Forthcoming and Online First Articles

International Journal of Networking and Virtual Organisations

International Journal of Networking and Virtual Organisations (IJNVO)

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International Journal of Networking and Virtual Organisations (10 papers in press)

Regular Issues

  • The Nexus Between Allied Policies of GST And FDI With Dependent Telecom Policies of Licensing and Universal Service in India.   Order a copy of this article
    by Pankaj Mishra, Netra Pal Singh, Ayesha Farooq 
    Abstract: The Indian telecom industry has witnessed sustained grievances from the operators on telecom and allied policies. This paper analyses if such behavior is due to gaps in policy formulation, gaps in implementation or are an ex-post rent seeking behavior. Using the conceptual framework from Lemke and Harris-Wai (2015), the author analyzed if there was adequate telecom stakeholder participation in FDI and GST policy formulation. The causal map of regulation from Coglianese (2012), was used to evaluate gaps in the implementation of FDI and GST for telecom. In FDI policy formulation, the stakeholders were included at the discretion of the DPIIT , and the process is mainly inter-ministerial. In GST policy formulation the operators and DoT were involved in all the stages. DoT did all required changes in the telecom policy that were triggered by FDI and GST policies. Stakeholder participation did not result in lower ex-post issues rather the provisions
    Keywords: Policy Formulation; Stakeholder Participation; rent seeking; telecommunications.
    DOI: 10.1504/IJNVO.2023.10054116
     
  • The Triggers on Compulsive Online Shopping of Jeans   Order a copy of this article
    by D. Manimegalai, Senthilkumar S 
    Abstract: This study investigates the antecedents of compulsive online shopping for jeans and identifies the compulsive shoppers of jeans. This descriptive research collects data through an online survey; the sample size is 205
    Keywords: compulsive online shopping; internal and external triggers; online usage; buzz.
    DOI: 10.1504/IJNVO.2023.10055603
     
  • An Efficient Optimal Load Balancing Algorithm For Distributed File Systems in Cloud Environment   Order a copy of this article
    by Manjula H. Nebagiri, Latha P. H 
    Abstract: Efficient operations in distributed environments can be obtained by load balancing (LB). LB has turned out to be a vital and interesting research area with respect to the cloud owing to the swift augmentation of cloud computing, and the more services together with better outcomes demand of the clients. The work has developed a framework named an efficient optimal LB (EOLB) for distributed files system to beat the challenges faced in LB. LB was done by means of the framework centred on node distribution together with task distribution. Centred upon the data aspects as well as cloud servers, say CPU in addition to memory usage, together with disk IO occupancy rate, etc. it renders task distribution. Experimental analysis exhibits that the framework attains a better response rate of 74.68 ms, and a processing time (PT) of 0.43 ms, in addition, remains to be efficient when weighed with the prevailing methods.
    Keywords: cloud computing; virtual environment; distributed cloud computing; load balancing; improved K-means clustering; IKMC; modified cockroach swarm optimisation; MCSO.
    DOI: 10.1504/IJNVO.2023.10056519
     
  • Architectural Framework For Multiplayer Cooperative Cloud Gaming To Optimize Quality Of Service   Order a copy of this article
    by Nimmagadda Srilakshmi, Naresh Kannan 
    Abstract: The gaming industry is getting more attraction from cloud services providing gaming applications for cooperative multiplayer gaming. Real-time services like cloud gaming are possible by performing necessary process-intensive tasks within the cloud. In this paper, an architectural model for supporting cooperative gaming towards multiplayer is proposed to improve the quality of service in terms of bandwidth and latency compared to existing architectural models. According to this study, the time it takes to change a video has grown by 95% compared to how well Ad hoc mobile cloudlets and the cloud do at sharing videos. Although P-frames, I-frames, and B-frames account for 23%, 78%, and 94% of the resource consumption, density in intra-stream P-frames is also considered. Similarly, resource and CPU use based on skewness are effective compared to mobile devices’ 95% faster video sharing and 77% shorter link delays.
    Keywords: cloud gaming; quality of service; cooperative multiplayer gaming; social networking.
    DOI: 10.1504/IJNVO.2023.10056762
     
  • An Improved Data Aggregation for Fog Computing Devices in Internet of Things   Order a copy of this article
    by M. Jalasri, L. Lakshmanan 
    Abstract: Diverse data that have private information are stored in the cloud by institutions and users. Fog computing has progressed with regard to service latency and has also been comprehensively studied. A proposal has been made in this work to secure IoT data, a clustering algorithm that utilises backup cluster head (CH) for network performance enhancement, and also utilises a multi-route protocol for data transmission towards the fog system. Comparisons are made between the proposed algorithm and the energy efficient heterogeneous clustering algorithm (EEHCA). A novel particle swarm optimisation (PSO) and river formation dynamics (RFDs) algorithm was proposed in this work for effective CH election in wireless sensor network (WSN) to efficiently transmit data towards the base station (BS) with minimised energy. This technique bypasses local optima during the solution search, leading to significantly improved results. RFD-EEHCA outperforms EEHCA by 8.53% and PSO by 8.09% in terms.
    Keywords: cloud computing; internet of things; IoT; fog computing; security; wireless sensor network; WSN; routing; clustering.
    DOI: 10.1504/IJNVO.2024.10060435
     
  • Topic text detection by clustering algorithm for social network media   Order a copy of this article
    by Sha Sha 
    Abstract: The advent of the Internet era has promoted the development of social network media, making the number of people active in these social network platforms greatly increase, and the resulting large amount of data and information makes the fast location retrieval of topics of interest a problem. This paper detected topic texts of social network media by the modified particle swarm optimisation-based K-means (MPSO-means) clustering algorithm to achieve topic text clustering effect and alleviate the problem of inconvenience caused by information overload. The results of the study showed that the clustering results of short texts showed a trend of outperforming long texts; and the MPSO-means algorithm was closer to 1 than the other two algorithms in the values of silhouette coefficient, clustering purity, and homogeneity, with better clustering effect, and also consumed the shortest time in detection, only 1,196 s.
    Keywords: text clustering; social network media; topic text; modified particle swarm optimisation-based K-means.
    DOI: 10.1504/IJNVO.2024.10060582
     
  • Anomalous Data Detection in Cognitive IoT Sensor Network   Order a copy of this article
    by Vidyapati Jha, Priyanka Tripathi 
    Abstract: Recent research in the internet of things (IoT) focuses on the insertion of cognition into its system architecture and design, which introduces the new discipline known as cognitive IoT (CIoT). The cognitive internet of things sensor network defines a new paradigm for bridging the gap between the virtual and the real world. Sensors integrated into the CIoT network serve as the primary data collectors. These sensors are used in hazardous or unmanaged a situation, which makes sensor readings prone to errors and abnormalities. Since sensor data are essential to the system's operation, the quality of various data-centric CIoT services will ultimately depend on the accuracy of sensor readings. However, detecting anomalies in sensor data is a complex process because CIoT sensor networks are frequently resource-constrained devices with limited computation, networking, and storage power. To fulfil the objectives, an effective and affordable cognitively-inspired detecting method is required. Therefore, this research proposed a novel technique to identify the anomaly in sensor node data. The experimental evaluation is conducted on the environmental data of 21.25 years, and detection accuracy reveals the efficacy of the proposed method over competing approaches.
    Keywords: anomaly; probability; sensor network; cognitive IoT; CIoT.
    DOI: 10.1504/IJNVO.2024.10061110
     
  • Hybridized Pre-trained deep network with Aspen Lupus Bidirectional long short term memory classifier for Image-based Event classification   Order a copy of this article
    by Shrikant P. Sanas, Tanuja Sarode 
    Abstract: The proposed Aspen-Lupus optimisation-based BiLSTM classifier (ALO opt BiLSTM) is employed in this research to develop an event classification model that accurately identifies the events. The pre-trained hybridised model, which is proposed for feature extraction, is developed via a conventional hybridisation of the VGG-16 and ResNet-101 models. The deep BiLSTM classifier gathers the collected features and utilises them to effectively increase prediction accuracy. The development of the proposed ALO algorithm resulted from the typical hybridisation of the Aspen and Lupus optimisation. Based on the achievements, at training percentage 90, the accuracy of 95.65%, sensitivity of 94.27%, specificity of 96.63% in database-1 respectively is attained and for database-2, achievements of 94.22% in accuracy, 92.86% insensitivity and 95.18% in specificity is acquired.
    Keywords: event classification model; Aspen-Lupus optimisation; BiLSTM classifier; border collie; grey wolf; hybrid pre-trained model.
    DOI: 10.1504/IJNVO.2024.10061488
     
  • Influence of Sense of Virtual Brand Community on Value Co-Creation   Order a copy of this article
    by Bingzhou Li, Wei Yu 
    Abstract: The research objective is to formulate and verify a theoretical model about the influence of sense of virtual brand community on value co-creation of enterprises with self-efficacy and psychological contract as moderating variables. Four hypotheses are presented based on theoretical deduction. This article uses the empirical research design and survey methodology. The data analysis approaches include reliability test, validity analysis, descriptive statistics, variance analysis, correlation analysis, regression analysis, path analysis of structural equation model and hierarchical regression analysis. By collecting data with 275 valid questionnaires in many virtual brand communities, this research empirically confirms that sense of virtual brand community has a positive impact on value co-creation. Moreover, customer self-efficacy and psychological contract with an enterprise respectively positively moderate the relationship between sense of virtual brand community and value co-creation. However, the model does not give the specific mediating influence mechanism of sense of virtual brand community on value co-creation. An enterprise should enhance the cultivation of sense of virtual brand community and improve a customer's self-efficacy and psychological contract. Theoretically, this article enriches the human sense and communication analysis in the marketing context and explores new antecedents and moderating factors of customer value co-creation for the whole enterprise.
    Keywords: sense of virtual brand community; value co-creation; self-efficacy; psychological contract; communication platform.
    DOI: 10.1504/IJNVO.2024.10061492
     
  • Retaining remote workers: Factors that affect virtual and hybrid workers' job retention   Order a copy of this article
    by Vasu Thirasak, Nopadol Rompho 
    Abstract: This study examines factors from Herzberg's motivation-hygiene theory, Deci's self-determination theory, and life-course fit theory to understand their effects on virtual and hybrid workers' job retention. Data were collected from 623 respondents in Thailand, and structural equation modelling and data analysis techniques were used to test the relationships between pay, promotion, supervision, fringe benefits, life-course fit, intrinsic motivation, and extrinsic motivation and job retention for virtual and hybrid workers, as well as the moderating effects of job level and virtual intensity. The results indicate that motivator-hygiene factors pay, promotion, supervision, and fringe benefits do not significantly contribute to the job retention of virtual and hybrid workers. However, the relationships between life-course fit, intrinsic motivation, and extrinsic motivation and job retention were significant. This is one of the very few studies that applies these theories in the context of virtual and hybrid work, which expands the theories boundaries of knowledge.
    Keywords: remote work; virtual work; hybrid work; job retention; motivators; hygiene factors; intrinsic motivation; extrinsic motivation.
    DOI: 10.1504/IJNVO.2024.10062140