Factors That Enhance Consumer Trust in Human-Computer Interaction: An Examination of Interface Factors and Moderating Influences

The Internet coupled with agent technology presents a unique setting to examine consumer trust. Since the Internet is a relatively new, technically complex environment where human-computer interaction (HCI) is the basic communication modality, there is greater perception of risk facing consumers and hence a greater need for trust. In this dissertation, the notion of consumer trust was revisited and conceptually redefined adopting an integrative perspective. A critical test of trust theory revealed its cognitive (i.e., competence, information credibility), affective (i.e., benevolence), and intentional (i.e., trusting intention) constructs. The theoretical relationships among these trust constructs were confirmed through confirmatory factor analysis and structural equation modeling. The primary purpose of this dissertation was to investigate antecedent and moderating factors affecting consumer trust in HCI. This dissertation focused on interface-based antecedents of trust in the agent-assisted shopping context aiming at discovering potential interface strategies as a means to enhance consumer trust in the computer agent. The effects of certain interface design factors including face human-likeliness, script social presence, information richness, and price increase associated with upgrade recommendation by the computer agent were examined for their usefulness in enhancing the affective and cognitive bases for consumer trust. In addition, the role of individual difference factors and situational factors in moderating the relationship between specific types of computer interfaces and consumer trust perceptions was examined. Two experiments were conducted employing a computer agent, Agent John, which was created using MacroMedia Authorware. The results of the two experiments showed that certain interface factors including face and script could affect the affective trust perception. Information richness did not enhance consumers’ cognitive trust perceptions; instead, the percentage of price increase associated with Agent John’s upgrade recommendation affected individuals’ cognitive trust perceptions. Interestingly, the moderating influence of consumer personality (especially feminine orientation) on trust perceptions was significant. The consequences of enhanced consumer trust included increased conversion behavior, satisfaction and retention, and to a lesser extent, self-disclosure behavior. Finally, theoretical and managerial implications as well as future research directions were discussed

A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems

Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functionalities of the systems mentioned above. The objective of this paper is to define a process algebraic framework for the modeling of systems that use (i) trust and reputation to govern the interactions among nodes, and (ii) communication models characterized by a high level of adaptiveness and flexibility. Hence, we propose a formalism for verifying, through model checking techniques, the robustness of these systems with respect to the typical attacks conducted against webs of trust.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

On the motivating impact of price and online recommendations at the point of online purchase

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierDo online recommendations have the same motivating impact as price at the point of online purchase? The results (n = 268) of an conjoint study show that: (1) when the price is low or high relatively to market price, it has the strongest impact (positive and negative) on the likelihood of an online purchase of an mp3 player, (2) when the price is average to market price, online recommendation and price are equal in their impact at the point of online purchase, and, (3) the relative impact from price increases when online shopping frequencies increases. The implications these results give are that online retailers should be aware that online recommendations are not as influential as a good offer when consumers purchase electronics online. However, other customer recommendations have a stronger impact on novice online shoppers than towards those consumers that shop more frequently online

Honesty, social presence, and self-service in retail

Retail self-service checkouts (SCOs) can benefit consumers and retailers, providing control and autonomy to shoppers independent from staff. Recent research indicates that the lack of presence of staff may provide the opportunity for consumers to behave dishonestly. This study examined whether a social presence in the form of visual, humanlike SCO interface agents had an effect on dishonest user behaviour. Using a simulated SCO scenario, participants experienced various dilemmas in which they could financially benefit themselves undeservedly. We hypothesised that a humanlike social presence integrated within the checkout screen would receive more attention and result in fewer instances of dishonesty compared to a less humanlike agent. Our hypotheses were partially supported by the results. We conclude that companies adopting self-service technology may consider the implementation of social presence to support ethical consumer behaviour, but that more research is required to explore the mixed findings in the current study

Agent modelling of cluster formation processes in regional economic systems

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

A quantitative narrative on movement, disease and patch exploitation in nesting agent groups

Abstract Animal relocation data has recently become considerably more ubiquitous, finely structured (collection frequencies measured in minutes) and co-variate rich (physiology of individuals, environmental and landscape information, and accelerometer data). To better understand the impacts of ecological interactions, individual movement and disease on global change ecology, including wildlife management and conservation, it is important to have simulators that will provide demographic, movement, and epidemiology null models against which to compare patterns observed in empirical systems. Such models may then be used to develop quantitative narratives that enhance our intuition and understanding of the relationship between population structure and generative processes: in essence, along with empirical and experimental narratives, quantitative narratives are used to advance ecological epistemology. Here we describe a simulator that accounts for the influence of consumer-resource interactions, existence of social groups anchored around a central location, territoriality, group-switching behavior, and disease dynamics on population size. We use this simulator to develop new and reinforce existing quantitative narratives and point out areas for future study. Author summary The health and viability of species are of considerable concern to all nature lovers. Population models are central to our efforts to assess the numerical and ecological status of species and threats posed by climate change. Models, however, are crude caricatures of complex ecological systems. So how do we construct reliable assessment models able to capture processes essential to predicating the impacts of global change on population viability without getting tied up in their vast complexities? We broach this question and demonstrate how models focusing at the level of the individual (i.e., agent-based models) are tools for developing robust, narratives to augment narratives arising purely from empirical data sources and experimental outcomes. We do this in the context of nesting social groups, foraging for food, while exhibiting territoriality and group-switching behavior; and, we evaluate the impact of disease on the viability of such populations

Channels, consumers and communication: online and offline communication in service consumption

This paper reports on a study that investigated consumer use of e-services in a multichannel context. To develop a deeper understanding of what makes consumers decide to use the online channel, and contrary to most HCI studies on the use of e-services that focus on the use of the online channel in relative isolation, this study examined consumer channel-choice beyond the instances of internet use. The consumption behaviour of its participants was investigated across channels in an in-depth qualitative study. The analysis of the elicited rich data focused specifically on the investigation of voluntary consumer movements between online and offline channels during the course of a consumption process. The results indicate that participants often use multiple channels in parallel and frequently switch between channels. Literature from marketing and consumer research was used as the perspective to explore the rationale for the complex and dynamic reported consumer behaviour

Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented