• 제목/요약/키워드: Decision-making processes

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온라인 고객 리뷰에 대한 텍스트마이닝을 활용한 고객가치제안 방법 (Customer Value Proposition Methodology Using Text Mining of Online Customer Reviews)

  • 한영경;김철민;박광호
    • 산업경영시스템학회지
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    • 제44권4호
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    • pp.85-97
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    • 2021
  • Online consumer activities have increased considerably since the COVID-19 outbreak. For the products and services which have an impact on everyday life, online reviews and recommendations can play a significant role in consumer decision-making processes. Thus, to better serve their customers, online firms are required to build online-centric marketing strategies. Especially, it is essential to define core value of customers based on the online customer reviews and to propose these values to their customers. This study discovers specific perceived values of customers in regard to a certain product and service, using online customer reviews and proposes a customer value proposition methodology which enables online firms to develop more effective marketing strategies. In order to discover customers value, the methodology employs a text-mining technology, which combines a sentiment analysis and topic modeling. By the methodology, customer emotions and value factors can be more clearly defined. It is expected that online firms can better identify value elements of their respective customers, provide appropriate value propositions, and thus gain sustainable competitive advantage.

Determinants of Improving the Financial Security of Retired Women in Malaysia

  • ZAINUDDIN, Halimatul Nadia;MOHAMAD, Nor Edi Azhar;RAJADURAI, R. Jegatheesan V.;SAPUAN, Noraina Mazuin;SANUSI, Nur Azura
    • The Journal of Asian Finance, Economics and Business
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    • 제9권6호
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    • pp.11-21
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    • 2022
  • The perspectives on aging women's financial security during their retirement years are based on their behavior, planning, and decision-making processes during their working years. Elderly women are considered vulnerable and have a longer life expectancy, lower-income, and limited financial understanding compared to males; therefore, drastic steps need to be taken to improve their financial stability and quality of life. The current study sought to determine the most important contributors to retired women's financial health by measuring the value of four factors/variables: capability, opportunity, willingness, and biopsychosocial. This study used a mixed model approach, with qualitative analysis in the first phase involving a focus group discussion session, a pilot analysis, and quantitative analysis for phase two involving the distribution and collection of questionnaires completed by retired women. The surveys were distributed across Malaysia in five distinct zones and yielded 339 usable replies to support the theory. The outcomes of the Multiple Regression Analysis in Malaysia revealed that capability, opportunity, and biopsychosocial factors are significant predictors of retired women's financial security, whereas the willingness indicator lacked statistical significance.

The Impact of Ownership Structure and Audit Quality on Carbon Emission Disclosure: An Empirical Study from Indonesia

  • TARIGAN, Bahagia;PRAMONO, Agus Joko;RUSMIN, Rusmin;ASTAMI, Emita Wahyu
    • The Journal of Asian Finance, Economics and Business
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    • 제9권4호
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    • pp.251-259
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    • 2022
  • This study investigates the impact of ownership structures and audit quality on carbon emission disclosure. It also examines how audit quality affects the relationship between ownership structures and carbon emission disclosure. This research includes 106 standalone sustainability reports from non-financial companies that were listed on the Indonesia Stock Exchange (IDX) between 2015 and 2018. Our findings show that family and concentrated ownerships convey less information about carbon emissions. Our results fail to demonstrate that disclosure of carbon emissions could be a corporation's approach to respond to stakeholder pressure and public visibility and to provide legitimacy for its existence. We also find a positive and significant association between high-quality (Big4) auditors and carbon emission performance. Our further result suggests that Big4 auditors seem to compromise their high standard quality on auditing family and concentrated ownership firms. They fail to influence their family and concentrated ownership clients to be socially responsible. Policymakers should support the existence of Big4 auditors as a driver of carbon emission performance. Top management should be proactive to tackle carbon emission issues by adopting stakeholder-driven mechanisms and establishing legitimacy with society. Nevertheless, the involvement of family and highly concentrated shareholders in decision-making processes and information disclosure should not be encouraged.

XML-based Information Model for Interactive Electronic Technical Manual for Urban Regeneration Project

  • Sunghoon Kang;Hyun-Soo Lee;Moonseo Park;Jin-Wook Jung
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.841-846
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    • 2009
  • Recently, the construction industry is getting more complex and sophisticated having the characteristics of a mega project. Mega project pursues a value that can't be gained with an approach of seeing a project as just a simple sum of different parts but a mutual combination. However, the current manuals can't fulfill the needs for supporting, therefore, need a tool to support the decision making and an IETM is expected to take this role. Despite the a lot of expected advantages of IETM, it is still difficult to apply because of the frequent changes of information of detailed process and its complexity. In this research, as part of developing an IETM, we aim to propose a system frame which is based on the analysis of processes of a project. It is basic part of IETM to give information to users and IETM consists of normal mode that offers general information about the urban regeneration project and user-specified mode that gives classified and reorganized information to user. For supporting these functions, IETM should be stored in a form that can classify the information about urban regeneration project and be tagged with meaningful tags. Moreover IETM developers have to consider the interoperability of IETM because it ultimately should be coordinated with overall Project Management System like an iPMIS. We used XML for solution of interoperability because it stores information as just text-file that doesn't need a special form.

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Leveraging Reinforcement Learning for Generating Construction Workers' Moving Path: Opportunities and Challenges

  • Kim, Minguk;Kim, Tae Wan
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.1085-1092
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    • 2022
  • Travel distance is a parameter mainly used in the objective function of Construction Site Layout Planning (CSLP) automation models. To obtain travel distance, common approaches, such as linear distance, shortest-distance algorithm, visibility graph, and access road path, concentrate only on identifying the shortest path. However, humans do not necessarily follow one shortest path but can choose a safer and more comfortable path according to their situation within a reasonable range. Thus, paths generated by these approaches may be different from the actual paths of the workers, which may cause a decrease in the reliability of the optimized construction site layout. To solve this problem, this paper adopts reinforcement learning (RL) inspired by various concepts of cognitive science and behavioral psychology to generate a realistic path that mimics the decision-making and behavioral processes of wayfinding of workers on the construction site. To do so, in this paper, the collection of human wayfinding tendencies and the characteristics of the walking environment of construction sites are investigated and the importance of taking these into account in simulating the actual path of workers is emphasized. Furthermore, a simulation developed by mapping the identified tendencies to the reward design shows that the RL agent behaves like a real construction worker. Based on the research findings, some opportunities and challenges were proposed. This study contributes to simulating the potential path of workers based on deep RL, which can be utilized to calculate the travel distance of CSLP automation models, contributing to providing more reliable solutions.

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Customer Experience Management: An Innovative Approach to Marketing and Business on the Fashion Retail Industry

  • Arineli, Adriana
    • 융합경영연구
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    • 제4권2호
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    • pp.1-19
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    • 2016
  • The purpose of this study was to examine the issues involved in offering superior customer experience on fashion retail stores in Brazil. The approach used to access CEM (Customer Experience Management) issues was a special questionnaire with 23 questions, through a research with managers of three important brazilian fashion retail chains (focused on class A clients). Some statistical techniques were used for data processing. It was possible to analyze the aspects that impact on the customer experience and their relevance. it was possible to realize that CEM is effective in increasing productivity and, so, it can be used as a guideline matrix management in decision making to promote superior customer experiences. The classical management is usually conservative and avoids to deal with strategies that do not necessarily involve numbers. Dealing with intangible and so subtle experience is unusual and a huge challenge, but sometimes it is necessary to look beyond the obvious and accessible statistics. If CEM is a strategy to focus on operations and processes of a business around the customers experiences with the company, it is essential to structure it and find out its effectiveness.

TOWARDS A SPATIAL FRAMEWORK FOR SUPPORTING BUILDING CONSTRUCTION INSPECTION

  • Saud Aboshiqah;Bert Veenendaal;Robert Corner
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.558-565
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    • 2013
  • The process and efficiency of monitoring building and construction violations is a concern of the construction industry. The detection of violations requires appropriate and sufficiently accurate spatial information to manage and support a comprehensive inspection process and monitor compliance. A building inspection workflow must extract appropriate spatial and measurement in-formation from a variety of sources, identify potential violations across a range of compliance criteria and determine the quality of resulting inspection reports. This paper presents a framework for supporting building inspections using spatial information and methods to detect construction violations and compliance. Current inspection processes involve issues around the identification of building violations, access to building regulations and existing spatial information, integration of a range of spatial and non-spatial information, and the quality of decisions within the inspection workflows. A survey of building inspectors was conducted and used together with the issues identified to establish the requirements for a spatial inspection framework. The results demonstrate how such a framework can support improved decision-making and reduced fieldwork effort in detecting and measuring the accuracy of building violations involving building placements, street offsets and footprint areas.

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THE IDENTIFICATION OF MALAYSIAN CONTRACTOR SATISFACTION DIMENSIONS: A STRATEGY FOR CONTINUOUS IMPROVEMENT

  • Md Asrul Nasid Masrom;Martin Skitmore;Adrian Bridge
    • 국제학술발표논문집
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    • The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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    • pp.335-339
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    • 2011
  • The unique characteristics of the construction industry - such as the fragmentation of its processes, varied scope of works and diversity of its participants - are contributory factors to poor project performance. Several issues are unresolved due to the lack of a comprehensive technique to measure project outcomes including: inefficient decision making, insufficient communication, uncertain site conditions, a continuously changing environment, inharmonious working relationships, mismatched objectives within the project team and a blame culture. One approach to overcoming these problems appears to be to measure performance by gauging contractor satisfaction (Co-S) levels, but this has not been widely investigated as yet. Additionally, the key Co-S dimensions at the project level are still not fully identified. This paper concerns a study of satisfaction dimensions, primarily by a postal questionnaire survey of construction contractors registered by the Malaysian Construction Industry Development Board (CIDB). Eight satisfaction dimensions are identified that are significantly and substantially relate to these contractors - comprising: project cost performance, schedule performance, product performance, design satisfaction, site safety, project profitability, business performance and relationships between participants. -Each of these dimensions is accorded different priority levels of satisfaction by different contractors. The output of this study will be useful in raising the awareness and understanding of project teams regarding contractors' needs, mutual objectives and open communication to help to deliver a successful project.

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감성분석을 통한 소프트 파워의 수치화 분석 (Quantification Analysis of Soft Power through Sentiment Analysis)

  • 안민;김봉현
    • 산업과 과학
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    • 제3권2호
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    • pp.1-7
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    • 2024
  • 본 논문은 감성분석을 통한 소프트 파워의 수치화를 주제로 다루고 있다. 감성분석은 텍스트, 음성, 이미지 등 다양한 데이터에서 감정이나 감성을 탐지하고 분석하는 과정을 의미한다. 따라서, 본 논문에서는 감성분석을 통해 소프트 파워를 어떻게 수치화할 수 있는지에 대한 방법론과 그 의의를 탐구하였다. 소프트 파워는 국가나 단체가 다른 국가나 단체의 행동을 원하는 방향으로 영향을 주는 능력을 의미한다. 이는 군사적 또는 경제적 수단보다는 문화, 가치관, 정치체제 등의 부드러운 요소에 의해 구축되며, 감성분석은 이러한 부드러운 영역을 측정하고 이해하는 데 유용한 도구로 활용되고 있다.

A Study on Diabetes Management System Based on Logistic Regression and Random Forest

  • ByungJoo Kim
    • International journal of advanced smart convergence
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    • 제13권2호
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    • pp.61-68
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    • 2024
  • In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.