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Open Access
Article
Publication date: 7 June 2021

Tamoor Khan, Jiangtao Qiu, Ameen Banjar, Riad Alharbey, Ahmed Omar Alzahrani and Rashid Mehmood

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO2 emissions, farming areas and the labor force in China.

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Abstract

Purpose

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO2 emissions, farming areas and the labor force in China.

Design/methodology/approach

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

Findings

The Johansen test findings have shown that the fruit crop growth, energy use, CO2 emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO2 emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO2 will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO2 emissions to agricultural areas to fruit crops.

Originality/value

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.

Details

International Journal of Climate Change Strategies and Management, vol. 13 no. 2
Type: Research Article
ISSN: 1756-8692

Keywords

Open Access
Article
Publication date: 23 November 2020

Md. Nazmul Haque, Mustafa Saroar, Md. Abdul Fattah and Syed Riad Morshed

Public-Private Partnership (PPP) is a common practice in both the public and private sectors. PPP has been an important instrument to achieve Sustainable Development Goals (SDGs…

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Abstract

Purpose

Public-Private Partnership (PPP) is a common practice in both the public and private sectors. PPP has been an important instrument to achieve Sustainable Development Goals (SDGs) at the national level. However, the role of PPP at the subnational level is often scarcely studied. Using Khulna city of Bangladesh as a case, this paper aims to assess the role of PPP projects in the attainment of SDGs.

Design/methodology/approach

The research was conducted in the Central Business District (CBD) of Khulna, on a total of 4.6 kilometers stretches of road medians in the CBD where landscaping was done through the PPP approach. Besides the collection of secondary data from official records, primary data were collected through site visits, field surveys and interviews of PPP project partners.

Findings

The result shows that 89 percent of the respondents (road users) were pleased with the landscaping done on the road medians. Similarly, about 86 percent of the respondents felt more comfortable and safer to use the roads. Well-maintained road medians allow road-crossing at a regular interval which reduces the chance of an accident. The private parties have installed promotional billboards on the road medians and saved BDT 10.82 million a year. The public authority saves the maintenance budget amounting to BDT 23 million a year. The project achieves a triple-win situation. Despite some limitations, this PPP project has taken Khulna a step forward to achieve SDGs.

Originality/value

The findings have policy implications as the PPP project has enhanced the resilience of Khulna by addressing the relevant SDGs.

Details

Public Administration and Policy, vol. 23 no. 3
Type: Research Article
ISSN: 1727-2645

Keywords

Open Access
Article
Publication date: 1 March 2022

Md. Abdul Fattah, Syed Riad Morshed, Md. Mojammel Hoque, Md. Fazle Rabbi and Irin Akter Dola

The emergence of COVID-19 and its spread led to severe social, economic and livelihood impacts around the world. This study documented the socioeconomic impacts of COVID-19…

1853

Abstract

Purpose

The emergence of COVID-19 and its spread led to severe social, economic and livelihood impacts around the world. This study documented the socioeconomic impacts of COVID-19 outbreaks and lockdown on the lower-income groups. Also illustrated the impacts on the attainment of SDGs in the context of the slums of Chittagong City.

Design/methodology/approach

Both qualitative and quantitative data have been collected from the 150 respondents through questionnaire surveys in the slums.

Findings

The lockdown led to the decrease of 90% of the respondents' income level and affected the livelihoods of 97.33% of the respondents, with an overall score of 3.22 ± 0.67 on a four-point Likert-type scale. About 96.67% of respondents' psychological conditions have been affected high to extreme, with an overall score of 3.19 ± 0.68. The pandemic affected 74.67% of respondents' food habits, 95.33% of respondents' child education, increased domestic violence and deteriorated social security, basic service facilities and hygiene practices among the slum dwellers. The severity of COVID-19 outbreaks on the lower-income people makes it critical for the government to attain the SDG 1, SDG 2, SDG 3, SDG 4, SDG 5 (Target 5.1, 5.2) SDG 6 and SDG 16.

Originality/value

The findings of the study will help governments, policymakers, international organizations to adopt measures to mitigate the effects of the outbreaks.

Details

Frontiers in Engineering and Built Environment, vol. 2 no. 2
Type: Research Article
ISSN: 2634-2499

Keywords

Open Access
Article
Publication date: 19 September 2017

Wahid Ullah, Takaaki Nihei, Muhammad Nafees, Rahman Zaman and Muhammad Ali

This study aims to investigate risks associated with climate change vulnerability and in response the adaptation methods used by farming communities to reduce its negative impacts…

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Abstract

Purpose

This study aims to investigate risks associated with climate change vulnerability and in response the adaptation methods used by farming communities to reduce its negative impacts on agriculture in Pakistan.

Design/methodology/approach

The study used household survey method of data collection in Charsadda district of Khyber Pakhtunkhwa province, involving 116 randomly selected respondents.

Findings

Prevalent crops diseases, water scarcity, soil fertility loss and poor socio-economic conditions were main contributing factors of climate change vulnerability. The results further showed that changing crops type and cultivation pattern, improved seed varieties, planting shaded trees and the provision of excessive fertilizers are the measures adapted to improve agricultural productivity, which may reduce the climate change vulnerability at a household level.

Research limitations/implications

The major limitation of this study was the exclusion of women from the survey due to religious and cultural barriers of in Pashtun society, wherein women and men do not mingle.

Practical implications

Reducing climate change vulnerability and developing more effective adaptation techniques require assistance from the government. This help can be in the form of providing basic resources, such as access to good quality agricultural inputs, access to information and extension services on climate change adaptation and modern technologies. Consultation with other key stakeholder is also required to create awareness and to build the capacity of the locals toward reducing climate change vulnerability and facilitating timely and effective adaptation.

Originality/value

This original research work provides evidence about farm-level vulnerability, adaptation strategies and risk perceptions on dealing with climate-change-induced natural disasters in Pakistan. This paper enriches existing knowledge of climate change vulnerability and adaptation in this resource-limited country so that effective measures can be taken to reduce vulnerability of farming communities, and enhance their adaptive capability.

Details

International Journal of Climate Change Strategies and Management, vol. 10 no. 3
Type: Research Article
ISSN: 1756-8692

Keywords

Open Access
Article
Publication date: 8 December 2020

Matjaž Kragelj and Mirjana Kljajić Borštnar

The purpose of this study is to develop a model for automated classification of old digitised texts to the Universal Decimal Classification (UDC), using machine-learning methods.

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Abstract

Purpose

The purpose of this study is to develop a model for automated classification of old digitised texts to the Universal Decimal Classification (UDC), using machine-learning methods.

Design/methodology/approach

The general research approach is inherent to design science research, in which the problem of UDC assignment of the old, digitised texts is addressed by developing a machine-learning classification model. A corpus of 70,000 scholarly texts, fully bibliographically processed by librarians, was used to train and test the model, which was used for classification of old texts on a corpus of 200,000 items. Human experts evaluated the performance of the model.

Findings

Results suggest that machine-learning models can correctly assign the UDC at some level for almost any scholarly text. Furthermore, the model can be recommended for the UDC assignment of older texts. Ten librarians corroborated this on 150 randomly selected texts.

Research limitations/implications

The main limitations of this study were unavailability of labelled older texts and the limited availability of librarians.

Practical implications

The classification model can provide a recommendation to the librarians during their classification work; furthermore, it can be implemented as an add-on to full-text search in the library databases.

Social implications

The proposed methodology supports librarians by recommending UDC classifiers, thus saving time in their daily work. By automatically classifying older texts, digital libraries can provide a better user experience by enabling structured searches. These contribute to making knowledge more widely available and useable.

Originality/value

These findings contribute to the field of automated classification of bibliographical information with the usage of full texts, especially in cases in which the texts are old, unstructured and in which archaic language and vocabulary are used.

Details

Journal of Documentation, vol. 77 no. 3
Type: Research Article
ISSN: 0022-0418

Keywords

Open Access
Article
Publication date: 28 July 2023

Guido Veronese, Anas Ismail, Fayez Mahamid, Basel El-Khodary, Dana Bdier and Marwan Diab

This study aims to explore the effect of mental health in terms of depression, anxiety, stress, fear of COVID-19 and quality of life (QoL) on the reluctance to be vaccinated in a…

Abstract

Purpose

This study aims to explore the effect of mental health in terms of depression, anxiety, stress, fear of COVID-19 and quality of life (QoL) on the reluctance to be vaccinated in a population of Palestinian adults living in occupied Palestinian territories and Israel.

Design/methodology/approach

The authors recruited 1,122 Palestinian adults who consented to participate in the study; 722 were females, and the mean age of the sample was 40.83 (SD 8.8). Depression, anxiety, and stress scale (DASS), World Health Organization QoL-BREF, FCov-19 and reluctance to the vaccine scale were administered; hierarchical regression analysis was applied to test vaccine reluctance as a dependent variable, and mental health, fear of COVID-19 and QoL as independent variables. This study hypothesized influence of such variables on the vaccine choice with differences due to the participants’ geographical locations.

Findings

Findings showed an effect of mental health, particularly depression, QoL and fear of COVID on vaccine reluctance, with depression and fear of COVID in the West Bank and Gaza, while in Israel, QoL played a role in vaccination choices.

Research limitations/implications

The future needs to be comprehended more thoroughly to discover mutations and fluctuations over time in vaccine hesitancy and the increasing role of psychological distress, diminished QoL and fear of Covid-19. Online recruitment might not have allowed the study to include the most disadvantaged strips of the Palestinian population.

Practical implications

Human rights perspectives must be considered in public health and public mental health policies to ensure the QoL and well-being for the Palestinian population during and following the pandemic.

Social implications

The crumbling of the Palestinian health-care system exacerbated the sense of dread among the population and made them less likely to vaccinate. The pandemic-like spread of Covid-19 prompts a plea for the global community to actively advocate for the urgent re-establishment of equity, autonomy and durability of the medical infrastructure in the occupied territories and equal entitlements for the Palestinians in Israel.

Originality/value

The results demonstrated the importance for public mental health to consider the multiple levels implied in the vaccine refusal in Palestine and Israel among the Palestinian population.

Details

Journal of Public Mental Health, vol. 22 no. 4
Type: Research Article
ISSN: 1746-5729

Keywords

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