Editorial: Innovation and technology for a better future: insights from Asia and UAE

What the paper says

Innovation and technological advancement create new opportunities for companies and organizations to enhance operational efficiency, develop innovative products and services, generate new business opportunities and strengthen competitiveness. Deep-tech innovations present both significant opportunities and complex challenges that firms must address to survive and thrive in increasingly uncertain and dynamic environments. Investment in strategic human capital, the generation of new knowledge and the pursuit of breakthrough innovations are essential to paving the way towards more sustainable and environmentally responsible futures for all (Cheng et al., 2026; Li and Li, 2026; Lytras and Ordóñez de Pablos, 2008; Wang and Thai, 2026; Zhang et al., 2023; Zhang et al., 2026; Zhou et al., 2026).Sustainability has emerged as a crucial topic for companies, nations and regionals, requiring organizations to integrate environmental, social and governance considerations into innovation and technology development. The convergence of deep tech innovation, digital technologies, mobile payment solutions and sustainability-oriented strategies is essential for fostering more resilient and inclusive digital futures. Therefore, discussing innovation and technology is critical for understanding the drivers of economic growth, job creation and competitiveness in the digital and green transitions.Issue 3 of the Journal of Science and Technology Policy Management features a regular collection of 11 papers. These contributions cover a range of topics, including data analytics, digital healthcare, frugal innovation, government e-services, knowledge management and the intersection of science and technology with sustainability. The issue facilitates discussions on these subjects across a variety of countries, including Bangladesh, India, Iran, Iraq, Pakistan, the Philippines, Tanzania, the UAE and Vietnam.The first paper titled “An SME approach to data analytics by management accountants in the transition economy of Vietnam” (by Trinh) affirms that “data analytics (DA) is an emerging topic in management science at large organizations; however, accountants in small and medium-sized enterprises (SMEs) are believed to be lagging far behind in the usage of DA. This study aims to provide a deep understanding of the actual DA activities undertaken by management accountants (MA) and to draw on SMEs’ characteristics to take advantage of DA applications. This study used a qualitative approach by conducting in-depth interviews with 31 accounting and finance practitioners at senior levels of SMEs, following the use of the MAXQDA 2022 application for data analysis. Findings in this study suggest variance and trend analysis as the two most popular tasks of DA, and advanced tasks such as contingency analysis, financial modelling, sentiment analysis and regression analysis are unfully performed in SMEs. The outcomes revealed that DA is not anticipated to affect the responsibilities but to expand the role and scope of management accounting. This study simultaneously builds a theoretical framework about the antecedents, in terms of the external and internal drives and the characteristics of SMEs’ owner-managers, that are most common in all types of SMEs that encourage MA to use a specific technology, data analysis in a more advanced way instead of searching for determinants that affect the adoption of technology in general, as previous studies have conducted”.The paper titled “Quality assurance of science and technology universities in Bangladesh: a catalyst for sustainable employment during the 4IR” (by Alam, Ogawa and Ahsan) presents the results of a study that reports “the quality of Bangladesh’s science and technology universities (STUs) in ensuring sustainable employment of graduates during the Fourth Industrial Revolution (4IR) by assessing their vigilance in skill development activities and exploring students’ perspectives on the university. This research used mixed methods: a close-ended five-point Likert scale questionnaire to understand students’ perspectives and a thematic analysis of the interviews of students, faculties, policymakers and relevant stakeholders. The data was collected through a random sampling method where 1,000 university students took part in the quantitative analysis along with other respondents for the qualitative portion. The analysis was done with a 99% confidence level and a 4.5% margin of error. Bangladesh’s STUs still have a long way to go to ensure quality education and generate sustainable employment for their graduates. The universities’ preparation to comprehend the 4IR is not at the expected level. In addition, despite students’ favourable perception of universities as providers of qualified labour, there is a significant mismatch between supply and demand”.The paper titled “The impact of buying external technology on employment and air quality: an empirical approach in Vietnamese manufacturing SMEs” (by Nguyen and Le) aims to “evaluate the current situation of buying external technology in Vietnamese manufacturing small and medium enterprises (SMEs) from 2013 to 2018. This paper also aims to examine the effect of buying technology on employment and environmental quality in Vietnam. External technology purchase and its impact on employment and environmental quality are taken from the Vietnam annual enterprise survey and the using technology in production survey from 2013 to 2018. The estimation is based on a feasible generalized least squares method. This study finds that external technology purchase in manufacturing SMEs increases the employment rate in the industries. External technology purchase in Vietnamese manufacturing SMEs also increases the level of environmental pollution. This is a negative side of purchasing technology for production because if the technology used is old, outdated and of poor quality, it will increase environmental pollution. In addition, the growth in employment increases air pollution. This shows that purchasing advanced technology selectively helps to increase the employment rate in Vietnamese manufacturing sector, which is followed by a positive impact on environmental quality”.The paper titled “Understanding the academic use of KM-driven metaverse technology: Insights from medical colleges” (by Abdulmuhsin, Owain and Alkhwaldi) discusses a study that analyses “the behavioural intentions of educators within medical colleges at Mosul Universities concerning the adoption of Knowledge Management-Driven metaverse technology (KM-D-MT). Rooted in an adapted Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, the research aims to enrich the understanding of Metaverse adoption factors, exploring correlations among key constructs such as performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value, hedonic motivation and interaction. Furthermore, the study investigates the mediating roles of knowledge generation and knowledge sharing in the relationship between interaction and behavioural intention. The research employs a quantitative approach, gathering 278 responses from educators in medical colleges. Structural Equation Modelling-Partial Least Squares (SEM-PLS) is used to analyse the data, rigorously examining the reliability and validity of research instruments. The investigation involves an extensive evaluation of various factors influencing educators’ intentions to adopt KM-D-MT, using a cross-sectional design. The study reveals significant positive impacts of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value and hedonic motivation on behavioural intention to adopt KM-D-MT. Interaction is identified as a key factor positively influencing knowledge sharing and knowledge generation. Furthermore, knowledge sharing and knowledge generation exhibit positive correlations with behavioural intention. Interaction indirectly impacts behavioural intention through the mediating roles of knowledge generation and knowledge sharing, highlighting the transformative potential of metaverse technology in reshaping knowledge processes”.The paper titled “Revolutionizing primary healthcare in Tanzania: Unravelling the contextual factors on electronic health record systems implementation for effective decision support” (by Mwogosi) discusses the results of a “qualitative case study aims to identify and analyse the factors influencing the implementation and effectiveness of electronic health record systems (EHRS) in primary health-care (PHC) facilities in Tanzania. This study aims to explore ways to optimize the use of EHRS for better health-care service delivery. The study uses a qualitative case study design. Data were collected through interviews and focus groups conducted with health-care workers and information and communication technology officers at the PHC facilities in Tanzania. Purposive sampling and data source triangulation were used to address potential biases and limitations associated with the study’s small sample size. This study identifies several key findings related to the implementation and effectiveness of EHRS in Tanzanian PHC facilities. The primary obstacles include inadequate technical infrastructure, poor internet connectivity and insufficient financial resources. The study suggests a comprehensive strategy for improving EHRS, emphasizing patient and health-care professional involvement in system design, investments in technical infrastructure and connectivity, data quality and accuracy and ongoing technical support and training. This research contributes to the existing body of knowledge by offering a nuanced understanding of the Tanzanian health-care context. It emphasizes the need for tailored solutions and strategies specific to the region’s challenges and opportunities. The study’s originality lies in its focus on EHRS in the Tanzanian context, providing valuable insights for future initiatives. A key policy implication underscores the importance of a supportive regulatory framework, dedicated resources and consistent stakeholder communication for successful EHRS implementation”.The paper titled “The mediating roles of trust on intentions toward mobile wallet adoption in social health insurance: a deep learning–based SEM-ANN analysis” (by Catacutan and Mabesa) explores “the factors influencing Filipinos’ intention to adopt mobile wallets to pay social health insurance premiums. The authors used an integrative model framework using the key indicators from the lenses of the technology acceptance model, the unified theory of acceptance and usage of technology Model 2 and the theory of planned behaviour with trust serving as a mediator. The sample size was calculated using an inverse square root ratio composed of 624 survey participants purposively identified across selected cities in the Philippines. The formulated hypotheses were examined using partial least squares structural equation modelling and deep learning-based artificial neural networks. The results substantiate this study’s integrative model explaining the positive influence and relative importance of perceived usefulness, habit and subjective norms in developing trust in mobile wallet applications. Moreover, health insurance literacy, subjective norms and trust positively and significantly drive individuals’ intentions to adopt mobile wallets as a payment platform for social health insurance premiums. The mediation analysis also exemplified that trust positively mediates the influences of technology acceptance factors such as perceived usefulness, habit and subjective norms in the intention of individuals to adopt mobile wallet applications in social health insurance payment of premiums”.The paper titled “Factors influencing customers’ adoption of mobile payment in Pakistan: application of the extended meta-UTAUT model” (by Hassaan and Yaseen) states that “mobile payment (or m-payment), a relatively new digital banking system targeting Pakistani customers, is rapidly expanding. This study aims to explore the elements that impact customer behaviour and encourage the adoption of m-payment in Pakistan. This study used a quantitative research design, surveying 315 m-payment users residing in three Pakistani cities. A conceptual framework was developed by extending the meta-unified theory of acceptance and use technology (meta-UTAUT) model to incorporate institutional privacy concerns (IPC) and institutional source reliability (ISR). Data analysis was conducted using partial least squares structural equation modelling via Smart PLS 4.0 software. This study’s results indicate that behavioural intention (BI) is the primary driver of m-payment use behaviour. The findings also reveal that attitude (AT), performance expectancy (PE), facilitating conditions (FC), social influence (SI), effort expectancy (EE), IPC and ISR significantly influence BI. Notably, PE and FC are positively associated with AT, while EE and SI have no significant impact on AT. This study has two key limitations. First, its focus on only Pakistani m-payment users limits the broader applicability of the results. Second, the cross-sectional design overlooks potential longitudinal changes in users’ attitude. Future research should aim to recruit diverse country samples and conduct comparative studies, thereby enhancing the understanding of m-payment adoption”.The paper titled “Applying fuzzy logic to balanced scorecard for the performance evaluation of government E-services” (by Sohaib, Arman, Begum and Arshi) aims to “assess the performance of United Arab Emirates (UAE) Government e-services by using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology, integrating insights from the balanced scorecard (BSC) framework across financial, customer, internal business and learning and growth perspectives. Using the fuzzy TOPSIS method, this paper evaluates three e-services in the UAE against 12 criteria representing the balanced scorecard perspectives. Expert evaluation and sensitivity analysis are used to identify the most sustainable e-service alternative. The study findings emphasize the importance of prioritizing customer-centric metrics, improving service reliability and efficiency, and investing in employee training to enhance e-government service performance in the UAE. Sensitivity analysis reinforces the robustness of our results and identifies key criteria influencing decision-making. The data was collected only from experts in selected UAE Government departments. This may affect the generalization of the findings. Also, only three e-services were evaluated. Future studies could include various e-services not covered in this study and use different multi-criteria decision-making methods”.The paper titled “Serial mediation effect of service innovation and word of mouth on mutual fund investment decision through mobile customer relationship management” (Deb, Jain, Marwah and Deb) explores “the effect of mobile customer relationship management (mCRM), service innovation (SI) and word of mouth (WOM) on the investment decisions (IDs) of mutual fund investors. This paper presents a new model for impacting the IDs of mutual fund investors. To verify the suggested model, Partial Least Squares with Structural Equation Modelling are used. For analysis, a survey questionnaire is designed, and data inputs were invited from more than 400 online mutual fund investors in Delhi NCR. The outcomes reveal that the ID of mutual fund investors is significantly influenced by WOM. WOM, in turn, is significantly impacted by mCRM applications through SI playing a mediating role”.The paper titled “Investigating the moderating role of technology turbulence and innovation capabilities in servant leadership, knowledge management and frugal innovation” (by Bazyar, Abbasi and Khanachah) analyses “the impact of servant leadership on knowledge management and its subsequent connection to cost-saving innovation. The study further explored these relationships by examining the mediating roles of innovation capabilities and technological volatility. The research is applied in purpose and employs a descriptive-survey method for data collection. It follows a qualitative-quantitative approach, utilizing expert interviews in the qualitative phase. The sample consists of 35 managers and expert professors with knowledge management experience in universities and high-tech industries, selected through the snowball method. Data collected from Iranian organizations were analysed using AMOS software. The results revealed a positive correlation between servant leadership and knowledge management. Knowledge management demonstrated a significant positive relationship with cost-saving innovation. Additionally, technological volatility and innovation capabilities were identified as crucial factors influencing the connection between knowledge management and innovation, particularly in promoting frugality. While this research provides a comprehensive model, it acknowledges specific limitations that warrant further investigation. The study predominantly focused on Iranian organizations, suggesting an opportunity to broaden its scope to include diverse organizational perspectives from various cultural and geographical contexts. Moreover, a promising avenue for future research involves exploring entrepreneurial orientation as a potential mediating variable. Given its significant impact on organizational dynamics, introducing entrepreneurial orientation could enhance our understanding of its effects on both knowledge management and the promotion of frugal innovation. This expansion may illuminate the intricate interplay between entrepreneurial orientation, knowledge processes and innovative practices, contributing to a more sophisticated discussion on effective organizational strategies”.Finally, the paper titled “How to optimize government R&D budget allocation? A review of recent studies and research gaps” (by Alizadeh and Domyeh) observes that “Research and Development (R&D) activities are important for technological innovation and present opportunities for entrepreneurship. These activities depend on the flow of funding. This paper aims to review approaches used in R&D project selection and budget allocation. This study conducts a systematic review, examining the content of 60 relevant papers (spanning 2000–2022) concerning public R&D budget allocation. The analysis focuses on allocation methodology, R&D output evaluation, budget allocation efficiency and the management of uncertainty in the allocation process. The systematic review reveals different methods proposed for allocating government R&D budgets. These methods range from classical optimization, multi-criteria analysis and hierarchical analysis to techniques such as balanced scorecard, data envelopment analysis and analytic hierarchy process, including fuzzy approaches. Recent trends indicate an increase in the use of advanced optimization, integration and simulation algorithms. Performance indicators for reflecting R&D project outputs or goals can be categorized into four main groups: output (e.g. publications, patents, graduates), outcome, productivity (e.g. citations, patent references, articles and patents per capita) and sector-specific metrics”.