As environmental pollution and natural resource depletion are seriously threatening human beings’ well-being, consumers’ concern about environmental issues has substantially increased. Accordingly, increasing consumers consider themselves to be environmentalists and support environmental protection by consuming green products. In response, more and more firms follow the popular trend by conducting green marketing practices. As a result, green markets are demonstrating greater growth compared to conventional markets these days. On the other hand, advances in artificial intelligence (AI) and robotics are transforming the way of consumer-firm interactions in various industries including the green industry. More and more industries and firms adopt AI agents to replace or assist human employees. Deposit the pervasive and rapid nature of the transformation, however, we have limited knowledge of how the transformation of consumer-firm interaction influences green product marketing practices. Accordingly, the current research aims to investigate how the adoption of AI agents in green marketing strategies impacts consumers’ responses and further explore which mechanism underlying the process. To examine our hypotheses, we conducted a series of studies, and we collected the data through an online survey platform. Our findings demonstrated that consumers’ reaction was sufficiently different when they interact with AI agent compared to human agent in a green consumption context. Our findings contribute to enriching prior literature on green and AI by integrating each other and also provide practical implications for marketers in the related industries.

PURPOSES : The actual service life of repair methods applied to cement concrete pavement is analyzed based on de-icing agent usage. METHODS : Highway PMS data pertaining to de-icing agent usage are classified into three grades: low (1~5 ton/lane/year), medium (5~8 ton/lane/year), and high (greater than 8 ton/lane/year). The repair methods considered include diamond grinding, patching, joint repair, partial depth repair, and asphalt overlay on five major highways. The service life of each repair method is analyzed based on the usage level of the de-icing agent. RESULTS : The service lives of the applied repair methods are much shorter than expected. It is confirmed that the service life afforded by diamond grinding, patching, and joint repair methods are not significantly affected by the use of de-icing agents, whereas that afforded by asphalt overlay and partial depth repair methods is affected significantly. The service life afforded by the asphalt overlay and partial depth repair methods decreases at high usage levels of the de-icing agent (greater than 8 ton/lane/year). CONCLUSIONS : Among the repair methods considered, the service life afforded by partial depth repair and asphalt overlay is affected significantly by the amount of de-icing agent used. Additionally, the differences between the expected and actual analyzed service lives should be considered in the next-generation maintenance strategy for cement concrete pavements.

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.