scholarly journals Effects of climate and environmental variance on the performance of a novel peatland-based integrated multi-trophic aquaculture (IMTA) system: Implications and opportunities for advancing research and disruptive innovation post COVID-19 era

2022 ◽  
pp. 153073
Author(s):  
E.A. O'Neill ◽  
A.P. Morse ◽  
N.J. Rowan
Keyword(s):  
Disruptive Innovation ◽  
Environmental Variance

Disruptive innovation and operationalization in local and sustainable food systems: Examining the University of Toronto-Local Food Plus partnership

2019 ◽  
Vol 6 (1) ◽  
pp. 120-139
Author(s):  
Lori Stahlbrand
Keyword(s):  
Food Systems ◽  
Large Scale ◽  
Food System ◽  
Local Food ◽  
Disruptive Innovation ◽  
Government Support ◽  
Sustainable Food ◽  
University Of Toronto ◽  
The University

This paper traces the partnership between the University of Toronto and the non-profit Local Food Plus (LFP) to bring local sustainable food to its St. George campus. At its launch, the partnership represented the largest purchase of local sustainable food at a Canadian university, as well as LFP’s first foray into supporting institutional procurement of local sustainable food. LFP was founded in 2005 with a vision to foster sustainable local food economies. To this end, LFP developed a certification system and a marketing program that matched certified farmers and processors to buyers. LFP emphasized large-scale purchases by public institutions. Using information from in-depth semi-structured key informant interviews, this paper argues that the LFP project was a disruptive innovation that posed a challenge to many dimensions of the established food system. The LFP case study reveals structural obstacles to operationalizing a local and sustainable food system. These include a lack of mid-sized infrastructure serving local farmers, the domination of a rebate system of purchasing controlled by an oligopolistic foodservice sector, and embedded government support of export agriculture. This case study is an example of praxis, as the author was the founder of LFP, as well as an academic researcher and analyst.

Effective Customer Support System of Life Insurance Companies

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Rajesh Srivastava ◽  
Dr. Preeti Sharma
Keyword(s):  
Life Insurance ◽  
Economies Of Scale ◽  
New Technologies ◽  
Insurance Industry ◽  
Integrated Approach ◽  
Customer Experience ◽  
Disruptive Innovation ◽  
Insurance Companies ◽  
Insurance Business ◽  
Strategic Imperative

Increased competition, new technologies and the shift in power from the provider to the customer have produced unrelenting pressure on life insurance business. The market forces point to one overwhelming strategic imperative: customer-focused strategy. Customers are willing to build long-term relationships based on trust and mutual respect with firms that provide a differentiated and personalized service offering. Over the past few years, life insurance industry responded to intensified competition and high customer attrition by entering each other’s markets to capture greater “wallet share” and ostensibly lower their economies of scale. The service delivery process is influenced by quality of personnel, information technology, internal processes, human resource practices, and even an institution’s own change orientation. Now a day’s customers are demanding seamless, multi-channel sales and service experiences. Simultaneously, other players are looking for opportunities to invade this space or to redefine it through disruptive innovation. The result is forcing life insurance companies to examine a more balanced, integrated approach to the customer experience and growth. This research, we analyze the need, preference and satisfaction of customers in life insurance business and provide perspective on how to improve the customer experience.

Humans as a Service

2018 ◽  
Author(s):  
Jeremias Prassl
Keyword(s):  
Business Models ◽  
Disruptive Innovation ◽  
Level Playing Field ◽  
Employment Relationships ◽  
Playing Field ◽  
On Demand ◽  
Gig Economy ◽  
Wide Range ◽  
Digital Work ◽  
Stable Employment

The rise of the gig economy is disrupting business models across the globe. Platforms’ digital work intermediation has had a profound impact on traditional conceptions of the employment relationship. The completion of ‘tasks’, ‘gigs’, or ‘rides’ in the (digital) crowd fundamentally challenges our understanding of work in modern labour markets: gone are the stable employment relationships between firms and workers, replaced by a world in which everybody can be ‘their own boss’ and enjoy the rewards—and face the risks—of independent businesses. Is this the future of work? What are the benefits and challenges of crowdsourced work? How can we protect consumers and workers without stifling innovation? Humans as a Service provides a detailed account of the growth and operation of gig-economy platforms, and develops a blueprint for solutions to the problems facing on-demand workers, platforms, and their customers. Following a brief introduction to the growth and operation of on-demand platforms across the world, the book scrutinizes competing narratives about ‘gig’ work. Drawing on a wide range of case studies, it explores how claims of ‘disruptive innovation’ and ‘micro-entrepreneurship’ often obscure the realities of precarious work under strict algorithmic surveillance, and the return to a business model that has existed for centuries. Humans as a Service shows how employment law can address many of these problems: gigs, tasks, and rides are work—and should be regulated as such. A concluding chapter demonstrates the broader benefits of a level playing field for consumers, taxpayers, and innovative entrepreneurs.

Are e-learning Webinars the future of medical education? An exploratory study of a disruptive innovation in the COVID-19 era

2020 ◽  
pp. 1-10
Author(s):  
Colin J. McMahon ◽  
Justin T. Tretter ◽  
Theresa Faulkner ◽  
R. Krishna Kumar ◽  
Andrew N. Redington ◽  
...  
Keyword(s):  
Deep Learning ◽  
Carbon Footprint ◽  
Quantitative Research ◽  
Survey Design ◽  
Hybrid Approach ◽  
Disruptive Innovation ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
E Learning ◽  
The Impact

Abstract Objective: This study investigated the impact of the Webinar on deep human learning of CHD. Materials and methods: This cross-sectional survey design study used an open and closed-ended questionnaire to assess the impact of the Webinar on deep learning of topical areas within the management of the post-operative tetralogy of Fallot patients. This was a quantitative research methodology using descriptive statistical analyses with a sequential explanatory design. Results: One thousand-three-hundred and seventy-four participants from 100 countries on 6 continents joined the Webinar, 557 (40%) of whom completed the questionnaire. Over 70% of participants reported that they “agreed” or “strongly agreed” that the Webinar format promoted deep learning for each of the topics compared to other standard learning methods (textbook and journal learning). Two-thirds expressed a preference for attending a Webinar rather than an international conference. Over 80% of participants highlighted significant barriers to attending conferences including cost (79%), distance to travel (49%), time commitment (51%), and family commitments (35%). Strengths of the Webinar included expertise, concise high-quality presentations often discussing contentious issues, and the platform quality. The main weakness was a limited time for questions. Just over 53% expressed a concern for the carbon footprint involved in attending conferences and preferred to attend a Webinar. Conclusion: E-learning Webinars represent a disruptive innovation, which promotes deep learning, greater multidisciplinary participation, and greater attendee satisfaction with fewer barriers to participation. Although Webinars will never fully replace conferences, a hybrid approach may reduce the need for conferencing, reduce carbon footprint. and promote a “sustainable academia”.

scholarly journals HealthTEC Innovation Design - a proposal for a novel Master degree program based on Unmet Clinical Need, global Healthcare Challenges, and 21st century skills

2020 ◽  
Vol 6 (3) ◽  
pp. 599-603
Author(s):  
Michael Friebe
Keyword(s):  
Machine Learning ◽  
21St Century ◽  
21St Century Skills ◽  
Data Analytics ◽  
Industrial Revolution ◽  
Data Gathering ◽  
Healthcare Systems ◽  
Disruptive Innovation ◽  
Incremental Innovation ◽  
Healthcare Provision

AbstractThe effectiveness, efficiency, availability, agility, and equality of global healthcare systems are in question. The COVID-19 pandemic have further highlighted some of these issues and also shown that healthcare provision is in many parts of the world paternalistic, nimble, and often governed too extensively by revenue and profit motivations. The 4th industrial revolution - the machine learning age - with data gathering, analysis, optimisation, and delivery changes has not yet reached Healthcare / Health provision. We are still treating patients when they are sick rather then to use advanced sensors, data analytics, machine learning, genetic information, and other exponential technologies to prevent people from becoming patients or to help and support a clinicians decision. We are trying to optimise and improve traditional medicine (incremental innovation) rather than to use technologies to find new medical and clinical approaches (disruptive innovation). Education of future stakeholders from the clinical and from the technology side has not been updated to Health 4.0 demands and the needed 21st century skills. This paper presents a novel proposal for a university and innovation lab based interdisciplinary Master education of HealthTEC innovation designers.

scholarly journals Evolutionary Stability for Interactions among Kin under Quantitative Inheritance.

Genetics ◽  
1989 ◽  
Vol 121 (4) ◽  
pp. 877-889
Author(s):  
A B Harper
Keyword(s):  
Inclusive Fitness ◽  
Fitness Function ◽  
Quantitative Inheritance ◽  
Evolutionarily Stable Strategies ◽  
Environmental Variance ◽  
Pairwise Interactions ◽  
Simplifying Assumptions ◽  
Multilocus Model ◽  
Evolutionarily Stable

Abstract The theory of evolutionarily stable strategies (ESS) predicts the long-term evolutionary outcome of frequency-dependent selection by making a number of simplifying assumptions about the genetic basis of inheritance. I use a symmetrized multilocus model of quantitative inheritance without mutation to analyze the results of interactions between pairs of related individuals and compare the equilibria to those found by ESS analysis. It is assumed that the fitness changes due to interactions can be approximated by the exponential of a quadratic surface. The major results are the following. (1) The evolutionarily stable phenotypes found by ESS analysis are always equilibria of the model studied here. (2) When relatives interact, one of the two conditions for stability of equilibria differs between the two models; this can be accounted for by positing that the inclusive fitness function for quantitative characters is slightly different from the inclusive fitness function for characters determined by a single locus. (3) The inclusion of environmental variance will in general change the equilibrium phenotype, but the equilibria of ESS analysis are changed to the same extent by environmental variance. (4) A class of genetically polymorphic equilibria occur, which in the present model are always unstable. These results expand the range of conditions under which one can validly predict the evolution of pairwise interactions using ESS analysis.

scholarly journals Characterization of Deleterious Mutations in Outcrossing Populations

Genetics ◽  
1998 ◽  
Vol 150 (2) ◽  
pp. 945-956 ◽  
Author(s):  
Hong-Wen Deng
Keyword(s):  
Genetic Variation ◽  
Genetic Variance ◽  
Estimation Bias ◽  
Deleterious Mutations ◽  
Environmental Variance ◽  
Higher Power ◽  
Sib Mating ◽  
The Mean ◽  
Simulation Results

Abstract Deng and Lynch recently proposed estimating the rate and effects of deleterious genomic mutations from changes in the mean and genetic variance of fitness upon selfing/outcrossing in outcrossing/highly selfing populations. The utility of our original estimation approach is limited in outcrossing populations, since selfing may not always be feasible. Here we extend the approach to any form of inbreeding in outcrossing populations. By simulations, the statistical properties of the estimation under a common form of inbreeding (sib mating) are investigated under a range of biologically plausible situations. The efficiencies of different degrees of inbreeding and two different experimental designs of estimation are also investigated. We found that estimation using the total genetic variation in the inbred generation is generally more efficient than employing the genetic variation among the mean of inbred families, and that higher degree of inbreeding employed in experiments yields higher power for estimation. The simulation results of the magnitude and direction of estimation bias under variable or epistatic mutation effects may provide a basis for accurate inferences of deleterious mutations. Simulations accounting for environmental variance of fitness suggest that, under full-sib mating, our extension can achieve reasonably well an estimation with sample sizes of only ∼2000-3000.

Sign in / Sign up

Export Citation Format

Share Document