Decision Of Retailer Research Articles

Analysis of the Interactive Game Between Manufacturers and Retailers Considering the Free-Riding Effect on the Internet

Against the backdrop of an increasingly sound supply chain system and thriving e-commerce, it is becoming increasingly common for retailers to introduce their own brands of products and for manufacturers to open up direct online sales channels. The existence of these two supply chain decisions is complex and involves interactions. Moreover, the introduction of online direct sales channels will bring about differences in prices and service quality between channels, resulting in a free-riding effect on the internet. However, existing related research rarely considers the role of network free-riding effect in this supply chain system. This article integrates the network free-riding effect into the supply chain model by setting the network free-riding rate. According to whether retailers introduce their own brand products and manufacturers open up online direct sales channels, four supply chain scenarios are formed, and the reverse recursion method is used to obtain the profit functions for each of these four scenarios. Then, a Stackelberg game model is established to determine the response strategies of manufacturers and retailers based on the changes in profits of manufacturers caused by retailer decisions and the changes in profits of retailers caused by manufacturer decisions. Through analysis, it was discovered that a key factor affecting decision-making within the supply chain system is the retailer’s channel advantage. When the channel advantage of retailers is strong, manufacturers will open up online direct sales channels to weaken the channel advantage of retailers. Retailers will not introduce their own brand products but are more inclined to cooperate with manufacturers. When the channel advantage of retailers is weak, retailers will attract consumers and consolidate their channel advantage by introducing high-quality, low-priced private label products, while manufacturers will maintain cooperation with retailers and adopt a strategy of not opening up online direct sales channels. We also analyzed the Nash equilibrium state under different channel advantages of retailers.

Factors Influencing Selection of Dairy Products by Retailers with Special Reference to Amul - A Study in Raipur

This report summarizes the comprehensive analysis of the behavior of retailers, product range, and promotion strategies by the fast-moving consumer goods (FMCG) companies in the dairy products industry. The study was done during a two-month internship at Amul, with an objective to get practical knowledge about the distribution, marketing, and sales activities of FMCG companies through General Trade, Modern Trade, and Horeca channels. These considerations include profit margins, available products, reliable supply chain, and brand equity to arrive at a conclusion. Thereby, findings suggest the preference of retailers for trusted brands by the consumers having quality assurance and consistent supplies because of the perishability aspect related with dairy products such as milk, curd, and paneer. In addition, kiosk events, wall paintings, and shutter advertisements have proven to have a positive effect on the visibility of the brand and engagement of the consumers with the brand, thus affecting the decision of retailers to stock. Shelf space allocation was also observed to depend on consumer demand, brand promotions, and product differentiation in competitive retail environments. Through market visits and retailer feedback, the study provided actionable recommendations to strengthen Amul's brand presence and optimize product turnover. This internship emphasized the importance of close relationships and support mechanisms from strong retailers in fostering brand loyalty and market growth in the FMCG industry. Keywords: Distribution Efficiency, Brand Loyalty in Dairy, Retailer Relationship Management.

Literature Review on IoT-based Smart Retailing Management Systems in the Context of Smart Cart

Abstract: IoT technology has revolutionized retail, giving rise to Smart Retailing Management Systems (SRMS). This review explores IoT-based SRMS focusing on smart carts, investigating enhancements in shopping experiences like RFID tags, dynamic inventory management, and personalization. By comparing research and products, it evaluates SRMS in technology, cost, reliability, security, power use, and components. The goal is to unveil SRMS’s strengths and weaknesses, aiding retail progress. Objective: This study aimed to review IoT-based Smart Retailing Management Systems (SRMS) centered on smart carts, explore IoT's role in enhancing shopping, spotlighting RFID tags, dynamic inventory, and personalization, and evaluate SRMS via tech, cost, reliability, security, power, and components, unveiling diverse strengths and weaknesses. Method: A literature search in previous works and patents was conducted. The findings to pinpoint trends, tech shifts, and research gaps were analyzed. The real-world studies were synthesized to discuss IoT-based SRMS progress and an inclusive view of various approaches and outcomes was offered. Conclusion: IoT-based SRMS, especially in smart retail carts, elevate shopping via RFID tags, dynamic inventory, and personalization. The comparative analysis exposes SRMS potential and constraints, offering insights for informed retail decisions and advancement.

How does viewing food products in 2D or 3D affect consumer evaluations?

This study examines the influence of changes in visual information (2D vs. 3D) and product characteristics (healthy vs. unhealthy) on consumer purchase intention, expected satiety, and expected volume with regard to food products. The participants were asked to answer a questionnaire for each food sample displayed in 2D or 3D. The results reveal that the 3D food model has significantly higher scores for expected volume and satiety than does the 2D model, along with a significant interaction between visual information and product characteristics. For healthy foods, the expected volume, expected satiety, and purchase intention were significantly higher in the 2D than in the 3D model. For unhealthy foods, scores for the three variables were significantly higher in the 3D than in the 2D food model. This indicates an inverse relationship based on the healthiness of the food product. The study posits that changing the visual information from 2D to 3D strengthened the image of healthy and unhealthy foods as having low and high volumes, respectively, resulting in a more favorable purchase intention. The results of this study advance our understanding of the applicability of different image types when promoting food products, thereby enabling and guiding well-informed decisions of online retailers and other stakeholders in the design of food products for advertisements and other purposes in the food service industry.

Optimisation of retailer take-back of low and medium-value products for a circular economy

Used product take-back plays a significant role in the transition to a Circular Economy. Many businesses are introducing retailer-level take-back schemes for low and medium-value products by deploying collection bins for customers to drop off used products. However, the literature has not given much attention to these schemes compared to those with high recovery value products. The viability of such schemes depends on several factors, including the volume of returns and the contamination in the collection bins. We consider a two-echelon reverse supply chain consisting of a retailer taking back low and medium-value used products and delivering them to a recycler for value recovery. We mathematically model the optimal retailer decisions, including the return incentive paid to customers, investment in contamination reduction, the number and capacity of bins, their product assignment, and time between shipments from the retailer to the recycler, and apply the optimisation model to a case study. In addition, our numerical experiments with globally representative parameter value combinations provide generalisable insights for theory and practice. For example, recycling low-value products like plastic containers is economically infeasible for retailers under all conditions. However, including at least one medium-value product, such as apparel, in a take-back programme aids in offsetting its costs. Investing in reducing contamination for any product type is financially unwarranted unless the costs of separation and disposal exceed that of contamination reduction investment. Furthermore, combining multiple product streams into fewer bins could improve financial results, but keeping bins separate may offer psychological benefits to users.

Policies for Selecting the Advance Selling Mode in a Supply Chain Considering Network Externalities

ABSTRACTThe marketing strategy of advance selling new products through e‐commerce channels is becoming increasingly popular among merchants and users. In advance selling on e‐commerce platforms, network externalities and the probability of consumer satisfaction with products are important factors affecting consumers' strategic behavior. This study considers network externalities and the probability of consumer satisfaction with products in the advance selling decision‐making problem in the supply chain. Using game theory and prospect theory, three scenario models—advance selling considering network externalities, advance selling without considering network externalities, and nonadvance selling—are designed to construct theoretical models for supply chain decision‐making. The optimal decision‐making problem of supply chain members is discussed. Furthermore, through a comparison of pricing, demand and profits, the impacts of advance selling with or without considering network externalities on the decisions of retailers and manufacturers are analyzed. By comparing the differences in decision‐making between manufacturers and retailers, the feasible area for advance selling under network externalities is obtained. Furthermore, through numerical experiments, the impacts of the strength of network externalities, and the probability of consumer satisfaction with products on the decision‐making of supply chains are analyzed.

Financial hedging incentive contracts in global supply chains: A distributionally robust approach

AbstractThis paper developed a global supply chain with a supplier and a retailer in different countries. When exchange rate and demand risks are concentrated in retailer, a distributionally robust approach is used to formulate an optimized robust ordering strategy. Furthermore, the effect of financial hedging incentive contracts on the robust decisions and the profits of the global supply chain is explored. Our findings show that the correlation between exchange rate and demand does not affect the robust decisions of retailer. The effectiveness of financial hedging incentive contracts depends on the trade‐off between transaction costs of financial hedging and the degree of supplier incentives and the growth rate of order quantity.

Robust pricing and inventory decisions in ship‐from‐store omnichannel operations

AbstractThis work studies the deployment of the ship‐from‐store omnichannel strategy and the pricing and inventory decisions for an online retailer. Robust optimization models are constructed for the online‐only and the ship‐from‐store modes under a budgeted uncertainty set. The ARIMA model is used to predict the parameter values of the budgeted uncertainty set using historical demand data. The closed‐form optimal solution for the online‐only mode is obtained. The robust counterpart model for the ship‐from‐store mode is converted to a mixed integer quadratic programming model. Numerical studies are conducted to validate the theoretical results and to verify the effectiveness and practicality of the developed robust optimization solution approach. The results show that adopting a ship‐from‐store strategy may hurt the retailer's profit if a significant proportion of consumers are time‐sensitive with high travel cost. The ship‐from‐store strategy is optimal if it significantly boosts market growth.

Premium pricing and capacity rationing for advance selling with consumers regret

Retailers of iconic products commonly implement premium advance selling, which typically triggers regret in consumers. A premium advance selling strategy is centered around differences in pricing and capacity rationing between two selling periods. We develop a decision-theoretic model to capture the key dynamics of a retailer and a unit mass of consumers. We analyze the retailer's decisions on premium pricing and capacity rationing both separately and jointly. We characterize the retailer's strategy equilibrium under certain market conditions and investigate the effect of consumers anticipated regret on the outcomes. Our findings highlight the importance of the relative strength of regret and the difference between premium and spot pricing when a retailer adopts premium advance selling. Our analysis further identifies the forces driving a retailer's use of disparate selling strategies. We contribute to the field by offering tangible insights into whether and how premium advance selling should be adopted to help retailers more proactively leverage or mitigate consumers' regret.

Research on Green Supply Chain Decision-Making Considering Consumers' Low Carbon Awareness and Cost Sharing

With the global vigorous promotion of the development of green economy, advocating the practice of green concept, sustainable development has become a new problem that the world attaches great importance to. This paper considers the factors of consumers ' low-carbon awareness, discusses the pricing decisions in different situations, and looks for the optimal decisions of manufacturers and retailers. It is found that the enhancement of consumers ' low-carbon awareness is conducive to the increase of supply chain profit, and the retailer 's cost sharing ratio can improve the supply chain profit within a certain range.

Exploring the impacts of ecommerce activities on the spatial resilience of warehouse clubs: the role of retail agglomeration

PurposeAs ecommerce becomes more prevalent, traditional brick-and-mortar retailers such as warehouse clubs (WCs) face the challenging task of maintaining and growing their customer base. This study aims to unravel the combined impact of retail agglomeration and ecommerce activities on consumer foot traffic (also referred to as “footprint”) at WC stores, placing an emphasis on the locational strategies adopted by WCs in this evolving retail landscape.Design/methodology/approachMobile-based customer foot traffic data for Costco, a major U.S. WC chain, is sourced for our analysis. We use Principal Component Analysis (PCA) to identify dimensions of general merchandise (GM) and narrow-range merchandise (NM) retail agglomeration. Two-stage least squares (2SLS) regressions are used to explore how the intensity of ecommerce activities and WC locational choices within retail agglomerations impact WC foot traffic.FindingsOur analysis highlights a notable decline in WC store visits attributable to both GM and NM ecommerce activities, with GM ecommerce presenting a more significant competitive challenge to WCs. Regarding retail agglomerations, proximity to GM clusters that include a diverse range of supercenters, department stores, and club stores, is associated with an increase in WC customer visits within their vicinity. In contrast, the influence of NM agglomerations is mixed; clusters adjacent to grocery stores lead to higher WC customer traffic compared to those focused on other specialized stores. These findings underscore the strategic importance of location in mitigating the adverse effects of ecommerce competition. Additionally, our study uncovers intricate dynamics between GM and NM retail clusters and ecommerce activities, demonstrating varied impacts on WC customer footprint.Research limitations/implicationsAccess to customer footprint data illustrates the potential of this data source for retail decision making and researchers. Our analysis is limited to one chain, notably Costco.Practical implicationsOur findings underscore the need for retailers to adeptly navigate the evolving retail landscape, including the confluence between physical and digital retail environments, to secure future success. In particular, our results emphasize the benefits of locating stores within mixed retail agglomerations and underline the need to consider the broader retail landscape in location decisions.Social implicationsThe rise of ecommerce in the U.S. has reshaped consumer behavior and altered local shopping districts’ communal dynamics. This change may spur policy interventions to help physical stores compete with online retailers, emphasizing the importance of retail diversity and community-centric environments to sustain communal retail interactions amidst digital advancements.Originality/valueThe paper makes use of a unique dataset to provide a first assessment of the combined effects of retail agglomeration and ecommerce activities on consumer foot traffic for WC retailers. Thus, this paper provides insights into the impacts on consumer shopping behavior from the dynamic interactions between physical retail clusters and online shopping behaviors.

Optimal decisions of retailer's loans from bank

AbstractThis study employs the Stackelberg game model to explore an innovative financing model where the retailer directly borrows from the bank under conditions of symmetric information. Diverging from traditional research, this study uniquely incorporates the concept of the margin rate into the decentralised decision analysis among retailer, supplier, and bank. The finding indicates that the capital of the retailer and margin rate significantly influence financing decisions within the supply chain, thereby impacting profitability for all stakeholders. Specifically, we find that the margin rate plays a crucial role in optimising retailer financing decisions, supplier pricing strategies, and bank risk management. These insights offer a fresh perspective for banks to establish appropriate margin rates and loan interest rates, effectively managing loan risks and maximising supply chain profitability.

Integrated inventory replenishment and online demand allocation decisions for an omnichannel retailer with ship-from-store strategy

Retailing has changed dramatically from single-channel brick-and-mortar stores to multi-channel and omnichannel retailers over the last few decades. Omnichannel retailers employ different strategies to integrate online and offline sales channels as well as order fulfillment processes. Among these strategies, the ship-from-store is the most popular and widely accepted among retailers. It enables retailers to use inventory from store locations to fulfill online demand. An omnichannel retailer with a distribution center and a retail store has to make important, interlinked decisions — (1) how much inventory to keep at the retail store, and (2) where to fulfill the online demand from and how much. In this work, we model the integrated inventory replenishment and online demand allocation decisions for an omnichannel retailer employing the ship-from-store strategy. We analyze this problem for both single-period and multi-period settings. We extend the analytical framework of the single-period problem by providing a finite-horizon Markov decision process (MDP) formulation for the multi-period problem. Our findings suggest that for a single-period setting, decentralized inventory replenishment and demand allocation system maximizes the profit of the omnichannel retailer for low values of the incentive for fulfilling the online demand through store inventory, while for sufficiently high values of the incentive, a pooled system provides the optimal profit. An increment in the discount factor has the same effect on the optimal decisions in a multi-period setting as that of salvage value in a single-period setting for a given value of the incentive for the ship-from-store strategy. We also provide several extensions (such as cross selling, endogenous and correlated demand streams) of our analytical framework for the multi-period problem.

Factors Influencing Tax Declaration Decisions on Social Networks of Online Retailers in Vietnam

The growth of e-commerce and online retail in Vietnam, particularly on social networks, has presented challenges for the government’s tax authorities. Preventing tax loss through inspections can be difficult due to missing or incomplete taxpayer data from transaction processing servers. Explaining undeclared or incompletely declared revenue in online trading transactions on the server or the Internet can be challenging, especially for retail activities and service provision for businesses and individuals selling on social networking. In Vietnam, the Tax Management Law 2019 established the tax rates online retailers must pay. However, tax collection for social network retailers still depends on tax authorities encouraging them to self-declare their revenue. Current research and practice show that very few sellers on social networks participate in the self-declaration of revenue to pay taxes. Moreover, few studies focus on factors affecting the participation of online retailers in Vietnam in tax declaration and payment, especially those selling on social networks, and most lack a solid theoretical foundation. Through a review of related studies, this research has identified several factors that affect tax payment decisions for retailers on social networks in Vietnam. The study also provides several recommendations to promote and enhance retailers’ tax declaration and payment decisions on social networks in Vietnam.

Personalized pricing versus showrooming: competition between online and offline retailers

AbstractThis study examines how personalized pricing affects customers’ showrooming behavior in the duopoly competition with horizontal product differentiation between traditional and online retailers. For the available personalized pricing strategies, we obtained the optimal decisions for both retailers in the scenarios with and without showrooming. Our results indicate that adopting personalized pricing under particular conditions enables each retailer to be more profitable, even in the presence of showrooming purchases. This finding explains why an increasing number of online and offline retailers have implemented personalized pricing based on technical means and consumer purchase records. It is also demonstrated that personalized pricing can counter showrooming behavior of consumers amidst the competition between both retailers, which provides a novel theoretical basis for dealing with cross‐channel shopping in multichannel retail competition. We further clarify how retailers can avoid being trapped in a prisoner's dilemma when both sides have access to personalized pricing. Also, the adoption of personalized pricing can improve consumer surplus and social welfare.

Innovation and Distribution: an Equilibrium Model of Manufacturing and Retailing

Abstract This paper proposes a model of the distribution channel to study the decisions of manufacturers, retailers and consumers. The model is used to study how retail distribution affects manufacturing and consumers. As the cost of distribution falls, the retail sector increases assortment size and allows a larger mass of manufacturers to enter, allowing consumers to buy more variety. Entry primitives in manufacturing and retailing determine vertical pricing power. The equilibrium of the model predicts that the national retail sector is a fraction of the total economy that depends on the demand for variety. It is not affected by, e.g., consumer transportation cost or income. Data support this prediction.

Automatic pricing and replenishment decision of vegetable products based on heuristic optimization algorithm

This paper aims to investigate the application of heuristic algorithms to optimize pricing and replenishment strategies in retail markets, using vegetable products as an example. Traditional optimization methods are usually unable to solve complex real-world retail decision problems. Heuristic algorithms offer a promising solution by providing near-optimal results in a reasonable time. In this paper, the DPSO algorithm is combined with Genetic Algorithm (GA) and Simulated Annealing (SA) to create a comprehensive optimization framework. This hybrid optimization approach embodies the synergy among DPSO, GA and SA, and is able to dynamically adjust pricing and replenishment strategies. Experimental results demonstrate the effectiveness of this optimization strategy to maximize supermarket profitability while satisfying consumer and retailer demands. Finally, the transformative power of heuristic algorithms in retail management is exemplified and the utilization of data-driven strategies associated with them is advocated for better and sustainable development.

Contract design and order decision of online retailer's sharing surplus demand with offline retailer

Contract design and order decision of online retailer's sharing surplus demand with offline retailer

The impact of reference price effect on pricing decisions

PurposeThe paper attempts to discuss the impact of reference price effect on pricing decisions.Design/methodology/approachWith the growth of the Internet and e-commerce, more and more customers purchase products in through online channels and choose products by comparing different prices and services, and the reference price effect has an impact on pricing decisions. To investigate the impact of consumers' reference price effect on the dual-channel supply chain, the authors establish a basic model consisting of a single dominant manufacturer and a single downstream retailer, and analyze the optional decisions under different situations and discuss the influence of reference price effect. Finally, a number case verifies the validity and rationality of the proposed model.FindingsThe results show that (1) the reference price effect has varying effects on the price, channel demand and income of manufacturers and retailers in the channel depending on the role of customers' channel preferences. (2) The manufacturer's online channel demand and profits always increase with the reference pricing effect, whereas the retailer's offline demand and profits always decline. (3) When the proportion of consumers preferring offline is higher, the manufacturer's network price and wholesale price increase with the reference price effect, while the retailer's retail price decreases with the reference price effect; when the proportion of consumers preferring offline is lower, the opposite is true, and the centralized decision results are consistent with the decentralized decision results.Practical implicationsThis paper can clarify the impact of consumer reference price effects on the operation of dual-channel supply chains, and help inform pricing decisions of manufacturers and retailers in dual-channel supply chains.Originality/valueThe proposed approach can well analyze the impact of consumer reference price effect and give channel their optional decisions.

Firms' diverse market beliefs can facilitate information sharing and improve profit performance

AbstractA supplier sells a product through a retailer to the market with uncertain demand. The retailer has a signal useful for updating the forecast of market uncertainty, while the supplier can offer a payment to acquire the retailer's signal, termed information sharing. Due to differential means of market access and methods of data analysis, the supplier and the retailer hold diverse beliefs about market conditions. A firm is more confident about market conditions as it perceives the market to be less uncertain. The supplier can be either aware or unaware of the retailer's market belief. In the former case, the supplier correctly predicts the retailer's belief‐based response and makes decision accordingly. In the latter case, the supplier infers the retailer's market belief from the retailer's decision about signal disclosure. We unveil the concrete circumstances where the supplier gains access to the retailer's signal, which would not occur when they held the same accurate market belief. Moreover, with the actual profit performance as the measure, the firms can benefit from holding diverse market beliefs, albeit not simultaneously. The supplier's knowledge of the retailer's market belief can facilitate information sharing but can have detrimental effects on the firms' actual profit performance. Given the opportunity, the retailer may report a market belief that is less confident than its real market belief in communicating with the supplier, which can deter information sharing but has intricate effects on the firms' profits.