International Journal of Technology, Policy and Management (12 papers in press)

Regular Issues

• Emergence of FinTech Technologies as a Game Changing Innovation in the Digitalised Era  
  by Diwakar Chaudhary, Shubhash Kumar Verma, Rashi Baliyan, Pooja Singh, Khadilkar Sujay Madhukar 
  Abstract: FinTech is a powerful mix of new digital technologies and changing customer needs. It's not just changing financial services; it's changing everything. Its game-changing features make access more open, personalise solutions, and speed up deals. For example, they can help people who don't have bank accounts by automating investments. But, like any change, it has problems, like digital divides, security worries, and rules that make it hard to use. We can guide FinTech toward a future where its transformative power helps everyone by putting an emphasis on ethical considerations, responsible innovation, and openness. This will pave the way for a fairer and more prosperous financial environment. This is not just a great piece of technology; it's also a call to action, a chance to change the story of finance with FinTech as our strong tool. Let's see how it can change things and work together to make the future a place where financial services really meet everyone's needs.
  Keywords: Digitalization; Fintech; Disruption; Block chain; AI.
  DOI: 10.1504/IJTPM.2026.10066899
   
  
• Connecting People, Cultures, and Skills: BRI's Influence on Tourism and Human Capital  
  by Aamir Shahzad, Syed Mudasser Abbas, Wisal Ahmad 
  Abstract: This study explores the social impact of China’s Belt and Road Initiative (BRI) on tourism and human capital development in the countries that host BRI projects BRI is a global development strategy that aims to enhance economic integration and cooperation among participating countries, which leads to an increase in tourist flow to the host countries Tourism provides various benefits to the local people, such as improving their skills, creativity, language abilities, and training opportunities, which are crucial for developing human capital Human capital is a key factor for achieving economic growth, social development, global competitiveness, and individual well-being However, tourism also has negative impacts, such as environmental degradation, cultural erosion, and social conflicts, that need to be addressed This study reviews and compares the literature on previous economic integration and experiences of different countries that are involved in BRI The study intends to provide valuable insights for policymakers and stakeholder
  Keywords: Human Capital Development; BRI Projects; Social Impact; Tourism Growth; and Tourist Host Interactions.
  
  
• The Impact of Globalisation on Business Management: Strategies for Multinational Success  
  by Gang Chen 
  Abstract: Business globalization is the practice of organizations operating across borders and with less inclination for doing so within their own nation. Businesses are encouraged to internationalise as part of globalisation and significantly expand the volume and variety of cross-border money. Globalization has significantly changed the corporate environment, posing both possibilities and challenges for international business. The objective of this study is to examine the way globalisation affects company management and practical strategies for succeeding in a globalised economy. This research produces and assesses a model that examine at the connection between business performance, E-Commerce utilization and globalisation. The data utilised in this study was gathered from a comprehensive survey of businesses in these industries conducted across multiple countries. The data and hypothesis were statistically analysed using regression analysis, factor analysis and descriptive statistics. The outcomes demonstrated that increased E-Commerce utilisation and enhanced performance are both consequences of globalisation.
  Keywords: Globalization; Business; E-Commerce; Performance; Multinational Industries.
  DOI: 10.1504/IJTPM.2025.10069253
   
  
• Comparative Examination of the Input-Oriented and Output-Oriented R&D Technical Efficiency in OECD  
  by Constantinos Tsamadias, Stylianos Margaritis, Christos Staikouras, Emmanuel Mamatzakis 
  Abstract: Using the non-parametric method of data envelope analysis (DEA), this study empirically explores and compares the technical efficiency of Research & Development (R&D) in 35 OECD countries from 2013 to 2020. Our model offers accurate estimations and corrects for misspecification. We assess both technical efficiency that is output oriented and technical efficiency that is input oriented. Additionally, we make a distinction between narrow R&D, which encompass both basic and applied research, and broad R&D, which also include experimental development. Once we derive efficiency we proceed with a thorough comparison evaluation utilising four criteria for all models, all countries, and all groups of countries. The findings show that efficiency varies between countries and between models. The northern European countries received the highest efficiency scores, confirming their dominance in R&D at global level. The findings are crucial not only for the academics but also for national and international policymakers since they give guidance for the necessary actions to increase R&D efficiency.
  Keywords: DEA; R&D; Input and Output Oriented Efficiency; OECD.
  DOI: 10.1504/IJTPM.2026.10070186
   
  
• Financial Fraud Identification Technology Based on FL Model and MLP Neural Network  
  by Zhenyu Chu, Xuewu Lai 
  Abstract: The phenomenon of data silos in financial institutions leads to poor application performance of federated machine learning models. Therefore, a financial fraud recognition system based on a federated learning model and a multi-layer perceptron neural network was studied and designed. Firstly, a federated learning model based on the federated average algorithm was used to achieve joint training of various financial institution nodes, and a composite minority class oversampling algorithm was used for data balancing preprocessing. The validation in the credit card transaction dataset confirmed that the accuracy of the financial fraud recognition system in sample classification recognition in the training set was 99.60%, and the recognition effect in the test set was 99.21%. Compared with other training models, the proposed system had an average increase of 2.15% in area under the curve and an average increase of 2.18% in geometric mean. These results confirm that the proposed financial fraud identification system has superior financial fraud identification performance while meeting the conditions of user data privacy and security.
  Keywords: Federated machine learning; Multi-layer perceptron; Financial fraud identification; Joint training; Data balancing preprocessing.
  DOI: 10.1504/IJTPM.2026.10070744
   
  
• Economic Recovery after the Pandemic: Improving Public Policy Tools  
  by Oksana V. Pliusnina, Ilya Pokamestov, Evgeniya A. Badokina, Larisa M. Butova, Tatyana Sobolevskaya 
  Abstract: The pandemic has shown that the level of maturity of the economic system is not decisive in the face of external challenges. The leading positions in the future will be occupied by those countries whose economies are highly adaptable to changes. This is achieved by improving the mechanisms of public policy. The purpose of the study is to identify the peculiarities of the functioning of the Russian economy during the pandemic, as well as to identify public policy measures aimed at increasing the adaptive capabilities of the state's economy during the period of change. The authors identified the features of the implemented state policy and support for the national economy during the pandemic crisis. China's best practices in implementing effective measures implemented during the pandemic are being investigated. The authors justified measures to increase the adaptive potential of the Russian national economy during the recovery period after the pandemic.
  Keywords: state policy; management; regulatory mechanisms; pandemic; national economy; Russia; China.
  DOI: 10.1504/IJTPM.2026.10070880
   
  
• Rethinking ICT and Digital technology Policy Designing to Harness Artificial Intelligence for Accelerating Gender Equity and Youth Empowerment in Sub-Saharan Africa.  
  by Blessing Masamha, Palesa Sekhejane, Uzma Alam 
  Abstract: Mainstreaming gender in ICT policies in Africa remains challenging since women and youths are disproportionately affected by AI technologies. The mapping of policy gaps and subsequent rethinking of ICT and AI policy development pathways to advance gender equity and youth empowerment in Africa was done. A case study design was adopted with a qualitative archival and reflective analysis of policy blueprints, plans, and strategy documents (62) from eleven African countries. High-level regional multi-stakeholder workshops were held in the ECOWAS, SADC, and COMESA regions. The policy gaps exist due to limited bottom-up consultative processes, policy incoherence, minimal multi-sectoral co-designing and co-implementation frameworks, and limited verifiable achievement indicators. Thematic analysis used NVIVO 14 software, and few countries referred to women and youths in their policy blueprints, with Liberia (14%), Sierra Leone (10%), and South Africa (5%) emerging high. Only Rwanda had an AI policy with no focus on gender and youth empowerment.
  Keywords: Policy; ICTs; Artificial intelligence (AI); gender equity; youth empowerment; sub-Saharan Africa.
  DOI: 10.1504/IJTPM.2026.10071137
   
  
• Research on Innovative Grid Data Management based on Traceability Model and Community Blockchain Technology  
  by Silong Wu, Junting Deng, Jiaojiao Zhang 
  Abstract: Smart grid data centres hold a lot of high-value data, but since each data centre has a limited variety of resources, data exchange is crucial to carrying out an efficient data mining process. However, centralised systems that lack shared object authentication are often used in conventional data-sharing models, which makes it challenging to build trust and protect data privacy. This makes overcoming the issue of data islands challenging. This article suggests a blockchain-based data-sharing incentive model for edge smart grid scenarios in order to address the aforementioned issues. Initially, the approach achieves the security and traceability of the smart grid data-sharing process by using blockchain and proxy re-encryption technologies. Second, game theory is used in the design of the data-sharing incentive algorithm to optimise data owners' readiness to share their data. The scheme in this paper has significant advantages over the others in terms of functionality and computational overhead.
  Keywords: blockchain; smart grid data; smart contract; conditional proxy re-encryption.
  DOI: 10.1504/IJTPM.2026.10071326
   
  
• Evaluating Technological Impacts on Stock Market Behaviour: a Machine Learning and NLP Approach to Socio-Economic Analysis  
  by Richa Handa, Pavani Sirigiri, Bisahu Ram Sahu, Bijay Kumar Paikaray, Madhusmita Mohanty, Lata Algamkar 
  Abstract: Indian stock market is influenced by Politics, finance, and various other internal and foreign issues. It is very challenging for academicians to predict the behavior of the stock market accurately. Nowadays, people communicate their ideas on social media on various topics depending on what they wish to write. Social media plays a very important role in knowing about the current trends of stock data as people nowadays share their views on social media, whether positive or negative. In this study, we analyze sentiments of people on the stock market using Twitter data and classify it using machine learning techniques to develop an analytical model such as Bernoulli Naive Bayes, SVM (Support Vector Machine), and Logistic Regression and perform a comparative study to find out which model is outperforming for sentiment analysis of Indian stock market.
  Keywords: Stock Data; Semantic Analysis; Twitter; social media; Bernoulli Naive Bayes; SVM; Socio-Economic.
  DOI: 10.1504/IJTPM.2026.10071605
   
  
• The Knowledge City and Regional Application of Labour Insurance Supply Management from Big Data Algorithms  
  by Yanhua Wang, Jie Duan, Wei Gu, Jing Duan, Haitao Liu 
  Abstract: This paper investigated the effectiveness of labour insurance supply management in knowledge cities and regional applications through the use of big data (BD) algorithms. It compared the Big Data Algorithm-Based Management (BDAM) model with the traditional rule-based management (RBM) model across key metrics, including efficiency, safety, innovation, sustainability, costs, and resource utilisation. Results indicated that the BDAM model significantly outperformed the RBM model, with higher resource allocation efficiency (16% to 39% vs. 17.54% to 67.71%), superior safety levels (53.49% to 62.10% vs. 29.32% to 36.57%), and better innovation and sustainability scores. Although the BDAM model incurred higher initial costs, it demonstrated cost savings over time, with costs decreasing from 18.95 to 16.25, and maintained higher resource utilisation efficiency (0.737 to 0.810 vs. 0.573 to 0.635). The study emphasised the BDAM models flexibility, scalability, and potential for integration with other smart city components.
  Keywords: big data algorithms; labor insurance supply management; knowledge city; regional applications; resource utilization efficiency.
  DOI: 10.1504/IJTPM.2027.10071606
   
  
• The Impact of Globalisation on Technology Transfer: Assessing the Role of Multinational Corporations and International Trade in Driving Technological Innovation in Emerging Economies  
  by Siyang Mei, Yuxi Zhang, Renfeng Deng, Xin Liu, Feng Li 
  Abstract: The study's goal is to find out how changes in geopolitics and geoeconomics impact the process of creating a global energy system. There is a lot of talk in the paper about how the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) and the Regional Comprehensive Economic Partnership (RCEP) deals have changed. There are more and more people going around the world. A global SWOT analysis and the New Globalization Scenario Matrix (NGSM) help us figure out and guess what the main global trends will be in the future. The current events in the world could improve the system's performance, leading to faster energy changes. There is now a new way to look at the IPE of energy around the world after this event. This is one way that realism and liberalism work well together to create a new type of global liberalism.
  Keywords: The Correlative SWOT Analysis; Geoeconomics ; Modern Geopolitics; Descriptive Statistics; Basic Inspection; Regulation Effect Test; Heterogeneity Test.
  DOI: 10.1504/IJTPM.2026.10072210
   
  
• A Multi-Level Approach for Asymmetric Technological Cooperation  
  by Seyedamirreza Enjavi, Shaban Elahi, Ali Shayan, Esmaeil Mousavi 
  Abstract: Asymmetric technological cooperation (ATC) is crucial for the knowledge-based economy, enabling significant science and technology transfer. This study highlights ATCs importance in public policy and examines various ATC processes and programs, alongside policymakers motivations to intervene. Using meta-synthesis, the research consolidates relevant literature to define a typology of ATC activities and the policies that promote them. The study adopts a multi-level framework niche, regime, and landscape levels to analyse policy measures that facilitate ATC by driving socio-technical system changes. It argues that effective ATC depends on active policymaker involvement to support and manage these systemic transitions. Ultimately, the paper emphasises that policymakers play a vital role in enabling ATC, which is essential for fostering technological progress and sustaining knowledge-based economic growth.
  Keywords: asymmetric technological cooperation; collaboration; facilitation policy; incumbent; startup.
  DOI: 10.1504/IJTPM.2027.10072399