User Satisfaction Research Articles

Analyzing User Satisfaction of a Study Abroad Guidance Company Website Using the Customer Satisfaction Index (CSI) Method

XYZ is an education technology company dedicated to assisting Indonesian students in gaining acceptance to universities worldwide through full scholarship, partial, or self-funding. Until 2024, XYZ has a thousand alumni accepted in 46 countries and many universities worldwide. One of the marketing trackers that XYZ has is the website. With this website, the company will deliver the service to customers and receive user feedback to run and improve their services. The measurement of user satisfaction level can be used to improve the quality of service in digital media. The method used in this study to measure user satisfaction level is the Customer Satisfaction Index (CSI), which evaluates satisfaction across five (5) dimensions: usability, information quality, assurance, reliability, and data accessibility. This method's result shows a value of 83.64%, which means the XYZ website performance is in the "Very Satisfied" category. These findings suggest that XYZ Company's website is highly effective and has a "Very Satisfied" result category in meeting user needs, paving the way for continued success in their mission to assist Indonesian students in pursuing global education opportunities

Quicklib: A Rapid Library Management Solution

QuickLib is a new kind of library management system that puts special focus on remote access features while streamlining resource monitoring, user administration, and cataloging. User convenience and accessibility are limited by the frequent lack of effective remote access options in traditional library management systems. QuickLib fills this need by enabling users to access library resources from any location with an internet connection. In comparison to conventional systems, QuickLib's efficiency, usability, and performance are highlighted in this paper's presentation of its architecture, implementation, and assessment. Findings show that QuickLib is more efficient in terms of speed, responsiveness, and user satisfaction than other solutions, which makes it a great tool for libraries and educational establishments looking to update their library services. Keywords— Library Management System, Remote Access, Efficiency, User-Centric Design

Research and application of power equipment monitoring and fault diagnosis

Power equipment monitoring and fault diagnosis are important parts of power system operation and maintenance. By monitoring the status and performance parameters of power equipment in real time, and timely discovering and diagnosing potential fault problems, the reliability, safety and economy of the power system can be improved. At present, this research has made significant progress, but there are still some research gaps that need to be further explored and resolved. Through the research and application of power equipment monitoring and fault diagnosis, this paper aims to improve the reliability, safety and economy of power grid, reduce the risk of failure, optimize equipment operation and maintenance strategies, and improve power supply quality and user satisfaction. Condition monitoring and fault diagnosis are very important for the normal operation of the power system equipment, which can not only strengthen the fault diagnosis of the power system equipment, but also avoid the problem of large-scale paralysis caused by the failure of the power system equipment.

Performance Evaluation of Railway Infrastructure Managers: A Novel Hybrid Fuzzy MCDM Model

Modern challenges such as the liberalization of the railway sector and growing demands for sustainability, high-quality services, and user satisfaction set new standards in railway operations. In this context, railway infrastructure managers (RIMs) play a crucial role in ensuring innovative approaches that will strengthen the position of railways in the market by enhancing efficiency and competitiveness. Evaluating their performance is essential for assessing the achieved objectives, and it is conducted through a wide range of key performance indicators (KPIs), which encompass various dimensions of operations. Monitoring and analyzing KPIs are crucial for improving service quality, achieving sustainability, and establishing a foundation for research and development of new strategies in the railway sector. This paper provides a detailed overview and evaluation of KPIs for RIMs. This paper creates a framework for RIM evaluation using various scientific methods, from identifying KPIs to applying complex analysis methods. A novel hybrid model, which integrates the fuzzy Delphi method for aggregating expert opinions on the KPIs’ importance, the extended fuzzy analytic hierarchy process (AHP) method for determining the relative weights of these KPIs, and the ADAM method for ranking RIMs, has been developed in this paper. This approach enables a detailed analysis and comparison of RIMs and their performances, providing the basis for informed decision-making and the development of new strategies within the railway sector. The analysis results provide insight into the current state of railway infrastructure and encourage further efforts to improve the railway sector by identifying key areas for enhancement. The main contributions of the research include a detailed overview of KPIs for RIMs and the development of a hybrid multi-criteria decision making (MCDM) model. The hybrid model represents a significant step in RIM performance analysis, providing a basis for future research in this area. The model is universal and, as such, represents a valuable contribution to MCDM theory.

Evaluation of Satisfaction with Spatial Reuse of Industrial Heritage in High-Density Urban Areas: A Case Study of the Core Area of Beijing’s Central City

Industrial heritage is regarded as an important stock of spatial resources in cities, which highlights its utilization value for urban regeneration in high-density urban areas. With the dramatic increase in the number of industrial heritage reuse projects, how to scientifically evaluate the satisfaction with their spatial reuse is a key part of the solution for the mutual balance between heritage preservation and urban renewal. This paper takes eight industrial heritage conversion and utilization projects in the high-density core area of Beijing’s central city as examples; establishes an evaluation system for the satisfaction with the spatial reuse through six dimensions, namely, functional replacement, transportation accessibility, carrying capacity, public space, boundary form, and recognition of value; and uses the IPA method to evaluate the cases. This method is used to determine the degree of user satisfaction with the spatial reuse of industrial heritage in the core area of Beijing’s central city and to summarize the advantages and problems of its reuse. The results of this study reveal a trend toward the “community-oriented” re-generation of industrial heritage in the core area of Beijing’s central city, and this paper proposes recommendations for adaptive use to support high-quality urban regeneration work.

Natural Language Processing (NLP) in Recommendation Systems

This paper delves into the application of Natural Language Processing (NLP) techniques in recommendation systems, specifically focusing on novel approaches to enhance recommendation accuracy and user satisfaction. The utilization of NLP algorithms has revolutionized how content is recommended to users, leveraging linguistic analysis and machine learning to understand user preferences and provide tailored suggestions. Our research explores various NLP methodologies, including sentiment analysis, topic modelling, and semantic analysis, to extract meaningful insights from textual data. Furthermore, we investigate the integration of deep learning models, such as neural networks and transformer architectures, to capture complex patterns and improve recommendation precision. A key highlight of our study is the introduction of a novel recommendation method termed "Knowledge Graph Embedding for Contextual Recommendation." This innovative approach combines knowledge graph representation with contextual understanding, allowing for more nuanced and personalized recommendations based on user interactions, historical data, and contextual relevance. We delve into the intricacies of this technique, detailing its implementation, training process, and evaluation metrics.

Development and Preliminary Evaluation of a Bimodal Foot Prosthesis for Walking and Running.

People often alternate between bouts of walking and running, for instance, when adults participate in recreational activities. Transitioning between activities can be challenging for prosthesis users because existing prosthetic feet are not well-suited for both tasks. Meanwhile, switching between prostheses for different tasks is often impractical. Collectively, these challenges can present barriers to physical activity participation for people with limb loss, which can negatively impact social or physical health. This work describes the development and evaluation of a passive bimodal prosthetic foot prototype with different configurations and stiffnesses for walking and running. Users rated the bimodal prosthesis higher for standing and walking compared to a running prosthesis (+2.3 for both tasks on a 7-point Likert scale). Users rated the bimodal prosthesis higher for running compared to a walking prosthesis (+1.7 and +0.5 for 2.0 and 2.5 m/s running, respectively). Changing from walking to running mode increased the device's stiffness by 23-84%, depending on the user's preference. Users could switch between bimodal prosthesis walking and running modes quickly (21.3 ± 12.0 seconds). Overall, the preliminary results were encouraging in terms of user satisfaction, stiffness change between modes, and mode-switching speed. These findings motivate future exploration of this bimodal prosthesis concept.

Florio® HAEMO: A Longitudinal Survey of Patient Preference, Adherence and Wearable Functionality in Central Europe.

florio® HAEMO is a hemophilia treatment monitoring application (app) offering activity tracking and wearable device connectivity. Its use might support everyday activities for people with hemophilia. The aim of this study was to evaluate user satisfaction, long-term usage and the impact on data entry when pairing a wearable with a hemophilia monitoring app. This is a follow-up of a two-part user survey conducted in Central Europe. People with hemophilia and parents/caregivers of children with hemophilia using florio HAEMO and who completed part one were invited to complete a second online questionnaire at least 4months later. Fifty participants (83.3%) who completed part one of the survey continued to use the florio HAEMO app and completed part two. Of 14 participants who chose to use the app with a wearable, more than half (57.1%) were aged between 13 and 25years. Overall, the results demonstrated that florio HAEMO is very easy or rather easy to use, especially for individuals pairing the app with a wearable. Most people using a wearable indicated that florio HAEMO was very or rather important in bringing certainty to daily activities (85.7%). Notably, 14 of 36 (38.9%) non-wearable users indicated that they would prefer to pair the app with a wearable in the future. Adherence to the florio HAEMO app is maintained over an extended period of use. Pairing the app with a wearable might enable easier access to app features, increase data entry motivation and provide more certainty about daily activities for people with hemophilia.

Exploring the symbiotic relationship between smart technologies and thermal comfort in urban environments

The study's primary focus is to gather profound insights into user perceptions and preferences related to living in smart environments prioritizing thermal comfort and energy efficiency. This objective is pursued through meticulous surveys designed to capture the nuanced experiences of residents, unravelling the intricate relationship between smart technologies and their impact on daily life within these intelligent living spaces. The findings from these quantitative surveys become a valuable repository of information that sheds light on the intricate dynamics of user satisfaction and experience, providing a holistic understanding of the role played by smart technologies in shaping thermal comfort in the built environment. Additionally, the research sets out to assess the specific influence of smart technologies on thermal comfort within the urban settings of Turkey. By narrowing the focus to this geographical context, the study aims to draw region-specific insights that can be instrumental in tailoring smart living solutions to the unique needs and nuances of the Turkish urban landscape. This contextual analysis allows for a nuanced understanding of how smart technologies operate in diverse urban environments, providing a foundation for targeted interventions and improvements. A core objective of the study is to distil actionable recommendations for architects, designers, and urban planners. These recommendations are crafted with the intention of guiding the creation of user-centric spaces within the built environment that not only meet but exceed expectations in optimizing thermal comfort. By translating survey findings and regional assessments into practical suggestions, this research aims to empower professionals in the field to integrate smart technologies seamlessly into their designs, ultimately contributing to the development of intelligent, sustainable, and people-focused spaces. In summary, the study positions itself as a comprehensive exploration of the symbiotic relationship between smart technologies and thermal comfort. Through a meticulous examination of user perceptions, regional influences, and actionable recommendations, the research seeks to chart a course for a future where the built environment actively supports and enhances thermal comfort, thereby improving the overall quality of life for its residents.

The Influence of Brand Leadership and Brand Experience on Satisfaction and Repurchase Intention on E-commerce Brand

The purpose of this study is to empirically test the effect of brand leadership on its four dimensions, namely quality, value, innovation, popularity and brand experience on satisfaction and repurchase intention in Tokopedia customers. The population in this study are individuals as consumers who have transacted or shopped online at Tokopedia, are at least 18 years old, and live in West Jakarta. The sample in this study that met the criteria was 222 respondents who were selected using non-probability sampling through convenience sampling techniques. Data collection was carried out by questionnaire via google form which was distributed online. The data that has been successfully collected is processed using PLS-SEM. The results of this study indicate that quality, value, innovation, popularity and brand experience have a positive and significant effect on satisfaction. Then, the results also show that quality, popularity, brand experience, and satisfaction have a positive and significant effect on repurchase intention. However, value has a negative but significant effect and innovation has no significant effect on repurchase intention. Thus, Tokopedia must pay attention to quality, value, innovation, popularity, and brand experience to increase user satisfaction so as to generate repurchase intentions through Tokopedia.

Can Large Language Models Be Good Companions?

Developing chatbots as personal companions has long been a goal of artificial intelligence researchers. Recent advances in Large Language Models (LLMs) have delivered a practical solution for endowing chatbots with anthropomorphic language capabilities. However, it takes more than LLMs to enable chatbots that can act as companions. Humans use their understanding of individual personalities to drive conversations. Chatbots also require this capability to enable human-like companionship. They should act based on personalized, real-time, and time-evolving knowledge of their users. We define such essential knowledge as the common ground between chatbots and their users, and we propose to build a common-ground-aware dialogue system from an LLM-based module, named OS-1, to enable chatbot companionship. Hosted by eyewear, OS-1 can sense the visual and audio signals the user receives and extract real-time contextual semantics. Those semantics are categorized and recorded to formulate historical contexts from which the user's profile is distilled and evolves over time, i.e., OS-1 gradually learns about its user. OS-1 combines knowledge from real-time semantics, historical contexts, and user-specific profiles to produce a common-ground-aware prompt input into the LLM module. The LLM's output is converted to audio, spoken to the wearer when appropriate. We conduct laboratory and in-field studies to assess OS-1's ability to build common ground between the chatbot and its user. The technical feasibility and capabilities of the system are also evaluated. Our results show that by utilizing personal context, OS-1 progressively develops a better understanding of its users. This enhances user satisfaction and potentially leads to various personal service scenarios, such as emotional support and assistance.

Smart Health Monitoring with Power-Aware IoT Using a Wireless Body Area Network

Smart health monitoring systems have become increasingly popular in recent years due to the growth of the Internet of Things (IoT) technology and its applications in healthcare. This project proposes an IoT-based smart health monitoring system that utilises an ESP32 Microcontroller, MAX30100 Pulse Oximeter Heart Rate Sensor Module, MLX90614 ESF Non-Contact Human Body Infrared Temperature Measurement Module, LCD 16*2, 3.7v 2000mAh Lithium Battery, TP4056 1A Li-Ion Lithium Battery charging Module, and some buttons. The system is designed to monitor the user's heart rate, blood oxygen level, and body temperature in real-time and display the readings on an LCD screen as well as an IoT web page. The project aims to provide an affordable, portable, and user-friendly smart health monitoring solution that can be used at home, in hospitals, or other healthcare settings. The project methodology involved a combination of hardware and software components, including circuit design and programming using the Arduino IDE. The system was tested and evaluated for its performance, accuracy, and usability using a sample population. The results showed that the system was effective in monitoring the user's vital signs and displaying the readings in real-time. The system was found to be accurate and reliable, with a high level of user satisfaction and ease of use. Overall, the IoT-based smart health monitoring system proposed in this project has significant implications for healthcare, particularly in terms of remote monitoring, telemedicine, and personalised healthcare. The system has the potential to improve patient outcomes, reduce healthcare costs, and increase access to healthcare services. The project also highlights the potential of IoT technology in healthcare and the need for further research and development in this area

Augmented Reality and Wearable Technology for Cultural Heritage Preservation

Augmented Reality and Wearable Technology for Cultural Heritage Preservation

Association Between Demographic Characteristics of Users’ and Overall Satisfaction with Water Supply Service

Water constitutes an indispensable resource for various aspects of daily life, encompassing essential needs such as drinking, cooking, sanitation, and irrigation. Beyond household applications, diverse livelihood activities, including livestock management, gardening, crop cultivation, food processing, aquaculture, and fisheries, also rely on water. The assessment of customer satisfaction holds paramount significance in driving performance enhancements for service providers, even within government-owned entities offering critical services like water supply. This research aims to scrutinize the interplay between overall satisfaction with water services and its determinants, including satisfaction with water quality, and various parameters such as water supply hours, tap pressure, supplied water quantity, management responsiveness and communication, and water tariff. Anticipatedly, water supply hours, quantity, and quality are expected to exert a crucial influence on user satisfaction. Although users express a satisfaction level above neutral, it falls short of reaching a fully satisfactory level. Key contributors to user satisfaction involve aspects such as water supply hours, pressure, quantity, and quality, while complaints about water supply yield slightly lower satisfaction. Satisfaction with water service hours, quantity, and quality emerges as a driving force for overall satisfaction. The analysis reveals no significant association between overall satisfaction and demographic variables such as occupation, gender, age, education, and the main income source. However, a noteworthy association exists between satisfaction with water pressure and the water collection method, and a robust link is observed between satisfaction with water quality and respondents' water treatment practices. The provision for complaints is significantly associated with satisfaction regarding management responsiveness and communication. Multiple regression analysis underscores a positive relationship between overall satisfaction with water services and satisfaction with water quality and supply hours, indicating that higher satisfaction with these factors enhances overall satisfaction with water services.

Subscription intentions for ChatGPT plus: a look at user satisfaction and self-efficacy

PurposeThis study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.Design/methodology/approachThe study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.FindingsThe results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.Research limitations/implicationsThe study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.Practical implicationsThis research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.Originality/valueThis study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.

Implementasi Python-PPTX dan Dom-to-Image dalam Pembangunan Sistem Otomatisasi Laporan Berbasis Web di PT. XYZ

PT. XYZ is a leading retail company in Indonesia operating in a highly dynamic industry. Despite using PowerPoint (PPT) presentation reports as a key communication tool with its business partners, PT. XYZ's report creation process is still done manually. This leads to time wastage, the risk of errors, and disruptions to operational efficiency. The purpose of this research is to implement Python-pptx for the automation of report compilation and dom-to-image for the integration of visual data. The goal is to overcome the main challenges faced by PT. XYZ. The research methodology includes problem identification, literature review, system requirements analysis, system design, application development, and system testing. The results of this research include the successful implementation of Python-pptx and dom-to-image in building a web-based automated reporting system at PT. XYZ. System testing demonstrates the success of this technology, ensuring user satisfaction, and preparing the system for more efficient use.

Optimization of physical education teaching resources and service mode under the background of big data and cloud computing

With the rapid development of big data and cloud computing, the field of physical education has begun to actively explore the application of these new technologies. Big data can collect and analyze a large amount of teaching information, help understand students’ learning needs and preferences, optimize resource allocation, and improve teaching efficiency. Cloud computing can realize the online and personalized teaching resources and services, providing convenient and rich learning experience. This study first analyzes the role and influence of big data and cloud computing in the optimization of physical education teaching resources and service mode, and then verifies the actual effects of these technologies through empirical research, analyzes the existing problems and potential challenges, and puts forward corresponding solutions and suggestions. The results show that big data and cloud computing help to improve the efficiency and user satisfaction of physical education, and have important value in promoting the modernization of physical education.

A Usable Encryption Solution for File-Based Geospatial Data within a Database File System

Developing a security solution for spatial files within today’s enterprise Geographical Information System (GIS) that is also usable presents a multifaceted challenge. These files exist in “data silos” of different file server types, resulting in limited collaboration and increased vulnerability. While cloud-based data storage offers many benefits, the associated security concerns have limited its uptake in GIS, making it crucial to explore comparable alternative security solutions that can be deployed on-premise and are also usable. This paper introduces a reasonably usable security solution for spatial files within collaborative enterprise GIS. We explore a Database File System (DBFS) as a potential repository to consolidate and manage spatial files based on its enterprise document management capabilities and security features inherited from the underlying legacy DBMS. These files are protected using the Advanced Encryption Standard (AES) algorithm with practical encryption times of 8 MB per second. The final part focuses on an automated encryption solution with schemes for single- and multi-user files that is compatible with various GIS programs and protocol services. Usability testing is carried out to assess the solution’s usability and focuses on effectiveness, efficiency, and user satisfaction, with the results demonstrating its usability based on the minimal changes it makes to how users work in a collaborative enterprise GIS environment. The solution furnishes a viable means for consolidating and protecting spatial files with various formats at the storage layer within enterprise GIS.

User Satisfaction on Library Resources and Services in BMS College of Law, Bangalore-A Study

The main motive of this study was to examine and analyze the users’ satisfaction with library resources and services among the faculty members and students of BMS College of Law, Bangalore. The present study demonstrates the satisfaction levels of users towards various library resources and services provided by the college library. The result of the study found that a large number of respondents were satisfied with library resources and services. It also finds that the books had become a most widely used resources and circulation services was emerged most preferred service. Some suggestions have been given by the respondents to make about the library resources and services more effective and efficient manner.

Smart allocation and sizing of fast charging stations: a metaheuristic solution

ABSTRACT The widespread adoption of electric vehicles (EVs) hinges significantly on effective network management, particularly the allocation and sizing of fast-charging stations (FCS) for EV users. Applying queuing theory based on M/M/c, the model seeks to identify the most effective number of chargers to minimise waiting time for electric vehicle users and ensure optimal utilisation of the FCS. The problem is formulated as a multi-optimisation problem where finding the optimal solution is done by implementing the non-dominated sorting genetic algorithm focusing on EV user satisfaction, voltage stability, and carbon dioxide emissions. Simulation results indicate that the model successfully enhances EV user satisfaction, environmental impact, and overall FCS utilisation. In a comparative analysis with state-of-the-art models, the proposed approach demonstrates a notable 40% improvement in EV user satisfaction and a significant 45% enhancement in FCS utilisation. This proves the effectiveness of the proposed model in optimising the performance of the network.