This research is conducted to investigate the factors affecting the accounting information systems quality. Data was collected by using questionnaire delivered to 347 participants who are board of director’s members and managers. The statistical methods approaches are employed to address the research issues including Explanatory Factor Analysis (EFA) and Ordinary Least Squares (OLS). The findings showed that various factors had significant impacts on the accounting information systems quality including (i) organization culture, (ii) manager participation, (iii) information technology, (iv) information technology knowledge of managers, (v) accounting knowledge of managers, (vi) accounting information applications, (vii) consultation of external experts and (viii) training activities for users in accounting information systems. Based on the research results, some key intuitive recommendations were proposed aiming to improve the accounting information systems quality of Vietnamese Enterprises.

In this paper, we consider the inventory model for perishable items with quadratic trapezoidal type demand rate, that is, the demand rate is a piecewise quadratic function under constant deterioration rate. The model consider allows for shortages and the demand is partially backlogged. The model is solved analytically by minimizing the total inventory cost. The result is illustrated with numerical example. Finally, we discuss sensitivity analysis for the model.

Linear matching method (LMM) is one of the effective numerical methods for the limit and shakedown analysis, which computes the converging upper series by solving iteratively linear elastic analysis with Young’s modulus varying in space. LMM, which is capable of implementing by using the commercial finite element packages such as ABAQUS and ANSYS has been widely used in the practical applications including fatigue, creep and composite analysis. Nevertheless, LMM could not ensure numerical accuracy for discontinuous problems such as crack analysis since it computes the mechanical quantities including stress, strain and displacement on the base of conventional finite element method, likewise other numerical methods for the limit and shakedown analysis. Meanwhile, extended finite element method (XFEM), recently proposed, is an attractive numerical method for the analysis of discontinuous problems which enriches finite element approximate space by some special functions. In this paper, authors proposed a very straightforward method for the limit analysis by the combination of XFEM with LMM. Numerical validation is done for two types of typical fracture specimens. Numerical examples show that the limit analysis by combining XFEM with LMM gives more accurate result compared with the one by combining of conventional finite element method with LMM. Furthermore, we demonstrated that the choice of enrichment region plays an important role in the improvement of numerical accuracy of our proposed method.

Investigating the Customer Satisfaction Measurement (CSM) plays an important role in determining the range of customer needs and expectations resulting from delivered products or received services. In this research, a novel approach is proposed for measuring the customer’s satisfaction measurement. Due to ambiguity and lack of information related to evaluation criteria, in the proposed model, the customer feedbacks are considered as linguistic terms and due to the dominance of non –linear relations on behaviors and judgments of human, the result is obtained using a Fuzzy Neural Network. In continuation, roles of the fuzzy inference system for customer’s satisfaction are defined and determined for different conditions of customer’s judgments. Applicability of the proposed model has been successfully implemented through a case study for investigating the customer’s satisfaction on the basis of both qualitative and quantitative inputs.

In the present day, focused commercial centers, offering exchange credit, have turned into a usually received strategy. Past inventory models under reasonable postponement in installments generally accepted that the request of the things was either consistent or simply relying on the retail cost. In this paper, we proposed to sum up, two distribution centers inventory model for crumbling things when the provider offers the retailer to defer period and thus the retailer gives to postpone period to their clients. The request design has been figured in a powerful example, which can be communicated in a straight or exponential shape. Shortages were not permitted. The differing criteria and lead time, smashing expenses were thought to be constant elements of unit cost and lead time, separately. From these, a basic iterative calculation to acquire the ideal renewal number and time booking was given. At last, numerical cases were introduced to show the model and investigation of different parameters was additionally performed. Likewise, the impact of changes in the diverse parameters in the ideal aggregate cost was graphically displayed and the suggestions were examined in details.

This study is targeted towards the explosive behavior of crypto-currencies, namely Bitcoin, Etherium, Litecoin and Ripple by investigating the crypto-currencies bubbles and the causal link between Bitcoin and other three crypto-currencies prices, using GSADF and wavelet coherence tests. The study aims to answer the following questions which have not been investigated in the literature to our best knowledge (i) Was there any bubble in the prices of Bitcoin, Etherium, Litecoin and Ripple and between 01.09.2016 and 01.04.2019? If yes, why (ii) was there any linkage between Bitcoin and Etherium, Litecoin and Ripple? Our findings reveal that (a) there were some bubbles in the crypto-currencies for the periods investigated; (b) there was a positive correlation between Bitcoin and Etherium, Litecoin and Ripple in the short-run; (c) changes in Bitcoin prices lead changes Etherium, Litecoin and Ripple prices in the long run at different periods.

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.

The objective of this study is to propose solutions to attract investment capital for tourism development in Thanh Hoa province, Vietnam. Based on the theoretical framework following eclectic or “OLI model” developed by Dunning and Narula (1996) [Dunning, J., & Narula, R. (2003). Foreign direct investment and governments: catalysts for economic restructuring. Routledge.] and data of 660 questionnaires collected from a survey of tourism investors in Thanh Hoa provinces, we found some important influential factors affecting the attraction of investment for tourism development in Thanh Hoa province. In particular, the local government’s policy of attracting capital appears to have the highest level of importance. The study has some policy implications to increase the attractiveness of investment capital in tourism development in the area.

This paper considers the capacity determination in a closed-loop supply chain network when a queueing system is established in the reverse flow. Since the queueing system imposes costs on the model, the decision maker faces the challenge of determining the capacity of facilities in such a way that a compromise between the queueing costs and the fixed costs of opening new facilities could be obtained. We develop a De Novo programming approach to determine the capacity of recovery facilities in the reverse flow. To this aim, a mixed integer nonlinear programming (MINLP) model is integrated with the De Novo programming and the robust counterpart of this model is proposed to cope with the uncertainty of the parameters. To solve the model, an interactive fuzzy programming approach is combined with the hard worst case robust programming. Numerical results show the performance of the developed model in determining the capacity of facilities.

In today’s dynamic business environment, the product mix and demand may vary from period to period. Therefore, the same configuration of cellular systems will not be optimal in different periods. In this paper, a new mixed integer non-linear mathematical programming model is presented to design dynamic cellular manufacturing systems and combines several design features including multi-period production planning, alternate routings, system reconfiguration, duplicate machines, lot splitting, workload balance among machines and cells, cell size limits, and material flow between machines. The required capacity for parts production is modeled based on flow shop perspective and the aim of mixed integer model is to find optimal independent cells, the quantity of machine types in each cell, and production quantity of the parts during each period of the time horizon. Since this problem belongs to NP-hard class, a three-phase approach is developed to solve the model for practical purposes. Phase 1 finds a feasible solution, phase 2 finds the neighbor solutions, and phase 3 improves a feasible solution. To analyze the computational efficiency, eight test problems with different sizes are considered and the optimal and near-optimal solutions are compared. The efficiency of the algorithm in terms of the objective function values and computational times is shown by the obtained results.