The need for effective information systems that can help in efficient transportation management has become essential. This study presents the potential benefits of developing a decision support system used by a trucking company for routing and scheduling. Our study investigates how customer exibility factors affect the utilization of transportation resources and establishes a vehicle scheduling model for better allocation of transportation resources with a time window. The results show vehicle savings from 25% up to 70% per day given different levels of exibility in delivery times. Increased capacity utilization can be achieved by considering only customer exibility in the model. Our study implies that incorporating customer exibility into the information system can help transportation organizations have the capability to gain control over management to cut costs and improve service.

Many retailers have extended their extant online channels (i.e., websites) to mobile channels for communicating with and delivering their products or services to customers. However, retailers have trouble delivering a cohesive and seamless customer experience across the Web and mobile channels. To address this challenge, we propose a way for retailers to enrich customers' seamless experiences across channels by configuring mobile channels (functionality- and interactivity-oriented configurations) along with traditional Web channels. This study theoretically contributes a research framework that posits the role of mobile channels as an extension of existing websites. It also provides practical insight for effectively articulating an e-commerce strategy in cross-channel electronic commerce.

As sensor technologies and image processing technologies make collecting information on users' behavior easy, many researchers have examined automatic emotion recognition based on facial expressions, body expressions, and tone of voice, among others. Specifically, many studies have used normal cameras in the multimodal case using facial and body expressions. Thus, previous studies used a limited number of information because normal cameras generally produce only two-dimensional images. In the present research, we propose an artificial neural network-based model using a high-definition webcam and Kinect to recognize users' emotions from facial and bodily expressions when watching a movie trailer. We validate the proposed model in a naturally occurring field environment rather than in an artificially controlled laboratory environment. The result of this research will be helpful in the wide use of emotion recognition models in advertisements, exhibitions, and interactive shows.

The purpose of marketing via Facebook is to convince consumers to become fans of a brand. Facebook constructs virtual brand communities that enable brand fans to interact with these brands. This study investigates the antecedents and consequences of fan participation characterized by the breadth and depth of brand fans' like, comment, and share activities. An empirical analysis with 204 survey respondents reveals that expected benefits, such as brand information, social interaction ties, playfulness, and incentive, have positive effects on fan participation. Furthermore, fan participation increases fan's attitudinal loyalty, which then positively affects behavioral loyalty. Theoretical and practical implications of the findings as well as future research directions are also discussed.