key drivers
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2022 ◽  
Vol 174 ◽  
pp. 107054
L. Fabrizi ◽  
F. Cappella ◽  
F. Spagnoli ◽  
L. Nigro ◽  
A.M. Niveau-De-Villedary ◽  

2022 ◽  
Peer Schouten

There are so many roadblocks in Central Africa that it is hard to find a road that does not have one. Based on research in the Democratic Republic of Congo (DRC) and the Central African Republic (CAR), Peer Schouten maps more than a thousand of these roadblocks to show how communities, rebels and state security forces forge resistance and power out of control over these narrow points of passage. Schouten reveals the connections between these roadblocks in Central Africa and global supply chains, tracking the flow of multinational corporations and UN agencies alike through them, to show how they encapsulate a form of power, which thrives under conditions of supply chain capitalism. In doing so, he develops a new lens through which to understand what drives state formation and conflict in the region, offering a radical alternative to explanations that foreground control over minerals, territory or population as key drivers of Central Africa's violent history.

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Nitin Gupta ◽  
Prem Vrat ◽  
Ravindra Ojha

PurposeThe education sector acts as an input for every other sector and contributes around 7% to the service industry; hence, it is important to identify, measure and analyze the drivers that impact the delivered service quality.Design/methodology/approachThis paper used different approaches to identify measure and analyze the drivers that impact the service quality. In addition to a thorough literature review, qualitative tools like brainstorming, the focused group technique, and the survey technique have been used. Decision-making tools like the analytic hierarchy process (AHP), and a quantitative tool, one-sample t-test, with the help of MINITAB software, were used to analyze the inputs received from 179 experts. By using the stated approach, the planned research outcomes have been achieved.FindingsQuality of teachers, quality of students, quality of policies, and quality of facilities have been identified as the key drivers that impact quality of education. The paper highlights that the people quality drivers play a significantly important role in the quality of education when compared to the quality of non-people drivers. From the statistical analysis of the hypotheses, it was inferred that the People quality consisting of the quality of a teacher and the quality of students are the two prominent drivers to the Quality of education. This paper demonstrates the importance of the quality of a teacher and its significance to the quality of education. The recommendations made might be considered for the implementation, which can improve the quality of education in the country.Research limitations/implicationsThis paper is focused on the data collected from the experts in the top-ranked management institutes only. The data from the experts from undergraduate institutions and other management institutes could have added more value.Practical implicationsIn the paper, the drivers were identified and further analyzed to suggest that teacher quality is a dominant driver of education quality. The findings also suggest that there should be a high focus on having a great quality teacher as compared to the facilities. The weights identified will enable the researcher to arrive at the overall quality scores of any Institute. As a part of the process, the user just needs to collect the ratings from the end customers (the parents of the students) against each driver, and the institute level scores can be derived. These scores can then be used by the Institute's management to analyze the results and improve upon the weak areas to improve the delivered service quality in the education sector.Originality/valueA holistic approach to exploring major drivers that impact the quality of education is a new approach. Moreover, using different tools like AHP, hypothesis testing, t-test, using the coefficient of variation in a single paper has not been attempted before. The revalidations of accepted hypotheses with respondents is also a new approach.

2022 ◽  
Dorsa Toghani ◽  
Sharon Zeng ◽  
Elmir Mahammadov ◽  
Edie I. Crosse ◽  
Negar Seyedhassantehrani ◽  

Tissue stem cells are hierarchically organized. Those that are most primitive serve as key drivers of regenerative response but the signals that selectively preserve their functional integrity are largely unknown. Here, we identify a secreted factor, Semaphorin 4A (Sema4A), as a specific regulator of myeloid-biased hematopoietic stem cells (myHSC), which are positioned at the top of the HSC hierarchy. Lack of Sema4A leads to exaggerated myHSC (but not downstream balanced HSC) proliferation after acute inflammatory stress, indicating that Sema4A enforces myHSC quiescence. Strikingly, aged Sema4A knock-out myHSC expand but almost completely lose reconstitution capacity. The effect of Sema4A is non cell-autonomous, since upon transplantation into Sema4A-deficient environment, wild-type myHSC excessively proliferate but fail to engraft long-term. Sema4A constrains inflammatory signaling in myHSC and acts via a surface receptor Plexin-D1. Our data support a model whereby the most primitive tissue stem cells critically rely on a dedicated signal from the niche for self-renewal and life-long persistence.

2022 ◽  
Martin Lindegren ◽  
Aurelia Pereira Gabellini ◽  
Peter Munk ◽  
Karen Edelvang ◽  
Flemming Hansen

Abstract Non-indigenous species (NIS) pose a major threat to biodiversity and the functioning and services of ecosystems. Despite their rapid spread in coastal waters worldwide, biotic invasions are widely disregarded in marine conservation planning. To guide conservation actions, a better understanding of the underlying mechanisms determining the success of NIS are therefore needed. Here we develop a joint modelling approach to identify the key drivers and community assembly processes determining the occurrence of invasive benthic invertebrates, using Danish coastal waters as a case study. To reflect factors affecting the introduction, establishment and spread of NIS throughout the area, we compiled long-term monitoring data on NIS, as well as information on commercial shipping, environmental conditions and estimates of larvae settling densities derived from drift model simulations informed by species traits. We then applied a set of species distribution models to identify the key drivers determining the occurrence of NIS. Our results demonstrate a significant positive effect of vessel activity, a negative effect of depth and bottom salinity, as well as a positive effect of the simulated settling densities on the probability of presence. Taken together, our results highlight the role of commercial shipping, habitat characteristics and passive advection of early-life stages on the success of NIS. Our joint modelling approach provide improved process understanding on the key community assembly processes determining the presence of NIS and may serve to guide monitoring, management and conservation planning in order to limit future invasions and their negative consequences on coastal ecosystems.

2022 ◽  
pp. 1-62
Ajit K. Sahoo ◽  
Vikram Vishal ◽  
Mukul Srivastava

Placement of the horizontal well within the best landing zone is critical to maximize well productivity, thus identification of the best landing zone is important. This paper illustrates an integrated semi-analytical workflow to carry out the stratigraphic characterization of the Eagle Ford shale to identify the best landing zone. The objective of this work is twofold: 1) to establish a workflow for stratigraphic characterization and 2) to understand the local level variability in the well performance.To establish the workflow, we have used the production data, petrophysical information and regional reservoir property maps. As a first step of the workflow, we subdivided the Eagle Ford shale into nine smaller stratigraphic units using the wireline signatures and outcrop study. In the second step, we have used statistical methods such as linear regression, fuzzy groups and theory of granularity to capture the relationship between the geological parameters and the well performances. In this step, we identified volume of clay (Vclay), hydrocarbon filled porosity (HCFP) and total organic carbon (TOC) as key drivers of the well performance. In the third step, we characterized the nine smaller units and identified four stratigraphic units as good reservoirs with two being the best due to their low Vclay, high HCFP and high TOC content.Finally, we reviewed the well paths of four horizontal wells with respect to the best stratigraphic units. We observed that production behavior of these wells is possibly driven by their lateral placement. The better producing wells are placed within the middle of the best stratigraphic units whereas the poor wells are going out the best stratigraphic units. This investigation provides a case study that demonstrates the importance of integrating datasets to identify best landing zones and the suggested workflow can be applied to other areas and reservoirs to better identify targetable zones.

2022 ◽  
pp. 261-272
Sablu Khan ◽  
Hesham Magd

This study mainly focuses on the identification of barriers and drivers to agriculture entrepreneurship. Entrepreneurship not only includes the creation of new ventures or start-ups but includes innovation and growth. Agri-entrepreneurship can address the current issues of lower farm mechanisation and low productivity of the livestock sector. It can be helpful for farmers in general and agri-entrepreneur in particular. Understanding barriers and drivers to agri-entrepreneurship have become a necessity in current times. Agriculture entrepreneurship has the ability to raise the living standards and helps in the creation of wealth not only for the entrepreneurs but also for other farmers. Agriculture entrepreneurship is beneficial in the global food supply in least-developed and developing countries. The purpose of this chapter is to familiarise the readers with the meaning, prospects, barriers, and key drivers of agri-entrepreneurship to engage in agri-entrepreneurship.

2022 ◽  
Vol 35 (1) ◽  
pp. 0-0

This study investigated integrated elderly care services supply chains using a combination of Decision Making Trial and Evaluation Laboratory (DEMATEL), Interpretative Structural Modeling (ISM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), The research identifies the key factors related to the emergency response capabilities of elderly service supply chains and the most important ways to improve them. The integrated DEMATEL-ISM-TOPSIS method provides new theoretical support for the management of elderly care service supply chains.

2022 ◽  
Vol 174 ◽  
pp. 121272
Vahid Jafari-Sadeghi ◽  
Hannan Amoozad Mahdiraji ◽  
Donatella Busso ◽  
Dorra Yahiaoui

2022 ◽  
Vol 60 (4) ◽  
Deborah Bentivoglio ◽  
Giorgia Bucci ◽  
Matteo Belletti ◽  
Adele Finco

Abstract: Recently, the agricultural sector has had to face several challenges related to the innovation process, the most significant of which seems to be that of its digital transformation. As a consequence, the issue of digital technology adoption is becoming of important scientific interest due to its potential impact on products, services, processes, and new business models. In general, the adoption behavior can be indirectly explained by studying factors that lead a firm to innovate; among these factors, the literature emphasizes the function of networks. The objective of the paper is to investigate the role of networks as key drivers of precision agriculture technologies adoption. To achieve this goal, qualitative research was developed by using 8 case studies recollected among that few Italian farms which can be defined as innovative for having already experienced precision agriculture. Results show that only a few farms can develop and manage innovations internally; success often requires cooperation between individual actors and organizations. Finally, the paper provides some practical advice and a set of propositions for those farms that are trying to achieve digital technological innovations.

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