Social Robots in Retail: Emotional Experiences a Critical Driver of Purchase Intention

The purpose of the current study is to explore whether emotional experiences prompted due to human-social robot interaction in retail environments significantly influence consumers' purchase intentions. This present study focuses primarily on emotional experience, comprising factors, namely, enjoyment, arousal, and emotional involvement. The study tests the conceptual model on a sample of 229 respondents using the PLS-SEM (Partial Least Squares – Structural Equation Modeling) approach. The results reveal that emotional experiences significantly impact consumers’ purchase intentions in retail settings. All three emotional experiences, including enjoyment, emotional involvement, and arousal were significant in shaping consumers' purchase intentions. The study findings offer unique insights for manufacturers developing social robots for the retail sector. The present research extends the current body of work exploring hedonic predictors of consumers' purchase intentions in novel socio-technical contexts, such as social robotics

An Introduction to Causal Inference Methods for Observational Human-Robot Interaction Research

Quantitative methods in Human-Robot Interaction (HRI) research have primarily relied upon randomized, controlled experiments in laboratory settings. However, such experiments are not always feasible when external validity, ethical constraints, and ease of data collection are of concern. Furthermore, as consumer robots become increasingly available, increasing amounts of real-world data will be available to HRI researchers, which prompts the need for quantative approaches tailored to the analysis of observational data. In this article, we present an alternate approach towards quantitative research for HRI researchers using methods from causal inference that can enable researchers to identify causal relationships in observational settings where randomized, controlled experiments cannot be run. We highlight different scenarios that HRI research with consumer household robots may involve to contextualize how methods from causal inference can be applied to observational HRI research. We then provide a tutorial summarizing key concepts from causal inference using a graphical model perspective and link to code examples throughout the article, which are available at https://gitlab.com/causal/causal_hri. Our work paves the way for further discussion on new approaches towards observational HRI research while providing a starting point for HRI researchers to add causal inference techniques to their analytical toolbox.Comment: 28 page

Graphical models for social behavior modeling in face-to face interaction

International audienceThe goal of this paper is to model the coverbal behavior of a subject involved in face-to-face social interactions. For this end, we present a multimodal behavioral model based on a Dynamic Bayesian Network (DBN). The model was inferred from multimodal data of interacting dyads in a specific scenario designed to foster mutual attention and multimodal deixis of objects and places in a collaborative task. The challenge for this behavioral model is to generate coverbal actions (gaze, hand gestures) for the subject given his verbal productions, the current phase of the interaction and the perceived actions of the partner. In our work, the structure of the DBN was learned from data, which revealed an interesting causality graph describing precisely how verbal and coverbal human behaviors are coordinated during the studied interactions. Using this structure, DBN exhibits better performances compared to classical baseline models such as Hidden Markov Models (HMMs) and Hidden Semi-Markov Models (HSMMs). We outperform the baseline in both measures of performance, i.e. interaction unit recognition and behavior generation. DBN also reproduces more faithfully the coordination patterns between modalities observed in ground truth compared to the baseline models

Explainable post-occupancy evaluation using a humanoid robot

The paper proposes a new methodological approach for evaluating the comfort condition using the concept of explainable post occupancy to make the user aware of the environmental state in which (s)he works. Such an approach was implemented on a humanoid robot with social capabilities that aims to enforce human engagement to follow recommendations. The humanoid robot helps the user to position the sensors correctly to acquire environmental measures corresponding to the temperature, humidity, noise level, and illuminance. The distribution of the last parameter due to its high variability is also retrieved by the simulation software Dialux. Using the post occupancy evaluation method, the robot also proposes a questionnaire to the user for collecting his/her preferences and sensations. In the end, the robot explains to the user the difference between the suggested values by the technical standards and the real measures comparing the results with his/her preferences and perceptions. Finally, it provides a new classification into four clusters: True positive, true negative, false positive, and false negative. This study shows that the user is able to improve her/his condition based on the explanation given by the robot

온라인 상품평의 질과 상품평 작성자의 사진이 상품 및 쇼핑몰에 대한 소비자 평가에 미치는 영향

학위논문 (석사)-- 서울대학교 대학원 : 언론정보학과, 2012. 8. 이은주.본 연구는 온라인 상품평의 질과 상품평 작성자의 사진이 소비자의 태도 형성에 미치는 효과를 밝히고자 했다. 이와 동시에, 상품 유형이 상품평의 질과 작성자 사진의 효과에 어떠한 변화를 줄 수 있는지, 즉 상품 유형의 중재 효과 가능성에 대해서 살펴 보았다. 이를 위해, 2 (상품평의 질: 높음 vs. 낮음) x 2 (상품평 작성자 표현: 실제 사진 vs. 도형) x 2 (상품 유형: 경험재 vs. 검색재) 요인설계를 적용한 실험을 252 명의 대학생을 대상으로 온라인에서 실시했다. 실험에 사용된 상품평들은 대부분 해당 상품에 대해 긍정적인 태도를 취하도록 고정되었다. 실험 결과 발견된 주요한 결과는 다음과 같다. 먼저, 고품질 상품평을 읽은 참여자들의 경우, 저품질 상품평을 읽은 참여자들에 비해 상품평 작성자, 해당 상품, 그리고 온라인 쇼핑몰 웹사이트을 더욱 긍정적으로 평가하는 경향을 보였다. 다음으로, 상품평 작성자들의 사진은 도형(느낌표)과 사회적 실재감에서 차이를 보이지 않았으며, 나아가 상품평 작성자, 해당 상품, 그리고 쇼핑몰 웹사이트에 대한 평가에서도 차이를 보이지 않았다. 하지만, 사진이 있을 때, 사람들은 고품질 상품평을 읽었을 때, 저품질 상품평을 읽었을 때에 비해 더 쇼핑몰을 긍정적으로 평가하는 경향을 보였다. 또한, 사람들은 사진을 보았을 때 판매자로부터 주어진 상품 설명을 정확히 기억하지 못하는데 반해, 상품평의 내용을 기억하는 능력에서는 사진을 보지 못한 사람들과 차이가 없었다. 마지막으로, 상품 유형은 상품평 작성자의 사진과는 상호작용이 없었지만, 상품평의 질과의 상호작용효과가 존재했다. 즉, 실제 구매 후 경험하기 이전에도 쉽게 상품의 질을 예측할 수 있는 검색재의 경우, 고품질 상품평이 저품질 상품평에 비해 상품 구매 의사를 더 증가시켰지만, 실제 경험 없이 상품의 품질을 측정하기 어려운 경험재의 경우에는 고품질 상품평과 저품질 상품평 간에 구매 의사 차이가 나타나지 않았다. 이상의 결과들이 갖는 이론적 및 실용적 함의를 논의에 제시했다.This study aimed to elucidate the effects of review quality and reviewer representation in forming consumers attitudes. In so doing, if, and if so, how product type varies the effects of those two factors was also explored. In order to answer these questions, a 2 (review quality: high vs. low) x 2 (reviewer representation: photos vs. abstract figure) x 2 (product type: experience vs. search) between-subject experiment was conducted online. The product reviews used were mostly positive toward the target product. First, participants who read high quality product reviews evaluated the reviewers, product and seller website more positively than those who read low quality reviews. Second, reviewers profile photos did not evoke higher or lesser social presence than abstract figures did. Likewise, there was no difference in evaluations of reviewers, product, and website between photos and figures. However, photos made people more likely to differentiate high quality reviews from low quality reviews, with high quality reviews eliciting more positive website evaluation than low quality reviews. In addition, photos hindered correct recognition of product descriptions (information given by the seller), although they did not significantly alter the recall of review content (information given by the reviewers). Third, product type interacted with review quality, but not with reviewer representation. For search goods, which refers to the products whose quality is easily predicted before purchase, high quality reviews significantly increased purchase intention. However, the effect of review quality was not found for experience goods, which are defined as the products whose values are hardly assessed before firsthand experience. Theoretical and practical implications of these results were discussed.Introduction 1 Literature Review 4 EFFECTS OF REVIEW QUALITY 4 EFFECTS OF REVIEWER REPRESENTATION 8 PRODUCT TYPE AS A MODERATOR 17 Research Questions and Hypotheses 24 Method 27 PILOT TEST 1 27 PILOT TEST 2 28 MAIN EXPERIMENT 34 Participants 34 Procedure 34 Experiment stimuli 34 Measures 38 Results 41 MANIPULATION CHECK 41 HYPOTHESIS TESTS 41 Affective reactions 41 Behavioral intention 46 Cognitive reactions 48 Discussion 51 THEORETICAL IMPLICATIONS 51 LIMITATIONS AND FUTURE DIRECTIONS 55 Conclusion 59 References 60Maste

Generating Competitiveness through Trending Marketing Strategies, Case of Gen Z Consumers in the Restaurant Industry

Implementing marketing strategies is crucial for hospitality organisations to reach their target markets and improve their performance and competitive advantage. Hence, this study examines the impact of various trending marketing strategies on the restaurant industry's competitiveness among Gen Z consumers. Using the asset-process-performance (APP) framework, this research involves six measured constructs: service robots, social media, online advertisements, website experiences, brand love and competitiveness. The samples of 301 survey questionnaires were collected from Gen Z consumers in the restaurant industry. Statistical Package for Social Science (SPSS) was used to conduct the data analysis of this study, and based on the findings, service robots, social media, online advertisements, website experiences, and brand love demonstrated a significant impact on the restaurant industry's competitiveness among Gen Z consumers. Further, the research provides practical implications by better understanding Gen Z consumers, implementing appropriate marketing strategies accordingly, and impacting practice in the restaurant industry.https://ijmmu.com/index.php/ijmmu/article/view/4597/3948http://dx.doi.org/10.18415/ijmmu.v10i4.459710pubpub

An emotion and memory model for social robots : a long-term interaction

In this thesis, we investigate the role of emotions and memory in social robotic companions. In particular, our aim is to study the effect of an emotion and memory model towards sustaining engagement and promoting learning in a long-term interaction. Our Emotion and Memory model was based on how humans create memory under various emotional events/states. The model enabled the robot to create a memory account of user's emotional events during a long-term child-robot interaction. The robot later adapted its behaviour through employing the developed memory in the following interactions with the users. The model also had an autonomous decision-making mechanism based on reinforcement learning to select behaviour according to the user preference measured through user's engagement and learning during the task. The model was implemented on the NAO robot in two different educational setups. Firstly, to promote user's vocabulary learning and secondly, to inform how to calculate area and perimeter of regular and irregular shapes. We also conducted multiple long-term evaluations of our model with children at the primary schools to verify its impact on their social engagement and learning. Our results showed that the behaviour generated based on our model was able to sustain social engagement. Additionally, it also helped children to improve their learning. Overall, the results highlighted the benefits of incorporating memory during child-Robot Interaction for extended periods of time. It promoted personalisation and reflected towards creating a child-robot social relationship in a long-term interaction