The dynamic nature of the market with constant technological developments continuously changes expectations from users over time. This drives businesses to alter their product and service offerings to maintain a competitive advantage, stable growth and, high customer satisfaction. Since economic goals drive businesses, it is often assumed that abundance of choice options is better, and will eventually result in increased profitability for the business. However, this is not necessarily the case. Consumers may experience a subjective state of mind termed as “choice overload” when presented with a plenitude of choice options. Consequently, consumers may fall victim to indecision, reduced customer satisfaction, and increased regret, to name a few. Previous research has formulated a cohesive understanding of choice overload in consumer decision making. Extant research in the field of consumer behaviour has identified several antecedents and concomitants of choice overload experienced by consumers. A vast bulk of research has also discovered repugnant effects of choice overload, due to context-dependency and other intrinsic and extrinsic factors influencing the choice overload effect. As a result, the questions of when and whether large assortments are detrimental to consumers remains open. This, offers an opportunity to extend the literature in this field by considering different contextual factors and variables that were thus far overlooked. The present study specifically aims to reduce the research gap that exists between Human-Computer Interaction (HCI) by understanding the choice overload effect, within the domain of e-tourism. Apprehension of the choice environment and consumer purchase behaviour is essential to close this existing gap and increase customer satisfaction. In this study, choice complexity is considered as an antecedent of choice overload. Choice complexity encapsulates two structural factors of the choice set – number of alternatives and number of attributes/levels. These factors allow for the construction of a measurement variable for choice complexity (entropy) where high entropy translates to high choice complexity. Moreover, individual differences in maximizing behavioural tendency (in terms of strategy and goal) are investigated. When consumers score high on maximizing tendency strategy, they optimize choice through employing a strategy of extensive information search. Similarly, when consumers score high on maximizing tendency goals, they strive to obtain the best possible choice from the available alternatives. Post-choice satisfaction is defined as the post-decision evaluation of the choice selected by the consumer. Specifically measured on two constructs - general satisfaction and outcome satisfaction. General satisfaction measures satisfaction of the consumer related to the process of arriving at a decision. Whereas, outcome satisfaction measures satisfaction related to the certainty in the choice decision. A choice experiment practically assessed the relationship between choice complexity and post-choice satisfaction, moderated by consumer purchase behaviour. The experimental design consisted of a Low Complex (LC) choice set and a High Complex (HC) choice set (distinguished based on entropy measurements) that allowed for the measurement and comparison of perceived complexity in a complicated choice environment. Respondents conducted a post-choice questionnaire designed to assess post-choice satisfaction and perceived choice complexity. Consumer purchase behaviour was assessed in a different section of the survey based on two different scales - maximizing tendency strategy and maximizing tendency goal. Statistical analysis was conducted on the obtained data to find the relationship between the variables under study. The experiment established the existence of choice complexity in e-tourism. Results showed an inverse relationship between choice complexity and post-choice satisfaction indicating that respondents were less satisfied with their choice when presented with a choice set of high choice complexity. Moreover, maximizing tendency strategy negatively influenced this relationship. Maximizers (i.e., respondents who scored high on the scale assessing maximizing behavioural tendency for strategy), extensively search through alternatives, eventually to formulate trade-offs and comparisons between the alternatives presented. Such maximizers were less satisfied with their choice having gone through a choice set of high complexity as compared to a choice set of low complexity. No such effects were found for the scale, maximizing tendency goals. The detriments of offering too much choice are real. Businesses within service industries such as e-tourism are therefore recommended to improve the quality/quantity of content due to intrinsic (i.e., intangibility, high monetary value, less purchase frequency) and extrinsic (i.e., a high number of alternatives and number of attributes/levels) factors. Each of these factors may make the service offering more complex for consumers to choose from. Managerial implications of the present study include the perspective (technology-centered view and human-centered view) that businesses can adopt. This perspective acknowledges the existence of choice complexity and maximizing tendencies, thereby optimizing the digitized environment towards better personalization. Doing this correctly would result in increased customer satisfaction due to better adaptation of digital environments by businesses to the needs and behaviours of consumers. The inclusion of entropy accurately provides the amount of information in bits; this measurement variable could be used by businesses to improve their algorithms. Finally, some companies in e-tourism have already begun to implement similar strategies, and reported in a significant increase in customer satisfaction, reservations, and overall sales. This gives evidence towards the practical importance of this study, and further emphasizes that businesses can indeed optimize their approach specifically towards the quality/quantity of content provided to consumers. In conclusion, the present study shows a negative relationship between choice complexity and post-choice satisfaction, with the inclusion of maximizing tendencies within the domain of e-tourism. Business may derive implications from this research to optimize their digital environments through increase in content personalization and reduction in choice complexity.