• 디지털융복합연구
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• 제19권10호
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• pp.203-208
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• 2021

본 연구는 감정지능이 개인적 특징으로 전문화된 구성원의 이직을 방지하는 것과 고객지향이 중요하므로 고객지향과의 관계를 온라인쇼핑몰 콜센터 상담사를 대상으로 검증하였다. 배포한 170부 중 불성실한 응답 22부를 제외한 148부(87.05%)가 분석에 이용되었다. 실증분석에 활용된 도구는 SPSS 25.0이다. 연구결과는 다음과 같다. 첫째, 감정활용은 고객지향에 정(+)의 영향을 미치는 것으로 나타났다. 둘째, 타인감정인식도 고객지향에 정(+)의 방향으로 유의한 영향을 미치는 것으로 나타났다. 셋째, 자기감정인식은 고객지향에 정(+)의 영향을 미치는 것으로 나타났다. 넷째, 감정조절성은 고객지향에 정(+)의 영향을 미치는 것으로 나타났다. 본 연구의 시사점은 자신이 느끼는 감정의 원인과 자신의 감정을 이해하여야 고객의 요구에 즉각적으로 응대하고 고객의 일을 본인의 일처럼 생각하여 고객지향성을 가질 수 있다는 것이다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.232-234
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• 2022

빅데이터는 고객 관계 관리, 관계 마케팅, 금융 업무 개선, 신용정보 및 위험 관리 분야에서 크게 활용되고 있다. 더욱이 최근에 COVID-19 바이러스로 인하여 비대면 금융거래가 보다 활발해지면서 고객과의 관계 측면에서 금융 빅데이터의 활용이 더 요구되고 있다. 고객 관계 측면에서 금융 빅데이터는 기술적인 접근보다 감성적적인 접근이 필요한 시기가 도래하였다. 관계 마케팅 측면에서도 인지적, 이성적, 합리적인 면보다는 감성적인 면을 중요시 할 필요성이 대두되었다. 하지만, 기존의 금융 데이터는 텍스트 형태의 고객 거래 데이터, 기업재무정보, 설문지등을 통하여 수집되고 활용되었다. 본 연구는 SNS를 통하여 고객의 문화 활동, 여가 활동 기반의 고객의 감성적인 이미지 데이터 즉, 비정형 데이터를 획득하여 고객의 활동 이미지를 인공지능 CNN 알고리즘으로 분석한다. 활동 분석은 다시 주석을 달은 인공지능에 적용하고, 주석에 나타난 행동 모델을 분석하는 인공지능 빅데이터 모델을 설계한다.

• International Journal of Contents
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• 제17권1호
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• Asia Marketing Journal
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• 제20권2호
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• pp.65-83
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• 2018

Technological advances are bringing autonomous vehicles to the ever-evolving transportation system. Anticipating adoption of these technologies by users is essential to vehicle manufacturers for making more precise production and marketing strategies. The research investigates regulatory focus and consumer innovativeness with consumers' adoption of autonomous vehicles (AVs) and to consumers' subsequent willingness to pay for AVs. An online questionnaire was fielded to confirm predictions, and regression analysis was conducted to verify the model's validity. The results show that a promotion focus does not have a significantly positive effect on the automation level at which consumers will adopt AVs, but a prevention focus has a significantly positive effect on conditional AV adoption. Consumer innovativeness, consumers' novelty-seeking have a significantly positive relationship with high and full AV adoption, and consumers' independent decision-making has a significantly positive effect on full AV adoption. The higher the level of automation at which a consumer adopts AVs, the higher the willingness to pay for them. Finally, using a neural network and decision tree analyses, we show methods with which to describe three categories for potential adopters of AVs.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.489-498
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model. The data set for the tests is collected from a convenience store G, which is the number one in its brand in S. Korea. This data set contains sales information on customer transactions from September 1, 2005 to December 7, 2005. About 1,000 transactions are selected for a specific item. Using this data set, it suggests an integrated model predicting whether a customer buys or not buys a specific product for target marketing strategy. The performance of integrated model is compared with that of other models. The results from the experiments show that the performance of integrated model is superior to that of all other models such as Association Rule, Frequency Matrix, and Rule Induction.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.371-380
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• 2020

With the 4th industrial revolution, many advanced information technologies are being applied to the area of construction engineering and project management. These applications are usually focusing on design, construction and operation stage and are producing many meaningful fruits. Even though these studies are very important for the development of the construction industry, this study insists that the other stage perspective such as construction business also should be emphasized. Because business phase has significant impacts on the success of a construction project as well as design, construction and operation phase. So, this study reviewed the intelligent-approach papers in planning and marketing, estimation and bid, contract and claim, and project financing fields. This study provides some insights such as values, difficulties, limitations and future directions of business intelligence application.

• International Journal of Advanced Culture Technology
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• 제6권2호
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• pp.58-64
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• 2018

This main purpose of the study is to identify social network of communicators sharing information on Bokjiro for publicizing welfare policy. This study employs NodeXL pro to understand networks and their role in the social network. The data for social network analysis was collected from Twitter for a week. The result of the analysis shows that the social network of communicators on Bokjiro does not have many nodes. It also has an independent network with high possibility of information distortion. Little communicators have controlling power in information flow in one way of communication. According to the result, it is not effective for marketing strategy of welfare policy in providing online information through Bokjiro. The study suggests that the government should use the transactional approach to marketing based on agent-oriented activity focusing on the exchange relationship between information providers and demanders in an age of networked intelligence.

• Asia Marketing Journal
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• 제26권2호
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• pp.129-144
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• 2024

This research is on how people's trust in human-like AI-based service will influence customer engagement (CE). This study will discuss the relationship between trust and CE and explore how people's trust in AI affects CE when they lack knowledge of the company/brand. Items from the philosophical study of trust were extracted to build a scale suitable for trust in AI. The scale's reliability was ensured, and six components of trust in AI were merged into three dimensions: trust based on Quality Assurance, Risk-taking, and Corporate Social Responsibility. Trust based on quality assurance and risk-taking is verified to positively impact customer engagement, and the feelings about AI-based service fully mediate between all three dimensions of trust in AI and CE. The new trust scale for human-like AI-based services on social media sheds light on further research. The relationship between trust in AI and CE provides a theoretical basis for subsequent research.

• 한국인공지능학회지
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• 제6권2호
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• pp.23-27
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• 2018

Korea has a high proportion of self-employment. Many of them start the food business since it does not require high-techs and it is possible to start the business relatively easily compared to many others in business categories. However, the closure rate of the business is also high due to excessive competition and market saturation. Cafés and restaurants are examples of food business where the business analysis is highly important. However, for most of the people who want to start their own business, it is difficult to conduct systematic business analysis such as trade area analysis or to find information for business analysis. Therefore, in this paper, we predicted business status with simple information using Microsoft Azure Machine Learning Studio program. Experimental results showed higher performance than the number of attributes, and it is expected that this artificial intelligence model will be helpful to those who are self-employed because it can easily predict the business status. The results showed that the overall accuracy was over 60 % and the performance was high compared to the number of attributes. If this model is used, those who prepare for self-employment who are not experts in the business analysis will be able to predict the business status of stores in Seoul with simple attributes.

• 지능정보연구
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• 제9권1호
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• pp.179-193
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• 2003

군집화(clustering)는 주어진 객체들 중에서 유사한 것들을 몇몇의 집단으로 그룹화 하여 각 집단의 성격을 파악하는데, 실제적으로 각 객체가 유사한지 그렇지 않은지를 측정할 수 있는 도구가 필요하다. 기존의 군집화에서 객체간에 유사하다는 의미는 각 군집(cluster)안에 있는 객체들이 같은 속성 값이 많으면 많을수록 객체간에 유사성이 높아 유사도가 높은 객체끼리 군집을 이루게 된다는 것을 의미했다. 그 중에서도 범주형 속성을 갖는 군집화는 같은 속성 값이면 1, 서로 다르면 0으로 표현하여 유사성을 측정하는 방법이다. 제안된 알고리듬은 속성 값을 0과1로만 표현하는 것에 대한 문제점을 제시하고 서로 다른 속성이라도 속성간에 친밀한 관계가 있다는 개념을 도입하여 어느 정도 유사한 지를 보여준다. 같은 객체간에 같은 값을 갖는 속성이 하나로 없더라도 구해진 유사도에 의해 유사한 개체끼리는 하나의 군집이 될 수 있는 알고리듬을 만든 후 그 군집에 속해 있는 고객들의 니즈와 구매 선호도에 따라 적절한 타겟 마케팅(Target Marketing)을 할 수 있다.