The aim of the present study is to examine the influence of website quality on consumer’s e-loyalty, noting the mediating role of e-trust, e-satisfaction, and perceived enjoyment. Besides, this study examines the consequence of consumer’s e-loyalty. Survey data collected from 594 respondents aged at least 16 years and performed some online shopping through websites in Vietnam. Based on the theoretical framework, PLS-SEM using SmartPLS 3.0 software was deployed to discover links between the constructs. The results showed a positive effect of website quality on e-loyalty, which was mediated partially through consumer e-trust and e-satisfaction. Moreover, e-loyalty had a positive association with electronic word of mouth (eWOM) as well. The main findings of this research provide some empirical implications for Internet marketers and online retailers in Vietnam. E-vendors should understand the customers’ expectations and e-loyalty regarding online shopping to attract new customers as well as to retain their existing customers.

Vietnam is one of the most popular tourist destinations in the Asia-Pacific region and its tourism industry has been growing unprecedentedly over the past few years. However, the Vietnamese tourism industry (VTI) is concerned with the weakness competitive factor. This paper aims to analyze Green Supply Chain Management Practice (GSCM) and its effect on the destination image of Vietnam as the way to improve the completeness. The paper seeks to examine internal environment management (IEM) practices; external environment (EE) and environmental regulation (ER), as possible drivers to GSCM practices and its destination image. The empirical analysis used data from 269 questionnaires which were valid for analysis, through applying the PLS- SEM method. The result of path analysis indicates that the path between internal environmental management and GSCM practice in the VTI was highly significant; internal environmental management (IEM) had a significant impact on the external environment and also had a significant impact on destination image in VTI. The external environment has also maintained a significant impact on the GSCM practices of the VTI and on destination image in VTI. There is also a positive relationship between GSCM and destination image in VTI. As a result, it can be concluded that all hypotheses are supported. This paper concludes with a discussion of the implications of the findings from the study for tourism managers.

A real inventory system for single item with specific demand characteristics motivates this works. The demand can be seen as two types of independent demand, where compound Poisson process describes the characteristics of each demand. The first type of demand is rarely occurred with relatively large size, while the second type of demand is often happened with relatively small size. In order to maintain inventory level, every time the first type of demand occurs a replenishment of stock is conducted which follows order-up-to-level inventory policy. In order to find the optimal inventory decision for that system, a mathematical model of the system is developed with the objective to minimize expected total inventory cost. Some of model assumptions are infinite replenishment, deterministic lead time, and completely backlogged shortages. To solve the model, it is then divided into two sub-problems and classical optimization technique is employed to help find the solution of each sub problem.

In this paper, two policies are considered for supporting periodical publications by the government: direct subsidy payment to these publications and opening new facilities which could help with integration and reduce delivery costs. For this aim, a mixed-integer linear mathematical model is presented that minimizes total costs while considering social welfare. The robust programming approach developed by Bertsimas and Sim is used to cope with uncertain parameters. In order to validate the model and investigate its applicability and advantages, the magazines’ subscriptions in Tehran is selected as a case study. The output of the model demonstrates that when social welfare is not considered, the risk-averted supply chain will focus on low-cost areas of the chain, which are the central areas of Tehran. However, when minimum social welfare is assured, the supply chain pays attention to all areas. Also, the government should increase supply capacity by opening new facilities, and it should differentiate between areas when paying direct subsidies.

This paper aims to investigate factors affecting the application of management accounting in Vietnamese enterprises. Quantitative research was conducted and data was collected by sending questionnaires to 120 companies in the manufacturing, trading and service sectors in Vietnam. 6 factors were selected to measure the application of management accounting in enterprises through correlation and regression analysis. The results showed that 5 out of 6 factors positively associated with the level of management accounting application; including firm size, organizational culture, organizational structure, technology and human resources operations. In particular, corporate culture has the highest impact and opinion of managers has the lowest impact on management accounting application. Business environment has a negative impact on management accounting application in enterprises. Based on the research results, suggestions and recommendations are proposed for enterprises regarding application of management accounting. The research provided an overview of management accounting application and its benefits to enterprises. Whereby, it helps managers have a better understanding of management accounting and future directions for application. Moreover, the research results will be useful for managers to identify factors influencing their management accounting practices and improve the current management process applied in organizations.

The purpose of this paper is to provide a method of process reference to supply chain relationships in a downstream sector. It serves as a tool to analyze collaboration between entities in the supply chain strategy. The study is categorized into the case study research in Malaysian oil palm refineries. The data collection is accomplished through semi-structured interview using snowball sampling and observation by visiting four oil palm refineries based on selecting non probability sampling technique through purposive personal judgment. Most of downstream industries select produced end products with the aim of getting greater margins. Nevertheless, a process reference analyzes that the downstream industry distributes semi-finished products to the international market than producing end products in the local market. There are the effects of supply chain relationships between upstream and downstream. Furthermore, entities that have the high dependencies tend to follow the strategy of the dominant entities consequently network of business process driven by the strong entities. The result gives implication to leverage SCOR model for analyzing the supply chain relationships between entities. It can be applied to any industry that decide the effective collaboration with their supplier, distributor and buyer.

The main purpose of this study was to investigate students’ academic performance (SAP) before, during, and after the COVID-19 pandemic in face-to-face (F2F) and online learning (OL) instructions. The study also attempted to determine the impact of gender and academic major on students’ academic performance. For the results of semester grade point average (SGPA), the findings of the study showed better SAP in F2F learning as compared to OL learning, while the results of grade point average (GPA) indicated better SAP in OL learning than in F2F learning. The findings supported the stated hypotheses by indicating the positive impact of gender and academic major on SAP in F2F and OL learning, before, during, and after the COVID-19 pandemic. The regression analysis revealed that the demographic variables can predict up to 18% variations in the student’s academic performance. These findings offer valuable insights for practical strategies to improve SAP in F2F and OL learning.

This study conducts a comprehensive literature review to understand the direction and trends in contemporary labor studies, emphasizing significant global issues attracting scientific attention. Employing a scientometric approach, recent research data is explored using bibliometric analysis. The research adopts a mixed-methods approach, utilizing National Labor Statistics and conducting Focus Group Discussions (FGD) for nuanced insights into labor conditions in Indonesia. A bibliometric analysis of Scientific Labor Research Articles in Scopus (2020-2022) identifies trends and classifies global labor-related topics. Results highlight challenges in the labor landscape, driven by technological advancements and globalization, impacting job security, creating skill gaps, and raising concerns about the Fourth Industrial Revolution. The informal sector, particularly pronounced in Indonesia, poses challenges related to poverty, inequality, and the gig economy. Emerging issues like informal care for the elderly, social capital, and informal learning call for nuanced policy approaches. Indonesia's aging population adds complexity, requiring sustainable support mechanisms for healthcare and social services. The digital landscape, specifically Fintech, plays a significant role, yet research gaps persist. Bridging the digital talent gap is crucial for effective digital transformation, necessitating collaboration between government, educational institutions, and industry players. Challenges in Fintech development highlight the importance of initiatives promoting digital literacy, ethical practices, and regulatory frameworks. In conclusion, a holistic and collaborative approach is essential for navigating complexities and fostering sustainable economic growth.

Deep learning techniques are making significant contributions to the rapid advancements in forecasting. A standout algorithm known for its ability to produce accurate forecasts by recognizing temporal autocorrelation within the data is the Long Short-Term Memory (LSTM) algorithm, a component of Recurrent Neural Networks (RNN). The LSTM method employs both stateless and stateful architecture approaches, providing versatility in its application. This research aims to compare stateful and stateless algorithms in LSTM models, focusing on forecasting stock prices, such as those of Apple Inc. This comparative analysis is crucial, taking into account various characteristics of time series data, including the benefits and drawbacks of temporal autocorrelation. The comparison results reveal that, despite the stateful algorithm requiring more computational time, it achieves greater accuracy than the stateless approach. The forecast indicates a potential upward trend in share prices for the period of January to December 2024, according to the projected outlook for Apple's stock value. However, it is essential to exercise prudence in interpreting these results, considering that share price fluctuations are influenced by a significant number of variables.

As the workforce worldwide goes through a transformative shift towards remote work, this paper discusses the positive effects of this quite flexible work arrangement on team’s innovation performance (TIP) in multinational, non-governmental organizations (NGOs). Adopting cross-sectional, quantitative research design, empirical data were collected through a survey of 268 employees of multinational NGOs operating in Jordan. The collected data were, then, analyzed using structural equation modeling. The results of the analysis showed that remote work has significant, positive effects on TIP in NGOs. Of the various remote work features investigated, spatial flexibility has the highest effect. The study results contribute to the ongoing discourse on the future of the work styles and have implications for leaders, policymakers, and practitioners who seek promoting innovation in multinational NGOs.