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The paper aims to provide an efficient dispatching schedule for ready-mix concrete (RMC) trucks and create a balance between batch plants and construction sites.

The paper focused on developing a new metaheuristic swarm intelligence algorithm using Java code. The paper used statistical criterion: mean, standard deviation, running time to verify the effectiveness of the proposed optimization method and compared its derivatives with other algorithms, such as genetic algorithm (GA), Tabu search (TS), bee colony optimization (BCO), ant lion optimizer (ALO), grey wolf optimizer (GWO), dragonfly algorithm (DA) and particle swarm optimization (PSO).

The paper proved that integrating GWO and DA yields better results than independent algorithms and some selected algorithms in the literature. It also suggests that multi-independent batch plants could effectively cooperate in a system to deliver RMC to various construction sites.

The paper provides a compelling new hybrid swarm intelligence algorithm and a model allowing multi-independent batch plants to work in a system to deliver RMC. It fulfills an identified need to study how batch plant managers can expand their dispatching network, increase their competitiveness and improve their supply chain operations.

This study aims to examine the determinants of Generation Z's intention to support sustainable development in tourism, with a focus on Nha Trang, Vietnam (a coastal city with famous tourism activities).

The study was conducted with an aid of SPSS 20.0 and SmartPLS 4.0 softwares to analyze the data collected from 394 valid respondents in Ho Chi Minh City through a cross-sectional method with a self-administered survey.

Empirical evidence revealed that sustainable tourism attitude, sustainable tourism belief and perceived sustainable destination image positively influenced Generation Z's support intentions toward sustainable tourism. In addition, perceived sustainable destination image also indirectly impacted intention to support sustainable tourism through the sustainable tourism attitude and/or belief (both single and sequential mediations).

This is among pioneering studies to figure out that knowledge negatively moderated the relationship between sustainable tourism attitude and intention to support sustainable tourism.

The paper is aimed at examining the mediating role of action and coping plans in reducing intention-behaviour gap as a function of underlying perceived self-efficacy [action self-efficacy (ActS) and coping self-efficacy (CopS)] in organic food (OF) consumption.

A cross-sectional study was designed to examine the moderating role of perceived self-efficacy in the intention–plans–behaviour relationship. To test the theoretical framework, data from 453 valid questionnaires were recruited in Hanoi (Vietnam) and were analysed to test validity and reliability before being evaluated for hypothesis testing by Smart-PLS 4.0.

The results indicate that action and coping plans have significant positive effects on the relationship between intention and behaviour. CopS has a significant positive effect on the two paths of the intention-coping plan-behaviour mediation, whereas action plan (AP) has merely a significant positive link to the intention-AP path.

There are several limitations of the paper, including a small and undiversified-characteristic sample and general OF.

The findings of the study make recommendations for marketers to boost OF consumption in Vietnam.

This is the first study to examine a dual-moderated mediation model in narrowing the intention-behaviour gap, especially in the context of OF consumption. Particularly, the notions of plan and self-efficacy are divided into sub-constructs on the basis of different functions and both paths in the intention-plan-behaviour mediation are investigated. AP and coping plan are served as dual mediators, whereas ActS is regarded as moderator for both paths of intention-AP-behaviour link and CopS is examined as moderator for both paths of intention–coping plan–behaviour relationship, providing a holistic mechanism in translating intention into behaviour.

This chapter focuses on the potential of urban agriculture to support progress in SDG targets 2.1, 2.2, 2.3, and 2.4 in Ho Chi Minh City (HCMC), Vietnam. The chapter integrates findings from the British Council-funded project, ‘Urban Resilience from Agriculture through Highly Automated Vertical Farming in the UK and Vietnam’, undertaken in collaboration with Middlesex University, Van Lang University, and local agricultural stakeholders in HCMC. Food security in the city faces multiple challenges ranging from significant in-migration, decreasing area of cultivated land, the impact of the Covid-19 pandemic that continues to depress the economy and disrupt food supply chains, and climate change impacts affecting the environment and people throughout the city. HCMC accommodates a substantial agricultural sector, which is evolving from traditional to modern production practices. City’s leaders established numerous policies that emphasise green, circular economies, climate change resilience, and low carbon emissions fuelling demand for agricultural solutions that integrate traditional and modern technologies that can be embedded in the local topography, soil types, architectural space, and native culture. Findings from greenhouse trials, community awareness surveys, and stakeholder-led workshops point to a range of high-technology-supported agriculture models that, if applied flexibly throughout the varying context of the urban area, have good scope to help Ho Chi Minh City and meet its growing need for food as well as its sustainability aspirations.

This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.

The KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.

The findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.

To connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.

The presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.