Measuring populist discourse with semantic text analysis: an application on grassroots populist mobilization

Populism is a concept employed to qualify the political behavior of a large number of actors at a worldwide scale, with scientists classifying the latter into populists and non-populists according to dimensions such as ideology, strategy, discourse, economic policy, and even style. This article analyzes existing schools of thought on the nature of populism and argues that conceptualizing populism as a specific type of anti-elite discourse in the name of the People is both conceptually and methodologically the most coherent and useful way to understand the phenomenon. Additionally, it suggests discarding crude, dichotomous classification in favor of a gradated view of populist mobilization by means of quantifying populist discourse and observing its spatial and temporal variation. It adds value to current methods of measurement by demonstrating why and how clause-based semantic text analysis can provide optimal quantitative results while retaining qualitative elements for mixed-methods analysis. Aiming, moreover, at expanding the scope of populism studies by overcoming a narrow view that focuses exclusively at party system developments, it applies semantic text analysis to the study of grassroots mobilization during the Great Recession. Results point to the wide use of populist discourse on the part of movement activists seeking an inclusive language when framing disparate social grievances in a given constituency, a finding with important implications with regards to how populism can facilitate straddling the divide that purportedly distinguishes institutionalized party system behavior from the social movement milieu.     

Using integrated quality assessment for hotel service quality

In the age of growing foreign tourism, providing excellent quality service at hotels is increasingly more important. Service quality and customer satisfaction have gradually been recognized as key factors used to gain competitive advantage and customer retention. Most companies conducted satisfaction surveys of their customers, with a view of using analysed results to identify attributes of potential improvement. However, this kind improvement decisions on the attributes with a lower satisfaction level needs not to be appropriated. Thus, to achieve higher levels of overall satisfaction with the hotel experience, this study combined four simple methods, including Kano’s model, refined Kano’s model, Importance-Satisfaction model, and the Improvement index, to evaluate two types of hotels. The integrated approach of service quality measurement is based on the importance and satisfaction survey of the quality attributes. The survey, with 24 attributes and service items, were administrated to a random sample of 400 customers at one business hotel and one resort hotel in Taiwan. The strategies of these two kinds of hotels were compared and discussed in this study. On the basis of the key quality attributes identified by employing the integrated approach, which are significantly different from those identified on the basis of a simple satisfaction survey, hotels can make appropriate decisions on specific areas for improvement to further enhance the hotel service quality in Taiwan.     

Shannon information in record data

In this article we present results on the Shannon information (SI) contained in upper (lower) record values and associated record times in a sequence of i.i.d continuous variables. We then establish an interesting relationship between the SI content of a random sample of fixed size, and the SI in the data consisting of sequential maxima. We also consider the information contained in the record data from an inverse sampling plan (ISP).     

Minimax price bounds in incomplete markets

This paper develops an approach to tighten the bounds on asset prices in an incomplete market by combining no-arbitrage pricing and preference-based pricing, and the approach is applied to a call option in the absence of dynamic rebalancing. With the no-arbitrage pricing, it is straightforward to obtain the initial bounds, which are too wide to be of practical uses. By accepting that a representative agent exhibits risk aversion from a benchmark pricing kernel, it is possible to narrow the bounds considerably. Using the unbiased minimax deviation implicit in the parameters, one can restrict further the set of reasonable values on assets in incomplete markets.     

Dispersive ordering of fail-safe systems with heterogeneous exponential components

Let X ₁, . . . , X _n be independent exponential random variables with respective hazard rates λ₁, . . . , λ _n , and Y ₁, . . . , Y _n be independent and identically distributed random variables from an exponential distribution with hazard rate λ. Then, we prove that X _2:n , the second order statistic from X ₁, . . . , X _n , is larger than Y _2:n , the second order statistic from Y ₁, . . . , Y _n , in terms of the dispersive order if and only if

$\lambda\geq \sqrt{\frac{1}{{n\choose 2}}\sum_{1\leq i < j\leq n}\lambda_i\lambda_j}.$

We also show that X _2:n is smaller than Y _2:n in terms of the dispersive order if and only if

$ \lambda\le\frac{\sum^{n}_{i=1} \lambda_i-{\rm max}_{1\leq i\leq n} \lambda_i}{n-1}. $

Moreover, we extend the above two results to the proportional hazard rates model. These two results established here form nice extensions of the corresponding results on hazard rate, likelihood ratio, and MRL orderings established recently by Pǎltǎnea (J Stat Plan Inference 138:1993–1997, 2008), Zhao et al. (J Multivar Anal 100:952–962, 2009), and Zhao and Balakrishnan (J Stat Plan Inference 139:3027–3037, 2009), respectively.