Examining the adoption of agricultural drones among Pakistani farmers : a modified technology acceptance model | |
| Author | Ahmed, Muhammad |
| Call Number | AIT Thesis no.AB-23-07 |
| Subject(s) | Aeronautics in agriculture--Pakistan Drone aircraft--Pakistan Agricultural innovations--Pakistan Cost effectiveness |
| Note | A Thesis submitted in partial fulfillment of the requirements for the degree of Master of Agribusiness Management in Agribusiness Management |
| Publisher | Asian Institute of Technology |
| Abstract | Pakistan is generally classified as an agriculture-dependent economy, where most of the farmers, majorly small-scale farmers, still use orthodox measures and technologies for farming. However, several agribusiness firms have started providing modern technologies to the farms to revive the agricultural sector and meet future food demand. In this regard, drone technology is one of the several technologies used in precision agriculture to increase input efficiency and overall output. The current study developed two research questions: What factors impact agricultural drone technology adoption? Is the adoption of agricultural drones beneficial compared to its cost? About the first study question, the current study is one of the first studies undertaking the adoption of drone technology in rural Pakistan, mainly in the Rahim Yar Khan district, where most of the drone companies operate. It collected data from randomly selected 130 farmers utilizing drone technology services. The data was analyzed using the structural equation modeling (SEM) technique in SmartPLS. The results suggest a statistically significant impact of all study variables on drone technology adoption; notably, perceived usefulness (β = 0.537, t-stat = 4.580), results demonstrability (β = 0.106, t-stat = 1.684), and subjective norms (β = 0.435, t-stat = 3.626) positively and significantly impact behavioral intention to adopt drones, whereas perceived cost (β = -0.141, t-stat = 1.339) negatively and significantly impacts behavioral intention. In addition, subjective norms (β = 0.686, t-stat = 13.080) and results demonstrability (β = 0.197, t-stat = 1.977) positively and significantly impact the perceived usefulness of agricultural drones. Lastly, the results suggest that PU significantly and positively mediates the (i) relationship between SN and BI (β = 0.376, t-stat = 4.287) and (ii) the relation between RD and BI (β = 0.046, t-stat = 1.684).Regarding the second study question, the results of the benefit-cost (BCA) depict that the benefits of this agricultural drone adoption significantly outweigh its adoption cost, implying that the technology is feasible for farmers. Specifically, the results of the input cost difference before and after drone adoption show that the average per acre savings in input cost reduction is 5,728 PKR (28 USD), the difference in terms of Maunds per acre before and after drone adoption is 131 Maunds (5.24 metric tons), the average reduction in fertilizer costs per acre is 2,415 PKR (12 USD), the average per-acre pesticide savings after drone adoption is 2,225 PKR (11 USD), and the average labor cost reduction is 1,748 PKR (9 USD) after the adoption of agricultural drones for spraying. However, the other variables in this dataset in terms of input costs, i.e., seed cost, sowing cost, land preparation cost, irrigation cost, and harvesting cost, are not significantly affected by the agricultural drone adoption, and the cost of these variables remain the same even after drone adoption. The possible reasons may include agricultural drones not being used for irrigation, sowing, land preparation, and harvesting purposes.Next, this study also performed the benefit-cost ratio (BCR) test to calculate the ratio of benefit to cost, and the value is 1.64, showing that the viability of sugarcane after drone adoption has increased by 1.64 units, whereas the results of the paired-sample t test suggest the statistically significant differences between input costs, yield, revenue, and BCR. Lastly, smartphones (N = 8.20) were the most frequent source of information. Likewise, the most frequent benefit of using agricultural drones was improved crop quality (N = 61), the most concerned cost of using agricultural drones was high maintenance cost (N = 58), and the most frequent factor influencing the adoption of agricultural drones was cost-effectiveness (N = 48). The majority of the farmers were risk-takers (N = 50). These findings provide substantial managerial implications for drone adoption in developing countries like Pakistan. Specifically, drone companies can introduce discounted prices and membership cards for farmers to reduce the effects of high perceived costs, whereas to cultivate the effects of results demonstrability and subjective norms, drone companies can establish demonstration plots for farmers and organize farmers’ meetings, respectively. |
| Year | 2023 |
| Type | Thesis |
| School | School of Environment, Resources, and Development |
| Department | Department of Food, Agriculture and Natural Resources (Former title: Department of Food Agriculture, and BioResources (DFAB)) |
| Academic Program/FoS | Agribusiness Management (AB) |
| Chairperson(s) | Zulfiqar, Farhad |
| Examination Committee(s) | Datta, Avishek;Himanshu, Sushil Kumar |
| Scholarship Donor(s) | CSI Scholarships;AIT Scholarships |
| Degree | Thesis (M. Am.) - Asian Institute of Technology, 2023 |