Evolution of indigenous tourism among the Lacandon of Chiapas: an application of Weaver’s model

ABSTRACT

In this paper, Weaver’s six-stage indigenous tourism model is applied to the Lacandon Maya (Hach Winik) of Chiapas, Mexico. Based on a comprehensive review of the anthropological and historical literature on this indigenous group, combined with longitudinal ethnographic and collaborative research performed with tourism entrepreneurs, the Lacandon tourism experience is assessed from the pre-European period until present. By analysing a case study of indigenous tourism in Mexico, a developing country in another geographical region and with a different colonial past, this work supplements Weavers’ perspective. The results show that the fourth and fifth stages of Weaver’s model coincide in this case study, while the sixth stage is still incomplete. Although the Lacandon case has its peculiarities and bearing in mind that several different factors should be considered in the Latin American context, the model proves to be an interesting tool for indigenous tourism analysis in developing countries.     

Geometrical Interpretation of the Mean and the Constant in a Box-Jenkins Time Series Model

Certain manuals and computer programs mistakenly identify the mean with the constant in Box-Jenkins time series models. In this paper, it will be shown that (a) the mean and the constant have different values in autoregressive models, and (b) they have an algebraic and graphical relationship.     

Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting

Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.     

Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

Extracting Nonlinear Signals from Several Economic Indicators

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one‐step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two‐step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, especially in the vicinity of turning points, although its gains diminish as the quality of the indicators increases. Additionally, we also obtain decreasing returns of adding more indicators with similar signal‐to‐noise ratios. Using the four constituent series of the Stock–Watson coincident index, we illustrate these results for US data. Copyright © 2014 John Wiley & Sons, Ltd.     

Automatically extracting tourism-related opinion from Chinese social media

Existing tourism-destination investigations of Chinese texts remain weak, and no approach is available to realize Chinese context semantically and automatically. To resolve this, we provide a novel method based on qualitative analysis for studying the online opinions of Chinese tourists regarding the destinations to which they travel. Both traditional and simplified Chinese forums were chosen as the object of study. Spain was selected as a travel destination to evaluate the proposed method. After processing the natural language, unstructured Chinese content is analysed to derive the general sentiment and relevant topics regarding the destination through user comments on social media. The proposed method allows us to understand what tourists are interested in and how they form opinions about tourist destinations.     

Public–private wage gap in Latin America (1992–2007): A matching approach

Using matching methods, we estimate the public–private wage gap for urban workers in eleven Latin American countries for the 1992–2007 period. These methods do not require any estimation of earnings equations and hence no validity-out-of-the-support assumptions; furthermore, this approach allows us to estimate not only the average wage gap but also its distribution. Our main findings indicate that the average public sector worker earns more than his/her private counterpart, and that this differential increased over the 1992–2007 period. Important differences along the wage distribution are also shown in the results; in fact, public servants in the highest percentiles of the wage distribution generally earn less than their private sector equivalents. Nonetheless, the percentile at which a positive wage gap becomes a wage penalty shifted over the period as the average wage gap experienced by most countries widened. Still, the most qualified public sector workers do face a wage penalty. Furthermore, indicators of government effectiveness show no relationship with the country ranking according to the public–private wage gap.     

What Prevents Firms from Advancing in their Environmental Strategy?

The aim of this paper is to analyze the determinants of the strategic environmental behavior of firms and, more specifically, the external and internal barriers that limit and sometimes even prevent the environmental adaptation. The analysis focuses on a sample of industrial firms that have at least three workers and that are located in Aragón, a region situated in the northeast of Spain. In order to achieve this objective, first the theoretical literature on the topic is reviewed. Subsequently, from the firms which were sampled, the existence of an underlying structure among the totality of barriers is studied. Finally, this structure is analyzed in order to determine if it has any influence on the degree of proactivity of the firm’s environmental strategy.

The relationship between store image and store brand equity: A conceptual framework and evidence from hypermarkets

Retailers are making considerable efforts to improve their brand management. The challenge they face, however, is how best to integrate coherently their stores, as brands, and their various distributor brands (store brands, private labels, etc.), in order to increase their brand equity and offer the market differential value that will stimulate customer loyalty. From this perspective, it is crucial for retailers to investigate the relationship between the store and their own brands. This study proposes two theoretical models showing the mechanism whereby store image helps increase the equity of a specific type of distributor brand (the store brand). The approach used in this analysis is based, on the one hand, on defining brand equity through its components, using the model in Aaker (1991), and on the other, on including (social and strategic) corporate dimensions in measuring store image. The empirical research made in the hypermarket sector in the Basque province of Gipuzkoa backs the majority of the proposed hypotheses. The results show that store image can be used by retailers to influence all components of store brand equity, essentially through its commercial and strategic dimension. This research is intended to address the clear lack of research on store brand equity.     

Key service innovation drivers in the tourism sector: empirical evidence and managerial implications

This study highlights the importance of market orientation and the use of information and communication technologies (ICT) as determinants of service innovation activity for companies in the tourism sector. In doing so, the study provides a means to classify companies as innovative or not. Using a sample of 100 Spanish firms from different branches of the tourism sector, we confirm and extend prior research. In particular, market orientation??especially a customer orientation??is critical for developing new services that lead to competitive advantages. In addition, ICT have a dual, direct, and indirect influence on service innovation.