影響青年農民接受物聯網科技的關鍵因素及其效果

Abstract

臺灣逐漸步入高齡化的社會型態，且缺乏年輕人投入來促進農業的新陳代謝，導致產業的人力結構加速老化。整體農業人力正面臨斷層的隱憂，也是現在政府相關單位極力解決的農業問題，導入新科技以促進農業的永續發展，便是其中重要的政策工具。因應智慧農業的發展趨勢，本調查研究旨在理解青農對於農作資訊的重視度排序，並分析其採用物聯網科技與獲取關鍵資訊意願的關係。 本研究文獻探討主題包括有：（一）臺灣智慧農業政策概觀；（二）農作資訊與農民應用科技；（三）科技接受模式。本研究係以45 歲以下之農民為研究對象。本研究共回收552 份問卷，首先剔除掉無效問卷，有效樣本數共計399 份，再運用SPSS for Windows 21 進行統計分析，以敘述統計進行人口變項的分析，再進行平均數、標準差、因素負荷量、t 檢定、變異數分析（ANOVA），以及迴歸（regression）等統計分析。 本研究結果顯示，臺灣青農最重視的農作資訊為：市場資訊、氣候資訊、病蟲害資訊、水土資訊、農政資訊、農業人力資訊，以及專業諮詢資訊；而資金資訊、農地資訊、田間即時影像，則是青農重視度偏低的三項資訊。本研究應用「科技接受模型」分析臺灣青農採用物聯網科技的意願，所得結果發現，農民組織與家人支持和對軟硬體廠商的信任感，是決定青農採用此物聯網感知系統的最重要因素。而物聯網系統的便利性和有用性也很關鍵，亦即產品在設計上必須要讓青農覺得好用且有用才行。有趣的是，對於資訊系統操作自我效能越高的青農，越沒有意願要採用物聯網感知系統。 透過本研究結果，可以理解臺灣青農對於各項農作資訊的重視度排序，以做為科技業者研發產品之適用性依據；物聯網科技廠商可藉本研究結果，重新審視並調整產品設計，以加速臺灣農業物聯網感知系統的推動；政府也可藉此為臺灣「智慧農業計畫」提供可能修正之方向；另在充份理解青農實際需求與科技使用意願下，政府亦可以規劃出更有效的鼓勵措施；最後，本研究結果也為農業科技的創業者提供可遵循之準則。

Taiwan is gradually entering an aging society. The lack of young people’s input to promote agricultural industry has led to an accelerated aging of the labor structure. The overall agricultural manpower is facing the troubles of aging labor structure. It is also the serious problem that the government agencies are trying to resolve. The introduction of new technologies to promote the sustainable development of agriculture is an important policy tool. In response to the development trend of smart agriculture, the purpose of this study is to understand the priority of young farmers on farming information and analyze the relationship between their adoption of Internet of Things (IoT) technology and their willingness to obtain key farming information. The topics discussed in the literature review include: (1) an overview of smart agriculture policy in Taiwan; (2) farming information and farmers’ applied technology; (3) technology acceptance model. This study is based on under 45-year-old farmers. A total of 552 questionnaires were collected in the process, and only 399 valid samples were used for the subsequent analyses. SPSS for Windows 21 was used for descriptive analysis in this study. Other statistical analyses such as factor analysis, t test, analysis of variance (ANOVA), and multiple regression were also preformed. The results of this study revealed that the six highest-priority categories of farmwork information are market, climate, pests and diseases, soil and water, agricultural policy, agricultural manpower, and professional consultation, whereas funds, real-time images, and farmland information are the three lowest-priority categories. Based on Technology Acceptance Model, this study analyzed Taiwan’s young farmers’s intentions to adopt IoT technology. The results found that organizational support and trust in manufacturers are the factors that promote the use of IoT systems by young farmers. In addition, the convenience and usefulness of the IoT system are also critical; that is, the system must be designed to make young farmers feel convenient and useful. Interestingly, for those who have higher self-efficiency in operating information systems, the less intentions they are to adopt the IoT context-aware system. Through the results of this study, the priority of Taiwan’s young farmers to various farming information can be understood. This can be used as a basis for the applicability of products developed by IoT product companies to accelerate the promotion of Taiwan’s agricultural IoT system. In addition, the government can also use the results to provide directions for possible amendments to Taiwan’s “smart agriculture project”. The government can also plan effective incentive measures to encouraging young farmers to adopt high technology. Finally, these results also provide guidelines for entrepreneurs of agricultural technology to follow.