IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2306.12176.html
   My bibliography  Save this paper

The Skill-Task Matching Model: Mechanism, Model Structure, and Algorithm

Author

Listed:
  • Da Xie
  • WeiGuo Yang

Abstract

We distinguished between the expected and actual profit of a firm. We proposed that, beyond maximizing profit, a firm's goal also encompasses minimizing the gap between expected and actual profit. Firms strive to enhance their capability to transform projects into reality through a process of trial and error, evident as a cyclical iterative optimization process. To characterize this iterative mechanism, we developed the Skill-Task Matching Model, extending the task approach in both multidimensional and iterative manners. We vectorized jobs and employees into task and skill vector spaces, respectively, while treating production techniques as a skill-task matching matrix and business strategy as a task value vector. In our model, the process of stabilizing production techniques and optimizing business strategies corresponds to the recalibration of parameters within the skill-task matching matrix and the task value vector. We constructed a feed-forward neural network algorithm to run this model and demonstrated how it can augment operational efficiency.

Suggested Citation

  • Da Xie & WeiGuo Yang, 2023. "The Skill-Task Matching Model: Mechanism, Model Structure, and Algorithm," Papers 2306.12176, arXiv.org, revised Oct 2023.
  • Handle: RePEc:arx:papers:2306.12176
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2306.12176
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jeremy Lise & Fabien Postel-Vinay, 2020. "Multidimensional Skills, Sorting, and Human Capital Accumulation," American Economic Review, American Economic Association, vol. 110(8), pages 2328-2376, August.
    2. Edward P. Lazear & Paul Oyer, 2012. "Personnel Economics [The Handbook of Organizational Economics]," Introductory Chapters,, Princeton University Press.
    3. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    4. Edward P. Lazear, 1995. "Personnel Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262121883, April.
    5. David H. Autor & Michael J. Handel, 2013. "Putting Tasks to the Test: Human Capital, Job Tasks, and Wages," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 59-96.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    7. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    8. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    9. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    10. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    11. Aruna Ranganathan, 2023. "When the Tasks Line Up: How the Nature of Supplementary Tasks Affects Worker Productivity," ILR Review, Cornell University, ILR School, vol. 76(3), pages 556-585, May.
    12. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gallipoli, Giovanni & Makridis, Christos A., 2018. "Structural transformation and the rise of information technology," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 91-110.
    2. Lo Bello,Salvatore & Sanchez Puerta,Maria Laura & Winkler,Hernan Jorge, 2019. "From Ghana to America : The Skill Content of Jobs and Economic Development," Policy Research Working Paper Series 8758, The World Bank.
    3. Goos, Maarten & Rademakers, Emilie & Röttger, Ronja, 2021. "Routine-Biased technical change: Individual-Level evidence from a plant closure," Research Policy, Elsevier, vol. 50(7).
    4. Kaltenberg, Mary & Foster-McGregor, Neil, 2020. "The impact of automation on inequality across Europe," MERIT Working Papers 2020-009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Sergio Ocampo, 2019. "A task-based theory of occupations with multidimensional heterogeneity," 2019 Meeting Papers 477, Society for Economic Dynamics.
    6. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    7. Georg Graetz, 2019. "Labor Demand in the Past, Present, and Future," European Economy - Discussion Papers 114, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    9. Dengler, Katharina & Matthes, Britta, 2018. "The impacts of digital transformation on the labour market: Substitution potentials of occupations in Germany," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 304-316.
    10. Maarten Goos & Melanie Arntz & Ulrich Zierahn & Terry Gregory & Stephanie Carretero Gomez & Ignacio Gonzalez Vazquez & Koen Jonkers, 2019. "The Impact of Technological Innovation on the Future of Work," JRC Working Papers on Labour, Education and Technology 2019-03, Joint Research Centre.
    11. Ljubica Nedelkoska & Frank Neffke, 2019. "Skill Mismatch and Skill Transferability: Review of Concepts and Measurements," Papers in Evolutionary Economic Geography (PEEG) 1921, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2019.
    12. Nicola Cassandro & Marco Centra & Dario Guarascio & Piero Esposito, 2021. "What drives employment–unemployment transitions? Evidence from Italian task-based data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 1109-1147, October.
    13. Sabrina Aufiero & Giordano De Marzo & Angelica Sbardella & Andrea Zaccaria, 2023. "Mapping job complexity and skills into wages," Papers 2304.05251, arXiv.org.
    14. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    15. Albinowski, Maciej & Lewandowski, Piotr, 2024. "The impact of ICT and robots on labour market outcomes of demographic groups in Europe," Labour Economics, Elsevier, vol. 87(C).
    16. Maximiliano Dvorkin & Alexander Monge-Naranjo, 2019. "Occupation Mobility, Human Capital and the Aggregate Consequences of Task-Biased Innovations," Working Papers 2019-064, Human Capital and Economic Opportunity Working Group.
    17. Armanda Cetrulo & Dario Guarascio & Maria Enrica Virgillito, 2020. "Anatomy of the Italian occupational structure: concentrated power and distributed knowledge," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(6), pages 1345-1379.
    18. Lucas van der Velde, 2020. "Within Occupation Wage Dispersion and the Task Content of Jobs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1161-1197, October.
    19. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    20. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2306.12176. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.