MNL and RPL results

We analyzed the choice experiment data using the MNL, RPL, and LC models in NLOGIT 5.0.

Table 6.4 presents results of the MNL and RPL model specifications. The first column shows the MNL model with all parameters fixed. In the second column, the RPL model is presented.

We estimated the RPL model using 1,000 Halton draws for the simulations as this was needed to produce stable results. The results show that all the attribute coefficients for the two specifications have the expected signs and are statistically significant justifying the appropriate choice of the attributes.

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However, we observed some differences with regard to the results of the storage form and production claim attributes. Specifically, in the MNL model, fresh has the highest marginal utility while the antibiotic/hormone-free claim is the highest in the RPL model. Comparing the specifications, we find that the goodness-of-fit measures (i.e., log-likelihood, Pseudo R², Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC)) significantly improved with the RPL model.

Table 6.4: Parameter estimates from the MNL and RPL models

Variables

Note: ^*** Denotes statistical significance at the 1% level.

Since the RPL model fits the data better than the MNL model, we limit our discussion to the results from the RPL model. In line with assumptions usually employed in the literature, we assumed that all the attributes (i.e., country-of-origin, product form, storage form, and production claim) except price and the opt-out option are random and normally distributed.

Making the price parameter fixed is in line with other empirical studies (e.g., Rigby & Burton, 2005; Tonsor et al., 2009; Ortega et al., 2016). The price is fixed to avoid problems in the derivation of WTPs if the distribution of the price coefficient is close to or contains zero (Rigby

& Burton, 2005). For the analysis, we converted the price variable from per 1.3kg to per kg.

Results from the RPL model show that all of the estimated coefficients for foreign, cuts (parts), fresh, and antibiotic/hormone-free claim, are statistically significant at the 1% level.

Associated with each of the mean coefficient estimates of the random parameters are estimated standard deviations, which indicates the amount of variation around the sample population. The significance of the standard deviations of the attribute coefficients shows

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whether taste differences vary significantly across the population of consumers. The estimated standard deviation of each random parameter coefficient is significantly different from zero at the 1% level. This implies that there is heterogeneity in the preferences for the various chicken meat attributes. To evaluate further preference heterogeneity in the RPL model, we allowed for correlation among the random chicken attribute parameters. The diagonal values in the Cholesky matrix denote the true standard deviation of each random parameter after the cross-correlated parameter terms have been unconfounded (Hensher et al., 2005). As shown in Table 6.4, the values in the diagonal of the Cholesky matrix were all statistically significant, indicating evidence of persistence preference heterogeneity, even after allowing cross-correlations to exist among attribute parameters.

As expected, there is clear evidence against the opt-out option. The ASC parameter, which represents the ‘none of these’ option, is negative and significant. This indicates that the surveyed respondents tended to highly prefer any of the chicken products presented (i.e., either Option A or Option B), as opposed to the ‘none of these’ option regardless of the levels of the attributes in Options A and B. The fixed price parameter is negative and statistically significant, which is consistent with economic theory. The negative sign indicates that the likelihood of purchase would decline as the price increased.

Considering the country-of-origin with Ghana as the reference, we observe that the estimated coefficient for foreign is statistically significant and negative. This suggests that respondents perceive domestic chicken as a more valuable product than imported chicken. This is generally consistent with findings reported in the literature regarding the importance of country-of-origin and a preference for domestic meat. For instance, Pouta et al. (2010) reported that consumers in Finland value domestically produced broiler meat over that from Denmark, Brazil, and Thailand. Similarly, Balcombe et al. (2016) found that UK consumers place a high value on chicken breast from the UK over other countries in the EU or outside the EU. Thus, the preferences exhibited by respondents in this study are generally in accordance with the previous literature. This finding can be attributed to consumer ethnocentrism (Shimp & Sharma, 1987; Orth & Firbasová, 2003), consumer sense of identity and feeling of belongingness (Verlegh & van Ittersum, 2001) or consumer relating domestic products to freshness, taste, and high quality (Chambers et al., 2007).

The positive and significant coefficient related to the product form (cuts) shows that on average consumers prefer chicken cuts to whole-dressed chicken. However, the effect of cuts is relatively small, which might be due to the fact that both cuts and whole-dressed are all convenient forms of chicken meat compared to live birds –– the form in which domestic

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chickens are mainly sold. Another possible explanation for the relatively small marginal utility could be due to uncertainty among respondents in the cuts they were buying. For instance, the significant heterogeneity found in the cuts could imply that respondents have preferences for different cuts (such as leg quarters/thighs, wings, backs, etc.), which were not captured by this study. Notwithstanding, cuts appear to come with a higher level of convenience in comparison to whole-dressed, especially with regard to the ease and amount of time spent in preparation.

Hence, it is not surprising that they are preferred over the whole-dressed chicken. Consumer preference for convenient chicken is consistent with previous studies in Ghana (Woolverton &

Frimpong, 2013) and Kenya (Bett, Peters, Nwankwo, & Bokelmann, 2013). In contrast, Kwadzo, Dadzie, Osei-Asare, and Kuwornu (2013) found that households in Ghana preferred whole-dressed to chicken cuts (parts). However, compared to live birds, they found that chicken parts are the most preferred.

Freshness is an important quality cue used by consumers to assess the safety of meat products (Becker, Benner, & Glitsch, 2000). In this regard, the estimated coefficient of the storage form attribute reveals that consumers prefer fresh to frozen chicken meat. The preference for fresh chicken meat over frozen shows that freshness is an important quality attribute for consumers and hence a year-round supply of fresh chicken meat in retail markets is essential. The result is consistent with Bett et al. (2013) who found that consumers in Kenya preferred fresh to frozen chicken meat. Consumers received the highest marginal utility from the production assurance. Specifically, the coefficient of the attribute level antibiotic/hormone-free claim is positive and statistically significant. This implies that consumer utility increases when an antibiotic/hormone-free claim is made for a chicken meat product. The result suggests that consumers in Ghana are similarly concerned about food safety as those in developed countries. Owusu-Sekyere, Owusu, and Jordaan (2014) reported a similar observation of consumer concern for safety in beef. Therefore, it would appear that in Ghana irrespective of the meat type, safety plays a major role in consumers’ meat choice. The result is also consistent with similar findings of food safety concern among consumers in Asia and Africa (Jabbar, Baker, & Fadiga, 2010).