The Impact of Research Collaboration Intention on Technology Transfer in Virtual Academic Communities: A Conditional Process Model

2021 ◽  
Author(s):  
Chunlai Yan ◽  
Hongxia Li
Keyword(s):  
Technology Transfer ◽  
Process Model ◽  
Research Collaboration ◽  
Academic Communities ◽  
The Impact

scholarly journals Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

2020 ◽  
Vol 13 (1) ◽  
pp. 56
Author(s):  
Tino Herden
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Success Factors ◽  
Research Collaboration ◽  
Future Research ◽  
Structured Interviews ◽  
Chain Management ◽  
Domain Specific ◽  
The Status ◽  
The Impact

Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains.Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin.Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed.Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.

scholarly journals Evaluating interventions with victims of intimate partner violence: a community psychology approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Cinzia Albanesi ◽  
Carlo Tomasetto ◽  
Veronica Guardabassi
Keyword(s):  
Intimate Partner Violence ◽  
Social Services ◽  
Psychological Health ◽  
Partner Violence ◽  
Process Model ◽  
Professional Training ◽  
Phenomenological Approach ◽  
Intimate Partner ◽  
Structured Interviews ◽  
The Impact

Abstract Purpose Intimate Partner Violence (IPV) is one of the most common forms of domestic violence, with profound implication for women's physical and psychological health. In this text we adopted the Empowerment Process Model (EPM) by Cattaneo and Goodman (Psychol Violence 5(1):84–94) to analyse interventions provided to victims of IPV by a Support Centre for Women (SCW) in Italy, and understand its contribution to women’s empowerment. Method We conducted semi-structured interviews with ten women who had been enrolled in a program for IPV survivors at a SCW in the past three years. The interviews focused on the programs’ aims, actions undertaken to reach them, and the impact on the women’s lives, and were analysed using an interpretative phenomenological approach. Results Results showed that the interventions provided by the SWC were adapted according to women's needs. In the early phases, women’s primary aim was ending violence, and the intervention by the SCW was deemed as helpful to the extent it provided psychological support, protection and safe housing. Women’s aims subsequently moved to self-actualisation and economic and personal independence which required professional training, internships, and social support. Although satisfying the majority of the women’s expectations, other important needs (e.g., economic support or legal services) were poorly addressed, and cooperation with other services (e.g., police or social services) was sometimes deemed as critical. Conclusions By evaluating a program offered by a SCW to IPV survivors through the lens of the EPM model, we found that women deemed the program as effective when both individual resources and empowerment processes were promoted. Strengths, limitations and implications are discussed.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals Male and Female Partner-Caregivers’ Burden: Does It Get Worse Over Time?

2018 ◽  
Vol 59 (6) ◽  
pp. 1103-1111 ◽  
Author(s):  
Joukje C Swinkels ◽  
Marjolein I Broese van Groenou ◽  
Alice de Boer ◽  
Theo G van Tilburg
Keyword(s):  
Caregiver Burden ◽  
Process Model ◽  
Female Partner ◽  
General View ◽  
Data Set ◽  
Change Over Time ◽  
Men And Women ◽  
Wear And Tear ◽  
The Impact ◽  
Over Time

Abstract Background and Objectives The general view is that partner-caregiver burden increases over time but findings are inconsistent. Moreover, the pathways underlying caregiver burden may differ between men and women. This study examines to what degree and why partner-caregiver burden changes over time. It adopts Pearlin’s Caregiver Stress Process Model, as it is expected that higher primary and secondary stressors will increase burden and larger amounts of resources will lower burden. Yet, the impact of stressors and resources may change over time. The wear-and-tear model predicts an increase of burden due to a stronger impact of stressors and lower impact of resources over time. Alternatively, the adaptation model predicts a decrease of burden due to a lower impact of stressors and higher impact of resources over time. Research Design and Methods We used 2 observations with a 1-year interval of 279 male and 443 female partner-caregivers, derived from the Netherlands Older Persons and Informal Caregivers Survey Minimum Data Set. We applied multilevel regression analysis, stratified by gender. Results Adjusted for all predictors, caregiver burden increased over time for both men and women. For female caregivers, the impact of poor spousal health on burden increased and the impact of fulfillment decreased over time. Among male caregivers, the impact of predictors did not change over time. Discussion and Implications The increase of burden over time supports the wear-and-tear model, in particular for women. This study highlights the need for gender-specific interventions that are focused on enabling older partners to be better prepared for long-term partner-care.

scholarly journals How Can E-Cigarette Fear Appeals Improve the Perceived Threat, Fear, Anger, and Protection Motivation of Young People

2021 ◽  
Vol 12 ◽  
Author(s):  
Chengzhi Sun ◽  
Fangfei Wang ◽  
Mengmeng Jiang
Keyword(s):  
Young People ◽  
Process Model ◽  
Good Control ◽  
Fear Appeals ◽  
Smoking History ◽  
Protection Motivation ◽  
Fear Appeal ◽  
People’S Perception ◽  
Young Smokers ◽  
The Impact

The lack of awareness regarding the risks of e-cigarettes and the misleading business propaganda caused an increase in the popularity of e-cigarettes among young people. The effective communication of the risks associated with e-cigarettes is an important part of current work to control their usage, and the use of fear appeals is an effective method to achieve good control. Based on the Extended Parallel Process Model (EPPM) and Appraisal-Tendency Framework (ATF), this article presents a 2 × 2 control experiment to test the impact of fear appeals on the perception of risk, emotions, and behavioral motivation of young people aged 35 and less. A total of 333 valid samples of adolescents and young adults were included to investigate the different response paths to fear appeals among young people of different age, sex and smoking history. The results show that high-threat, high-efficacy fear appeals are able to: (1) significantly increase young people’s perception of the e-cigarette-associated threats, (2) trigger fear and anger amongst young people, and (3) stimulate their self-protection motivation. Fear appeals do not have an impact on young people’s perception of efficacy, regardless of their level of threat and efficacy. High fear appeals can also increase young people’s perception of threat, which in turn enhances their anger and protection motivation. Furthermore, while this type of fear appeal can enhance young women’s perception of efficacy, it cannot enhance the perception of e-cigarette risks in adolescents, young men and young smokers, regardless of their level of threat and efficacy. Young non-smokers have a higher perception of the risks involved in the use of e-cigarettes compared with young smokers.

scholarly journals Understanding Low-value Care and Associated De-implementation Processes: A Qualitative Study of Choosing Wisely Interventions Across Canadian Hospitals

2021 ◽  
Author(s):  
Gillian Parker ◽  
Monika Kastner ◽  
Karen Born ◽  
Nida Shahid ◽  
Whitney Berta
Keyword(s):  
Process Model ◽  
Healthcare Providers ◽  
Implementation Process ◽  
Choosing Wisely ◽  
Structured Interviews ◽  
Team Members ◽  
Implementation Processes ◽  
Healthcare Settings ◽  
National Campaigns ◽  
The Impact

Abstract Background:Choosing Wisely (CW) is an international movement comprised of national campaigns in more than 20 countries to reduce low-value care (LVC). Hospitals and healthcare providers are examining existing practices and putting interventions in place to reduce practices that offer little to no benefit to patients or may cause them harm. De-implementation, the reduction or removal of a healthcare practice is an emerging field of research. Little is known about the factors which (i) sustain LVC; and (ii) the magnitude of the problem of LVC. In addition, little is known about the processes of de-implementation, and if and how these processes differ from implementation endeavours. The objective of this study was to explicate the myriad factors which impact the processes and outcomes of de-implementation initiatives that are designed to address national Choosing Wisely campaign recommendations.Methods:Semi-structured interviews were conducted with individuals implementing Choosing Wisely Canada recommendations in healthcare settings in four provinces. The interview guide was developed using concepts from the literature and the Implementation Process Model (IPM) as a framework. All interviews were conducted virtually, recorded, and transcribed verbatim. Data were analysed using thematic analysis.Results:Seventeen Choosing Wisely team members were interviewed. Participants identified numerous provider factors, most notably habit, which sustain LVC. Contrary to reporting in recent studies, the majority of LVC in the sample was not ‘patient facing’; therefore, patients were not a significant driver for the LVC, nor a barrier to reducing it. Participants detailed aspects of the magnitude of the problems of LVC, specifically the impact of harm and resources. Unique factors influencing the processes of de-implementation reported were: influence of Choosing Wisely campaigns, availability of data, lack of targets and hard-coded interventions.Conclusions: This study explicates factors ranging from those which impact the maintenance of LVC to factors that impact the success of de-implementation interventions intended to reduce them. The findings draw attention to the significance of unintentional factors, highlight the importance of understanding the impact of harm and resources to reduce LVC and illuminate the overstated impact of patients in de-implementation literature. These findings illustrate the complexities of de-implementation.

scholarly journals Simulating the impact of vaccination rates on the initial stages of a COVID-19 outbreak in New Zealand (Aotearoa) with a stochastic model

2021 ◽  
Author(s):  
Leighton M Watson
Keyword(s):  
New Zealand ◽  
Stochastic Model ◽  
Process Model ◽  
Branching Process ◽  
Total Population ◽  
Median Number ◽  
Vaccination Rate ◽  
Vaccination Rates ◽  
The Impact ◽  
Different Levels

Aim: The August 2021 COVID-19 outbreak in Auckland has caused the New Zealand government to transition from an elimination strategy to suppression, which relies heavily on high vaccination rates in the population. As restrictions are eased and as COVID-19 leaks through the Auckland boundary, there is a need to understand how different levels of vaccination will impact the initial stages of COVID-19 outbreaks that are seeded around the country. Method: A stochastic branching process model is used to simulate the initial spread of a COVID-19 outbreak for different vaccination rates. Results: High vaccination rates are effective at minimizing the number of infections and hospitalizations. Increasing vaccination rates from 20% (approximate value at the start of the August 2021 outbreak) to 80% (approximate proposed target) of the total population can reduce the median number of infections that occur within the first four weeks of an outbreak from 1011 to 14 (25th and 75th quantiles of 545-1602 and 2-32 for V=20% and V=80%, respectively). As the vaccination rate increases, the number of breakthrough infections (infections in fully vaccinated individuals) and hospitalizations of vaccinated individuals increases. Unvaccinated individuals, however, are 3.3x more likely to be infected with COVID-19 and 25x more likely to be hospitalized. Conclusion: This work demonstrates the importance of vaccination in protecting individuals from COVID-19, preventing high caseloads, and minimizing the number of hospitalizations and hence limiting the pressure on the healthcare system.

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