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Asserts that innovation, which plays a key role in product and process improvement in many companies, is the very lifeblood of high technology firms. Considers that because technological change is a function of the economic growth model then technological substitution must be a sub‐function of this model. The ability to forecast technological substitution in the long‐term macro view enables strategic planners to develop trends for their specific technological application. Begins with a brief statement of the problem, followed by a discussion of the theoretical framework, review of related literature, methodology, findings, discussion of findings and their implications and, finally, recommendations to practitioners.

Disruptive technologies in the global logistics industry are often regarded as a threat to the existing business models of incumbents’ companies. Existing research, however, focuses mainly on whether technologies have disruptive potential, thereby neglecting when such disruptive transitions occur. To understand the timing of potential disruptive technological change, this paper aims to investigate the elements of the underlying ecosystem shaping these transitions.

Building on the established ecosystem framework from Adner and Kapoor (2016a), this paper constructs four categories of technology substitution to assess how quickly disruptive change may occur in the global logistics industry and defines key technology substitution determinants in logistics to emphasize the role of ecosystems for further consideration into disruptive innovation theory.

Based on the key determinants, this paper proposes first definitions of distinctive ecosystems elements linked to the three types of innovations, namely, sustaining innovations, low-end disruptions and new-market disruptions, thereby integrating ecosystems into Christensen’s (1997) disruptive innovation theory.

By developing a framework that conceptualizes the pace of technology substitution, this paper contributes to a more nuanced understanding of how logistics managers and academics can better predict disruptive transitions and develop strategies to allocate resources.

The purpose of this paper is to investigate three issues: how does an innovative search (local search and boundary-spanning search) impact firm innovation performance of latecomers; how does capability reconfiguration (capability evolution and capability substitution) mediates the relationship between innovative search and firm innovation performance; and how does the technological leapfrogging process (initial stage, following stage, synchronization stage and leading stage) moderate the relationship between capability reconfiguration and firm innovation performance.

A “resource-capability-performance” theoretical framework was developed to explore the relationships between local/boundary-spanning search, capability reconfiguration and firm innovation performance. The data were collected by sending out surveys to managers and employees in various industries in mainland China. These hypotheses were tested using structural equation models and hierarchical regressions.

The results showed that: innovative search has a direct causal relationship to capability reconfiguration; local search and boundary-spanning search are conducive to improve the innovation performance of latecomers; the impact of local search and boundary-spanning search on innovation performance is realized through the completion of mediating role of capability reconfiguration; there are differences in the path of local search and boundary-spanning search affecting the capability reconfiguration of enterprise innovation performance; and the relationship between innovative search, capability reconfiguration and enterprise innovation performance evolves with the enterprise in different stages of technological leapfrogging.

This study explores the relationship and the path of innovative search to firm innovation performance and analyzes the path difference between local search and boundary-spinning search, which enriches the research of organizational search and enterprise innovation. This paper reveals the whole path of innovative search affecting innovation performance, discusses the important role of capability reconfiguration and makes incremental contributions to dynamic capability theory. It studies the evolution of innovative search on innovation performance under the background of technological leapfrogging, which provides a new perspective for the study of organizational search and capability-based theory.

Purpose – The aim of this paper is to examine the diffusion of a new surgical procedure with lower per-case cost and how its diffusion path is affected by the simultaneous introduction of a new drug class that may be an effective treatment to prevent surgery. In particular, we examine whether a process of technology substitution exists that influences the diffusion process of the surgical technology. Given their different cost implications, the interaction of these two different technologies, surgery and drug intervention, is relevant from the perspective of health expenditure. This is of particular interest in health care as technology adoption and diffusion has been cited as a major driver of expenditure growth. Such expenditure growth has been increasingly targeted through the use of market-orientated policy tools aimed at increasing efficiency. Our research is thus addressing the question of how economic incentives influence the diffusion process and we discuss the impact of a set of incentives on hospital behavior.

Design/methodology – Hospital admission data for the financial years 1998/1999 to 2007/2008 in England are used to empirically test the contribution of prescription uptake and market-oriented reforms. Dynamic panel data models are used to capture any changes in technology preference during the period of study.

Findings – Our results suggest that the hospital sector exhibits a strong new technology preference, tempered by the interaction of competition for patients and the ability of the primary care sector to substitute treatments.

Value/originality – Given the current fast technological change, we examine the technological race occurring in the health care sector. We account simultaneously for the diffusion of different technologies not only within the same typology but also with technologies of a different class.

The purpose of this paper is to examine the effect of biased technology on employment distribution and labor status in income distribution of China. It also testifies a threshold effect of the capital per labor and employment distribution on labor status from biased technology.

This paper presents a normalized supply-side system of three equations to measure the bias of technology in China. Linear and threshold regressions approaches are applied over cross-province panel data to investigate the influence which biased technology has on labor status under different capital per labor and employment distribution regimes.

This paper empirically shows that technology has been mostly capital-biased in China. The regression results indicate that capital-biased technology impairs labor income status and tend to modify employment distribution and labor income between industries. Furthermore, it reveals the threshold effect of capital per labor and employment distribution on the relationship between biased technology and labor status.

This paper extends the literature by explaining labor status from the perspective of biased technology and the effect of inter-industry employment distribution in China. It further explores the asymmetric effect of biased technology on labor productivity and income, which promotes inter-industry labor mobility and modifies employment distribution. This paper highlights the implications of this explanation for labor relations and human resource management.

Due to rapid technological evolution driven by display manufacturers, the television (TV) market of flat panel displays has been fast growing with the advancement of digital technologies in broadcasting service. Recently, organic light-emitting diode (OLED) successfully penetrated into the large-size TV market, catching up with light-emitting diode (LED)-liquid-crystal display (LCD). This paper aims to investigate the market penetration of OLED technologies by determining their technology adoption rates based on a diffusion model.

Through the rapid evolution of information and communication technology, as well as a flood of data from diverse sources such as research awards, journals, patents, business press, newspaper and Internet social media, data mining, text mining, tech mining and database tomography have become practical techniques for assisting the forecaster to identify early signs of technological change. The information extracted from a variety of sources can be used in a technology diffusion model, such as Fisher-Pry where emerging technologies supplant older ones. This paper uses a comparison-based prediction method to forecast the adoption and diffusion of next-generation OLED technologies by mining journal and patent databases.

In recent years, there has been a drastic reduction of patents related to LCD technologies, which suggests that next-generation OLED technology is penetrating the TV market. A strong industry adoption for OLED has been found. A high level of maturity is expected by 2026.

For OLED technologies that are closely tied to industrial applications such as electronic display devices, it may be better to use more industry-oriented data mining, such as patents, market data, trade shows, number of companies or startups, etc. The Fisher-Pry model does not address the level of sales for each technology. Therefore, the comparison between the Bass model and the Fisher-Pry model would be useful to investigate the market trends of OLED TVs further. Another step for forecasting could include using industry experts and a Delphi model for forecasting (and further validation).

Fisher-Pry growth curves for journal publications and patents follow the expected sequence. Specially, journal publications and patents growth curves are close for OLED technologies, indicating a strong industry adoption.

Many models of markets are based on assumptions of rationality, transparency, efficiency, and homogeneity in various combinations. This paper aims to explain why markets routinely and repeatedly make “mistakes” that are inconsistent with these simplifying assumptions.

System dynamics models are used to show how misestimating demand growth, allowing financial discipline to lapse, unrealistic business planning, and misperception of technology trajectories can produce disastrously wrong business decisions. Examples are drawn from airlines, telecommunications, IT, aerospace, energy, and media.

The undesirable outcomes can include vicious cycles of investment and profitability, market bubbles, accelerated commoditization, excessive investment in dead‐end technologies, giving up on a product that becomes a huge success, waiting too long to reinvent legacy companies, and changes in market leadership. Differentiating transient phenomena from the longer term trends, movement away from vertically integrated business models, and effective use of early warning signs avoid these mistakes, or at least limit the damage that they cause.

Decision makers tend to rely on simple mental models which have serious limitations. They become increasingly deficient as problems grow more complex, as the environment changes more rapidly, and as the number of decision makers increases. The amplification and tipping dynamics typical of highly coupled systems, for example, bandwagon, network, and lemming effects, are not anticipated. Behavioural factors that play critical roles in the evolution of markets often are misunderstood or ignored.

The paper illuminates the effects of bounded rationality, imperfect information, and fragmentation of decision making on the behavior of markets. Models which assume, at least implicitly, that decision makers understand the structure of the market and how it produces the dynamics which can be observed or might potentially occur can be dangerous simplifications and seriously misleading.

This paper aims to analyse the technological, economic and environmental impacts of disruptive innovations in the transportation mobility market.

The paper gathered data from World Bank and 13 open sources in an exploratory, descriptive and applied investigation on potentially disruptive transport innovations outcomes in G7 and BRICS (Brazil, Russian Federation, India, China and South Africa) economies, businesses and societies.

The results suggest positive implications for technological leapfrogging of electric vehicles (EV), autonomous vehicles (AVs) and electric vertical take-off and landing (eVTOLs), such as gains in energy consumption, infrastructure improvement, greenhouse gas emissions reduction, economic growth and the opportunity for new disruptive technologies to improve or even revolutionize the transportation ecosystem.

This study has clear limitations as it compares G7 and BRICS hypothetical scenarios where internal combustion vehicles were replaced by new technologies, ceteris paribus. Even so, as theoretical implications, the study presents market scenarios for EVs, AVs and eVTOLs technologies, bringing benefits to the disruptive innovation theory by expanding the understanding of the subject and also opening avenues of investigation by exploring new technological, economic and environmental possibilities.

This study emphasises potentially disruptive technologies’ technological, economic and sustainable benefits to countries through technological leapfrogging. The organizations can delve into results to investigate forthcoming markets and seek advantageous positions. Economic and social gains from leapfrogging could motivate government bodies to finance research focusing on EVs, AVs and eVTOLs diffusion.

The paper’s originality resides in aggregating multiple data sources to compare technological leapfrogging in G7 and BRICS transportation. The different views allowed for exploring the potential outcomes of EVs, AVs and eVTOLs on economic, sustainability and market dimensions in developed and developing countries.

The purpose of this paper is to investigate the effect of inter-platform competition on the adoption of different broadband technologies (i.e. among xDSL, fibre-optic technologies, and hybrid fibre coaxial (HFC)), examine the direction of the effect, and identify potential technology convergence and the speed of technology innovation.

It uses Lotka-Volterra equation to determine the dynamic competition pattern for xDSL, fibre-optic technologies, and HFC.

The influence of inter-platform competition on the adoption rate may vary depending on the market conditions, the phase of the adoption period, and the types of competing technology. Even though new technology has competitive advantage, it still requires time to acquire market share. Even though fibre-optic is leading in the market, alternative technologies have also garnered significant market share in the early stage. Specifically, HFC has gained its own market position, making it a valuable alternative in the short term. Nonetheless, the market will eventually converge to fibre-optics.

The findings show that inter-platform competition does not always exert positive influence on broadband adoption as indicated in previous literature. Instead, the influence may vary from negative to neural. This information is an important knowledge addition to the literature. Overall, the study has important implications to governmental effort in managing market competitions and in planning national broadband infrastructure policies. It also provides valuable implications on how ISPs should strategize their investment in new broadband technologies.

Technological innovations can have Important strategic implications for individual companies and can greatly influence industries as a whole. Yet, not all technological change is strategically beneficial. This article focuses on ways to recognize and exploit the competitive significance of change.