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研究生:蔡恩心
研究生(外文):En-Hsin Tsai
論文名稱:運用數據探勘技術來發現影響台灣女性就業的潛在因素
論文名稱(外文):The Use of Data Mining Techniques to Discover the Influential Factors of Women’s Employment in Taiwan
指導教授:王群孝
指導教授(外文):Chun-Hsiao Wang
學位類別:碩士
校院名稱:國立中央大學
系所名稱:人力資源管理研究所
學門:商業及管理學門
學類:其他商業及管理學類
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:72
中文關鍵詞:影響台灣女性就業因素資料探勘決策樹人力資源管理政策結婚與生育
外文關鍵詞:influential factors of women’s employment in Taiwandata miningdecision treehuman resource management policymarriage and childbirth
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本研究透過政府之長期調查,運用數據探勘之決策樹技術生成預測模型,旨在獲得台灣女性面臨結婚與生育階段時影響其就業考量的潛在因素與規則。利用2016年資料庫中2741筆職業婦女資料作為實證研究樣本。研究結果顯示二項特徵:最小孩童三歲前主要照護者和婦女結婚前之就業類型(是否為部分工時、臨時性或人力派遣工作)是預測台灣工作婦女經歷婚育階段就業考量之最重要的潛在影響因素。本研究成果能夠提升台灣婦女於制定人力資源管理策略或公共雇傭政策的品質,藉由相對易於解釋、計算成本不昂貴的資料探勘技術與善用組織周圍的既存資料,本研究所提供之婦女就業考量方向得以更有效率的方式,來協助台灣政府與企業促進台灣婦女的勞動參與率。
This study uses decision tree of data mining technique to generate predictive models from national survey data, aiming at obtaining the influencing factors with rules that affect Taiwanese women’s employment considerations during the periods of marriage and childbirth. We use a sample of 2741 Taiwan mother workers in 2016 in our empirical research. Our results discover that two potential influencing factors, namely, major carer for the youngest child when he/she was under the age of 3 and job type before marriage (i.e., whether you are part-time, temporary or dispatched workers), predict Taiwanese female workers’ employment considerations during the periods of marriage and childbirth. Our findings could improve the quality in formulating successful human resource strategies or public employment policies for Taiwanese women. Via relatively easy to interpret, computationally inexpensive data mining approach and utilize the existing data in the surrounding organizations, we provide the directions of women's employment considerations could help government and companies to boost female labor force participation with a more effective way.
1 INTRODUCTION 1
2 LITERATURE REVIEW 4
2-1 GENDER EQUALITY AND EMPOWERMENT 4
2-2 GENDER DIVERSITY 7
2-3 INFLUENTIAL FACTORS OF WOMEN’S EMPLOYMENT 10
2-4 DATA MINING 12
2-5 DECISION TREE 16
2-5-1 Decision Tree Induction 16
2-5-2 Decision Tree Algorithms 18
3 RESEARCH FRAMEWORK 22
4 RESEARCH METHOD 25
4-1 DATA SOURCES 25
4-2 BUILDING THE MODEL 26
4-2-1 Data Understanding 26
4-2-2 Data Preparation 29
4-2-3 Modeling 31
4-2-4 Results 34
4-2-5 Evaluation 36
4-2-6 The Comparison of decision tree findings from the Woman's Marriage, Fertility and Employment Survey in 2016 and 2013 38
5 CONCLUSIONS 43
5-1 A REVIEW OF THE IMPORTANT RESEARCH FINDINGS AND DISCUSSION 43
5-2 APPLICATIONS OF THE STUDY 46
5-3 LIMITATIONS OF THE STUDY AND RECOMMENDATIONS FOR FUTURE RESEARCH 50
REFERENCES 51
APPENDIX A 60
APPENDIX B 61
APPENDIX C 62
〔1〕 Azar, A., Rajaeian, A., Sebt, M. V., & Ahmadi, P. (2013). A model for personnel selection with a data mining approach: A case study in a commercial bank. SA Journal of Human Resource Management, 11(1), 1-10.
〔2〕 Berg, P., Bosch, G., & Charest, J. (2014). Working-time configurations: A framework for analyzing diversity across countries. ILR Review, 67(3), 805-837.
〔3〕 Boyar, S. L., Maertz Jr, C. P., Pearson, A. W., & Keough, S. (2003). Work-family conflict: A model of linkages between work and family domain variables and turnover intentions. Journal of Managerial Issues, 175-190.
〔4〕 Breiman, L., Friedman, J. H., Olshen, R. A. & Stone, P. J. (1984). Classification and regression trees. CA: Wadsworth International Group.
〔5〕 Cabrera, E. F. (2009). Fixing the leaky pipeline: Five ways to retain female talent. People & Strategy, 32, 40-45.
〔6〕 Campbell, K., & Mínguez-Vera, A. (2008). Gender diversity in the boardroom and firm financial performance. Journal of Business Ethics, 83(3), 435-451.
〔7〕 Chen, X., Ye, Y., Williams, G., & Xu, X. (2007, May). A survey of open source data mining systems. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 3-14. Springer, Berlin, Heidelberg.
〔8〕 Chien, C.-F., & Chen, L.-F. (2008). Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems with Applications, 34, 280-290.
〔9〕 Cox, T., Jr. (2001). Creating the multicultural organization: A strategy for capturing the power of diversity. San Francisco, CA: Jossey-Bass.
〔10〕 Directorate-General of Budget, Accounting, and Statistics, Executive Yuan, R.O.C. (2017a). Home page: Manpower utilization survey, 2016. Retrieved on February 25, 2019, from https://srda.sinica.edu.tw/datasearch_detail.php?id=78
〔11〕 Directorate-General of Budget, Accounting, and Statistics, Executive Yuan, R.O.C. (2017b). Yearbook of manpower survey statistics 2016. Retrieved February 25, 2019, from https://srda.sinica.edu.tw/srda_freedownload.php?recid=78&fileid=1339
〔12〕 Directorate-General of Budget, Accounting and Statistics, Executive Yuan (2017c). Woman's marriage, fertility and employment survey, 2016. Retrieved on February 26, 2019, from https://srda.sinica.edu.tw/datasearch_detail.php?id=160
〔13〕 Directorate-General of Budget, Accounting, and Statistics, Executive Yuan, R.O.C. (2017d). Report on women’s marriage, fertility and employment. Retrieved February 26, 2019, from https://srda.sinica.edu.tw/srda_freedownload.php?recid=160&fileid=2023
〔14〕 Directorate-General of Budget, Accounting, and Statistics, Executive Yuan, R.O.C. (2019). Manpower survey: Series abstract. Retrieved February 26, 2019, from https://srda.sinica.edu.tw/browsingbydatatype_result.php?category=surveymethod&type=4&typeb=007&csid=30
〔15〕 Directorate-General of Budget, Accounting and Statistics, Executive Yuan (2014). Woman's marriage, fertility and employment survey, 2013. Retrieved on April 6, 2020, from https://srda.sinica.edu.tw/datasearch_detail.php?id=159
〔16〕 Duxbury, L. E., & Higgins, C. A. (1991). Gender differences in work–family conflict. Journal of Applied Psychology, 76, 60-73.
〔17〕 Economist Intelligence Unit. (2012). Women’s economic opportunity 2012 index and report, 1-47. Retrieved on March 15, 2019, from https://www.trestlegroupfoundation.org/wp-content/uploads/2012/03/EIU_WEO_2012March62.pdf
〔18〕 Ellemers, N., & Rink, F. (2016). Diversity in work groups. Current Opinion in Psychology, 11, 49-53.
〔19〕 Ernst and Young. (2009). Groundbreakers: Using the strength of women to rebuild the world economy, 1-20. Retrieved on February 25, 2019, from www.womenable.com/content/userfiles/E&Y-Groundbreakers.pdf
〔20〕 Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996a). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-54.
〔21〕 Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996b). Knowledge discovery and data mining: Towards a unifying framework. In KDD, 96, 82-88.
〔22〕 Fayyad, U., Piatesky-Shapiro, G., & Smyth, P. (1996c). The KDD process for extracting useful knowledge from volumes of data. Communications of the ACM, 39, 27-34.
〔23〕 Gender Equality Committee of the Executive Yuan. (2016). the works done on gender equality, 1-49. Retrieved on January 21, 2019, from https://www.gec.ey.gov.tw/en/News.aspx?n=B0625F9590273BBA&sms=47200F4FE3C9E6A0
〔24〕 Gender Equality Committee of the Executive Yuan. (2017). Gender equality policy guidelines, 1-26. Retrieved on March 24, 2020, from https://gec.ey.gov.tw/File/186AB96D8BB45760
〔25〕 Ghayyur, M., & Jamal, W. (2012). Work-family conflicts: A case of employees' turnover intention. International Journal of Social Science and Humanity, 2(3), 168.
〔26〕 Ghosh, R. (2016). Gender and diversity in India: contested territories for HRD?. Advances in Developing Human Resources, 18(1), 3-10.
〔27〕 Greenhaus, J., & Beutell, N. (1985). Sources of conflict between work and family roles. Academy of Management Review, 10, 76-88.
〔28〕 Gorunescu, F. (2011). Data mining: Concepts, models and techniques, vol. 12. Springer Science & Business Media.
〔29〕 Haan, P., & Wrohlich, K. (2011). Can child care policy encourage employment and fertility?: Evidence from a structural model. Labour Economics, 18(4), 498-512.
〔30〕 Hajian-Tilaki, K. (2013). Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian Journal of Internal Medicine, 4(2), 627-635.
〔31〕 Hall, S. (2019). Starbucks and best buy just rolled out a hot new benefit—And you can too [Blog]. Retrieved from https://gusto.com/blog/benefits/child-care-benefit
〔32〕 Han, Jiawei, Kamber, Micheline, & Pei, Jian. (2012). Data mining: Concepts and techniques. Waltham, MA: Morgan Kaufmann.
〔33〕 Hand, D., Mannila, H., & Smyth, P. (2001). Principles of data mining. Cambridge: The MIT Press.
〔34〕 Heath, R., & Jayachandran, S. (2017). The causes and consequences of increased female education and labor force participation in developing countries. In The Oxford Handbook of Women and the Economy, 345-367. Oxford University Press.
〔35〕 Henry, O., & Evans, A. J. (2007). Critical review of literature on workforce diversity. African Journal of Business Management, 72-76.
〔36〕 Herring, C. (2009). Does diversity pay?: Race, gender, and the business case for diversity. American Sociological Review, 74(2), 208-224.
〔37〕 The Wall Street Journal. (2011, April 11). Industry by Industry: How to move forward. Retrieved February 25, 2019 from http://www.womeninecon.wsj.com/special-report.pdf
〔38〕 Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258-268.
〔39〕 Jantan, H., Hamdan, A. R., & Othman, Z. A. (2010). Human talent prediction in HRM using C4. 5 classification algorithm. International Journal on Computer Science and Engineering, 2(8), 2526-2534.
〔40〕 Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms. John Wiley & Sons.
〔41〕 Keith, P., & Schafer, R. (1980). Role strain and depression in two-job families. Family Relations, 29, 483-488.
〔42〕 Kent, M. (2010, December). "Women's economic empowerment ... will drive the world's economy". Vital Speeches of the Day, 76(12), 558.
〔43〕 Kundu, S. C. (2001). Managing cross-cultural diversity. Delhi Business Review, 2(2), 1-8.
〔44〕 Kurgan, L. A., & Musilek, P. (2006). A survey of knowledge discovery and data mining process models. The Knowledge Engineering Review, 21(1), 1-24.
〔45〕 Lu, L., Kao, S. F., Chang, T. T., Wu, H. P., & Cooper, C. L. (2008). Work/family demands, work flexibility, work/family conflict, and their consequences at work: A national probability sample in Taiwan. International Journal of Stress Management, 15(1), 1.
〔46〕 Lytvynenko, T. I. (2016). Problem of data analysis and forecasting using decision trees method. In Proceedings of the 10th International Conference of Programming UkrPROG'2016 , 220-226.
〔47〕 Mather, P., & Tso, B. (2016). Classification methods for remotely sensed data. CRC press.
〔48〕 McKinsey & Company. (2015). The power of parity: How advancing women’s equality can add $12 trillion to global growth. Retrieved February 25, 2019 from https://www.mckinsey.com/featured-insights/employment-and-growth/how-advancing-womens-equality-can-add-12-trillion-to-global-growth
〔49〕 McKinsey & Company. (2018). The power of parity: Advancing women’s equality in Asia Pacific. Retrieved March 27, 2020 from https://www.mckinsey.com/featured-insights/gender-equality/the-power-of-parity-advancing-womens-equality-in-asia-pacific
〔50〕 Miller, T., & del Carmen Triana, M. (2009). Demographic diversity in the boardroom: Mediators of the board diversity–firm performance relationship. Journal of Management Studies, 46(5), 755-786.
〔51〕 Netemeyer, R. G., Brashear-Alejandro, T., & Boles, J. S. (2004). A cross-national model of job-related outcomes of work role and family role variables: A retail sales context. Journal of the Academy of Marketing Science, 32(1), 49-60.
〔52〕 Noland, M., Moran, T., & Kotschwar, B. R. (February, 2016). Is gender diversity profitable? Evidence from a global survey. (PIIE Working Paper16-3). Retrieved from https://www.piie.com/publications/working-papers/gender-diversity-profitable-evidence-global-survey
〔53〕 Őnday, Ő. (2016). Global workforce diversity management and the challenge of managing diversity: Situation on world and in Turkey. Global Journal of Human Resource Management, 4(1), 31-51.
〔54〕 Pignatti, N. (2016). Encouraging women’s labor force participation in transition countries. IZA World of Labor.
〔55〕 Østergaard, C. R., Timmermans, B., & Kristinsson, K. (2011). Does a different view create something new? The effect of employee diversity on innovation. Research Policy, 40(3), 500-509.
〔56〕 Rajadhyaksha, U., Korabik, K., & Aycan, Z. (2015). Gender, gender-role ideology, and the work–family interface: A cross-cultural analysis. Gender and the Work-Family Experience, 99-117. Springer, Cham.
〔57〕 Ranjan, J., Goyal, D. P., & Ahson, S. I. (2008). Data mining techniques for better decisions in human resource management systems. International Journal of Business Information Systems, 3, 464-481.
〔58〕 Ritter-Hayashi, D., Vermeulen, P. A. M., & Knoben, J. (2016). Gender diversity and innovation: The role of women’s economic opportunity in developing countries. (DFID Working Paper). Radboud University Nijmegen.
〔59〕 Rothausen, T. J. (1999). “Family” in organizational research: A review and comparison of definitions and measures. Journal of Organizational Behavior, 20, 817-836.
〔60〕 Scholz, C. (1984). OR/MS methodology—A conceptual framework. Omega, 12(1), 53-61.
〔61〕 Shore, L. M., Randel, A. E., Chung, B. G., Dean, M. A., Holcombe Ehrhart, K., & Singh, G. (2011). Inclusion and diversity in work groups: A review and model for future research. Journal of Management, 37(4), 1262-1289.
〔62〕 Strohmeier, S., & Piazza, F. (2013). Domain driven data mining in human resource management: A review of current research. Expert Systems with Applications, 40(7), 2410-2420.
〔63〕 Taneja, S., Pryor, M. G., & Oyler, J. (2012). Empowerment and gender equality: The retention and promotion of women in the workforce. Journal of Business Diversity, 12(3), 43-53.
〔64〕 Tan, P. N., Steinbach, M., & Kumar, V. (2006). Introduction to Data Mining, Addison Wesley.
〔65〕 Terjesen, S., Couto, E. B., & Francisco, P. M. (2016). Does the presence of independent and female directors impact firm performance? A multi-country study of board diversity. Journal of Management and Governance, 20(3), 447-483.
〔66〕 Todd, C. M., & Deery-Schmitt, D. M. (1996). Factors affecting turnover among family child care providers: A longitudinal study. Early Childhood Research Quarterly, 11(3), 351-376.
〔67〕 Von Hippel, C., Issa, M., Ma, R., & Stokes, A. (2011). Stereotype threat: Antecedents and consequences for working women. European Journal of Social Psychology, 41(2), 151-161.
〔68〕 Wentling, R. M., & Palma-Rivas, N. (2000). Current status of diversity initiatives in selected multinational corporations. Human Resource Development Quarterly, 11(1), 35-60.
〔69〕 Wirth, R., & Hipp, J. (2000). CRISP-DM: Towards a standard process model for data mining. In Proceedings of the Fourth International Conference on the Practical Application of Knowledge Discovery and Data Mining, 29-39, Citeseer.
〔70〕 Zhou, M., Ren, J., Qi, J., Niu, D., & Li, G. (2007). Emerging technologies in knowledge discovery and data mining. Lecture Notes in Computer Science, 4819, 87-98.
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