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Task complexity is one of the significant factors that influences and is used for forecasting employee performance and determining labor cost. However, the complexity level of tasks is unstructured, dynamic and complicated to perform. This paper develops a new method for evaluating the complexity level of tasks in the production process to support production managers to control their manufacturing systems in terms of flexibility, reliability to production planning and labor cost.

The complexity level of tasks will be analyzed based on the structuralist concept. Using the structure of task, the factors that significantly affect the task complexity in an assembly line will be defined, and the complexity level of the task will be evaluated by measuring the number of task components. Using the proportional 2-tuples linguistic values, the difference between the complexity levels of tasks can be compared and described clearly.

Based on the structure of the task, three contributory factors including input factors, process-operation factors and output factors that significantly affect the task complexity in an assembly line are identified in the present study. The complexity level of the task is quantified through analyzing the details of the three factors according to two criteria and six sub-criteria within the textile case study.

The proposed approach provides a new insight about the factors that have an effect on the complexity of tasks in production and remedies some of limitations of previous methods. The combination of experts' experience and scientific knowledge will improve the accuracy in determining the complexity level of tasks.

This study enhances the financial modelling of companies undergoing an Initial Public Offering (IPO) by focusing on internal capability determinants and IPO proceeds.

A hybrid logistic regression and shallow-depth decision tree approach are employed to predict the initial three-year post-IPO performance of companies listed on the Stock Exchange of Thailand (SET) using data from 2002 to 2021.

The results demonstrate that these models not only perform competitively against complex machine learning algorithms but also surpass them in terms of interpretability, an essential feature in financial modelling. The proposed approach effectively captures the effects of each determinant, offering valuable insights into strategic resource allocation and investment decision-making during transition years.

This study introduces a novel application that integrates logistic regression with decision trees to predict multiclass financial performance, filling the gap between complex machine learning techniques and interpretable financial models. It offers practical tools for companies and investors to make informed decisions in challenging post-IPO environments.

“The world needs science, science needs women” is the message given by UNESCO in the program for the development of women in science” (UNESCO, 2017). In Vietnam, women’s participation and achievements in scientific research is considered a great and important resource for industrialization and modernization. Even so, are there gender differences in scientific achievement in the social science research institutes in Vietnam? What factors influence the scientific achievement of female social researchers? The answers will be based on data from a 2017 survey with a sample of 756 researchers, of which 77.6% were female. The survey was conducted by the Vietnam Academy of Social Sciences, a leading, ministry-level national center for the social sciences in Vietnam. This chapter analyzed the scientific achievements of researchers through their position as principal investigators of research projects and their publications, and factors that may impact this. Bivariate and multivariate analyses of factors that may affect the scientific achievement of researchers found that gender differences in academic achievement in the social sciences in Vietnam was still prevalent. Female researchers’ scientific achievements were lower than those of their male counterparts. The contribution to science of Vietnamese female researchers was limited by many different factors; the most important were the academic rank of the researchers and gender stereotype that considered housework the responsibility of women.

Open social innovation has become a critical practice for firms competing in volatile markets. Simultaneously, the rise of digital technologies has opened opportunities across sectors, making digital transformation a key driver of corporate change. This study examines the impact of internal and external factors, such as social capital, absorptive capacity and government support, in facilitating open social innovation and digital transformation activities, which may ultimately enhance business performance.

Data were collected through a questionnaire survey distributed to management members across various enterprises in a wide range of industries in Vietnam. A total of 289 valid responses were obtained, and the research hypotheses were tested using partial least squares structural equation modeling.

First, open social innovation positively influences digital transformation, with absorptive capacity mediating this relationship. Second, social capital directly affects open social innovation and indirectly impacts digital transformation through open social innovation. Third, digital transformation directly enhances business performance, while absorptive capacity indirectly influences business performance through digital transformation. Finally, government support directly impacts business performance and indirectly influences digital transformation via open social innovation.

By integrating social capital theory and the resource-based view, this research significantly advances the understanding of the complex relationships among government support, social capital, open social innovation, digital transformation, absorptive capacity and business performance.

Recognition that not every climate adaptation policy is a good one has shifted attention to new tools and methods to measure the adequacy and effectiveness of adaptation policies. This study aims to propose and apply and applies an innovative adaptation policy assessment framework to identify the extent to which climate adaptation policies in Vietnam exhibit conditions that are likely to ensure a sufficient, credible and effective adaptation.

In total, 21 conditions, categorized under five normative principles and covering critical issue areas in adaptation domain, form the climate adaptation policy assessment framework. The principles were double-checked and tested in case studies through observations and analyses of policy documents to ensure that each condition should be distinct and not overlapping across principles. To see if the principles and attendant conditions were able to capture all relevant aspects of adaptation, the authors used structured expert judgment. In total, 39 policy documents pertaining to climate change adaptation were selected for qualitative document analysis. In-depth interviews with local officials and experts were conducted to address data gaps.

The study reveals major weaknesses constituting a reasonably worrisome picture of the adaptation policies in Vietnam since several critical conditions were underrepresented. These results shed new light on why some adaptation policies falter or are posing adverse impacts. The findings suggest that a sound policy assessment framework can provide evidence on what effective adaptation policy looks like and how it can be enabled. The framework for climate adaptation policy assessment in this study can be easily adjusted and used for different socio-environmental contexts in which new conditions for policy assessment might emerge.

The findings show underlying weaknesses constituting a reasonably worrisome picture of the adaptation regime in Vietnam. In the absence of mechanisms and measures for accountability and transparency in policy processes, adaptation in Vietnam appears more likely to be prone to maladaptation and corruption. While solving these problems will not be easy for Vietnam, the government needs to evaluate whether the short-term gains in sustaining the existing adaptation policies really make progress and serve its long-term climate-adaptive development goals.

Although interpretations of adaptation effectiveness may be very divergent in different normative views on adaptation outcomes, the authors argue that a common, agreed-upon effectiveness can be reached if it is clearly defined and measurable in adaptation policies. Thus, the climate adaptation policy assessment framework proposed in this study is critical for policymakers, practitioners, donors and stakeholders dealing with adaptation to better understand the weaknesses in policymaking processes, pinpoint priority areas of action and timely prevent or prepare for possible adverse impacts of policies.

Nowadays, under climate change contexts, natural disasters are becoming stronger in intensity and probability. The impacts of natural disasters on people and the environment are also getting worse. The purpose of this study was conducted to provide a method of assessing disaster risks, in particular, floods for human life in Mid Central Vietnam.

The pre-disaster assessment method was used based on the analysis of hazard factors (Hazard-H), exposure to hazards (Exposure-E) and vulnerability (Vulnerability-V).

Flood disaster risks in the area are assessed and displayed on spatial maps. The districts in coastal plains of Quang Ngai and Thua Thien Hue provinces have the highest levels of risk. These assessments will play an important role in supporting flood prevention and mitigation in the region.

According to the authors, this is the first study assessing the flood risk in Vietnam on the pre-disaster perspective. The assessment provides a plain point of view on natural disaster impacts that supporting disaster prevention services.

This study aims to investigate the relationship between corporate tax avoidance and stock price crash risk and the moderating effects of corporate governance.

This study investigates the relationship between corporate tax avoidance and stock price crash risk using the sample consisting of listed firms in Vietnam for the period of 2011–2020 using panel regressions.

The authors find that there is a positive relationship between tax avoidance and stock price crash risk. Foreign ownership weakens the impacts of tax avoidance on stock price crash risk, while managerial ownership strengthens the impacts. Female Chief Executive Officers (CEOs) and female chairpersons weaken this relationship. Board gender diversity and state ownership have insignificant moderating impacts.

These findings could help the stock market build better internal monitoring mechanisms to reduce the impacts of tax avoidance on future stock price crash risk. Investors can recognize the characteristics of corporate governance, especially foreign ownership, managerial ownership, female CEOs and female chairpersons when making investment decisions. The policy makers should consider policies to attract foreign investment and support women entrepreneurship.

This paper contributes to the literature on the impacts of tax avoidance on stock price crash risk in emerging countries. This paper is the first to investigate the influence of corporate governance mechanisms including state ownership, foreign ownership, female CEOs and chairpersons and board gender diversity on this relationship.

This paper aims to present a hybrid review combining the theory, context, characteristics and methodology (TCCM) framework and bibliometric analysis of international business research from 1991 to 2023, shedding light on the field’s growth, trends and key contributors.

Relevant papers were selected using the preferred reporting items for systematic reviews and meta-analyses model. Initially, this paper conducted a descriptive analysis to identify prolific institutions, countries and journals. Using bibliometric techniques and the TCCM framework, this paper analyzed theory, context and method visualized through word clouds and keyword co-occurrence. The characteristic aspect was analyzed using bibliographic coupling to identify major themes, providing a comprehensive understanding of the most significant factors in international business research.

The analysis of a data set comprising 5,644 documents reveals a steady increase in the annual growth rate of publications, highlighting the growing significance of international business in the global economy. First, this paper noticed a significant increase in publications in leading international business journals, with the Journal of International Business Studies being the most prolific. Second, using the TCCM framework, this paper discovered that the resource-based view, institutional theory, transaction cost theory and internalization theory are predominant in international business research. Most studies have concentrated on firm or enterprise-level entities, followed by country-level analyses. This paper also identified six main themes: (1) innovation and strategy, (2) market, (3) HR impact and leadership, (4) marketing, (5) internationalization and (6) entrepreneurship. Quantitative methods have been the most frequently used research design, followed by qualitative and mixed methods.

The study offers researchers and practitioners a roadmap for future investigations, collaboration and innovation in international business, thereby advancing the knowledge and understanding of this complex field within a globally interconnected economy.

This study provides insights into growth and trends, identifying journals, clustering research topics and enhancing theoretical and methodological understanding in the field of international business.

Building on my earlier work (Dang, 2007, 2008), this chapter provides an updated review of the private tutoring phenomenon in Vietnam including the reasons, scale, intensity, form, cost, and legality of these classes. In particular, this chapter offers a comparative analysis of the trends in private tutoring between 1998 and 2006 using all available data.

This chapter analyzes data from different sources, including (i) the 2006 Vietnam Household Living Standards Measurement Survey (VHLSS), (ii) the 1997–1998 Vietnam Living Standards Measurement Survey (VLSS), (iii) the 2008 Vietnam Household Testing Survey (VHTS), and (iv) local press in Vietnam. Quantitative methods are used.

Several (micro-)correlates are examined that are found to be strongly correlated with student attendance at tutoring, including household income, household heads’ education and residence areas, student current grade level, ethnicity, and household sizes. In particular, I focus on the last three variables that received little attention in the previous literature on the determinants of tutoring.

This chapter provides an updated and systematic review of the private tutoring phenomenon in Vietnam. Findings are highly relevant to the ongoing debates on private tutoring among all stakeholders in Vietnam, as well as policymakers/researchers in other countries. Suggestions are proposed on current gaps in the literature for future research.