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This study aims to investigate Sri Lankan Government university students’ acceptance of Chat Generative Pretrained Transformer (ChatGPT) for educational purposes. Using the unified theory of acceptance and use of technology 2 (UTAUT2) model as the primary theoretical lens, this study incorporated personal innovativeness as both a dependent and moderating variable to understand students’ ChatGPT use behaviour.

This quantitative study used a questionnaire survey to collect data. A total of 500 legitimate undergraduates from 17 government universities in Sri Lanka were selected for this study. Items for the variables were adopted from previously validated instruments. Partial least squares structural equation modelling (PLS-SEM) using SmartPLS 4 was used to investigate latent constructs’ relationships. Furthermore, the variables’ relative relevance was ranked using a two-stage artificial neural network analysis with the SPSS 27 application.

The results of the analysis revealed that eight of the nine proposed hypotheses were confirmed. The most significant determinants of behavioural intention were habit and performance expectancy, closely followed by hedonic motivation and perceived ease of use. Use behaviour was highly influenced by both behavioural intention and personal inventiveness. Though personal innovativeness (PI) was suggested as a moderator, the relationship was not significant.

The research highlights the impact of habit, performance expectancy and perceived ease of use on students’ acceptance of AI applications such as ChatGPT, emphasising the need for efficient implementation techniques, individual variations in technology adoption and continuous support and training to improve students’ proficiency.

This study enhances the comprehension of how undergraduate students adopt ChatGPT in an educational setting. The study emphasises the significance of certain variables in the UTAUT2 model and the importance of PI in influencing the adoption of ChatGPT in educational environments.

The purpose of this study is to detect the effect of some natural cellulosic polymers in their nano forms with the addition of zinc oxide nanoparticles on restoring the lost mechanical strength of degraded papyrus without any harmful effects on the inks.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

The effect of strengthening materials was studied on cellulose and carbon ink, which makes this study closer to reality as the manuscript is the consistent structure of cellulose and inks, whereas most of the literature stated the impact of consolidation materials on the strengthening the cellulosic supports without attention to their impact on inks.

This study aims to investigate the causal relationships among environmental, social and governance reporting (ESGR), stakeholder sustainability awareness, use of artificial intelligence (AI), sustainability culture, innovation performance and climate resilience of organizations across diverse sectors in Sri Lanka.

A survey was conducted among 327 respondents, including senior accounting professionals, operations managers and functional heads to gather company-level data in various industries in Sri Lanka. A disjoint two-stage approach validated the measurement model, and the partial least squares structural equation model (SEM) was used to test the proposed hypotheses.

The analysis evidences the mediating role of stakeholders' sustainability awareness on the relationship between ESGR and sustainability culture. Furthermore, it emphasizes the role of sustainability culture in driving climate resilience. Innovation performance acts as a moderator, strengthening the relationship between the use of AI and sustainability culture.

The study suggests that organizations should strategically use ESGR, integrate AI and prioritize stakeholder engagement to strengthen their commitment to sustainability. These provide insight for decision-making in organizations seeking to align with sustainable business practices.

It explores the use of AI to enhance ESGR and sustainability culture, providing a broader understanding of how organizations manage AI and stakeholders in sustainability issues.

This study examined public perceptions of law enforcement agencies in Mogadishu, Somalia. Specifically, the researchers examined the predictors of public trust in the police in Somali post-conflict contexts.

Data were collected through an online cross-sectional survey of 425 Mogadishu residents. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data and test the hypothesized relationship.

The results revealed that perceived police accountability, performance and professionalism significantly and positively influence public trust in the Somali police force.

This study provides practical recommendations for Somalia’s policymakers and law enforcement agencies. It emphasizes the importance of implementing stronger accountability systems, programs to enhance performance and training in professional conduct as key approaches to restoring and maintaining public confidence in the police force. These initiatives are crucial for preserving social stability and ensuring public safety in a society recovering from conflicts.

This study fills a significant gap in the literature by providing a comprehensive framework that combines performance and social learning theories to explore public trust in the police within a post-conflict context. The findings contribute valuable knowledge on the factors that can enhance public trust in law enforcement in countries recovering from conflict, particularly Somalia.

This study aims to investigate the co-movement and information transmission between conventional and Islamic equity indices in Sri Lanka.

This study uses daily data of All Share Price Index and Dow Jones Islamic Market Sri Lanka Index from 2013 to 2023 for conventional and Islamic proxies. Descriptive statistics, cross-correlation, dynamic conditional correlation (DCC)-GARCH and wavelet analysis were used for the investigation.

Analyses reveal synchronous correlation yet lead-lag dynamics between the indices. The Islamic index has lower volatility, clustering and persistence than the conventional index. Localized volatility patches and scale-dependent synchronicity suggest diversification opportunities to optimize risk-adjusted returns.

The insights from this study are important for investors to optimize diversified portfolios by exploiting time-varying correlations. The identified lead-lag dynamics, bidirectional information flows and scale-dependent synchronization between the indices enable both investors to predict market movements for effective asset allocation and regulators to monitor market efficiency and stability and implement shock mitigation measures.

This study uniquely integrates DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and wavelet analysis to examine the dynamic, time-varying relationships between Islamic and conventional equity markets in Sri Lanka’s dual financial system. This approach helps embrace both short-run changes and long-run movements to gain in-depth co-movement and spillovers, as well as potential diversification gains within an emerging financial market.

This study aims to comprehensively examine the relationship between initial public offering (IPO) activities and macroeconomic factors in Sri Lanka.

This study uses principal component analysis (PCA) and autoregressive distributed lag (ARDL) techniques to examine the relationship between IPO activities and macroeconomic factors. Ten macroeconomic variables are transformed into principal components (factors) using PCA. Then, ARDL is applied to investigate the long- and short-term relationships between IPO activities and the transformed macroeconomic factors.

The empirical investigation identifies three principal factors from the ten macroeconomic variables, of which two factors have a significant long-run association with IPO activities: “return on investment (RTOI)” and “economic and market development (ECMD).” In the short run, “trade openness and banking sector development (TOBD)” and RTOI are significantly associated with IPO activities.

The study was based on 30 years of observations, which passed all diagnostic tests but may be insufficient for generalizing the findings. Future studies could use high-frequency data (monthly or quarterly) to increase the number of observations and repeat the method and analysis. Also, while the symmetrical ARDL method was used in this study, an asymmetrical ARDL method may provide more insightful results and interpretations.

The study highlights the importance of considering both long- and short-term associations when analyzing the impact of macroeconomic variables on IPO activities.

This study is the first to comprehensively examine the relationship between IPO activities and macroeconomic variables using PCA and the ARDL technique. The study provides insight into the macroeconomic factors that influence IPO activities in Sri Lanka and highlights the importance of considering long- and short-term associations.

This study aims to explore the motives behind the company’s decision to go public in Sri Lanka.

This study adopts the explanatory sequential mixed-method approach based on the benefit-cost trade-off theory, incorporating survey-based descriptive statistics of 143 respondents from listed companies in the Colombo Stock Exchange (CSE) followed by content analysis of 52 initial public offering prospectuses and 11 interviews with top management of listed companies.

Companies primarily go public to raise capital for long- and short-term growth, followed by enhancing corporate image and governance structure. Also, they go public to rebalance capital structure, lower the cost of capital, diversify risk, compete in their product market and grab market timing opportunities. Furthermore, the qualitative analysis established that companies are going public also for value addition, broadening the ownership structure, establishing new strategic partnerships and funding for working capital requirements, which are not highlighted in previous studies.

These findings offer valuable insights for policymakers aiming to attract new companies to CSE, which would contribute to the capital market development of Sri Lanka.

This study combines quantitative survey and qualitative content analysis in a single investigation, revealing novel motives for going public that were not previously identified. This approach allows for a more comprehensive topic exploration, including the participants’ experiences and perceptions, while minimizing bias and maximizing robustness. This study is more comprehensive than previous studies that relied on descriptive statistics.

The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively designing and managing a single-supplier multi-retailer cold chain for fresh produce with deterministic demand to minimize the total cost, which includes cooling, loss of value and carbon emission costs.

The global stability index (GSI) method and the non-Arrhenius model are integrated to describe the behavior of food quality degradation. The power-of-two (PoT) policy is adopted in determining the coordinated replenishment policies for the suppliers and retailers, and an appropriate wholesale price structure that can achieve the coordination of the chain is presented.

The properties of the cold chain are uncovered, and an appropriate wholesale price scheme that achieves chain coordination with the optimal PoT decision is provided. In the numerical examples, different scenarios are investigated, and it is found that the cold chain parameters influence the optimal decisions in certain ways.

The PoT policy – an efficient policy to determine the replenishment strategy – has not been adopted in finding the solution of a single-supplier multi-retailer cold chain in the literature. Also, no study has compared the uncoordinated and coordinated cold chain. Moreover, in the existing literature, the wholesale price is usually a constant rather than having a coordinated scheme. This research aims to fill these research gaps.

Muslim engagement with cryptocurrencies (CC) raises fundamental questions rooted in religious faith: How should Muslims integrate Islamic Accounting principles like zakat into this new and rapidly evolving financial paradigm? Thus, it is essential to understand CC holders’ perceptions thoroughly and whether they are willing to pay zakat using crypto assets. This research aims to explore factors influencing Muslim CC holders’ intention to pay zakat on CC, emphasizing financial risk, theory of planned behavior (TPB) constructs and Shariah compliance’s moderating role.

This attempt uses a quantitative approach through a cross-sectional research design, using purposive sampling to gather data from Muslim CC holders. An extended theory of planned behavior (ETPB) model is applied to comprehensively analyze the key factors influencing intentions to pay zakat on CC. SmartPLS software is used to generate meaningful findings.

The study finds that financial risk associated with CC exerted a negative influence on TPB constructs, attitude (ATT), social norms (SN) and perceived behavioral control regarding zakat on CC (PBC). However, ATT and PBC positively shaped holders’ intention to pay zakat on CC. Interestingly, Shariah compliance-moderated interactions of TPB constructs on payment intentions were statistically significant.

With the rise of CC, a profound transformation is underway in the financial landscape. As this evolution unfolds, it becomes increasingly essential for stakeholders to understand how zakat could fit into such a new and rapidly evolving paradigm. A pioneering effort was made in this study by exploring Muslim CC holders’ intentions to fulfill zakat obligations, bridging a significant gap in the literature.

This study aims to investigate the intentions of Muslim cryptocurrency (CC) holders to fulfil their zakat obligations on digital assets, exploring the unique motivations and barriers within this emerging financial landscape.

The research uses a quantitative approach and a cross-sectional research design through online surveys, using purposive sampling to gather data from Muslim CC holders. The integrated model, known as the theory of planned behaviour and social cognitive theory (TPB-SCT) model, is used to comprehensively analyse the key factors influencing intentions to pay zakat on cryptocurrencies (CCs).

The study reveals that attitude towards zakat on CCs and perceived behavioural control regarding zakat on CCs have a significant and positive effect on the intention to pay. In contrast, subjective norms show no significant influence. CCs-related financial risk exerts a negative impact on intention. Moreover, CCs-related zakat knowledge and adherence to Shariah compliance are strongly associated with intention. These findings provide insights into the intricate dynamics of religious compliance within the evolving realm of digital assets.

Outcomes offer profound indications to stakeholders, including financial institutions, zakat agencies, policymakers and the community, on how to integrate zakat into this new and rapidly evolving financial paradigm like CC.

A pioneering effort was made in this study by exploring the intentions of Muslim CC holders to fulfil zakat obligations, bridging a significant gap in the existing literature. Developing and validating an integrated model of TPB-SCT in the realm of zakat on CC enriches the literature with a novel theoretical framework.