The Champion of Images: Understanding the role of images in the decision-making process of online hotel bookings

Images are vitally important in interesting consumers and helping them to make decisions. Images of a hotel are particularly important and were used to sell hotels even before the Internet, when travel agencies would often have brochures about hotel properties that they used to entice travelers. On many online travel agency (OTA) websites, the hotel\u27s image can take up 33% of the space on the hotel property page, but the importance of this image in the decision-making process has yet to be studied. For many OTAs, there are currently no quantitative analytic methods that help determine which image to display in this critical location. In this research, we use deep learning to extract information directly from hotel images and we apply image analytics to understand the importance of this information in the online hotel booking process. To provide managerial insights, we will combine a prediction model, with the t-distributed Stochastic Neighbor Embedding (t-SNE) to classify and understand the types of images hotels generally use as their thumbnail or champion image and what aspects of these images elicit consumers to consider and book a hotel

Micro-Level Interactions in Business-Nonprofit Partnerships

While most research on business-nonprofit partnerships has focused on macro and meso perspectives, this paper pays attention to the micro level. Drawing on various theoretical perspectives from both marketing and management, we conceptually relate the outcomes of active employee participation in such partnerships to consumer self-interest. We also explore empirically whether and when self-interest affects consumers’ responses towards firms in relation to business-nonprofit partnerships. The study reveals that self-interest can directly influence consumers’ behavioral responses towards firms (i.e. switching and buying intentions, and word of mouth), whereas the impact on evaluative responses in terms of attitude and trust is only weak. The fit between the firm and the nonprofit partner (company-cause fit) turns out to moderate this effect, with consumer self-interest only playing a role if fit is high. Implications for research and practice are discussed

Return on interactivity: The impact of online agents on newcomer adjustment

As service offerings grow in both range and complexity, how service providers and their customers interact is becoming increasingly important. In response to the challenge of optimizing these interactions, companies have introduced sophisticated online "socialization agents," whose purpose is to help new customers more effectively adjust to and function within the service environment. The objective of these online agents, or virtual employees, is to help customers evaluate new or unfamiliar service offerings, as well as help companies achieve greater levels of service delivery and financial performance. To investigate this, the authors analyze the process by which online agents help both new and current customers adjust to and function within new, unfamiliar, or complex service contexts. They examine the impact of an online agent on account performance in the banking industry. They find that both interaction style and content of the online agent significantly influence the newcomer adjustment process over time, which in turn influences firm-level performance