When does user experience count more than price? How do online travel agencies generate customer loyalty as an intermediary?

ONLY PEER REVIEWED SOURCES What is needed? Introduction Research Question Literature review Methodology why selected, how it will answer the question as asked, what access to people/ organizations is required, and is access guaranteed. Foreseen limitations Research schedule/Timeline Bibliography Here from the first proposal: What is converting online views into transactions and how to win over customer in online hotel booking? The assumption is that user experience during the booking and the travel research is a key (often more important than price benefits) to generate returning users in the competitive landscape for the augmented product offered by online travel agencies (OTAs). Through multiple choice survey comparable to an A/B test I will explore what is driving customer conversion (lookers to bookers) and win over customers with user experience (during, pre-, and post-sale) allowing companies to differentiate themselves within this often monopolistic competition. This will include features that are supported through the technological advancement by the internet of things, economies of scale, big data, machine learning, customization and potentially leading to the conclusion that the biggest companies (with the largest and most relevant data sets) have the biggest advantage to lead in creating the best user experience as a barrier of entry. What are the benefits and risk of data collection for customization? Know-your-customer has grown into a full new meaning due to the extent that not only demographic data is ready available but also most relevant information about current location, recent online searches and activities are often accessible to third parties without users being fully aware. The switch from desktop pc to always online smartphones allows silent monitoring and limited two way communication at all times. Nailing to understand the exact moment when a person searches with the intend to buy is key in order to maximise the ROI of online marketing. Machine learning algorithms are widely applied to predict user behaviour and display customized content. Where is the ethical line for this customization and when does it become manipulation? The survey will explore users feelings about the customization and also give examples of ethical and unethical usage. The paper will also explore organizational and operating models that provide the information governance required to advance and touch the risks these models are facing. The dissertation will include elements of strategic management, information management, as well as organizational behaviour. A quantitative online survey to complete existing published survey on this topic to support claims that users return to certain websites / applications as they considered the information offered most relevant or the experience more convenient over others.