Using Deep Learning for Identifying Social Media Customer Service Opportunities

Social media is commonly used by organizations to address customer service issues like complaints. For example, this is common in the airline industry, but not all organizations utilize it. However, the latest natural language processing (NLP) techniques can enable organizations to identify complaints—and other social media customer service opportunities—automatically. This exploratory work demonstrates a system for identifying complaints in social media using these NLP techniques that significantly improves upon the current state-of-the-art. We discuss implications for research, practice and future work

Examining Post Adoption Usage: Conceptual Development and Empirical Assessment

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Family, Ethnic Entrepreneurship, And The Lebanese Of Kansas

As they entered the elegant lobby of the Waldorf Astoria, Elias G. Stevens and his wife, Handuma, must have marveled at how their lives turned out. They had both been born and raised in what was once the Ottoman province of Syria. They had come to the United States at the turn of the century, found their way to Wichita, Kansas, and worked hard to build a successful candy and tobacco business. They were in New York to meet with representatives from Philip Morris. Surveying the accommodations, however, Handuma noticed a major problem that had to be addressed right away. She insisted they find a grocery store, and the family headed out. A while later, the Stevens entourage returned, marching through one of the most sophisticated hotels in the country carrying bags loaded with provisions. Back in the room, Handuma dutifully arranged the food on dishes to set before the company representatives. To her, it was unthinkable to host such important guests without offering them something to eat and drink. The Stevenses understood the needs and nuances of American consumerism, while never forgetting the ancient Arab tradition of hospitality

An Integrated Temporal Model of Belief and Attitude Change: An Empirical Test With the iPad

Bhattacherjee and Premkumar (2004) propose a temporal model of belief and attitude change to understand fluctuating patterns of information technology (IT) usage. However, they overlook the role of perceived enjoyment in the process of temporal IT usage. Perceived enjoyment has become an increasingly important part of how consumers assess technology. Thus, we build on Bhattacherjee and Premkumar’s model (BP model) and propose a new model by investigating the comparative role of perceived usefulness (PU) and perceived enjoyment (PE) for explaining temporal changes in users’ beliefs and attitudes toward IT usage. We name our proposed model the integrated temporal model (ITM). Through an empirical study of iPad usage in a classroom setting at three different stages, we found that 1) the effect of PE on PU was stronger at the pre-usage (vs. post-usage) stage and that its effect was stronger at the initial-usage (vs. later-usage) stage; 2) while PE has a stronger effect than PU on attitude at both pre-usage and initial-usage stages, that was not the case at the later-usage stage; instead, the effect of PU on attitude was stronger at the later-usage (vs. initial-usage) stage; 3) the effect of disconfirmation on modified PU and PE was stronger at the initial (vs. later) stage, while the effect of PU and PE expectation on modified PU and PE was weaker at the initial (vs. later) stage. Our study extends the BP model to IT with hedonic elements (i.e., the iPad) and is the first of its kind to empirically examine the combined and relative impact of PU and PE on the temporal usage of IT with hedonic elements in the classroom setting

iPad Usage Among University Athletes

Presentation given during the Student Success: Web and Mobile Technologies to Support Student Learning track

Judging University Competitions with iPads

We study the use of iPads in judging competitions at a university. Prior to iPads, judges used multiple paper forms. The process was time consuming and labor intensive. After using iPads, judges were asked about their experience with the new process. We share our findings from approximately 100 judges