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This study aims to analyze the moderating roles of familiarity, generation and gender on the impacts of coronavirus fear-uncertainty on the destination image and visiting intentions post-COVID-19.

This paper seeks to provide evidence for a research conclusion by conducting a survey of 431 potential travelers of various nationalities who visited Egypt. The data were examined using structural equation modeling with a multigroup analysis and PROCESS MACRO.

The findings indicated that the links between coronavirus fear-uncertainty, the destination image and intention to visit were significantly different from one gender and generation group to another. Moreover, it showed that destination familiarity moderates the negative effects of coronavirus fear-uncertainty on the destination image and intention to visit.

To the best of the authors’ knowledge, this paper is the first to explore the moderating role of destination familiarity, generation and gender in the effects post-COVID-19 of coronavirus fear-uncertainty on the destination image and travelers’ intention to visit using generational cohort theory and gender schema theory.

The main purposes of this article are twofold: (1) to investigate the unexplored connections among destination gender personality, destination stereotypes, brand attachment and destination brand love and (2) to examine the moderating role of destination involvement in the association between destination stereotypes and destination brand attachment (DBA).

The conceptual model is evaluated using qualitative methods (i.e. three focus groups, six academic experts and a pilot study). In addition, using an empirical study with 610 international travelers who visited Egypt selected by systematic random sampling, 8 hypotheses were analyzed and tested using structural equation modeling (SEM) by AMOS 23, confirmatory factor analyses and exploratory factor analyses.

The study’s results suggest that destination gender plays a vital role in enhancing stereotypes, stereotypes positively affect attachment and DBA positively affects destination brand love. Finally, the results show that destination involvement moderates the dual influence of the warmth and competence of stereotypes on destination attachment.

The research supports the contention that social perception mechanisms are crucial in destination brand perception. It offers new understandings of the association between customers' destination brand perceptions and their responses to destinations.

This paper contributes to the travel literature by analyzing a novel model of destination gender personality, stereotypes, DBA and destination brand love using both social role (SR) theory and a stereotype content model (SCM). Besides attempting this task, it explores the moderating role of destination involvement in the association between stereotypes and destination attachment using the elaboration likelihood model.

This paper aims to investigate the underlying mechanisms that come into play in the relationship between technology orientation (TO) and performance in technology firms. In doing so, this paper explores how different levels of TO affect firm innovativeness, how different levels of firm innovativeness affect performance and the moderating role of risk-taking propensity in the relationship between innovativeness and performance.

Data were collected from 112 information technology firms. Control variables include firm size and age and industry effects. The model was tested using PLS-based SEM.

Results show that in technology firms, innovativeness plays a mediating role in the relationship between TO and firm performance, the relationship between TO and firm innovativeness is curvilinear, the relationship between innovativeness and performance is curvilinear and risk-taking propensity moderates the curvilinear relationship between innovativeness and performance.

The shape of the relationships in the mediating paths between TO, innovativeness and performance, is curvilinear (inverted U-shaped). Managers in technology firms focused on bolstering the TO and/or innovativeness should be cognizant of the fact that beyond a certain level, they might actually be doing more harm than good. Additionally, managers seeking to reinforce the relationship between innovativeness and performance need to be sensitive to the role that risk-taking propensity plays in this relationship.

This paper aims to identify and explain the link between relational dynamics and the development of coordination capabilities of Fourth-Party Logistics Providers (4PL) within a supply chain (SC). We aim to demonstrate the critical role relational dynamics can play in converting trust from interpersonal to inter-organizational level and facilitate the improvement of capabilities to coordinate customer's SC activities.

Using semi-structured interviews with 78 logistics managers operating in 45 different logistics service providers located in France, we developed a set of propositions and built a conceptual framework. Exploratory qualitative research in the form of propositional discourse analysis (PDA) is used to develop propositions in our research to contribute to theory in supply chain management (SCM).

Results indicate that both interpersonal and inter-organizational trust is a convertible capital. Based on their dynamic interactions, these two levels of trust endow the supply chain partners with economic benefits that would otherwise be highly costly or even practically extremely difficult to achieve through complex socio-economic transactions (meso-social level).

Future research may test our conceptual model using primary and secondary data and conduct longitudinal case studies that are necessary to triangulate our results and thus strengthen our conclusions. The prospect of adding control variables to our model would be of considerable importance.

Our results suggest that “4PL” need to invest more in interpersonal relations to facilitate collaboration with their clients and enhance their capability to coordinate and manage customer's supply chain activities. The ability to convert interpersonal trust represents an invaluable capital contributing to the achievement of above-normal profits.

This work contributes to a better understanding of the coordination of supply chain activities through the development, mobilization and maintenance of social capital. While previous research explained the importance of trust in SCM, this paper explores and studies the process of converting interpersonal trust into social capital mobilized at the supply chain level. We add to the existing literature on structural and relational dimensions of social capital by offering a process-based explanation of the conversion of interpersonal trust into inter-organizational trust and its role in facilitating collaboration in logistics services.

This study's goal is to look at how visitors' experiences affect the indirect links between the destination's extrinsic motivations (DEMs) and tourists' intrinsic motives (TIMs), on the one hand, and the perceived destination image (PDI), on the other.

Using structural equation modeling, 613 tourists from different nationalities were used to test the five hypotheses.

The research results revealed that second-order destinations' extrinsic motivations directly impact TIM and PDI. It also showed that tourists' experiences as moderators reduce the direct effect of DEM on PDI for first-time visitors compared to repeat visitors. Moreover, it increases the direct effect of TIM on PDI for repeated visitors.

Destination managers can fix the problems that hurt their reputations and images by hiring police officers in tourist areas and cleaning tourist places. In the same way, destination managers and travel agencies should use AI tools to create social media marketing campaigns focusing on natural and historical monuments. Also, the marketing plans should stress the value for money (for example, lodging, food and attractions’ cost). Finally, destination marketers can make programs for repeat visitors, focusing on DEM and TIM.

This article tries to fill a gap in the research on PDI formation in emerging markets as a modern technique in destination marketing by using the push-intrinsic and pull-extrinsic theories. It also looks at how the tourists' experiences moderate the direct link between DEM, TIM and PDI. Lastly, this study examines how TIM affects a destination's image in emerging markets.

This paper aims to elaborate on current research on fourth party logistics “4PL” by offering a taxonomy that provides a deeper understanding of 4PL service offerings, thus drawing clear frontiers between existing 4PL business models.

The authors collected data using semi-structured interviews conducted with 60 logistics executives working in 44 “4PL” providers located in France. Using automatic analysis of textual data, the authors combined spatial visualisation, clustering analysis and hierarchical descending classification to generate the taxonomy.

Two key dimensions emerged, allowing the authors to clearly identify and distinguish four 4PL business models: the level of reliance on interpersonal relationships and the level of involvement in 4PL service offering. As a result, 4PL providers fall under one of the following business models in the taxonomy: (1) The Metronome, (2) The Architect, (3) The Nostalgic and (4) The Minimalist.

The study focuses on investigating 4PL providers located in France; thus, future studies should explore the classification of 4PL business models across different cultural contexts and social structures.

The findings offer valuable managerial insights for logistics executives and clients of 4PL to better orient their needs, the negotiations and the contracting process with 4PLs.

Using a Lexicometric analysis, the authors develop taxonomy of 4PL service providers based on empirical evidence from logistics executives; the work addresses the existing confusion regarding the conceptualisation of 4PL firms with other types of logistical providers and the role of in/formal interpersonal relationships in the logistical intermediation.

The purpose of this paper is to illustrate some methods to protect digital libraries using digital rights management (DRM) technologies and specifically the methods applied at the digital libraries of Jordan universities.

A descriptive research method has been used to examine the extent of DRM in digital libraries of universities in Jordan.

Majority of the universities in Jordan use different methods of protection including coding, identification, authenticity and digital watermark. However, methods including digital signature, digital fingerprint, copy detection systems and pay system have not been employed within Jordanian universities. The use of copyright management systems has been limited, which shows the weakness in the use of technological protection within the investigated libraries.

This study has shown contribution to the development of digital libraries that are based on the protection of new technology and are able to provide better services to users without concern about protecting publishers’ rights.

The purpose of this study is to address the impact of the related party transactions (RPTs) on firm value. The authors bring evidence from a usually ignored empirical setting: an African emerging market.

In particular, the authors focus on companies listed on the Egyptian stock market using a sample of EGX 30 from 2012 to 2017.

Unlike the literature, the authors find no significant relationship between RPTs and market value.

This research provides insights for policymakers and other interested parties concerning the perception of RPTs in Egypt.

The reported different findings of this study assure the intermediary role of the context and the local culture in the relationship between RPTs and firm value, in contrast to the negative view that is mostly reported in the literature.

Optimisation of grinding processes involves enhancing the surface quality and reducing the cost of manufacturing through reduction of power consumptions. Recent research works have indicated the minimum quantity lubrication (MQL) system is used to achieve near dry machining of alloys and hard materials. This study aims to provide an experimental analysis of the grinding process during machining of aluminium alloy (Al6061-T6). MQL nanofluid was used as the lubricant for the grinding operations. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality was studied. Adaptive neuro-fuzzy inference system (ANFIS) prediction modelling was used to predict the specific normal force, specific tangential force and surface quality, the ANFIS models were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further study shows that both the specific grinding forces and surface roughness are inversely proportional to the nanofluid concentration. Also, the depth of cut and table feed rate were found to have a directly proportional relationship with both the grinding forces and surface roughness. Moreover, higher MQL air pressure was found to offer better delivery of the atomised nanofluid into the grinding region.

Grinding experiments were performed using MQL nanofluid as the lubricant. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality has been studied.

The grinding process parameters were optimised using Taguchi S/N ratio analysis, whereas the prediction of the response parameters was done using ANFIS modelling technique. The developed ANFIS models for predicting the specific normal force, specific tangential force and surface quality were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further findings show that both the specific grinding forces and surface roughness are inversely proportional to the percentage of nanoparticle concentration in the lubricant. Also, the depth of cut and table feed rate were found to exhibit a direct proportional relationship with both the grinding forces and surface roughness, while high MQL air pressure was observed to offer more efficient delivery of the atomised nanofluid into the grinding region.

The work can applied into manufacturing industries to prevent unnecessary trials and material wastages.

The purpose of this study is to develop an artificial intelligent model for predicting the outcomes of MQL grinding of the aluminium alloy material using ANFIS modelling technique.

This study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.

This research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.

The result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.

These results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.