Meaningful Framing of IS Education Gamification

This study seeks to explore what short term goals are relevant to the IS field from the learners’ perspective

Information Seeking on Social Media Sites: An Exploratory Study

This study reports on a survey that was conducted to investigate the use of social media technologies for information seeking. The objective of this study is to gain an understanding of how best to provide information that is useful to information seekers. Four categories of information were explored; sensitive, sensational, political and casual information, across five social media technologies: social networks, micro-blogging sites, wikis, online forums, and online blogs. The results show that information seekers tend to use social networks, followed by microblogging sites for seeking information more than they do other social media technologies. This paper concludes with implications for practice and research

Effects of information importance and distribution on information exchange in team decision making

Teams in organizations are strategically built with members from domains and experiences so that a wider range of information and options can be pooled. This strategic team structure is based on the assumption that when team members share the information they have, the team as a whole can access a larger pool of information than any one member acting alone, potentially enabling them to make better decisions. However, studies have shown that teams, unlike individuals, sometimes do not effectively share and use the unique information available to them, leading to poorer decisions. Research on information sharing in team decision making has widely focused on the exchange of shared or unshared information in the hidden profile paradigm, neglecting the role of information importance. Informational influence theory holds that the importance of information may affect how information is processed for making decisions in teams. This study investigates information exchange processes to understand how teams can effectively exchange and use information available to them to make better decisions. The specific research question concerns the extent to which importance and distribution of information is associated with its exchange during discussion in distributed teams. Data are collected in a laboratory study involving subjects interacting with a computer-mediated decision support system. The results show that the importance of information, the distribution and the interaction of importance and distribution have significant main effects on information exchange. Teams tend to exchange a higher proportion of the more important information compared to the less important information. A third dimension is introduced to measure information distribution -- partially shared information -- and is found to have a strong main effect on information exchange. It is also found that the extent to which team members exchange more important information during discussion strongly correlates with the tendency to improve team performance. It is also found that task complexity is negatively correlated with information exchange performance. Teams tend to exchange a smaller proportion of information when working on complex tasks, compared to when working on simple tasks. This dissertation makes contributions in three areas. Firstly, a theoretical model is developed that allows for the investigation of the joint relationship of the importance of information and its distribution in team decision-making. Secondly, this work introduces a new approach to investigate information sharing, exchange and use in decision-making teams. Others can apply this approach fruitfully in investigating similar phenomena outside of the current domain. Finally, this work improves the understanding of information sharing and exchange processes in relation to the distribution of information and its importance

Twittermania: Understanding How Social Media Technologies Impact Engagement and Academic Performance of a New Generation of Learners

Twitter, a popular micro-blogging service, is increasingly evolving from being a mere chatting platform to a tool that is instrumental in affecting a desired learning and social change among individuals and organizations. Although using Twitter for learning while socializing represents a significant departure from its intended initial function, information systems (IS) researchers should further explore the impact and implications of social media technologies such as Twitter in the educational context. We draws on engagement theory and social impact theory to assess how social media technologies tools can support learning and improve students’ academic outcomes. We present an experiment in which we compared Twitter and a traditional discussion board to academically engage students over a 14-week period. The results show that actively using both Twitter and traditional discussion boards for engagement is related to student performance in the course. Social network analysis suggests that, by using Twitter, the students possibly created shared mental models that led them to engage with the class more, and therefore, better their performance

A Tale of Two Internet News Platforms-Real vs. Fake: An Elaboration Likelihood Model Perspective

This paper presents findings from a field analysis of real vs. fake news propagated on the Internet. Elaboration Likelihood Model (ELM) was used as a theoretical framework to investigate information presentation mechanisms used by real and fake content generators to persuade readers. ELM theorizes two routes through which information can inform attitudinal changes: a central route of high cognitive effort, and a peripheral route of low cognitive effort. We hypothesize that fake news sites favor the peripheral route by providing less information overall, and by providing more negative affective cues. Data was gathered from Internet platforms that publish real news and fake news. Results indicate that the amount of information disseminated by fake news platforms is lower than that of reputable platforms. Content analysis reveals that fake news with business impact are typically more negative in their valence compared to real news. Implications of our findings for theory and practice are discussed

You are What You Say: The Influence of Company Tweets on Its Stock Performance

This paper investigates the relationship between Twitter metrics and stock price performance of a company. The objective of this research is to contribute to the area of research that seeks to uncover the business value of social media platforms. Building on prior research, this paper identifies two categories of metrics that have been used to examine the relationship between Twitter metrics and stock performance of a company, namely traffic and motivation. While traffic is measured as volume of tweets, motivation is measured from two perspectives; polarity (positive, neutral, and negative) and emotion (positive emotion and negative emotion). Unstructured data from Twitter and Yahoo finance Website about Amazon was gathered to test the study hypothesis. A combination of machine learning techniques for text analytics and hierarchical regression analysis was used to analyze the data. Results indicate that emotional motivation expressed in tweets sent out by a company positively influences the company’s stock performance

Systematic Review of Gamification Research in IS Education: A Multi-method Approach

Gamification refers to the use of game mechanics and game dynamics in non-gaming environments and contexts. Gamification is increasingly gaining attention among system designers across various industries especially in education due to the benefits associated with its implementation. The adoption of gamification in information systems (IS) education is promising for engaging and motivating students to complete their degree programs. Call for research in this area is particularly on the increase in the IS field. Accordingly, we need to organize the aggregation of research in this area and use common terminologies to promote progressive research practice in the field. In this paper, we use a multi-method approach to systematically review existing research on gamification in IS education to identify common terminologies, identify trends in topics studied, highlight understudied areas, and, thus, present opportunities for future research. The multi-method approach combines classical systematic review method and social network analysis to provide additional insight into the knowledge structure of researchers involved in the gamification of IS education. This review also highlights possible interventions that can improve student retention in IS education through the design of effective gamified courses

Community by Design: Prioritizing the Factors that Drive Knowledge Use in Online Question & Answers Platforms

The question of how knowledge assets are utilized in the context of online communities is the primary impetus of this research. Using a multilevel approach, this paper investigates factors that influence the use of knowledge in an online question and answer platform (OQA). It focuses on three levels including informational, individual, and community, and reviews interactions across each level. The study tests the multilevel model with data from StackOverflow.com, a renowned online community for programmers to exchange knowledge assets, especially questions and answers about coding issues. Traditional hierarchical regression analysis proved insufficient to explicate the complexity associated with human decision-making processes with respect to asset utilization. However, a machine learning technique with a Chi-square automatic interaction detection algorithm provided a richer understanding of the relative importance of factors and their thresholds for influencing knowledge asset use

Impact of Social Media Influencers on Consumer Behaviors

The continuous evolution in the marketplace today presents opportunities for technology, consumers, and brand to interact to change consumer experiences. In particular, there is an emergence of brand influencer roles afforded by consumer interactions about brands on social media. Consumers that take on such roles are known as social media influencers. Social media influencers have revolutionized the way brands view their marketing strategies. With their vast reach and informative segments, social media influencers can promote products and brands without their audience even realizing it. Furthermore, this form of advertisement is appealing to consumers since it presents an organic approach to promoting brands. This study investigates this kind of advertisement to understand how messages that social influencers send during this process drive behaviors such as consumer preferences and consumer brand wellbeing. For this exploration, we focus on consumer brand preference and consumer brand wellbeing because they have been identified as important outcome variables in the literature (Inman et al. 2020). Brand preference is the act of choosing one brand over another (Ebrahim et al. 2016), and consumer wellbeing refers to a level of fulfillment that a brand causes the consumer to have (Suranyi-Unger 1981). Consumer brand wellbeing involves measuring how the brand will increase long-term satisfaction for its customers and assesses how their life is, in turn, better for purchasing from the brand. To understand the extent to which social media brand influencers affect consumer preferences and consumer brand wellbeing, we designed an experiment to investigate how consumers would react to influencer messaging. The stimuli created for this experiment were formatted as Instagram posts. Instagram biographies and photo captions were manipulated to fit into one of four conditions: sustainable, consumerism, hybrid (a combination of the two categories mentioned earlier), and control. Each message was tailored to match the influencer\u27s brand to make the advertisements seem as realistic as possible and based on prior research that shows consumers respond positively to influencer messaging that aligns with the influencer\u27s brand (Kim and Kim 2020). The stimuli were designed to mimic the feeling of scrolling on Instagram and to have the participant imagine that these pictures had just popped up on their feed. Preliminary data from a pilot study of university students from the United States shows that consumers respond more favorably to sustainable and hybrid messages unfavorably to consumerist messages. In addition, consumers responded to influencer messaging in the sustainable manipulation more than the others. Findings from this study will inform influencer marketing strategies on social media. In addition, we are interested in feedback on how to better position this research in the Information Systems space and other methodological and analytical approaches that will help us investigate how social technologies influence consumer behaviors in new ways. References Ebrahim, R., Ghoneim, A., Irani, Z., and Fan, Y. 2016. A Brand Preference and Repurchase Intention Model: The Role of Consumer Experience, Journal of Marketing Management (32:13-14), pp. 1230-1259. Inman, J., Campbell, M. C., Kirmani, A., and Price, L. 2020. JCR Call for Papers: “The Future of Brands in a Changing Consumer Marketplace” Special Issue: August 2021, Journal of Consumer Research (Editorial). Kim, D. Y., and Kim, H.-Y. 2020. Influencer Advertising on Social Media: The Multiple Inference Model on Influencer-Product Congruence and Sponsorship Disclosure, Journal of Business Research (In Press). Suranyi-Unger, T. 1981. Consumer Behavior and Consumer Well-Being: An Economist\u27s Digest, Journal of Consumer Research (8:2), pp. 132-143