You Never Get a Second Chance to Make a First Impression

Knowledge about users’ expectations and mental models is a key aspect of interface development. By meeting users’ expectations, errors may be prevented and interaction quality enhanced. In the case of online shops, this means that it is crucial to know where users expect to find the most common Web objects such as the search field, shopping cart, or navigation. In this chapter, we show how users’ mental models of an online shop can be analyzed and validated empirically. The resulting model shows where users typically expect to find the most common Web objects within an online store. This knowledge can be used to improve the first impression, orientation, and usability of your website.

Customer Acceptance of a New Interactive Information Terminal in Grocery Retailing

This chapter uses an extended version of the Technology Acceptance Model to analyze the customer acceptance of a new interactive information terminal for cooking recipes aimed at grocery shoppers. The results show that perceived usefulness, perceived ease of use, and perceived enjoyment influence the customer acceptance of the terminal via direct and indirect effects. Furthermore, the impact of these variables depends on individual differences in experience of Information Technology and the relevance of the information content. These findings carry several management and research implications.

From User Cognition to User Interaction Modalities in Consumer Behaviour

Information and Communication Technology (ICT) has revolutionized science and commerce and has increased the innovation and the spread of a variety of virtual environments applications. These innovations are the result of the both technological development and cognitive studies. The chapter aims to underline the relationships between Human-Computer Interaction (HCI) and consumer behaviour, focusing the attention on the 3-D virtual environments dedicated to electronic and Internet e-commerce (e-retail) services. We introduce how the 3-D interfaces can contribute to the successful impact of online retail. The importance of the relationship between customer and system concerns the effective potentiality of the user interface. If a user interface is ineffective, the system’s functionalities and usefulness will be limited and the users will be confused, frustrated, and annoyed, and therefore less likely to use the system again. Finally, we aim to outline the cognitive and technological aspects involved in the communication process between user and virtual e-retail system interface and directions for possible future research.

Recommendations to Buy in Online Retailing and Their Acceptance

Personal welcomings, individual assistance, as well as recommendations to inform and buy are becoming an integral part in online retailing. These new so-called personalization elements are assumed to increase the retailer’s share of wallet and the customer’s satisfaction. However, up to now only little is known about which external factors influence the customer’s acceptance of such personalization elements. This chapter discusses the forms of recommendations to buy and how their acceptance can be measured using the well-known Technology Acceptance Model (TAM) approach. An experiment is used, where volunteers are offered an online shopping experience with individually generated recommendations to buy. The experiment shows how high the acceptance of the generated recommendations is and how close this acceptance is connected to the quality and shopping relevance of the recommendations. Even though the results are limited to the specific recommendation types used, they give important implications for an adequate design of modern online shops.

Customer Intelligence as the Powerful Means for Turning Information into Profit

Increasing competition and decreasing customer loyalty forced retailers to obtain accurate information about customers’ existing and future needs, their profitability, behaviour, and trends in purchasing. Due to the rapid advancement in technology, retailers have easy access to vast amounts of information about their customers. They can collect and manage customer data and understand their behaviour patterns. The main purpose of the Customer Intelligence is to provide insight into customer’s needs, attitudes, and behaviors towards particular retailer, and all elements of its business as well. In such a way, the retailer is able to build deeper and more effective customer relationships and to improve company’s strategic decision. This chapter focuses on different aspects of Customer Intelligence and the growing interest and importance for its implementation in the praxis. Moreover, the chapter is trying to clarify some misunderstandings of the concept. The study conducted among retail companies dealing with ICT equipment and services on the Croatian market pointed out that Customer Intelligence provided retailers with a successful decrease of the rate of customer defection and a increase in revenues generated by customers.

Factors Affecting WiFi Use Intention

Wireless communications are here to stay; nevertheless, a number of individuals are still reluctant to use them for accessing the Web. This urges providers to better understand the concerns of consumers in order to better position the products and services in the market and to reduce the barriers that consumers may have in using WiFi – Wireless Fidelity Internet technologies. The present quantitative study was carried out for the purpose of assessing the effect of a number of constructs, identified in the past to affect the use of IT and WiFi use intention, as well as identifying the underlying factor structure of these constructs. It further aimed to assessing the overall attitudes and behavior of consumers towards WiFi use, as well as identifying and comparing WiFi users and non-users’ overall behavior towards WiFi use and their perceptions of factors determining WiFi adoption.

Mobile Purchase Decision Support Systems for In-Store Shopping Environments

Purchase decision-making is influenced by product information available in online or in-store shopping environments. In online shopping environments, the use of decision support systems increases the value of product information as information becomes adaptive and thus more relevant to consumers’ information needs. Correspondingly, mobile purchase decision support systems (MP-DSSs) may also increase the value of product information in in-store shopping environments. In this chapter, we investigate the use of a MP-DSS that is bound to a physical product. Based on Theory of Planned Behaviour, Innovation Diffusion Theory, and Technology Acceptance Model, we propose and evaluate a model to better understand MP-DSSs. Results indicate that perceived usefulness influences product purchases and predicts usage intentions and store preferences of consumers. We therefore discuss new business models for retail stores in which MP-DSSs satisfy both the information needs of consumers and the communication needs of retailers.

The Design of an Advanced Virtual Shopping Assistant for Improving Consumer Experience

The aim of this chapter is to propose the design of an anthropomorphic Virtual Shopping Assistant (VSA), endowed with an advanced system, to be used in the context of an innovative technologically based in-store service. The VSA is able to provide information based on a knowledge management system. It is based on the perceived best human typical seller’s characteristics, as well as on the results of psychological studies on consumers’ perception of virtual characters. In particular, its interface is anthropomorphic, and thus capable of displaying emotions. This VSA can be used as a mobile application or installed in stores.

Modeling Shopper Responses to Retail Digital Signage

In addition to the obvious application to retailers in improving business-to-consumer appeal to shoppers the findings are of use to suppliers of digital signage in business-to-business marketing of their systems to retailers.

The Evolution Tornado Retail

No attention at all was paid to the evaluation of philosophies offered by the steady upgrade of retail-technologies. While the period 1970/80 was still the push period, when the consumer industry wanted to push the penetration of its products the outlet was the “point of sales” (POS); in the 90ies due to ECR the outlet was rediscovered as the “point of purchase” (POP) with the buying decision and shelf-optimization as a central point; in the last decade big players like WalMart, ALDI, REWE pushed their outlets to be the “point of differentiation” (POD) to gain a Unique Sales Position (USP) in the market. The next big “technological jump forward” will be the intertwining of Facebook, YouTube, and Twitter with new media of retailers. Consumers can gain much more impact onto the listing of products, onto services within a store. It might be the time when the outlets become a “point of consumers” (POC) again.