The price premium of an environmentally friendly product

Kapelianis, Dimitri; Strachan, Sandra Article The price premium of an environmentally friendly product South African Journal of Business Management Provided in Cooperation with: University of Stellenbosch Business School (USB), Bellville, South Africa Suggested Citation: Kapelianis, Dimitri; Strachan, Sandra (1996) : The price premium of an environmentally friendly product, South African Journal of Business Management, ISSN 2078-5976, African Online Scientific Information Systems (AOSIS), Cape Town, Vol. 27, Iss. 4, pp. 89-95, https://doi.org/10.4102/sajbm.v27i4.813 This Version is available at: https://hdl.handle.net/10419/218161 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ S.Afr.J.Bus.Manage.1996 27(4) 89 The price premium of an environmentally friendly product Dimitri Kapelianis & Sandra Strachan Department of Business Economics, School of Economic and Business Studies, University of the Witwatersrand, Private Bag 3, P.O. Wits, 2050 Republic of South Africa Received August 1996 r- The relationship between marketing and the environment has recently received considerable attention. Much of the literature in this_ fi~ld deals wit~ the premia that consumers are willing to pay for environmentally friendly products as well as th_e charactenst1cs ~hat ~escnbe these consumers. The methods used for estimating these premia are, however, methodolog1cally flawed. This article presents a model for calculating premia on the basis of part-worth utilities derived from conjoint analysis. The authors find that racial and educational differences exist in willingness to pay a premium. These differences persist even when variances in other variables (for example, income) are controlled. _ __J Die verhouding tussen bemarking en die omgewing geniet in die laaste tyd baie aandag. 'n Groot deel van die literatuur hieroor ondersoek die premie wat verbruikers bereid sou wees om vir omgewingsvriendelike produkte te betaal en beskryf die eienskappe van hierdie verbruikers. Die metodes wat gebruik word om hierdie premies te bereken, is egter nie korrek nie. Hierdie artikel beskryf 'n prosedure wat gedeeltelike nutswaardes uit saamgevoegde-analise gebruik om hierdie premies te bereken. Daar word bevind dat persone van verskillende rasse en opvoedingsvlakke bereid is om verskillende premies te betaal. Hierdie verskille bestaan ook wanneer daar vir ander veranderlikes (byvoorbeeld inkomste) gekontroleer word. Introduction The interface between marketing and the environment has become one of the most discussed issues in the popular marketing press. There remains, however, a dearth of solid academic research into the topic, especially in South Africa. As a result, it is hardly surprising that this discussion is characterized by unsubstantiated claims and the often shallow reporting of commercial research results. Three central themes can be found in this literature: the premium that consumers are willing to pay for an environmentally friendly product; the characteristics that describe these consumers; and the proportion of the market that these consumers represent. We review the existing literature on this topic examining such issues as the concept of green marketing, the nature of externalities and price premia, market segmentation and market size. In the empirical section of the article, we discuss our research methodology; deal with issues of data analysis -in particular, conjoint analysis and the method used for calculating the premium of an environmentally friendly product; and we present and discuss our research results. The final section presents some suggestions for further research and our concluding comments. Literature review Marketing concept, societal marketing and green marketing: a brief overview According to Bell & Emory ( 1971: 38), the marketing concept is an attempt to operationalize a basic philosophy of marketing. The traditional marketing concept has at its core three essential elements: firstly, the belief that the firm should adopt a customer-driven orientation; secondly, this effort should be integrated across the entire firm; and finally, that profit maximization should be pursued as the firm's end goal. McDaniel & Rylander point out, however, that 'questions were raised regarding whether the marketing concept leads to misplaced emphasis on customer "want" satisfaction while ignoring the long-run best interests of society and the environment' (1993: 4). It was as a result of this line of questioning that Kotler ( 1976: 16-18) delineated his now famous societal marketing concept -the addition of societal welfare as a fourth tenet to the traditional marketing concept. Green marketing flows naturally from the philosophy of societal marketing. McDaniel & Rylander (1993: 4) have defined it as marketers' attempts to develop strategies targeting the environmental consumer. It is this and more. Vandermerwe & Oliff ( 1990: 10-11) indicate that 'green' has become a shorthand term for a number of issues dealing with, amongst others, resource depletion, waste emission and accumulation, and harmful products. Concept of externalities and price premia for green products In the language of economists, an externality (which can be either positive or negative) occurs when a discrepancy exists between social and private benefits or social and private costs (Hirshleifer, 1988: 472). Broadly speaking, negative externalities arise when the actions of some people detrimentally affect others -and these others are not consulted to give their consent nor are they compensated should they suffer any loss. Pollution is the most widely cited example of such an externality. It is at this point that economics and green marketing are connected -the production and consumption of products that are harmful to the environment affects not only the parties to the contract but also third parties. Traditionally, three public policy approaches to the problem of externalities have been cited (Hirshleifer, 1988: 474-475). These are tax-subsidy adjustments, unitization and property right reassignments. Firms can be taxed at a level equal to the monetary value of the negative externality. Ideally, this money would then be passed on to injured parties to compensate them for any loss incurred. Alternatively, the externality can be internalized in the sense that the producer of the externality is also its consumer. Finally, Coase's famous theorem ( 1960) states that externalities will not occur provided that property rights are adequately defined, enforced and exchangeable and that there are no transaction costs. 90 A further remedy for the extemality problem lies outside the realm of public policy. A consumer boycott can lead to an environmentally harmful product being withdrawn and replaced by a green product -often at a higher price. In so doing, the externality is internalized and the cost of . t~e transaction is borne only by the parties to the contract. This 1s exactly what occurred in the Netherlands with a boycott of aerosols containing chlorotlurocarbons (CFCs) which deplete the ozone layer (Simon, 1992: 269). This last remedy links the concept of negative externalities to that of price premia for green products. As Simon points out, '(t)he ultimate measure of environmental commitment is clearly the consumer's willingness to pay ... a green premium on an eco-safe product' (1992: 276). A number of authors have reported on these premia, including Cavanaugh (1993), Davis (1991), Prokop (1993), Thomas ( 1989), Vandermerwe & Oliff ( 1990) and Wasik ( 1992). The reported premia range from a low of about 5% (Davis, 1991: 16) to a high of between 15 and 50% (Vandermerwe & Oliff, 1990: 11). Reported premia are probably inaccurate as a result of the research methodology adopted in previous studies. The existence and/or amount of a premium is normally calculated on the basis of one of three questions posed to consumers: I. Are you willing to pay more for a green product? 2. Are you willing to pay x percent more for a green product? 3. How much more are you willing to pay for a green product? Merely asking a consumer the price premium they are willing to pay is insufficient. This question in no way manages to capture the decision process and trade-offs engaged in by the consumer when choosing between a green and non-green product. Furthermore, this technique increases the respondent's tendency to engage in socially desirable behaviour. While no one can be certain of the extent of premium overstatement, Celente (quoted in Wasik, 1992: 16) goes so far as to state that 'marketers who believe ... consumers are willing to pay an environmental premium will suffer financially'. Market segmentation It seems fairly obvious that consumer willingness to pay a premium for a green product may vary by segment. The consumer characteristics that influence environmental concern is one of the consistent themes in the literature. Table I contains a summary list of these characteristics. The hypothesized relationship between each of these variables and social responsibility/green commitment is briefly discussed below. Age Anderson & Cunningham (1972) find an inverse relationship ~t~een age and social consciousness but not at a statistically significant level. In a later replication and extension, Kinnear, Taylor & Ahmed (1974) deliver the same finding. Children Thomas (I 989: 116) states that the presence of children in the household increases the consumer's willingness to take action S.Afr.J.Bus.Manage.199 6 27141 Table 1 List of variables impacting upon social responsibility or green commitment Variable Age Children Education Employment Gender Income Study Anderson & Cunningham, 1972 Kinnear. Taylor & Ahmed, 1974 wa~ik. 1992 Kinnear, Taylor & Ahmed, 1974 Murphy, Kangun & Locander. 1978 Thoma~. 1989 Kinnear, Taylor & Ahmed, 1974 Murphy, Kangun & Locander. 1978 Roper, 1990 Simmons, 1992 Wa~ik, 1992 Anderson & Cunningham, 1972 Kinnear, Taylor & Ahmed, 1974 Murphy, Kangun & Locander, 1978 Murphy, Kangun & Locander, 1978 Thoma~. 1989 Wasik, 1992 Adams, 1990 Kinnear. Taylor & Ahmed, 1974 Murphy. Kangun & Locander, 1978 Roper, 1990 Simmons. 1992 Wa~ik, 1992 Race Murphy, Kangun & Locander, 1978 Socio and psycho- Anderson & Cunningham, 1972 graphic variables Kinnear, Taylor & Ahmed, 1974 Webster, 1975 in terms of buying green products. Both Wasik ( 1992: 16) and Oliver Murphy (quoted in Kreitzman, 1989: 44) concur with this statement. Kinnear et al. ( 1974), however, fail to find any empirical support for this relationship. Education In a summary of previous academic research, Murphy. Kangun & Locander (I 978: 61) report a positive relationship be· tween level of education and environmental commitment. Simon (1992: 276) states that two large scale commercial studies (Roper in 1990 and Simmons in 1991) both confirm this result. Kinnear et al. ( 1974), however. find no support for this relationship. Employment Anderson & Cunningham (1972) find that occupation varies directly with social responsibility scores. Kinnear et al. (1974) does not find any relationship between nature of employment and ecological concern. Gender Thomas (l 989: 116) and Wasik ( 1992: 16) both state that women are generally more environmentally conscious than men. S.Afr.J.Bus.Manage.1996 27(4) They fail, however, to provide any empirical evidence for their statements. Kreitzman ( 1989: 44) quotes a study (by the British research company Diagnostics) that provides some support for this relationship. Income Adams ( 1990: 82) and Wasik (l 992: 16) state that there is a positive relationship between income and environmental concern. Two large scale commercial studies (Roper in 1990 and Simmons in 1991) also find the same linkage. These results are contradicted by Anderson & Cunningham (1972) who find no such relationship, whilst Kinnear et al. (1974) establish a modest positive linkage. Race Murphy et al. (1978) remains the only study to have examined the relationship between race and socially conscious consumption. The major conclusion they draw is that 'white respondents do differ from their black counterparts in environmental concerns' (Murphy, 1978: 65). Sociographic and psychographic variables Anderson & Cunningham (1972); Kinnear et al. (1974); and Webster ( 1975) all find that these variables are generally better predictors of social consciousness than demographic variables. Market size Considerable work has been done in estimating the size of green market segments throughout the world with widely varying results. This is probably due to divergent definitions of green consumerism and the fact that the countries in which Table 2 Estimates of green markets 91 research has been conducted are very different. Table 2 lists the studies that have attempted to estimate green market size, the countries in which these studies were conducted, their findings, and their definition of green consumerism. Empirical research Research methodology Our research methodology draws upon and extends the work of Herberger & Buchanan ( 1971) by addressing the relationship between environmental information and product choice. We used deodorant aerosol cans as our physical stimuli because the debate surrounding the effects of CFCs upon the ozone layer has been widely publicized (see for example, McDaniel, 1993; Mcintosh, 1991; and Simon, 1992). In addition, we assessed respondent reaction when environmentally friendly products carried higher prices. We interviewed 160 respondents in mall intercepts in the Witwatersrand region using a quota sampling technique. A two-factor experimental design was employed: environmental friendliness of products at two levels (deodorant aerosol can displays an ozone friendly label versus deodorant aerosol can does not display an ozone friendly label); and price at four levels (a realistic base price, 5% premium, 10% premium and 15% premium). Thus, respondents were asked to rank in order of preference a total of eight cans of deodorant. Upon completion of the rank ordering, respondents completed a questionnaire indicating (in order): a 16 item 'desire for social recognition' scale; occupational status; level of education; age category; income category; and presence of young children in household. The interviewer also noted the respondent's gender and race. The desire for social recognition measures were sourced from the Personality Research Study Country Size(%) Definition Bendixen, Sandler & Seligman, South Africa 33 Give preference to green products over other 1994 products whenever there is a choice Cavanaugh, 1993 USA 40-70 Willing 10 pay premia of 6-10% for environmentally friendly products Corrado, 1989 Britain 42 Consciously chosen one product over another for environmental reasons Gallup (quoted by Thomas. 1989) USA 50 Pay at least I 0% more for ozone-friendly aerosols Gallup (quoted by Simon, 1992) Japan 40 Avoided environmentally harmful products USA 57 Denmark 65 Holland 68 UK 75 Canada 77 West Germany 81 Gallup (quoted by Wa~ik, 1992) USA 90 Willing to make a special effort to buy product~ from companies trying 10 protect the environment Market Research Africa, 1990 South Africa 53.4 Prepared to pay more for products which are environmenl friendlier and they display a label Markel Research Africa, 1993 South Africa 50.6 Prepared to pay more for products which display an environment friendly label Prokop, 1993 USA 78 Willing to pay more for product~ that are environmentally benign 92 Form (Form E) developed by Jackson in 1974. The defining traits of a person with a high desire for social recognition include approval seeking, making a good impression, seeking respectability and recognition, being concerned about social propriety and behaving appropriately (Jackson, 1974). Eight of the 16 social recognition items were reverse scaled to reduce acquiescence bias. The demographic measures were sourced from South Africa's All Media and Products Survey (AMPS) which has demonstrated its validity and reliability in years of fieldwork. Analysis conducted Conjoint analysis was conducted on each individual's rank ordering to determine the utility (or disutility) that they would receive from consuming a green product. Louviere defines this technique as 'a generic term (used) ... to refer to a number of paradigms ... that are concerned with the quantitative description of consumer preferences or value tradeoffs' (1994: 223). The theoretical underpinnings of the technique are based upon the work of Lancaster (1966) who demonstrated that the utility a consumer receives from a product can be decomposed into the utility received from each of the attributes that combine to constitute the product. These component utilities are known as part-worth utilities. The overall utility of an alternative can then be calculated using the basic conjoint analysis model (Malhotra, 1993: 689): m Ir.; (X) L L aijxii ()) i = lj = I where: U(X) = overall utility of an alternative a.i = the part-worth contribution or utility associated with the jth level (j, j = I, 2, ... k;) of the ith attribute k; = m = X;i = = (i, i= I, 2, ... m) number of levels of attribute i number of attributes I if the jth level of the ith attribute is present O otherwise This equation is subject to the constraint that: A:, Ia;j= o j=I (2) The part-worth utility associated with the product's environmental friendliness (displays an ozone friendly label versus ~oes not display an ozone friendly label) was aggregated with the part-worth utility associated with the product's price (realistic base price, 5% increase, 10% increase, 15% increase). This procedure produced eight total utilities for each of the 160 respondents: (green product at 0%, 5%, 10% and 15% premium; and non-green product at 0%, 5%, 10% and 15% premium). Two regressions were run for each respondent: one on the total utilities of the green rroduct, and one on the total utilities of the non-green product. Thus, a total of 320 regressions were run. For each respondent, we calculated the price of the S.Afr J .Bus.Manage.1996 27141 green alternative at a total utility level of zero (using the a and p values from the regression output) as well as the price of non-green alternative at a total utility level of zero (again using the a and P values from the regression output). From these two prices, we then calculated the premium that a consumer was willing to pay for the green alternative. Since the analysis conducted was relatively complex, it was necessary to run a validation check. The authors therefore developed an algorithm to calculate the average premium. This algorithm and its derivation are contained in the appendix. The regression technique produced an average premium of 5.9%, whilst the algorithm produced an average premium of 5.5%. A t-test revealed that these average premia were not significantly different at an a-level of 0.05 (t = 0.57; p = 0.56). Despite the fact that both techniques produced similar results, it was found that the algorithm technique was not as robust as the regression technique. Therefore, all further results are based upon the latter method. Results Seventeen respondents were removed from the sample because an infinite positive premium was calculated for them - they consistently chose green products over non-green products but their rankings in terms of price appeared to be totally random. Similarly, three respondents were removed from the sample because an infinite negative premium was calculated for them. The removal of respondents reduced the total sample size to 140. Table 3 presents a frequency distribution of premia calculated for respondents. As can be seen from Table 3, a substantial proportion of respondents -about 18.13% of our total sample -priced the green alternatives at a discount to the non-green alternatives. This finding is unique and makes it difficult to directly compare our results with those of prior research. Therefore, the outputs of all further analyses are presented for both the full sample (140 respondents) and a reduced sample (114 respondents) with discount seekers removed. Table 4 presents the summary statistics for the premium distributions excluding infinite premia. Table 3 Premium frequency distributions Premium n % Negative infinite premium 3 1.88 -30S p<-20 0.63 -20Sp<-10 9 5.63 -IOSp<O 16 10 p=O 32 20 OSp< 10 35 21.88 10Sp<20 43 26.88 20Sp<30 2 1.25 30Sp<40 2 1.25 Positive infinite premium 17 10.63 Total 160 100 S.Afr.J.Bus.Manage.1996 27(4) Table 4 Summary statistics for premium frequency distribution Full Reduced Measure sample sample n 140 114 Mean 5.9 9.39 Median 2.36 3.77 Standard deviation 11.72 9.47 Minimum value -22.14 0 Maximum value 34.73 34.73 Range 56.87 34.73 To determine the relationship between consumer characteristics and price premia, respondents were classified into two mutually exclusive and exhaustive groups for each variable. Table 5 presents the premium summary statistics for these variable subgroups. We used t-tests to determine whether or not the premium means for the groups of each variable in Table 5 were different at a statistically significant level. Table 6 presents the results of the t-tests. For the full sample, the results of the t-tests indicate that the only variable with a significant difference (at an a-level of 0.05) in mean premium was race. For the reduced sample, the results indicate that the only variables with significant differences in mean premium were race (at an a-level of0.01) and education (at an a-level of 0.05). These results may be due to variances in an underlying variable such as income or employment status. Therefore, two-way ANOVAs were run to test this hypothesis. However, no significant interactions were found. 93 Discussion of results While many of our findings are consistent with previous research, we also obtained some results that were totally unexpected. Obviously, the most surprising result is the existence of a substantial proportion of respondents. about 18. 13% of our total sample, who seek a discount when purchasing green products. This result has not been found in any prior research. The only explanation we can offer is that these respondents probably perceive green products as being less effective than their non-green counterparts. We also found that 20% of our total sample did not respond to the difference between green and non-green products. These respondents were not willing to pay a premium for either of the options. These two results confirm Kinnear etal.'s (1974: 23) conclusion that there may well exist 'a substantial segment that exhibits little or no concern about the pollution aspects of products'. Approximately 61.88% of our sample were willing to pay a premium for green products. This result is in the range indicated by previous research. Our mean premium of 5.5% (for the full sample) is at the bottom of the range of premia found in previous studies. It is necessary to bear in mind, however, that this figure is skewed downwards by the inclusion of respondents with negative premia. On the other hand, our mean premium of9.39% (for the reduced sample) is consistent with the results of previous studies. Prior research has also not mentioned consumers who state they are willing to pay a positive infinite premium for green products. Whilst this result may be an artifact of our research methodology, it is nevertheless intuitively pleasing -although these consumers may not have the money to purchase more expensive green products, we believe they cannot be persuaded to buy non-green products at any price. When faced with the choice of a relatively cheap non-green product and a green product at a substantial premium they would probably choose not to purchase either of the alternatives. The same Table 5 Premium summary statistics for subgroups Variable Category Full sample Reduced sample n mean s.d. n mean s.d. Age < 35 years 80 7.4 11.78 68 10.32 9.80 ~ 35 years 59 3.6 11.28 45 7.70 8.72 Children Children in household 67 5.57 12.91 53 10.02 9.93 No children in household 71 6.08 I0.54 59 8.76 9.01 Education At most some high school 63 4.65 11.42 54 7.36 9.46 At least high school completed 75 6.79 11.95 58 11.17 9.15 Employment Employed full time 88 7.08 10.46 74 9.55 9.14 Not employed full time 49 3.65 13.61 37 9.16 10.17 Gender Male 73 7.71 10.57 62 10.15 9.23 Female 67 3.94 12.65 52 8.48 9.76 Income < R 1500 per month 72 6.38 11.37 64 8.51 9.81 ~ R 1500 per month 62 5.57 11.96 46 10.50 8.84 Race Black 74 4.07 I0.42 63 6.52 8.69 White 66 7.96 12.8 51 12.93 9.26 Social index <0.5 41 6.94 12.82 33 11.35 9.42 ~ 0.5 99 5.48 11.27 81 8.58 9.43 94 Table 6 Results of t-tests Full sample Reduced sample Variable df t value p value df t value p value Age 137 1.91 0.05 Ill 1.45 0.15 Children 136 -0.25 0.8 110 0.71 0.48 Education 136 -1.06 0.28 110 -2.17 0.03* Employment 135 1.64 0.1 109 0.21 0.84 Gender 138 1.91 0.05 112 0.94 0.35 Income 132 0.40 0.68 108 -1.09 0.28 Race 138 -1.98 0.04* 112 -3.81 o.oo•• Social index 138 0.66 0.5 112 1.42 0.16 *Significant at an a-level of0.05 **Significant at an a-level ofO.O I. reasoning probably holds true for respondents for whom a negative infinite premium was calculated. For the full sample, the only variable with a significant difference (at an a-level of 0.05) in mean premium is race. Whites are willing to pay a mean premium of 7.96% whilst Blacks are willing to pay a mean premium of only 4.07%. For the reduced sample, race is again significant, this time at an a-level of 0.01. Once more, Whites are willing to pay a greater premium than Blacks -12.93% compared to 6.52%. These results are consistent with those of Murphy et al. (1978) who found that White consumers are more environmentally conscious than their Black counterparts. South Africa's history is one of racial inequality and it is possible that the difference in mean premium may result from variances in an underlying variable such as income or employment status. The fact that the two-way ANOVAs show no significant interactions refutes this explanation. Corder ( 1991) provides a possible answer. Under Apartheid, Blacks were forced to live in generally squalid townships. As a result, environmental concern in this group is centred around the more immediate issue of litter as opposed to the more distant concept of ozone depletion. Corder (1991: 8) states that 69% of Blacks are aware of litter as a global issue (in comparison to 91 % of Whites), but only 8% of Blacks are aware of the depletion of ozone as a global issue (in comparison to 83% of Whites). For the reduced sample, mean differences in premium according to educational level are also significantly different at an a-level of 0.05. Respondents with at most some high school education are willing to pay an average premium of 7.36%. This premium increases to 11.17% amongst respondents who have at least completed high school. This result suggests that education plays a vital role in increasing levels of environmental awareness. Conclusion The major ~oncl_usion. that can be drawn from this study is[ that ~reat d1spanty exists in consumer willingness to pay a\ premium for green products. Some consumers demand a dis-\ count f~r th~se products, others state that they are willing to\ pay an mfimte premium, and some do not respond to the dif- ~ere~ce _between green and non-green products. The major i 1mphcat1on of these findings is that the onus rests upon the 1. S.Afr.J .Bus.Manage.1996 27( 4) marketer to practice segmentation and target the green con- ! sumer. In South Africa at leas~, this consumer is probably i White _and well educated but this may change rapidly in the! _(uture.' Certainly, further cross-cultural replication is needed before a more definitive conclusion can be drawn. It is hoped, however, that further research in this field will use methodologies that approximate more closely the consumer's decision and trade-off processes when choosing between green and non-green products. Acknowledgement The authors wish to express their gratitude to: Sigma Assessment Systems for permission to use the social recognition test scales; colleagues who provided valuable input, in particular, C. Corder, S. Davidson, J. de Villiers, N. Higgs and M. Polonsky; and S. da Silva and S. Meyer for assistance with the data analysis. References Adams, R. 1990. 'The greening of consumerism', Accountancy, pp. 81-82. Anderson, W.T. & Cunningham, W.H. 1972. 'The socially conscious consumer', Journal of Marketing, 36(3): 23-31. Bell, M.L. & Emory, C.W. 1971. 'The faltering marketing concept', Journal of Marketing, 35(4): 37-42. Bendixen, M.T., Sandler, M. & Seligman, D .. 1994. 'Consumer perceptions of environmentally friendly products', South African Journal of Business Management, 25(2): 59-64. Cavanaugh, H.A. 1993. 'Power marketing', Electrical World, pp. • 19-20. Coase, R.H. 1960. 'The problem of social cost', Journal of Law and Economics, 3: 1-44. Corder, C.K. 1991. 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Appendix The algorithm used to calculate the premia is given by: where: p = 3i>i = 3g = 3-g = m, = m., = (3) premium of a green product over a non-green product part-worth utility of price at the }th level part-worth utility associated with the product being green part-worth utility associated with the product being non-green gradient of the total utility function for a green product gradient of the total utility function for a non-green product P&1 = price of a green product at the }th level Pn&1 = price of a non-green product at the }th level When total utility equals zero, the premium of a green product over a non-green product is given by: (4) where: Pg = price of a green product when total utility equals zero Png = price of a non-green product when total utility equals zero This equation simplifies to: p = [p 11 -1] *100 Pn11 It is then necessary to solve for p, and p.,. 95 (5) The total utility for a green product can be represented by: (6) where: TU,r= total utility of a green product c, = total utility of a green product when price equals zero. For the sake of simplicity, let us solve for p, when total utility equals zero. This is simply: (7) Similarly, the price of a non-green product when total utility equals zero is given by: (8) where: c., = total utility of a non-green product when price equals zero Thus substituting (7) and (8) into (5), and with some re-ar- ranging, we get: ' c!lmni: ] p = ---1 c m '- nx ,: • 100 (9) We still need to solve for c, and c.,. Re-arranging (6) we get: ( 10) But, from (I) we also know that the total utility of a green product at the jth price level can be given by: (11) where: TU,r, = total utility of a green product at the jth price level Thus by specifying j and substituting ( 11) into ( I 0) we get: (12) And similarly: (13) Finally, substituting (12) and (13) into (9) we get: (14)