Technological Forecasting at the Stock Market

Under the assumption that competition (Darwinian in nature) reigns in the stock market, we analyzethe behavior of company stocks as if they were species competing for investors’ resources. The approachrequires the study of dollar values and share volumes, daily exchanged in the stock market, via logistic growthfunctions. These two variables, in contrast to prices, obey the law of natural growth in competition, which likeevery natural law, is endowed with predictability. A number of unexpected insights about the stock marketemerge. The forecasts indicate that whereas there is no looming crash in the near future, no significant growthshould be expected either. The DJIA is to hover around 9500 depicting large erratic excursions above andbelow this level for a few years. The use of Volterra-Lotka equations demonstrates that the 1987 crash alteredthe stock-bond interaction from a symbiotic to a predator-prey relationship with stocks acting as predators. This research work has lead to the publication of the book "An S-Shaped Trail to Wall Street" by T. Modis,(Growth Dynamics, Geneva, 1999).

A Second Lease on Life for Technological Forecasting

According to the metaphor of the business seasons developed by T. Modis in his book "Conquering Uncertainty" the Journal (TF&SC), which is celebrating its 30th anniversary this year, is traversing a "fall" season. In fall seeds are put in the ground for the next season's crop. A promising such “seed” for a new generation of technological-forecasting activities is biology-related studies.

Industry 4.0 whithin Innovation: Bibliometric Analysis

Introduction: the purpose of this research is to analyze the relationships and growth trends of Industry 4.0 within the global universe of current literature on innovation, limited to the subject area of business, administration, and accounting by means of a bibliometric analysis. Method: Scopus is used as a database for the analysis of 513 documents for the period from 1998 to 2021. VOS viewer was used for processing Scopus database and elaboration of figures representing the relationships between samples. Results: the number of documents is exponentially growing, starting with a trend in 2017 and increasing ever since. The most dynamic source is Technological Forecasting And Social Change. The author with most documents is Voight, K. L. with 10, and the most distinguished institution is the University of Johannesburg with 14 documents. The country with more documents is Italy, with 69. According to the database 69 % of the total documents are articles and 23,4 % are conference papers. The number of documents in the area of Business, Management and Accounting, with 513 documents, exceeds by far any other area, representing 42 % of all documents. The funding sponsor with more documents is the National Natural Science Foundations of China with 13 documents. Some of the most updated organizations are Department of Mechanical & Industrial Engineering, The center for digital labor markets. The country with more documents is United Kingdom with 50 documents and 584 citations, followed by United States with 1110 citations. United States has mainly bonds with China, Australia, United Kingdom, Germany and Italy. United Kingdom has mainly bonds with France, Italy, Germany and United States. China’s main relations are Australia, United States, Pakistan, Taiwan, Turkey, Brazil and South Korea. Italy’s main bonds are France, Spain, Brazil, Russian Federation, United Kingdom, Austria and Portugal. It could be determined that countries are mostly grouped in 6 clusters. Conclusion: Although there are not many publications yet, it can be inferred that the term industry 4.0 within the available literature of innovation will keep increasing exponentially over time reinforcing relations between authors, institutions and countries. Based on the current state of literature, the subject area of business, management, and accounting will keep on being the one that encompasses most of the available documents.

Mapping Innovation Diplomacy in Denmark and Sweden

Summary The aim of this article is to identify and map innovation diplomacy actions in Denmark and Sweden using the ‘functions of innovation systems’ approach. Based on Hekkert et al.’s seven key system functions (Marko P. Hekkert, Roald A. A. Suurs, Simona O. Negro, Stefan Kuhlmann and Ruud E. H. M. Smits, ‘Functions of Innovation Systems: A New Approach for Analysing Technological Change’, Technological Forecasting & Social Change 74 (4) (2007), 413-432), the article assess the role of the Ministry of Foreign Affairs (MFA) in meeting governments’ innovation targets. The empirical analysis, including twelve semi-structured interviews with seventeen career diplomats, reveals the key initiatives that countries are taking in furthering their homeland’s innovation aims or ambitions. The study also asks whether the ‘diplomacy for innovation’ approach of both Scandinavian MFAs are consistent with the ‘whole-of-government’ and ‘whole-of-society’ approaches.

Using ontology in scientific and technological forecasting

The case is made and proposals are drawn for the development of ontologies of scientific and technological forecasting to secure national interests based on the descriptions of expertise in the forecast domain and the methodology of concept maps. Concept maps of scientific and technological advances are visualised and applicability is described for ontological methods in scientific and technological forecasting, as well as the specifics of automation. The novel contribution of the research findings consists in the authors' systemic and comprehensive approach in describing the ontological principles of scientific and technological forecasting to secure national interests. This eliminates the ambiguity in approaches and conceptualisations of the processes of scientific and technological forecasting. The proposed ontological system of scientific and technological forecasting to secure national interests offers a systemic approach to forecast development and uniform interpretations of the concepts involved. All that would doubtlessly contribute to quality forecasting.