Electronic Retailing Research Articles

Ratio Analyses Estimating Financial Risk: Econometric Study Retail Companies the Indonesia Stock Exchange 2020-2023

Aims: This study analyses the effect of activity ratios, sales growth, profitability, and company size on the financial distress of retail companies on the Indonesia Stock Exchange from 2020 to 2023. Study Design: The study uses data on activity ratios, sales growth, profitability, and company size as independent variables and financial distress as the dependent variable. Place and Duration of Study: The research was conducted in retail companies listed on the Indonesia Stock Exchange with a population of retail company subsectors and using purposive sampling criteria. The research data used financial reports published in 2020-2023. Methodology: This type of research is quantitative. The research was tested with SPSS 25 using logistic regression. The total population in the study was 32 types of companies in the retail subsector with several types of companies such as drug retail & distributors, food retail & distributors, supermarkets & convenience stores (minimarkets), department stores, apparel & textile, automotive retail, and electronic retail. Purposive sampling obtained 108 unbalance data for 4 years of observation listed on the Indonesia Stock Exchange in 2020-2023 financial distress was tested with the Altman Z-Score method through logistic regression test. Result: Utilizing logistic regression and the Altman Z-Score, the study reveals that activity ratios and profitability significantly negatively affect financial distress, while sales growth and company size do not have a significant impact. Conclusion: These findings provide valuable insights for stakeholders, emphasizing the importance of optimizing asset efficiency and profitability to mitigate financial distress.

The relationship between antecedents of reverse logistics implementation and economic performance in retail: empirical study for the electronic sector

ABSTRACT This research develops a conceptual model to elucidate the relationship between antecedents of reverse logistics implementation and economic performance. A mixed-methods approach was employed, with qualitative research exploring antecedents and quantitative analysis using 405 responses from Vietnamese electronic retail enterprises to test hypotheses. The findings identified institutional pressure, resource commitment, IT capability, and corporate reputation as antecedents of reverse logistics implementation, exerting direct and/or indirect effects on economic performance. PLS-SEM analysis generated research results consistent with the previously established theoretical conceptual model, and IPMA highlighted institutional pressure and resource commitment as impactful factors despite their low average scores. Notably, resource commitment plays a moderating role in dampening the positive relationship between institutional pressure and reverse logistics implementation. This study provides deeper insights into reverse logistics theory, supporting retail decision-making to enhance economic performance. However, variations in study scope may lead to differences in outcomes, presenting a significant challenge.

Customer Satisfaction with Chatbot Tools in Electronics Retail in VietnamCurrently, Chatbot tool is being used a lot in e-retail businesses due to its convenience, speed and usefulness, so the study of factors affecting customer satisfaction with Chatbot

Customer Satisfaction with Chatbot Tools in Electronics Retail in VietnamCurrently, Chatbot tool is being used a lot in e-retail businesses due to its convenience, speed and usefulness, so the study of factors affecting customer satisfaction with Chatbot

Do Firm Size, Corporate Governance, and Tax Panning Effect on Earning Management?

This research aims to test the influence of firm size, good corporate governance, and tax planning on earnings management. The type of research used is quantitative descriptive verification research. This research uses a sample of retail firms in the Food Retail and Distributors, Supermarkets and Convenience Stores, and Electronics Retail sectors, which are listed on the Indonesia Stock Exchange (IDX) for the 2017-2021 period. The sampling technique in this research is purposive sampling with a sample size of 40 firms. This research uses secondary data, namely firm financial reports obtained from the official websites www.idx.co.id and www.idnfinancials.com. The analytical method used is multiple linear. The results of this research indicate that firm size, corporate governance, and tax planning do not affect earnings management. The managerial implication of this research is that firm managers need to understand that firm size, CG, and tax planning are interrelated in influencing earnings management. Managers must ensure that the tax management strategies used do not violate GCG principles and remain within the corridors of applicable tax regulations earning.

AI Companion: Revolutionizing Sales and Services During Product Advisor and Consumer Interaction

In today's fast-paced consumer electronics industry, staying ahead of the competition and satisfying customers are top priorities. This research investigates the use of AI-powered tools, particularly conversational AI and chatbots, to improve customer interaction and boost sales in electronic retail. As digital platforms become more dominant over traditional sales channels, these AI tools offer significant benefits by delivering personalized, efficient, and timely customer service. The analysis examines various AI technologies, including Large Language Models (LLMs) and retrieval- augmented generation, which enhance consumer interaction. The study also explores the practical implications and challenges of implementing these technologies, with a focus on how they can streamline operations, improve customer experiences, and drive sales. Different models like DialoGPT, Flan-T5, and Mistral 7B are evaluated for their effectiveness in real- time consumer interactions, highlighting the importance of continuous adaptation and learning within AI systems to meet consumer demands and keep up with technological advancements.

Large Language Models in Consumer Electronic Retail Industry: An AI Product Advisor

This paper explores the development of an AI product advisor utilizing large language models (LLMs). Firstly, we discuss the needs and the current problems faced by industry. Subsequently, we reviewed past works by various scholars regarding AI Assistant in Retail and Other Industries, and LLM Models and techniques used in generative AI chatbot for sales and service activity related works. Next, we assessed the performance of various models including Llama2B, Falcon-7B, and Mistral-7B, in conjunction with advanced response generation techniques such as Retrieval Augmented Generation (RAG), fine-tuning through QLora and LLM chaining. Our experimental findings reveal that the combination of Mistral-7B with the RAG and LLM chaining technique enhances both efficiency and the quality of model responses. Among the models evaluated, Mistral-7B consistently delivered satisfactory outcomes. We deployed a prototype system using Streamlit, creating a chatbot-like interface that allows users to interact with the AI advisor. This prototype could potentially increase the productivity of frontliners in the retail space and provide benefits for the industry.

Interplay between Past, Present and Future: ExploringAnalyzing The Effects Of Promotional Offers: Online Vs. Omni Channel Electronics Retailers

Interplay between Past, Present and Future: ExploringAnalyzing The Effects Of Promotional Offers: Online Vs. Omni Channel Electronics Retailers

Joint green dynamic order batching and picker routing problem using PSO with global worst experience

With the increasing importance of various countries’ initiatives on reducing carbon emissions (e.g., carbon border adjustment mechanism, CBAM), intelligent order picking systems have assisted electronic retailers in realizing a green supply chain. Previous studies on picker routing operations focused on adopting offline static customer order information to carry out operational decisions. However, in practice, the customer order information is updated dynamically; and high-efficiency warehouse layouts have been increasingly concerned. Therefore, this study creates a mixed-integer programming model for minimizing both the total carbon footprint and the total penalty cost for delayed orders in the joint order batching and picker routing problem with dynamic arriving orders and shipping time constraints in a high-efficiency fishbone warehouse layout. To solve this complex problem, a particle swarm optimization algorithm that integrates the swarm’s previous global and local worst experiences and a migration mechanism is further proposed to increase solution quality and computing efficiency. In addition, a three-dimensional space for the warehouse floorplan and shipping time constraints is designed to divide orders into batches to address the constraints. Theoretical analysis of this algorithm is conducted, and experimental analysis shows that this algorithm finds superior solutions than current practical strategies, to offer a valuable reference for carbon emission reduction in greening warehousing.

BEST BUY CO., INC.

In 2007, Best Buy was the leading electronics retailer in the United States with more than 941 stores, revenue totaling $31 billion, and a market cap of $21 billion. In 2005, Best Buy had adopted a new business model, culture, and customer-segmentation template called Customer Centricity. This move created volatility in the price of Best Buy stock because of the higher-than-expected employee costs that went with this new way of doing business and the difficulty of executing the old and the new business models simultaneously while the new model was rolled out. Best Buy responded to Wall Street's short-term focus in a myriad of ways. It first asked for investor patience, and stressed the strong operating results achieved in Best Buy stores operating under the new model. But in June 2007, after the stock dropped again, the CEO knew he had to decide whether to open more Best Buy stores, increase the company's dividend, or increase the stock-repurchase program.

Collection Responsibility Choice for Competing E-Tailing Supply Chains With Consumer Returns

For implementing consumer returns policy in e-tailing, to whom consumers should return their purchases is a crucial operations decision. We develop game models of competing e-tailing supply chains to study how price competition, channel structure of competitor, and consumer returns policy affect collection responsibility scenario. There are two collection responsibility scenarios: manufacturer collection and electronic retailer (e-tailer) collection. We find that in the common e-tailer setting, the channel collection efficiency and existence of the fixed cost are important for the manufacturer to decide whether to accept the e-tailer's transfer of collection responsibility; if manufacturer collection is optimal for a manufacturer, then it is a win-win scenario for both the manufacturer and the e-tailer, i.e., they are better off using manufacturer collection. If e-tailer collection has higher channel efficiency than manufacturer collection, then e-tailer collection is chosen; otherwise, in the presence of fixed cost, we show that 1) both manufacturers collect returned products if market scale is large, the e-tailer collects them if market scale is small; otherwise, different collection responsibility scenarios are used; 2) price competition accounts for the coexistence of different scenarios and reduces the range of manufacturer collection; 3) the channel structure of competitor can reverse the effect of price competition degree on collection responsibility; and 4) the manufacturer with higher restocking fee has a smaller incentive to collect returns products.

Role of IT capacity in customer churn for electronic retailers in oligopoly market using game theory approach

Role of IT capacity in customer churn for electronic retailers in oligopoly market using game theory approach

Тенденції та моделі розвитку електронної торгівлі в умовах цифрової економіки

At the present stage of the rapid formation of the information space, there is a need to use the instruments of the digital economy. One such instrument is e-commerce. The aim of the article is to identify current trends and models of development of e-commerce in the context of digitalization. To achieve this goal, the methods of analysis and synthesis, comparison, expert surveys, statistical analysis, structural and logical generalization were used. The article examines trends and patterns of development of the world e-commerce market. The dynamics of the main indicators of activity of Ukrainian wholesale and retail trade enterprises, which use information and communication technologies, are analyzed. It is defined that in modern economic conditions it is expedient to develop and implement a digital strategy for managing the commercial activities of trade enterprises on the basis of the conception of interaction marketing, theories of networks and stakeholders, which should contain the following elements: use of information instruments and digital channels; formation of a qualitatively new culture of marketing communications (integration of digital channels of marketing communication into a single system); ways to improve the quality of customer service; creation of an omnichannel environment based on the integration of all digital channels, retail outlets and back-office into a single information space. The key trends that will influence the development of e-commerce in the digital economy include: personalization of products and communication through information technology; adaptive approach to interaction with consumers; building a business strategy for brands, advertising and marketing strategies using digital instruments; application of an integrated approach to the management of commercial activities; creation of a fundamentally new marketing structure (the emergence of specialists in consumer preferences and data processing); acquisition of skills in collecting large databases and using them; ensuring multi-channel practice in marketing communications; implementation of chatbots as one of the most effective ways to provide instant customer support; development of business models for the organization of electronic retail.

Scanner data and the problem of selecting a price index formula

Scanner data are electronic transaction data most often from retail chains and obtained from electronic retail terminals. The identification of products takes place after scanning their characteristic barcode (e.g. EAN or GTIN), thus in the case of scanner data, we have full product information (price, sales volume, weight, description, etc.) at the most disaggregated level. In the cases of many countries, as well as Poland, this type of data is a valuable alternative source of information when estimating inflation. This paper discusses the main advantages but also the challenges of using scanner data in the CPI measurement. The main purpose of the paper, however, is to discuss the problem of selecting an optimal price index formula that would be appropriate for the highly dynamic (in terms of product rotation) scanner data. The considerations, supported by examples of empirical studies, will be demonstrated using the PriceIndices package in the R environment.

Sustainability via Extended Warranty Contracts: Design for a Consumer Electronics Retailer

Warranty is one of the most important attributes of any product, from both manufacturer and consumer points of view. Although the retailers connect manufacturers to customers by selling goods, traditionally, they have isolated themselves from warranty-related matters such as customer complaints and maintenance costs. However, recent trends in consumer behavior toward extended warranty contracts have changed this approach. While retailers have started to generate considerable revenue from the sale of these contracts, sustainability is also achieved by longer product life cycles. This study analyzed the failure behavior of different classes of cell phone products and their related costs through a chain of consumer electronics retailer operating in Türkiye. To compete on pricing and customer service, a novel policy was designed for the retailer to honor the contracts in house rather than underwriting to a third party insurer as the industry standard. The maintenance records of 328 previous failures were analyzed to plot a failure model. Failure mode and effects analysis was carried out to identify failure classes and the respective costs for extended warranty design for cell phones. The expected warranty costs for coverage of the third, fourth, and fifth years of operation were determined. The results show that the retailer may achieve the same level of profit by increasing customer satisfaction along with the sustainability of the product through repair actions.

Customer Trust and Interaction Quality as a Mediating: The Effect of Quality of Information on Purchase Decision

E-retail has one of the problems, such as not being able to provide examples of goods products that consumers want in digital form; therefore, this affects consumer purchasing decisions. Many factors underlie consumer purchasing decisions in e-retail. This study aims to analyze the role of customer trust and interaction quality in mediating the influence of quality of information on purchase decisions in electronic retail (E-Retail). The population in this study is e-retail users aged 18 years and over who have used or are currently using e-retail. The sample used was 100 people. The analysis technique uses Partial Least Square (PLS). The results showed that quality of information influences purchasing decisions and customer trust, customer trust influences purchasing decisions, quality of information influences interaction quality, and interaction quality influences purchasing decisions and customer trust. It was also found that customer trust and interaction quality can mediate the influence of quality of information on purchasing decisions.

Analisis Rantai Nilai Industri Ritel Elektronik (Studi Kasus: PT. Electronic City Indonesia Tbk)

This research aims to produce a map of the industrial value chain at PT. Electronic City Indonesia Tbk uses the industrial value chain analysis model. Researchers use the case study method, an empirical investigation method that examines a recent case or phenomenon in depth and reality, especially when the boundary between wonder and context is unclear. The subject of this research is PT. Electronic City Indonesia Tbk. The results of the research yield information on a list of companies engaged in the Indonesian electronics retail industry, a list of companies as product suppliers for the Indonesian retail sector where they are part of the product manufacturer and assembler industry (PT. Sony Electronics Indonesia, PT. Samsung Electronics Indonesia, PT. Sharp Electronics Indonesia, PT. LG Electronics Indonesia, and others) and a list of companies that are suppliers to the product assembly industry in Indonesia located outside Indonesia (Samsung Electronic, Sharp Corporation, LG Group, and Sony Corporation and others). The value chain of the e-commerce industry conducted by PT Electronic City Indonesia Tbk is relatively simple because it only has links with producers/suppliers and end consumers. There are four actors in the value chain of the retail electronics industry: component or raw material supplier companies, manufacturing companies, retail electronics companies, and end consumers. PT. Electronic City Indonesia Tbk has no products produced under its brand and does not carry out a value-added process. This can be a threat if manufacturers or suppliers experience production problems because it will hinder product sales in the retail electronics industry.

Identifying online purchasing intention in Egypt: a fuzzy set qualitative comparative approach

PurposeThe diffusion of electronic commerce has a notable impact on the economy's prosperity. This paper embraces complexity theory principles to examine the factors affecting Internet users' acceptance and use of electronic retailers. It is essential for the sustainability of electronic retailers to understand the motivations impacting online consumer behaviour. Symmetrical and asymmetrical methods are combined to examine the relationship between perceived ease of use, perceived enjoyment, web characteristics, online consumer reviews (OCRs) and online purchase intention. Further, symmetry and differences between males and females were examined.Design/methodology/approachData collected from 425 online consumers using an online structured survey was analysed using structural equation modelling (SEM) and fuzzy set qualitative comparative analysis (fsQCA). The net effects and causal configurations of the four proposed variables and online purchase intention were examined.FindingsThe SEM findings confirmed the significance of perceived enjoyment, website characteristics and OCRs on online purchase intention. Perceived enjoyment mediated the relationship between perceived ease of use and online purchase intention. The multi-group analysis confirmed the difference in antecedent impacts between males and females. The fsQCA findings revealed that multiple recipes lead to the occurrence of online purchase intention; in addition, the recipes leading to its absence do not mirror the previous ones.Originality/valueThe present study embraces complexity theory concepts in understanding online purchase intention using fsQCA methodology; further, the role of gender in online consumer behaviour was highlighted in the result discussion.

Prediction of customer review’s helpfulness based on sentences encoding using CNN-BiGRU model

<p>The infrastructure of smart cities is intended to save citizens’ time and effort. After COVID-19, one of such available infrastructure is electronic shopping. Online consumer reviews have a big influence on the electronic retail market. A lot of customers save time by deciding which products to buy online by evaluating the products’ quality based on user reviews. The goal of this study is to forecast if reviews based on reviews representation mining will be helpful while making online purchases. Predicting helpfulness is used in this suggested study to determine the usefulness of a review in relation to glove vector encoding of reviews text. Using an encoding-based convolution neural network and a bidirectional gated recurrent unit, the authors of this study constructed a classification model. The suggested model outperformed these baseline models and other state-of-the-art techniques in terms of classification outcomes, reaching the greatest accuracy of 95.81%. We also assessed the effectiveness of our models using the criteria of accuracy, precision, and recall. The outcomes presented in this study indicate how the proposed model has a significant influence on enhancing the producers’ or service providers’ businesses.</p>

Employment Trends and Relative Influence of U.S. Retail Subsector Employments on GDP

This paper studies employment trends of the U.S. retail industry and its twelve subsectors for the period 1998 through 2021. The retail subsectors are: motor vehicle and parts dealers (NAICS 441), furniture and home furnishing stores (NAICS 442), electronics retail stores (NAICS 443), building material retail stores (NAICS 444), food and beverage stores (NAICS 445), health and personal care retail stores (NAICS 446), gasoline stations (NAICS 447), clothing and accessories retail stores (NAICS 448), sporting goods, hobby goods, books, and music retail stores (NAICS 451), general merchandise stores (NAICS 452), miscellaneous retail stores (NAICS 453), and nonstore retail stores (NAICS 454). Comparing the pre-pandemic (2017-19) and post-pandemic (2019-21) employment growth rates, this study finds nonstore retailers (NAICS 454) and Food and beverages stores (NAICS 445) to be the most pandemic-proof subsectors in terms of retail employment. Besides multi-jurisdictional employment trends of this industry, this paper also explores the state-level influence of retail sub-sectoral employments on U.S. GDP using a fixed panel regression model. The retail subsectors that displayed statistically significant positive correlation with GDP are motor vehicle dealerships, health and personal care stores, clothing stores, and nonstore retailers such as electronic shopping and mail order businesses. Among the control variables, state-level total patent counts had statistically significant positive correlation with GDP.

Unraveling the Impact of Covid-19: Financial Distress and Resilience in Indonesian Retail Giants

This study aims to analyze whether PT. Matahari Department Store Tbk, PT. Hero Supermarket Tbk, PT. MAP Active Adiperkasa Tbk, and PT. Erajaya Swasembada Tbk experienced financial distress during the 2019-2021 period. The sample of these four companies was selected using purposive sampling. Data analysis using the Altman Z-score method. It was found that two companies, PT. Hero Supermarket Tbk in 2019 and 2020, with Z-scores of 2.9510 and 2.5147, and PT. Matahari Department Store Tbk in 2020-2021 with Z-scores of 2.1954 and 2.6608 are in the gray area. Between the two companies, PT. Hero Supermarket Tbk is facing financial distress in 2021 with a Z-score of 0.9288. PT. MAP Active Adiperkasa Tbk and PT. Erajaya Swasembada Tbk, is in healthy financial condition, because their Z-score is greater than 2.88. In conclusion, this study is an important financial health analysis conducted for companies operating in the Supermarket & Convenience Store, Clothing & Textile Retail, and Electronic Retail industries. The Altman Z-score has proven to be a valuable tool in identifying the risk of financial distress