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There is limited research on the factors that influence people’s continued use of mobile payments in developing countries, and it is likely that these factors vary from country to country. This study aims to explore how the factors affecting the continued use of mobile payments differ between Jordan and India, using the Unified Theory of Acceptance and Use of Technology (UTAUT2) as a framework. Additionally, this study extends the UTAUT2 model by including other factors such as trust, advertising value, payment culture, awareness, smartphone experience, and satisfaction. The study employs the fuzzy Analytic Hierarchy Process (AHP) approach to rank the factors that affect the intention to continue using mobile payments. The results suggest that price value and payment culture have the greatest influence on both Jordanian and Indian perceptions. Furthermore, habit was found to be the third most important factor affecting Jordanian perceptions, while smartphone experience was the third most significant factor affecting Indian perceptions.

There is difficulty in knowing how to weigh the factors of software quality models so that decision-making can be eased. Furthermore, previous work was limited to undertake evaluation and selection of appropriate software quality model based upon multi-criteria in the context of smart health applications. This paper aims to evaluate and select an appropriate model of software quality based on multi-criteria decision-making (MCDM) by three phases of framework. Firstly, investigation of software quality models and factors that were identified based on ‘fuzzy delphi’. Secondly, identification of quality models that have uniform multi-criteria so that a decision matrix could be established. Uniform multi-criteria were used in the decision matrix as the basis of the models of quality and the multi-criteria. Subsequently, MCDM approach is adopted and the bases used in the employment of the MCDM approach for the eva luation and selection of the software quality model were technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy analytical hierarchy process (FAHP). The results demonstrated that seven quality factors could be considered as the key factors based upon fuzzy delphi, i.e., usability, maintainability, reliability, interoperability, portability, modifiability, and efficiency. Also, reults shows that McCall is the most appropriate model.

Distributed computing services in cloud environments are easily accessible to end users. These services are delivered to end users via a subscription-based model. The “infrastructure as a service” (IaaS) cloud model is one of the best cloud environment models for running data- and computing-intensive applications. Real-world scientific applications are the best examples of data and computing intensiveness. For their implementation, scientific workflow applications need high-performance computational resources and a large volume of storage. The workflow tasks are linked based on computational and data interdependence. Considering the high volume and variety of scientific workflows (SWs), the resources of the IaaS cloud model require managing energy efficiently and without failure or loss. Therefore, in order to address the issues of power consumption and task failure for real-world SWs, this research work proposes a replication-based dynamic energy-aware resource provisioning (R-DEAR) strategy for SWs in an IaaS cloud environment. The proposed strategy, R-DEAR, is a resource- and service-provisioning strategy that implements a replication-based fault-tolerant and load-balancing mechanism. The proposed R-DEAR strategy schedules the tasks of a scientific workflow with a replication-based fault-tolerant mechanism. The proposed R-DEAR strategy also manages the power consumption of IaaS cloud resources dynamically through a load-sharing process. Simulation results show that the proposed R-DEAR strategy reduces energy consumption, execution cost, and execution time by 9%, 15%, and 18%, respectively, as compared with the existing state-of-the-art strategy.

In m-commerce, privacy and security are major concerns. Existing research has examined the privacy and relationship, security, and intention to use. However, the determinants of privacy and security in mobile commerce remain largely unexplored. A study based on UTAUT2 and trust examines the factors that influence mobile commerce privacy and security. By using the approach of hybrid SEM/ANN analysis, it is possible to detect non-linear and non-compensatory relationships. According to linear and compensatory models, the absence of one determinant can be compensated for by another. The decision-making process of consumers is actually quite complex, and non-compensatory or linear models tend to simplify it. The sample is collected by using a mobile commerce application in order to gather 890 datasets on mobile commerce consumers. Findings: (1) Two determinants of M-commerce acceptance and use had an explicit and significant positive effect. Security and individual are two of these factors. (2) Privacy concerns have a severe negative impact on M-commerce acceptance and use. (3) Trust is found to partially mediate the effect on behavioral intentions of Security Factors (SCF), Privacy Factors (PRF), and Individual Factors (INF) on m-commerce in Jordan (INTENTION). According to the integrated model, m-commerce offers 71% privacy, security, and trust. Doi: 10.28991/ESJ-2022-06-06-018 Full Text: PDF

A review is conducted to deeply analyse and map the research landscape of current technologies in finger vein (FV) biometric authentication in medical systems into a coherent taxonomy. This research focuses on articles related to the keywords ‘biometrics’, ‘finger veins’ and ‘verification’ and their variations in three major databases, namely, Web of Science, ScienceDirect and IEEE Xplore. The final set of collected articles related to FV biometric authentication systems is divided into software- and hardware-based systems. In the first category, software development attempts are described. The experiment results, frameworks, algorithms and methods that perform satisfactorily are presented. Moreover, the experiences obtained from conducting these studies are discussed. In the second category, hardware development attempts are described. The final articles are discussed from three aspects, namely, (1) number of publications, (2) problem type, proposed solutions, best results and evaluation methods in the included studies and (3) available databases containing different scientific work collected from volunteers, such as staff and students. The basic characteristics of this emerging field are identified from the following aspects: motivations of using FV biometric technology in authentication systems, open challenges that impede the technology’s utility, authors’ recommendations and future research prospects. A new solution is proposed to address several issues, such as leakage of biometrics that leads to serious risks due to the use of stolen FV templates and various spoofing and brute-force attacks in decentralised network architectures in medical systems, including access points and various database nodes without a central point. This work contributes to literature by providing a detailed review of feasible alternatives and research gaps, thereby enabling researchers and developers to develop FV biometric authentication medical systems further. Insights into the importance of such a technology and its integration into different medical applications and fields are also provided.

This paper proposes a smart real-time health-monitoring structured for hospitals distributor based on wearable health data sensor. Health data were received from multiple heterogeneous wearable sensors, such as electrocardiogram (ECG), oxygen saturation sensor (SPO2), blood pressure monitor and non-sensory measurement (text frame), from 500 patients with different symptoms. Triage level and health-care services were identified based on the new four-level remote triage and package localisation (4LRTPL). The numbers of health-care services that represent hospital status were collected from 12 hospitals located in Baghdad City. This study constructed a decision matrix based on the crossover of ‘multi-health-care services’ and ‘hospital list’ within Tier 4. The hospitals were then ranked using MCDM techniques, namely, integrated analytic hierarchy process (AHP) and VlseKriterijumskaOptimizacija I KompromisnoResenje (VIKOR). Mean ± standard deviation was computed to ensure that the hospital ranking undergoes systematic ranking for objective validation. This research provided scenarios and checklist benchmarking to evaluate the proposed and existing health recommender frameworks. Results corroborated that (1) the integration of AHP and VIKOR effectively solved hospital selection problems; (2) in the objective validation, significant differences were recognised between the scores of groups, indicating that the ranking results were identical; (3) in evaluation, the proposed framework exhibited an advantage over the benchmark framework with a percentage of 56.25%; and (4) hospitals with multiple health-care services received the highest ranks, whereas hospitals with fewer health-care services received low ranks.

While mobile marketing is widely practised in developed countries, this is not always the case for developing countries, such as Jordan, where the acceptance level for mobile marketing remains low. This study aims to uncover the predictors for the behaviour of Jordanian customers with regard to the acceptance of mobile marketing. For this purpose, a questionnaire based on quantitative research was conceived. This investigation involved the unified theory of acceptance and use of technology (UTAUT2), which was extended to include two additional variables: ‘trust’ and ‘risk’. For the empirical testing of the model, data was collected from 321 respondents, and the hypotheses were tested through variance-based structural equation modelling. SmartPLS 3.0 was used to analyse the data. The findings from this study suggest that performance expectancy, effort expectancy, hedonic motivation, social influence, price value, facilitating conditions, habit and risk significantly influence the behavioural intention of customers regarding the adoption of mobile marketing. On the other hand, the trust factor was found to be an insignificant predictor in this area.