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Health Sector at the Crossroads
Published in Ahmed Elngar, Ambika Pawar, Prathamesh Churi, Data Protection and Privacy in Healthcare, 2021
Arindam Chakrabarty, Uday Sankar Das, Saket Kushwaha
The modern healthcare system is largely embedded in technological development. In a technology life cycle, we have three phases: Introduction (I), growth (G) and maturity (M). The level of technology proceeds from lower to higher, from T1 to T2 to T3, where T3 is the superior technology at a particular point of time, assuming that T3 > T2 > T1; however, in any technology life cycle (TLC) there shall be no “decline phase” even though it remains primitive or becomes obsolete. This is simply because technological development is a staircase approach where the obsolete TLC has its foundation of knowledge system that becomes a prerequisite for constructing a higher order of technologies. The world is witnessing rapid development in the field of science and technology, part of which is experimented with and applied in the healthcare system by augmenting sophisticated health devices, surgical instruments or even operative techniques. That makes the healthcare system highly dynamic and bountiful of divergence in the healthcare scenario.
EEMS2015 organizing committee
Published in Yeping Wang, Jianhua Zhao, Advances in Energy, Environment and Materials Science, 2018
As a technology is born, it culminates, and it decays always through a series of complex processes, and we could divide the whole development process into several characteristic stages. According to the technical maturity, the whole technology lifecycle can be defined as four stages: embryonic stage (E), growth stage (G), mature stage (M), and decline stage (D). And as we can see in Figure 1, we call it “E-G-M-D” mode.
A model for selecting appropriate technology for incubator-university collaboration by considering the technology transfer mechanism
Published in International Journal of Production Research, 2018
R.B. Seno Wulung, Katsuhiko Takahashi, Katsumi Morikawa
The contribution of this paper is twofold. First, we propose a technology selection model for incubatees and compare the profit gained using new and old technologies that incorporate the absorptive capacity of the incubatees for absorbing the technology. Second, we use a profit-sharing scheme for the university as a technology provider that can solve the problems of university technology commercialisation. From the proposed model, we can investigate the influence of several factors in the decision-making process. Those factors are the profit-sharing percentage, the customer acceptance, technological obsolescence and the technological levels of incubatees. The profit-sharing percentage represents the amount of incubatee’s profit that will be shared with the university. The customer acceptance shows the customer perspective on the incubatee’s product that results from using the new technology. Technology obsolescence indicates the propensity of the technology will be obsolete related to the technology life cycle. The technological levels of incubatees reflect the absorptive capacity of the incubatees. The remainder of this paper is organised as follows. Section 2 describes the model’s development and our analytical models. Section 3 presents a numerical analysis. Section 4 presents a discussion of the results. Section 5 summarises and concludes the work and provides recommendations for future work.
Production and operations management for intelligent manufacturing: a systematic literature review
Published in International Journal of Production Research, 2022
Liping Zhou, Zhibin Jiang, Na Geng, Yimeng Niu, Feng Cui, Kefei Liu, Nanshan Qi
Although these business assets are reported separately, they are deeply interdependent in practice (Culot et al. 2020). Physical assets are required to be matched with the suitable capabilities to unleash both tangible and intangibles abilities (Nimbalkar et al. 2020). Additionally, not all abilities are needed in any circumstance. Manufacturers should optimise the configurations between technological complexity and organisation transformation stages of the technology life cycle to avoid technology substitution (Moeuf et al. 2018; Cagliano et al. 2019).