IDEAS home Printed from https://ideas.repec.org/a/fan/macoma/vhtml10.3280-maco2018-003004.html
   My bibliography  Save this article

L?impatto dei Big Data sulle attivit? di pianificazione & controllo aziendali: In caso di studio di una PMI agricola Italiana

Author

Listed:
  • Sebastiano Cupertino
  • Gianluca Vitale
  • Angelo Riccaboni

Abstract

This contribution represents one of the first studies that analyze the role of the current process of digitization and automation in facilitating the introduction of new planning and control practices and/or modifying some already existing ones for small and medium-sized enterprises (SMEs). In particular, the analysis of the case study shows how the adoption of a Decision Support System (DSS) by a SME has led to the formalization of some control activities traditionally processed in a consuetudinary way in the agricultural sector. The analysis also revealed that the company manager has played a decisive role in the introduction of the DSS and that the implementation of such an innovation has improved the awareness of managerial and production actions with a view also to sustainability issues.

Suggested Citation

  • Sebastiano Cupertino & Gianluca Vitale & Angelo Riccaboni, 2018. "L?impatto dei Big Data sulle attivit? di pianificazione & controllo aziendali: In caso di studio di una PMI agricola Italiana," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 59-86.
    • Handle: RePEc:fan:macoma:v:html10.3280/maco2018-003004
    as

    Download full text from publisher

    File URL: http://www.francoangeli.it/riviste/Scheda_Rivista.aspx?IDArticolo=62731&Tipo=ArticoloPDF
    Download Restriction: Single articles can be downloaded buying download credits, for info: https://www.francoangeli.it/DownloadCredit
    ---><---

    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. Trip, G. & Thijssen, G. J. & Renkema, J. A. & Huirne, R. B. M., 2002. "Measuring managerial efficiency: the case of commercial greenhouse growers," Agricultural Economics, Blackwell, vol. 27(2), pages 175-181, August.
    2. Sonka, Steve, 2014. "Big Data and the Ag Sector: More than Lots of Numbers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 17(1), pages 1-20, February.
    3. Lisa Jack, 2006. "Protecting agricultural accounting in the UK," Accounting Forum, Taylor & Francis Journals, vol. 30(3), pages 227-243, September.
    4. Puig-Junoy, Jaume & Argiles, Josep M., 2004. "The influence of management accounting use on farm inefficiency," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 5(2), pages 1-20, August.
    5. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    6. Yanping Cheng & Yunjuan Kuang & Xiutian Shi & Ciwei Dong, 2018. "Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    7. Jeremy Phillipson & Matthew Gorton & Marian Raley & Andrew Moxey, 2004. "Treating Farms as Firms? the Evolution of Farm Business Support from Productionist to Entrepreneurial Models," Environment and Planning C, , vol. 22(1), pages 31-54, February.
    8. Josep Argilés & E. Slof, 2003. "The use of financial accounting information and firm performance: an empirical quantification for farms," Accounting and Business Research, Taylor & Francis Journals, vol. 33(4), pages 251-273.
    9. William G. Ouchi, 1979. "A Conceptual Framework for the Design of Organizational Control Mechanisms," Management Science, INFORMS, vol. 25(9), pages 833-848, September.
    10. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    11. 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.
    12. Robert Simons, 1994. "How new top managers use control systems as levers of strategic renewal," Strategic Management Journal, Wiley Blackwell, vol. 15(3), pages 169-189, March.
    13. Gandomi, Amir & Haider, Murtaza, 2015. "Beyond the hype: Big data concepts, methods, and analytics," International Journal of Information Management, Elsevier, vol. 35(2), pages 137-144.
    14. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    15. Luciano Marchi, 2018. "Quale metodologia di ricerca sulle tematiche di Management Control?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 5-10.
    16. Olsson, Rolf, 1988. "Management for Success in Modern Agriculture," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 15(2/3), pages 239-259.
    17. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    18. Narasimha Rao Vajjhala & Ervin Ramollari, 2016. "Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 2, January -.
    19. Langfield-Smith, Kim, 1997. "Management control systems and strategy: A critical review," Accounting, Organizations and Society, Elsevier, vol. 22(2), pages 207-232, February.
    20. Jack, Lisa & Florez-Lopez, Raquel & Ramon-Jeronimo, Juan Manuel, 2018. "Accounting, performance measurement and fairness in UK fresh produce supply networks," Accounting, Organizations and Society, Elsevier, vol. 64(C), pages 17-30.
    21. Morten Jakobsen, 2017. "Consequences of intensive use of non-financial performance measures in Danish family farm holdings," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 14(2), pages 137-156, June.
    22. 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.
    23. Frizzo-Barker, Julie & Chow-White, Peter A. & Mozafari, Maryam & Ha, Dung, 2016. "An empirical study of the rise of big data in business scholarship," International Journal of Information Management, Elsevier, vol. 36(3), pages 403-413.
    24. Daniela Mancini, 2016. "Accounting Information Systems in an Open Society. Emerging Trends and Issues," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2016(1), pages 5-16.
    25. Martin Giraudeau, 2017. "The farm as an accounting laboratory: an essay on the history of accounting and agriculture," Accounting History Review, Taylor & Francis Journals, vol. 27(2), pages 201-215, May.
    26. Andrea Cardoni, 2018. "Le sfide evolutive del Management Control tra relazioni strategiche, innovazione e discontinuit?: a knowledge transfer matter?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(1), pages 5-15.
    27. Shao, Benjamin B.M. & Lin, Winston T., 2016. "Assessing output performance of information technology service industries: Productivity, innovation and catch-up," International Journal of Production Economics, Elsevier, vol. 172(C), pages 43-53.
    28. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    29. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    30. Galanopoulos, Konstantinos & Aggelopoulos, Stamatis & Kamenidou, Irene & Mattas, Konstadinos, 2006. "Assessing the effects of managerial and production practices on the efficiency of commercial pig farming," Agricultural Systems, Elsevier, vol. 88(2-3), pages 125-141, June.
    31. Otley, David T., 1980. "The contingency theory of management accounting: Achievement and prognosis," Accounting, Organizations and Society, Elsevier, vol. 5(4), pages 413-428, October.
    32. Giraudeau, Martin, 2017. "The farm as an accounting laboratory: an essay on the history of accounting and agriculture," LSE Research Online Documents on Economics 74106, London School of Economics and Political Science, LSE Library.
    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. Marco Montemari & Christian Nielsen, 2021. "Big data for business modeling: Towards the next generation of performance measurement systems?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 5-10.
    2. Nicola Castellano & Elisabetta Magnaghi, 2019. "Editoriale. Tratti di innovazione nei sistemi di controllo e risk management," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2019(3), pages 5-10.
    3. Andrea Cappelli & Iacopo Cavallini, 2021. "The Potential of Big Data Analysis in the Shipbuilding Industry: A Way of Increasing Competitiveness," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 53-74.
    4. Paola Paoloni & Martina Manzo & Veronica Procacci, 2023. "The impact of the pandemic crisis on the digital transition process of Italian SMEs," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2023(2 Suppl.), pages 83-107.

    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. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    2. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    3. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
    4. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    5. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    6. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    7. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    8. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    9. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    10. Acharya, Abhilash & Singh, Sanjay Kumar & Pereira, Vijay & Singh, Poonam, 2018. "Big data, knowledge co-creation and decision making in fashion industry," International Journal of Information Management, Elsevier, vol. 42(C), pages 90-101.
    11. Osama Musa Ali Al-Darras & Cem Tanova, 2022. "From Big Data Analytics to Organizational Agility: What Is the Mechanism?," SAGE Open, , vol. 12(2), pages 21582440221, June.
    12. S. Vijayakumar Bharathi, 2017. "Prioritizing and Ranking the Big Data Information Security Risk Spectrum," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 183-201, September.
    13. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    14. Francesco Badia & Fabio Donato, 2022. "Opportunities and risks in using big data to support management control systems: A multiple case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(3), pages 39-63.
    15. Manuela Nocker & Vania Sena, 2019. "Big Data and Human Resources Management: The Rise of Talent Analytics," Social Sciences, MDPI, vol. 8(10), pages 1-19, September.
    16. Samuel Sponem, 2002. "L'Explication De La Diversite Des Pratiques Budgetaires : Une Approche Contingente," Post-Print halshs-00584534, HAL.
    17. Côrte-Real, Nadine & Ruivo, Pedro & Oliveira, Tiago & Popovič, Aleš, 2019. "Unlocking the drivers of big data analytics value in firms," Journal of Business Research, Elsevier, vol. 97(C), pages 160-173.
    18. Chenhall, Robert H., 2003. "Management control systems design within its organizational context: findings from contingency-based research and directions for the future," Accounting, Organizations and Society, Elsevier, vol. 28(2-3), pages 127-168.
    19. Ana Filipa Roque, 2018. "Control Systems and Strategy: A Literature Review," GATR Journals jmmr201, Global Academy of Training and Research (GATR) Enterprise.
    20. Ashrafi, Amir & Zareravasan, Ahad, 2022. "An ambidextrous approach on the business analytics-competitive advantage relationship: Exploring the moderating role of business analytics strategy," Technological Forecasting and Social Change, Elsevier, vol. 179(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:fan:macoma:v:html10.3280/maco2018-003004. 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: Stefania Rosato (email available below). General contact details of provider: http://www.francoangeli.it/riviste/sommario.aspx?IDRivista=166 .

    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.