Competitive Retail Market Research Articles

Leveraging Machine Learning to Optimize Pricing and Restocking Strategies for Fresh Vegetables

In the competitive and diverse retail market, restocking and pricing perishable vegetables is challenging. Using big data and machine learning to analyze sales data, this research can build predictive models to refine these strategies and predict trends[1][2]. This research analyzed sales data from 2020 to 2023, identifying key trends in sales volumes, seasonality, and consumer preferences. It incorporated these findings into a multi-objective programming model that also considered wholesale and loss rates. This research used statistical tests like the Kruskal-Wallis and Mann-Whitney U to detect significant sales differences across vegetable categories, while the Spearman correlation showed strong seasonal and culinary impacts on consumer buying behaviors. To optimize freshness and maximize sales and profits, this research utilized genetic algorithms and regression analyses, including an effective XGBoost model. This model had a Mean Absolute Percentage Error of 16.97 and an R² of 0.94, aiding in predicting daily sales and improving pricing strategies and restocking schedules. These methods helped enhance decision-making, ensuring vegetable freshness and maximizing profitability, with projected profits reaching ¥41,582.87. This study not only highlights the effectiveness of integrating big data and machine learning in the retail sector but also sets a benchmark for operational efficiency in managing perishable goods.

Green electricity product menu design for retailers without knowing consumer environmental awareness

Adverse selection problem due to asymmetry of consumer environmental awareness (CEA) could reduce electricity retailer's profit and obstructs renewable energy (RE) consumption. This study analyzes mechanism design problem of retailer constricted by RE consumption quota to incentive consumers display true CEA in competitive retail market. Based on principal-agent theory, we develop an extended principal-agent model with the addition of an RE consumption quota constraint to design a green electricity product menu which includes the green level, the price and electric quantity. Influence of information symmetry and quota setting on product attributes, retailer's profit, consumer utility, RE consumption is analyzed, and results show that: (1) Compare to symmetric information, under asymmetric information, green level of product provided to consumers with CEA (denoted as C1) distorts upward, information rent is greater than zero when quota is large, while green level of product provided to consumers without CEA (denoted as C2) distorts downward, with no information rent. (2) Under asymmetric information, unit environmental premium (UEP) of green electricity positively relates to proportion of C1, CEA level, and incremental WTP, and reaches the maximum value at a certain quota. (3) Under asymmetric information, retailer's profit and RE consumption positively relates to proportion of C1, and CEA level. (4) Under asymmetric information, quota difference could contribute to improve retail service quality under competitive retail market, and RE consumption elevation.

Predicting demand for new products in fashion retailing using censored data

In today’s highly competitive fashion retail market, it is crucial to have accurate demand forecasting systems, namely for new products. Many experts have used machine learning techniques to forecast product sales. However, sales that do not happen due to lack of product availability are often ignored, resulting in censored demand and service levels that are lower than expected. Motivated by the relevance of this issue, we developed a two-stage approach to forecast the demand for new products in the fashion retail industry. In the first stage, we compared four methods of transforming historical sales into historical demand for products already commercialized. Three methods used sales-weighted averages to estimate demand on the days with stock-outs, while the fourth method employed an Expectation-Maximization (EM) algorithm to account for potential substitute products affected by stock-outs of preferred products. We then evaluated the performance of these methods and selected the most accurate one for calculating the primary demand for these historical products. In the second stage, we predicted the demand for the products of the following collection using Random Forest, Deep Neural Networks, and Support Vector Regression algorithms. In addition, we applied a model that consisted of weighting the demands previously calculated for the products of past collections that were most similar to the new products. We validated the proposed methodology using a European fashion retailer case study. The results revealed that the method using the Expectation-Maximization algorithm had the highest potential, followed by the Random Forest algorithm. We believe that this approach will lead to more assertive and better-aligned decisions in production management.

Assessing the Feasibility Study of XYZ Company’s New Supermarket Branch in Menteng, Central Jakarta

XYZ Company plans to expand into Jakarta’s supermarket market, leveraging Indonesia’s growth in the food and beverage industries. With a population of 273 million in 2024, urbanization, a rising middle class, and evolving consumer behaviours drive sector growth. XYZ Company, with over 40 successful stores in Bali and Lombok, aims to enter Jakarta’s competitive retail market, dominated by players like Hero Supermarket and Carrefour. This feasibility study uses a mixed-methods approach, including interviews, surveys, financial reports, and market analyses. Financial metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and payback period indicate the project’s viability, with costs estimated at Rp. 22,858,000,000.00. Marketing analysis, using SWOT, TOWS, and Porter’s Five Forces, reveals opportunities for differentiation through premium product offerings and food courts, enhancing customer experience and foot traffic. Significant opportunities for XYZ Company to differentiate include leveraging the growing middle class and diverse consumer preferences. Integrating food courts within supermarkets, a strategy used by competitors like Transmart Carrefour and Grand Lucky Supermarket, can significantly enhance customer experience. Focusing on premium products and readyto-eat meals can attract a broader customer base. Strategic recommendations involve selecting high-traffic locations, expanding the online presence, and adopting sustainable practices to control costs and appeal to environmentally conscious consumers. The study emphasizes adapting to market trends and maintaining financial prudence for long-term profitability. In conclusion, the feasibility study offers a comprehensive analysis of XYZ Company’s proposed expansion into Jakarta. By focusing on strategic market entry, financial planning, and risk management, XYZ Company can successfully establish its presence in Jakarta’s competitive retail market, ensuring sustainable growth and profitability.

Beyond the Box: Packaging and Branding as Tools for Differentiation in a Competitive Retail Market

The study's goal was to investigate how customers perceive various design components of milk tea packaging and to provide crucial data for businesses about consumer appeal and the significance of design features from the customer's viewpoint. This study aims to contribute to the body of knowledge already available in the packaging and marketing fields by shedding more light on the psychology of color and its effects on packaging and marketing. It expounds upon several facets of packaging and encapsulates the conclusions of the latest studies carried out thus far, which have examined packaging from various angles. There is an importance in studying and delving into the deep essence of branding and packaging so that consumers notice businesses' packages first and represent the brand. Ensuring that the packaging aligns with the company's brand and beliefs is crucial. The brand's packaging should communicate its goals, core values, and distinctive selling points. The researcher employed the following methods to gather information: (1) analysis, (2) interviews/personal interviews, and (3) validated tool/guide. Qualitative information was gathered from 20 tool replies. The study's findings demonstrated the significance of packaging design in customer purchasing habits. Through the analysis of customer perception, it was discovered that packaging design components including color, graphics, and product details are important since they are part of decision-making and guarantee the customer's focus. Based on the results, it was determined that an effective milk tea package design could be produced through collaboration between the client and the business. Additional studies might examine the design features of various product packaging.

THE IMPACT OF SOCIAL MEDIA ON CONSUMER BEHAVIOUR

This study delves into the intricacies of consumer behaviour within the realm of social media commerce, aiming to uncover the motivations driving purchases and the types of products preferred by consumers in this digital landscape. Through a quantitative research approach, data were collected via surveys distributed to a sample of social media users. Analysis revealed that trust, authenticity, convenience, and social interactions are significant factors influencing consumer decisions to purchase through social media platforms. Additionally, the study identified a diverse range of commodities transacted on these platforms, with lifestyle and fashion-related items being prominent. The emergence of niche markets and influencer marketing strategies further exemplifies the evolving nature of social media-driven commerce. These findings provide valuable insights for businesses and marketers seeking to refine their strategies and capitalize on the opportunities presented by social media commerce. In the digital age, comprehending the motives and preferences of consumers is crucial for achieving success in the fiercely competitive online retail market. Keywords: Social media, Consumer behaviour, Consumer trust, social media advertising, Online brand presence, social media platforms, Consumer preferences.

Price optimization for manufacturers in a competitive retail market: imported products and online crowdfunding option

AbstractThis study explores how manufacturers in the competitive supply chain can set prices and secure funding effectively. We use game theory to look at how competition between domestic and foreign manufacturers affects pricing decisions. Our research investigates how a domestic manufacturer can improve its market share by addressing financial challenges through modern financing methods. In this scenario, a domestic manufacturer competes with a foreign one to attract a retailer’s market share and profits. The retailer decides what products to buy and how to price them based on bid prices and demand. We also consider that the domestic manufacturer will use online crowdfunding platforms to tackle its financial problem. Hence, our study sets up a supply chain where competition revolves around both operational and financial decisions. Mathematical models are developed to analyze how costs, finances, market potential, and price sensitivity impact various parts of the supply chain. The results reveal that decisions made on the crowdfunding platform significantly influence other supply chain decisions. Manufacturers and retailers need to pay attention to the financial decisions made on this platform to maximize profits. Also, domestic and foreign manufacturers should consider customer preferences for their products when setting prices. Finally, the results demonstrate that a domestic manufacturer can gain a competitive edge in the retail market by carefully considering both product pricing and financial decisions, including those made on the lending platform.

A Case Study on the Impact of Brand Image on Customer Buying Behaviour with Special Reference to Nilgiris Supermarket in Mangalore

Purpose: The study aims to explore how the brand image of Nilgiris Supermarket influences customer perceptions and purchasing decisions. By examining this relationship, the research provides valuable insights into the role of brand image in the retail industry. Research Design: The methodology employed in this case study includes a combination of primary and secondary data collection. Primary data is gathered through surveys and interviews with customers of Nilgiri Supermarket. The findings from these sources contribute to a comprehensive understanding of the impact of brand image on customer buying behaviour. Findings: The research findings highlight the significant influence of brand image on customer perceptions and behaviours. A positive brand image can create a sense of trust, reliability, and quality among customers, leading to increased loyalty and repeat purchases. Moreover, a strong brand image can attract new customers and enhance the store's competitive advantage in the market. The case study specifically analyzes various aspects of Nilgiri Supermarket's brand image, such as its reputation, product quality, pricing strategy, customer service, and store atmosphere. It investigates how International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 01 | January - 2024 SJIF Rating: 8.176 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM28211 | Page 2 these elements contribute to customer perceptions and influence their buying decisions. The study also explores the role of advertising, social media presence, and word-of-mouth in shaping the brand image and customer buying behavior. The results of the case study demonstrate the positive impact of Nilgiri Supermarket's brand image on customer buying behaviour. Customers perceive the brand as trustworthy, offering high-quality products at reasonable prices, and providing excellent customer service. These positive perceptions lead to increased customer satisfaction, loyalty, and a willingness to recommend the supermarket to others. In conclusion, this case study sheds light on the importance of brand image in influencing customer buying behaviour towards Nilgiri Supermarket. The findings highlight the significance of maintaining a positive brand image to attract and retain customers in the competitive retail market. The research provides practical insights for Nilgiri Supermarket and other retailers seeking to enhance their brand image and strengthen customer relationships. Keywords: Brand Image, Customer Buying Behaviour, Retail Industry, Customer Perceptions, Competitive Advantage.

The role of membership fees in online retail market competition

In the rapidly growing yet fiercely competitive online retail industry, the prevailing trend of adopting a paid membership system appears to be contradictory to the commonly observed principles of free and subsidized services over the Internet. Thus, this study proposes a competition model based on the assumption of heterogeneity in consumers’ online shopping search costs, in order to elucidate the underlying mechanism of this phenomenon. The findings reveal that e-commerce platforms that implement a paid membership system are best equipped to navigate marketing campaigns. Meanwhile, as long as a certain degree of promotional and discounted activities are present in the online market, retailers seeking profit maximization will find this system to be most effective for generating profits that surpass the market level. Furthermore, the comparative static analysis and numerical simulations in this study offer valuable insights to managers in their decision-making regarding membership fees and retail pricing.

Computer Vision Based Planogram Compliance Evaluation

Arranging products in stores according to planograms, optimized product arrangement maps, is an important sales enabler and necessary for keeping up with the highly competitive modern retail market. Key benefits of planograms include increased efficiency, maximized retail store space, increased customer satisfaction, visual appeal, and increased revenue. The planograms are realized into product arrangements by humans, a process that is prone to mistakes. Therefore, for optimal merchandising performance, the planogram compliance of the arrangements needs to be evaluated from time to time. We investigate utilizing a computer vision problem setting—retail product detection—to automate planogram compliance evaluation. Retail product detection comprises product detection and classification. The detected and classified products can be compared to the planogram in order to evaluate compliance. In this paper, we propose a novel retail product detection pipeline combining a Gaussian layer network product proposal generator and domain invariant hierarchical embedding (DIHE) classifier. We utilize the detection pipeline with RANSAC pose estimation for planogram compliance evaluation. As the existing metrics for evaluating the planogram compliance evaluation performance assume unrealistically that the test image matches the planogram, we propose a novel metric, called normalized planogram compliance error (EPC), for benchmarking real-world setups. We evaluate the performance of our method with two datasets: the only open-source dataset with planogram evaluation data, GP-180, and our own dataset collected from a large Nordic retailer. Based on the evaluation, our method provides an improved planogram compliance evaluation pipeline, with accurate product location estimation when using real-life images that include entire shelves, unlike previous research that has only used images with few products. Our analysis also demonstrates that our method requires less processing time than the state-of-the-art compliance evaluation methods.

Novel Decentralized Peer-to-Peer Gas and Electricity Transaction Market between Prosumers and Retailers Considering Integrated Demand Response Programs

This paper proposes a novel peer-to-peer (P2P) decentralized energy market consisting of retailers and prosumers considering integrated demand response (IDR). Retailers can trade electrical energy and gas with prosumers in a P2P way to maximize their welfare. Since they are equipped with electrical storage and power self-generation units, they can benefit from selling power not only to the upstream network but also to prosumers. In peer-to-peer transactions, the prosumers purchase electricity as well as gas from retailers. Because of their access to the competitive retail market, including some retailers, they enjoy more freedom to reduce their energy supply cost. In addition, the prosumers are equipped with an energy hub consisting of combined heat and power (CHP) units and electric pumps, allowing them to change their energy supply according to price fluctuations. Furthermore, they have some changeable electrical and thermal load enabling them to change their load if needed. To clear the proposed P2P decentralized market, a fully decentralized approach called the fully decentralized alternating direction method of multipliers (ADMM) is applied. This method does not require a supervisory entity and, thus, preserves the players’ private information. The numerical studies performed on a system with two retailers and multiple prosumers demonstrate the feasibility and effectiveness of the proposed decentralized market. The results also show that the proposed decentralized algorithm achieves the optimal global solution, compared with the centralized approach.

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer’s individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers’ energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer’s new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

Why We Choose Cooperative Advertising? An Analysis of Channel Competition

Conventional wisdom believes that the spring-up of cooperative advertising is owing to the difference between the manufacturer's national advertising and the retailer's local advertising. This paper develops a channel competition model to investigate the efficiency when manufacturers or retailers shoulder the responsibility of advertising. It is found that if manufacturers sponsor advertising, they are likely to engage in fierce advertising competition. Yet if it is the retailers who decide the advertising volume, they have not any motivation to advertise at all! This is because all the extra earnings received from advertising would be robbed by the manufacturers. Therefore, it is claimed that cooperative advertising may be a consequence of the retailer's downstream role. In a competitive retail market, the downstream sector is not as likely as the upstream firm to invest heavily in advertising, thereby avoiding the prisoner's dilemma.

Mediating Role of Perceived Value on the Relationship Among Perceived Risks, Perceived Quality, and Purchase Intention of Private Label Brands

In the current competitive retail market, retailers constantly strive to deliver products to consumers at a better value. Consumers are becoming more price sensitive but still seeking quality products. A retailer can establish value with a brand. Consequently, retailers are introducing their own private label brands (PLBs), which also differentiate their products from competitors. The role of perceived value in the purchase behavior of PLBs and its relationship with quality and various risk dimensions has received scant consideration in the retailing literature. Our study suggests perceived value is a mediating part in associations amid perceived quality, perceived risks, and purchase intention of PLBs. A structural equation modeling approach was adopted to test the proposed hypotheses with a convenience sample of 458 consumers of retail department stores obtained via a cross-sectional survey. The results demonstrate that the role of perceived value is vital in strengthening the association of consumer-perceived quality and purchase intention of PLBs as well as minimizing the consumer’s risks as they intend to buy PLBs. Overall, the study contributes to the emerging retail and consumer behavior literature regarding the role of perceived value in purchase intention of PLBs.

Research on the Operation Measurement and Evaluation Method of Retail Packages under the Background of Electricity Market

With the liberalization of the electricity market, building a diversified and open competitive electricity retail market has become the focus of market reform and development. In the initial stage of the the retail market, the operating status of retail companies is an important evidence for the analysis of the current development of the retail market and the formulation of relevant rules. This paper designs a retail allocation method and proposes different business calculation and analysis methods based on 9 different types of retail packages in Yunnan electricity retail market. Based on a two-tier evaluation index system for retail packages and the electricity sales company, the FCE method combined with the AHP is used to evaluate the operating states of the electricity sales company and the retail packages.

An Intelligent Point-of-sale System for Mobile Retailors

In a fiercely competitive retail market, the biggest competitive advantage of the physical channel over the virtual channels is the product experience and service. Increasing the professionalism of the salespeople and improving service should be prioritized in physical retail. I use the AIDA model to construct a consumers’ purchase guiding system named “intelligent point-of-sale” (iPOS) that integrates the sales recommendation rule model. Through the app, consumers and salespeople interact with each other and the model recommends appropriate product combinations to the consumers. The system assists salespeople to guide consumers towards a purchase to improve transaction conclusion rate and company profitability.

Utilitarian Motives and Purchase Behaviour of Indian Mall Shoppers

Today most of the shopper shows purchase behavior from shopping mall retailers, as the utilitarian shoppers are distinguished by their intrinsic tendency to strike a utility-based shopping. Therefore, study tries to strengthen the association and promotion of utilitarian shopping motives with purchase behavior at shopping mall via search and purchase intentions. Confirmatory factor analysis and structural equation modeling analysis has been used to analyze and validate the proposed research framework. Study findings support the relationship between utilitarian shopping motives and purchase behavior, where both the search intention and purchase intention show significant positive influence on purchase behavior of Indian shoppers. Study also identifies the moderating role of gender on all the proposed relationships. Therefore, the outcomes would be helpful for the shopping mall retailers to plan their promotional activities effectively and efficiently for utilitarian shoppers. Similarly, the findings could also be useful for academicians and researchers to identify the shoppers buying behavior at shopping mall and help them to find out some more variables, related to consumer behavior in this highly competitive retail market scenario.

Residential electricity pricing in Texas's competitive retail market

Abstract Using a large sample of residential retail electricity plans advertised on the Public Utility Commission of Texas's Power-to-Choose website between January 2014 to December 2018, we analyse how a retail price quote varies with its per MWh procurement cost forecast based on wholesale prices and other product attributes. Our panel regression analysis finds that a retail price quote partially passes through 43% to 47% of a wholesale price forecast changes and embodies a risk premium that increases with wholesale price forecast volatility. Prepayment and time-of-use plans contain price premia. The price premia associated with higher-than-average renewable energy contents in the early years of our sample have largely vanished by 2018. Longer contract terms come at a higher price. Finally, increased one-month lagged customer switching tends to be associated with reduced retail price quotes.

A “parasite market”: A competitive market of energy price comparison websites reduces consumer welfare

This article is about energy price comparison websites (PCWs). Using the example of Great Britain, it studies whether a competitive market of energy PCWs or a single non-commercial PCW can serve consumers better. Results are unambiguous. Households currently pay more than £100 million per year through their energy bills to commercial energy PCWs. The business model of these PCWs is largely based on creating deviations from consumer choice considered ideal by the regulator. As a result, people overpay for energy and retail market competition is adversely affected. Furthermore, commercial PCWs do not efficiently increase consumer engagement, so more households are on expensive tariffs than in the alternative system. Commercial PCWs also introduce a number of risks. As trade-offs in the competitive case are unavoidable, regulatory changes cannot make the market better than the one-non-profit-site solution. A single non-commercial PCW, such as the one operated by Citizens Advice, can provide a higher quality service at a substantially lower cost. Therefore, the interests of consumers can best be protected by shutting down commercial PCWs. A theoretical insight is that a competitive market of PCWs emerges if not explicitly prohibited by regulation, but reduces consumer welfare: this should be considered a “parasite market”.

The Impact of Competitors’ Store Flyer Advertisements on EDLP/High-Low Chain Performance in a Highly Competitive Retail Market: GPS Information and POS Data Approach in Japan

The Japanese retail market has a high degree of competition among many small stores that use promotional (high-low) pricing strategies. Because store advertisement flyers are effective tools for such retailers, they play a very important role in Japan. However, despite the large impact made by flyers of competitive retail chains in various trade areas, the effects of advertising flyers has not been investigated in Japan, nor has this advertising strategy been investigated in Western countries. In this study, we obtained store traffic information using global positioning system (GPS) data from shoppers’ smartphones, with flyer information from 80 retail chain stores located in different trading areas. We found that while own-store flyers had a positive effect on that store’s performance, competitors’ flyers had negative effects on performance; indeed, these negative effects were of a magnitude that should not be ignored. Store-specific factors and trading area demographics also affect the effectiveness of store flyers. Furthermore, we found that high-low shoppers are more sensitive to competitors’ flyers than are customers who purchase at everyday low prices (EDLP). The results can help EDLP chains stop the practice of designating a loss leader brand.