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This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

Supplier segmentation provides companies with suitable policies to control each segment, thereby saving time and resources. Sustainability has become a mandatory requirement in competitive business environments. This study aims to develop a clustering-based approach to sustainable supplier segmentation.

The characteristics of the suppliers and the aspects of the purchased items were considered simultaneously. The weights of the sub-criteria were determined using the best-worst method. Then, the K-means clustering algorithm was applied to all company suppliers based on four criteria. The proposed model is applied to a real case study to test the performance of the proposed approach.

The results prove that supplier segmentation is more efficient when using clustering algorithms, and the best criteria are selected for sustainable supplier segmentation and managing supplier relationships.

This study integrates sustainability considerations into the supplier segmentation problem using a hybrid approach. The proposed sustainable supplier segmentation is a practical tool that eliminates complexity and presents the possibility of convenient execution. The proposed method helps business owners to elevate their sustainable insights.

Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic.

The total emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) were estimated using the SPD-GIZ emission calculation model.

The results show that CO₂ has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity.

The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26.

In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) using a method combining both top-down and bottom-up approaches.

Tourism is one of the most notable features of the contemporary globalised world. The tourism industry is becoming increasingly vital to the economy of many developing and developed countries around the globe. The demand of the tourism industry has posed a challenge for tourism training providers to move towards a more responsive and internationalised curriculum to enhance work readiness for tourism graduates who are expected to work with an increased number of international tourists. The purpose of this paper is analyse whether and how internationalisation has been implemented in the tourism training programmes across six institutions in Vietnam.

The research deployed case studies as research strategy with interviews and document analysis as two instruments of data collection.

The major findings show that even though the tourism industry demands graduates to possess global competency, knowledge and skills, the curriculum does not prioritise the internationalisation dimensions and the faculty members are not facilitated to be internationally active in their roles. Overall, internationalisation is still fragmented and ad hoc in these institutions even though the private institutions in this research appear to be more responsive to the trend of internationalisation in education than their public counterparts.

The paper provides recommendations on how to effectively embed internationalisation components into local tourism training programs in Vietnam.

The research bridges the gap in the literature on internationalisation of the local tourism programme in non-English-speaking countries.

The purpose of this paper is to analyse the determinants of the saving behaviour of Vietnamese households and to explore the possible heterogeneity of household saving propensities.

The authors estimate the effects of household characteristics on Vietnamese household saving rates by means of a quantile regression approach using the Vietnam Household Living Standard Survey 2010 data set.

The results suggest that the way household characteristics influence saving rates is different for each quantile of the household saving rate distribution. Household characteristics tend to have stronger effects at lower quantiles. Particularly, the marginal propensity to save of households at low quantiles is higher than those at high quantiles. Analysing rural and urban households separately, the authors find evidence that household and household head characteristics have stronger significant effects for rural than for urban households. Children and elderly members should be treated as part of the household labour force, instead of household dependency, since both of them increase household saving rates.

This research contributes to the literature on Vietnamese household saving behaviours, especially for households living in urban areas.