Covid-19 has been causing a large-scale pandemic, along with the rapid development of information technology. Information technology means such as digital applications will be one of the effective tools to help manage public investment and investment in general in Vietnam. Public investment management at autonomous universities in Vietnam is in the final stage of completion in terms of procedures, legal documents, and implementation. This study was designed to shed light on the factors that affect the management of public investments at Vietnamese autonomous universities. The study's data was gathered from a survey of 126 public investment managers at autonomous universities in Vietnam. Factor analysis and multivariate regression methods were used to analyze the influence of factors on public investment management at autonomous universities in Vietnam. According to research findings, the capacity of public investment management agencies at autonomous universities; Distribution of funds for the implementation of public investment projects; administrative procedures, legal provisions, and the actual context affect public investment management at autonomous universities in Vietnam. With Standardized Coefficients = 0.482, distribution of funds for implementation of public investment projects at schools at autonomous universities were the most influential factors. The research results are the foundation for proposing solutions to improve the efficiency of public investment management at these universities in Vietnam such as promulgating legal documents, building public investment management processes suitable to the characteristics of universities, developing, and proactively implementing works in investment management and operating results of public investment in autonomous University.

In the present work, a multi-response optimization method is used to optimize the machining parameters in turning of glass fiber reinforced polymer (GFRP) composites. Parameters like spindle speed (N), feed rate (f) and depth of cut (d) are taken to obtain the responses such as surface roughness (Ra) and material removal rate (MRR). Taguchi’s L9 orthogonal array has been used for machining the work-piece. Analysis of variance (ANOVA) has been carried out to check the significant process parameter in a single objective performance characteristic. The multiple performance characteristics have been analysed using Grey relational analysis and an appreciable result has been reported with this approach.

Increasingly, e-skills are required to enable effective use of digital technologies. The present paper examines the influence of e-skills on use of e-services in the hospitality industry. We employ a conditional mixed-process approach and the results of a residential survey in Kosovo to investigate whether e-skills boost e-services in hospitality. Our findings suggest that e-skills are important to explain different behaviors related to use of e-services. The facilitating conditions, expected performance, social influences and perceived value of the services have a positive impact while perceived risks to privacy have a negative impact on behavioral intention. We also find that gender and income have a positive effect on both behavioral use and behavioral intention while age has no effect on either dimension.

In this paper, a robust bi-level model is proposed to optimize decisions related to distribution and evacuation aid after earthquake. Usually in disastrous situation foreign countries help the affected country by sending relief commodities. In this problem, the foreign countries try to minimize their shipping costs and the affected country seeks to minimize its total costs which include inventory, operation, and transportation expenses. This situation is a game between different decision makers after a catastrophic disaster. To deal with this situation, a bi-level model is proposed in which the affected country is the leader and suppliers are the followers. To validate the proposed robust model, we consider Tehran probable earthquake in region 1 as a case study. Then the advantages of using bi-level modeling against considering just one player's point of view is provided. The sensitivity analysis of the experiments are presented to explore the effects of various parameters to show managerial insights that can guide DMs under a variety of conditions.

The objective of this paper is to develop an integrated production inventory model for reworkable items with exponential demand rate. This is a three-layer supply chain model with perspectives of supplier, producer and retailer. Supplier delivers raw material to the producer and finished goods to the retailer. We consider perfect and imperfect quality products, product reliability and reworking of imperfect items. After screening, defective items reworked at a cost just after the regular manufacturing schedule. At the beginning, the manufacturing system starts produce perfect items, after some time the manufacturing system can undergo into “out-of-control” situation from “in-control” situation, which is controlled by reverse logistic technique. This paper deliberates the effects of business strategies like optimum order size of raw material, exponential demand rate, production rate is demand dependent, idle times and reverse logistics for an integrated marketing system. Mathematica is used to develop the optimal solution of production rate and raw material order for maximum expected average profit. A numerical example and sensitivity analysis is illustrated to validate the model.

Mass media is a crucial advertising platform and serves as an awareness platform for herbal product businesses. The rising popularity of herbal product consumption is due to the changing of lifestyle and health problems. With the increasing demand for herbal products globally, studies related to the herbal products purchase behaviour are considered very limited. Hence, the current study is written to investigate the structural relationship of mass media on attitude, social influence, product safety and its impact on purchase behaviour of Herbal products in Malaysia. By applying the Attitude-Behaviour Context Theory, this study used several variables, namely mass media toward attitude, social influence, and product safety and purchasing behaviour of herbal products. This study was designed using a quantitative approach through a survey questionnaire. A total of 467 respondents from seven states in Peninsular Malaysia have participated in this study and collected using the intercept survey. The data were analysed using structural equation modelling with a partial least square approach (SEM-PLS) and assisting SmartPLS 3.3.3. The results showed that mass media has a significant positive effect on attitude, social influence and product safety. Also, attitude, social influence and product safety have a significant positive impact on the purchase behaviour of herbal products. In conclusion, this study identified that mass media influence on attitudes is the strongest predictor, followed by the effects of the mass media on social influence. These findings indicated that the mass media play an essential role in influencing attitude, social influence, and product safety. Followed by attitude, social influence, and product safety that significantly impact the purchase behaviour of herbal products. The finding of this study provides insightful information to the entrepreneurs regarding consumers purchase behaviour.

In most industrial environments, it is usually considered that machines are accessible throughout the planning horizon, but in real situation, machines may be unavailable due to a scheduled preventive maintenance where the periods of unavailability are known in advance. The main idea of this paper is to consider different preventive maintenance policies on machines regarding open shop scheduling problem (OSSP) with sequence dependent setup times (SDST) using immune algorithm. The preventive maintenance (PM) policies are planned for maximizing availability of machines or keeping minimum level of reliability through the production horizon. The objective function of the paper is to minimize makespan. In total, the proposed algorithm extensively is compared with six adaptations of existing heuristic and meta-heuristic methods for the problem through data sets from benchmarks based on Taillard’s instances with some adjustments. The results show that the proposed algorithm outperforms other algorithms for this problem.

This paper is about creating a hybrid QFD-based approach in which the best supplier is selected considering changing customer needs. In most previous studies employing a QFD approach, the possibility of changing customer needs is ignored. On the other hand, supplier selection is a challenging problem that could have been addressed by such a QFD. This paper attempts to create a hybrid QFD-based approach in which the internal relations between the elements are considered. It connects the new QFD to suppliers’ qualifications to create a hybrid supplier selection process. The best suppliers are selected based on the priorities of customer needs for each level of the product improvement plan. When a product is to be developed, the proposed methodology seems to create an efficient solution for supplier selection problem with respect to quality factors.

The purpose of this study is to examine the determinants of behavioral intentions to use of mobile health (m-Health) applications in Jordan through examining the mediating role of perceived trust and its influence on the behavioral intention to use such applications. A conceptual model was developed based on the extant literature. A questionnaire survey was administered to a convenient sample of 318. Data was analyzed using smart PLS 3. The findings suggest that patients’ behavioral intentions to use m-Health applications are positively affected by perceived ease of use, perceived security, social influence and perceived trust of these applications. Perceived Trust was also found to mediate the relationship between these factors and the behavioral intention. Discussion, conclusions, implications, research limitations and areas for future research are also provided.

In this study an integrated model is proposed for the location inventory routing problem under uncertainty. This problem involves determining the location of distribution centers (DCs) in a three echelon supply chain. The DCs receive orders from the customer and according to a continuous review inventory replenishment policy place orders to the supplier. The products are directly shipped from the supplier to the DCs. The vehicles start from the DCs to fulfill the demands of the customers. Determining the routing of the vehicles is one of the decisions involved in this problem. The demands of customers are stochastically distributed and the capacity of DCs are limited. If one of the DCs undergo a disruption and is unable to fulfill the demands of the customers, shortage may occur. Moreover in the proposed model the shortage is considered as partial backlogging. This means that if shortage occurs, some of the orders result in lost sales and other orders are fulfilled in the next period. In order to optimally solve the proposed model a nonlinear integer programming (INLP) model is developed. However, since the problem is NP-hard, the mathematical formulation cannot be efficiently solved for large sized instances of the problem. Therefore an outer approximation method is developed to solve the problem more efficiently. The computational results show the efficiency of the proposed method.