TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
Scope & Guideline
Forecasting Change, Empowering Progress
Introduction
Aims and Scopes
- Technological Innovation and Its Impact:
The journal emphasizes the examination of technological innovations and their effects on various sectors, including healthcare, energy, and agriculture. It investigates how these innovations can foster economic growth, improve efficiency, and contribute to sustainability. - Interdisciplinary Approaches:
Research published in this journal often employs interdisciplinary methodologies, integrating insights from fields such as economics, sociology, environmental science, and management. This approach helps to understand the multifaceted impacts of technology on society. - Sustainability and Environmental Impact:
A significant focus is placed on the role of technology in promoting sustainability and addressing environmental challenges. Studies often analyze the effectiveness of green technologies and policies in reducing carbon emissions and enhancing resource efficiency. - Digital Transformation:
The journal explores the implications of digital transformation across industries, analyzing how digital technologies reshape business models, consumer behavior, and organizational practices. - Socio-Technical Systems:
Research in this journal frequently addresses the socio-technical dimensions of innovation, examining how social factors, governance, and institutional frameworks influence technological adoption and diffusion.
Trending and Emerging
- Artificial Intelligence and Machine Learning:
There is a growing body of research investigating the implications of AI and machine learning technologies on various sectors, including healthcare, finance, and supply chain management. This trend highlights the increasing integration of AI into business processes and decision-making. - Sustainability and Green Technologies:
Emerging studies are increasingly focusing on sustainability, particularly how technological innovations can contribute to environmental goals, such as carbon neutrality and resource efficiency. This reflects a broader societal shift towards sustainable practices. - Digital Economy and E-Governance:
Research is trending towards understanding the impacts of the digital economy and e-governance on economic performance and citizen engagement, particularly in the wake of the COVID-19 pandemic, which has accelerated digital transformation. - Blockchain Technology:
Blockchain is gaining attention not just for cryptocurrencies but as a transformative technology in various fields, including supply chain management, healthcare, and finance, emphasizing its potential for enhancing transparency and efficiency. - Social Innovation and Community Engagement:
There is an increasing focus on social innovation, particularly how technology can facilitate community engagement and address social issues. This trend aligns with a broader interest in the role of technology in promoting inclusive growth.
Declining or Waning
- Traditional Manufacturing Technologies:
Research related to traditional manufacturing processes has decreased as the focus shifts towards Industry 4.0 and smart manufacturing technologies. The transition to digital and automated processes is overshadowing older methodologies. - Linear Economic Models:
There is a waning interest in purely linear economic models, as the discourse increasingly embraces circular economy principles and sustainability-driven frameworks that consider environmental impacts. - Basic Technological Adoption Studies:
Studies focusing solely on the basic adoption of technologies without considering contextual factors, such as social influence or environmental impact, are becoming less prevalent as researchers seek more nuanced analyses. - Sector-Specific Innovations:
Research concentrating on isolated sector-specific innovations, such as those limited to one industry, has diminished in favor of cross-sectoral studies that emphasize interconnectedness and systemic changes. - Short-Term Forecasting Models:
The emphasis on short-term forecasting models has decreased, with a growing preference for long-term scenarios that incorporate broader socio-economic and environmental factors.
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