Search results

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.

The purpose of this paper is to present a contingency model to examine how technological capacity, promotion capacity, and technological substitution affect the supplier collaboration‐new product performance relationship.

This study uses data from a Government survey of technological innovation. A total of 201 machinery/electronics equipment manufacturing firms in Taiwan comprise the sample. A Tobit regression analysis is adopted to analyze the data.

It is found that technological capacity and promotion capacity enhance the effect of supplier collaboration on new product performance. Technological substitution mitigates the relationship between supplier collaboration and new product performance.

The sample of this study just focuses on machinery/electronics equipment manufacturing firms. The new insights of this study imply that by failing to consider the contingency roles of technological capacity, promotion capacity, and technological substitution, previous research may have assumed away the conditions external and internal to a firm and thus may have reached an oversimplified view of the link between supplier collaboration and product innovation performance.

Firms can improve the effect of supplier collaboration on product innovation by enhancing their technological capacity and promotion capacity.

The paper makes contributions to explain why some firms attain better new product performance than others under the same level of supplier collaboration.

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.

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.

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.

The purpose of this paper is to explain the role of firm resources and environmental variables for pursuing new product commercialization in high‐tech markets.

The research design employed for the study consisted of both exploratory and descriptive phases. To begin with, a focused literature review was performed to develop a theoretical framework with seven research hypotheses, which was then empirically validated through a carefully executed survey conducted on the products managers of high tech firms.

The study results have supported six research hypotheses, viz. technology acquisition intent (TAI) to new product commercialization relationship, direct influence of dominant design, market heterogeneity, and network externalities on the firm's TAI relationship. The results of hierarchical regression analysis indicated that the “dominant design to TAI” and the “network externalities to TAI” relationships are significantly moderated by firm resources. However, the “market heterogeneity to TAI” relationship is found to be not moderated by firm resources.

Findings of the study have significant implications to extant product management theory and practice. The study highlights the most important environmental variables in high‐tech markets that act as antecedents to a firm's TAI and the effect of TAI on new product commercialization. Further, the study reveals the differential effects of these antecedent variables across firms owing to the varying levels of resource availability.

The paper reports the significant outcomes of an important study on product management that attempted to establish the linkages across environmental variables, firm resources, and firm's technology strategy in pursuing the new product commercialization.

The emergence of a pharmaceutical drug as a late entrant in a homogeneous category is a relevant issue for strategy implementation in the pharmaceutical industry. This paper aims to suggest a methodology for making pre-launch forecasts with a complete lack of information for a late entrant.

The diffusion process of the emerging entrant is estimated using the diffusion dynamics of pre-existing drugs, after an appropriate assessment of the drug’s entrance point. The authors’ methodology is applied to study the late introduction of a pharmaceutical drug in Italy within the category of ranitidine. Historical data of seven already active drugs in the category are used to assess and estimate ex ante the dynamics of a late entrant (Ulkobrin).

The results of applying the procedure to the ranitidine market reveal a high degree of accuracy between the ex post observed values of the late entrant and its ex ante mean predicted trajectory. Moreover, the assessed launch date corresponds to the actual date.

The category has to be homogeneous to ensure a high degree of similarity among the existing drugs and the late entrant. For this reason, radical innovations cannot be forecast with this methodology.

The proposed approach contributes to the still challenging research field of pre-launch forecasting by estimating the dynamic features of a homogeneous category and exploiting them for forecasting purposes.

In this paper, an analysis is presented of the research funding towards nanotechnology at the National Nanotechnology Initiative (NNI) and its relationship to the research output in Nanoscope, an application area of nanotechnology.

The paper analyzes the data collected from 1997 till 2006 and derives a definitive time lag between the allocation of research funds and issued patents and published journals. This assessment is achieved by identifying growth trends in patents, funds and publications and doing a curve‐fit analysis using the Fisher‐Pry model. Linear regression analysis is used to show the correlation between the funding and research outputs. Alongside, non‐linear programming objective function optimization technique is used to derive the time lag in years for each of the research outputs from the year of funds granted.

This paper demonstrated that there is a strong correlation between research funding and different research outputs. The time lag between funding and patents issued is evident from the patent trend analysis and Bibliometric analysis. In the case of Nanoscope, the patent time lag was found to be approximately five to six years, for journal article it was approximately two to three years and conference presentations happened right after the funding. The research outputs showed similar trends and were found to be interdependent as evident from our mathematical analysis.

While this study has shown that lag times exist within the chosen example of Nanoscope, and furthermore can be calculated to a precise degree, further data points in terms of additional emerging technologies would support the hypothesis in a more general term. A future study can look at developing technology roadmaps of the future based on the funding happening today.

The work takes bibliometric analysis to a further intelligence and establishes key linkages between these indicators.