World's Best Scientists 2026 revealed!
Technological Forecasting and Social Change
H-index 127

Technological Forecasting and Social Change

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Business and Management 2 273 556 97

Additional Metrics

Number of Best Scientists*: 629
Documents by Best Scientists*: 1061
Top 100 Ranked Scientists*: 38
SCIMAGO H-index: 209
SCIMAGO SJR: 3.472
Impact Factor: 13.3

Overview

Top Research Topics at Technological Forecasting and Social Change?

Technological Forecasting and Social Change focuses on Marketing, Knowledge management, Industrial organization, Process (engineering) and Context (language use). The Knowledge management study tackled is a key component of adjacent topics in the area of Futures studies. Research on Process (engineering) addressed in the journal frequently intersections with the field of Management science.

  • Marketing (13.54%)
  • Knowledge management (12.05%)
  • Industrial organization (10.55%)

What are the most cited papers published in the journal?

  • The future of employment: How susceptible are jobs to computerisation? (2429 citations)
  • Functions of innovation systems: A new approach for analysing technological change (1596 citations)
  • A simple substitution model of technological change (883 citations)

Research areas of the most cited articles at Technological Forecasting and Social Change:

The most cited publications explore disciplines such as Marketing, Knowledge management, Management science, Process (engineering) and Industrial organization. The most cited articles link adjacent topics like Knowledge management with Context (language use). The studies on Management science discussed at the most cited publications can also contribute to research in the domains of Delphi method, Delphi and Futures studies.

What topics the last edition of the journal is best known for?

  • World War II
  • Law
  • China

The previous edition focused in particular on these issues:

Technological Forecasting and Social Change investigates areas of study like Context (language use), Knowledge management, Industrial organization, Process (engineering) and Perspective (graphical). Context (language use) research featured in it incorporates concerns from various other topics such as Production (economics), Sustainability, Subsidy and Economic geography. Digital transformation, Dimension (data warehouse) and Openness to experience are some topics wherein Knowledge management research discussed in it have an impact.

Issues in Industrial organization were discussed, taking into consideration concepts from other disciplines like Mergers and acquisitions, Wind power, High tech, Renewable energy and Sample (statistics). The studies on Process (engineering) discussed can also contribute to research in the domains of Corporate governance and Product (category theory).

The most cited articles from the last journal are:

  • Investigating the spill overs and connectedness between financial globalization, high-tech industries and environmental footprints: Fresh evidence in context of China (2 citations)
  • The effects of government subsidies on the sustainable innovation of university-industry collaboration (1 citations)
  • Facing transition phase two: Analysing actor strategies in a stagnating acceleration phase (1 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Technological Forecasting and Social Change (based on the number of publications) are:

  • Harold A. Linstone (159 papers) absent at the last edition,
  • Joseph F. Coates (116 papers) absent at the last edition,
  • Joseph P. Martino (61 papers) absent at the last edition,
  • Alan L. Porter (41 papers) absent at the last edition,
  • Robert U. Ayres (31 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Technological Forecasting and Social Change (based on the number of publications) are:

  • Utrecht University (85 papers) published 1 paper at the last edition, 2 less than at the previous edition,
  • Portland State University (69 papers) published 1 paper at the last edition, 5 less than at the previous edition,
  • Chinese Academy of Sciences (68 papers) published 1 paper at the last edition, 12 less than at the previous edition,
  • Delft University of Technology (67 papers) absent at the last edition,
  • National Research University – Higher School of Economics (67 papers) published 1 paper at the last edition, 9 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2022 edition, 29.76% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.56% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.78% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.25% of all publications and 64.41% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities and Future Scope in Technological Forecasting and Social Change

The multidisciplinary nature of the research areas in 'Technological Forecasting and Social Change' opens up numerous career opportunities. Scholars can opt for marketing roles where they can utilize knowledge management skills and employ their understanding of industrial organizations. There are also promising career paths in Management Science and Industrial Engineering, which are in high demand in the corporate sector. Moreover, the intersection of these fields with futures studies enables professionals to devise long-term strategic plans for businesses and economies. Such aptitude is particularly valuable in institutions focused on policy planning, economic development, and business strategy. The constant evolution of technology also ensures that new avenues will continue to open up. For instance, the onset of digital transformation and data warehousing has seen a surge in demand for expertise in areas like Knowledge Management. Similarly, growing consciousness about sustainability has driven the significance of fields like Renewable Energy and Economic Geography. This multidisciplinary approach adopted by the 'Technological Forecasting and Social Change' thus not only widens the academic and research horizons of the scholars, but their professional and career opportunities as well. For individuals looking to pursue higher studies in these areas, certain institutions like the great business schools in Missouri offer specialized degrees in these subjects. Given the robust career prospects and continuous advancements in technology, future scope in these research fields appearing in 'Technological Forecasting and Social Change' look promising.

Top Publications

  • Green innovation and environmental performance: The role of green transformational leadership and green human resource management

    Sanjay Kumar Singh;Manlio Del Giudice;Manlio Del Giudice;Manlio Del Giudice;Roberto Chierici;Domenico Graziano

    (2020)
    1257 Citations
  • CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting

    Ganesh Dash;Justin Paul;Justin Paul

    (2021)
    964 Citations
  • Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process

    Gianluca Elia;Alessandro Margherita;Giuseppina Passiante

    (2020)
    940 Citations
  • Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries

    Amine Belhadi;Sachin Kamble;Charbel Jose Chiappetta Jabbour;Angappa Gunasekaran

    (2021)
    790 Citations
  • Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises

    Unknown

    (2022)
    755 Citations
  • Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities

    Surajit Bag;Jan Ham Christiaan Pretorius;Shivam Gupta;Yogesh K. Dwivedi

    (2021)
    731 Citations
  • Analyzing the relationship between green innovation and environmental performance in large manufacturing firms

    Shafique Ur Rehman;Sascha Kraus;Syed Asim Shah;Dmitry Khanin

    (2021)
    652 Citations
  • Corporate social responsibility and environmental performance : the mediating role of environmental strategy and green innovation.

    Sascha Kraus;Shafique Ur Rehman;F. Javier Sendra García

    (2020)
    646 Citations
  • The relationship between digitalization and servitization: The role of servitization in capturing the financial potential of digitalization

    Marko Kohtamäki;Vinit Parida;Vinit Parida;Pankaj C. Patel;Heiko Gebauer

    (2020)
    483 Citations
  • Artificial intelligence and innovation management: A review, framework, and research agenda✰

    Naomi Haefner;Joakim Wincent;Joakim Wincent;Vinit Parida;Vinit Parida;Vinit Parida;Oliver Gassmann

    (2021)
    403 Citations

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