ISSN: 2226-3624
Open access
This qualitative research investigates the confluence of strategic thinking and advanced deep learning algorithms in elevating the expertise of senior librarians in Malaysian agri-business research. It emphasizes the role of librarians specializing in agricultural information services and aims to uncover their strategic methodologies and adaptability to emerging technologies. Through extensive interviews, the study reveals the intricate aspects of librarians' strategic decision-making and their application of deep learning algorithms in supporting agri-business research. The paper critically assesses the employment of advanced deep learning techniques, including neural networks and machine learning, to enhance information retrieval and data analytics in the agri-business sector. It introduces the Agri-Business Integrated Framework (ARI Framework), an innovative strategy designed to advance agri-business research. This framework merges strategic thinking with effective deep learning applications, providing guidance for librarians and researchers in managing agri-business complexities and leveraging new technologies. The adoption of the ARI Framework is intended to improve decision-making processes, optimize resource management, and encourage sustainable practices in agri-business research, thereby making a significant contribution to the development of the field.
Arshad, F. M., Shaffril, M. H. A., & Abu Samah, B. (2016). Agriculture 4.0: The future of farming technology. Journal of Agricultural Science, 8(6), 240. https://doi.org/10.5539/jas.v8n6p240
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.
Brown, K., & Davis, R. (2019). Overcoming technological infrastructure limitations for integrating deep learning algorithms in agri-business research. Journal of Agricultural Informatics, 10(1), 23-35. https://doi.org/10.17700/jai.2019.10.1.547
Bryson, J. M. (2004). Strategic planning for public and nonprofit organizations: A guide to strengthening and sustaining organizational achievement (3rd ed.). Jossey-Bass.
Connaway, L. S., & Radford, M. L. (2017). Academic library engagement in high-impact practices. Library Management, 38(8/9), 434-448.
Devare, M., Arnaud, E., Antezana, E., & King, B. (2023). Governing Agricultural Data: Challenges and Recommendations. In H.F. Williamson & S. Leonelli (Eds.), Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development (pp. 11). Springer, Cham. https://doi.org/10.1007/978-3-031-13276-6_11
Dias, A., Teixeira, N., & Brandão, E. (2015). Strategic thinking and risk management in entrepreneurship. Journal of Business Research, 68(7), 1592-1597.
Eden, C., & Ackermann, F. (2004). Cognitive mapping expert views for policy analysis in the public sector. International Journal of Public Administration, 27(6), 447-459.
García, S., Sanz, J., & Fernández, A. (2018). Deep learning for plant identification using vein morphological patterns. Computers and Electronics in Agriculture, 153, 46-56. https://doi.org/10.1016/j.compag.2018.02.016
Goodwin, N., & Wright, G. (2010). Decision analysis for management judgment (4th ed.). Wiley.
Hart, S., & Dowell, G. (2011). Strategic clarity revisited: Complexity, strategic decision-making, and implications for environmental sustainability. Journal of Business Ethics, 104(1), 59-74. https://doi.org/10.1007/s10551-011-0893-2
Hurlbert, M. (2016). Socio-ecological systems and environmental management: Toward a broader understanding of institutions and complexity. Sustainability, 8(7), 640. https://doi.org/10.3390/su8070640
Hurlbert, M., & Gupta, J. (2015). Governing complexity: Analyzing and applying the concepts of governance effectiveness and social-ecological systems. International Journal of the Commons, 9(2), 396-427. https://doi.org/10.18352/ijc.511
Hurlbert, M. (2018). Interactions between people and complex ecological systems: A conceptual framework. Ecosystems, 21(4), 708-723. https://doi.org/10.1007/s10021-017-0185-y
Huston, A. (2020). Strategic thinking in complex problem solving. Oxford University Press.
Isaacs, R. T. (2018). Risk management in agriculture. In Risk and Uncertainty in Agriculture (pp. 27-44). Springer.
Ireland, R. D., Hitt, M. A., & Vaidyanath, D. (2002). Alliance management as a source of competitive advantage. Journal of Management, 28(3), 413-446. doi: 10.1177/014920630202800307
Ireland, R. D., & Webb, J. W. (2007). A cross-disciplinary exploration of entrepreneurship research. Journal of Management, 33(6), 891-927.
Jha, K., Doshi, A., Patel, P., & Shah, M. (2019). A comprehensive review on automation in agriculture using artificial intelligence. Artificial Intelligence in Agriculture, 2, 1-12. https://doi.org/10.1016/j.aiia.2019.05.004
Johnson, L., & Chen, H. (2018). Ensuring availability and quality of data for deep learning algorithms in agri-business research. International Journal of Information Management, 42, 120-130. https://doi.org/10.1016/j.ijinfomgt.2018.06.006
Kamilaris, A., & Prenafeta-Bold?, F. X. (2018). Deep learning in agriculture: A survey. Computers and Electronics in Agriculture, 147, 70-90. https://doi.org/10.1016/j.compag.2018.02.016
Kamilaris, A., Kartakoullis, A., & Prenafeta-Bold?, F. X. (2020). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143, 105702. https://doi.org/10.1016/j.compag.2017.09.037
Khoo, C. S., Rozaklis, L., & Hall, H. (2012). Are Malaysian librarians ready for information literacy?: A case study. Journal of Librarianship and Information Science, 44(1), 38-49.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. https://doi.org/10.1038/nature14539
Leite, D. F. B., Padilha, M. A. S., & Cecatti, J. G. (2019). Approaching literature review for academic purposes: The Literature Review Checklist. Clinics, 74, e1403. https://doi.org/10.6061/clinics/2019/e1403
Liedtka, J. (1998). Strategic thinking: Can it be taught? Long Range Planning, 31(1), 120-129. https://doi.org/10.1016/S0024-6301(97)00091-0
Mintzberg, H., Ahlstrand, B., & Lampel, J. (1998). Strategy safari: A guided tour through the wilds of strategic management. Free Press.
Mittal, S., Gera, R., & Batra, N. (2016). Strategic entrepreneurship in an era of technological disruption. In Strategic Management in the 21st Century (pp. 187-207). Emerald Group Publishing Limited.
Mutula, S. M., & Brakel, P. A. (2006). Towards a model of information behavior of library and information science professionals in Africa. Information Development, 22(1), 43-51.
Panda, S., Kaur, P., & Kaur, N. (2023). The Role of Agriculture Libraries in Advancing Sustainable Development Goals: A Study in Indian Perspective. In G. Rathinasabapathy [et al.] (Eds.), Agricultural Libraries and Sustainable Development Goals: The Way Forward, Presented on 06 October 2023 at the International Conference of Agricultural Librarians and User Community (ICALUC 2023), 2023, NIPA® GENX ELECTRONIC RESOURCES & SOLUTIONS P. LTD., New Delhi, India, pp. 675-694
Sa’ari, H., & Goulding, A. (2024). Unleashing the Entrepreneurial Competencies of Academic Librarians: Insights from Strategic Thinking. In: Alareeni, B., Elgedawy, I. (eds) AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises. Studies in Systems, Decision and Control, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-031-42085-6_47
Saravani, S. J., & Haddow, G. (2018). The mobile divide in the academic library. The Journal of Academic Librarianship, 44(1), 8-19. https://doi.org/10.1016/j.acalib.2017.11.003
Schönfeld, R. C., & Sweeney, M. E. (2017). Academic libraries. In International Encyclopedia of Organizational Communication. Wiley.
Snowden, D. J., & Boone, M. E. (2007). A leader's framework for decision making. Harvard Business Review, 85(11), 68-76.
Tenopir, C., King, D. W., Christian, L., & Volentine, R. (2016). Library impact on the research lifecycle: Data management, scholarly communication, and cultural change. College & Research Libraries, 77(5), 604-626.
The World Bank. (2022). Malaysia. Retrieved from https://data.worldbank.org/country
Townley, C. T. (2011). Reframing information architecture. Springer.
Waas, T., Hugé, J., Verbruggen, A., Wright, T., & Block, T. (2014). Environmental decision-making in the face of uncertainty. In T. Waas, J. Hugé, A. Verbruggen, & T. Wright (Eds.), Sustainable development: A multidisciplinary approach (pp. 157-169). Springer.
Weick, K. E. (1995). Sensemaking in organizations. Sage.
Wong, C. Y., Lee, J. L., & Lim, S. L. (2021). Addressing limited comparative study and partnership opportunities in agri-business research: Insights from neighboring countries. Journal of Agricultural Science, 159(4), 421-432. https://doi.org/10.1017/S0021859621000089
Yin, R. K. (2009). Case Study Research: Design and Methods (5th ed.). Sage Publications.
Zhou, Z. H., Zhang, R., Slowik, A., Wu, X. J., Michalska, M., Zhang, J., ... & Tadeusiewicz, R. (2020). Applications of deep learning in agriculture: A review. Artificial Intelligence in Agriculture, 4, 58-78. https://doi.org/10.1016/j.aiia.2020.06.001
(Sa’ari et al., 2024)
Sa’ari, H., Adenan, H., & Goulding, A. (2024). How Can Deep Learning and Strategic Thinking Transform Agri-Business Research in Malaysian Academic Libraries? International Journal of Academic Research in Economics and Management and Sciences, 13(1), 33–50.
Copyright: © 2024 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode