Interactivity and its Facets Revisited: Theory and Empirical Test

Johnson, Grace; Bruner, Gordon C.; Kumar, Anand

doi:10.2753/joa0091-3367350403

Cited by 234 publications

(214 citation statements)

References 29 publications

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“…This is in alignment with others who have done work in this domain (such as Johnson et al 2006). For formative constructs, the direction of causality is from the measures to the latent construct, rather than the other way around (Jarvis et al 2003).…”

supporting

confidence: 57%

“…Despite the potential for interactivity provided by the Internet, little attention has been paid to how interactivity might be more fully utilized (Johnson et al, 2006). Rice (1984) defined interactivity as the capability of a computer-enabled communication system that permits exchange of roles between the sender and receiver in real or delayed time so that communicators have more control over the structure, pace, and content of the communication.…”

Section: Introductionmentioning

confidence: 99%

“…Johnson et al (2006) tested the relationship of perceived interactivity to attitude toward the website and involvement. Lee (2005) examined various components of interactivity related to trust.…”

Section: Introductionmentioning

confidence: 99%

“…Johnson et al (2006) developed a platform on a website for an herbal antidepressant that allowed users to know through an 'at-a-glance' X-Y plot diagram how many other users found the product useful, at what dosages, and for how long. Users could click or 'plot' their current mood onto this interactive canvas, which was essentially a collaborative visualization populated by members of the community.…”

mentioning

confidence: 99%

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Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses

Cyr

Head

Ivanov

2009

International Journal of Human-Computer Studies

277

218

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A B S T R A C T 1Novel applications of website interactivity are important to attract and retain online users. In this empirical study five designs for interactivity are examined using different web-poll interfaces. The goal of the investigation is to examine perceived interactivity in a model which includes most commonly tested cognitive elements such as efficiency and effectiveness, but augments this model with the inclusion of a cognitive-affective element for trust, and an affective element of enjoyment. More specifically, a model is created to validate the relationship of perceived interactivity (comprised of user control, user connectedness, and responsiveness of the web-poll application) to efficiency, effectiveness, trust and enjoyment, of the website. In turn, efficiency, effectiveness, trust, and enjoyment are tested for their influence on user behavioral intentions for e-loyalty. All relationships in the model are supported. In addition, exploratory evaluation of qualitative comments is conducted to investigate additional insights between the five web poll treatments in this investigation. The research confirms the complexity of a model in which cognitive, cognitive-affective and affective elements are present, and advances knowledge on the consequences of perceived interactivity. In additional to theoretical advancements, the research has merit for web designers and online marketers regarding how to enhance interactive online web applications. K E Y W O R D Sperceived interactivity, e-loyalty, web-poll design . IN T R O D U C T IO NDespite the potential for interactivity provided by the Internet, little attention has been paid to how interactivity might be more fully utilized (Johnson et al., 2006). Rice (1984) defined interactivity as the capability of a computer-enabled communication system that permits exchange of roles between the sender and receiver in real or delayed time so that communicators have more control over the structure, pace, and content of the communication.Although interactivity has numerous dimensions, a common theme is that the website successfully provides information to the user, is perceived as responsive, and allows a sense of connection -often with other users. While previous research has aimed to conceptually unravel contributing factors to interactivity, there is relatively little empirical work that systematically examines the consequences of interactivity. There are some exceptions. Jiang 1 An earlier version of this paper was accepted for presentation at the Sixth Pre-ICIS HCI Research in MIS Workshop (HCI/MIS'07), Montreal, 2007. The authors sincerely appreciate the suggestions of three anonymous reviewers. 3and Benbasat (2007) examined interactivity related to purchase intention and intention to return to the website. Johnson et al. (2006) developed a platform on a website for an herbal antidepressant that allowed users to know through an 'at-a-glance' X-Y plot diagram how many other users found the product useful, at what dosages, and for how long. Users could click...

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supporting

confidence: 57%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses

Cyr

Head

Ivanov

2009

International Journal of Human-Computer Studies

277

218

View full text Add to dashboard Cite

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“…Researchers have investigated customer-service provider interactions (Yim, Tse, & Chan, 2008), the effects of physical characteristics of employees on customers' perceptions of employees (Gorn, Jiang, & Venkataramani, 2008;Naylor, 2007), tendencies for customers to mimic the behavior of others (Tanner et al, 2008), and the influence of nonverbal information on online customer interactions (Johnson, Bruner, & Kumar, 2006). However, there appears to be no prior research examining relationships between customer nonverbal expressions and underlying feelings and its use as a measurement device.…”

Section: Nonverbal Behavior As a Key Component Of The Retail Environmentmentioning

confidence: 99%

Can you trust a customer's expression? Insights into nonverbal communication in the retail context

Puccinelli

Motyka

Grewal

2010

Psychology and Marketing

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Synthesizing knowledge from psychology and marketing research, an understanding of nonverbal communication can help address when and how customers express their underlying feelings in retail interactions that are not evident in direct verbal expressions. Examining nonverbal behavior as an indirect measure of consumer response can enable retailers to better understand the needs of their customers. Nonverbal communication theory is used to develop a conceptual framework that builds on prior research on the situation, expressivity, social status, display rules, and their effects on customer expression. Lay wisdom suggests that customer expression should be revealing (e.g., "the eyes are the windows to the soul"). However, research reveals a myriad of situational factors that may lead customers to mask their true feelings. This paper offers nine theoretical propositions and summarizes research evidence related to these pro-positions from various substantive domains for marketing research.

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Factors influencing users' adoption and use of conversational agents: A systematic review

Ling

Tussyadiah

Tuomi

et al. 2021

Psychology and Marketing

104

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As artificially intelligent conversational agents (ICAs) become a popular customer service solution for businesses, understanding the drivers of user acceptance of ICAs is critical to ensure its successful implementation. To provide a comprehensive review of factors affecting consumers' adoption and use of ICAs, this study performs a systematic literature review of extant empirical research on this topic. Based on a literature search performed in July 2019 followed by a snowballing approach, 18 relevant articles were analyzed. Factors found to influence human‐machine cognitive engagement were categorized into usage‐related, agent‐related, user‐related, attitude and evaluation, and other factors. This study proposed a collective model of users' acceptance and use of ICAs, whereby user acceptance is driven mainly by usage benefits, which are influenced by agent and user characteristics. The study emphasizes the proposed model's context‐dependency, as relevant factors depend on usage settings, and provides several strategic business implications, including service design, personalization, and customer relationship management.

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Interactivity and its Facets Revisited: Theory and Empirical Test

Cited by 234 publications

References 29 publications

Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses

Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses

Can you trust a customer's expression? Insights into nonverbal communication in the retail context

Factors influencing users' adoption and use of conversational agents: A systematic review

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