Search results

Given the challenging economic conditions and unstable employment situation in developing countries like Iran, sustainable development has become a primary focus. With coastlines along both the north and south, the growth and development of coastal and marine tourism could provide a solid foundation for generating stable and continuous income streams. This research investigates the factors that facilitate and hinder communication between local communities and key stakeholders in the development of coastal tourism.

The research community comprised local communities, tourists, and government officials involved in tourism processes. Participants were selected based on specific criteria through targeted sampling, resulting in a total of 17 samples. The primary research tool utilized was semi-structured interviews. Interview questions were developed within the frameworks of two theories: social exchange and social network theory. Data analysis was conducted using thematic analysis methods.

The results indicated that all the promoting and inhibiting factors can be categorized into four themes: economic, socio-cultural, environmental, and institutional governance. According to the analyzed data, the inhibiting factors in the environmental sector significantly outnumber the driving factors. In contrast, in the other sectors, the gap between the driving and inhibiting factors is smaller.

This research provides a novel perspective on advancing green evangelism. By strengthening emotional connections with the brand, green evangelism lays the groundwork for developing green respect and green credibility. This approach, which focuses on enhancing emotional bonds with the brand, contributes to the expansion of the green brands in developing countries. Therefore, instead of direct advertising for green brands, the focus should be on attracting key customers to form a community dedicated to the green brand.

This paper investigates the role of nexus supplier transparency, which involves the collective information disclosure to the public by second-tier nexus suppliers, as an alternative mechanism for mitigating buyer environmental, social and governance (ESG) risk exposure. We also examine buyer supply network accessibility as a moderating factor that facilitates collecting detailed information and undertaking corrective actions accordingly.

We collected a sample of 428 focal buyer firms and their supply networks up to third-tier suppliers. Data were obtained from Bloomberg and RepRisk databases. We identified critical nexus suppliers using data envelopment analysis (DEA) and tested hypotheses using regression analysis.

The results show that the benefits of nexus supplier transparency, such as reducing buyer ESG risk exposure, differ depending on the type of nexus supplier disclosing information and buyer supply network accessibility. Informational nexus supplier transparency was found to be beneficial. However, the results revealed the double-edged sword of monopolistic nexus supplier transparency, which benefits buyers with higher levels of accessibility but increases risk exposure for buyers with lower accessibility.

This study demonstrates that the transparency of critical second-tier suppliers mitigates buyer ESG risk exposure by providing information about lower tiers in the supply network. Challenging the notion of the focal buyer as the main orchestrator of supply chain initiatives, our alternative perspective opens a new avenue for risk management in multi-tier supply chains.

The main purpose of this paper is given below: To present a mathematical model of a two-phase Stefan problem including a moving phase change material and variable thermophysical properties. To find a numerical solution of the problem to discuss the dependence of considered phase change problem on variable thermal conductivity, variable specific heat and Peclet number.

In this paper, a numerical solution of the problem is obtained using the front-fixing method in tandem with the explicit finite difference scheme. The authors have also discussed the consistency and stability of proposed numerical scheme.

In this study, it is observed that the considered scheme is an efficient tool that provides sufficiently accurate results for exploring the behaviors of moving interface (free boundary) and temperature profile for a nonclassical two-phase free boundary problem. In this study, the authors have observed that the parameters α1 and α2 influence the temperature profiles of the liquid region and the solid region. It is also found that the free boundary propagates faster when the authors increase the parameter α1 or decrease the parameter α2.

From the literature, it is seen that most of the two-phase problems with free boundary in an infinite domain are considered by the authors with constant thermophysical properties. Because it is possible to establish an analytical solution of two-phase problems with free boundary in case of an infinite domain. Moreover, a two-phase problem in a finite domain involving moving phase change material with the unidirectional speed is not considered. Therefore, the authors have considered a two-phase free boundary problem with variable thermal coefficients.

This paper aims to investigate the reliable thickness, and more generally, the geometric and material parameter determination of thin electrically conductive and diamagnetic coatings on conductive and ferromagnetic substrates, e.g. steel, using eddy current testing (ECT).

The analytical model of an ECT coil arrangement known from the literature is analyzed to evaluate the numerical simulation performed by a Finite Element (FE) program. The latter is used to investigate the influence of the sheet edge on the measurement result. Finally, a measurement setup is presented and the unknown geometric and material parameters are estimated from measurement data of different sample sheets at different air gaps.

Generally, valid mesh rules are found for a very accurate FE analysis of eddy current problems with large air gaps. The influence of large air gaps on the parameter estimation is emphasized. Moreover, the formulated hypotheses can be widely confirmed by measurements.

In this paper, electrical steel sheets coated with a conductive oven-cured ink are used. This sample configuration creates a discrete transition between the substrate and the coating as present in the analytical modeling approaches. Furthermore, the ferromagnetic substrate’s nonlinear B-H curve is not considered in the analytical model so far.

The analytical model is known from the literature. However, real practical measurements have not been carried out with the discussed setup. Furthermore, well-known literature on eddy current measurements usually only considers constant and very small air gaps.

This paper aims to examine the responses of cryptocurrency markets to the U.S. Securities and Exchange Commission’s (SEC) announcement on June 5, 2023, concerning the charges against Binance. This paper investigates the intraday market reactions and volatilities of a set of cryptocurrencies (Bitcoin, Ethereum, Ripple, Cardano and Litecoin) to this announcement as an event and explore if these reactions are consistent with the prediction of overreaction hypothesis or uncertain information hypothesis.

Considering the day when the SEC filed the lawsuit against Binance as an unexpected event, we classify the price movements of a set of cryptos on the event day as either unexpected favorable news or unexpected unfavorable events. We examine whether the behavior of the prices of the crypto is consistent with the predictions of the overreaction hypothesis (OH) proposed by De Bondt and Thaler (1985) or the uncertain information hypothesis (UIH) suggested by Brown et al. (1988).

The results suggest that the cryptocurrency markets faced a return volatility surge, no matter if investors regarded this event as favorable or unfavorable, and the markets’ responses are mixed. The results of supremum augmented Dickey−Fuller (SADF) and generalized SADF (GSADF) do not support the bubble behavior in selected cryptocurrency series.

The essential implication is that the action of the SEC had an evident impact on the volatility of cryptocurrency markets. This consequence should be seriously considered, as the role of the SEC in regulating the digital asset markets becomes more critical following the approval of the Bitcoin ETFs, early 2024.

To the best of the authors’ knowledge, this is the first paper investigating the cryptocurrencies’ markets reactions to the SEC lawsuit against Binance. It sheds light to the market reactions using intraday data.

The study aims to explore how Soret and Dufour diffusions, thermal radiation, joule heating and magnetohydrodynamics (MHD) affect the flow of hybrid nanofluid (Al₂O₃-SiO₂/water) over a porous medium using a mobile slender needle.

To streamline the analysis, the authors apply appropriate transformations to change the governing model of partial differential equations into a group of ordinary differential equations. Following this, the authors analyze the transformed equations using the homotopy analysis method within Mathematica software, leading to the derivation of analytical solutions. This study investigates how changing values for porous medium, MHD, Soret and Dufour numbers and thermal radiation influence concentration, temperature and velocity profiles. In addition, the research assesses the effects on local Sherwood number, skin friction and Nusselt number.

In this investigation, the authors explore the movement of a needle away from its origin ( ε > 0). As the magnetic and porous medium parameters increase, there is a correspondence decrease in the velocity profile. Simultaneously, an increase in the Dufour number and thermal radiation parameter yields to a higher temperature profile, whereas arise in the Soret number results in an enhanced concentration profile. Furthermore, growth in the magnetic field parameter is correlated with a reduction in skin friction, Nusselt and Sherwood numbers. In addition, an examination of the data reveals that an escalation in the thermal radiation parameter is associated with an elevation in the Nusselt number. Moreover, an elevation in the Dufour number results in an augmentation in the Nusselt number.

These results have practical applications across diverse fields, including heat transfer enhancement, energy conversion systems, advanced manufacturing and material processing.

This study is distinctive in its investigation of the flow of hybrid nanofluid (Al₂O₃-SiO₂/water) over a slender, moving needle. The analysis includes joule heating, MHD, porous medium, thermal radiation and considering the effects of Soret and Dufour.

This study investigates the potential of low-income countries to mitigate technological lock-ins by exploiting windows of opportunity (WOOs). Given their inherent inclination toward path dependency, these countries often face challenges in diversifying beyond their established technological trajectories. We examine the pivotal role of adopting shorter cycle times of technologies (CTTs) in opening technological WOO, triggering unrelated diversification and accelerating technological catch-up.

Using fixed-effect regression models, we analyze country-level patent data within the neurotechnology domain from 1995 to 2021 – a period marked by significant technological change since 2010. Our focus lies in comparing diversification and catch-up trends between low-income and high-income countries, while evaluating the performance of CTT.

Our findings reveal that as low-income countries increase their knowledge complexity (KC), they tend to be locked into existing technological paths. To mitigate lock-in risks, they can strategically adopt technologies with shorter CTTs. These technologies act as catalysts, opening up technological WOOs and stimulating unrelated diversification. KC presents a double-edged sword in the catch-up process, but unrelated diversification can eliminate this dilemma.

Our study introduces the KC-CTT framework, proposing practical strategies to enhance and sustain countries’ competitive advantages.

Diversification and catch-up emerge from two separate bodies of literature but present a conceptual overlap. This research bridges the gap between the two literatures by investigating the impact of CTT as their predictor variable.

We aim to compare multifunctionality, ecosystem services and just transition as overall conceptual approaches to understand agri-food systems.

This is a theory-motivated literature study.

This paper argues that the concepts of multifunctionality and ecosystem services are unsuitable for considering the systemic complexities of today’s food system in order to tackle its grave environmental and social problems. Furthermore, these two concepts tend to neglect the negative externalities of food systems and overemphasize the positive ones. The notion of just transition puts justice and sustainability at the center of agri-food studies and defines targeted systemic interventions in food systems.

While the approach of just transition is only starting to be widely applied to the agriculture–food nexus, we argue that it is better suited to re-orient diets, production processes, the value chain and labor conditions in a more sustainable direction. The just transition approach is also useful in drafting systemic policy innovations.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0740

This paper aims to clarify how organizations manage their participation in networks to share and jointly create knowledge but also risk unwanted knowledge spillovers at the same time. As formal governance, trust and observation are less applicable in informal networks, the authors need to understand how members address the need to protect knowledge by informal practices. The study aims to investigate how the application of knowledge protection practices affects knowledge sharing in networks. The insights are relevant for organizational and network management to control knowledge risks but harvest the benefits of network engagement.

The authors opted for an exploratory study based on 60 semi-structured interviews with members of 10 networks. In two rounds, network managers, representatives and members of the networks were interviewed. The second round of interviews was used to validate the intermediate findings. The data were complemented by documentary analysis, including network descriptions.

Through analyzing and building on the theory of psychological contracts, two informal practices of knowledge protection were found in networks of organizations: exclude crucial topics and share on selected topics and exclude details and share a selected level of detail. The authors explored how these two practices are enacted in networks of organizations with psychological contracts.

Counter to intuition that the protection of knowledge can be strengthened only at the expense of knowledge sharing and vice versa, networks benefitted from more focused and increased knowledge sharing while reducing the risk of losing competitive knowledge by performing these knowledge protection practices.

This study aims to develop a neurocomputational approach using the Levenberg–Marquardt artificial neural network (LM-ANN) to analyze flow and heat transfer characteristics in mixed convection involving radiative magnetohydrodynamic hybrid nanofluids. The focus is on the influence of morphological nanolayers at the fluid–nanoparticle interface, which significantly impacts coupled heat and mass transfer processes.

This research simplifies a complex system of higher-order nonlinear coupled partial differential equations governing the flow between orthogonal coaxially porous disks into ordinary differential equations via similarity transformations. These equations are solved using the shooting method, and parametric studies are conducted to observe the impact of varying important parameters. The resulting data sets are used to train, validate and test the LM-ANN model, which ensures high predictive accuracy. Machine learning and curve-fitting techniques further enhance the model’s capability to generate detailed visualizations.

The findings of this study indicate that increased nanolayer thickness (0.4–1.6) significantly improves thermal performance, while changes in the chemical reaction parameter (0.2–1) have a notable effect on enhancing the Sherwood number. These results highlight the critical role of morphological nanolayers in optimizing thermal and mass transfer efficiency in MHD nanofluids.

This research provides a novel neurocomputational framework for understanding the thermal and mass transfer dynamics in MHD nanofluids by incorporating the effects of interfacial nanolayers, an aspect often overlooked in conventional studies. The use of LM-ANN trained on computational data sets enables high-fidelity predictive analysis, offering new insights into the enhancement of thermal and mass transfer efficiency in hybrid nanofluid systems.