Nik Taylor a & Tania D. Signal b a Department of Sociology, Flinders University, Adelaide, Australia b Department of Behavioural & Social Sciences,

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1 This article was downloaded by: [Dr Kenneth Shapiro] On: 09 June 2015, At: 08:20 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Journal of Applied Animal Welfare Science Publication details, including instructions for authors and subscription information: Willingness to Pay: Australian Consumers and On the Farm Welfare Nik Taylor a & Tania D. Signal b a Department of Sociology, Flinders University, Adelaide, Australia b Department of Behavioural & Social Sciences, CQUniversity, Rockhampton, Australia Published online: 22 Sep To cite this article: Nik Taylor & Tania D. Signal (2009) Willingness to Pay: Australian Consumers and On the Farm Welfare, Journal of Applied Animal Welfare Science, 12:4, , DOI: / To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the Content ) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or

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3 JOURNAL OF APPLIED ANIMAL WELFARE SCIENCE, 12: , 2009 Copyright Taylor & Francis Group, LLC ISSN: print/ online DOI: / Willingness to Pay: Australian Consumers and On the Farm Welfare Nik Taylor 1 and Tania D. Signal 2 1 Department of Sociology, Flinders University, Adelaide, Australia 2 Department of Behavioural & Social Sciences, CQUniversity, Rockhampton, Australia The success of welfare legislation for nonhuman animals rests upon primary producer compliance that, in turn, is affected by public willingness to pay (WTP) for such initiatives. Although the topic of the welfare of animals on farms (and relevant legislation) is becoming increasingly important to the Australian public, there remain relatively few recent assessments of the variables that may affect WTP and, therefore, support initiatives aimed at improving the welfare of animals living on farms. This study surveyed 1,224 community members in Queensland, Australia. The study assessed respondents self-rated knowledge of, and concern regarding, farm animal welfare. In addition, the survey asked respondents how much more they would be prepared to pay for animal-based products to ensure that they came from a source where the Five Freedoms were met. Although self-rated knowledge and level of concern were found to affect WTP, the study found only concern for farm animal welfare actually predicted consumer behavior. Further analyses showed a potential confound between knowledge levels and locality. This article discusses the implications of this for future initiatives to increase WTP. It has been argued that attention is increasingly focused on the welfare of nonhuman animals as opposed to animal production in postmaterialistic societies (Boogaard, Oosting, & Bock, 2006). One explanation for this has been that the original social contract between human and nonhuman animal, which turned Correspondence should be sent to Nik Taylor, Department of Sociology, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia. nik.taylor@flinders.edu.au 345

4 346 TAYLOR AND SIGNAL on the provision of food and shelter from humans and the provision of economic largesse from animals, has been replaced (Rollin, 1989). The original social contract is suggested to have necessitated the fair and just treatment of animals due to human interests, that is, harm to the animal caused (economic) harm to the human. Intensive practices combined with a shift away from rural living and the increasing ability of humans to manipulate animal environments led to a move away from such a symbiotic relationship toward a more mechanistic one, which required external regulation (Rollin, 1989). The ways of keeping animals in modern agricultural practices also gave rise to a new and different set of welfare-related issues to those in the traditional ethic. For example, certain (new) diseases were reproduced and spread quickly within modern housing systems; different physical and psychological needs of animals kept in confinement became apparent (Barber, 2007). An attendant, pervasive problem with this shift in focus has been that little consensus remains concerning the actual definition of animal welfare. Not only do tensions exist between scientific, lay, and social/moral/ethical definitions but also debates proliferate concerning the differences between, and within, animal welfare and animal rights (Francione, 1996; Fraser, 1993; McGlone, 1993; Rollin, 1993; Taylor, 1999). There is also the distinction between physical and psychological well being; although the former is fairly widely accepted as an indicator of welfare, the latter is more contested. Swanson (1995) suggests that the psychological dimension should include (a) good health (due to proven links between physical and mental well being), (b) the exhibition of varied types of species-typical behavior, (c) freedom from distress, and (d) the ability to adapt and cope with the environment. Consensus regarding appropriate ways to measure animal welfare has also been notoriously difficult to achieve (Broom, 1986; Dawkins, 1980), with arguments covering issues such as the importance of the inclusion of animal preferences (Broom, 1991); the necessity of using a precise and scientific definition of welfare (Broom, 1991); and specifically what indicators may be used to identify poor welfare, such as housing and growth rate (Broom, 1986). Holistic approaches based on assessing a variety of animal needs are usually the preferred approach, for example, the Animal Needs Index (Bartussek, 1995). Gonyou (1993) argues that there are essentially three types of definition concerning animal welfare: legal, public, and technical. Legal definitions are those that can be correctly interpreted by the judicial system; technical definitions are those used by scientists and industry; and public definitions are the result of public knowledge about, empathy toward, and activism for animals. Gonyou suggests that the term welfare should be used to indicate the longterm implications of animal well being, whereas the term well being should be used to address the current state of the animal. In contrast, Fraser (1993) argues that there are three main criteria for defining animal welfare: a high level of biological function, freedom from suffering, and positive experiences such

5 AUSTRALIAN WTP FOR WELFARE LEGISLATION 347 as comfort and contentment. Regardless of the debate in the literature, there appears to be some consensus that the Five Freedoms, originally based on the recommendations of the Brambell Committee (1965) and revised by the Farm Animal Welfare Council (FAWC; 1993) and variations thereof, offer a utilitarian definition of animal welfare; however, it must be noted that there is still no wholesale consensus on issues of measurement. The Brambell Committee was appointed to examine the conditions in which livestock are kept under systems of intensive husbandry and to advise whether standards ought to be set in the interests of their welfare, and if so, what should they be. (cmnd. 2836) The Brambell report represents the first clear articulation of the Five Freedoms, which have since become the in-principle basic needs of animals on the farm, which are deemed necessary to meet to ensure their welfare. They are 1. Freedom from hunger, thirst, and malnutrition; 2. Freedom from discomfort; 3. Freedom from pain, injury, and disease; 4. Freedom to express normal behavior; and 5. Freedom from fear and distress. These ideals have remained a benchmark within animal welfare science and practice and, where in place, frame the general codes by which (livestock) farmers are expected to abide. Moreover, they are now trickling down into public consciousness: for example, the current practice whereby the Royal Society for the Prevention of Cruelty to Animals labels eggs produced in particular ways freedom eggs. This occurs in several countries, including the United Kingdom and Australia (Freedom Food, 2009). Animal welfare has become of considerable concern in the last 3 decades; for example, it is reputed to be the topic about which parliamentary ministers receive most mail (Broom, 1994), and Hurnich (1995) has argued that public interest in animal welfare during the 20th century is the most outstanding ethical development (p. 561) to affect modern-day agriculture. This public interest in animal welfare has, arguably, led to many changes in animal welfare laws over the last decade or so. For example, member states of the European Union (EU) have begun phasing out conventional battery cages for laying hens (Croney & Millman, 2007), and the keeping of pregnant sows in isolation has been banned in the EU since 2001 (Commission of the European Communities, 2002, 626 final). The main areas identified as of public concern include modern animal housing practices; the perceived unnaturalness of intensive production practices, and the transport and slaughter of animals (McInerney, 1994). However, research has revealed that there may be an inconsistency between public attitudes toward

6 348 TAYLOR AND SIGNAL farm animal welfare and consumer practices regarding animal-welfare-friendly products. That is, actual consumer behavior may not match expressed intentions regarding willingness to pay for welfare-friendly produce. In a student-based study (n D 140), Bennett (1996) investigated concerns respondents may have had about animal welfare. Using a case study relating to the banning of battery cages in egg production he investigated whether, and how much, respondents would be willing to pay (WTP) to support more welfarefriendly practices. He found that 81% were concerned that animals would suffer in order to produce food generally, that 72% would support legislation aimed at phasing out battery cages, and that more than 80% expressed WTP for such legislation in terms of an increase in the price of eggs (Bennett, 1996). Subsequent to this, Bennett (1997) surveyed 2,000 people in the United Kingdom in order to elicit their concerns (if any) about general animal welfare and their WTP to support specific legislation to phase out the use of cages in egg production in the EU by He found that 43% of his respondents were very concerned about farm animal suffering in the food process and that 46% were somewhat concerned. In a later paper (using the same data set), Bennett (1998) reported that respondents WTP was positively correlated with their stated level of concern for farm animal welfare and demographic variables such as income and education, whereas WTP was negatively correlated with age. However, only 62% of his respondents indicated that they had actively altered their behavior in line with these concerns, largely through buying freerange products such as eggs. Similarly Holloway (1998) found that 80% of those surveyed in the United Kingdom were willing to pay more for pig meats that came from alternative (more welfare friendly) systems. In contrast, the pig farmers he surveyed argued that the increased production costs needed to comply with stricter legislation meant that consumers often ignored their products for cheaper overseas meat, which was often produced using the very methods the public was lobbying against in the first place (Holloway). Singer (2006) recently suggested that an individual s knowledge of farm animal production processes may also affect their WTP. Specifically, Singer theorized that WTP would be higher in those with more knowledge of modern animal-production processes. Increased urbanization of modern society has led to a progressively removed form of knowledge regarding animals gained through, for example, nature programs and zoos rather than through exposure to primary production processes. For example, there is a general consensus among members of the public that free-range animals are preferable to intensively kept animals (Appleby, 1996). Rogers, Appleby, Keeling, Robertson, and Hughes (1989) asked three groups of people (agriculturalists, general public, and welfarists) to rate six systems of egg production (battery, modified cages, perchery, deep litter, straw yard, and free range) in eight different areas (ease of egg collection, risk of disease, ease of maintenance, bird frustration, adequacy of space, ease of

7 AUSTRALIAN WTP FOR WELFARE LEGISLATION 349 inspection of birds, expense, and adequacy of light). They found that all groups preferred the less intensive measures. Despite the fact that many welfarists have pointed out problems inherent to extensive farming, there remains a general perception that animals kept free range and/or outdoors have higher standards of welfare than those kept in intensive conditions. Jasper and Nelkin (1992) attribute this to sentimental anthropomorphism, which they suggest is symptomatic of increasing urbanization and its attendant shift in focus from animals as components in food-production processes to animals as increasingly meaningful members of society/family; that is, animals who regularly interact with humans in an urban setting are increasingly perceived as subjects. For example, several authors (Sanders, 2003; Taylor, 2007) have recently documented the ways in which caretakers attribute the status of personhood to their companion animals. In contrast, animals who are removed from this interpersonal realm are increasingly ignored and/or designated as objects ; this further serves to distance urban humans from them and the attendant foodproduction processes of which they are a component. The effect of these changes on both WTP and attitudes toward animal welfare generally is unknown. In addition, within an Australian context, animal welfare issues are increasingly becoming matters of public concern: For example, the solicitation of public input into the proposed Model Code of Practice for the Welfare of Animals Pigs (revised; Animal Welfare Group, 2007) debates regarding live export. Coupled with a growing recognition of the myriad roles that animals play in Australian society (Franklin, 2006) and with public opinions regarding animal welfare, which may differ from professional definitions (Gonyou, 1993), this growing concern necessitates an up-to-date assessment of the variables that may affect WTP and therefore support animal welfare initiatives. Thus, there is a need to benchmark the existing WTP of Australian consumers and ascertain demographic and attitudinal variables that may have an impact on WTP for welfare initiatives. Given prior research regarding WTP specifically (Bennett, 1998) and attitudes toward the treatment of animals generally (Signal & Taylor, 2006), it is expected that the following will affect WTP: personal knowledge of modern (animal-based) food production practices; concern for farm animal welfare generally; and demographic variables such as age, gender, income level, and locality (metro or rural area). Participants METHOD The Centre for Social Science Research at CQUniversity administered a telephone survey to a random sample of 2,795 adults over the age of 18 who were

8 350 TAYLOR AND SIGNAL residing in Queensland at the time. The survey resulted in a sample of 1,224 valid responses from 612 males and 608 females; ages ranged from 18 to 85 with an average age of 48, equalling a response rate of 44%. Apparatus As part of the annual Queensland Social Survey researchers were invited to contribute up to 10 questions that reflected their research interests. The survey instrument therefore consisted of three components: (a) standardized introduction, (b) demographics, and (c) researcher-contributed questions. The demographic questions included gender, age, marital status, strength of religious belief, length of time living in the current community, income, political beliefs, and the respondent s home location in a metro or rural area (as defined by the Australian postal service). Further demographic information regarding the following was also collected: 1. Education level (primary, secondary, tertiary-technical, tertiary-university); 2. Current occupation (coded using major categories listed in an online job search engine [ resulting in six categories: Primary Industries, Education, Health Care, White Collar, Blue Collar, and Other); and 3. Occupation status (full or part-time employment). In this survey, the researcher developed questions that required respondents to indicate on a Likert scale (from 1 D not concerned to 5 D extremely concerned) how concerned they were regarding general welfare issues for farmed animals and how much knowledge they felt they had regarding modern animal-based food production practices (from 1 D none at all to 5 D an extensive amount). Finally, respondents were asked how much more would they be prepared to pay for animal-based foods (eggs, dairy, meat) in order to ensure that it came from a source where the Five Freedoms are met (1 D I would not pay more, 2 D <5% more, 3 D 5 10% more, 4 D 10 20% more, 5 D 20 40% more, and 6 D >40% more). It needs to be noted here that respondents were not asked whether they were vegetarian/vegan or how much they currently spent on food. Questions and percentage ranges were developed following examination of the literature (Bennett, 1998; Harper & Henson, 2001). Procedure The 2005 Queensland Survey sample was drawn from a telephone database using a computer program to select, with replacement, a simple random sam-

9 AUSTRALIAN WTP FOR WELFARE LEGISLATION 351 ple of phone numbers within the region. All duplicate, mobile, and business numbers were purged from the computer-generated list. Nursing homes and other collective dwellings such as youth hostels were also deleted from the sample. To ensure a sample representative of the wider Queensland population, one person in the household was selected (based on gender and age) as the respondent for the 20-min interview; analysis of the final sample indicated that, although representative of the wider Queensland population, it slightly overrepresented those in the age group. Queensland is Australia s secondlargest state and the third most populous with more than 3.6 million inhabitants. More than 50% of the population lives in rural or regional settings with agriculture being one of the main industries in the state. According to the Australian Natural Resources Atlas (2009), agricultural activities cover 147 million hectares with livestock grazing representing 96% of this area. The agricultural sector was worth $5.7 billion in Queensland in 1996 and Cropping represented $2.6 billion, livestock industries $2.2 billion, and horticulture $0.9 billion. The current survey was deliberately kept short and simple in order to be accessible and pragmatic for use in a telephone survey. Furthermore, the aim of this study, to ascertain up-to-date benchmark information regarding consumer attitudes toward animal welfare in Australia across a large, representative sample, necessitated a simple design. Due to the large sample size and the apparent normality of the data (as determined via SPSS 13.0), parametric tests (ANOVA and t tests) are utilized. The practice of treating Likert-scale generated data in this manner is well established and acceptable as long as assumptions of normality and sample size are met (Knapp, 1990; Pell, 2005). RESULTS The data were entered into SPSS for Windows (13.0); data cleaning and consistency checks were performed resulting in 1,224 cases. As can be seen in Figure 1, 14% of respondents (n D 156), when asked how much more they would be WTP for animal-based products in order to ensure the Five Freedoms, stated that they would not pay more. In contrast, the largest cohort observed indicated that they would be willing to pay 5 10% more for this type of food (34%; n D 399). The following demographic variables were found to have a nonsignificant (main) effect on WTP: 1. Type of religious belief: F (17, 1101) D 0.606, p D.890; 2. Strength of religious belief: t(783) D 0.352, p D.725; 3. State political affiliation: State: F (10, 1060) D 1.653, p D.087;

10 352 TAYLOR AND SIGNAL FIGURE 1 Respondents reported willingness to pay for animal-based food products that meet the Five Freedoms. 4. Federal: F (10, 1068) D 1.485, p D.139), Ownership of current dwelling: t(457) D 0.326, p D.745; 5. Occupation: F (5, 703) D 0.282, p D.923; 6. Marital status: F (5, 1141) D 1.838, p D.103); 7. Employment status: employed/not employed in past week, t(1140) D 1.786, p D.074; 8. Status of those not currently in paid employment: retired, student, F (4, 419) D 1.823, p D.123; 9. Education level: F (3, 1138) D 0.798, p D.495; 10. Presence of a child in the current dwelling: t(1143) D 0.606, p D.545; and 11. Respondent s place of residence in a metro or rural area: t(1130) D 0.484, p D.629). Although the demographic variables were found to have no significant (main) effect on WTP, an interaction effect between ownership of current dwelling and gender was found to be significant, F (1, 1114) D 4.174, p D.041, as

11 AUSTRALIAN WTP FOR WELFARE LEGISLATION 353 indeed was the effect of gender alone. Overall, women showed significantly higher WTP than did men in the sample, t(1143) D 2.215, p D.027. When the interaction between gender and home ownership was examined, men who owned their current dwelling reported lower WTP than men who currently rented their dwelling (3.16 vs. 3.39). The opposite pattern for women was found (own home 3.43 vs. renting 3.26). Personal and household income levels were both found to have a significant effect on WTP, F (3, 1144) D 3.012, p D.029; F (3, 1144) D 4.864, p D.002, respectively, with WTP generally decreasing as reported weekly income level decreased. Post hoc tests (Tukey s HSD) determined that the significant difference lay between those personally earning less than AUS$500/week and any other (personal) income level. Within the household income demographic, the difference lay between those households earning up to AUS$1,000/week and those earning more than AUS$1,000/week. An analysis of potential gender interaction effects failed to show any significant interaction between income (personal or household) and gender on WTP, F (3, 1144) D 0.636, p D.592; F (3, 1144) D 1.132, p D.335, respectively. Age was also found to have a significant effect on WTP, F (5, 1134) D 2.252, p D.047, with WTP generally decreasing as age increased, regardless of gender, F (4, 1134) D 0.123, p D.974. Post hoc analyses (Tukey s HSD) showed that those in the 55 years and over cohort had significantly lower WTP than any other age group. Given that this age group may consist of a disproportionate number of low-income earners (retired or in receipt of government-provided income support), further analyses were conducted to determine if either personal or household income levels significantly interacted with age in regard to WTP. However, neither household nor personal income level was found to significantly interact with age, F (12, 1134) D 1.319, p D.201; F (11, 1134) D 1.613, p D.090. Participants were asked to rate their level of knowledge regarding modern animal-based food production from 1 (none at all) to 5 (extensive knowledge). As can be seen in Figure 2, the majority of respondents rated their knowledge level as None or Limited (n D 260 and n D 461, respectively). Self-rated knowledge of modern, animal-based food production processes was found to have a significant effect upon WTP, F (4, 1142) D 2.632, p D.033, in that higher levels of knowledge were related to higher WTP. Graphical analyses (WTP as a function of self-rated knowledge) determined that the greatest disparity appeared to be between those who reported knowing anything and those who reported knowing nothing. Post hoc analyses (Tukey s HSD) confirmed this. Although no significant interaction was found between gender and knowledge level, F (4, 1136) D 1.449, p D.216, graphical analyses suggested that women generally had higher WTP at all levels of knowledge with the exception of those in the no knowledge cohort. Within this group, males reported higher WTP than females (however, this was not significant).

12 354 TAYLOR AND SIGNAL Respondents reported knowledge of modern animal-based production pro- FIGURE 2 cesses. As can be seen in Figure 3, when asked how concerned they were regarding general welfare issues for farmed animals, 6.3% (n D 77) replied that they were not concerned at all; the largest cohort (n D 444) indicated that they were concerned. Analyses showed that a respondent s reported level of concern had a significant effect on the respondent s WTP, F (4, 1142) D , p D.000, with higher concern levels relating to higher WTP. Although no significant interaction was found between gender and concern level, F (4, 1136) D 0.265, p D.901, graphical analyses suggested that women had marginally higher WTP with the exception of those in the not concerned category. Within this group, males reported slightly higher WTP than did females: this was not significant. A multiple, stepwise regression was conducted to assess the predictive ability of the variables found to significantly affect WTP. WTP was entered as the dependent variable with gender, income (personal), age, knowledge of animal production processes, and overall concern for farm animal welfare entered as independent variables. The subsequent regression equation predicted approximately 10% of the variance in WTP scores (adjusted r 2 D 0.101, F.5;1129/ D

13 AUSTRALIAN WTP FOR WELFARE LEGISLATION 355 FIGURE 3 Respondents reported concern regarding general welfare issues for animals who are part of the food production process , p D.000). Examination of the standardized beta coefficients determined that concern for farm animal welfare was the strongest predictor (ˇ D 0.279, t D 9.529, p D.000), followed by income (ˇ D 0.119, t D 3.786, p D.000), age (ˇ D 0.097, t D 3.380, p D.001), and gender (ˇ D 0.071, t D 2.278, p D.023). Interestingly, knowledge of animal production processes failed to reach significance (ˇ D 0.043, t D 1.474, p D.141). DISCUSSION The aim of this study was to explore and quantify some of the potential demographic and attitudinal variables that may affect an individual s willingness to pay for animal-welfare-friendly produce. As expected, variables found to affect attitudes toward animals generally also significantly affected WTP, gender, income level, and age. Unsurprisingly, self-rated knowledge of animal-based production and concern for farm animal welfare generally also significantly affected WTP.

14 356 TAYLOR AND SIGNAL Given that previous research has suggested a disparity exists between respondents stated intent and actual behavior regarding WTP, the results of the regression analysis are important. Of note was the fact that although self-rated knowledge level significantly affected WTP, it did not significantly predict WTP. Various authors have suggested that elevation of consumer knowledge levels regarding animal production processes will result in a concomitant increase in WTP. Prima facie, the current results would suggest otherwise; that is, although knowledge levels have a significant effect on stated WTP, this may not translate into actual behavior. However, it must be noted that this study elicited self-rated knowledge of animal production processes rather than assessing that knowledge more objectively. Hence, the lack of predictive ability may in part be explained by an extension of arguments regarding sentimental anthropomorphism (Horowitz & Bekoff, 2007; Jasper & Nelkin, 1992) in that the knowledge level of urban participants is actually related to their experiences of urban animals rather than animal production processes per se. Therefore, this may result in a stated intent to pay more for welfare-friendly food that is not based on knowledge of actual production processes and therefore is not predictive of WTP. Linked closely to this is that respondents indicated concern for animals may generally represent concern for urban animals specifically. Given this potential confound regarding participants self-rated knowledge, a further analysis was conducted to ascertain if there was any interaction between locality (metro vs. rural), knowledge level, and WTP. Although overall levels of WTP were found to be similar for both groups (support for a 5 10% increase in the cost of animal-based food products), a significant interaction effect was found, F (1, 1120) D 6.436, p D.011, between WTP, locality, and knowledge levels although not between locality, income, and WTP, F (1, 1145) D 0.115, p D.735. Specifically, although WTP was unaffected by relative levels of knowledge for rural participants, self-rated knowledge levels did affect WTP of metro participants. That is, those from a metro locality with little or no knowledge showed significantly lower WTP than those from a metro locality who stated they had at least some knowledge of modern animal production processes. Thus, it would appear that, for metro participants specifically, some awareness (albeit that this may not equate to actual knowledge) of animal-based production processes significantly affects WTP. It may therefore be that increasing actual knowledge of such production processes within metro-based populations would result in both an increase in expressed WTP and actual consumer behavior as proposed by Singer (2006). Given that recent Queensland government figures suggest that nearly two thirds of the state s population, approximately 2.7 million (Rohlin & Taylor, 2006), reside in metropolitan areas, an increase in WTP within this cohort would be significant.

15 AUSTRALIAN WTP FOR WELFARE LEGISLATION 357 In terms of rural participants, the lack of interaction between expressed knowledge levels and WTP is not particularly surprising. Previous research measuring expressed attitudes toward the treatment of animals has found that those living in rural areas tend to have more utilitarian attitudes toward animals (Kellert, 1980; Signal & Taylor, 2006). Furthermore, those in the rural community may well be involved in, and also know more about, animal-based production processes in the first place. This makes discussion about how to increase their knowledge somewhat moot. Thus, the hypothesis that increasing individuals knowledge levels regarding animal-based production will lead to a concomitant increased WTP may well only be supported when discussing metro communities. It should also be noted that rural dwellers such as farmers are likely to be the group most affected by animal welfare legislation either directly or indirectly in that they are likely to be stakeholders of some kind. Thus, any costs incurred in implementing more animal-welfare-friendly practices are likely to be borne by them; this, in turn, makes compliance and support less likely (Austin, Deary, & Willock, 2001). If this is the case, then measures aimed at increasing metro participants WTP are even more important to ensure that rural stakeholders are not unfairly burdened with any associated costs. CONCLUSION Due to methodological constraints, a limit of this study was the fact that participants were asked to rate their knowledge of animal-based production processes generally, as opposed to in a species-specific manner. It is recommended that future research solicit knowledge of species-specific production processes, such as egg production and pork, and investigate potential links and WTP for speciesspecific food products. For example, there may be differences in consumer WTP for welfare-friendly initiatives that will affect pigs as opposed to hens or deer as opposed to cows. Future research may also need to consider potential differences in WTP due to the end product such as dairy produce as opposed to beef. Such specific information may be needed in order to maximize the effect on WTP of any future information campaigns aimed at metro populations. REFERENCES Animal Welfare Group. (2007). Model Code of Practice for the Welfare of Animals Pigs (revised). Submitted to Primary Industries Ministerial Council. Retrieved December 10, 2008, from Appleby, M. (1996). Can we extrapolate from intensive to extensive conditions? Applied Animal Behaviour Science, 49,

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