scholarly journals ASSESSING ON THE ECONOMIC EFFICIENCY OF THE CLIMATE CHANGE ADAPTION MODELS IN TRA VINH: THE CROP CONVERSION MODEL

2019 ◽  
Vol 1 (26) ◽  
pp. 31-38
Author(s):  
Loan Thi Thuy Nguyen
Keyword(s):  
Climate Change ◽  
Regression Analysis ◽  
Economic Efficiency ◽  
Positive Impact ◽  
Labor Cost ◽  
Farm Households ◽  
Vegetable Crops ◽  
Conversion Model ◽  
Factors Influencing

According to the survey of 162 farm households in Tra Vinh province, this article compares and evalutes the economic efficiency of the crop conversion model  (from rice to vegetable). The results show that the incomes of these farm households were 3 times higher than those of rice farm households, approximately 5.7 million VND/0.25 acre /year. In addition, the regression  analysis was applied in this study to identify and quantify the factors influencing the economic efficiency of the conversion model. The results confirm the interaction between vegetable crops, rice – vegetable rotational crops, labor cost, age and the ethnicity of  householders. In particular, the households’ awareness of climate change has a positive impact on the economic efficiency of the model. Finally, the research suggests some solutions to the improvement of the economic efficiency of the crop conversion model which adapts to climate change.

scholarly journals Trends in Chemical Wood Surface Improvements and Modifications: A Review of the Last Five Years

Coatings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1514
Author(s):  
Pierre Blanchet ◽  
Simon Pepin
Keyword(s):  
Climate Change ◽  
Wood Surface ◽  
Research Laboratory ◽  
Positive Impact ◽  
Economic Factors ◽  
Self Healing ◽  
Fire Retardancy ◽  
Wood Treatment ◽  
Factors Influencing ◽  
Tackle Climate Change

Increasing the use of wood in buildings is regarded by many as a key solution to tackle climate change. For this reason, a lot of research is carried out to develop new and innovative wood surface improvements and make wood more appealing through features such as increased durability, fire-retardancy, superhydrophobicity, and self-healing. However, in order to have a positive impact on the society, these surface improvements must be applied in real buildings. In this review, the last five years of research in the domain of wood surface improvements and modifications is first presented by sorting the latest innovations into different trends. Afterward, these trends are correlated to specifications representing different normative, ecologic and economic factors which must be considered when expecting to introduce a wood treatment to the market. With this review, the authors hope to help researchers to take into consideration the different factors influencing whether new innovations can leave the research laboratory or not, and thereby facilitate the introduction of new wood surface treatments in the society.

scholarly journals Vegetation Response to Climate and Climatic Extremes in Northwest Bangladesh: A Quantile Regression Approach

2021 ◽  
Author(s):  
Mohammad Ahsan Uddin ◽  
A S M Maksud Kamal ◽  
Shamsuddin Shahid
Keyword(s):  
Climate Change ◽  
Regression Analysis ◽  
Quantile Regression ◽  
Positive Impact ◽  
Maximum Temperature ◽  
Time Lags ◽  
Vegetation Response ◽  
Climatic Extremes ◽  
Quantile Regression Analysis ◽  
Nonparametric Correlation

Abstract The present study assessed the vegetation response to climate in the water-stressed northwest Bangladesh (NWB). The quantile regression analysis was employed to evaluate the effect of climate and climatic extremes on vegetation. The nonparametric correlation analysis was used to assess the climatic influence on vegetation for various time lags. Besides, the modified Mann-Kendall (MMK) test was conducted to understand the changes in climate and vegetation to anticipate the climate change impacts on vegetation. Satellite estimation of Normalized Difference Vegetation Index (NDVI) and observed rainfall and temperature data collected from five locations of the study area for the period 1982-2018 was used for this purpose. The results revealed a negative effect of rainfall, a positive impact of maximum temperature on vegetation in monsoon and a positive influence on minimum temperature on vegetation in winter. Quantile regression analysis revealed a significant negative influence of extreme rainfall and a positive impact of maximum temperature on vegetation for the whole NWB. Overall, the study revealed a greater influence of temperature than rainfall on vegetation change in the region. The trend analysis revealed a reduction in rainfall (-2.56 mm/decade) and a rise in temperature (0.176ºC/decade), and thus, an increase in vegetation (0.014 per decade). The results indicate the positive effect of climate change on vegetation, positively impacting the environment and water resources in the study area.

scholarly journals Climate risks and adaptation strategies of farmers in East Africa and South Asia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jeetendra Prakash Aryal ◽  
Tek Bahadur Sapkota ◽  
Dil Bahadur Rahut ◽  
Paswel Marenya ◽  
Clare M. Stirling
Keyword(s):  
Climate Change ◽  
South Asia ◽  
East Africa ◽  
Institutional Support ◽  
Adaptation Strategies ◽  
Farm Households ◽  
Farming Practices ◽  
Alternative Employment ◽  
Climate Risks ◽  
Factors Influencing

AbstractUnderstanding major climate risks, adaptation strategies, and factors influencing the choice of those strategies is crucial to reduce farmers’ vulnerability. Employing comprehensive data from 2822 farm households in Ethiopia and Kenya (East Africa; EA) and 1902 farm households in Bangladesh, India, and Nepal (South Asia; SA), this study investigates the main climate risks that farmers faced and the adaptation strategies they used. Among others, excessive rainfall and heightened crop pest/disease incidence are commonly observed climate-induced risks in all study areas, while cyclones and salinity are unique to Bangladesh. Drought is prevalent in Ethiopia, India, Kenya, and Nepal. Farmers in those countries responded with strategies that include change in farming practices, sustainable land management, reduce consumption, sell assets, use savings and borrowings, seek alternative employment and assistance from government or NGO. In general, farmers faced several multiple climate risks simultaneously and they responded with multiple adaptation strategies. Therefore, this study used a multivariate probit (MVP) approach to examine the factors influencing the adoption of adaptation strategies. Unlike other studies, we also tested and corrected for possible endogeneity in model estimation. All the countries mentioned have low adaptive capacity to address climate change, which is further weakened by inadequate governance and inefficient institutions. We observed significant differences in the choice of adaptation strategies between male-headed households (MHHs) and female-headed households (FHHs), as well as across countries. Generally, MHHs are more likely to seek additional employment and change agricultural practices, while FHHs and households headed by older persons tend to reduce consumption and rely on savings and borrowings. Institutional support for adaptation is much less in EA compared to SA. Training on alternative farming practices, enhancing non-farm employment options, better institutional support, and social security for older farmers are crucial for climate change adaptation in both regions.

An Investigation on Extrinsic and Intrinsic Rewards on Employee Retention among Gen Y: A Study in Malaysian Manufacturing Companies

2020 ◽  
Vol 3 (1) ◽  
Keyword(s):  
Regression Analysis ◽  
Employee Retention ◽  
Future Research ◽  
Manufacturing Companies ◽  
Extrinsic Reward ◽  
Intrinsic Rewards ◽  
Gen Y ◽  
Intrinsic Reward ◽  
Factors Influencing ◽  
The Relationship

The aim of this study is to investigate the relationship between extrinsic and intrinsic reward on retention among Gen Y employees in Malaysian manufacturing companies. The data was collected from 113 respondents worked in manufacturing companies located in Seri Kembangan, Selangor using questionnaires. Multiple regression analysis was conducted to test the hypotheses. The results showed both extrinsic and intrinsic reward are the factors influencing retaining Gen Y in manufacturing companies. The discussion on the analysis, limitation of the study, recommendation for future research and conclusion were discussed at the end of this study. In a nutshell, it was proven extrinsic reward and intrinsic reward has contributed to the retention of Gen Y employees.

PROFESSIONAL ATTRIBUTES OF INTERNAL AUDITORS IN RIAU

2018 ◽  
Vol 3 (2) ◽  
pp. 161
Author(s):  
Satria Tri Nanda
Keyword(s):  
Regression Analysis ◽  
Audit Quality ◽  
Hypotheses Testing ◽  
Internal Auditors ◽  
Factors Influencing ◽  
Professional Attributes ◽  
Professional Care ◽  
Positive Effect

<p><em>This research aims to identify the factors influencing the audit quality of auditors at Inspektorat Provinsi Riau. The population in this research were auditor, examiner, assistant examiner, and P2UPD (Pengawas Penyelenggara Urusan Pemerintah di Daerah) in charge at the Inspectorate in Riau Province and all Inspectorates in Districts and Cities in Riau Province. A total of 290 set of questionnaire were sent and a number of 184 of questionnaires were processed. Using regression analysis conducted by SPSS, the hypotheses testing analysis results show that experience, responsiveness, professional care, executive involvement</em><em>t, planning</em><em> and auditability have significant and positive effect on audit quality. These results indicate that the higher the levels of experience, responsiveness, professional care, executive involvement and auditability of Inspectorate officials, the better the quality of audit performed by the Inspectorate Officials of Riau Province.</em></p>

scholarly journals Factors Affecting Secondary Traumatic Stress of Nurses Caring for COVID-19 Patients in South Korea

2021 ◽  
Vol 18 (13) ◽  
pp. 6843
Author(s):  
Mee Sun Lee ◽  
Sujin Shin ◽  
Eunmin Hong
Keyword(s):  
Social Support ◽  
Regression Analysis ◽  
Traumatic Stress ◽  
Secondary Traumatic Stress ◽  
Direct Care ◽  
Hierarchical Regression ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Affect Patient Care ◽  
Significant Factors

The secondary traumatic stress (STS) of nurses caring for COVID-19 patients is expected to be high, and it can adversely affect patient care. The purpose of this study was to examine the degree of STS of nurses caring for COVID-19 patients, and we identified various factors that influence STS. This study followed a descriptive design. The data of 136 nurses who had provided direct care to COVID-19 patients from 5 September to 26 September 2020 were collected online. Hierarchical regression analysis was conducted to identify the factors influencing STS. Participants experienced moderate levels of STS. The regression model of Model 1 was statistically significant (F = 6.21, p < 0.001), and the significant factors influencing STS were the duration of care for patients with COVID-19 for more than 30 days (β = 0.28, p < 0.001) and working in an undesignated COVID-19 hospital (β = 0.21, p = 0.038). In Model 2, the factor influencing STS was the support of a friend in the category of social support (β = −0.21, p = 0.039). The nurses caring for COVID-19 patients are experiencing a persistent and moderate level of STS. This study can be used as basic data to treat and prevent STS.

Factors Influencing Innovation and Industrial Performance in Chinese Manufacturing Industry

2017 ◽  
Vol 14 (06) ◽  
pp. 1750040 ◽  
Author(s):  
Nnaemeka Vincent Emodi ◽  
Girish Panchakshara Murthy ◽  
Chinenye Comfort Emodi ◽  
Adaeze Saratu Augusta Emodi
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Product Innovation ◽  
Manufacturing Industry ◽  
Positive Impact ◽  
Export Performance ◽  
Patent Application ◽  
New Product ◽  
Factors Influencing ◽  
Industrial Performance

This study investigates the factors influencing the Chinese manufacturing industry’s innovation and industrial performance utilizing a panel data approach on a sample of Chinese manufacturing enterprises over the period of 2008–2013. The industries were grouped according to related sectors into five groups, a general group was also created which included the whole data sample. The study found that research and development (R&D) expenditure positively influenced the growth of product innovation and industrial performance, but not necessarily knowledge innovation and export performance. Also, expenditure on new product development had a positive impact on both innovation and industrial performance. The growth of patent application was discovered to be influenced by an R&D project and foreign patent license. Finally, the number of enterprises and firm size (i.e. number of employees) contributed positively to the industrial output performance. The findings suggest that industrial R&D and new product development influences the success of product innovation and sales performance. The study recommends that the government should set up policies that will stimulate industrial R&D, while supporting technology transfers from foreign partners. Most importantly, government policies on the development of the industry should be addressed on a sectorial level and not a “one-size-fit-all” type of policy.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

Evaluation of Imazethapyr for Weed Control in Leafy Vegetable Crops

1996 ◽  
Vol 10 (2) ◽  
pp. 253-257 ◽  
Author(s):  
Joan A. Dusky ◽  
William M. Stall
Keyword(s):  
Regression Analysis ◽  
Weed Control ◽  
Crop Yield ◽  
Relative Sensitivity ◽  
Leafy Vegetable ◽  
Field Conditions ◽  
Vegetable Crops ◽  
Weed Species ◽  
Common Lambsquarters ◽  
Common Purslane

Imazethapyr was evaluated PRE and POST in five lettuce types and chicory under Florida field conditions. The relative sensitivity of leafy crop vigor (most sensitive to most tolerant) to imazethapyr PRE, based on 20% inhibition determined using regression analysis, was as follows: Boston > bibb > crisphead > romaine > leaf > escarole > endive. Leafy crop injury increased as the rate of imazethapyr applied POST increased, with all leafy crops responding in a similar manner. Surfactant addition increased imazethapyr phytotoxicity. Imazethapyr PRE treatments at 0.067 kg ai/ha provided greater than 80% control of livid amaranth, common purslane, flatsedge, and common lambsquarters. Imazethapyr POST at 0.067 kg/ha, with surfactant provided control greater than 85% of all weed species. Greater than 85% spiny amaranth control was provided by imazethapyr POST at 0.017 kg/ha. Use of surfactant with imazethapyr did not improve spiny amaranth control over imazethapyr with no surfactant. POST treatments did not decrease leafy crop yield compared with the hand-weeded check. Imazethapyr applied PRE reduced crop yield compared to the POST treatments and the hand-weeded control.

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