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      Consumer preferences for wild game meat: evidence from a hybrid choice model on wild boar meat in Italy

      , , ,
      Agricultural and Food Economics
      Springer Science and Business Media LLC

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          Abstract

          The increasing numbers of wild animals in Europe is leading, on the one hand, to growing problems stemming from their interaction with human activities. On the other, many European countries have still not developed national supply chains to market wild game. Instead, these supply chains could represent a win–win strategy in providing a sustainable alternative to production via intensive livestock farming and developing rural territories. Our aim was to understand consumer behaviour towards wild game meat. We conducted a choice experiment on wild boar meat on a sample of Italian consumers (625). The application of a hybrid model combining a structural equation model and a latent class analysis allowed us to identify the antecedents of attitude towards wild game meat and to analyse consumer choices by utilising attitude as an explanatory variable. The results provide useful suggestions to implement rural development policies and offer food for thought in the area of consumer behaviour.

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          Most cited references83

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          Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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            Coefficient alpha and the internal structure of tests

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              Comparative fit indexes in structural models.

              P. Bentler (1990)
              Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Agricultural and Food Economics
                Agric Econ
                Springer Science and Business Media LLC
                2193-7532
                December 2022
                August 05 2022
                : 10
                : 1
                Article
                10.1186/s40100-022-00231-w
                35070637
                037ef158-d1f8-4263-ba5b-fee62748bcdd
                © 2022

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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