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A Typology-Based Approach for Assessing Qualities and Determinants of Adoption of Sustainable Water Use Technologies in Coping with Context Diversity: The Case of Mechanized Raised-Bed Technology in Egypt

Author

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  • Quang Bao Le

    (Resilient Agricultural Livelihood Systems Program (RALSP), International Center for Agricultural Research in the Dry Areas (ICARDA), 2 Port Said Str., Maadi, Cairo 11711, Egypt)

  • Boubaker Dhehibi

    (Resilient Agricultural Livelihood Systems Program (RALSP), International Center for Agricultural Research in the Dry Areas (ICARDA), El-Rawaby Neighborhood, Yousef el Sukkar Str. Building No. 8, Amman 11195, Jordan)

Abstract

Mechanized raised-bed technology (MRBT) is recognized as an important measure to achieve higher crop productivity and water-use efficiency in intensive irrigated systems. Development efforts on spreading this technology require adequate understanding of the qualities and drivers of farmers’ adoption of MRBT. Research in agricultural innovation adoption has identified the importance of the socio-ecological context (SEC) that influences the livelihood of farmers adopting new technologies. This study introduces an agricultural livelihood systems (ALS) typology-based approach for guiding concrete analytical steps and statistical methods in evaluating the effects of system SEC diversity in two Egyptian governorates. We objectively classify a population of sampled farming households into a limited number of ALS types and use inferential statistics for the whole sampled population and individual ALS types to discover adoption drivers. Values added by the ALS approach confirm the widespread role of common determinants of MRBT adoption across ALS types, household groups subject to the effects MRBT, and show new causal effects. The presented advanced approach and empirical findings will be useful for enhancing targeting and out-scaling of MRBT practices toward achieving sustainable agricultural water uses at scale.

Suggested Citation

  • Quang Bao Le & Boubaker Dhehibi, 2019. "A Typology-Based Approach for Assessing Qualities and Determinants of Adoption of Sustainable Water Use Technologies in Coping with Context Diversity: The Case of Mechanized Raised-Bed Technology in E," Sustainability, MDPI, vol. 11(19), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5428-:d:272401
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    1. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    2. Margaret Pepe & Holly Janes & Gary Longton & Wendy Leisenring & Polly Newcomb, 2004. "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic or Prognostic Marker," UW Biostatistics Working Paper Series 1035, Berkeley Electronic Press.
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    1. Akmal Akramkhanov & Adkham Akbarov & Shakhzoda Umarova & Quang Bao Le, 2022. "Agricultural Livelihood Types and Type-Specific Drivers of Crop Production Diversification: Evidence from Aral Sea Basin Region," Sustainability, MDPI, vol. 15(1), pages 1-19, December.

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