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Article
Publication date: 20 September 2022

Robin Cyriac and Saleem Durai M.A.

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes…

Abstract

Purpose

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes (MNs) in the network. As RPL is designed to work under constraint power requirements, its route updating frequency is not sufficient for MNs in the network. The purpose of this study is to ensure that MNs enjoy seamless connection throughout the network with minimal handover delay.

Design/methodology/approach

This study proposes a load balancing mobility aware secure hybrid – RPL in which static node (SN) identifies route using metrics like expected transmission count, and path delay and parent selection are further refined by working on remaining energy for identifying the primary route and queue availability for secondary route maintenance. MNs identify route with the help of smart timers and by using received signal strength indicator sampling of parent and neighbor nodes. In this work, MNs are also secured against rank attack in RPL.

Findings

This model produces favorable result in terms of packet delivery ratio, delay, energy consumption and number of living nodes in the network when compared with different RPL protocols with mobility support. The proposed model reduces packet retransmission in the network by a large margin by providing load balancing to SNs and seamless connection to MNs.

Originality/value

In this work, a novel algorithm was developed to provide seamless handover for MNs in network. Suitable technique was developed to provide load balancing to SNs in network by maintaining appropriate secondary route.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Open Access
Article
Publication date: 26 March 2024

Charles Kirschbaum and Luiz Ojima Sakuda

The purpose of the article is to explore the perceptions of Brazilian game developers about the power relations between them and the sponsors of digital game platforms. It also…

Abstract

Purpose

The purpose of the article is to explore the perceptions of Brazilian game developers about the power relations between them and the sponsors of digital game platforms. It also aims to identify forms of collective action that developers can use to counteract the asymmetry of power.

Design/methodology/approach

The research employed an abductive approach, seeking empirical evidence that would challenge consolidated theory. To achieve this, semi-structured interviews were conducted with 25 Brazilian developers. The data were analyzed qualitatively using NVivo software. The aim was to resolve theoretical ambiguities identified in the literature review and to explore unexpected findings.

Findings

The study explores Brazilian game developers' perceptions through interviews, revealing their experiences within the industry’s concentrated structure and their use of collective action to navigate power dynamics.

Research limitations/implications

The study's focus on Brazil limits the generalizability of its findings to the broader game development industry.

Practical implications

The study suggests Brazilian game devs can leverage collective action to counteract power imbalance with platforms, collaborate through events and projects and facilitate internationalization of their games.

Social implications

The study suggests collective action could empower developers to challenge platform dominance and foster a stronger community among Brazilian game developers.

Originality/value

The article’s value lies in examining Brazilian devs' experiences within their specific industry context and highlighting collective action as a potential strategy for developers.

Details

Innovation & Management Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2515-8961

Keywords

Article
Publication date: 30 August 2022

Devika E. and Saravanan A.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems…

51

Abstract

Purpose

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

Design/methodology/approach

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

Findings

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

Originality/value

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 17 February 2023

Piriya Pholphirul, Akkaranai Kwanyou, Pungpond Rukumnuaykit, Teerawat Charoenrat and Kitisak Srijamdee

This study aims to analyze social networking and network centrality in the case of community enterprises, which the existing literature has not addressed. To do so, the authors…

Abstract

Purpose

This study aims to analyze social networking and network centrality in the case of community enterprises, which the existing literature has not addressed. To do so, the authors use the survey of community enterprises from the One Tambon One Product (OTOP) entrepreneurship program of Nong Khai border province in Thailand as a case study.

Design/methodology/approach

Social network analysis (SNA) is a tool to study and understand the relationship patterns of units of analysis, which can be individual, household, community or production units, and how those units interact through social or economic activities. Network positions are important when identifying the centralization of links in a particular network. If a representative is close to the center of a network, it is possible that the production unit will be able to contact or coordinate with a greater number of other members of the cluster, create knowledge sharing, promote collaboration and then typically demonstrate greater performance.

Findings

The results show that overall, local government agencies play a critical role in the community enterprise relationship network, while private entities are the least active group. Enterprises in partnerships with external agencies are mostly cooperating with branding and marketing dimensions, followed by the design dimension. There is no cooperation regarding production and distribution. Most community enterprises have established at least a one-dimensional network of cooperation with external agencies; only five community enterprises have isolated nodes with no partnerships having been created within this group.

Research limitations/implications

The study was limited by the surveys having been conducted in a single area and, therefore, can be used only as a case study for this area. Surveys in larger group sizes and in a wider range of areas would lead to results with greater applicability and reliability.

Practical implications

These results bring to mind policy proposals to increase the competitiveness of community enterprises through the development of social networks as follows: firstly, knowledge should be created with community enterprise operators to understand their supply chains and analyze the strengths and weaknesses and core competencies of their enterprises; and secondly, enterprises should be educated about which agencies can assist businesses at each stage in the value chain system and encouraged to ask for help in adding value at each stage of production.

Social implications

A “OTOP to Business Networking” platform for community and private enterprises should be created with projects/activities that offer venues to exchange business learning and opportunities. Holding meetings among people in a variety of business sectors may help inspire entrepreneurs to innovate to further their businesses, which can lead to networking businesses conducting activities across community enterprises and the private sector for the mutual benefit of producing merchandise for large customers and markets. Learning systems, production techniques and cooperation should be created, as well as opportunities to increase market share and profitability, if this platform is successful.

Originality/value

This paper is the first study, to the best of the authors’ knowledge, to utilize SNA to examine the use of social networking among community enterprises participating in Thailand’s OTOP entrepreneurship program in Nong Khai province. The results show that overall, local government agencies play a critical role in the community enterprise relationship network, while private entities are the least active group. Therefore, the government can play an important role in helping to develop a network of community enterprises with external entities at each stage of the value chain to enhance the competitiveness of each enterprise.

Details

Journal of Entrepreneurship in Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4604

Keywords

Article
Publication date: 2 February 2024

Pushkar Pushp and Faisal Ahmed

The discourse on global value chains (GVC) is undergoing a transformation in terms of its conceptualisation, theorisation and pragmatic applications. Today, the production systems…

Abstract

Purpose

The discourse on global value chains (GVC) is undergoing a transformation in terms of its conceptualisation, theorisation and pragmatic applications. Today, the production systems have become more complex as global economic order continues to witness marked geo-economic manoeuvring. Thus, the direction of discourse on GVC ought to move from mere theoretical propositions toward becoming more evidence based. There have been recent studies that have used the governance and upgrading propositions by Gary Gereffi and others to seek quantitative evidence. This study aims to decipher the quantitative discourse on GVC and to set the emerging and future research agenda.

Design/methodology/approach

Through a systematic literature review, the authors first analyse the quantitative studies on GVC carried out during the last two decades. The authors then outline a future research agenda and examine a few relevant modelling techniques that could potentially be used to solicit newer evidence in GVC research.

Findings

The authors categorise the quantitative discourse on GVC into three crucial themes, namely, GVC framework, GVC participation and position, environmental aspects and regionalisation in GVC. The most commonly used quantitative techniques are gravity model, panel data estimation, structural decomposition analysis and computable general equilibrium modelling.

Originality/value

This paper contributes to the GVC discourse in two ways. Firstly, the authors argue that the theoretical frameworks within the GVC discourse should be complemented by evidence-based quantitative studies. Secondly, the authors suggest potential modelling techniques that can be used on the emerging and future research agenda.

Details

Critical Perspectives on International Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-2043

Keywords

Open Access
Article
Publication date: 7 October 2021

Enas M.F. El Houby

Diabetic retinopathy (DR) is one of the dangerous complications of diabetes. Its grade level must be tracked to manage its progress and to start the appropriate decision for…

2517

Abstract

Purpose

Diabetic retinopathy (DR) is one of the dangerous complications of diabetes. Its grade level must be tracked to manage its progress and to start the appropriate decision for treatment in time. Effective automated methods for the detection of DR and the classification of its severity stage are necessary to reduce the burden on ophthalmologists and diagnostic contradictions among manual readers.

Design/methodology/approach

In this research, convolutional neural network (CNN) was used based on colored retinal fundus images for the detection of DR and classification of its stages. CNN can recognize sophisticated features on the retina and provides an automatic diagnosis. The pre-trained VGG-16 CNN model was applied using a transfer learning (TL) approach to utilize the already learned parameters in the detection.

Findings

By conducting different experiments set up with different severity groupings, the achieved results are promising. The best-achieved accuracies for 2-class, 3-class, 4-class and 5-class classifications are 86.5, 80.5, 63.5 and 73.7, respectively.

Originality/value

In this research, VGG-16 was used to detect and classify DR stages using the TL approach. Different combinations of classes were used in the classification of DR severity stages to illustrate the ability of the model to differentiate between the classes and verify the effect of these changes on the performance of the model.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 4 December 2023

Nidhi Sharma and Nilesh Arora

There has been considerable discussion about the utilization of social media effectively in tourist research. Still, there is a paucity of information about its usage for…

Abstract

Purpose

There has been considerable discussion about the utilization of social media effectively in tourist research. Still, there is a paucity of information about its usage for ecotourism destination selection. The study aims to determine critical factors influencing travelers' behavioral and electronic word-of-mouth (e-WOM) intentions to use Instagram reels to select an ecotourism destination.

Design/methodology/approach

This study is based on the motivated consumer innovativeness theory and technology acceptance model. Purposive sampling was applied to acquire data from Instagram users. Data were gathered from 445 respondents and 415 valid responses were analyzed using partial least square structural equational modeling.

Findings

The findings of the study confirmed the positive impact of perceived ease of use, socially motivated consumer innovativeness and hedonically motivated consumer innovativeness on travelers' attitude except for perceived usefulness. The outcomes also revealed a significant influence of travelers' attitude on behavioral and e-WOM intention.

Research limitations/implications

The study's findings were intended to offer insights into traveler behavior to critical players in the tourism sector, including destination marketers, travel companies, the government and policymakers. They must comprehend how useful Instagram is for the tourist industry, which will help them better understand how to attract travelers through Instagram reels to market their destination.

Originality/value

The current investigation is the first attempt to investigate the travelers' behavioral and e-WOM intentions to use Instagram reels to select an ecotourism destination.

Details

Journal of Hospitality and Tourism Insights, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9792

Keywords

Article
Publication date: 13 March 2024

Şeyma Şahin and Abdurrahman Kılıç

The ultimate objective of this study is to compare the impact of face-to-face and online flipped learning on students' academic achievements and their perspectives on learning and…

Abstract

Purpose

The ultimate objective of this study is to compare the impact of face-to-face and online flipped learning on students' academic achievements and their perspectives on learning and teaching, offering valuable insights to the field.

Design/methodology/approach

The study utilized a quasi-experimental research method that involves pre-test and post-test control groups.

Findings

The results indicated that face-to-face and online flipped learning positively impacted learning, with comparable contributions to academic achievement. However, we found that online flipped learning did not affect students' beliefs about learning and teaching, while face-to-face flipped learning positively influenced them.

Originality/value

As distance learning becomes increasingly important in our modern era, this research aims to explore the use of active learning methods, including discussion, writing, animation, drawing, association, analysis, knowledge measurement and games, in virtual learning environments, such as online flipped learning. The study seeks to enhance the existing literature on the impact of face-to-face and online flipped learning models on student success. Additionally, it aims to address a significant gap in the literature by determining the effect of these models on students' epistemological and pedagogical beliefs, which can impact their motivation, learning outcomes, academic achievements and decision-making processes.

Details

Journal of Applied Research in Higher Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-7003

Keywords

Article
Publication date: 16 January 2024

Kasmad Ariansyah, Ahmad Budi Setiawan, Alfin Hikmaturokhman, Ardison Ardison and Djoko Walujo

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency…

Abstract

Purpose

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

Design/methodology/approach

This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

Findings

FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

Originality/value

This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 29 December 2023

Charles Ogechukwu Ugbam, Chi Aloysius Ngong, Ishaku Prince Abner and Godwin Imo Ibe

This study examines the nexus of bond market development and economic growth from 2015 to 2022.

Abstract

Purpose

This study examines the nexus of bond market development and economic growth from 2015 to 2022.

Design/methodology/approach

The system-generalized method of moments (GMM) is employed on economic growth, government market capitalization, corporate market capitalization, bond yield, interest rate spread, trade openness and investment level.

Findings

The findings show that the government bond market, corporate bond capitalization and bond yield positively impact the gross domestic product (GDP). The results equally reveal a causal link between the corporate bond market, bond yield and GDP.

Research limitations/implications

Governments should emphasize creating, developing and sustaining bond markets in the economies of developing countries to boost economic activity by promoting structural transformation. Policymakers should improve the implementation of existing rules and regulations while complementing them with new ones since well-developed bond markets provide alternative sources of financing that make economies financially resilient. Policymakers should encourage the issuance of corporate bonds to enhance the efficiency of the capital markets and mobilize funds for economic growth stimulation. Governments and corporations should diversify their sources of funding into the bond markets since the bond yields are favorable to economic growth.

Originality/value

Earlier studies presented arguable results on the bond market development and economic growth nexus. Several findings indicate a positive link; others give a negative link between bond market development and economic growth. Some show causal directions, while other reveal none. The contradictory results motivate research. This research results contribute to the literature in that the government bond market, corporate bond capitalization and bond yield positively impact the GDP of developing nations.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

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