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The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.

Studies on the Transit-Oriented Development (TOD) for Bangkok are found sparingly. The TOD concept is a supportive development for the rapidly changing city in order to reduce urban transport problems while encouraging people to shift transport modes to use public transportations instead of private cars. This study discusses the context of TOD in the density, the design, and the diversity of land use around transit stations among successful stations in many countries. There were 18 station areas in Bangkok which, by using the TOD Readiness score, the assessment of the stations implies that the higher scoring transit stations are more compatible to supporting pedestrian use of the transit station with lower car dependency. The 4 top-scoring stations were assessing by using multinomial logistic regression model. The study has found TOD scores and the frequent uses of the stations consequently encourage the commuters around the station areas decided to rely on public transport instead of car dependency. This is an effort to overcome the understanding of the station areas by reducing the complexity of the TOD contexts to any transit station in Thailand to be eligible for future study.