373 research outputs found

    A consumer perspective e-commerce websites evaluation model

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    Existing website evaluation methods have some weaknesses such as neglecting consumer criteria in their evaluation, being unable to deal with qualitative criteria, and involving complex weight and score calculations. This research aims to develop a hybrid consumer-oriented e-commerce website evaluation model based on the Fuzzy Analytical Hierarchy Process (FAHP) and the Hardmard Method (HM). Four phases were involved in developing the model: requirements identification, empirical study, model construction, and model confirmation. Requirements identification and empirical study were to identify critical web-design criteria and gather online consumers' preferences. Data, collected from 152 Malaysian consumers using online questionnaires, were used to identify critical e-commerce website features and scale of importance. The new evaluation model comprised of three components. First, the consumer evaluation criteria that consist of the important principles considered by consumers; second, the evaluation mechanisms that integrate FAHP and HM consisting of mathematical expressions that handle subjective judgments, new formulas to calculate the weight and score for each criterion; and third, the evaluation procedures consisting of activities that comprise of goal establishment, document preparation, and identification of website performance. The model was examined by six experts and applied to four case studies. The results show that the new model is practical, and appropriate to evaluate e-commerce websites from consumers' perspectives, and is able to calculate weights and scores for qualitative criteria in a simple way. In addition, it is able to assist decision-makers to make decisions in a measured objective way. The model also contributes new knowledge to the software evaluation fiel

    An effective evaluation model and improvement analysis for national park websites: A case study of Taiwan

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    [[abstract]]Taiwanese National Park Headquarters employ advanced information technologies to attract travellers, researchers, and other visitors, but it is likely that not all Headquarters have clear knowledge about how successful their websites are. This study proposes an effective model for evaluating national park websites. The model first applies the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to cope with the interdependencies between evaluation criteria. Next, it uses the Analytic Network Process (ANP) to compute weights for each criterion. Finally, it uses the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to rank Taiwanese national park websites. Overall, the results show that each national park website must be improved in order to become a high quality website. Furthermore, the weight-variance analysis suggests managerial actions based on two-dimensional maps for improving website quality. Therefore, this study not only provides a comprehensive and systematic approach that quantitatively measures a website's overall performance, but also contributes to practical applications in terms of providing worthwhile recommendations for building an ideal website

    Hierarchical outranking methods for multi-criteria decision aiding

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    Els mètodes d’Ajut a la Decisió Multi-Criteri assisteixen en la pressa de decisions implicant múltiples criteris conflictius. Existeixen dos enfocaments principals per resoldre aquest tipus de problemes: els mètodes basats en utilitat i d’outranking, cadascun amb les seves fortaleses i debilitats. Els mètodes outranking estan basats en models d’elecció social combinats amb tècniques d’intel·ligència artificial (com gestió de dades categòriques o d’incertesa). Son eines per una avaluació i comparació realista d’alternatives, basant-se en les necessitats i coneixements del prenedor de la decisió. Una de les debilitats dels mètodes outranking és la no consideració de jerarquies de criteris, que permeten una organització natural del problema, distingint diferents nivells de generalitat que modelen les relacions taxonòmiques implícites entre criteris. En aquesta tesi ens enfoquem en el desenvolupament d’eines d’outranking jeràrquiques i la seva aplicació en casos d’estudi reals per problemes de classificació i rànquing.Los métodos de Ayuda a la Decisión Multi-Criterio asisten en la toma de decisiones involucrando múltiples criterios conflictivos. Existen dos enfoques principales para resolver éste tipo de problemas: los métodos basados en utilidad y de outranking, cada uno con sus fortalezas y debilidades. Los métodos outranking están basados en modelos de elección social combinados con técnicas de Inteligencia Artificial (como gestión de datos categóricos o de incertidumbre). Son herramientas para una evaluación y comparación realista de alternativas, basándose en las necesidades y conocimientos del tomador de decisión. Una de las debilidades de los métodos outranking es la no consideración de jerarquías de criterios, que permiten una organización natural del problema, distinguiendo distintos niveles de generalidad que modelan las relaciones taxonómicas implícitas entre criterios. En ésta tesis nos enfocamos en el desarrollo de herramientas de outranking jerárquicas y su aplicación en casos de estudio reales para problemas de clasificación y ranking.Multi-Criteria Decision Aiding (MCDA) methods support complex decision making involving multiple and conflictive criteria. MCDA distinguishes two main approaches to deal with this type of problems: utility-based and outranking methods, each with its own strengths and weaknesses. Outranking methods are based on social choice models combined with Artificial Intelligence techniques (such as the management of categorical data or uncertainty). They are recognized as providing tools for a realistic assessment and comparison of a set of alternatives, based on the decision maker’s knowledge and needs. One of the main weaknesses of the outranking methods is the lack of consideration of hierarchies of criteria, which enables the decision maker to naturally organize the problem, distinguishing different levels of generality that model the implicit taxonomical relations between the criteria. In this thesis we focus on developing hierarchical outranking tools and their application to real-world case studies for ranking and sorting problems

    Usability Testing of a Web Portal for Ornamental Plants and Flowers in Arusha, Tanzania

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    This research article published by Engineering, Technology & Applied Science Research Vol. 10 No. 3 (2020): June 2020The Information and Communication Technology (ICT) adoption has steadily advanced in the horticulture sector in Tanzania. This study aims to test and give feedback regarding the usability of a developed web portal prototype for ornamental plants and flowers in Arusha City. The stakeholders are botanists and researchers who search for plant and flower information (taxonomy), small scale farmers, herbalists, and the Arusha City Council. The assessments were organized and conducted in groups where each stakeholder was given access to the web portal for 2 days. Questionnaires were distributed to get feedback from each participant (a total of 48 participants). Multicriteria satisfaction analysis was chosen to measure user satisfaction measuring usability factors such as service quality, technical quality, information quality, and system quality. The overall obtained results had a mean score above 3.5 (70%) on a five-point scale Likert scale analysis

    A Software Product Line Approach to Ontology-based Recommendations in E-Tourism Systems

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    This study tackles two concerns of developers of Tourism Information Systems (TIS). First is the need for more dependable recommendation services due to the intangible nature of the tourism product where it is impossible for customers to physically evaluate the services on offer prior to practical experience. Second is the need to manage dynamic user requirements in tourism due to the advent of new technologies such as the semantic web and mobile computing such that etourism systems (TIS) can evolve proactively with emerging user needs at minimal time and development cost without performance tradeoffs. However, TIS have very predictable characteristics and are functionally identical in most cases with minimal variations which make them attractive for software product line development. The Software Product Line Engineering (SPLE) paradigm enables the strategic and systematic reuse of common core assets in the development of a family of software products that share some degree of commonality in order to realise a significant improvement in the cost and time of development. Hence, this thesis introduces a novel and systematic approach, called Product Line for Ontology-based Tourism Recommendation (PLONTOREC), a special approach focusing on the creation of variants of TIS products within a product line. PLONTOREC tackles the aforementioned problems in an engineering-like way by hybridizing concepts from ontology engineering and software product line engineering. The approach is a systematic process model consisting of product line management, ontology engineering, domain engineering, and application engineering. The unique feature of PLONTOREC is that it allows common TIS product requirements to be defined, commonalities and differences of content in TIS product variants to be planned and limited in advance using a conceptual model, and variant TIS products to be created according to a construction specification. We demonstrated the novelty in this approach using a case study of product line development of e-tourism systems for three countries in the West-African Region of Africa

    Feature info : improving the visualization and usability of GIS background information in the context of a mobile tourist application

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    Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesFeature info is an interactive map tool that allows viewing background information about a map feature in response to a user action. Mobile devices come with a number of limitations, e.g. small screen real estate and the variety of screen sizes, that can affect map and feature info usability. Existing recommendations for feature info design [1], [2], [3] focus mostly on content, i.e. effective communication of data, leaving the “interaction design” aspect overlooked. This Master’s Thesis attempts at improving the visualization and usability of feature info interfaces in the context of mobile tourist applications and presents nine feature info design guidelines that address specific usability problems. The problems were identified through heuristic evaluation of five tourist applications and a user interview. Literature survey and two usability experts provided ideas regarding how several of these problems can be resolved. Three guidelines were evaluated in a lab-based usability test with twenty participants. On average, assessed guidelines demonstrated a significant positive effect on feature info usability by decreasing task completion time by 33% and increasing task completion rate and System Usability Scale (SUS) score by 26% and 28% respectively. Proposed guidelines are not restricted by any specific use case and can be applied to other application domains. Researchers and business practitioners can use the guidelines as a reference in their daily work

    Model to evaluate customer satisfaction in e-commerce through multi-criteria and semantic analysis

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    Trabajo de Grado (Profundización)Se presenta un modelo de evaluación multicriterio para la medición de satisfacción del cliente en el sector de comercio electrónico, el modelo propone 7 criterios objetivos de evaluación, a saber: seguridad, información, producto o servicio, distribución logística, diseño del sitio, servicio al cliente y usabilidad, cada criterio tiene un peso estimado según la importancia percibida por los clientes. Se extraen los comentarios de la red social Facebook de dos plataformas de comercio electrónico que operan en Colombia y se realiza la medición de satisfacción del cliente obteniendo resultados importantes para la toma de decisiones empresariales.1. INTRODUCTION 2. PROBLEM STATEMENT 3. OBJETIVES 4. CONCEPTUAL FRAMEWORK 5. THEORETICAL FRAMEWORK 6. STATE OF THE ART 7. METHODOLOGY 8. VIGILANCIA TECNOLÓGICA 9. ONTOLOGY FOR E-COMMERCE 10. RESULTS 11. CONCLUSIONS 12. FUTURE WORKS 13. REFERENCESMaestríaMagister en Ingeniería y Gestión de la Innovació

    Knowledge aggregation in people recommender systems : matching skills to tasks

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    People recommender systems (PRS) are a special type of RS. They are often adopted to identify people capable of performing a task. Recommending people poses several challenges not exhibited in traditional RS. Elements such as availability, overload, unresponsiveness, and bad recommendations can have adverse effects. This thesis explores how people’s preferences can be elicited for single-event matchmaking under uncertainty and how to align them with appropriate tasks. Different methodologies are introduced to profile people, each based on the nature of the information from which it was obtained. These methodologies are developed into three use cases to illustrate the challenges of PRS and the steps taken to address them. Each one emphasizes the priorities of the matching process and the constraints under which these recommendations are made. First, multi-criteria profiles are derived completely from heterogeneous sources in an implicit manner characterizing users from multiple perspectives and multi-dimensional points-of-view without influence from the user. The profiles are introduced to the conference reviewer assignment problem. Attention is given to distribute people across items in order reduce potential overloading of a person, and neglect or rejection of a task. Second, people’s areas of interest are inferred from their resumes and expressed in terms of their uncertainty avoiding explicit elicitation from an individual or outsider. The profile is applied to a personnel selection problem where emphasis is placed on the preferences of the candidate leading to an asymmetric matching process. Third, profiles are created by integrating implicit information and explicitly stated attributes. A model is developed to classify citizens according to their lifestyles which maintains the original information in the data set throughout the cluster formation. These use cases serve as pilot tests for generalization to real-life implementations. Areas for future application are discussed from new perspectives.Els sistemes de recomanació de persones (PRS) són un tipus especial de sistemes recomanadors (RS). Sovint s’utilitzen per identificar persones per a realitzar una tasca. La recomanació de persones comporta diversos reptes no exposats en la RS tradicional. Elements com la disponibilitat, la sobrecàrrega, la falta de resposta i les recomanacions incorrectes poden tenir efectes adversos. En aquesta tesi s'explora com es poden obtenir les preferències dels usuaris per a la definició d'assignacions sota incertesa i com aquestes assignacions es poden alinear amb tasques definides. S'introdueixen diferents metodologies per definir el perfil d’usuaris, cadascun en funció de la naturalesa de la informació necessària. Aquestes metodologies es desenvolupen i s’apliquen en tres casos d’ús per il·lustrar els reptes dels PRS i els passos realitzats per abordar-los. Cadascun destaca les prioritats del procés, l’encaix de les recomanacions i les seves limitacions. En el primer cas, els perfils es deriven de variables heterogènies de manera implícita per tal de caracteritzar als usuaris des de múltiples perspectives i punts de vista multidimensionals sense la influència explícita de l’usuari. Això s’aplica al problema d'assignació d’avaluadors per a articles de conferències. Es presta especial atenció al fet de distribuir els avaluadors entre articles per tal de reduir la sobrecàrrega potencial d'una persona i el neguit o el rebuig a la tasca. En el segon cas, les àrees d’interès per a caracteritzar les persones es dedueixen dels seus currículums i s’expressen en termes d’incertesa evitant que els interessos es demanin explícitament a les persones. El sistema s'aplica a un problema de selecció de personal on es posa èmfasi en les preferències del candidat que condueixen a un procés d’encaix asimètric. En el tercer cas, els perfils dels usuaris es defineixen integrant informació implícita i atributs indicats explícitament. Es desenvolupa un model per classificar els ciutadans segons els seus estils de vida que manté la informació original del conjunt de dades del clúster al que ell pertany. Finalment, s’analitzen aquests casos com a proves pilot per generalitzar implementacions en futurs casos reals. Es discuteixen les àrees d'aplicació futures i noves perspectives.Postprint (published version

    Developing a visitor decision support system for natural tourist destinations

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    As the number of tourists/visitors and particularly nature-based tourists to any particular protected area increases, management of the visitors and providing them with the facility to support their recreation or holiday planning is increasingly becoming important and popular. Walking, one of the most popular nature-based activities in natural locations provides opportunities for visitors to experience and explore natural environments and enjoy the beauty of landscape. The quality of visitor experiences along walking tracks could be increased if visitors have the potential to select appropriate walks from among the available walking tracks in terms of their time availability, ability and desire in a natural tourist destination. A visitor decision support system is developed in this research project to support visitors in making their decision on a suitable walking track when they are faced with a number of alternative track options. The system is developed using geo-visualisation approach in GIS and a geo-visualisation tool, Google Earth. The system is developed through a case study approach. Mornington Peninsula National Park, Victoria, Australia was selected as the study area to apply and evaluate the system. The Park offers a wide range of walking track options with various spatial characteristics such as track length, track slope and track surface type. Literature reviews and a visitor preference survey were used to find out the most important factors for visitors on selection of a walking track. This resulted in identifying a set of key visitor preference factors including track location, track length and duration of walking time, available sights (scenic attractions), degree of difficulty, track information and available recreational activities and facilities. Considering the key visitor preference factors, a spatial database was built using existing data and data collected through a field survey using a Global Positioning System (GPS) receiver and photography. The key factors were used as a base to determine a series of walking track selection criteria. The criteria can be used to support visitors in selecting a walking track through two main sections of the system: GIS-based section and geo-visualisation section. Through the GIS-based section a query selection form is available. The form consists of a set of criteria including track geographical location, duration of walking time, track slope and track surface type. Each criterion includes a range of track characteristic classes. Through the geo-visualisation section, more information was added to Google Earth including opportunity for sightseeing and recreational activities as well as information about track safety, boardwalks, steps, ramps, track width and existing recreational facilities and information centres. Using a sample user survey the system was evaluated. The evaluation outcomes proved that the system is useful in supporting users to find their desired walking track from among a number of available alternatives. The developed system provides the possibility of having an optimum (most favourable under given circumstances) and better quality walking experience by offering more detailed data about the tracks

    Isolation and distinctiveness in the design of e-learning systems influence user preferences

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    When faced with excessive detail in an online environment, typical users have difficulty processing all the elements of representation. This in turn creates cognitive overload, which narrows the user's focus to a few select items.In the context of e-learning, we translated this aspect as the learner's demand for a system that facilitates the retrieval of learning content – one in which the representation is easy to read and understand.We hypothesized that the representation of content in an e-learning system's design is an important antecedent for learner preferences.The aspects of isolation and distinctiveness were incorporated into the design of e-learning representation as an attempt to promote student cognition.Following its development, the model was empirically validated by conducting a survey of 300 university students. We found that isolation and distinctiveness in the design elements appeared to facilitate the ability of students to read and remember online learning content. This in turn was found to drive user preferences for using e-learning systems.The findings provide designers with managerial insights for enticing learners to continue using e-learning systems
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