Profit always be the top priority of banking operation over the years. Commercial banks maximize the net interest margin by charging more interests to the borrowers and offering lower interests to the depositors. Their aggressive lending strategies can sometimes result in credit risk, moral hazard and non-performing loans. Some studies found that non-performing loans have negative impact on the bank’s profitability; some argued otherwise. This paper aims at investigating the impact of non-performing loans on the ability to make profit of Vietnamese commercial banks in the period of 2008 to 2017 and draws a conclusion as well as recommendations to mitigate the risk.

The optimum selection of process parameters has played an important role for improving the surface finish, minimizing tool wear, increasing material removal rate and reducing machining time of any machining process. In this paper, optimum parameters while machining AISI D2 hardened steel using solid carbide TiAlN coated end mill has been investigated. For optimization of process parameters along with multiple quality characteristics, principal components analysis method has been adopted in this work. The confirmation experiments have revealed that to improve performance of cutting; principal components analysis method would be a useful tool.

This paper proposes a method to quote the due date and the price of incoming orders to multiple customers simultaneously when the contingent orders exist. The proposed method utilizes probabilistic information on contingent orders and incorporates some negotiation theories to generate quotations. Rather than improving the acceptance probability of quotation for single customer, the method improves the overall acceptance probability of quotations being submitted to the multiple customers. This helps increase the total expected contribution of company and acceptance probability of entire new orders rather than increasing these measures only for a single customer. Numerical analysis is conducted to demonstrate the working mechanism of proposed method and its effectiveness in contrast to sequential method of quotation.

In the existing literature, there are a huge number of studies focused on p-hub median problems and inventing heuristic or metaheuristic algorithms for solving them. But such analogous body of literature does not exist for its counterpart problem; p-hub center problem. In fact, since p-hub center has been lately introduced and has a particular objective function, minimizing the maximum cost between origin-destination nodes, there are few studies investigating the problem and the challenges for solving it. In this study, after presenting a complete definition of the uncapacitated multiple allocation p-hub center problem (UMApHCP) two well-known metaheuristic algorithms are proposed to solve the problem for small scale and large scale standard data sets. These two algorithms are one single solution-based algorithm, Simulated Annealing (SA), and one population-based metaheuristic, Genetic Algorithm (GA). Because of the particular nature of the problem, Dijkstra’s algorithm has been incorporated in the fitness function calculation part of the proposed methods. The numerical results of running the GA and SA for standard test problems show that for smaller scale test problems, single solution-based SA shows greater performance versus GA but for larger scales of data sets the GA generally yield more desirable solutions.

The present paper studies the reliability analysis of the casting process in foundry work using a probabilistic approach. As foundry industries in many developing countries suffer from poor quality of casting due to improper management, lack of resources and wrong working methods followed, which results in the decrement of productivity. Hence, to ensure the quality and productivity, favorable steps must be taken. The considered casting system has four main types of defects; namely mold shift, shrinkage, cold shut and blowholes. The complete casting system can fail due to the misalignment of the mold and combination of defects such as shrinkage and blow holes and can also fail by defects of shrinkage, blow holes and cold shut, simultaneously. The system is analyzed with the help of the supplementary variable technique and Laplace transformation. The availability, reliability, mean time to failure, sensitivity analysis and cost-effectiveness have been evaluated for the considered system. The results have been shown with the help of graphs, which predicts the behavior of the casting process system when any one of the defect or more than one defect appears.

The purpose of the current paper is to identify influential aspects of published literature and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis. The study analyzed 1225 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis. The analysis revealed that most of the information was derived from the Finance Research Letters. Moreover, the United Kingdom is the most cited country, while Tianjin University in China has the highest publications affiliations. Furthermore, the analysis shows that the keyword analysis of cryptocurrency literature had four classes of research streams in cryptocurrency, namely, cryptocurrency, Blockchain, Fintech, and currency, representing the most upcoming trends. The present study makes a significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among some identified research streams as future research agenda.

The brisk spread of Covid-19 led educational policymakers and organizations to opt for better alternatives to resume the students' educational journey. In this context, Microsoft Teams remained one of the most devoted and credible online platforms that greatly facilitated the educational process across the globe. Current research also analyzed Microsoft Teams acceptance using the self-proposed conceptual model supported by the Technology Acceptance Model by Davis. We employed the survey method and examined the gathered using the applied Structural Equation Modelling (SEM). Results indicated that there is a significant impact of Covid-19 on the Perceived Ease of Use (p> 0.000) and Perceived Usefulness (p> 0.000). Besides, the relationship between Perceived Ease of Use and Perceived Usefulness also remained significant (p> 0.000). Moreover, the proposed relationship between Attitude, Perceived Ease of Use, and Perceived Usefulness also remained substantial (p> 0.009 and p> 0.000). However, the relationship between Attitude and Behavioral Intention remained insignificant (p> 0.556). Finally, the relationship between Behavioral Intention and Microsoft Teams Acceptance remained significant (p> 0.088). Thus, we concluded that Microsoft Teams is an effective study tool that unites students and instructors in the United Arab Emirates. It governs eLearning experiences and, therefore, provides a virtual environment to students and directly influences our perceptions and behavior.

This paper empirically identifies the predictors influencing the use of promo code in Jordan. This research extended TAM and TBP models with perceived enjoyment and brand image in the context of digital shopping features. The study utilized 379 surveys distributed in Jordan and analyzed the data using SEM. Findings of this study confirmed the proposed model, where brand image, perceived enjoyment, perceived behavior control and social influence significantly predict customers behavioral intention to use promo code with an R2 = 59%. The model of this study also supported the role of perceived ease of use and social influence in predicting brand image. Discussion and conclusion are depicted at the end of this paper.

This paper focuses on five-star hotels in Jordan to investigate the impact of influencer marketing on overall brand equity. The mediating role played by brand awareness and customer brand engagement between influencer marketing and overall brand equity is tested. The survey method is employed to conduct this research, and data is collected from 300 respondents. The proposed hypotheses are tested using structural equation modeling. The results indicate that influencer marketing directly influenced overall brand equity, brand awareness and customer brand engagement partially mediate the relationship between influencer marketing and overall brand equity.

In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected users follows a logarithmic function. Our study examines the Indonesian Twitter data users with tweets about covid19 vaccination resulted in dynamic influencer rankings over time. From these results, it can also be seen that the users with the highest number of followers are not necessarily the top influencer.