Technological Forecasting Research Articles

Application of Multimodal Logistics for the Use of Demolition Products for Damaged Areas

The relevance of the problem under study is due on the one hand to the need to reclaim disturbed areas formed as a result of construction activities, on the other hand to the need to find useful use of demolition products of buildings and structures. The purpose of the work is to study the possibility of using multimodal logistics for the use of demolition products in the reclamation of disturbed areas, using the example of granite quarries. Geoecological, technological and economic forecasting of multimodal logistics of urban agglomeration demolition products will allow to develop the most optimal schemes of their useful use. As a result of research, mathematical models have been developed for predicting the formation of a transport and logistics chain for the removal of demolition products from objects. For the first time, a scheme has been developed for choosing a method of moving demolition products depending on the range of the burial place for making substantiating decisions on their removal in the process of designing measures for the reclamation of granite quarries from the point of view of geoecological and economic expediency. It is scientifically justified to use demolition products as fillers of spent granite quarries for temporary storage, partial or complete filling with subsequent reclamation of spent quarries. The materials of the article can be useful for the development of technological solutions for the reclamation of disturbed areas using demolition products of buildings and structures.

Design and Evaluation of Two-Stage Membrane-Separation Processes for Propylene-Propane Mixtures.

Propylene is industrially produced in a mixture with propane and generally separated from the mixture via distillation. However, because distillation is an energy-consuming process, a more efficient separation process should be developed to mitigate both carbon dioxide (CO2) emissions and production costs. In this study, a two-stage membrane-separation process was designed, and its CO2 emission and production costs were evaluated. The separation processes were designed to minimize energy consumption using different membrane combinations (two recently developed membranes each). To evaluate the separation processes using various membrane combinations, two indicators, i.e., CO2 emissions and total annual costs (TACs), were estimated based on the process simulation (Pro/II, version 10.1.1) results, including energy consumptions, operation expenditure, and capital expenditure. These results were compared to the distillation processes as benchmarks, and the advantages of the membrane-separation process were discussed. In the comparison, carbon taxes were implemented for assessing these two independent indicators as a single indicator, i.e., TAC with carbon tax. Furthermore, using the same scheme, model membranes were also employed in the two-stage membrane-separation process as case studies of technological forecasts.

Societal Technological Megatrends: A Bibliometric Analysis from 1982 to 2021

This article presents a bibliometric analysis of scientific publications investigating technological megatrends at the societal level, through the parallel analysis of 549 documents from Scopus and 291 documents in Web of Science (WoS) using the VOSviewer software and the Excel component of the MS Office 365 package. The main purpose of this study was to obtain an overview of the evolution of the research on the subject of technological megatrends from the perspective of interest, domains, geographical areas, sources, authors and cocitation networks, research clusters of countries, and cluster-related concepts. The results showed that publications on technological megatrends started in 1982, but from a scientific point of view they started in 1983 (Scopus) and 1984 (WoS), and that they display an increasing trend after 2010. Technological Forecasting and Social Change, Nature, SAE Technical Papers, VDI Berichte, Harvard Business Review, Advances in Intelligent Systems and Computing, and Sustainability represent the most important sources, and Gibbs, Kraemer, Dedrick, Kim, Chmiela, Sauceda, Müller, Tkatchenko, Pratt, Sarmiento, Montes, Ogilvie, Marcus, Perez, Brownson, D. Mourtzis, M. Doukas, and Bernidaki are the most notorious researchers in the field. At the societal level, technological megatrends are closely related to foresight, globalization, industry 4.0, the internet of things, digitalization, technology, artificial intelligence, innovation, the future, and sustainability. This study is original and useful for researchers in the context of the lack of similar studies on this subject.

Preliminary design and technology forecast synthesis for solar-powered high altitude aircraft

High altitude long endurance solar aircraft is a very attractive platform for applications ranging from remote sensing to telecommunication. In contrast to conventional aircraft, the operation of solar-powered one is highly dependent on available solar enengy, which imposes strong constraints on total takeoff mass, and, thus, energy balance becomes dependent on the season and latitude of planned operations. Despite tremendous success in many projects from Helios to Zephyr, energy balance at high altitudes is still not favorable in a range of latitudes and seasons. In this study, a design space for a solar-powered aircraft mission, constrained by its energy balance is explored. It is found that the tradeoff that should be made between seasonal and spatial capabilities for continuous flight of a solar-powered aircraft. The influence of key technologies on solar aircraft perpetual flight capabilities in different regions and seasons is identified. To do that, solar cell efficiency and energy storage specific energy are considered as design parameters in range of available forecasts. In the end, available technology forecasts are synthesized on the precision agriculture case to show which technological level is required to make 6 moths mission possible.

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

Technology Forecasting of Unmanned Aerial Vehicle Technologies through Hierarchical S Curves

This study aims to propose a technology forecasting approach based on hierarchical S-curves. The proposed approach uses holistic forecasting by evaluating the S-curves of sub-technologies as well as the main technology under concern. A case study of unmanned aerial vehicle (UAV) technologies is conducted to demonstrate how the proposed approach works in practice. This is the first study that applies hierarchical S-curves to technology forecasting of unmanned aerial vehicle technologies in the literature. The future trend of the UAV technologies is analysed in detail through a hierarchical S-curve approach. Hierarchical S-curves are also utilised to investigate the sub-technologies of the UAV. In addition, the technology development life cycle of technology is assessed by using the three indexes namely, (1) the current technological maturity ratio (TMR), (2) estimating the number of potential patents that could be granted in the future (PPA), and (3) forecasting the expected remaining life (ERL). The results of this study indicate that the UAV technologies and their sub-technologies are at the growth stage in the technology life cycle, and most of the developments in UAV technology will have been completed by 2048. Hence, these technologies can be considered emerging technologies.

Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model

• The paper presents a longitudinal analysis of the content and topics of the journal technological forecasting and social change. • There are clear bureaus or tranches of literature in the journal corresponding to its long-term mission of technological forecasting and of technology assessment. • The paper demonstrates the use of the non-negative matrix factorization technique on text data. • The paper demonstrates a hierarchical structure of topics is present in the technological forecasting and social change literature, and that this hierarchical structure can be identified through introspection of topic analysis matrices. This article examines the knowledge structure of the journal Technology Forecasting and Social Change (TFSC) from its inception in 1969 until 2020. In this paper we argue that the structure of knowledge in the field of technological forecasting is more complex than a topic model – a bag of words – can in fact effectively reveal. Therefore we propose and demonstrate a hierarchical model that selectively combines topics at varying levels of generality. The resultant analysis, which is based on non-negative matrix factorization, reveals four distinct branches of technology forecasting work, composed of seven distinct topics. Each topic and branch are examined individually through a detailed examination of terms and keywords. Representative works and authors in each of the branches are also identified. The method enables the examination of the complex structure of knowledge in a scientific journal in a succinct representation. The resultant analysis can assist future researchers, enabling them to better position their work, and to better identify the key references across the various subject silos.

Forecasting Directions, Dates, And Causes of Future Technological Revolutions concerning the Growth of Human Capital

Technology forecasting is an important and critical issue that determines the starting point of planning and is considered as a management tool directly related to the future. In the previous research items, the development of renewable energy technologies was of concern. Moreover, due to the increasing need of countries to produce electricity and facing the lack of resources, this research focuses on forecasting photovoltaic technology. Accordingly, in this paper, for technological research in the field of solar energy, the patents extracted from one of the most famous renewable energy databases in the United States (US patent database) between 200 and 2020 were examined. Next, research gaps were analyzed by using the artificial neural network clustering method and also by analyzing covered and uncovered compounds. The results show that in the future, photovoltaic technology research will move towards the third generation of technology (organic materials) as well as focus on environmental parameters and their effects on the performance of photovoltaic systems.

Technology Forecasting and Roadmapping of Intelligent Manufacturing by 2035

Technology Forecasting and Roadmapping of Intelligent Manufacturing by 2035

Development Forecast of Energy Storage Technology: A Case Study of Chemical Energy Storage in China

Development Forecast of Energy Storage Technology: A Case Study of Chemical Energy Storage in China

Research on cost prediction of civil engineering construction based on multi-dimensional data mining

The accuracy of the cost prediction of civil engineering is an important step in the refined management of modern civil engineering. Therefore, a research on the cost forecast of civil engineering based on multi-dimensional data mining is proposed, which combines data mining technology and cost forecasting. Based on the results of data mining, the predictive data is preprocessed, and the factor that has the greatest impact on the cost is screened out, which is the installation cost of the building in the project. And design a fitting function to preprocess the data. Establish a civil engineering cost prediction model. The first step is to determine historical indicators, search for corresponding historical data based on actual engineering data, and transform the prediction characteristics of the data, and finally complete the civil engineering cost prediction, and finally prove it through test experiments. The method’s engineering cost prediction accuracy is relatively high.

The Effect of Several Factors on Inclusive Growth in the Coastal Village – Badung

The purpose of this research is to understand the role of government, social entrepreneurship, and utilization of information & communication technology on the performance of BUMDes and Inclusive growth in a coastal village, Badung regency. The primary data used here include the perceptions of villagers in the coastal village of Badung Regency, Bali Province, while the secondary data used consists of GRDP, per capita income, poverty, open unemployment and others. The location of research was carried out in the coastal village of Badung Regency, with a total of 16 villages. Village samples were taken using a systematic sampling method. The population in this study was 13,730 people and 200 (two hundred) people were sampled from this population. The population sample was taken using the proportional purposive sample method. The data analysis technique used is a structured equation model (SEM) assisted by path analysis. The results of the research are based on the results of data analysis namely 1) The role of government, and social entrepreneurship has a positive and significant effect on the use of ICT, 2) The role of government, social entrepreneurship, ICT has a positive and significant effect on BUMDes performance, 3) The role of government, social entrepreneurship, ICT, performance BUMDes has a positive and significant effect on inclusive growth, 4) the role of government, social entrepreneurship has a significant indirect effect through the use of ICT on BUMDes performance, 5) the role of government, social entrepreneurship has a significant indirect effect through ICT on inclusive growth, and 6) the role government, social entrepreneurship, ICT have a significant indirect effect through BUMDes performance on inclusive growth. Reference BPS, Indonesia. (2019). Statistik Idonesia (2019). Rilis 4 Juli (2019) (00.01 WIB) Revisi 1, 4 Juli (2019). BPS – Provinsi Bali. (2019). Laporan Bulanan Data Sosial Ekonomi Desember (2019). Dwipayanti, K., & Kartika, I. N. (2020). Pengaruh Modal, Pengalaman Kerja dan Lama Usaha Terhadap Produktivitas Serta Pendapatan BUMDes di Kabupaten Bandung. E-Jurnal EP Unud, 9(2), 354–382. Ghozali, Imam. (2006). Analisis Multivariate Dengan Program SPSS, Semarang: Badan Penerbit Universitas Dipenogoro. Hanna, N. A role for the state in the digital age. J Innov Entrep7, 5 (2018). https://doi.org/10.1186/s13731-018-0086-3. Negoro, Abul H. S. (2019). Inovasi BUMDES dalam Pengelolaan Potensi Kewirausahaan Masyarakat Pesisir, Prosiding F. ISIP. http: // repository. unej.ac.id/ handle/ 123456789/89835. Kadek, , Candra, D., Sinarwati, N. K., & Arie, M. (2017). Efektivitas pengelolaan dana pada badan usaha milik desa kerta danu mandara di desa songan a. E-Journal S1 Ak Universitas Pendidikan Ganesha, 8(2), 1–10. Nicholls, A. (2006). Introduction. In A. Nicholls (Ed). Social Entrepreneurship: New Models of Sustainable Chage, Oxford: Oxford University Press. Pradnyani, S. P. (2019) Peranan Badan Usaha Milik Desa (Bumdes) Dalam Meningkatkan Kesejahteraan Masyarakat Di Desa Tibubeneng Kuta Utara, Sintesa Prociding, Universitas Dhyana Pura, Badung. Saskara dan Marhaeni (2017). The Role of Social Capital and Business Strategies in Developing the Business of Banten to Increase Balinese Women’s Employment. Journal of Comparative Asian Development, Vol. 16, Issue 1. https://doi.org/10.1080 /15339114.(2017). 1292930. Yoon, H., Yun, S., Lee, J. and Phillips, F. (2015). Entrepreneurship in East Asian Regional Innovation Systems: Role of Social Capital, Journal Technological Forecasting and Social Change, 100, pp. 83–95. doi: 10.1016/ j. techfore. (2015).06.028. Yunis et al. (2018). The role of ICT and innovation in enhancing organizational performance: The catalysing effect of corporate entrepreneurship. Journal of Business Research, 88 (2018) 344-356.

제품-기술로드맵 개발을 강화하기 위한 예측모델링에 관한 실증 연구

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

Tension in the data environment: How organisations can meet the challenge

Big Data is becoming ubiquitous - widely applied across organisations, industry sectors and society. However, the opportunities and risks it presents are not yet fully understood. In this paper we identify and explore the tensions that Big Data can create at multiple levels, focusing on the need for organisations to meet the challenges that can arise. We draw on insights from twelve papers published in the Special Issue of Technological Forecasting & Social Change entitled “Tension in the Data Environment: Can Organisations Meet the Challenge?” in order to build a ‘Multi-Layer Tensions Model’ that highlights key pressures and challenges in the BD environment. We find evidence of tensions of three types, which we summarise as “Organisational Learning”, “Organisational Leadership” and “Societal” tensions. We contribute, first, by identifying and developing a nuanced understanding of the tensions faced in the Big Data environment; and second, by elaborating on the capabilities that can be developed and the actions taken to maximise the benefits of Big Data. We end with a “Learning, Leading, Linking” framework, which points to implications for practice and a future research agenda.

The Future of Hybrid and Inorganic Perovskite Materials: Technology Forecasting

Perovskite (PSK) materials have received extensive attention because of their potential use as the active layer of different applications, including capacitors, sensors and detectors, memories, catalysts, fuel cells, and optoelectronic devices (solar cell and light‐emitting diode). Herein, the past, current, and future status of these applications are focused on. The state of each application is investigated using diverse technology indicators. It reveals that among all the applications, the optoelectronic application is the youngest one and has not yet reached the technology growth stage though it possesses most of the recently published patents. Using a technology investment potential evaluation method, the most potent area for investment is explored, indicating that detectors and sensors are the ones with the biggest investment potentials. Remarkably, PSK solar cell dedicates more than 70% of the patents to itself with the highest predicted efficiency of 30% that will be achieved in 2023 according to the curve fitting method and in 2030 according to the S‐curve method. As a perspective, currently, the highest efficiency and stability are achieved for small‐sized PSK solar cells, it is expected that they would be commercialized in electronic equipment applications first, and after overcoming the challenges, large‐scale modules would enter the markets.

Identifying the Market Scenarios for Supercritical CO2 Power Cycles

Abstract The technology management methods and the “technology foresight” allow organizations and stakeholders in a particular market/sector to create an advantage out of technological breakthroughs, sustain and expand technological competitiveness, and identify and evaluate new technological options. Several concepts are used depending mainly on the actual status of an evaluated technology. To identify the status of the supercritical carbon dioxide (sCO2) power generation technologies, an extensive “technology exploration” task was performed by creating a technology profile through collecting a database. This allowed for creating technological forecasts “scenario approach” for the sCO2 power cycles. In this article, the sCO2 power technology is explored, evaluated in relation to current commercial competitive power generation technologies, and forecasted to give an insight into future trends of the novel sCO2 power cycle in the future market. The outcome is the analysis of qualitative and quantitative data of the sCO2 technology for short- to long-term forecasts, which could help identify the economic and market value of the sCO2 power cycle. Three possible market scenarios were identified and combined with a survey distributed among experts to assess different market penetration levels of the sCO2 technology.

ІННОВАЦІЙНЕ ПІДПРИЄМНИЦТВО В УМОВАХ ОБМЕЖЕНЬ І КРИЗИ

The report of the World Intellectual Property Organization (WJPO) for 2020 statistically confirms the connection between the global financial crises and falling spending on research and development. The purpose of this article is to systematize and content analysis of financial and information-cognitive limitations of the emergence and formation of innovative small businesses in crisis and post-crisis periods. The study shows that, first, the investment of the business sector in research and development is more stable than in government agencies. This is due to the fact that during the crisis the state is forced to expand the general support of the population and the most affected part of the business, including small businesses. Second, investment in research and development and innovation are the basis for further economic recovery and growth. Third, before the COVID-19 pandemic, the global economy had not yet fully recovered from the 2008 financial crisis. This affects the innovative activity of small businesses. In the face of ongoing crises, small innovative enterprises face different types of constraints and barriers. In particular, it is the reduction of venture capital and the share of the state in the financing of research and development, as well as the transfer of knowledge on high-tech technologies. The government’s solution to the problem with the help of industrial parks requires a more detailed technological foresight analysis. In developed countries, in addition to the expert opinions of the scientific, business and political communities, the population is encouraged, taking into account their views on technology prospects and the state of the environment. Accordingly, sufficient technological literacy and cognitive ability of the population is assumed. Technological literacy of entrepreneurs who are going to use high-tech and especially breakthrough technologies must be above the amateur level. In the future, it is planned to conduct a content analysis of existing technological foresight forecasts.

Does the method for Military Utility Assessment of Future Technologies provide utility?

The Military Utility Assessment of Future Technologies (MUAFT) method was developed as a cost-efficient alternative to methods such as NATO's Disruptive Technology Assessment Games, to be used as a part of the Swedish Armed Forces' long-term capability development process. The question addressed in this study is whether MUAFT can be considered to have validity in its context and thus if it has potential to be useful to other small to medium size states. The analysis was based on an operationalization of Clark's framework for science and technology intelligence analysis, combined with a military capability centric view of military utility. MUAFT reports from 2012 to 2018 were reviewed in terms of how they satisfy five key criteria. The study shows that MUAFT provides utility, if used by a suitably composed group of experts, who are aware of the method's limitations. The limitations mainly originate from a lack of explicit support for assessing the impact of forces for change, other than technological forces, on military capability development. The expert group serves as the synthesizing bridge between technology forecasts and military utility assessments. Therefore, comprehensive expertise is needed in various military technology specialisations, in the sponsor's military capabilities and in subjects necessary to master in order to assess other influential societal forces for change.

A tailored-fit model evaluation strategy for better decisions about structural equation models

Proper measurement of technology knowledge and social change enables managers to advance strategies in technology management. Structural equation modeling is the ideal method in Technological Forecasting and Social Change (TFSC) and other leading journals to assess the measurement quality of the relevant decision variables and understand how they are related. However, a myriad of indicators are now available to judge how suitable these measurements are (i.e., how well they fit). Despite a consensus that fit indicators are highly context-dependent and no “one-fits-all approach” emerges, a more contingent perspective is surprisingly missing. To fill this gap, we advocate for a “tailored-fit model evaluation strategy” that is specific to the situation at hand to exploit the particular strengths of fit indicators. Motivated by a synthesis of structural equation modeling in TFSC, our simulation study finds that three critical distinctions regarding (a) model novelty, (b) focus on measurement or structural models, and (c) sample size are vital. The proposed strategy demonstrates that, in many contexts, only a few indicators are recommended to avoid artificially inflated Type I/II errors. We provide a decision tree to reach more accurate decisions in model evaluation in order to better theorize and forecast technological and social challenges.

Ferrous Metallurgy Production in Russia: How Will the COVID-19 Pandemic Affect?

Metallurgy is one of the key industries both in Russia and in the world. It has a significant influence on the situation in related industries. Therefore, the current state analysis of ferrous metallurgy production and its formation based on the short-term technological forecast is essential. Based on the foregoing, the research was aimed at analyzing the current state of ferrous metallurgy production in Russia and the impact of the COVID-19 pandemic on the prospects for industry development in the short term. The research studies the state of the ferrous metallurgy production in Russia and abroad before the COVID-19 pandemic, as well as the volume of industrial production in ferrous metallurgy and the industry structure. The COVID-19 pandemic has triggered a serious global recession, necessitating an analysis of the forecast for the development of the ferrous metallurgy industry. The research concludes that the Russian ferrous metals market is so far affected to a lesser extent compared to the European one.