International Journal of Mobile Communications (27 papers in press)

Regular Issues

• 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
   
  
• 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
   
  
• 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
   
  
• Design of a variable digital filter based on all pass transformation with low-power modified conventional full adder and low-power Wallace tree multiplier to eliminate noise from sensor nodes  
  by Baluprithviraj Krishnasamy Natarajan, Vijayachitra Senniappan, Malathi Subramanian Ramasundaram, Francis H. Shajin 
  Abstract: Variable digital filters (VDF) are essential components in digital signal processing, which find applications in audio processing and telecommunications. Current VDF designs often face challenges in delay, area consumption, and power efficiency. In this manuscript, design of all pass transformation fed variable digital filter using low power modified conventional full adder and low-power Wallace tree multiplier (APT-VDF-LPMCFA-LPWTM) is proposed. The proposed design is utilised for enhancing the filter efficiency by reducing noise in the sensor nodes. The proposed low power modified conventional full adder (LPMCFA) design is incorporated with carry prediction. Moreover, the proposed LPWTM is used for minimising the design complexity and power utilisation. The proposed filter attains 26.58%, 12.3%, 16.41% and 38.07% lower delay than the existing designs, FIR-Rdx2-LCSLA, FIR-RCA-VM, FIR-VL-CSKA-BM and PPA-VDRCA-FIR-ECG respectively. Simulation results of the proposed filter show improved noise reduction and reduced power consumption compared to conventional designs.
  Keywords: communication; signal processing; low power modified conventional full adder; LPMCFA; low-power Wallace tree multiplier; LPWTM; sensor nodes noise.
  DOI: 10.1504/IJMC.2025.10068712
   
  
• Taking charge of my health in my way! Exploring consumers continuous usage intention and brand loyalty toward health wearable devices: a hybrid method of PLS-SEM and artificial neural network  
  by Zhucheng Shao, Jessica Sze Yin Ho, Nguyen Xuan Truong , Dang Van My, Garry Wei-Han Tan 
  Abstract: Facing the low continuous use intention on Health Wearable Devices (HWDs) today, this study evaluates the effects of both individual and technical attributes on perceived satisfaction, thus affecting brand loyalty and continuous use intention by extending the Stimulus-Organism-Response (S-O-R) theory. An online self-administered questionnaire, consisting of 360 valid responses, is adopted for data collection and then conducts a hybrid analytical method that combines Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN). The findings show that health-consciousness, convenience, measurement accuracy and affordance significantly affect perceived satisfaction, which in turn affects brand loyalty and continuous use intention. Besides, brand loyalty positively relates to ongoing use intention. This study strengthens the role of S-O-R theory in continuous behavioural intention on HWDs by integrating individual and technical attributes and provides practical suggestions to manufacturers for enhancing consumer satisfaction and brand loyalty.
  Keywords: health wearable devices; HWDs; continuous use intention; brand loyalty; stimulus-organism-response theory; PLS-SEM-ANN; consumer behaviour.
  DOI: 10.1504/IJMC.2026.10068963
   
  
• Configurational analysis of negative purchase intention of online paid knowledge -evidence from China  
  by Yanhui Song, Deyu Min, Shiji Chen 
  Abstract: Following a period of rapid development in China, the knowledge payment industry is confronted with challenges such as declining repurchase rates. Exploring the negative purchase intention of online paid knowledge can aid in identifying the underlying causes of user attrition, thereby offering both theoretical underpinnings and practical insights for industry development. Focusing on the Chinese knowledge payment market, we introduce a novel variable, content type, and propose a conceptual model of negative purchase intention of online paid knowledge comprising six antecedent variables at three levels. We collected 375 samples using the questionnaire method and analysed the data using fuzzy-set qualitative comparative analysis (fsQCA). Through this method, we identify five sets of antecedent configurations and alternative relationships among the factors contributing to consumers’ negative intentions to purchase. Finally, we offer corresponding suggestions for the identified configurations to provide guidance for knowledge payment platform managers.
  Keywords: online knowledge payment; negative purchase intention; configuration perspective; fsQCA; chinese knowledge payment platforms.
  DOI: 10.1504/IJMC.2025.10069111
   
  
• Social media and social capital revisited: social trust and community satisfaction as catalysts of civic participation  
  by Dam Hee Kim, Joshua Von Herrmann, Seungahn Nah 
  Abstract: The current study seeks to advance our theoretical understanding of how the use of social media can facilitate civic participation by considering the different types of social media use as well as social capital. For social capital, this study considers psychological indicators (i.e., social trust and community satisfaction). Also, this study distinguishes active informational use of social media (i.e., expressive, searching, and sharing activities) from passive informational use of social media (i.e., simply viewing information). Analyses of a national survey conducted in South Korea (n = 1,294) show that active, not passive, informational social media use positively predicts civic participation. Importantly, active informational social media use facilitates civic participation among individuals with strong psychological social capital such as social trust and community satisfaction.
  Keywords: social media; social capital; civic participation; uses and gratifications; social trust; community satisfaction.
  DOI: 10.1504/IJMC.2026.10069231
   
  
• Peer communication emotional - arousal relationship in social media apps: the roles of benefit communication and social identity  
  by Li-Ling Liu 
  Abstract: The relationship between peer communication and emotional arousal has received little attention in social media research. The present research fills this research gap by exploring how benefit confirmation and social identity affect this relationship. This study collected questionnaire responses from 300 Taiwanese respondents; the findings indicated that peer communication significantly affected the aforementioned relationship. Specifically, the peer communication-social identity-emotional arousal relationship was stronger than the peer communication-benefit confirmation-emotional arousal relationship. This study was the first to explore the interrelationships between peer communication, benefit confirmation, social identity, and emotional arousal in relation to social media app use. The results revealed that the mediating effects of benefit confirmation and social identity on the relationship between emotional arousal and peer communication should not be overlooked.
  Keywords: social media app; SMA; peer communication; benefit confirmation; social identity; emotional arousal.
  DOI: 10.1504/IJMC.2026.10069232
   
  
• Elucidating mobile AR continuance intention: a dual fitting mechanism  
  by Hao Chen, Shuiqing Yang, Yuangao Chen, Shuang Zheng, Miao Zhang, June Wei 
  Abstract: Mobile Augmented Reality (AR) technology has revolutionized conventional human-computer interfaces and dramatically reshaped consumer behaviours. Based on task-technology fit (TTF) model and emotional fit theory, a research model reflected the dual fitting mechanism underlying mobile AR continuance intention was developed and analyzed by using data collected from 408 users of mobile AR services. Results from the structural equation modelling reveal that task mobility and spatial presence affect mobile AR continuance intention mainly via emotional fit, while confidence in AR influences mobile AR continuance intention predominantly through task-technology fit. In addition, technology fluency affects mobile AR continuance intention via both task-technology fit and emotional fit. Compared with mobile AR utilitarian applications, technology fluency has a greater impact on task-technology fit when using mobile AR hedonic applications. However, in terms of mobile AR hedonic applications, spatial presence exerts a greater impact on task-technology fit when compared with mobile AR utilitarian applications.
  Keywords: mobile augmented reality; continuance intention; task-technology fit; emotional fit; mobile AR application.
  DOI: 10.1504/IJMC.2026.10069686
   
  
• Multi-objective resource allocation for satellite-based cognitive IoT communications using power-domain NOMA  
  by Jizheng Yang, Amin Mohajer 
  Abstract: The rapid growth of IoT devices and the demand for efficient data transmission have made advancements in satellite communication essential. This paper introduces a novel framework for multi-objective resource allocation in satellite-based cognitive IoT communications using power-domain NOMA. Our method integrates serverless computing and multi-objective optimisation to enhance satellite network performance. The framework dynamically manages resources like bandwidth and power, ensuring low latency and optimal performance using backhaul traffic optimisation. Key steps include analysing network data to predict future needs, employing real-time functions for adaptive resource allocation, and using multi-objective optimisation to configure satellite constellations for minimal latency, reduced power consumption, and maximised throughput. Extensive simulations validate the framework’s effectiveness, demonstrating significant improvements in data rate, energy efficiency, and overall performance. Specifically, our proposed NOMA.QAM framework achieves a 25% reduction in bit error rate (BER) and a 30% increase in spectral efficiency compared to traditional NOMA with SIC. Additionally, it demonstrates a 20% improvement in energy efficiency, highlighting its potential for energy-constrained applications. These results indicate that the integration of power-domain NOMA with serverless computing and multi-objective optimisation provides a promising solution for advancing satellite-based cognitive IoT communication systems, ensuring efficient, reliable, and scalable network management.
  Keywords: cognitive IoT; multi-objective optimisation; satellite communications; dynamic resource management; power-domain NOMA.
  DOI: 10.1504/IJMC.2026.10069895
   
  
• Enhancing customer satisfaction and customer loyalty by means of mobile service: the case of fitness club  
  by Chien-Chung Teng, Cheng-Chung Cheng, Di-Qun Xu, Chang-Dian Huan 
  Abstract: This study analysed the impact of mobile service quality in fitness clubs on customer satisfaction and loyalty, identifying key service quality items that require improvement. This study adopts a questionnaire survey method, collecting data on mobile service quality, customer satisfaction, and loyalty from members of fitness clubs in Fujian, China. A total of 381 valid questionnaires were collected. Data analysis was conducted using Statistical Package for the Social Sciences (SPSS), linear structural relations (LISREL) statistical software, and importance-performance and gap analysis (IPGA). Statistical analysis indicates that mobile service quality positively impacts customer satisfaction and loyalty. Customer satisfaction acts as a mediator between mobile service quality and customer loyalty, facilitating the indirect effect of service quality on loyalty. Using IPGA, we identified five key quality items of fitness clubs mobile service that require improvement.
  Keywords: service management; mobile service quality; quality improvement; fitness club management; IPGA.
  DOI: 10.1504/IJMC.2026.10070818
   
  
• Deep learning-driven mobile crowd sensing for secure and efficient Hajj pilgrimage management  
  by Mohammed Naif Alatawi  
  Abstract: The annual Hajj pilgrimage attracts millions of people, necessitating effective crowd management strategies to ensure safety and enhance the experience for all participants. With the advent of digital technologies, machine learning techniques have become pivotal in analysing crowd behaviour and managing resources in real-time. This study explores the integration of deep learning methods in mobile crowd sensing frameworks, specifically within an IOTA-based decentralised environment, to address challenges such as data authenticity, privacy protection, and real-time anomaly detection. Using a logit-boosted convolutional neural network model, this research achieved an accuracy of 99.5% in identifying anomalous events, outperforming traditional machine learning models. The results demonstrate the models capacity to provide a robust framework for detecting potential threats and ensuring secure, efficient information exchange during large-scale events. These findings underscore the potential of deep learning-enhanced crowd sensing in transforming the management of high-density gatherings. This approach not only enhances safety but also optimises resource allocation based on crowd density predictions. Future applications of this framework could extend to other large-scale gatherings, offering scalable solutions for various crowd management scenarios.
  Keywords: mobile crowd sensing; MCS; deep learning; IOTA framework; convolutional neural network; CNN; real-time anomaly detection; crowd behaviour analysis; privacy protection; large-scale event management.
  DOI: 10.1504/IJMC.2026.10070819
   
  
• Exploring how system, information, and service quality shape goal-congruent usage and outcome in intelligent voice assistants  
  by Hyeon Jo 
  Abstract: In an increasingly digital age, intelligent voice assistants (IVAs) are becoming an integral part of daily life, providing both utility and entertainment value to their users. The global pandemic has accelerated this trend, amplifying the importance of these digital companions. In light of this shift, our study aims to elucidate the factors leading to goal-congruent usage and outcomes of IVAs. Data was collected from 248 IVA users to validate the proposed research model. We employed the partial least squares method to test our hypotheses. Our findings revealed that system quality significantly influences both the perceived utilitarian and hedonic value of IVAs. Similarly, information quality was found to significantly impact both utilitarian and hedonic value. Interestingly, service quality was predominantly linked to utilitarian value. Furthermore, the study indicates that the utilitarian value is a key enabler of goal-congruent outcome and usage. Similarly, hedonic value plays a substantial role in driving both the goal-congruent outcome and usage.
  Keywords: intelligent voice assistant; IVA; goal-congruent outcome; GCO; information system success factors.
  DOI: 10.1504/IJMC.2026.10071057
   
  
• Determinants of people’s online participation in public affairs: the role of locus of control and big-five personality traits  
  by Guan-Yu Lin, Ching-Yun Chen, Yi-Shun Wang 
  Abstract: This study was designed to explore the determinants of e-participation in public affairs by developing and validating an e-participation model that elucidates the relationships among personality traits (i.e., big-five personality traits and locus of control), motivations (i.e., intrinsic motivation and extrinsic motivation), e-participation intention and actual e-participation. The developed model was tested on data from 244 participants using the partial least squares (PLS) approach. The results indicate: e-participation intention positively influences actual e-participation; intrinsic motivation mediates the relationships between agreeableness and e-participation intention and between extraversion and e-participation intention; extrinsic motivation mediates the relationship between agreeableness and e-participation intention; openness to experience positively and directly impacts e-participation intention; and internal locus of control negatively and directly impacts e-participation intention. The findings of this study provide several important theoretical and practical implications for promoting greater e-participation by citizens in public affairs.
  Keywords: online participation; intrinsic motivation; extrinsic motivation; locus of control; big-five personality traits; public affairs.
  DOI: 10.1504/IJMC.2026.10071297
   
  
• Examining generative AI user payment intention: a perceived value perspective  
  by Tao Zhou, Yan Liu 
  Abstract: As a knowledge payment behavior, user payment is crucial to the profitability and continuous development of generative AI platforms. However, users often lack the motivation and intention to make payment. The purpose of this study is to investigate the payment intention of generative AI users based on the perceived value theory. We used both methods of SEM and fsQCA to conduct data analysis. The results found that perceived benefits (functional benefits and social benefits) positively affect perceived value, whereas perceived costs (privacy risk, misinformation, and low transparency) negatively affect perceived value, which further affects payment intention. The results suggest that generative AI platforms should increase perceived benefits and diminish perceived costs in order to improve the perceived value and facilitate user payment intention.
  Keywords: generative AI; perceived value; payment intention; privacy risk; misinformation.
  DOI: 10.1504/IJMC.2026.10072180
   
  
• Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems  
  by M. Amanullah, K. Ananthajothi, Moorthy Agoramoorthy 
  Abstract: The rainfall forecast is essential to the fields of hydrology and meteorology. However, the prediction accuracy of existing methods for both shorter and longer-term rainfall forecasting is consistently low. The decreased performance of atmospheric forecasting models under various circumstances causes fluctuations in predicting accuracy. This paper proposes a novel method called Deep Convolutional Spiking Neural Network optimised with Sandpiper optimisation algorithm fostered Long-term and Short-term Rainfall forecasting (RP-DCSNN-SPOA). The primary source of the long and short-term rainfall (LSTR) data is the Sudan IRA rainfall forecast dataset. Then, the gathered data is pre-processed using anisotropic diffusion Kuwahara filtering to recover the missing values. The DCSNN is used to predict the rainfall forecast. Then, the Sandpiper Optimisation Algorithm (SPOA) is used to enhance the DCSNN classifier that accurately forecasts the rainfall. The proposed method achieves 28%, 22.64% and 28.35%, greater accuracy, 20%, 26.64% and 23.35% greater precision when compared with existing models.
  Keywords: sandpiper optimisation technique; Kuwahara filtering; rainfall forecasting; deep convolutional spiking neural network.
  DOI: 10.1504/IJMC.2026.10072144
   
  
• Beneath the prosperity of social commerce: a perspective from a trust-centred online review ecology  
  by Yan Li, Hongjie He, Bojiao Mu, Yaru Jin, Kun Shi 
  Abstract: The fast development of social commerce (s-commerce) has matured the online review ecology. However, it lacks an in-depth theoretical analysis of this ecology and its functions in consumers’ purchases in s-commerce. By dissecting this ecology into its three pillars: the review community, content, and system, this study proposes the relationships among those pillars by extending the TAM with trust and identifies four information cues that are helpful for building this trust. The structural equation modeling was employed to test the proposed research model based on 391 valid samples. The results verify the distinctiveness of trust in the review community in s-commerce and show that this trust can facilitate consumers’ use of the s-commerce platform for shopping via increasing the perceived usefulness of the review system and reducing the perceived risk of online shopping. Moreover, four information cues contribute to the development of trust in the review community.
  Keywords: online review ecology; trust in the review community; social commerce; technology acceptance model; TAM; trust development.
  DOI: 10.1504/IJMC.2026.10072447
   
  
• 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 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
   
  
• 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: In order to optimally allocate power among EE-SE, NOMA requires more computational time and transmission signals. The hybrid heuristic-based multi-objective function model is a prop to maximise such efficiencies in the NOMA systems. The major aspect of this novel approach is increasing the energy efficiency (EE) and spectral efficiency (SE) without any degradation or loss of information. Over the NOMA system, factors like beam forming vectors optimised the time and power allocation using the newly designed hybrid algorithm hybrid black widow and rat swarm optimiser (HBWRSO) for maximising efficiency. Further, the proposed algorithm is employed to derive the fitness function with the help of three constraints: SE, EE, and outage probability. Lastly, the system's efficacy is examined, and the corresponding results are carried out. Therefore, the findings reveal that it has maximised 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. Utilising 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 synergise 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
   
  
• Reviewer reliability with sentiment analysis using DECE optimiser  
  by S.S. Arumugam 
  Abstract: Due to the rapid advancement of internet technology in recent years, online shopping has become facilitated to users for selling and purchasing. The first step is to pre-process the data from Amazon's product recommendations before feeding it to an ensemble classifier made up of large scale pinball twin support vector machine (LSPTSVM), categorical gradient boosting (CGB) and integrated fuzzy decision tree (IFDT) that classifies the outcomes into three categories: good, bad, average. In general, the classifier does not adapt any optimisation models to define the optimum parameter and to achieve the exact classification. This manuscript proposes a chaotic equilibrium optimiser (CEO) technique to optimise the classifier that classifies precisely. The proposed approach is activated in MATLAB. The proposed method reaches a lower mean absolute error 28.32%, 22.82% and 23.56%, a higher mean absolute percentage error 28.62%, 19.82% and 22.36% and a mean square error 25.31%, 20.33% and 14.2% less than the existing systems.
  Keywords: categorical gradient boosting; CGB; chaotic equilibrium optimiser; CEO; deep ensemble classifier; integrated fuzzy decision tree; IFDT; large scale pinball twin support vector machine; online product shopping reviews; sentiment analysis; recommendation system.
  DOI: 10.1504/IJMC.2025.10070674
   
  
• The application of cloud and IoT-based architectures for digital twins in smart cities: a bibliometric study  
  by Mindong Zhu, Mehdi Darbandi, Habibeh Nazif, Faradillah Amalia Rivai 
  Abstract: Due to the swift advancement of the IoT and global cloud computing, various sectors have progressively transitioned towards a contemporary society characterised by intelligence. These technologies have gradually permeated the realm of smart cities and addressed urban problems that develop due to enhancing urbanisation without establishing policies that focus on well-being. Because of their importance in many fields, this work aims to present a thorough understanding of the longitudinal state and knowledge structure of cloud- and IoT-based infrastructures for digital twins (DT) in smart cities. The present investigation uses bibliometric analysis to explore the growing trend of dynamic publications associated with the advanced technologies integrated into DT in smart city publication productivity. 2,500 publications from 22 journals between 2013 and 2023 are carefully evaluated to reveal the current trend of cloud and IoT research topics. The results indicate the importance of cloud and IoT-based architectures for DT in smart cities.
  Keywords: cloud computing; internet of things; IoT; smart cities; digital twins; DT; bibliometric review.
  DOI: 10.1504/IJMC.2025.10068400
   
  
• Effect of gender on usability, purchase intention, perceived usefulness and perceived ease in using SVVR e-commerce  
  by Chien-Hui Lee, Min-Chi Chiu, Chung-Hua Chu 
  Abstract: Technological advancements and pandemics have shifted consumer behaviour from physical stores to online shopping, driven by the convenience of no spatial or temporal constraints and reduced contact risks. This study explores how customers adapt to online shopping innovations, such as virtual reality (VR) environments, using spherical video-based virtual reality (SVVR) simulations. VR technology offers a shopping experience free from time, space, and pandemic concerns. The study found that familiarity with mobile technology boosts willingness to shop in virtual environments, especially among women who value perceived usefulness, link function, and menu function. Importance-performance analysis (IPA) evaluated customer perceptions of usefulness, ease of use, functionality, and purchase intentions, providing strategies to improve satisfaction and e-commerce within the SVVR framework.
  Keywords: service quality; spherical video-based virtual reality; SVVR; importance-performance analysis; IPA.
  DOI: 10.1504/IJMC.2025.10071056
   
  
• 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 the future development of LBA services to know 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
   
  
• Consumers' hierarchy value structure on social commerce: a means-end chain approach  
  by Hong-Wen Lin, Yu-Ling Lin, Ya-Cing Jhan 
  Abstract: This study employs the means-end chains theory to explore the attributes emphasised by social commerce consumers and the resulting psychological values. We employ methods such as laddering interviews, content analysis, implication matrix, and hierarchical value map to construct the hierarchical value structure of 'platform attributes – consumption consequences – psychological values' from the consumer's perspective. The study categorised and summarised 12 platform attributes, ten consumption consequences, and eight psychological values. Additionally, this study extends the three main attribute categories of social commerce, an area previously unexplored by other research. The results indicate that a higher proportion of consumers seek support from social media technologies, followed by community interactions and commercial activities within the social commerce environment. These findings help online sellers to understand the most valued elements for consumers. The sellers could make promotion strategies based on these findings.
  Keywords: social commerce; means-end chains; motivations; hierarchy value structure.
  DOI: 10.1504/IJMC.2025.10068549