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Tourism, poverty alleviation and nature conservation : the state of contemporary research

Artikkeli perustuu kirjallisuuskatsaukseen, joka on tehty 17 lehden 112 vertaisarvioidusta artikkelista vuosilta 2003-2007.