A novel Bass-type model for product life cycle quantification using aggregate market data

Guo, Xuezhen

doi:10.1016/j.ijpe.2014.07.018

Cited by 19 publications

(10 citation statements)

References 59 publications

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“…Guo [24] used aggregate market data in Bass Modeling to provide a distinct, dynamic, and local perspective on consumer purchasing behavior across the entire life cycle of a product. Similarly, in the course of our research, we performed a case study where complete seasonal data for fashion sandals was recorded and variables of attention, fitting and sales were used to establish the LCA model for fashion sandals.…”

Section: Discussionmentioning

confidence: 99%

“…Further, several types of algorithms were proposed to fit the curves of sales [21,22]. For instance, the Comperz Model [8] was used to predict daily consumption of products; while those with a shorter life cycle might be assessed by the Bass or Modified Bass Model [6,23,24]. Thereby, according to the LCA, retailers can master the rhythms of the product and make as much profit as possible.…”

Section: Introductionmentioning

confidence: 99%

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Bass-Modeling for Fast Fashion Lady's Shoes Based on Consumer Behavior

Keyu¹,

He²,

Liang³

et al. 2019

LFJ

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BASS-MODELING FOR FAST FASHION LADY'S SHOES BASED ON CONSUMER BEHAVIOR ABSTRACT. Fast fashion is prevalent in the retail industry, however, plotting its life cycle becomes problematic as that feedback from sales record is even considered to be late for them. So, variables in the process of consumer behavior are potential ones for life cycle assessment of fast fashion products. Currently, most studies of Bass model chose the sales data, but whether the Bass model can also be applied for those in consuming process has not been evaluated; meanwhile, if the modeling based on consumer behaviors such as attention and fitting are available, we can project forward in time and make predictions much earlier than those based only on sales. Therefore, we developed a special system and it was used to collect the attention and fitting records. Our results show that only moderate Bass-fitting results were found for individual-level data; while, good to excellent results could be obtained for the accumulated data. Further, a moderate to good correlation was found between the sales and attention on one hand, and sale and fitting on the other. Regression models including Bass Model equations could be applied to predict the sales by either the attention or the fitting data. Overall, variables of consumer behavior, such as attention and fitting, were found to be suitable for Bass Modeling; further they were found to be good indicators to predict sales. These efforts advanced the time required to predict the sales trend of fast fashion sandals and make the predictive protocols more reliable. KEY WORDS: LCA, RFID, attention-fitting-buying model, attention and fitting, off-line retailing MODELUL BASS APLICAT ÎN CAZUL PANTOFILOR DE DAMĂ ÎN REGIM DE MODĂ RAPIDĂ PE BAZA COMPORTAMENTULUI CONSUMATORILOR REZUMAT. Moda rapidă este predominantă în industria de vânzare cu amănuntul, însă, trasarea ciclului său de viaţă devine problematică, întrucât feedback-ul provenit din înregistrările de vânzări este considerat întârziat în acest caz. Aşadar, variabilele în comportamentul consumatorului sunt variabilele potenţiale pentru evaluarea ciclului de viaţă al produselor de modă rapidă. În prezent, majoritatea studiilor care utilizează modelul Bass au selectat datele din vânzări, dar nu s-a analizat dacă modelul Bass poate fi aplicat şi în cazul procesului de consum; în acelaşi timp, dacă modelele bazate pe comportamentele consumatorilor sunt disponibile, cum ar fi atenţia şi potrivirea, putem proiecta în timp şi face predicţii mult mai timpuriu decât doar pe baza vânzărilor. Prin urmare, s-a dezvoltat un sistem special şi a fost utilizat pentru colectarea înregistrărilor privind atenţia şi potrivirea. Rezultatele noastre arată că s-au găsit doar constatări moderate utilizând modelul Bass pentru datele la nivel individual, în timp ce rezultate bune şi excelente s-au obţinut pentru datele acumulate. Mai mult, s-a găsit o corelaţie moderată până la bună între vânzări şi atenţie pe de o parte, şi între vânzare şi potrivire pe de altă parte. Modelele de ...

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bass-Modeling for Fast Fashion Lady's Shoes Based on Consumer Behavior

Keyu¹,

He²,

Liang³

et al. 2019

LFJ

View full text Add to dashboard Cite

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“…However, as the Bass model was developed for product categories, it needs to incorporate the competition effect in order to study the market de-mand of individual brands. Furthermore, the market performance of a new product can be exposed to many influences, such as marketing-mix ( Danaher et al, 2001 ), technological advances ( Jiang and Jain, 2012 ), seasonal effect ( Radas and Shugan, 1998 ), crosscountry issues ( Putsis et al, 1997 ), and repeated purchase ( Guo, 2014 ). This complexity can be further increased by the coupling and dynamics of those influences.…”

Section: Introductionmentioning

confidence: 99%

Understanding New Products’ Market Performance Using Google Trends

Chumnumpan

Shi

2019

Australasian Marketing Journal

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This paper seeks to empirically examine diffusion models and Google Trends' ability to explain and nowcast the new product growth phenomenon. In addition to the selected diffusion models and Google Trends, this study proposes a new model that incorporates the two. The empirical analysis is based on the cases of the iPhone and the iPad. The results show that the new model exhibits a better curve fit among all the studied ones. In terms of nowcasting, although the performance of the new model differs from that of Google Trends in the two cases, they both produce more accurate results than the selected diffusion models.

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“…Life cycles of conventional market products have traditionally been studied extensively in the scientific literature (see evolution, for example, in Catry & Chevalier versus Guo ). There is some consensus that normally, a product subjected to demand has a growth phase (after its release), a mature stage (where the product can be consolidated in the market) and a final decline phase (when the product loses its appeal against the competition or becomes obsolete and is replaced by another or when it is no longer profitable for its seller).…”

Section: Introduction: Spanish Tourism Policies In the 1960smentioning

confidence: 99%

Geographic Information System (GIS) Analysis of Impacts in the Tourism Area Life Cycle (TALC) of a Mediterranean Resort

García-Ayllón

2015

Journal of Tourism Research

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Tourism in Spain has evolved from being a residual sector in the economy during the 1950s to become at present the main source of wealth in the country. The Spanish Law of Centres and National Tourist Interest Areas of 1963 created numerous new resorts on the coast whose life cycle is now over 50 years. On the Mediterranean coast, urban development and tourism model processes have been developed with major feedback to each other. In this context, it is particularly interesting to evaluate the results obtained since the decade of the 1960s in order to achieve sustainable tourism. This paper analyses a paradigmatic case study located on the Spanish Mediterranean coast. A diagnosis that explains the evolution of the life cycle tourist destination as a consumer product is carried out using geographic information system analysis of the urban plot. The mutation of the target customer, the real estate overcrowding, or the seasonality of demand will be the variables to be evaluated in order to assess the final return of the managed product. Copyright © 2015 John Wiley & Sons, Ltd.

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A novel Bass-type model for product life cycle quantification using aggregate market data

Cited by 19 publications

References 59 publications

Bass-Modeling for Fast Fashion Lady's Shoes Based on Consumer Behavior

Bass-Modeling for Fast Fashion Lady's Shoes Based on Consumer Behavior

Understanding New Products’ Market Performance Using Google Trends

Geographic Information System (GIS) Analysis of Impacts in the Tourism Area Life Cycle (TALC) of a Mediterranean Resort

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