본 연구는 노인장기요양기관의 윤리경영, 직무착근도, 고객지향성, 조직문화와의 관계 를 규명하되, 요양보호사의 윤리경영, 직무착근도, 고객지향성, 조직문화의 수준은 어느 정도인지를 파악하고, 이들 간의 관계를 조직문화가 매개하는지 검증하는데 목적이 있다. 이를 위해 본 연구에서는 충청지역에 소재하고 있는 노인장기요양기관의 요양보호사 626명의 설문을 실시하였는데 본 연구의 주요결과는 요양보호사가 인식하고 있는 윤리 경영 수준은 5점 척도 기준에서 평균 3.760, 조직문화 수준은 평균 3.501점으로 나타났는 데 관계문화가 가장 높고 위계문화가 가장 낮게 나왔다. 직무착근도 수준은 평균 3.524 를 보여주었고, 고객지향성 수준은 3.79로 나타났다. 윤리경영이 조직문화, 직무착근도, 고객지향성에 직접적으로 정적 영향을 미치는 것으 로 나타났고, 조직문화가 직무착근도에 직접적인 영향을 미칠 뿐만 아니라 고객지향성에 도 영향을 미치며, 윤리경영은 조직문화에 영향을 미치으로 윤리경영이 직무착근도에까 지 영향을 미치는 것을 알 수 있었다. . 한계점과 후속연구를 제언하자면 첫째, 노인장기요양기관의 특성에 맞는 윤리경영 측 정도구가 개발될 필요가 있다. 둘째, 다양한 지역의 요양보호사를 대상으로 본 연구와 유 사한 연구가 진행된다면 노인장기요양기관의 조직 윤리경영과 조직문화 수립 기여에 기 반이 될 것이라 판단된다. 셋째, 조직문화유형인 Quinn과 McGrath(1985)의 4가지 유형인 관계문화, 합리문화, 위계문화, 개발문화를 고찰하였다. Quinn과 McGrath(1985)의 4가지 문화유형만 연구한 것은 아쉬운 측면인데 본 연구 역시 마찬가지의 한계를 가지고 있다 고 하겠다. 넷째, 본 연구는 한 번의 설문을 수집하여 횡단적인 연구만 실시되어 변인들 간의 관계가 왜곡 될 수 있는 가능성을 가지는 한계가 있다.

As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

This study applies optimization-based algorithm to develop combination classification methods. We propose a genetic algorithm-based combination classification method of multiple decision trees to improve predictive accuracy, optimize classification rules, and interpret classification results. The basic algorithm for decision tree has been constructed in a top-down recursive divide-and-conquer manner. Based on different split measures (attribute selection measures), different decision tree algorithms can be produced, and then multiple decision trees can be formed. We proposed the parallel combination model of multiple decision trees. On top of the combination model, multiple decision trees are parallel combined. Each decision tree produces its own classification rules according to training samples from which one can present the classification result using probability distribution of target class label. At the bottom, the classification result of each decision tree serves as the input for combination algorithm in producing classification result and rules for the combination model. Combination algorithm adopts weighted summation of the outputs of probability measurement levels from individual decision trees, while genetic algorithm optimizes connection weight matrix. Finally the target class label with the largest probability output value is selected as the decision result for combination classification methods. The proposed method is applied to the issues of customer credit rating assessment and customer response behaviour pattern recognition in CRM. From the simulation results it is concluded that the proposed method has higher predictive accuracy than single decision tree. Moreover, it retains good interpretability and optimizes classification rules.

The channel transformation to omni-channel is currently in progress in the retail industry. For the progress to occur, facilitating meaningful experiences of customers in their customer journeys, capturing such experiences through various channels and touch points, and then analyzing the information acquired as big data are required (Lemon and Verhoef, 2016). With the increase in the number of customer experiences being observed through the internet and mobile communication, the focus is now on engagement. However, there have not yet been many studies conducted to deliberate comprehensively on how the engagements of behavioral aspects captured through various channels and the evaluation indicators of customers, as represented by the RFM or LTV, are related in a broader sense. The purpose of this research is to clarify the relational structure from a comprehensive perspective that are not constrained by monetary amounts. This paper showed results using data from the retailer. This research is divided broadly into two stages. The first stage identifies the engagements of behavioral aspects and the relationship between the respective behaviors, as well as the typification of behavioral patterns. The second stage involves clarifying the relationship between the customer’s evaluation indicators and engagement behaviors. The engagement behaviors are basically correlated with RFM, however authors found that there is no relationship between specific engagement behavior and RFM in the group of low rank customers. On the other hand, using different types of services or shops from the core business strengthens the customer relationship. Finally, the relationship between the types of engagement behaviors and the respective customer evaluation indicators is presented in the conclusion.

The purpose of this study is to explore the effects of social media in Customer Relationship Management (CRM) based on a theoretical foundation. Social media was firstly used as a new communication tool by internet users, and is being commercialized as a powerful tool to build and maintain long-term relationships between customers and businesses. This study focuses on service sectors and aims to clarify how social media helps companies innovate traditional CRM. Social CRM is seen as one of these service innovations and is highlighted in this paper.

The principal objective of this study was to categorize service attributes on the basis of the asymmetric and non-linear relationship existing between service attributes and customer satisfaction. Researchers generally assume that service attribute performances and customer satisfaction are both symmetrical and linear. That is to say, improvements in attribute performance will inevitably result in increased customer satisfaction. However, this is not always the case. Certain attributes have been shown not to create satisfaction even when improved, and others do not create dissatisfaction even when their performance ratings become negative. Understanding this relationship is crucial not only to researchers, but also to service managers. Service managers can arrange their priorities with regard to which attributes must be improved or promoted first, in an environment of limited technical, financial, and human resources. Many studies into this asymmetric and non-linear relationship have recently been conducted, beginning with Herzberg's motivation-hygiene theory (1976) and the disconfirmation theory, which was eventually developed into Kano's model (1984). This study attempted to determine the impact level of service attributes on incidents of satisfaction or dissatisfaction. It used 30 service attributes generated by Park (2008) in the CIT research into family restaurants. The data were collected from 600 participants, 300 incidences of satisfaction and 300 incidents of dissatisfaction, via an online survey. The t-test was used to confirm the difference between the satisfaction group's and dissatisfaction group's attributes. 11 attributes were found to be significant at a level of p>0.05. This indicates that the 11 attributes exerted different impacts on satisfaction and dissatisfaction, which confirmed the asymmetric and non-linear relationship. 14 attributes were categorized into the core service, 1 attribute into the quality service, 7 attributes into the basic service, and 8 attributes into the neutral service. Strategic customer service management was recommended for the 'A' family restaurant as an example, on the basis of the asymmetric and non-linear relationship and the characteristics of the four service factors.

많은 게임 개발자와 마케터들은 고객의 정보 분석과 질적 서비스 제공을 위해 지속적으로 진보하는 다양한 인터넷기술을 이용하고 있다. 하지만 일반적으로 활용되는 인터넷 고객분석 기술로서는 웹 페이지나 커뮤니티 활동으로부터 의 단편적인 게이머의 정보만을 얻을 수 있을 뿐이다. 이러한 문제점을 해결하기 위해서 구체적이고 객관적인 게이머의 감성을 표현 할 수 있는 방안으로 게임성에 대한 체계적 이해를 위하여 형용사 시소리스를 이용함으로써 감성적 표현을 플레이어의 의도에 따라 정확하게 나타낼 수 있도록 형용사의 의미적 상관관계를 분석할 수 있는 모델을 제시하여 실제로 게이머에 대한 정보를 지속적으로 수집하고 분석할 수 있는 시스템을 구축하여 효과적인 서비스를 제공하기 위하여 고객에 대한 체계적인 관리 모델인 CRM(Customer Relationship Management)을 게임에 적용 하고자 한다.

본 연구는 정기선 해운기업의 고객관계관리의 실제적인 내용을 살펴보고, 이러한 고객관계관리를 촉진시키는 조직의 전반적인 특성들을 고찰하여 조직특성과 고객관계관리와의 관계를 분석하고, 고객관계관리가 조직성과에 미치는 영향에 대하여 실증분석을 실시하였다. 분석결과, 정기선 해운기업의 고객관계관리에 영향을 미치는 조직특성은 시장지향성과 최고경영자의 지원으로 확인되었으며, 고객관계관리는 종업원만족도, 서비스경쟁력 향상, 재무적 성과, 그리고 고객만족도와 재구매의도에 유의한 영향을 미치는 것으로 확인되었다. 본 연구는 정기선 해운기업의 고객관계관리를 전사적 차원에서 조직문화와 관리체계 등의 조직특성들과 연계되어 시행되어야 한다는 것을 제시하였으며, 이러한 조직특성들을 바탕으로 한 고객관계관리 전략이 정기선 해운기업의 조직성과와 고객차원의 만족도 및 재구매의도의 전반적인 경영성과에 영향을 미치게 된다는 것을 실증함으로써, 정기선 해운기업의 고객관계관리를 해운기업 및 고객 관점에서 종합적으로 조사 분석하였다는데 연구의 의의가 있다고 하겠다.