Title: Consumers preferences for apple fruits in Tirana market using a conjoint analysis

Transcription

1 Title: Consumers preferences for apple fruits in Tirana market using a conjoint analysis Prof. Ass. Dr. Engjell Skreli Lecturer, Faculty of Economics and Agribusiness, Agricultural University of Tirana Koder-Kamez, Tirane, Albania [email protected] Dr. Drini Imami Lecturer, Faculty of Economics and Agribusiness, Agriculture University of Tirana Koder-Kamez, Tirane, Albania [email protected] Prof. Dr. Tatjana Dishnica Director of Extenssion Services, Ministry of Agriculture Food and Consumer Protection Dr. Alban Jaupi Faculty of Economics and Agribusiness, Agricultural University of Tirana Koder-Kamez, Tirane, Albania [email protected] Alban Cela Student, Faculty of Economics and Agribusiness, Agricultural University of Tirana Koder-Kamez, Tirane, Albania [email protected] Arbi Fortuzi, Student, Faculty of Economics and Agribusiness, Agricultural University of Tirana Koder-Kamez, Tirane, Albania [email protected] 1

2 Abstract The objective of this study is to analyze consumer preferences for apple in Tirana focusing on these attributes: origin, price, size and variety, using Conjoint Choice Experiment (CCE). Variety is by far the most important attribute for three out of four consumer groups that have been identified; however, different consumer groups prefer different varieties. Origin is the second most important attribute for the two largest consumer groups, with domestic apple being preferred to import ones, while size is the third most important attribute fort these groups, with larger apple being preferred to smaller ones. This is the first time that consumer preferences for fresh fruits are analyzed applying CCE in Albania, and implications of this study are quite important for industry stake-holders, given the importance of apple within Albanian agriculture sector. Keywords: Conjoint Choice Experiment (CCE), latent class analysis, apple, consumer preferences, Tirana 2

3 Introduction Background Albania is a country with scarce land and capital resources and relatively abundant labor resources. This type of resources endowment calls for labor intensive industries. During transition period, starting from beginning of 1990 till today, labor intensive industries, including fruit tree production, have developed faster than other types of products. Domestic production of apple in Albania is rapidly increasing, as a result of new plantations. Production of apple has increased significantly since 2000, being tripled, according to Food and Agriculture Organization Statistical Database (FAOSTAT 2009). Production of apple is expected to further increase in the coming years, due to young plantations, stimulated by the subsidy scheme introduced by Ministry of Agriculture, Food and Consumer Protection (MAFCP). Problem Statement Domestic production of apple currently covers around 3/4of the domestic supply (MAFCP 2009), or 59% according to more conservative assessment (FAOSTAT 2009). This share has increased significantly as compared to 2000 when domestic supply was strongly dominated by imports, as production has increased substantially by more than half. However imports are still high, covering a relatively high share of the domestic supply (38% versus 26%, FAOSTAT versus MAFCP respectively). Apple makes up more than 1/5 of total fruits imports in Albania. The ongoing high presence of imports can be partially explained by lack of domestic supply in certain months of the year and partially by preference of (certain) consumer groups for certain apple varieties sourced by imports. While there have been several studies on the apple value chain by several organizations (DSA, 2009) there has not been conducted an in depth consumer survey to identify consumer preferences for apple by variety, origin, and other product attributes. Understanding consumer preferences is important in the context of decision-making of key stakeholders, including MAFCP, producers themselves as well as development agencies that operate in the sector. 3

4 Objectives The purpose of this study is to analyze consumer preferences for apple and to evaluate the relative importance for Albanian apple attributes such as cultivar, price, origin, and size using Conjoint Choice Experiment (CCE). Specifically, the research objectives are: (1) to evaluate apple attributes that are important to consumers in Tirana market, and (2) to discuss the results and provide marketing and policy implications. Methods and procedures First and Second Design Stage Identifying Product Attributes and their Levels Product attributes and their levels have been based on literature review, expert assessment and focused group discussions. Four important attributes were included in the study: color (variety), origin, price, and fruit size. Color (variety). Color has consistently been an important attribute in previous fruit and vegetable analyses. The relative importance for color of apples was 20 percent in Manalo s study (1990) and 17.98% in Jerko and Kovačić (2009). Other studies (Campbell s et al., 2004; Frank et al., 2001) show that color is important for other fruits and vegetables. In our study we have chosen to make a correspondence between color and apple variety. Though consumers do not pay much attention to variety (focused group discussion), apple variety are important in terms of policy implications. While color means variety (pictures have been shown to interviewees), variety means taste (Refer to Table 2). Origin. Origin is a quite important attribute. Jerko and Kovačić (2009) found that relative importance of origin for apple was Halbrendt (2004) found that more than half of consumers would pay more for locally grown avocado. Consumer surveys in Albania on other agri-food products such as olive oil have found a strong preference and willingness to pay for locally grown products (Chan-Halbrendt et al, 2010). Price. Although price is not a product attribute as such, it is commonly included as an attribute in conjoint analyses because it is a major factor in product selection (Gillespie et al. 1998). 4

5 Size. Expert opinions support that size is important attribute apple. Albanian consumers are not enough familiar with quality concept as such (fruit size, color, labeling). Fruit size may be used as a proxy for quality. Large fruit size may also be perceived as being produced using hormones. This is supposed to be clarified collecting supporting information through questionnaire. Other theoretically important attributes like freshness, safety, quality, and method of production are judged to be (based on focused group discussions and expert opinions) either less important than selected attributes or difficult to assign precise attribute level. Table 1: Apple attributes and their level Attribute level Attributes Color (Variety) Price Origin Fruit size Red (Starking) 50 Imported Large (8 cm) Yellow (golden) 80 Local Small (5 cm) Green (Granny Smith) 110 Red yellow striped (Fuji) 150 As discussed earlier, variety means a taste, as follows: Starking (Sweet-bitter), Golden Delicious (Sweet-mild and fragrant), Granny Smith (Pleasantly tart-sweet and juicy), Red chief (Sweet and crispy) Third and Fourth Design Stage Choice of Experimental Design and Construction of Choice Sets In this study, CCE will be used to evaluate consumer preferences and the relative importance of Albanian apple attributes. The proposed method for this research originated theoretically from Lancaster (1966) in which the utility of a product is based on the bundle of attributes it represents. CCE was developed by Louviere and Woodworth (1983) and has been recently widely applied to consumer preferences surveys. CCE has been used before for fruits and other food products (Halbrendt & al., 2004). This approach has been recently successfully applied for the first time in Albania to olive oil product (Halbrendt et al., 2010), identifying consumer preferences and clustering consumer groups according to preferences for product attributes and socio-demographic variables. 5

6 Table 1 will give a brief description of the design stages of a CCE. Table 2: Design stages for a Conjoint Choice Experiment Stage Selection of attributes Description Selection of apple attributes has been done based on the literature review, expert interview and focused group discussions. Assignments of attributes level Choice of experimental design Construction of choice sets The range of attributes is also determined by literature review, expert interview and market situation. The attribute levels have been assigned such as to be reasonable and realistic. Fractional factorial design is used to reduce the possible combinations which combine the levels of the attributes that reduces respondents fatigue and also provide efficiency in model estimation The profiles identified by the experimental design are then paired and grouped into choice sets to be presented to respondents. Measurement of Choice of the survey administration i.e. face-to-face interview preference Source: Chan-Halbrendt et al., 2010 The idea that all goods can be described by their characteristics, also known as attributes, is the basis of CCE. For CCE, the most important attributes and their levels have to be determined when designing the study. Using the conjoint choice method with Latent Class Analysis (LCA) to analyze the data collected is an improvement on the traditional (i.e. one class) aggregated model analysis. The standard aggregated model has to deal with the independence of irrelevant alternatives problem, which affects the predictions of market niches. Latent classes take into consideration different segments with different utility preferences within a certain group or class. In LCA, respondents are grouped, according to their choices in the conjoint choice experiment. The choices that respondents made are considered mainly based on their attribute preferences and their sociodemographics. 6

7 Fifth Design Stage Data Collection- Survey Location, Sample Size and Survey Technique Questionnaire design. A questionnaire has been designed based on literature review, expert interviews and two focus groups. Structured questionnaires contain 12 profiles in triple choice sets. Figure 1: Example of the questionnaire choice sets Questionnaire has been designed to collect also supporting information on socio-demographic issues (income, age, gender and employment), consumer behavior and eating habits (amount of money spent on apple and frequency of buying, etc.), etc. Sample design. There have been conducted 250 face-to-face interviews in the Tirana. We choose Tirana for a number of reasons (i) purchasing power is concentrated mainly in Tirana (ii) Tirana is a reasonably good representative of the country - due to internal migration (during last twenty years, Tirana has grown from 200,000 to around 700,000 inhabitants), and (iii) interviews in Tirana reduce substantially travelling and subsistence costs. A sample size of 250 questionnaires is deemed as representative and has been used in other similar surveys (Chan-Halbrendt et al, 2010). Data collection, data entry and validation. Data have been collected by well trained and motivated interviewers and the process has been closely followed by the faculty staff. Questionnaire has been properly coded in order to better manage data entering and data 7

8 processing. A data entry file has been prepared and data have been entered and validated in a SPSS database. Sixth Design Stage Data Analysis: Conjoint Choice Model Using Latent Class Analysis (LCA) Approach In CCE, the assumption is that a respondent would choose the product or profile that would give them the maximum utility. According to random utility model, a respondent s utility can be written as equation (1): (Lusk and Schroder, 2004): U ij = Vij + eij (1), Where, U ij represents total utility of consumer i derived from the product j, and V ij is the systematic component of the utility function determined by the product attributes, and e ij denotes a stochastic error. Assuming that is linear in parameters, the functional form of the utility function for alternative j can be expressed as Vij = β j + α jpij (2), where j represents the product attributes, P ij is the price of alternative j for consumer i, βj are the coefficients representing alternative specific constants for each product attributes (part worth utilities), and α j are coefficients representing the effects of j th product price on utility. As shown by Lusk and Schroder (2004), the probability, P ij, that consumer i chooses alternative j is given by the multinominal logit model (MNL) model: µ V ij e ij = (2) k c e P µ V ik Where µ is a scale parameter that is inversely related to the variance of the error term As discussed by Lusk and Schroder, (2004), willingness to pay (WTP) are derived by determine the price difference necessary to invoke indifference between two alternatives. Total WTP to from alternative j versus none option is simply calculated as the ratio of the alternative specific 8

9 constant (part worth utilities) to the price coefficient: β/α. Marginal WTP for alternative (attribute) j versus alternative (attribute) k can be calculated as a difference between total WTP for alternative j and total WTP for alternative k, or as a difference between alternative specific constant (part worth utilities) of attribute j and k and the price: (β j - β k )/α; price coefficient, α, in this case is unique in case we take into consideration that β j and β k are attributes of the same products being priced. The first step of the latent class analysis was to determine the optimal number of distinct classes for the dataset. Four criteria were used to the optimal number of distinct classes: (i) percentage certainty; the higher the better, (i) Consistent Akaike Info Criterion (CAIC); the lower the better, (i) Chi square; the higher the better and (iv) relative Chi square; the higher the better. Results and interpretation Selection of the model with optimal number of distinct classes Based on CAIC, the four class model has been preferred to three class model and five class model. CAIC decreases substantially when passing from three class model to four class model, showing that four class model matches better that data, as shown in the following table: Table 3: Summary criteria of best replications Groups Replication Pct Cert CAIC Chi Sq Rel Chi Sq Additionnally, the four class model retains two classes from the three class model; the third class is divided in two. Though, when passing from four class model to five class model CAIC continues to decrease, the rate of decrease is lower, as shown graphically in Annexes. Moreover, five class model contains two very small classes of around 9%. 9

10 Importance of attributes for four class model The first group represents almost half of the respondents (namely 44.7 percent) while the second group represents 30.5 percent these are the two largest two groups and together make up more than ¾ of the total number of consumers. The third and four groups (which are also the smallest) represent respectively 14.3 and 10.6 percent of the consumers. Details of the four classes estimated parameters are described below in Table 6 and 7. Table 4: Importance of attributes by groups Group 1 Group 2 Group 3 Group 4 Share of each class 44.70% 30.50% 14.30% 10.60% Attributes Variety Origin Size Price Varity and origin are the most important attributes for Group 1. This group prefers green (Granny smith) variety, and dislikes Yellow and Red Yellow in comparison to other varieties. Consumers in this group prefer domestic apple to import ones, and of bigger size apple to smaller ones. Price is the most important attribute for Group 2. Price has significant negative value. That implies that consumers in this group are oriented primarily from lower price (cheaper) apple. Similar to Group 1, domestic apple are preferred to import ones, and bigger size apple to smaller ones. Variety is not important and no attribute level is significant for this group. For Group 3, the most important attribute, is variety - it prefers yellow, and dislikes green and red-yellow apple in comparison to other varieties. Consumers in this group prefer smaller apple, while show no significant preference for the attribute of the origin. Variety is by far, the most important attribute also for Group 4, which prefers Red apple and dislikes green and red-yellow apple in comparison to other varieties. Consumers in this show no significant preference for the attributes of the origin and size. 10

11 Utilities and significance and consumers willingness to pay The following table summarizes part worth utilities (parameters) and their significance. Based on these estimates, one may compute consumers willingness to pay for apple varieties, and willingness to pay for domestic versus imported apple, big versus small apple (or vice-versa). Table 5: Parameter Estimates: part worth utilities Group 1 Group 2 Group 3 Group 4 Variety Value t Value t Value t Value t Red (Starking) Yellow (Golden) Green (Granny Smith) Red Yellow Striped Origin Domestic Imported Size Big (8 cm) Small (5 cm) Price Price The first class of consumers is willing to pay 13.6 ALL for each kg of domestic apple as compared to imported apple ((0.34-(-0.34))/(-0.05) 1. Additionally, they are willing to pay 17.4 ALL per green apple versus yellow apples and 4.8 ALL per kg of big apples versus small apples. The third class of consumers seem to be quite the opposite of first class; the third class of consumers is willing to pay ALL 7.9 for yellow apples versus green apples, and 3.4 ALL for small apples versus big apples. The fourth class seems to prefer red apples, since they are ready to pay ALL 27.6 per kg of red apples versus green apple. 1 Marginal WTP = (β j - β k )/α; refer to Methods and Procedures, Sixth Design Stage 11

12 Conclusions and recommendations The objectives of study were (1) to evaluate the apple attributes that are important to consumers in Tirana market, and (2) to discuss the results and provide marketing and policy implications considering that insight into consumer preferences for main apple attributes is essential information for industry stakeholders, including, farmers, traders, policy-makers and donors. Information about various consumer groups and their share provides milestones for farmers and for policy-makers as well as, particularly MoAFCP to better orient its support subsidy schemes and technical assistance. Study results reveal that origin variety, and size is quite important attributes. Variety is so important that the first group can be named green group, the third group can be named yellow group and the forth group may be colored red. The largest group, the first one, is willing to pay more than 17 ALL per kg of green apple versus yellow apple. There is a clear preference for domestic versus imported apple in three out of four groups. For the first group which is the largest, there is a clear willingness to pay for domestic apples versus imported apples. That having said, there is a preference for imported apple in third group. The preference for imported apples in this group is coupled with preference for green apple. Size comes out to be important as well, in three out of four classes. Study results may have marketing and policy implications. In terms of marketing, it is important that investors think not in terms of producing and selling apple, but producing and selling the right apple variety. This is also important in terms of government policy support. Additionally, government may consider supporting domestic production of apple variety that are more preferred by consumers; study shows that green apple are preferred to other varieties and consumers are willing to pay more for it. Importance attached by consumers to fruit size should have an adequate response by both private actors and government in terms of grading policy. 12

13 References 1. Barber, Silvia, G., C. Chan-Halbrendt, J. Krishna Kumar, T. Radovich and K. Love. Hawaii Avocado Industry Analysis: Part 2: Buyer Preference Focus. University of Hawaii, Cooperative Extension Service, Economic Issues. July Campbell, B.L., & Al Fruit Quality Characteristics That Affect Consumer Preferences for Satsuma Mandarins. HortScience 39(7) 3. Chan-Halbrendt, C., Zhllima, E., Sisior, G., Imami, D., Leonetti, L., 2010, Consumer Preference for Olive Oil: The Case of Tirana, 2010 IAMA World Symposium, Boston, USA, and forthcoming in IFAMR Journal. 4. Chan-Halbrendt, C., Imami, D., Zhang, Q., Zhllima, E., Leonetti, L., 2010, Latent Class Analysis of Consumer Preferences for Wine in Tirana, Albania, 2010 IAMA World Symposium, Boston, USA. 5. DSA, 2009, Value Chain and Market Analysis of Apple, Technical Report prepared for SNV 6. FAOSTAT, 2009, 7. Frank, C.A. & Al Consumer Preferences for Color, Price, and Vitamin C Content of Bell Peppers. HortScience 36(4) 8. Gillespie, J & Al Opinions of Professional Buyers Toward a New, Alternative Red Meat: Ostrich. Agribusiness 14(3) 9. Jerko, M., Kovačić, D., The Importance of Apple attributes: a Comparison of Selfexplicated and Conjoint Analysis Results 10. Lancaster, K, 1966, A New Approach to Consumer Theory. Journal of Political Economy. 74 (2), Leonetti, L., Imami, D., Rapushi, P., Kongoli, R., Nani, A., 2010, Analysis of fruits sector in Albania, Technical Report prepared for GTZ and EU 12. Louviere, J. J. and G. G. Woodworth Design and analysis of simulated consumer choice or allocation experiments: An approach based on aggregated data. Journal of Marketing Research 20: Luce, R., 1959, Individual choice behavior. New York: Wiley 14. Lusk, J. and Schroder, T., 2004, Are choice experiments incentives compatible? A test with high quality differentiated beef steaks. 15. Manalo, A.B Assessing the Importance of Apple Attributes: An Agricultural Application of Conjoint Analysis. Northeastern Journal of Agricultural and Resource Economics 19(2) 16. McFadden, D., 1973, Conditional logit analysis of qualitative choice behavior. Frontiers in Econometrics, edited by P. Zarembka, Academic Press 17. MoAFCP, 2009, Data provided by request from the statistical sector of Ministry of Agriculture, Food and Consumer Protection 18. USAID s AAC, 2009, Value Chain Analysis of Apple, Technical Report prepared by DAI 13

14 Annexes Disstribution of cases by group solution Two group solution Three group solution Four group solution Five group solution 5000 CAIC 4800 AIC Number of groups 14