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The advent of artificial intelligence technologies, exemplified by platforms such as ChatGPT, has created a profound global impact, with a particular resonance in education. This research aims to integrate the information systems success (ISS) model with the stimulus-organism-response (SOR) paradigm to explore how information quality and service quality individually, jointly, congruently, and incongruently affect higher education students’ trust in ChatGPT, satisfaction, and continuance usage intention.

We employed a sophisticated methodology - polynomial regression with response surface analysis - and conducted our study with a sample of 468 higher education students selected in Vietnam using a three-phase stratified random sampling approach to evaluate the hypotheses developed.

The findings indicate that both information and service quality influence higher education students’ trust directly and positively in ChatGPT, satisfaction, and continuance usage intention. Moreover, a balance between information quality and service quality can increase students’ level of trust in ChatGPT, satisfaction, and intention to continue using it. Nevertheless, a significant incongruity between information quality and service quality will likely reduce trust in ChatGPT, satisfaction, and the intention to continue using the service.

This research is one of the first to offer a shred of empirical evidence about how information quality and service quality interact congruently and incongruently with each other to trigger higher education students’ trust in ChatGPT, satisfaction, and continuance usage intention of ChatGPT. It thus offers valuable insights for leveraging the benefits and mitigating potential challenges associated with adopting this innovative technology in educational settings.

This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.

The purpose of this study is to identify the key barriers to the adoption of blockchain technology (BCT) in the construction industry. This investigation seeks to understand the challenges that hinder the implementation of blockchain in this sector.

The study begins with a comprehensive review of relevant literature to identify the main barriers to blockchain adoption in construction. It then uses an integrated approach using total interpretive structural modeling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement to investigate the interrelationships among these barriers. In addition, the decision-making trial and evaluation laboratory (DEMATEL) method is used to establish cause-and-effect relationships between the identified barriers.

The study’s integrated TISM and DEMATEL methodology reveals several crucial barriers to blockchain adoption in the construction industry, including regulatory uncertainty, data privacy and security concerns, limited knowledge and expertise and dependence on blockchain operators. It also identifies scalability issues, uncertain benefits and lack of collaboration as dependent barriers, influenced by other identified barriers.

This study contributes original value by applying an integrated methodological approach to understand the complex interrelationships and dependencies among barriers to blockchain adoption in the construction industry. The findings provide decision-makers with insights to prioritize and effectively manage the key driving barriers, enhancing the understanding and strategic planning for blockchain implementation in this sector.

This study aims to use social media data mining to revitalize and support existing urban infrastructure monitoring strategies by extracting valuable insights from public opinion, as current strategies struggle with issues such as adaptability to changing conditions, public engagement and cost effectiveness.

Twitter messages or “Tweets” about public infrastructure in the Philippines were gathered and analyzed to discover reoccurring concerns in public infrastructure, emerging topics in public debates and the people’s general view of infrastructure services.

This study proposes a topic model for extracting dominating subjects from aggregated social media data, as well as a sentiment analysis model for determining public opinion sentiment toward various urban infrastructure components.

The findings of this study highlight the potential of social media data mining to go beyond the limitations of traditional data collection techniques, as well as the importance of public opinion as a key driver for more user-involved infrastructure management and as an important social aspect that can be used to support planning and response strategies in routine maintenance, preservation and improvement of urban infrastructure systems.

The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.

A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.

It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.

This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.

Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.

This paper analyzes the differential experiences of women in the Canadian labour market who hold lower-skilled jobs and have school-age children during two waves of Covid compared with more typical conditions pre-pandemic. The article seeks to test the hypothesis that workers at the intersection of womanhood, motherhood and precarious employment would endure even more disadvantageous labour market outcomes during the Covid pandemic than they did prior to it.

We employ a Gender-Based Plus (GBA+) and intersectionality lens to examine the differential effect of Covid on the effect of the trifecta of being a woman in a lower-skilled job and facing a motherhood penalty from school-age children. We use a Difference-in-Difference framework with Canadian Labour Force Survey (LFS) data to examine the differential effect of two waves of Covid on three labour market outcomes: employment, hours worked and hourly wages.

We find that being a woman in a lower-skilled job with school-age children is associated with lower employment, hours worked and wages in normal times compared to males in those same situations. Such women also face the most severe adjustment consequence from the Covid shock, with that adjustment concentrated on the margin of employment and restricted to the First Wave and not the subsequent Omicron Wave.

The paper studies a specific intersectional group, assesses pre-pandemic, peak-pandemic and late-pandemic differences in labour market outcomes and runs separate estimations for different job skill levels. We also study a more comprehensive list of labour market outcomes than most studies of a similar nature.

This paper aims to explore the unintended effect of socially responsible human resource management (SRHRM) on employee task performance via three components of role stress: role conflict, role ambiguity and role overload.

Data was collected from 360 employees who were working in companies in the south of Vietnam and the study hypotheses were tested using structural equation modelling (SEM).

The results indicate that SRHRM increases role conflict, role ambiguity and role overload, which negatively affect employee task performance.

The key practical implication of our study is that SRHRM may decrease employee task performance via role conflict, role ambiguity and role overload. Managers should be aware of these findings and devise a plan to reduce the role stress that results from implementing SRHRM.

This study provides empirical evidence of the destructive consequences of SRHRM and contributes to a more complete perspective of how SRHRM affects employee performance.

This paper aims to investigate whether official development assistance (ODA) inflows to developing countries (lower-middle and low income) can cause the symptoms of Dutch disease or not.

This study applies the methodology of dynamic panel data estimation with a one-step system generalized methods of moment (GMM) for the sample of 59 developing countries from 2001 to 2019.

The results indicate that ODA (as a percentage of gross domestic product (GDP)) rises by 1%, the real effective exchange rate (REER) appreciates by 0.252%. This finding reveals that these selected developing countries have faced the symptoms of Dutch disease. The countries with the higher ODA ratio have a higher effect of the Dutch disease, and the managed floating exchange rate regime is the lowest impacted, when compared to the fixed and flexible exchange rate.

The selected countries are recommended to use ODA inflows right and efficiently. These ODA inflows should be invested in productive sectors or support for production rather than in consumption. The managed float exchange rate regime is applied to reduce the symptom of Dutch disease for the selected countries. The good cooperation of monetary and fiscal policies is important to absorb the huge ODA inflow and sterilize the adverse effects of the disease.

The paper contributes to the literature and empirical of the Dutch disease. An adverse effect of the huge ODA inflow to the developing countries appreciated of the real exchange rate and caused the symptom of the dutch disease.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0777

M-wallets have emerged as one of the most important financial innovations of the 21st century, enabling users to carry digital cash by securely storing payment methods on their mobile devices. However, the continued use of m-wallets varies among people for several reasons. This study used the technology continuation theory (TCT), gamification and trust factors to examine the variables affecting consumers' intentions to continue using mobile wallets.

The SmartPLS partial least squares software was used to analyze data from 431 m-wallet users in Vietnam using the structural equation modeling technique.

The data revealed that the research model can predict users' intentions to continue using mobile wallets. TCT constructs demonstrated strong exploratory power in explaining consumer satisfaction and attitudes towards m-wallets. Furthermore, the study confirmed the direct effect of the perceived effectiveness of gamification on perceived ease of use and attitude, as well as its indirect effect on consumers' continued use intentions of mobile wallets via attitude. In addition, the trust negatively influenced consumers' intentions to continue using m-wallets.

The findings of this study can help researchers, practitioners and policymakers improve m-wallet design, development and adoption, as well as advance financial technology and define the future of digital payments in terms of consumer attraction, engagement and financial inclusion.

Based on TCT theory, this study enriches m-wallet research by examining two important factors, gamification and trust, and thus provides insights into how to improve consumers’ intentions to continue using m-wallets in developing countries. This study offers timely insights into theory and practice regarding these factors. It therefore paves the way for researchers and practitioners to learn how easy, enjoyable and secure the end-user experience should be to keep users engaged with m-wallets.

This research paper aims to examine the influence of greater female participation on the board of directors on the environmental transparency of companies.

To achieve the purpose of this study, the authors analyzed the environmental transparency of 412 companies in the energy sector, headquartered in 19 countries, during a four-year period (2016 to 2019).

The data reveal that gender diversity has a positive effect on the environmental transparency of companies in developed countries and on the total model. Furthermore, after removing the US companies, the results remained the same, indicating that companies with more women on the board tend to have greater environmental transparency. Regarding corporate governance variables, the results show that companies that have a corporate social responsibility committee tend to have greater environmental transparency, both in emerging countries and in developed countries.

The findings indicate that if companies aim to have greater environmental transparency, they must encourage female participation on boards, giving them equal opportunities for professional growth. Organizations must deconstruct the ideology that women are fewer valuable members of their boards, which limits their contribution to organizational success. Additionally, regulators can encourage greater female participation on boards through the implementation of quota laws.

The authors’ evidence indicates that the presence of women on board is an antecedent of greater quality in the dissemination of environmental information. Thus, managers of companies in the energy sector must understand that diversity on the board affects communication with its stakeholders through environmental transparency.