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Purpose: to analyze the ability of the National Health Insurance mobile service quality to build BPJS brand image and public trust to increase intention to use online services during the Covid period. The background of this research is based on the phenomenon in the form of complaints on the quality of online services and research gaps on the effect of service quality on the intention to use online services. Brand image and trust are offered as a mediation for gaps in previous research results. Design/ methodology/approach: The type of research is quantitative, using a pre-existing measurement scale related to mobile service quality, brand image, trust and intention. Involving a sample of 140 BPJS users during the Covid pandemic. It is difficult to identify the population size, the sample size is determined by the formulation of a constant value of 5 multiplied by 28 indicators. The technique of selecting respondents was carried out by means of non-probability random sampling. PLS SEM model as an analysis tool. Findings: The results of this study indicate that the direct relationship of mobile service quality on brand image, trust and intention shows significant positive results. Furthermore, the influence of brand image on trust shows significant results. The influence of brand image and trust on intention is also found to be significantly positive. Practical/implications: although management policies encourage customers to use mobile services more, the public still considers the trustworthy image of BPJS to develop their intention to use mobile application services. The government must remain consistent in ensuring that the quality of mobile service is not compromised because the implications for BPJS image and public trust are at stake. Through the person in charge at BPJS, the government must continue to consistently evaluate and improve the system and educate the public regarding this BPJS health mobile service system. Originality/value: This research offers new insights, filling gaps in studies on national health insurance mobile services during the Covid-19 Pandemic
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With the expansion of internet penetration and the adoption of mobile apps, usage of food delivery applications has increased significantly during the pandemic. The study's main objective was to examine the antecedents and consequences of food delivery app engagement among urban and semi-urban customers in India during COVID-19. The data were collected from 269 semi-urban respondents and 301 urban respondents. The stimulus organism and response (SOR) model has been used to understand consumers' antecedents and consequences of food delivery app engagement during the pandemic. The study used the structural equation modelling method to test the relationship between the variables. The study's findings showed that the mobile application's perceived ease of use, enjoyment, and time convenience found a significant effect among urban and semi-urban customers. This study is limited to urban and semi-urban customers with cross-sectional survey data. The study has explored a few antecedents and consequences of mobile food delivery app engagement.
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: The effects of the pandemic can translate into a variety of physical and emotional reactions that are affecting the population, particularly the elderly Panamanian population, who have not been able to overcome the mainly emerging challenges of an infectious disease with health implications. physical and has also profoundly affected their well-being and mental health. To allow the Panamanian elderly population to improve emotional self-control and mental relaxation, we propose a software architecture for the development of a recommendation system integrating: artificial intelligence (AI), internet of things (IoT) and mobile applications. Keywords: Covid-19, AI, IoT, Mobile apps, Machine learning. 1.Introducción La Covid-19 es, sin lugar a duda, la mayor catástrofe del siglo XXI, probablemente la crisis global más significativa después de la segunda guerra mundial. En este artículo, proponemos el diseño de una arquitectura altamente integral y flexible basada en diferentes elementos de TIC que permitirá extraer datos de un sensor, analizarlos y realizar recomendaciones a pacientes panameños adultos mayores con afecciones psicológicas o reacciones emocionales posteriores al contagio de la Covid-19 (post-covid-19), basado en la utilización de componentes como IA, IoT y aplicaciones móviles para lograr el autocontrol emocional y relajación mental.
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As an effect of the digital transformation encountered by higher education institutions in the post-pandemic phase, the current study aims to inspect the factors affecting the actual use of mobile learning among higher education students. A novel hybrid model based on the information system success and technology acceptance models was proposed and tested. The study included 400 undergraduate and postgraduate students from four Saudi universities who responded to a questionnaire consisting of two parts and seven dimensions, with a total of 26 items. For the analysis, a quantitative approach was applied using structural equation modeling. The results displayed that information quality had no impact on the actual use of mobile learning among higher education students. In contrast, other quality factors (system quality, service quality, and satisfaction) and perceived factors (perceived usefulness and perceived ease of use) had a positive effect. Accordingly, this study proposed an integrated framework to assist decision makers at higher education institutions in scaffolding students to develop their educational performance by depending on mobile applications comprising high-quality factors that address their real needs. This would also enable higher education institutions to enhance their digital transformation experience, thus contributing to achieving positive learning sustainability after the pandemic.
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This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19's economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease;current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.
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This study was carried out in New Bussa, Niger state, Nigeria to test the infallibility of the contention that coronavirus outbreak and suspension of physical educational services that accompanies its outbreak will positively or negatively affect demand for and adoption of electronic education (e-education) by students of various educational institutions in Nigeria. The study adopted an online survey made available via Google form to residents of the study area. Furthermore the online survey was accompanied by personal interview of school administrators and tertiary institution students. The survey questionnaire was made accessible to participants that were encouraged to fill the questionnaire online between 18th of October and 10th of November, 2020. The data retrieved were analysed using descriptive statistics and t-test. It was found that demand for and adoption of e-education through software resources was not significantly affected by coronavirus outbreak (μduring=3.90, μbefore=3.72, p>0.05), while e-education through radio and television broadcast was found to be significantly affected by coronavirus outbreak (μduring=4.83, μbefore=4.53, p<0.05). Level of income (as such, high cost of data) was found to have effect on demand for and adoption of e-education software resources. Furthermore, social media channels and generalised software applications (with reduced or no cost of data) were found to be the most adopted software resources at the expense of proprietary e-education software resources. It is therefore recommended that Nigerian government should find a way to reduce internet access cost to enable effective adoption of electronic education through mobile and website applications.
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Mobile broadband (MBB) penetration has deepened globally over the last twenty years. This is largely due to the adoption of smart devices, improved mobile communications network coverage, and the perpetual drive to develop ever faster mobile and wireless communication technologies. However, information on the quality of service (QoS) delivered by MBB operators to the end users remains an issue of concern. This has driven independent researchers and mobile communication industry regulators to develop methodologies for independent and unbiased evaluation of the QoS offered by MBB networks. This paper provides a detailed review of MBB adoption and penetration across several regions of the world. It also includes the existing methodologies for evaluating the performance of MBB systems as experienced by the end user. Specifically, methodologies such as the drive and walk tests, crowd-sourced mobile device-based methods and the software applications they employ, and the dedicated measurement testbeds are reviewed. Based on this, the challenges of adopting each of the methods are discussed in order to make a case for the development of more robust, partially autonomous and scalable MBB measurement platforms for the future.
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COVID-19 has had a broad impact on society, and a profound impact on education, thus, distance online courses are seen as a way to continue schooling during the pandemic. This study employed Android Studio to develop an APP calculus learning test system which can be used for self-review exercises and allows students to make good use of mobile apps to conduct post-learning and self-testing of calculus at home, and immediately determine their learning results. In addition, through back-end access, teachers can view students' learning scores and the number of wrong and correct questions, and thus, know the effect of individual students' self-review. During the COVID-19 pandemic, as teachers and students cannot interact in class at school, teachers can use the APP calculus learning test system to provide distance remedial teaching to students who fall behind during the course.
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In early 2020, the world was shocked by the outbreak of COVID-19. World Health Organization (WHO) urged people to stay indoors to avoid the risk of infection. Thus, more people started to shop online, significantly increasing the number of e-commerce users. After some time, users noticed that a few irresponsible online retailers misled customers by hiking product prices before and during the sale, then applying huge discounts. Unfortunately, the "discounted” prices were found to be similar or only slightly lower than standard pricing. This problem occurs because users were unable to monitor product pricing due to time restrictions. This study proposes a Web application named PriceCop to help customers' monitor product pricing. PriceCop is a significant application because it offers price prediction features to help users analyse product pricing within the next day;thus, it can help users to plan before making purchases. The price prediction model is developed by using Linear Regression (LR) technique. LR is commonly used to determine outcomes and used as predictors. Least Squares Support Vector Machine (LSSVM) and Artificial Bee Colony (ABC) are used as a comparison to evaluate the accuracy of the LR technique. LSSVM-ABC was initially proposed for stock market price predictions. The results show the accuracy of pricing prediction using LSSVM-ABC is 84%, while it is 62% when LR is employed. ABC is integrated into SVM to optimize the solution and is responsible for the best solution in every iteration. Even though LSSVM-ABC predicts product pricing more accurately than LR, this technique is best trained using at least a year's worth of product prices, and the data is limited for this purpose. In the future, the dataset can be collected daily and trained for accuracy.
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The purpose of this study is to address two major issues: (1) the spread of epidemics such as COVID-19 due to long waiting times caused by a large number of waiting for customers, and (2) excessive energy consumption resulting from the elevator patterns used by various customers. The first issue is addressed through the development of a mobile application, while the second issue is tackled by implementing two strategies: (1) determining optimal stopping strategies for elevators based on registered passengers and (2) assigning passengers to elevators in a way that minimizes the number of floors the elevators need to stop at. The mobile application serves as an input parameter for the optimization toolbox, which employs the exact method and multi-objective variable neighborhood strategy adaptive search (M-VaNSAS) to find the optimal plan for passenger assignment and elevator scheduling. The proposed method, which adopts an even-odd floor strategy, outperforms the currently practiced procedure and leads to a 42.44% reduction in waiting time and a 29.61% reduction in energy consumption. Computational results confirmed the effectiveness of the proposed approach.
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With the development of computer and information technology, mobile teaching has enjoyed pride of place among teaching mediums in the past two decades. To visually explore the mobile learning hotspots and trends present in international journals, this study adopted two science mapping tools (CiteSpace and VOSviewer) to first detect and then visualise emerging trends (i.e., hotspots) in the mobile learning literature. A total of 528 mobile learning articles published between 2003 and 2021 that appeared in 21 international educational technology journals indexed in the SSCI database were retrieved for bibliometric analysis. The results show (1) there was a remarkable increase in academic output in this field starting in 2008 that topped out in 2021;(2) co-authorship with academics from diverse countries/regions and institutions was evident;(3) three trending foci in the literature include defining mobile learning, designing learning systems, and exploring mobile learning effectiveness;and (4) the high-frequency co-cited publications focus on the effectiveness of mobile devices via different research methods. This study provides scholars with an accessible summary of the current trends in mobile learning, identifies the active researchers in this field, and reports on which outlets are most relevant for research produced on this topic. In addition, the findings have direct implications for the education and private sectors. Mobile devices are not widely adopted in classroom settings and are often considered a learning tool more suited for out-of-class assignments or practice. Therefore, it is necessary for information technology educators to invest in actively initiating the integration of mobile technology into the classroom. Those in the technology industry should aim to develop mobile devices and relevant educational applications/software that can be utilised not only within the confines of the classroom but also to bridge in-class and out-of-class learning.
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In this paper, we present CoFighter, a mobile application for prevention and management of COVID-19 and other related pandemics in the globalized world. We took advantage of the proliferation of mobile smart devices in every home to design and implement an Android application for COVID-19 and similar pandemics. Since the outbreak of COVID-19 pandemic in 2019, there has been even more serious pressures on governments and health institutions on the best way to provide appropriate and reliable guide to individuals on how to contain the virus and similar pandemics in the future. Citizens have not been adequately informed of the various provisions and guides by their governments and the wide usage of social media had led to the spread of fake news, misinformation and conspiracy theories. It therefore becomes very necessary to develop a dynamic information repository in the form of a mobile application to help combat the spread of any pandemic whenever the need arises. The application provides information on COVID-19, vaccine challenges, prevention guides and cases management and timely updates to keep citizens properly and adequately informed. It makes provision for future similar pandemics that could throw the world into chaos as the CORONA virus did in 2019. The weaknesses and challenges observed in most popularly existing COVID-19 applications were highlighted and implemented in CoFighter. CoFighter provides users, governments and health workers with a platform not only to manage COVID-19 and other similar pandemics in the future, but also helps frontline health workers to better manage the pandemics. The developed application runs on an Android device with Android version 4.2 or higher and can be used not only to manage COVID-19 pandemic, but also to manage economic crisis and similar future pandemics. CoFighter is available via the Repository: https://github.com/OkeyIsOkay/CoFighter-Project.
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The structural analysis module is a challenge for both teachers and students. The module content is usually presented to students in the form of a set of equations when solved, the structure of internal forces is obtained. Usually, the assignments adopted in such modules are paper‐based exams. Such a strategy may assess the capacity of the students to employ different sets of equations to solve a problem. However, this is not enough for a vivid educational atmosphere. Transforming these equations into a digital simulation is the best solution for the education process. Digitalization is more appealing to nowadays students and it gives the teacher a wide spectrum of discussions without the hindrance of calculations time. It is also a mitigation for the online teaching process during the Covid‐19 pandemic. This paper presents a digital simulation of different structures using a simple tool that enables students to visualize the simultaneous interaction between geometry, loading, boundary conditions, and internal forces. Furthermore, transforming this tool into an offline mobile app helps both the teacher and the student to gamify the investigation of any structure.
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Libraries are adapting to the changing times by providing mobile services. One hundred fifty-one libraries were chosen based on circulation, with at least one library or library system from each state, to explore the diverse services provided to mobile users across the United States. According to the data, mobile apps, mobile reference services, mobile library catalogs, and mobile printing are among public libraries' most-frequently offered services, as determined by mobile visits, content analysis, and librarian survey responses. Every library examined had at least one mobile website, mobile catalog, mobile app, or webpage adapted for a mobile device. Following the COVID-19 outbreak, services such as mobile renewal, subscriber database access, mobile reservations, and the ability to interact with a librarian were expanded to allow better communication with customers-all from the comfort and safety of their own homes. Libraries are continually looking for innovative methods to assist their mobile customers as the world changes.
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Featured ApplicationThe same tool could be used repeatedly to track the changes in CMJ performance. Average jump heights should be analyzed. Practitioners and sports professionals without extensive knowledge of assessment could self-administer CMJ tests using these devices.Mobile applications and portable assessments make remote self-assessment of the countermovement jump (CMJ) test possible. This study aimed to investigate the concurrent validity and test–retest reliability of three portable measurement systems for CMJ. Thirty physically active college students visited the laboratory twice, with two days in between, and performed three jumps each day. All jumps were recorded by My Jump 2, HomeCourt, and the Takei Vertical Jump Meter (TVJM) simultaneously. Results indicated significant differences among the three systems (p < 0.01). HomeCourt tended to present the highest jump height mean value (46.10 ± 7.57 cm) compared with TVJM (42.02 ± 8.11 cm) and My Jump 2 (40.85 ± 7.86 cm). High concurrent validities among assessments were found (r = 0.85–0.93). Good to excellent reliability of jump assessments was demonstrated (ICC3,1 = 0.80–0.96). Reliable coefficients of variation were shown in all measurements (2.58–5.92%). Significant differences were revealed among the three apparatuses while they demonstrated high intra-device test–retest reliability. TVJM was the most reliable, and average jump heights were recommended for analysis.
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Leisure trips have become more important in an era where people are increasingly concerned with quality of life. Leisure trips are unique in that they are not as strict as mandatory trips, while, at the same time, they have wider characteristics because of their flexibility. Research on leisure trips from developing countries is still under-represented as there is still a focus on commuting trips. This study aims to identify factors that influence the mode of transportation choice for leisure trips by domestic travelers who live in cities surrounding Bandung, Indonesia. Data were collected using stated-preference self-report questionnaires distributed to locals who have the intention to travel for leisure in Bandung in the future. Based on responses from 305 respondents with a total number of 1220 observations, a multinomial logit model was estimated. It was found that trains and buses were selected more often by locals than other modes of transportation, including private cars, for leisure trips. Our model showed that locals considered travel time and travel costs as the most significant factors in selecting the mode of transportation for their leisure trips. Besides the existence of online transportation—hailing rides through mobile apps—as an alternative, this study also reveals payment method to be a unique consideration of locals when travelling leisurely in this digital era.
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Mobile messaging apps are currently a popular method in Malaysia for communicating while on the go, owing to its convenience, reliability, and contact-free feature of mobile application. Fueled by mobile internet and smartphone growth, mobile messaging apps have become a strong force in the mobile app sector, offering users an alternative to SMS-based texting paired with social media elements and enhanced features, such as group chats and photo sharing. The study was anchored using the unified theory of acceptance and use of technology 2 theory. A survey with 150 respondents and PLS analysis is used to determine the antecedents of mobile application continuance usage during the COVID-19 pandemic. The results revealed that there is an influence in the usage of mobile messaging apps among the younger generation in Malaysian public university students during the COVID-19 pandemic. The main implication shows that mobile application among young generations in public universities has become popular. The convenience usage of the internet has turned the world into a global village.
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The challenge to guarantee healthy aging has become a major social concern. Due to the cognitive deficits related to age, hectic daily activities, and multiple medications prescriptions, the elders often tend to forget their pills intakes. This has a colossal impact on their health and life. Moreover, the recent pandemic of COVID-19 has accentuated the importance to provide independent and autonomous living for the elderly. This paper presents a pill management system based on loT intended for aged individuals. The proposed system is a smart pill dispenser associated with a mobile application. The main actors of the system are the patient, the doctor, the pharmacist, and the patient's caregiver and/or relative, each having restricted access to the system via specific credentials. The prescription is directly edited on the mobile application by the doctor and the scheduling and filling of the pillbox is done wirelessly by the pharmacist. The reminding of medications intakes in this system is done gradually to help the patient adhere to his/her prescription. First, it notifies the patient about his/her scheduled pill by a mobile notification then via the pill dispenser using LCD, LED, and buzzer. The implemented system also allows the doctor and caregiver to keep a tab of the patient's intakes. Furthermore, the pill dispenser is featured with a locking mechanism to ensure medication dosage control and prevent drugs abuse. Experiments show that the proposed system is appreciated by the elderly and encourages them to take their pills successfully and safely without causing any disturbance.
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In the context of software development, requirement engineering is one of the crucial phases that leads to software project success or failure. According to several disruptive changes in the software engineering landscape as well as the world's challenge of virus pandemic, the provision of practical and innovative software applications is required. Therefore, issues resolution in requirement elicitation is potentially one of the key success factors resulting in enhanced quality of system requirement. The authors have striven to create new ways of requirement elicitation according to factor effects of communication, culture, competency, and stakeholder, by incorporating tools, processes, methods, and techniques to solve the problems comprehensively, and then proposed an adaptive and applicable conceptual framework. To illustrate these effects, the authors performed a literature review from the past 8 years, and then data analysis from interviews of 27 practitioners, observations and focus groups of software development in real-life projects.
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Many cities in Indonesia are prone to disasters, and the Coronavirus disease (COVID-19) pandemic taught a lesson on how important for a city to be resilient to disaster. Previous studies indicated that smart city initiatives could improve a city's resilience toward disasters. This paper sheds light on how implementing innovative initiatives can improve a city's resilience toward disasters. We review the existing literature on smart city and resilient city concepts and conduct a focus group discussion with the representative of the local government of Tangerang city, Banten province of Indonesia, to understand how the city improves its resilience towards disaster by implementing smart city initiatives. The results indicate that city has developed various software applications and community engagement programs to break the chain of transmission. The results also suggest that city leadership and citizen engagement play an essential role in developing a smart and resilient city.