Determining Segmentation in Sales Response across Consumer Purchase Behaviors

Bucklin, Randolph E.; Гупта, Сунил; Siddarth, S.

doi:10.2307/3151847

Cited by 130 publications

(130 citation statements)

References 8 publications

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“…Hypothesis 3: The relationship between price and loyalty of the consumers of sportswear was confirmed and it is compatible with the results of Cadogan and Foster (2000) and Bucklin (1998).…”

Section: Resultssupporting

confidence: 79%

“…Price becomes a focal point in consumer judgment about the value of the product and their assessment of the value of the goods at retail shops (De Ruyter & Bloemer, 1999). According to Bucklin (1998), price can significantly influence the choice of the consumers and their purchase behavior. He also emphasized that price cuts and discounts accelerates the process of finding required products for the families and thus increases the chance for replacement of other brands.…”

Section: Pricementioning

confidence: 99%

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A study on relationship of brand characteristics and customer satisfaction with brand loyalty

Nasirabadi¹,

Bokaei²

2013

10.5267/j.msl

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Brands are considered as valuable assets of a company both economically and strategically. Thus, having customers who are loyal to a brand is one of the main goals of businesses companies. Identifying and anticipating the customers' needs are vital to the enterprises gaining competitive advantage and market segmentation. Maintaining and enforcing customers' loyalty is a strategic challenge for companies seeking to keep and promote their competitive status in the market. High brand loyalty of the customers generates competitive advantage for the company and it increases the income and decreases the costs of marketing. In addition to increasing the market share, loyalty allows to ask for higher prices compared with its competitors. This study seeks to investigate the factors influencing customer loyalty to sport brands. The statistical population of this research was Tehran city. Using simple cluster sampling, 502 customers of four known brand sports, i.e. Nike, Puma, Adidas, Reebok, and Fila were chosen. Furthermore, a questionnaire, which assessed seven variables including reputations, brand name, brand image, brand loyalty, customer satisfaction, promotion and the price was used and the hypotheses were analyzed using statistical tests such as KolmogorovSmirnov test (K-S test), Spearman correlation, simultaneous linear regression and binomial test. The findings suggested that the brand name has a strong correlation with brand loyalty. Moreover, variables such as reputation, brand image, customer satisfaction, price and promotions also have positive and significant effect on the brand loyalty.

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Section: Resultssupporting

confidence: 79%

Section: Pricementioning

confidence: 99%

A study on relationship of brand characteristics and customer satisfaction with brand loyalty

Nasirabadi¹,

Bokaei²

2013

10.5267/j.msl

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“…The first decomposition of sales effects, based on models of household data, is provided by Gupta (1988) who shows that the sales elasticity of a promotion equals the category incidence elasticity plus the brand choice elasticity plus the quantity elasticity. Chiang (1991), Chintagunta (1993) and Bucklin/Gupta/Siddarth (1998) provide additional empirical results based on alternative or enhanced model formulations and estimation methods. Bell /Chiang/Padmanabhan (1999) show that on average about 75 percent of the sales elasticity is attributable to the brand choice elasticity.…”

Section: Sales Promotion and Sales Promotion Modelsmentioning

confidence: 99%

How Promotions Work: SCAN*PRO-Based Evolutionary Model Building

Heerde

Leeflang

Wittink

2002

Schmalenbach Bus Rev

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We provide a rationale for evolutionary model building. The basic idea is that to enhance user acceptance it is important that one begins with a relatively simple model. Simplicity is desired so that managers understand models. As a manager uses the model and builds up experience with this decision aid, she will realize its shortcomings. The model will then be expanded and will lead to the increase of complexity.Evolutionary model building also stimulates the generalization of marketing knowledge. We illustrate this by discussing different extensions of the SCAN*PRO model. The purpose of published model extensions is to increase the knowledge about "how promotions work" and to provide support for more complex decisions. We summarize the generated knowledge about how promotions work, based on this process. JEL-Classification: M31.

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“…The truncated Poisson regression model is also used by Ailawadi and Neslin (1998) and Bucklin, Gupta and Siddarth (1998), among others. The purchase quantity probability is given by…”

Section: Purchase Quantitymentioning

confidence: 99%

“…As available inventory is typically not observed in commonly available scanner data, it is usually taken into account by postulating some underlying process. In the literature, a popular assumption is that the consumption rate of a household is constant over time, see Bucklin and Gupta (1992), Bucklin, Gupta and Siddarth (1998), Chintagunta (1993), Gupta (1988), Mela, Jedidi and Bowman (1998), Neslin, Henderson and Quelch (1985), among others. However, this convenient assumption might not always be appropriate.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Utility Maximization Model for Product Category Consumption

2002

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in A Dynamic Utility Maximization Model for Product Category ConsumptionAbstract It is conceivable that the "whether to buy" and "how much to buy" decisions in the purchasing process of households are influenced by the inventory process.In this paper we therefore put forward a model for consumption, where we rely on established economic theory. We incorporate this model in a model for purchase behavior. Our consumption specification, which is derived from utility maximization principles, is more flexible than an ad hoc approach, which has recently been proposed in the literature. We illustrate our model for yogurt purchases, and show that our model yields important additional and useful insights. One such insight is that promotion anticipation behavior turns out not only to occur in the purchasing process, but also in the consumption process.

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Determining Segmentation in Sales Response across Consumer Purchase Behaviors

Cited by 130 publications

References 8 publications

A study on relationship of brand characteristics and customer satisfaction with brand loyalty

A study on relationship of brand characteristics and customer satisfaction with brand loyalty

How Promotions Work: SCAN*PRO-Based Evolutionary Model Building

A Dynamic Utility Maximization Model for Product Category Consumption

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