Agricultural Economics and Development

Agricultural Economics and Development

An Empirical Study on Revenue Model Selection for E-Commerce Businesses in the Agricultural Sector: A Recommender System Approach

Document Type : Original Article

Authors
Masoumeh Niknam 1
Farid Ahmadi 2
Hashem Kalbkhani 3
1 MSc. Student in Information Technology, Urmia University of Technology, Urmia, Iran
2 Associate Professor, Department of Computer and Information Technology Engineering, Urmia University of Technology, Urmia, Iran
3 Associate Professor, Department of Electrical Engineering, Urmia University of Technology, Urmia, Iran
10.30490/aead.2024.363114.1543
Abstract
Introduction: This study aimed at proposing suitable business and revenue models for businesses venturing into electronic commerce within the agricultural sector. The research methodology included an in-depth examination and classification of top global businesses in various sectors, with a focus on identifying the challenges and revenue models employed by them.
Materials and Methods: The study utilized qualitative evaluation indices to assess the business models of top Iranian and foreign websites and applications. Data mining methods, clustering techniques, and MATLAB data mining tools were employed to classify businesses and compare them with global counterparts. The research identified and categorized the challenges and revenue models of top businesses across various sectors, with a specific focus on the agricultural domain.
Results and Discussion: The study used valuable insights, presenting ten significant challenges within the agricultural sector, which are used for clustering businesses and proposing revenue models tailored to this specific industry. In addition, it introduced a model for businesses to identify suitable revenue models by recognizing the addressed challenges and their functional domain. The proposed model serves as a comprehensive guide for businesses seeking to establish a presence in electronic commerce within the agricultural sector.
Conclusion: This study highlighted the potential for policymakers to update the identified challenges based on evolving environmental requirements. Moreover, by drawing insights from successful global businesses, the study suggested the possibility of updating clustering and revenue models to align with current industry trends and best practices.
Keywords
Electronic Commerce
Application
Agricultural Sector
Business Models
Revenue Models
Data Mining
Clustering
Qualitative Evaluation
MATLAB

Subjects

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