The Effect of Product Type on Consumer Preferences for Website Content Elements: An Empirical Study

This study attempts to demonstrate empirically how the importance of website content in online purchasing varies across 2 product categorizations: goods versus services and hedonic versus utilitarian products. We conducted an experiment that showed that when purchasing services, customers value evaluative elements and risk‐reducing content, while consumers buying goods may be satisfied with fewer features. In addition, selling hedonic products could be more effective when focusing on large and unique assortment. Websites selling utilitarian products, on the other hand, may profit from investing in instrumental website content. The study validates the guiding role of product type in website design, and suggests that incorporating product tactics into design likely contributes to the development of websites tailored to specific consumer groups.     

Click trading: A case study of Moneynet

Moneynet, launched in 1997, was the United Kingdom’s first comparison website in financial services. It enables its users to specify their needs and then select from suitable product providers, who in turn benefit from potential customers with refined needs.This article makes both a theoretical and applied contribution to the Information Systems literature. It develops an amended version of the Porter value chain, which it terms the click chain, as a theoretical framework which is then used to analyse Moneynet. This framework analyses how Moneynet creates value and in doing so identifies key implications for comparison websites and product providers.     

Determining the performance of website-based relationship marketing

Company websites are an important instrument for relationship marketing activities. We present a methodological framework that aligns website performance assessment and marketing intelligence for evaluating the performance of relationship marketing activities. In this context, we develop an extended web mining approach that integrates managerial perspectives in the analyst’s investigation of the customer-website interaction based on historical clickstream data.This approach enables quantification of the moderating effect of a website’s structure and content regarding website-based relationship marketing. The applicability of our approach is demonstrated by clickstream data of 477,471 visitor sessions on a software developer’s website. The results provide detailed insights into the usage behavior on a website and the mechanisms to enhance e-commerce efficiency via website optimization.     

Defining qualitative assessing parameters of Iran banks website

The present research aims to provide list of qualitative parameters of bank websites in Iran in order to provide a pattern for designing bank web services and assess the extent of the banks’ success in obtaining qualitative necessities and on-line customer-orientation. According to the other researchers’ findings, websites qualitative parameters are categorized into four groups: efficiency, reliability, attractiveness, and responsibility. Delphi technique is the methodology employed in order to analyze the degree of these factors in Iranian electronic banking users. All the four above-mentioned factors, as the websites qualitative parameters, were true about Iran banks, too. Nevertheless, there was no agreement of the way of attracting the customers to security issues. Iranian banks can set these parameters as their pattern in order to reduce the expenses of lost opportunities and improve the quality of their own website services. Qualitative parameters obtained from the results of this research suggest priorities for designing Iranian banking websites. These factors can be considered as the indexes in assessing the degree of success in providing the customers’ needs.     

The influence of web aesthetics on customers’ PAD

One key focus of an online retail website is to enhance the consumers’ online shopping behavior. Based on the Stimulus-Organism-Response (S-O-R) framework and pleasure, arousal, and dominance (PAD) emotional model, we investigated the relationship between consumers’ emotional model and purchase behavior from the perspective of web aesthetics, and how web aesthetics affect their purchase behaviors through the emotional model. Using 441 questionnaire responses and structural equation modeling, we verified that both aesthetic formality and aesthetic appeal influence purchase behaviors through the emotional model. In the emotional model, web aesthetics have significant and positive influences on control, which is composed of behavior control, cognitive control, and decisional control. Control indirectly influences pleasure through the mediations of energetic arousal and tense arousal. Additionally, pleasure and searching on other websites positively influences purchasing behavior. The aim of this study was to provide practical recommendations in the establishment of a pattern of web aesthetics that influence consumers’ emotions.     

Is paid search overrated? When bricks-and-mortar-only retailers should not use paid search

While bricks-and-mortar-only retailers do not offer online purchasing, they often take advantage of multi-channel management strategies to reach consumers in a pre-purchase phase. We investigate whether paid search can increase the sales of brick-and-mortar retailers who promote their offers via an informational website. Although a sizeable one third of all retailers still trade without an online-shop, previous work has been silent about the effects of paid search for them. We make use of a randomized field experiment and an end-to-end tracking mechanism to investigate the cross-channel behavior of individual consumers. Our empirical results suggest that, whilst paid search increases the number of potential customers through enhancing the reach of marketing initiatives, store sales are not increased. We conclude that customers who search online to buy offline primarily use paid search as a navigational shortcut to the retailer’s website. Consequently, bricks-and-mortar-only retailers seeking to increase store purchases should approach paid search with caution.     

An anticipation model of potential customers’ purchasing behavior based on clustering analysis and association rules analysis

This paper proposes an anticipation model of potential customers’ purchasing behavior. This model is inferred from past purchasing behavior of loyal customers and the web server log files of loyal and potential customers by means of clustering analysis and association rules analysis. Clustering analysis collects key characteristics of loyal customers’ personal information; these are used to locate other potential customers. Association rules analysis extracts knowledge of loyal customers’ purchasing behavior, which is used to detect potential customers’ near-future interest in a star product. Despite using offline analysis to filter out potential customers based on loyal customers’ personal information and generate rules of loyal customers’ click streams based on loyal customers’ web log data, an online analysis which observes potential customers’ web logs and compares it with loyal customers’ click stream rules can more readily target potential customers who may be interested in the star products in the near future.     

Discovering recency,frequency, and monetary (RFM) sequential patterns from customers’ purchasing data

In response to the thriving development in electronic commerce (EC), many on-line retailers have developed Web-based information systems to handle enormous amounts of transactions on the Internet. These systems can automatically capture data on the browsing histories and purchasing records of individual customers. This capability has motivated the development of data-mining applications. Sequential pattern mining (SPM) is a useful data-mining method to discover customers’ purchasing patterns over time. We incorporate the recency, frequency, and monetary (RFM) concept presented in the marketing literature to define the RFM sequential pattern and develop a novel algorithm for generating all RFM sequential patterns from customers’ purchasing data. Using the algorithm, we propose a pattern segmentation framework to generate valuable information on customer purchasing behavior for managerial decision-making. Extensive experiments are carried out, using synthetic datasets and a transactional dataset collected by a retail chain in Taiwan, to evaluate the proposed algorithm and empirically demonstrate the benefits of using RFM sequential patterns in analyzing customers’ purchasing data.     

Characteristics of online group-buying website and consumers intention to revisit: the moderating effects of visit channels

Online group-buying (OGB) is a relatively new market, but has attracted much academic attention. Under intensive competition, it is essential for OGB websites to maintain customers’ revisit. This paper identified three context-specific characteristics of an OGB website and investigated the impact of these features on customers’ revisit intention. Furthermore, the effects of these features were proposed to vary among different visit channels. A theoretical model was developed and tested based on 258 valid responses collected through an online survey. The results indicated the distinct effects of OGB features and supported the contingent impact of visit channels. Specifically, timeliness and inconsistency had stronger negative influence on revisit intention for indirect visitors, while the effect of richness is significant for both the direct and indirect visitors.     

Multi-faceted quality and defect measurement for web software and source contents

In this paper, we examine external failures and internal faults traceable to web software and source contents. We develop related defect and quality measurements based on different perspectives of customers, users, information or service hosts, maintainers, developers, integrators, and managers. These measurements can help web information and service providers with their quality assessment and improvement activities to meet the quality expectations of their customers and users. The different usages of our measurement framework by different stakeholders of web sites and web applications are also outlined and discussed. The data sources include existing web server logs and statistics reports, defect repositories from web application development and maintenance activities, and source files. We applied our approach to four diverse websites: one educational website, one open source software project website, one online catalog showroom for a small company, and one e-Commerce website for a large company. The results demonstrated the viability and effectiveness of our approach.     

Beyond utilitarian factors: User experience and travel company website successes

Travel websites are extensively used by travelers for their travel bookings, yet little is known about the hedonic effectiveness of such experiences for the customer. The end users of these websites are customers who may not always be sophisticated information system (IS) users. Further, traditional utility based measures of customer evaluation are dated with respect to the interactive nature of the technology in use and the hedonic benefits that may result from the use of the technology. The evaluation of IS needs to include hedonic measures facilitated by the interactive technology in addition to the traditional utility based measures. We propose and test an evaluation model for retail travel websites that combines the traditional utility based measures with hedonic measures which collectively create a more comprehensive measure for the IS evaluation of consumer focused websites. Thus rooted in theory, the model extends DeLone and McLean’s model of IS Success by adding the construct of User Experience. The model was tested on a sample of 255 customers of travel websites targeted at the Indian market. The results indicate that both utility based and hedonic measures are important factors for customer IS (travel website in this study) evaluation. The larger implications for theory and practice of IS evaluation are explained.     

A motives framework of social media website use: A survey of young Americans

Social media is increasingly important in daily life and is an especially important social interaction mechanism for young people. Although research has been conducted evaluating user types based on motives for using social media, no such framework has been extended to social media websites. We extend previous research by evaluating the underlying structure of social media website usage motivations using a 13 item survey and evaluations from 19 different social media websites administered to 1686 young Americans. Using a multidimensional scaling approach, we uncover 2 major motive dimensions underlying social media website use: fun-related and content-specific. Based on the derived dimensions, we generate a graphical “quadrant” system for classifying social media websites and depict all 19 social media sites based on their quadrant. We propose that our quadrant system can be used by other researchers to further refine understanding of social media website usage motives.     

How a Retailer’s Website Quality Fosters Relationship Quality: The Mediating Effects of Parasocial Interaction and Psychological Distance

Due to strong economic growth in Internet development, the number of website users in Asian countries has increased dramatically. Online retailers such as Alibaba have been remarkably successful, but few research articles focus on the field of website usability and human–website interaction. As retailing websites become increasingly relational, consumers may tend to humanize brand personalities and develop a parasocial relationship with their favorite retail website. Based on the uses and gratification theory, this study empirically examined the effects of parasocial interaction and psychological distance in mediating the conceptual link between website quality and relationship quality in the context of a retailer’s website in China. The results showed that parasocial interaction and psychological distance are both full mediators between website quality and relationship quality. This research reveals that parasocial interaction can occur not only from interactions with brands but also between customers and a retail website. The findings support the value of using appropriate website strategies (e.g., web personification, design aesthetics, and usability) to build an intimate brand–customer relationship.     

Factors affecting female user information adoption: an empirical investigation on fashion shopping guide websites

With the prosperity of online shopping platforms, similar or even the same products tend to have a large variety of sources to be purchased from. More and more consumers seek the product information from online review websites before making a purchase, as they are willing to provide reviews or share their purchase experience. These behaviors turn the online review websites into vertical and community-based sales channels. Based on the Information Adoption Model, this study conducted an empirical investigation to analyze female users’ information adoption process when using fashion shopping guide website. The results show that information quality and source credibility have significant impact on information usefulness, which in turn contributes to information adoption. In addition, users with different levels of purchasing motivation demonstrate different dependence on information quality and source credibility.     

Understanding online customer repurchasing intention and the mediating role of trust – an empirical investigation in two developed countries

Although e-commerce adoption and customers’ initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers’ intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed.     

Understanding online purchase intentions: contributions from technology and trust perspectives

This paper explores factors that influence consumer's intentions to purchase online at an electronic commerce website. Specifically, we investigate online purchase intention using two different perspectives: a technology-oriented perspective and a trust-oriented perspective. We summarise and review the antecedents of online purchase intention that have been developed within these two perspectives. An empirical study in which the contributions of both perspectives are investigated is reported. We study the perceptions of 228 potential online shoppers regarding trust and technology and their attitudes and intentions to shop online at particular websites. In terms of relative contributions, we found that the trust-antecedent ‘perceived risk’ and the technology-antecedent ‘perceived ease-of-use’ directly influenced the attitude towards purchasing online.     

大型Web站点逻辑域挖掘算法

通过进一步发展Wen-Syan Li等人提出的Web站点逻辑域理论,该文提出Web站点逻辑域核模型及建立在其上的逻辑域挖掘算法。该算法通过对Web站点超链接的图结构进行运算,得到Web站点逻辑域。与Wen-Syan Li算法对比测试,结果表明在获得相同逻辑域个数的情况下,克服了其采用启发式方法所带来的效率问题。在对4个大型Web站点的单独测试中,平均能够达到85%的逻辑域挖掘精度。     

Optimal design of link structure for e-supermarket website

The objective of this research is to optimize the link structure of webpages for an e-supermarket. Customers are looking for greater convenience in shopping when they visit the website of an e-supermarket, while e-supermarket managers prefer webpages that contain information about profitable products to be visited more frequently. In order to balance the interests of both parties and to aid the webmaster in updating the website regularly, we present a mathematical model with the objective of minimizing the overall weighted distances between webpages. An updating algorithm is used to determine the distance between pages. It is proved to be more efficient under certain special circumstances. We propose the statistical Hopfield neural-network and the strategic oscillation-based tabu-search algorithms as solving methods. The former is appropriate for optimizing small-scale problems. The latter is good at solving large-scale problems approximately. The preliminary validity of the model and the performance of the algorithms is demonstrated by experiments on a small website and several large websites, using randomly generated data. The destination pages that customers and website managers preferred are proved to be more accessible after optimization.     

Fuzzy multiple-criteria decision making in the determination of critical criteria for assessing service quality of travel websites

Travel websites provide customers diverse services including travel information and products through the internet. More and more people are used to plan their itineraries and acquire travel information by visiting travel websites. In the face of the strong competition environment, in order to profit by making customers proceed with transactions on the websites, travel websites should pay more attention to the improve the electronic service quality (e-SQ). e-SQ evaluation for travel websites can be treated as a multiple-criteria decision making (MCDM) problem modeled by the given hierarchical structure. As for evaluating e-SQ, since the traditional Likert scales cannot deal with uncertain assessments according to human intuition for the service quality evaluation, the fuzzy number is employed to measure decision-makers’ subjective preference. This paper aims to develop a genetic-algorithm-based method to automatically determine the degrees of importance of respective criteria. Then, critical criteria for evaluating service quality can be easily identified. In the empirical study, four representative travel websites in Taiwan are selected to determine the critical criteria concerned by customers. The findings provide useful information to travel websites for improving e-SQ.