A Proposed Model for Consumer-Based Brand Equity Analysis on Social Media Using Data Mining and Social Network Analysis

Online social networks have expanded their “virtual borders,” making the Internet more like an environment of social interaction than a business tool. However, even before the emergence and expansion of social media, marketing professionals were interested in identifying consumers' perceptions about brands. Thus, operational models have been proposed to facilitate such a task. Those models, however, can be expensive and inconvenient, since the models use questionnaires for data collection. To help overcome this problem, this article proposes a model for brand equity analysis from the consumer perspective expressed in social networks using opinion mining techniques and social network analysis. The application of the proposed model on data collected from Twitter made it possible to analyze five brand equity dimensions: brand awareness, brand loyalty, perceived sentiment, perceived quality, and brand associations. The results reached by the application of the model show that brand equity can be analyzed from data retrieved from virtual social networks, disclosing how consumers perceive brands in such an environment, without using questionnaires, enabling different brands in different contexts. Those data can be analyzed under both objective and replicable criteria for each of the brand equity elements that make up the model.     

Measuring customer experience in service: A systematic review

The aim of this systematic review is to identify how customer experience in the service sector has been measured in relevant publications in the marketing field. A sample of 33 papers was collected from two electronic databases—the Web of Science (Thomson Reuters) and Scopus (Elsevier)—covering a large number of publications. After analyzing the articles and reviewing the customer experience literature, the following are our main contributions: (i) clarification of the concepts that appear in the literature review of customer experience in the service sector; (ii) classification of the variables, scales, and constructs related to customer experience in service; (iii) demonstration of the service experience as the preponderant construct that is used to measure customer experience in service; and (iv) proposal of a new dimension—the concept of ‘pre-experience’—to measure customer experience in service. These contributions can provide a more solid basis for measuring customer experience in service.     

Strategic currency hedging and global portfolio investments upside down

The literature on the convenience of currency hedging of international portfolio investments has not reached a final verdict. There are arguments for (Perold and Schulman [Perold, A.F. and Schulman, E.C. (1988). The free lunch in currency hedging: implications for investment policy and performance standards, Financial Analysts Journal, May/June Vol. 44, No. 3: 45-52]) and against (Froot [Froot, K. (1993). Currency hedging over long horizons. NBER Working Paper 4355.] and Campbell et al. [Campbell, J.Y., Viceira, L.M. and White, J.S. (2003). Foreign currency for long-term investors. The Economic Journal, Volume 113, Number 486, (March), pp. C1-C25(1)]). This paper analyzes the perspective of global investors based in emerging markets, for which hedging should imply increasing expected returns. The question thus is whether currency hedging is a “free lunch” in this case. No free lunch exists, as it turns out. Hard currencies act as natural hedges against global (and local) portfolio losses, since they tend to appreciate with respect to emerging market currencies when the world portfolio return is negative. Therefore, in this case currency hedging increases volatility—although also increasing expected returns. This result is likely to hold generally for relatively open economies with flexible exchange rate regimes.     

A continuous time approach to the pricing of bonds

This paper develops an arbitrage model of the term structure of interest rates based on the assumptions that the whole term structure at any point in time may be expressed as a function of the yields on the longest and shortest maturity default free instruments and that these two yields follow a Gauss-Wiener process. Arbitrage arguments are used to derive a partial differential equation which must be satisfied by the values of all default free bonds. The joint stochastic process for the two yields is estimated using Canadian data and the model is used to price a sample of Government of Canada bonds.     

Joint estimation using revealed and stated preference data: An application using a national forest

We combine contingent behaviour with travel cost data to estimate the change in the recreational use value of a National Forest due to quality and price changes. Instead of the usual improvement scenario, a hypothetical deterioration in the conditions of the forest due to a fire is considered. A dataset containing five observations for each respondent enabled the estimation of three models for which the number of scenarios differed. The results show that visitors are sensitive to price and quality changes and that in the forest fire scenario the intended number of trips would be reduced and that respondents would experience a welfare loss. Signs of inconsistency between preferences expressed by revealed and intended behaviour were found. This research also provides some indications that strategic bias affects answers to price changes.     

Growth machines and social movements in mature tourist destinations Costa del Sol-Málaga

Abstract

The purpose of this study is to analyse the new processes of tourism growth and its conflicts from the perspective of social movements. First, the urban growth machine analysis model is applied by the systematisation of six projects. Second, the resistance movements against those projects and whether this resistance could be the start of local tourism degrowth policies are examined. The methodology is qualitative, based on documentary analysis, participatory observation, discussion groups and interviews. The case study is the destination of Costa del Sol-Málaga. The results enable the development of the urban growth machine model in tourist destinations. Meanwhile, social movements demystify the argument based on neoclassical economic progress. The social movements condemn the effects of large-scale top-down projects, and implement alternative bottom-up proposals. Although the social movements do not reject tourism, they call for greater control over its impact, denounce unlimited growth, overtourism and the loss of urban quality of life. These movements advocate a lifestyle linked to the everyday space, which they believe is threatened by excessive urban-tourism growth. They are a symptom of the need to devise a proposal using the principles of degrowth.     

Benchmark priors for Bayesian model averaging

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, ‘diffuse’ priors on model-specific parameters can lead to quite unexpected consequences. Here we focus on the practically relevant situation where we need to entertain a (large) number of sampling models and we have (or wish to use) little or no subjective prior information. We aim at providing an ‘automatic’ or ‘benchmark’ prior structure that can be used in such cases. We focus on the normal linear regression model with uncertainty in the choice of regressors. We propose a partly non-informative prior structure related to a natural conjugate g-prior specification, where the amount of subjective information requested from the user is limited to the choice of a single scalar hyperparameter g_0j. The consequences of different choices for g_0j are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with classical information criteria are provided. More importantly, we examine the finite sample implications of several choices of g_0j in a simulation study. The use of the MC³ algorithm of Madigan and York (Int. Stat. Rev. 63 (1995) 215), combined with efficient coding in Fortran, makes it feasible to conduct large simulations. In addition to posterior criteria, we shall also compare the predictive performance of different priors. A classic example concerning the economics of crime will also be provided and contrasted with results in the literature. The main findings of the paper will lead us to propose a ‘benchmark’ prior specification in a linear regression context with model uncertainty.