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This study intends to utilize eye tracking for the appearance of a robot, which is one of the trends in social robot design research. We suggest a research model with the entire stage from the consumer gaze response to the perceived consumer beliefs and further their attitudes toward social robots. Specifically, the eye tracking indicators used in this study are Fixation, First Visit, Total Viewed Stay Time, and Number of Revisits. Also, Areas of Interest are selected to the face, eyes, lips, and full-body of a social robot. In the first relationship, we check which element of the social robot design the consumer’s gaze stays on, and how the gaze on each element affects consumer beliefs. The consumer beliefs are considered as the social robot’s emotional expression, humanness, and facial prominence. Second, we explore whether the formation of consumer attitudes is possible through two major channels. One is the path that the consumer beliefs formed through the gaze influence their attitude, and the other is the path that the consumer gaze response directly influences the attitude. This study made a theoretical contribution in that it finally analysed the path of consumer attitude formation from various angles by linking the gaze tracking reaction and consumer perception. In addition, it is expected to make practical contributions in the suggestion of specific design insights that can be used as a reference for designing social robots.

Composites using a resin-impregnated grid layer and a thermocompression-bonded PET nonwoven fabric are being developed as an alternative material for under-cover of vehicles. This material is lightweight and low-cost, and has excellent sound absorption performance and durability. In this study, the tensile properties and Poisson’s ratio of thermocompression-bonded PET nonwoven fabrics prepared by needle-punching were measured. The specimen was formed by thermocompression bonding using hot press. Stress-strain curves of the 2 mm-thick specimens were calculated using a tensile tester and digital image correlation (DIC). The specimen thickness increased with increasing displacement along the tensile load direction in the thermocompression-bonded PET nonwoven fabrics prepared by needle-punching. This phenomenon started at the plastic region in the MD specimen and at the elastic region in the TD specimen. The Poisson’s ratio in each plane was also calculated. Thus, the basic properties required to simulate the mechanical behavior of the thermocompression-bonded PET nonwoven fabrics prepared by needle-punching were evaluated.

Researcher in the fields of business management, marketing and consumer studies have become increasingly interested in psychological ownership, expanding beyond the previous focus on the organizational context and into the online context. This study was designed to verify the outcomes of psychological ownership experienced by an individual in an online environment and to examine how psychological ownership affects an individual's way of thinking. Specifically, we conducted one study that focuses on the behavior of protecting personal information online and analyzes the interaction between level of psychological ownership regarding an online service (high vs. low) and the method of framing the message (gain vs. loss). The results showed that, among users with a high degree of psychological ownership regarding the online service, messages with gain framing were more effective than loss framed ones, whereas, among users with low psychological ownership, loss framed messages were more effective than gain framed ones. The second study took the perspective of user information processing; it was designed to verify that psychological ownership can change an individual's time orientation. With psychological ownership fixed at a consistent level, we evaluated the interaction between time orientation (past-oriented vs. future-oriented) and the method of framing the message (gain vs. loss). We found that, in online services, past-oriented users were more effectively targeted by gain framed messages than by loss framed ones to influence the user's password-changing behavior. Conversely, among future-oriented users, loss framed messages were more effective than gain framed ones in influencing the user's password-changing behavior.

Today, consumer-created information such as online consumer reviews have become important and popular, playing a key role in consumer decision making. Compared with expert-created information, each piece of information is less powerful or persuasive, but their aggregation can be more credible and acceptable. This concept is called collective intelligence knowledge. This study focuses on the persuasive effect on consumer product attitudes of consumer-created information compared to expert-created information. Using source credibility and familiarity theory, the study reveals how prior brand attitudes can play a moderating role in the persuasive effect of consumer-created information and expert-created information. Specifically, this study shows how consumer-created information is more persuasive when consumers have more favorable prior brand attitudes, while expert-created information is more persuasive when consumers have less favorable prior brand attitudes. Based on the results, this study proposes practical strategies for information structure, curation, and presentation. If a company has a good-quality brand evaluation of its products, it should increase the weight of consumer-created information such as online consumer reviews. Otherwise, the company needs to first improve brand evaluation through expert-created information such as third-parties or power-blogger reviews.

With the development of the Internet, consumers can acquire a variety of information, however, as the amount of information continuously increases, it becomes difficult for consumers to make decisions. In this era of information overload, online curation services are emerging to help consumers choose the information they want. In these online services, information is grouped and classified according to certain criteria and presented to consumers. In this context, there are typical goal-derived and taxonomic categories in the method of structuring information. This study investigated the effect of category types on the categorization attitude of consumers according to their psychological ownership of online services. To this end, this study confirmed the interaction effect of category types (goal-derived vs. taxonomic) and the degree of psychological ownership (higher vs. lower). As a result, users with higher (as opposed to lower) psychological ownership of online curation services revealed a more effective attitude toward categorization in the goal-derived (as opposed to taxonomic) type. The results of this study suggest implications on how to structure information in consideration of the psychological state of consumers in an online context and are expected to be useful guidelines for practitioners such as service providers, marketers, and UX(User Experience)/UI(User Interface) designers.

The development of information technology, in an online context, has expanded into collective consumption, e.g., crowdfunding projects. Moreover, people feel a sense of psychological ownership (&ldquo, it is mine&rdquo, ) toward projects they invest in, even if their attributes are immaterial or intangible. This research focuses on changes in psychological ownership based on the characteristics of crowdfunding projects, which are collectively invested in with others, and the attributes of objects (tangible/intangible). Specifically, this research seeks to determine how psychological ownership is affected by information about the amount of money invested by others in a shared project. Additionally, this research investigates whether psychological ownership changes based on others&rsquo, investment (less/more) and the attributes (tangible/intangible) of the project. The findings from the empirical analysis indicate that psychological ownership changes based on information regarding other people&rsquo, s investment in a shared crowdfunding project. The results also show that, in projects with tangible attributes, psychological ownership changes based on investment information, however, no changes were observed in projects with intangible attributes.

In modern society, multitasking is necessary for a worker to accomplish a final goal by their deadline, which could be pursued for either a single goal or multiple goals. Moreover, a worker who has the authority to prioritize their tasks can make plans about the process of behavioral strategies to perform each task by making a to-do list. This strategy is a way of unpacking that which seems to affect the expectancy of goal attainment and heighten the value and importance of the goal. Otherwise, a worker could write a to-do list without specific action plans. These effects of unpacking and packing can be used as management strategies for multitasking engagement and could impact a worker&rsquo, s cognition differently depending on the goal relations, including if there is a single goal or multiple goals. On the one hand, in pursuit of a single goal, unpacking can facilitate a worker&rsquo, s judgment of the importance of the task. On the other hand, in pursuit of multiple goals, a worker&rsquo, s judgment of one task&rsquo, s importance can conflict with another task due to contradictory unpacking guidelines. Additionally, self-regulation as an intrinsic motivation empowers conscious intentions to neglect the cognitive effects of the to-do list. Therefore, those with low self-regulation tend to be encouraged by the effect of unpacking, but those with high self-regulation have the effects of unpacking inhibited. This theoretical model was constructed to identify the cognitive mechanism and the role of self-regulation on boundary conditions in regard to the different effects on unpacking. This study was confirmed via the two-way experiment (single- and multiple-goal x packing and unpacking) to explore the effects of the cognitive mechanism on task importance. The following test was performed via the three-way experiment, using an additional variable, the levels of self-regulation (low self-regulation and high self-regulation), to verify whether they inhibit cognitive effects. This study suggests that the judgment of task importance is different in accordance with goal relations, packing and unpacking, and self-regulations for sustainable management strategies of multitasking.

Investors use annual reports that companies mandatorily disclose every fiscal year-end when they make important investment-related decisions. The Securities and Exchange Commission in the United States has implemented and monitors the “Plain-English Rule” to create a transparent and readable annual report. However, only a general guideline exists for the description of annual reports (Plain English Rule), and there are no specific regulations on volume and format. As such, it is risky to interpret business managers’ positive expressions because the data can include business managers’ subjective opinions and viewpoints from the companies’ perspectives. Additionally, the business managers’ unrevealed tendencies, such as strategic reporting or cognitive bias, remain unknown. Therefore, this study focuses on the narrative sections of the annual reports that companies need to disclose after every fiscal year-end and uses text mining to determine the relationship between the assessment information of companies created by business managers and the performance of companies. The methodology of this study is grounded in text-mining. To analyze these relationships, we collected all the 10-Ks of all public firms in the United States and employed the text-mining method to identify the tones of these 10-K narratives to determine whether they changed in line with current earnings levels. Additionally, we explore factors that could give rise to tone flexibility among reports and examine companies whose tone was more positive relative to their current performance to ascertain how future performance might differ from current performance.

The explosive growth of the internet as the main source of information and knowledge has greatly impacted the manner in which people make use of their memory. As a result, interest in the internet environment, and in particular in the role of transactive memory in a social media environment, has been heightened. Transactive memory is the shared memory system that is formed through interactions between people. Through social media, people have been able to form various human networks, which in turn have made it possible to acquire new information and knowledge. In this sense, the utility of transactive memory has been further increased in a social media environment. This study introduced social interaction, social presence, self-monitoring, and core self-evaluation as the factors impacting the formation of transactive memory capacity. The impacts of transactive memory capability on the tertius iungens orientation and individual job performance were also verified. Data from 225 workers was collected to verify the research model introduced in this study, which was empirically verified using a structural equation model. The study revealed that the four antecedent factors included in the research model significantly impacted individuals’ transactive memory capability and that the transactive memory capability positively influenced the tertius iungens orientation and job performance. Lastly, the results of the study were discussed, and the theoretical and practical implications were introduced.

Recently, user-generated content (UGC) has been in the limelight. This study investigates why Internet users share their own UGC and reveals how the motives behind UGC sharing affect UGC sharing intentions both quantitatively and qualitatively. Based on motivations established in existing online communication literature, theoretical UGC motives are identified. Using online surveys administered to 300 users in South Korea, factor analysis is performed to identify empirical UGC sharing motives, and regression analyses shows how UGC sharing motives affect UGC sharing intention in terms of quality and quantity. A total of 10 theoretical UGC motives are consequently factorized into five motives. It is revealed that three motives—self-creation, self-expression, and reward—are related to individual purposes. Users get enjoyment from creating content, they want to be recognized by others, and further expect to be rewarded socially and economically. The other two motives, community commitment and social relationships, are related to social purposes. Users share UGC as a means of communication, desire feedback from others, and want to feel a sense of belonging within certain communities. All of these motives positively affect UGC sharing intention. This is the first study to empirically clarify UGC sharing motives. In addition, this study reveals UGC-centric self-creation and self-expression motives, which have not been the focus of previous online communication studies. Finally, the research results suggest how UGC site managers can adopt practical strategies related to UGC management.

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning.,This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time.,Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes.,Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.

BACKGROUND Obesity rates are rising worldwide, and represent a major healthcare challenge. Digital therapies, using technological aids, have emerged as a new approach to this global health challenge. The majority of digital therapy tools for combatting obesity include contents based on behavior therapy. However, guidelines for setting the goal weight for individual patients, which is the first step in the behavioral transformation, have yet to be established. Hence, with users of digital therapies, little is known of changes in outcome in relation to goal weight, usage, and dietary patterns, as these have not been studied in detail. OBJECTIVE The purpose of this study was 1) to investigate the association between goal weight and weight loss in relation to baseline BMI, and 2) to identify the relationship between goal weight and usage patterns of digital therapies for obesity in relation to baseline BMI. METHODS The analyses were based on data obtained from Noom users who enrolled in the coaching program between January 2017 and January 2019. A total of 3,098 users aged between 18 and 65 were selected, based on the criteria of having a BMI ≥ 23 (kg/m^2) and being a continuous user. Based on the BMI criteria defined by the WHO for the Asia-Pacific region, and goal weight, we hierarchically classified users into three BMI groups (Pre-obese, Obese class I, Obese class II), with each BMI group classified into three-goal weight subgroups (Goal weight: 10%). We performed a t-test and an ANOVA to compare weight loss, usage, and dietary pattern within BMI groups and goal weight groups. RESULTS 3,098 participants paid coaching program between January 1, 2017, and January 1, 2019, were included in the analysis. 1,892, 1,513, 503 participants were classified in pre-obese, Obese class I, Obese class II. Average weight loss according to goal weight was significantly different only within obese class I (P CONCLUSIONS This study found that weight loss depending on goal weight was different in obese class I using digital therapeutics; also demonstrated the goal weight was more related to the dietary pattern than usage pattern of the mobile application for body weight management.

Individuals&rsquo, lives and behaviors progressively change as information technology evolves. Through the rapid growth of information technology, individuals can access abundant information and virtual networks and create online communities for information and knowledge exchange and other intellectual pursuits. Some of the most important aspects of community success involve the engagement, participation, and active discussion of and among community members. This study focuses on the user-generated content (UGC) community and explores the mechanism for formation of community attachment from the perspective of the content capital and social capital of community members. In addition, this study demonstrates the moderating effect of membership duration on the mechanism of community attachment formation. Finally, this study reveals that the attachment formed with content and social capital can affect the decision to either continue to participate in a current UGC service site, or move to an alternative site.

Recently, Internet activity by consumers adopting innovation or purchasing products has increased markedly. To understand this phenomenon, our study focuses on the correlation between purchase behavior and search activity. Utilizing the product classifications established in previous studies, we classify physical products into durable, nondurable, and industrial goods. We then empirically analyze case studies to determine the correlation between Internet searches and product purchases. Our research results show that the correlation between sales and search traffic is more significant for consumer goods than for industrial goods; furthermore, in the consumer goods category, search traffic is a particularly strong predictor of sales in the case of consumer durable goods. These results may be self-evident, implicit in the definition of each product category. However, the presented findings confirm that even among nondurable goods, search traffic can be a significant predictor of purchases, depending on both price and frequency of purchases. In contrast, for durable goods, search traffic may not be strongly indicative of actual purchases for new products, for which traffic simply reflects rising interest. We also show that PC searches are a stronger predictor of sales than mobile searches. The conclusions drawn from this study provide an important foundation for effectively using search statistics in technology business management to formulate marketing strategies as well as to forecast and analyze the adoption of new technology based on real-time monitoring of the changing involvement with each product.

This study examines the influence of the tertius iungens orientation on knowledge-sharing activities and individual job performance within enterprise social media environments. The empirical analysis reveals that knowledge self-efficacy, social interaction ties, and the norm of reciprocity positively influence the tertius iungens orientation and knowledge-sharing activities in social media, while enjoyment of helping does not have a significant influence. In addition, the tertius iungens orientation has a significant impact on knowledge-sharing activities in social media, which in turn influences individual job performance. Based on the results of this analysis, this study discusses the research findings and proposes theoretical and practical implications of the study as well as the research's limitations. The influence of tertius iungens orientation within social media context.The impact of individual and social factors on tertius iungens orientation.The relationship between tertius iungens orientation & knowledge-sharing activities.The indirect effect of tertius iungens orientation on individual job performance.Theoretical and practical implications for enterprise knowledge management.

It is widely known that consumer satisfaction, as well as consumer voice and loyalty, affect firms' performance. Prior studies on consumer satisfaction have focused on expectancy disconfirmation theory and its effects on satisfaction related to disconfirmation with consumer expectation and with perceived performance. This study classified consumer expectation into should-expectation and will-expectation, and investigated how disconfirmation with these expectations affects consumer satisfaction differently based on regulatory focus. Specifically, for promotion-focused consumers, disconfirmation of will-expectation has a more significant influence on consumer satisfaction than that of should-expectation. For prevention-focused consumers, disconfirmation of should-expectation has a more significant influence on consumer satisfaction. The results of this study provide academic insights that not only generic expectation (will-expectation) but also should-expectation play an important role in determining consumer satisfaction according to regulatory focus. In addition, it is expected that the findings can be used as a guide to manage consumer expectation in practice.

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

In recent years, many researchers have devoted their attention to using search traffic information gathered from Google Insights to carry out consumer attitude research. The purpose of this study is to assess the effectiveness of using search traffic information to analyze actual consumer attitudes regarding a product. By comparing the results of conventional survey-based attitude research with the results of search traffic information, this study reveals that search traffic information indicates consumers' level of interest regarding a product, the product attributes that they are considering, and the importance of each attribute to them. Also, it demonstrates the potential benefits of search traffic analysis, which can be useful for forecasting consumer preferences regarding products. Focusing on the Prius, a hybrid car, this study shows that search traffic information serves as an accurate indicator of consumer attitudes, and even succeeds in identifying consumers' hidden attitudes toward the Prius, which can be explained by cognitive dissonance theory. Finally, this study utilizes search traffic information to forecast changes in consumer attitudes and to develop an econometric model of consumer demand for the Prius by incorporating environmental variables such as the WTI (West Texas Intermediate) price. This study concludes that search traffic information offers new potential advantages, in that it not only overcomes the limitations imposed by the high cost of conducting surveys, in terms of money and time, but also helps to reduce the distortions caused by conscious or unconscious errors committed by survey respondents.