Technological Complementarities Research Articles

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry's transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry's markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

Online energy management strategy for ammonia-hydrogen hybrid electric vehicles harnessing deep reinforcement learning

Powertrain electrification and fuel decarbonization play pivotal roles in the pursuit of carbon peak and carbon neutrality within the realm of transportation. Ammonia and hydrogen are essential carbon-neutral fuels suited for deployment in heavy-duty, long-haul transportation applications. The technological complementarity of ammonia and hydrogen can be realized in the current context by combining various energy conversion devices. Energy management strategy (EMS) is one of the critical technologies in hybrid systems. In this study, a novel EMS based on deep reinforcement learning (DRL) is proposed for a heavy-duty automotive hybrid system containing an ammonia-hydrogen internal combustion engine (ICE), a fuel cell system (FCS), an ammonia electrolysis cell (AEC), and Li-ion batteries (LB). To address the protracted training times and convergence challenges intrinsic to DRL, a fuzzy logic control (FLC) is introduced to provide expert demonstrations during the DRL agent's learning process. The incorporation of FLC not only facilitates the convergence speed of the DRL algorithm, but also strikes a good balance between the operation efficiency improvement and battery SOC maintenance. The simulation results show that the proposed EMS improves average efficiency by 2 % with a modest 0.75 % SOC reduction across four operational scenarios compared to the FLC-based EMS. After thorough validation of the proposed EMS, a parametric study is conducted to examine three key parameters: charge mode threshold, FCS power change rate limit, and hybrid mode threshold. The study aims to offer valuable insights for formulating the EMS of the ammonia-hydrogen hybrid system.

Evolutionary game analysis on cross-border cooperative R&D of intelligent new energy vehicle industry

PurposeIntelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.Design/methodology/approachThe authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.FindingsResults showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.Research limitations/implicationsThe research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.Originality/valueThe INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

How do New Ventures Thrive in Ecosystem Venturing: The Impacts of Alliance Strategy and Technology Interdependence

AbstractNew ventures in an innovation ecosystem can not only receive benefits, but also face challenges. It is important to examine defence mechanisms that new ventures can employ for their healthy development in the innovation ecosystem. Based on resource dependence theory, combining with arguments from innovation ecosystems literature, this paper proposes that new ventures’ technological alliances with core competitors of ecosystem investors can be used as a social defence in ecosystem venturing. Furthermore, we investigate the moderator effects of technological interdependence – technological similarity and technological complementarity on the impacts of such a defence mechanism. Using longitudinal information of 4903 investor‐investee dyads in ecosystem venturing, we find that (1) technological alliances with core competitors of the ecosystem investor has a positive relationship to venture performance, and (2) such relationship is negatively moderated by technological complementarity. Our findings provide important implications for research on innovation ecosystems and resource dependence theory.

Symphony of sustainability: how technology similarity impacts international trade patterns in environmental goods.

The global consensus on sustainable development and environmental cooperation has prompted the promotion of trade in environmental goods (EGs) for green growth. This study delves into the diversity of EGs trade patterns, using decomposed environmental technology similarity indicators to reveal the technological drivers. Linking innovation indicators to trade performance in EGs provides new insights into the determinants of inequality in environmental governance cooperation. Based on an extended gravity model, we empirically analyze their impact on bilateral EGs trade flows among 176 countries over the period 2002-2019. The study finds that (1) the global EGs trade network presents a "core-periphery" structure, with increased network density and participation of developing countries. (2) Technology similarity contributes significantly to EGs trade. Compared to competition, technology complementarity has a greater impact on EGs trade flows. (3) The influence of technology similarity varies across trade patterns and product complexity explains the mechanisms, with technology complementarity promoting more trade in high-complexity products, mainly concentrated in the trade from Northern countries, while technology competition greatly promotes the export of low-complexity products from the South. (4) Technology similarity helps to overcome information barriers in EGs trade, and its trade-enhancing effects exhibit geographical regionalization. The findings offer empirical evidence on the technological drivers of EGs trade and provide policy implications for fostering inclusive global environmental governance and enhancing the competitive advantages of Southern countries, fostering more opportunities for green growth.

The Informational Role of Artificial Intelligence in higher Education in the New era

The advent of artificial intelligence (AI) technology has ushered in an era of intelligent education, catalyzing profound changes in teaching methods and reshaping the roles of educators. This paper explores the intricate relationship between technology, education, and teachers by drawing upon relevant theories from the field of technological sociology, particularly the concept of "one skill for one person." It scrutinizes the evolving role of teachers in the context of artificial intelligence, delving into the mechanisms that underpin their functions in this rapidly evolving educational landscape. Through a historical examination of educational technology innovation, this paper delineates a three-tiered transformation in the relationship between artificial intelligence and university teachers, spanning from "technology exclusion" to "technology complementarity" and finally to "technology dependence." The paper used a mixed-methods strategy, combining qualitative and quantitative approaches. These phases illustrate the evolving synergy between human educators and AI, ultimately contributing to the modernization of the educational system and the enhancement of educational capabilities. This research sheds light on how the integration of AI can enhance the educational experience and empower educators, ensuring the continued advancement of education in the digital age.

НОВІ ТЕХНОЛОГІЇ ПЕРЕХОДУ ДО ЦИРКУЛЯРНОЇ ЕКОНОМІКИ В ЛАНЦЮЖКУ СТВОРЕННЯ ВАРТОСТІ ПЛАСТИКОВИХ МАТЕРІАЛІВ

Plastic waste has risen to the forefront of scientific and political debate as a global problem that needs to be addressed urgently. The circular economy model, supported by politicians, academics and corporations, represents a viable pathway to achieving a more sustainable level of development. New and disruptive technologies can accelerate the transition to a circular economy, but their application to the plastics transition is not yet fully understood. Based on a systematic literature review, this paper aims to understand the role of key emerging technologies in the transition to a circular economy in the plastics value chain, their potential impact, and the barriers to their adoption and diffusion. Using the ReSOLVE framework, the analysis shows that four technology sets related to Industry 4.0, the distributed economy, biological systems and chemical recycling are the main enablers of the transition to a circular economy, rather than individual technologies. The complementarity of technologies and the changes required from a systemic perspective are discussed, as well as governance and implementation proposals to overcome barriers and resistance to the transition. To date, the research literature has not systematically analysed how new technologies that have been identified as enablers of the circular economy relate to the dynamics of plastic value chains. In addition, there is a great need to better understand how innovative technologies can provide more sustainable solutions in value chains and how more circular alternatives to plastic waste management and recycling can be leveraged. Understanding the opportunities not only from the perspective of individual firms and business models in plastics value chains, but also from a systemic perspective, is key to developing meaningful and effective forms of governance to shape and support the transition to a circular economy. Intending to fill this gap in the literature, the paper seeks to understand the role of key emerging technologies in the transition to a circular economy in the plastics value chain, their potential impacts, and barriers to adoption and diffusion.

ANALYSING THE IMPACT OF TECHNOLOGY ADOPTION ON EFFICIENCY IN US WHOLESALE AND DISTRIBUTION: A COMPREHENSIVE REVIEW OF ANALYTICAL STRATEGIES

The adoption of Artificial Intelligence (AI) and its integration with other digital technologies is reshaping the operational landscape of US firms, with significant implications for the wholesale and distribution sectors. Drawing on insights from the Advanced Business Survey (ABS) technology module, this study evaluates the impact of Artificial Intelligence (AI) on the efficiency and innovation within the U.S. wholesale and distribution sectors. Analysing data from over 30 peer-reviewed articles, it investigates AI's pervasiveness and correlation with various business outcomes. Findings indicate a marked increase in AI adoption, contradicting prior forecasts of widespread unemployment and suggesting a complex interplay with job creation and skill evolution. This study highlights the synergistic potential when AI is integrated with other technologies, affirming theories of technological complementarities. It also addresses the role of policy in fostering an environment conducive to the growth of an AI-augmented workforce. The implications of this research extend to the formulation of strategies that ensure businesses capitalise on AI's benefits, and it paves the way for future inquiries into the longitudinal consequences of AI within the economic fabric. The study's conclusions advocate for ongoing adaptation and investment in human capital as essential components of thriving in the rapidly advancing technological era.

Evolutionary game analysis of inter-organizational trust and technology sharing behavior in enterprise collaborative innovation

In the era of the knowledge economy, how integrating into the network of collaborative innovation and promoting technology sharing has become the key to enhancing the competitiveness of enterprises. It is well known that inter-organizational trust is essential to technology sharing. Firstly, this paper discussed how inter-organizational trust plays a role in technology-sharing behavior. Secondly, based on “organization is bounded rational”, we established an evolutionary game model to analyze the influencing factors of technology sharing. Finally, we used the numerical simulation method to verify the model. Research shows that affective trust facilitates technology acquisition and cognitive trust facilitates technology sharing. The synergetic benefit distribution coefficient influences the evolutionary equilibrium strategy of technology sharing, and there is an optimal synergistic benefit distribution coefficient that maximizes the willingness of both enterprises to share technology. Technology transfer cost and technology leakage risk negatively affect technology-sharing behavior. The degree of technology complementarity, trust coefficient, incentive coefficient, and the ability of shared technologies to transform into synergistic benefits positively influence technology-sharing behavior. The research provides a new way to solve the practical problem of collaborative innovation technology sharing among enterprises.

Teachers’ Perceived Barriers to Technology Integration during Online Learning

The COVID-19 pandemic has had a significant impact on education, forcing schools to close and move to remote learning. Prospective math teachers are particularly challenged by technology integration. This is because mathematics is a subject that is often taught in a traditional, lecture-based format. It can be challenging for prospective math teachers to find effective ways to use technology online to demonstrate teaching and learning mathematics. In this study, the researchers investigated the perceived barriers to technology integration experienced by prospective math teachers during emergency remote learning. This study used a descriptive correlational survey design given to fifty-one (51) respondents enrolled at Surigao del Norte State University (SNSU). Data analysis was performed using SPSS. Moreover, the researchers utilized descriptive statistics such as frequency distributions and measures of central tendency, and non-parametric tests such as Fisher’s exact tests to treat the data. The results showed that the respondents demonstrated moderately positive beliefs regarding the appropriateness of curriculum content for the technology used and the complementarity of technology and content in the course. Second, the respondents generally had a high level of commitment to attending synchronous online learning sessions. Third, gender, age, and income class do not play a significant role in determining respondents' perceived barriers to technology integration. Lastly, there was no significant relationship between respondents' perceived barriers to technology integration and their self-reported attendance (p = 0.099). However, the p-value was close to the conventional threshold for statistical significance (p 0.05), suggesting that there may be a weak association between these two variables.

Towards a partnership of teachers and intelligent learning technology: A systematic literature review of model‐based learning analytics

AbstractBackgroundWith increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction.ObjectiveThe paper reviews the current research on intelligent learning technology designed to make models of student learning and instruction transparent to teachers, an area we call model‐based learning analytics. We intended to gain an insight into the coupling between the knowledge models that underpin the intelligent system and the knowledge used by teachers in their classroom decision making.MethodsUsing a systematic literature review methodology, we first identified 42 papers, mainly from the domain of intelligent tutoring systems and learning analytics dashboards that conformed to our selection criteria. We then qualitatively analysed the context in which the systems were applied, models they used and benefits reported for teachers and learners.Results and ConclusionsA majority of papers used either domain or learner models, suggesting that instructional decisions are mostly left to teachers. Compared to previous reviews, our set of papers appeared to have a stronger focus on providing teachers with theory‐driven insights and instructional decisions. This suggests that model‐based learning analytics can address some of the shortcomings of the field, like meaningfulness and actionability of learning analytics tools. However, impact in the classroom still needs further research, as in half of the cases the reported benefits were not backed with evidence. Future research should focus on the dynamic interaction between teachers and technology and how learning analytics has an impact on learning and decision making by teachers and students. We offer a taxonomy of knowledge models that can serve as a starting point for designing such interaction.

Technoliberalism and the Complementary Relationships between Humanitarian, Conservation, and Entrepreneurial Dronework in Indonesia

Criticism of commercial drones as violators of personal privacy or unsafe public annoyances continues to influence public and academic discourse. At the same time, the commercial drone’s benefits for humanitarian, conservation, industry, and emissions-reduced delivery have also become evident. That such a powerful technology which enhances vision, movement, and force-from-afar could have ambivalent properties appears contradictory. Drawing from the physics and diplomatic work of Niels Bohr, the article argue that drone dualities are complementary rather than contradictory. This theory of complementarity is supported by Bernard Stiegler’s theories including technicity, which argues for hominization or the coevolutionary complementarity of humans and technology, and pharmacology, a bifurcation of technicity into complementary sanitive and poisonous possibilities. This article brings complementarity into the present by linking it to the theory of technoliberalism which situates technicity’s bifurcation in the context of liberalism, namely, the complementary relationship between social liberalism for the collective good and economic liberalism for market benefit. This theory of technoliberal complementarity is examined through ethnographic research into humanitarian, conservation, and economic dronework on the Indonesian islands of Bali, West Papua, and Java in 2018. Complementarity does not elide the importance of dissonance. Instead, it reframes it as a result of interdependent tensions, not their opposition. In this manner, complementarity is a synthetic theory about the generative frictions inherent in technocultural production.

ASSESSMENT OF THE EFFECTIVENESS OF THE IMPLEMENTATION OF MANAGEMENT TECHNOLOGIES IN THE ENTERPRISE

The influencing factors on the use of new management technologies are identified and the relationship between the functional components of the process of introducing new management technologies and the factors affecting it is determined. Variations in determining the effectiveness of the implementation and use of management technologies in the company's activities are summarized. An analysis of the effectiveness of the stages of implementation of management technologies was carried out in accordance with the stages of their use. The results of the implementation of management technologies are clearly presented, taking into account the content of the implemented management technology and data on the implementation results. The work focuses on the conceptual characteristics of the principles of combining the functional information spaces of the enterprise in the context of the creation and management of knowledge as a value of the support system for making managerial decisions, therefore, the issue of applied methods and technical support of the complementarity of management technologies of various information spheres of business, taking into account their close relationship, requires further development communication and development of information and cognitive technologies. Keywords: management technologies, technological and managerial maturity, integration, effectiveness, management, enterprise readiness.

한·중 문화 및 교육 교류의 미래와 전망

This study aims to analyze the status of cultural and educational exchanges and present problems and improvements on the 30th anniversary of Korea-China diplomatic relations. The inflection point of the Korea-China diplomatic bridge can be largely divided into two periods. The first period is from the establishment of diplomatic relations with the Korean Wave and the Korean Wave, until the Korean-Chinese relationship was issued in 2016, and the second period is from the Korean-Chinese relationship to the present day. Rather than exclusive confrontation between Korea and China, it is necessary to create a common identity of East Asian culture through close cooperation based on capital and technological complementarity, set a big goal of fostering global cultural industries, and form a friendly cooperative relationship in the global market. In addition, efforts should be made together to mark the upcoming 100th anniversary by reorganizing cultural exchanges that have been stalled.

기술관련성과 불확실성이 R&D 전략적 제휴 형성에 미치는 영향

Prior studies on R&D alliances have assumed that technological complementarity is a subset of or a moderate level of technological similarity.
 This study suggests that technological similarity and complementarity are two distinct concepts and affect firms’ decision-making in R&D alliance formation differently. While firms conduct local searches to identify alliance partners that possess similar areas of technological knowledge, they also conduct relatively distant searches to identify alliance partners with complementary areas of knowledge. As such, R&D alliances focusing on technological similarity bear low project-specific uncertainty regarding the outcome of an alliance, whereas those driven by technological complementarity involve high project- specific uncertainty. Based on this observation, we investigate the impact of technological similarity and complementarity on the likelihood of R&D alliance formation between established pharmaceutical companies and biotechnology ventures within the biopharmaceutical industry. We find that while technological similarity is positively associated with the formation of late-stage R&D alliances, technological complementarity is positively associated with early-stage R&D alliance formation. We also find that in the presence of high uncertainty regarding an established pharmaceutical firm’s future performance, the positive effect of technological similarity on the likelihood of R&D alliance formation is amplified. However, the positive effect of technological complementarity on the likelihood of R&D alliance formation is diminished.

A Morphology-Driven Method for Measuring Technology Complementarity: Empirical Study Involving Alzheimer's Disease

Abstract Purpose Measuring the exact technology complementarity between different institutions is necessary to obtain complementary technology resources for R&D cooperation. Design/methodology/approach This study constructs a morphology-driven method for measuring technology complementarity, taking medical field as an example. First, we calculate semantic similarities between subjects (S and S) and action-objects (AO and AO) based on the Metathesaurus, forming clusters of S and AO based on a semantic similarity matrix. Second, we identify key technology issues and methods based on clusters of S and AO. Third, a technology morphology matrix of several dimensions is constructed using morphology analysis, and the matrix is filled with subjects -action-objects (SAO) structures according to corresponding key technology issues and methods for different institutions. Finally, the technology morphology matrix is used to measure the technology complementarity between different institutions based on SAO. Findings The improved technology complementarity method based on SAO is more of a supplementary and refined framework for the traditional IPC method. Research limitations In future studies we will reprocess and identify the SAO structures which were not in the technology morphology matrix, and find other methods to characterize key technical issues and methods. Furthermore, we will add the comparison between proposed method and traditional and mostly used complementarity measurement method based on industry chain and industry code. Practical implications This study takes medical field as an example. The morphology-driven method for measuring technology complementarity can be migrated and applied for any given field. Originality/value From the perspective of complementary technology resources, this study develops and tests a more accurate morphology-driven method for technology complementarity measurement.

Knowledge for a warmer world: A patent analysis of climate change adaptation technologies

Technologies can help strengthen the resilience of our economy against existential climate-risks. We investigate climate change adaptation technologies (CCATs) in US patents to understand (1) historical patterns and possible drivers of innovation; (2) scientific and technological requirements to develop and use CCATs; and (3) CCATs’ potential technological synergies with mitigation. First, in contrast to mitigation, innovation in CCATs only slowly takes off, indicating a relatively low awareness of investors for solutions to cope with climate risks. We discuss how historical trends in environmental regulation, energy prices, and public support may have contributed to patenting in CCATs. Second, CCATs form two main clusters: science-intensive ones in agriculture, health, and monitoring technologies; and engineering-intensive ones in coastal, water, and infrastructure technologies. Analyses of technology-specific scientific and technological knowledge bases inform directions for how to facilitate advancement, transfer and use of CCATs. Lastly, CCATs show strong technological complementarities with mitigation as more than 25% of CCATs bear mitigation benefits. While not judging about the complementarity of mitigation and adaptation in general, our results suggest how policymakers can harness these technological synergies to achieve both goals simultaneously.

Developing a Conceptual Partner Matching Framework for Digital Green Innovation of Agricultural High-End Equipment Manufacturing System Toward Agriculture 5.0: A Novel Niche Field Model Combined With Fuzzy VIKOR.

Digital green innovation (DGI) is the core factor that affects the digitalization and decarbonization strategy of agricultural high-end equipment manufacturing (AHEM) system. Although AHEM enterprises actively cooperate with academic research institutes to develop agricultural high-end equipment, there are many obstacles in the process of DGI. Moreover, the integration of digital technology and green innovation from the perspective of partner matching for the AHEM system has not been fully introduced in current literature. Hence, this study aimed to (i) establish a suitable framework system for the AHEM system in general, (ii) quantify the selection of DGI by academic research institutions based on niche theory, and (iii) propose an extended niche field model combined with fuzzy VIKOR model. First, a theoretical framework consisting of three core elements of technology superposition, mutual benefit, and mutual trust, and technological complementarity was constructed based on niche intensity and niche overlap degree. DGI ability superposition of technology, mutual trust, and technical complementarity are beneficial for transferring DGI knowledge from academic research institutes to the AHEM industry. Second, triangle fuzzy number and prospect theory combined with the VIKOR method were introduced into the field theory to construct the complementary field model of DGI resources. The niche field model has been successfully applied to practical cases to illustrate how the model can be implemented to solve the problem of DGI partner selection. Third, the results of a case study show that the criteria framework and the niche field model can be applied to real-world partner selection for AHEM enterprises. This study not only puts forward the standard framework of niche fitness evaluation based on niche theory but also establishes the niche domain model of innovation partner selection management based on niche theory. The standard framework and novel niche field model can help enterprises to carry out digital green innovation in the development of high-end agricultural equipment. The study has the following theoretical and practical implications: (i) constructing a criteria framework based on niche theory; (ii) developing a novel niche field model for DGI partner selection of AHEM enterprises; and (iii) assisting AHEM enterprises to perform DGI practice.

How Susceptible are Skills to Obsolescence? A Task-Based Perspective of Human Capital Depreciation

This article investigates the link between human capital depreciation and job tasks, with an emphasis on potential differences between education levels. Using data from the German Socio-Economic Panel, fixed effects panel regression is applied to estimate an extended Mincer equation based on Neumann and Weiss’s model. Human capital gained from higher education levels depreciates at a faster rate than other human capital. The depreciation rate is also higher for specific skills compared to general skills. Moreover, the productivity-enhancing value of education diminishes faster in jobs with a high share of non-routine interactive, non-routine manual, and routine cognitive tasks. These jobs are characterized by greater technology complementarity or more frequent changes in core-skill or technology-skill requirements. The presented results point to the urgency of elaborating combined labor market and educational and lifelong learning policies to counteract the depreciation of skills. Education should focus on equipping workers with more general skills in all education levels and adapt educational programs to take into account the rapid upgrade of production technologies and changing competency requirements.

Industry 4.0: What makes it a revolution? A historical framework to understand the phenomenon

This paper takes a historical approach to analyse the Fourth Industrial Revolution, denominated Industry 4.0. Although its technologies are more evolutive than disruptive, their combination and gradual improvement promise significant impacts on the economy and society, thus characterising a veritable revolution. However, the pace of diffusion depends on profit expectation, competition intensity, the regulatory system, financial availability, demand, the labour market, and attitudes towards the new technologies. To enhance understanding of the phenomenon, we describe a framework with three contextual elements of the history of each revolution: technological complementarities, economic institutions, and social structure.