Customer Experience Research Articles

Evaluating the millennial mothers’ relationship building process with baby care brands across two emerging economies

PurposeThis study aims to explore the motivators of mothers’ experience on their engagement behavior in the case of baby care toiletries. Additionally, the role of Brand trust and commitment have also been evaluated.Design/methodology/approachThe conceptual model was empirically tested based on the data collected through a survey using 320 samples from India and 431 samples from Sri Lanka. Data were analyzed using structural equation modeling.FindingsSensory and behavioral dimensions of brand experience can be considered as key drivers of brand trust and brand commitment among millennial mothers in the context of baby care toiletries. It was observed that brand trust had a significant positive impact on brand commitment. There was a significant relationship between brand trust, brand commitment and customer engagement. It was also inferred that brand loyalty is the consequence of customer engagement.Practical implicationsMarketers should gear up initiatives targeting new mothers through healthy aspects and genuine packaging to strengthen the mother’s trust through periodic uses of the product.Originality/valueThe present study is one of the unique empirical investigations that examine the antecedents of consumer engagement in the less researched context of high inherent risk products like baby toiletries.

Adoption of environmental technologies in the hotel industry: development of sustainable intelligence and pro-environmental behavior

Innovative environmental technologies such as solar energy, hydroelectricity, waste-to-energy, and rainwater reuse sources have the potential to completely transform the modern world to reduce climate change and dependency on fossil fuels. This study aims to investigate the role of environmental innovative technologies on customers' experiences of hotels with a mediating role of sustainable intelligence. The study theorizes that environmental innovative technologies enhance customers ‘experience and attitude towards hotels. The innovation diffusion theory is utilized as a main theoretical framework to address the research problem. The data was collected from tourists/visitors at top hotels with a usable sample size of 222 respondents. Survey results reveal that innovative technologies in the context of Environmental Responsibility and Economic Responsibility have a significant influence on Pro-Environmental Behaviour with the full mediating role of Sustainable Intelligence. These findings have important implications when implementing innovative technologies in the tourism industry to (1) improve customer satisfaction, experience, and attitude towards the hotels and destinations; (2) provide guidelines in tourism development policy and marketing; (3) help government agencies to effectively use pro-environmental technologies to change consumer attitude. After the investigation, some intriguing theoretical and practical conclusions have been made.

Transactional Marketing: Impact And Interjections on Customer Experience

The purpose of this paper is to provide a detailed description of the fundamental characteristics of the global scientific production related to transactional marketing and customer experience in the fields of management, business and accounting. This analysis is based on the quantitative evolution of the publications, the methodological approaches used, the units of study, the thematic clusters identified, the countries of origin, the prominent authors and the scientific journals that have published papers related to this topic. The methodology adopted is framed within a descriptive and reflexive documentary approach to the literature, which is based on the review of scientific documents indexed in Elsevier's Scopus and makes use of the VOSviewer software. The selection of texts was made following specific criteria, including key terms such as "transactional marketing" and "customer experience", as well as the limitation to the field of "Business, Management and Accounting". In addition, a specific period was considered, covering the years 2018 to 2022.

Investigating the Relationship Between Brand Equity and Customer Loyalty the Moderating Effect of Customer Satisfaction in the Telecom Industry

The study explores the connection between brand equity and customer loyalty in the telecom industry. It specifically examines how customer satisfaction plays a moderating role in this relationship. The research employed structural equation modeling and involved 386 Ethio telecom customers. Several aspects were evaluated, including reliability, convergent validity, and sample adequacy. The study's findings highlight a strong positive correlation between brand equity and customer loyalty within the telecom industry. Factors such as positive brand image, perceived quality, brand awareness, and brand associations were found to have significant influences on customer loyalty. Furthermore, customer satisfaction was identified as a moderator, enhancing the positive impact of brand equity on loyalty. Based on the results, the study emphasizes the importance of brand equity and customer satisfaction in fostering loyalty in the telecom industry. It suggests that telecom companies should invest in building a strong brand image, improving perceived quality, increasing brand awareness, and cultivating favorable brand associations. Policymakers and regulators are also encouraged to create a competitive telecom market that promotes innovation, high-quality service delivery, and reasonable pricing. The practical implications of these findings are significant for the industry. They underscore the need for strong brand equity strategies and the delivery of exceptional customer experiences. By prioritizing these aspects, telecom companies can enhance customer loyalty and gain a competitive advantage in the market.

A study on driving factors for enhancing financial performance and customer-centricity through digital banking

Purpose This study aims to develop a customer-centric model based on an online customer experience (OCE) construct relating to e-loyalty, e-trust and e-satisfaction, resulting in improved Net Promoter Score for Indian digital banks. Design/methodology/approach This study used an online survey method to gather data from a sample of 485 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using partial least squares structural equation modelling to further investigate the research hypotheses. Findings The main factors determining digital banks’ OCE were perceived customer centrality, perceived value and perceived usability. Additionally, relevant constructs were evaluated using importance-performance map analysis. Research limitations/implications This study used convenience sampling for the urban population using digital banking services; therefore, the outcome may be generalized to a limited extent. To further strengthen digital banking, it would be valuable to imitate studies in other countries. Originality/value There is a lack of research on digital banking and OCE in India; thus, this study will help rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between online customer satisfaction, loyalty, trust and the bottom line of financial institutions using these factors as dependent variables instead of traditional measures.

Incidence of Employer Brand on Organizational Commitment Factors in University Professors

In competitive environments, the implementation of human management strategies strengthens organizational commitment. This paper analyses the impact of the employer branding on the factors of organizational commitment. The elements of the study were 369 university professors from private and public institutions in Arequipa, and Smart PLS 4.0 software was used for the statistical contrast. The results explain that the employer brand experience has a positive impact on the affective factors, identification with objectives-values and morale. Furthermore, it contributes to the understanding of the theoretical links between the consequences of employer branding and the determinants of organizational commitment factors, both of which are relevant to human resource management in the dynamic environment. 

Understanding the Nexus: Business Intelligence and its Impact on Customer Experience Across Diverse Work Sectors

In the 21st-century hyper-competitive business landscape, comprehending and improving customer experience (CX) is highly quintessential for sustainable success across diverse industry sectors. Customers today hold more options in pursuing a luxurious lifestyle compared to their predecessors, yet their expectations continue to be on a constant surge. To meet these rising expectations, today's organisations strongly emphasize incorporating the best industry practices to ensure a high-end customer experience [1]. One such practice that has been included in recent times is integrating business intelligence and analytics. By leveraging advanced analytics tools and techniques, businesses can extract valuable insights from vast datasets, enabling informed decision-making and proactive strategies [2]. Business intelligence and analytics play a vital role in this practice by providing real-time data analysis, predictive modelling, and actionable recommendations, empowering organizations to optimize operations, enhance customer experiences, and stay ahead in today's dynamic marketplace [3]. The following paper aims to explore the vital role Business Intelligence (BI) plays in enhancing customer experience across various sectors. By applying a comprehensive review and analysis methodology, the study will seek to investigate how BI tools, strategies, and analytics influence user experience metrics, organizational performance, and competitive advantage in disparate sectors. Moreover, it further aims to determine the significance of leveraging data-driven insights garnered through business intelligence processes to comprehend customer behaviours, preferences, and sentiments across diverse sectors, ranging from retail and hospitality to finance and healthcare. The paper will bolster the aforementioned analysis by synthesising empirical case analysis, diving into the multifaceted impacts of Business Intelligence and Analytics on Customer Experience. Furthermore, the paper aims to examine the role of BI in optimizing operational efficiencies, streamlining processes, and fostering innovation to meet evolving customer expectations and market demands. Alongside this, it will dive deeper into issues such as data privacy concerns, and underscore the importance of organizational culture, leadership support, and cross-functional collaboration in fostering a BI-driven CX-centric mindset within diverse work environments. Through empirical evidence and industry case studies, the paper will seek to demonstrate how Business Intelligence adoption correlates with improved customer satisfaction scores and profitability metrics across diverse sectors. Towards the end, the paper will present a concluding argument by highlighting key insights, implications, and the imperative of investing in robust data infrastructure, analytics capabilities, and talent development initiatives to unlock the full transformative power of Business Intelligence in driving superior customer experiences. It will eventually underscore the need for continuous evaluation, adaptation, and innovation in Business Intelligence strategies to stay abreast of evolving customer preferences, technological advancements, and competitive dynamics. By illuminating the transformative impact of Business Intelligence on Customer Experience metrics, organizational performance, and competitive advantage, the study aims to provide valuable insights and guidelines for leveraging data-driven strategies to drive customer-centric innovation and sustainable growth in an increasingly dynamic business landscape.

Factors Affecting Consumer Behaviour In Indian Fashion Retail Industry- A Study Of Recent Trends And Preferences.

This study investigates the multifaceted realm of consumer behavior within the Indian fashion retail industry, focusing on the intricate interplay of various factors shaping purchasing decisions. With an ever-evolving market landscape, understanding recent trends and preferences becomes paramount for businesses striving to remain competitive and relevant. Drawing upon a comprehensive review of literature and empirical research, this paper aims to dissect the intricate web of influences that drive consumer behavior in the Indian context. Key factors such as cultural nuances, economic dynamics, social influences, and technological advancements are scrutinized to unravel their impact on consumer preferences and buying patterns. Through surveys, interviews, and data analysis, insights are gleaned into the evolving tastes and preferences of Indian consumers in the realm of fashion retail. Additionally, the role of marketing strategies, brand perception, and customer experience in shaping consumer decisions is explored. The findings of this study not only provide valuable insights for businesses operating in the Indian fashion retail sector but also contribute to the broader understanding of consumer behavior dynamics in a rapidly evolving market environment. By staying attuned to the pulse of consumer preferences and adapting strategies accordingly, businesses can navigate the complex terrain of the Indian fashion retail industry with agility and foresight.

Data to Decisions: Optimizing E-commerce Sales Potential with Analytics

Descriptive, diagnostic, predictive, and prescriptive analytics play crucial roles in optimizing the performance and user experience of an e-commerce site. Descriptive analytics involves examining historical data to gain insights into past performance, enabling businesses to identify trends, patterns, and anomalies. This analysis helps in understanding what has happened, such as identifying popular products or peak sales periods, and provides a foundation for further analysis. Diagnostic analytics goes beyond descriptive analytics by examining why certain events occurred, identifying factors that influenced outcomes, and uncovering strengths, weaknesses, and areas for improvement within an e-commerce platform. Predictive analytics utilizes statistical algorithms and machine learning techniques to forecast future trends and outcomes, enabling businesses to anticipate customer preferences, demand for specific products, and potential sales opportunities. By leveraging predictive insights, e-commerce sites can adjust strategies, inventory levels, and marketing campaigns proactively to stay ahead of the competition and meet evolving customer needs. Prescriptive analytics takes predictive insights to the next level by recommending specific actions or strategies to optimize business processes and achieve desired outcomes. This could involve personalized product recommendations, targeted marketing strategies, or dynamic pricing adjustments based on real-time data analysis. By harnessing these four types of analytics, e-commerce businesses can make informed, data-driven decisions, enhance customer experiences, drive sales growth, and maximize profitability.

The AI Revolution: How Artificial Intelligence is Reshaping Marketing Strategies

This paper explores the transformative impact of Artificial Intelligence (AI) on modern marketing practices. It examines how AI applications are revolutionizing various aspects of marketing, including customer experience, campaign personalization, content creation, and market research. The paper analyzes real- world examples and data to showcase the effectiveness of AI implementation. It also discusses potential challenges and ethical considerations surrounding AI in marketing. Finally, the paper explores the future potential of AI and its role in shaping the marketing landscape of tomorrow.

دور التجارة الإلكترونية في التأثير على المسؤولية الاجتماعية: دراسة تطبيقية على شركة نون

E-commerce is considered one of the modern phenomena that has significantly impacted businesses, exerting a noticeable influence on corporate social responsibility. The aim of the study was to understand the role of e-commerce in influencing corporate social responsibility through an analysis of a case study on Noon company. The descriptive-analytical methodology was followed, and a questionnaire was used as a data collection tool. A total of 375 questionnaires were distributed, and 352 valid responses were retrieved, resulting in a response rate of 94%. The study results demonstrated that e-commerce plays a crucial role in enhancing the social responsibility of Noon company. Additionally, the results indicated a statistically significant positive impact of e-commerce on the economic, legal, ethical, and humanitarian dimensions of corporate social responsibility. The study recommended that Noon company's management should raise awareness among its employees about the concept of e-commerce by enabling and training them on specialized e-commerce programs and fostering a social culture conducive to e-commerce. Furthermore, the management should activate electronic payment processes through its website by accepting credit cards, smart cards, or electronic checks, and continue to develop and update the technological infrastructure of Noon company, including e-commerce platforms and secure payment systems, to enhance customer experience and trust.

IoT Based Smart Trolley for Auto Billing

This paper proposes the development of a Smart Trolley system aimed at enhancing the shopping experience by automating the billing process. The system integrates Raspberry Pi, a low-cost, credit-card-sized computer, and RFID (Radio-Frequency Identification) technology to create an efficient and seamless checkout process for customers in retail environments. The Smart Trolley employs RFID tags attached to products and an RFID reader mounted on the trolley to identify items as they are placed inside. The Raspberry Pi processes the RFID data and maintains a running total of the items in the trolley. Additionally, it communicates with the store's database to retrieve product information and pricing. Through this integration, the Smart Trolley eliminates the need for manual scanning of each item at checkout, reducing waiting times and enhancing overall efficiency. Moreover, the system provides real-time updates on the total bill, allowing customers to track their expenses as they shop. This paper outlines the design, implementation, and testing of the Smart Trolley system, demonstrating its effectiveness in automating the billing process while improving the shopping experience for customers. The proposed system holds promise for revolutionizing retail operations, offering a glimpse into the future of smart, technology-driven shopping solutions. Key Words: Autobilling, Rasberry Pi, RFID(EM-18), LCD, Smart Shopping, IoT.

Digital human calls you dear: How do customers respond to virtual streamers’ social-oriented language in e-commerce livestreaming? A stereotyping perspective

Social-oriented language as a linguistic style can improve customer experiences in various service contexts, involving both human employees and AI-enabled service agents. The emergence of digital human characters in e-commerce livestreaming, also known as virtual streamers, raises the question: Can social-oriented language used by virtual streamers increase the customers' purchase intention? However, the theoretical understanding of whether, how, and when the interaction effect between virtual streamers' social-oriented language and product type influences purchase intention remains far from conclusive. Based on the stereotype content model (SCM), we developed a theoretical model to explain the mechanism between virtual streamers' linguistic style and customers’ purchase intention. A multi-method study combining two online experiments, one lab experiment, and one focus group was conducted to explore the effectiveness of social-oriented language (Study 1: N = 321; Study 2: N = 292; Study 3: N = 120; Study 4: N = 9). Participants in both Study 1 and Study 2 were recruited online and were randomly assigned to a condition in 2 (linguistic style: social-oriented vs. task-oriented) × 2 (product type: experience vs. search) between-subjects experimental design. Participants were recruited in the university by three blind-to-hypothesis experimenters in Study 3 and were randomly assigned to a condition in 2 (linguistic style: social-oriented vs. task-oriented) × 2 (product type: experience vs. search) × 2 (virtual streamer type: human-like vs. animated) between-subjects experimental design in the behavioral lab. Participants in Study 4 were recruited from a large WeChat group specifically interested in online shopping discounts. The results of Study 1 indicate the effect of social-oriented language on purchase intention solely in the experience product condition. Study 2 demonstrates the mediating role of perceived warmth and perceived competence, and confirms a compensatory effect and a positive relationship between perceived warmth and competence. Study 3 verifies the moderating role of the virtual streamer type while a focus group Study 4 supports the findings from Studies 1–3. Our findings extend the livestreaming commerce literature by exploring the implications of social-oriented language and task-oriented language when the live streamer is a digital human rather than a human. Also, we provide fresh insights into the literature on human-AI interactions by unraveling both the cognitive mechanism and the boundary condition, deepening our understanding of a novel but under-investigated phenomenon. Furthermore, our findings provide practical implications for livestreaming commerce practitioners.

Research on the Collaborative Effects of Live-streaming Sales and Community-based Supply Chain: A Case Study of He Shi You Xuan

The development of the digital economy has led to an increasingly close integration of e-commerce and supply chains. Many businesses have introduced live streaming for product promotion to boost sales and reduce shopping costs for users. China's vast online population provides extensive opportunities for the development of e-commerce. Previous research on e-commerce and supply chains has primarily focused on the impact and challenges that e-commerce poses to supply chain management. However, there is limited research on the key aspects affecting customer experience. The analysis covers various aspects, including logistics cost control, time cost control, service levels, user stickiness, inventory backlog, and live streaming cost control. By examining this novel combination of e-commerce and community-based supply chains, the paper aims to provide theoretical insights for exploring and optimizing the integration of e-commerce and community-driven supply chain models, ultimately enhancing e-commerce services.

Leveraging business intelligence solutions for urban parking management

Efficient parking management is essential for enhancing customer experience, mobility, accessibility, and overall quality of life in urban areas. In recent years, parking analytics have emerged as valuable tools for understanding drivers’ behavior and developing data-driven management strategies. However, the application of these tools is often hindered by the complexity of data extraction, transformation, loading and analysis. Additionally, the implementation of these tools can be time-consuming and costly, further limiting their practical use for operators and urban authorities. To address this issue, this paper presents the development of a Business Intelligence tool specifically designed to facilitate parking management through the automated flow of transaction data between collection, processing, and analysis systems. The tool provides easy-to-use analytical capabilities that allow parking managers to analyze parking transaction data, identify trends and patterns, and make informed decisions about parking management quickly and easily. The cost-effective implementation of this tool presents a valuable solution for managing on-street parking in urban areas. This study highlights the potential of Business Intelligence tools for parking management and contributes to improving the effectiveness of parking management.

Pioneering Digital Transformation in a Future-Ready World

In today's rapidly evolving business landscape, digital transformation has become imperative for companies aiming to thrive in the long term. This paper explores the concept of digital transformation and its significance in preparing organizations for the opportunities and challenges of a future-ready world. Digital transformation involves leveraging digital technology to fundamentally reshape corporate processes, business models, and customer experiences. Key technologies driving this transformation include artificial intelligence (AI), the Internet of Things (IoT), edge computing, 5G technology, blockchain, and cybersecurity. While digital transformation offers immense benefits such as improved efficiency, enhanced customer experiences, and increased innovation, organizations face barriers such as cultural resistance, organizational silos, and regulatory constraints. Overcoming these obstacles requires a concerted effort, including fostering a culture of innovation, breaking down organizational barriers, and adhering to regulations. By embracing digital transformation and leveraging emerging technologies, organizations can position themselves for success in an increasingly digital world

AI-INFUSED CHATBOTS FOR CUSTOMER SUPPORT: A CROSS-COUNTRY EVALUATION OF USER SATISFACTION IN THE USA AND THE UK

As organizations increasingly integrate artificial intelligence (AI)-infused chatbots into their customer support strategies, understanding user satisfaction becomes paramount. This abstract provides an overview of a cross-country evaluation that examines user experiences with AI-driven chatbots for customer support, drawing insights from both the USA and the UK. The evaluation explores the deployment of AI-infused chatbots in customer service scenarios, focusing on how users in these two regions interact with and perceive the effectiveness of chatbot interactions. The study considers the impact of cultural nuances, linguistic variations, and user expectations on the overall satisfaction with AI-driven customer support. In the USA, a market known for its technological adoption and diverse consumer landscape, the evaluation investigates how AI-infused chatbots contribute to enhancing customer experiences. It explores factors such as response time, accuracy, and the adaptability of chatbots in addressing diverse customer queries. In the UK, with its unique cultural and linguistic characteristics, the study examines how AI-driven chatbots align with customer expectations and preferences. It considers the role of chatbots in streamlining customer interactions, providing timely resolutions, and maintaining a high level of user satisfaction. Through a comparative analysis, the evaluation aims to identify patterns, disparities, and commonalities in user satisfaction with AI-infused chatbots in customer support between the USA and the UK. It delves into the challenges faced by chatbots in understanding and responding to regional linguistic nuances, cultural sensitivities, and the adaptability required for diverse customer demographics. The abstract encapsulates the essence of the cross-country evaluation, shedding light on the evolving landscape of AI-driven customer support and its implications for user satisfaction in distinct markets. Insights from this evaluation contribute to the ongoing discourse on optimizing AI-infused chatbot experiences for diverse customer bases, offering valuable considerations for businesses seeking to enhance their customer support strategies on an international scale.. Keywords:  Ai-Infused Chatbots, Customer Support, USA, UK, Cultural Nuances, Technological Landscapes.

Customer experience (CX), employee experience (EX) and human experience (HX): introductions, interactions and interdisciplinary implications

PurposeThe purpose of this paper is to provide an overview of what (service) experience is and examine it using three distinct perspectives: customer experience (CX), employee experience (EX) and human experience (HX).Design/methodology/approachThe present conceptualization blends the marketing and organizational behavior/human resources management (OB/HRM) disciplines to clarify and reflect over the meaning of (service) experience. The marketing discipline illuminates the concept of CX, whereas the OB/HRM discipline illuminates the concept of EX. The concept of HX, which transcends CX and EX, is examined in light of its recent development in service research. For each of the three concepts, key themes are identified, and future research directions are proposed.FindingsBecause the goal that individuals seek to achieve depends on the role they are enacting, each of the three perspectives on experience (CX, EX and HX) should have a different focal point. CX requires to focus on the process of solving customer goals. EX necessitates to think in terms of organizational context and job content that support employees. Finally, the focus of HX should be on well-being via enhanced gratification, and reduced violation, of basic human needs.Originality/valueThis paper offers an interdisciplinary perspective on (service) experience and simultaneously addresses CX, EX and HX in order to reconcile the different perspectives on experience in service research.

Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation

The analysis of students’ attitudes and perceptions represents a basis for enhancing different types of activities, including teaching, learning, assessment, etc. Emphasis might be placed on the implementation of modern procedures and technologies, which play an important role in the process of digital transformation. Among them is artificial intelligence—a technology that has already been found to be applicable in various sectors. When it comes to education, several AI-based tools and platforms can be used by students and teachers. Besides offering customized learning experiences, AI may play a significant part in establishing the concept of sustainability, especially when concerning the achievement of sustainable development goal 4. This paper investigates students’ intention to use artificial intelligence in education, taking three predictors from the UTAUT model and AI awareness as the moderator. The analysis included students from the Autonomous Province of Vojvodina, Republic of Serbia. For the purpose of the research, the partial least squares structural equation modeling (PLS-SEM) method was applied. Hereby, two models (without and with a moderator) were tested to examine the main and moderating effects, respectively. Regarding the results, while interaction terms were non-significant, the impacts of performance expectancy, effort expectancy, and social influence on behavioral intention were significant and positive.

Online Review Analysis from a Customer Behavior Observation Perspective for Product Development

Observing customers is one of the methods to uncover their needs. By closely observing how customers use products, we can indirectly experience their interactions and gain a deep understanding of their feelings and preferences. Through this process, companies can design new products that have the potential to succeed on the market. However, traditional methods of customer observation are time-consuming and labor-intensive. In this study, we propose a method that leverages the analysis of online customer reviews as a substitute for direct customer observations. By correlating a customer journey map (CJM) with online reviews, this research establishes a verb-centric analysis that produces a CJM based on online review data. Various text analysis techniques were utilized in this process. When applying online retail site review data, our method of customer observation required one week. This proved to be more efficient in comparison with traditional customer observation methods, which typically need at least one month to complete. Additionally, we observed that the customer behavior-based VOC (voice of customer) identified during the CJM mapping process offers broad insights that are distinct from traditional product feature-centric review analyses. This behavior VOC can be effectively utilized for product improvement, new product development, and product marketing. To verify the usefulness of the behavior VOC, we asked product development experts to evaluate the quantitative analysis results of the same reviews. The experts evaluated the CJM as useful for product conceptualization and selecting technology priorities.