Jehad Imlawi, Dawn Gregg
Informatics for Health and Social Care,Pages: 1-17.
Participation of health-care professionals in online health communities is essential for these communities to achieve their goals of improving health outcomes. However, little research has been conducted to understand what motivates health-care providers to participate in such communities. This study utilizes the expectancy/value theory to identify the factors that might affect health professionals’ intentions to continue contributing health knowledge in online health communities (OHCs). Specific motivators driving health professionals’ continuance intentions in OHCs include intrinsic motivators (helping motivator, self-efficacy, and moral obligation), and extrinsic motivators (reputation). This study also investigates how health professionals’ satisfaction in the OHC mediates the relationship between the study motivators and the continuance intentions. The study also suggests that health professional characteristics have
Sumate Permwonguswa, Jiban Khuntia, Dobin Yim, Dawn Gregg, Abhishek Kathuria
Health Systems,Vol. 7, Issue 3, Pages: 181-194.
Health infomediary systems are emerging as important knowledge sharing platforms that help patients manage their own health outside of traditional health care delivery models. Patients participate in health infomediaries to learn from other patients’ experiences and knowledge. Knowledge sharing is an important aspect of the success of a health infomediary. Factors related to self-concept have been widely studied in the domains of psychiatry and psychology, in settings such as mental health and behavioural well-being, but remain unexplored in the digital health context. In particular, it is not known how self-concept influences knowledge sharing behaviours in health infomediaries. This study posits that self-efficacy, social identity, and self-stigma drive knowledge sharing in an infomediary through emotional empowerment and appearance-contingent self-esteem. We use the health belief model as a foundation to
Michael A Erskine, Dawn G Gregg, Jahangir Karimi, Judy E Scott
Information Systems Frontiers,Pages: 1-16.
Increasingly, spatial decision support systems (SDSS) help consumers, businesses and governmental entities make decisions involving geospatial data. Understanding if, and how, user- and task-characteristics impact decision-performance will allow developers of SDSS to maximize decision-making performance. Furthermore, scholars can benefit from a more comprehensive understanding of what specific characteristics influence decision-making when using an SDSS. This paper provides a synthesis of relevant research and presents a two-factor experiment (n=200) designed to measure the impact of user- and task-characteristics on decision-performance. Using Cognitive Fit Theory (CFT) as the theoretical framework, we investigate the effect of geospatial reasoning ability (GRA), input complexity, task complexity, and user perceptions of task-technology fit (PTTF), on geospatial decision-making
Dawn Gregg and Madhavan Parthasarathy
Small Business Economics, Vol. 49, Issue 2, August 2017 pp. 405–419
With 40% of the world able to access the internet, online marketplaces provide the small entrepreneur with a hitherto incomprehensible opportunity to reach a global audience with very low barriers to entry and low risk. Yet, academic research has not studied the factors unique to online businesses that affect their long-term survival. This study is the first of its kind that does so using data gathered from eBay’s feedback system in 2004, 2009, and 2013. The results present data on the rate of discontinuance of eBay ventures. Further, a logistic regression analysis suggests that unique factors such as venture size, age, and feedback reputation positively influence the likelihood of long-term survival of an eBay venture. Based on these results and the ensuing discussion, implications for researchers and practitioners are provided.
Mohamed Alsharo, Dawn Gregg and Ronald Ramirez
Information and Management, Vol. 54, Issue 4, August 2017, Pages. 479-490
Organizations utilize virtual teams to gather experts who collaborate online to accomplish organizational tasks. The virtual nature of these teams creates challenges to effective collaboration and team outcomes. This research addresses the social effects of knowledge sharing on virtual teams. We propose a conceptual model which hypothesizes a relationship between knowledge sharing, trust, collaboration, and team effectiveness in virtual team settings. The findings suggest that knowledge sharing positively influences trust and collaboration among virtual team members. The findings also suggest that while trust positively influences virtual team collaboration, it does not have a significant direct effect on team effectiveness.
Michael Erskine, Dawn Gregg, and Jahan Karimi
Journal of Computer Information Systems, Volume 56, Issue 2, pp. 175-184
Online mapping services, such as Google Maps and Bing Maps have become increasingly popular. In addition to providing map, navigation and directory information, such services provide third-party applications with a framework including geospatial-visualization capabilities. For instance, consumers often use location-based services (LBS) and spatial decision support systems (SDSS) to locate the nearest restaurants, search for ideal homes, navigate specific routes and effectively participate in car and bike sharing programs. Organizations utilize SDSS to perform retail site selection, manage global assets and to optimize supply chains. While geospatial visualization is a vital capability of online mapping services, little is understood about how it impacts the acceptance of technology. Through a partial least squares analysis of 577 subject responses, this paper demonstrates that the user-acceptance of geospatial-visualization is influenced by utilitarian, hedonic and cognitive measures. This paper concludes with a discussion of the implications of these results to research and practice.
Jehad Imlawi, Dawn G. Gregg, and Jahan Karimi
Computers & Education, Vol. 88, pp. 84-96
Social network sites provide the opportunity for building and maintaining online social network groups around a specific interest. Despite the increasing use of social networks in higher education, little previous research has studied their impacts on student’s engagement and on their perceived educational outcomes. This research investigates the impact of instructors’ self-disclosure and use of humor via course-based social networks as well as their credibility, and the moderating impact of time spent in these course-based social networks, on the students’ engagement in course-based social networks. The research provides a theoretical viewpoint, supported by empirical evidence, on the impact of students’ engagement in course-based social networks on their perceived educational outcomes. The findings suggest that instructors who create course-based online social networks to communicate with their students can increase their engagement, motivation, and satisfaction. We conclude the paper by suggesting the theoretical implications for the study and by providing strategies for instructors to adjust their activities in order to succeed in improving their students’ engagement and educational outcomes.
Michael A Erskine, Dawn G Gregg, Jahangir Karimi, and Judy E Scott
International Journal of Human-Computer Interaction, Volume 31 Issue 6 , pp 402-412.
An understanding of geospatial reasoning ability (GRA) is essential to human-computer interaction research, as many recent consumer and commercial technologies require an ability to interpret complex geospatial data. Individuals, as well as government, commercial and military organizations, use such technologies regularly. For instance, consumer technologies including online mapping services and in-vehicle navigation systems are increasingly prevalent. Business leaders rely on geospatial data when making decisions using geospatial data, there is conflicting evidence on the impact of GRA on the decision-making process. This paper suggests applying a multi-dimensional measure of GRA to facilitate a better understanding of such interactions. Furthermore, this paper proposes a new measurement instrument developed through a rigorous scale development procedure and validated through an exploratory (n=300) analysis.
Judy E. Scott, Dawn G. Gregg, and Jae Hoon Choi
Information Systems Frontiers, Vol 17 Issue 1, January 2015, pp. 177-191.
“Lemon” complaints reveal that online auction experiences can turn sour. Theory on information asymmetry explains how “lemons” could drive high quality items away from a market leaving a dominance of poor quality goods. In this paper we analyze “lemon” complaints using content analysis and hierarchical logistic regression. In the data collection of 306 complaints from 8 product categories in online auctions, the results show that compared to standard products “lemons” are much more likely if the product category is for functional items, such as computers and consumer electronics; non-standard items with product description complexity, such as collectibles; and fragile items, such as pottery and glassware. Contrary to expectations, clothing and jewelry, representing sensory products, did not have a statistically significant impact on the frequency of “lemons”. Although two seller negative feedback rating measures did predict non-receipt of goods, seller and buyer ratings and experience did not predict “lemons”.
Toan Ong, Michael Mannino, & Dawn Gregg
Electronic Commerce Research and Applications, Vol. 13, Issue 2, March-April 2014, pp. 69-78
This exploratory study investigates the linguistic characteristics of shill reviews and develops a tool for extracting product features from the text of product reviews. Shill reviews are increasingly used to manipulate the reputation of products sold on websites. To overcome limitations of identifying shill reviews, we collected shill reviews as primary data from students posing as shills. Using semi-automated natural language processing techniques, we compared shill reviews and normal reviews on informativeness, subjectivity and readability. The results showed evidence of substantial differences between shill reviews and normal reviews in both subjectivity and readability. Informativeness appears to be a mixed separator of shill and normal reviews so additional studies may be necessary. Overall, the study provides improved understanding of shill reviews and demonstrates a method to extract and classify features from product reviews with an eventual goal to increase effectiveness of review filtering methods.
Jehad Imlawi & Dawn Gregg
International Journal of Human-Computer Interaction, Vol. 30 Issue 2, February 2014, pp. 106-125
This study proposes an engagement model that supports acceptance and use of course-based online social networks for engaging student, and hence, improving the instructor’s credibility. This research demonstrates that instructors who create course-based online social networks can increase student engagement in these online social networks, and improve the instructor’s credibility. This increase in engagement is seen when the instructor posts private information related to the course and when the instructor makes humorous posts. However, it is not seen when the instructor posts private information unrelated to the course. These results should be useful for instructors who are trying to improve student engagement and to enhance their own credibility.
This research utilizes Communication Privacy Management theory and Instructional Humor Processing theory to expand our understanding of how instructor self-disclosure and use of humor via a course-based social network impacts student outcomes. The research also contributes to the theory by providing an engagement model that is unique to online educational settings.
Michael A Erskine, Dawn G Gregg, Jahangir Karimi, and Judy E Scott
Axioms, Vol. 3 Issue 1, December 2013, pp.10-30
Organizations that leverage their increasing volume of geospatial data have the potential to enhance their strategic and organizational decisions. However, literature describing the best techniques to make decisions using geospatial data and the best approaches to take advantage of geospatial data’s unique visualization capabilities is limited. This paper reviews the use of geospatial visualization and its effects on decision performance, which is one of the many components of decision-making when using using geospatial data. Additionally, this paper proposes a comprehensive model allowing researchers to better understand decision-making using geospatial data and provides a robust foundation for future research. Finally, this paper makes an argument for further research of information-presentation, task-characteristics, user-characteristics and their effects on decision-performance when utilizing geospatial data.
J.P. Hasley and D. Gregg
Journal of Technology Research, (2013) Vol. 5. 53 pages
Hundreds of studies have attempted to define, measure, or otherwise explain how website visitors think, feel, and behave during and after visits to transaction-oriented business-to-consumer retail websites. This article reviews the predominant endpoints described in the peer-reviewed literature over the past decade for user-website interactions with e-tail websites. Results suggest that although scores of user-website interaction outcomes have been reported in the peer-reviewed literature, most of those endpoints represent one of ten high-level user-website interaction outcomes (confirmation/disconfirmation, trust, perceived risk, engagement, purchase intentions, actual purchase behavior, satisfaction, repeat website visit intention or behavior, repeat purchase intention or behavior) either directly or indirectly. This article provides a new information technology systems-based taxonomy for relevant outcomes to define website outcomes, identifies their common characteristics, and summarizes the relationships so far reported in the peer-reviewed literature.
Brandon Beemer and Dawn G. Gregg
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 3(1), January 2013, pp. 74-84.
The evolution of eCommerce over the past decade has resulted in a wide range of tools that enable consumers to make better decisions about the products or services that they are purchasing. One class of tools that are now widely used in a variety of eCommerce domains are mashups, which combine disparate sources of information (e.g. price, product reviews, seller reviews) to support buyer decision making. Previous academic studies examining decision support tools for eCommerce domains have focused on how these tools affect information search, consideration set size, and the impact on the quality of the decision made. This paper discusses dynamic interaction, the degree to which a user can revisit and revise their inputs and consider alternative solutions during a decision. The effects of dynamic interaction on confidence and intention was investigated in an experiment, the results of which indicated that increasing dynamic interaction increased the perceived diagnosticity (i.e., the extent to which the user believes the tool is useful to evaluate a product) of the mashup and the overall confidence in the decision. In addition, a post-hoc analysis of decision quality suggests that increased levels of dynamic interaction also improve the overall quality of the decision made.
Joseph Hasley and Dawn G. Gregg
Journal of Theoretical and Applied Electronic Commerce Research, December 2010, 5(3), pp. 27-38.
This study describes and demonstrates the Website Information Content Survey (WICS), which is intended to provide practitioners and researchers with a means of systematically describing website information content. In an exploratory survey of twenty business-to-consumer websites across five e-commerce domains, we demonstrate how the survey can be used to make cross-website comparisons that can identify potential gaps in a website’s information content. The results of this study offer actionable guidance to practitioners seeking to match their website’s information mix to customer’s demands for product, company, and channel information. The WICS tool enables future investigation of hypothesized relationships between website information content and user-website interaction outcomes
Beemer, Brandon and Gregg, Dawn
Decision Support Systems, Vol. 49 Issue 4, November 2010, pp. 386-395.
In response to the need for knowledge based support in unstructured domains, researchers and practitioners have begun developing systems that mesh the traditional attributes of knowledge based systems (KBS) and decision support system (DSS). One such attribute being applied to KBS is dynamic interaction. In an effort to provide a mechanism that will enable researchers to quantify this system attribute, and enable practitioners to prescribe the needed aspects of dynamic interaction in a specific application, a measurement scale was derived from previous literature. Control theory was used to provide the theoretical underpinnings of dynamic interaction and to identify its conceptual substrata. A pretest and exploratory study was conducted to refine the derived scale items, and then a confirmatory study was conducted to evaluate the nomological validity of the measurement scale.
Steven Walczak, Deborah Kellogg and Dawn Gregg
International Journal of Information Systems in the Service Sector, Vol. 2 Issue 4, October 2010, pp. 39-56.
Today’s purchase processes often require complex decision-making and consumers frequently use Web information sources to support these decisions. Increasing amounts of information, however, can make finding appropriate information problematic. This information overload, coupled with decision complexity, can increase the time to make a decision and reduce decision quality. This creates a need for tools that support these decision-making processes. Online tools that bring together data and partial solutions are one option to improve decision-making in complex, multi-criteria environments. An experiment using a prototype mashup application indicates that these types of applications may significantly decrease the time spent and improve the overall quality of complex retail decisions.
Communications of the ACM Vol. 53, Issue 4, 5 pages
Collective intelligence is a fundamentally different way of viewing how applications can support human interaction and decision making. Most pre-Web 2.0 applications have focused in improving the productivity or decision making of the individual user. The emphasis has been on providing the tools and data necessary to fulfill a specific job function. Under the collective intelligence paradigm, the focus is on harnessing the intelligence of groups of people to enable greater productivity and better decisions than are possible by individuals working in isolation. The processes involved in designing and implementing specialized collective intelligence applications are discussed in the context of DDtrac, a web-based application that allows for the easy collection and summary of special education data.
Gregg, Dawn G. and Walczak, Steven
Electronic Commerce Research, Vol. 10 Issue 1, p. 1-25
This study measures the value of website quality in terms of its impact on trust, intention to transact and price premiums. Prior research on online auctions has focused on the use of reputation systems for building trust in online auction vendors and subsequently to generate price premiums. This study examines the extent to which trust can be induced by improving the quality of online auction listings for both new and existing auction ventures. A survey of 701 eBay users is conducted which compares the price premiums of two nearly identical online auction businesses, one that has online auction listings with a perceived high quality and the other that has substantially lower perceived quality. Results of this study indicate that website quality can explain 49 % of the variation in the trust for eBay sellers. In fact, it shows that sellers with good website quality are all perceived to be equally trustworthy regardless of their eBay reputation; whereas sellers with poor website quality are not perceived to be trustworthy even if they have a high eBay reputation score. The results also show that the trust resulting from increased website quality increases intention to transact and results in price premiums of 12% (on average) for sellers with higher quality listings. Theories from marketing, economics, and social psychology are used to explain why website quality induces trust in unknown vendors without providing any concrete evidence regarding the vendor’s past history.
Steven Walczak and Dawn Gregg
Journal of Theoretical and Applied Electronic Commerce, Vol 4, Issue 3, pp. 17-29.
Electronic commerce research has shown that factors like website quality and vendor reputation influence consumer behaviors, including: trust, intention to transact, and return visits. However, these factors are typically studied in isolation and frequently show conflicting results. This paper proposes a unifying model of online identity (or e-image) that combines the various factors that influence user perceptions of an e-business. Survey results support the importance of a wide variety of e-image factors when forming impressions online and show that while information content is the foremost concern for most users, other factors vary depending on the role of the user in establishing a relationship with the owner of the online identity.