IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v278y2019i2p481-497.html
   My bibliography  Save this article

Enterprise design through complex adaptive systems and efficiency measurement

Author

Listed:
  • Herrera-Restrepo, Oscar
  • Triantis, Konstantinos

Abstract

Managerial policies affect enterprise operations facilitating or impeding the achievement of goals. Enterprises can operate individually or might also be part of a group of interconnected enterprises. For an enterprise operating as part of a (de)centralized group of enterprises with a similar or complementary mission and under the same or different ownership, the coordination of decisions and actions is important. Using the concept of network as an arrangement of interconnected nodes, this paper deals with enterprises as the members of a network, and with enterprise transactions as the connections among its members. We consider coordination exhibiting connectivity, feedback, and adaptation. These features are not only typical of enterprise networks, but also of complex adaptive systems (CAS). By considering enterprise networks as CAS, we study managerial policies that affect the coordination among the members of enterprise networks and the subsequent effect on technical efficiency both at the individual member enterprise and network levels. To approximate the effects of coordination-driven managerial policies, we consider flocking behavior from natural ecosystems, which the CAS literature studies, as a proxy for managerial policies. We simulate the relationships between managerial policies and technical efficiency in an enterprise network of deregulated power plants through an agent-based model. Experimental results inform when and how managerial policies enhance the coordination among network members and allow for the investigation of the relationships that exist between individual decisions and collective influences. These relationships result in an emergent goal seeking network behavior with respect to the goal of achieving technical efficiency.

Suggested Citation

  • Herrera-Restrepo, Oscar & Triantis, Konstantinos, 2019. "Enterprise design through complex adaptive systems and efficiency measurement," European Journal of Operational Research, Elsevier, vol. 278(2), pages 481-497.
  • Handle: RePEc:eee:ejores:v:278:y:2019:i:2:p:481-497
    DOI: 10.1016/j.ejor.2018.12.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718310245
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.12.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. Timmer & P. Borm & J. Suijs, 2000. "Linear Transformation of Products: Games and Economies," Journal of Optimization Theory and Applications, Springer, vol. 105(3), pages 677-706, June.
    2. Fang, Lei, 2013. "A generalized DEA model for centralized resource allocation," European Journal of Operational Research, Elsevier, vol. 228(2), pages 405-412.
    3. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    4. Chen, Ci & Yan, Hong, 2011. "Network DEA model for supply chain performance evaluation," European Journal of Operational Research, Elsevier, vol. 213(1), pages 147-155, August.
    5. Rungsuriyawiboon, Supawat & Stefanou, Spiro E., 2007. "Dynamic Efficiency Estimation: An Application to U.S. Electric Utilities," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 226-238, April.
    6. Francis L. Dougherty & Nathaniel P. Ambler & Konstantinos P. Triantis, 2017. "A complex adaptive systems approach for productive efficiency analysis: building blocks and associative inferences," Annals of Operations Research, Springer, vol. 250(1), pages 45-63, March.
    7. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    8. Jiro Nemoto & Mika Goto, 2003. "Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 191-210, April.
    9. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    10. Warren Vaneman & Konstantinos Triantis, 2003. "The Dynamic Production Axioms and System Dynamics Behaviors: The Foundation for Future Integration," Journal of Productivity Analysis, Springer, vol. 19(1), pages 93-113, January.
    11. Paradi, Joseph C. & Zhu, Haiyan & Edelstein, Barak, 2012. "Identifying managerial groups in a large Canadian bank branch network with a DEA approach," European Journal of Operational Research, Elsevier, vol. 219(1), pages 178-187.
    12. Peter Bogetoft & Jens Hougaard, 2003. "Rational Inefficiencies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 243-271, November.
    13. A Medina-Borja & K S Pasupathy & K Triantis, 2007. "Large-scale data envelopment analysis (DEA) implementation: a strategic performance management approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1084-1098, August.
    14. Avkiran, Necmi Kemal, 2015. "An illustration of dynamic network DEA in commercial banking including robustness tests," Omega, Elsevier, vol. 55(C), pages 141-150.
    15. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    16. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    17. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    18. Chen, Chien-Ming, 2009. "A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks," European Journal of Operational Research, Elsevier, vol. 194(3), pages 687-699, May.
    19. Wu, Desheng Dash, 2010. "BiLevel programming Data Envelopment Analysis with constrained resource," European Journal of Operational Research, Elsevier, vol. 207(2), pages 856-864, December.
    20. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    21. Yao Chen & Liang Liang & Feng Yang, 2006. "A DEA game model approach to supply chain efficiency," Annals of Operations Research, Springer, vol. 145(1), pages 5-13, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ponta, Linda & Puliga, Gloria & Lazzarotti, Valentina & Manzini, Raffaella & Cincotti, Silvano, 2023. "To copatent or not to copatent: An agent-based model for firms facing this dilemma," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1349-1363.
    2. Carayannis, Elias G. & Grigoroudis, Evangelos & Wurth, Bernd, 2022. "OR for entrepreneurial ecosystems: A problem-oriented review and agenda," European Journal of Operational Research, Elsevier, vol. 300(3), pages 791-808.

    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. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    3. Victor John M. Cantor & Kim Leng Poh, 2020. "Efficiency measurement for general network systems: a slacks-based measure model," Journal of Productivity Analysis, Springer, vol. 54(1), pages 43-57, August.
    4. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    5. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    6. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    7. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    8. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.
    9. Shiping Mao & Marios Dominikos Kremantzis & Leonidas Sotirios Kyrgiakos & George Vlontzos, 2022. "R&D Performance Evaluation in the Chinese Food Manufacturing Industry Based on Dynamic DEA in the COVID-19 Era," Agriculture, MDPI, vol. 12(11), pages 1-19, November.
    10. Hampf, Benjamin, 2017. "Rational inefficiency, adjustment costs and sequential technologies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1095-1108.
    11. Mohammad Nourani & Qian Long Kweh & Irene Wei Kiong Ting & Wen-Min Lu & Anna Strutt, 2022. "Evaluating traditional, dynamic and network business models: an efficiency-based study of Chinese insurance companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(4), pages 905-943, October.
    12. AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," LIDAM Discussion Papers CORE 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    14. Hsiao-Yin Chen & Chin-wei Huang & Yung-Ho Chiu, 2017. "An intertemporal efficiency and technology measurement for tourist hotel," Journal of Productivity Analysis, Springer, vol. 48(1), pages 85-96, August.
    15. Chiu, Yung-ho & Huang, Kuei-Ying & Chang, Tzu-Han & Lin, Tai-Yu, 2021. "Efficiency assessment of coal mine use and land restoration: Considering climate change and income differences," Resources Policy, Elsevier, vol. 73(C).
    16. Del Barrio-Tellado, María José & Gómez-Vega, Mafalda & Gómez-Zapata, Jonathan Daniel & Herrero-Prieto, Luis César, 2021. "Urban public libraries: Performance analysis using dynamic-network-DEA," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    17. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    18. Li, Ying & Chiu, Yung-ho & Lin, Tai-Yu, 2019. "Coal production efficiency and land destruction in China's coal mining industry," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    19. Khosro Soleimani-Chamkhorami & Saeid Ghobadi, 2021. "Cost-efficiency under inter-temporal dependence," Annals of Operations Research, Springer, vol. 302(1), pages 289-312, July.
    20. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.

    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:eee:ejores:v:278:y:2019:i:2:p:481-497. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.