23,547 research outputs found

    What facilitates consumers accepting service robots? A conceptual framework

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    Confronting with an increasing number of robots swarming into service industries to replace human personnel, studies regarding what drives consumers to use service robots leave to be, unfortunately, still fragmented. Motivated by this, based on a content analysis of the existing studies, this paper establishes a conceptual framework to comprehend the current literature for in-depth understanding concerning customer attitude and their intention to use service robots. Drawing upon a triangulation of perspectives on end-user (i.e., technology user, consumer, and network member) in adoption research, this framework adopts technology acceptance theories, service quality, and expectancy-value theory to set up the skeleton. Furthermore, the antecedents impacting customer acceptance of service robots are subdivided into robot-design, consumer-oriented, relational components, as well as exogenous factors. This paper not only elaborates on the present situation of service robot acceptance research but also promotes it by developing a comprehensive framework regarding the effect factors

    Reciprocity in a Two-Part Dictator Game

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    We conduct a dictator game experiment in which recipients in an initial game become dictators in a second game. When the subjects paired remain the same, the amount sent back is strongly correlated with the amount received, despite the fact that the interaction is anonymous and is known to be one-time and zero-sum in nature. When the initial recipient is instead paired with a third subject, a less significant and lower-valued correlation between amounts received and sent is exhibited. Intelligence and personality test results, gender, and other characteristics also help to predict sending behavior and degree of reciprocity.reciprocity, dictator game, cognition, personality, altruism

    Siri, Alexa, and Other Digital Assistants: A Study of Customer Satisfaction With Artificial Intelligence Applications

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    Siri, Alexa, and other digital assistants are rapidly becoming embraced by consumers and the adoption is projected to grow from 390 million to 1.8 billion for the period of 2015 to 2021. Digital assistants are offering benefits to consumers while also proving to be a disruptive technology for businesses. Coupling digital assistants with other artificial intelligence technologies offers the potential to transform companies by creating more efficient business processes, automating complex tasks, and improving the customer service experience. Businesses have begun integrating this technology into their operations with the expectation of achieving significant productivity gains. Customer satisfaction has been discussed extensively throughout marketing literature. Yet, there is little empirical evidence of customer satisfaction with digital assistants. This study used PLS-SEM to analyze 244 survey responses obtained from a cross-section of consumers. Using the Expectations Confirmation Theory as its foundation, the study identified that expectations and confirmation of expectations substantially explained customer satisfaction with digital assistants. For practice, the study provides guidance which allows firms to prioritize marketing and managerial activities. Firms should focus priorities on assisting digital assistant users to become aware of new skill capabilities while also providing relevant examples of how these skills can be used to meet user needs. In addition, priorities should be focused on assisting users with understanding how the average person can use digital assistants to perform more than just mundane tasks with relative ease. These priorities were identified as areas of high importance for customer satisfaction and require performance improvements

    How do potential users perceive the adoption of new technologies within the field of Artificial Intelligence and Internet-of-Things? - A revision of the UTAUT 2 model using Voice Assistants

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    The following study investigates the perception potential users have when considering the adoption of voice assistants (VAs). VAs are considered to possess characteristics linkable to both, Artificial Intelligence (AI) and the Internet-of-Things (IoT). This thesis aims to provide a deeper understanding of the determinants influencing the adoption of the new VA technology using the Unified Theory of Acceptance and Use of Technology 2 model (UTAUT 2), a theoretical model explaining technology adoption and usage behaviour. The amount of gadgets being released to the market which possess characteristics of the AI and IoT technology increases constantly, while the 2012 version of the UTAUT 2 model was not constructed for these. In a qualitative approach conducting four focus groups, the aim of this study is to find out about the perceptions of potential future users on the VA technology and as a consequence amend the current UTAUT 2 model to fit newly upcoming technologies which possess similar characteristics as VAs within the AI and IoT field. The study found out that while hedonic motivation seems to be of inferior relevance, the determinants data security, compatibility and relationship with the device are essential influencing factors to take into consideration when trying to fully understand users’ technology adoption perceptions. However, the fact that these technologies are still in the early stage of adoption make it difficult for future users, to fully judge their own adoption behaviour if they are no members of the early innovation adoption curve stages. For further research, it is recommended to look into different sampling groups and apply the model resulting from this study to new upcoming technologies within the area of AI and IoT

    Conversational commerce: entering the next stage of AI-powered digital assistants

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    Digital assistant is a recent advancement benefited through data-driven innovation. Though digital assistants have become an integral member of user conversations, but there is no theory that relates user perception towards this AI powered technology. The purpose of the research is to investigate the role of technology attitude and AI attributes in enhancing purchase intention through digital assistants. A conceptual model is proposed after identifying three major AI factors namely, perceived anthropomorphism, perceived intelligence, and perceived animacy. To test the model, the study employed structural equation modeling using 440 sample. The results indicated that perceived anthropomorphism plays the most significant role in building a positive attitude and purchase intention through digital assistants. Though the study is built using technology-related variables, the hypotheses are proposed based on various psychology-related theories such as uncanny valley theory, the theory of mind, developmental psychology, and cognitive psychology theory. The study’s theoretical contributions are discussed within the scope of these theories. Besides the theoretical contribution, the study also offers illuminating practical implications for developers and marketers’ benefit

    Technology as Actors in Service Systems

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    Service systems are defined as dynamic configurations of resources (people, organizations, technology and shared information), interconnected internally and externally by value propositions with other service systems. Resources are constantly evolving, as are the capabilities and roles of resources in service systems. Cognitive technologies incorporate rapidly advancing artificial intelligence (AI) capabilities. Therefore, their roles are on a trajectory of increasing agency and self-directed interactions with other resources and service systems. With this in mind, a framework for service systems in which AI- based cognitive assistants (CAs) become responsible actors is the current research challenge. Because AI- based CAs have already started to play different roles in service systems. One contribution of this research is to clarify that service system entities are responsible actors, and address the question: Under what conditions does a technology such as a Cognitive Assistant (CA) become a responsible actor

    People’s Interactions with Cognitive Assistants for Enhanced Performances

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    When cognitive computing enabled smart computers are growing in our daily lives, there are not many studies that explain how people interact and utilize these solutions, and the impact of these smart machines to people’s performance to do things. In this paper, a theoretical framework for boosting people’s performance using cognitive assistants (CAs) was developed and explained using the data analysis from 15 interviews. The results show that people interaction with CAs enhance their levels of cognition and intelligence that help them to enhance their capabilities. Enhanced capabilities help people to enhance their performance

    Interpersonal Styles and Labor Market Outcomes

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    This paper develops a framework to understand the role of interpersonal interactions in the labor market including task assignment and wages. Effective interpersonal interactions involve caring, to establish cooperation, and at the same time directness, to communicate in an unambiguous way. The ability to perform these tasks varies with personality and the importance of these tasks varies across jobs. An assignment model shows that people are most productive in jobs that match their style and earn less when they have to shift to other jobs. An oversupply of one attribute relative to the other reduces wages for people who are better with the attribute in greater supply. We present evidence that youth sociability affects job assignment in adulthood. The returns to interpersonal interactions are consistent with the assignment model.Interpersonal Interactions, Wage Level, Wage Structure

    Social capital and the decline in HIV transmission - A case study in three villages in the Kagera region of Tanzania.

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    We present data from an exploratory case study characterising the social capital in three case villages situated in areas of varying HIV prevalence in the Kagera region of Tanzania. Focus group discussions and key informant interviews revealed a range of experiences by community members, leaders of organisations and social groups. We found that the formation of social groups during the early 1990s was partly a result of poverty and the many deaths caused by AIDS. They built on a tradition to support those in need and provided social and economic support to members by providing loans. Their strict rules of conduct helped to create new norms, values and trust, important for HIV prevention. Members of different networks ultimately became role models for healthy protective behaviour. Formal organisations also worked together with social groups to facilitate networking and to provide avenues for exchange of information. We conclude that social capital contributed in changing HIV related risk behaviour that supported a decline of HIV infection in the high prevalence zone and maintained a low prevalence in the other zones
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