隨著國人平均壽命延長，我國已於2018年邁入高齡社會，高齡少子化趨勢對除影響我國勞動力供給總量外，工作年齡人口高齡化發展亦將影響我國勞動生產力。世界主要國家為因應人口結構轉型所造成的國家勞動力「質變」與「量變」，分別提出產業數位轉型或智慧化發展政策，以維持國家勞動生產力水準。對此，本研究先行盤點影響勞動生產力之因素並透過多元迴歸模型進行實證分析，了解製造業資本深化、產業技術升級、勞動力素質及勞動市場效率等構面因素，對我國製造業勞動生產力的影響效果。並借鏡日本德國等標竿國家勞動政策經驗，研提我國勞動政策建議。根據本研究實證結果顯示，資本深化有助於促進我國製造業勞動生產力成長，未來若進一步搭配勞動力培訓措施使勞工具備操作智慧化設備或數據分析應用能力，方可進一步推升我國製造業勞動生產力；在產業技術升級方面，我國製造業研發投入需更加重視商業應用價值或將研發支出資本化，將有助於提升我國製造業勞動生產力；再者，我國現正處於勞動市場轉型階段，高素質勞動力雖有助於提升勞動生產力，但低階工作仍依賴產業外籍勞工作為補充性勞動力。
在數位科技的應用下勞工工作時間空間不再受限，未來就業市場將朝向彈性多元發展，另一方面數位科技加速知識資訊傳遞，職能訓練較以往更具彈性。易言之，數位科技除了改變企業作業流程以及員工工作內容外，企業可進一步就員工工作表現紀錄及教育培訓歷程，透過數據分析協助員工職涯發展並提升企業整體績效。為因應未來勞動市場非典型就業者增加趨勢並維持勞動市場效率，日本、德國在產業政策上除了思考如何透過產業技術維持勞動生產力外，同時關注如何應用新科技解決社會問題，並透過勞動政策文件，向國人描述未來的動勞市場發展願景，凝聚社會各界共識。基此，我國可效法日本、德國擴大次級勞動力勞動參與搭配政策誘因賦予雇主協助勞工職能發展責任，提升企業高齡化人力資源意識，促進勞工終身學習，協助我國勞動市場從引進產業外籍勞工填補勞動缺口的過渡階段，逐步朝向日本、德國勞資雙方共同追求工作生活品質的概念發展。

With the extension of the average life expectancy of the Taiwanesspeople, Taiwan has entered the old age society in 2018. In addition to affecting the total labor supply in Taiwan, the ageing population will also affect the labor productivity of our country. Several major countries of the world, have successively proposed industrial digital transformation or intelligent development policies to maintain the national labor productivity level in response to the national labor force's “quality change” and “quantity change” which caused by transformation of the demographic structure( Such as Industry 4.0). This study firstly investigates the factors affecting labor productivity and conducts empirical analysis through multiple regression models. It draws on the experience of national labor policies such as Japan and Germany to study Taiwan's labor policy recommendations. . According to the empirical results of this study, the deepening of capital will help to promote the growth of labor productivity in Taiwan's manufacturing industry. If the government further cooperates with labor training measures in the future to enable labor to operate intelligent equipment, data analysis and application capabilities, it can further boost the labor productivity of Taiwan's manufacturing industry; In terms of industrial technology upgrading. Taiwan's manufacturing R&D investment needs to pay more attention to commercial application value or capitalize R&D expenditure, which will help to improve labor productivity in Taiwan's manufacturing industry; Furthermore, Taiwan is now in the transition stage of the labor market. Although high-quality labor helps to improve labor productivity, low-level occupations still relies on industrial foreign labor as supplementary labor.
Under the application of digital technology, the labor's time space is no longer limited, and the future employment market will be oriented towards flexible and diversified development, on the other hand, digital technology accelerates the transmission of knowledge and information, and vocational training is more flexible than ever. In other words, in addition to changing the business process and the content of employees' work, companies can further assist the development of employees' careers and improve the overall performance of the company through data analysis and Digital Technology. In addition to thinking about how to maintain labor productivity through industrial technology, Japan and Germany pay attention to how to apply new technologies to solve social problems. In order to adapt increasing the trend of the atypical workers in the future labor market and maintain the efficiency of the employment market, using policy documents to describe the vision of the future development of the employment market to the people of the country and then become the consensus. Taiwan can learn the policy measures of Japan and Germany to expand the labor participation of secondary laborers, and use incentives to give employers assistance in the development of labor functions, enhance the awareness of aging human resources, and promote lifelong learning. Assisting Taiwan's labor market from the introduction of industrial foreign labor to make up for the labor gap, and gradually moving toward the stage, which pursue the concept of work and life quality.

一、中文部分
尹國信(2008)，週休二日對勞動生產力與受雇人數影響之研究。臺北大學經濟學系學位論文。
李仲辰(2009)。從貿易調整協助方案看美國如何協助勞工因應國際貿易影響。臺灣勞工季刊，20，78-87。
邱祈豪（2010）。2008年日本勞動派遣法草案及派遣實態之研究。台灣勞動評論，2(1)，85。
吳惠林、藍科正(1995)。台灣的勞動品質提高對勞動生產力的影響。台灣經濟，222，1-33。
吳惠林、杜英儀、彭素玲、王怡修(2014)。改善我國中高齡與高齡者勞動參與之因應對策。勞動部委託專題研究計畫。臺北: 中華經濟研究院。
林祖嘉、黃啓宏(2006)。對外投資與勞動結構調整：臺灣的實證分析。人文及社會科學集刊，18(1)，171-214。
林慈芳(2011)。工資與經濟成長之分析：全球趨勢與臺灣實證。國發會研究報告。
徐美、陳明郎(2010)。縮短工時對產業勞動生產力變動之影響-分量迴歸模型之應用。經濟論文叢刊，38(4)，523-559。
黃耀民、蔡秉晃(2017)。我國非勞動力人口變動對經濟與勞動市場之影響分析。國家發展委員會自行研究。
陳威凱（2016）。台灣職業訓練探討-以德國為借鏡與比較。科技與人力教育季刊，3(2)，14-38。
陳淑娟（2015）。德國職業定向計畫對我國職業試探教育之啟示。國家教育研究院教育脈動電子期刊，4。取自http://pulse.naer.edu.tw/content.aspx?type=F&sid=174
許惠妙、張婉珍(2013)。人事主管工作壓力之分析與討論。人文暨社會科學期刊，9(1)，11-19。
張秋蘭（2016）。日本Job Card 制度對我國就業促進機制的反思。臺灣勞工季刊，45。
張景福、盧其宏、劉錦添(2011)。勞工組成特性對工廠生產力及薪資之影響:以台灣電子業工廠為例。經濟論文叢刊，2，177-212。
張源泉（2009）。德國職業教育法體系與其發展。教育資料集刊，34，263-283。
張智奇、鄧量元（2014）。就業中心與地方產業整合促進就業安定之對策研究。取自勞動部，勞動安全及職業安全衛生研究所
詹立宇、陳志成、張明宗（2005）。臺灣製造業產業分工與勞動生產力之探討。臺灣銀行季刊，56（2），94-115。
劉光哲,王仁甫,楊浩彥(2015)。ICT投資對臺灣GDP影響研析。電子商務學報，17(2)，139-182。
羅鈺珊. (2018). 數位經濟下勞動市場的機會與挑戰. 經濟前瞻, (175), 64-71
內政部統計處編（民107，9月21日）。內政統計通報。民107年9月21日，取自內政部，http://www.moi.gov.tw/
行政院主計總處（2016）。缺工及人力需求統計。取自：https://www.dgbas.gov.tw/ct.asp?xItem=40747&ctNode=4988&mp=1
行政院主計總處(2016)。行業標準分類（第10次修定）。
行政院主計總處（2018）。就業與失業統計資料庫。取自；https://win.dgbas.gov.tw/dgbas04/bc4/timeser/more_f.asp
行政院主計總處102年產值勞動生產力趨勢分析報告提要分析。
行政院主計總處103年產值勞動生產力趨勢分析報告提要分析。
行政院主計總處104年產值勞動生產力趨勢分析報告提要分析。
行政院主計總處105年產值勞動生產力趨勢分析報告提要分析。
行政院主計總處106年產值勞動生產力趨勢分析報告提要分析。
取自：https://www.dgbas.gov.tw/ct.asp?xItem=35322&ctNode=3252&mp=1
http://laws.ilosh.gov.tw/IoshCustom/Web/YearlyReserachReports/Detail?id=2824
勞動部(2017)，2017年國際勞動統計報告。勞動統計。取自：http://statdb.cla.gov.tw/html/nat/9810menu.htm
勞動部（2017）。國際勞動統計，取自：https://www.mol.gov.tw/statistics/2452/2457/
勞動部，2011-2017職類別薪資調查報告。取自：https://pswst.mol.gov.tw/psdn/Query/wFrmQuery00.aspx
國家發展委員會委員會 (2018)。臺灣經濟發展歷程與策略。台北市：作者。取自：https://www.ndc.gov.tw/News_Content.aspx?n=2FCE778D5736A84E&sms=2597E3A78A9C1482&s=D37D9EBFB9165868
國家發展委員會委員會 (2018)。中華民國人口推計2018年至2065年。台北市：作者。取自：https://ws.ndc.gov.tw/Download.ashx?u=LzAwMS9hZG1pbmlzdHJhdG9yLzEwL3JlbGZpbGUvMC8yODY3L2MyNTIzNTk1LTJiZTMtNDI0Yy05NWQ2LWIxMDk4YTA1N2NhNi5wZGY%3d&n=MTA35bm054mI5Lq65Y%2bj5o6o5Lyw5aCx5ZGKdjkgLWZpbmFsLnBkZg%3d%3d&icon=..pdf
 
二、英文部分
Ashworth, M. J. (2006). Preserving knowledge legacies: workforce aging, turnover and human resource issues in the US electric power industry. The International Journal of Human Resource Management, 17(9), 1659-1688.
Bardazzi, R., & Duranti, S. (2016). Atypical work: a threat to labour productivity growth? Some evidence from Italy. International Review of Applied Economics, 30(5), 620-643.
Billett, S., Dymock, D., Johnson, G., & Martin, G. (2011). Last resort employees: older workers' perceptions of workplace discrimination. Human Resource Development International, 14(4), 375-389.
Brown, M., Pitt-Catsouphes, M., McNamara, T. K., & Besen, E. (2014). Returning to the workforce after retiring: A job demands, job control, social support perspective on job satisfaction. The International Journal of Human Resource Management, 25(22), 3113-3133.
Bundesministerium für Arbeit und Soziales(2015)，Work 4.0 Green Paper
Bundesministerium für Arbeit und Soziales(2018)，Work 4.0 White Paper
Chanlett-Avery, E., & Nelson, R. M. (2014). Womenomics. Japan: In Brief, CRS Report, 43668
Collis, D. J., & Junker, T. (2017). Digitalization at Siemens. Harvard Business School Case 717-428, February 2017. (Revised August 2018.)
Drabe, D., Hauff, S., & Richter, N. F. (2015). Job satisfaction in aging workforces: an analysis of the USA, Japan and Germany. The International Journal of Human Resource Management, 26(6), 783-805.
Duell, N., Grubb, D., Singh, S., & Tergeist, P. (2010). Activation policies in Japan.
Elisabeth Botsch(2015)，The Policy on Gender Equality in Germany，Directorate-General for Internal Policies，Policy Department Citizen’s Rights and Constitutional Affairs.
Froehlich, D. E. (2017). Older managers’ informal learning in knowledge-intensive organizations: Investigating the role of learning approaches among Austrian bank managers. The International Journal of Human Resource Management, 28(2), 399-416.
Goštautaitė, B., & Bučiūnienė, I. (2015). The role of work characteristics in enhancing older employees' performance: evidence from a post-Soviet country. The International Journal of Human Resource Management, 26(6), 757-782.
He, W., Goodkind, D., & Kowal, P. (2017). An aging world: 2015. United States Census Bureau. March 2016.
Hess, M. (2018). Expected and preferred retirement age in Germany. Zeitschrift für Gerontologie und Geriatrie, 51(1), 98-104.
Henkens, K., Remery, C., & Schippers, J. (2008). Shortages in an ageing labour market: an analysis of employers' behaviour. The International Journal of Human Resource Management, 19(7), 1314-1329
Ito, Y.(2007)，Choice for FDI and Post-FDI Productive，RIETI Discussion Paper Series 07-E-049
Jorgenson, D. W., & Khuong, M. V. (2010). Potential growth of the world economy. Journal of Policy Modeling, 32, 615-631.
Joseph Li, C. S., Chen, T. Y., & Yang, P. Y. (2016). Local Embeddedness, Market Focus, and Productivity: Evidence of Taiwanese Manufacturing MNE Subsidiaries in China. Growth and Change, 47(4), 596-611
Kondo, A., & Shigeoka, H. (2017). The effectiveness of demand-side government intervention to promote elderly employment: evidence from Japan. ILR Review, 70(4), 1008-1036.
Kohlrausch, B. (2012). Youth unemployment in Germany: Skill biased patterns of labour market integration. Friedrich-Ebert-Stiftung, Internat. Dialogue
Kooij, D. T., Jansen, P. G., Dikkers, J. S., & De Lange, A. H. (2010). The influence of age on the associations between HR practices and both affective commitment and job satisfaction: A meta‐analysis. Journal of Organizational Behavior, 31(8), 1111-1136.
Kooij, D. T., de Lange, A. H., Jansen, P. G., & Dikkers, J. S. (2013). Beyond chronological age. Examining perceived future time and subjective health as age-related mediators in relation to work-related motivations and well-being. Work & Stress, 27(1), 88-105.
Korkmaz, S., & Korkmaz, O. (2017). The Relationship between Labor Productivity and Economic Growth in OECD Countries. International Journal of Economics and Finance, 9(5), 71-76.
Lacuesta, A., Puente, S., & Cuadrado, P. (2011). Omitted variables in the measurement of a labor quality index: the case of Spain. Review of Income and Wealth, 57(1), 84-110.
LIU, K. C., & LIAOB, W. C. (2017). A study of strategy of Small Economies facing the Transition of large Economies Industrial Structure,Journal of Industrial Strategic Management,2(2),77-89.
McNamara, T. K., Parry, E., Lee, J., & Pitt-Catsouphes, M. (2012). The effect of training on organizational performance: differences by age composition and cultural context. The International Journal of Human Resource Management, 23(6), 1226-1244
Meurs, J. A., Breaux, D. M., & Perrewé, P. L. (2008). The family and HRM in North America: how demographic and social changes are shifting the way work–family issues are managed by organizations and employees. The International Journal of Human Resource Management, 19(8), 1455-1471.
M. Fleischmann, F. Kostera and J. Schippers(2015).Nothing ventured, nothing gained! How and under which conditions employers provide employability-enhancing practices to their older workers.The International Journal of Human Resource Management,26(22),2908-2925.
Macnaughtan, H. (2015). Womenomics for Japan: is the Abe policy for gendered employment viable in an era of precarity?. The Asia-Pacific Journal, 13(12/1).
Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., ... & Sanghvi, S. (2017). Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey Global Institute
Midtsundstad, T. I. (2011). Inclusive workplaces and older employees: an analysis of companies' investment in retaining senior workers. The International Journal of Human Resource Management, 22(06), 1277-1293.
Neugart, M. (2005). Why German labour market reform has begun. Economic Affairs, 25(3), 11-16.
Nahla Samargandi(2018).Determinants of labor productivity in MENA countries.Emerging Markets Finance and Trade,54(5), 1063-1081.
OECD(2017)，Key policies to promote longer working lives- Country note 2007 to 2017
OECD, 2001. OECD Productivity Manual: A Guide to the Measurement of Industry-Level and Aggregate Productivity Growth. Paris：OECD.
Oka, M. (2008). Japan: Towards employment extension for older workers. In P. Taylor (Ed.)
Schad-Seifert, A. (2018). Japans moderne Gesellschaft verstehen-Theorieansätze in den Cultural Studies.
Schwerdt, G., & Turunen, J. (2007). Growth in euro area labor quality. Review of Income and Wealth, 53(4), 716-734.
Tavani, D. (2013). Bargaining over productivity and wages when technical change is induced: implications for growth, distribution, and employment. Journal of Economics, 109(3), 207-244.
Tomiura, E. (2007). Foreign outsourcing, exporting, and FDI: A productivity comparison at the firm level. Journal of International Economics, 72(1), 113-127. UN Department of Economic and Social Affairs (2015), Population Division. World Population Ageing 2015.
Vukšić, G. (2016). Effects of private ownership, trade, and foreign direct investment on labor productivity growth in transition economies: evidence from the Croatian manufacturing industry. Emerging Markets Finance and Trade, 52(2), 322-335.
Wamboye, E., Adekola, A., & Sergi, B. (2016). ICTs and labour productivity growth in sub‐Saharan Africa. International Labour Review, 155(2), 231-252.
Yamaguchi, S. (2017). Family Policies and Female Employment in Japan. The Japanese Economic Review, 68(3), 305-322.
Zamparelli, L. (2015). Induced innovation, endogenous technical change and income distribution in a labor‐constrained model of classical growth. Metroeconomica, 66(2), 243-262.
内閣府(2012) 「平成22年度年次経済財政報告(経済財政政策担当大臣報告)─需要の創造による成長力の強化─」、http://www5.cao.go.jp/j-j/wp/wp-je10/10b03010.html。
厚生労働省(2017)，「IoT・ビッグデータ・AI等が雇用・労働に与える影響に関する研究会 報告書」
厚生勞動省於「2035工作方式」((働き方の未来2035)
總務省情報通信政策研究所(2017)，「AIネットワーク社会推進会議 報告書2017」