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Particles are of the controlled release delivery systems. Also, topically applied olive oil has a protective effect against ultraviolet B (UVB) exposure. Due to its sensitivity to oxidation, various studies have investigated the production of olive oil particles. The purpose of this study was to use chitosan and sodium alginate as the vehicle polymers for olive oil.

The gelation method used to prepare the sodium alginate miliparticles containing olive oil and particles were coated with chitosan. Morphology and size, zeta potential, infrared spectrum of olive oil miliparticles, encapsulation efficiency and oil release profile were investigated. Among 12 primary fabricated formulations, formulations F₅ (olive oil loaded alginate miliparticles) and F₁₁ (olive oil loaded alginate miliparticles + chitosan coat) were selected for further evaluations.

The size of the miliparticles was in the range of 1,100–1,600 µm. Particles had a spherical appearance, and chitosan coat made a smoother surface according to the scanning electron microscopy. The zeta potential of miliparticles were −30 mV for F₅ and +2.7 mV for F₁₁. Fourier transform infrared analysis showed that there was no interaction between olive oil and other excipients. Encapsulation efficiency showed the highest value of 85% in 1:4 (olive oil:alginate solution) miliparticles in F₁₁. Release study indicated a maximum release of 68.22% for F₅ and 60.68% for F₁₁ in 24 h (p-value < 0.016). Therefore, coating with chitosan had a marked effect on slowing the release of olive oil. These results indicated that olive oil in various amounts can be successfully encapsulated into the sodium-alginate capsules cross-linked with glutaraldehyde.

To the best of the authors’ knowledge, no study has used chitosan and sodium alginate as the vehicle polymers for microencapsulation of olive oil.

The COVID-19 pandemic has caused widespread disruptions to global industries, with the textile sector in South Asia being particularly hard hit. While previous studies have focused on the performance of textile sectors in individual countries, there is a gap in the literature on the comparative impact of the pandemic on the textile industry in South Asian nations. This study aims to fill this gap by investigating the performance of the textile sector in South Asian countries and identifying best practices for overcoming the pandemic’s adverse effects.

Using a comparative approach, this study analyzes the impact of COVID-19 on the performance of the textile sector in Pakistan, India and Bangladesh.

Our findings reveal that COVID-19 significantly negatively impacts the textile industry in Pakistan and India. However, Bangladesh has shown effective practices to support the textile industry and mitigate the pandemic’s adverse effects.

The findings of this study hold considerable implications for legislators, leaders, investors and supply chain management professionals operating within the South Asian textile sector. This research has the potential to inform policymakers in formulating strategies to facilitate the textile sector’s resilience during emergencies like the COVID-19 pandemic.

This paper provides significant theoretical additions to the current body of literature regarding the impact of COVID-19 on the textile sector in South Asia. The research uses the global value chain (GVC) theory as a theoretical framework to enhance understanding of the impact of global supply chains and interdependencies on the textile sector in the region.

This paper aims to understand how a sustainable entrepreneur through his/her sustainable innovation can implement the three pillars of sustainable development, i.e. economic, social and environmental pillars, and how an entrepreneurial opportunity can be sought in environmental problems to develop a new product.

A qualitative research approach using a single-case study design has been adopted. It discusses the case of an Indian sustainable entrepreneur working for the cause of reducing plastic pollution in India and providing employment to rural women from economically weaker backgrounds. Data was primarily collected through semi-structured interviews, which were analyzed through thematic analysis.

The paper shows how an entrepreneur through entrepreneurial opportunity discovery and sustainable innovation contributes toward sustainable development.

This study highlights the need for institutional support by governments for a wide spectrum of sustainable enterprises as they can help the governments in achieving sustainable development goals at local levels. It will also act as a representative example for the entrepreneurs about how one can covert an environmental problem into an opportunity, through sustainable innovation.

The originality of the study lies in the presentation of an innovative idea developed by the entrepreneur for addressing the problem of plastic waste. The case used here demonstrates that sustainable entrepreneurship, through sustainable innovation, can deal with multiple economic, social and environmental issues.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

Money laundering (ML) is the process used to convert the proceeds of crimes into lawful form. This global problem promotes social ills, corruption and organized crimes. Various instruments are used to counter individual illicit behavior. However, in low-income countries, these regulations are not common because of weak institutions, poor governance and a lack of awareness about the negative consequences of ML. In these countries, multinational corporations take advantage of poor law and order, lower environmental regulations and corruption and shift their domestic operations into foreign countries.

This study uses a multiple mediator model to investigate the link between foreign direct investment (FDI), environmental degradation measured as CO₂ emissions (CE), exports and ML for 118 countries between 2008 to 2018.

Results indicate that FDI promotes exports and CE, leading to illicit financial flows.

Policymakers should enforce checks on foreign funds flow and adopt illicit flow mitigation measures to minimize ML globally.