Technological Revolution Research Articles

The metaverse, a new frontier for innovative business models

The next revolutionary technology that will have an impact on society in the coming decades is called metaverse, which allows immersive encounters in both virtual and real-world environments. Metaverse, while still in the concept stage, merges the digital and physical realms, allowing users to move easily between them. How does metaverse influence sustainable development, organizational competitiveness and business innovation? This is the question from which this research started. In addition to identifying future obstacles, the paper proposes research options to help organisations fully exploit the opportunities and capabilities of metaverse. Investigating the current limitations and expansion potential of metaverse, including the impact on different industries and economic sectors, is the main focus of this research. The data collection tool was the questionnaire that we distributed to groups in different companies in Romania, being completed by employees from both executive and management departments. In this study, we developed a conceptual model to investigate the factors that could positively influence the evolution of innovative business models in Romania. We opted for structural equation modelling using SmartPLS4 software. The present research also contributes to identifying and addressing the challenges and risks associated with metaversion. The analysis indicates that although the adoption of digital business models and innovative management practices is significant, their immediate impact on the long-term success of companies in the metaverse is somewhat limited. The metaverse represents both a risk and an excellent opportunity for entrepreneurs to leverage digital services for growth. We believe this research is necessary to uncover new innovative business opportunities, as understanding rapid technological change allows companies to remain competitive and adopt new technologies effectively.

Biofuel: A sustainable and clean alternative to fossil fuel

Increasing fuel consumption has threatened energy supply stability, raising significant environmental and economic concerns for many countries. As global energy demand rises, reliance on fossil fuels poses serious challenges, including greenhouse gas emissions and resource depletion. In response, substantial efforts are made to develop and adopt clean renewable fuel alternatives. Replacing fossil fuels with biofuels can significantly reduce emissions of carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matter (PM), and tropospheric ozone (O3). Recent advances in the development of biofuels via genetic engineering have larger prospects for commercial-scale production. However, large-scale production remains challenging; therefore, to address this issue, it is vital to convert biomass into biofuels by developing revolutionary technology to improve biofuel production to meet present and future energy demands. The study aims to analyze alternative renewable energy sources and recent trends in the production of biofuel that are required to meet the demands of the global energy sector and economy while also considering future demand and utilization.

Agenda for psychological and behavioural science of transformative behavioural change

Abstract Since the emergence of psychological and behavioural science, one of its foundational goals has been to explain human behaviour. Although the discipline has been highly successful in this endeavour, there is an elephant in the room. Psychological and behavioural science has neglected studying the most challenging aspect of human behaviour−transformative behavioural change. This change can be described as a fundamental and difficult-to-achieve shift in someone’s actions that involves a transformation of one’s way of living. Understanding transformative behavioural change is essential not only for psychological and behavioural science to accomplish its foundational goal but also to maintain its contemporary relevance. Indeed, it is imminent that both solving the world’s biggest issues (e.g., climate change) and living through major disruptions (e.g., technological revolution) will require people to transform their behaviour. In this perspective, I first review and discuss previous relevant research, and then propose a seven-step agenda for how psychological and behavioural science can become the science of transformative behavioural change.

Analysis of Spatial Effects of New Energy Vehicles Based on Semi-parametric Spatial Durbin Model

The global scientific and technological revolution and industrial change are developing rapidly, the integration of automotive technology with energy, transportation and information and communication fields is accelerating, and electrification, internet connectivity and intelligence have become the main trends. Therefore, studying the impact of digital development on the growth of new energy vehicle industry and consumer purchase intention is of great theoretical and practical significance for the digital transformation of automobile companies. In this paper, based on the provincial panel data of new energy vehicles in China from 2016 to 2023, we constructed the index system of digital economy and economic development, used the entropy method to calculate the level of development, and conducted spatial autocorrelation tests using global and local Moran indices. Considering the non-linear relationship between variables, a semi-parametric spatial Durbin model is established using local polynomial estimation to explore the impact of digital economy on new energy automobile industry. The results of the study show that the development of digital economy promotes the development of new energy automobile industry to a certain extent, but its development level may have a negative impact if it is too low or too high.

Digital Architectural Form Generation Through Pixel System-Driven Image Feature Information

This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. Information in architecture is mainly used as an analytical tool for functional design optimization. However, the Fourth Industrial Revolution and advances in information and communication technology have positioned information as a core value-creating tool. Consequently, there is a growing need to develop methodologies for effectively applying information to architectural design generation. This study combines digital technology with images, which directly influence architectural design, transforming them into numerical information. By systematizing the three-dimensional form generation process using low-level image feature information, it analyzes the relationship between the characteristics of valuable information and the generated forms. This approach helps identify the interrelationships between the characteristics of valuable information and the generated forms, the complementarity needed to mitigate the limitations of valuable information, and the potential for architectural applications of the three-dimensional form generation methodology utilizing image information. This approach reduces labor and enhances architectural aesthetics by instantly generating diverse early design alternatives. Such research can provide a more logical basis for avoiding intuitive judgments during the design decision-making process. It can also lay the groundwork for information-centric design systems in architecture.

Application of Digital Literacy Using Mapalus Techniques in Learning in North Sulawesi

Entering the era of the fourth world industrial revolution in this case information technology has become the basis of human life. In this era almost all life effects utilize digital, including in learning, one of which is digital literacy. Along with technological advances and the increasing individualism of society due to globalization, for this reason this study collaborates digital literacy and local culture, namely mapalus which means cooperation in learning in North Sulawesi. The purpose of the study is to determine the process of implementing digital literacy with the mapalus technique and to evaluate the effects of implementing digital literacy with the mapalus technique in learning. This research is a descriptive qualitative type of research. The data collection techniques used are observation, interviews and documentation. The results of the study show that the application of digital literacy in learning facilitates easy access for students to materials and assignments given by educators. This also increases students' interest in using technology in the learning process and by using the malapus technique which makes students work together and work together to complete the tasks given in learning.

Do the technological anxiety, privacy and physical risks matter in retail customers'‏ ‏adoption of AR‏ ‏apps? An extended UTAUT2 approach

PurposeDue to augmented reality (AR) technology improvements, the retail industry has embraced smart retailing as its primary business model. Therefore, organizations must comprehend the intricacies of AR adoption to persuade clients to adopt this revolutionary technology effectively. Thus, the current study proposes and evaluates a comprehensive model that includes unified theory of acceptance and use of technology (UTAUT2), privacy concerns, physical risks and technological anxiety to predict customers’ intention to use AR apps in the retail industry in the Egyptian context.Design/methodology/approachThe current study examines 398 responses from Egyptian shoppers using partial least squares structural equation modeling (PLS-SEM). Snowball sampling was employed in the existing study. The participants were selected using a “self-selection” strategy, which is an excellent method for research investigations in which the participants freely participate.FindingsConsumers’ intentions to use AR apps in retail settings are positively impacted by task-technology fit, performance expectation, effort expectancy, social influence, facilitating conditions and hedonic motivation. Conversely, privacy and physical risks negatively affect customers’ intention to use AR apps in retail. Furthermore, technological anxiety serves as a moderator factor in these connections.Originality/valueTo the best of our knowledge, the current study is considered the first to test the role of UTAUT2, privacy and physical risks on users' behavioral intentions toward adopting AR apps in retail. It also examines technological anxiety as a moderator in the retail setting.

Utilizing Virtual Reality Tours in Language Learning

Virtual reality (VR) has been recognized as a revolutionary technology in education, providing a multitude of benefits that enhance learning experiences and outcomes. By immersing students in interactive and engaging environments, VR can make abstract concepts tangible, foster deeper understanding, and accommodate diverse learning styles. With VR, students can be fully engaged in dynamic and stimulating environments, which can transform abstract concepts into concrete experiences. This immersive approach can promote a deeper grasp of the subject matter. An example demonstrated how VR may engage students and foster interactive learning by enabling them to investigate intricate systems and surroundings that would be unfeasible or inconvenient (Freina & Ott, 2015). In addition, VR was shown to provide affordances that are believed to enhance learning, such as the first-person experience and the sense of being present in a particular location, also known as presence or spatial presence (Mikropoulos & Natsis, 2011). Although these advantages have been documented, the implementation of this technology has proven challenging or unfeasible for many teachers and learners due to financial constraints. VR photos and videos, which are commonly referred to as 360-degree media, have become readily available resources that can be utilized to create low-cost immersive experiences for people who are learning. Researchers have claimed that previous research has demonstrated the usefulness of these tools in boosting spatial presence and interest among participants in virtual reality tours that were conducted as part of one-off investigations (Petousi et al., 2023). However, these findings need to be supported by research over extended periods of time in a variety of educational settings to gain an understanding of the intricacies and limitations of this technology-based instructional approach. This poster describes two initiatives in which VR tours have been integrated into language learning settings. The first initiative employed a design-based research methodology to assess the efficacy of VR tours among online learners in France and Japan while the second initiative is an ongoing project that focuses on teaching the Filipino Language in a Japanese classroom using blended learning. This poster showcases the results of research conducted as part of the initiatives. The findings demonstrate the positive impact of virtual reality tours on student motivation and highlights the role of various factors, including instructional material, learners' personal traits, and the physical environment in which they engage in online learning, in addition to spatial presence and technological novelty. Moreover, this poster presents information regarding the process of improving the tours and lessons, as well as the platforms and technologies that were utilized to address concerns regarding usability and sustainability.

Fostering Inclusive Green Growth in Chinese Cities: Investigating the Role of Artificial Intelligence

In the new round of global technological revolution and industrial transformation, artificial intelligence (AI) provides an opportunity to foster urban inclusive green growth (IGG). On the basis of scientifically measuring the IGG level and AI development level of Chinese cities from 2010 to 2022, this paper systematically explores the impact and internal mechanism of AI on IGG. This study finds that AI development significantly promotes urban IGG, and this conclusion still holds after a series of robustness and endogeneity tests. The effect of AI on IGG will exhibit heterogeneity because of differences in urban characteristics such as government financial support, information infrastructure development, and innovation and entrepreneurship vitality. Mechanism test reveals that AI development fosters urban IGG through digital technology innovation and industrial structure optimization. Furthermore, AI development has a positive spatial spillover effect on IGG in neighboring cities. This study provides valuable theoretical insights and policy ideas for planning in emerging economies to promote high-quality economic development and ecological civilization through the application of AI technology.

Modern Technology: A Potential Tool to Impart English Language Skills

The present paper discusses the Lingua Franca of the world ‘English language’ and the role of technology in learning and teaching the English language effectively. The 21st-century modern technology has enabled learning and teaching of English very simple. We have a lot to choose from in the world of technology both hardware and software tools: Radio, TV, C.A.L.L, M.A.L.L, CD Rom, Computers, OHP, iPods, the Internet, Electronic Dictionary, Email, Blogs and Audio Cassettes, PPT’s, Videos, DVDs or VCD’s. Technology has brought a revolution in the life of people and completely changed their interaction and work dynamics. Industries were also greatly influenced and couldn’t escape the technical revolution. As a result, technology plays a vital role in teaching and learning. Using technology to teach English has a lot of advantages. Learners can get benefit from traditional educational institutions and also from online education. At the English lessons online we can unite to do the desired task. Different software programs, applications are available in learning Vocabulary, Pronunciation skills, Grammar, and LSRW skills. Many students in developed countries are making use of technology to learn the English language. But many more in underdeveloped countries fail to use tech tools for learning purposes due to inadequate tech facilities.

The Transformative Impact of Artificial Intelligence and Machine Learning on Marketing Operations

This comprehensive article explores the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on modern marketing operations. The research delves into key areas where AI and ML are revolutionizing marketing strategies, including hyper-personalization, predictive analytics, and conversational AI. Through an analysis of recent developments and case studies, the article demonstrates how AI-driven personalization significantly enhances customer engagement and relevance, with some implementations showing up to 25% increase in revenue and 15% improvement in customer retention rates. The article also examines the role of predictive analytics in shifting marketing strategies from reactive to proactive approaches, enabling more accurate forecasting of customer behavior, campaign performance, and market trends. Furthermore, the evolution of chatbots and conversational AI is explored, highlighting their capacity to automate lead qualification, scale customer engagement, and gather real-time insights without increasing manual input. The integration of AI in marketing operations is shown to improve campaign management efficiency, enhance personalization capabilities, and facilitate future-focused campaign development. However, the research also addresses the challenges and ethical considerations associated with AI integration in marketing, including data privacy concerns, skill gaps, and the need to balance automation with human creativity. This article provides a comprehensive overview of how AI and ML are reshaping the marketing landscape, offering valuable insights for marketers, researchers, and business leaders navigating this technological revolution.

A Review of Current Research and Future Development of Autonomous Driving Technology

Abstract: At present, the automobile industry is undergoing a new round of technological revolution, and autonomous driving technology is also experiencing a period of rapid development, with very active research and technology iteration. Autonomous driving can prevent accidents that occur due to human errors such as inattentiveness and driver fatigue, thereby enhancing road safety. Additionally, autonomous technology helps alleviate traffic congestion and optimize flow by utilizing coordinated driving strategies, such as vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I), enabling platooning, intelligent rerouting, and other advanced driving techniques. The autonomous driving system can control the vehicle according to the optimal driving strategy, can drive the vehicle in a smoother way, optimize fuel consumption or power use, thereby reducing operating costs and improving travel experience, and has a wide range of application potential and potential social value. This paper summarizes the current research status and development trend of autonomous driving technology, summarizes the current research status of autonomous driving technology from the aspects of environmental perception, machine learning, control execution, etc., while also projecting future directions for the field. Advancements in this technology have the potential to revolutionize transportation, offering significant convenience and transforming daily life. Moreover, it can promote the development of major industries, increase national GDP, affect urban planning and layout, and even improve our living environment and benefit ecological construction.

Role of Artificial Intelligence in IoT

Artificial Intelligence (AI) and the Internet of Things (IoT) are two revolutionary technologies shaping modern industries. AI enables machines to learn from data and make autonomous decisions, while IoT connects devices, allowing them to communicate and exchange information. The convergence of these technologies, known as AIoT (Artificial Intelligence of Things), has immense potential to transform daily life and business operations. AI enhances IoT by adding intelligence to device networks, improving efficiency and automating processes. For example, AI-powered IoT systems can perform predictive maintenance in industrial settings, preventing costly machine failures. In smart buildings, AI can optimize energy usage, reducing both costs and environmental impact. However, integrating AI with IoT poses significant challenges. One major issue is the vast amount of data generated by IoT devices, which AI requires to function effectively. Managing this data efficiently is critical. Additionally, IoT devices are vulnerable to cyber-attacks, making security a key concern. Protecting these systems from potential threats is essential to safely realize the benefits of AIoT. Despite these challenges, the combination of AI and IoT promises to drive future advancements across industries, enabling smarter, more connected systems that optimize decision-making, reduce costs, and improve overall efficiency.

Optimizing university-industry collaboration mechanisms for engineering talent development in the nuclear power sector

In the context of the ongoing scientific and technological revolution and industrial transformation, the primary goal of engineering education is to develop innovative and skilled professionals who can address the evolving needs of economic and social development. The success of this endeavor is contingent upon the effectiveness of university-industry collaboration in creating robust talent cultivation models. This study identifies and constructs key elements of a safeguard mechanism for such collaborations, including laws, regulations, management systems, and operational frameworks. A survey was conducted among university and industry leaders engaged in cooperative projects within the nuclear power sector, revealing significant insights into the current state and deficiencies of existing mechanisms. Based on these findings, the study proposes targeted strategies and recommendations for enhancing the effectiveness of these collaboration mechanisms.

Advances in mRNA LNP-Based Cancer Vaccines: Mechanisms, Formulation Aspects, Challenges, and Future Directions

After the COVID-19 pandemic, mRNA-based vaccines have emerged as a revolutionary technology in immunization and vaccination. These vaccines have shown remarkable efficacy against the virus and opened up avenues for their possible application in other diseases. This has renewed interest and investment in mRNA vaccine research and development, attracting the scientific community to explore all its other applications beyond infectious diseases. Recently, researchers have focused on the possibility of adapting this vaccination approach to cancer immunotherapy. While there is a huge potential, challenges still remain in the design and optimization of the synthetic mRNA molecules and the lipid nanoparticle delivery system required to ensure the adequate elicitation of the immune response and the successful eradication of tumors. This review points out the basic mechanisms of mRNA-LNP vaccines in cancer immunotherapy and recent approaches in mRNA vaccine design. This review displays the current mRNA modifications and lipid nanoparticle components and how these factors affect vaccine efficacy. Furthermore, this review discusses the future directions and clinical applications of mRNA-LNP vaccines in cancer treatment.

The Nexus Between Digital Technology, Innovation, Entrepreneurship Education, and Entrepreneurial Intention and Entrepreneurial Motivation: A Systematic Literature Review

Entrepreneurship Education (EE) is renowned for developing students’ managerial aptitudes, skills, and ideas for self-reliance. The inclusion of digital technology and innovation in EE is necessary to enhance Entrepreneurial Intention (EI) and Entrepreneurial Motivation (EM) for technological revolution and economic development. The aim of the systematic literature review is to (i) identify the current study on digital technologies, innovation, EE, EI, and EM, (ii) highlight how digital technology and innovation shape EE to achieve EI and motivation among students, and (iii) offer new advice on the future EE in a digital era. A search strategy was instituted to ascertain the required publications from Scopus, Web of Science, DOAJ, IEEE, ProQuest, SAGE Journals, Taylor & Francis, and Wiley. The publications were between 2010 and 2024, with no language restrictions. Out of the 108 identified publications from the search, 69 publications representing 54 separate papers were used in the review. Digital transformation in EE requires significant studies to determine its role in economic development and job creation. This review identified several themes in the publications, such as innovation, motivation, skills development, digital technology, EE’s impact, and factors of EE. The sustainability and future expectations of EE through digital technology and innovation are highlighted in the review. The study identified several findings, such as factors depriving EE, such as experience, investment, teachers, infrastructure, technology, market size, government, competition, culture, and funds. Further findings are a strategic vision of EE through policies to embrace innovation and digital technology practices and to achieve EM and EI. Also, the selected papers for the review are current publications at 61.1%, the quantitative method at 42.3% and journal articles at 88.9%. It is prudent to review EE’s appropriateness in a digital and innovative environment and to identify the impact on EM and EI among students.

A model for sustainable development: Advancing digital food retailing

The technological revolution has driven food retail towards self-service technologies (SSTs). The supermarket concept thrived due to consumer convenience and direct food access. This qualitative study explored the modernization of food retail through new technologies, focusing on Canadian stakeholders’ perceptions. Using a grounded theory approach, it aimed to create a sustainable digital food system model addressing social and moral food access aspects. Findings revealed that digitalization in food retail is driven by economic motives and stakeholders’ desire for collaboration and partnership to support food access.

Artificial Intelligence: Intensifying or Mitigating Unemployment?

The rapid development of Artificial Intelligence (AI) is simultaneously fostering a proliferation of novel job opportunities while rendering some traditional roles obsolete and specific skills outdated. Previous research has failed to consider the short-, medium-, and long-term variations in AI’s impact on unemployment, which may lead to an incomplete understanding of the AI-employment relationship. This paper examines daily data from January 4, 2013, to August 12, 2024, utilising advanced wavelet-based Quantile on Quantile Regression (QQR) methodology to assess AI’s impact on the Unemployment Index (UI) across quantiles and time scales, with a sample size of 2820 drawn from a larger dataset totalling 4241 observations. The conclusions reveal that AI generally positively impacts UI in the short term, especially with AI at 0.6-0.7 quantiles, as automation replaces workers faster than new job roles emerge and skills transform. However, in the medium term, positive and negative effects balance as new jobs and skills emerge through continuous industrial restructuring. In the long run, AI predominantly mitigates UI by further enhancing economic development, fostering skill upgrading, and facilitating market adjustments, but this result does not hold during AI at 0.7 quantiles and UI at the highest quantiles, such as Coronavirus Disease 2019 (COVID-19). Under new technological revolution and industrial transformation, we formulate China-specific suggestions to avert potential AI-induced unemployment crisis from short-term, medium-term, long-term, and sector-specific perspectives.

Theoretical design of Z-scheme photocatalyst for water splitting with excellent catalytic performance: GeSe/PtS2 heterojunction

In the face of the urgent need for energy transition, Z-scheme heterojunctions are considered highly suitable candidates for future photocatalytic applications, owing to their exceptional optoelectronic characteristics and high catalytic efficiency. This paper systematically investigates the geometric structure, optoelectronic properties, and catalytic efficiency of the GeSe/PtS2 heterojunction through detailed first-principles calculations. The findings indicate that the band structure of the GeSe/PtS2 heterojunction presents a staggered Type-Ⅱ band alignment and exhibits an indirect band gap measuring 1.75 eV. Charge transfer analysis reveals that under the interplay of an intrinsic electric field directed from GeSe to PtS2 and the band bending occurring at the heterojunction interface, the GeSe/PtS2 heterojunction conforms to the obvious Z-scheme electron transfer mechanism characteristics. This facilitates the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) to proceed smoothly on opposite sides of the heterojunction. Across the pH range of 0 to 14, the heterojunction's band edge positions successfully span the redox potentials of water, and can still meet the hydrolysis potential requirements under strain. In addition, the GeSe/PtS2 heterojunction not only effectively compensates for the poor absorption of PtS2 monolayer to visible light, but also achieves a wider visible light absorption range through the strain-induced redshift in the spectrum. At the same time, the solar to hydrogen (STH) efficiency of up to 15.56% further underscores the substantial catalytic potential of the GeSe/PtS2 heterojunction, offering promising design strategies for a technological revolution in the field of photocatalysis.

Introduction to latent variable energy-based models: a path toward autonomous machine intelligence

Abstract Current automated systems have crucial limitations that need to be addressed before artificial intelligence can reach human-like levels and bring new technological revolutions. Among others, our societies still lack level-5 self-driving cars, domestic robots, and virtual assistants that learn reliable world models, reason, and plan complex action sequences. In these notes, we summarize the main ideas behind the architecture of autonomous intelligence of the future proposed by Yann LeCun. In particular, we introduce energy-based and latent variable models and combine their advantages in the building block of LeCun’s proposal, that is, in the hierarchical joint-embedding predictive architecture.