Understand Customer Satisfaction Research Articles

Towards a better understanding of customer satisfaction with shopping mall food courts

PurposeIn this study, we examined the attributes that determine shoppers’ satisfaction with food courts in shopping malls and the effects of this satisfaction on behavioural intentions towards shopping malls.Design/methodology/approachThe data for this study were collected from 380 shoppers who visited food courts in shopping malls located in Hyderabad, India. The data were analysed using structural equation modelling.FindingsThe results indicate that fair prices, authenticity and the quality of the food, service and environment predict shoppers’ dining satisfaction and behavioural intentions. The findings also indicate that satisfaction with food court experiences has a strong positive influence on shoppers’ intention to revisit shopping malls.Practical implicationsFood service providers in Indian shopping malls should recognise that offering suitably priced and high-quality experiences is vital for sustaining their businesses in the long term as well as offer prompt service and warm hospitality to visitors to enhance customer satisfaction.Originality/valueThis study has implications for mall operators and food court managers seeking to enhance customer satisfaction with food courts and sustain the success of shopping malls. To the best of our knowledge, this is the first study to examine the factors that influence shoppers’ dining satisfaction and behavioural intentions in this context.

Pricing Strategies and Customer Satisfaction in Coffee Shops: A Case Study in Camarines Norte, Philippines

This study examines the impact of pricing strategies on customer sat-isfaction, aiming to improve customer experiences and foster long term loyalty within the coffee shops business in Camarines Norte, Philippines for the year 2022. Utilizing a descriptive correlational research design, data was collected through face-to-face interviews with 150 respondents selected via purposive sampling. The findings reveal that the majority of respondents were females aged 15-30, vis-ited coffee shops weekly. Sixty-two (62) percent of the respondents describe that coffee shops establishments used competitive-based pricing. Among various pricing strategies, value-based pricing was perceived as the most effective, with an average rating of 4.60. Re-spondents strongly agreed that service quality aligned with pricing strategies significantly influences customer satisfaction, scoring an average of 4.26. A test of significant relationship using Biserial corre-lation coefficient between competitive pricing, value-based pricing, and product bundle pricing regarding the impact on customer satis-faction cues indicate a statistically significant relationship at p<0.05, denoting a positive relationship between the pricing strategies and customer satisfaction. The study concludes that pricing strategies is a crucial element of the marketing mix that directly affects customer satisfaction and business profitability. Although, no universal pricing strategy may exist, understanding customer satisfaction is essential for identifying effective pricing policies. Therefore, it is recommended that coffee shops need to develop comprehensive business models to enhance pricing strategies aimed at increasing market share and sus-taining growth in the coffee shop sector.

Ethnic Food Truck Consumers’ Satisfaction: A Combination of PLS-SEM and fsQCA Analysis

Food trucks represent a unique dining option that encompasses elements such as culinary innovation, small business entrepreneurship, and cultural diversity. Grounded in the self-determination theory, this research aimed to examine a framework of ethnic food truck visitors’ satisfaction using symmetric and asymmetric approaches. Drawing from a sample of 416 online respondents, the symmetric analysis revealed that brand image mediated the relationship between the quality concepts (food quality and delivery quality) and satisfaction. In addition, destination image mediated the relationship between authenticity concepts (food authenticity and atmosphere authenticity) and satisfaction. Cuisine type partially moderated the structural model consisting of quality, image, and satisfaction. Through an asymmetric approach, the study identified configurations predicting high and low satisfaction, highlighting the combined effects of multiple ingredients. These insights provide valuable theoretical and managerial implications for understanding customer satisfaction within the food truck industry.

Assessing Customer Satisfaction towards Electric Vehicle in Mysore Using the KANO Model

The study is entrenched in the recognition that the automotive industry is undergoing a significant transformation, with EVs emerging as a vital solution to reduce carbon emissions and foster sustainable transportation. Understanding customer satisfaction in this context is crucial for manufacturers and policymakers to support the broader adoption of EVs. The research problem is centered on the limited understanding of how specific EV features impact customer satisfaction, particularly in emerging markets like Mysore. This gap in knowledge poses a challenge for manufacturers aiming to align their products with customer expectations and for policymakers promoting sustainable transportation. The study addresses this by applying the Kano Model, a framework that categorizes product attributes into different needs—basic, performance, excitement, indifferent, and reverse—based on their impact on customer satisfaction. The research methodology involves a descriptive study based on a survey of 150 respondents from Mysore. The data were collected through primary and secondary sources adopting a convenient sampling method. The analysis for the study is done by simple percentage method. The results shows that the majority of respondents are young, educated, and earn less than Rs. 50,000 per month, indicating that EV adoption is not limited to higher-income individuals. There is a strong preference for two-wheeled EVs, with most respondents having used their EVs for less than a year, reflecting a growing interest in the market. The Kano Model analysis shows varying levels of satisfaction across different EV attributes. For instance, respondents expressed high satisfaction with the reliability, safety features, and battery life of their EVs, but there were concerns about the availability of charging stations and the maintenance costs. The study also identifies performance attributes, such as EV range and cost savings on fuel, as significant factors driving customer satisfaction. Excitement needs, including advanced technology features and the design of EVs, also play a crucial role in enhancing customer satisfaction. However, certain indifferent needs, such as the color options and brand of the EV, were found to have minimal impact on customer satisfaction.

A STUDY ON CUSTOMER SATISFACTION TOWARDS THE DIGITAL BANKING FEATURES OFFERED BY PRIVATE SECTOR BANKS

General Background: The banking industry is crucial for economic development, serving as a catalyst for growth in both agricultural and industrial sectors. As banks support modernization through financial products, they significantly impact the livelihoods of farmers and the expansion of businesses, ultimately fostering economic prosperity. Specific Background: In an increasingly competitive landscape, exemplary customer service emerges as a vital component for banks to establish trust and loyalty. Effective communication, salesmanship, and courtesy are essential attributes for bank staff, directly influencing customer satisfaction and retention. Knowledge Gap: Despite the growing importance of digital banking features, there is limited research investigating the factors influencing customer satisfaction within the private banking sector, particularly concerning the relationship between the quality of digital banking services and customer perceptions. Aims: This study aims to analyze customer satisfaction with digital banking features provided by private sector banks, identifying key factors that contribute to satisfaction or dissatisfaction. Results: Utilizing a mixed-methods approach, quantitative data will be collected through structured surveys, complemented by qualitative insights from in-depth interviews. A minimum sample size of 50 participants will be targeted to ensure statistical power and generalizability of findings. Novelty: This research addresses a critical gap in understanding customer satisfaction within the context of digital banking, emphasizing the need for continuous innovation and improvement in service delivery. Implications: By identifying key determinants of customer satisfaction, the study offers actionable insights for banks to enhance digital services, build trust, and improve customer loyalty. The findings are expected to contribute to the broader discourse on digital banking, guiding strategic decision-making in a rapidly evolving financial landscape.

Self-service technologies: A bibliometric analysis

In this paper, we applied bibliometric methods to analyze the field of self-service technology (SST). Our goal was to identify the most impactful publications and journals, comprehend the key topics studied as well as the emerging trends and forecast future research trends in this domain. The Scopus database was used to extract 490 documents related to SST between 2000 and 2023. Our analyses include the most cited papers, sources of publications, bibliographic coupling, and topic modeling. As the body of literature continues to expand, we identified the most influential source “Journal of Service Marketing” which holds a prominent position in this area. The citation analysis revealed the highly influential papers that have made significant contributions to their respective fields. Notably, Meuter [Meuter, ML, AL Ostrom, RI Roundtree and MJ Bitner (2000). Self-Service Technologies: Understanding Customer Satisfaction with Technology-Based Service Encounters] in the realm of SST emerged as the most frequently cited paper, exerting substantial influence in academic literature. We applied bibliometric coupling in this field, which resulted in the discovery of seven clusters in SST. These clusters shed light on various aspects associated with these topics, offering valuable insights. The findings of this research offer valuable insights to study researchers by bringing clarity to this research field. Finally, the study presents the implications and recommendations for researchers. The findings of this paper offer valuable insights to study researchers by bringing clarity to the fields of the study.

EVALUASI TINGKAT KEPUASAN KONSUMEN DALAM PEMBELIAN PRODUK KURMA XYZ DI KOTA SURABAYA

XYZ company encountered business challenges with stagnant sales. Therefore, understanding customer satisfaction is crucial because customer preferences provide essential insights for designing effective marketing strategies to cultivate customer loyalty and compete in the market. This study aimed to identify consumer characteristics, assess consumer satisfaction levels, and evaluate the importance of attributes influencing date palm consumer satisfaction at XYZ outlets in Surabaya City. The research utilized Importance Performance Analysis (IPA) and Customer Satisfaction Index (CSI) tools, focusing on five variables: Price, Product, Ease of Acquisition, Packaging, and Packaging Design. The CSI calculation revealed a satisfaction score of 60.7%, indicating that consumers were reasonably satisfied with XYZ date products. IPA analysis identified six attributes requiring improvement to better align with customer expectations: affordable product pricing, pricing commensurate with the quality, product taste, product aroma, and branding logos. These findings are instrumental for XYZ in identifying areas that need enhancement to elevate product quality and meet customer expectations effectively. Keywords: Importance Performance Analysis; Customer Satisfaction Index ; Satisfaction; Consumer

Do Underlying Physical Specifications of a Servicescape Matter? The Case of the Cruise Industry

Understanding customer satisfaction in the cruise industry has mainly focused on intangible attributes like dining and spa experiences. This study explores the impact of cruise-ship servicescape, shaped by physical characteristics such as size and width. Our research confirms the impact of servicescape on passenger satisfaction within the cruise industry. Specifically, passengers typically prefer newer, stable, and less crowded ships. We advocate for greater attention to servicescape design for a distinct, sustainable competitive advantage. Recognizing its significance can enhance customer experiences and market positioning. In addition to contributing to the research on the cruise industry and servicescape literature, this study provides valuable insights for industry stakeholders to enhance their understanding and management of customer satisfaction.

Evaluation of Home Product Quality Using the Importance-Performance Analysis Method at PT. Galaxy Alam Semesta

Government support for the property sector through incentive policies, such as the Ministry of Finance Regulation on Government-Borne Value Added Tax (VAT-GOV) on properties, was reintroduced in 2024 to boost economic growth, focusing on the delivery of new landed houses and new apartment units. In this context, property and real estate companies are required to maintain customer satisfaction, which is the key to the company's success. Customer satisfaction not only reflects product quality but also influences the company's brand image. To understand customer satisfaction with product quality, particularly landed houses, PT. Galaxy Alam Semesta conducts periodic surveys of its customers. However, survey results from the first semester of 2023 indicated that customer satisfaction with the quality of houses was still below the company's standards. Therefore, this research aims to evaluate the quality of PT. Galaxy Alam Semesta's houses using the Importance-Performance Analysis method. This research will identify attributes that need quality improvement priority, with the hope of enhancing customer satisfaction and the company's image, as well as utilizing the House of Quality to determine the priority of these improvement proposals. The analysis results indicate that the attributes requiring quality improvement priority are even and non-streaky paint, straight wall corners, even wall and ceiling surfaces, smoothly and easily operable doors and windows, neat and even paint and sealant, even tile installation, and precise and neat installation of door and window accessories. From the analysis of the proposed improvement, five main priorities were identified: increasing the frequency of supervision and inspection to ensure compliance with quality standards, setting limits on the number of units overseen by building supervisors, using higher quality paint, evaluating the quality of door accessories and tile materials, and conducting regular evaluations and selections of contractors.

Evaluating Arabic Emotion Recognition Task Using ChatGPT Models: A Comparative Analysis between Emotional Stimuli Prompt, Fine-Tuning, and In-Context Learning

Textual emotion recognition (TER) has significant commercial potential since it can be used as an excellent tool to monitor a brand/business reputation, understand customer satisfaction, and personalize recommendations. It is considered a natural language processing task that can be used to understand and classify emotions such as anger, happiness, and surprise being conveyed in a piece of text (product reviews, tweets, and comments). Despite the advanced development of deep learning and particularly transformer architectures, Arabic-focused models for emotion classification have not achieved satisfactory accuracy. This is mainly due to the morphological richness, agglutination, dialectal variation, and low-resource datasets of the Arabic language, as well as the unique features of user-generated text such as noisiness, shortness, and informal language. This study aims to illustrate the effectiveness of large language models on Arabic multi-label emotion classification. We evaluated GPT-3.5 Turbo and GPT-4 using three different settings: in-context learning, emotional stimuli prompt, and fine-tuning. The ultimate objective of this research paper is to determine if these LLMs, which have multilingual capabilities, could contribute to enhancing the aforementioned task and encourage its use within the context of an e-commerce environment for example. The experimental results indicated that the fine-tuned GPT-3.5 Turbo model achieved an accuracy of 62.03%, a micro-averaged F1-score of 73%, and a macro-averaged F1-score of 62%, establishing a new state-of-the-art benchmark for the task of Arabic multi-label emotion recognition.

A Study of Satisfaction Level of Current Account Holders of Akola Urban Co-Operative Bank

Cooperative banks are witnessing steady growth and development, playing a crucial role in promoting financial inclusion, a cornerstone of economic and national advancement. These banks are particularly instrumental in supporting micro and small enterprises in their business endeavors. Renowned for their customer-centric services, cooperative banks contribute significantly to the financial landscape. This research paper focuses on The Akola Urban Co-operative Bank Ltd., analyzing the overall satisfaction levels of its current account holders. Utilizing various statistical tools, the study delves into understanding customer satisfaction across different banking facilities such as overdrafts, RTGS/NEFT, demand drafts, and more. Furthermore, the paper emphasizes the importance of raising awareness about the services offered by cooperative banks. Customer feedback and recommendations are explored, highlighting areas for potential improvement, notably the enhancement of the bank's mobile banking services.

Customers’ Satisfaction: Predictor of Loyalty among Guests of Beach Resorts in Misamis Oriental

Understanding customer satisfaction and loyalty is key for businesses to improve their services and build lasting relationships with customers, ensuring long-term success. The study aimed to assess how customer satisfaction affects loyalty at resorts in Initao, Misamis Oriental, Philippines. Using a descriptive correlational design, it randomly selected 302 regular customers from various beach resorts in the area. Data was gathered from these participants via survey questionnaires, which provided insights for analyzing the correlation between customer satisfaction and loyalty. The findings showed that most respondents were satisfied with the resort services, which included threshold, performance, and excitement attributes. Participants were assessed as being 'loyal' across both behavioral and attitudinal dimensions. Additionally, it was determined that these three attributes of customer satisfaction - threshold, performance, and excitement - had a significant influence on the participants' loyalty to the beach resorts they visited. These findings highlight the crucial importance of service quality and staff behavior in cultivating lasting customer loyalty in the competitive beach resort industry. Consequently, it is advised that beach resorts invest in extensive staff training programs to foster positive attitudes and deliver exceptional service.

Airline Customer Satisfaction Prediction

As the aviation industry evolves, understanding customer satisfaction has become critical for airlines pursuing to thrive in a competitive market. This research paper investigates the dynamics of airline customer satisfaction by analyzing reviews posted on Skytrax, a popular online platform known for its extensive collection of airline reviews. The study analyzes the essential features that are required for customer satisfaction in airline business, as well as performs a comparative analysis of various machine learning classifier algorithms by employing different metrics. The purpose of this comparison was to determine the most effective algorithm among them. The dataset utilized in the research consisted of reviews and ratings given by customers obtained through web scraping data from SkyTrax. Before data was transmitted to algorithms, data was cleaned using various techniques, data imputation, and removal of outliers, and removal of dependable and comparable features using various statistical methods. SMOTE imbalance approach was used in analyzing the level of bias in data. The study employs a range of metrics including accuracy score, precision, recall, f1-score, and confusion matrix, in order to compare different machine learning classifier algorithms, such as KNN, Random Forest, Decision Trees, and Logistics Regression, amongst others.

A Study on Customer Satisfaction towards Steel Furniture in Kasaragod

The study was conducted to understand Customer Satisfaction Towards Steel Furniture in Kasaragod, North part of Kerala state, India. Customer Satisfaction is buzzword today, as soon as right here every body the usage of this Customer’s Satisfaction is suffering from the importance placed by using the customers on each of the attitudes of the product/service. The minds of customers would be reflected on the preference and selection of brands available in the market. Thus, it is necessary for the manufacturers to evaluate the customers’ satisfaction towards branded furniture. The mission of this study is to continue their tradition of customer focused approach providing the best products balancing it with quality and economical price in tune with the wishes and expectation of the customers in this fast-changing global scenario.

A Study on Maybelline Products: A Review on Customer Satisfaction

This research aims to conduct a comprehensive study on Maybelline products, a renowned brand in the beauty and cosmetics industry, with a specific focus on understanding customer satisfaction. Maybelline, a subsidiary of L'Oréal, has established itself as a global leader in offering a diverse range of makeup and beauty products. Employing a mixed-methods research design, combining online reviews, surveys, and interviews, this study seeks to explore the perceptions, preferences, and overall satisfaction levels of consumers using Maybelline products. Key objectives include analyzing customer reviews on various platforms, assessing the factors influencing customer satisfaction, identifying popular and well-received products, and understanding customer expectations from the brand. The study also aims to uncover any challenges or areas for improvement as perceived by customers. The findings of this research are expected to contribute valuable insights to Maybelline and the broader beauty industry, aiding in the enhancement of product offerings, marketing strategies, and overall customer satisfaction.

Customers Perspective with Respect to Payment Apps in Rural Area: A study of selected village of Sonipat

This comprehensive study, conducted in a selected village of Sonipat, examines the customers' perspective towards payment apps in a rural setting, in line with India's "Digital India" initiative. The study encompasses an extensive demographic analysis and hypothesis testing, revealing key insights into the adoption, usage, and perception of digital payment applications among rural populations. The research, which involves a sample size of 120 individuals, primarily focuses on understanding customer satisfaction, trends, challenges, and the impact of these payment apps. Key findings indicate a predominant use among younger, educated males, with Google Pay being the most favored app. Despite the growing trend towards digitalization, traditional payment methods still persist, highlighting a gradual transition in financial behavior. The study also points out the critical role of gender in technology adoption and notes the necessity for inclusive digital literacy programs. Overall, the study contributes valuable insights into the evolving landscape of digital payments in rural India, highlighting both progress and areas needing attention for a more comprehensive digital integration.

Understanding Customer Satisfaction Factors: A Logistic Regression Analysis

Background: In the dynamic landscape of modern business, understanding customer satisfaction is crucial for success and competitiveness. This research intends to analyze the various elements that affect customer contentment, concentrating on the impact of demographic characteristics, economic inclinations, and involvement in loyalty programs. Methods: Employing logistic regression analysis, this research analyzes data collected from a diverse customer base across various industries. The study explores the relationship between customer satisfaction (binary dependent variable) and key independent variables, including age, income level, and loyalty program participation. Model validation is conducted through the Hosmer-Lemeshow test, along with the assessment of model fit using Cox & Snell and Nagelkerke R² metrics. Multicollinearity is checked using the Variance Inflation Factor (VIF). Results: The logistic regression model reveals that age and income level significantly influence customer satisfaction, with younger customers and individuals with greater income levels being more probable to report satisfaction. Additionally, participation in loyalty programs emerges as a strong predictor of customer satisfaction. The model demonstrates good fit and predictive ability, as indicated by statistical tests and graphical analyses, including an ROC curve and a Predicted Probability Plot. Conclusions: The research offers significant understanding into the determinants of customer satisfaction, highlighting the importance of demographic factors, economic status, and loyalty programs. These findings offer both theoretical contributions to the field of customer satisfaction research and practical implications for business strategies focused on customer engagement and loyalty.
 
 Received: 17 November 2023 / Accepted: 17 February 2024 / Published: 5 March 2024

Analysis of Sports Facility Service Quality on Goro Consumer Satisfaction Arena Makassar

This research is a quantitative descriptive study that aims to clarify customer satisfaction at Goro Arena. The population in this study was 145 members registered at Goro Arena. Sampling technique with the accidental sampling method. The sample was 22 members who were doing sports activities at the Goro Arena. The instrument used to understand customer satisfaction is a questionnaire. The data analysis technique uses using quantitative descriptive analysis method with percentages. Based on the research analysis, the quality of sports facility services on customer satisfaction at the Makassar Goro Arena is very satisfactory with a percentage of 57%. According to Parasuraman in Jayanti (2016), the form of service quality application uses the concept of "RATER" which stands for Responsiveness, Assurance, Tangibles, Empathy, and Reliability. Viewed through the aspects of service satisfaction of the Goro Arena facility, the following data were obtained: the responsiveness factor (responsiveness) was included in the very satisfied group by 70%; the assurance factor (assurance) was included in the very satisfied group by 50%; the tangibles factor was included in the satisfied group by 53%; the empathy factor (empathy) was included in the very satisfied group by 60%; the reliability factor (reliability) was included in the very satisfied group by 50%. From these results, it can be seen that the quality of sports facility services to customer satisfaction in Goro Arena Makassar has a very satisfying category.

Examining the Influence of Security Perception on Customer Satisfaction: A Quantitative Survey in Vietnam


 INTRODUCTION: This study explores the elements that impact consumer satisfaction in e-commerce settings, focusing on the perception of security. The prominence of e-commerce highlights the necessity of understanding customer satisfaction determinants, emphasizing the importance of creating a secure e-commerce environment.
 OBJECTIVES: Four hypotheses focused on security perception, customer service, product information, and website design affecting customer satisfaction were established and tested. A sample of Vietnamese consumers was utilized to examine these relationships empirically.
 METHODS: This study employed a quantitative research approach. The multiple linear regression analysis was used to test the research hypothesis. The SPSS (IBM) Version 26 software was used for statistical data treatment.
 RESULTS: The results revealed that security perception, customer service, and product information significantly influenced customer satisfaction, whereas website design did not. Notably, security perception emerged as a critical determinant of customer satisfaction. The outcomes of this study augment the existing scholarly resources, offering substantiated data concerning the significance of security perceptions in influencing customer gratification.
 CONCLUSION: Practical implications for online retailers include prioritizing enhancing security features, improving customer service, and providing comprehensive product information. However, this study may restrict the generalizability of the results, highlighting the need for additional research in various circumstances.

CUSTOMERS ATTITUDE AND SATISFACTION TOWARDS ONLINE SHOPPING: A STUDY IN ERODE DISTRICT OF TAMILNADU

Objectives: In the rapidly expanding e-commerce market of India, understanding customer satisfaction across diverse age groups is crucial. This survey aims to provide insights into the determinants of customer satisfaction in online purchasing, focusing on participants from the Erode District. By exploring age-specific trends, the study seeks to uncover distinct preferences and expectations among different age cohorts in online shopping. The objectives include examining customers' online shopping habits, attitudes, and satisfaction based on their age groups.
 
 Methods: Participants from the Erode District of Tamil Nadu, India, were involved in this survey. The methodology likely involved collecting data through structured questionnaires, interviews, or online surveys tailored to capture various aspects of participants' online shopping experiences. The survey may have incorporated demographic information, shopping behaviors, preferences, and satisfaction levels to analyze age-specific trends accurately. Statistical analysis methods were likely employed to interpret the gathered data and derive meaningful insights.
 
 Results: The results of the survey provide valuable insights into the online shopping habits, attitudes, and satisfaction levels of customers in the Erode District across different age groups. It likely revealed significant trends and patterns regarding preferred shopping platforms, product categories, payment methods, and factors influencing overall satisfaction. The findings may also highlight any disparities or similarities in shopping behaviors and satisfaction levels among distinct age cohorts, offering actionable insights for e-commerce firms and policymakers.
 
 Conclusion: Understanding customer satisfaction in online purchasing is essential for the sustainable growth of the e-commerce sector. This survey conducted in the Erode District underscores the significance of recognizing age-specific preferences and behaviors among online shoppers. By comprehending the diverse needs and expectations of customers across different age groups, businesses and governments can formulate targeted strategies to enhance the online shopping experience, drive customer satisfaction, and foster the continued expansion of the e-commerce market in India.