Service attribute importance and strategic planning: An empirical study

There is growing evidence that attribute importance is a function of attribute performance. Several studies reported that service quality attributes fall into three categories: basic, performance, and excitement. Thus, the identification of attribute importance is significantly important as a key to customer satisfaction evaluation and other behavioural intentions. According to customer behaviour literature, attribute importance can be measured in two ways: (1) self-stated importance, and (2) statistically inferred importance. The article evaluates two methods according to their impact on overall customer satisfaction measurement and, managerial implementation. A case study is conducted on the telecommunication industry for analysis

The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence

The most-noted studies on the impact of microcredit on households are based on a survey fielded in Bangladesh in the 1990s. Contradictions among them have produced lasting controversy and confusion. Pitt and Khandker (PK, 1998) apply a quasi-experimental design to 1991–92 data; they conclude that microcredit raises household consumption, especially when lent to women. Khandker (2005) applies panel methods using a 1999 resurvey; he concurs and extrapolates to conclude that microcredit helps the extremely poor even more than the moderately poor. But using simpler estimators than PK, Morduch (1999) finds no impact on the level of consumption in the 1991–92 data, even as he questions PK’s identifying assumptions. He does find evidence that microcredit reduces consumption volatility. Partly because of the sophistication of PK’s Maximum Likelihood estimator, the conflicting results were never directly confronted and reconciled. We end the impasse. A replication exercise shows that all these studies’ evidence for impact is weak. As for PK’s headline results, we obtain opposite signs. But we do not conclude that lending to women does harm. Rather, all three studies appear to fail in expunging endogeneity. We conclude that for non-experimental methods to retain a place in the program evaluator’s portfolio, the quality of the claimed natural experiments must be high and demonstrated.microcredit; impact evaluation; Grameen Bank; Bangladesh; replication; mixed-process models

Determinants of pollution abatement and control expenditure: Evidence from Romania

The aim of the present study is to shed some light on the factors affecting Pollution Abatement and Control Expenditure (PACE) in the context of a transition economy such as Romania, in contrast to the existing literature which mostly focuses on developed economies. Specifically, we use survey data of the Romanian National Institute of Statistics and estimate Multilevel Regression Model (MRM) to investigate the determinants of environmental behaviour at plant level. Our results reveal some important differences vis-à-vis the developed countries, such as a less significant role for collective action and environmental taxes, which suggests some possible policy changes to achieve better environmental outcomes

Revisiting individual and group differences in thermal comfort based on ASHRAE database

Different thermal demands and preferences between individuals lead to a low occupant satisfaction rate, despite the high energy consumption by HVAC system. This study aims to quantify the difference in thermal demands, and to compare the influential factors which might lead to those differences. With the recently released ASHRAE Database, we quantitatively answered the following two research questions: which factors would lead to marked individual difference, and what the magnitude of this difference is. Linear regression has been applied to describe the macro-trend of how people feel thermally under different temperatures. Three types of factors which might lead to different thermal demands have been studied and compared in this study, i.e. individual factors, building characteristics and geographical factors. It was found that the local climate has the most marked impact on the neutral temperature, with an effect size of 3.5 °C; followed by country, HVAC operation mode and body built, which lead to a difference of more than 1 °C. In terms of the thermal sensitivity, building type and local climate are the most influential factors. Subjects in residential buildings or coming from Dry climate zone could accept 2.5 °C wider temperature range than those in office, education buildings or from Continental climate zone. The findings of this research could help thermal comfort researchers and designers to identify influential factors that might lead to individual difference, and could shed light on the feature selection for the development of personal comfort models

Revisiting Guerry's data: Introducing spatial constraints in multivariate analysis

Standard multivariate analysis methods aim to identify and summarize the main structures in large data sets containing the description of a number of observations by several variables. In many cases, spatial information is also available for each observation, so that a map can be associated to the multivariate data set. Two main objectives are relevant in the analysis of spatial multivariate data: summarizing covariation structures and identifying spatial patterns. In practice, achieving both goals simultaneously is a statistical challenge, and a range of methods have been developed that offer trade-offs between these two objectives. In an applied context, this methodological question has been and remains a major issue in community ecology, where species assemblages (i.e., covariation between species abundances) are often driven by spatial processes (and thus exhibit spatial patterns). In this paper we review a variety of methods developed in community ecology to investigate multivariate spatial patterns. We present different ways of incorporating spatial constraints in multivariate analysis and illustrate these different approaches using the famous data set on moral statistics in France published by Andr\'{e}-Michel Guerry in 1833. We discuss and compare the properties of these different approaches both from a practical and theoretical viewpoint.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS356 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Revisiting the Far Right Violent Extremist Threat: Violent Extremist Plot Success From 1948 Through 2017

Far Right violent extremists have successfully executed over 150 violent plots in the United States in just the past decade. This exploratory study analyzed Far Right violent extremist plot success with the plot success of Islamist violent extremists, Far Left violent extremists, and Single Issue violent extremists based on publicly available data from the Profiles of Individual Radicalization in the United States (PIRUS) for the period of 1948 through 2017. By evaluating existing literature on Far Right violent extremism and analyzing the available PIRUS data, it was discovered that while Far Right violent extremists executed more successful violent plots than the other violent ideological extremist groups, Far Left violent extremists proportionally had more successful violent plots. A sample from the PIRUS database was explored, and the analysis demonstrates that the variables of Far Left radicalization, violence against persons and property, and plot preparation are significantly correlated with violent plot success