The Impact of Digital Marketing on the Marketing Performance of Local Identity Farmers in Maha Sarakham Province - Masaunjik, Nava; Yangkham, Piyawan; Kiangkhwa, Thirasak; Wanichkittikul, Kotchanipa; Thotham, Amorn (Interdisciplinary Academic and Research Journal, 2022)
Digital transformation has played a role in society, economy, and environment that has changed the paradigm of living and operations of the organization including agriculture as the main occupation in many countries. It is necessary to learn the innovations that occur to apply them for the greatest benefit of people, society, and the economy. The purposes of this research were: 1) to study the importance of digital marketing of local identity farmers. 2) to study the level of marketing performance of local identity farmers., and 3) to study the influence of the importance of digital marketing on the marketing performance of local identity farmers. Collecting data from 400 farmers in Maha Sarakham Province and a set of questionnaires were the research tool. Statistics used for data analysis were mean, standard deviation, multiple correlation analysis, and stepwise multiple regression analysis. The results revealed the following findings; 1) farmers had opinions about digital marketing in general aspect at a high level and had an average of 4.17, the averages are arranged in descending order as follows: social media marketing aspect had an average of 4.22, content marketing aspect had an average of 4.18, Value Chain aspect had an average of 4.10., 2) farmers had opinions about marketing performance in general aspect at a high level and had an average of 4.16, the averages are arranged in descending order as follows: customer retention aspect had an average of 4.25, sales growth aspect had an average of 4.18, market share aspect had an average of 4.16, profitability aspect had an average of 4.05., and 3) digital marketing had positive relationship and impact on marketing performance of local identity farmers and the forecast in standard score (b) form of 0.498, 0.163, and 0.143, and has a multiple correlation coefficient (R) of 0.633, a forecasting power (R2) of 0.401, and a forecasting power of 40.10%.