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4424 J. Med. Plants Res. Table 1. Definition of variables. Variable name Variable definition Consumers' individual characteristic Health functions of the products Consumers' behavior Marketing factors A1 Male = 0, Female = 1 A2 Less than 29 years old = 1, 30-39 years old = 2, 40-49 years old = 3, 50-59 years old = 4, Over 60 years old = 5 A3 High school graduates and below = 1, University graduates = 2, Post graduates = 3 A4 Less than 4000 RMB = 1, 4001-7000 RMB = 2, 7001-10000 RMB = 3, 10001-13000 RMB = 4, More than 13001 RMB = 5 A5 Unmarried = 0, Married = 1 A6 Civil servant and public institution personnel = 1, Enterprise employee = 2, Service industries personnel = 3, Self employed = 4, Freelance = 5, Student =6, Others = 7 B1 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 B2 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 C1 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 C2 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 C3 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 C4 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 C5 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 D1 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 D2 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 D3 Very unimportant = 1, Unimportant = 2, No opinion = 3, Important = 4, Very important = 5 Variables of the model are evaluated as: A1 gender, A2 age, A3 education, A4 household monthly income, A5 marital status, A6 profession, B1 consumer attitudes of health functions, B2 consumer attitudes of active ingredient content, C1 taste of the products, C2 brand image, C3 comparative purchasing behavior, C4 gifts, C5 package, D1 price, D2 place, D3 media advertisement. development of industry is to establish a technological alliance, and speed up the development of common techniques and application of integrated innovations, to strengthen self-discipline and monitoring of production, and to expand sales market. Chen et al. (2001) considered that the potential market demand for C. sativus is huge, but we should pay attention to breeding, tissue culture and cultivation, guiding the consumers properly, and implementing the C. sativus industrialization project. With the product demand for C. sativus increasing rapidly, it is important for enterprises to establish the development strategy and provide policy advices based on market demand. The objective of this study is twofold: first, to estimate willingness to pay for C. sativus, and secondly, to examine heterogeneity in consumer valuation of functionality in C. sativus and to determine the effect of individual characteristics on consumers' choice decisions. This study contributes to the improvement and broadening of current knowledge about C. sativus demand in several ways. For this purpose, we analysed the variables of the consumers' individual characteristic, health functions of the products, consumers' behaviour and marketing factors. In addition, the results will also be of interest to government agencies and manufacturers who could use the information derived from this study in determining marketing strategies and setting up new policy tools. METHODOLOGY The data used in this paper was obtained from a survey on consumers' willingness to pay for C. sativus in June and July 2011. The survey was conducted face-to-face and through the internet. Considering the differences in economic development level and density of population among different cities and different districts within the cities, we used stratified sampling and random sampling to draw our subjects. The specific sites for investigation were chosen based on the administrative function zoning in Beijing, Shanghai, Hangzhou, Ningbo, Wenzhou, Shenyang, Guangzhou, Xi'an, Wuhan and Nanjing. Logistic model is used for analysis of consumers' willingness to pay for C. sativus. Logistic model describes the behaviour of consumers with a common consumption objective when they are faced with a variety of goods. However, the goods and choices must be highly differentiated by their individual attributes. Assuming that consumers' willingness to pay for C. sativus is dependent variable y, we divided influencing factors into four dimensions (Table 1):
consumers' individual characteristic (6 variables), health functions of the products (2 variables), consumers' behavior (5 variables) and marketing factors (3 variables). The model assumes that y obeys the binomial distribution, the probability y = 1 is equal to P, consumers' definite answers are represented by 1, negative answers are represented by 0. The probability distribution functions of y is expressed as follows: f y ( y) = p ( 1− p) ( 1−y) , y = 0, 1 The probability of consumers' willingness to pay for C. sativus can be calculated according to the following equation: ⎛ m ⎞ ⎡ ⎛ m ⎞⎤ p( y) = f ⎜α β jχ ⎟ ij ⎢ ⎜ α β jχ ⎟ ⎜ + ∑ ⎟ = 1/ 1+ exp ⎜ − + ∑ ij ⎟⎥ + μi ⎝ j= 1 ⎠ ⎢⎣ ⎝ j= 1 ⎠⎥⎦ In this equation, P(y) is the probability of consumers' willingness to pay for C. sativus, χij is independent variables of No.j influencing factors, βj is the regression coefficients of No.j influencing factors, m is the number of the influencing factors, α is the regression intercept, µi is the random disturbance term of No.i observed objects. All the data analyses were carried out using SPSS17.0 software. RESULTS A total of 467 respondents from the survey returned the completed questionnaires (response rate 46.7%). 138 of the respondents would pay for C. sativus, which accounted for 29.6%. Statistical description of the survey sample is presented in Table 2. In consumers' individual characteristic, gender, age, education, family monthly income, marital status and profession were investigated. The survey results demonstrate that the male respondents constitute 51.8% of the respondents while female respondents constitute 48.2% of it. 53.1% of the respondents are high school graduates and below, 33.6% of the respondents are university graduates and 13.3% of the respondents are post graduates. Average monthly income of sampled households which is less than 4000 RMB accounts for 30.6%, 4001 to 7000 RMB accounts for 19.9%, 7001 to 10000 RMB accounts for 16.7%, 10001 to 13000 RMB accounts for 13.9%, and more than13001 RMB accounts for 18.8%. In health functions of the products, consumer attitudes of health functions and active ingredient content are surveyed. Survey results revealed that 62.9% of the respondents consider health functions important or very important and 68.1% of it believes active ingredient content is important or very important. In consumers' behaviour, taste of the products, brand image, comparative purchasing behavior, gifts and package are surveyed. Survey results indicate that 82.0% of the respondents consider taste of the products important or very important and 73.0% of it believes brand image is important or very important. In marketing factors, price, place and media advertisement are investigated. The survey results demonstrate that 37.0% of the respondents consider price as unimportant or fairly unimportant while 31.9% of it believe price is important or (1) (2) Hong et al. 4425 very important. KMO is a measure of sampling adequacy that indicates the proportion of common variance that might be caused by underlying factors. High KMO values (close to 1) generally indicate that factor analysis may be useful, which is the case in this study: KMO = 0.727, if the KMO test value is less than 0.5, factor analysis will not be useful. Bartlett’s test of sphericity indicates whether the correlation matrix is an identity matrix, indicating that variables are unrelated. A significance level less than 0.05 indicates that there are significant relationships among variables, which is the case in this study: χ2 =5206.487 (P=0.000). The Cronbach's alpha coefficient represents the degree of internal consistency of items within a test, and values can theoretically range from 0 (zero internal consistency) to 1 (perfect internal consistency). In this study, the value of Cronbach's alpha is 0.108, when Cronbach's alpha value is up to 0.542 after deleting A6 and D3. So, A6 and D3 were deleted; the remaining 14 items were selected to evaluate consumers' willingness to pay for C. sativus. In order to get 467 consumers' cross-sectional data, we used the logistic regression analysis. In the course of data processing, taking all the variables into it, obtained test results are shown in Table 3. Nagelkerke R² and Cox and Snell R² statistics attempt to quantify the amount of variance explained by the logistic regression model. The probability of the observed results, given the estimated parameters, is known as the “likelihood”. Since likelihood is a small number of less than one, it is customary to use “-2LL” (−2 log likelihood) as a measure of the model's goodness of fit. A good model is one in which there are high values of Nagelkerke R² and Cox and Snell R² statistics (the closer the values are to the unit, the higher is the variability of the endogenous variables ability to be explained) as well as high likelihood of the observed results (that is, with a low value of -2LL). In this study, Nagelkerke R² is 0.373, Cox and Snell R² is 0.262 and - 2LL is 424.821. Model can better fit the overall sample data; independent variables have a good explanation for dependent variable. DISCUSSION Consumer preferences for certain food attributes are important for government agencies and manufacturers (Gao and Schroeder, 2009). In the past, different preference elicitation methods have been used by economists and market researchers to obtain the willingness to pay for certain product attributes. In this study, consumers' gender has a significant positive impact on willingness to pay for C. sativus. The survey results illustrate that female consumers are more willing to pay for C. sativus. They accept more information about C. sativus and are prone to purchase impulsively. Moreover, they are more sensitive to the advertisement, store promotions, packaging and so on. Therefore,
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Electronic submission of manuscript
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Page 95 and 96: Table 1. Percentage yield extracts
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