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Introduction: The effect of environmental regulations or green policies on the financial health of businesses is still up for debate. The Prime Minister of India presented a bold plan to achieve net-zero emissions by 2070 at the COP26 climate summit in Glasgow (UK). Following this announcement, numerous Indian companies voluntarily committed to becoming carbon neutral to support the ambitious emission reduction targets. A growing body of research examines the link between environmental standards compliance and businesses’ sustainability measures, and how they affect their overall performance (profitability, stock returns, or output generation).

Purpose: The research assesses the effect of these voluntary announcements on the stock performance of Indian companies in the context of voluntary commitments to reduce carbon emissions.

Methodology: Concentrating on the announcement impact of carbon neutrality commitments/carbon emissions reductions of 52 Indian companies, the study considers carbon neutrality pledges/carbon emissions reduction from 2018 to 2022. The sample companies list was taken from various indices on the National Stock Exchange. A standard event study methodology is applied to compute abnormal returns during the event window of (−10, 10).

Findings: The results show that companies announcing the carbon neutrality pledges/carbon emissions reduction received significantly negative abnormal returns of 0.49% on announcement day. The cumulative average abnormal returns for different windows are also negative. It signifies that investors don’t value the environmentally sustainable actions of firms. It may also be because of investors’ ignorance of carbon neutrality pledges and their importance, highlighting the need to educate investors about the significance of corporate sustainability initiatives.

The objective of this chapter is to analyse the performance of the UiPath (PATH) company on the New York Stock Exchange, in the context of the war between Russia and Ukraine, and to predict the closing price of the PATH stock using autoregressive integrated moving average with (ARIMAX) and without (ARIMA) exogenous variable methods and autoregressive neural networks (NNAR, NNARX).

UiPath has gained a significant reputation in the IT market and has become a point of interest in recent years. However, the current context is marked by an event of international impact, the war between Russia and Ukraine. In this context, this analysis will consider performance from two perspectives: forecasts of the closing price and forecasts of the closing price with an exogenous variable, namely the war between Russia and Ukraine.

In the analysis that follows, we will address a forecast of the stock closing price using ARIMA, ARIMAX, NNAR and NNARX, as well as analysis of changing points and structural breaks of the series.

The changing points in the mean and variance but also the breaks in the structure justify the course of the closing price. From the information extracted in the analysis, it can be concluded that market sentiment is currently pessimistic due to the downward trend in the price. Both the public and the shareholders are disappointed with the performance of PATH stock and are waiting for the next change point that will change the trend of the series.

This study tries to examine the effect of artificial intelligence (AI) drivers on the willingness to adopt the human capital supply chain (HCSC) in manufacturing firms (MFs) in developing countries (DCs) including Jordan, Saudi Arabia, Bahrain, Qatar and the United Arab Emirates, which are listed in the Chambers of Industry of these countries.

The quantitative methodology with a simple random sampling method was adopted using a questionnaire survey-based approach to collect data from 233 out of 1,055 participants (human resource (HR) managers and information technology (IT) senior managers) from various MFs (private and commercial), representing a 22% response rate. Covariance-based structural equation modeling (CB-SEM) was used to analyze the raw data using Amos V.25.

The results of this study showed that there are positive and statistically significant direct association effects between the reliability of use (RoU), competitive pressures (CPs) and user confidence (UC) factors on the willingness to adopt AI in HCSC in the MFs in DCs. At the same time, there is no significant effect on a firm’s infrastructure readiness (FIRs), in addition to the indirect effect of UC in the relationship between CPs and FIRs on the willingness to adopt AI in HCSC.

Such findings of this study can provide insightful implications for stakeholders and policymakers regarding the importance of using predictive AI drivers' effect on willingness to adopt the HCSC in the MFs in DCs as emerging economies. Additionally, the managers might focus on the existence of a significant positive indirect effect of UC as a mediating factor in the relationship between FIRs and willingness to adopt AI and its applications in HCSC systems and departments.

The goal of this study is to better understand the driving force behind the use of artificial intelligence (AI) in pharmaceutical manufacturing firms (PMFs) that are recognized as developing countries in the Middle East and North Africa (MENA) region that are listed by the Chambers of the Industries of Jordan, the Kingdom of Saudi Arabia, Morocco, and Algeria. Furthermore, the effect of adopting and using AI in managing raw materials (RMs), products, parts, and components for PMFs through supply chains (SCs).

A self-administrated questionnaire survey was used to gather data from 95 out of 511 participating managers (e.g. manufacturing, supplying, IT, operational, and logistical managers) utilizing a quantitative technique with a random sample size. In fact, 18.8% of the 89 different manufacturing firms (MFs) in the MENA area responded, with five to six managers from each company. The raw data was analyzed using partial least squares structural equation modeling (PLS-SEM).

The study’s findings show that the readiness to embrace artificial intelligence (AI) in the production management supply chain performance (PMSCP) of pharmaceutical manufacturing firms in the Middle East and North Africa (MENA) is positively and significantly influenced directly and indirectly by sustainable strategic supplier reliability (SSSR), shipping process dependability (SPD), technological factors (TFs), and infrastructure transformational development capability (ITDC).

As the studied countries are growing economies, such study findings might offer insightful consequences for stakeholders and policymakers regarding the significance of using artificial intelligence system adoptions in pharmaceutical manufacturing enterprises in the MENA region. The managers may also concentrate on the strong positive direct and indirect links between SSSR, SPD, TFs, and ITDC preparedness to accept AI adoption and its applications and systems in supply chain and production management departments and the consequences of informational and product delivery.

In recent years, natural dyes have attracted significant attention globally because of growing public awareness of the environment and health hazards associated with synthetic dyes. Natural dyes can provide special aesthetic qualities as well as the ethical significance of a product which is environmentally friendly. By keeping this burning issue in mind, this study aims to explore the dyeing properties of various unexplored environmentally friendly natural dyes.

In this study, the aqueous extract of coconut leaves is used for dyeing purpose. The silk and jute fabrics were dyed with the extract alone as well as in combination with metal salts as mordants by employing pre-, meta- and postmordanting techniques. The dyeing properties of the colored samples were evaluated by measuring their color strength; CIEL*a*b* values; and color fastness to washing, light and rubbing.

A yellow shade was achieved when the fabric samples were dyed solely with the extract. However, shade variations were observed when different mordants and mordanting techniques were applied. In all the cases, metallic salts improved the color fastness properties of dyed samples to washing, light and rubbing especially for the silk fabric.

To the best of the authors’ knowledge, this is the first report on a natural dye extracted from the leaves of coconut. Leaf as the source of dye has added an extra advantage, as it is reproducible and can be collected easily without harming the plants. The reported dye could be an attractive choice for sustainable and eco-friendly dyeing.

This paper assesses the environment of legitimacy by determining the role of institutional quality and policy uncertainty on the performance of five major South Asian stock markets (India, Pakistan, Bangladesh, Sri Lanka, and Nepal) using 21 years data from 2000 to 2020. The focus of this study is to approach the issue of the environment of legitimacy that leads to sustained market returns.

Panel cointegration tests of Kao and Pedroni are applied, and the Dynamic Panel Vector Autoregressive (PVAR) model is used to determine the estimates.

ADF P-Values of both Kao and Pedroni tests show that the panels are cointegrated; the statistical significance of the results of the Kao and Pedroni panel cointegration test confirms cointegration among the variables. After determining the most appropriate lag, the analysis is done using PVAR. The results indicate that institutional quality, policy uncertainty, and GDP positively affect stock market return. Meanwhile, government actions and inflation negatively affect stock market returns. On the other hand, stock market return positively affects institutional quality, government action, policy uncertainty, and GDP. While stock market return negatively affects inflation.

The sample is taken only from a limited number of South Asian countries, and the period is also limited to 21 years.

Based on our research findings, we have identified several policy implications recommended to enhance and sustain the performance of stock markets.

This paper uses a unique analytical tool, which gives a better insight into the problem. The value of this work lies in its findings, which also have practical implications and theoretical significance.

This study aims to investigate the effect of push, pull, balanced, and emotional factors on the motivational level of female entrepreneurship in Haryana state, India.

A quantitative study was conducted in Haryana's five districts among 384 women entrepreneurs using a convenience sampling method with a structured questionnaire. This study used structural equation modeling (SEM) to test the hypotheses.

The study found that Push, Emotional Factors, and Challenges have a significant impact on the motivational level of women’s entrepreneurship and Challenges only mediate with the Push and Pull factors.

Generalization of results based on data from a few districts of Haryana state in India. A cross-sectional study was performed as a Longitudinal study helps in analyzing the changing character of women entrepreneurs and the prime reasons behind their success. Non-probability sampling technique was used in the study whereas probability sampling technique promotes reliability and reduces systematic error and sampling bias.

Pull factors can be promoted through mentoring, counseling, and entrepreneurship training programs. Creating a conducive external environment with job security and financial support from external agencies is essential. The Government of India should take the necessary steps to reduce the hindrances faced by women entrepreneurship while raising funds through banks and financial institutions.

The study employed a mediating variable, challenges, to investigate the impact of factors on the motivational levels of women entrepreneurs. To the best of our knowledge, this approach has not been utilized in previous research, making the current study a novel contribution to the field.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

Entrepreneurship education (EE) through innovative teaching techniques (ITEE) and entrepreneurial intention (EI) are two essential components of entrepreneurship development. Using the assumptions of the Theory of Planned Behavior (TPB), we took three constructs: attitude (ATT), subjective norms (SUBNs), and perceived behavioral control (PBC), and from the assumption of Human Capital (HC) theory, we constructed another variable, ITEE. Thus, the fundamental objective of this study is to find out the essential predictor of EI between entrepreneurial antecedents (ATT, SUBNs, PBC) and ITEE through an artificial neural network (ANN).

Using the snowball sampling technique, a highly structured questionnaire was sent to respondents. Finally, a sample size of 397 business graduate students was chosen.

The findings revealed that two dimensions of entrepreneurial antecedents (attitude and subjective norm) positively impacted EI. Furthermore, ITEE partially mediated the relationship between two dimensions of entrepreneurial antecedents (attitude and subjective norm) and EI. Moreover, through ANN, we found that attitude (ATT) was a crucial predictor of EI among business graduate students in Bangladesh.

In this study, only business graduate students were included as respondents; thus, further research should include students from other departments or disciplines to generalize the findings.

This study covers numerous actors in terms of practical contributions, including students, academics, the government, and the state. This article should draw the attention of Bangladesh government policymakers regarding the significance of ITEE for developing entrepreneurship. The research framework of this study proposed that ITEE should implement antecedents of entrepreneurship into business education, boosting the ability of students to make judgments, which will also enhance EI in the future.

Integrating the TPB theory with human capital theory represents a significant scholarly advancement in business education for graduate students in Southeast Asia, namely Bangladesh. Furthermore, we developed a novel ITEE scale by synthesizing information from many literary sources, providing valuable insights for future researchers.