Examining the Linkages of Technology Adoption Enablers in Context of Dairy Farming Using ISM-MICMAC Approach

In the context of agribusiness, technology and innovation have led to major transformations in many countries. Precision dairy farming technologies enable cost optimization, quality control, waste reduction, achieving economies of scale, efficiency in dairy resource utilization, improvement in productivity, standardized processes, enhanced decision support system and overall farm management. Despite being an overall production-wise rich country, India’s dairy sector lacks in terms of yield per cattle, overall dairy farm output, effective herd management and lack of effective technology acceptance and implementation. With the help of NGT based outcome, this research is an attempt to showcase the enablers of technology adoption in dairy farming and how these enablers interact with each other in a hierarchical form using ISM methodology. Experience in the dairy business, competitive pressure and digital literacy were found as the most crucial and driving enablers. However, agreeableness and managerial interest were found as the most dependent enablers of technology adoption. The interpretations drawn from the model can help the decision makers, policy makers and farmers not only in India but can serve as the base for other nations dependent upon agriculture to understand the inter dependency among enablers and suggestions to plan and channel technology adoption by focusing upon critical ones.

在农业综合经营语境下，技术与创新已推动多国实现深刻变革。精准奶牛养殖技术可实现成本优化、质量管控、废弃物减量化、规模经济达成、乳品资源利用效率提升、生产力提高、流程标准化、决策支持系统升级以及农场整体管理优化。尽管印度从整体生产维度来看属于农业生产大国，但其乳业仍存在诸多短板：单头奶牛产奶量偏低、奶牛场整体产出不足、有效的畜群管理缺失，以及技术接纳与落地实施的有效性不足。本研究依托名义小组技术（Nominal Group Technique，NGT）的研究成果，旨在阐明奶牛养殖领域技术采纳的驱动影响因素，并借助解释结构模型法（Interpretive Structural Modeling，ISM）呈现这些因素间的层级互动关系。研究表明，乳业从业经验、竞争压力与数字素养是最为关键的驱动类影响因素。然而，亲和性特质与管理层关注度则是技术采纳过程中最具依附性的影响因素。本模型得出的解读结论，不仅可为印度的决策者、政策制定者与养殖户提供实践参考，同时也能为其他依赖农业的国家提供基础分析框架，帮助其理解各影响因素间的相互依存关系，并通过聚焦关键因素，规划并高效推进技术采纳工作。