Retail Industry Research Articles

Unveiling the Disruptive Force: Analyzing the Impact of Digital Shopping

The present research aims to analyze the influence of digital shopping on the traditional retail industry in Tamil Nadu. The present research executes a quantitative analysis utilizing the SPSS version 23 software package. A structured questionnaire survey technique is employed to gather the data from the traditional retailers in Tamil Nadu. A judgment sampling strategy has been adopted for analysis. The objective of the method is to collect data relating to conventional retailers' perceptions of the impact of online shopping applications. Descriptive statistics, ANOVA, regression, and Pearson correlation analysis were performed in the research. The study's outcomes revealed that digital shopping significantly impacts the growth and profitability of the offline retail industry. Furthermore, the study also evaluates the socio-economic and psychological factors prompting the purchasing behavior of consumers in Tamil Nadu. The study recommends that traditional retailers enhance their strategies to improve their business over online retail marketers.

Financial Analysis of China Duty-Free Group under the Framework of Harvard Analysis

Due to the COVID-19 in 2019-2022, global resident home quarantine, the economic downturn has led to lower household consumption levels than those before the epidemic, but with the economic and political policy and regulation and the availability of vaccines. Global COVID-19 is essentially over, at this time, the tourism retail industry is the main driver of economic recovery. In the tourism retail industry, China's duty-free industry is also a giant in the international retail industry. China Duty-Free Group has industry advantages, this article is based on the financial situation of China Duty-Free Group under the framework of Harvard analysis. Through the Oriental Fortune network, The National Bureau of Statistics of China, The China Immigration Bureau, statistic Data analysis on the China Duty-Free Group's environment and financial situation to analyze the development status and prospects of China Duty-Free Group, Conclusion for China Duty-Free Group after COVID-19 and acquisitions this year, the financial indicators in the capital increase have decreased. But this does not affect the dominant position of China Duty-Free Group in the future development, suggestions that China Duty-Free Group should hold the first position in China's duty-free industry in China's future development, from the Asian market to the international market in the global duty-free industry, make the full use of assets to expand their market share in the global tax-free industry.

Breaking into the black box of consumers’ perceptions on metaverse commerce: An integrated model of UTAUT 2 and dual-factor theory

The advent of the metaverse has unveiled new promises for the retailing industry, yet little empirical research has explored the factors influencing consumer adoption intention in this context. This study aims to fill this gap by employing an integrated model of UTAUT 2 - “The Unified Theory of Acceptance and Use of Technology 2”, and Dual-factor Theory to investigate both barriers and enablers in metaverse commerce adoption. Using a sample size of 567 respondents, the data analysis method employed in this study is Structural Equation Modeling (SEM) with Partial Least Squares (PLS). The results reveal the driving factors affecting consumer adoption intention in metaverse commerce. The study identifies perceived technological, regulatory, and cyber risks as significant barriers to consumer adoption intention in metaverse commerce. Conversely, the findings highlight the importance of performance and effort expectancy, perceived herd behaviour, hedonic motivation, and consumer innovativeness as key enablers driving consumer adoption intention in metaverse commerce. Interestingly, subjective norms were found to have an insignificant effect in this context. This research contributes to understanding consumer behaviour in the emerging field of metaverse commerce and provides valuable insights for practitioners and policymakers. The identified barriers and enablers can guide strategic decision-making, allowing businesses to address consumer concerns and capitalize on the factors that drive adoption intention in this novel environment. Future research avenues could explore additional factors and delve deeper into the dynamics of consumer behaviour within the metaverse.

WINNING MECHANISMS OF SURVIVAL: A CASE OF “BUL-ANON” RETAILERS IN RURAL PHILIPPINES

This study focused on the challenges faced by a group of independent and small retailers called Bul-anon retailers and identified coping mechanisms adopted. The study was conducted to investigate the coping me­chanisms that can be utilized by other members of the retail industry to continue to thrive despite difficulties. Findings indicated that the challenges faced by the Bul-anon retailers revolved around three of the four primary business functions: marketing, finance/accounting, and operations. To avoid the significant impact of the above challenges, retailers adopted coping mechanisms to stay in business amidst large department stores and other businesses. How they handled their customers, being customer-oriented, was the winning mechanism for the survival of these retailers.

A Financial Analysis and Valuation of Home Depot

This study aims to research and analyze the firm’s valuation of Home Depot by exploring the company’s background and recent events, evaluating company performance, forecasting future development, and discovering the firm’s strategy and risk. The performance evaluation uses liquidity, solvency, and profitability to assess the firm operations and use of resources. The additional valuation adopts current and next year’s forecast financial data to measure the company’s EPS and revenue growth rate, P/E, PEG, and GP/A ratios. The results show that Home Depot has high liquidity, high profitability, and low solvency from its operational performance, as well as a high long-term valuation forecast in the home improvement retail industry. This consequence implies that Home Depot may have efficient business management and sound financial health by effectively meeting short-term obligations and using assets to generate revenue. Meanwhile, the company may also pose several risks, including an unstable economic environment, difficulty meeting long-term obligations, the continued decline in annual gross margins and ROIC, and potential stock overvaluation for investors.

Corporate Value Assessment based on the EVA Model and Relative Valuation

As a risk-averse commodity, gold has seen new development opportunities in retail due to factors (e.g., geopolitical risks and conflicts, economic uncertainties, and inflation). Consequently, more and more investors are focusing on the gold retail industry. Evaluating the value of gold retail enterprises using scientific and effective methods is of great significance to both managers and investors. Therefore, this paper uses Chow Tai Seng, a Chinese gold retail enterprise, as a case study. Based on the company's development characteristics, we employ the EVA absolute valuation method and relative valuation methods including P/E, P/B and P/S ratios for valuation. The study finds that although its EVA values show a general downward trend from 2019 to 2023, they remain positive, indicating that the company's overall development is still on track. The development of enterprise valuation theory has gone through the MM (Modigliani-Miller) theory, Free Cash Flow Valuation Model, and the Capital Asset Pricing Model, among others. These theoretical models have gradually improved, and the theoretical system is continuously evolving. By summarizing and reviewing valuation theories and methods, this paper employs the DDM for valuation and the P/E ratio method under relative valuation based on the company's development characteristics. Combining these two valuation methods with the company's actual financial data and relevant value theories, the company can attract investors and address undervaluation by increasing its exposure through modern multimedia channels and enhancing data transparency.

Drivers of metaverse adoption for enhancing marketing capabilities of retail SMEs

Small and medium-sized enterprises (SMEs) rely on a thriving distribution network and digital technologies, including the metaverse, to remain competitive. The retail industry is perceived as a portfolio-based and granular business. Hence, retail SMEs can be a key source of innovation and a major source of growth that need technical flexibility to react quickly to changing customer needs. Therefore, grounded in the TOE framework, this study is undertaken to explore the drivers of metaverse adoption for enhancing the marketing capabilities of retail SMEs. Online surveys were used to gather primary data from 300 marketing practitioners employed in retail SMEs. Subsequently, the data were analysed using quantitative research methodology. The finding reveals that the metaverse is gaining attention from retail SMEs due to its technological, organisational, and environmental drivers, as well as its ability to provide immersive experiences to customers. Thereafter, metaverse adoption enhances the marketing capabilities of SMEs with new sales channels, tailored marketing, and increased customer reach with an understanding of the marketplace focused on customer relations, market research, and cross-management capabilities.

System development for enhancing social media advertisement engagement through XLNet-based personality classification

This research focuses on addressing the challenge of implementing personalized advertisements in the retail industry, where existing methods often face complexities that hinder their swift and large-scale adoption. The primary objective of this study was to develop a scalable and efficient social media advertisement personalization system by employing advanced personality classification techniques. The system utilizes the myPersonality dataset, grounded in the Big 5 OCEAN traits theory, to accurately classify user personalities. By integrating the XLNet model, optimized for personality classification, the system achieves a classification accuracy of 97.47 %, with precision, recall, and F1-Score values of 0.95, 0.94, and 0.94, respectively. The findings demonstrate that personalized advertisements, driven by accurately classified personality traits, significantly enhance user interaction rates, showing a 24 % improvement over generalized advertisements. This improvement in engagement suggests that the system can effectively personalize advertisements to resonate more deeply with users, fostering stronger connections between users and the advertised content. The proposed system's high accuracy and improved interaction rates make it a valuable addition to current marketing strategies, enhancing both engagement and conversion rates. This innovative approach has the potential to transform personalized advertising, making it more effective and widely adoptable within the marketing sector

Spatial Distribution Characteristics and Influencing Factors of the Retail Industry in Ningbo City in Eastern China Based on POI Data

Spatial Distribution Characteristics and Influencing Factors of the Retail Industry in Ningbo City in Eastern China Based on POI Data

The Influence of Store Atmosphere, Perceived Price, and Customer Experience on Repurchase Intention at Niceso Rungkut Surabaya

The advancement of modern technology and economic growth have made Indonesia a very potential retail market, especially in the modern retail sector. In addition, retail competition is also increasing with the presence of foreign retailers competing with domestic retailers. The domestic retail industry in question is Niceso. The purpose of this research is to understand the reasons for purchase, perceptions of Niceso, and the level of consumer desire in influencing repeat purchase behavior at the store. This research employs a quantitative research method, and the measurement of variables is conducted using a Likert scale. The sampling technique uses non-probability sampling through a convenience sampling approach, and the sample size obtained is 102 respondents. The data analysis technique used is the PLS (Partial Least Square) method. This method is used to conduct validity and reliability tests, structural model, and hypothesis testing from the existing data. The results of this study indicate that store atmosphere, perceived price, and customer experience each contribute and have a significant influence on the repurchase intention of Niceso Rungkut Surabaya consumers.

Review of literature on capital structure: Independent and Dependent Variables

Choosing a capital structure presents many difficulties for businesses. Choosing the right balance between debt and equity is one of the most important decisions. A poor capital structure decision has the power to completely ruin any company's success. Researchers have shown interest in analyzing the capital structure of the companies. The main objective of this paper to review these empirical studies of capital structure and to identify frequently used parameter by the researchers for last 14 years. The empirical capital structure literature is reviewed in this paper, with a focus on works released since 2010. The research paper also intends to address particular issues for further investigation while highlighting the significant gaps in the literature on the factors influencing capital structure and it compares the outcomes of practical research with theoretical expectations. This study investigates the independent factors and their dependent effects that lead companies to stray from ideal capital structures. This study primarily focuses on review of studies in the context of: (i) Capital structure in the banking and financial institutions sector; (ii) Capital structure in the metals industry; (iii) Retail industry; (iv) Software industry; and (v) Pharmaceutical industry. Only secondary data were used in this present study.

Strategy for striking the omnichannel balance in Retail 4.0

PurposeThe rise of Industry 4.0 led to digitally-enabled evolutionary and radical changes in all branches of the retail industry, resulting in the emergence of the distinct term “Retail 4.0”. Within this paradigm, particular emphasis is placed on forming a balanced system of omnichannel sales and customer service, allowing reaching a synergistic effect in the face of constant changes, turbulence and uncertainty in the business environment. The main objective of this study is to offer and justify a practical strategy for optimal utilization of sales channels and customer service provision within the Retail 4.0 paradigm.Design/methodology/approachThe conceptual argument of the study is based on the review of the literature and illustrative case studiesFindingsThe decision-making model proposed in this study provides a roadmap for retailers. It underscores the need for a data-driven approach, where decisions are informed by real-time analytics and customer insights. This model also advocates for a flexible yet structured approach to managing various sales channels, ensuring that each channel complements and enhances the other.Originality/valueThe study offers and justifies an original five-stage process model for forming a balanced system of omnichannel sales and customer service.

Customer gratitude expressions and FLEs’ prosocial behavior: insights from delighted customers

PurposeThis study aims to investigate the impact of customers’ delight on the likelihood of frontline employees (FLEs) receiving expressions of gratitude from customers, as well as the subsequent effects on their customer-focused and coworker-focused behaviors. Additionally, it examines how customer orientation moderates the relationship between FLE’s likelihood of receiving customer gratitude expressions and their performance behaviors.Design/methodology/approachThe study used a sample from a Canadian retailer specializing in the sale of artistic and creative materials for artists, crafters and hobbyists. Longitudinal data was collected through a survey administered to frontline employees, unit managers and customers, spanning 7 assessment waves over a 12-month period. In total, the data set comprised 1,609 individual observations and 3,533 customers nested within 35 business units. The hypotheses were tested by using a multilevel longitudinal modeling approach.FindingsThis research has yielded important insights. First, significant relationships emerged between enhanced customers’ delight and an increased likelihood of FLEs receiving expressions of gratitude from customers. Second, gratitude expressions received from customers were found to be positively associated with prosocial behaviors toward both customers and coworkers. Third, the findings indicate that the impact of receiving customer gratitude expressions on FLEs’ performance behaviors is more pronounced for employees with a high level of customer orientation.Practical implicationsThis study highlights the importance of investing in relationship-building strategies aimed at enhancing customers’ delight. This can motivate customers to express their gratitude toward service employees and to elicit higher prosocial behaviors from employees.Originality/valueThis study offers theoretical insights into gratitude, customer behaviors and employee performance in the retail industry. A pivotal contribution of this study to marketing literature lies in its paradigm shift, redirecting attention from the traditional examination of firm-customer relationships to a nuanced exploration of customer–employee relationships.

Research on the Path of Low Carbon Transformation of Traditional Retail Enterprises Empowered by Digital Technology

The retail industry is an integral part of the service sector. In the context of the booming development of the service industry and digital technology, this paper explores the low-carbon transformation path for traditional retail enterprises empowered by digital technology. Initially, a literature review reveals that as the overall scale of the service industry continues to expand, its negative impact on the environment is also intensifying. Reducing energy consumption and carbon emissions has become a rigid constraint faced by the service industry; Meanwhile, digital technology is becoming an important means to empower traditional service enterprises in their low-carbon transformation. Subsequently, through case study analysis, it is pointed out that digital technology can empower the low-carbon transformation of traditional retail enterprises from three aspects: reducing energy consumption, decreasing emissions, and saving resources. Finally, in response to the existing obstacles in implementing low-carbon transitions such as insufficient motivation for transition, constraints on investment costs in low-carbon technologies, and difficulties in managing energy and carbon emissions, practical paths for digital technology to empower the low-carbon transformation of traditional retail enterprises are proposed. These include enhancing the motivation for enterprise low-carbon transition, overcoming constraints on capital and talent, and improving technical support capabilities for the transformation.

Growth hacking business analytical tools for small and medium enterprises

ABSTRACT This study focuses on the growth hacking business analytical tools for small and medium enterprises to improve their business operations. The study analysed 11 prominent sectors, namely retail, e-commerce, travel, finance, telecom, healthcare, customer support, sales review, project management, insurance and manufacturing industries, to identify the critical challenges and propose solutions using predictive business analytics. The Triangulation approach has been employed through literature review, interview with SME startups incubated in IIT Madras Research Park and other SMEs in Chennai to provide an organized framework using an “Industry outlook Analysis” that suggest business analytical tools to overcome their challenges due to lack of resources. The study suggests that affordable predictive analytics can help SMEs overcome these challenges by providing insights into customer behaviour, operational efficiency and market trends. Overall, the study highlights the importance of data-driven decision-making tools that are available for SMEs to remain more competitive in the market environment.

Quantitative PCR assays as a monitoring tool for bacterial genera in fresh fish fillets

Fresh fish fillets are a valuable but highly perishable food, and their rapid microbial deterioration is a drawback for food safety and sustainability of aquaculture, food and retail industries. Quantitative PCR (qPCR) assays based on 16S rRNA gene (16S) sequences were developed for the most abundant bacteria genera detected by metagenomics in fresh or processed fish fillets. The efficiency and specificity of six qPCR assays (for 16S of all bacteria or genera Shewanella, Pseudomonas, Carnobacterium, Janthinobacterium and Massilia) was verified using in silico predictions, cloning, sequencing and phylogenetic analyses of amplicons obtained from refrigerated control or high-pressure processed (HPP) European sea bass (Dicentrarchus labrax) fillets. In HPP sea bass fillets, significant decreases in total bacteria 16S and of Shewanella, Pseudomonas, Carnobacterium and Janthinobacterium 16S compared to control fillets were confirmed by qPCR, after 11 days of refrigerated storage. The qPCR assays were successfully applied to monitor microbial contamination during refrigerated storage of fresh fillets from commercial (retail) sea bass and gilthead sea bream (Sparus aurata). Significant increases in total bacterial and Shewanella, Pseudomonas, Carnobacterium and Janthinobacterium contamination were detected after 7–14 days. 16S copy number for total bacteria and the four target genera positively correlated with total viable counts using culture enumeration. 16S of Massilia, that is abundant in fresh fish fillets, did not significantly change during storage. The six validated qPCR assays developed are proposed as specific, sensitive, culture-independent methods for monitoring quality or processing outcomes for fish fillets during cold chain storage.

The Way of Tea Drinking Survival in the Internet Era----- Taking Heytea as an Example

The Internet model has promoted the development of commerce, not only the traditional retail industry has been developed, and the catering industry such as milk tea and coffee shops is booming. As the first generation to open the online operation model, although the Internet + model has begun to take shape, there are still gaps in the relevant tea drinking culture. Based on the literature research method and case analysis method, this paper analyzes the existing marketing model of Heytea and proposes relevant improvement policies, with the purpose of widening the gap with other related tea brands and improving the core competitiveness of its products. As the earliest generation of beverage stores to enter the Internet + model, Heytea has rich experience in marketing planning, online and offline marketing activities. This paper analyzes the marketing based on the Internet + model through researching the brand cross-border co-branding and innovative marketing activities of Heytea.

Navigating Inventory Management Challenges in Contemporary Fashion Retailing: A Circular Economy Approach

Our research focuses on decreasing the pollution caused by excess inventory in the fashion retailing industry. We choose to focus on this problem due to the lack of solutions in this region. In the past, people just focused on how to use environmentally friendly materials and how to produce with the lowest amount of pollution. To find a new method to solve the pollution problem during and after the consumers purchasing, we built a model containing the primary fulfillment, retailers, secondary fulfillment, secondary retailers, brands and factories, etc. We use them as examples to find out how to end the combustion of excess inventory. We try to change the linear (in the end, the clothes are useless and combusted) to a circle(we could use one raw material several times) to avoid lots of pollution. The final answer is that we did that by increasing the service age of the products and information transparency inside the fashion retailing industry.

The emotional side of price: reference price as a decision maker in consumer purchase

PurposeThe objective of this study is to elucidate the influence of reference price on consumers' willingness to buy (WTB). Additionally, the study seeks to investigate the impacts of consumer perceived value (CPV): emotional, social, and monetary levels in relation to reference price and WTB. Furthermore, it aims to identify the moderating effect of product type, distinguishing between hedonic and utilitarian products.Design/methodology/approachData collection was conducted through an anonymous questionnaire survey using a web-based platform called Prolific. The sample consisted of 258 individuals. The study performed experimental studies to assess the connections among variables and used structural equation modeling as well as Hayes' PROCESS macro models 4 and 8.FindingsPresenting reference price alongside regular prices for products significantly enhances WTB. Furthermore, the mediating effect of the CPV exhibited a significant influence, particularly in the emotional and monetary dimensions but not although the social aspect. Additionally, the findings unveiled substantial variations in the mediating effect of CPV when examining hedonic versus utilitarian products.Research limitations/implicationsPresenting reference price alongside regular prices for products significantly enhances WTB. Furthermore, the mediating effect of the CPV exhibited a significant influence, particularly in the emotional and monetary dimensions but not although the social aspect. Additionally, the findings unveiled substantial variations in the mediating effect of CPV when examining hedonic versus utilitarian products.Originality/valueThe study contributes to the literature by integrating emotional values into pricing strategies. Furthermore, the findings provide insight for managers into establishing a consistent method for implementing price display advertisements on the basis of the product type within the retail industry.

Supply chain efficiency a structural analysis in turkey's retail sector

Goal: To investigate the impact of the Internet of Things (IoT) on the effectiveness and environmental friendliness of supply chains in Turkey's retail industry. Methodology: Applies structural equation modeling to examine data from 315 retail experts, specifically investigating the impact of IoT on supply chain integration and agility within a defined timeframe. This methodology involves doing a thorough examination of the adoption of technology and its impact on operational performance. Results: Finds notable enhancements in supply chain performance by implementing IoT, as demonstrated by improved integration, flexibility, and immediate access to real-time data. These technological improvements enhance the sustainability, efficiency, and flexibility of supply chain systems. Limitations of the investigation: Recognizes limitations pertaining to the study's extent, techniques for gathering data, and the possible fluctuations in IoT adoption rates among various retail industries. Practical implications: Proposes practical approaches for retail managers to utilize IoT technology in order to enhance supply chain efficiency and sustainability, highlighting the significance of integrating technology and implementing responsive mechanisms. Originality: This study provides unique and valuable insights into how the Internet of Things (IoT) can contribute to the improvement of sustainable supply chain practices in the Turkish retail industry. It serves as a valuable resource for both professionals and researchers who are interested in the intersection of technology, sustainability, and supply chain management.