What drives the performance and causality of green bond indices?

This paper empirically assesses the performance of green bond indices and the causality of that performance using a range of financial and commodity data. We present new insights from the novel application of datasets, neural networks and performance measurements. We find that green bond indices do not outperform the market when factors beyond market return are considered. We find that Brent crude oil has the most significant effect on certain indices, a finding that contrasts with other studies on green bonds. A greater sensitivity to oil prices and global green equities also evinces a negative impact on a green bond index's ability to outperform the market. For the first time, a linear causal relationship is established between Title Transfer Facility (TTF) returns and green bond index returns. Additionally, a fundamental shift in causal relationships is observed over the COVID-19 period. In this way, we contribute to the literature on sustainable green bonds and the impact of COVID-19. These insights provide more clarity to market participants for navigating the uncertainties of both the global energy transition and the postpandemic period. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

A Situational Based Reliability Indices Estimation of ULT Freezer using Preventive Maintenance under Fuzzy Environment

Reliability of high demand machines is quite necessary and it can be maintained through proper and timely maintenance, Ultra-low temperature (ULT) freezer is one of those kinds of machines which are in high demand during covid-19 pandemic for the storage of vaccine. The rapid production of vaccines for the prevention of coronavirus disease 2019 (COVID-19) is a worldwide requirement. Now the next challenge is to store the vaccine in a ULT freezer. It's become really a big problem to store the vaccine which creates the demand of ULT freezer. The present paper investigates a situational based performance of the ULT freezer with the aim to predict the impact of different component failures as well as human errors on the final performance of the same. For the study, it is not possible to extract the parameters (failure rate and repair time) of the components that never failed before. Thus, to overcome this difficulty, here authors use the possibility theory. Authors present the available data in Right triangular fuzzy number with some tolerance as suggested by system analyst. The lambda-tau methodology and arithmetic operations on right triangular generalized fuzzy numbers (RTrFN) are used to find the various performance parameters namely MTTF, MTTR, MTBF, reliability, availability, maintainability (RAM) and ENOF, under fuzzy environment. The proposed model has been studied using possibility theory under working conditions, preventive maintenance as well as under the rest of conditions. This study reveals the most and least critical component of the ULT freezer which helps maintenance department to plan the maintenance strategy accordingly.

Measuring College Students' Satisfaction with the Teaching Effectiveness of Online English Courses Based on the IPA Model

The English learning ability and academic performance of pre-service teachers affect the future professional development of preschool and primary education teachers. The English course has been transferred to online due to COVID-19. Whether the practicability of e-learning is consistent with students' expectations primarily affect teaching effectiveness. A paired-sample t-test on the importance and satisfaction of online English learning effectiveness of pre-service teachers from freshmen to juniors at a private university revealed no significant difference in the overall importance and satisfaction. Then the coordinated system is constructed according to the Importance -Performance Analysis (IPA) to identify the critical indicators for improving the teaching effect of online courses. The results imply that network stability and teachers' timely responses to students' questions should be concentrated. In addition, students are pretty satisfied with the e-learning platform, teaching quality and management, which should be further maintained. The suggestions for improving the effectiveness of online English teaching in private universities are proposed accordingly. © 2023 IEEE.

Deep learning and Gaussian Mixture Modelling clustering mix. A new approach for fetal morphology view plane differentiation.

The last three years have been a game changer in the way medicine is practiced. The COVID-19 pandemic changed the obstetrics and gynecology scenery. Pregnancy complications, and even death, are preventable due to maternal-fetal monitoring. A fast and accurate diagnosis can be established by a doctor + Artificial Intelligence combo. The aim of this paper is to propose a framework designed as a merger between Deep learning algorithms and Gaussian Mixture Modelling clustering applied in differentiating between the view planes of a second trimester fetal morphology scan. The deep learning methods chosen for this approach were ResNet50, DenseNet121, InceptionV3, EfficientNetV2S, MobileNetV3Large, and Xception. The framework establishes a hierarchy of the component networks using a statistical fitness function and the Gaussian Mixture Modelling clustering method, followed by a synergetic weighted vote of the algorithms that gives the final decision. We have tested the framework on two second trimester morphology scan datasets. A thorough statistical benchmarking process has been provided to validate our results. The experimental results showed that the synergetic vote of the framework outperforms the vote of each stand-alone deep learning network, hard voting, soft voting, and bagging strategy.

Research on Affective Interaction in Mini Public Transport Based on IPA-FMEA

In the promotion of sustainable modes of transport, especially public transport, reasonable failure risk assessment at the critical moment in the process of service provider touch with users can improve the service quality to a certain extent. This study presents a product service touch point evaluation approach based on the importance–performance analysis (IPA) of user and failure mode and effect analysis (FMEA). Firstly, the authors capture service product service touch points in the process of user interaction with the product by observing the user behavior in a speculative design experiment, and perform the correlation analysis of the service product service touch point. Second, the authors use the IPA analysis method to evaluate and classify the product service touch points and identify the key product service touch points. Thirdly, the authors propose to analyze the failure of key product service touch points based on user-perceived affective interaction and clarify the priority of each key touch point. Finally, reluctant interpersonal communication, as the key failure caused by high risk, is derived according to the evaluation report, which leads to establishing new product service touch points and improving the overall user experience to promote sustainable transports with similar forms and characteristics.

A Study on the Usage Factors of Mobile Banking Apps by Korean Banks in Vietnam: Focused on the Viewpoints of App User and App Provider

Purpose - Vietnam has the fastest growing digital economy in Southeast Asia and is emerging as a critical overseas market for Korean banks in the post-COVID-19 era. Accordingly, many Korean banks entered the Vietnamese market to overcome the limitations of the saturated domestic financial market and create new revenue sources. This study examined the current status of digital finance in Vietnam and the cases of Korean banks that have succeeded in the Vietnamese market. Then, importance-performance analysis (IPA) was conducted on local customers, managers and staff members of Korean banks in Vietnam. Design/methodology - In this study, we analyzed the importance and satisfaction factors of mobile banking app usage in Vietnam through IPA. In particular, we identified the differences between the two groups by considering the viewpoint of customers who use mobile banking apps and that of managers and staff members who provide mobile banking services. Findings - The IPA results from the customer group and managers and staff members group were generally similar, but differences were observed in Ease of Use (Technology), Innovativeness (Organization), and Increase in Revenue (Economic). In the case of the customer group, Ease of Use (Technology) is located in the second quadrant, which shows low satisfaction compared to high importance. However, in the managers and staff members group, Ease of Use (Technology) is located in the first quadrant, which indicates high importance and high satisfaction. This difference in perception can cause complaints from local customers;thus, it is necessary to change the perception of the technological aspect for ease of use of mobile banking apps in consideration of the customer's position. In addition, it is necessary to allocate the resources invested in the Innovativeness (Organization) and Increase in Revenue (Economic) to Ease of Use (Technology). Originality/value - In this study, based on the HOTE framework, factors for using mobile banking apps were derived, and IPA was conducted targeting local customers (app user) and managers and staff members (app provider) of Korean banks in Vietnam. Through this, we presented the results of empirical analysis that can help Korean banks efficiently utilize limited resources and budgets.

A retrospective overview of the Journal of Public Budgeting, Accounting and Financial Management using bibliometric analysis

Purpose - The study aims to explore a retrospective overview of the Journal of Public Budgeting, Accounting and Financial Management, a prestigious international journal in the discipline. It also analyses the bibliometric information of its publications between 2011 and 2021 in terms of authors, countries, documents, themes, topics and sources.Design/methodology/approach - The performance analysis and science mapping were conducted using the data from Scopus between 2011 and 2021. The bibliometric information of 301 publications was visualised through the analysis types, such as co-authorship, co-citation and bibliographic coupling, through the VOSviewer software programme.Findings - The main finding is that the journal has recently improved in several areas (e.g. its productivity and visibility, citations, index scores and international collaborations). Although financial aspects such as accounting and accountability, financial management and public budgeting maintained their importance during the analysing period, some other features were revealed as new research themes. However, there are some research gaps regarding sustainable development goals, climate change and other matters, and the solutions for them through public fiscal policies.Research limitations/implications - The analyses are primarily backwards oriented by their very nature. Although they were excellent at portraying the past, the findings provided limited information about subjects that would be hot topics in future. The study has some limitations. The information on publications was collected from the Scopus database. However, bibliometric analyses were conducted from 2011 to 2021 as its data on Scopus did not cover before 2011. Second, the data are dynamic over time and may contain various changes in the future. Therefore, the bibliometric analysis may be repeated by including new studies of JPBAFM in the following years.Social implications - A performance analysing that the editorial team could benefit from in order to monitor the productivity of JPBAFM, one of the popular and favoured journals in the discipline, was conducted in this paper. The editorial team may also find ideas for the intellectual development of the journal as a result of mapping the performance of the publications.Originality/value - The bibliographic analysis of the Journal of Public Budgeting, Accounting and Financial Management has yet to be conducted. The study presents comprehensive findings on the performance and bibliometric analysis of the journal to guide authors and readers.

Promoting Green Buildings and Low-Carbon Design Strategies of Green B&B Rooms for Sustainable Tourism after COVID-19

COVID-19 opened a window of opportunity to change the green development of the hospitality industry. For many years, Chinese tourists have been the world's largest source of outbound tourists. Therefore, this study attempted to improve built-environment strategies for green rooms at B&Bs using the empirical statistics of Chinese tourists after the end of COVID-19 control measures and different green B&B standards, combining IPA (importance-performance analysis). For the lack of a green built-environment study from a tourism perspective, this study can be used mainly for improving the green satisfaction of urban B&Bs as it attempted to fill the gaps in research on green B&B rooms. This study will significantly help improve the quality of green rooms for the B&B industry in the future, and it also provides an improved green B&B room sample for other countries and regions. Moreover, it is an optimistic attempt at hospitality and tourism recovery. © 2023 by the authors.

A Comprehensive Review of Machine Learning Techniques for Predicting the Outbreak of Covid-19 Cases

At present, the whole world is experiencing a huge disturbance in social, economic, and political levels which may mostly attributed to sudden outbreak of Covid-19. The World Health Organization (WHO) declared it as Public Health crisis and global pandemic. Researchers across the globe have already proposed different outbreak models to impose various control measures fight against the novel corona virus. In order to overcome various challenges for the prediction of Covid-19 outbreaks, different mathematical and statistical approaches have been recommended by the researchers. The approaches used machine learning and deep learning based techniques which are capable of prediction of hidden patterns from large and complex datasets. The purpose of the present paper is to study different machine learning and deep learning based techniques used to identify and predict the pattern and performs some comparative analysis on the techniques. This paper contains a detailed summary of 40 paper based on this issue along with the use of method they applied to obtain the purpose. After the review it has been found that no model is fully capable of predicting it with accuracy. So, a hybrid model with better training should be employed for better result. This paper also studies different performance measures that researchers have used to show the efficiency of their proposed model.

A Comprehensive Study to Investigate Student Performance in Online Education during Covid-19

During the recent Covid-19 pandemic, there has been a tremendous increase in online-based learning (e-learning) activities as nearly every educational institution has transferred its programs to digital platforms. This makes it crucial to investigate student performance under this new mode of delivery. This research conducts a comparison among the traditional educational data mining techniques to detect the best performing classifier for analyzing as well as predicting students' performance in online learning platforms during the pandemic. It is achieved through extracting four datasets from X-University student information system and learning platform, followed by the application of 6 classifiers to the extracted datasets. Random Forest Classifier has demonstrated the highest accuracy in the first two out of the four datasets, while Simple Cart and Naïve Bayes Classifiers presented the same for the remainder two. All the classifiers have demonstrated medium to high TP rates, class precision and recall, ranging from 60% to 100% for almost all of the classes. This study emphasized the attributes that have a direct impact on students' performance. The outcomes of this study will assist the instructors and educational institutions to identify important factors in the analysis and prediction of student performance for online program delivery.

Evaluating supply chain resilience using supply chain management competencies in the garment industry: a post COVID analysis

This study contributes to the complex adaptive system theory by offering a valid hierarchical model to evaluate the theory's important features related to resilience. The garment industry in Bangladesh encountered disruption in the supply chain during the COVID-19 pandemic and the supply chain competencies played a vital role in overcoming the crisis. Limited studies are built on a solid theoretical foundation and considered supply chain competencies in assessing supply chain resilience. This study aims to develop a multi-criteria hierarchical measurement structure by considering the supply chain competencies to evaluate supply chain resilience. Fuzzy Delphi method and Fuzzy importance and performance analysis approach were applied for the study purpose. Findings reveal health and safety management, information management system, business intelligence, innovation capabilities management, technological innovation, and artificial intelligence as critical criteria, and data, information, and computing, technological innovation and adaptation are critical aspects that require improvement. [ FROM AUTHOR] Copyright of Journal of Industrial & Production Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Sustainability for the festival policy: Focused on community and visitors

Purpose: To explore the evaluation between tourists' and residents' satisfaction with the tool of Importance-Satisfaction Analysis originally introduced by Importance-Performance Analysis. Design/methodology/approach: A survey was conducted at Anseong Matchum Land, the venue of the festival, and respondents were selected by the convenience sampling method. Also, rest areas at the festival site were used for data collection and 309 out of 400 were judged to be valid. Included in the questionnaires was a series of Likert-type questions about the respondent's satisfaction with 18 attributes of the festival and the importance of these attributes to overall satisfaction with the festival. Findings: The results of this research show that the average degree of importance for the 18 attributes is 3.89, and the degree of satisfaction is 3.02. The result identified that parking lot, rest area, and washroom were found included in "Concentrate Here" quadrant of the ISA matrix as needed to prior management in this festival. Research limitations/implications: This study tried to look into local heritage festival regarding comparative per-ception between festival goers and local residents with ISA to provide that actual problems and potential solutions to the decision-makers of the city to make a sustainable festival. However, it is difficult to extend the results of this festival to other festivals and further research is needed in the future. Originality/value: This research tried to find out the gap between perceived Importance and Satisfaction and to identify actual management problems regarding facilities and services of the festival by ISA analysis originally introduced by Importance-Performance Analysis. This study suggested what festival organizers should prepare for the festival that will be activated after the Covid 19 pandemic. © 2023 People and Global Business Association.

Performance Analysis of Agriculture Students in Adapting to Distance Learning During COVID-19 Pandemic through Educational Data Mining (EDM) Technique

This study intends to collect information on how undergraduate agriculture students at Central Philippines State University, Negros Occidental, Philippines assess the effects of the switch to distance learning. The objective is to identify student performance and surprising benefits using education data mining techniques and to use that information to suggest workable solutions for future crises in higher education. The C4.5 algorithm was used to examine how well respondents adapted to distance learning using the decision tree analysis model. One hundred fifty students accomplished a google form in conducting the survey. Given that many courses in the agricultural education system are practical in character and a complete transition to online mode may not be possible, the insights from this can help develop the curriculum for the new standard in the system. © Roman Science Publications Inc.

Opportunities for emerging market LLPs to improve the service quality of automotive parts exports in post-COVID-19

This research article proposes the service quality measures for four automotive lead logistics providers (LLPs) to improve the parts export business based at emerging markets such as India, China and Thailand. These measures have emerged from the pre-COVID-19 perception study on service quality from 117 global automotive professionals from auto original equipment manufacturers (OEMs). Multi-criteria decision-making (MCDM) framework and questionnaire survey method was applied. It concludes with the results of different methods such as service quality (SERVQUAL), importance-performance analysis (IPA) and improvement factor (IF), to explain the significance of export business and where to improve their service quality post-COVID-19. The result shows that the service quality factors of IPA model had wide-ranging reflection for LLPs to focus in comparison with SERVQUAL and IF to gauge the perception of automotive OEMs concerning the service quality of LLPs in the industry post-COVID-19. Copyright © 2022 Inderscience Enterprises Ltd.

Quality assessment of E-learning website using asymmetric impact–performance analysis and Kano's customer satisfaction model: a case study based on WebQual 4.0

Purpose: Using asymmetric impact–performance analysis for examining an asymmetric relationship between user satisfaction and website features, the present research aims to identify features of high priority for quality improvement. For doing so, the current research was conducted in the context of the E-learning website of the most prestigious university in Iran, namely, the University of Tehran. Design/methodology/approach: The main question was which of the three groups of basic, performance and excitement factors has the required dimensions of the quality of the website based on the model WebQual 4.0 by considering Kano's user satisfaction model and impact–performance analysis. This is a descriptive survey, applied and cross-sectional study. The study population included Tehran University's students who enrolled in virtual courses in the academic year 2020–2021 from which a sample of 457 students was selected. The data collection tool was the questionnaire of Webqual 4.0, as well as a researcher-made questionnaire to measure end-user satisfaction. Findings: Using structural equation modeling and multiple regression, the findings showed that the customer's overall satisfaction with the mentioned website is primarily affected by the feature interaction with services, including the two structures of trust and empathy, and then the dimensions of usability and quality of information. Examining the Webqual 0.4 dimensions indicated that the website usability dimension is a part of the high-performance excitement factors group, the information quality dimension is a part of the high-performance basic factors group and the website interaction dimension is in the low-performance basic factors group. Originality/value: The research is highly innovative taking the theoretical model of Kano and methodological investigation of asymmetric impact–performance analysis into consideration alongside the WebQual 4.0 as a fundamental model for website assessment. Moreover, the research was conducted on an E-learning website, which is unique and a necessity amid the COVID-19 pandemic. © 2022, Emerald Publishing Limited.

An Analysis of Health Perceptions and Performance in Elementary Students in Korea during the ongoing COVID-19 Pandemic.

During the coronavirus disease 2019 (COVID-19) pandemic, social distancing guidelines changed lifestyles, including increased sedentary time, physical inactivity, and disrupted sleep patterns among children. The purpose of the present study is to analyze the health awareness (mental health, disease, physical activity, sleep, eating habit, and hygiene health management) of elementary school students during the COVID-19 pandemic, and use the importance-performance analysis (IPA) technique to identify gender differences in health perceptions. We collected data on 1006 students, which was analyzed using frequency analysis, reliability testing, independent sample t-tests, and importance-performance analysis (IPA). A median importance value of 0.163 and a median performance value of 4.048 were selected as cross points to distribute the IPA matrix into four quadrants. The highest performance was given for wearing a mask and sanitary practice; the IPA matrix indicated that the sense of belonging, happiness, trust, and movement activity were located in quadrant I. Children's regular physical activity and level of physical activity were low, especially that of girls. Children's sleep management was poor. Their physical activity and sleep-related factors must be improved under the facilitation of the national government, public education institutions, and families.

Energy analysis of a phase change material embedded heat exchanger for air conditioning load reduction in different Indian climatic zones

Air conditioning (AC) systems for tropical countries like India account for sixty percent of the total energy needs of a building. With the onset of COVID-19, the increase of fresh air ventilation rate has been recommended by various guidelines for indoor spaces which increase the load on the AC system. The present study attempts to reduce this burden through retrofitting a phase change material (PCM) embedded pin fin heat exchanger into an air-conditioning system. The heat exchanger is designed to cater to the peak load fluctuations for cities in three hot climatic zones of India, viz., Jaisalmer, Kolkata, and Delhi. Dodecanol with a melting temperature of 24 degrees C, is chosen as the appropriate PCM material for these locations. The optimal pin fin diameters are estimated through an entropy generation minimization analysis for the three locations. A heat transfer analysis of the PCM embedded heat exchanger is further presented through an analytical approach to estimate the PCM mass requirement and energy savings potential. The masses of the PCM estimated for Jaisalmer, Kolkata, and Delhi are 11.36 kg, 22.42 kg, and 19.35 kg, respectively for their respective peak load fluctuations of 0.25 kW, 0.28 kW and 0.48 kW. Energy savings of up to 4.7 % for Delhi, 2 % for Kolkata, and 2.75 % for Jaisalmer are identified with the PCM embedded heat exchanger incorporation. The results show the potential of such PCM thermal storage in reducing the peak energy demands of buildings amidst various environmental and health concerns.

Changes in vertical jump performance and body composition before and after COVID-19 lockdown

This study aimed to determine the effects of a 16-week COVID-19 lockdown on body composition and vertical jump performance. Thirteen martial artists participated in this study. Participants were tested at: 1) pre-lockdown (pre), 2) post-lockdown (post), 3) two-weeks-post-lockdown (post+2), and 4) four-weeks-post-lockdown (post+4). Repeated-measures-ANOVAs were conducted with post-hoc analyses. Differences were observed in vertical jump height (VJH) (10.33%), peak velocity (PV) (3.10%), reactive-strength-index-modified (RSImod) (13.8%), and peak-propulsive-power (PPP) (6.00%) from pre-to-post. There as an increase from post-to-post+2 in VJ (13.06%), PV (4.12%), RSImod (14.0%), and PPP (4.66%). There was an increase from post to post+2 in VJH (10.8%), PV (3.1%), RSImod (14.0%), and PPP (3.0%). Fat mass (FM) and BF% increased from pre to post (13% and 11%, respectively) and decreased from post to post+4 (8% and 11%, respectively);fat-free mass (FFM) decreased from pre-to-post (11%) and decreased from post-to-post+4 (8%). There were moderate associations (rmc = 0.42-0.47) between FFM and VJH, FMM and PPP, FFM and PV, BF% and PV, and FM and PV. While the lockdown resulted in a significant decrease in vertical jump performance and increases in BF and FM, participant's performance returned to pre-lockdown levels after only 2-4 weeks of post-lockdown training by decreasing BF, FM, and increasing FFM. © Faculty of Education. University of Alicante.

Addressing the impact of COVID-19 lockdown on energy use in municipal buildings: A case study in Florianópolis, Brazil.

COVID-19 has spread quickly to several countries following the initial outbreak of the disease. As a consequence, several measures have been taken to mitigate the virus spread worldwide. In the city of Florianópolis, in southern Brazil, a strict lockdown was implemented on 16 March 2020. Although commercial activities were allowed to resume 21 April, a complete lockdown of municipal public buildings (e.g., administrative buildings and schools) lasted up to 5 August 2020. Reports in the literature emphasize the influence of occupant presence and actions on energy use in buildings. Therefore, the objective of this study was to assess the impact of the COVID-19 lockdown on the electric energy use of municipal buildings in Florianópolis. A large database with monthly electric energy use data was provided by the City Hall and analyzed. Firstly, the consumer units were grouped into three categories: systems, services and buildings. This revealed that buildings were directly affected by the lockdown measures, but systems and services were not. Therefore, an in-depth evaluation of health centers, administrative buildings, elementary schools and nursery schools was conducted and mean electric energy reductions of 11.1 %, 38.6 %, 50.3 %, and 50.4 %, respectively, were observed. Although it may initially seem unexpected, municipal health centers had a small electric energy use reduction, because they were not directly responsible for COVID-19 treatment, as patients were forwarded to specific facilities. Walkthroughs and energy audits were performed in an administrative building, an elementary school, and a nursery school, to gain a deeper understanding of the consumption trends. It was observed that municipal buildings present a basal energy use intensity even when the buildings are unoccupied. Energy audits verified that stand-by loads and vital loads, such as lighting for safety and computer servers, play a key role in this share of energy use.