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4th International Conference on management Science and industrial engineering, MSIE 2022

作者： Prasetyo, Yogi Tri Regondola-Bolata, Lauren Nadlifatin, Reny Persada, Satria Fadil Chuenyindee, Thanatorn Ardiansyahmiraja, Bobby School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines Continuous Quality Improvement Office Mapúa University Manila Philippines Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Entrepreneurship Department Binus Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok10220 Thailand Faculty of Business and Economics Universitas Surabaya Surabaya Indonesia

ISBN: (纸本)9781450395816

Student feedback is an important part of service quality of a private university. The purpose of the study was to evaluate undergraduate students' feedback towards service quality of private university. A total of 1555 questionnaires and a total of 201 negative comments were collected from one private university in the Philippines during one academic year. For students' comments, classification schemes were utilized to organize the meaningful categories. It showed that negative personality traits of the employees and poor student accommodation were two most frequent negative comments. Classification schemes were found as a powerful tool to evaluate the students' feedback towards service quality. Finally, that this approach can be applied and extended to analyze students' feedback in different private universities worldwide. © 2022 ACM.

关键词： Quality of service

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Portfolio Selection Using Mean Variance Theory Based on the 30-year Historical Returns of Selected Subsectors of the Philippine industrial Sector

Portfolio Selection Using Mean Variance Theory Based on the ...

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IEEE International Conference on industrial engineering and engineering management

作者： A. D. Yamanaka M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadlifatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Finance Chung Yuan University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

Portfolio selection is an important part of investment management that aims to select the right combination of assets to achieve an optimal risk-return ratio. This study integrates the Mean-Variance Theory utilizing the 30-year historical returns of the Philippine Stock Exchange. Three subsectors of the industrial Sector were used as the investment pool. The back-test results showed that the MeanVariance portfolios of selected subsectors can outperform the industrial sector and not the market. Stakeholders must be cautious when investing in these three subsectors, considering the values obtained from the simulations. There are recommended portfolio selections wherein companies have a specific allocation that investors and financial managers can use whenever they decide to invest in these subsectors. Overall, this study offers a framework for investors to use as a guide in diversifying their stakes in the Philippine Stock Exchange.

关键词： Companies Benchmark testing industrial engineering Market research Stakeholders Resource management Stock markets Portfolios Optimization Investment

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Mean Variance Portfolio Selection Utilizing Services Subsector’s (Media, Telecommunications, and Information Technology) 30-Year Philippine Stock Exchange Trading Data

Mean Variance Portfolio Selection Utilizing Services Subsect...

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IEEE International Conference on industrial engineering and engineering management

作者： E.D. Salazar M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadilfatin Myra F. Contreras School of Industrial Engineering and Engineering Management Mapúa University Intramuros School of Graduate Studies Mapúa University Intramuros Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institur Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

The Philippine Stock Exchange (PSE), established in 1927, has significantly evolved, especially since the 1980s with major reforms and technological advancements. This paper analyzes the performance of portfolios in the Media, Telecommunications, and Information Technology sectors listed on the PSE over a 30year span. Using mean-variance analysis, it evaluates portfolio optimization by balancing risk and return. Drawing on data from 1993 to 2022, the study examines portfolios across various risk-return frontiers (RRFs) and compares the service sector’s performance. The results highlight varying portfolio metrics across RRFs, with some showing outperformance and higher RRFs leading to diminishing returns. The study also identifies key companies with significant stock allocations, providing strategic insights for portfolio construction. These findings offer investors guidance on optimizing portfolio strategies within the PSE for better decision-making and investment outcomes.

关键词： Measurement Decision making Companies Media Telecommunications Resource management Stock markets Portfolios Optimization Investment

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Grinding wheel specification cybernetic recommendation with multi-task multi-imbalanced learning in smart manufacturing system

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Advanced engineering Informatics 2024年 61卷

作者： Yao, Kuo-Ching Chen, Tzu-Li Chen, James C. Li, Chia-Ruei International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan Kinik Company New Taipei23942 Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei106335 Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu300044 Taiwan

Over the years, the grinding wheels industry has played a crucial role in mechanical engineering. Grinding wheel specification is composed of various factors such as abrasive type, wheel grade, bond type, and more, which are derived from customer workpiece operation information. Traditionally, the determination process of grinding wheel specifications is complicated. Experienced engineers need to check out the limitation and consider the interaction of each factor. When the new specification order comes, engineers have to spend a lot of time on historical data search and discussion. Recently, the application of artificial intelligence attracts more and more attention in the manufacturing industry. Through collecting historical data, the model has the ability to extract the domain knowledge, predict the specification that does not exist, and reduce the decision time. However, when training the model, this grinding wheel specification faced multiple imbalanced targets and multi-task issues. In the past, research efforts primarily focused on studying single-task learning (STL) algorithms. Seldom of them has a systematic way to discuss the model determination of multiple targets and correlation influence, especially on the tabular-type dataset. In this study, we proposed a multiple resampling chain multi-task learning framework to address the issue of data science. To tackle the multi-task imbalance resampling problem, we also proposed a resampling strategy called Multiple Resampling Chain. Moreover, we conducted a sensitivity analysis to examine the correlation effect on model improvement. Finally, we proposed a cyber-recommendation system that integrates the training model and interface to provide a more intuitive way of specification prediction. This system not only can help engineers to improve the time spent on making decisions, but also make the whole manufacturing process to be more intelligent. © 2024 Elsevier Ltd

关键词： Grinding (machining)

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Gradient Boosting Model for Water Quality Forecasting

Gradient Boosting Model for Water Quality Forecasting

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International Conference on Data Analytics and management, ICDAM 2023

作者： Panda, Parnani Banerjee, Sushovan Mishra, Sushruta Shashidhar, Chitra de Albuquerque, Victor Hugo C. Reis, Marcello Singh, Pooja Kalinga Institute of Industrial Technology Deemed to Be University Bhubaneswar India Department of Commerce and Management Seshadripuram College Bengaluru560020 India Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza Brazil Federal University of Ceará Ceará Brazil Fort Lauderdale United States Lead of the Biomedical Data Analytics Research Group Bengaluru India Federal Institute of Ceará Ceará Brazil Meteora Consultoria Fortaleza Brazil Galgotias University Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819965465

The aim of our study is to evaluate the quality of water using machine learning methods. Potability is a subjective word that quantifies water quality. In this research, a variety of metrics were used to measure general potability of the water. The prescribed elements are applied like variable matrix to denote water quality. The article used three different classification methods, with success rates ranging from 84.27 to 93.16%, to predict the water quality class including ensemble approach like Random Forest (RFC), SVM for classification (SVC), as well as XGBoost. The Gradient Boosting approach, out of all the ones used, received the greatest accuracy (93.16%), precision (96.3%), recall (92.76%) and F-score (94.54%). Also, it achieved the least computational delay with a mean latency of 1.34 s. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Water quality

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Contingency perspective to bridge human capital perception to achieve ambidexterity in environmental dynamism

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Social Sciences and Humanities Open 2024年 9卷

作者： Yunita, Tyna Sasmoko, Sasmoko Bandur, Agustinus Alamsjah, Firdaus Management Department BINUS Business School Doctor of Research in Management Bina Nusantara University Jakarta 11480 Indonesia Faculty of Economics and Business Universitas Bhayangkara Jakarta Raya Jakarta Indonesia Management Department BINUS Business School Doctor of Research in Management & Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta 11480 Indonesia Industrial Engineering Department BINUS Graduate Program—Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

Environmental change and technological disruption are expanding phenomena impacting today's economic world. A dynamic business environment can inspire companies to engage in both exploitative and exploratory innovation at the same time. Traditional financial technologies have evolved substantially over the past decade. Although the environment challenges technology to adapt to business sustainability, artificial intelligence has not replaced human bankers. There is, however, a scarcity of research on the relationship between ambidextrous work and human capital, indicating that few studies have been undertaken. To better understand how banks can achieve such organizational ambidexterity, we develop a framework that investigates the combined effects of organizational human capital (O-HC), environmental dynamism (END), and technological capacity (TEC) on organizational ambidexterity (ORA). The theory of contingency is the theoretical foundation of the subject. This quantitative analysis used a sample size of sixty-three executives from Indonesia's banking industry and was analyzed using PLS-SEM and SPSS to determine the measurement and structural models. The results show that TEC and O-HC directly affected ORA, but END did not. We also found that firms with O-HC are more likely to utilize high TEC to promote ORA. The findings of this study provide practitioners with insight into how they can promote human capital and TEC as pillars of ambidextrous banking. This research contributes to the literature on ORA and offers managers insights on aligning their knowledge practices to develop TEC when pursuing ORA. © 2024 The Authors

关键词： Environmental dynamism Organizational ambidexterity Organizational human capital Technological capacity

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Achieving Supply Chain 4.0 and the Importance of Agility, Ambidexterity, and Organizational Culture: A Case of Indonesia

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第2期8卷

作者： Alamsjah, Firdaus Yunus, Erlinda N. BINUS Graduate Program—Master of Industrial Engineering Industrial Engineering Department Bina Nusantara University Jakarta 11530 Indonesia Operations Excellence Department PPM School of Management Jakarta 10340 Indonesia

This study explores the key determinants of Supply Chain 4.0 (SC4.0) maturity in the context of a developing country by examining the relationships between supply chain ambidexterity, supply chain agility, and the maturity of SC4.0. The study was carried out using the survey method involving 154 managers from Indonesian manufacturing companies. The SC4.0 maturity model was developed and tested using structural equation modeling. From our analysis, it was found that supply chain ambidexterity emphasizing on innovation positively influences the companies’ agility and SC4.0 maturity levels, and supply chain agility partially mediates supply chain ambidexterity. This paper contributes to the operationalization of SC4.0 maturity determinants that incorporate innovation and technological aspects and extends the extant literature by empirically elaborating the determinants and antecedents of SC4.0 maturity that may expedite the achievement of SC4.0 maturity. This implies that companies and supply chain professionals aiming at achieving their SC4.0 maturity should do so by being outward-looking and, at the same time, foster supply chain collaboration with external networks. This paper is pioneering the empirical study on SC4.0 and offers a means to achieving SC4.0 maturity through SC ambidexterity and SC agility, particularly in the context of a developing country. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

关键词： open innovation organizational culture Supply Chain 4.0 maturity supply chain agility supply chain ambidexterity

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A DEA-CCR Model Application in Clustered Stocks Portfolio with Technical Investment Strategies and Mean-Variance Model

A DEA-CCR Model Application in Clustered Stocks Portfolio wi...

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IEEE International Conference on industrial engineering and engineering management

作者： M.M. Navarro M. N. Young Y.T. Prasetyo J.L. Camino B.B. Navarro V.T. Ramos School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines Department of Industrial Engineering Technological Institute of the Philippines Quezon City Philippines International Bachelor Program in Engineering Yuan Ze University Taiwan Department of Civil Engineering Technological Institute of the Philippines Quezon City Philippines Department of Electrical Engineering Technological Institute of the Philippines Quezon City Philippines

The stock market is one of the investment options that offer the best potential returns. However, investors are aware of the risk associated with their investments, which is why stock portfolios are established to diversify investments or distribute investments. Managing a portfolio may be challenging because there are so many different stocks. One of the challenges is deciding how much money to invest and how to allocate it for the best results. This paper used the K-means Algorithm for cluster analysis in identifying Decision Making Unit (DMU), the stocks will be grouped according to their characteristics considering their risk and return. Asset allocation per clustered portfolio was performed and the Mean-Variance Model was used to optimize clustered portfolios. This paper aims to use Data Envelopment Analysis (DEA) to evaluate the efficiency of these clustered portfolios/DMUs. In addition, this paper introduces subjective choice in decision-making using the criterion's level of importance to help investors decide which among these efficient DMUs is a better option. The results show 4 Efficient DMUs for 2019 Data, and 3 Efficient DMUs in 2020 Data. All simulations were carried out using the MATLAB environment platform.

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Portfolio Selection and Comparative Portfolio Analysis of Transportation Services, Hotel and Leisure, and Education Subsectors Against Service Sector in the Philippine Market Using Mean-variance Model

Portfolio Selection and Comparative Portfolio Analysis of Tr...

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IEEE International Conference on industrial engineering and engineering management

作者： E. L. Cruz M. N. Young T. N. Chuahay Y. Prasetyo S. Persada R. Nadilfatin M. Contreras School of Industrial Engineering and Engineering Management Mapua University Manila Philippines School of Graduate Studies Mapua University Manila Philippines Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This paper presents a framework for portfolio selection in the transportation services, hotel and leisure, and education subsectors of the Philippine market using the mean-variance model. Using the service sector and the broader market as benchmarks, this study spans 7,670 test days from January 1, 1993, to December 31, 2022, identifying optimal risk-return factors (RRFs) of $\mathbf{0. 4}$ for transportation, 0.2 for hotel and leisure, and 0.3 for education. Furthermore, the higher percentage allocations the investors are recommended to invest in are International Container Terminal Services, Inc., Waterfront Philippines, Incorporated, and Far Eastern University, Incorporated. Paired t-test results, with p-values below 0.01 and 0.05, indicate these subsectors can outperform the service sector. The study also conducted a comparative analysis with 30-year historical data to crisis periods like the Global Financial Crisis (GFC) and the COVID-19 pandemic, exhibiting distinct performance trends and emphasizing the need for tailored strategies during economic disruptions. The findings of this research may provide an alternative portfolio selection model for investors seeking to optimize their investment portfolios.

关键词： COVID-19 Analytical models Pandemics Education Transportation Stability analysis Resource management Stock markets Portfolios Resilience

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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE management SYSTEMS IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on Information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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