What makes Internet users visit cyber stores again? key design factors for customer loyalty

Lee, Jung Won; Kim, Jin-Woo; Moon, Jae Yun

doi:10.1145/332040.332448

Cited by 108 publications

(76 citation statements)

References 16 publications

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“…Moreover, the few existing proposals of strategies usually base on generating a new pseudonym for each new transaction, what is known as transaction pseudonyms [9]. However, vendors usually try to avoid this kind of strategies by means of different approaches to achieve customer loyalty such as price discounts, allotment of points that can be used for future purchases, and so on [31].…”

Section: Related Workmentioning

confidence: 99%

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Strategies for avoiding preference profiling in agent-based e-commerce environments

et al. 2013

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Agent-based electronic commerce is known to offer many advantages to users. However, very few studies have been devoted to deal with privacy issues in this domain. Nowadays, privacy is of great concern and preserving users' privacy plays a crucial role to promote their trust in agent-based technologies. In this paper, we focus on preference profiling, which is a wellknown threat to users' privacy. Specifically, we review strategies for customers' agents to prevent seller agents from obtaining accurate preference profiles of the former group by using data mining techniques. We experimentally show the efficacy of each of these strategies and discuss their suitability in different situations. Our experimental results show that customers can improve their privacy notably with these strategies.

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Section: Related Workmentioning

confidence: 99%

“…Vendors usually try to avoid this strategy. They usually conduct different approaches to achieve customer loyalty such as price discounts, allotment of points that can be used for future purchases, and so on [31]. Therefore, customers may be interested in strategies between Unique Pseudonym and Pseudonym per negotiation.…”

Section: Pseudonym Per Negotiationmentioning

confidence: 99%

Strategies for avoiding preference profiling in agent-based e-commerce environments

et al. 2013

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“…44 In particular, studies on product involvement reveal that the product involvement level is related to online purchase intentions 45 and to the relative importance of factors affecting e-customers loyalty. 46 All the above studies focus on online customers and do not investigate the role of product characteristics (for example, involvement) from the retailers ' perspective. Although the extant literature shows that product involvement provides important implications for strategy development (for example, advertising strategies 47 ), no empirical evidence exists regarding internet marketing strategies.…”

Section: Websites Of Low-high Product Involvementmentioning

confidence: 99%

Tracing customer orientation and marketing capabilities through retailers’ websites: A strategic approach to internet marketing

Tsiotsou

Rigopoulou²,

Kehagias³

2010

J Target Meas Anal Mark

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The study extends the concepts of customer orientation and marketing capabilities to an online retailing context while it examines the ability of product involvement to distinguish retailers ' websites. The objectives of this article are: (a) to identify the degree of customer orientation as manifested on retailers ' websites, (b) to investigate the marketing capabilities revealed through their websites and (c) to examine the role of involvement as a differentiating factor in an online context. A twofold methodological approach was taken by employing content analysis and concept mapping. The results indicate that a certain degree of customer orientation and marketing capabilities are revealed through retailers ' websites while the above constructs can be used to identify distinct website groups. Moreover, the degree of customer orientation and marketing capabilities as refl ected on these websites differ signifi cantly between product categories of high and low involvement. Managerial implications for managing websites ' customer orientation and marketing capabilities are discussed.

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“…exhibit customer loyalty), Lee, Kim and Moon (2000) found that trust was a function of three factors: (i) the comprehensiveness of the information given out to customers; (ii) the perception of shared values between the customer and the store and (iii) the quality of communication between the store and the customer. …”

Section: Stage 3: Subsequent Relationship Developmentmentioning

confidence: 99%

Personalisation and Trust: A Reciprocal Relationship?

Briggs

Simpson

Angeli

2004

Designing Personalized User Experiences in eCommerce

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What makes Internet users visit cyber stores again? key design factors for customer loyalty

Cited by 108 publications

References 16 publications

Strategies for avoiding preference profiling in agent-based e-commerce environments

Strategies for avoiding preference profiling in agent-based e-commerce environments

Tracing customer orientation and marketing capabilities through retailers’ websites: A strategic approach to internet marketing

Personalisation and Trust: A Reciprocal Relationship?

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