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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

This paper aims to examine the impact of bank managerial ability on the cost of loans using an extensive data set of US banks from 2001:Q1 to 2021:Q2.

First, the authors use multiple fixed-effects estimation to estimate the impact of managerial ability on bank loan pricing. In addition, the authors also perform different econometrics regression methods to test the robustness of the model including: Prais–Winsten regression, Newey–West regression and the Fama McBeth method, instrumental variable regression, propensity score matching method and quantile regression.

The results show that banks with higher managerial ability tend to provide loans with lower costs, and this effect is stronger at larger banks. In addition, research results from the quantile regression model show that the negative impact of managerial ability on the cost of loans will be stronger at banks with higher lending costs.

To the best of the authors’ knowledge, this study is one of the first to investigate this relationship between managerial ability and bank loan pricing from the supply side. In addition, this paper examines the impact of bank managerial ability on the loan costs of banks of different sizes, as well as differs across the distribution of the dependent variable. Therefore, this paper is of particular interest to regulators and policymakers.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

Over energy consumption is one of the causes of global warming and climate change. To deal with this issue, using energy-efficient appliances is strongly encouraged and cultivating consumer loyalty toward energy-efficient appliances is crucial for long-term sustainability. This study investigates the effects of multiple dimensions of perceived value on consumer satisfaction and three outcomes of consumer loyalty (i.e. willingness to pay a premium, repurchase intention and word-of-mouth intention), considering the moderating role of the product category.

Quota sampling based on age and gender and snowball sampling methods were applied to recruit 423 participants for this study. A combination of partial least squares structural equation modeling (PLS-SEM), importance-performance map analysis (IPMA) and necessary condition analysis (NCA) was employed to examine the proposed model.

Functional, price, emotional and environmental values positively impact consumer satisfaction, enhancing the three dimensions of consumer loyalty. The product category moderates the effects of perceived value dimensions on consumer satisfaction. Moreover, the IPMA results highlight that functional value and environmental value are the most essential but underperforming value attributes. The NCA results indicate that social value is a necessary condition for consumer satisfaction.

This study is one of the pioneers in integrating PLS-SEM, IPMA and NCA approaches to comprehensively unpack the relationships between perceived value dimensions, consumer satisfaction and consumer loyalty in the context of energy-efficient appliances. The findings offer theoretical and practical importance for academics, retailers, producers and policymakers to encourage consumer loyalty toward energy-efficient appliances.

This study aims to reveal the impact mechanism of franchisor-owned resources, franchise relationship quality and franchisee's dynamic capabilities on franchisee performance, with the moderating role of cultural sensitivity.

The sample consisted of 290 middle managers and team leaders at 113 hotels and food and beverage settings participating in the international- and domestic franchises in Ho Chi Minh City, Vietnam. A partial least squares structural equation model (PLS-SEM) is used to analyse the data.

The result reveals that franchisor-owned resources, franchise relationship quality and franchisee's dynamic capabilities significantly impacted franchisee performance. Furthermore, cultural sensitivity has a beneficial role in the effect of franchise relationship quality on franchisee performance.

This study develops an integrated analytical framework of franchisee performance from the franchisee's perspective, contributing to integrating international business theory in franchising studies, namely the resource-based view, dynamic capability view and relationship-marketing theory.

While the application of blockchain technology in the organic food supply chain has been increasingly recognized, the extant knowledge of how blockchain-driven traceability influences consumer perceptions and purchase intentions remains underexplored. Grounded in the stimulus-organism-response theory, this study aims to construct a moderated mediation model to examine blockchain-enabled traceability’s direct and indirect impacts on organic food purchase intention through perceived blockchain-related information transparency, considering the moderating role of blockchain-based trust.

A purposive sample of 5,326 Vietnamese consumers was surveyed using the PROCESS macro to test the proposed hypotheses.

The findings indicate that blockchain-enabled traceability significantly enhances perceived blockchain-related information transparency, which positively influences organic food purchase intention. Furthermore, blockchain-based trust was found to positively moderate both the direct effect of transparency on purchase intention and the indirect impact of traceability on purchase intention through transparency.

Practical and managerial insights for stakeholders in the organic food sector are also discussed.

These results contribute to the literature by extending the stimulus-organism-response model to the context of blockchain technology in supply chains and highlighting the critical role of trust in moderating the effectiveness of technological innovations.

This research aims to investigate how organisational and contextual factors affect supply chain collaboration and how that, in turn, influences firms' competitive advantage in the garment industry in the context of Vietnam, a developing country.

Following a qualitative research design, in-depth interviews were conducted with senior managers who are involved in supply chain collaboration in twelve garment companies in Vietnam. The data were recorded, transcribed and analysed using NVivo 12. Based on the literature and interview findings, a research model underpinned by the relational view (RV) and institutional theories, with organisational and contextual factors being the antecedents and competitive advantage as the outcome of supply chain collaboration, was proposed.

The findings showed that organisational and contextual factors induce both internal, supplier and customer supply chain collaboration. There is also a positive relationship between supply chain collaboration and competitive advantage. Based on these findings, a strategy matrix for supply chain collaboration is also put forward.

This is one of the first empirical attempts to investigate the role of organisational and contextual factors as potential antecedents of supply chain collaboration and its effects on competitive advantage in the garment industry. The research is expected to enrich both the literature and management practices on supply chain collaboration in the context of developing countries.

Travel destinations worldwide are seeking smart ways to reduce the negative impact of tourism, and the public bike rental service (PBRS) is one of them. To investigate the usage intention of this service among visitors, the author of this research employs an integrated approach consisting of two psychological frameworks: the Norm Activation Model (NAM) and the Technology Acceptance Model (TAM).

The integrated NAM-TAM model is implemented to conduct a survey (sample n = 777) with visitors to Hanoi, Danang, and Ho Chi Minh City regarding the factors underlying their intentions to continue using the PBRS TNGo.

Structural equation models suggested that: (1) the NAM-TAM can explain behavioural intention to use a smart PBRS. Perceived Usefulness (PU), Perceived Ease of Use (PE), and Awareness of Consequences (AC) have positive and significant impacts on Attitude Towards Using (AT) and, thus, on Behavioural Intention to Use (BI). Also, Personal Norms (PN) positively influence BI. (2) Among the four independent variables, tourists' AC produces the most potent effect on the intention to continue using a PBRS.

This study can start a new research direction of combining the NAM with other theoretical frameworks to explain customer behaviour in the field of sustainable tourism practices. Future research should explore the proposed model based on comparisons of different tourists’ backgrounds, including nationality, length of stay, spending level, visiting purpose, etc.

This research provides strategic implications for destination management organisations in boosting the use of PBRS amongst tourists, contributing to the environmental sustainability targets of the tourism industry.

This study responds to the existing gap by examining both functional value (indicated by PU and PE) and perceived environmental/social value (proxied by AC) in forming tourists’ attitudes towards PBRS and their usage intention. Our study, therefore, actively contributes to the research stream of tourist behaviour in the field of sustainable tourism practices from the altruistic behavioural perspective.

This study explores the effects of gender and participation in agricultural cooperatives on biodiversity conservation farming practices in vegetable production.

This study used data collected from a survey of 627 vegetable farmers in Viet Nam and employed the Ordered Probit regression model to examine the effects of gender and participation in agricultural cooperatives on biodiversity conservation farming practices.

We find that female vegetable farmers are more likely to conduct biodiversity conservation farming practices than male farmers. This gender difference is, however, removed when participation in agricultural cooperatives is controlled, suggesting that agricultural cooperatives effectively facilitate biodiversity conservation farming practices.

It is noted that our study is not free from some limitations. First, we conducted our study on vegetable farmers only. The biodiversity conservation practices in vegetable cultivation might be different from other types of farming. Future studies should be conducted with other types of agricultural cultivation. Second, we do not have enough data to explain why female farmers are more likely to adopt biodiversity conservation practices than male farmers. Future studies should capture biological and social aspects of gender differences to address this limitation.

This study contributes to the literature on biodiversity conservation by presenting empirical evidence on the effects of gender and agricultural cooperatives. Participation in agricultural cooperatives is revealed to facilitate the adoption of biodiversity conservation practices. In addition, we find that the education of farmers, the number of years that farmers have been living in the local area and the quality of land and water are positively related to the adoption of biodiversity conservation practices in vegetable production.