Search results

The purpose of this paper is to examine two popular price promotion strategies – price matching guarantees (PMGs) and everyday low prices (EDLP) – and their effects on Chilean consumer behavior in terms of consumer perceptions of low prices, search behavior and purchase intention.

A quasi experiment with three scenarios was conducted to test price promotion effects. Subjects were instructed to respond a questionnaire that included the dependent variables.

Results show that EDLP and PMG strategies increase perceptions of low prices and affect purchase intentions. These effects are significantly higher for stores offering EDLP than PMG. However, when consumers are exposed to two or more price promotion strategies (rather than one) they reduce their purchase intentions for a specific store and increase their search intentions.

This is an initial study exploring the effects of price promotion strategies on consumers. Future research could test the hypotheses advanced in the study across different samples and contexts (supermarkets, department stores, convenience stores, and other retailers) and might privilege external validity, using experiments mimicking decisions with real consequences.

Retailers and marketers in Latin America – particularly those companies stressing price or value as their differential advantage – should consider the use of price promotions when designing marketing strategies. On the other hand, retailers should be aware that an intensive use of these of promotions could lead to increases in consumer search behavior.

While findings from the USA suggest that price promotion strategies can be effective in several contexts, there has been a limited number of studies addressing whether such strategies are effective in other countries, particularly in Latin America and emerging nations.

This article aims to estimate the relationship between brand loyalty and price promotions on the German yoghurt market. It considers consumer loyalty to various corporate brands and their respective sub-brands to analyze promotional strategies between and within certain corporate brands with a larger loyal consumer segment and a moderate strength of consumer loyalty are well suited for effective price promotions following the idea of loss leader by Lal and Matutes (1994).

The paper’s approach follows Allender and Richards’ (2012) and extends to explicitly considering the product line management of every manufacturer in the market. In the first step, a random coefficient logit specification is estimated to compute measures of brand loyalty for each brand. In the second step, the relationship between brand loyalty measures and the frequency and depth of price promotions is analysed.

The results suggest that weaker corporate brands are promoted more aggressively supporting the model hypotheses by Koças and Bohlmann (2008). Within the manufacturer’s product line, sub-brands with a larger loyal consumer segment and a moderate strength of consumer loyalty are more often used for effective price promotions which reflects the idea of loss leading first introduced by Lal and Matutes (1994).

The results are limited to a static relationship between brand loyalty and price promotions. Analyzing the dynamics of the relationship between brand loyalty and price promotions should prove fruitful in enhancing the understanding of retailer strategies and provides additional implications for managerial decisions in retailing.

Managers need to be more aware of the linkages between product line management and promotional strategies. Changes in the product line management may require a redirection of the promotional measures and strategies.

Consumer behavior with respect to brand loyalty to some extent determines price promotional strategies of retailers. The promotional strategies provide opportunities to save expenditures, especially for non-loyal and low income households.

Matching and analyzing two detailed (consumer, retail) scanner data sets to investigate the relationship between the measures of brand loyalty and the retailers’ price promotional strategies. Novel is the modeling of two different dimensions of brand loyalty (size and strength) and the consideration of sub-brands. The results clearly show that promotional strategies vary not only between corporate brands but also between sub-brands of the same corporate brand.

This paper investigates a dual-channel supply chain in which a manufacturer offers coupons in the online channel and the retailer in the offline channel. The optimal pricing and coupon promotion policies are explored, and the brand image under different promotion scenarios is studied.

Three differential game models, namely no coupon is offered, coupons offered by the manufacturer and coupons offered by the retailer, are constructed.

The results show that the manufacturer and retailer intend to conduct coupon promotions under a large coupon redemption rate. Coupon promotion derives a higher price and profit for the issuers, and the manufacturer can free-ride on the retailer's coupon promotion. The retailer's profit in the retailer-promotion scenario may be lower than that in the manufacturer-promotion scenario in some special conditions. Besides, price, coupon face value, brand image and profit increase over time. After multiple cycles game, the operational strategy evolves to an optimal equilibrium status.

This paper provides guidance and advice for dual-channel supply enterprises to implement joint pricing and coupon promotion strategies under multiple sales seasons.

The purpose of this paper is to capture the dynamic variations in sales of a product based upon the dynamic estimation of the time series data and propose a model that imitates the price discounting and promotion strategy for a product category in a retail organization. A modest attempt has been made in the study to capture the relationship between the sales promotion, price discount and the batch procurement strategy of a particular product category to maximize sales volume and profitability.

Time series data relating to sales have been used to model the sales estimates using moving average and proportional and derivative control; thereafter a sales forecast is generated to estimate the sales of a particular product category. This provides valuable inputs for taking lot sizing decisions regarding procurement of the products that considerably impact the sales promotion and intelligent pricing decisions. A conceptual framework is developed for modeling the dynamic price discounting strategy in retail using fuzzy logic.

The model captures the lag effect of sales promotion and price discounting strategy; other strategies have been formulated based upon the sales forecast that was done for taking the lot sizing decisions regarding procurement of products in the selected category. This has helped minimize the inventory cost thereby keeping the profitability of the retail organization intact.

There is no appropriate empirical data to verify the models. In light of the research approach (modeling based upon historical time series data of a particular product category) that was undertaken, there is a possibility that the research results may be valid for the product category that was selected. Therefore, the researchers are advised to test the proposed propositions further for other product categories.

The study provides valuable insight on how to use the real-time sales data for designing a dynamic automated model for product sales promotion and price discounting strategy using fuzzy logic for a retail organization.

This paper aims to understand empirically how shares of standard and premium private label (PL) products affect a retailer’s marketing mix decisions toward national brands (NBs).

Using a comprehensive store-level data set covering 52 categories and 130 stores of two retailer chains during 2003-2009, this paper examines how shares of standard and premium PLs affect retailer marketing strategies for NB retail prices, promotions and product assortments. The empirical analysis uses a simultaneous equations model estimated by the generalized method of moments approach and controls for endogeneity between PL shares and NB decisions and potential confounding variables including consumer, manufacturer and retailer factors.

Standard PL shares are associated positively with NB retail prices and negatively with NB promotions and assortments. In contrast, premium PL shares are associated positively with NB retail prices, promotions and assortments.

The results indicate that retailers make strategic NB decisions through multitier PLs. Specifically, the evidence suggests that retailers use standard and premium PLs differently in promotion and assortment decisions toward NBs. NB manufacturers need to be cognizant of the increasing marketing power of retailers through their multitier PLs.

Prior research has mainly focused on the role of PLs as a strategic weapon to gain power in the channel and its impact on NB pricing decisions in a single PL context. After accounting for potential confounding factors (retailer, consumer and manufacturer) and endogeneity, the authors find empirical evidence that retailers appear to leverage standard and premium PLs differently in some marketing mix decisions toward NB. In particular, the results reveal PL performance to be a determinant of retailer NB assortment decisions.

Since 2016, organized retailers in Colombia have struggled against a new retail format: Hard-discount stores. This sales channel fulfills essential shopping basket products with consistent low prices. To be competitive and preserve their market position, organized retailers must improve their processes and their pricing decisions. Promotions and discounts have been considered as an effective alternative to compete. This study analyzes the impact of joint prices decisions over the individual and global financial key performance indicators when a collaborative strategy is adopted. Our case study comprises a supermarket chain Colombian retailer and a consumer packaged-goods manufacturer to analyze its supply chain performance. The analysis considers different product categories (food, personal care, and cosmetics) and country regions. The results highlight that benefits are unequally distributed along different echelons and supply chain performance is affected when pricing decisions are made independently.

This paper aims to develop an optimal buyback promotion strategy for enterprises, including multibuyback strategy and self-buyback strategy, taking both the consumer's multichannel psychological acquisition attributes and remaining market into account.

Based on the game theory and Hotelling model, the authors formulate a new model to study the equilibrium of different buyback models, given the utility maximization of the consumers, the profit maximization and the constraint on nondecreasing market share of the enterprises, and the authors conduct comparative analysis.

Intuitively, enterprises buying back products of other brands would appeal to some consumers. However, the authors find that after implementing the multibuyback scheme, enterprises may not be able to seize competitors' markets or even lose their original customer base in the context considered in this article counterintuitive. In addition, the size of remaining market share and the consumer's multichannel psychological acquisition affect the choice of buyback promotion strategies. Moreover, after implementing multibuyback scheme, customers with old products subsidize those who receive additional discounts. Finally, the authors point out that the buyback strategy choices of companies with different goal-oriented are diverse.

This study has a very solid realistic background and provides guidance for enterprises to implement buyback promotion strategies. In addition, the authors unearth new influencing factors to provide a reasonable explanation for different buyback strategies in reality.

To the best of the authors’ knowledge, this study is one of the first to explore the multibuyback promotion strategy as a new buyback method, where the two influencing factors the authors have not been proposed so far.

To explore US consumers' perceptions of the level of fun associated with non‐price retail promotions and to predict likelihood of participation among demographic groups.

The study employs a sample generated from retail forward panel data (n=500) to assess the impact of demographic variables including gender, age, educational attainment, income and household size on consumer perceptions and likelihood of participation in five types of non‐price retail promotions. Descriptive and inferential statistical techniques (t‐tests, regression) are used to evaluate the data.

Identifies demographic groups who perceive high levels of fun associated with non‐price retail promotions and examines relationships between demographics and likelihood of participation in these types of promotions.

Generalizations of the findings of this study to markets outside the USA are limited due to the differences in consumers and forms of retail promotion within various markets. Future studies could examine perceptions of non‐price retail promotions across international markets as well as identify additional predictors of response to non‐price retail promotions.

This research provides retailers that operate within the USA specific knowledge of consumers' perceptions of non‐price retail promotions and identifies demographic characteristics of consumers who are likely to participate in such activities. As price competition in the sector continues to evolve, understanding non‐price forms of competition is critical to superior performance and survival in the industry.

This exploratory study uses demographics as a framework for examining consumers' perceptions of and likelihood of participation in non‐price retail promotions. The paper is unique because there are few similar empirical studies focused specifically on non‐price retail promotions.

The purpose of this paper is to capture the dynamic variations in sales of a product based upon the dynamic estimation of the time series data and propose a model that imitates the price discounting and promotion strategy for a product category in a retail organization.

Time series data relating to sales has been used to model the sales estimates using moving average and proportional and derivative control; thereafter a sales forecast is generated to estimate the sales of a particular product category. This provides valuable inputs for taking lot sizing decisions regarding procurement of the products and selection of suppliers. A hybrid model has been proposed and explained with a hypothetical case, which considerably impacts the sales promotion and intelligent pricing decisions.

A conceptual framework is developed for modeling the dynamic price discounting strategy in retail using fuzzy logic. The model imitates sales promotion and price discounting strategy. This has helped minimize the inventory cost thereby keeping the profitability of the retail organization intact.

There is no appropriate empirical data to verify the models. In light of the research approach (modeling based upon historical time series data of a particular product category) that was undertaken, there is a possibility that the research results may be valid for the product category that was selected. Therefore, the researchers are advised to test the proposed propositions further for other product categories.

The study provides valuable insight on how to use the real-time sales data for designing a dynamic automated model for product sales promotion and price discounting strategy using fuzzy logic for a retail organization.

Considering the network externalities of online selling, this paper builds three different online direct selling models: manufacturer direct selling (MN model), network platform direct selling (NN model) and retailer direct selling (RN model). The optimal advertising and pricing decision and corporate profits under each selling model are investigated.

Combining the characteristics of online direct selling, this paper formulates direct selling models that are dominated by different companies as Stackelberg game models. Numerical analyses are carried out, along with the comparison of the equilibrium solutions for each model.

The authors' research shows that increasing network externalities is conducive to the development of enterprises. The network platform's profit is the lowest in the RN model and the highest in the NN one. The comparison of manufacturers' profits between the MN model and the NN model primarily depends on consumers' sensitivities for sales price and advertising promotion level. The manufacturer does not benefit from the RN model due to the lowest efficiency.

Coupled with three different online direct selling models and detailed analyses of the optimal solutions, this study has enriched the theoretical foundation of online direct selling. Moreover, this study extends the research of network externalities to the field of e-commerce, revealing the network externalities' influence on the decision-making of the e-supply chain.