Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented

Predicting Purchase Proneness of Anonymous User in Mobile Commerce

In recent years, mobile commerce is developing rapidly because of the popularity of mobile devices. However, for the difficulty of the mobile device input, the users of the e-commerce websites usually don’t log on the website when they are browsing, which resulting in a situation that a large number of website visitors are anonymous users. In order to increase sales revenue and expand market share, an effective prediction of anonymous users’ purchases proneness is very helpful in providing targeted marketing strategy for website to induce anonymous users to purchase. In the past, customer segmentation was mainly analyzed and modeled by customers’ historical data. But the history data of anonymous users can’t be obtained on mobile commerce sites. This method is difficult to put into management practice. In order to solve this problem, this paper proposes a method based on random forest of using user clickstream data to forecast purchase proneness in real time. This method includes two stages: the model training part and the user purchasing proneness prediction part. In the model training part, a classifier based on random forest algorithm is trained. In the users\u27 predicting part, the classifier is used to predict the user\u27s purchase proneness in real time. The method proposed can be effectively applied in the real-time prediction of anonymous users\u27 purchasing proneness, and the results of prediction will help enterprises implement the marketing measures in real time

O lado comportamental dos agentes de recomendação : uma revisão bibliométrica

Recommendation agents have been used to assist consumers in online purchase for almost 20 years. Their use has been studied in academic research with two different approaches. The first one addresses computational problems related to generating accurate recommendations. The other seeks to understand how user interaction with recommendation agents can alter behaviors in online shopping. Through bibliometric and scientometric methods, this study looked for the most influential papers, authors and journals in the field of behavioral recommendation research. In the present work, only articles investigating behavioral aspects of recommendation usage were considered. The identified articles were analyzed in terms of their methodology, variables and repercussion. At the end, a total of 175 articles published in journals from many different fields of academic research were found, attesting the multidisciplinary nature of this topic. Most of the studies were empirical investigations using experimental methodology, however theoretical papers showed to be more influential. It was possible to identify 29 different dependent variables used to measure the effects of recommendations in online assisted purchase. The 19 independent variables used in these studies were related to characteristics of the recommendation agent, user characteristics or vendor characteristics. Results also showed that the field still lacks confirmatory studies capable of creating a greater assurance for the knowledge already developed in the field.um período de cerca de 20 anos. Sua utilização atualmente é estudada na pesquisa acadêmica a partir de duas diferentes abordagens. A primeira se destina à resolução de problemas computacionais relacionados à geração de recomendações acuradas. A segunda tem como intuito entender como a interação do usuário com agentes de recomendação pode alterar seu comportamento de compra online. Usando um método bibliométrico e cientométrico, este estudo buscou os artigos, autores e publicações mais influentes no campo de pesquisa comportamental. Isto significa que apenas artigos que investigaram aspectos comportamentais do uso de recomendações foram considerados. Os artigos identificados foram também analisados em termos de sua metodologia, variáveis e repercussão. A maioria dos estudos se tratavam de investigações empíricas usando metodologia experimental, entretanto os artigos teóricos se demonstraram mais influentes. Também foi possível identificar 29 variáveis dependentes usadas para medir os efeitos das recomendações em compras online assistidas. As 19 variáveis independentes usadas nesses estudos estavam relacionadas com características do agente de recomendação, características do usuário ou características do vendedor. Os resultados também demonstraram que o campo ainda carece de estudos confirmatórios capazes de criar mais certeza para o conhecimento já desenvolvido na área

Examining the role of online motivations in consumer online shopping intention using technology acceptance model

Electronic commerce sales continue rising due to Internet growth. However, online retailers may not be doing enough to promote their products causing them to forego potential profits. Understanding the impact of motivational factors on consumer intention to shop online will enable online retailers to design effective ebusiness strategy that engage users, leading to additional purchases. In this study, the researcher modified the Technology Acceptance Model (TAM) to reflect the impact of some online motivational factors in online shopping. The TAM posits perceived ease of use (PEOU) and perceived usefulness (PU) contribute to an individual‘s behavioral intention. Research has shown motivational factors have the ability to influence PEOU and PU. Although many studies have used the model to better understand e-commerce, the problem is that they have ignored some important external variables. This study adopted a quantitative research methodology using surveys to collect research data from survey subject. A structural equation modeling software (Analysis of Moment Structures or AMOS) was applied to examine the direct and mediating effects hypotheses. The analysis of the data has supported some purposed relationships. It was found that convenience, social media, and personalization positively influence to consumer perceived usefulness of online shopping, and consumer intention to shop online. Moreover, perceived enjoyment positively influences to consumer intention to shop online, and website attributes positively affects perceived ease of use of online shopping. While, results failed to support relationships between the information density and consumer intention to shop online. This research makes several theoretical contributions and provides further insights on the effects of online shopping motivations on consumer behavior particularly in Malaysia. Methodological and practical implications were discussed and several potential avenues for future research were identified and proposed. Generally, this study improves our knowledge on what factors drive consumers to shop online, how they work, and what their implications are for customers and online retailers

Effects of recommendations on decision effort for consumers’ choice

Intelligent systems have been used in electronic commerce for the purpose of personalization. They are intended to tailor product offers, recommendations and even the whole website design to specific users needs and characteristics. Such personalization features are supposed to facilitate decision making process, make internet browsing easier and give the Internet users a sense of social feeling and individualization in their online activity. The present dissertation thesis is the result of an experimental research addressed to test the effects, over time, of recommendations generated by implicit elicitation methods. For that, an experimental website was created, where 189 participants completed a series of five purchase tasks with an interval of one week between each task. Results indicated that recommendations do not have a significant effect on decision effort during initial interactions, but after the second interaction, there is an observable effect of recommendations on time to make a decision. On average, time to make a decision was 21.4% lower for subjects in a test group when compared to the control group. The presence of recommendations generated by implicit elicitation methods at the website was also tested as a moderator of the relationship between involvement with the purchase task and decision effort. It was possible to observe that an analysis considering involvement with the task, presence/absence of recommendations and familiarity with the website these variables interacted in a moderated moderation model capable of explaining 40.25% of the variance of the dependent variable. This moderating effect, however, proved to be significant only after the third purchase took place. Additionally, results demonstrated that recommendation acceptance was not related to effort reduction, what led to the conclusion that recommendations may not be influencing consumers’ choices, but being used as frames of reference that provide parameters for decision making. That was also verified by looking at the variance in the purchase choices between people who executed purchases with recommendations when compared to the control group. Results suggest that recommendations can be important aids to reduce consumer effort, but their influence will only be effective after consumers are familiarized with the website. E-commerce companies can benefit from such information by adapting the way they manage and present recommendations to their visitors.Sistemas inteligentes têm sido usados no comércio eletrônico como ferramentas de personalização. Eles são destinados a criar ofertas individualizadas de produtos, recomendações direcionadas e até mesmo modificar o design do website para atender a características específicas de usuários. Tais possibilidades de personalização têm o intuito de facilitar o processo de tomada de decisão, melhorar a navegação e fornecer aos usuários da Internet uma sensação de contato social e de individualização em suas atividades online. A presente tese é o resultado de uma pesquisa experimental destinada a testar os efeitos, ao longo do tempo, de recomendações geradas por meio de métodos implícitos de elicitação de preferências. Para isso, foi criado um website experimental, no qual 189 participantes completaram um série de cinco tarefas de compras com um intervalo de uma semana entre cada tarefa. Os resultados foram analisados a partir da técnica do modelo das trajetórias latentes. Foi possível identificar, a partir disso, que recomendações não têm um efeito significativo no esforço para tomada de decisão nas interações iniciais, mas depois da segunda interação, há uma influência observável da presença de recomendações no tempo utilizado para a tomada de decisão. Em média, tempo para a tomada de decisão foi 21,4% menor para sujeitos no grupo teste quando comparados com o grupo controle. Procurando desvendar os mecanismos através dos quais as recomendações geram a redução no esforço para a tomada de decisão ao longo do tempo, uma análise de moderação foi realizada, incluindo-se como variáveis o envolvimento com a tarefa de compras e a familiaridade com o website, medida a partir do número de interações de compras. Com base nisso, considerou-se que o modelo mais adequado para testar a interação da presença de recomendações geradas por métodos implícitos de elicitação das preferências no website seria analisá-la como um moderador da relação entre envolvimento com a tarefa de compras e esforço para a tomada de decisão. Foi possível observar que em uma análise incluindo envolvimento com a tarefa, presença/ ausência de recomendações e familiaridade com o website estas variáveis interagiram entre si em um modelo de moderação moderada, capaz de explicar 40,25% da variância na variável dependente. Este efeito moderador, entretanto, somente demonstrou ser significativo depois da terceira compra simulada. Adicionalmente, os resultados indicaram que a aceitação da recomendação não estava relacionada com a redução no esforço para a tomada de decisão, o que levou à conclusão de que recomendações podem não estar influenciando as escolhas dos consumidores diretamente, mas sendo usadas como pontos de referência que fornecem parâmetros para a tomada de decisão. Isso foi também verificado ao analisar a variância nas escolhas de compras entre os sujeitos que executaram compras com recomendações e os sujeitos no grupo de controle. Os resultados sugerem que as recomendações podem fornecer auxílio importante para a redução do esforço do consumidor na tomada de decisão, mas sua influência se torna efetiva apenas depois que os consumidores estão familiarizados com o website. As companhias de e-comerce podem se beneficiar com tais informações adaptando a maneira com a qual gerenciam e apresentam recomendações aos seus vistantes

Análisis y modelización de la adoptación de los sistemas de recomendación en el comercio electrónico

404 páginasTesis doctoral (Lectura 07/02/2013). Director: Francisco José Martínez López (Universidad de Granada). Tribunal: Martínez López, Francisco José, Univ. de Huelva, presidente; Padilla Meléndez, Antonio (secretario); Ortigueira Sánchez, Manuel (vocal); Luna Huertas, Paula (vocal); García Ordaz, María Mercedes (vocal). Se puede afirmar que la historia de las relaciones entre los individuos y las organizaciones se divide en dos, antes y después de la aparición de Internet, la penetración de los PC y de la banda ancha. En el campo organizacional, las Tecnologías de la Información y las Comunicaciones (TIC), se refieren al amplio espectro de tecnologías de base de los Sistemas de Información, y que se constituye en un importante recurso, que facilita la continua adaptación del Sistema de Información a los cambios internos y del entorno. La aplicación de los sistemas de información a las actividades organizacionales, caso concreto que nos interesa, el marketing, se constituye en una herramienta para que la empresa se mantenga competitiva en el mercado. Las relaciones de intercambio desarrolladas en los mercados electrónicos posibilitan la comunicación bidireccional entre las partes y entre cada una de ellas y el propio medio, exigiendo a las organizaciones implementar un marketing interactivo en términos de producto, precio, distribución y comunicación, en el que consumidor dirija el proceso de intercambio. El desarrollo del comercio en los mercados electrónicos y las aplicaciones de los sistemas de información al marketing, han tomado características del comercio tradicional y han sido adaptadas al electrónico, caso específico la adaptación que han realizado una gran cantidad de empresas comerciales en la Web a las recomendaciones a sus usuarios a través de los sistemas de recomendación (RS), entendidos como sistemas que realizan recomendaciones de productos que están buscando, o basadas en sus gustos o preferencias. Este es tema central de este trabajo, pero no enfocado a su parte técnica, sino a la comprensión de los factores que explican el comportamiento online de los consumidores frente a los RS de determinada website (WS), por lo que se propone un modelo teórico, sustentado por once hipótesis principales y otras subordinadas, la cuales son el resultado de la integración reflexiva de la Teoría de la Acción Razonada, de la adaptación Trust-TAM y de la Teoría del Comportamiento Planeado. Del análisis y corroboración del modelo, se puede concluir que el proceso de adopción del sistema de recomendación de cierto website se conforma sobre la base que a) el usuario percibe la opinión de otros con respecto al uso de los sistemas de recomendación en general y del particular de un determinado website; b) el grado de confianza que le merece al consumidor la interacción e información proporcionada por el sistema de recomendación; c) la percepción de utilidad de uso del sistema de recomendación que tiene su usuario; y d)la actitud del individuo hacia el sistema de recomendación de un website particular

Evaluating e-business models for the UK and Malaysian companies.

Despite the benefits offered by e-business, there is a lack of indication that its functionality is being widely harnessed in practice. Research evidence suggests that the fear of lagging behind in adopting the technology (Internet) has rushed many firms to blindly engage in e-business initiatives without deriving much benefit. In addition, firms are facing technical, managerial, and cultural issues while adopting e-business strategies in business, which has resulted in failing to appreciate its potential benefits. In addition, most of the research on e-business depends heavily on qualitative methods such as case studies and anecdotes suggesting a weak connection between theory and measures. This thesis is inspired by the perceived lack of theory and empirical data to guide and characterise the internet-based initiatives and gauge the scale of their impact on firm performance. It seeks to better understand and utilise the factors that contribute to the success of e-business implementation. Building upon e-business literature, an E-Business Capability (EBC) framework is developed. A questionnaire is designed and data from 143 UK and 208 Malaysian firms is collected to empirically test the model using structural equation modelling (SEM) approach. More specifically, a set of twenty empirical models are tested to ascertain the validity and impact of e-business capability factors (EBC) on business performance. Results from the analyses have revealed that the proposed factors (business strategy, supply chain strategy and e-business adoption) embedded with "technological", "organisational" and "people" (TOP) dimensions, play a significant role in influencing e-business to be implemented successfully in multiple industry sectors. In addition, this study also seeks to add an international dimension to this debate by investigating the influence of EBC factors in the context of developed (UK) and developing (Malaysian) countries.The results of this study show that the proposed conceptual model is able to provide an efficient framework to assess the firm's readiness for Internet adoption in the hope of reaping the e-business benefits. This theoretical framework has included a number of e-business requirements that need to be taken into consideration within the firm. These specific indicators are able to measure the readiness of a firm for emerging e-business. In addition, these indicators also allow managers to identify which of the factors lack strategic implementation when considering e-business adoption. Therefore, managers are able to evaluate the readiness for current and future e-business development within their firms and how they must enhance "technology" "organisation" and "technology" dimensions within each of the EBC factors to improve e-business performance. This study is able to guide researchers in how an empirical study may be conducted based on the theoretical foundations in the e-business implementation domain. For practitioners, this study offers a useful framework to assess the "technological" conditions incorporated into each of the EBC factors to leverage e-business initiatives and pursue better e-business performance

An integrated framework for recommendation systems in e-commerce

[[abstract]]The Internet has become a popular medium for information exchange and knowledge delivery. Several traditional social activities have moved to the Internet, such as distance learning, tele‐medical system and. traditional buying and selling activities. Online merchants must know what users want, so providing recommendation services is an important strategy. Analyzes users’ on‐line behavior and interests, and recommends to them new or potential products. The analysis mechanism is based on the correlation among customers, product items, and product features. An algorithm is developed to classify users into groups and the recommendation is based on the classification. The system can help merchants to make suitable business decisions and provide personalized information to the customers. A generic mobile agent framework for e‐commerce applications is proposed. The aforementioned collaborative computing architecture for the recommendation system is based on the framework.[[notice]]補正完