International Journal of Mobile Communications (33 papers in press)

Regular Issues

• When do people share different health rumors? An empirical study in the COVID-19 context in China
  by Xin Zhang, Peng Yu, Liang Ma 
  Abstract: One of the most important questions confronting managers is how to control different rumours. Although previous literature has studied the antecedents of users’ rumours sharing intention, little research has focused on how different rumour types (dread and wish rumour) affect sharing intention and its’ boundary conditions. To fill this research gap, this study conducted two empirical studies based on elaboration likelihood model (ELM) to explore how the way of processing rumours varies with rumour type. The results show that: 1) in dread rumour studies, central cues have a positive effect on sharing intention, while only source credibility in peripheral cues has a positive effect on sharing intention; 2) in wish rumour studies, peripheral cues have a positive effect on sharing intention, while only perceived utility in central cues has a positive effect on sharing intention; 3) enjoy in helping others positively moderate the relationship between rumour characteristics and sharing intention.
  Keywords: rumour sharing intention; credibility; perceived utility; perceived persuasiveness; enjoy in helping others; elaboration likelihood model; ELM; China.
  DOI: 10.1504/IJMC.2025.10060820
   
  
• A new energy-aware resources scheduling method for mobile Internet of thing using a hybrid optimization algorithm  
  by Jiuhong Yu, Kang Hou, Haiyang Zhang, Branislav Kostic, Ming Yang, Habibeh Nazif 
  Abstract: This paper suggests a hybrid optimisation technique for scheduling mobile internet of things (IoT) resources that integrates the grasshopper optimisation algorithm with the crow search algorithm to address these issues. The GOCSA hybrid algorithm is designed to effectively increase the benefits of the two methods and produce a standard execution. MATLAB is used to explore the simulation. Other algorithms are contrasted with the suggested approach. The model simulation shows that the suggested technique applying the proposed method on MIoT greatly improves energy consumption and decreases delay time in comparison to conventional methods.
  Keywords: resource scheduling; mobile; internet of things; IoT; energy; optimisation; algorithm; mobile IoT; MIoT.
  DOI: 10.1504/IJMC.2025.10062645
   
  
• A new fuzzy-based nature-inspired routing method for mobile internet of things (MIoT)  
  by Chenchen Gao, Amin Salih Mohammed 
  Abstract: In the ever-evolving landscape of the IoT, the need for efficient and reliable routing methods is paramount. With the surge in mobile IoT devices, traditional routing algorithms have shown limitations in adapting to dynamic and unpredictable network conditions. Designed for static networks, these algorithms struggle to cope with the dynamic nature of mobile IoT, where devices are constantly on the move, leading to frequent network topology changes. To address these shortcomings, there is a pressing need for innovative routing methods capable of handling the unique challenges posed by mobile IoT. To address these challenges, this paper proposes a fuzzy-based nature-inspired routing method. One of the best algorithms that can be combined with fuzzy logic for routing in mobile IoT is the flower pollination optimisation (FPO) algorithm. Rigorous testing and simulations reveal that the proposed approach outperforms current methods across various metrics, including energy consumption, network lifetime, end-to-end delay, and packet drop ratio.
  Keywords: IoT; mobile; routing; energy; FPO algorithm; fuzzy logic.
  DOI: 10.1504/IJMC.2025.10063145
   
  
• Switch to a new version or keep status quo? The explanation for users to update software from push-pull-mooring perspective  
  by Xue Sun, Yuhao Li 
  Abstract: Companies invest high-volume costs in software maintenance but often failed to receive equivalent feedback from users (e.g., resistance to update). This research aims to shed light on the update motivation of users. In the context of online meetings (OMs), this study is guided by the status quo bias and the application technology innovation theory to establish an updating motivation model framed by push-pull-mooring (PPM). The model was verified using the PLS method based on an online survey with 380 samples. The results indicated that push factors, pull factors, and mooring factors have significant impacts on the OM users’ update intention. A multi-group comparison further shows that the cognitive resource moderates the effects of pull and mooring factors on the OM update.
  Keywords: status quo bias; SQB; cognition resource; push-pull-mooring; PPM; software update; migration in IS; online meeting.
  DOI: 10.1504/IJMC.2025.10063219
   
  
• Exploring the influence of new media and mobile technologies at tertiary education in a developing country: a case study of teacher-student interactions in Northern Cyprus during the COVID-19 pandemic  
  by Ahmet Iyici, Ülfet Kutoglu Kuruç 
  Abstract: COVID-19 pandemic and technological developments have changed the attribute and form of human communication. The main purpose of this quantitative research was to delve into the influence of digital technologies over communication and teacher-student interactions amid the pandemic at a major university in Northern Cyprus. The findings indicated that the use of digital technologies cultivated teacher-student interactions in or out of school settings, transformed the roles of teachers into facilitators and mentors, and increased teachers’ accessibility. The new phase also assisted students to comprehend the topics discussed in class easily. Furthermore, technological innovations created new sources of information for both parties to enhance course contents, boost students’ self-esteem, allow education out of the school settings and escalate the effectiveness of education by promoting self-cultivation. Mobile technologies removed communication barriers between educators and learners by allowing them to reinforce their interactions virtually, yet, they cause technology addiction and decline face-to-face communication.
  Keywords: adult learning; distance education; online learning; learning communities; media in education; mobile communications.
  DOI: 10.1504/IJMC.2025.10063255
   
  
• Blockchain based packet parser architecture for securing cyber-infrastructure and internet of things networks with auto-metric graph neural network  
  by R. Deepa, S. Subasree, N.K. Sakthivel, Amit Kumar Tyagi 
  Abstract: Block-chain technology, also known as cryptographic ledger technology, has recently been used to transport transactions and information securely through networks, primarily to increase security. AGNN long Block-chain based Packet Parser architecture is proposed for enabling cyber security at IoT devices. IoT architecture is processed on basis of 3 layers that are named as cloud layer, edge layer and device layer. Every node in edge layer is configured by proposed Auto-metric Graph Neural Network with BC-PP for analyzing cyber-attacks. Proposed method is decentralized between edge nodes at edge layer of networks. Proposed technique will be executed on working platform of python device. Performance of proposed algorithm is evaluated under performance metrics, accuracy, detection time, attack probability, packet drop ratio, packet delivery ratio, computational time, delay. Here proposed method provides 8.76%, 24.6%, 21.46% high accuracy, 69.53%, 45.5%, 66.7% lower detection time, 4.4%, 8.2%, 10% lower computation time comparing to existing methods respectively.
  Keywords: Internet of things network; Cyber security; Block chain Based Packet Parser Architecture; Auto-metric Graph Neural Network.
  DOI: 10.1504/IJMC.2025.10063283
   
  
• Knowledge sharing platform users' switching intention from the perspective of the push-pull-mooring framework  
  by Rui Wang, Dingyu Ye, Zhengzhi Jia, Dongmin Cho 
  Abstract: This study investigates user switching intentions on knowledge sharing platforms (KSPs) in China using an extended push-pull-mooring (PPM) framework. It aims to identify factors influencing users’ decisions to retain or switch KSPs, providing insights for user retention strategies. A structural equation model was employed, using 330 valid responses from an online survey. The findings reveal that push effects (dissatisfaction, privacy concern, perceived overload), pull effects (attractiveness of alternatives, information need, social need, and entertainment need), and mooring effects (switching cost, media attachment) significantly influence KSP users’ switching intentions. Mooring effects moderate the relationship between push effects and switching intention, but not between pull effects and switching intention. Personal innovativeness positively impacts switching intention. These findings help KSP providers understand users’ switching intentions and formulate relevant theories, services, and regulations.
  Keywords: knowledge sharing platform; push-pull-mooring model; switching intention; personal innovativeness; PLS-SEM.
  DOI: 10.1504/IJMC.2025.10063767
   
  
• The enchantment of live broadcasters and online impulse buying  
  by Edward C. S. Ku, Chun-Der Chen, Ya-Hui Chan, Ling-Ling Liu 
  Abstract: This study examines the elements of external information that influence buyers’ psychological state and subsequent behavioural intention from the perspectives of emotion and source credibility. The sample consists of people with impulse buying experience on Taobao and JD.com. We contacted the online retailers and asked them to provide their buyers with an invitation message and a hyperlink to our survey, and 517 valid questionnaires were returned. The results show that review helpfulness, product enticement, and trust in broadcasters significantly contribute to online buyers’ emotional responses, while the influence of emotional response on impulse buying is moderated by the effect of online retailer stickiness. Impulse buying has become a critical issue; increasingly, more online retailers focus on impulse buying mechanisms to understand how to enhance best buying behavioural. This study provides an overall understanding of impulse buying with online retailers.
  Keywords: impulse buying; review helpfulness; product enticement; trust in broadcasters; emotional responses; online retailers.
  DOI: 10.1504/IJMC.2025.10063857
   
  
• Predictors of Instagram use for user productivity: self-control, notifications, and checking habits  
  by Cemil Akkas, Aykut Hamit Turan 
  Abstract: Social networking sites usage may result in individuals’ heightened procrastination and lowered productivity. Based on the temporal motivation theory (TMT), this study investigates the antecedents of Instagram use for procrastination and their effects on users’ productivity. A survey (N = 356 Instagram users in Turkey) is administered, and the structural equation modelling (SEM) is run respectively to gather and analyse the data. Self-control is revealed to be a predictor of Instagram use for procrastination, yet no significant relationship is found to be prevalent between notifications and checking habits with the Instagram use for procrastination. Furthermore, procrastination, the frequency of checking Instagram, and notifications received from this application have been shown to have a detrimental influence on productivity, as expected. Similarly, self-control and productivity are shown to have a positive correlation. We also suggested some theoretical and practical implications.
  Keywords: procrastination; self-control; notifications; checking habits; Instagram; productivity; SEM.
  DOI: 10.1504/IJMC.2025.10064102
   
  
• The study of social networking site characteristics on consumer trust towards positive WOM and purchase intention  
  by Lu-Wen Liao, Chun-Tsen Yeh, Pei-Chun Fang, Wan-Ting Sun 
  Abstract: Social commerce is the process of selling products and services directly through social media such as social networking sites (SNSs). In recent years, social commerce has experienced a significant expansion, especially in cross-border e-commerce and during the COVID-19 pandemic. Important characteristics of SNSs include intimacy, familiarity, expertise, and interactivity. This study examined the influence of these four characteristics on consumer trust as well as the influence of trust in turn on purchase intention and positive word-of-mouth (WOM). This investigation was based on the stimulus-organism-response framework in which shopping experience was included as a moderator. We confirmed positive correlations between familiarity, expertise, and interactivity with consumer trust as well as positive correlations between trust with purchase intention and positive WOM. There was no significant relationship between intimacy and consumer trust. We also found that shopping experience played a crucial moderating role in the relationships between familiarity, expertise, and interactivity with trust.
  Keywords: social networking site; SNS; S-O-R model; social networking site characteristics; purchase intention; shopping experience.
  DOI: 10.1504/IJMC.2025.10064114
   
  
• Border Collie optimisation algorithm for Twitter sentiment classification based on enhanced Elman spike neural network  
  by D. Divya, Annamalai Pandiaraj, Chinnaraj Govindasamy 
  Abstract: The sentiment classification field has been increasingly interesting for academic and industrial study due to the widespread development of online reviews. Many sentiment classification approaches are developed to carry out sentiment analysis. Nevertheless, the information retrieval is not carried out precisely, inefficient, and does not converge as quickly. To overwhelm these issues, an enhanced Elman spike neural network optimised with border collie optimisation algorithm for Twitter sentiment classification (EESNN-BCOA-TSC) is proposed in this paper for classifying the Twitter data. Here, the Twitter data is amassed from Twitter sentiment dataset. Then the input Twitter data is pre-processing. These pre-processed data is fed to the fast discrete curvelet transform with wrapping algorithm (FDCT-WA) for extracting the features. These extracting features are fed to EESNN-BCOA that categorises the Twitter data as positive, negative or neutral. The proposed EESNN-BCOA-TSC technique is activated in Python. From the analysis, it attains better accuracy of 99.7%, sensitivity of 98.8%, and F1-score 98.9%.
  Keywords: social media; Twitter; enhanced Elman spike neural network; Border Collie optimisation algorithm; Twitter sentiment dataset.
  DOI: 10.1504/IJMC.2025.10064219
   
  
• Understanding open source community user contribution from the S-O-R perspective  
  by Tao Zhou, Qingqing Yuan 
  Abstract: User contribution creates the content of open source communities and it is crucial to the sustainable development of the communities. However, users often lack the motivation and intention to contribute their knowledge. Based on the S-O-R model, this research examined open-source community user contribution by integrating both social and technological perspectives. A mixed method of SEM and fsQCA is used in this research. The results found that social factors (social interaction and social support) and technological factors (system quality) significantly affect the sense of virtual community, which further affects user contribution intention. The fsQCA results revealed that in the three paths triggering user contribution intention, social interaction and a sense of virtual community appear as the common core conditions. The results suggest that open source communities need to encourage users’ social interactions and develop a supportive climate to enhance the sense of virtual community and facilitate their contribution.
  Keywords: open-source community; S-O-R; contribution; sense of virtual community; SOVC; social interaction.
  DOI: 10.1504/IJMC.2025.10064407
   
  
• Gamification, socialisation, or self-purpose? Who is using the swarm app and why?  
  by Haldun Çolak, Tahsin Percin Batum 
  Abstract: The study looks at how and why users use Swarm app with Foursquare combining hedonistic and utilitarian benefits with gratification factors in terms of gamer types. Swarm is the best location based social media (LBSM) because it satisfies all the factors. Since the app is mostly used by young people, data from 195 university students was collected and analysed using least squares structural equation modelling (PLS-SEM). The empirical findings show strong correlations between gratification factors (gamification, socialisation, and self-purpose) and hedonic and utilitarian benefits. The results also indicate that hedonic benefit fully mediates the relation between gratification factors and intention. The results of multigroup analysis (MGA) show that different user types moderate a large portion of the overall model, implying that user characteristics are important explanatory factors because they explain why and how different user types use Swarm. By focusing on gratification, the study expands knowledge and provides new insights.
  Keywords: uses and gratifications; U&G; user types; social networks; PLS-MGA.
  DOI: 10.1504/IJMC.2025.10064622
   
  
• Performance analysis of 3D M-tier heterogeneous networks using adaptive multi-stream carrier aggregation  
  by Rekha Mathivanan, Bhuvaneswari Mariappan 
  Abstract: In recent days, heterogeneous networks (HetNets) gaining enhances range of attention as the promising concept in mobile networking. Several cellular standards like long term evolution (LTE) are introduced for the mobile devices that were not appropriate for Low power devices. In this paper, a new-fangled next generation 3D HetNet model is proposed by placing the small cells positions in the HetNet Environment under realistic constraints. An approach of Adaptive Multi-stream carrier aggregation (AMCA) is proposed for enhancing the bandwidth amount of the HetNet users. The 3D M-tier HetNet with AMCA is adopted mainly for eliminating cross-tier interference and increasing energy efficiency (EE). This method is employed for transmitting healthcare related data under IoT-based mobile (m)-health application scenario. The proposed work performance estimation is made with respect to phase response metrics, EE, error vector magnitude (EVM) and absolute in-band emission for varied range of carrier components (CCs).
  Keywords: heterogeneous networks; carrier components; CCs; LTE advanced; adaptive multi-stream carrier aggregation; AMCA; 3D M-tier HetNet; healthcare application.
  DOI: 10.1504/IJMC.2025.10064691
   
  
• Understanding young adults’ use of mobile banking: the integration of the UTAUT, D&M, and PMT models  
  by Muhammad Ashraf Fauzi, Christine Nya-Ling Tan 
  Abstract: Recognising factors driving m-banking adoption among young adults is crucial for improving user performance. However, little knowledge exists of their acceptance and usage. Thus, this research investigates the factors driving m-banking adoption among young adults in higher education institutions. It integrates three theoretical models: the Unified Theory of Acceptance and Use of Technology (UTAUT), the Delone and McLean (D&M) IS theory, and the protection motivation theory (PMT). A self-administered survey was distributed to university students in Malaysia using a quantitative technique approach. The partial least squares structured equation modelling results showed that performance expectancy, facilitating condition, system quality, information quality, and perceived severity significantly correlate with intention. However, effort expectancy, social influence, service quality, trust, perceived privacy, perceived security, perceived vulnerability, and satisfaction did not. This study bridges research gaps to provide a comprehensive knowledge of how these models increase m-banking services’ acceptance and usage, particularly among young adults.
  Keywords: M-banking; young adults; university students; unified theory of acceptance and usage of technology; DeLone and McLean IS theory; D&M; protection motivation theory; PMT.
  DOI: 10.1504/IJMC.2025.10064926
   
  
• Why people discontinue using smart wearable devices: an integrated benefit-risk perspective  
  by Shin-Horng Chen, Cheng-Kui Huang, Wan-Ching Cheng 
  Abstract: With the vigorous development of science and technology, people have increasingly relied on the convenience of emerging technologies in the recent years, making wearable devices one of the fastest-growing and popular products. However, after enjoying these devices for a while, there may be multiple risk and benefit considerations, affecting the users’ intention to stop using them. Although there are many studies on the use intention of information technology, few studies have discussed the discontinuance issue of smart wearable devices. Therefore, we propose an integrated model, consisting of the perceived risk and the perceived benefit, to explore the factors that affect the users’ intention to terminate the usage of smart wearable devices. A questionnaire survey was conducted, and 529 valid questionnaires were collected to analyse the samples using structural equation modelling. The result showed that our model had 57% explanatory variability. The findings and implications are beneficial to researchers and practitioners.
  Keywords: discontinuance usage; perceived risk; perceived benefit; smart wearable device.
  DOI: 10.1504/IJMC.2025.10065067
   
  
• Bayesian multi agent based load balance for control video traffic in Wireless Mesh Network (WMN)  
  by G.P. Raja, Arthanari Vadivalagan Santhosh Babu 
  Abstract: In this manuscript, Bayesian multi agent based prioritised load balancing is proposed for controlling video traffic in a wireless mesh network (BMA-PLB-CVT-WMN) to overcome such limitations. The Bayesian multi-agent based prioritised load balancing scheme enhances video packet balance and load performance by minimising end-to-end delay. This scheme deploys multiple agents routing agent, a traffic monitoring agent, and a traffic controlling agent to manage video traffic efficiently in a WMN. Initially, the routing agent facilitates optimal path selection for video packets from source to destination nodes, ensuring reliable delivery. The traffic monitoring agent, guided by the Bayesian theorem, identifies abnormal traffic. Finally, the traffic controlling agent, employing the prioritised load balancing algorithm, balances video packet loads at node queues, significantly improving load performance and reducing end-to-end delays during transmission in the network. The proposed method attains a higher end to end delay and a lesser execution time compared to existing techniques, respectively.
  Keywords: abnormal traffic; Bayesian theorem; load balancing; routing agent; traffic controlling agent; traffic monitoring agent; video packet.
  DOI: 10.1504/IJMC.2025.10065112
   
  
• Customer intention in using mobile payment: perspectives of attitudes and mooring effects  
  by Chien-Ta Ho, Jhong-Min Yang, Tung-Miao Chang 
  Abstract: In many cases, consumers’ positive and negative attitudes towards technology often coexist, making it challenging to determine whether these attitudes encourage or deter adoption at any given moment, even if positive/negative factors are strong, some consumers may not adopt or abandon the technology due to the mooring effects of environmental factors. This study establishes an innovative A-M model. We evaluate the model using 306 valid samples for the structural equation modelling (SEM) analysis. The findings indicate that positive attitudes, negative attitudes, and mooring effects coexist in the user’s mind because of the reflections of technology characteristics, individual perceptions, and environmental and contextual variables. Only the positive attitudes affect consumers’ intentions to use m-payment significantly. Furthermore, the mooring effect’s moderating effects were limited to the relationship between negative attitudes and usage intentions. This paper concludes by discussing the academic and practical implications and suggestions for further research.
  Keywords: mobile payment; positive attitudes; negative attitudes; mooring effects; intention to use.
  DOI: 10.1504/IJMC.2025.10066122
   
  
• Exploring the influence of trust transfer and privacy calculus on the intention to disclose information on social media payment  
  by Jengchung Victor Chen, Khulan Tuvshinbat, Sinh Thi Thu Tran 
  Abstract: Social media payment recently has arisen to be a new form of digital payment and has the characteristics of both mobile payment and social media. This paper develops a model to investigate the trust transfer mechanism from social media and mobile payment to social media payment, the calculus of risks and benefits as key factors on users’ intention to disclose information on social media payment and the moderating roles of trust on the relationships between perceived risks and intention and between perceived benefits and intention. A two-stage experiment was conducted to collect data to empirically test the research model. The results show that the structural assurance trust of social media and the competence, benevolence, and integrity trust of mobile payment successfully transfer into trust in social media payment. Trust in social media payment, perceived risks, and perceived benefits are found to significantly lead to the intention to disclose information to social media payment. However, trust in social media payment does not influence the relationships between perceived risks and intention and between perceived benefits and intention. This hints that users would judge based more on objective information rather than be influenced by subjective trust.
  Keywords: social media payment; mobile payment; social media; trust transfer; privacy calculus; intention to disclose.
  DOI: 10.1504/IJMC.2025.10066630
   
  
• iBlockcity: a blockchain-based smartcity architecture for secure data transmission in smartcities using the internet of everything  
  by Senthil Prakash Kuppusamy , Mahendrakumar Subramaniam, Prabhavathy Sundaram, Vanitha Krishnan 
  Abstract: The smartcity’s complex design raises several security issues for a diverse device ecosystem. A device management system is needed to control each node because an attacker is more likely to get in through a single device or node in a network of different devices. This article suggests a blockchain-based smartcity architecture for secured data transmission in smartcities using the internet of everything (IoE) called iBlockcity. The proposed architecture integrates various technologies like blockchain, IoE, machine learning, and cloud computing to create a secure and efficient system for data transmission. In addition, principal component analysis (PCA) is utilised for feature extraction and data reduction to enhance the systems performance. The proposed architecture ensures secure data transmission using blockchain technology for authentication and encryption. iBlockcity utilises machine learning methods to optimise data processing and power usage. The suggested method is tested using a simulation environment with different datasets, and the results show that the iBlockcity effectively ensures secure data transmission in smartcities. The proposed iBlockcity architecture provides a robust and reliable solution for smartcity applications that require safe and efficient data transmission.
  Keywords: blockchain; smartcity; security; internet of everything; IoE.
  DOI: 10.1504/IJMC.2025.10067344
   
  
• Evaluation factors for consumers to open mobile positioning function to receive and to click location-based advertising  
  by Heng-Li Yang, Shiang-Lin Lin 
  Abstract: Local-based advertising (LBA) service is the newest application of mobile advertising, it can transmit the advertisement concerning consumers’ geographical location, and can more effectively achieve the marketing effect. However, LBA service is still a newly emerged mobile application service. As a result, there are not yet many consumers who are willing to enable the positioning function in their mobile devices to receive and click the LBA. Therefore, it would be essential for future development of LBA services what evaluation factors would make the consumers willing to enable the mobile positioning function to receive LBA and to click the received LBA. Accordingly, this study combined FAHP and DEMATEL to conduct a two-phase analysis: 1) the factors evaluated by consumers to receive the LBA; 2) the factors to click for watching the received LBA. The most critical evaluation factors were reported.
  Keywords: local-based advertising; consumption value theory; privacy risk; fuzzy AHP; DEMATEL.
  DOI: 10.1504/IJMC.2025.10067345
   
  
• Intelligent resource allocation for 5G cloud-radio access networks  
  by Naveen Kumar 
  Abstract: The growing demand for mobile data services has driven efforts to improve the quality of service (QoS) in beyond 5G (B5G) networks. Moving beyond conventional static methods, 5G enables flexible programming using software-defined networking, slicing, and network capability exposure to optimise QoS. A key advancement in 5G is the cloud-radio access network (C-RAN), which separates baseband processing units from remote radio heads and centralises them in the cloud. This paper introduces an adaptive, QoS-aware resource allocation model for multi-tenant, multi-service C-RAN scenarios. A deep reinforcement learning (D-RL) approach is used to achieve optimal resource distribution. Experimental validation with a 5G prototype based on open air interface (OAI) confirms the superiority of this method in terms of network throughput, prediction accuracy, and system utilisation compared to other resource allocation techniques.
  Keywords: 5G; cloud-radio access network; C-RAN; artificial intelligence; deep reinforcement learning; Q-learning; quality of service; QoS; resource allocation.
  DOI: 10.1504/IJMC.2025.10067346
   
  
• Design of effective non-orthogonal multiple access system by maximising spectral and energy efficiency using hybrid heuristic optimisation approach  
  by R. Prameela Devi, N. Prabakaran  
  Abstract: Power allocation for the trade-off between EE-SE for uplink systems of NOMA, however, it still has a problem that remains unresolved. The hybrid heuristic-based multi-objective function model is a prop to maximize such efficiencies in the NOMA systems. The major aspect of this novel approach is increasing the SE and Energy Efficiency (EE) without any degradation or loss of information. Over the NOMA system, the factors like beam forming vectors optimized the time and power allocation using the newly designed hybrid algorithm Hybrid Black Widow and Rat Swarm Optimizer (HBWRSO) for maximizing efficiency. Further, the proposed algorithm is employed to derive the multi-objective function with the help of three constraints: SE, EE and outage probability. Lastly, the system's performance is examined, and the corresponding results are carried out. Therefore, the findings reveal that it has maximized the SE and EE compared to baseline methodologies.
  Keywords: non-orthogonal multiple accesses; spectral efficiency; energy efficiency; hybrid black widow and rat swarm optimiser; RSO; beam forming vector; time allocation; power allocation.
  DOI: 10.1504/IJMC.2025.10067375
   
  
• Factors and mechanisms influencing the resilience of peer-to-peer accommodation hosts during the COVID-19 crisis: insights from a qualitative study  
  by Junjing Wang, Maomao Chi, Rui Huang, Wenjing Li 
  Abstract: The COVID-19 pandemic has profoundly impacted the Peer-to-Peer (P2P) accommodation sector and significantly affected P2P accommodation hosts. The substantial disruption of this sector calls for academic exploration of the mechanisms leading to resilience of P2P accommodation hosts during crises. This qualitative study involved interviews with 19 hosts who successfully navigated the challenges presented by the pandemic. Utilizing coping theory and the concept of platform governance, we identified key determinants of host resilience, including threat appraisal, capability appraisal, problem-focused coping strategies, emotion-focused coping strategies, incentive, formal control, and informal control. Our findings revealed that host resilience stemmed from a complex interplay between internal mechanisms and external environment, a dynamic we described as the hosts’ coping process. Furthermore, the governance mechanisms of P2P accommodation platform were found to potentially synergize with these coping processes and co-influence resilience outcomes. This study not only extends the application of coping theory to the resilience of micro-entrepreneurs but also provides practical insights for P2P platforms and their hosts to effectively manage and overcome the challenges induced by crises.
  Keywords: peer-to-peer; P2P; accommodation platform; host resilience; coping theory; platform governance; crisis management; qualitative study.
  DOI: 10.1504/IJMC.2025.10067660
   
  
• Analysing key factors affecting user satisfaction and continuance intention in VR headsets  
  by Hyeon Jo, Jooyoung Kim 
  Abstract: The rapid evolution of VR technology necessitates a deeper understanding of the factors influencing user satisfaction and continuance intention. This study investigates the impact of sensory affordance, system quality, and navigation design on user satisfaction and continuance intention, employing the expectation-confirmation model (ECM). The research aims to elucidate how these factors shape user experiences and sustained engagement with VR headsets. Using partial least squares structural equation modelling (PLS-SEM) and a sample size of 268 VR users, the study tests several hypotheses. Findings indicate that sensory affordance significantly impacts navigation design and confirmation but not perceived usefulness. System quality influences navigation design, confirmation, and perceived usefulness, underscoring its critical role. Navigation design significantly affects confirmation, perceived usefulness, and satisfaction. Confirmation strongly impacts both perceived usefulness and satisfaction, which in turn, drive continuance intention. Satisfaction emerges as a crucial determinant of continued use.
  Keywords: virtual reality; VR headset; continuance intention; expectation-confirmation model; ECM; design.
  DOI: 10.1504/IJMC.2025.10067554
   
  
• The impact of gamification features on customer brand engagement: A study in entertainment mobile apps  
  by Amir Reza Konjkav Monfared, Mohammad Ghaffari, Mohammad Nematpour, Mohammadreza Barootkoob, Milad Mohebali Malmiri, Leila Malekpur 
  Abstract: This study aims to develop a conceptual model to investigate the influence of main features of gamification (entertainment, interactivity, innovation, and sociability) on costumers brand engagement in terms of emotional, cognitive, and behavioural dimensions on SnappQ as the online social and entertaining application. A survey employing researcher-developed-questionnaire was conducted by collecting data from 233 customers using SnappQ in Iran. The structural equation modelling method was employed to investigate research hypotheses. The findings of this study revealed that gamification features have a significant relationship with customer brand engagement. Following the findings, employing gamified services and gamification features in online social and entertaining platforms help managers to satisfy customers psychological needs, and this leads them to have to learn the manner of managing their customers to engage them profitably. The findings help marketing managers/practitioners to understand how to enhance customers motivation to engage with the desired brand by designing different gamification features.
  Keywords: gamification feature; customer engagement; cognitive engagement; emotional engagement; behavioural engagement.
  DOI: 10.1504/IJMC.2025.10067555
   
  
• Weather prediction based on wireless sensor network and internet of things with analysis using hybrid SSOA with MA  
  by Priya Shamu, Anila Sathishkumar  
  Abstract: Weather forecasting is a rapidly expanding field that forecasts the weather in a specific location at a certain time weather forecasting is regarded as the most essential aspect of study since it involves numerous real-time problems. These are the specifications for weather-detecting wireless sensor networks. In this paper, we suggest combining the mayfly algorithm (MA) with the shuffled shepherd optimisation algorithm (SSOA). A collection of climatic data is used to carry out the experiments. The data is split into heat, wind, and rain based on meteorological factors such as temperature, humidity, and clouds. The weather is expected to verify the suggested qualifying techniques at a high degree of accuracy, based on the results achieved. The result demonstrates that the hybridised SSOA and MA technique is effective and precise in forecasting meteorological conditions. This experiment was conducted out on agricultural land utilising a wireless sensors network and IoT.
  Keywords: agriculture fields; wireless sensor network; WSN; climate monitoring; weather prediction; hybrid SSOA.
  DOI: 10.1504/IJMC.2025.10067753
   
  
• How to measure customers' perceived service quality of smart restaurants?
  by Ching-Chan Cheng, Ming-Chun Tsai, Ya-Yuan Chang, Cheng-Ta Chen 
  Abstract: Smart restaurants are a new type of restaurant that can be applied to restaurant halls and kitchens through the use of the internet of things (IoT) and communication technology, which can be used to reduce the service contact between service staff and customers during COVID-19. Effective evaluation of the service quality of various restaurants is a primary task for the restaurant industry, but previous restaurant service quality scales cannot fully measure the service quality of smart restaurants. Based on the above reasons, this study developed a smart restaurant service quality scale (SRSERV scale) through rigorous research procedures. The SRSERV scale had considerate service, responsiveness, fun and novelty, reliability, service efficacy, and empathy dimensions, with a total of 30 items. The implications of these dimensions were fully discussed in this study. The SRSERV scale could allow smart restaurant operators to accurately measure the service quality of smart restaurants to improve service quality.
  Keywords: smart restaurant; service quality; service quality scale.
  DOI: 10.1504/IJMC.2025.10060709
   
  
• Factors influencing users' rumour spreading intention during public health emergencies: based on protection motivation theory
  by Peng Yu, Xin Zhang, Liang Ma 
  Abstract: With the development of social media and information technology, dealing with the infodemic in public health emergencies has become particularly important. Existing research on exploring the primary rumour-spreading motivation and process under the COVID-19 context is limited. This study aims to explore the factors influencing rumour spreading and reveals its mediation process and boundary condition. Based on protection motivation theory and using structural equation modelling analysing data from 423 users, the results showed that: 1) issue involvement has a positive effect on both threat appraisal (perceived severity and perceived vulnerability) and coping appraisal (self-efficacy and response efficacy), however, the effect of issue involvement on response cost is not significant; 2) perceived vulnerability and coping appraisal positively influence the intention to spread rumour by forming the attitude to spread rumour (protection motivation); 3) when the tie strength between the user and the information receivers is at a high level, the user's attitude to spread rumour has a more positive effect on intention to spread rumour.
  Keywords: rumour spreading; protection motivation theory; issue involvement; intention to spread rumour.
  DOI: 10.1504/IJMC.2025.10060821
   
  
• To reveal or conceal? Sponsorship disclosure in health apps and its impacts on sponsor motive attributions, credibility and download intentions  
  by Eunsin Joo 
  Abstract: Amid the growing corporate sponsorship for health and wellness apps, this study employed attribution theory and sponsorship literature to assess how users perceive and evaluate sponsors, their intentions, and the apps themselves. An online experiment examined the influence of sponsor identification within apps on users' attitudes toward the sponsor, app credibility, and app download intentions. It further explored whether download intentions were sequentially influenced by perceived sponsor motives (either altruistic or self-serving), sponsor attitude and app credibility. Results indicated that when sponsorship was disclosed at any level, users were more likely to perceive sponsors as having self-serving motives. However, perceptions of sponsors' altruistic motives varied based on the degree of disclosure. Apps and sponsors were positively evaluated when associated with altruistic motives of sponsors, whereas negative evaluations arose from perceptions of self-serving motives. Both theoretical and managerial implications for mobile marketing communications and health app development are discussed.
  Keywords: sponsorship disclosure; motive attributions; altruistic motives; self-serving motives; health app; app evaluations; cause-related marketing; mobile marketing communication.
  DOI: 10.1504/IJMC.2025.10062241
   
  
• The impact of perceived value and trust on mobile payment reuse intention: the mediating role of user satisfaction
  by Jhong-Min Yang 
  Abstract: Although m-payment usage in Taiwan has expanded year after year, research on reuse intention appears to be limited. According to this study, perceived convenience, perceived benefit, and perceived mobility will continue to produce perceived value, affecting user satisfaction and eventually the decision to continue using. Online, 326 valid samples were obtained. According to the findings of the measurement model analysis and structural model analysis of structural equation modelling, user satisfaction has a full mediation impact between perceived value and intention to reuse, as well as between trust and intention to reuse MP. The comprehensive findings and academic and practical consequences are reported at the end of this work.
  Keywords: mobile payment; user satisfaction; perceived value; trust; social influence.
  DOI: 10.1504/IJMC.2025.10060676
   
  
• Enhanced genetic-chaos based grasshopper optimisation algorithm for efficient crash risk prediction using novel deep learning model
  by D. Deva Hema, K. Ashok Kumar 
  Abstract: The development of the road transport advanced collision avoidance system, which aids in accident prevention, heavily relies on accident risk prediction. The prediction of crash risk before a collision has been made possible by a number of deep learning algorithms and hybrid data driven models. In the existing convolutional-neural-network-long-short-term-memory (CNN-LSTM) model, the hyper parameters are not optimised which affects the crash risk prediction system efficiency. Therefore, to improve the collision risk prediction performance, enhanced genetic-chaos based grasshopper optimisation algorithm (EGCGOA) has been developed which optimises CNN-LSTM model's hyper parameters. CNN and LSTM are employed for data extraction and prediction respectively. The performance of EGCGOA has been evaluated with test functions, which prove the efficiency algorithm. The next generation simulation project (NGSIM) dataset was utilised to test the EGCGOA-CNN-LSTM, and it performs better than conventional techniques. The accuracy has increased which is greater than the previous model, based on the results.
  Keywords: crash risk prediction; LSTM; feature extraction; reaction time; parameter optimisation.
  DOI: 10.1504/IJMC.2025.10061199
   
  
• Energy-efficient coverage in wireless sensor networks based on stacked contractive auto encoder with Manta Ray foraging optimisation algorithm  
  by S. Muthukumarasamy, B.R. Tapas Bapu 
  Abstract: In this manuscript, energy-efficient coverage in WSN based on stacked contractive auto encoder with Manta Ray foraging optimisation algorithm is proposed. Initially, IF-RFKM clustering approach is proposed for dividing the ROI as several clusters and defines the cluster head. Then SCAE determines the sensing radius for best coverage and move sensor nodes accordingly. Finally, MRFO algorithm is proposed for increasing the network lifespan by decreasing energy consumption in the sensor nodes. The proposed EECO-SCAE-MRFO-WSN method is implemented in MATLAB, its effectiveness is validated under performance metrics, such as coverage rate, covering percentage, delay, throughput, computation time, network lifetime, residual energy and energy consumption. The proposed EECO-SCAE-MRFO-WSN method has attained 36.8%, 34.75%, 21.86% higher coverage rate, 34.6%, 30.9%, 26.87% lower delay, 7.96%, 12.65%, 9.65% higher network lifetime, and 19.87%, 16.8%, 10.9% lower energy consumption than the existing methods, like energy-efficient coverage enhancement for 3-D WSN depending on vampire bat optimiser (EECO-VBO-WSN).
  Keywords: Manta Ray foraging optimisation; region of interest; stacked contractive auto encoder; SCAE; wireless sensor network.
  DOI: 10.1504/IJMC.2025.10061758