Retail Service Research Articles

Организационно-экономические и управленческие решения развития розничных услуг торговых сетей на основе внедрения системы управления лояльностью покупателей

The article is devoted to the study of the issue of improving the process of interaction with customers and the development of organizational, economic and managerial solutions for the development of retail services of trading networks based on the development and implementation of modern digital solutions for managing loyalty systems. The work conducts research in the field of improving customer interaction processes, namely maintaining the customer base and attracting new customers, provides an overview of loyalty programs in Russia and digital solutions for automating customer loyalty management systems. The promising areas of customer loyalty management identified during the review were confirmed by data from open sources. The relevance of the topic is due to the proposal to manage a loyalty system based on the digitalization of this business process. The authors examined the problem of increasing the customer focus of retail chains, which is popular in the current economic conditions, based on the introduction of a customer loyalty system. An accessible way to solve the problem was identified, which consists in the development and implementation of an information system for loyalty management. The functional composition of the information system being developed to ensure the effective implementation of the business process is indicated, and a list of organizational and economic measures for the successful implementation of the system is provided.

A comprehensive view of biometric payment in retailing: A complete study from user to expert

The new financial and commercial scenario driven by technological advances has undergone a rapid reconfiguration in the recent years. Innovation has generated new payment alternatives that are transforming the concept of money and payment habits among consumers. One of the most novel payment systems nowadays is known as biometric payment. Improved payment systems will improve retailing and consumer services. The aim of this study is to develop an analysis of biometric payment based on two complementary studies. In the first one, the variables predicting the intention to use this technology are determined on a sample of 1905 potential users by means of different feature selection methodologies from artificial intelligence in a holistic model that integrates the principles of the UTAUT2 model, the General Risk Theory, and the Trust Theory. In the second study, two panels of Fintech industry experts compare these results. The overall insights obtained show that perceived risk, trust, and social influence are the variables that, from the experts’ experience, users consider most important when employing this technology. This research provides useful information for financial and business decision-makers in companies interested in commercializing this type of technology.

Participation and returns from informal service-oriented non-farm enterprises: Evidence from a survey of Nigerian households.

We investigate the factors that influence the selection and productivity of informal service-oriented family enterprises in Nigeria. Using nationally representative micro-data from the Nigerian General Household Survey (2010-2015), we employed random-effect probit and selectivity-adjusted regression models to estimate and analyze the results. The findings reveal that the location of informal Non-Farm Household Enterprises (NFHEs)-whether home-based or non-home-based-significantly impacts the wholesale, retail, personal, and consultancy service sectors operated by informal NFHEs. This impact remains significant even after accounting for variations in individuals, households, or locational characteristics. Furthermore, when considering selectivity in the earnings equation, we found that home-based informal enterprises exhibit lower productivity compared to non-home-based enterprises, a difference that varies across sectors. Overall, factors such as the gender of business owners, educational levels, geopolitical zones, infrastructure, and business characteristics play a crucial role in determining the locational and productivity disparities among service-oriented enterprises in Nigeria. Key recommendations stemming from this study include addressing gender-based segregation and economic disparities, prioritising financial inclusion for small business development, bridging infrastructure gaps, and implementing policies that acknowledge and bolster the informal sector.

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.

Exploring how retail and logistics service provider managers make sense of sustainability in last mile delivery

PurposeAn increasing number of last mile deliveries (LMDs) pose many sustainability challenges that retailers and logistics service providers (LSPs) can address. Using cognitive frames (CFs) as a lens, this study explored how retail and LSP managers make sense of sustainable LMDs.Design/methodology/approachThe methodological approach used is a multiple embedded case study. The data were obtained from interviews with retailers and LSPs, supplemented with secondary data for triangulation.FindingsThe findings present the operational aspects of LMDs that managers associate with sustainability and indicate that retail and LSP managers frame sustainability primarily as emission reduction. Managers indicate an externalization of responsibility and a compartmentalization of the supply chain, in which social sustainability is not associated with the last mile. Most managers indicate hierarchical CFs regarding sustainability, in which sustainability is an important topic but is subordinate to economic interests.Practical implicationsCollaboration between retailers, LSPs and other stakeholders is viewed as challenging but could alleviate some of the sustainability shortcomings and aid in the paradoxical framing and inclusion of social issues.Originality/valueA conceptualization of managerial CFs for sustainable LMDs, together with empirical frame indicators and three propositions, is presented, providing novel insights into how paradoxical CFs could make LMDs more sustainable. This approach illuminates the possibilities for how to untangle the operational manifestations of managerial framing and adds to the empirical exploration of CFs in supply chain management.

Applying k‐nearest neighbors to time series forecasting: Two new approaches

AbstractThe k‐nearest neighbors algorithm is one of the prominent techniques used in classification and regression. Despite its simplicity, the k‐nearest neighbors has been successfully applied in time series forecasting. However, the selection of the number of neighbors and feature selection is a daunting task. In this paper, we introduce two methodologies for forecasting time series that we refer to as Classical Parameters Tuning in Weighted Nearest Neighbors and Fast Parameters Tuning in Weighted Nearest Neighbors. The first approach uses classical parameters tuning that compares the most recent subsequence with every possible subsequence from the past of the same length. The second approach reduces the neighbors' search set, which leads to significantly reduced grid size and hence a lower computational time. To tune the models' parameters, both methods implement an approach inspired by cross‐validation for weighted nearest neighbors. We evaluate the forecasting performance and accuracy of our models. Then, we compare them to other approaches, especially, Seasonal Autoregressive Integrated Moving Average, Holt Winters, and Exponential Smoothing State Space Model. Real data examples on retail and food services sales in the United States and milk production in the United Kingdom are analyzed to demonstrate the application and efficiency of the proposed approaches.

The impact of support on behavioural intention in a customer-to-customer retail service context

ABSTRACT Although previous studies have focused on customer behaviour in an e-commerce context, few have examined experience with customer-to-customer (C2C) platforms. Thus, the main purpose of this study was to identify the relative impact of two types of support (i.e. emotional and information) on customers’ behavioural intention in the C2C area. A total of 181 valid questionnaires on the C2C platform experience was collected and analysed using partial least squares structural equation modelling. The results show that both emotional and information support are major drivers of customer trust in sellers and the C2C platform. Also, the impact of customer trust on behavioural intention was evaluated. Last, multi-group analysis identified the differences in customer behaviour across gender, age, and income. Emotional support is a stronger determinant of trust among male, old, and low-income customers, whereas information support is more impactful in female and young C2C customers. The current study contributes to the internet commerce literature by providing an integrative view of collaborative consumption.

The application of database systems in information management

Database technology has always been a focal point of interest for enterprises and organizations in the field of information management. With the continuous growth and diversification of information, effective information management has become crucial. This paper aims to explore the extensive applications of database systems in information management. Firstly, the paper reviews relational and non-relational databases. Subsequently, it delves into the current applications of database systems in various domains, including enterprise management, retail, education, and government and public services. In the realm of enterprise management, database systems provide a solid foundation for information management by ensuring the timeliness, accuracy, and reliability of data. In the retail industry, they support inventory management, sales analysis, and enhance the user experience. In education, database systems are used for student information management, teaching data analysis, and online learning. In the government and public services sector, they facilitate information sharing and data transparency, while playing a critical role in crisis management and emergency response. This paper highlights the significance and diverse applications of database systems in different domains, offering insights into the current research trends and future prospects in this field.

Consumer’s acceptance of retail service robots: mediating role of pleasure and arousal

ABSTRACT This study explores the influence of consumer emotions, specifically pleasure and arousal, on the intention to use retail service robots. Through a survey of 323 people using an online snowball sampling technique and analysis via the PLS-SEM method, it finds that subjective norms, technological self-efficacy, habitual behavior, and attitudes significantly affect users’ intentions. The research notably reveals that pleasure plays a more crucial role than arousal in mediating how consumers’ perceptions impact their willingness to interact with these robots. By integrating the Theory of Reasoned Action, self-efficacy theory, and the PAD model (pleasure, arousal, dominance), the study enhances the understanding of human-robot interaction. It provides actionable insights for businesses, suggesting that emphasizing emotional aspects, particularly pleasure, can be a strategic approach to encourage the adoption of service robots. These insights are valuable for designing marketing strategies and service experiences that effectively increase consumer engagement with robotic technology. Top of Form.

Serving customers through chatbots: positive and negative effects on customer experience

PurposeService research offering a view of both the dark and bright sides of smart technology remains scarce. This paper embraces a critical perspective and examines the conflicting outcomes of smart services on the customer experience (CX), with a specific focus on chatbots.Design/methodology/approachThis study uses empirical research methods to examine a single case study where an online retail service provider implemented a chatbot for customer service. Using discourse analysis, we analysed 7,167 conversations between customers and the chatbot over a two-year period.FindingsThe analysis identifies seven general themes related to the effects of the chatbot on CX: interaction quality, information gathering, procedure literacy, task achievement, digital trust, shopping stress and shopping journey. We illuminate both positive (i.e. having a pleasant interaction, providing information, knowing procedures, improving tasks, increasing trust, reducing stress and completing the journey) and negative outcomes (i.e. having an unpleasant interaction, increasing confusion, ignoring procedures, worsening tasks, reducing trust, increasing stress and abandoning the journey).Originality/valueThe paper develops a comprehensive framework to offer a clearer view of chatbots as smart services in customer care. It delves into the conflicting effects of chatbots on CX by examining them through relational, cognitive, affective and behavioural dimensions.

Towards innovation capability in retail services: managing the tensions of exploration and exploitation

ABSTRACT Retailing is said to be at a critical period where much higher demands are being placed on retail actors to develop their capability for explorative innovation for lasting competitive advantage. Developing innovation capabilities is a challenging pursuit, however, and is a topic that is under-researched in the retail context. This paper thus investigates tensions that emerge when retail firms pursue explorative innovation in an organisational context characterised by exploitation-oriented activity, and how these are managed through various organisational mechanisms. The findings from our multiple case study reveal how developing innovation capability in incumbent retail firms gives rise to complex tensions related to strategic intent, organisational culture and structure. These are perceived as organisational paradoxes and managed as such due to the need to balance these opposing poles, emphasising the need for balance instead of making an explicit choice. Retail incumbents establish differentiating mechanisms for innovation, complemented by various integrative mechanisms. The study shows that in order to enable explorative, radical innovation in retail firms, innovation work needs to be differentiated from that of ongoing operations, provided that integration is facilitated at operational and strategic levels. By focusing on incumbent retail firms using exploration-exploitation paradox as a theoretical lens, the study contributes with new perspectives on building innovation capability in this context. The paper gives evidence to how developing innovation capabilities lies in the management of these complex tensions as paradoxes using the combination of differentiation and integration mechanisms.

Marketing Communication Strategy in the Retail Sector: Examining Repurchase Intention

In the face of intensifying market competition, the significance of retail marketing strategies and tactics cannot be understated, as they are pivotal in enhancing customers’ satisfaction, fostering loyalty in customers, and ultimately elevating the likelihood of repurchase intentions. This research strives to discern the distinct attributes of customers and gauge their perceptions of the marketing strategies employed by Hypermarket Companies. Additionally, it examines the interplay between customer satisfaction, loyalty, and the consequent cultivation of repurchase intentions. Furthermore, the study explores the foundational retail marketing strategies that underpin the establishment of customer loyalty. The analytical approach encompasses Confirmatory Factor Analysis, SEM-PLS, and Biplot techniques. The findings underscore a customer profile primarily comprising males within the 18–29 age bracket, married, childless, holding undergraduate degrees, enjoying middle-income status, and engaged as private sector employees. Notably, the paramount driver shaping loyalty is the quality of retail service. It is intriguing to note that while the retail mix strategy within Bandung's hypermarkets is predicted to wield no direct influence on loyalty, marketing communication emerges as a potent determinant significantly impacting repurchase intentions. This study contributes to understanding customer behavior and loyalty in hypermarkets. It sheds light on the critical role of service quality in building loyalty. It highlights the importance of effective marketing communication for encouraging repurchase intentions and offers valuable insights for retail marketing strategies. Doi: 10.28991/ESJ-2024-08-01-08 Full Text: PDF

Development And Validation of A Scale For Measuring Petro Retail Service Quality: A Bilateral Approach

Purpose: Global retail fuel markets are being disrupted by a number of broad themes that are being highlighted by the emergence of alternative energy, new mobility models, and elevated customer expectations that are centered around convenience and personalization. Consumers express a need for individualized products and services that take into account each individual. Digital is becoming the norm in the new situation. The changing purchasing habits of customers are a result of technological advancements. As a result, factors affecting the consumer experience have also changed. The purpose of the study is to ascertain Petro Retail's service quality scale from an Indian standpoint. 
 Design /Methodology/ Approach: The study was conducted from October to December 2022 at fuel stations in Mumbai and Ranchi with face-to-face interviews with OMC officials at HQ and field levels. The primary data was collected through a Quantitative field studyanalysedlyzed using suitable statistical tools. Exploratory Sequential Mixed Method design ( Qual-Quan ) was followed for the study.
 Findings and Originality: Technology advancements significantly impact consumers and industries and transform people's lifestyles and behaviour. Predictive analytics, artificial intelligence, and the Internet of Things are important components in developing customer-facing projects that result in the creation of service protocols for improved purchasing experiences.
 Technology adoption in petroleum retail is dispersed, with IoT, automation, and AI/ML-based technological solutions being tested in isolated ways without a centralized understanding of the whole value chain. Utilizing assets more efficiently is the main goal of this type of technology adoption. Nevertheless, few applications have been explored to improve consumer purchasing behavior, such as identification and satisfaction. In the digital age, IoT is altering customer expectations and controlling the experience in India's petroleum retail industry from the viewpoints of both service providers and customers (a dyadic approach). Accordingly, the service quality has also evolved over a period of time. There is very limited work carried out on the Petro Retail service quality. The scale developed with the bilateral approach shall help academians and industry managers to understand the service quality in petro retail, and the “BISQUE” constract can be used for measuring the same. The study is one of its kind on the aspect of petro retail.

“With great power comes great responsibility”: Exploring the role of Corporate Digital Responsibility (CDR) for Artificial Intelligence Responsibility in Retail Service Automation (AIRRSA)

Scholars conceptualized the role of Corporate Digital Responsibility (CDR) to emphasize the ethical issues unique to the digital context by pushing all the actors involved in developing and integrating digital technologies and related data processing to act ethically and responsibly. However, how to apply AI services more ethically and develop AI equipped with moral/ethical intelligence are still open questions.Accordingly, this paper aims to understand the managerial applications and tools of Corporate Digital Responsibility (CDR) in AI retail service automation to identify the CDR value for consumers and retail managers. We link the five AI intelligence types (verbal-linguistic, logic-mathematical, visual-spatial, social, and speed-processing) to CDR strategies to produce value for retailers and consumers. Specifically, we define intelligent retail service automation, emphasizing actions, tools, and (privacy) concerns, and discuss the role of CDR in AI for intelligent retail service by developing the new concept of Artificial Intelligence Responsibility in Retail Service Automation (AIRRSA). Finally, we provide implications for scholars, managers, and policy-makers while proposing future challenges.

A priority queueing-inventory approach for inventory management in multi-channel service retailing using machine learning algorithms

PurposeNowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.Design/methodology/approachThis paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.FindingsTo investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.Originality/valuePrioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

The Analisis Retail Service, Customer Experience, Switching Barriers, Kepuasan Konsumen Terhadap Loyalitas Konsumen UMKM Ritel

Malls and modern retail stores established in Jember Regency are connected to each other even though they are close together, causing problems for SMEs engaged in the retail business. Therefore, it is necessary to explore how to make consumers loyal to retail SMEs by introducing retail services, changing barriers through customer experience and consumer satisfaction, so that retail SMEs can continue to exist and develop. The aim of this research is to determine the barriers to consumer loyalty through customer experiences with retail services and consumer satisfaction in retail MSMEs located in Jember Regency. The design of this research is confirmatory research and at the same time explanatory research. The research population is all buyers from MSME retail companies in Jember Regency. Standardization of Retail MSMEs that sell daily needs and the mini market concept. The research sample was taken using non-probability sampling technique using purposive sampling and random sampling. The sample size of this research is 225 respondents. The data analysis method used in this study is; descriptive statistical analysis and structural equation modeling (SEM) using SEM-PLS. The results of the research are: Retail services have no effect on consumer satisfaction, customer experience has an effect on consumer satisfaction. Barriers to change affect consumer satisfaction. Retail services influence consumer loyalty. Customer experience influences consumer loyalty. Switching barriers do not affect consumer loyalty. Consumer satisfaction influences consumer loyalty. Retail services have no effect on consumer loyalty through consumer satisfaction. Customer experience influences consumer loyalty through customer satisfaction. Switching barriers does not affect consumer loyalty through consumer satisfaction.

Wait time speeds up: effects of scent arousal on time perception in service marketing

PurposeThis study examines the effects of scent arousal on consumers' time perception in retail service environments and further explores how the effect is moderated by consumer-perceived stress.Design/methodology/approachA laboratory experiment (Study 1) and a field experiment (Study 2) were conducted to examine the relationship between scent arousal and time perception and the mediating effect between scent arousal and consumers' store evaluations. Another laboratory experiment (Study 3) was conducted to explore how consumers' stress modifies the scent arousal effect.FindingsConsumers in a low-arousal scent condition perceived a shorter duration of time than those in a high-arousal scent condition. This finding was verified in a field experiment, whereas scent arousal affects consumers' store evaluations through the mediating effects of time perception. However, the impact of scent arousal on time perception was attenuated in high-stress conditions.Originality/valueTime duration perception is an important indicator in the retail service marketing process. Evidence shows that underestimating time duration in the shopping process represents positive responses. This study extends prior research by examining how scent arousal influences time perception and how consumers' stress moderates scent arousal’s effect.

Big Data Analysis in Consumer Behavior: Evidence from the Retail, Healthcare, and Financial Services Industries

As a matter of fact, big data analytics has quickly become one of the cornerstones of various industries such as retail, healthcare, and financial services. This study delves into the applications of big data analytics within various sectors, exploring how models such as AISAS, PDCA, and customer segmentation can assist organizations in crafting successful data-driven strategies. Based on case studies, it is found that retailers utilizing the AISAS model can significantly increase customer engagement and optimize marketing strategies, while healthcare organizations applying PDCA through big data analytics improve patient outcomes and operational efficiencies. Financial services using customer segmentation models experience improved customer satisfaction and profitability. Big data analytics enable more customized, efficient decision-making processes. This extensive review explores how big data analytics can provide tailored solutions to complex industry problems. The findings from this investigation can assist businesses across multiple sectors understand both its practical benefits and possible downsides when implemented into operations.

Customer satisfaction in retail services: a study with reference to Kottayam district in Kerala

Purpose: the main aim of this research paper is to ascertain the factors influencing the service quality of retail services in the study area and to identify the strategies of retail services leading to customer satisfaction of retail services as well as to measure the influence of demographic variables on the level of satisfaction of retail services. Method: the comprehensive framework for ascertaining customer satisfaction on service quality of retail services was subsequently accompanied by the collection of data through a structured questionnaire. The researcher used convenience sampling method and collected 384 responses and used confirmatory factor analysis, linear multiple regression analysis, structural equation model and one way analysis of variance. Findings: it is found that the customer satisfaction of retail services and their quality can be judged by the retail stores location and the relationship maintained by the employees. The customers expect the staff in the retail services have good knowledge about the products and to have empathy in dealing with their customers. The ambience of retail services outlets and their layout are the predominant factors offer best satisfaction to the customers. Practical Implications: the present research is focusing on the unaddressed issues to determine the factors of retail services empirically namely, the strategies of retailer services having their limitations of measurement and how can they be measured, the role of service quality on offering customer satisfaction through the retailer’s services and the demographic variables deciding the level of satisfaction of customers on retail services. Originality/Value: the quality of retail service comprises a healthy interaction between service seekers and service providers. The retailers strategies are to be designed in such a way the performance exceeds the expectations of customers and make them as the customers with high satisfaction and delighted and need to ascertain the factors responsible for customer satisfaction in retail services in retail sector, which is not much done by past researchers

К ВОПРОСУ О ВНЕДРЕНИИ СКВОЗНЫХ ЦИФРОВЫХ ТЕХНОЛОГИЙ В СФЕРУ РОЗНИЧНОГО БАНКОВСКОГО ОБСЛУЖИВАНИЯ

The article analyzes the features of the use of end-to-end digital technologies in modern banking, the uncontrolled introduction of which is associated with serious risks to the security of the state, business and citizens. At the same time, the author reveals the problem of systematization of end-to-end digital technologies, gives a brief description of each type of such innovation, and describes the mechanism of its application by credit institutions in the field of retail services. The author focuses on the risks that the process of uncontrolled introduction of end-to-end digital technologies entails. The importance of scientific research in this area is also emphasized.