MATHEMATICAL MODELING FOR THE ORGANIZATIONAL BEHAVIOR DUE TO AN EDUCATIONAL INNOVATION VIA COMPARTMENTAL ANALYSIS

10.6036/10237 ◽  
2021 ◽  
Vol DYNA-ACELERADO (0) ◽  
pp. [ 1 p.]-[ 1 p.]
Author(s):  
LUIS CARLOS FÉLIX HERRÁN ◽  
ROSALBA FERNANDEZ LOPEZ ◽  
VICTOR BENITEZ BALTAZAR ◽  
ALEJANDRO SAID ◽  
YASSER DAVIZON CASTILLO ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Stability Analysis ◽  
Organizational Behavior ◽  
Educational Innovation ◽  
Compartmental Analysis ◽  
Technical Note ◽  
Technological Educational ◽  
The Impact

This technical note presents the mathematical modeling for the organizational behavior in a university, considering a technological educational innovation. This by applying compartmental analysis, considering the impact at strategic, tactical, and operational levels. Keywords: Mathematical modeling; Stability analysis; Compartmental analysis; Organizational behavior; Educational innovation

scholarly journals ORGANIZATIONAL DEVELOPMENT DUE TO A TECHNOLOGICAL EDUCATIONAL INNOVATION

2021 ◽  
Vol 7 (1) ◽  
pp. [10 p.]-[10 p.]
Author(s):  
LUIS CARLOS FÉLIX HERRÁN ◽  
ROSALBA FERNANDEZ LOPEZ ◽  
VICTOR BENITEZ BALTAZAR ◽  
ALEJANDRO SAID ◽  
YASSER DAVIZON CASTILLO ◽  
...  
Keyword(s):  
Organizational Learning ◽  
Organizational Behavior ◽  
Organizational Development ◽  
Research Work ◽  
Educational Innovation ◽  
Research Problem ◽  
Technological Educational ◽  
Remote Lab ◽  
Intermediate Element ◽  
The Impact

ABSTRACT: This study presents a research work about the impact of a technological educational innovation implementation, titled Remote Laboratories, on the Organizational Development, from the perspective of Organizational Behavior. This innovative analysis approach raises the research problem as a system where the input is an educational innovation and the output is Organizational Development. An intermediate element is the Organizational Learning and correlations are constructed from the perspective of Organizational Behavior. The proposed system has a feedback to detect the opportunity areas based on the desired performance indices. The findings generated from the case study are supported by a research methodology that includes: problem´s description, hypothesis, participants, instruments, analysis of results, findings and conclusions. The obtained results are relevant for the industry because they can serve as a reference to managers responsible for the technological innovation. Findings and conclusions constitute a collection of experiences that could contribute to increase organizational development of educational institutions and companies. Keywords: organizational behavior, organizational learning, organizational development, remote lab, educational innovation

scholarly journals Red tape and psychological capital: a counterbalancing act for professionals in street-level bureaucracies

2020 ◽  
Author(s):  
A Dudau ◽  
G Kominis ◽  
Y Brunetto
Keyword(s):  
Local Government ◽  
Organizational Behavior ◽  
Psychological Capital ◽  
Negative Impact ◽  
Practical Implication ◽  
Well Being ◽  
Government Employees ◽  
Street Level ◽  
Red Tape ◽  
The Impact

Abstract Assuming that red tape is inevitable in institutions, and drawing on positive organizational behavior, we compare the impact of individual psychological capital on the ability of street-level bureaucrats (SLBs) with different professional backgrounds to work within the confines of red tape. The two SLB professions investigated here are nurses and local government employees; and the work outcomes of interest to this study are well-being and engagement. The findings show that red tape has a different impact on each professional group but, encouragingly, they also indicate that psychological capital has a compensatory effect. Implications include nurses requiring more psychological resources than local government employees to counteract the negative impact of red tape. A practical implication for managers is that, if perception of red tape in organizations is set to increase or to stay constant, enhancing the psychological capital of professionals in SLB roles, through specific interventions, may be beneficial to professionals and organizations alike.

Best Practices for Modeling Egocentric Social Network Data and Health Outcomes

2021 ◽  
pp. 193758672110137
Author(s):  
Jacqueline M. Burgette ◽  
Jacquelin Rankine ◽  
Alison J. Culyba ◽  
Kar-Hai Chu ◽  
Kathleen M. Carley
Keyword(s):  
Social Network ◽  
Best Practices ◽  
Health Outcomes ◽  
Organizational Behavior ◽  
Network Data ◽  
Egocentric Networks ◽  
Covariate Selection ◽  
Social Network Modeling ◽  
Egocentric Network ◽  
The Impact

Objective/Aim: We describe best practices for modeling egocentric networks and health outcomes using a five-step guide. Background: Social network analysis (SNA) is common in social science fields and has more recently been used to study health-related topics including obesity, violence, substance use, health organizational behavior, and healthcare utilization. SNA, alone or in conjunction with spatial analysis, can be used to uniquely evaluate the impact of the physical or built environment on health. The environment can shape the presence, quality, and function of social relationships with spatial and network processes interacting to affect health outcomes. While there are some common measures frequently used in modeling the impact of social networks on health outcomes, there is no standard approach to social network modeling in health research, which impacts rigor and reproducibility. Methods: We provide an overview of social network concepts and terminology focused on egocentric network data. Egocentric, or personal networks, take the perspective of an individual who identifies their own connections (alters) and also the relationships between alters. Results: We describe best practices for modeling egocentric networks and health outcomes according to the following five-step guide: (1) model selection, (2) social network exposure variable and selection considerations, (3) covariate selection related to sociodemographic and health characteristics, (4) covariate selection related to social network characteristics, and (5) analytic considerations. We also present an example of SNA. Conclusions: SNA provides a powerful repertoire of techniques to examine how relationships impact attitudes, experiences, and behaviors—and subsequently health.

scholarly journals Linked(In)g Sport Management Education with the Sport Industry: A Preliminary Study

2021 ◽  
Vol 13 (4) ◽  
pp. 2275
Author(s):  
Samuel López-Carril ◽  
Miguel Villamón ◽  
María Huertas González-Serrano
Keyword(s):  
Social Media ◽  
Sport Management ◽  
Management Education ◽  
Educational Innovation ◽  
Two Dimensions ◽  
Management Tools ◽  
Sport Industry ◽  
Post Test ◽  
Management Students ◽  
The Impact

Social media are one of the most valuable management tools used by sport managers in the fulfilment of their daily tasks. However, the studies that share and analyse the impact of educational experiences that incorporate social media into sport management education for professional purposes are scarce to date. Thus, this study presents an educational innovation piloted in a sport management course where LinkedIn—the social media most associated with the professional sphere—is introduced through an experiential learning methodology, as a driver of students’ career development and as a tool to keep up to date and interact with the sport industry. To assess the learning outcomes, a new scale was developed and tested. A total of 90 Spanish undergraduate sport management students (M = 22.71; SD = 3.84) participated in the study, partaking in a pre-test and a post-test. Regarding the results linked to the testing of the scale, the statistical analysis reflects the scale’s two-dimensional nature, explaining 68.78% of the variance, presenting good psychometric properties (α = 0.95). On the other hand, significant increases in all the scale items between the two measures were obtained, with large effects size in the two dimensions (Cohen’s d ≥ 0.80). Therefore, it is concluded that LinkedIn can help to develop the professional profile of sport management students, Linked(In)g what is taught in the classroom with what the sport industry demands.

Mathematical modeling of the impact of a pulse seismic source on geological media

2020 ◽  
Author(s):  
E. A. Efimov ◽  
V. M. Sadovskii ◽  
O. V. Sadovskaya
Keyword(s):  
Mathematical Modeling ◽  
Seismic Source ◽  
The Impact

scholarly journals Technical note: Boundary layer height determination from Lidar for improving air pollution episode modelling: development of new algorithm and evaluation

2017 ◽  
Author(s):  
Ting Yang ◽  
Zifa Wang ◽  
Wei Zhang ◽  
Alex Gbaguidi ◽  
Nubuo Sugimoto ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Air Pollution ◽  
High Performance ◽  
Accurate Determination ◽  
Technical Note ◽  
Strong Increase ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Retrieval Algorithms ◽  
The Impact

Abstract. Predicting air pollution events in low atmosphere over megacities requires thorough understanding of the tropospheric dynamic and chemical processes, involving notably, continuous and accurate determination of the boundary layer height (BLH). Through intensive observations experimented over Beijing (China), and an exhaustive evaluation existing algorithms applied to the BLH determination, persistent critical limitations are noticed, in particular over polluted episodes. Basically, under weak thermal convection with high aerosol loading, none of the retrieval algorithms is able to fully capture the diurnal cycle of the BLH due to pollutant insufficient vertical mixing in the boundary layer associated with the impact of gravity waves on the tropospheric structure. Subsequently, a new approach based on gravity wave theory (the cubic root gradient method: CRGM), is developed to overcome such weakness and accurately reproduce the fluctuations of the BLH under various atmospheric pollution conditions. Comprehensive evaluation of CRGM highlights its high performance in determining BLH from Lidar. In comparison with the existing retrieval algorithms, the CRGM potentially reduces related computational uncertainties and errors from BLH determination (strong increase of correlation coefficient from 0.44 to 0.91 and significant decrease of the root mean square error from 643 m to 142 m). Such newly developed technique is undoubtedly expected to contribute to improve the accuracy of air quality modelling and forecasting systems.

scholarly journals The Relationship between Person Organization Fit, Person-Job-Fit and Turnover Intention in Banking Sector of Pakistan: The Mediating Role of Psychological Climate

2012 ◽  
Vol 2 (3) ◽  
pp. 172 ◽  
Author(s):  
Masoodul Hassan ◽  
Ammara Akram ◽  
Sana Naz
Keyword(s):  
Organizational Behavior ◽  
Turnover Intention ◽  
Banking Sector ◽  
Negative Relationship ◽  
Psychological Climate ◽  
Job Fit ◽  
Mediating Role ◽  
Person Organization Fit ◽  
The Impact ◽  
The Relationship

In last few decades, employees’ job related attitudes and behaviors have remained topics of considerable interest in the fields of organizational behavior and human resource management. This study aims to explore the impact of person-organization-fit and person-job-fit on employee turnover intention while considering psychological climate as a mediating variable. Sample for this research is consisted of 260 employees from top five commercial banks of large cities of Pakistan. SPSS 17 is used for analyzing the data. Correlation and regression analysis is used to test the direct and mediating relationship between key variables. Results indicate that both person-organization-fit and person-job-fit have negative relationship with turnover intention. Psychological climate partially mediates the relationship between person-organization-fit and turnover intention while fully mediates the relationship between person-job-fit and turnover intention.

scholarly journals The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Miguel A. L. Nicolelis ◽  
Rafael L. G. Raimundo ◽  
Pedro S. Peixoto ◽  
Cecilia S. Andreazzi
Keyword(s):  
Mathematical Modeling ◽  
Intensive Care ◽  
Road Traffic ◽  
Geographic Spread ◽  
Boomerang Effect ◽  
Entry Points ◽  
Entire Country ◽  
Major Factors ◽  
The Impact ◽  
Care Availability

AbstractAlthough international airports served as main entry points for SARS-CoV-2, the factors driving the uneven geographic spread of COVID-19 cases and deaths in Brazil remain mostly unknown. Here we show that three major factors influenced the early macro-geographical dynamics of COVID-19 in Brazil. Mathematical modeling revealed that the “super-spreading city” of São Paulo initially accounted for more than 85% of the case spread in the entire country. By adding only 16 other spreading cities, we accounted for 98–99% of the cases reported during the first 3 months of the pandemic in Brazil. Moreover, 26 federal highways accounted for about 30% of SARS-CoV-2’s case spread. As cases increased in the Brazilian interior, the distribution of COVID-19 deaths began to correlate with the allocation of the country’s intensive care units (ICUs), which is heavily weighted towards state capitals. Thus, severely ill patients living in the countryside had to be transported to state capitals to access ICU beds, creating a “boomerang effect” that contributed to skew the distribution of COVID-19 deaths. Therefore, if (i) a lockdown had been imposed earlier on in spreader-capitals, (ii) mandatory road traffic restrictions had been enforced, and (iii) a more equitable geographic distribution of ICU beds existed, the impact of COVID-19 in Brazil would be significantly lower.

Effect of the Condition Number of the Inverse Fourier Transform Matrix on the Solution Behavior of the Time Spectral Equation System

2020 ◽  
Author(s):  
Sen Zhang ◽  
Dingxi Wang ◽  
Yi Li ◽  
Hangkong Wu ◽  
Xiuquan Huang
Keyword(s):  
Fourier Transform ◽  
Stability Analysis ◽  
Condition Number ◽  
Inverse Fourier Transform ◽  
Real Life ◽  
Equation System ◽  
Time Instant ◽  
Transform Matrix ◽  
Spectral Equation ◽  
The Impact

Abstract The time spectral method is a very popular reduced order frequency method for analyzing unsteady flow due to its advantage of being easily extended from an existing steady flow solver. Condition number of the inverse Fourier transform matrix used in the method can affect the solution convergence and stability of the time spectral equation system. This paper aims at evaluating the effect of the condition number of the inverse Fourier transform matrix on the solution stability and convergence of the time spectral method from two aspects. The first aspect is to assess the impact of condition number using a matrix stability analysis based upon the time spectral form of the scalar advection equation. The relationship between the maximum allowable Courant number and the condition number will be derived. Different time instant groups which lead to the same condition number are also considered. Three numerical discretization schemes are provided for the stability analysis. The second aspect is to assess the impact of condition number for real life applications. Two case studies will be provided: one is a flutter case, NASA rotor 67, and the other is a blade row interaction case, NASA stage 35. A series of numerical analyses will be performed for each case using different time instant groups corresponding to different condition numbers. The conclusion drawn from the two real life case studies will corroborate the relationship derived from the matrix stability analysis.

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