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What farmer types are most likely to adopt joint venture farm business structures?
Author(s) -
Kragt Marit E.,
Lynch Brendan,
Llewellyn Rick S.,
Umberger Wendy J.
Publication year - 2019
Publication title -
australian journal of agricultural and resource economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 49
eISSN - 1467-8489
pISSN - 1364-985X
DOI - 10.1111/1467-8489.12332
Subject(s) - attractiveness , profitability index , productivity , marketing , business , population , flexibility (engineering) , diversity (politics) , preference , latent class model , industrial organization , economics , microeconomics , management , statistics , mathematics , economic growth , finance , psychology , demography , sociology , anthropology , psychoanalysis
Joint venture (JV) farm structures have the potential to increase the productivity and profitability of traditional family farms. However, such structures are not widely adopted within the farm business community. Furthermore, knowledge on the relative attractiveness of different JV models to farmers is limited. We use a choice experiment to explore what JV structures are preferred by Australian farmers, and how farmers’ socio‐demographic and attitudinal characteristics influence the type of JV structure preferred. A latent class analysis revealed significant unobserved preference heterogeneity amongst the population. We identify four latent classes that differ in their preferences regarding the number of JV partners, access to new machinery, and/or the opportunity for additional annual leave. All classes of farmers displayed positive preferences for operational decision‐making with other JV partners, although they varied in their preferences towards final operational responsibility. The diversity in preferences shows that there is no ‘one size fits all’ JV design, leaving opportunities for a range of JV decision models. Such flexibility in JV design is likely to have advantages when seeking JV partners, with a significant proportion of the sampled population open to collaborative decision‐making models.