Abstract
Information provided by geotagged photos allow us to know where and when people have been, supporting a better understanding about tourist's movement patterns across a destination. The aim of this paper is to study tourists' movement patterns during their staying in Porto through the analysis of geotagged photos in order to fulfill marketing segmentation in an innovative way. For that purpose, the SPADE algorithm was used to find sequence patterns of tourists paths based on the time and location of the photos collected. Then, the K-Mode clustering algorithm was applied to these sequences in order to find identical behaviors in terms of paths followed by tourists. At the same time, in order to understand the influence of the different attractions on tourists' paths, we performed a Social Network Analysis of the touristic attractions (spots, museums, streets, monuments, etc.). Based on the time and location of the photos collected, along with personal information, it was possible to understand tourists' frequent movements across the city and to identify market segments based on a hybrid strategy.

Abstract
The automation of tasks is increasingly a current practice in the organizational environment, and this practice reduces the need for manpower and often reduces the errors associated with the human factor. In the present document a solution will be presented to automatically generate the source code of a mockup, having as input an image corresponding to the prototype. In the development of this project techniques of Deep Learning will be used, especially Convolutional Neural Networks for the detection and classification of objects in images. The developed solution provides the code base of a mockup in less than 60 seconds, with an average error rate 15.85%.

Abstract
Grapevine yield prediction during phenostage and particularly, before harvest is highly significant as advanced forecasting could be a great value for superior grapevine management. The main contribution of the current study is to develop predictive model for each phenology that predicts yield during growing stages of grapevine and to identify highly relevant predictive variables. Current study uses climatic conditions, grapevine yield, phenological dates, fertilizer information, soil analysis and maturation index data to construct the relational dataset. After words, we use several approaches to pre-process the data to put it into tabular format. For instance, generalization of climatic variables using phenological dates. Random Forest, LASSO and Elasticnet in generalized linear models, and Spikeslab are feature selection embedded methods which are used to overcome dataset dimensionality issue. We used 10-fold cross validation to evaluate predictive model by partitioning the dataset into training set to train the model and test set to evaluate it by calculating Root Mean Squared Error (RMSE) and Relative Root Mean Squared Error (RRMSE). Results of the study show that rf_PF, rf_PC and rf_MH are optimal models for flowering (PF), colouring (PC) and harvest (MH) phenology respectively which estimate 1484.5, 1504.2 and 1459.4 (Kg/ha) low RMSE and 24.6%, 24.9% and 24.2% RRMSE, respectively as compared to other models. These models also identify some derived climatic variables as major variables for grapevine yield prediction. The reliability and early-indication ability of these forecast models justify their use by institutions and economists in decision making, adoption of technical improvements, and fraud detection. © 2019 Asian Agricultural and Biological Engineering Association

Abstract
The objective of this study is to understand to what extent hedonic and utilitarian consumer profiles are affected by situational factors and how in turn they impact shopping centre patronage. A six step multiple regression analysis corresponding to six different shopping centres has been applied to two clusters of consumers. The data are based on consumers' hedonic/utilitarian customer profile. First, results show that in general the impact on shopping centre patronage is largely affected by proximity, convenience and accessibility variables, which are more relevant among the utilitarian profile consumers. On the other hand, in the hedonic profile segment, affect, that is, the experience of feeling or emotion is the relevant variable explaining patronage. Second, the predictive contribution of these variables on patronage varied according to the shopping centres' positioning. With the findings of the present study, retail managers can formulate marketing strategies, which will attract retail consumers towards their shopping centre and also help them to enhance the significant factors that influence retail store consumer's purchase decision. Also, this investigation contributes to the diagnosis of how consistent is the retailers' in their positioning strategy in targeting the market segments. The present research integrates both situational factors and hedonic as well as utilitarian consumer profiles along with the role of situational dynamics to explain shopping centres' patronage.

Abstract
Purpose The purpose of this paper is to examine and compare the influence of age, education, income, product involvement and sales promotion (SP) characteristics on consumer attitudes towards SP across eight culturally dissimilar environments. Design/methodology/approach A multi-country mall intercept and mail survey was conducted in Brunei, China, Hong Kong, Indonesia, Malaysia, New Zealand, Singapore and Thailand (n=4,125 respondents). Findings Country, education level and income significantly influence consumer attitudes towards SP. Some countries show a significant monetary value interaction effect. Consumers using delayed-reward SPT reported a significantly more positive attitude towards SP. Discounts and coupons are the two most highly ranked SP across the sampled countries. Research limitations/implications - Limitations include the use of intercept and mail sampling. Extending the study to include additional Asian countries and other regions would benefit the understanding of cultural influences on SP. Practical implications - Multinational marketing managers should consider three aspects of SP implementation strategy: cultural and demographic factors, interaction between delayed-reward SP and socio-demographics variables; country specific SP preferences to promote both sales and brand equity. Originality/value This study investigates and extends research on SP across cultures. In particular the research helps better understand the impact of demographic factors and culture on attitudes towards SP, and implementation of global promotions.

Abstract
PurposeThis paper aims to examine the mediating role of brand satisfaction and brand trust in brand equity antecedents and outcomes through an empirical investigation of brand equity elements.Design/methodology/approachA survey was conducted in Pune and Mumbai, two prominent cities of India. A structured questionnaire focussed on garnering responses on measuring brand equity antecedents and outcomes was circulated to the cell phone users. The questionnaire aimed to assess the role of two additional variables, namely, brand satisfaction and brand trust, in the existing and the conceptual model of brand equity (Keller, 2001). Based on the data analysis, a structural equations path and the mediating model were developed.FindingsThe findings of this study show that the new brand equity model is highly relevant in predicting brand equity as compared to the existing brand equity model (Keller, 2001). The brand equity mediation model clearly elucidates the role of brand trust and brand satisfaction.Research limitations/implicationsWith reference to a theoretical contribution, the study broadens the existing hypothetical model of brand equity. The findings of this research provide a strategic and analytical model for brand managers to build brand relationships among their consumers.Originality/valueThe present study challenges the existing model of brand equity (Keller, 2001) and further makes an effort to fill in the gaps in the existing theoretical model of brand equity.