New model of endowment insurance driven by insurance technology - a case study of Taikang endowment community

2020 ◽  
Vol 6 (1) ◽  
pp. 9-18
Author(s):  
Jian Chen ◽  
Jin Xiong ◽  
Danning Xie ◽  
Junyuan Zhang ◽  
Xiaoting Gu ◽  
...  
Cities ◽  
2013 ◽  
Vol 31 ◽  
pp. 394-403 ◽  
Author(s):  
Elham Akhondzadeh-Noughabi ◽  
Somayeh Alizadeh ◽  
Ali-Mohammad Ahmadvand ◽  
Behrouz Minaei-Bidgoli

2018 ◽  
Vol 7 (2) ◽  
pp. 30
Author(s):  
Cristian Lucas Endler ◽  
Pedro Paulo de Andrade Júnior

This article aims to propose a new model of technological innovations, as well as using it in a case study in the automotive industry. After an analysis of the main scientific databases, it was verified that the present work is unprecedented in presenting a unified model of identification and management of technological innovations. In methodological terms, the bibliometric and systemic analyzes were performed in order to identify the main technological innovations inherent in the automotive industry. In terms of research results, a cohesive innovation model was obtained, which, once based on the concepts of sensitive innovation and latent innovation, allows the identification and the consequent valuation of the economic potential of the main technological innovations in the area desired by the manager who will apply it. As an example, the model was applied specifically in the automotive sector, but its methodology can be generalized to any area of industrial production.


2021 ◽  
Vol 2 (3) ◽  
pp. 74-98
Author(s):  
Peter Hugo Nelson

ABSTRACT Students develop and test simple kinetic models of the spread of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Microsoft Excel is used as the modeling platform because it is nonthreatening to students and it is widely available. Students develop finite difference models and implement them in the cells of preformatted spreadsheets following a guided inquiry pedagogy that introduces new model parameters in a scaffolded step-by-step manner. That approach allows students to investigate the implications of new model parameters in a systematic way. Students fit the resulting models to reported cases per day data for the United States using least squares techniques with Excel's Solver. Using their own spreadsheets, students discover for themselves that the initial exponential growth of COVID-19 can be explained by a simplified unlimited growth model and by the susceptible-infected-recovered (SIR) model. They also discover that the effects of social distancing can be modeled using a Gaussian transition function for the infection rate coefficient and that the summer surge was caused by prematurely relaxing social distancing and then reimposing stricter social distancing. Students then model the effect of vaccinations and validate the resulting susceptible-infected-recovered-vaccinated (SIRV) model by showing that it successfully predicts the reported cases per day data from Thanksgiving through the holiday period up to 14 February 2021. The same SIRV model is then extended and successfully fits the fourth peak up to 1 June 2021, caused by further relaxation of social distancing measures. Finally, students extend the model up to the present day (27 August 2021) and successfully account for the appearance of the delta variant of the SARS-CoV-2 virus. The fitted model also predicts that the delta variant peak will be comparatively short, and the cases per day data should begin to fall off in early September 2021, counter to current expectations. This case study makes an excellent capstone experience for students interested in scientific modeling.


2022 ◽  
pp. 92-116
Author(s):  
Andrea Altundag

The purpose of this chapter is to illustrate the application of advanced data analytics in the domain of strategic procurement and its effects on processes, people, and on the procurement business model itself. Advanced data analytics are generally accepted as being one of the key enablers for organisations to build their capabilities to adapt quickly and navigate through volatile business circumstances successfully. Strategic procurement is in a pivotal position in a network of external suppliers and internal stakeholders, and thus ideally positioned to benefit from the introduction of advanced data analytics. However, to date, the application of these technologies has been limited, and clear evidence of benefits delivery is yet to be demonstrated. This chapter draws upon research results from a detailed case study in the aviation industry to assess the benefits of advanced data analytics in the strategic procurement function and puts forward a maturity model of relevance to both researchers and procurement professionals.


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