The Digitization of Public Services and Its Contribution to the Quality of Service in Relation to User Satisfaction

In recent years, some governments have been working on solutions to transform public administrations and provide high-quality services to users. The United Nations has recommended integrating digital technology into various aspects of life, including public services. The objective is to offer real-time, high-quality digital services, improve the delivery of public services, enhance their effectiveness and efficiency, while achieving objectives such as transparency, interoperability and citizen satisfaction. However, most governments in developing countries are unable to keep up with this trend. As a result, they often create digital public services that fall short of users’ expectations. This study aims to identify the fundamental factors influencing the quality of service in relation to user satisfaction and to explore the relevance of digital technology in implementing this quality within Cameroon public administrations. To achieve this, we used a qualimetric research method, which included non-directive interviews, questionnaires, and structured observations. The results showed that the public services offered in our study environment did not meet users’ expectations. However, the study identified the fundamental aspects to be considered in providing quality public services connected to user satisfaction, as well as the strengths of digitization in achieving this quality.

Research on Multi-Objective Optimization Model of Industrial Microgrid Considering Demand Response Technology and User Satisfaction

In the process of wind power,coal power,and energy storage equipment participating in the operation of industrial microgrids,the stable operation of wind-storage industrial microgrids is guaranteed by considering demand response technology and user satisfaction.This paper firstly sorts out the status quo of microgrid operation optimization,and determines themain requirements for user satisfaction considering three types of load characteristics,demand response technology,power consumption benefit loss,user balance power purchase price and wind power consumption evaluation indicators in the system.Secondly,the operation architecture of the windstorage industrialmicrogrid is designed,and themulti-objective optimizationmodel of the wind-storage industrial microgrid is established with the comprehensive operating cost and user satisfaction as the target variables,and the corresponding solution method is mentioned.Finally,a typical wind-storage industrial microgrid is selected for simulation analysis,and the results showthat,(1)Considering the demand response technology,the comprehensive operating cost of the wind-storage industrial microgrid per day is 5292.63 yuan,the user satisfaction index is 0.953,and the wind power consumption rate reaches 100%.(2)By setting four scenarios,it highlights that the grid-connected operation mode is superior to the off-grid operation mode.Considering the demand response technology,the load curve can be optimized,and the time-of-use electricity price can be fully used to coordinate the operation of each unit,which enhances the wind power consumption capacity.The compromise solution of the system comprehensive operating cost and user satisfaction under the confidence level of 0.95 is obtained,namely(5343.22,0.94).(3)The frontier curve shows that in the process of model solving,it is impossible to optimize any sub-objective by changing the control variables,which proves that there is a close relationship between the comprehensive operating cost of the system and the confidence level,which can provide effective guidance for the optimal operation of industrial microgrids.

A case study of customer satisfaction for information technology solutions

There are numerous information technology solutions including hardware and software. A company that provides the solution should have knowledge of the customer needs in the purpose of sailing strategy or upgrade policy. The needs are also directly connected to the user satisfaction. However, the users have respective points of view in the needs as well as they may not identify the requirements to improve the solution. SERVQUAL can be an appropriate method to define and measure the customer satisfaction for the information technology solutions. As a case study of the customer satisfaction, the modified SERVQUAL items and scoring method are applied to a cyber-infrastructure system named CyberL ab in Korea. The measurement results of user satisfaction for CyberL ab are provided to confirm that our proposed method performs as we intended. From the results, we can score the satisfaction level of users and identify their needs in the various aspects. The total user satisfaction level for CyberL ab is scored by 88.3.

Enhancing the Prediction of User Satisfaction with Metaverse Service Through Machine Learning

Metaverse is one of the main technologies in the daily lives of several people,such as education,tour systems,and mobile application services.Particularly,the number of users of mobile metaverse applications is increasing owing to the merit of accessibility everywhere.To provide an improved service,it is important to analyze online reviews that contain user satisfaction.Several previous studies have utilized traditional methods,such as the structural equation model(SEM)and technology acceptance method(TAM)for exploring user satisfaction,using limited survey data.These methods may not be appropriate for analyzing the users of mobile applications.To overcome this limitation,several researchers perform user experience analysis through online reviews and star ratings.However,some online reviews occasionally have inconsistencies between the star rating and the sentiment of the text.This variation disturbs the performance of machine learning.To alleviate the inconsistencies,Valence Aware Dictionary and sEntiment Reasoner(VADER),which is a sentiment classifier based on lexicon,is introduced.The current study aims to build a more accurate sentiment classifier based on machine learning with VADER.In this study,five sentiment classifiers are used,such as Naïve Bayes,K-Nearest Neighbors(KNN),Logistic Regression,Light Gradient Boosting Machine(LightGBM),and Categorical boosting algorithm(Catboost)with three embedding methods(Bag-of-Words(BoW),Term Frequency-Inverse Document Frequency(TF-IDF),Word2Vec).The results show that classifiers that apply VADER outperform those that do not apply VADER,excluding one classifier(Logistic Regression with Word2Vec).Moreover,LightGBM with TF-IDF has the highest accuracy 88.68%among other models.

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

Different types of pandemics that have appeared from time to time have changed many aspects of daily life.Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown.The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these applications.The manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming task.Therefore,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these apps.This research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning methods.To the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi Arabia.The findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app store.Different methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

A Structural Topic Model for Exploring User Satisfaction with Mobile Payments

This study explored user satisfaction with mobile payments by applying a novel structural topic model.Specifically,we collected 17,927 online reviews of a specific mobile payment(i.e.,PayPal).Then,we employed a structural topic model to investigate the relationship between the attributes extracted from online reviews and user satisfaction with mobile payment.Consequently,we discovered that“lack of reliability”and“poor customer service”tend to appear in negative reviews.Whereas,the terms“convenience,”“user-friendly interface,”“simple process,”and“secure system”tend to appear in positive reviews.On the basis of information system success theory,we categorized the topics“convenience,”“user-friendly interface,”and“simple process,”as system quality.In addition,“poor customer service”was categorized as service quality.Furthermore,based on the previous studies of trust and security,“lack of reliability”and“secure system”were categorized as trust and security,respectively.These outcomes indicate that users are satisfied when they perceive that system quality and security of specific mobile payments are great.On the contrary,users are dissatisfied when they feel that service quality and reliability of specific mobile payments is lacking.Overall,our research implies that a novel structural topic model is an effective method to explore mobile payment user experience.

An empirical study on user satisfaction in relation to those influencing factors for the development of database resources

In taking into full consideration of the technology acceptance model(TAM),this empirical study has made a few assumptions and also has formulated a model for the study on the level of satisfaction of database users. This research project was conducted by collecting relevant data from library users of five universities. Specifically, it aimed to measure database users' level of satisfaction and tried to find factors affecting these graduate students who are using databases regularly at their university libraries. An analysis of the collected data shows that the level of database users' satisfaction could be directly affected by the database service quality, the easiness of accessing the system and user perceived notion of usefulness of those databases that they use often. This study also found that database users' gender could be a significant factor in their perceived notion of easiness of accessing databases, and also in their perceived notion of satisfaction for their successful information retrieval operations. The frequency of accessing databases by these graduate students has an impact on users' perceived notion of easiness of database access. The users' school classifications could make a significant difference in their perceived notion on the extent of usefulness of a particular database.

User satisfaction-based quality evaluation model and survey analysis of network information service

On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.

Electricity-Carbon Interactive Optimal Dispatch of Multi-Virtual Power Plant Considering Integrated Demand Response

As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.

Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network

Under the development of computing and network convergence,considering the computing and network resources of multiple providers as a whole in a computing force network(CFN)has gradually become a new trend.However,since each computing and network resource provider(CNRP)considers only its own interest and competes with other CNRPs,introducing multiple CNRPs will result in a lack of trust and difficulty in unified scheduling.In addition,concurrent users have different requirements,so there is an urgent need to study how to optimally match users and CNRPs on a many-to-many basis,to improve user satisfaction and ensure the utilization of limited resources.In this paper,we adopt a reputation model based on the beta distribution function to measure the credibility of CNRPs and propose a performance-based reputation update model.Then,we formalize the problem into a constrained multi-objective optimization problem and find feasible solutions using a modified fast and elitist non-dominated sorting genetic algorithm(NSGA-II).We conduct extensive simulations to evaluate the proposed algorithm.Simulation results demonstrate that the proposed model and the problem formulation are valid,and the NSGA-II is effective and can find the Pareto set of CFN,which increases user satisfaction and resource utilization.Moreover,a set of solutions provided by the Pareto set give us more choices of the many-to-many matching of users and CNRPs according to the actual situation.

Performance evaluation of residential buildings in public housing estates in 0gun State, Nigeria： Users＇ satisfaction perspective

This study assessed the performance of residential buildings in public housing estates in urban areas of Ogun State Southwest Nigeria. It was based on the notion that users＇ satisfaction with dwelling units is a measure of the performance of residential buildings in meeting their needs and expectations. A cross sectional survey of 452 household heads in nine public housing estates was conducted in the study area. Data were obtained using structured questionnaire and observation schedule; and were subjected to descriptive statistics and factor analysis. A mean satisfaction score of 3.21 was observed; indicating that the respondents were generally satisfied with the performance of the different components of the buildings. Satisfaction levels were generally higher with privacy and sizes of living and sleeping areas than the availability of water and electricity in the buildings. The type, location and aesthetic appearance as well as size of main activity areas were the most predominant factors that determined satisfaction and indeed the performance of the buildings in meeting users＇ needs and expectations. The paper highlights critical areas where attention is needed in order to improve the performance of residential buildings and users＇ satisfaction with public housing projects in Nigeria.

Computing the User Experience via Big Data Analysis:A Case of Uber Services

As of 2020,the issue of user satisfaction has generated a significant amount of interest.Therefore,we employ a big data approach for exploring user satisfaction among Uber users.We develop a research model of user satisfaction by expanding the list of user experience(UX)elements(i.e.,pragmatic,expectation confirmation,hedonic,and burden)by including more elements,namely:risk,cost,promotion,anxiety,sadness,and anger.Subsequently,we collect 125,768 comments from online reviews of Uber services and perform a sentiment analysis to extract the UX elements.The results of a regression analysis reveal the following:hedonic,promotion,and pragmatic significantly and positively affect user satisfaction,while burden,cost,and risk have a substantial negative influence.However,the influence of expectation confirmation on user satisfaction is not supported.Moreover,sadness,anxiety,and anger are positively related to the perceived risk of users.Compared with sadness and anxiety,anger has a more important role in increasing the perceived burden of users.Based on these findings,we also provide some theoretical implications for future UX literature and some core suggestions related to establishing strategies for Uber and similar services.The proposed big data approach may be utilized in other UX studies in the future.

A study on service quality evaluation of digital libraries in China based on tetra-class model

Purpose: This study intends to evaluate the service quality of academic digital libraries(DLs)in China. By utilizing tetra-class model which concentrates on categorizing services according to their contributions to user satisfaction, this paper attempts to visually categorize the specific DL service elements to reveal their present performances, and then further explain the categorizing variations among different groups of users to discover the user preference.Design/methodology/approach: This paper carries out a survey to evaluate user experience on 27 typical DL services summarized from our investigations of representative Chinese university DLs. Based on the five-point Likert-type scale evaluation, the users’ attitudes toward specific service element are divided into negative and positive dimensions. Afterwards,a correspondence analysis is applied to calculate the contributions to satisfaction and dissatisfaction of each service element based on tetra-class model. As a result, the DL service elements of Chinese academic libraries are classified into four categories(i.e. Basic, Secondary,Plus, and Key). Finally, we compared the categorizing variations.Findings: The results show that the DL service elements of Chinese academic libraries are all distributed in Basic and Key services regarding information retrieval and informationorganizing; 80% of the interaction services elements are Plus services, while 50% of the Secondary services are information-providing services. The results also reveal that service categorization is obviously influenced by the users’ education background, especially their disciplines. Furthermore, the users who are older, more highly-educated, or studying in higher reputation universities are more likely to evaluate DL services as either critical or useless.Research limitations: Tetra-class model cannot reveal the interplay among the DL service elements. In addition, the user segmentation in our studies is limited to the sample structure.Practical implications: This empirical study focuses on the evaluation of DL services of academic libraries in China, the analyses of their current performances could provide useful reference for the assessment of other types of Chinese DLs. Moreover, the consideration of user characteristics(gender, age, and education background, etc.) in the DL evaluation would help librarians improve DL services to meet the users’ various needs in teaching and doing scientific research.Originality/value: Different from the frequently-used factor analysis which focuses on the relationship among factors and user satisfaction, this paper tries to use and compare element distributions of different user segments while focusing on various service objectives. Factor analysis shows some flaws as used to measure the element with selected indicators, for it ignores the fact that the indicators which measure the same factor would have different degrees of impacts on user satisfaction. However, the tetra-class model can better visually analyze the performance of each DL service element from its contributions to satisfaction and dissatisfaction, which would help librarians to better understand users’ need and offer DL services more efficiently.

Impact Analysis of EV Charging with Mixed Control Strategy

EVs （electric vehicles） have been widely accepted as a promising solution for reducing oil consumption, air pollution and greenhouse gas emission. The number of EVs is growing very fast over the years. However, the high adoption of EVs will impose a burden on the power system, especially for neighborhood level network. In this paper, we propose a mixed control framework for EV charging scheduling to mitigate its impact on the power network. A metric for modeling customer＇s satisfaction is also proposed to compare the user satisfaction for different algorithms. The impacts of the proposed algorithms on EV charging cost, EV penetration and peak power reduction are evaluated with real data for a neighborhood level network. The simulation results demonstrate the effectiveness of the proposed algorithms.

Potential of plant identification apps in urban forestry studies in China:comparison of recognition accuracy and user experience of five apps

Information on species composition of an urban forest is essential for its management.However,to obtain this information becomes increasingly difficult due to limited taxonomic expertise.In this study,we tested the possibility of using plant identification applications running on mobile platforms to fill this vacuum.Five plant identification apps were compared for their potential in identifying urban tree species in China.An online survey was conducted to determine the features of apps that contributed to users’satisfaction.The results show that identification accuracy varied significantly among the apps.The best performer achieved an accuracy of 74.6%at the species level,which is comparable to the accuracy by professionals in field surveys.Among the features of apps,accuracy of identification was the most important factor that contributed to users’satisfaction.However,plant identification apps did not perform well when used on rare species or outside of the regions where they have been developed.Results indicate that plant identification apps have great potential in urban forest studies and management,but users need to be cautious when deciding which one to use.

Evaluation of Urban Park Design Criterias in the Case of Taraqi Park,Herat,Afghanistan

The objective of this study is to define park design standards,determine the user expectations of the parks and evaluate the defined standards in the case of Taraqi Park in Herat city.On-site detection,observation and questionnaire survey methods were utilized in the study.The conformity of the park area with international standards were evaluated while general satisfaction towards the park was tried to be determined by virtue of surveys made with the users of the park.The results revealed that the current status of the park was poor,design and management of the park needs urgent improvements.Taraqi Park is the most visited park of the city in which the overall design of the park,facilities,management and maintenance systems are observed inadequate according to standards,rules and regulations of urban parks.

Enhanced Information Systems Success Model for Patient Information Assurance

The current health information systems have many challenges such as lack of standard user interfaces,data security and privacy issues,inability to uniquely identify patients across multiple hospital information systems,probable misuse of patient data,high technological costs,resistance to technology deployments in hospital management,lack of data gathering,processing and analysis standardization.All these challenges,among others hamper either the acceptance of the health information systems,operational efficiency or expose patient information to cyber attacks.In this paper,an enhanced information systems success model for patient information assurance is developed using an amalgamation of Technology Acceptance Model(TAM)and Information Systems Success Model(ISS).This involved the usage of Linear Structured Relationship(LISREL)software to model a combination of ISS and Intention to Use(ITU),TAM and ITU,ISS and user satisfaction(US),and finally TAM and US.The sample size of 110 respondents was obtained based on the total population of 221 using the Conhrans formula.Thereafter,simple random sampling was employed to select members within each category of employees to take part in the study.The questionnaire as a research tool was checked for reliability via Cronbach’s Alpha.The results obtained showed that for ISS and ITU modeling,only perceived ease of use,system features,response time,flexibility,timeliness,accuracy,responsiveness and user training positively influenced the intention to use.However,for the TAM and ITU modeling,only TAM’s measures such as timely information,efficiency,increased transparency,and proper patient identification had a positive effect on intension to use.The ISS and US modeling revealed that perceived ease of use had the greatest impact on user satisfaction while response time had the least effect on user satisfaction.On its part,the TAM and US modeling showed that timely information,effectiveness,consistency,enhanced communication,and proper patients identification had a positive influence on user satisfaction.

Open-Label Real-World Pharmacy Purchaser Study of Two Fixed-Dose Combination OTC Cold Treatments;Wick MediNait, Wick DayMed Capsules or a Combination of Both

Acute upper respiratory tract infections, i.e. common colds cause multiple symptoms and affect adults on average 2 - 4 times a year and children 6 - 8 times per year. Thousands of non-prescription, over-the-counter products are used by sufferers, aimed at relieving the various both er some symptoms such as cough, nasal congestion, sore throat, etc. This study evaluated real-world effectiveness of Wick MediNait or Wick DayMed medicines alone and together in a combination as a day and night treatment regimen. Adult cold sufferers were recruited in pharmacy by pharmacy staff following self-purchase of either Wick MediNait, Wick DayMed capsules, or the combination of DayMed and MediNait. Participants completed online questionnaires before and after product use (evening of the first day for DayMed and the morning after using MediNait at bedtime). For the primary endpoint “Wick MediNait was effective at relieving my symptoms”, there was a statistically significant difference (p < 0.0001) in the users who Strongly Agreed or Agreed vs. Neither Agreed or Disagreed, Disagreed or Strongly Disagreed. Further, all symptoms evaluated (cough, runny nose, nasal congestion, fever, headache, sore throat, muscle aches and pains, sneezing) were statistically improved after MediNait and DayMed alone and when both were used, and users were satisfied with both treatments. All treatments were well tolerated with minimal adverse event reporting. The diurnal use of DayMed capsules combined with the nocturnal use of MediNait allows cold sufferers to efficiently self-manage their symptom relief throughout the day and night.

A survey of public needs for digital information service in libraries and museums

Purpose:The purpose of the research is to investigate public needs for digital information service in the Chinese libraries and museums and seek ways to help these public service institutions improve their service to meet user needs.Design/methodology/approach:An online questionnaire survey was used to study the publicneeds for digital information service provided by libraries and museums.A total of 474 valid questionnaires were retrieved for analysis.Findings:The primary purpose of using the digital library and museum service was for knowledge acquisition,followed by work or class assignment and leisure and entertainment.Users need one-stop information service that provides information and service in a more integrated form and allows cross-database searching as well.Research limitations:A majority of the respondents were young and middle-aged people who often use the Internet.We would need to increase our sample size and include different groups of users such as children and retirees to make the sample more representative.Practical implications:Libraries and museums should collaborate to provide the users with one-stop digital information service.Meanwhile,the research can serve as a reference source for the future studies of digital library and museum service.Originality/value:Few studies were published on the public needs for digital library and museum service in China.This study bridges the gap and contributes to our understanding of the Chinese users’ needs for digital information service in libraries and museums.

User Satisfaction-Aware Edge Computation Offloading in 5G Multi-Scenario

Edge computation offloading has made some progress in the fifth generation mobile network(5G).However,load balancing in edge computation offloading is still a challenging problem.Meanwhile,with the continuous pursuit of low execution latency in 5G multi-scenario,the functional requirements of edge computation offloading are further exacerbated.Given the above challenges,we raise a unique edge computation offloading method in 5G multi-scenario,and consider user satisfaction.The method consists of three functional parts:offloading strategy generation,offloading strategy update,and offloading strategy optimization.First,the offloading strategy is generated by means of a deep neural network(DNN),then update the offloading strategy by updating the DNN parameters.Finally,we optimize the offloading strategy based on changes in user satisfaction.In summary,compared to existing optimization methods,our proposal can achieve performance close to the optimum.Massive simulation results indicate the latency of the execution of our method on the CPU is under 0.1 seconds while improving the average computation rate by about 10%.