Cira Mendoza

Bio: Cira Mendoza is an academic researcher from University of Las Palmas de Gran Canaria. The author has contributed to research in topics: Tourism & Data envelopment analysis. The author has an hindex of 4, co-authored 5 publications receiving 79 citations.

A DEA Travel–Tourism Competitiveness Index

Abstract: Travel and tourism competitiveness has been paramount in the research agenda for transport, tourism and economics over the last decades because a larger number of destinations and businesses have entered into the international tourism market. Different approaches have been postulated to measuring, modeling and managing competitiveness in tourism. The present study aims to create a composite index of the travel and tourism competitiveness to rank 139 countries worldwide. Our sample is based on some of the data collected in “The Travel & Tourism Competitiveness Report 2011”, and the method is based on the virtual efficiency DEA model. An analysis of the competitiveness by geographical area and income is also analyzed. Finally some policy implications are discussed.

A DEA Approach to Measure the Quality-of-Life in the Municipalities of the Canary Islands

Abstract: The notion of the quality of life has always intrigued economists, sociologists and other researchers in the area of social science. Since the genesis of the definition of Gross Domestic Product (GDP) as a truthful measure of well-being and economic development, other sophisticated methodologies have been proposed in the literature to measure the quality-of-life (QOL) that extend in a multidimensional way this complex concept. Measuring QOL in municipalities consists in finding a set of comparable attributes that can be weighted by some metric in order to construct a synthetic index. Thus, the narrow vision obtained by a single measure as the GDP, in which differences in the QOL cannot be fully analyzed, is overcome. Based upon a refinement of data envelopment analysis (DEA)—the cross-efficiency method, the current paper develops a synthetic QOL index that is based in 19 partial indicators which present the tradeoffs of different dimension for the 87 municipalities of the Canary Islands in Spain. Marginal rates of substitution are calculated to evaluate the tradeoffs on QOL dimensions. A method is also proposed to determine the scores chart of each municipality which can be used as a tool to policy makers in order to establish a program of improving the ranking position of the municipality identifying the critical QOL factors.

Determinants for sun-and-beach self-catering accommodation selection: A stated preference approach

Abstract: Self-catering accommodation is an important lodging alternative in some tourist destinations. Attributes such as the size, furniture and equipment; pool area; quietness; accessibility to beach; or Wi-Fi play an important role in the selection of this type of accommodation. Understanding tourists’ preferences is essential to improve services and gain competitiveness. In this article, a stated choice experiment between two hypothetical self-catering apartments is carried out in Maspalomas, a world renowned destination in the south of Gran Canaria, Spain. Consistent multinomial and mixed logit model specifications that incorporate systematic and random taste variation within tourists’ preferences are estimated. Willingness to pay for improving different service quality attributes is obtained. The findings are crucial and provide important insights to managers and policymakers in order to streamline the marketing and promotional strategies, as well as to make optimal investment decisions.

Regional Spanish Tourism Competitiveness. A DEA-MONITUR approach

Abstract: The aim of this paper is to analyse the regional tourist competitiveness performance in Spain. We use the seven pillars of tourism from a very detailed and complete database compiled by the Spanish Government –MoniTUR 2010 as primary data. Thus, we calculate a DEA-MONITUR regional tourist competitiveness index in order to compare and rank the total 17 Spanish Autonomous Communities using data envelopment analysis (DEA). Our results show how this performance is very different among regions, and the position of each of the laggard Autonomous Communities should be analysed by their respective destination management organizations (DMOs) in order to envisage adequate corrective measures.

Assessing service quality using fuzzy numbers and TOPSIS: an application to self-contained and serviced apartments

Abstract: This research paper proposes a methodological framework to assess the service quality (SQ) of self-contained and serviced apartments (SCSAs). The study is based on 2,753 surveys administered in a SCSA resort located in the south of Gran Canaria Island. SQ is based on a questionnaire that contains a list of 48 attributes. The answers' format is based on a four-facial expressions scale that cannot be easily transformed in a numeric scale. Thus, the ambiguity and possible biased analysis has partly overcome applying the fundaments of the fuzzy set theory. TOPSIS approach is then employed to obtain a synthetic SQ indicator. Finally, an observation-attribute relative performance analysis is developed to identify the operational areas that need improvement or can keep up the good work. The findings of this study may assist managers and policy planners with important insights about the attributes that tourists value more.

On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness

Abstract: In recent times, composite indicators have gained astounding popularity in a wide variety of research areas. Their adoption by global institutions has further captured the attention of the media and policymakers around the globe, and their number of applications has surged ever since. This increase in their popularity has solicited a plethora of methodological contributions in response to the substantial criticism surrounding their underlying framework. In this paper, we put composite indicators under the spotlight, examining the wide variety of methodological approaches in existence. In this way, we offer a more recent outlook on the advances made in this field over the past years. Despite the large sequence of steps required in the construction of composite indicators, we focus particularly on two of them, namely weighting and aggregation. We find that these are where the paramount criticism appears and where a promising future lies. Finally, we review the last step of the robustness analysis that follows their construction, to which less attention has been paid despite its importance. Overall, this study aims to provide both academics and practitioners in the field of composite indices with a synopsis of the choices available alongside their recent advances.

Performance of French destinations: Tourism attraction perspectives

Abstract: In this paper, we assess and compare the performance of French tourism destinations, using the Data Envelopment Analysis (DEA) two-stage procedure, where in the first stage the efficiency score are calculated, and then followed in the second stage by a bootstrapped truncated regression model. In the context of France such analysis takes an additional importance, especially as the country is expected to face a decrease in its tourism competitiveness. A discussion in terms of D-attraction and E-attraction is also proposed and policy recommendations are derived.

Human development and data envelopment analysis: A structured literature review ☆ ☆☆

Abstract: Given the importance the concept of productive efficiency has on analyzing the human development process, which is complex and multidimensional, this study conducts a literature review on the research works that have used the data envelopment analysis (DEA) to measure and analyze the development process. Therefore, we researched the databases of Scopus and Web of Science, and considered the following analysis dimensions: bibliometrics, scope, DEA models and extensions used, interfaces with other techniques, units analyzed and depth of analysis. In addition to a brief summary, the main gaps in each analysis dimension were assessed, which may serve to guide future researches.

A PCA–DEA approach to measure the quality of life in Estonian counties

Abstract: This paper investigates the application of a PCA–DEA model to assess the quality of life (QOL) scores in Estonian counties and analyses the model's results. The dataset is a balanced panel of 15 Estonian counties covering the period from 2000 to 2011. We consider a PCA–DEA model as an alternative method to estimate and predict QOL scores and rankings of Estonian counties. The method consists of a two-stage analysis that begins with a principal component analysis. In the second stage, the standard DEA is used. The results from the conventional DEA model and the PCA–DEA model are compared and discussed. A comparison of the methodologies demonstrates that a PCA–DEA model provides a powerful tool for performance ranking. The rankings of Estonian counties using QOL scores for different model specifications are presented. Finally, the QOL ranking of Estonian counties is revised using PCA–DEA.