Search results

This study examines the preparedness and responsiveness of Malaysian academic librarians in handling disruptions in library services during a disaster.

This qualitative approach involved semi-structured interviews with decision-makers, chief librarians and library managers from five selected public universities.

Thematic and qualitative data analysis produced several key themes based on (1) disaster preparedness involving policies, plans, asset protection, risk management, coordination of disaster management and preparative measures; and (2) disaster response involving strategies for information and communication access, community engagement, emergency response teams and procedures, and resource availability.

The findings are expected to be useful for policymakers in formulating policies and guidelines for library disaster management plans.

The interruptions of academic library services during a disaster may result in the disruption of the information sources and social information networks of students, academics and researchers alike. Effective disaster management is also the library’s responsibility to protect collections that belong to society at large.

This is one of the first attempts in disaster management research to focus on the preparedness and responses of academic libraries in Malaysia in the face of disasters. Therefore, the results of this study can be used as a baseline for policymakers to prepare policies, guidelines and manuals for management in the event of a disaster.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

By examining the impact of the day of the week during the COVID-19 pandemic and the subsequent economic recession, it is possible to provide insights into market behaviour during volatile times that can be furnished to investors and policymakers for informed decisions.

This study investigates the day-of-the-week effect on the Colombo Stock Exchange (CSE), with particular emphasis on the variations in this effect during the COVID-19 pandemic and the subsequent economic crisis.

The study applies the Exponential Generalised Autoregressive Conditional Heteroskedasticity (EGARCH) model, allowing for the evaluation of asymmetric responses to positive and negative shocks. The data span from January 2006 to December 2022 and are segmented into different periods: the entire sample, war and post-war periods, the COVID-19 pandemic and the economic crisis period, each reflecting distinct market conditions.

The study uncovers a significant day-of-the-week effect on the CSE. Mondays and Tuesdays typically show a negative effect, while Thursdays and Fridays display a positive impact. However, this pattern shifts notably during the COVID-19 pandemic, with all weekdays exhibiting significant positive impact, and varies further across different waves of the pandemic. The economic crisis period also shows unique weekday effects, particularly before and after an important political event.

This study aims to test the Kuznets curve between economic growth and child labor, along with the influence of exports, household size and rural population in the context of Pakistan.

To achieve the research objective, this study applied the unit root test, bound co-integration test, and autoregressive distributive lags (ARDL) method for the period of 1972–2021.

The findings show an inverted U-shaped relationship between economic growth and child labor indicating that at the beginning stage of economic development, child labor increases due to lower per capita household and subsequently, in the long-run of economic development, child labor decreases due to the higher per capita households. Moreover, the results also show that exports, household size and rural population have a positive influence on increasing child labor.

The policymakers and government of Pakistan need to focus on long-term economic growth policies, ensure free quality education and cheap equipment which practices minimum manpower to reduce the threat of child labor.

Having long-run economic growth, the government of Pakistan need to equally benefit the households and the poor population to reduce child labor and enhance the social welfare of society.

To the best of the authors’ knowledge, this is the first study that investigates the Kuznets curve relationship between economic growth and child labor in the context of Pakistan. Moreover, this study contributes to the reduction in child labor through long-term economic growth in the context of Pakistan.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0387

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

Purpose: The COVID-19 pandemic has been a good example of a Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) world. Higher educational institutions (HEIs) have faced a massive hit because the jobs in this industry have become unexpected. Considering the most valuable assets ‘Teachers’ crunched in the VUCA crisis, the study intends to determine if personal harmony (PH) and organisational citizenship behaviour (OCB) would enhance teachers’ job satisfaction (JS).

Design/methodology/approach: Data are collected from the teachers of Indian HEIs and teachers who have experienced the impact of the COVID-19 catastrophe (VUCA). Considering the pandemic restrictions, data have been collected through an online survey (N = 364).

Practical Implications: PH is an individual’s internal quality and attribute that cannot be developed on force or situational need. Even in an uncertain situation, teachers have tried their best to contribute through professional service. Hence, people who possess PH contribute their best even though unsatisfied with their jobs.

Originality/value: This study has focused on finding the relationship between two different variables, PH and OCB (which has not been explored in Asian countries, majorly in India, where it has a vast cultural diversity and structure influencing the educational policies) that hinders the factors influencing JS, where these two variables are highly influenced by hygiene factors such as values, culture, ethical standards, personal belief, leadership styles, and fair treatment showcased by the organisations/institutions.

Introduction: ‘Ecotourism’ refers to tourism that promotes and preserves a site’s eco-heritage to make tourists aware of the cultural past and protect the environment at the same time. The elementary impression behind ecotourism is that it signifies an appealing alternative to the mass tourism paradigm, significantly altering the natural and social circumstances of tourist destinations worldwide.

Purpose: To study the various factors responsible for the prospects and development of ecotourism, including marketing strategies, which necessitates and deliberates for society’s well-being and the safeguarding of the landscape.

Need for the study: This research provides perceptions into the economic, environmental, and social factors and the marketing tools that influence the sustainable development of ecotourism and to address the historical neglect or minimal consideration of environmental impacts associated with tourism practices.

Methodology: The study involved quantitative analysis gathering primary data from 100 respondents and inclusion of secondary data sourced from journals and articles. The collected data underwent testing and analysis, employing descriptive statistical analysis, analysis of variance (ANOVA), correlation analysis, and structural equation modelling (SEM). These analyses successfully established relationships among the variables under investigation.

Findings: The study recommends a futuristic plan to boost the sustainable growth of ecotourism on the basis of the findings of the study.

Practical implication: The research underscores the pivotal role of local community engagement, education, enhanced visitor experiences, and strategic promotion facilitated by eco-smart technologies in fostering the sustainable growth of ecotourism destinations.

Introduction: Sustainability and Industry 4.0 have recently influenced the global economy. With the Industrial Revolution 4.0, there has been a significant focus on digital sustainability in enterprises. Micro, small and medium enterprises (MSMEs) are the most vulnerable sections regarding new transformations.

Purpose: Even during the COVID-19 pandemic, when all businesses had no option other than to adopt digitisation, MSMEs faced tremendous issues to make this shift. Despite the immense focus on digital sustainability, some deterrents exist to its adoption in MSMEs. Contemporary research focuses on determining the critical deterrents to digital sustainability in MSMEs.

Methodology: This chapter employs the interpretive structural modelling technique, and Matrice impacts Croises Multiplication Appliqué a classement (MICMAC) analysis to identify and further classify the deterrents to digital sustainability in MSMEs.

Findings: Legal barriers and firms’ economic conditions are identified as the major deterrents. Eliminating these deterrents would help minimise the minor ones too. To deliver global sustainability goals, digital sustainability must be duly adopted everywhere.

Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka.

Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis.

Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model.

Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant.

Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.