Agribusiness Review - Vol. 6 - 1998

Paper 2
ISSN 1442-6951

MEAT CONSUMPTION PATTERNS OF MEAT CONSUMPTION:
SOME AUSTRALIAN EVIDENCE

Christine E. Storer - Geoffrey N. Soutar - Murray H. Hawkins

ABSTRACT

A study of Perth metropolitan consumers was undertaken to provide insights into meat consumption patterns. Current meat use patterns are described, as well as the meat benefits sought by shoppers. The market was segmented based on meat use patterns and eight segments were found that were labelled ‘light meat eaters', ‘moderate meat eaters', ‘beef eaters', ‘white meat eaters', ‘lamb eaters', ‘chicken eater', ‘heavy meat eaters' and ‘mutton eaters' in order of size. Differences in the lifestyle, demographic and socio-economic characteristics of the segments were examined and their marketing implications were considered.

• INTRODUCTION
• RESEARCH DESIGN
• RESULTS OBTAINED
• CONCLUSIONS
• REFERENCES
• Appendix A - Lifestyle Questions
• Appendix B - Meat Benefits Questions

INTRODUCTION

The way Australians eat meat has changed significantly in recent years. Per capita consumption of red meats has fallen steadily, while white meat consumption has, until recently, risen ( Western Australian Meat Marketing Corporation 1991 ). During 1994-95 meat consumption fell over nine percent, with the largest falls in mutton (43 per cent) and beef (8 per cent) consumption, while poultry consumption fell slightly (3 per cent) ( Australian Bureau of Statistics 1996 ). Similar patterns are evident in Europe ( Ritson 1988 ; Meat and Livestock Commission (UK) 1993 ) and North America (Australian Meat & Live-stock Corporation (New York) 1991 ).

There have been a number of reasons suggested for these changes in meat consumption patterns. These include reduced household time for cooking, especially in two income households and changes in cooking, shopping and storage technologies. Quick and easy to prepare meals and semi-prepared foods have become popular ( McKinna et al. 1984 ; Tuller & Morris 1988 ; Chris Adams Research Pty Ltd 1990 ; MLC 1993 ), while package technology has allowed meat to be stored for longer periods, increasing the range of available food options ( Caredes 1988 ; Egan, Eustace & Shay 1988 ; Wheatley 1996 ). Freezers have also had an impact, allowing food to be purchased less often ( McKinna et al. 1984 ). Microwave ovens have also affected eating patterns as microwave ovens can thaw and cook meat more quickly ( McKinna et al. 1984 ; Bartley, Ball & Weeks 1988 ; Gough 1993 ). Further, people tend to eat out more often and fewer people eat set meals at home ( Harrington 1988 ; Waslien 1988 ; Haines 1992 ; Nayga 1994 ; Wheatley 1996 ).

Changes in retail patterns have also affected consumption patterns. Greater retail competition has increased the variety of meat alternatives and ensured consumers have more information in the form of package notes and point of sale recipes ( McKinna et al. 1984 ; Tuller & Morris 1988 ; Caredes 1988 ; Duff 1989 ). It is also apparent that consumers now shop for meals where once they shopped for set weights of meat and vegetables ( Wheatley 1996 ). Consequently, meat faces increased competition from rice, pasta and prepared foods. This is in addition to the competition faced between types of meat which fluctuates depending on the relative prices.

Health awareness has also played a part as consumer concerns about a healthy diet and life style have increased ( Australian Meat & Live-Stock Corporation (AMLC) 1994 ). Medical studies suggest that fat, cholesterol and food additives can contribute to a variety of ills, including cancer and heart disease ( Kempster 1987 ; Caredes 1988 ; Tuller & Morris 1988 ; Waslien 1988 ). Animal meat that contains ‘saturated fats' and cholesterol has not fared well in this environment, particularly with health conscious consumers ( McKinna et al. 1984 ; Hopkins and Congram 1985 ; Everett 1987 ; Pulter & Frazao 1991 ). There seems to be a move towards leaner meat among those who changed their meat eating patterns ( Storer 1994 ) and a cut back in the use of fats and oils and a restriction on red meat consumption ( AMLC 1994 ).

Such changes have affected many consumers but the problem is that little is known about people's general patterns of meat use, making it difficult for meat marketers to develop and implement rational marketing strategies. A study of Perth consumers was undertaken to provide some insights to these changes and the results obtained are discussed in the present paper. The aim was not only to describe current meat use patterns but also to segment the market so that strategies could be tailored to meet the needs of different consumers ( Wind 1978 ; Kotler, Chandler, Brown & Adam 1994 ). The next section of the paper outlines the study's approach while subsequent sections examine the results obtained and their implications for meat marketers.

RESEARCH DESIGN

The present study was undertaken in the Perth metropolitan area. Data were collected from household food purchasers or preparers in July and October 1992 so that seasonal differences in consumption could be examined. An initial examination of the data, however, did not suggest there were significant differences. The two data sets were therefore combined and analysed together. The data were collected by telephone by a commercial public opinion polling organisation. A total of 582 useable responses were obtained and analysed within the study.

Respondents were asked how many times in a two week period the meats shown in Table I were cooked and whether they considered their households were heavy, medium, light or non users of those meats. The dependent variable used in the segmentation analysis was developed from these use data. A number of activity, interest and opinion questions, based on those used by Soutar and Clarke (1981) , were asked to evaluate respondents' general life styles and to understand their views on food related issues ( Appendix A ). Respondents were also asked about the importance attached to various meat benefits, such as visual, oral, convenience, health and entertainment characteristics ( Appendix B ). In addition, personal information was collected, including age, gender, education, employment, family and marital status and country of birth, as well as information on food and meat expenditure.

The data were analysed in a number of steps. Initially, descriptive statistics were computed to obtain a feel for the data and to understand the nature of consumers' meat consumption patterns. The meat consumption data were then cluster analysed to determine if there were meat-use-segments with distinctive consumption patterns. Segmentation was based on the respondents' perceived level of use of each type of meat because this is how they relate to messages in the market place.

In the present study the two-stage clustering procedure suggested by Helsen and Green (1991) and contained in Bretton- Clark's ProClus procedure was used ( Bretton-Clark 1993 ). Ward's hierarchical procedure initially determined the appropriate number of clusters after which a replicated K-means clustering procedure was used to obtain the final solution. As will be seen in the next section, eight clusters were found. Consequently discriminant analysis was used to investigate differences between the backgrounds of the various groups as the dependent variable (group membership) is nominally scaled ( Klecka 1980 ; Hair et al. 1992 ). The results of these various analyses are outlined in the next section.

RESULTS OBTAINED

Overall meat consumption is shown in Table I. As can be seen from the table, despite reductions in red meat consumption, beef remains the most commonly eaten of the six types measured, with chicken the second most commonly eaten meat. Mutton was least commonly consumed and, as already noted, mutton consumption has fallen even more drastically in recent years. Lamb consumption was also low, reflecting a change in Australian red meat consumption from lamb to beef in recent years. As can be seen from the percentage of non-users, very few people consume mutton and hogget but almost everybody in the sample consumed beef.

Table I: Level Meat Consumption by Type

1. Number of times cooked per fortnight

However, as was noted in the previous section, the present study was more concerned with patterns of consumption. Consequently, the meat use data were cluster analysed using Helsen and Green's (1991) two-stage procedure to determine if there were distinct segments. The procedure suggested that there were eight distinct clusters with the average level of meat use as shown in Table II.

Table II: Meat Consumption Clusters - Average Consumption Scores

Type of Meat

1 Per cent figure is percentage of sample in relevant cluster

The average use figures provide an indication of the nature of meat consumption in each group. Group 1 members are ‘chicken eaters' while group 2 members consume relatively large amounts of all the meats included and can be termed ‘heavy meat eaters'. Group 3 also tended to eat all of the meats but less often. Consequently, they can be termed ‘moderate meat eaters.' Group 4 respondents ate very little meat and were termed ‘light meat eaters.' Group 5 members are ‘beef eaters' while Group 6 respondents are ‘white meat eaters.' Group 7 members are ‘lamb eaters' and group 8 respondents are ‘mutton eaters.' Interestingly, pork was the only one of the six meats included that did not have a distinct user group. As can be seen in the table, the largest groups were the moderate and light meat eating groups, while the mutton and heavy meat eaters were the smallest groups, perhaps indicating relatively low meat use overall.

The next stage in the analysis was to investigate the background variables collected in the study to see if the various groups had distinctive profiles. Before that analysis was undertaken, however, some preliminary examination of the benefit items was necessary as the thirty four items included in the survey were interrelated and it was necessary to determine if there were meaningful benefit dimensions. Principal components analysis was used for this purpose and the stability of the principal components was determined by Everett and Entrekin's (1980) procedure. In this case, only the stability coefficients of the first four factors were found to exceed 0.80. Consequently, a four factor solution that explained fifty percent of the variance in the data was accepted. The factor loadings of the benefit statements after a varimax rotation are shown in Table III.

As can be seen from the table, the factor structure makes considerable sense. The first factor was related to the attributes of meat itself and was termed ‘meat characteristics.' The second factor was related to health issues questions and was termed ‘health issues.' The third factor was related to the way meat was perceived in social situations and was termed ‘entertainment issues.' The final factor was related to statements about cooking and storage and was termed ‘convenience.' A small number of statements had low communalities and factor loadings and were not included in the four factors but were retained as separate variables in the subsequent analysis (value for money, appeals to children, appeals to adults and appropriate portion sizes).

The mean scores on the summed scales developed from the principal components analysis, together with their alpha reliabilities ( Cronbach 1951 ), are shown in Table IV . As can be seen from the table, the four factors were reliable and can be used with confidence in subsequent analysis. The meat characteristics were the most important factor consumers took into account when purchasing, but health issues and whether the meat provides value for money were also very important. Entertainment issues and whether or not the meat appeals to children were the least important perceived benefits.

Table III: Factor Loadings - Meat Benefit Statements 1

Principal Component

1 Based on a 7 point Importance scale on which higher scores imply greater importance. Decimal point and loadings below 0.40 have been excluded to improve readability

Table IV: Meat Benefit Dimensions - Mean Scores and Reliabilities

The final analysis was to investigate if there were differences between the backgrounds of the meat use groups. Since group membership, the dependent variable, was nominally scaled, discriminant analysis was used ( Klecka 1980 , Hair et al 1992 ). The potential explanatory variables were the set of life style statements as well as a number of typically collected demographic and socio-economic indicators, including age, gender, country of birth, family status, income, education and occupation. The analysis revealed four significant functions that, using the I squared statistic suggested by Peterson and Mahajan (1976) , explained thirty four percent of the variance between the groups. The groups were generally significantly different from each other, although ‘mutton eaters' did not appear to have any distinguishing background characteristics. The structural correlations that show the relationship between the obtained discriminant functions and the explanatory variables ( Johnson 1977 ) are presented in: 

Table V Background Variables - Structural Correlations

The first function seemed to differentiate between ‘larger families' and ‘single people', with the latter being more likely to undertake regular exercise. The second function differentiated ‘traditional females', while the third identified creative ‘home oriented' respondents. The fourth function identified ‘students' in the sample. The position of the eight groups on each function can be determined by examining the group centroids' scores on each dimension. In the present case, the relative positions (High, Moderate-High, Average, Moderate-Low and Low) are shown in Table VI.

Table VI: Meat Use Groups - Group Centroids Relative Positions

The information in Table VI suggests that chicken eaters were likely to be ‘students' or ‘traditional females' but unlikely to be in ‘larger families'. Heavy meat eaters were likely to come from traditional and larger families who enjoy working and being creative around the home. Moderate meat eaters also were likely to come from larger families but were average on the other dimensions. Light meat eaters were likely to be single males, perhaps because they were unwilling to take the time needed to prepare many meat dishes and because they were likely to eat out more often. Beef eaters were also likely to come from larger families but did not enjoy being creative at home and so were less willing to cook other types of meat that might take more effort. White meat eaters were more likely to be students and less likely to come from larger families. Lamb eaters were more likely to be traditional females, while mutton eaters enjoyed being creative at home.

CONCLUSIONS

Overall, when shopping for meat, consumers placed the most importance on meat characteristic factors such as flavour, tenderness, appetising, tastiness, juiciness, quality, freshness, colour, variety and aroma when cooked. Also of importance were value for money and health issues, such as fat, cholesterol, nutritional value, calories, fibre, waste and artificial additives. Convenience, appeal to adults and appropriate portion sizes were of lesser importance. Entertainment issues and whether meat appeals to children were the least important factors.

The market was segmented into eight distinct consumer groups. The largest groups were light meat eaters (19 per cent) and moderate meat eaters (18 per cent), followed by beef eaters (16 per cent). The smallest groups were mutton eaters (4 per cent) and heavier meat eaters (5 per cent). Light meat eaters were likely to be single males who undertook regular exercise. If they do not prepare many meat meals at home, there may be an opportunity for meat marketers to provide meat in more convenient prepacked forms such as kebabs, mini roasts, marinated cubes/strips and stir fries. Provision of cooking instructions would also be important. Moderate meat eaters were likely to come from larger families. Marketing to maintain their consumption patterns could use families as the theme.

Beef eaters were also likely to come from larger families but did not enjoy being creative at home and were less willing to try new things when cooking. They were concerned with meat characteristics such as flavour, tenderness, appetising, tastiness, juiciness, quality, freshness, colour, variety and aroma when cooking. They were less concerned with health aspects of meat, perhaps because they sought to reduce cognitive dissonance. Marketing messages to this group could focus on meat characteristics and larger families. To market new meat cuts, convenience and ease of use characteristics would need to be emphasised. Quality labelling would assist these people in their selection, making meat more attractive to this group.

The white meat eaters (chicken and fish) made up 14 per cent of the sample and attached the greatest importance to health issues. White meat eaters were more likely to be students and less likely to come from larger families. Chicken eaters (12 per cent) were likely to be students or traditional females but unlikely to be in larger families. Marketing messages focusing on these aspects would be appropriate. Meat could be packaged in small portions and recipes added that are suitable for small groups of people.

Heavy meat eaters were likely to come from traditional and larger families who enjoyed working and being creative around the home. They attached greater importance to all benefits sought in purchasing meat, perhaps because they were the most involved consumer segment. As the number of larger traditional families continues to decline, this group may get smaller over time and be of less interest to marketers.

Increasing education about the effects of diet on health may explain why red meat per capita consumption has been falling. It may also indicate an opportunity to red meat marketers to target health aspects of their product such as high iron levels and healthier leaner cuts. However, depending on the segment being targeted, the type of marketing message must differ.

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Appendix A - Lifestyle Questions

Could you tell me on a scale from 1 to 7 how much you agree with each of the following statements with 1 meaning ‘Strongly Disagree' and 7 meaning ‘Strongly Agree'?

Appendix B - Meat Benefits Questions

Could you tell me on a scale of 1 to 7 how important the following characteristics are when purchasing meat? (1 represents ‘Not At All Important' and 7 ‘Extremely Important')