Repeat Buying Behavior for Ornamental Plants: A Consumer Profile. Marco Palma¹, Alba Collart², and Charles R. Hall³

Transcription

1 Repeat Buyng Behavor for Ornamental Plants: A Consumer Profle Marco Palma¹, Alba Collart², and Charles R. Hall³ ¹ Assstant Professor and Extenson Economst, Department of Agrcultural Economcs, Texas A&M Unversty, 4 TAMU, College Staton, Texas, Emal: mapalma@tamu.edu ² Graduate Assstant, Department of Agrcultural Economcs, Texas A&M Unversty, 4 TAMU, College Staton, Texas, 77845; ³ Professor, Department of Hortcultural Scences and Holder of the Ellson Char n Internatonal Florculture. Texas A&M Unversty. Selected Paper prepared for presentaton at the Southern Agrcultural Economcs Assocaton Annual Meetng, Orlando, Florda, February 6-9, 009 Copyrght 009 by the authors. All rghts reserved. Readers may make verbatm copes of ths document for non-commercal purposes by any means, provded that ths copyrght notce appears on all such copes.

2 Introducton The florculture and nursery ndustry has evolved rapdly n recent years. The ntroducton of mass-market retalers such as supermarkets, department stores and Internet-based busnesses has changed the marketng paradgm of florculture. Compared to the other food products such as mlk, meat, ctrus, etc., florculture and nursery crops lack an extensve marketng lterature. In general, the demand for all products s hghly dependant on ts characterstcs or attrbutes. For most food products, the prevalng characterstcs are to satsfy nutrtonal needs and/or taste. Even though ornamental plants do not satsfy any nutrtonal needs, they possess other mportant characterstcs that nfluence the buyng decson; and because ornamentals are not essental for survval, a substantal porton of the populaton s comprsed of non-buyers or nfrequent buyers. Therefore there s a consderable gap for the decson of buyng or not, and buyng ntensty. Ths decson s lnked to consumer demographcs and the buyng occasons and perods. Understandng how consumers make choces of whether to buy or not and the perceptons of the characterstcs of the products they do buy s essental to understandng ornamental demand. Florculture and nursery products are purchased for varous reasons such as expresson of love or frendshp, a way to express thankfulness or apprecaton, and beautfcaton purposes ether for self use or as gfts. These attrbutes of flowers and plants cannot be quantfed drectly; therefore the satsfacton ganed from the consumpton of these goods s closely related to the purpose of the purchase (Grapunthong, 00). Ths also mples that the demand for these products can be nfluenced by the characterstcs or preferences of buyers and the reasons for buyng the

3 products. Ths stuaton becomes evdent durng specal seasonal calendar occasons (.e., Mother s Day, Valentne s Day, etc), where the consumpton of ornamental products s substantally hgher compared to non-calendar occasons. The man objectve of ths paper s to analyze the man factors affectng consumer frequency of purchasng ornamental plants. There s extensve lterature regardng demand analyss for tradtonal agrcultural products; however, studes on the demand sde for florculture products are very lmted n the lterature. Mller (983) performed an extensve sub-sector analyss for the fresh cut-flower ndustry n the U.S. by analyzng the structure, conduct and performance of the exstng condtons of the ndustry to try to predct future trends. Mller observed that there were specal calendar occasons when the demand for flowers was substantally hgher and other non-calendar occasons where the demand was substantally lower. He also determned that the demand for flower arrangements was nelastc, meanng that consumers are not hghly responsve to changes n prce of floral products. Tllburg (984) analyzed a panel of cut flower and potted plant consumers n the Netherlands to relate aspects of consumer behavor to marketng varables and demographc characterstcs of households. He dentfed three market segments: the frst segment conssted of 44 percent of the households and was senstve to prces but nsenstve to natonal advertsements; the second segment conssted of 40 percent of the households, and was nsenstve to both prces and advertsements; and the thrd segment, wth 3 percent, was senstve to both prces and advertsng. Behe (989) analyzed the consumer purchasng behavor of Pennsylvanans at the retal level. She recommended three ways to segment retal flower markets: by product, 3

4 volume of purchase, and by locaton of the purchase. Behe et al. (99a) carred out an analyss of consumer purchases of floral products n Oho supermarkets usng prncpal components analyss. Behe et al. (99b) followed up on her prevous study and appled cluster analyss to dentfy the most mportant factors affectng floral buyng decsons. Becker (993) studed dfferences n servce qualty between supermarkets and florsts n Texas. He found that the dfferences on the types of retal outlets were based on the types of products sold, custom desgn and other n-store servces, delvery optons and convenence. Rmal (998) analyzed the effects of generc and brand promotons on sales of fresh cut-flowers at the retal level n the U.S. Grapunthong (00) analyzed the demand drvers for fresh cut-flowers and ther substtutes n the U.S. Grapunthong found that all drect prce effect coeffcents wth the seasonal and actual varables were statstcally sgnfcant and changes n the relatve prces had a sgnfcant mpact on flower market shares among fresh cut-flowers, potted flowerng plants, and dry/artfcal flowers. Ward (004) evaluated the mpacts of the Flower Promoton Organzaton (FPO) advertsng campagn on cut-flower sales, concludng that the promotons have mpacted the demand for flowers through ncreasng buyer frequency and through attractng new buyers. He found that about 87 percent of the ncrease n demand for the promotonal programs s from the ncreased number of transactons per buyer. Ward found that the demographc group that responded the most to the promotonal program were female buyers that purchase flowers for self-use. Ths was consstent wth the target of the FPO promoton program. Yue and Behe (008) analyzed consumer preferences for dfferent floral retal outlets. They used a consumer panel data collected by the Amercan Floral Endowment 4

5 from 99 to 005 were used to evaluate consumers' choce of dfferent floral retal outlets among box stores, tradtonal freestandng floral outlets, general retaler, other stores, and drect-to-consumer channels. When studyng the aforementoned lterature regardng the demand for floral and other ornamental products, t s apparent that there are many factors that affect ther demand. These factors can be grouped nto three man categores: external, controlled, and seasonal factors. External factors of demand nclude nflaton, wages, prces, unemployment rate, demographc factors and other economc varables. Controlled factors of demand may be used to change perceptons and awareness wth the use of promotons, product development and nnovatons. Seasonal factors also affect the demand for flowers. There are certan calendar occasons when the demand for flowers s hgher compared to other non-calendar occasons. The most common calendar occason dates are Mother s Day and Valentne s Day (Ward, 997). Ths paper wll concentrate on evaluatng some of the controlled factors of demand affectng ornamental purchases durng non-calendar occasons and hence lookng at core ornamental buyers. Because ornamental plants are non-essental for survval, n a typcal month the percentage of the populaton that buys flowers s relatvely low. From ths fact arses the need to understand how ornamental buyers make the choce to purchase and to have a measure or profle of consumer ntensty. Demand analyses for ornamental products dffer among other agrcultural commodtes n the sense that for other agrcultural commodtes, the quantty consumed s used drectly n the analyss. In the case of florculture products, a consumer purchase quantty s ambguous and closely ted to the type of ornamental plant; for example, a quantty of one may refer to one sngle stem 5

6 rose, or an arrangement of a dozen roses and several other plants. Hence, ths study replaces quantty (number of unts) observed by the number of transactons gven on a defned perod of tme. In dong so, all propertes (or restrctons) of the demand functon are stll satsfed. Repeat buyng occurs when a consumer buys a product more than once n a gven perod of tme. Consumers are nfluenced by pre-purchase needs, perspectves, atttudes, the experence of prevous usage, and external nfluences such as advertsng and promoton programs, retal avalablty, personal sellng and word of mouth effects, and dfferences n products, servces and prces. The consumer has to make decsons regardng what products to buy and at what prces and where to buy the products. All of these characterstcs form a post-buyng experence n the customer s mnd after the purchase takes place; based on all these factors a consumer would choose dependng on the level of satsfacton or utlty obtaned from the product or servce whether to repurchase the product or not. There are bascally three cases of repeat buyng stuatons that can be defned. Frst, f a consumer buys more than one product n one or more purchase occasons (transactons) n a gven tme perod. In ths case, consumers dffer n how often they repeat buy the products. The frequency of buyng would be 0 for a consumer that dd not purchase the product and for consumers that purchased the product once. For repeat buyers, the frequency wll be, 3, 4, etc., dependng on the number of repeat buyng occasons they purchased the product. The second way of repeat buyng refers to consumer that may buy the product n more than one tme perod, or multple transactons n a gven perod. Then a model can be formulated for repeat buyng behavor under 6

7 statonary and no trend condtons. The thrd and last form of repeat buyng behavor s that more than one unt may be purchased on the same purchase occason (Ehrenberg, 988). Data and Methods The data were obtaned through an electronc mal survey conducted n July of 008 to a representatve sample of the Texas populaton consstng of 880 ndvduals provded by MarketTools Corporaton, a company specalzed n market research and onlne survey servces. From the total sample, approxmately 3% were actual consumers of the ornamental ndustry s products, lowerng the fnal number of usable responses to 74 observatons. The dependent varable s frequency of buyng for ornamental plants. It s defned as the number of transactons per month ( f = 0,,,3,..., n ) and t s a functon of the purpose of the purchase (PP), seasonalty (S), and several demographc characterstcs, ncludng age, gender, martal status, ncome, ethncty, educaton, and regon. The purpose of the purchase s to use the ornamental plants for self consumpton or gfts. The frequency of buyng of flowers s affected by seasonal factors. As an example, the frequency of buyng and the total number of buyers ncrease durng specal calendar occasons such as Mother s Day, Valentne s Day, Chrstmas, etc. Snce our data are not tme seres, monthly seasonalty can not be evaluated. The varable seasonalty s a dscrete varable that dentfes self descrbed specal occason buyers only (non-habtual buyers), versus habtual ornamental buyers. The dependent varable frequency of buyng s censored and therefore the Tobt model s used for the estmaton. The general frequency of buyng econometrc model can be wrtten as: 7

8 f = β + β AGE + β AGE3 + β AGE4 + β FEMALE + β MARRIED + β INC + β INC3 + β INC4 + β ET + β ET3 + β EDU + β EDU3 + β REG 7 + β REG3 + β PP + β S + ε () where all varables used n the model and ther defnton are presented n Table. Because the dependent varable n our regresson model equaton has a lower lmt (.e. zero), and the dependent varable takes the value of zero for a large number of sample observatons (4.8%), conventonal multple regresson analyss s not an approprate technque to be used (Lung-Fe and Maddala, 985). In order to account for ths truncaton on the data set the Tobt model can be specfed as follows (Greene, 000): f = * x β + ε, () where x s the ( K) vector of explanatory varables and ε ~ N(0, σ ) and t s ndependent of other errors. Thus for any household the buyng frequency model would take the form: f = f f 0 (3) * f * > f = 0 f f 0. * From the total number of observatons N n the sample, the number of observatons can be dvded nto two groups; one for whch f = 0, N 0 ; and another for the number of observatons for whch f > 0, N. In order to observe the statstcal problems arsng from the censored sample problem, consder leavng out of the analyss the N 0 observatons for whch f = 0. For the remanng N sample observatons, they are complete observatons. Hence, one can use least squares estmators to estmate β. The problem s that ths estmator s based and nconsstent. In order to prove that, one 8

9 can wrte down the expectaton of the observed values of f condtonal on the fact that f > 0 : E [ f f 0] = x + E( ε f > 0) > β (4) If the condtonal expectaton of the error term s zero, then the estmates of the least square regresson on N would provde an unbased estmator for β. However ths s not the case; f the ε are ndependent and normally dstrbuted random varables, then the expectaton would be: [ ε f > 0] = E[ ε ε > x β ] > 0 E (5) It can be shown that ths condtonal expectaton can also be expressed n the followng manner: where φ and E [ ε > x β ] φ ε = σ (6) Φ Φ are the standard normal probablty dstrbuton functon (p.d.f), and cumulatve dstrbuton functon (c.d.f.) evaluated at ( x β / σ ) ; therefore n the regresson model, f f > 0, then, f = x β + ε φ = x β + σ Φ + u (7) f we apply the regular least squares procedures the term φ σ s omtted. Snce that Φ term s not ndependent of x the results are based and nconsstent. In order to estmate the parameters β and σ consstently, maxmum lkelhood estmaton (MLE) procedures were used. The lkelhood functon of the sample has a 9

10 component for the observatons that are postve, and one for the observatons that are zero. For the observatons f = 0 t s known that x β + ε < 0 or expressed n a dfferent way, ε < x β, then, Pr ε x β ε (8) σ σ [ f = 0] = Pr[ < x β ] = Pr < = Φ If we defne the product of the observatons over the zero lower lmt level to be Π 0 and the product over the postve observatons to be Π, the lkelhood functon of the Tobt model s gven by: ( Φ ) ( πσ ) exp{ ( f x β ) } σ l = (9) 0 The correspondng log-lkelhood functon would be: ( ) ( ) ( ) ( f β ) / ln(π ) / lnσ x Φ N N L = lnl = ln (0) σ 0 Then the frst order condtons are: L = β σ 0 φx + Φ σ ( f x β ) x () L σ = 3 σ 0 ( x β ) φ N Φ σ + 4 σ ( f x β ). The parameters were estmated wth Tme Seres Processor (TSP). The estmaton procedure uses the analytc frst and second dervatves n equaton to obtan maxmum lkelhood estmates va the Newton-Raphson algorthm. The startng values for the parameters are obtaned from a regresson on the observatons wth postve f values. The numercal mplementaton nvolves evaluatng the normal densty and cumulatve normal dstrbuton functons. The cumulatve dstrbuton functon s computed from an asymptotc expanson, snce t has no closed form. The rato of the 0

11 densty to the dstrbuton functon, used n the dervatves, s also known as the Inverse Mlls Rato (Hall, 99). Results and Dscusson The survey sample was a far representaton of the Texas populaton based on selected soco-demographc characterstcs ncludng martal status, gender, ethncty, and ncome. About 60% of respondents were marred compared wth 54% of the populaton n Texas. The percentage of females n the sample was 53% versus 50% for Texas; and 53% of the total number of respondents had an ncome of more than $50,000 compared to 47% of Texas populaton. The ethncal dstrbuton of the sample was smlar to the U.S. Census Bureau data, wth Caucasans accountng for the majorty of responses n the survey and comprsng the majorty of the true populaton, followed by Hspancs. The hghest educatonal degree obtaned from 78% of the sample populaton was a bachelor s degree compared wth 9% of Texas populaton. Table presents a comparson of survey respondent s demographc characterstcs wth actual populaton averages. Most respondents (78.5%) reported to be non-habtual ornamental buyers or purchasers of ornamental plants durng specal calendar buyng occasons only. Most (84%) ornamental products n Texas were purchased for self-consumpton purposes. The preferred outlets to purchase ornamental products were garden centers (7%), followed by nurseres (40%), chan stores (3%), and supermarkets (30%). Respondents were also asked to rate the mportance of several aspects n the purchase decson ncludng prce (3.89/5), vbrant colors (3.85/5), low-care demand (3.83/5), drought tolerance (3.64/5), season (3.57/5), guaranteed growth (3.5/5), lght demand or requrement (3.34/5), and organc (.58/5). The weghted average ratng of

12 these aspects clearly suggests that prce s the most mportant feature, followed very closely by vbrant colors and low-care demand (low mantenance). The ratng of organcally-grown and lght requrement mples that these two features are typcally not very mportant to Texas consumers when makng purchasng decsons for ornamental plants. For nstance, 45% of the respondents assgned low ratngs of or to organcallygrown products and 36% confrmed that lght requrement was not a feature they carefully seek for when buyng an ornamental plant. The parameter estmates of the buyng frequency model for ornamentals are presented n Table 3. The strong sgnfcance of the sgma parameter suggests that for the data truncaton, the lower lmt level of zero can not be gnored and the estmaton method must deal wth the asymptotc dstrbuton of the data. Ths parameter refers to the estmated standard devaton of the resdual. In ths model, 97 out of 64, or 74.6% of the usable observatons were postve. The frequency of buyng for the average respondent was.53 transactons per month. The sgn of the parameters can be nterpreted as an ncrease (postve), or decrease (negatve) n the monthly frequency of buyng, or transactons per month. The margnal effects represent the change n the monthly frequency of buyng for an addtonal unt of the varable. Snce most of the varables n the model are dummy varables, then margnal effects are nterpreted as the change n the number of transactons per month assocated to that dummy varable. There was no statstcal sgnfcant nfluence assocated wth younger age groups and frequency of buyng. Age3 (40-55 years old) and Age4 (more than 55 years old) both decrease the frequency of buyng. For ndvduals of years of age, frequency of buyng was reduced by 0.07 transactons per month, whle ndvduals older than 55 had

13 0.06 less transactons per month. Respondents wth ncomes between $5,000 and $49,999 had a hgher frequency of buyng, wth 0.07 more transactons per month. No other ncome groups had statstcally sgnfcant effects on frequency of buyng. One of the reasons why older households have lower frequency of buyng may be because they tend to have landscapng servces performed by contractors and do not deal wth buyng ornamental plants as often. In contrast, medum ncome level respondents may do most of ther gardenng or landscapng themselves. Ethncty also had no statstcally sgnfcant effects on buyng frequency. The two varables wth the hghest effects on frequency of purchasng were purpose of the purchase and seasonalty, wth both varables ncreasng the frequency of buyng. When the purpose of the purchase was for self-use, the model showed an ncrease n the number of transacton per month of 0.. The seasonalty varable sought to dfferentate between those makng most of ther purchases durng specal calendar occasons, such as Valentne s Day, Mother s Day and Chrstmas, etc. and those ndvduals who also purchase ornamentals n non-calendar occasons. Non-specal occason buyers ncrease frequency of buyng. If a respondent was a specal occason buyer, then the frequency of buyng was reduced by transactons per month. Indvduals wth a college degree tend to make 0.08 less transactons per month. We dd not fnd any statstcally sgnfcant dfferences n frequency of buyng among Texas regons. Summary and Conclusons Ths paper used an electronc survey conducted n Texas to study the man factors affectng the frequency of purchase, measured n transactons per month, for ornamental plants. The frequency of buyng for the average respondent was.53 transactons per 3

14 month. Whle we found several dfferences n demographc characterstcs of respondents, the two factors that mpacted the frequency of ornamental plant buyng the most were the purpose of the purchase and seasonalty. Self consumpton of ornamental plants, and respondents not buyng products mostly durng specal calendar occasons (habtual buyers) ncreased the number of transactons per month by 0. and 0. respectvely. Older age groups (Age3: years, and Age4: 55 or older) and respondents wth a college degree actually had a lower frequency of buyng. Indvduals wth medum ncome levels ($5,000 to $49,999) ncrease frequency of buyng by 0.07 transactons per month. One of the reasons why older households have lower frequency of purchase may be because they tend to have landscapng servces performed and do not deal wth buyng ornamental plants as often. In contrast, medum ncome level respondents may do most of ther gardenng themselves. We found no statstcally sgnfcant effects of ethncty or regonal dfferences n the state of Texas on frequency of buyng. Lterature Cted Becker, W.A Products, Servces, and Consumer Perceptons of Servce Qualty n the Retal Floral Industry of Texas. PhD Dssertaton. Texas A&M Unversty. College Staton, Texas. Behe, B.K Floral Purchase Behavor of Pennsylvanans. PhD Dssertaton. Pennsylvana State Unversty. Unversty Park, Pennsylvana. Behe, B.K., T.A. Prnce, and H.K. Tayama. 99a. Analyss of Consumer Purchases of Floral Products n Supermarkets. Hortscence. Vol. 7.: Behe, B.K., T.A. Prnce, and H.K. Tayama. 99b. Market Segmentaton of Supermarket Floral Customers. Hortscence. Vol. 7.: Ehrenberg, A.S Repeat-Buyng, Facts, Theory and Applcatons. Oxford Unversty Press. New York, New York. 4

15 Grapunthong, N. 00. Demand Drvers for Fresh Cut Flowers and Ther Substtutes: An Applcaton of Household Expendture Allocaton Models. Ph.D. Dssertaton. Food and Resource Economcs Department. Unversty of Florda. Ganesvlle, Florda Greene, W.H Econometrc Analyss. 4th Edton. Prentce Hall. Upper Saddle Rver, New Jersey. Hall, B.H. 99. Tme Seres Processor Verson 4.. Reference Manual. Palo Alto, Calforna. Lung-Fe, L. and Maddala, G.S The Common Structure of Tests for Selectvty Bas, Seral Correlaton, Heteroscedatcty, and Non-normalty n the Tobt Model. Internatonal Economc Revew. Vol. 6. No..: -0. Mller, M Commodty Sub-Sector Analyss of Cut Flower Industry. PhD. Dssertaton. Food and Resource Economcs Department. Unversty of Florda. Ganesvlle, Florda. Rmal, A.P Effect of Generc and Brand Promotons of Fresh Cut Flowers on the Use of Retal Flower Outlets. Ph.D. Dssertaton. Food And Resource Economcs. Unversty of Florda. Ganesvlle, Florda. Tlburg, A.V Consumer Choce of Cut Flowers and Pot Plants. Agrcultural Unversty. Wagenngen, The Netherlands. Ward, R.W Evaluatng Promoflor: Have the Promotons of Fresh Cut Flowers and Greens Had an Impact. Natonal Promoflor Councl. UF/PER97#. Unversty of Florda. Ganesvlle, Florda. Ward, R.W Estmated the Impact of FPO s Generc Promotons of Fresh Cut Flowers: Analyss Through Phase VI. Research Paper. Food And Resource Economcs. Unversty of Florda. Ganesvlle, Florda. Yue, C. and B.K. Behe Estmatng U.S. Consumer s Choce of Floral Retal Outlets. Hortscence. Vol. 43. No. 3:

16 Table. Descrpton of varables ncluded n an ornamental plant buyng frequency model. Varable Descrpton Soco-demographc characterstcs AGE Age between 5-39 years old (= f true and 0 otherwse) AGE3 Age between years old (= f true and 0 otherwse) AGE4 More than 55 years old (= f true and 0 otherwse) FEMALE If gender s a female (= f true and 0 otherwse) MARRIED Marred martal status (= f true and 0 otherwse) INC Income level (= f ncome between $5,000- $49,999 and 0 otherwse) INC3 Income level (= f ncome between $50,000-$74,999 and 0 otherwse) INC4 Income level (= f ncome s $75,000 or more, and 0 otherwse ET Ethncty (= f ethncty s Hspanc, and 0 otherwse) ET3 Ethncty (= f ethncty s other, and 0 otherwse) EDU Educaton level (= f college degree, and 0 otherwse) EDU3 Educaton level (= f graduate school, and 0 otherwse) Consumer habts S PP Regon DREG DREG3 Seasonalty (= f habtual buyers non specal occason only- and 0 otherwse) Purpose of the purchase (= f self consumpton and 0 otherwse) Regon: Central Texas (= f true and 0 otherwse) Regon: South Texas (= f true and 0 otherwse) Dummy varables base levels AGE Age group of under 5 years INC Income group of under $5,000 ET Ethncty s Caucasan EDU Educaton level s hgh school or less REG Regon s north 6

17 Table. Representatveness of the survey respondents relatve to the Texas Census populaton data. Survey Data Census Data Demographc varables Frequency Percentage Percentage Martal status Marred Sngle Gender Male Female Educaton level Hgh School College Graduate School Ethncty Afrcan Amercan Caucasan Amercan Indan Hspanc Asan/Pacfc Islander Other 6..3 Age Less than More than Income Under $5, $5,000-$50, $50,00-$75, $75,00-$99, $00,000-& above Source: U.S. Census Bureau, 000 and Amercan Communty Survey 7

18 Table 3. Results from a tobt model analyzng the frequency of buyng ornamental plants. Tobt Coeffcent Standard t-value Margnal Error Effects Intercept ** Soco-demographc characterstcs AGE AGE ** AGE * FEMALE MARRIED INC ** INC INC ET ET EDU *** EDU Consumer habts PP 0.764** S.394*** Regon REG REG SIGMA.8776*** Number of usable observatons 74 * P-value 0., ** P-value 0.05, *** P-value 0.0 8