Abstract
Purpose - This study aims to investigate the reliability of a mystery client (MC) as a service evaluation technique taking into consideration personal differences of the MC agents. Design/methodology/approach - The ratings from 144 MCs from 355 evaluations of computer and electronic stores were cross analyzed with eight psychographic and demographic profile variables. Findings - MCs who were highly involved in the product category were more critical of service responsiveness with respect to product demonstrations and listening to customer requirements. On the other hand, MCs with stronger faith in intuition were more inclined to rate services higher on empathy with respect to employees making a conscientious effort to understand customers' needs. Practical implications - Depending on the service marketing goals, managers learn to define which aspects of MC profile they should consider or avoid during the recruitment as well as becoming more critical when they analyze the evaluation reports to avoid an interpretation bias. Originality/value - The usefulness of the MC tool relies on its reliability and credibility as a marketing research technique. It was identified that the MC personality traits are more likely associated with marketing service evaluation variability.

Abstract
This paper develops a theoretical model to define tourism destination brand's online content. Message strategies and positioning attributes that brands want to communicate are the main inputs to develop communication content. However, the relationship between message strategies and attributes has not been studied in the literature. Our research examines this relationship, using 400 online brochures from around the world. Based on the positioning attributes and message strategies, a taxonomy is developed to analyse online brochures through content analysis. A comprehensive benchmark model was designed to assist tourism destination managers and advertisers while planning the concept and production of their online tourism brochures, and a new creative methodology based on several workable strategic alternatives are proposed.

Abstract
Destination image is critical for the development of tourism, particularly for islands where the scarcity of resources requires special care in focusing on the few determinants the islands have. This paper aims to describe the most perceived image determinants by tourists of Cape Verde. Based on a convenience sample of 627 international tourists, a second order factor analysis model was validated through the model fit measures. Despite a scarcity of resources, the results suggest that the image of Cape Verde is a multidimensional construct comprising five factors: natural attractions, man-made attractions, amenities, culture and price. Among these, the man-made and natural attractions as well as amenities are the most important image determinants for Cape Verde. Potentially there is a plurality of dimensions to be appreciated in the positioning process. Challenging many studies which have almost exclusively emphasised the attractions of natural resources, the tourism sector of this destination can offer a major and more flexible competitive advantage. The results may be helpful to other African countries which share similar developmental constraints with Cape Verde. © 2017 Nova Science Publishers, Inc.

Abstract
Simulation is a computer-based experimentation tool suitable to determine the efficacy of a previously untried decision. In this paper, we present a model of climate change. The goal behind this project is to provide a test-bed to evaluate theories related to the Earth system so as to test and evaluate metrics such as greenhouse gases and climate change in general. The proposed approach is based on a multi-agent model which has as input a representation of nature and as output the changes that will occur on Earth within a given instant of time. Most views about climate change do not take into account the real severity of the subject matter; however, the present perspective is given in a way so as to make non-experts aware of the risks that are threatening life on Earth. Just recently, the general population has developed considerable sensitivity to these issues. One important contribution of this work is to use agent-based modeling and simulation as an instructional tool that will allow people to easily understand all aspects involved in the preservation of the environment in a more aware and responsible way.

Abstract
In order to improve their competitive performance, airline companies often adopt as a strategy to establish arrangement between two or more organizations agreeing to cooperate on a substantial level. This strategy is often known as airline alliances. A paradigm to analyze the collective intelligence behavior which emerges from a group, as a strategic alliance, is the flocking behavior. Inspired by the Cucker and Smale algorithm (C-S) we propose a new version of the flocking behavior algorithm applied to airline alliances. Our goal is to understand the link between strategic alliances and flocks. For this new approach, metrics were obtained for the parameters of C-S algorithm, namely position, velocity and influence, where the latter uses cooperative games. Besides, reinforcement learning mechanisms have been explored. Some relevant outputs for airline alliances as the permanence rate and the growth rate were computed for each of the five configurations in analysis.

Abstract
In the past years, data has become increasingly fast and volatile, making the ability to track its evolution an highly significant part of the value extraction process. In this work we present a framework to monitor evolution of clusters and present its use on real world data. We develop a framework over a previous one by Oliveira and Gama from 2013. Its biggest contribution is the addition of the concept of control area. This area will create a region around the cluster where it is still possible to establish associations with clusters from other time points. It aims to expand the search scope for cluster associations while diminishing the number of false positives. Changes to the transition definitions and detection algorithm are also introduced to accommodate the existence of this area. We demonstrate this framework at work in a real world scenario testing it with a telecom industry dataset and make a detailed analysis of the obtained results.