The sport marketing field has neglected to study the Latino population despite escalating amounts of consumer research within the marketing literature focusing on this market segment. Therefore, the purpose of our study was to examine the potential predictors of conative loyalty (i.e., purchase intentions) of the Latino fan by testing the Model of Sport Spectator Conative Loyalty (Model B) on a Latino sample. In addition, we wanted to compare the relationships within the model between Latinos and Non-Latinos to study the potential differences between the two market segments. The participants were Latino (n= 127) and Non-Latino (n= 186) attendees of a professional Major League Baseball game in the Southeastern United States. Even though the model results were very similar for both groups, differences do exist between Latinos and Non-Latinos in terms of specific sport consumer behavior relationships (e.g., BIRGing and CORFing on Conative Loyalty).

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The Internet is constantly evolving, producing many new data sources that can be used to help us gain insights into the cyber threat landscape and in turn, allow us to better prepare for cyberattacks. With this in mind, we present an end-to-end real-time cyber situational awareness system which aims to retrieve security-relevant information from the social networking site Twitter.com. This system classifies and aggregates the data extracted and provides real-time cyber situational awareness information based on sentiment analysis and data analytics techniques. This research will assist security analysts in rapidly and efficiently evaluating the level of cyber risk in their organization and allow them to proactively take actions to plan and prepare for potential attacks before they happen.