The main goal of this study is to investigate the classification capability of several machine learning (ML) techniques, including decision tree (DT), multilayer perceptron (MLP) network, Naïve Bayes, radial basis function (RBF) network, and support vector machine (SVM) for predicting purchase decisions. The application case is related to consumer purchase decisions of domestic goods in the context of Vietnam. Firstly, factors influencing Vietnamese consumers’ purchase decision of domestic products were identified. Then, data from 240 consumers in Vietnam were collected. Different classifying models based on ML techniques were developed to analyse the sampling data after the performances of the models were evaluated and compared using confusion matrix, accuracy rate and several error indexes. The results indicate that the DT(J48) obtained the highest performance with the corrected prediction percentage of 91.6667%. The findings also show that machine-learning techniques can be used to explicitly in forecasting Vietnamese consumers’ purchase behaviour.

Evaluating research productivity of lecturer is a vital process of universities for teaching improvement and administrative decision making. Lecturers’ research productivity evaluation is a difficult and sensitive problem which has many objective and subjective criteria, complexity and imprecision. Therefore, the evaluation of lecturers’ research productivity can be viewed as a multi-criteria decision making (MCDM) problem in vague environment. This study develops an integrated MCDM approach for evaluating the lecturers’ research productivity. In the proposed approach, a fuzzy analytic hierarchy process (AHP) is applied to determine the weights of criteria. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method using interval neutrosophic sets is further adopted for showing the preference order of the lecturers’ research productivity in an educational organization. Finally, the proposed approach is applied to solve the lecturers’ research productivity evaluation problem in the case of University of Economics and Business, Vietnam National University, Hanoi (UEB-VNU).

In every nation's Green Growth Strategy, enterprise's green investment plays a vital role for sustainable development. In order to develop green investment activity for sustainable development, it is necessary to identify factors affecting green finance and sustainable development of businesses. This study identifies and measures the factors affecting green investment in Vietnamese using the Exploratory Factor Analysis (EFA) methodology to process the dataset from 208 businesses in different industries in 2018.The results show that most of the factors, which were included in the survey, were reliable, maintained statistical significance, and converged into the group of factors. The factors in the survey includes Infrastructure for green investment, Difficulties in approaching funding for green investment activities, Incentives to access capital for green investment, Understanding of enterprises' green investment, Support from the Government in accessing to fund for green investment, The capital that businesses can access for green investment, The enterprise plans to implement green investment projects actively and the special incentives of green investment. Notably, the group of factors about green investment awareness, awareness on accessing green capital, the role of the Government, and green capital mobilization tools had substantial impacts on the green investment implementation of Vietnamese businesses. On that basis, the proposed recommendations focus on the central role of the Government, the legal framework, the diversification of green financing, and green capital mobilization tools. Raising awareness of businesses in accessing and using these capital raising tools as well as promoting green investment communication are solutions according to the evaluation of more than 200 surveyed enterprises.

This study was conducted to measure the level of economic linkage in key economic zones in central Vietnam generally and to measure the level of economic linkage in the tourism sector. Secondary data were collected from the Statistical Yearbook published by the General Statistics Office and the Local Bureau of Statistics and primary data collected from surveys of 102 hotels and tourism firms in the center of Vietnam. We used the Moran Index (I) to quantify overall economic aggregation across the region and that scoring method was used to measure the degree of linkage in regional tourism. The results show that the level of overall regional economic linkages was very low and this was also relevant when analyzing the tourism sector in some areas of the center of Vietnam. Based on the results, some recommendations are given for strengthening economic linkages in key economic regions of Vietnam.

The paper studies the monetary approach to exchange rate for a group of five Pacific Basin economies, using quarterly data for the period of post – Asian financial crisis. Estimated results reveal that for Thailand and the Indonesia which were most affected by Asian financial crisis, monetary model did not work for explaining exchange rate movements. For Korea and Malaysia, the results show that there were long-run relationships between exchange rates and their monetary variables. However, the proportionality hypothesis of exchange rate to relative money supply did not hold for the two countries. Conversely, for Vietnam, it appears that the monetary model worked well in explaining exchange rate movements. Especially, the estimated coefficients of money and output variables are consistent with any traditional variants of monetary model.

Caring for cancer patients may create several negative emotions for their family members. Therefore, reducing or alleviating negative feelings are essential in improving mental and physical health of cancer patients’ family members. This research aims to identify the priority levels of the strategies used by cancer patients’ family members to cope with negative emotions, utilizing Analytic Hierarchy. Next, the proposed model is applied in the cases of Vietnamese cancer patients’ family members. Four groups of coping strategies against negative emotions of cancer patients’ family members are used in the model, including: (1) positive emotion-focused coping strategies; (2) negative emotion-focused coping strategies; (3) positive action-focused coping strategies; (4) negative action-focused coping strategies.

Distribution centers selection is a vital task of any company to reduce costs, improve efficiency of transport flows, which yields customer satisfaction. To select the suitable distribution centers, many quantitative and qualitative criteria must be considered in the selection process. Therefore, distribution centers selection can be seen as a multi-criteria decision making (MCDM) problem under vague environment. Single-valued complex neutrosophic sets (SVCNSs), which is generalized of fuzzy sets, complex fuzzy sets and intuitionistic fuzzy sets; can better represent the vague information than the other sets. This paper aims to propose a new the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach based on SVCNSs to select the locations of distribution center. In the proposed TOPSIS approach, the importance weights of criteria, the ratings of alternatives, and their aggregated values are assessed and evaluated using SVCNSs. Then, this paper defines the operational rules of SVCNSs and calculates the aggregated weighted ratings of alternatives. Furthermore, the score, accuracy and certainty function are developed to rank the alternatives. Last, an application to the distribution center location selection is presented to show the advantages of the proposed approach.

The study aims to examine the impact of supply chain linkages on the performance of businesses. Quantitative research is used by implementing the analysis of the SEM linear structure model. A survey is conducted consisting of 598 samples - experienced managers who had the knowledge of the management of supply chain activities in enterprises in Vietnam. Research results show that supply chain linkages, although not having a direct impact, has an indirect impact on the business performance of enterprises through the intermediary factors of trust and business strategy and the opportunistic behaviors of the participating members. Also, research has demonstrated that opportunistic behaviors have negative effects on trust among members of the supply chain.

The goal of this research is to investigate the relationship between human resource management and tourism supply chain management, as well as the effects of human resource and tourism supply chain on customer satisfaction and operation performance. The research was carried out in Vietnam at several tourist destinations. The study found 297 viable samples after screening the sample. A Partial Least Squares (PLS) algorithm was used to process the data. The study's findings revealed a link between human resources and supply chain management in the tourism business. Furthermore, the study discovered that human resource management uncertainty had an impact on organizational performance.

Prior studies suggest that differentiating strategy (DS) has an intervening impact on the relationship between entrepreneurial orientation (EO) and performance. However, they only examine the impacts based on each dimension of EO, provide a lack of theory underpinning why this strategy is the mediator, and focus on the manufacturing industry of an emerging market. Addressing these gaps, the purpose of this study draws from the contingency theory in strategic management to examine whether this strategy is the mediator in the context of Vietnam. Partial least square structural equation modeling used to assess the research model with data collected from 142 SMEs operating in Vietnam. The result indicates that DS fully has an intervening effect on the association between EO and SMEs' performance.