Unbundling the information needs of new-generation agricultural companies

Journal title MANAGEMENT CONTROL
Author/s Silvia Macchia
Publishing Year 2022 Issue 2022/2 Suppl. Language English
Pages 25 P. 117-141 File size 290 KB
DOI 10.3280/MACO2022-002-S1006
DOI is like a bar code for intellectual property: to have more infomation click here

Anteprima articolo

FrancoAngeli is member of Publishers International Linking Association, Inc (PILA), a not-for-profit association which run the CrossRef service enabling links to and from online scholarly content.

Over the past decades, the interest in Precision Agriculture (PA) has increased in most developed countries. The adoption of new technologies in agriculture is com-plex. PA improves efficiency, product quality, the rational use of chemicals and biological resources, and the preservation of the environment. Because of the need to invest in technology for sustainability and profitability, the sector becomes in-creasingly data driven. However, this data becomes valuable and strategic only if effectively managed. This study, through a critical literature review on selected topics, sheds light on PA’s information potential for farms’ managerial processes. It investigates the im-pact of PA on profitability, the features of farmers’ decision making, and the spec-ificities of Decision Support Systems for agribusinesses. Given the sector character-istics, the discussion of findings leads to the identification of aspects that should be carefully considered when designing an information system for new-generation agricultural companies. Considering the limited amount of previous research on the decision-making process in farming and the challenges posed by the use of technology, the authors believe that this study could assist researchers, practition-ers, and farmers interested in increasing their knowledge of the issue.

Keywords: Agritech, Precision agriculture, Decision support systems, Integrated information management, Farm management extension.

  1. Ali S., Green P., Robb A., Masli A. (2022), Governing information technology (IT) investment: A contingency perspective on organization’s IT investment goals, Australian Journal of Management, 47(1), pp. 3-23.
  2. Andrade E.P., Bonmati A., Esteller L.J., Brunn S., Jensen L.S., Meers E., Anton A. (2022), Selection and application of agri-environmental indicators to assess potential technologies for nutrient recovery in agriculture, Ecological Indicators, 134, pp. 1-12.
  3. Arksey H., O’Malley L., (2005), Scoping studies: towards a methodological framework. International Journal of Social Research Methodology, 8(1), pp. 19-32.
  4. Aubert B. A., Schroeder A., Grimaudo J. (2012), IT as enabler of sustainable farming: an empirical analysis of farmers’ adoption decision of precision agriculture technology, Decision Support Systems, 54(1), pp. 510-520.
  5. Auernhammer H. (2001), Precision farming – the environmental challenge, Computers and electronics in agriculture, 30(3), pp. 31-43.
  6. Barnosky A.D., Matzke N., Tomiya S., Wogan G.O.U., Swartz B., Quental T.B. (2011), Has the Earth’s sixth mass extinction already arrived?, Nature, 471, pp. 51-57.
  7. Bellvert J., Mata M., Vallverdú X., Paris C., Marsal J. (2021), Optimizing precision irrigation of a vineyard to improve water use efficiency and profitability by using a decision-oriented vine water consumption model, Precision Agriculture, 22(2), pp. 319-341.
  8. Bhimani B. (2003), Management Accounting in the Digital Economy, Oxford University Press.
  9. Bochtis D.D., Sorensen C.G., Green O., (2012), A DSS for planning of soil-sensitive field operations, Decision Support System, 53(1), pp. 66-75.
  10. Buckwell A. (2014), The sustainable intensification of European agriculture, The Rise Foundation, Bruxelles.
  11. Carroll A.K., Halabi B. (2015), Increasing the usefulness of farm financial information and management: A qualitative study from the accountant’s perspective, Qualitative Research in Organisations and Management, 10(3), pp. 227-242.
  12. Cerf M., Jeuffroy M., Prost L., Meynard J. (2012), Participatory Design of Agricultural Decision Support Tools: Taking Account of the Use Situations, Agronomy for Sustainable Development, 32(4), pp. 899-910.
  13. Cisternas I., Velásquez I., Caro A., Rodríguez A. (2020), Systematic literature review of implementations of precision agriculture, Computers and Electronics in Agriculture, 176(1): 105626.
  14. Cosby A.M., Falzon G.A., Trotter M.G., Stanley J.N., Powell K.S., Lamb D.W. (2016), Risk mapping of redheaded cockchafer (Adoryphorus couloni) (Burmeister) infestations using a combination of novel k-means clustering and on-the-go plant and soil sensing technologies, Precision Agriculture, 17, pp. 1-17.
  15. CREA (2021), Annuario dell’agricoltura italiana 2019, CREA Consiglio per la Ricerca in Agricoltura e l’analisi dell’Economia agraria, Roma.
  16. Czimber K., Galos B., 2016, A new decision support system to analyze the impacts of climate change on the Hungarian forestry and agricultural sectors, Scandinavian Journal of Forest Research, 31(7), pp. 664-673.
  17. Diakosavvas D., Psaltopoulos D., Wesseler J. H. H., Skuras D. (2016), Farm management practices to foster green growth (No. IKEEBOOK-2020-618), OECD.
  18. Edersheim E. H., Vanderbosch B. (1991), How to make accounting count: Causal-based accounting, Journal of Cost Management, Winter, pp. 5-17.
  19. European Commission, (2014), Precision agriculture. An opportunity for EU farmers. Potential support with the CAP 2014-2020, European Union.
  20. Eurostat (2018), Archive: Small and large farms in the EU – statistics from the farm structure survey, -- available from https://ec.europa.eu/.
  21. Fenu G., Malloci F.M. (2020), DSS LANDS: A decision support system for agriculture in Sardinia, HighTech and Innovation Journal, 1(3), pp. 129-135.
  22. Finco A., Bucci G., Belletti M., Bentivoglio D. (2021), The Economic Results of Investing in Precision Agriculture in Durum Wheat Production: A Case Study in Central Italy, Agronomy, 11(8): 1520.
  23. Fountas S., Pedersen S.M., Blackmore S. (2004), ICT in Precision Agriculture. Diffusion of Technology an Overview of Precision Agriculture, in Gelb E., Offer A. (eds), ICT in Agriculture: Perspective of Technological Innovation, ResearchGate, Berlin, Germany.
  24. Fountas S., Wulfsohn D., Blackmore B., Jacobsen H., Pedersen S.M. (2006), A model of decision-making and information flows for information-intensive agriculture, Agricultural Systems, 87(2), pp. 192-210.
  25. Frank H., Gandorfer M., Noack P.O. (2008), Ökonomische Bewertung von Parallelfahrsystemen, in: Müller R.A.E., Sundermeier H.-H., Theuvsen L., Schütze S., Morgenstern M.: Referate der 28, GIL-Jahrestagung in Kiel, pp. 47-50.
  26. Frascarelli A. (2016), Valutazione economica dell’agricoltura di precisione, in Casa R. (a cura di), Agricoltura di Precisione. Metodi e tecnologie per migliorare l’efficienza e la sostenibilità dei sistemi colturali, Edagricole, Bologna, pp. 213-228.
  27. Gatti M., Chiucchi M.S. (2017), Context matters. Il ruolo del contesto negli studi di controllo di gestione, Management Control, 3, pp. 5-10.
  28. Ginanneschi M. (2021), L’impatto della pandemia di Covid-19 sul Made, Italyagroalimentare, FoodHub Magazine, December, 11, pp. 54-69.
  29. Gualandi E. (2015), La diffusione su scala reale e i possibili risparmi operativi, Speciale Agricoltura di precisione, Terra e Vita, 40, pp. 1-5.
  30. Harling K.F., Quail P. (1990), Exploring a general management approach to farm management, Agribusiness, 6(5), pp. 425-441.
  31. Higgins V., Bryant M., Howell A., Battersby J. (2017), Ordering Adoption: Materiality, knowledge and farmer engagement with precision agriculture technologies, Journal of Rural Studies, 55, pp. 193-202.
  32. Jellason N.P., Conway J.S., Baines R.N. (2021), Understanding impacts and barriers to adoption of climate-smart agriculture (CSA) practices in North-Western Nigerian drylands, Journal of Agricultural Education and Extension, 27, pp. 55-72.
  33. Jürschik P., Giebel A., Wendroth O. (1998), Verarbeiten von Ertragsdaten aus Mähdreschern, Tagung Landtechnik, Düsseldorf, Germany, pp. 215-221.
  34. Kernecker M., Knierim A., Wurbs A., Kraus T., Borges F. (2020), Experience versus expectation: Farmers’ perceptions of smart farming technologies for cropping systems across Europe, Precision Agriculture, 21, pp. 34-50.
  35. Kitchen N.R., Snyder C.J., Franzen D.W. (2002), Educational Needs of Precision Agriculture, Precision Agriculture, 3, pp. 341-351.
  36. Knight S., Miller P., Orson J. (2009), An up-to-date cost/benefit analysis of precision farming techniques to guide growers of cereals and oilseeds, Research Review, 35(6): 2820.
  37. Kopishynska O., Utkin Y., Galych O., Marenych M., Sliusar I. (2020), Main Aspects of the Creation of Managing Information System at the Implementation of Precision Farming, 2020 IEEE 11th International Conference on Dependable Systems, Services and Technologies (DESSERT), pp. 404-410.
  38. Korte M., Lee K., Fung C.C. (2013), Evolving IT management frameworks towards a sustainable future, in Linger H. et al. (eds.), Building sustainable information systems, Springer, New York, pp. 271-284.
  39. Kudryashova Y.N., Lazareva T.G., Makushina T.N., Chernova Y.V. (2020), The organization of management accounting as a mechanism to improve the efficiency of agricultural enterprises, BIO Web of Conferences, 17, pp. 1-28.
  40. Kusunose Y., Rezaul M. (2016), Imperfect forecasts and decision making in agriculture, Agricultural Systems, 146, pp. 103-110.
  41. Laurance W.F., Sayer J., Cassman K.G. (2014), Agricultural expansion and its impacts on tropical nature, Trends in Ecological Evolution, 29, pp. 107-116.
  42. Lauzier M., Lemieux N., Montreuil V.L., Nicolas C. (2020), On the transposability of change management research results: a systematic scoping review of studies published, Journal of Organizational Change Management, 33(5), pp. 859-881.
  43. Lazzari M., Longoni A., Beretta E. (2015), Indagine e messa a punto di un modello di valutazione sulle tecniche di agricoltura di precisione per l’incremento della sostenibilità economica ed ambientali delle produzioni agricole milanesi, Coldiretti Milano e Monza-Brianza, CCIAA, Milano, pp. 1-60.
  44. Lee C.L., Strong R., Dooley K.E. (2021), Analyzing Precision Agriculture Adoption across the Globe: A Systematic Review of Scholarship from 1999-2020, Sustainability, 13, pp. 95-102.
  45. Leeuwis C. (2004), Communication for rural innovation:Rethinking agricultural extension, Blackwell Science, Oxford, UK.
  46. Lindblom J., Lundström C., Ljung M., Jonsson A., (2017), Promoting sustainable intensification in precision agriculture: Review of decision support systems development and strategies, Precision Agriculture, 18, pp. 309-331.
  47. Liu W., Shao X.F., Wu C.H., Qiao P. (2021), A systematic literature review on applications of information and communication technologies and blockchain technologies for precision agriculture development, Journal of Cleaner Production, 298: 126763.
  48. López O.L., Hiebl M. R.W. (2015), Management Accounting in Small and Medium-Sized Enterprises: Current Knowledge and Avenues for Further Research, Journal of Management Accounting Research, 27(1), pp. 81-119.
  49. Loures L., Chamizo A., Ferreira P., Loures A., Castanho R., Panagopoulos T. (2020), Assessing the Effectiveness of Precision Agriculture Management Systems in Mediterranean Small Farms, Sustainability, 12, pp. 3765-3780.
  50. Luening R. (1989), Farm records can improve profitability, in United States Department of Agriculture (eds), Farm management: How to achieve your farm business goals, The yearbook of agriculture, pp. 103-112.
  51. Matthews K.B., Schwarz G., Buchan K., Rivington M., Miller D. (2008), Wither Agricultural DSS?, Computers and Electronics in Agriculture, 61(2), pp. 149-59.
  52. McConnell M.D. (2019), Bridging the gap between conservation delivery and economics with precision agriculture, Wildlife Society Bulletin, 43(3), pp. 1-7.
  53. Meyer-Aurich A., Weersink A., Gandorfer M., Wagner P. (2010), Optimal site-specific fertilization and harvesting strategies with respect to crop yield and quality response to nitrogen, Agricultural Systems, 103(7), pp. 478-485.
  54. Mintert J., Widmar D., Langemeier M., Boehlje M., Erickson B. (2016), The challenges of precision agriculture: is big data the answer, in eds, Southern Agricultural Economics Association Annual Meeting, San Antonio, Texas, pp. 1-9.
  55. MIPAAF (2015), Linee guida per lo sviluppo dell’agricoltura di precisione in Italia, Ministero delle politiche agricole alimentari e forestali, Gruppo di lavoro per lo sviluppo dell’Agricoltura di Precisione.
  56. Musemwa L., Mushunje A.V. Muchenje Aghdasi F. Zhou L. (2013), Factors affecting efficiency of field crop production among resettled farmers in Zimbabwe, Fourth International Conference, September 22-25, Hammamet, Tunisia from African Association of Agricultural Economists (AAAE).
  57. Ndemewah S.R., Menges K., Hiebl M.R.W. (2019), Management accounting research on farms: what is known and what needs knowing, Journal of Accounting & Organizational Change, 15(1), pp. 58-86.
  58. Öhlmér B., Olson K., Brehmer B. (1998), Understanding farmers’ decision making processes and improving managerial assistance, Agricultural Economics, 18(3), pp. 273-290.
  59. Ojua M. O. (2017), The desirability of the adoption of strategic management accounting techniques (SMATS) for decision making by agricultural firms in Nigeria, Imperial Journal of Interdisciplinary Research, 3(1), pp. 1635-1648.
  60. Oleson J.E., Sorensen P., Thomson I.K. (2004), Integrated Nitrogen input systems in Denmark, in Mosier A.R., Syers J.K., Freney J.R., Agriculture and the nitrogen cycle, Island press, Washington, pp. 129-140.
  61. Oyewo B. (2021), Do innovation attributes really drive the diffusion of management accounting innovations? Examination of factors determining usage intensity of strategic management accounting, Journal of Applied Accounting Research, 22(3), pp. 507-538.
  62. Pathak H.S., Brown P., Best T. (2019), A systematic literature review of the factors affecting the precision agriculture adoption process, Precision Agriculture, 20(6), pp. 1-25.
  63. Paustian M., Theuvsen L. (2017), Adoption of precision agriculture technologies by German crop farmers, Precision Agriculture, 18, pp. 701-716.
  64. Pisante M. (2016), Linee Guida per lo sviluppo dell’Agricoltura di Precisione, Terra e Vita, 42, pp. 54-56.
  65. Poppe K.J. (1991), Information needs and accounting in agriculture, The Hague, Agricultural Economics Research Institute LEI, The Hauge, Netherlands.
  66. Porter M.E. (1985), Competitive Advantage. Creating and Sustaining Superior Performance, Free Press, New York.
  67. Power D.J. (2002), Decision Support Systems: Concepts and Resources for Managers, Greenwood Quorum Books, Santa Barbara, USA.
  68. Puig-Junoy J., Argiles J.M. (2004), The influence of management accounting use on farm inefficiency, Agricultural Economics Review, 5(2), pp. 47-66.
  69. Quinn M. (2011), Routines in management accounting research: further exploration, Journal of Accounting and Organizational Change, 7(4), pp. 337-357.
  70. Raponi M. (2017), Internazionalizzazione delle imprese agribusiness e l’importanza del made in Italy, StreetLib, Milano.
  71. Robertson M., Carberry P., Brennan L. (2007), The economic benefits of precision agriculture: case studies from Australian grain farms, Crop and Pasture Science, 60(1), pp. 1-47.
  72. Rom A., Rohde C. (2007), Management accounting and integrated information systems: A literature review, International Journal of Accounting Information Systems, 8(1), pp. 40-68.
  73. Rossi V., Salinari F., Poni S., Caffi T., Bettati T. (2014), Addressing the implementation problem in agricultural decision support systems, Computers and Electronics in Agriculture, 100, pp. 88-99.
  74. Rougoor C.W., Trip G., Huirne R.B. M., Renkema J.A. (1998), To define and study farmers’ management capacity: theory and use in agricultural economics, Agricultural Economics, 18(3), pp. 261-272.
  75. Schimmelpfennig D. (2016), Farm profits and adoption of precision agriculture, research paper 217. Washington DC: U.S. Department of Agriculture, Economic Research Service, pp. 1-46.
  76. Schimmelpfennig D. (2018), Crop production costs, profits, and ecosystem stewardship with precision agriculture, Journal of Agricultural and Applied Economics, 50(1), pp. 81-103.
  77. Schimmelpfennig D. (2019), Precision agriculture. Agricultural Resources And Environmental Indicators, Economic Information Bulletin, n. 208, pp. 56-60.
  78. Schimmelpfennig D., Ebel R. (2016), Sequential Adoption and cost savings from precision agriculture, Journal of Agricultural and Resource Economics, 41(1), pp. 97-115.
  79. Scuderi A., La Via G., Timpanaro G., Sturiale L. (2022), The Digital Applications of “Agriculture 4.0”: Strategic Opportunity for the Development of the Italian Citrus Chain, Agriculture, 12(3), pp. 400-413.
  80. Shank J.K., Govindarajan V. (1993), Strategic Cost Management – The New Tool for Competitive Advantage, Free Press, New York.
  81. Silva A., Malaquias R.F. (2020), Factors associated with the adoption of financial management practices by farmers in the state of Minas Gerais, Brazil, Journal of Education and Research in Accounting, 14(3), pp. 328-351.
  82. Speziale M.T., Klovienė L. (2014), The relationship between performance measurement and sustainability reporting: a literature review, Procedia-Social and Behavioral Sciences, 156, pp. 633-638.
  83. Steinmayr T. (1999), Analyse lokaler Ertragsdaten zur Ableitung relevanter Teilschläge, Poster for the Bavarian Research Center for Agricultural Engineering of the Technical University of Munich, Weihenstephan, Germany.
  84. Tamagnone M., Balsari P., Marucco P. (2003), Use and performance of electronic devices in machinery for rice cultivation in Italy, XXX Ciosta-Cgr V Congress Proceedings, Turin, Italy, September 22-24, 2, pp. 691-699.
  85. Tantalaki N., Souravlas, S., Roumeliotis M. (2019), Data-Driven Decision Making in Precision Agriculture: The Rise of Big Data in Agricultural Systems, Journal of Agricultural and Food Information, 20(4), pp. 344-380.
  86. Thorburn P.J., Jakku E., Webster AJ., Everingham Y.L., (2011), Agricultural Decision Support Systems Facilitating Co-Learning: A Case Study on Environmental Impacts of Sugarcane Production, International Journal of Agricultural Sustainability, 9(2), pp. 322-333.
  87. Timmermann C., Gerhards R., Kuhbauch W. (2003), The Economic Impact of Site-Specific Weed Control, Precision Agriculture, 4, pp. 249-260.
  88. Tranfiel D., Denyer D., Smart P., (2003), Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review, British Journal of Management, 14, pp. 207-222.
  89. Trip G., Thijssen, G., Renkema J., Huirne R. (2002), Measuring managerial efficiency: the case of commercial greenhouse growers, Agricultural Economics, 27(2), pp. 175-181.
  90. Trivelli L., Apicella A., Chiarello F., Rana R., Fantoni G., Tarabella A. (2019), From precision agriculture to Industry 4.0: Unveiling technological connections in the agrifood sector, British Food Journal, 121(8), pp. 1730-1743.
  91. Turban E., Liang T.P., Aronson J.E. (2005), Decision Support Systems and Intelligent Systems, Pearson Prentice Hall, New Jersey, USA.
  92. Udias A., Pastori M., Dondeynaz C., Moreno C.C., Ali A., Cattaneo L., Cano J., (2018), A decision support tool to enhance agricultural growth in the Mekrou river basin (West Africa), Computer Electronic Agriculture, 154, pp. 467-481.
  93. Van Meensel J., Lauwers L., Kempen I., Dessein J., Van Huylenbroeck G. (2012). Effect of a Participatory Approach on the Successful Development of Agricultural Decision Support Systems: The Case of Pigs2win, Decision Support Systems, 54(1), pp. 73-98.
  94. Vecchio Y., Agnusdei, G.P., Miglietta, P.P., Capitanio F. (2020), Adoption of Precision Farming Tools: The Case of Italian Farmers, International Journal of Environmental Research and Public Health, 17(3), pp. 869-885.
  95. Wilson P., Hadley D., Asby C. (2001), The influence of management characteristics on the technical efficiency of wheat farmers in eastern England, Agricultural Economics, 24(3), pp. 329-338.
  96. Yost M., Kitchen N., Sudduth K., Sadler E., Drummond S., Volkmann M. (2017), Long- term impact of a precision agriculture system on grain crop production, Precision Agriculture, 18(5), pp. 823-842.
  97. Zhai Z., Martínez J.F., Beltran V., Martínez N.L. (2020), Decision support systems for agriculture 4.0: Survey and challenges, Computers and Electronics in Agriculture, 170, pp. 135-156.

Silvia Macchia, Unbundling the information needs of new-generation agricultural companies in "MANAGEMENT CONTROL" 2 Suppl./2022, pp 117-141, DOI: 10.3280/MACO2022-002-S1006