The adoption of digital and mechanized innovations in rice farming systems remains uneven across gender groups, particularly in developing agricultural economies where socio-cultural norms, resource access, and technological literacy vary significantly. This study proposes a Gender-Responsive Technology Acceptance Model (GRTAM) to examine the determinants influencing digital innovation adoption in rice farming systems. The framework integrates classical Technology Acceptance Model (TAM) constructs with gender-sensitive variables such as decision-making autonomy, access to agricultural information, and perceived socio-economic benefits.

Drawing upon empirical and conceptual insights from prior studies (Ambong & Paulino, 2020; Mariano et al., 2012), this research synthesizes evidence on how gender moderates adoption behavior in agricultural technology contexts. The study further incorporates mechanization constraints highlighted in Philippine and Asian rice farming systems (Abad, 2021; Alvaro et al., 2021). A comparative literature synthesis reveals that female farmers often face structural barriers in accessing and utilizing improved rice technologies, despite their significant role in agricultural productivity.

The proposed model emphasizes behavioral intention, perceived usefulness, and perceived ease of use, while extending TAM with gendered socio-economic constructs. Findings from literature synthesis suggest that gender-responsive interventions significantly enhance adoption rates and improve farm-level efficiency. The study contributes to the growing body of knowledge on agricultural digital transformation and provides a theoretical foundation for policymakers and agritech developers to design inclusive innovation systems.

Gender-responsive model, Technology Acceptance Model (TAM), rice farming systems, digital agriculture

Abad, R. (2021). Rice Machinery Requirement in La Union, Philippines: A Basis for Prioritizing Deployment. Recoletos Multidisciplinary Research Journal, 9(2), 129–146. https://doi.org/10.32871/rmrj2109.02.01

Addison M., Aidoo R., Ohene-Yankyera K. Gender effect on adoption of selected improved rice technologies in Ghana. Journal of Agricultural Science. 2018;10(7)

Aduwo, O., Aransiola, J., Ikuteyijo, L., Alao, O., Deji, O., Ayinde, J., Adebooye, O., & Oyedele, D. (2019). Gender differences in agricultural technology adoption in developing countries: a systematic review. Acta Horticulturae, 1238, 227–238. https://doi.org/10.17660/actahortic.2019.1238.24

Alshurideh, M.T., Al Kurdi, B., Masa'deh, R. and Salloum, S.A. (2021), "The moderation effect of gender on accepting electronic payment technology: a study on United Arab Emirates consumers", Review of International Business and Strategy, Vol. 31 No. 3, pp. 375-396. https://doi.org/10.1108/RIBS-08-2020-0102

Alave, K. L. (2012, 28). Philippine farmers among least mechanized in Southeast Asia. INQUIRER.net. https://globalnation.inquirer.net/41993/philippine-farmers-among-least-mechanized-in-southeast-asia

Alvaro, L. L. R., Angeles, M. K. S., Celis, E. C., Cruz, V. S. D., Ebron, J. J. D., Espiritu, I. V., & Esquivel-Santos, M. G. (2021). Effects of Farm Mechanization on the Lives of Rice Farm Workers of Cabanatuan City, Nueva Ecija. International Journal of Advanced Engineering Management and Science, 7(8), 12–17. https://doi.org/10.22161/ijaems.78.3

Ambong, R. M. A. (2022). Methods of Rice Technology Adoption Studies in the Philippines and Other Asian Countries: A Systematic Review. Research on World Agricultural Economy, 3(2), 15–24. https://doi.org/10.36956/rwae.v3i2.513

Ambong, R. M., & Paulino, M. A. (2020). Analyzing rice farmers' intention to adopt modern rice technologies using technology acceptance model (TAM). Asian Research Journal of Agriculture, 21-30. https://doi.org/10.9734/arja/2020/v13i130094

Ani, P. A. B. & Casasola, H.C (2020). Transcending barriers in agriculture through gender and development. FFTC Agricultural Policy Platform (FFTC-AP). [Online]. https://ap.fftc.org.tw/article/1872

Aryal, J., Farnworth, C., Khurana, R., Ray, S., Sapkota, T., Rahut, D.B. (2020). Does women's participation in agricultural technology adoption decisions affect the adoption of climate-smart agriculture? Insights from Indo-Gangetic Plains of India. https://doi.org/10.1111/rode.12670

Bautista, E. G., Kim, J. S., Kim, Y. J., & Panganiban, M. E. (2017). Farmer's Perception on Farm mechanization and Land reformation in the Philippines. Journal of the Korean Society of International Agriculture, 29(3), 242–250. https://doi.org/10.12719/ksia.2017.29.3.242

Bautista, E., Regalado, J. C., Juliano, A. S., & Beltran, J. C. (2023). Davalos, E.Z and J. M. Subaba, J.M, Eds., "RCEF Mechanization Program Annual Report 2022," Philippine Center for Postharvest Development and Mechanization, Philippines, ISSN: 2960-3706, 2022. Accessed: Jun. 29, 2024. [Online]. Available: https://rcef.philmech.gov.ph/?page=aboutRcef. Rice-Based Biosystems Journal, 10(1), 113–122.

Bautista, E (2020). Mechanization of rice and rice-based farming. https://www.philrice.gov.ph/wp-content/uploads/2021/08/3_Rice-Farm-Mechanization-and-Modernization-Program.pdf

Beshir B., Wagary D., (2014). Determinants of smallholder farmers' hybrid maize adoption in the drought prone Central Rift Valley of Ethiopia. African Journal of Agricultural Research. 2014;9(17):1334–1343.

Binyamin, S. S., Rutter, M. J., & Smith, S. (2020). The moderating effect of gender and age on the students' acceptance of learning management systems in Saudi higher education. Knowledge Management & E-Learning, 12(1), 30–62. https://doi.org/10.34105/j.kmel.2020.12.003

Bourdillon M., Hebinck P., Hoddinott J., Kinsey B., Marondo J., Mudege N., Owens T., (2002). International Food Policy Research Institute; Washington, DC: 2002. Assessing the impact of HYV maize in resettlement areas of Zimbabwe. Summary report.

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2023). Correction to: Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management. https://doi.org/10.1007/s10490-023-09880-x

Chow, M., Herold, D. K., Choo, T., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use second life for enhancing healthcare education. Computers & Education, 59(4), 1136-1144. https://doi.org/10.1016/j.compedu.2012.05.011

Dalman, N. a. M., Aguhob, N. R. A., Buniel, N. R. J. N., Tado, N. N. C. M., Osoteo, N. M. R. B., & Belivestre, N. C. M. C. (2023). Assessment on the Level of Mechanization in the Rice Production and Post-Production Systems in Surigao Del Sur. Proceedings of International Exchange and Innovation Conference on Engineering & Sciences (IEICES), 9, 201–206. https://doi.org/10.5109/7157972

Davalos, E.Z and J. M. Subaba, J.M, Eds., "RCEF Mechanization Program Annual Report 2022," Philippine Center for Postharvest Development and Mechanization, Philippines, ISSN: 2960-3706, 2022. Accessed: Jun. 29, 2024. [Online]. Available: https://rcef.philmech.gov.ph/?page=aboutRcef

Diiro G., Ker A., Sam A., (2015). The role of gender in fertilizer adoption in Uganda. African Journal of Agricultural and Resource Economics. 2015;10(2):117–130

Doss C., (2006). Analyzing technology adoption using microstudies: Limitations, challenges, and opportunities for improvement. Agricultural Economics. 2006;34(3):207–219.

Doss, C., Mwangi, W., Verkuijl H., and de Groote H. (2003). Adoption of maize and wheat technologies in Eastern Africa: A synthesis of the findings of 22 case studies. CIMMYT economics working paper 03-06. Mexico, DF: CIMMYT.

Feder, G., & Umali, D. L. (1993). The adoption of agricultural innovations. Technological Forecasting and Social Change, 43(3-4), 215-239. https://doi.org/10.1016/0040-1625(93)90053-a

Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33(2), 255-298. https://doi.org/10.1086/451461

Foyster, R. (2020). How Technology Is Helping Rural Women Get Ahead In Agriculture. Available at: https://womenlovetech.com/how-technology-is-helping-rural-women-get-ahead-in-agriculture/

Gaya, H., Tahir, A., & Bamire, A. (2021). Gender Differentials in the Adoption of Drought-Tolerant Maize Varieties among Farmers in the Northern Region of Ghana. Journal of Biology, Agriculture and Healthcare, 11(20). https://doi.org/10.7176/jbah/11-20-04

Gebre, GG., Isoda H., Rahut DB., Amekawa Y., Nomura H., (2019). Gender differences in the adoption of agricultural technology: The case of improved maize varieties in southern Ethiopia.

Goswami, A., & Dutta, S. (2016). Gender Differences in Technology Usage—A Literature Review. Open Journal of Business and Management, 04(01), 51–59. https://doi.org/10.4236/ojbm.2016.41006

Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, S. (2021). An Introduction to Structural Equation Modeling. In: Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Classroom Companion: Business. Springer, Cham. https://doi.org/10.1007/978-3-030-80519-7_1

Hair, J.F., Hult, G. T., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.

Hair, Joe; Hollingsworth, Carole L; Randolph, Adriane B; Alain Yee Loong Chong. (2017) "An updated and expanded assessment of PLS-SEM in information systems research", Industrial Management & Data Systems, Vol. 117 Issue: 3, pp.442-458, https://doi.org/10.1108/IMDS-04-2016-0130

Huo, Y., Ye, S., Wu, Z., Zhang, F., & Mi, G. (2022). Barriers to the development of agricultural mechanization in the north and Northeast China plains: A farmer survey. Agriculture, 12(2), 287. https://doi.org/10.3390/agriculture12020287

Huyer, S. (2016). Closing the Gender Gap in Agriculture. Gender Technology and Development, 20(2), 105–116. https://doi.org/10.1177/0971852416643872

Kassa Y., Kakrippai R., Legesse B. Determinants of adoption of improved maize varieties for male headed and female-headed households in West Harerghe zone, Ethiopia. International Journal of Economic Behavior and Organization. 2013;1(4):33–38.

Kawarazuka, N., Prain, Gordon, Forsythe, L., Mayanja, S., Mudege, N.N., Babini, C., Polar, V. (2018). Gender in Agricultural Mechanization: Key guiding questions. Lima, Peru: CIP.

Khatiwada, D., Dutta, J. P., Shrestha, K., Adhikari, G., & Paudel, H. (2021). Economic Impact of Agricultural Mechanization In Rice Farming In Shivasatakshi Municipality Of Jhapa District, Nepal. Food and Agri Economics Review, 1(1), 41–45. https://doi.org/10.26480/faer.01.2021.41.45

Kline, R. B. (2023). Structural Equation Modeling. In Cambridge University Press eBooks (pp. 535–558). https://doi.org/10.1017/9781009010054.026

Lui, T. K., Zainuldin,M. H., Yii, K. J., Lau, L. S., and Go, Y. H. (2021). Consumer adoption of alipay in Malaysia: the mediation effect of perceived ease of use and perceived usefulness. Pertanika J. Soc. Sci. 29. doi: 10.47836/pjssh.29.1.22

Luis, J., Paris, T., Pede, V., & Rola-Rubzen, M. F. (2015). Rural Labor Outmigration and Gender Dimension in an Assessment of Farm Technical Efficiency: A Case Study in Selected Rice Villages in the Philippines. Asian Journal of Agriculture and Development, 12(1), 53–65. https://doi.org/10.37801/ajad2015.12.1.4

Manila Standard (2022, January 26). 6 challenges faced by rice farmers in the Philippines. Manila Standard. https://manilastandard.net/?p=314202588

Manfre C., Rubin D., Nordehn C. 2018. Assessing how agricultural technologies can change gender dynamics and food security outcomes.

Mariano, M. J., Villano, R., & Fleming, E. (2012). Factors influencing farmers' adoption of modern rice technologies and good management practices in the Philippines. Agricultural Systems, 110, 41–53. https://doi.org/10.1016/j.agsy.2012.03.010

Miguel, C., Sarmiento, J. M., Estaña, L. M., Limpoco, M. a. A., Calag, V., Novero, A., & Alviola, P. (2021). Neighborhood Effects in Hybrid Rice Adoption in Davao del Sur, Philippines. The Philippine Journal of Science, 150(6A). https://doi.org/10.56899/150.6a.10

Mishra, A. K., Khanal, A. R., & Mohanty, S. (2017). Gender differentials in farming efficiency and profits: The case of rice production in the Philippines. Land Use Policy, 63, 461-469. https://doi.org/10.1016/j.landusepol.2017.01.033

Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions: Implications for a changing work force. Personnel Psychology, 53(2), 375-403. https://doi.org/10.1111/j.1744-6570.2000.tb00206.x

Mtega, W.P., Ngoepe, M., Dube, L., (2016). Factors influencing access to agricultural knowledge: The case of smallholder rice farmers in the Kilombero district of Tanzania. South African Journal of Information Management. 18(1), 1-8.

Mujawamariya, G., Zenna, N., Leonard, L., Andrianina, I. T., & Ramiaramanana, D. (2022). A gendered outlook into the adoption of improved rice varieties in Madagascar. Gender Technology and Development, 26(1), 1–27. https://doi.org/10.1080/09718524.2022.2034095

Mustafa, M. H., Ahmad, M. B., Shaari, Z. H., & Jannat, T. (2021). Integration of TAM, TPB, and TSR in understanding library user behavioral utilization intention of physical vs. E-book format. The Journal of Academic Librarianship, 47(5), 102399. https://doi.org/10.1016/j.acalib.2021.102399

Nićin, N. (2021). Women in Agricultural Technology. Available at: https://dione-project.eu/women-in-agriculture-technology/

OECD. (2001). Adoption of technologies for sustainable farming systems. Wageningen Workshop Proceedings (pp. 3-149). Paris: OECD Publications.

Ogada, M.J., Mwabu, G. & Muchai, D. Farm technology adoption in Kenya: a simultaneous estimation of inorganic fertilizer and improved maize variety adoption decisions. Agric Econ 2, 12 (2014). https://doi.org/10.1186/s40100-014-0012-3

Orge, R., Subaba, J. M., Beltran, J. C., Martin, R., & Corales, A. (2022). RICE MECHANIZATION MODELS FOR SMALLHOLDER FARMERS: A CASE IN THE PHILIPPINES. RICE-BASED BIOSYSTEMS JOURNAL, 10, 33–40.

Paman, U., Khairizal, Wahyudy, H. A., & Bahri, S. (2019). Farm power sources and machinery contribution in small rice farming operations in Kampar region, Indonesia. IOP Conference Series: Earth and Environmental Science, 347(1), 012117. https://doi.org/10.1088/1755-1315/347/1/012117

Paulino MA, Amora JT (2019). Towards the development of crop productivity model. Review of Integrative Business and Economics Research. 2019;8(4): 412-422.

Puntumetakul, R., Yodchaisarn, W., Emasithi, A., Keawduangdee, P., Chatchawan, U., & Yamauchi, J. (2014). Prevalence and individual risk factors associated with clinical lumbar instability in rice farmers with low back pain. Patient Preference and Adherence. https://doi.org/10.2147/ppa.s73412

Purnawirawan, N., Pelsmacker, P. D., & Dens, N. (2012). Balance and sequence in online reviews: how perceived usefulness affects attitudes and intentions. Journal of Interactive Marketing, 26(4), 244–255. doi:10.1016/j.j

Rezvani, S., Dokhanian, S., Roustapisheh, N., & Heidari, S. (2022). The Effectiveness of System Quality, Habit, and Effort Expectation on Library Application Use Intention: The Mediating Role of Perceived Usefulness, Perceived Ease of Use, and User Satisfaction. International Journal of Business Information Systems.