• 경영과정보연구
• /
• 제5권
• /
• pp.61-79
• /
• 2000

This research suggests the strategic adoption methodology of Customer Relationship Management. The backgrounds of CRM is the business environment changing that Market power is shifting to the customer who has unprecedented powers of choice today. The strategic adoption of Customer Relationship Management determines the value, needs and preferences of each customer or customer segment. Customer Relationship Strategy is an explicitly defined plan for how a company has decided to connect with, relate to, and focus on its chosen customers to create value. Deliberate decisions must be made, often involving trade-offs, so that investments are aligned with customer needs and value. Plan defined in terms of target customers value proposition, role in value delivery, and risk/reward sharing. All customers are not created equal; specific customers and/or customers segments are more desirable/valuable to pursue. Key premise of CRM is that value can be created by changing company's business model to better connect with customers. Area of service of Customer Relationship Management are as follows. Portfolio strategy, Market Opportunity Assessment, Brand Equity, Market Positioning, Pricing, Channel Strategy, Market Segmentation. Target Market Identification, Customer LifeTime Value Analysis, Customer Profitability, Customer Connections Economics Analysis. The objects of CRM are maximizing customer service effectiveness, improving customer loyalty, increasing customer service efficiency, optimizing intelligence about customer behaviors and preferences.

• 한국산업융합학회 논문집
• /
• 제25권3호
• /
• pp.467-476
• /
• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• 대한융합한의학회지
• /
• 제5권1호
• /
• pp.25-44
• /
• 2023

Objectives: Gaming disorder has been viewed as a disease in the DSM-5 and ICD-11. Its essential symptoms are loss of control over gaming, gaming becoming a markedly prioritized activity over other activities of daily living, and continued and excessive use of gaming despite negative problems occurring. Methods: Children and adolescents are especially vulnerable to gaming disorder because the striatal pathways related to reward develop earlier than the control regions of the prefrontal cortex. It is also associated with decreased dopamine D2 receptors. Addiction is related to 'want' and is explained by incentive-sensitization. In addition, allostasis, in which homeostasis is continuously achieved at a new target value, is also related to gaming disorder. In addition, personality causes, unchangeable factors, and external factors can influence on the onset of gaming disorder. Results: Prevention is the best solution for gaming disorder, and the role of parents is important. For gaming disorder, bupropion is used, cognitive-behavioral therapy and family-based therapy are also beneficial. Herbal medicine treatment such as Antler velvet and ginseng can be effective. Electroacupuncture and acupuncture using PC6, SP6, and LR3 has a correlation with relieving Internet craving. Ear-acupuncture was also effective in treating addiction. Conclusion: Psychologically, 'want' is an intense longing for reward and motivation, and is related to addiction. This 'want' may rather be related to avoidance, and game addiction in children and adolescents may be due to wanting to escape from academic stress or avoidance of comparison. Therefore, the importance of 'like', which gives pleasure in itself, increases. It can also be explained with Sasang Constitutional Medicine.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2006년도 춘계종합학술대회
• /
• pp.115-119
• /
• 2006

채널은 무선망에 있어서 한정된 주요 자원 중의 하나이다. 다양한 채널 관리 기법들이 제시되어 왔으며, 최근 들어 가드채널의 최적화 문제가 부각되고 있다. 본 논문에서는 신경망을 이용한 지능적인 채널 관리 기법을 제안한다. 신경망의 학습 데이터 생성과 성능분석을 위하여 SRN(Stochastic Reward Net) 채널 할당 모델이 개발된다. 제안된 기법에서 신경망은 지도학습 방법인 역전파 알고리즘을 이용하여 최적의 가드채널 값 g를 계산하도록 학습한다. 학습된 신경망을 이용하여 최적의 g를 계산하고, 이를 SRN모델에서 구해진 결과와 비교한다. 실험결과는 신경망에서 구한 가드채널 수와 SRN 모델로부터 구한 가드채널 수의 상대적 차이가 없음을 보여준다.

• Asia pacific journal of information systems
• /
• 제17권4호
• /
• pp.1-29
• /
• 2007

The brand-based online community recently plays an important roles for consumers to facilitates searching and sharing information among them. Firms often find such a brand community as a critical channel to gain collective intelligence for developing new ideas and products. As a new web platform such as web 2.0 has been introduced, consumers could more easily participate in the new social networks created by sharing mutual value and belief among themselves. Accordingly firms began to recognize potentials of online brand assets and pay attention to the importance of online brand community loyalty. Previous research related to online community tends to focus on identifying the antecedents of community loyalty and their subsequent impacts on brand. They, however, tend to neglect the importance of individual characteristics of online community users. As integrating the fragmented variables with an individual characteristics, therefore, this study reexamined the impacts of interactivity, information, reward, and personalization services provided by an online brand community on the sense of community, community loyalty, and brand attitude. Also, this study investigated how users' individual characteristics(need for cognition: NFC) can play moderating roles among the variables identified in the previous research. A field survey was administrated and 671 valid samples were collected. In order to test the hypothesis we conducted the multi-sample structural equation modeling(MSEM) between two groups(a group with high vs. a group with low level of NFC). Results show that previously identified variables such as interactivity, information, reward, and personalization services have significant effects on the sense of community as previous research demonstrated. Subsequently, the sense of community positively influences the community loyalty and brand attitude. However, when considering the NFC as a moderating variable, we found that the effect of interactivity and reward service on the sense of community was stronger for a group with a lower level of NFC compared to a group with a higher level, while the effect of information providing service on the sense of community was stronger for a group with a higher level of NFC compared to a group with a lower level. This research revealed that NFC can affect the degree of individual perception on the sense of community which has been considered as an important indicator for the community loyalty and brand attitude. Hence, when firms developing customer relation strategy through building an online brand community, they need to reflect customers' NFC and accordingly provide varying degree of interactivity, information, reward, and personalization services.

• 인지과학
• /
• 제28권4호
• /
• pp.245-265
• /
• 2017

최근 인지적 통제에 대한 연구들은 최적의 통제 수준이 보상과 비용에 의해 결정된다는 것을 밝혀냈다. 보상이 가지는 가치는 주관적이며 이에 따라 최적의 신호 강도도 달라진다. 우리는 인지적 통제에 대한 노화의 영향에 대한 연구 결과들이 비일관적인 이유가 노인이 탄력적으로 통제 신호를 조절한 결과일 수 있다고 보았다. 다시 말해, 노인은 최적의 통제 수준을 결정하는 능력을 잘 유지하고 있을 수 있는데, 이는 전대상회의 역할로 알려져 있다. 반면 인지적 통제에서 노화에 따른 기능의 감퇴는 주로 규칙 표상의 유지와 억제에서 나타나는데, 이는 주로 외측전전두피질이 담당하고 있다. 본 연구는 청년과 노인에게 보상의 유형을 조절한 Go-Nogo 과제를 수행하게 하여 각 보상 조건에서 행동결과와 ERN(Error-Related Negativity) 크기를 비교하였다. 두 집단 모두는 각 연령에게 가장 중요하다고 여겨지는 조건에서 가장 뛰어난 행동 수행과 가장 큰 ERN 크기를 나타내었다. 또한 노인은 d'과 정확률에서는 연령차를 나타내었으나 ERN의 크기에서는 연령차를 나타내지 않았다. 이와 같은 결과는 인지적 통제의 각 과정에 대한 노화의 영향이 상이할 수 있을 가능성을 보여준다.

• 한국산림과학회지
• /
• 제105권4호
• /
• pp.496-504
• /
• 2016

숲길에 대한 국민들의 관심이 높아지면서 숲길체험활동에 대한 확대가 중요한 시점이다. 본 연구는 건전한 숲길이용을 위한 체험활동의 목표를 달성하고, 이용자의 만족도를 충족시키기 위해 숲길체험지도사의 조직몰입과 직무동기를 중점으로 두 변수간의 관계를 규명하고, 직무동기 요인에 따른 조직몰입도의 차이를 확인하였다. 연구결과 첫째, 숲길체험지도사 직무동기는 '개인적 만족추구', '일 자체의 가치', '외적 보상 인정'요인으로 구분되었고, 개인적 만족추구, 일 자체의 가치, 외적 보상 인정 순으로 높게 나타났다. 둘째, 직무동기는 조직몰입과 정의 상관관계가 있었으며, 특히 개인적 만족추구와 외적 보상 인정에 있어서 정의 영향을 미치는 것으로 분석되었다. 숲길체험지도사의 직무동기의 하위요인 가운데 '개인적 만족추구'는 타 하위요인보다 직무몰입과의 관계에 미치는 영향이 큰 것으로 나타나, 숲길체험지도사로서의 활동이 개인에게 자부심을 가질 수 있도록 하는 등의 개인적 만족감을 높여주는 방안 강구가 필요하다.

• 한국산학기술학회논문지
• /
• 제19권4호
• /
• pp.254-264
• /
• 2018

본 연구의 목적은 학교급식 조리종사자의 이직의도에 미치는 직무환경 요인(six areas)과 태도 요인(조직몰입)의 영향을 확인하고, 직무환경이 요인이 이직의도에 영향을 미치는 과정에서 조직몰입의 매개역할을 확인함으로써 이직의도를 낮추기 위해 조직이 개입할 수 있는 요소를 찾기 위함이다. 연구대상은 학교급식 현장에서 근무 중인 조리사로 총 205명의 자료를 분석에 이용하였다. 측정변인 중 직무환경은 여섯 가지 요인(작업량, 통제감, 보상, 공정성, 커뮤니티, 가치)이 측정되었으며, 조직몰입은 정서적 몰입과 계속적 몰입으로 구분하여 측정하였다. 연구결과 직무환경 요인 중 직무의 가치, 작업량, 보상 및 직원 간 커뮤니티를 부정적으로 지각할수록 정서적 몰입이 낮게 나타났고, 통제감과 공정성을 부정적으로 지각할수록 계속적 몰입이 높게 나타났으며, 보상과 커뮤니티를 부정적으로 지각할수록 이직의도가 높게 나타났다. 조직몰입과 이직의도의 관계에서는 정서적 몰입만이 이직의도에 부적 영향을 미치고 있었다. 이러한 관계를 직무환경 요인이 조직몰입을 매개로 이직의도에 영향을 미치는 매개모형으로 구성하여 검증한 결과, 직무환경 요인들 중 이직의도에 직접영향을 미치는 요인은 보상과 커뮤니티뿐이었으며, 여섯 하위요인 모두 정서적 몰입의 매개를 통해 이직의도에 통계적으로 유의한 영향을 미치고 있는 것으로 나타났다. 이러한 결과는 직무환경 변인이 개인의 태도 변인을 통해 행동으로 이어지는 과정을 보여주는 것으로써, 물리적 보상이나 작업량 등 조직이 쉽게 조정하기 어려운 직무환경 요인의 영향이 존재하는 경우에도 교육이나 사회적 지지 등 다양한 개입을 통해 종업원의 정서적 몰입을 유지해 줌으로써 이직의도의 증가를 통제할 수 있음을 확인하였다는데 의미가 있다.

• Journal of information and communication convergence engineering
• /
• 제19권1호
• /
• pp.1-7
• /
• 2021

Reinforcement learning is an area of machine learning that studies how an intelligent agent takes actions in a given environment to maximize the cumulative reward. In this paper, we propose a new MAC protocol based on the Q-learning technique of reinforcement learning to improve the performance of the IEEE 802.11 wireless LAN CSMA/CA MAC protocol. Furthermore, the operation of each access point (AP) and station is proposed. The AP adjusts the value of the contention window (CW), which is the range for determining the backoff number of the station, according to the wireless traffic load. The station improves the performance by selecting an optimal backoff number with the lowest packet collision rate and the highest transmission success rate through Q-learning within the CW value transmitted from the AP. The result of the performance evaluation through computer simulations showed that the proposed scheme has a higher throughput than that of the existing CSMA/CA scheme.

• 제어로봇시스템학회논문지
• /
• 제3권4호
• /
• pp.350-356
• /
• 1997

It is desirable for autonomous robot systems to possess the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Although Q-learning requires a lot of memory and time to optimize a series of actions in a continuous state space, it may not be easy to apply the method to such a real environment. In this paper, for continuous state space applications, to solve problem and a triangular type Q-value model\ulcorner This sounds very ackward. What is it you want to solve about the Q-value model. Our learning method can estimate a current Q-value by its relationship with the neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to move smoothly in a real environment. To show the validity of our method, navigation comparison with Q-learning are given and visual tracking simulation results involving an 2-DOF SCARA robot are also presented.