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1 – 10 of 417
Article
Publication date: 5 July 2023

Hani Alkayed, Ibrahim Yousef, Khaled Hussainey and Esam Shehadeh

This article provides the first empirical study on the effects of the COVID-19 pandemic on sustainability reporting in US financial institutions using institutional, stakeholder…

Abstract

Purpose

This article provides the first empirical study on the effects of the COVID-19 pandemic on sustainability reporting in US financial institutions using institutional, stakeholder and legitimacy theories.

Design/methodology/approach

The study used the independent sample t-test and Mann–Whitney U test throughout as well as OLS, random effects, fixed effects and heteroskedasticity corrected model to test the impact of the COVID-19 pandemic on sustainability reporting in the US financial sector. A sample from all listed US financial firms was used after controlling for both the Refinitiv Eikon sector classification and the NAICS sector classification.

Findings

Using U Mann–Whitney test and independent sample t-test the study revealed that the average ESG score for the pre-COVID19 period is 53% compared with 62.3% for the COVID-19 period, indicating that the sustainability reporting during COVID-19 is much higher compared with the pre-pandemic period. The findings of regression analysis also confirm that the US financial companies increased their sustainability reporting during the COVID-19 pandemic.

Research limitations/implications

This study is an early attempt to look at how the COVID-19 epidemic has affected financial reporting procedures, although it is focused only on one area and other entity-related factors like stock market implications, company governance, internal audit practice, etc could have been considered.

Practical implications

This research offers useful recommendations for policymakers to create standards for regulators on the significance of raising sustainability awareness. The findings are crucial for accounting regulators as they work to implement COVID-19 and enforce required integrated reporting rules and regulations.

Originality/value

The study provides the first empirical evidence on the impact of the COVID-19 pandemic on sustainability reporting, by examining how US financial institutions approach the topic of sustainability during the COVID-19 pandemic and assessing the pandemic's current consequences on sustainability.

Details

Journal of Applied Accounting Research, vol. 25 no. 2
Type: Research Article
ISSN: 0967-5426

Keywords

Article
Publication date: 17 May 2022

Qiucheng Liu

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of…

Abstract

Purpose

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Design/methodology/approach

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Findings

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Originality/value

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Details

Library Hi Tech, vol. 41 no. 5
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 14 February 2022

Shristy Maharjan, Pramen P. Shrestha and Deekshitha Srirangam

The purpose of this study is to determine whether there is a correlation between mobilization costs and project schedule performance of highway projects. In addition to this, the…

Abstract

Purpose

The purpose of this study is to determine whether there is a correlation between mobilization costs and project schedule performance of highway projects. In addition to this, the study will also determine if the mobilization costs are helping small or large highway projects in terms of improving the schedule performance.

Design/methodology/approach

The data of 206 highway projects were collected from the Department of Transportation of two states with the help of questionnaire survey. The cost, schedule and mobilization costs data were collected. The performance metrics related to construction schedule growth and construction intensity were developed in order to test the research hypotheses: mobilization costs will increase the schedule performance of highway projects. The data were also divided into two groups based on project cost and analyzed to check whether the mobilization costs impact the schedule performance of these highway projects. Spearman's correlation test was conducted to determine the correlation between dependent and independent variables. In addition, a Mann–Whitney test was conducted to determine the difference in medians of construction schedule growth and the construction intensity of these two groups of projects.

Findings

One major study finding was that there was no strong linear correlation between the mobilization cost percentage and the construction schedule growth and construction intensity of highway projects. However, the study found the projects that have 9% or more mobilization costs had significantly better schedule growth compared to the projects that have less than 9% mobilization costs. When data were analyzed based on the project size, it was found that this pattern was seen only in large projects costing equal to or more than $5 million.

Practical implications

This study's findings have very crucial practical implications to state DOTs contract engineers. This study shows that the highway contract engineers need to provide the right amount of mobilization costs to complete their projects on and before schedule. If the correct amount of mobilization costs is not provided to the contractors, the impact of these mobilization costs on reducing the schedule growth will be negligible. The findings of this study will assist public agency decision makers to complete their projects on or before time by including the mobilization costs provision in the contract. The state DOTs can improve their schedule performance by providing enough financial help to the contractors so that they can improve their cash flows and complete projects successfully within the given timeframe.

Originality/value

This paper contributes to the existing body of knowledge by validating the impact of mobilization costs on the schedule performance of highway projects. There has been no empirical study conducted prior to this to identify the role of mobilization costs on reducing the schedule growth of highway projects.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 5
Type: Research Article
ISSN: 0969-9988

Keywords

Open Access
Article
Publication date: 3 April 2023

Ashraf Mishrif and Asharul Khan

The border closure and lockdowns due to Covid-19 pandemic resulted in partial closure of many industrial and commercial complexes, halted the performance of key strategic sectors…

Abstract

Purpose

The border closure and lockdowns due to Covid-19 pandemic resulted in partial closure of many industrial and commercial complexes, halted the performance of key strategic sectors such as logistics and supply chains, and thus disrupted the global value chains and the economy. The authors argue, however, that the pursuit of survival has driven companies to innovate and use digitization to overcome the negative consequences of the pandemic. More specifically, in this paper the authors aim to assess the success and challenges faced by companies in digitization policy design, adoption and implementation and their effects on firms’ operation, outputs and customer base during Covid-19.

Design/methodology/approach

Sixty-one samples of the companies surveyed between 10 January and 30 April 2021 were analyzed, using the Krushkal–Wallis test and Independent-Samples Mann–Whitney U test to identify the relationships between variables including operation, overall output, customer base, digitization policy, technology use and implementation costs of new technologies.

Findings

Results revealed a positive impact of digitization on the operation and overall outputs, while no effect was observed on the customer base. Analysis also showed that only 1.8% of companies were able to fully implement digitization, and that the cost of technology prevented most companies from using emerging technology or implementing their digitization policy.

Research limitations/implications

While the research has practical implications, it is not without flaws. For instance, the outcome of technology varies as per geographic area and people. The study was conducted in the Sultanate of Oman, a developing country in the Middle East region; therefore, it is difficult to generalize the outcomes suited to developed countries. The developed countries usually have a population quite used to the advanced technologies so some of the issues raised in the study might not work in the logistics and supply chain sectors of the developed countries. Such countries need separate studies.

Practical implications

The findings will have implications for both supply chain companies as well as the technology providers. The supply chain companies will invest in technology infrastructure and add technology as an important component in their business models. The technology providers will consider the costs of implementation and adoption issues of technology in the supply chain companies.

Originality/value

To the best of authors' knowledge, no work has been produced on logistics and supply chain companies considering the technological sustainability during the time of Covid-19. The study will improve understanding of the digitization policy design, adoption and implementation and their effects on logistics and supply chain companies’ performance.

Details

Journal of International Logistics and Trade, vol. 21 no. 3
Type: Research Article
ISSN: 1738-2122

Keywords

Article
Publication date: 3 May 2023

Henrik Bathke, Hendrik Birkel, Heiko A. von der Gracht and Stefanie Kisgen

In the era of digital disruption and customer loyalty loss, it has become even more important to shape the experience journey of a firm’s stakeholders. The benefits of experience…

Abstract

Purpose

In the era of digital disruption and customer loyalty loss, it has become even more important to shape the experience journey of a firm’s stakeholders. The benefits of experience data (XD) analysis for a competitive advantage and firm performance are well proven in the business-to-customer context. Therefore, this study aims to explore the limited exploitation of XD in the business-to-business (B2B) context.

Design/methodology/approach

The data of 338 B2B firms is generated through computer-assisted telephone interviewing using a structured interview guideline. A Mann–Whitney U test and binary linear regression are applied to test hypotheses derived from literature.

Findings

The results suggest that XD non-collectors see XD increase efficiency, whereas XD collectors view XD strategically beyond customer data. Additionally, the successful application of XD in firms can be fostered by connecting XD with operational data through digitalised processes, strategic usage and data collection at certain defined points of time.

Originality/value

This study contributes to the understanding of XD perception between collectors and non-collectors and develops determinants for the successful application of XD management. Based on the results, B2B marketing executives from academics and practice can foster the implementation of XD management to improve all firm’s stakeholders’ experiences. In this way, this study contributes to the understanding of managing not only customers’ but other stakeholders’ experiences.

Details

Journal of Business & Industrial Marketing, vol. 38 no. 12
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 29 March 2024

Aminuddin Suhaimi, Izni Syahrizal Ibrahim and Mariyana Aida Ab Kadir

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to…

Abstract

Purpose

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

Design/methodology/approach

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

Findings

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

Originality/value

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 8 September 2023

Ross Dowsett, Noel Kinrade, David Whiteside, Dillon Lawson, Cleveland Barnett, Daniele Magistro and Luke Wilkins

Despite the perceived benefits of implementing virtual reality (VR) training in elite sport, arguably the most important element – the perceptions of practitioners – has been…

Abstract

Purpose

Despite the perceived benefits of implementing virtual reality (VR) training in elite sport, arguably the most important element – the perceptions of practitioners – has been largely understudied. Therefore, the present study aims to explore practitioners' perceptions of VR training in elite football and baseball, with a focus on the important factors, obstacles, perceived knowledge and practical use of the technology.

Design/methodology/approach

A quantitative approach measuring practitioner perceptions via an online questionnaire was adopted. Football respondents (n = 25) represented practitioners from major football leagues across the world, and baseball respondents (n = 15) represented practitioners from Major League Baseball.

Findings

Both football and baseball respondents reported that the most important factor for implementation of VR training was improvement in on-field performance (technical and tactical); whilst cost was viewed as the biggest obstacle. Both football and baseball respondents also noted that the most likely group to receive VR training would be injured and rehabilitating athletes. Mann–Whitney U tests revealed that football respondents perceived coach (p = 0.02) and executive approval (p < 0.001) as significantly greater obstacles than baseball respondents.

Originality/value

This research provides novel and invaluable information for stakeholders within VR regarding what the elite organisations of different sports perceive as the most important factors for implementation, as well as greatest obstacles preventing use. This information should guide future development and marketing of VR training systems in sport.

Details

Sport, Business and Management: An International Journal, vol. 13 no. 6
Type: Research Article
ISSN: 2042-678X

Keywords

Article
Publication date: 11 May 2023

Noor Ismael, Khader Almhdawi, Ala’a Jaber, Saddam Kana'an and Sana'a Al Shlool

This study aims to investigate the differences in participation patterns between children with autism spectrum disorders (ASD) and children with typical development (TD) in Jordan.

Abstract

Purpose

This study aims to investigate the differences in participation patterns between children with autism spectrum disorders (ASD) and children with typical development (TD) in Jordan.

Design/methodology/approach

The study used a cross-sectional comparative design and convenient and snowball sampling. The sample consisted of 60 children (30 ASD and 30 TD), mean age (nine years), who completed the Children’s Assessment of Participation and Enjoyment and the Preferences for Activities of Children (CAPE/PAC) via interview. Analyses consisted of descriptive statistics and Mann-Whitney U tests.

Findings

Children with ASD had significantly lower participation Diversity (U = 24.00, p < 0.000) and Intensity (U = 110.00, p < 0.000) than children with TD. In addition, children with ASD had significantly lower participation preference in Physical (U = 145.50, p < 0.000), Self-Improvement (U = 163.50, p < 0.000), Skill-Based (U = 281.00, p = 0.01), Social activities (U = 307.50, p = 0.03) and total PAC scale score (U = 246.50, p = 0.003). However, children with ASD had significantly higher Enjoyment (U = 274, p < 0.000) than children with TD.

Originality/value

Children with ASD have restricted participation patterns due to certain ASD features like extreme sensory processing patterns. However, limited research compared participation patterns between school-aged children with ASD and children with TD. This study concluded that participation patterns in children with ASD are different from children with TD.

Details

Journal of Children's Services, vol. 18 no. 2
Type: Research Article
ISSN: 1746-6660

Keywords

Article
Publication date: 25 April 2023

Sukhvinder Angoori and Sanjeev Kumar

This paper examine beneficiary women's awareness of the harmful effects of traditional cooking fuels and the benefits of cleaner cooking fuel (LPG) in the Indian state of Haryana…

Abstract

Purpose

This paper examine beneficiary women's awareness of the harmful effects of traditional cooking fuels and the benefits of cleaner cooking fuel (LPG) in the Indian state of Haryana after the inception of Pradhan Mantri Ujjwala Yojana.

Design/methodology/approach

Descriptive statistics, factor analysis, confirmatory factor analysis, Mann–Whitney U test and Kruskal–Wallis H test were used for the data analysis.

Findings

The paper finds that the women of the scheduled caste were highly aware of the hazards of traditional cooking fuel. They perceived that the usage of LPG led to significant health and environmental improvements. However, the refilling was low among the respondents. So, the only low awareness was not the cause of the low refilling of LPG among Ujjwala beneficiaries.

Research limitations/implications

Technological advancement, accessibility and successful adoption require convergence with socio-economic and institutional aspects. It was evident that focus on technology might not necessarily serve developmental purposes if it is not integrated correctly with socio-economic and institutional factors. These should have conversed with the household's needs, preferences, affordability, social structures, policy support and delivery mechanism, as it was observed that, in different cases, high-end technologies have limited access.

Originality/value

This study shows that the low awareness is not the barrier to the adoption of cleaner cooking technologies in India. So, the policymakers have to revive and further investigate the real cause of the low adoption of cleaner cooking technologies in India.

Details

Technological Sustainability, vol. 2 no. 3
Type: Research Article
ISSN: 2754-1312

Keywords

Article
Publication date: 3 July 2023

Zahra Mirzaei-Azandaryani, Yousef Javadzadeh, Elnaz Shaseb and Mojgan Mirghafourvand

Because of the importance of having enough sleep in life and health, this study aims to determine the effect of vitamin D supplementation on sleep quality and pregnancy symptoms…

Abstract

Purpose

Because of the importance of having enough sleep in life and health, this study aims to determine the effect of vitamin D supplementation on sleep quality and pregnancy symptoms (primary outcomes) and side effects (secondary outcome).

Design/methodology/approach

In this triple-blind randomized controlled clinical trial, 88 pregnant women with gestational age of 8–10 weeks and serum vitamin D concentration less than 30 ng/ml were allocated into vitamin D (n = 44) and control (n = 44) groups by blocked randomization method. The vitamin D group received a 4,000 IU vitamin D pill, and the control group received a placebo pill daily for 18 weeks. Independent t-, Mann–Whitney U and ANCOVA tests were used to analyze the data.

Findings

The post-intervention mean (SD: standard deviation) of total sleep quality score in the vitamin D and placebo group were 1.94 (2.1) and 4.62 (1.71), respectively. According to the Mann–Whitney U test, this difference between the two groups was statistically significant (p < 0.001). The mean (SD) of pregnancy symptoms in the vitamin D and placebo groups was 23.95 (16.07) and 26.62 (13.84), respectively, and there was no significant difference between the two groups based on ANCOVA test (p = 0.56). Considerable side effects were not observed in any groups.

Originality/value

This study was conducted due to the contradictory results of the effect of vitamin D on sleep quality and the high prevalence of sleep disorders and pregnancy symptoms.

Details

Nutrition & Food Science , vol. 53 no. 8
Type: Research Article
ISSN: 0034-6659

Keywords

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