• The Korean Journal of Franchise Management
• /
• v.3 no.1
• /
• pp.26-45
• /
• 2012

Market players have realized the importance of brand power and tried to develop effective marketing programs which focus on consumer's brand experience. This study aims to investigate brand experience and brand personality effect on brand attitude which is overall consumer's faith toward brands and repurchase intention in food-franchised by Structural Equation Model. As results, both brand experience and brand personality affect brand attitude although brand experience has more influence than brand personality. As consumers show positive brand experience and attitude, repurchase intention is higher. Brand attitude plays a mediation role in the relation of brand experience and personality, and repurchase intention. Also brand experience shows more influence than others on repurchase intention.

• Asia Marketing Journal
• /
• v.11 no.1
• /
• pp.39-72
• /
• 2009

With the growing importance of accountability, it is getting necessary to test the impact of marketing expenditure on marketing performance. Including recent ROM, we can find a few researches about marketing accountability. But there are a few problems about definitions and metric of marketing expenditure and marketing performance. Therefore, by defining and analyzing the impact of marketing expenditure on marketing performance, we are going to set the classification scheme of marketing expenditure and marketing performance. Based on research findings, new definitions and metrics are proposed as follows. First, we suggest the classification scheme of marketing expenditure. Marketing expenditure is defined as expense accounts in the balance sheet for doing marketing tasks. Marketing expenditures includes many accounts, for example, marketing research, advertising, sales promotion, foreign market development, physical distribution, after services. Among these marketing investment, advertising expenses have a positive effect on marketing performance. Second, we suggest the classification scheme of marketing performance. Already, marketing performance has been defined as financial metrics, customer metrics, market metrics, and corporate social responsibility. But, in this study, we find that the process model is not relevant for explaining association between the performance metrics. The process model is a virtuous cycle: "customer metrics→market metrics→financial metrics→firm valuation metrics." But, in this study, it is not supported or a little significant association between these metrics. Based on these results, we suggest the balance model or flower model as the classification scheme of marketing performance.

• Knowledge Management Research
• /
• v.24 no.3
• /
• pp.173-193
• /
• 2023

Digital transformation and the COVID-19 pandemic have facilitated the rapid development and dissemination of non-face-to-face technologies such as self-service technologies (SSTs). This research investigates how motivation factors affect consumers' negative responses to digital shadow work (DSW) in SSTs which decreases their continuous use intention of SSTs. Also, we examine whether the grafication delay ability moderates the relationship between consumers' negative responses to DSW and their continuous use intention of SSTs. By an analysis of usable 450 user respondents via SmartPLS 4.0, perceived benefits was found to significantly influence consumers' negative responses to DSW. Also, consumers' negative responses to DSW can significantly decrease their intention to continue using SSTs. Further, the effect of negative responses to DSW on continuous use intention of SSTs is stronger in case of consumers with low gratification delay ability than in case of consumers with high gratification delay ability. The study findings contribute to providing some strategies for companies operating SSTs by examining the effects of consumer's responses to DSW and gratification delay ability on the continuous usage intention of SSTs.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.347-373
• /
• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.6
• /
• pp.141-158
• /
• 2022

This study identifies related factors by analyzing the effects of the psychological characteristics and competency factors of traditional market merchants on business performance, and at the same time verifies the moderating effect of government support policies. The research focus was on verifying the causal relationship. This study was conducted targeting the representative traditional market merchants in the metropolitan area who have experience in traditional market specialization projects or are currently in the process of specialization projects. An empirical study was performed based on the collected data. The analysis results are as follows. First, it was found that self-esteem as a psychological characteristic factor of merchants, customer management competency as merchant competency, and informatization capability had a significant positive (+) effect on financial performance among business performance. Second, as a result of examining the moderating effect of government support policies, it was found that product capability had a significant positive (+) effect on financial performance among business performance. It was found that self-esteem and product competency had a significant positive (+) effect on the will to continue business among business performance. The practical results of this study are the research papers to measure the business performance of traditional market merchants using the government support policy as a moderating variable, using the psychological characteristics and competency factors of traditional market merchants as independent variables. For this purpose, it will be positively evaluated that the psychological characteristics of merchants and merchant competency factors affect business performance, and that meaningful research results are derived by analyzing the moderating effect of government support.

• Information Systems Review
• /
• v.23 no.3
• /
• pp.127-158
• /
• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Information Systems Review
• /
• v.23 no.3
• /
• pp.159-176
• /
• 2021

Obviating user churn is a prominent strategy to capitalize on online games, eluding the initial investments required for the development of another. Extant literature has examined factors that may induce user churn, mainly from perspectives of motives to play and game as a virtual society. However, such works largely dismiss the service aspects of online games. Dissatisfaction of user needs constitutes a crucial aspect for user churn, especially with online services where users expect a continuous improvement in service quality via software updates. Hence, we examine the relationship between a game's quality management and its user base. With text mining and survival analysis, we identify complaint factors that act as key predictors of user churn. Additionally, we find that enjoyment-related factors are greater threats to user base than usability-related ones. Furthermore, subsequent quasi-experiment shows that improvements in the complaint factors (i.e., via game patches) curb churn and foster user retention. Our results shed light on the responsive role of developers in retaining the user base of online games. Moreover, we provide practical insights for game operators, i.e., to identify and prioritize more perilous complaint factors in planning successive game patches.

• Information Systems Review
• /
• v.18 no.4
• /
• pp.121-140
• /
• 2016

Today, consumers are interested in branded apps as new marketing channels. Consumers do not have ready access to information that will enable them to judge the quality of a particular product or service before purchase, but they will gain such information with branded apps. As they need to be actively chosen and downloaded to users' smartphone by the users themselves, branded apps have greater marketing effectiveness and influence than traditional channels. Therefore, corporations that place emphasis on interactions with customers anticipate a new marketing effect with their branded apps. With previous research on smartphone applications as a background, this research finds key factors in branded apps that influence users' satisfaction. Additionally, the study centers on the relationship in which satisfaction in the branded app significantly influences the purchase intention for the branded product/service.

• Information Systems Review
• /
• v.21 no.1
• /
• pp.23-38
• /
• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.55-78
• /
• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.