How perceived cognitive needs fulfillment affect consumer attitudes toward the customized product: The moderating role of consumer knowledge

Voluntary participation in adaptive customization (AC) entails consumers’ own mental engagement that evokes perceptions of cognitive needs fulfillment (CNF). This study examined the effect of CNF perceived during the process of AC services on felt emotions and consumer attitudes toward the customized product, and the moderation role of consumer knowledge. A total of 327 Americans participated in an online survey after experiencing AC services at 3 actual retail websites. The results revealed the following: (a) Perceived CNF (competence and autonomy) increased positive felt emotions (pleasure and arousal); (b) out of the two emotions, felt pleasure (not arousal) significantly contributed to positive consumer attitudes toward the customized product; (c) subjective levels of consumer knowledge showed a partial moderating effect in the relationships between CNF and felt emotions, (d) but did not do so in the relationships between felt emotions and consumer attitudes toward the customized product.     

An experimental economics approach toward quantifying online privacy choices

The importance of personal privacy to Internet users has been extensively researched using a variety of survey techniques. The limitations of survey research are well-known and exist in part because there are no positive or negative consequences to responses provided by survey participants. Such limitations are the motivation for this work. Experimental economics is widely accepted by economists and others as an investigative technique that can provide measures of economic choice-making that are substantially more accurate than those provided by surveys. This paper describes our efforts at applying the techniques of experimental economics to provide a foundation for (a) estimating the values that consumers place on privacy and various forms of security (encryption, HIPAA, etc.) and for (b) quantifying user responses to changes in the Internet environment. The contribution of this study is a better understanding of individual decision-making in the context of benefits and costs of making private information available to Internet sites. Preliminary results from a series of pilot studies are consistent with optimizing behaviors, indicating that continued application of experimental economics techniques in the quantification of Internet user actions in privacy/security space will be illuminating. Our results show that Internet users place great value on security measures, both regulatory and technical, that make identity theft much less likely. Our Web-based experiments indicate that privacy- and security- enhancing protections are likely to be subject to moral hazard responses, as participants in our online experiments became more aggressive in their Internet usage with greater protection in place.

How to select search keywords for online advertising depending on consumer involvement: An empirical investigation

In paid search advertising on Internet, advertisers bid for specific keywords. Consumer involvement affects a consumer’s purchase intention. However, there has been no research on selecting keywords in paid search advertising depending on consumer involvement from the advertisers’ perspective. Our paper investigates the effects of several factors including impressions, click-through rate, conversion rate, the number of competitors and the quantity of online customer reviews on the performance of individual keywords. Our analysis shows that regardless of consumer involvement, the conversion rate and the number of reviews significantly affect to the performance of individual keywords but the click-through rate does not. In addition, the effects of impressions and the number of competitors partially exist depending on consumer involvement. This study provides managerial insights into paid search advertising and can give some assumptions in the theoretical modeling literature for allocating advertising budgets.     

Using online consumer reviews as a source for demographic recommendations: A case study using online travel reviews

Online consumer reviews play an important role in the decision to purchase services online, mainly due to the rich information source they provide to consumers in terms of evaluating “experience”-type products and services that can be booked using the Internet, with online travel services being a significant example. However, different types of travelers assess each quality indicator differently, depending on the type of travel they engage in, and not necessarily their cultural or age background (e.g. solo travelers, young couples with children etc.). In this study, we present architecture for a demographic recommendation system, based on a user-defined hierarchy of service quality indicator importance, and classification of traveler types. We use an algebraic approach to ascertain preferences from a large dataset that we obtained from the popular travel website Booking.com using a web crawler and compared with the customer-constructed preference matrix. Interestingly, the architecture of the evaluated recommendation system takes into account already defined demand characteristics of the hotels (such as the number of reviews of specific consumer types compared to the total number of reviews) in order to provide an example architecture for a recommendation system based on user-defined preference criteria.     

Internet-based e-shopping and consumer attitudes: an empirical study

This paper analyses consumer attitudes towards Internet-based e-shopping. It aims to provide a theoretically and empirically grounded initial reference position, against which later research can explore and interpret the effects of changes in variables representing consumer preferences and shifts in these preferences on the success or failure of B2C e-commerce over the Internet. Because of the opportunity to sample at the outset and of ceteris paribus conditions following from the tendency for other factors such as e-transactions cost to remain small and constant, Singapore data were employed. Regression analysis shows that the life content of products, transactions security, price, vendor quality, IT education and Internet usage significantly affect the initial willingness of Singaporeans to e-shop on the Internet. Generalising, we suggest that Internet-based B2C e-commerce can profitably be introduced or promoted along similar dimensions in socio-geographically and technologically similar situations.     

Internet-based e-banking and consumer attitudes: an empirical study

Consumer attitudes toward the usefulness of and willingness to use Internet e-retail banking were identified and measured. Our survey was undertaken in Singapore, because its geography and well-developed infrastructure implied similar and small physical- and tele-communication costs, thereby highlighting the differences between traditional and Internet-based retail banking upon the latter’s introduction. The data showed that expectations of accuracy, security, network speed, user-friendliness, user involvement and convenience were the most important quality attributes underlying perceived usefulness. Regression discovered that willingness to use depended significantly on the first five factors, allowing the interdependencies or marginal rates of substitution between them to be estimated. Our results draw attention to demand-side changes in explaining the recent slowdown in Internet e-retail banking, and may also be useful for development planning and marketing.     

Predicting consumer intentions to shop online: An empirical test of competing theories

The proliferation of commercial Web sites providing consumers with a new medium to purchase products and services has increased the importance of understanding the determinants of consumer intentions to shop online. This study compared the technology acceptance model and two variations of the theory of planned behavior to examine which model best helps to predict consumer intentions to shop online. Data were gathered from 297 Taiwanese customers of online bookstores, and structural equation modeling was used to compare the three models in terms of overall model fit, explanatory power and path significance. Decomposing the belief structures in the theory of planned behavior moderately increased explanatory power for behavioral intention. The results also indicate that the decomposed theory of planned behavior provides an improved method of predicting consumer intentions to shop online. Finally, the implications of this study are discussed.     

Predicting consumer intentions to shop online: An empirical test of competing theories

The proliferation of commercial Web sites providing consumers with a new medium to purchase products and services has increased the importance of understanding the determinants of consumer intentions to shop online. This study compared the technology acceptance model and two variations of the theory of planned behavior to examine which model best helps to predict consumer intentions to shop online. Data were gathered from 297 Taiwanese customers of online bookstores, and structural equation modeling was used to compare the three models in terms of overall model fit, explanatory power and path significance. Decomposing the belief structures in the theory of planned behavior moderately increased explanatory power for behavioral intention. The results also indicate that the decomposed theory of planned behavior provides an improved method of predicting consumer intentions to shop online. Finally, the implications of this study are discussed.     

Consumers rule: How consumer reviews influence perceived trustworthiness of online stores

Two studies examined the impact of online store reviews on consumer trust in online stores. Based on the warranting principle, it was proposed that consumer reviews are a more important cue for judging the trustworthiness of an online store than the overall reputation of the store (Experiment 1) or assurance seals (Experiment 2). The role of dispositional trust was also examined. In both experiments, consumer reviews turned out as the strongest predictor of trustworthiness judgments. Store reputation had no significant effect. In Experiment 1, there was a main effect of dispositional trust on perceived trustworthiness. In Experiment 2, dispositional trust moderated the effects of reviews and assurance seals. High trusters were more influenced by the reviews of other consumers; and only high trusters tended to be influenced by assurance seals. The results show that consumer reviews play an important role in consumer decision making, indicating that online consumer communities indeed empower consumers.     

An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM

To understand the first purchase mechanism in online shopping, this study established an integrated model of initial trust and TAM. According to the analysis results, initial trust beliefs were significantly influenced by initial trust bases such as company reputation, structural assurance, and trusting stance, and initial trust beliefs indirectly influenced the first purchase intention through consumer attitude. In TAM constructs, only perceived usefulness directly influenced the usage attitude of online shopping systems, then indirectly influenced the first purchase intention. These results imply that online consumers consider perceived ease of use as a basic requirement for system design. It was also found that there is a time cushion between the time of first purchase and the time of belief formation. On the whole, these results reinforced the theory that a relationship between belief (trust and perceived usefulness) and intention was better explained when it was mediated by attitude.     

How to improve safety under convergence using stable storage

We present a new method for avoiding false privileges with the aid of stable storage. The method is motivated by the commitment in database systems. The commit guarantees that a write operation to stable storage has successfully completed. Since programs are stored in stable storage in self-stabilization, we assume that the stable values are also free from any transient fault. They sometimes give us additional information on whether a state is faulty or not. Using the stable values, we can improve our previous weakly time-adaptive protocol. We analyze the efficiency and the safety of our method and compare it with previously proposed ones. Furthermore, we extend our method by keeping an old version of stable values and show its usefulness.     

Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust

The growing presence of online travel communities is leading to great developments in the travel industry. Grounded in the innovation diffusion theory (IDT) and the technology acceptance model (TAM), this paper seek to develop and empirically test a comprehensive framework to examine the antecedents of customers' intention to participate in online travel community. Using SEM to analyse the data collected from a sample of 495 members, the results indicate that innovation diffusion theory and TAM with trust provide an appropriate model for explaining consumers' intention to participate; this intention in turn has a positive influence on intention to purchase and positive WOM. Furthermore, religiosity plays an important role in understanding consumers' behavioural intention. The results offer important implications for online service provider and are likely to stimulate further research in the area of online travel community.     

Scores vs. stars: A regression discontinuity study of online consumer reviews

With the rising popularity of consumer reviews, the design of the review system becomes increasingly crucial for e-commerce platforms and online retailers in their business decision-makings. Though the relationship between consumer reviews and sales has been extensively studied, only few studies have been conducted on the effects of different review designs. In this paper, we collect detailed review data from Meituan.com, a popular Chinese shopping website, to examine the effects of numerical presentation of consumer reviews (detailed to one decimal place) and graphical presentation of consumer reviews (in half-stars) on sales. By using a regression discontinuity design, we find that while consumer review scores may affect sales positively, the star presentation can create negative, rather than positive, jumps at cutoffs. Consumers restrict their attention to a star category; therefore, the “best” sellers in a lower star category are better off than the “worst” sellers in a higher star category. The incentive for review manipulation is strongly reduced, which in the long run will create trust and confidence for the review system as well as the sellers. For those sellers that are just below the cutoffs, simply crossing over the cutoffs would not lead to higher sales. Instead, they will have to substantially improve their service quality to attract consumers.     

Recommendation agent impact on consumer online shopping: The Movie Magic case study

A simulated online shopping environment with a recommender system based on collaborative filtering data has been developed to empirically test the impact of recommendation agents in an online retail environment. The report provides some background for the most widely used types of recommender system based on collaborative filtering. The Movie Magic system developed for this study is described, as well as the experiment assessing the impact of such an agent on product promotion effectiveness, customer satisfaction with the website, and customer loyalty to the website. Finally, the report discusses the implications of the results for system developers and managers interested in using Intelligent Agent technology for enhancing e-commerce. By corroborating the proposed relationships between the use of the recommender agent and improved product promotion, customer satisfaction and loyalty, the results should aid online businesses in further understanding the benefits and limitations of using a recommender agent to support e-commerce.     

Effects of interaction richness on consumer attitudes and behavioral intentions in e-commerce: some experimental results

A variety of information and communication media have been employed to support the interaction of consumers with products and sales representatives in electronic-commerce (EC). But, the question of what impact those media have on consumers in EC has not been sufficiently addressed in the literature. The objective of this study is to investigate the effect of the richness of consumers’ interaction with products and with sales representatives on changes in their attitude towards and their intention to use business-to-consumer (B2C) EC. Controlled lab experiments were conducted using two types of products and multiple levels of interaction richness. The results show that interaction richness has positive impact on consumers’ attitude towards B2C EC. Additionally, the study finds that the impact is stronger in the case of purchasing a high-complexity product than a low-complexity product, and that consumers’ attitude change is positively related with their intention to use B2C EC. Differential effects on two facets of attitude, ease of use in accomplishing the tasks and usefulness were observed leading to interesting implications and future research directions.     

An experimental analysis of local minima to improve neighbourhood search

The paper reports the results from a number of experiments on local search algorithms applied to job shop scheduling problems. The main aim was to get insights into the structure of the underlying configuration space. We consider the disjunctive graph representation where the objective function of job shop scheduling is equal to the length of longest paths. In particular, we analyse the number of longest paths, and our computational experiments on benchmark problems provide evidence that in most cases optimal and near optimal solutions do have a small number of longest paths. For example, our best solutions have one to five longest paths only while the maximum number is about sixty longest paths. Based on this observation, we investigate a non-uniform neighbourhood for simulated annealing procedures that gives preference to transitions where a decrease of the number of longest paths is most likely. The results indicate that the non-uniform strategy performs better than uniform methods, i.e. the non-uniform approach has a potential to find better solutions within the same number of transition steps. For example, we obtain the new upper bound 886 on the 20×20 benchmark problem YN1.

Scope and purpose

The paper reports a number of experiments with local search algorithms applied to job shop scheduling (JSS). The JSS problem is defined as follows: Given a number of l jobs, the jobs have to be processed on m machines. Each job consists of a sequence of m tasks, i.e., each task of a job is assigned to a particular machine. The tasks have to be processed during an uninterrupted time period of a fixed length on a given machine. A schedule is an allocation of the tasks to time intervals on the machines and the aim is to find a schedule that minimises the overall completion time which is called the makespan. The scheduling problem is one of the hardest combinatorial optimization problems (cf. M.R. Garey, D.S. Johnson, SIAM J. Comput. 4(4) (1975) 397. Many methods have been proposed to find good approximations of optimum solutions to job shop scheduling problems; for an overview (see E.H.L. Aarts, Local Search in Combinatorial Optimization, Wiley, New York, 1998). In our paper, the main aim is to get insights into the structure of the underlying configuration space. We consider the disjunctive graph representation where the objective function of job shop scheduling is equal to the length of longest paths. In particular, we analyse the number of longest paths, and our computational experiments on benchmark problems provide evidence that in most cases optimal and near optimal solutions do have a small number of longest paths. For example, our best solutions have one to five longest paths only while the maximum number is about sixty longest paths. Based on this observation, we investigate a non-uniform neighbourhood for simulated annealing procedures that gives preference to transitions where a decrease of the number of longest paths is most likely. The results indicate that the non-uniform strategy performs better than uniform methods, i.e., the non-uniform approach has a potential to find better solutions within the same number of transition steps. For example, we obtain the new upper bound 886 on the 20×20 benchmark problem YN1.     

The effect of negative online consumer reviews on product attitude: An information processing view

Online consumer reviews provide product information and recommendations from the customer perspective. This study investigates the effects of negative online consumer reviews on consumer product attitude. In particular, it examines the proportion and quality of negative online consumer reviews from the perspective of information processing. The elaboration likelihood model is used to explain the persuasive effect of the proportion and quality depending on product involvement. A high proportion of negative online consumer reviews elicits a conformity effect. As the proportion of negative online consumer reviews increases, high-involvement consumers tend to conform to the perspective of reviewers, depending on the quality of the negative online consumer reviews; in contrast, low-involvement consumers tend to conform to the perspective of reviewers regardless of the quality of the negative online consumer reviews. The experiment in this study uses 248 college students in Korea. The proposed hypotheses are tested by three-way analysis of covariance.     

An empirical study using task assignment patterns to improve theaccuracy of software effort estimation

In most software development organizations, there is seldom a one-to-one mapping between software developers and development tasks. It is frequently necessary to concurrently assign individuals to multiple tasks and to assign more than one individual to work cooperatively on a single task. A principal goal in making such assignments should be to minimize the effort required to complete each task. But what impact does the manner in which developers are assigned to tasks have on the effort requirements? This paper identifies four task assignment factors: team size, concurrency, intensity, and fragmentation. These four factors are shown to improve the predictive ability of the well-known intermediate COCOMO cost estimation model. A parsimonious effort estimation model is also derived that utilizes a subset of the task assignment factors and unadjusted function points. For the data examined, this parsimonious model is shown to have goodness of fit and quality of estimation superior to that of the COCOMO model, while utilizing fewer cost factors     

How virtual community participation influences consumer loyalty intentions in online shopping contexts: an investigation of mediating factors

Extant studies generally recognise that virtual community building is an effective marketing programme for forging deep and enduring affective bonds with consumers. This study extends previous research by proposing and testing a model that investigates key mediating processes (via trust, satisfaction and identification) that underlie the relationship between virtual community participation and consumer loyalty intentions. The authors test the hypotheses using data obtained from three large online retailing stores. Virtual community participation significantly enhances loyalty intentions, through both social mechanisms (via community identification) and psychological mechanisms (via trust and satisfaction). Moreover, the findings provide insights into the complex relationship between the two mechanisms in online shopping settings. Community identification is a pivotal factor for enhancing customer loyalty intentions. The results advance understanding of the process by which virtual community building facilitates the development of business-to-consumer relationships in the computer-mediated environment. The authors discuss the managerial implications of the findings, as well as avenues for further research.     

Consumer attitudes towards Internet gambling: Perceptions of responsible gambling policies,consumer protection,and regulation of online gambling sites

There is an insufficient understanding of consumer attitudes towards Internet gambling, which contributes to difficulties in developing policies to encourage the use of regulated online gambling sites. This research aimed to generate knowledge about consumer attitudes towards online gambling, specifically concerning the issues of player protection, regulation, and responsible gambling. An online survey was completed by 10,838 online casino and poker players from 96 countries. Responsible gambling features were generally viewed positively, particularly by casino game players, those who chased losses, and younger adults. Over one-third of participants reported having experienced a dispute with an online gambling operator. Respondents reported high levels of mistrust and concerns regarding online gambling and confusion regarding the appropriate regulation of Internet gambling. Consumer attitudes play a significant role in driving behavior and must be considered if regulators and operators are to effectively encourage online gamblers to use regulated gambling sites that include consumer protection and harm minimization measures. The results suggest that responsible gambling features, such as the ability to set spending limits, should be implemented on Internet gambling sites to increase consumer trust and favorable attitudes towards online gambling operators, and reduce disputes associated with excessive gambling.