Proposal of a Measuring Method of Customer s Attention and Satisfaction on Services

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1 417 Poposal of a Measuing Method of Custome s Attention and Satisfaction on s Yohei Yoshimitsu 1, Koji Kimita, Tatsunoi Haa 1, Yoshiki Shimomua, Tamio Aai 1 1 Dept. of Pecision Engineeing, School of Engineeing, Univesity of Tokyo, Tokyo, Japan Dept. of System Design, Tokyo Metopolitan Univesity, Tokyo, Japan Abstact Now a day, with the emeging gowth of the sevice industy, manufactuing companies ae convinced that thei poducts must be stengthened with sevice. Thus, we have developed a new discipline called Engineeing that aims to poduce a novel method to design sevice fom an engineeing viewpoint. In this pape, the authos popose an evaluation model that enables sevice designes to measue eceives. The authos poposed the Satisfaction Attibute Value Function as an evaluation model that suits man s behavio. Applying to an example, the esult of ou method had iche infomation than the esult of conjoint analysis. Keywods: Custome Satisfaction, Value Engineeing, Evaluation, Engineeing 1 INTRODUCTION The life cycle peiods of poducts ae shotened in ecent yeas, and sevice is paid attention as a way to achieve high additional value. Design pocess of sevices needs to include an evaluation that allows the designe to know how the sevice is ated by customes. In conventional engineeing, manufactuing poducts ae evaluated by functions they have. As sevices ae atifacts as same as poducts, the same method as fo manufactuing poducts is consideed applicable to sevice design. Fom the same point of view, we assume that the custome evaluates popeties of its functions and feels satisfied. Howeve, sevice is likely to be evaluated moe subjectively. Theefoe, we need a new model that epesents man s subjective behavio. This pape aims at poposing an evaluation method fo sevice designes that makes this degee of to be measued as quantitative value. This quantitative value of custome enables the designe to know, fo example, how much the pice can be inceased afte modified the sevice, o clea up which functions ae needed fo each maketing segment. In second chapte of this pape, models and concepts poposed in Engineeing [1] that ou poposal is based on ae intoduced. In thid section, we intoduce two cuent evaluation famewoks: Kano Model fom Engineeing and Pospect Theoy fom Behavioal Economics. In foth and fifth chapte, we popose a new evaluation method combining these methods. In sixth chapte, an application of the method is shown, and we make a compaison with conjoint analysis. Conclusions ae agued in seventh chapte. SERVICE ENGINEERING.1 Definition of sevice is geneally peceived as an activity that changes the state of a sevice eceive [1]. Figue 1 defines sevice; a sevice eceive eceives sevice contents fom a sevice povide though a sevice channel in ode to change own states by the contents. This state of a sevice eceive is called RSP (Receive State Paamete).In this definition, a sevice eceive is satisfied by only means of how much the eceive s states ae changed pefeably. Povide. View model feshness towels Contents Channel feshness of towels and bed linen keep the feshness of towels and bed linen feshness of towels State Change Receive Figue 1. Definition of keep the feshness of towels change towels when it s equied allowable of feshness of towels Receive State Paamete Function Paamete Attibute Paamete Function Entity Figue. View Model As Figue shows, a model witten in the fom of netwok diagams is called View Model [1]. The top node, a hatched cicle, indicates RSP. A squae epesents a function that influences a paamete connected with a dotted line. Each node epesents eithe function o attibutes of a sevice. The nodes suounded by the solid line at the left bottom illustate the ealization stuctue. 14th CIRP Confeence on Life Cycle Engineeing

2 418 A Function Paamete (FP), influencing diectly to the RSP, is called Contents Paamete (CoP) and FP influencing indiectly though CoP is called Channel Paamete (ChP). Each substantial atifact, constucting a sevice, is defined as entity, of which attibutes ae defined as attibute paametes (APs)..3 Existing Evaluation Method To design sevice effectively and moe value-added, designes needs a method to compae multiple sevices. We poposed Analytic Hieachy Pocess (AHP) [] based impotance analysis method of RSPs, a QFD [3] (Quality Function Deployment) based impotance analysis method of CoPs, and an influence analysis between a RSP and FPs using Dematel [4] method [5]. These methods enabled sevice designes to know which pat of sevice should be paid attention and made them easie to impove sevices. Howeve, these methods cannot make the designe know how much upgaded sevice is impoved. Fo this pupose, we need a method that evaluates sevices totally using the viewpoint of sevice eceives. 3. Pospect Theoy Pospect theoy was developed by Kahneman and Tvesky [9], which was oiginally poposed as a citicism of expected utility model in economics. It descibes how individuals evaluate losses and gains based on empiical evidence. It consists of two theoies: value function and weighting function. The fome descibes the elationship of value to gains and losses as illustated in Figue 4. Its hoizontal axis shows gains and losses in the fom of absolute values such as an inteest of investment o a ewad of lottey. The oigin indicates the pospect of the individual, which is called a efeence point. Its asymmety implies that losses give a stonge impact than gains. This featue is called loss avesion. Note that the cuve in Figue 4 tuns satuated when the losses o the gains become fathe fom the efeence point. value 3 SATISFACTION MODELS IN OTHER FIELDS Some studies have dealt with custome s. Kal Albecht categoized elationships between custome s expectation and povided poducts into fou levels [6]. Bend H. Schmitt advocated the concept of expeimental maketing and categoized custome expeiences into SENSE, FEEL, THINK, ACT, and RELATE [7]. In this chapte, two models on custome used in ou model is intoduced. 3.1 Kano Model A custome model was poposed fo quality management by Kano [8]. This model categoizes quality attibutes into five kinds of elements accoding to custome : attactive quality element, one-dimensional one, must-be one, indiffeent one, and evese one. Figue 3 illustates the fist thee quality elements out of the five. Hoizontal axis indicates the state of physical fulfillment on a paamete. Attactive quality elements influence little to custome, even if they ae not fulfilled physically. This is because the elements ae stongly expected. On the othe hand, must-be quality elements ae ecognized as mattes of couse, and thus makes geat dis once they ae little fulfilled. Non fullfillment Custome satisfied Attactive Quality Must-Be Quality Custome dissatisfied One- Dimensional Quality State of fulfillment Figue 3. Custome Satisfaction Model by Kano The weighting function epesents that individuals behave accoding to a psychologically biased pobability athe than its theoetical pobability. Individuals often misundestand the occuence pobabilities of phenomena, i.e., an individual expects the pefeable phenomenon in highe pobability than in its actual one when the pobability is vey low. 4 CUSTOMER SATISFACTION EVALUATION In this chapte, we popose a new evaluation method fo custome s. Fist, we define function called Satisfaction-Attibute Value function. This enables the designe to calculate of the eceive. Second, we popose an evaluation flow that uses the S-AV function. 4.1 Satisfaction - Attibute Value Functions We popose the "Satisfaction - Attibute Value (S-AV) function" in this section. The definition of the S-AV function ( ) is a bunch of mappings between (S FP ) of a eceive fo an RSP and FP values of a sevice (Equation 1). Hee, is expessed as a eal numbe fom -1 to 1. The designe can estimate of the eceive fo an RSP by using the S-AV function accoding to the value of FP. S losses S ( FPValue) gains Refeence Point Figue 4. Value Function of Pospect Theoy FP = (1) We defined the wod as change of an RSP accoding to the definition of sevice. The designe hadly knows the change of the RSP, which is an intenal state of a eceive. Howeve, the designe can estimate the change of the RSP fom changes of FPs, because the RSP is influenced by FPs. The value of FP is expessed in the fom of attibute value that is quantitative and visible by the designe. That is, the designe can estimate how the changes by changes of FPs by using the S-AV

3 419 function. A set of questionnaies to the eceives is used to decide the S-AV function. Details ae descibed in Chapte Expeimental Appaisal Impotance and Attention Impotance The fo the sevice is given by the weighted sum of fo each RSP. We assume that the weight is detemined by two classes of impotance, expeimental appaisal impotance and attention impotance. The fome is accumulated though epeat eceptions of a sevice and invesely popotional to the. The latte is used when the eceive evaluates afte eceiving the sevice. This impotance is popotional to the level of (o dis). We intoduce attention impotance to decide weight of a FP fo following evaluation steps. 4.3 Evaluation Steps [Step 1] Descibe in View Model In fist step, the designe has to descibe supposed sevice in view model. Above all, the designe should decide a pesona of the eceive. Pesona is a vitual chaacte of the eceive. Theefoe, to decide the pesona is just as same as to decide taget custome in maketing pocess. Descibing the sevice in the view model, the designe can decide RSPs that the eceive has and elationships between FPs and affected RSPs. [Step ] Decide Weight fo each FP Although a view model has a netwok stuctue of FPs, each FP does not influence equally on the RSP. Theefoe, to decide which FPs ae moe influential, the designe allocates weights to each FP. This step is done by the existing evaluation method using QFD and Dematel. [Step 3] Find S-AV Function fo each FP In thid step, setting S-AV functions on each FP, the designe can define elationships between about the RSP and each FP value. Namely, each FP has just one S-AV function. S-AV functions should be set on FPs placed at the end of the netwok stuctue. Instead of setting S-AV functions on these FPs, the designe can set on FPs that is affected by a few of these FPs. In this case, the designe needless to set S-AV functions on FPs that ae affected only by those aleady have S-AV functions. [Step 4] Set Attibute Paamete Values In this step, the designe configues supposed attibute value on FPs have S-AV functions. By setting attibute values, he/she becomes to be able to know supposed degee of given by each FP. [Step 5] Calculate Receive Satisfaction Finally, the designe can calculate eceive s fo the whole sevice. Satisfactions about each RSP ae given by following Equation. This equation means about RSP is given by weighted sum of S-AV functions. Hee, w FP is weight value obtained in Step. S () RSP = wfps FP Satisfaction fo the whole sevice is also calculated by the weighted sum of s fo RSPs, given by Equation 3. w RSP is the weight value given by the existing evaluation method fo allocating weight of each RSP using AHP. S (3) = w S RSP RSP This about the whole sevice is given as a eal numbe fom -1 to 1 as same as etun value of S-AV function. 5 FINDING S-AV FUNCTION In this chapte, we ague a concete method to find S-AV function defined and used in the pevious chapte. 5.1 Chaacteistics of the S-AV function S-AV function is one of so-called peceptions-minusexpectations models [11]. The basic ideas of these models ae that the eceive evaluates diffeence between the sevice expected and the sevice actually eceived. SERVQUAL [10], which is one of the famous evaluation methods fo sevice, is peception-minus-expectations model, too. Moeove, ou S- AV function has following chaacteistics fom the pospect theoy. Refeence Point Satisfaction is decided by diffeence between a sevice that the eceive expected and an actual sevice. Moeove, the expectation stongly depends on eceive s knowledge, expeience and othe pesonal factos. Theefoe, we match the efeence point to the pesonal diffeences in S-AV function. Using the concept of the efeence point, S-AV functions ae epesented by a combination of two functions connecting at an attibute value that the eceive expects. They ae called gain side function and loss side function espectively. Geneally, the eceive s expectation has two levels: desied and adequate [11]. The efeence point indicates an adequate level athe than a desied level. The ange fom the adequate level to the desied level is called zone of toleance. This means attibute values, which ae infeio to the adequate level, lead the eceive to dis. On the othe hand, attibute values exceed the adequate level satisfies the eceive. Loss Avesion Accoding to an expeiment of the pospect theoy, the eceive would judge it as loss and behave to avese loss, if an quality element of the sevice was wose than expected. Theefoe, the loss avesion featue in the pospect theoy is applicable to S-AV function. Howeve, this hypothesis involves a contadiction with the kano model, because loss at attactive quality does not cause dis accoding to the kano model. This contadiction is caused by diffeence of viewpoint. The value function in the pospect theoy discusses the whole value of a sevice. On the othe hand, the kano model agues a pat of a sevice. Accodingly, some pats of the sevice could be ignoed, even if actual qualities wee wose than expected. S-AV function has the same viewpoint as the kano model. Hence, we intoduce loss avesion featue only if the FP is categoized as One- Dimensional function. This means S-AV function has a constaint expessed as Equation 4. S ( a + b) < S ( a b) (4) + (a is magin fom the efeence point, b is attibute value on the efeence point)

4 40 Decease of Response Satisfaction fo a sevice geneally conveges if a functional pefomance was impoved to some extent. This tait is caused by the same psychological eason as the decease of esponse to value by inceasing gains o losses. Theefoe, the decease of esponse featue also can be applied. That is, the shape of S-AV function has a constaint expessed as Equation 5 and 6. If AV is bette than the efeence point, then d S < 0 (5) d( AV) If AV is wose than the efeence point, then d S > 0 (6) d( AV) 5. Classification of the S-AV function Applying Pospect Theoy, S-AV function obtained thee constaints fo its shape. Moeove, classifications of quality elements poposed by Kano model suggest futhe constaint to decide the shape of the S-AV functio. Hence, we intoduce Kano s thee quality elements to classifications of FPs as the following. Attactive Function If the FP is an attactive function, a decline in the functional pefomance will not be effect on the of the whole sevice. Theefoe, S-AV function on the FP has a constaint expessed as Equation 7. If AV is wose than the efeence point, then ( AV) = 0 (7) One-Dimensional Function The FP categoized as an one-dimensional function has no additional constaint except Loss Avesion mentioned befoe. Must-Be Function Likely as attactive function, if the FP is a must-be function, a functional pefomance exceeding eceive s expectation will not contibute to the fo the whole sevice. Theefoe, the S-AV function on the FP has a constaint expessed as Equation 8. If AV is bette than the efeence point, then ( AV) = 0 (8) Conside these constaints enumeated thus fa, the shape of S-AV functions ae to be constucted as Figue 5. Satisfaction AV Satisfaction AV Refeence Point Figue 5. Shapes of S AV Functions Satisfaction Attactive Quality One-Dimensional Quality Must-Be Quality AV 5.3 Deciding the S-AV function To calculate numeical, a concete numeical equation needs to be decided. Howeve, how pecise the numeical paametes of the equation ae less impotant, because the shape of function has lage decisive magnitude fo value itself. Accodingly, the shape of the function has to be decided caefully though the esult of maket suvey and use test on taget segment. In this section, we popose a simple method to decide appoximate S-AV function in the fom of numeical equation needed to calculate a numeical value. Hee, we epesent each side of the S-AV function using an exponential function expessed by Equation 9. b ( vc) = a S a 1 e (9) slope b a c v Figue 6. Shape of Appoximate Function In the equation, paamete a means the conveged maximum, paamete b means the slope at the efeence point, and paamete c means the attibute value at the efeence point. Vaiable v is an input value of this function that means attibute values. Figue 6 shows the shape of this function. We selected this appoximate function in the point of easiness to set the paamete values and capability in satisfying the constaints by the shape. An S-AV function is constucted with two exponential functions that have diffeent paamete values. If the FP is categoized as an attactive o a must-be function, it should be set unde the ule of Equation 7 o 8 espectively. In the following pat of this chapte, let us discuss the simplified method to decide an S-AV function using these exponential functions individually by categoies of FP. Attactive Quality Function The designe has to detemine two sides of functions. A function fo attibute values exceeding the efeence point is called gain side. Anothe function, which is infeio to the efeence point, is called loss side. If the FP is categoized as an attactive function, only the gain side function needs to be decided, because the value of the loss side function is always zeo (Equation 7). To keep consistency with one-dimensional quality element agued below, assume that an attactive function can povide 0.5 as the value at the maximum. Geneally, an attactive function is the eceive s need that is not yet geneally ecognized, so that we decided maximum povided by the best attibute value available in the maket as 0.4, leaving buffe to futhe. Thus, the designe can decide paametes of Equation 9 by setting paamete c to eceive expected attibute value, paamete a

5 41 to 0.5 and paamete b to satisfy maximum attibute value in the maket. One-Dimensional Function If the FP is categoized as one-dimensional function, the designe stat with the side that has the ange of attibute value available in the maket is wide. The function of this side is decided as the same method as attactive quality. Except the point if this side is the loss side, the minimum value at the wost attibute value is decided as Accoding to the loss avesion featue in the pospect theoy, the absolute value in the loss side is twice as lage as one in the gain side. It is empiically known that the magnitude of dis by losses is to.5 as much as it of by gains [9]. Seconday, the designe wok on with the othe side. As same as the fist side, the designe set a pai of an attibute value and a value. In this side, we use the attibute value that its distance fom the efeence point is as much as the maximum / minimum attibute value in the maket used in pevious step. The value at this attibute value is decided unde the same ule as pevious step, would be 0.4 o -0.8.Thus, the combination of these two functions constucts the S-AV function. Must-Be Function Stategy to decide S-AV function fo a FP of must-be function is the same as above two kinds. Namely, decide value at the minimum attibute value in the maket to The gain side function is expessed as Equation 8. By using above methods, the designe becomes to be able to decide S-AV function as the concete numeical equation. 6 APPLICATION TO AN EXAMPLE 6.1 Doo-to-doo pacel delivey sevice To veify the poposed method, we pefomed an expeiment settled on doo-to-doo pacel delivey sevices. We conducted a suvey and descibed the sevice on the view models. We focused on edelivey pat of the sevice and listed fou RSPs: flexibility of edelivey, in advance notification of pacel aival, delive pacel in safety and accept changes of addess o time fo delivey flexibly. Related FPs fo each RSP ae listed as shown in Table 1. Table 1. List of RSPs and FPs (patial) RSP FP Flexibility of (a) ealiest edelivey hou edelivey (b) latest edelivey hou (c) Max. to keep pacel (in the cente) (d) Fastest edelivey time fom ode 6. Method We decided the S-AV function by using a questionnaie about one of the RSPs "flexibility of edelivey. Respondents ae peson living alone o whose family going out on daytime (n=8). We pepaed questions fo each FP as shown in Table based on a method that Enze had impoved [1] the oiginal Kano method [8]. Additionally, we conducted conjoint analysis to the espondents in ode to make a compaison with ou method. Fo conjoint analysis, we pepaed fou sevices that have diffeent attibutes, is shown in Table 3. The espondents wee asked to ode the A-D. Also, AHP [] analysis was conducted to find out impotance of FPs. Table. Questions about (A) expectation and (B) kano class 1. ealiest edelivey hou (A) Which do you 1. befoe 6 AM. 6 AM 3. 7 AM think is the neaest 4. 8 AM 5. 9 AM AM quality you expect? 7. afte 10 AM (B) What do you 1. An ealie option must be available feel if actual quality. An ealie option is pefeable would be diffeent 3. It s all well and good fom you expectation? 4. I wouldn't mind Table 3. Pofiles fo conjoint analysis A B C D Attibute (a) Ealiest edelivey 6 AM 6 AM 9 AM 9 AM hou (b) Latest edelivey hou 7 PM 11PM 7 PM 1 AM (c) Max. to keep pacel (d) Fastest edelivey time fom ode Result m 6 h 6 h h 6.3 Result Table 4 shows the questionnaie esult. Each data in the table is the mode value of effective answes. Table 4. Classifications of FPs and Expectations fo FPs FP Ealiest Latest edelivey edelivey hou hou Max. to keep pacel Fastest edelivey time fom ode Class A 1 O O O Expectation 8 AM 10 PM 11 1h 10m + 3 Conjoint 4.1% 0.15% 14.10% 41.63% imp. AHP imp Attactive function. One-Dimensional function 3. Longe than 11 Table 5. Result of S-AV function evaluation A B C D (a) (b) (c) (d) Satisfaction fo RSP 1 S-AV ank Conjoint ank Weighted sum of using AHP impotance in table 4. Soted by fo RSP

6 4 Moeove, S-AV functions wee descibed based on expectation in Table 4 (Figue 7). Hoizontal axises show attibute value, and vetical axises show. Each shape of S-AV functions was decided by question B in table. The ange of attibute value was decided by an actual sevice. Although the ealiest edelivey hou of the actual sevice was 8 AM, we used 6 AM as the best ealistic attibute value. Latest edelivey hou of an actual sevice is 9 PM. Theefoe, the ange was assumed 9 AM 11 AM. Maximum to keep pacel of the actual sevice ae 90. Table 5 shows the esult of evaluation using S-AV functions in Figue 7. In this evaluation pocess, we used AHP method to decide impotance of FP to peseve independence fom conjoint analysis ( v 11) = e ( v 11) ( v+ S 70) = e ( v 70) { ( v+ S = 11) e }( v 11) { ( v+ S 70) = 1 e } ( v 70) (c) Max. to keep pecel (d) Fastest edelivey time fom ode Figue 7. S-AV function examples 6.4 Discussions 6 (hou of day) { 0.8( v+ 8) } = e ( v 8) = 0 ( v 8) (a) ealiest edelivey hou { } Compaison with the conjoint analysis The S-AV ank in table 5 was equal to the esult of the conjoint analysis. Moeove, ou method is supeio to the conjoint analysis in thee points: Fee fom limitations of the conjoint analysis: numbe of pofile and numbe of attibute. Shows not only ank but also degee of Less dependent on questionnaies, because S-AV functions can be eused. Individual diffeences in questionnaie esult In this example, we used the mode value to extact the epesented value. Howeve, the vaiance of each question was diffeent: the vaiance of expectation of (c), (d) was lage than (a), (b). This infomation could be used to categoize espondents and make anothe pesona. If anothe pesona was made, the S-AV function in Figue 7 would be changed and the evaluation would esult diffeently () (hou of day) -0.8 {.3( v ) } { 1.6( v+ 1 ) } = e ( v ) = e ( v ) (b) latest edelivey hou { } (min) 7 CONCLUSION This pape poposed a model fo sevice designes to calculate of the sevice eceive. The designe assumes the eceive s by his expectation fo each function. Using the model, the designe calculates fom the concete attibute values that epesent popeties of each function in actual sevice. By applying the method to an example, it was poved effective and possible to pedict the changes of quantitatively when the designe changes attibute values on some FPs. Moeove, the method enables the designe to know diffeences of each eceive cleae than conjoint analysis. This allows the designe to popose moe efficient and value-added impovement policies. Futue woks include claifying how the eceive changes impotance fo each RSP by eceiving sevice epeatedly. Besides, we will intoduce a concept of cost to the method and getting up to eal sevice eceive. Refeences: [1] Y. Shimomua, T. Tomiyama, Modeling fo Engineeing, In IFIP Intenational Fedeation fo Infomation Pocessing, Vol. 167, (ISSN (Pape) (Online)), pp , Spinge Boston, 005. [] T.L. Saaty: The Analytic Hieachy Pocess, 1980, McGaw-Hill. [3] Y. Akao: Quality Function Deployment, Poductivity Pess, Cambidge, Massachusetts, [4] Manasseo G., Semeao Q. and Tolio T., A New Method to Cope with Decision Makes' Uncetainty in the Equipment Selection Pocess, Annals of the CIRP, 53/1:389-39, 004. [5] Aai T, Shimomua Y. CAD System - Evaluation and Quantification. Annals of the CIRP, 005; 54-1: [6] K. Albecht, The Only Thing That Mattes : Binging the Powe of the Custome into the Cente of You Business, Collins, [7] B.H. Schmitt, Expeiential Maketing : How to Get Customes to Sense, Feel, Think, Act, Relate, Fee Pess, [8] N. Kano, N. Seaku, F. Takahashi, S. Tsuji, Attactive Quality and Must-Be Quality, Quality, Vol. 14, No., pp.39-48, the Japan Society fo Quality Contol, [9] D. Kahneman, A. Tvesky, "Pospect Theoy: An Analysis of Decision unde Risk", Econometica, XVLII, pp.63-91, [10] A. Paasuaman, V.A. Zeithaml, L.L. Bey, SERVQUAL: A Multiple-Item Scale fo Measuing Consume Peceptions of Quality, Jounal of Retailing, Vol. 64, No. 1, pp.1-40, [11] A. Paasuaman, L.L. Bey, V.A. Zeithaml Undestanding Custome Expectations of, Sloan Management Review, 3:3, pp.39-48, [1] M. Enze, K. Kopp, Application of Kano Model to Life Cycle Design, Poceedings of EcoDesign003: Thid Intenational Symposium on Envionmentally Conscious Design and Invese Manufactuing Tokyo, Japan Decembe 8-11, 003, pp , 003.