1. June 23, 2000(C) Masataka Yamada1 Anticipatory (Eagerly-awaited) Good/Service: Estimating Sales Patterns of Music CDs by Weibull Distribution Model Masataka Yamada Kyoto Sangyo University myamada@cc.kyoto-su.ac.jp Ryuji Furukawa Evergreen Japan Corporation r.furukawa@evergreen-japan.co.jp Hiroshi Kato Iihara Management Institute JDX01156@nifty.ne.jp Marketing Science Conference 2000, UCLA FR-A4, 9:00-10:30

2. June 23, 2000(C) Masataka Yamada2 1 Introduction From diffusion theory point of view, we define anticipatory (eagerly-awaited) good/service for one of products that indicate rapidly penetrating sales curves to give marketers new strategic implications. We pick up CD album as one of the anticipatory goods. Then, we test the hypothesis that the diffusion pattern of an anticipatory good/service is a rapidly penetrating one.

3. June 23, 2000(C) Masataka Yamada3 1 Introduction (continued) Second, we found that the diffusion patterns of anticipatory goods are much sharper than those of first purchases of groceries comparing the goodness of fit between Bass diffusion model and Weibull distribution model on the sales data of music CDs. Hence, those goods indicating sharper diffusion curves can be identified as anticipatory goods. Finally, we consider marketing strategy of new product introductions for anticipatory goods.

4. June 23, 2000(C) Masataka Yamada4 1.1 Classification of Products in Marketing Before we proceed to anticipatory good/service, we would like to review conventional product classifications. What is a product? A product is anything that can be offered to a market for attention, acquisition, use, or consumption that might satisfy a want or need. It includes physical objects, services, persons, places, organizations, and ideas (P. Kotler, 1988).

5. June 23, 2000(C) Masataka Yamada5 Physical products: automobiles, toasters, shoes, eggs and books Services (Service Products): haircuts, concerts, and vacations Persons: Barbra Streisand, we give her attention, buy her records, and attend her concerts Places: Hawaii can be marketed, in the sense of either buying some land in Hawaii or taking a vacation there.

6. June 23, 2000(C) Masataka Yamada6 Organizations: The American Red Cross can be marketed, in the sense that we feel positive toward it and will support it. Ideas: family planning, safe driving

7. June 23, 2000(C) Masataka Yamada7 Three Levels of Product Core Product: what is the buyer really buying? Core benefit or service Tangible Product: a quality level, features, styling, a brand name, and packaging. Augmented Product:delivery and credit, installation, after sale service, and warranty.

8. June 23, 2000(C) Masataka Yamada8 Some Examples of Product Classifications Nondurable goods, Durable goods and Services based on their durability or tangibility.

9. June 23, 2000(C) Masataka Yamada9 Consumer goods classification Consumer goods are classified on the basis of consumer shopping habits because they have implications for marketing strategy:

10. June 23, 2000(C) Masataka Yamada10 Industrial goods classification Industrial goods can be classified in terms of how they enter the production process and their relative costliness: Materials and Parts Supplies and Services Raw Materials Manufactured materials and parts Capital Items Installations Accessory equipment Supplies Business services

11. June 23, 2000(C) Masataka Yamada11 What is the purpose of product classifications? Marketers believe that each product type has an appropriate marketing-mix strategy. Or it gives marketers implications for marketing strategy.

12. June 23, 2000(C) Masataka Yamada12 An approach to Product Classification from Diffusion Theory of New Product We would like to add another approach to classify product for the decision making of marketing strategy from diffusion theory of new products.

13. June 23, 2000(C) Masataka Yamada13 2 Past Researches of Diffusion Patterns of New Products Fourt and Woodlock (1960), q=0, Exponential Curve, Grocery Products Mansfield (1961), p=0, Logistic Curve, Industrial Products Bass(1969), combined the above two Lekvall and Wahlbin (1973) Gatignon and Robertson (1985), 29 propositions Bayus(1993), Consumer Electronics and Electric Appliances Sawhney And Eliashberg (1996), Movies Patterns can be regarded as being continuous from S- shaped ones to J-shaped ones.

14. June 23, 2000(C) Masataka Yamada14 Correspondence between Bayus' Segments and the Classes ( The original data are taken from Table 5 on p. 1329, Bayus 1993 and all in the US market ) (1) fast initial growth with sales peaking quickly (segment #1) (2) a long introduction growth period (segment #4) * = Three Basic Patterns (3) a moderate introduction and growth period, with differences primarily in the market potential size (segment #2, #3, and #5)

15. June 23, 2000(C) Masataka Yamada15 (made from Table 1 on p. 123, Sawhney and Eliashberg 1996)

16. June 23, 2000(C) Masataka Yamada16 Our Classification Method of Diffusion Patterns Yamada, Masataka, Ruji Furukawa and Mamoru Ishihara (1997) Mahajan, Vijay, Eitan Muller and Rajendra K. Srivastava (1990)

17. June 23, 2000(C) Masataka Yamada17

18. June 23, 2000(C) Masataka Yamada18 Bass Continuous Time Domain Diffusion model Noting that we invented the following classification method and class map.

19. June 23, 2000(C) Masataka Yamada19 A Typical Pattern for the Respective Class

20. June 23, 2000(C) Masataka Yamada20 Class Map with Iso-Peak Time Curves

21. June 23, 2000(C) Masataka Yamada21 Table 1 Classification Criteria for Diffusion Patterns Class TimingLower bound p/q I 0 < < II< p/q < III< p/q < 1.000 IV 1.000 < p/q < V< < Upper bound

22. June 23, 2000(C) Masataka Yamada22 3 Adoption and Diffusion Process of New Product Announcement Awareness Introduction Knowledge Attitude Decision (Intension) Action (Adoption) Perceived Risk Marketing Mix Setting Marketing Mix Adjustment : things that influence indivisual person's adoption decision : things that firms influence indivisual person's adoption decision or things that are given Note that this conceptual model is made to answer the question why different diffusion patterns from S-shaped curve to J-curve exist. Initial Value (Attractiveness)Information, Involvement Value (Attractiveness) at the time of its adoption decision ∝ Initial Value ( Attractiveness) / Perceived Risk Time to act from its adoption decision ∝ 1 / Value (Attractiveness) at the time of its adoption decision Speed of Supply Response: Product, Manufacturing, Distribution, Cyberspace Personality and Attributes: Five categories of Rogers, Lifestyle Inventory of Similar Products, Existence of competing product categories Product CharacteristicsMarket Characteristics

23. June 23, 2000(C) Masataka Yamada23 3 Adoption and Diffusion Process of New Product Note that this conceptual model is made to answer the question why different diffusion patterns from S-shaped curve to J-curve exist. Announcement Awareness Introduction Knowledge Attitude Decision (Intention) Action (Adoption) Initial Value (Attractiveness) Perceived Characteristics of Innovativeness: (1) Relative Advantage, (2) Compatibility, (3) Complexity, (4) Trialability, (5) Observability. Price Excitement / Innovativeness Country, Region, Organization, Firm Brand Popularity: Director, Star, Producer, Songwriter, Composer, Artist Series, Junior Marketing Mix Setting Information, Involvement Word-of- mouth Communications Review, Publicity Advertisement Tie-up with multiple media Price decreasing Sample offering Marketing Mix Adjustment Perceived Risk Value (Attractiveness) at the time of its adoption decision ∝ Initial Value ( Attractiveness) / Perceived Risk Time to act from its adoption decision ∝ 1 / Value (Attractiveness) at the time of its adoption decision Speed of Supply Response: Product, Manufacturing, Distribution, Cyberspace Personality and Attributes: Five categories of Rogers, Lifestyle Inventory of Similar Products, Existence of competing product categories Product CharacteristicsMarket Characteristics : things that influence individual person's adoption decision : things that firms influence individual person's adoption decision or things that are given Skip

24. June 23, 2000(C) Masataka Yamada24 Back

25. June 23, 2000(C) Masataka Yamada25 Back

26. June 23, 2000(C) Masataka Yamada26 Value (Attractiveness) at the time of its adoption decision Initial Value ( Attractiveness) / Perceived Risk Back

27. June 23, 2000(C) Masataka Yamada27 Time to act from its adoption decision 1 / Value (Attractiveness) at the time of its adoption decision Back

28. June 23, 2000(C) Masataka Yamada28 Speed of Supply Response: Product, Manufacturing, Distribution, Cyberspace Personality and Attributes: Five categories of Rogers, Lifestyle Inventory of Similar Products, Existence of competing product categories Product CharacteristicsMarket Characteristics Back

29. June 23, 2000(C) Masataka Yamada29 4. Anticipatory (Eagerly-awaited) Good/Service Episode: Tickets for the national singer, Hikaru Utada’s first whole country concert tour are put on sale on April 22, 2000 and all of 70,000 seats are sold out within 90minutes. Also the sales of her new single “Wait and See~Risk~” have already exceeded 1.3 million CDs within first three days after its introduction. Her popularity seems to stop nowhere. (ZAX 4/23/00).

30. June 23, 2000(C) Masataka Yamada30 4.1 Definition ： An anticipatory (Eagerly-awaited) good/service is anything that can be offered to a market for attention, acquisition, use, or consumption that might satisfy an anticipatory want or need.

31. June 23, 2000(C) Masataka Yamada31 Examples: Computer software (Windows95), TV Game software (Final Fantasy), Movies with Celebrated Stars/Director (Terminator 2), Music CDs with Famous Artist/Group (Hikaru Utada).

32. June 23, 2000(C) Masataka Yamada32 Properties ： 1. High Value: Consumers want it eagerly and obtain it anyway when it becomes available because they like it. They may be fans, admirers, and the like. 2. Intensive Information Search: Consumers are willing to make great efforts to search for information about its content, available time and date, etc., to travel for obtaining it and so on. Often times, there are abundant supply of its information through firms’ marketing efforts.

33. June 23, 2000(C) Masataka Yamada33 Properties (continued) ： 3. Low Risk: Consumers basically like it because of their satisfaction with its previous version. Therefore, they have very little perceived risk on it. They anticipate the same or more level of satisfaction than before. 4. Low Risk: It should be reasonably priced so that consumers can tolerate its unsatisfactory performance even if it happens to be the case. 5. It may have “out of stock” or “sold out” risk but for certain products such as music by internet may not have this risk at all and at the same time it offers instantaneous supply responses for consumers.

34. June 23, 2000(C) Masataka Yamada34 My favorite artist My favorite single in it Reasons for Album CD Purchases Impression through TV, Radio and Stores From http://www.ongakudb.com/

35. June 23, 2000(C) Masataka Yamada35 4.2 Hypothesis Anticipatory good/service should take a rapid penetration diffusion pattern (Class V).

36. June 23, 2000(C) Masataka Yamada36 Operational Hypotheses H1: The rate of CDs whose diffusion patterns are rapid penetration diffusion patterns within the album CDs is greater than that of the single CDs. H2: Sales pattern of unknown singer’s debut single CD (unanticipatory good) does not take a rapid penetration diffusion pattern.

37. June 23, 2000(C) Masataka Yamada37 Operational Hypotheses(continued) H3: The sales patterns of the debut singles of new groups and singers who are produced through a well designed process such as “ASAYAN” contest program of TV Tokyo are rapidly penetrating ones. The cases of the debut singles of “Sun and Cisco-moon,” Ami Suzuki and “Morning Girls” are analyzed.

38. June 23, 2000(C) Masataka Yamada38 Data Used Authorized dealers of manufacturers, wholesaler-related stores, and mail order companies and companies for business uses are sharing the distribution channels of music CDs and records by 45%, 50%, and 5% respectively(Recording Industry in Japan 1999, Recording Industry Association of Japan 1999). Our data are the sales data of music CDs sold at one of national chains of convenience stores obtained through Iihara Management Institute, related to one of the major wholesalers, Seikodo(http://www.seikodo.co.jp/index.html).http

39. June 23, 2000(C) Masataka Yamada39 Some Details of Convenience Stores Usually convenience stores start to sell new CDs from 3pm on the day before the officially announced sales date by manufacturers. They generally open stores for 24 hours. The original data are disguised for proprietary reasons and the day before the announced sales date is treated as a one half day duration for our computation. Period for data collection:10/14/97-7/09/99 Number of CDs: 256 Number of data points: 56 days (eight weeks)

40. June 23, 2000(C) Masataka Yamada40 4.3 Results for Hypotheses Testing H1: The rate of CDs whose diffusion patterns are rapid penetration diffusion patterns within the album CDs is greater than that of the single CDs. The rate for album CDs: P 1 =119/121=0.983 A001 97/11/11 MAX4 Omnibus Western Music A009 97/12/11 Nobuteru Maeda HARD PRESSED The rate for single CDs: P 2 =135/153=0.882 H 0 can be rejected at F(3.5315)=0.999793

41. June 23, 2000(C) Masataka Yamada41 A Typical Rapid Penetration Curve We learned that albums can be regarded as anticipatory goods by almost 100%. Because A001 is an omnibus CD which does not have any particular artist, and A009 seems to demonstrate basically a rapid penetration pattern.

42. June 23, 2000(C) Masataka Yamada42 H2: Sales pattern of unknown singer’s debut single CD (unanticipatory good) does not take a rapid penetration diffusion pattern. We have only two unknown singers’ debut single CDs in our data. Their patterns are shown below:

43. June 23, 2000(C) Masataka Yamada43 H3: The sales patterns of the debut singles of new groups and singers who are produced through a well designed process such as “ASAYAN” contest program of TV Tokyo are rapid penetration ones. The cases of the debut singles of “Sun and Cisco-moon,” Ami Suzuki and “Morning Girls” are tested.

44. June 23, 2000(C) Masataka Yamada44 Ami Suzuki(from ORICON data)

45. June 23, 2000(C) Masataka Yamada45 “Morning Girls” (from ORICON data)

46. June 23, 2000(C) Masataka Yamada46 5. Model Fitting on CD Sales Data for Further Investigations and Model Finding for Better Forcasting Almost all the sales patterns seem to be taking rapid penetration curves by eye-ball inspection. Usually exponential model is fitted on this type of data. Note that exponential model is a special case of Bass diffusion model when the internal influence parameter, q, is zero. Also Weibull distribution model is fitted because of its better performance for the first several data points.

47. June 23, 2000(C) Masataka Yamada47 Weibull Distribution Weibull two parameter probability distribution function of adoption time (t) is given as follows: F t (t )=1-EXP (-(t/ ) c ), t >0 c: shape parameter, : scale parameter Let the potential market size be m, then the cumulative number of adoptions at the end of time t, Y t, can be given as below: Y t =m F t (t) Note for managerial convenience that when t=, regardless of the value of c, F t (t= )=1-EXP(-1)=0.63

48. June 23, 2000(C) Masataka Yamada48 Weibull Distribution(continued) In order to compute cumulative unit sales:Y 1, Y 2, Y 3,,, unit sales from t=0 to t=0.5, S 1, unit sales from t=0.5 to t=1.5, S 2, unit sales from t=1.5 to t=2.5, S 3,,, are summed up accordingly and respectively. Let t be an error, then our model becomes as follow: Y t =m F t (t )+ t, where, t ~N (0, 2 ) is assumed. PROC NLIN of SAS is used for the parameter estimation.

49. June 23, 2000(C) Masataka Yamada49 Adjusted R 2 : We did not use these criteria. Because we found that the following graphs better demonstrate the respective model performance. AIC: Model Selection Criteria

50. June 23, 2000(C) Masataka Yamada50 0.0 10.0 20.0 30.0 40.0 50.0 11121314151 ALBUM: Average Absolute Percentage Errors, n=121 t=day Average of e t 's (%) Bass Weibull e t =100*|Y t - y^ t |/Y t Y t =Cumulative Sales at t y^ t =fitted value for Y t Absolute Percentage Error:

51. June 23, 2000(C) Masataka Yamada51

52. June 23, 2000(C) Masataka Yamada52 median

53. June 23, 2000(C) Masataka Yamada53 Weibull Model fits better than Bass Model on the Music CD Sales Data This implies that diffusion patterns of anticipatory goods take much sharper pattern, especially during first few periods, than grocery goods whose first purchase sales patterns are generally believed to be exponential curves (Fourt and Woodlock (1960)).

54. June 23, 2000(C) Masataka Yamada54 Distribution of c (shape parameter) Stem Leaf # Boxplot 9 77 2 | 9 02233 5 | 8 559 3 | 8 000111222333344 15 | 7 55666666889999 14 +-----+ 7 000001112222334 15 | + | 6 556666677777777888889999 24 *-----* 6 00111112222334444 17 +-----+ 5 6666777789999 13 | 5 000113 6 | 4 589 3 | 4 ----+----+----+----+---- Multiply Stem.Leaf by 10**-1 mean= 0.697066, median=0.684119, N=117

55. June 23, 2000(C) Masataka Yamada55 Stem Leaf # Boxplot 9 0 1 * 8 8 2 1 * 7 7 1 1 * 6 5 1 * 6 5 5 3 1 * 4 5 1 0 4 4 1 0 3 9 1 0 3 0044 4 0 2 55579 5 | 2 00112222334 11 | 1 5555556667777888888899999 25 +--+--+ 1 0000011111222222233333444444444444 34 *-----* 0 556666777778888888999999999 27 +-----+ 0 244 3 | ----+----+----+----+----+----+---- Multiply Stem.Leaf by 10**+1 Distribution of alpha (scale parameter) mean=17.5, median=14.1, N=117

56. June 23, 2000(C) Masataka Yamada56 We proposed a new classification for product/service, namely, anticipatory good/service vs unaticipatory good/service from new product diffusion pattern perspective. We found that the diffusion pattern of anticipatory good/service takes the rapidly penetrating (J-shaped) pattern. We found that it can not be captured well by Bass diffusion (=exponential ) curve (ex. first purchase sales patterns of grocery goods). They are generally much sharper than those captured by Bass model. Hence, those goods indicating sharper rapid penetrating diffusion curves can be identified as anticipatory goods. Conclusions Therefore, diffusion strategy of new products for anticipatory good/service must be different from unaticipatory good/service.

57. June 23, 2000(C) Masataka Yamada57 Conclusions (continued) Marketing strategy for a new anticipatory good/service: (1) One should let consumers be involved from its development stage. Ex. (a) ASAYAN project of TV Tokyo; (b) use famous artists, movie stars, directors; (c) make it series etc. (2) Before the introduction of a new product, its promotion and publicity should be done as intensively and widely as possible into the target market. (3) The initial price should be set at the most reasonable level possible or free if possible.

58. June 23, 2000(C) Masataka Yamada58 Future Research Directions Analyze albums further. Analyze singles. Models for sales forecasts.

59. June 23, 2000(C) Masataka Yamada59 References Bass, Frank M. (1969), “A New Product Growth Model for Consumer Durables,” Management Science, Vol. 15 (January), 215-227. Bayus, Barry L. (1993), “High-Definition Television: Assessing Demand Forecasts for a Next Generation Consumer Durable,” Management Science, Vol. 39 (November), 1319-1333. Fourt, L. A. And Woodlock, J. W. (1960), "Early Prediction of Market Success for New Grocery Products," Journal of Marketing, Vol. 25 (October), 31-38. Gatignon, Hubert, Jehoshua Eliashberg and Thomas S. Robertson (1989), “Modeling Multinational Diffusion Patterns: An Efficient Methodology,” Marketing Science, Vol. 8, No. 3 (Summer), 231-247.

60. June 23, 2000(C) Masataka Yamada60 References(continued) Lekvall, Per and Clas Wahlbin (1973), “A Study of Some Assumptions Underlying Innovation Diffusion Functions,” Swedish Journal of Economics, 75,362-377. Mahajan, Vijay, Eitan Muller and Rajendra K. Srivastava (1990), “Determination of Adopter Categories by Using Innovation Diffusion Models,” Journal of Marketing Research, Vol. XXVII (February), 37-50. Mansfield, Edwin (1961), “Technical Change and the Rate of Innovation,” Econometrica, 29, October, 741-766. Sawhney, Mohanbir S. And Jehoshua Eliashberg (1996), “A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures,” Marketing Science, Vol.15, No. 2, 113-131.

61. June 23, 2000(C) Masataka Yamada61 References(continued) Yamada, Masataka, Ruji Furukawa and Mamoru Ishihara (1997) “A Classification Method of Diffusion Patterns with a Class Map,” ACTA HUMANISTICA ET SCIENTIFICA, UNIVERSITATIS SANGIO KYOTIENSIS, Vol. 28, No. 2, Social Science Series No. 14 (March), Kyoto Sangyo University, 59-82.