We explored the moderating impacts of product modularity and supply chain visibility for sustainability and operational initiatives, which entails a dramatic rethinking and reorganization of the production processes of manufacturing enterprises. Moderating effects of product modularity and supply chain visibility on links among supply chain pressure, technological pressure, sustainable practices, operational performance, and sustainability performance were included. A conceptual model was developed following the resource-based view and dynamic capability theories. Well-designed questionnaires collected data, and the total sample size for data analysis was 490 responses from small- and medium-sized manufacturing firms in Pakistan. Structural equation modeling was used to examine the proposed hypothesis. The first finding revealed that operational performance and sustainable performance both improve when companies implement sustainable practices. The second finding drawn from the data was that supply chain pressure and technological pressure have a positive effect on sustainable practices. The major finding of this work was grounded in the product modularity perspective, we argue that the relations among supply chain pressure, technological pressure, sustainable practices, operational performance, and sustainability performance are affected and moderated. The moderating effect of supply chain visibility existed and it has a positive moderating effect for the relationships from sustainable practices toward operational and sustainability performance. Surprisingly, moderating impact of visibility on relations from supply chain pressure and technological pressure towards sustainable practices was not significant.

The advantages of UAV video in flexibility, traceability, easy-operation, and abundant information make it a popular and powerful aerial tool applied in traffic monitoring in recent years. This paper proposed a systematic approach to detect and track vehicles based on the YOLO v3 model and the deep SORT algorithm for further extracting key traffic parameters. A field experiment was implemented to provide data for model training and validation to ensure the accuracy of the proposed approach. In the experiment, 5400 frame images and 1192 speed points were collected from two test vehicles equipped with high-precision GNSS-RTK and onboard OBD after completion of seven experimental groups with a different height (150 m to 500 m) and operating speed (40 km/h to 90 km/h). The results indicate that the proposed approach exhibits strong robustness and reliability, due to the 90.88% accuracy of object detection and 98.9% precision of tracking vehicle. Moreover, the absolute and relative error of extracted speed falls within ±3 km/h and 2%, respectively. The overall accuracy of the extracted parameters reaches up to 98%.

There have been many implementations of carbon credit incentives (CCIs) for promoting green travel, but research on quantifying the effectiveness remains limited. To fill this gap, this study focuses on residents’ daily transportation mode choices under the incentive of carbon credits by employing an integrated choice and latent variable (ICLV) model to adequately address the role of attitudinal variables related to carbon credits, such as perceived usefulness, perceived ease of use, and behavioral intentions. Data from a questionnaire survey show that the ICLV model provides a richer and more nuanced understanding of the green mode choice than a traditional multinomial logit (MNL) model, where the AIC value of the ICLV model (3901.17) is smaller than that of the MNL model (3910.09). Carbon credits exhibit diverse impacts across various modes of eco-friendly transportation and specific demographic groups. Commuting trips reveal noteworthy positive associations between carbon credits and the use of bicycles as well as metro/bus services. Moreover, carbon credits exert a more pronounced influence on individuals with higher education levels, older age groups, and owners of new energy vehicles, whereas their impact on high-income individuals is relatively constrained. Furthermore, perceptions of carbon credits are pivotal, with perceived utility emerging as the most influential factor. The results provide a scientific basis for formulating more effective policies regarding carbon credit and incentive measures in the future.