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The purpose of this paper is to present an effective optimization strategy applied in a physical structure optimization of a semiconductor power metal oxide semiconductor field‐effect transistor (MOSFET), with an expensive integration constraint computation.

In order to deal with inaccuracy due to inevitable numerical errors in the objective function calculation (the power losses of the power MOSFET) and in the constraint computation, the paper proposes to use the progressive quadratic response surface method (PQRSM).

The paper focuses on four aspects: the inevitable numerical errors in the power loss and the integration constraint computation; the response surface approximation (RSA) method; the PQRSM principle; and finally the comparisons of several optimization methods applied on this application problem.

An original optimization method, PQRSM, is proposed for reducing the oscillation problem of a semi‐analytical model. The optimization results of PQRSM have been compared with the evolution strategy (ES) algorithm, with similar results but faster computation.

Drought and salinity intrusion aggravated by climate change threaten agricultural livelihoods in Viet Nan's Mekong Delta. In response, authorities have built water management infrastructure for irrigation and salinity protection. This study assessed the impact of one such project, the Ba Lai dam in Ben Tre province, on the livelihoods of aquaculture farmers.

This study uses the Sustainable Livelihoods Framework to assess the impact of the Ba Lai dam on the livelihood capitals of 18 farming households in four communes, located both upstream and downstream of the dam.

The authors find that, apart from some positive effects, the dam has also brought negative environmental consequences, such as increased water pollution. The authors also find that farmers have responded to the changes by adapting their livelihood practices.

The samples were relatively small, encompassing four communes in Ben Tre province. On the other hand, this case study is instructive to the many ongoing infrastructure projects in the Vietnamese Mekong Delta.

The project have caused an increase in water-related social conflict.

The case of the Ba Lai dam provides a cautionary example for infrastructure-based water management plans, both in Viet Nam and more broadly. The study suggests the need to strengthen community participation and prioritize impacts of farmers' capital assets when constructing water management infrastructure for climate change adaptation.

In recent years, the development of metaheuristic algorithms for solving optimization problems within a reasonable timeframe has garnered significant attention from the global scientific community. In this work, a new metaheuristic algorithm inspired by the inflection mechanism of the avian influenza virus H5N1 in poultry and humans, taking into account its mutation mechanism, called H5N1.

This algorithm aims to explore optimal solutions for optimization problems by simulating the adaptive behavior and evolutionary process of the H5N1 virus, thereby enhancing the algorithm’s performance for all types of optimization problems. Additionally, a balanced stochastic probability mechanism derived from the infection probability is presented. Using this mechanism, the H5N1 algorithm can change its phrase, including exploitation and exploration phases. Two versions of H5N1, SH5N1 and MH5N1, are presented to solve single-objective optimization problems (SOPs) and multi-objective optimization problems (MOPs).

The performance of the algorithm is evaluated using a set of benchmark functions, including seven unimodal, six multimodal, ten fixed-dimension multimodal to solve SOPs, ZDT functions and CEC2009 has been used to demonstrate its superiority over other recent algorithms. Finally, six optimization engineering problems have been tested. The results obtained indicate that the proposed algorithm outperformed ten algorithms in SOPs and seven algorithms in MOPs.

The experimental findings demonstrate the outstanding convergence of the H5N1 algorithm and its ability to generate solutions of superior quality.

This paper aims to examine the impact of information and telecommunication technologies (ICT-proxied by mobile phone subscription and Internet usage) on carbon dioxide (CO2) emissions in the Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2018.

The Cross-section Autoregressive Distributed Lag (CS-ARDL) model is employed to address the potential cross-section dependence problem. Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used to test for robustness of results.

Results reveal contrasting effects of mobile phone subscription and Internet usage on CO2 emissions. While mobile phone penetration helps mitigate CO2 emissions, Internet usage tends to increase the emissions. Findings show that renewable energy is beneficial to the environment while economic growth is harmful to the environment. The effects of financial development and trade openness seem negligible.

This study offers practical implications for policymakers. As different proxies of ICT could have contradictory impact on CO2, governments should be cautious against utilizing ICT to mitigate CO2. Findings point to the benefits of renewable energy in alleviating CO2 emissions. Therefore, governments are strongly advised to implement policies facilitating renewable energy consumption.

Previous studies ignored the problem of cross-section dependence which could lead to biased results and cause misleading inferences. This study aims to fill this void in the literature.

In this study, we aim to investigate the connectedness spillovers among major cryptocurrency markets. Moreover, we also explore to identify factors driving this connectedness, particularly focusing on the sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies under Twitter-based economic uncertainties and US economic policy uncertainty. Finally, we investigate the extent to which cryptocurrency markets serve as a safe haven, hedge, and diversifier from news-based uncertainties.

This study employs the connectedness approach following the combination of Ando et al. (2022) QVAR and Baruník and Krehlík's (2018) frequency connectedness methodologies into the framework proposed by Diebold and Yilmaz (2012, 2014). The data covered from November 10, 2017, to April 21, 2023, and the factors driving cryptocurrency connectedness spillovers are identified and examined. The sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies, concerning Twitter-based economic uncertainties and US economic policy uncertainty, are analyzed. We apply the Wavelet quantile correlation (WQC) method developed by Kumar and Padakandla (2022) to explore the effects of Twitter-based economic uncertainties and US economic policy uncertainty on Cryptocurrency market connectedness risk spillovers. Besides, we check and present the robustness of WQC findings with the multivariate stochastic volatility method.

Our findings indicate that Ethereum and Bitcoin are net shock transmitters at the center of the connectedness return network. Ethereum and Bitcoin hold the highest market capitalization and value in the cryptocurrency market, respectively. This suggests that return shocks originating from these two cryptocurrencies have the most significant impact on other cryptocurrencies. Tether and Monero are the net receivers of return shocks, while Cardano and XRP exhibit weak shock-transmitting characteristics through returns. In terms of return spillovers, Ethereum is the most effective, followed by Bitcoin and Stellar. Further analysis reveals that Twitter economic policy uncertainty and US economic policy uncertainty are effective drivers of short-term and total directional spillovers. These uncertainty indices exhibit positive coefficient signs in short-term and total directional spillovers, which turn predominantly negative in different magnitudes and frequency ranges in the long term. In addition, we also document that as the Total Connectedness Index (TCI) value increases, market risk also rises. Also, our empirical findings provide significant evidence of Twitter-based economic uncertainties and US economic policy uncertainty that affect short-term market risks. Hence, we state that risk-connectedness spillovers in cryptocurrency markets enclose permanent or temporary shock variations. Besides, findings of the low value of long-term spillovers suggest that risk shocks in cryptocurrency markets are not permanent, indicating long-term changes require careful monitoring and control over market dynamics.

In this study, we find evidence that Twitter's news-based uncertainty and US economic policy uncertainty have a significant effect on short-term market risk spillovers. Furthermore, we observe that high cryptocurrency market risk spillovers coincide with periods of events such as the US-China trade tensions in January 2018, the Brexit process in February 2019, and the COVID-19 outbreak in November 2019. Next, we observe a decline in cryptocurrency market risk spillovers after March 2020. The reason for this mitigation of market risk spillover may be that the Fed's quantitative easing signals have initiated a relaxation process in the markets. Because the Fed's signal to fight inflation in March 2022 also coincides with the period when risk spillover increased in crypto markets. Based on this, we present evidence that the FED's communication mechanism with the markets can potentially affect both short- and long-term expectations. In this context, we can say that our hypothesis that uncertainty about the news causes short-term risks to increase has been confirmed. Our findings may have investment policy implications for portfolio managers and investors generally in terms of reducing financial risks.

Our paper contributes to the literature by examining the interconnectedness among major cryptocurrencies and the drivers behind them, particularly focusing on the role of news-based economic uncertainties. More broadly, we calculate the utilization of advanced methodologies and the incorporation of real-time economic uncertainty data to enhance the originality and value of the research, which provides insights into the dynamics of cryptocurrency markets.

This paper examines the role of the annual report’s linguistic tone in predicting future firm performance in an emerging market, Vietnam.

Both manual coding approach and the naïve Bayesian algorithm are employed to determine the annual report tone, which is then used to investigate its impact on future firm performance.

The study finds that tone can predict firm performance one year ahead. The predictability of tone is strengthened for firms that have a high degree of information asymmetry. Besides, the government’s regulatory reforms on corporate disclosures enhance the predictive ability of tone.

The study suggests the naïve Bayesian algorithm as a cost-efficient alternative for human coding in textual analysis. Also, information asymmetry and regulation changes should be modeled in future research on narrative disclosures.

The study sends messages to both investors and policymakers in emerging markets. Investors should pay more attention to the tone of annual reports for improving the accuracy of future firm performance prediction. Policymakers should regularly revise and update regulations on qualitative disclosure to reduce information asymmetry.

This study enhances understanding of the annual report’s role in a non-Western country that has been under-investigated. The research also provides original evidence of the link between annual report tone and future firm performance under different information asymmetry degrees. Furthermore, this study justifies the effectiveness of the governments’ regulatory reforms on corporate disclosure in developing countries. Finally, by applying both the human coding and machine learning approach, this research contributes to the literature on textual analysis methodology.

This research examines how bank competition and corporate social responsibility (CSR) affect the stability of Vietnamese commercial banks.

Utilizing data collected from 24 commercial banks spanning the period from 2015 to 2022, the paper employs the two-step system generalized method of moments (SGMM) regression method to find the impact of competition and CSR on commercial banks’ stability in Vietnam.

The key findings are (1) increased competition boosts commercial bank stability; (2) economic and environmental CSR initiatives adversely affect bank stability, while social CSR has a positive impact; (3) seven other factors are also identified to enhance bank stability, including bank size, cost management efficiency, independent management, inflation, gross domestic product (GDP) growth, monetary policy and volatility time.

Prior studies have not concurrently incorporated both CSR and bank competition in their investigations of bank financial stability. Specifically, the comprehensive components of CSR remain underexplored, with a predominant focus on its environmental dimension. This research stands out as one of the few endeavors scrutinizing the influence of competition and CSR on commercial bank financial stability in Vietnam, with a detailed investigation of all three components of CSR.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2024-0316

This study analyzes the factors that affect the decisions of micro-businesses to switch to enterprises in Thanh Hoa, Vietnam.

In order to explain the behavior of micro-businesses in switching to enterprises, the authors designed a questionnaire and collected survey data from 404 micro-businesses. The generalized structural equation modeling was applied to analyze the structured model with the dichotomous dependent variable.

First, the behavior of micro-businesses to switch was indirectly affected by needs and directly affected by attitudes, perceived behavioral control, subjective norm and institutional quality. Second, the subjective norms exerted the most influence on the behavior of the micro-businesses in switching. This finding implies that (1) the behavior of the micro-businesses depended on the assessments, perceptions and views of their friends, relatives and colleagues, and (2) the behavior to switch stems mainly from the desire to improve the businesses' position in society. Finally, both formal and informal institutions play an essential role in the behavior of the micro-businesses to switch to enterprises.

There have been no previous studies that have applied structured models to test the behavior of micro-businesses to switch to enterprises. Furthermore, previous studies had mainly addressed the psychological factors or needs of micro-businesses. In this study, apart from the above factors, the authors discuss the impact of institutions on the behavior of micro-businesses to switch.

Luxury and communism are perceived to be ideologically incompatible values. Prior to the end of the Cold War, luxury tourism and socialist economies had an accommodating relationship and were rationalised at the national level for foreign exchange revenues, showcasing national development in some instances and finally promoting leisure and political education. However, contemporary scholarship on political ideology and luxury tourism is limited given changes in the political and tourism domain over the last two decades. The start of luxury travel and increasing private promotion in Vietnam comes at a time where the communist regime is hurriedly developing the economy at a breakneck speed. Key cities like Hanoi and Ho Chi Minh City have become the forefront of luxury travel for Vietnam. Luxury malls, fine dining and five-star hotel resorts have sprung over the years in tandem with Doi Moi (economic restructuring). Tourism literature has seldom ventured into regime politics and luxury tourism. Using a historical approach, the chapter traces the preamble of luxury tourism in the age of Vietnam's modernity. A critical assessment of contemporary luxury tourism in Vietnam reveals a favourable relationship with socialist principles.

This paper aims to explore green technology (GT) transfer through the perceptions of both business managers and technology specialists, who have been identified as the foremost practitioners of this practice.

A total of 22 semi-structured interviews were conducted with business leaders and technology scientists. The interviewees were asked to share their views on the motivations for importing GT; their familiarity with, knowledge of and understanding of GT transfer and the current GT performance in their organization; the key strengths of GT transfer and its limitations; the barriers to the use of GT; and their usefulness. The theoretical framework of actors’ resistance to institutional demands of Oliver (1991) is used as a theoretical lens to investigate the perceptions of the interviewees.

This study suggests that despite some benefits of the adoption of GT, such as increasing competitive advantage and improving green operations, there are huge concerns over the use and importation of GT. More specifically, almost all the technicians were concerned about the technical risks resulting from the lack of operational tests, the old technologies and the lack of knowledge transfer. Meanwhile, the paucity of specific regulations, guidance and environmental standards has been reported by business managers as one of the primary constraints for this movement.

This research contributes to the emerging literature on GT transfers in the developing world. It proves that the lack of communication and the scarcity of a true champion for GT efforts have reduced the efficiency of GT transfer.

By shedding light on the intricate nature of the relationships arising from GT adoption in organizations, this paper aims to support business leaders and standard setters in making a decision regarding the implementation and promotion of GT transfer, especially in the context of developing countries.

To the best of the authors’ knowledge, this is one of the first studies to explore eco-friendly technology transfers in a developing country from the micro-level perspective of both business and technology practitioners of GT-recipient organizations.