Design for Sustainability: The Effect of Lettering Case on Environmental Concern from a Green Advertising Perspective

When Trustworthiness Meets Face: Facial Design for Social Robots

As a technical application in artificial intelligence, a social robot is one of the branches of robotic studies that emphasizes socially communicating and interacting with human beings. Although both robot and behavior research have realized the significance of social robot design for its market success and related emotional benefit to users, the specific design of the eye and mouth shape of a social robot in eliciting trustworthiness has received only limited attention. In order to address this research gap, our study conducted a 2 (eye shape) × 3 (mouth shape) full factorial between-subject experiment. A total of 211 participants were recruited and randomly assigned to the six scenarios in the study. After exposure to the stimuli, perceived trustworthiness and robot attitude were measured accordingly. The results showed that round eyes (vs. narrow eyes) and an upturned-shape mouth or neutral mouth (vs. downturned-shape mouth) for social robots could significantly improve people's trustworthiness and attitude towards social robots. The effect of eye and mouth shape on robot attitude are all mediated by the perceived trustworthiness. Trustworthy human facial features could be applied to the robot's face, eliciting a similar trustworthiness perception and attitude. In addition to empirical contributions to HRI, this finding could shed light on the design practice for a trustworthy-looking social robot.

Facial Anthropomorphic Trustworthiness Scale for Social Robots: A Hybrid Approach

Social robots serve as autonomous systems for performing social behaviors and assuming social roles. However, there is a lack of research focusing on the specific measurement of facial trustworthiness toward anthropomorphic robots, particularly during initial interactions. To address this research gap, a hybrid deep convolution approach was employed in this study, involving a crowdsourcing platform for data collection and deep convolution and factor analysis for data processing. The goal was to develop a scale, called Facial Anthropomorphic Trustworthiness towards Social Robots (FATSR-17), to measure the trustworthiness of a robot's facial appearance. The final measurement scale comprised four dimensions, "ethics concern", "capability", "positive affect", and "anthropomorphism", consisting of 17 items. An iterative examination and a refinement process were conducted to ensure the scale's reliability and validity. The study contributes to the field of robot design by providing designers with a structured toolkit to create robots that appear trustworthy to users.

Design for Pandemic Information: Examining the Effect of Graphs on Anxiety and Social Distancing Intentions in the COVID-19

To increase public awareness and disseminate health information, the WHO and health departments worldwide have been visualizing the latest statistics on the spread of COVID-19 to increase awareness and thus reduce its spread. Within various sources, graphs are frequently used to illustrate COVID-19 datasets. Limited research has provided insights into the effect of different graphs on emotional stress and ineffective behavioral strategies from a cross-cultural perspective. The result of current research suggests a graph with a high proportion size of the colored area (e.g., stacked area graph) might increase people's anxiety and social distancing intentions; people in collectivist culture might have a high level of anxiety and social distancing intentions; the effect of different graphs on social distancing intentions is mediated by anxiety experienced. Theoretical contribution and practical implications on health communication were also discussed in this study.

Three decades of green advertising – a review of literature and bibliometric analysis

Purpose

The purpose of this paper is to present an overview of the research which has been done during the past three decades on the topic of green advertising and identify gaps for future research.

Design/methodology/approach

The methodology that has been adopted for analysis is two-pronged – the first being a literature review with tabulation of data using excel sheets and bar graphs and the second being a bibliometric review using the software VOSviewer. Both approaches analyze the number of citations, keywords, authors, journals and countries. A database of 113 articles from 1990 to 2020 is generated from Web of Science.

Findings

Major contributors to the topic of green advertising research have been identified. Thematic classification is created to understand the subtopics of green advertising. Under this classification, nine subtopics have been identified. Six core research gaps have been identified for future research in the area of green advertising.

Practical implications

The study helps identify where green advertising research is being conducted, its growth potential and future prospects. This research work will enable the industry to gain new insights into this emerging field of green advertising for incorporating the same in their advertising campaigns in view of growing consumer concerns on environment.

Originality/value

The paper provides a comprehensive overview of the current status of research in green advertising. The paper is unique as it is the only review on the topic of green advertising. Given the increasing trend of going green among consumers, the paper adds tremendous value to the field of green advertising.

Trust in AI Agent: A Systematic Review of Facial Anthropomorphic Trustworthiness for Social Robot Design

As an emerging artificial intelligence system, social robot could socially communicate and interact with human beings. Although this area is attracting more and more attention, limited research has tried to systematically summarize potential features that could improve facial anthropomorphic trustworthiness for social robot. Based on the literature from human facial perception, product, and robot face evaluation, this paper systematically reviews, evaluates, and summarizes static facial features, dynamic features, their combinations, and related emotional expressions, shedding light on further exploration of facial anthropomorphic trustworthiness for social robot design.

How Should Green Messages Be Framed: Single or Double?

Researchers and marketers have been showing more interest in the areas of green product attributes. They found that consumers usually associate low quality with green products. Little is known about how to design a green message and how to present product attributes in the advertisement. The objective of this study is to examine the different impacts of message content (single vs. double message) and message order (green message presented first vs. later) on green brand attitude in green advertisement, and its moderating effects by its central and peripheral attributes. Two 2 × 2 experimental between-subjects designs were utilized to test the hypotheses. The results of Study 1 indicate that after consumers watched the double-message advertisement, they formed a significantly more positive green brand attitude toward the product compared to watching a single-message advertisement. The product attributes demonstrated their moderating effects on the above result. The central attribute expanded the difference between the double message and single message, but the peripheral attribute diluted the double-message effect. Study 2 examined the order effect in the double-message advertisement, and we found that presenting the green message first instead of later was the most effective method to persuade consumers. However, this effect was only significant when the green attribute of the product is the central attribute. The peripheral attribute would decrease the order effect in the double-message format. Implications and recommendations for future research are provided at the end of this paper.

Impact of Consumer Environmental Responsibility on Green Consumption Behavior in China: The Role of Environmental Concern and Price Sensitivity

Research on influence factors for green consumption has greatly advanced in recent years. However, little research has explored the effect of consumers’ environmental responsibility on green consumption and how this effect was mediated by environmental concern and moderated by price sensitivity, especially when consumers simultaneously pay close attention to environmental and personal interests. This study investigates the impact of environmental responsibility on green consumption via the mediation of environmental concern and the moderation of price sensitivity. The questionnaire survey method was used to collect data from 680 Chinese consumers via an online questionnaire. The empirical results reveal that environmental responsibility can promote environmental concern and enhance green consumption. Specifically, environmental responsibility has a positive impact on environmental concern and also has different positive effects on green consumption intention. Environmental concern positively affects green consumption intention and plays a partial mediation role in the relationship between environmental responsibility and green consumption intention. Price sensitivity plays a negative moderation role in the relationship among environmental responsibility, environmental concern and green consumption intention. The theoretical and managerial implications of the findings were discussed.