International Journal of Human-Computer Interaction

Alajmi, Mohammad A.; Said Ali, Maha

doi: 10.1080/10447318.2021.1988237pmid: N/A

This paper provides an empirical perspective on the antecedents and consequences of virtual conference participant/attendee behavior and continuance behavior through video-conference platforms using the Unified Theory of Acceptance and Use of Technology (UTAUT) combined with further related factors. The sample consisted of 209 participants and attendees of three Middle Eastern virtual conferences. Structural equation modeling (SEM) was employed to test the research model. The results indicate that performance expectancy, effort expectancy, facilitating conditions, and perceived trust are associated with actual participating/attending behavior, and that performance expectancy, effort expectancy, social influence, perceived trust, and system quality influence the intention of continuance participation/attendance behavior. The results further reveal the influence of use behavior on knowledge acquisition and the influence of continuance behavior on knowledge acquisition and communication quality. The implications for both theory and practice are provided based on the findings.

Hari, Harinder; Iyer, Radha; Sampat, Brinda

doi: 10.1080/10447318.2021.1988487pmid: N/A

Chatbots are virtual conversation agents that offer innovative features to connect with customers and thus offer a promising avenue to engage customers. Currently many private and nationalized banks are deploying chatbots for connecting and communicating with customers. This technology is expected to dominate the banking sector in the future by improving customer service. However, the success of banking chatbots will be effective when customers are satisfied with the chatbots and engage in using them. To probe in to the question, this study investigates the antecedents and consequences of customer brand engagement in using banking chatbots, with the lens of diffusion of innovation theory. The antecedents include interactivity, time convenience, compatibility, complexity, observability, and trialability. The consequences are satisfaction with the brand experience and customer brand usage intention. The theorized model has been validated with 470 Indian banking chatbot customers usable responses. The results suggest that trialability, compatibility, and interactivity positively influence customer brand engagement through a chatbot, thereby influencing satisfaction with the brand experience and customer brand usage intention. The paper presents theoretical and managerial implications which enable banks to strengthen customer engagement, satisfaction and brand usage intention through chatbots.

Saragih, Melissa; Morrison, Ben W.

doi: 10.1080/10447318.2021.1990518pmid: N/A

This study aimed to investigate people’s willingness to accept algorithmic over human advice, under varying conditions of previous algorithmic performance and decision significance. We randomly presented hypothetical scenarios to 218 participants. Scenarios differed in relation to decision context (i.e., choices relating to taxi-routes, movies, restaurants, medical interventions, savings strategies, and bush fire evacuation), and within each scenario past algorithmic performance was also varied (equal, above average, or far greater than the human expert). Participants were asked to rate decision significance, and their likelihood of choosing the algorithmic advice over the human expert. Based on participants’ perceived decision significance, scenarios were classified as either low- or high-stakes. We tested for differences in participants’ ratings of algorithmic acceptance across levels of past performance and decision significance. Results revealed that as past accuracy and decision significance increased, the likelihood of algorithmic advice adoption also increased. An interaction between past accuracy and decision significance indicated increased algorithmic advice acceptance under conditions of far greater previous performance, in high-, compared to low-stakes scenarios. These findings are contrary to a large body of past research wherein people’s algorithm aversion persisted despite superior algorithmic performance and have implications to human-algorithm interaction and system design.

Konstanti, Chrysanthi; Karapanos, Evangelos; Markopoulos, Panos

doi: 10.1080/10447318.2021.1990519pmid: N/A

Despite a wealth of behavior change theories and techniques available, designers often struggle to apply theory in the design of behavior change technologies. We present the Behavior Change Design (BCD) cards, a design support tool that makes behavioral science theory accessible to interaction designers during design meetings. Grounded on two theoretical frameworks of behavior change, the BCD cards attempt to map 34 behavior change techniques to five stages of behavior change, thus assisting designers in selecting appropriate techniques for given behavioral objectives. We present the design of the BCD cards along with the results of two formative and one summative study that aimed at informing the design of the cards and assessing their impact on the design process.

Tan, Hao; Peng, Shenglan; Liu, Jia-Xin; Zhu, Chun-Peng; Zhou, Fan

doi: 10.1080/10447318.2021.1990520pmid: N/A

The purpose of this research is to develop a methodology that combines the quantitative and the qualitative analysis to generate personas for products on social platforms. The user data on social platforms contain massive information relating to the lifestyle people have and the products people use or are interested. By analyzing the specific content generated by users on social platforms, e.g., content involving the term “tablet,” it is possible to reveal how the users consider or use the product, “tablet.” By analyzing the users’ homepages, the information relating to the users’ daily life can be found. We collected 276, 675 pieces of relevant data regarding the product, “tablet,” from 12, 965 online users on China’s widely used social media platforms. Then automatic user segments and the profiles of each group were generated and structured by natural language processing technology. The results of these quantitative analyses were then qualitatively examined by manual analyses, which provide additional insights and detailed descriptions on the automatically generated persona profiles. In this study, six personas representing distinct user types were created. The mixed method of combining the quantitative and qualitative methods makes the generation of personas faster and more insightful. The generated personas can represent real user behavior and characteristics and can provide insights into the products, which also can provide support on designing new products and optimizing existing products.

Roberts, James A.; David, Meredith E.

doi: 10.1080/10447318.2021.1990521pmid: N/A

The smartphone has become an integral part of modern life. Many people cannot imagine a life without their smartphone. The sole focus of this research is to create and validate a measure of smartphone orientation to reflect individuals’ interactions with their smartphones as a part of their everyday lifestyle. Presently, the literature offers a variety of smartphone addiction scales of which many suffer from inadequate assessment of the scale’s reliability, validity, theoretical underpinnings, and most scales have too many items. Additionally, research suggests that several of these scales are only weakly associated with actual smartphone use. Across three studies and 867 respondents, a rigorous process was undertaken to create and validate the Smartphone Orientation Scale (SOS). Study 1 involved defining smartphone orientation, creating the scale items, and using a survey of 288 US adults to assess the scale’s psychometric properties and nomological validity; scale analysis resulted in an 8-item SOS scale which exhibits both convergent and discriminant validity. Study 2 surveyed 163 undergraduates to further assess the validity of the SOS; results provide evidence of discriminant, convergent, and nomological validity. Study 3 utilized a survey of 416 undergraduates and found that the SOS was positively associated with social media usage, social media intensity, and actual smartphone use. Overall, the above research offers a valid, 8-item scale that can be used to measure the intensity of an individual’s smartphone orientation. Recent research shows that how we relate to our technology impacts our well-being. Future research directions and study limitations are also discussed.

Schomakers, Eva-Maria; Lidynia, Chantal; Ziefle, Martina

doi: 10.1080/10447318.2021.1994211pmid: N/A

The ongoing digitization and novel smart technologies can deliver enormous benefits to society and individuals. However, smart services often require the vast collection of data conflicting with users’ privacy. The integration of privacy concerns into acceptance research is needed to portray and predict user decisions in smart technologies. To allow a privacy-integrated prediction of users’ technology acceptance, we apply the privacy calculus theory to adoption behavior. We test the new model in three usage contexts, autonomous driving (transportation), activity trackers (fitness), and cardiac device remote monitoring (medical treatment). Using an online questionnaire, 624 German participants evaluated all three technologies. The model fits well in all contexts, although also context-related differences in the weighing of perceived benefits and privacy concerns showed. It is concluded that the trade-off between perceived benefits and privacy concerns is a central keystone not only for the willingness to disclose information but also for technology acceptance.