An Exploratory Study of Consumer Adoption of Online Shopping

An exploratory study was conducted to investigate consumer adoption of online purchase using a survey data set. Based upon the theory of innovation and self-efficacy theory, risk aversion, online proficiency, shopping convenience, and product choice variety were proposed to influence consumer intention to shop online, which, in turn, affects online purchases. Results of regression analyses revealed that all but shopping convenience were significant predictors of consumer intention to purchase online. In addition, consumer intention directly determines consumer purchases online. Finally, consumer intention to purchase online mediates the relationship of risk aversion, shopping convenience, and product choice variety to online shopping. Research and managerial implications of the findings were discussed.

The Next Generation of Shopbots

The huge growth of e-commerce has had a profound impact on users who can now choose from a vast number of options online. Inevitably, as the number of choices has increased, so has the need for tools to help users organize, manage and utilize information on these for better decision-making. Comparison shopping agents or shopbots can help users decide what to buy and enhance their online shopping experience. However, despite the high expectations, the immense potential of shopbots has not been fully realized. In this chapter, the author identifies the limitations and drawbacks of current shopbots, in particular, with regard to the underlying technology for building such systems. She then discusses how these technical limitations can be overcome by making use of the Semantic Web and Web Services. She also considers how shopbots can truly serve the user by providing personalized, impartial and flexible services.

Evolution of Web-Based Shopping Systems

This article offers a theoretical analysis of evolutionary processes in WBSS strategies. For that purpose, we propose a research model that shows strategy patterns. Based upon the model, we identified several types of strategies. In our research model, WBSS are classified into four types: (1) general-direct-sales (GDS); (2) general-intermediary-sales (GIS); (3) specialized-direct-sales (SDS); and (4) specializedintermediary- sales (SIS). On the basis of these four categories of WBSS, we analyze the characteristics of WBSS and suggest five evolution strategies for WBSS, which have implications for both theory and practice. Amazon.com’s strategic movements, such as product line expansion through alliance and acquisition, provide an exemplary case of the evolution of WBSS strategy. We expect that this research will serve as a guide for Internet businesses and as a catalyst for new research agendas relevant to Web-based shopping and electronic commerce.

Examining Online Purchase Intentions in B2C E-Commerce

Research on online shopping has taken three broad and divergent approaches viz, human-computer interaction, behavioral, and consumerist approaches to examine online consumer behavior. Assimilating these three approaches, this study proposes an integrated model of online shopping behavior, with four major antecedents influencing online purchase intent: Web site quality, customer concerns in online shopping, self-efficacy, and past online shopping experience. These antecedents were modeled as second-order constructs with subsuming first-order constituent factors. The model was tested using data from a questionnaire survey of 214 online shoppers. Statistical analyses using structural equation modeling was used to validate the model, and identify the relative importance of the key antecedents to online purchase intent. Past online shopping experience was found to have the strongest association with online purchase intent, followed by customer concerns, Web site quality, and computer self efficacy. The findings and their implications are discussed.

Comparison Shopping Behaviour in Online Environments

The aim of this chapter is to analyse antecedents of search engines use as prepurchase information tools. Firstly, there is a literature review of the factors influencing search engines use in online purchases. Then, there is an empirical analysis of a sample of 650 Spanish E-shoppers. Logistical regression is used to analyse the influence of demographics, surfing behaviour and purchase motivations on willingness to use search engines for E-shopping. Data analysis shows that experience as Internet user and as Internet shopper are negative key drivers of search engine use. Most of the utilitarian shopping motivations analyzed predict comparison shopping behaviour. Demographics are not determinant variables in the use of search engines in online purchases. This research enables companies to know the factors that potentially affect search engine use in E-shopping decisions and the importance of using search engines in their communication campaigns.

Comparison-Shopping Channel Selection by Small Online Vendors

Comparison-shopping is becoming the mainstream marketing channel for B2C ecommerce. More and more small online vendors are using shopbots to bring in customers. There are mainly two types of shopbots: those general shopbots that provide product comparison cross multiple heterogeneous product categories (like shopping.com) and the specialized shopbots that provide comparison within a single or a few highly-related product categories (like addall.com on books and music CD). The effectiveness of shopbot selection strategy by small online vendors is the focus on this paper. By analyzing data from shopbots and online vendors, the authors found there is significant positive correlation between the number of shopbots an online vendor participates and its traffic rank, which indicates the general effectiveness of using shopbots as a marketing channel. They also found that for online vendors competing on a niche product like college textbook, participating specialized shopbots brings in higher traffic. For competing in mainstream market, there is less significant correlation between participating general shopbots and higher traffic rank for vendors. They conclude that using general shopbots is a reactive strategy for small online vendors while using proper specialized shopbots could provide an edge for small online vendors.

Service Features, Customer Convenience, and Shopping Intention in the Context of Mobile Commerce

Technological advancements in Wireless communication and Internet capabilities are rapidly converging to provide an unprecedented level of convenience for online shopping. Despite much discussion regarding the unique capabilities of mobile commerce in supporting online shopping via unprecedented convenience, the relationship between mobile commerce service features and convenience perception remains an unanswered issue from both the vendor and customer points of view. Although the concept of consumer-perceived convenience has been extensively discussed in marketing and consumer behavior literature, in the context of mobile commerce, however, these discussions are subject to systematic validation with empirical data to be convincing. This study conducted a field survey to investigate how mobile commerce service features and customer perception of convenience are correlated. It also examined the effect of convenience on customers’ intention of shopping via their mobile communication devices. The primary data collected in Taiwan were used in the analysis. It was found the service features and customer convenience perceptions are significantly correlated. It also showed a significant relationship between the convenience perception and shopping intention. Further, there was a positive effect of convenience perception on shopping intention. The findings may have practical implications for mobile commerce strategists by providing more understanding of the mobile commerce success factors from a consumer behavior point of view.

Multi-Channel Retailing and Customer Satisfaction

Customer satisfaction/dissatisfaction can occur at/after the store, on the telephone, on the internet, after a catalog purchase. Customer satisfaction leads to repurchase/loyalty. Customer dissatisfaction leads to lower repurchase/loyalty. However, no research has looked at how satisfaction/dissatisfaction (S/D) in one channel affects the repurchase/loyalty in the same or different channels and the same/different stores. While S/D will increase/decrease the S/D in the same channel it does not always affect S/D in other channels the same way. In addition, S/D in a channel in one retailer may affect S/D in that same channel but in a different retailer.

How Good is Your Shopping Agent? Users' Perception Regarding Shopping Agents' Service Quality

The use of online shopping agents has increased dramatically in the last 10 years, as a result of e-commerce development. Despite the importance of these online applications, very few studies attempted to identify and analyse the main factors that influence the users’ perception regarding the service quality of online shopping agents, and consequently, the elements that determine the users’ choice of online shopping agents. The present study attempts to fill this literature gap, identifying on the basis of primary data analysis, the various circumstantial or personal factors that can determine the choice of a specific searching strategy and shopping agent.

Evaluation of Fuzzy Models to Support Online-Trust Assessment

Online trust is a critical element to the success of electronic commerce (e-commerce). Indeed it reduces the level of uncertainty that arises because of the lack of face-to-face interactions with vendors. In ecommerce purchaser-vendor interactions are subject to uncertainty, anonymity, and communication means reliability. This chapter discusses how some trust models have been developed to address these issues. Some models promote familiarity and competitiveness as part of the exercise of assessing online trust. This assessment uses fuzzy logic-based techniques.