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Open-access repositories (OARs) are essential for openly disseminating intellectual knowledge on the internet and providing free access to it. The current study aims to evaluate the growth and development of OARs in the field of technology by investigating several characteristics such as coverage, OA policies, software type, content type, yearly growth, repository type and geographic contribution.

The directory of OARs acts as the source for data harvesting, which provides a quality-assured list of OARs across the globe.

The study found that 125 nations contributed a total of 4,045 repositories in the field of research, with the USA leading the list with the most repositories. Maximum repositories were operated by institutions having multidisciplinary approaches. The DSpace and Eprints were the preferred software types for repositories. The preferred upload content by contributors was “research articles” and “electronic thesis and dissertations”.

The study is limited to the subject area technology as listed in OpenDOAR; therefore, the results may differ in other subject areas.

The work can benefit researchers across disciplines and, interested researchers can take this study as a base for evaluating online repositories. Moreover, policymakers and repository managers could also get benefitted from this study.

The study is the first of its kind, to the best of the authors’ knowledge, to investigate the repositories of subject technology in the open-access platform.

The study examined the comprehensive assessment of the efficacy of Library and Information Science (LIS) CPD programmes in the particular setting of Indian academic libraries in Northern India. The study systematically assessed the programmes' impact on four levels: behaviour, reaction, learning, and results, using Donald Kirkpatrick’s widely recognised evaluation model.

The research employed a census sampling method and a questionnaire to gather information from 177 respondents employed in university libraries.

The findings demonstrated that professionals were satisfied with the CPD programmes, eager to learn more and apply their newly acquired knowledge and skills at their workplaces, and interested in applying learning to get results. Moreover, the significant factors that hindered the implementation of learning in the workplace were a lack of management support and poor IT infrastructure.

The paper’s uniqueness and significance come from carefully examining the effects of CPD programmes in LIS within the particular setting of university libraries in Northern India.

The study aims to investigate the influence of HIX.AI, an artificial intelligence (AI) tool that humanizes the generated content, on the detection capabilities of AI-generated text detectors.

The study investigates the reliability of six AI-generated content detection tools by passing ten essays, five each generated using Chat Generative Pre-Trained Transformer (ChatGPT) and Bard (Gemini) before and after passing through HIX.AI, which humanizes the AI-generated content.

The study found that the selected AI-generated text detectors identified the generated content with inconsistencies. Some of the essays were falsely identified as human-written by a few detectors, indicating that the detectors are unreliable. Post-HIX.AI application found that all the essays were passed as human-written except two, which identified as AI-generated and mixed content by two separate detectors.

The findings present the evolving field of AI-generated text detectors and the tools that can bypass the detectors highlighting the difficulties in identifying the generated content in the presence of the humanization tool. Passing the generated content as human-written has serious consequences, especially in academics. Hence, the study recommends more robust detectors to distinguish human-written and AI-generated content accurately.

The study contributes to the existing literature on AI text detectors and highlights the challenges that humanization tools pose in identifying AI-generated text by AI text detectors.

Emerging nations strive to diminish their ecological impact to meet net-zero targets, yet encounter formidable hurdles in curbing their environmental footprint. This purpose necessitated the study into impact of stock market, renewable energy and international investment on the ecological footprint in emerging countries from 1990 to 2020.

The study used augmented mean group (AMG) estimator, cointegration and heterogenous panel causality approach.

Results from the AMG show that renewable energy consumption reduces environmental pollution in most countries except Mexico. The study disclosed that stock market capitalization decreases ecological footprint in emerging countries. Using both the Kao and Pedroni cointegration methods, the study affirms the existence of stable equilibrium relationship in the long term. The causality test concluded a bidirectional relationship between stock market and ecological footprint and a unidirectional link between international investment, clean energy and ecological footprint.

The research is limited to only emerging countries. Therefore, future research should examine the environmental impacts of renewable energy consumption in different countries and regions, taking into account the local environmental conditions, policies and practices. This would help to identify the best practices and standards for minimizing the ecological footprint of renewable energy technologies and maximizing their benefits for environmental sustainability.

The study found that stock market capitalization reduces ecological footprint in Brazil, China, Turkey and India. To foster a culture of sustainability in stock market development impact, academic policies should emphasize the integration of environmental education across disciplines. By promoting awareness of the ecological consequences of stock market activities, societies can cultivate a mindset that values responsible economic practices. This, in turn, can lead to informed decision-making at individual and institutional levels.

First, since the study found that clean energy reduces ecological footprint, advocating for utilization of clean energy sources could be a key priority in emerging countries. Governments should incentivize the development and adoption of renewable energy technologies, such as wind and solar power, by providing subsidies and tax benefits. Furthermore, increasing awareness among residents about the benefits of clean energy and promoting its utilization in both residential and commercial environments can expedite the transition to a more environmentally friendly energy combination.

First, it pioneers an exploration into the interplay between stock market capitalization, international investment, clean energy and ecological footprint in emerging countries. Secondary unlike, unlike prior research, this study uses methodologies that account for cross-sectional dependencies and a unique characteristic specific to each country. In addition, by using common correlated effects mean group, AMG, cointegration and causality procedures, this study distinctly isolates and analyzes empirical findings for each country, leading to policy-oriented outcomes.