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This study aims to investigate whether the extent of corporate disclosure, proxied by COVID-19-related disclosure, affects the dividend policy of listed firms.

The study uses a multinomial logistic regression model to examine the relation between corporate disclosure and the dividend policy of the 100 largest market-cap firms in Vietnam in 2021. The COVID-19 pandemic, with its unique impact on business operations, serves as the backdrop for this analysis.

The findings indicate that firms with more extensive COVID-19-related disclosure are more inclined to distribute dividends in the form of stocks or cash instead of omitting them.

This research contributes to the understanding of how corporate disclosure practices influence a firm’s financial decisions, particularly in the context of the COVID-19 pandemic. The findings hold implications for corporate financial decision-making during times of macroeconomic shock.

The process of predicting construction costs and forecasting price fluctuations is a significant and challenging undertaking for project managers. This study aims to develop a construction cost index (CCI) for Jordan’s construction industry using fuzzy analytic hierarchy process (FAHP) and predict future CCI values using traditional and machine learning (ML) techniques.

The most influential cost items were selected by conducting a literature review and confirmatory expert interviews. The cost items’ weights were calculated using FAHP to develop the CCI formula.

The results showed that the random forest model had the lowest mean absolute percentage error (MAPE) of 1.09%, followed by Extreme Gradient Boosting and K-nearest neighbours with MAPEs of 1.41% and 1.46%, respectively.

The novelty of this study lies within the use of FAHP to address the ambiguity of the impact of various cost items on CCI. The developed CCI equation and ML models are expected to significantly benefit construction managers, investors and policymakers in making informed decisions by enhancing their understanding of cost trends in the construction industry.

Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.

A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.

The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.

By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.

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.

This study's main goal is to explore how small and medium-sized enterprises (SMEs) in the food as well as beverage (F&B) area should evolve to survive in a bustled post-pandemic future.

Drawing on the knowledge-practice gap in the field of Entrepreneurial Orientation (EO) as well as Business Model Innovation (BMI), this study examines an integrated framework using the F&B sector as an empirical field of research. This study uses an empirical quantitative approach using the main information aggregated from a questionnaire administered during the study. The sample had 467 valid responses (71.08% response rate). This paper uses the Partial-Least Squares Structural Equation Model (PLS-SEM) to examine structural relationships because this technique is usually proposed for models with complex relations.

According to the research EO is directly and indirectly, correlated with BMI. The correlation is positive and significant. Simultaneously, corporate social responsibility (CSR) is partially mediated in the stated relation between EO as well as BMI, and CETA where it shows a positive moderation part in EO's influence on CSR. In particular, it elucidates how EO promotes CSR and BMI, alongside moderating part of circular economy principles adoption (CEPA).

These research findings suggest that SMEs in the F&B sector should transform the way they traditionally manage their businesses by applying circular economic principles into entrepreneurial orientation to promote CSR-based practices and acquire the resources obtained from internal and external stakeholders. Hence, their business can recover from post-pandemic effects and become resilient to future disruptions. Furthermore, this study suggests that adopting circular economy principles provides a key source of knowledge and insights that allows firms to sharpen their entrepreneurial orientation toward incorporating stakeholders and social environmental concerns into business models for sustainability, especially in the uncertain and drastic changing environment.

This study proposes a novel approach by which BMI is formed and evolved based on circular economy principles-oriented entrepreneurship and the synergies of stakeholders through undertaking corporate social responsibility practices. Drawing from the knowledge-practice gap, this research adds to the existing knowledge about EO as well as BMI with a conceptualized and operationalized empirical framework in a novel context that was not covered in current literature, especially in the context of uncertainties and disruptions experienced during COVID-19 outbreaks. The F&B sector was hit and how it should evolve to recover and build resilience is perceived as an urgent issue.

Several factors influence the costs of buildings. Thus, identifying the cost significant factors can assist to improve the accuracy of project cost forecasts during the planning phase. This paper aims to identify the cost significant parameters and explore the potential for improving the accuracy of cost forecasts for buildings using machine learning techniques and large data sets.

The Australian State of Victoria Building Authority data sets, which comprise various parameters such as cost of the buildings, materials used, gross floor areas (GFA) and type of buildings, have been used. Five different machine learning regression models, such as decision tree, linear regression, random forest, gradient boosting and k-nearest neighbor were used.

The findings of the study showed that among the chosen models, linear regression provided the worst outcome (r² = 0.38) while decision tree (r² = 0.66) and gradient boosting (r² = 0.62) provided the best outcome. Among the analyzed features, the class of buildings explained about 34% of the variations, followed by GFA and walls, which both accounted for 26% of the variations.

The output of this research can provide important information regarding the factors that have major impacts on the costs of buildings in the Australian construction industry. The study revealed that the cost of buildings is highly influenced by their classes.

The purpose of the article is to contribute to the body of research on digital transformation among members of the supply chain operating in an emerging economy. This paper researches the digital transformation trends happening across Vietnamese supply chains, by investigating the current adoption rates, predicted impact levels and financial investments being made in key Industry 4.0 technologies.

By using a semi-structured online survey, the experiences of 281 supply chain professionals in Vietnam were captured. Subsequently, statistical techniques examining variances in means, regression analysis and Monte Carlo simulation were applied.

The findings of this study offer a comprehensive understanding of Industry 4.0 technology in Vietnam, highlighting the prevalent technologies being prioritized. Big data analytics and the Internet of things are expected to have the most substantial impact on businesses over the next 5–10 years and have received the most financial investment. Conversely, Blockchain is perceived as having less potential for future investment. The study further identifies several technological synergies, such as combining advanced robotics, artificial intelligence and the Internet of things to build effective and flexible factories, that can lead to more comprehensive solutions. It also extends diffusion of innovation theory, encompassing investment and impact considerations.

This study offers valuable insights into the impact and financial investment in Industry 4.0 technologies by Vietnamese supply chain firms. It provides a theoretical contribution via an extension of the diffusion of innovation theory and contributes toward a better understanding of the current Industry 4.0 landscape in developing economies. The findings have significant implications for future managerial decision-making, on the impact, viability and resourcing needs when undertaking digital transformation.

This paper aims to determine the significance of tourist walkability on three community-based tourism sustainability indicators, namely, the economic, social and environmental benefits and costs impacting community’s quality of life through the lens of the triple bottom line approach with the institutional theory.

This study views institutions as either enabling or restricting the sustainable community-based tourism because institutions influence resource integration and value assessment by the beneficiary. Moreover, institutions also lead the co-creation of sustainable community-based tourism among various stakeholders. Drawing on this conceptualisation, the notion of sustainable community-based tourism is filtered through the lens of institutional theory. Thus, this work approaches sustainable community-based tourism as a dynamic process of co-creating a tourist destination formed by different actors’ and institutions within the ecosystem of the tourist destination. Meanwhile, the triple bottom line benefits and costs experienced by the overall community would produce net effects on the residents’ perceptions of sustainable tourism.

This paper classifies both tangible and intangible costs and benefits because of tourist walkability and its triple bottom line trade-offs experienced by tourists and residents. This paper penetrates new grounds by reviewing the triple bottom line impacts of tourist walkability on residents’ quality of life. Government policies as mediating variable and national culture and individual personalities of tourists and residents as moderating variables were discussed. A conceptual framework named Tourist Walkability Sustainable Tourism Impact on Residents (TWSTIR) is proposed. Finally, a Sustainable Community-based Tourism Strategic (SCBTS) model which is based on the two dimensions of intensity of tourist walkability and residents’ quality of life is proposed.

Research limitations may include a lack of assessment on political, technological and legal issues, and therefore, future research is warranted in these three areas. Some emotions and attitudes of the residents may not be captured since the Gross National Index (Gross National Happiness) may have its inherent blind spots.

This paper would be of interest to the scholarly world, as its original idea and concluding research agenda are burrowing into a new sub-field of tourism research. In view of growth and degrowth of sustaining community-based tourism, the SCBTS model is presented to provide directions for tourism policymakers and entrepreneurs to formulate and implement appropriate strategy for the tourist walkability activity per se and investment in the accompanying infrastructure.

This paper also presents the sacrifices and inequities in the communities and the relevance of government policies, national culture and individual personalities of tourists and residents, in which the attention of tourism policymakers and the communities that thrive on the travel and tourism industry should not be neglected.

The idea and discussion of this paper is original. This paper burrows into a new sub-field of tourism research. Tourist walkability needs more attention from the scholars, as this tourist activity can have positive and negative effects on residents’ quality of life. The TWSTIR framework is developed to discuss the relationships of tourist walkability, triple bottom line concept and residents’ quality of life within the sustainable community-based tourism scope. The SCBTS model is presented for tourism policymakers and entrepreneurs to perform appropriate strategy for the tourist walkability activity and investment in the accompanying infrastructure.

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.

This study aims to present the results of a comparative study on the most key reasons for the failure of sustaining activities of operational improvement (OI) methodologies from the different types of manufacturing enterprises that located in Vietnam.

This study presents survey results from 30 local manufacturing enterprises and 21 foreign direct investment (FDI) enterprises located in Vietnam – a developing country. The authors utilize a combination method to collect data, including online and direct survey. The targeted interviewees selected to answer the questionnaire are manufacturing managers and top managers working in productivity, quality, engineering and other departments in respective firms. The developed questionnaire is verified by five experts to ensure the validity and soundness.

The study uncover that 21 local enterprises (70%) have not issued standard forms for OI deployment and supervision, while 17 foreign enterprises (81%) have adopted a systematic management and clearly indicators for evaluation of OI outputs. In addition, the top three reasons for OI failure are differences between local and foreign enterprises. In term of OI methodologies, most of participated enterprises implemented Lean tools and principles while only 7.8% of the participated enterprises applied Six Sigma. Three vital findings are uncovered, including, first, 30% of local enterprises standardize and supervise forms of OI.

There is a limitation in sample size, with the number of participants of 51 enterprises. Among the participants, 27% of local enterprises are small and medium-sized enterprises (SMEs) while 60% of FDI enterprises from large-sized group. This was limited to making a generated conclusion in the comparison of failure factors between two types of enterprises. This partly affects the radical comparison of failure factors between local and FDI enterprises.

To the best of the authors' view, this is the first empirical study that compares the reasons for the failure for sustaining OI between local and foreign enterprises in a developing country. The result from this study will make contributions for further research in considering OI failure factors and then enhance effectiveness of OI methodologies in manufacturing companies.