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The incompatibility of natural fibers with polymer matrices is one of the key obstacles restricting their use in polymer composites. The interfacial connection between the fibers and the matrix was weak resulting in a lack of mechanical properties in the composites. Chemical treatments are often used to change the surface features of plant fibers, yet these treatments have significant drawbacks such as using substantial amounts of liquid and chemicals. Plasma modification has recently become very popular as a viable option as it is easy, dry, ecologically friendly, time-saving and reduces energy consumption. This paper aims to explore plasma treatment for improving the surface adhesion characteristics of sisal fibers (SFs) without compromising the mechanical attributes of the fiber.

A cold glow discharge plasma (CGDP) modification using N₂ gas at varied power densities of 80 W and 120 W for 0.5 h was conducted to improve the surface morphology and interfacial compatibility of SF. The mechanical characteristics of unmodified and CGDP-modified SF-reinforced epoxy composite (SFREC) were examined as per the American Society for Testing and Materials standards.

The cold glow discharge nitrogen plasma treatment of SF at 120 W (30 min) enhanced the SFREC by nearly 122.75% superior interlaminar shear strength, 71.09% greater flexural strength, 84.22% higher tensile strength and 109.74% higher elongation. The combination of improved surface roughness and more effective lignocellulosic exposure has been responsible for the increase in the mechanical characteristics of treated composites. The development of hydrophobicity in the SF had been induced by CGDP N₂ modification and enhanced the size of crystals and crystalline structure by removing some unwanted constituents of the SF and etching the smooth lignin-rich surface layer of the SF particularly revealed via FTIR and XRD.

Chemical and physical treatments have been identified as the most efficient ways of treating the fiber surface. However, the huge amounts of liquids and chemicals needed in chemical methods and their exorbitant performance in terms of energy expenditure have limited their applicability in the past decades. The use of appropriate cohesion in addition to stimulating the biopolymer texture without changing its bulk polymer properties leads to the formation and establishment of plasma surface treatments that offer a unified, repeatable, cost-effective and environmentally benign replacement.

The authors are sure that this technology will be adopted by the polymer industry, aerospace, automotive and related sectors in the future.

The relationship between ethnicity, religion and entrepreneurship is an emerging field, and an extremely important topic, considering the influence of these drivers on people’s lives and on entrepreneurs’ performance, in particular. This study aims to explore and contribute to a more robust understanding of this relationship.

The main trends were disclosed using Preferred Reporting Items for Systematic Reviews and Meta-Analysis and VOSviewer. The set of articles cover the annual period from 1973 to 2022. The coupling analysis founded links to produce a framework outlining an integrative state of the art intersecting ethnicity and religion and entrepreneurship spectrum study.

The analysis identified integrative relationships between the concepts of ethnicity, religion and entrepreneurship, which describe the direction of literature, resulting in five main categories.

This study offers a novel framework and in-depth understanding to delve into this interrelationship research agenda. Guided by the gaps in the literature, a set of outstanding avenues for future research are proposed.

This study aims to estimate the impact of refugee inflows on host countries’ entrepreneurial rates. The refugee crisis led to an increased scientific and public policy interest in the impact of refugee inflows on host countries. One important perspective of such an impact, which is still underexplored, is the impact of refugee inflows on host countries entrepreneurial rates. Given the high number of refugees that flow to some countries, it would be valuable to assess the extent to which such countries are likely to reap the benefits from increasing refugee inflows in terms of (native and non-native) entrepreneurial talent enhancement.

Resorting to dynamic (two-step system generalized method of moments) panel data estimations, based on 186 countries over the period between 2000 and 2019, this study estimates the impact of refugee inflows on host countries’ entrepreneurial rates, measured by the total early-stage entrepreneurial activity (TEA) rate and the self-employment rate.

In general, higher refugee inflows are associated with lower host countries’ TEA rates. However, refugee inflows significantly foster self-employment rates of “medium-high” and “high” income host countries and host countries located in Africa. These results suggest that refugee inflows tend to enhance “necessity” related new ventures and/ or new ventures (from native and non-native population) operating in low value-added, low profit sectors.

This study constitutes a novel empirical contribution by providing a macroeconomic, quantitative assessment of the impact of refugee from distinct nationalities on a diverse set of host countries' entrepreneurship rates in the past two decades resorting to dynamic panel data models, which enable to address the heterogeneity of the countries and deal with the endogeneity of the variables of the model.

This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

This study aims to fill various gaps detected in the literature on mass prestige (hereafter referred to as masstige) theory. The originality of the work stems from the multidimensional application of Paul’s (2015) model, the introduction of brand addiction as a construct from the consumer-brand relationship (CBR) theory within the context of wines and the exploration of a new and less studied sector in masstige strategies.

A structured questionnaire was distributed to collect data from masstige wine brand buyers in Portugal, of whom 166 completed the questionnaire correctly. A conceptual model was developed and tested using partial least squares structural equation modelling.

The findings include that only two dimensions of Paul’s (2015) masstige scale affect brand addiction: brand knowledge and excitement and status. Brand addiction has a positive effect on brand loyalty and electronic word of mouth (eWOM), and brand loyalty has a positive impact on eWOM. Theoretical and managerial implications were explored.

This research added a CBR perspective to masstige theory and applied masstige theory to wine brands for the first time. These three distinctive aspects collectively contribute to the novelty and significance of the research, opening up exciting possibilities for future investigations and providing a valuable contribution to the academic community and the wine industry alike.

The study aims to investigate the effect of corruption and crime on the investments by firms in emerging economies (EEs).

The study adopts the generalised methods of moments (GMM) estimator and data across 57 EEs.

The study shows that crime management, corruption and external quality assurance drive-up investments. Additionally, investments decline with firm age and crime incidence. Corruption and crime managements increase investments by exporting firms more than non-exporting firms investments. Also, external auditor services benefit investments by large firms more than small-medium firms.

There is a need for EEs to implement policies that will curtail corruption and create a level playing field and sustainable firm growth. EEs firms must be innovative to expand their productive investments and grow over time. Also, EEs firms should seek external quality certification, invest in internal security and monitor goods in transit.

In the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.

Employing the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.

Relevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.

Within the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

The purpose of this paper is to evaluate the perceptions of young agricultural entrepreneurs (agripreneurs, as a neologism, from now on), to understand what they consider as determinants in achieving entrepreneurial success in accordance with their type of farming.

This study uses primary data collected through a questionnaire, among 222 young agripreneurs who are active in lowland, semi-mountainous and mountainous regions of western Greece.

The approach used provided a clear evidence that perceived characteristics, such as internal funding and level of education/training, have a significant relationship with the perception of young agripreneurs’ success (YAS). Also, the perception of young agripreneurs for success varies by the type of farming. Crop production agripreneurs have a significantly higher need for participation in Producer Groups than in livestock production ones. Alternatively, gender, presents a significant relationship only with livestock production agripreneurs’ success.

The results of this study could help to design appropriate policy instruments and at the same time, promote and foster entrepreneurship on the one hand and provide suggestions for young agripreneurs to create sustainable new ventures on the other hand.

This study is original and valuable in the sense that provides the practical implications for understanding the entrepreneurial success and sustainability in a very critical segment of the agricultural sector.

Strategic management plays a pivotal role in the growth and success of organizations, significantly impacting their business performance and competitive edge. In today’s globalized markets, strategic management is gaining prominence as a means to enhance company performance and distinctiveness. Within this landscape, the evaluation of organizational effectiveness takes on heightened significance, complemented by the emergence of strategic management frameworks designed to secure enduring competitive advantages for businesses.

One of the best known approaches to organizational resource assessment is the value, rarity, inimitability and organizational-oriented (VRIO) framework. However, this tool comes with inherent limitations that have hindered its advancement, primarily related to the need for less subjective means of identifying and assigning weights to resources and capabilities during the evaluation process. This study, therefore, endeavored to refine the VRIO framework, making it more transparent and empirically robust. To achieve this aim, the framework was combined with the decision-making trial and evaluation laboratory (DEMATEL) method (i.e. a multiple criteria decision analysis (MCDA) method), and a real-life application was conducted.

The evaluation system created was tested, and the results demonstrate that the dual methodology used can increase the understanding of resource appraisal and lead to more informed and potentially better evaluations of resources and capabilities. The strengths and shortcomings of this new structured evaluation model are also analyzed.

The authors know of no prior work reporting the integrated use of VRIO and DEMATEL in this study context.