Gender Moderation in Gamification: Does One Size Fit All?

Organizations actively seek methods for increasing employee engagement by incorporating game elements in core systems and processes, in an effort to increase their perceived playfulness. However, little is known about the actual impact of these elements on perceived playfulness. This study includes results from three repeated experiments performed during a gamified academic course. The relationships between enjoyment of specific game elements, the way they increase perceived playfulness, and gender moderations of these relations were examined. All three experiments show that badges had a positive relation with perceived playfulness and were more enjoyable to women. Surprisingly, the results showed that when men were the majority of subjects in the group, the relations between the game elements and perceived playfulness were different from when men were a minority. These results provide important insight into what possibly influences perceived playfulness in gamified solutions

Information sharing as enabler for the virtual team: an experimental approach to assessing the role of electronic mail in disintermediation

This paper is an attempt to document empirically the relation between information sharing accomplished via electronic mail and the performance of teams. We report on an experimental study of the role of electronic mail in the operation of supply chains. A variation of the well known ‘Beer Game’ role-playing simulation game was computerized and implemented in an internet-based environment to study the information-sharing behaviour of teams. A total of 76 teams of four players each competed to achieve best net team profit. Results of the simulation game permit a detailed examination of email use in an organizational context. Findings indicate the expected significant correlation between email use to share information up the supply chain and net team profit. In other words, sharing information in the team has a positive impact on performance. The recorded behaviour of managers in the online simulation indicates that team members use electronic mail successfully to attempt disintermediation of the supply chain. When information is shared online, teams perform significantly better.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72054/1/j.1365-2575.2003.00149.x.pd

Global Contagion of Non-Viral Information

Contagion in Online Social Networks (OSN) is typically measured by the tendency of users to re-post information or to adopt a new behavior after exposure to that information/behavior. Most contagion research is bound by modeling: (i) only local neighbor-to-neighbor contagion (ii) the spread of viral information. However, most contagion events are non-viral and can also occur globally by non-neighbors through for example, exposure to information by exploratory browsing, or by content recommendation algorithms. This study is the first to address the phenomenon of both global and local contagion of non-viral information in a quantitative way. Analysis of Twitter networks reveals the prevailing nature of global contagion, the different temporal patterns between global and local contagion, and the ways it varies across topical categories. An interesting finding shows that users who retweeted due to global contagion have more Followers than those who retweeted due to local contagion

The Role of Followers and Followees in the Adoption of Innovations

An online social network is a key platform through which innovation diffuses. To learn about innovativeness, we simultaneously investigate two Twitter networks, the relationships network, following-follower relationships, and the activity network, the flow of tweets. Specifically, the innovativeness relations to the networks' indegree and outdegree, the volume of platform use, and the profile's age. The more active and central the user, the earlier the adoption. Innovativeness increases with the number of followers only when at least several of them adopt the innovation. Surprisingly, having more followees is linked to later engagement with the innovation. This association is mediated by the number of adopters' followees. Those who created a Twitter profile later are also more likely to adopt innovations later. This study is novel in distinguishing between the two networks and analyzing their interactions. Its contribution lies in identifying the innovativeness of users in an online social network platform diffusion

#MyIBDHistory on Twitter: Identifying Disease Characteristics Using Personal Tweets

Inflammatory bowel disease (IBD) is usually classified into Crohn's disease (CD) or ulcerative colitis (UC). Inconclusive cases are diagnosed with IBD unclassified (IBD-U). In 2018, IBD patients shared their disease history on Twitter and signed their tweets with #MyIBDHistory. In this research, we analyzed those tweets and built a logistic regression classifier that predicts patients' IBD type. We constructed tabular classification features and assessed their importance using the regression coefficients and association rules. We identified key features that distinguished CD from UC and used the classifier to predict the disease type of IBD-U patients. Our results correlated with IBD-related research. The two most prominent features that tilted the classification towards CD were suffering from fistulas or nutrient deficiencies. We identified gender differences in disease perspective prior to diagnosis. The research shows that the personal information shared by patients on Twitter can enhance existing medical knowledge regarding their disease

TEXT MINING AND TEMPORAL TREND DETECTION ON THE INTERNET FOR TECHNOLOGY ASSESSMENT: MODEL AND TOOL

In today´s world, organizations conduct technology assessment (TAS) prior to decision making about investments in existing, emerging, and hot technologies to avoid costly mistakes and survive in the hyper-competitive business environment. Relying on web search engines in looking for relevant information for TAS processes, decision makers face abundant unstructured information that limit their ability to assess technologies within a reasonable time frame. Thus the following qustion arises: how to extract valuable TAS knowledge from a diverse corpus of textual data on the web? To cope with this qustion, this paper presents a web-based model and tool for knowledge mapping. The proposed knowledge maps are constructed on the basis of a novel method of co-word analysis, based on webometric web counts and a temporal trend detection algorithm which employs the vector space model (VSM). The approach is demonstrated and validated for a spectrum of information technologies. Results show that the research model assessments are highly correlated with subjective expert (n=136) assessment (r \u3e 0.91), and with predictive validity valu above 85%. Thus, it seems safe to assume that this work can probably be generalized to other domains. The model contribution is emphasized by the current growing attention to the big-data phenomenon

A USER SURVEY OF A SITE PROVIDING CITIZEN INFORMATION: PRELIMINARY FINDINGS OF SHIL.INFO

This paper is about studying citizens’ information needs through a collection of different research lenses. We were interested in users of online, citizen rights web sites, such as the SHIL (http://shil.info) site. Our results report findings from three parallel data collection efforts. In order to gain a better understanding of how the SHIL website is used, and to compare the information needs and information sources used by SHIL, users and potential users unaware of the existence of the Website, were surveyed, using a trio of methods. We report several interesting differences between the three groups, and suggest future work on analyzing the site, its users, the content it provides and the needs it serves