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Source: Author
                        The initial search identified 120 records, including 61 from Google Scholar, 45 from
                  ScienceDirect, and 14 from MDPI. After removing 10 duplicate records, 110 studies
                  remained for the screening stage. These studies were screened based on their titles,
                  abstracts, and keywords to assess their relevance to the research topic.
                        To ensure the relevance and quality of the selected studies, specific inclusion and
                  exclusion criteria were applied. Studies were included if they examined digital technology
                  adoption in agriculture, focused on farmers or agricultural stakeholders, used quantitative
                  research methods, and were conducted in Vietnam. In contrast, studies were excluded if
                  they were review articles or meta-analyses (n = 7), not directly related to the research
                  topic (n = 1), not quantitative studies (n = 3), or conducted outside Vietnam (n = 84). No
                  studies were excluded based on publication year within the last ten years.
                        After applying the selection criteria and completing the screening and eligibility
                  assessment stages, 10 studies were included in the final systematic review. The overall
                  study selection process is illustrated in Figure 2, which presents the PRISMA flowchart of
                  the selected studies.
                        4. Results and discussion
                        The systematic literature review identified 42 significant variables influencing the
                  digital literacy and digital technology adoption of Vietnamese farmers. These
                  determinants can be categorised into five major groups: demographic and socioeconomic
                  factors, farm and market factors, institutional factors, digital factors, and behavioural
                  factors (see Table 1). This classification suggests that digital technology adoption in
                  Vietnamese agriculture is multidimensional, shaped not only by farmers’ personal
                  characteristics but also by farm conditions, institutional support systems, access to digital
                  infrastructure, and behavioural perceptions (Figure 3).
                        Among these groups, demographic and socioeconomic factors and farm–market
                  factors appear most frequently, indicating that structural characteristics of farmers and
                  their farming systems remain central determinants of technology adoption in Vietnam.
                        Table 1. Determinants of digital technology adoption in Vietnam.
                                                              Frequency    Frequency
                  Super Theme      Determinants                                         References
                                                              of Sig. (+)  of Sig. (-)
                                   Age                        2            9            (Tran et al.,
                                   Gender                     4            1            2024a); (Nguyen
                                   Education level               6                      et al., 2025b); (Le
                                   Ethnic differences         1                         et al., 2026);
                                   Farmer’s experience        1                         (Nguyen et al.,
                  Demographic      Type of household          1                         2025a); (Tran et
                  and              Number of family                                     al., 2024b);
                  Socioeconomic    workers                                 3            (Hoang, 2020a);
                  factors          Household rice income/                               (Hoang, 2020b);
                                   Total income/ Household 4                            (Hoang &
                                   annual income                                        Drysdale, 2021);
                                                                                        (Tran et al.,
                                   Access to credit           1            1            2019); (Le et al.,
                                                                                        2024)
                  Farm and         Farm size                  6                         (Tran, et al.,
                  Market           Squared farm size                       1            2024a); (Nguyen


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