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Innovation in agriculture The case of agricultural broadening through direct selling

Innovation in agriculture The case of agricultural broadening through direct selling. Anne Vuylsteke Promotor: Prof. G. Van Huylenbroeck. Plan of the presentation. Introduction General framework PhD Direct selling Research setting Results Conclusions. General framework PhD.

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Innovation in agriculture The case of agricultural broadening through direct selling

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  1. Innovation in agricultureThe case of agricultural broadening through direct selling Anne Vuylsteke Promotor: Prof. G. Van Huylenbroeck

  2. Plan of the presentation • Introduction • General framework PhD • Direct selling • Research setting • Results • Conclusions

  3. General framework PhD • Mainly based on the SUS-CHAIN project Innovation Organizational innovation Hybrid organizations • Economic performance • Organization • Impact on rural development • … Example of direct selling

  4. Direct selling • Typology (Marsden et al., 2000) • Face-to-face • Spatial proximity • Spatially extended • Importance of direct selling • Europe (Renting et al., 2003) • 1,4 million farms (20%) • impact differs: 7-10% of the total NVA in Germany, France, Italy; 2-4% in Netherlands, UK, Spain; < 1% in Ireland • Flanders (ALT, 2002) • 1.535 farmers (4,1%) • Joined turnover of € 166 million

  5. Research setting • Joint database (21 variables, 3.827 respondents) • Agriculture in the peri-urban region of Brussels • Food normalization practices • Broadening activities of farmers in West Flanders • Main hypothesis “Farmers who sell their produce directly to the consumer have specific personal and farm characteristics, have more time available, choose different marketing strategies and are located in another part of Belgium” • Descriptive statistics and Logit analysis

  6. Results – Descriptive analysis • Direct sellers … • Are significantly younger • Work more often with their partners • Obtained a degree of higher education • Collaborate more often with other farmers and authorities • Have a bigger area • Run a more extensive farm • Have another farm typology • Participate more in other short supply chains • …

  7. Results – Logit analysis • Prob (direct marketing) = 1 / (1+e^(-Z)) • Farmers with direct selling activities have specific personal characteristics Z = -4,414 + 0,016 age + 0,117 edfarm + 0,260 edpart + 0,257 successor + 0,641 coll • Different farm characteristics can be noticed according to the direct marketing status Z = -1,727 – 0,070 farmtyp + 0,000 sgm + 0,008 area

  8. Results – Logit analysis • The presence of direct selling activities depends on the time available at the farm Z = -2,137 + 0,359 partner + 0,510 pers + 0,000 sgmha – 0,132 mainocc • Direct sellers use different marketing strategies at their farm Z = -1,447 + 0,172 labels + 0,208 contract + 1,434 farmma • There is an influence of the geographical region of the farm on the presence of direct selling activities Z = -0,718 – 0,555 source

  9. Conclusions • The individual null hypotheses and the main hypotheses cannot be rejected • Low explanation power of the logit models: there are many other factors influencing the presence of direct selling activities

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