Chatbot or Human？The Impact of Chatbot Service Strategies on Recovery Satisfaction

Nowadays, more and more enterprises use chatbots in customer service, but a customer survey shows that most users prefer to choose human service employee rather than chatbots. What scenario can chatbots play a better role than human customer service, bringing better customer service satisfaction has become an issue of concern for enterprises. From the perspective of service recovery, this study explores what circumstances does customer service provide chatbots better service than human service employee? To this end, we proposed a matching effect model between the service recovery entity and customer requirement type, and on this basis, the moderating effect brought by different remedy schemes and communication styles of customer service is discussed. We plan to design mixed design vignette experiments to test our research model. The findings of this study are intended to give new insights for researchers and practitioners

Mapping dynamic social networks in real life using participants' own smartphones

AbstractInterpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies

Experiencers and the Ambiguity Objection

It is often asserted that we should believe that phenomenal consciousness exists because it is pretheoretically obvious. If this is the case, then we should expect lay people to categorize mental states in roughly the way that philosophers do, treating prototypical examples of (supposed) phenomenally conscious mental states similarly. Sytsma and Machery (2010) present preliminary evidence that this is not the case. They found that participants happily ascribed seeing red to a simple robot but denied that the robot felt pain. The most prominent response to this work has been the ambiguity objection, which charges that participants were interpreting ascriptions of seeing red in a purely informational way, such that their attributions of “seeing red” to the robot do not speak to the question of whether they recognize the phenomenality of this state. Peressini (2014) pushes an especially interesting version of the objection, presenting new empirical evidence and suggesting that lay people do in fact have a concept of phenomenality. In this paper, I respond to Peressini’s objections, and the ambiguity objection more generally, arguing that the new data does not undermine Sytsma and Machery’s conclusion

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Working Together with Conversational Agents: the Relationship of Perceived Cooperation with Service Performance Evaluations

Conversational agents are gradually being deployed by organizations in service settings to communicate with and solve problems together with consumers. The current study investigates how consumers’ perceptions of cooperation with conversational agents in a service context are associated with their perceptions about agents’ anthropomorphism, social presence, the quality of the information provided by an agent, and the agent service performance. An online experiment was conducted in which participants performed a service-oriented task with the assistance of conversational agents developed specifically for the study and evaluated the performance and attributes of the agents. The results suggest a direct positive link between perceiving a conversational agent as cooperative and perceiving it to be more anthropomorphic, with higher levels of social presence and providing better information quality. Moreover, the results also show that the link between perceiving an agent as cooperative and the agent’s service performance is mediated by perceptions of the agent’s anthropomorphic cues and the quality of the information provided by the agent

Blurring the Line Between Human and Machine: Marketing Artificial Intelligence

One of the most prominent and potentially transformative trends in society today is machines becoming more human-like, driven by progress in artificial intelligence. How this trend will impact individuals, private and public organizations, and society as a whole is still unknown, and depends largely on how individual consumers choose to adopt and use these technologies. This dissertation focuses on understanding how consumers perceive, adopt, and use technologies that blur the line between human and machine, with two primary goals. First, I build on psychological and philosophical theories of mind perception, anthropomorphism, and dehumanization, and on management research into technology adoption, in order to develop a theoretical understanding of the forces that shape consumer adoption of these technologies. Second, I develop practical marketing interventions that can be used to influence patterns of adoption according to the desired outcome. This dissertation is organized as follows. Essay 1 develops a conceptual framework for understanding what AI is, what it can do, and what are some of the key antecedents and consequences of its’ adoption. The subsequent two Essays test various parts of this framework. Essay 2 explores consumers’ willingness to use algorithms to perform tasks normally done by humans, focusing specifically on how the nature of the task for which algorithms are used and the human-likeness of the algorithm itself impact consumers’ use of the algorithm. Essay 3 focuses on the use of social robots in consumption contexts, specifically addressing the role of robots’ physical and mental human-likeness in shaping consumers’ comfort with and perceived usefulness of such robots. Together, these three Essays offer an empirically supported conceptual structure ¬for marketing researchers and practitioners to understand artificial intelligence and influence the processes through which consumers perceive and adopt it. Artificial intelligence has the potential to create enormous value for consumers, firms, and society, but also poses many profound challenges and risks. A better understanding of how this transformative technology is perceived and used can potentially help to maximize its potential value and minimize its risks

PSYCHOLOGICAL EFFECTS OF READING: THE ROLE OF NOSTALGIA IN RE-READING FAVORITE BOOKS

There are many positive outcomes from feeling nostalgic, including reductions in loneliness and greater meaning and social connectedness. My primary research goal was to investigate whether I could trigger feelings of nostalgia from re-reading an old favorite book, and whether this elicited nostalgia would increase feelings of connectedness and meaning in life and reduce loneliness. I designed a two-study package (one correlational study and one experiment) to assess re-reading novels. Trait nostalgia was positively associated with enjoyment of re-reading books (Study 1). Re-reading a favorite novel, relative to reading a new novel or a set of newspaper articles, elicited nostalgia. Further, nostalgia mediated the relation between reading condition on loneliness, meaning in life, and social connectedness (Study 2). Future work should focus on evaluating the nostalgic benefits of other forms of storytelling

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 359)

This bibliography lists 164 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jan. 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

마음지각이 챗봇의 사회적 지지에 미치는 영향

학위논문(석사) -- 서울대학교대학원 : 사회과학대학 심리학과, 2022. 8. 한소원.Chatbots have the potential to provide social support to users and improve their psychological wellbeing. Nevertheless, how user perception of chatbots influences the effects of social support is not fully understood. This study first investigated whether chatbot social support can have a positive impact on users’ stress management. Then, we examined whether mind perception in chatbots influenced the effectiveness of social support. In the experiment, the chatbot asked several questions about participants’ interpersonal stress events, and by answering these questions, participants wrote down their stressful experiences. Depending on the experimental conditions, the chatbot additionally provided two different kinds of social support: informational support (i.e., relationship advice) and emotional support (i.e., empathy and encouragement). We found that satisfaction with support had a positive effect on dealing with stressful situations. We also revealed that providing emotional support reduced the extent to which participants perceived the chatbot messages as useful compared to prompting only the writing of their stressful experiences. Further, participants were less satisfied with the support when they received emotional support rather than informational support from the chatbot. When participants perceived that the chatbot had a more humanlike mind, they were more satisfied with the support, and consequently perceived the support as more useful to resolve their stressful events. Our findings suggest that users might recognize the unique characteristics of chatbots and therefore expect different forms of support from that received by humans. In addition, the results show that users’ satisfaction with social support and mind perception is important for understanding the effects of support from chatbots.챗봇은 사용자에게 사회적 지지를 제공하고 그들의 심리적 안녕감을 높일 수 있는 잠재성을 지니고 있다. 그럼에도 불구하고 챗봇에 대한 사용자 지각이 챗봇의 사회적 지지 효과에 어떠한 영향을 미치는지에 대한 이해는 아직 부족하다. 본 연구는 우선 챗봇의 사회적 지지가 사용자의 스트레스 관리에 있어 긍정적인 영향을 주는지 탐구하였다. 그 후 챗봇에 대한 사용자의 마음지각이 챗봇의 사회적 지지 효과에 영향을 미치는지 확인하였다. 실험에서 챗봇은 참여자의 대인관계 스트레스 상황에 대하여 질문하였고, 참여자는 챗봇의 질문에 답하며 본인의 스트레스 상황을 글로 적었다. 실험 조건에 따라 챗봇은 정보적 지지 (i.e., 대인관계 조언)와 정서적 지지 (i.e., 공감과 격려), 두 가지 종류의 사회적 지지를 추가적으로 제공하였다. 분석 결과, 사회적 지지에 대한 만족감은 참여자의 스트레스 대처에 긍정적인 영향을 주는 것으로 나타났다. 스트레스 경험을 적어보도록 독려만 한 것에 비하여, 챗봇이 추가적으로 정서적 지지를 제공하였을 경우, 참여자가 챗봇의 메시지를 유용하다고 지각하는 정도가 감소하였다. 또한 챗봇에게 정보적 지지보다 정서적 지지를 받았을 때, 지지에 대한 참여자의 만족도가 감소하였다. 참여자가 챗봇에게 보다 인간 같은 마음이 있다고 지각할 때, 지지에 대한 만족도가 증가하였고, 지지가 스트레스 상황을 다루는데 유용하다고 지각하는 정도 또한 증가하였다. 본 연구의 결과는 사용자가 챗봇 고유의 특성을 인지하고 있기 때문에 인간이 제공하는 것과는 다른 형태의 지지를 챗봇에게 기대한다는 것을 시사한다. 또한 챗봇의 사회적 지지 효과를 이해함에 있어, 지지에 대한 사용자의 만족감과 챗봇에 대한 사용자의 마음지각이 중요하다는 것을 보여준다.Abstract i Table of Contents iii List of Tables iv List of Figures iv Chapter 1. Introduction 1 1.1. Social Support of Chatbots 1 1.2. Stress-Buffering Model and Perceived Social Support 3 1.3. Factors Influencing Social Support of Chatbots 4 1.4. Mind Perception 7 1.5. Mind Perception and Social Support 11 1.6. The Current Study 13 Chapter 2. Methods 16 2.1. Participants 16 2.2. Experiment Design 17 2.3. Materials and Measurements 19 2.4. Procedure 23 Chapter 3. Results 25 3.1. Effects of Social Support on Stress-Handling 25 3.2. Effects of Mind Perception on Social Support 33 Chapter 4. Discussions 39 4.1. Summary of Results 39 4.2. Implications 43 4.3. Limitations and Future Research 45 Chapter 5. Conclusion 48 References 49 Appendix 60 국문 초록 66석