• Title/Summary/Keyword: success intelligence

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An Exploratory Study on Policy Decision Making with Artificial Intelligence: Applying Problem Structuring Typology on Success and Failure Cases (인공지능을 활용한 정책의사결정에 관한 탐색적 연구: 문제구조화 유형으로 살펴 본 성공과 실패 사례 분석)

  • Eun, Jong-Hwan;Hwang, Sung-Soo
    • Informatization Policy
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    • v.27 no.4
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    • pp.47-66
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    • 2020
  • The rapid development of artificial intelligence technologies such as machine learning and deep learning is expanding its impact in the public administrative and public policy sphere. This paper is an exploratory study on policy decision-making in the age of artificial intelligence to design automated configuration and operation through data analysis and algorithm development. The theoretical framework was composed of the types of policy problems according to the degree of problem structuring, and the success and failure cases were classified and analyzed to derive implications. In other words, when the problem structuring is more difficult than others, the greater the possibility of failure or side effects of decision-making using artificial intelligence. Also, concerns about the neutrality of the algorithm were presented. As a policy suggestion, a subcommittee was proposed in which experts in technical and social aspects play a professional role in establishing the AI promotion system in Korea. Although the subcommittee works independently, it suggests that it is necessary to establish governance in which the results of activities can be synthesized and integrated.

An Analysis on Success Factor of CRM Implementation Using AHP Technique (AHP 기법을 이용한 CRM 도입의 성공요인분석)

  • Sin Taek-Su;Ham Jun-Seok;Hwang Jae-Hun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.463-466
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    • 2004
  • This paper suggests the evaluation method of success factors of CRM implementation using AHP technique, and presents why firms implement CRM, how it could be successfully implemented, and what is the most important factor. For the purpose, this study applies the method to department stores' industry. AHP structure consists of three steps to determine CRM's key success factors. First of all, strengthening loyalty of customers, improvement of service quality, upgrade of intelligence system and advancement of management process are selected as superordinate object (i.e. CRM-implementation goal). The next project factor, technology/data factor and organizational factor were decided as success factor of CRM-implementation. Subordinate criteria of project factor consist of 11 criteria. The experimental results of this study show that department stores think advancement of management process and improvement of service quality as most important purposes for CRM implementation. The results also indicate that among the subordinate success factors, accuracy of customer information, conversion to customer-oriented business model, practical use of experienced consultant, and establishing IT infrastructure for CRM are evaluated as most important success factors for CRM implementation.

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Emotional and Cognitive Determinants of Retail Salespersons' Emotional Labor and Adaptive Selling Behavior

  • KIM, Joonhwan;CHU, Wujin;LEE, Sungho
    • Journal of Distribution Science
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    • v.20 no.9
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    • pp.109-126
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    • 2022
  • Purpose: The role of salespersons' emotions in effective selling behavior garners attention among scholars and practitioners. Previous studies have investigated the effects of emotional intelligence and emotional labor on sales success separately. However, to understand the whole process, the relationships among salespersons' cognition, emotions, and behaviors should be considered simultaneously. Accordingly, we uniquely examined how salespersons' emotional intelligence (emotional antecedent) and customer orientation (cognitive antecedent) influence their emotional labor (deep acting vs. surface acting), adaptive selling behavior, and the selling results in the retail environment. Research design, data, and methodology: To improve methodological rigor, we used the dyadic approach. We measured 182 salespersons' emotional intelligence, customer orientation, and emotional labor, and 364 customers assessed the salespersons' adaptive selling behavior and selling results in the insurance and duty-free department retailing sectors. Result: The findings suggest that salespersons' customer orientation and emotional intelligence relate to deep-acting of emotional labor, affecting their adaptive selling behavior and relationship quality with customers. Conclusions: As for managerial implications, sales managers may well consider emotional intelligence levels when selecting salespersons in the retail industry. Additionally, practical training programs are required to cultivate customer orientation, emotional intelligence, and deep acting while performing emotional labor.

The Effect of Training, Information Technology, Intellectual and Emotional Intelligence on Teacher's Performance

  • INGSIH, Kusni;PRAYITNO, Agus;WALUYO, Dwi Eko;SUHANA, Suhana;ALI, Shujahat
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.577-582
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    • 2020
  • The performance of a teacher has an important role in the success of education in general. This study aims to determine the factors that affect the decline in teacher performance in one of the junior secondary schools in Indonesia. Based on the literature review, four exogenous variables were identified, namely, training, utilization of information technology, intellectual intelligence, and emotional intelligence. This study uses primary data, collected from a questionnaire distributed to respondents. The questionnaire items are measured using a Likert scale. The sample in this study were all teachers at MTS Darul Falah Sirahan, totaling 32 people. The analysis technique used in testing the hypothesis of this study is multiple regression analysis. Statistical product and service solutions are used as analysis tools. The results of this study indicate that only the variable 'utilization of information technology' has a positive and significant effect. However, the variables 'training,' 'intellectual intelligence,' and 'emotional intelligence' did not have a significant effect. This finding contradicts the literature in general. Therefore, this study recommends improving training methods, both those carried out internally by schools and by related agencies, and schools still need to optimize guidance and potential for teacher's intelligence in improving performance.

What factors drive AI project success? (무엇이 AI 프로젝트를 성공적으로 이끄는가?)

  • KyeSook Kim;Hyunchul Ahn
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.327-351
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    • 2023
  • This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.

Weight Analysis of Critical Success Factors for Business Intelligence System (비즈니스 인텔리젼스 시스템 성공요인의 중요도 분석)

  • Hong, Hyun-Gi
    • Journal of Digital Convergence
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    • v.10 no.7
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    • pp.93-98
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    • 2012
  • The rapid change of business environments request the company to act more smart and intelligent in making business strategies and planning the business processes. To meet this requirement, we need to have smart Business Intelligent System(hereinafter "BI") in the company. On the one hand, many korean companies had already installed BI system, and the other hand some companies have plans to implement BI Systems additionally to their Information System. It is very important to have the pictures which factors are critical to the successful implementation of BI, and to survey which critical success factor(hereinafter CSF) are important compared to each factors. In this paper data was gathered from companies already have their BI Systems. We measured IT-Infra maturity, User Education, and Company Organization, and Company Business Strategy, which are the critical success factors for the BI System. After surveying the CSF of BI System, we measured the weights among these factors by AHP. Factor analysis resulted in 6 major factors (Eigenvalue > 1.0), and the AHP analysis showed the list of CSF's weight list according to its significance priorities. The results of this paper could be the valuable references for the implementing process of the BI System in korean company.

The Mediating Effects of Bidirectional Knowledge Transfer on System Implementation Success

  • Kim, Jong Uk;Kim, Hyo Sin;Park, Sang Cheol
    • Asia pacific journal of information systems
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    • v.25 no.3
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    • pp.445-472
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    • 2015
  • Although knowledge transfer between two different parties occurs in IS development projects, the majority of prior studies focused on knowledge transfer from IT consultants to clients. Considering two parts of knowledge transfer in IS development projects, we must consider both 'where knowledge is transferred from' and 'where it is transferred to'. Therefore, in this study, we attempt to describe two different routes of knowledge transfer, such as knowledge transfer from an IT consultant to a client and knowledge transfer from a client to an IT consultant. In this regard, we have examined the effect of two different routes of knowledge transfer on system implementation success in IS development project. Specifically, we adopted the knowledge stock-flow theory to examine the causal relationship between IT consulting firms and clients in terms of knowledge transfer and eventual system implementation success. Survey data collected from 213 pairs of individuals (both clients and IT consultants) were used to test the model using three different analytic approaches such as PLS (partial least squares) and two types of mediated regression techniques. We found that knowledge transfers partially mediated both the relationships between IT consultants' IT skills (project members' business knowledge) and system implementation success. Furthermore, the effects of each knowledge transfer were distinguished by depending on the types of system, such as ERP or groupware. Our attempts have significant implications for both research and practice given the importance of effective knowledge transfer to IT consulting.

Critical Factors Affecting the Adoption of Artificial Intelligence: An Empirical Study in Vietnam

  • NGUYEN, Thanh Luan;NGUYEN, Van Phuoc;DANG, Thi Viet Duc
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.5
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    • pp.225-237
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    • 2022
  • The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

ETRI AI Strategy #2: Strengthening Competencies in AI Semiconductor & Computing Technologies (ETRI AI 실행전략 2: AI 반도체 및 컴퓨팅시스템 기술경쟁력 강화)

  • Choi, S.S.;Yeon, S.J.
    • Electronics and Telecommunications Trends
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    • v.35 no.7
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    • pp.13-22
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    • 2020
  • There is no denying that computing power has been a crucial driving force behind the development of artificial intelligence today. In addition, artificial intelligence (AI) semiconductors and computing systems are perceived to have promising industrial value in the market along with rapid technological advances. Therefore, success in this field is also meaningful to the nation's growth and competitiveness. In this context, ETRI's AI strategy proposes implementation directions and tasks with the aim of strengthening the technological competitiveness of AI semiconductors and computing systems. The paper contains a brief background of ETRI's AI Strategy #2, research and development trends, and key tasks in four major areas: 1) AI processors, 2) AI computing systems, 3) neuromorphic computing, and 4) quantum computing.

The Impacts of Project Governance, Agency Conflicts on the Project Success : From the Perspective of Agency Theory (프로젝트 거버넌스가 대리인 갈등 및 프로젝트 성공에 미치는 영향 : 대리인 이론 관점)

  • Jeong, Eun-Joo;Kim, Bo-Ram;Jeong, Seung-Ryul
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.3
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    • pp.11-20
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    • 2018
  • Recently companies have increased the new projects to improve and innovate the business process in order to adopt the advanced technologies such as IoT (Internet of Things), Big Data Analysis, Cloud Computing, mobile and artificial intelligence technologies for sustainable competitive advantages under rapid technological and socioeconomic external environmental changes. However, there are obstacles to achieve the project goals, corporate's strategy and objectives due to various kind of risks based on characteristics of projects and conflicts of stakeholders participated on projects. Hence, the solutions are required to resolve the various kind of risks and conflicts of stakeholders. The objectives of this study are to investigate the impact of the project governance, agency conflicts on the project success based on agency theory by using the statistical hypothesis testing the relationship among those variables. As a result of hypothesis testing, we could find that the project governance impacts positively on project success and negatively on the agency conflicts. Further, the agency conflicts impacts negatively on the project success. Finally, we could find that the agency conflicts such as goal conflict, different risk attitude and information asymmetry between project manager and team members impact negatively on the project success. Meanwhile, the project governance impact positively on the project success, negatively impact on the agency conflicts such as goal conflict, different risk attitude and information asymmetry between project manager and project team members. In order to increase the project success rate, the project governance institutions such as PGB (Project Governance Board), EPMO (Enterprise Project Management Office), PSC (Project Steering Committee) are needed to prevent or reduce the agency conflicts between project manager and team members.