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Article Citation - WoS: 37Citation - Scopus: 59Career Abandonment Intentions among Software Workers(Wiley, 2014) Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Misra, Sanjay; Soto-Acosta, PedroWithin the software development industry, human resources have been recognized as one of the most decisive and scarce resources. Today, the retention of skilled IT (information technology) personnel is a major issue for employers and recruiters as well, since IT career abandonment is a common practice and means not only the loss of personnel, knowledge, and skills, but also the loss of business opportunities. This article seeks to discover the main motivations young practitioners abandon the software career. To achieve this objective, two studies were conducted. The first study was qualitative (performed through semistructured interviews) and intended to discover the main variables affecting software career abandonment. The second study was quantitative, consisting of a Web-based survey developed from the output of the first study and administered to a sample of 148 IT practitioners. Results show that work-related, psychological, and emotional variable are the most relevant group of variables explaining IT career abandonment. More specifically, the three most important variables that motivate employees to abandon the career are effort-reward imbalance, perceived workload, and emotional exhaustion. In contrast, variables such as politics and infighting, uncool work, and insufficient resources influence to a lesser extent the decision to leave the career. (c) 2012 Wiley Periodicals, Inc.Article Citation - WoS: 31Citation - Scopus: 50Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: a Case Study of an International Bank(Wiley, 2015) Ogwueleka, Francisca Nonyelum; Misra, Sanjay; Colomo-Palacios, Ricardo; Fernandez, LuisThe customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six-step procedure. The back-propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.Article Citation - WoS: 67Citation - Scopus: 88Towards a Social and Context-Aware Mobile Recommendation System for Tourism(Elsevier, 2017) Colomo-Palacios, Ricardo; Jose Garcia-Penalvo, Francisco; Stantchev, Vladimir; Misra, SanjayLoyalty in tourism is one of the main concerns for tourist organizations and researchers alike. Recently, technology in general and CRM and social networks in particular have been identified as important enablers for loyalty in tourism. This paper presents POST-VIA 360, a platform devoted to support the whole life-cycle of tourism loyalty after the first visit. The system is designed to collect data from the initial visit by means of pervasive approaches. Once data is analysed, POST-VIA 360 produces accurate after visit data and, once returned, is able to offer relevant recommendations based on positioning and bio-inspired recommender systems. To validate the system, a case study comparing recommendations from the POST-VIA 360 and a group of experts was conducted. Results show that the accuracy of system's recommendations is remarkable compared to previous efforts in the field. (C) 2016 Elsevier B.V. All rights reserved.Article Citation - WoS: 21Citation - Scopus: 29Providing Knowledge Recommendations: an Approach for Informal Electronic Mentoring(Routledge Journals, Taylor & Francis Ltd, 2014) Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Soto-Acosta, Pedro; Misra, SanjayThe use of Web 2.0 technologies for knowledge management is invading the corporate sphere. The Web 2.0 is the most adopted knowledge transfer tool within knowledge intensive firms and is starting to be used for mentoring. This paper presents IM-TAG, a Web 2.0 tool, based on semantic technologies, for informal mentoring. The tool offers recommendations of mentoring contents built upon personal competencies of the mentee, combined with content and opinion tagging. To validate the tool, a case study comparing recommendations from the IM-TAG and a group of experts was conducted. Results show that the accuracy of IM-TAG's recommendations is notable and satisfactory. The main conclusions of this research may be valuable to organizations immersed in mentoring programs.Article Citation - WoS: 7Citation - Scopus: 14An Evaluation of Ict Infrastructure and Application in Nigeria Universities(Budapest Tech, 2014) Egoeze, Fidelis; Misra, Sanjay; Akman, Ibrahim; Colomo-Palacios, Ricardo; Computer EngineeringThe need for adequate ICT infrastructure/facility in higher education institutions cannot be overemphasized, even as availability and utilization of these facilities are at times the indices for rating universities. In this descriptive survey study, ICT infrastructure and the extent of usage in Nigeria universities were investigated. Questionnaire was the instrument used for gathering information and based on related literature. A total of 452 respondents comprised of students, lecturers and administrators randomly selected from a total of 15 universities from different regions of Nigeria participated. Data collected were analyzed using mean statistic analysis and analysis of variance (ANOVA).
