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Journal articles on the topic 'Innovation simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

Drake, Hilary, Darin Abbey, Chelsea Holmes, Anna Macdonald, Laura Mackinnon, JoAnne Slinn, and Jared Baylis. "Simulation Innovation." Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare 15, no. 6 (November 5, 2020): 427–31. http://dx.doi.org/10.1097/sih.0000000000000515.

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2

Roukouni, Anastasia, Heide Lukosch, Alexander Verbraeck, and Rob Zuidwijk. "Let the Game Begin: Enhancing Sustainable Collaboration among Actors in Innovation Ecosystems in a Playful Way." Sustainability 12, no. 20 (October 15, 2020): 8494. http://dx.doi.org/10.3390/su12208494.

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Logistics and transport systems are complex systems for which sustainable innovations are urgently needed. Serious games are an acknowledged tool for training, learning, and decision making, as well as for helping to introduce innovative concepts for complex systems. Technological innovations for the transport domain that can improve sustainability are usually heavily dependent on the collaboration among actors. A simulation gaming approach can help these actors in understanding the challenges involved, and in finding solutions in a playful, interactive way. Our research approach includes a thorough literature review on games for innovation and collaboration in transport networks, and the development of two dedicated simulation games addressing sustainability innovations for the Port of Rotterdam, the largest seaport in Europe and one of the largest in the world. The two innovation cases are truck platooning and multi-sided digital platforms for barge transportation, both improving the sustainability of hinterland transportation. The games serve as instruments to reveal interactions and tensions among actors, contribute to the interpretation of their behavior, and eventually help all parties to reach a better understanding on how innovation adoption can be fostered, using an innovation ecosystem perspective. We are convinced that serious gaming, by providing a better understanding of the innovation process, will help the implementation of sustainability innovations in complex systems.

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3

Walsh, K. "From simulation to innovation." BMJ 340, mar02 3 (March 2, 2010): c1200. http://dx.doi.org/10.1136/bmj.c1200.

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4

Liubkina, O., T. Murovana, A. Magomedova, E. Siskos, and L. Akimova. "Financial Instruments of Stimulating Innovative Activities of Enterprises and Their Improvements." Marketing and Management of Innovations, no. 4 (2019): 336–52. http://dx.doi.org/10.21272/mmi.2019.4-26.

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The article analyzes the importance of innovations as one of the main factors influencing the competitiveness of enterprises and economies of the world. The study is based on the author’s empirical research, grounded on the methodology of analysis of empirical data. The survey was carried out among legal entities and separate departments which operate regardless of its type. The study aimed to determine the importance of financial factors in limiting innovation activity and its potential in stimulating the innovation activity of enterprises. A survey was carried out among the enterprises on the factors that significantly influenced their decision to develop innovative projects or constrained implementation of innovation activities. The key challenges of innovation activity of enterprises were analyzed (law barriers, supply-side barriers, demand-side barriers, barrier on the demand and supply interface, lack of identified priorities, challenges of commercialization of the results of scientific and technical work, as well as weak development of infrastructure, labour problems). The research was also carried out by studying features of using financial instruments to stimulate innovation activity of enterprises, analysis of economic indicators characterizing the innovative activity of enterprises, analysis of strengths and weaknesses of innovation projects, as well as improvement of financial instruments for stimulating the implementation of innovations at enterprises. Based on the conducted research, long‑, medium- and short-term directions of financial support of innovative activity were determined. Financial instruments of stimulation innovation activity of enterprises are improved based on the analysis, taking into account socio-economic, political and other particular features of country’s development where such projects are implemented; studying the experience of implementing real innovative projects, analyzing strengths and weaknesses of these projects, feasibility of implementing similar projects under such conditions. Keywords: innovation, innovation ecosystem, innovative activities, investment, simulation of innovative processes, financial instruments.

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5

Prokopenko, Olha, Vitaliy Omelyanenko, T. Ponomarenko, and O. Olshanska. "Innovation networks effects simulation models." Periodicals of Engineering and Natural Sciences (PEN) 7, no. 2 (July 25, 2019): 752. http://dx.doi.org/10.21533/pen.v7i2.574.

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6

WINDRUM, PAUL. "Simulation Models of Technological Innovation." American Behavioral Scientist 42, no. 10 (August 1999): 1531–50. http://dx.doi.org/10.1177/00027649921957874.

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7

Lecomte, François, and Clément Buléon. "Innovation et simulation en formation." Soins 66, no. 856 (June 2021): 66–68. http://dx.doi.org/10.1016/s0038-0814(21)00169-9.

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8

Parvin, Albert Joseph, and Mario G. Beruvides. "Optimizing the Abandonment of a Technological Innovation." Systems 9, no. 2 (April 21, 2021): 27. http://dx.doi.org/10.3390/systems9020027.

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The primary objective of this study is to reveal macro-level knowledge to aid the optimization, evaluation, and strategic planning of technological innovation abandonment. This research uses an exploratory data analysis (EDA) approach to extract directional and associative patterns (macro-level knowledge) to assess technological innovation abandonment optimization. Deterministic and stochastic simulations are employed to reveal the impact of three factors on abandonment optimization, namely, a technological innovation’s diffusion rate, a technological innovation’s probability of achieving a given diffusion rate, and the point of abandonment. The patterns and insights revealed through the graphical examination of the simulation provide associative and directional knowledge to assess the abandonment optimization of technological innovation. These revealed patterns and insights enable decision-makers to develop an abandonment assessment framework for optimizing, evaluating, and proactively planning abandonment at the macro level.

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9

Ding, Shu Kui. "Independent Technology of CBTC System and Management Innovation in Urban Rail Transit." Applied Mechanics and Materials 236-237 (November 2012): 671–76. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.671.

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This paper introduces two technical innovations in the signal demonstration project of Beijing Subway Yizhuang Line: the “free wave antenna + waveguide” combined transmission and the "minimum system" simulation. It also summaries the demonstration project management concepts and innovative practice experiences. Analyzing the technology and management innovation, we expect to provide a reference for the progress of the autonomy of the other rail transport high-end and core technology.

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10

Kováčiková, Lea, Ferdinand Varga, Eva Kvaltínyová, Jana Plevková, and Tomáš Buday. "INNOVATION AND SIMULATION-BASED TEACHING TECHNIQUE IN PATHOLOGICAL PHYSIOLOGY." CBU International Conference Proceedings 4 (September 16, 2016): 727–31. http://dx.doi.org/10.12955/cbup.v4.840.

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Simulation-based learning in medicine has gained substantial importance. It is complementary to often limited clinical practice, and helps interconnect theoretical knowledge with practical training. Simulations are implicated in clinical subjects, but based on recent understanding, simulation can also be used in preclinical subjects, where it can support presented tasks. Simulation technology was used for elective practical sessions in a pathophysiology course, with both measurable outcomes and students’ feedback evaluated. This study was conducted in Slovakia with volunteers (n = 22), who were 3rd-year students of General Medicine (simulation group), paired with classmates in traditional seminars (control group; n = 22) with the same achievement grades. The control group had completed traditional seminars, whereas the simulation group had completed simulation-based seminars in cardiovascular pathophysiology. A standardized student feedback survey, visual analogue scale, and credit tests for regular pathophysiology were used to perform the analysis. Subjective feedback suggested positive outcomes in approximately 80% of students. An objective assessment showed that simulation-based seminars did not increase the theoretical knowledge as documented by 1st credit test (simulation vs control; 42 ± 6 vs 41 ± 4; p > 0.05), but rather their approach to clinical application of obtained information and motivation to study.

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11

Girzelska, Joanna, Ewa Guz, Magdalena Nieckula, and Marek Dąbrowski. "Medical simulation – innovation in nursing education." Pielegniarstwo XXI wieku / Nursing in the 21st Century 18, no. 4 (December 1, 2019): 231–35. http://dx.doi.org/10.2478/pielxxiw-2019-0034.

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AbstractAim. Analysis of the impact of educational simulation on the level of knowledge, skills and competences of nursing students.Methods. The research used a non-systematic literature analysis method. Literature was classified for analysis, from which the contents on the impact of educational simulation on the education process of nursing students were selected. During the qualification of the magazines Google Scholar was used. Articles published in electronic databases were used: EBSCOhost, MEDLINE, ScienceDirect.Conclusions. Education conducted using educational simulation in nursing not only increases the level of knowledge, skills and competences of students but also increases the quality of patient care and their security.

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12

DRENKARD, K., and B. GRESH. "Innovation in nurse executive developmentComputer simulation." Nurse Leader 2, no. 5 (September 2004): 36–38. http://dx.doi.org/10.1016/s1541-4612(04)00140-5.

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13

van den Hoogen, Jop, and Sebastiaan Meijer. "Gaming and Simulation for Railway Innovation." Simulation & Gaming 46, no. 5 (September 30, 2014): 489–511. http://dx.doi.org/10.1177/1046878114549001.

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14

Sechrist, Robert. "Microcomputer-Based Simulation of Innovation Diffusion." Social Science Computer Review 7, no. 2 (July 1989): 161–74. http://dx.doi.org/10.1177/089443938900700203.

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15

Rubinstein, Ran, Ravid Segal, and Imri Amiel. "Board 248 - Program Innovations Abstract Technology Innovation for Trauma Simulation (Submission #1011)." Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare 8, no. 6 (December 2013): 491. http://dx.doi.org/10.1097/01.sih.0000441513.01160.96.

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16

Kravchenko, Sergey. "Simulation of the national innovation systems development: A transnational and coevolution approach." Virtual Economics 2, no. 3 (July 7, 2019): 41–54. http://dx.doi.org/10.34021/ve.2019.02.03(4).

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The current state of scientific and technological development of the world economy is quite specific, because advanced technologies already known are too complicated for simple mechanical copying and borrowing, and most of the technologies of Industry 4.0 are in the making. Thus, the development and further exploitation of all kinds of innovations today, more than ever, require an appropriate environment - an effective national innovation system (NIS), which determines the country's ability to generate innovation, which is the key to high competitiveness and world leadership. However, the formation of a full-fledged innovation system of the country is quite complicated, for at least two reasons: first, there exist purely national features of functioning and cooperation of the main agents of change, and secondly, in the modern globalized world many of the most important for innovation processes go beyond the borders of individual countries, creating a unique transnational "ecosystem" with its distinctive features, which, undoubtedly, must be considered. The article proposes the scientific approach of reliable identification of national and transnational (supranational, global) innovation systems (TNIS) and the corresponding toolkit for simulating their development in the context of the quadruple helix concept. Identification of innovative systems is based on the methods of cluster analysis, genetic algorithms and neural network training. As a result, there have been identified and qualitatively interpreted four basic types of TNIS, which have stable characteristics determining the behavioural parameters and capabilities of the NIS included. A neural network has been built to identify NIS, which simplifies the process of simulating their development within the characteristic features of basic TNIS. It is established that the NIS of Ukraine belongs to the basic type of TNIS – “developed and developing countries with mixed extractive-inclusive institutions with a strong informal component (including the post-Soviet type)”. The results of its functioning against the background of global and relevant cluster leaders are not satisfactory and necessitate the adjustment of the further development vector. In order to demonstrate the capabilities of the neural network built, four supranational associations have been identified and analysed. The proposed approaches and tools will facilitate variant analytics and forecasting studies in substantiating the optimal directions for the individual NIS further development in the context of global and cluster trends.

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17

Flipse, S. M., K. H. Van Dam, J. Stragier, T. J. C. Oude Vrielink, and M. C. A. Van der Sanden. "Operationalizing responsible research & innovation in industry through decision support in innovation practice." Journal on Chain and Network Science 15, no. 2 (December 7, 2015): 135–46. http://dx.doi.org/10.3920/jcns2015.x004.

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This paper presents a tool that can help innovators to operationalize responsible research & innovation (RRI) in industry and offers decision support in their innovation project management. This tool is based on an earlier method of project quality assessment to identify innovative project success-related key performance indicators (KPIs). Based on real-world data and using structural equation modelling, a model is developed that relates the KPIs to one another and provides innovators with the opportunity to compare quality scores of current projects to a database of earlier successful and less successful project quality assessments. Building on this model, using a rapid prototyping approach based simulation and modelling, a scenario development tool has been developed that can predict success chances of current projects based on changing KPI score parameters. By highlighting the value of the KPIs in relation to RRI, and by elucidating what could be done to increase values of low scoring project KPIs, innovators who use the tool can evaluate possible actions they can deploy to increase the quality of their innovative projects, while simultaneously innovating in a more socially responsible way.

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18

Zhou, Huan, Shaojian Qu, Xiaoguang Yang, and Qinglu Yuan. "Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis." Discrete Dynamics in Nature and Society 2020 (November 3, 2020): 1–14. http://dx.doi.org/10.1155/2020/1738279.

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Based on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. Spatial weight matrices are constructed from two aspects of geographical characteristics and innovative input characteristics. The empirical results show significant spatial heterogeneity and spatial autocorrelation in economic growth, regional credit, and technological innovation. Both regional credit and technological innovation are important impacts to economic growth, whereas the interaction of regional credit and technological innovation has a negative effect on provincial economic growth. Therefore, we argue that China should rationally allocate regional credit resources, strengthen technological innovation capabilities, and boost the integrated development of regional credit and technological innovation. It is a particularly important way to facilitate regional economic integration and sustainable development.

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19

Wu, Rong, Zhiqiang Wang, and Qinfen Shi. "Increment of Heterogeneous Knowledge in Enterprise Innovation Ecosystem: An Agent-Based Simulation Framework." Complexity 2021 (July 19, 2021): 1–16. http://dx.doi.org/10.1155/2021/9550232.

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How can enterprises acquire knowledge resources quickly to maintain a competitive advantage in the market has become the focus of attention among academic circles and enterprises in the era of the knowledge economy. Based on the ecology theory, this paper analyzed the characteristics of the innovation subject and the rules of the heterogeneous knowledge interaction between innovation subjects. Then, this paper proposed a multiagent-based model of EIE (enterprise innovation ecosystem) heterogeneous knowledge increment to simulate the interactions between innovation subjects. By combining the biotic factors (government and service institutions) and abiotic factors (economical, social, and cultural), this paper designs eight different innovation environment scenarios to explore the dynamic impacts of these factors on EIE heterogeneous knowledge increment. The research findings were as follows: (1) In the introduction stage of innovation collaboration between innovation subjects, the same investment of the innovation elements in academic institutes is more beneficial to increasing system heterogeneous knowledge than investment in enterprises. (2) The cultivation of innovative biotic factors in service institutions is conducive to the rapid interaction of heterogeneous knowledge among the innovation subjects. Still, it is not suitable for areas with higher homogeneous knowledge because high homogeneous environment can easily lead to intensified market competition. (3) The cultivation of the abiotic innovation environment is conducive to maintain stable high-speed growth of EIE heterogeneous knowledge increment over a long period. (4) Without considering the cost of environmental cultivation, cultivating biotic and abiotic environments at the same time is the most beneficial choice to EIE heterogeneous knowledge increment.

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20

März, Sven, Monika Friedrich-Nishio, and Hariolf Grupp. "Knowledge transfer in an innovation simulation model." Technological Forecasting and Social Change 73, no. 2 (February 2006): 138–52. http://dx.doi.org/10.1016/j.techfore.2005.05.002.

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21

March, Alice, Matt Ander, Robin Huebner, Jeannine Lawrence, Patrick McIntyre, Karen Silliman, and Lea Yerby. "Board #226 - Program Innovation Technology-supported Simulation." Simulation in Healthcare: Journal of the Society for Simulation in Healthcare 9, no. 6 (December 2014): 457. http://dx.doi.org/10.1097/01.sih.0000459365.20060.bf.

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22

Gilbert, Nigel, Petra Ahrweiler, and Andreas Pyka. "Learning in innovation networks: Some simulation experiments." Physica A: Statistical Mechanics and its Applications 378, no. 1 (May 2007): 100–109. http://dx.doi.org/10.1016/j.physa.2006.11.050.

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23

Heshmati, Almas, and Flávio Lenz-Cesar. "Policy simulation of firms’ cooperation in innovation." Research Evaluation 24, no. 3 (May 8, 2015): 293–311. http://dx.doi.org/10.1093/reseval/rvv011.

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24

Wu, Chuanrong, and Deming Zeng. "Knowledge Transfer Optimization Simulation for Innovation Networks." Information Technology Journal 8, no. 4 (May 1, 2009): 589–94. http://dx.doi.org/10.3923/itj.2009.589.594.

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25

Fiegenbaum, Irina, Martin Ihrig, and Marko Torkkeli. "Investigating open innovation strategies: a simulation study." International Journal of Technology Management 66, no. 2/3 (2014): 183. http://dx.doi.org/10.1504/ijtm.2014.064591.

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26

Aboushanab, Tamer, and Saud M. AlSanad. "Simulation in Cupping Training: An Innovation Method." Journal of Acupuncture and Meridian Studies 10, no. 6 (December 2017): 409–10. http://dx.doi.org/10.1016/j.jams.2017.10.003.

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27

Shinohara, Kazunori, and Serban Georgescu. "Modelling Adopter Behaviour Based on the Navier Stokes Equation." ISRN Mathematical Analysis 2011 (December 15, 2011): 1–10. http://dx.doi.org/10.5402/2011/894983.

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Aiming to improve the current models describing the diffusion of innovation, a method based on an analogy with a physical system is presented. In particular, we model the movement of adopters of a particular innovation as a flow and the diffusion of the innovation as heat diffusion, thus making use of mathematical tools such as the Navier-Stokes equation. Building on our previous work, in this study we focus on the movement of adopters in the simulation domain, which we refer to as convection. As an application to modeling the convection phenomenon, we simulate the flow of people in a real building floor, the Tokyo Aquarium. Besides being a necessary part when simulating diffusion of innovations, such a modeling approach may also prove useful in different fields, such as deciding layout of public spaces or evacuation policies.

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28

Magnussen, Rikke. "Game-Like Technology Innovation Education." International Journal of Virtual and Personal Learning Environments 2, no. 2 (April 2011): 30–39. http://dx.doi.org/10.4018/jvple.2011040103.

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This paper examines the methodological challenges and perspectives of designing game-like scenarios for the implementation of innovation processes in school science education. This paper presents a design-based research study of a game-like innovation scenario designed for technology education for Danish public school students aged 13-15. Students play the role of company heads that develop intelligent music technology. This game-like learning environment was designed to develop innovation competencies through the simulation of a practical learning situation. The term “game-like” is used to denote that the scenario should not be considered an educational game, such as the educational computer games used in many schools today. The focus of the design is to include practices and tools from innovative professions and use game principles and elements to create a meaningful frame around the creative and innovative practices.

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29

Wu, Feng Qing. "Formation Mechanism and Simulation Research on Innovation Clusters." Advanced Materials Research 476-478 (February 2012): 2158–61. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.2158.

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With economic globalization and rapid development of science technology, a number of enterprises in the region work closely in the form of industrial clusters, with whose overall innovation capability increasing rapidly. It is in this situation that the conception of innovation cluster comes with the tide of fashion. This paper first reviews the study situation of networks; analyzing the structure of innovation clusters deeply, and then constructs an improved BA model to demonstrate the complex links among the innovation cluster nodes and explains their structural features, then simulate its formation mechanism and evolution process.

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30

Van Lysebetten, Saar, Frederik Anseel, and Diana R. Sanchez. "The Effects of Situation Variability in a Simulation-Based Training for Implicit Innovation Knowledge." Simulation & Gaming 51, no. 4 (May 22, 2020): 477–97. http://dx.doi.org/10.1177/1046878120914327.

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Background. During the last decades, the use of simulations for training purposes has sparked wide interest. However, it is unclear how training format characteristics may affect learning, resulting in a lack of evidence-based guidelines for training developers and organizations. Aim. We explore to what extent variation in the situations presented during a simulation training may improve learning outcomes. We test this research question in the context of a simulation-based training for improving innovation knowledge. Methods. A sample of 131 business students was invited to participate in a study with a pretest and two posttests (within 48 hours after and 4 weeks later) and three conditions: a control group without training, an experimental training group with low situational variation, and an experimental training group with high situational variation. Results and Conclusion. Compared to the control group, high but not low situational variation improved innovation knowledge. Participants’ prior innovation knowledge did not moderate the results. Hence, our findings indicate that ideally a simulation training includes multiple situations that offer learners various opportunities to practice innovation challenges.

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31

Zakharchenko, Pavlo V., Yana V. Glazova, Svitlana Α. Zhvanenko, Ganna P. Kostenko, Stanislav F. Kucher, and Viktor S. Mukhin. "Management of Innovation Processes In the Health Economy System of Ukraine." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 17 (July 9, 2021): 721–31. http://dx.doi.org/10.37394/232015.2021.17.69.

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In today's health economics, resort and recreation is one of the most lucrative areas of the economy. Ukraine has a strong resort and recreational potential, the effective development of which can bring real economic benefits. This requires the formation of a systemic strategy for the development of such systems, an integral part of which are innovations. The purpose of the article is to analyze and develop methods for managing innovations in the health economy of Ukraine with its further development. The author's concept, which is based on the methods of economic dynamics, multicriteria optimization and optimal management, is used as a methodological approach. That is the first time the proposed concept has been used to analyze, forecast and formulate innovation policy and the development of innovation processes in the health economy. It allows to build predictive scenarios of innovation development with a high degree of accuracy compared to existing approaches, and is more adequate and universal in a pandemic. As a result of the research the concept of innovation development strategy as a certain period of cyclical dynamics was substantiated, and scenarios of influence, development and implementation of innovations were obtained. The proposed approach provides an opportunity to consider the development of the health economy and, in particular, resort and recreational systems as a process of transformational change of innovation strategies. On this basis, a model is built that allows for a scenario description of the transformation of innovative strategies of resort and recreational systems. The proposed model allows for choosing an innovation policy, i.e. at what point in time to begin the implementation of a new resort and recreational technology, which includes decisions on the feasibility of its implementation in general. The simulation results can be used to form a new modern strategy for the development of the health economy in Ukraine.

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32

Xie, Linling, and Tie Wei. "Simulation modelling and analysis of balance mechanisms of innovation search in innovation network." International Journal of Simulation and Process Modelling 15, no. 1/2 (2020): 52. http://dx.doi.org/10.1504/ijspm.2020.10028716.

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Xie, Linling, and Tie Wei. "Simulation modelling and analysis of balance mechanisms of innovation search in innovation network." International Journal of Simulation and Process Modelling 15, no. 1/2 (2020): 52. http://dx.doi.org/10.1504/ijspm.2020.106966.

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34

Croland, Trina. "Board #210 - Program Innovation An Innovative Intern Preparatory Course." Simulation in Healthcare: Journal of the Society for Simulation in Healthcare 9, no. 6 (December 2014): 447. http://dx.doi.org/10.1097/01.sih.0000459349.95403.b2.

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35

Kreidler, Anja, and Meike Tilebein. "Driver or inhibitor for innovation?" Kybernetes 47, no. 2 (February 5, 2018): 359–68. http://dx.doi.org/10.1108/k-02-2017-0073.

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Purpose Literature is unanimous about the effects of functional diversity in new product development teams. This paper uses simulation modeling to investigate the contradictory and dynamic effects of functional team diversity on innovation revealed by empirical literature. This paper aims to start a discussion on this dynamic perspective of team diversity. Design/methodology/approach This paper presents a systemic approach toward investigating the contradictory and dynamic effects of functional team diversity on innovation by creating a simplified System Dynamics model of functional diversity in new product development teams. Findings Although the simulation model is highly simplified, it can integrate the contradictory results of empirical data and the dynamic component of teamwork. Therefore, it offers a new approach to investigating the effects of functional diversity on team innovation. Research limitations/implications The model is highly simplified and exemplary. No actual data are included, thus limiting the results as fully theoretical. Originality/value Empirical studies often analyze the effects of functional diversity on innovation in new product development teams. However, empirical data are unclear regarding the nature of the effects of functional diversity on innovation. Therefore, functional diversity is chosen for the simulation model as being the most controversially discussed diversity attribute. By applying a simulation model to the problem and adding a dynamic component to teamwork, we are contributing to the explanation for the contradictory findings in literature.

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36

Manohar, Priya A. "Thermomechanical Process Innovation via Computer Modeling and Simulation." Materials Science Forum 638-642 (January 2010): 3883–88. http://dx.doi.org/10.4028/www.scientific.net/msf.638-642.3883.

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A new approach is proposed in this paper that describes the development of flexible rolling technology in industrial processing of C – Mn and Low C - microalloyed steels. Scientific knowledge of industrially-significant processes for these materials is presently fragmented and scattered in published literature, which causes impediment to process innovation and optimization. In the current work, it is demonstrated that new process sequences could be developed by breaking down existing process routes in to key elements and then by recombining them to generate novel alternative and more efficient hot processing sequences. The proposed methodology establishes a platform for a more realistic assessment of existing process routes and the development of new hybrid process routes that combine ideas from alternative processes. This enables the identification of an optimal process sequence for specified steel compositions that also satisfies simultaneous design criteria such as process feasibility and property maximization. Application of the proposed algorithm in industrial-scale rod rolling of a medium C-Mn steel is demonstrated and discussed.

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Drake, Andrea, Susan F. Haka, and Sue P. Ravenscroft. "An ABC Simulation Focusing on Incentives and Innovation." Issues in Accounting Education 16, no. 3 (August 1, 2001): 443–71. http://dx.doi.org/10.2308/iace.2001.16.3.443.

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Current textbooks advocate activity-based costing (ABC) because it provides more detailed information on resource usage, leading to better cost control and reengineering of production processes. However, there is often little attention paid to how other organizational control features can affect the use of the information provided by ABC systems. This active learning simulation demonstrates that incentives can have a significant impact on how workers use ABC information to manage costs and innovate a production process. The simulation involves two student teams that are furnished with identical ABC cost driver information and either a tournament- or group-based incentive structure. The teams simulate a factory environment by creating products using a simple manufacturing process, while the remaining students observe the process and record differences in communication, innovative activity, and resulting profitability. The teams' outcomes under the two separate incentives illustrate the interaction of a firm's cost system with its incentive system. Typically, we find that more communication occurs among team members, more team-based innovations are created, and profit is higher under group incentives. We conclude that the use of ABC, without consideration of employee incentives, may not result in the desired cost control and process reengineering benefits. In this simulation, students are directly involved in providing the data, so they find the inferences drawn to be compelling.

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38

Besseghini, Eurosia, and Fabrizio Turchi. "Boosting medical technological innovation through finite element simulation." Reinforced Plastics 62, no. 1 (January 2018): 32–34. http://dx.doi.org/10.1016/j.repl.2017.11.004.

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39

Reed, Trent, Amy Hoyt, and Donna Quinones. "Board #237 - Program Innovation Improve Simulation Education Efficiency." Simulation in Healthcare: Journal of the Society for Simulation in Healthcare 9, no. 6 (December 2014): 464. http://dx.doi.org/10.1097/01.sih.0000459376.80980.d5.

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Scarbecz, Mark, Teresa Britt, and Marcia Seeberg. "Board #240 - Program Innovation Simulation and Dental Education." Simulation in Healthcare: Journal of the Society for Simulation in Healthcare 9, no. 6 (December 2014): 465. http://dx.doi.org/10.1097/01.sih.0000459379.26722.df.

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Aggarwal, Rajesh. "Simnovate: simulation, innovation and education for better healthcare." BMJ Simulation and Technology Enhanced Learning 3, Suppl 1 (March 2017): S1—S2. http://dx.doi.org/10.1136/bmjstel-2016-000184.

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Simulation has already transformed medical education, and holds the power to shape modern healthcare systems, communities and populations. Simnovate is a mission, a community and a partnership of passionate, driven and game-changing individuals, who wish to see the change we can make together, in the world, right now. Four domains were defined: patient safety, medical technologies, global health and pervasive learning, with domain group experts that span healthcare simulation, outcomes research, aviation, serious gaming, patient safety, economics, machine learning, biorobotics, implementation science, global health and the visual arts. Bringing together simulation, innovation and education, for better health and care.

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Starkweather, Angela Renee, and Suzie Kardong-Edgren. "Diffusion of Innovation: Embedding Simulation into Nursing Curricula." International Journal of Nursing Education Scholarship 5, no. 1 (January 20, 2008): 1–11. http://dx.doi.org/10.2202/1548-923x.1567.

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Wang, Bochao, and Young B. Moon. "Hybrid modeling and simulation for innovation deployment strategies." Industrial Management & Data Systems 113, no. 1 (March 11, 2013): 136–54. http://dx.doi.org/10.1108/02635571311289719.

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Deutsch, Ellen S., Nikolas H. Blevins, Jo A. Shapiro, Sonya Malekzadeh, and Craig Reickert. "Simulation: Disruptive Innovation and Our Quest to Excel." Otolaryngology–Head and Neck Surgery 147, no. 2_suppl (August 2012): P18. http://dx.doi.org/10.1177/0194599812449008a30.

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Kiesling, Elmar, Markus Günther, Christian Stummer, and Lea M. Wakolbinger. "Agent-based simulation of innovation diffusion: a review." Central European Journal of Operations Research 20, no. 2 (May 31, 2011): 183–230. http://dx.doi.org/10.1007/s10100-011-0210-y.

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Xia, Dehong, Gang Zhang, and Liang Guo. "Numerical simulation and innovation on magnesium reduction process." Journal of Thermal Science 15, no. 3 (September 2006): 269–73. http://dx.doi.org/10.1007/s11630-006-0269-2.

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Beavis, Andrew W., and James W. Ward. "Innovation in education: computer simulation in physics training." Journal of Physics: Conference Series 1305 (August 2019): 012057. http://dx.doi.org/10.1088/1742-6596/1305/1/012057.

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Vora, Samreen, Joyce Li, Maybelle Kou, Vivienne Ng, Amanda Price, Ilene Claudius, Shruti Kant, Elizabeth Sanseau, Manu Madhok, and Marc Auerbach. "ACEP SimBox: A Pediatric Simulation-Based Training Innovation." Annals of Emergency Medicine 78, no. 3 (September 2021): 346–54. http://dx.doi.org/10.1016/j.annemergmed.2021.03.040.

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Shultz, Thomas R., Marcel Montrey, and Lucy M. Aplin. "Modelling the spread of innovation in wild birds." Journal of The Royal Society Interface 14, no. 131 (June 2017): 20170215. http://dx.doi.org/10.1098/rsif.2017.0215.

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We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms.

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Ginters, Egils, Artis Aizstrauts, Dace Aizstrauta, Ieva Lauberte, Miquel Angel, Piera Eroles, Roman Buil, Peter Sonntagbauer, and Susanne Sonntagbauer. "FP7 FUPOL PROJECT – INNOVATION IN POLICY SCIENCE." CBU International Conference Proceedings 1 (June 30, 2013): 231–37. http://dx.doi.org/10.12955/cbup.v1.39.

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Mathematically justified planning of policy is extremely important because any wrong decision can lead to serious consequences. It is no secret that mathematical modelling and other advanced analytical methods are rarely used for policy planning and decision impact forecasting because those require specific knowledge. The FP7 FUPOL project aims at a completely new approach to traditional policy analysis providing direct access for policy decision makers to domain uses cases modelling and verification on FUPOL Simulator and visualisation of the results in the form suitable for beneficiaries. Policy domain uses cases models are versatile, therefore architecture of the simulator must fit to the requirements of complexity and usability that determines involving heterogeneous agent-based and system dynamics simulation technologies and distributed simulation. The article deals with FUPOL approach in policy modelling and simulation, simulator designing, and sustainability assessment of provided technology. The FUPOL approach promotes simultaneously running of heterogeneous use case simulation models enhancing performance of simulation session. Belonging to open source spreads potential users’ network thus reducing errors in simulation and also in policy decision making. Web services SOA based architecture enhances integration with other decision making and service tools.

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