Brickey, J.; Walczak, S.; and Burgess, T.
IEEE Transactions on Software Engineering, Vol 38 , Issue: 3, Page(s): 537 – 546
Current and future information systems require a better understanding of the interactions between users and systems in order to improve system use, and ultimately, success. The use of personas as design tools is becoming more widespread as researchers and practitioners discover its benefits. This paper presents an empirical study comparing the performance of existing qualitative and quantitative clustering techniques for the task of identifying personas and grouping system users into those personas. A method based on Factor (Principal Components) Analysis performs better than two other methods which use Latent Semantic Analysis and Cluster Analysis as measured by similarity to expert manually defined clusters.
Advances in Artificial Neural Systems, January 2012, # 1
Artificial neural network (ANN) modeling methods are becoming more widely used as both a research and application paradigm across a much wider variety of business, medical, engineering, and social science disciplines. The combination or triangulation of ANN methods with more traditional methods can facilitate the development of high-quality research models and also improve output performance for real world applications. Prior methodological triangulation that utilizes ANNs is reviewed and a new triangulation of ANNs with structural equation modeling and cluster analysis for predicting an individual’s computer self-efficacy (CSE) is shown to empirically analyze the effect of methodological triangulation, at least for this specific information systems research case. A new construct, engagement, is identified as a necessary component of CSE models and the subsequent triangulated ANN models are able to achieve an 84% CSE group prediction accuracy.
Christopher Sibona, Steven Walczak, Jon Brickey, and Madhavan Parthasarathy
International Journal of Healthcare Technology and Management, Vol. 12, Number 1, Pages 62-84
Physicians are adopting electronic medical records in much greater numbers today and are escalating the rate of adoption. The American Recovery and Reinvestment Act of 2009 provides incentives for physicians to adopt this technology. The objectives of this paper are to determine whether patient satisfaction is affected by computer use in the exam room and whether patients who have experienced computers in the exam room perceive differences in the utility of electronic medical records. Physicians received higher overall satisfaction scores when a computer was used to retrieve patient information. Physicians received similar satisfaction scores when a computer was used to enter patient information. Patients who have experienced electronic medical records perceive benefits such as increased portability of the record but do not believe that physicians who use electronic medical records produce better health outcomes. Patients who have experienced electronic medical records do not desire more control over their record than those who have traditional medical records.
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.
Steven Walczak and Richard Mann
Journal of Organizational and End User Computing, Vol. 22, Issue 4, 27 pages
Communities of practice have been heralded as a powerful knowledge management tool, especially for geographically disparate workgroups. Research into knowledge management (KM) in healthcare organizations is a needed research focus, given that differences exist in knowledge and knowledge management processes between healthcare and other organization types. The research presented in this paper examines the effectiveness of communities of practice as a knowledge sharing tool in a large and geographically disparate healthcare organization. Findings suggest that job role affects community members’ perceptions of the benefit and impact of communities of practice as well as their participation in such communities.
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.
Scott, Judy E. and Walczak, Steven
Information & Management Vol. 46 Issue 4, p. 221-232
Computer self-efficacy (CSE) is a person’s judgment of his or her ability to use a computer system. We investigated cognitive engagement, prior experience, computer anxiety, and organizational support as determinants of CSE in the use of a multimedia ERP system’s training tool. We also examined the impact of CSE on its acceptance. We determined the benefits of a sequential multi-method approach using structural equation modeling and neural network analysis. High reliability predictions of individual CSE were achieved with a sequential multi-method approach. Specifically, we obtained almost 68% perfect CSE group prediction overall, with almost 85% perfect CSE group prediction using fuzzy sets and over 94% accuracy within one group classification. The resulting CSE assessment and classification enables management interventions, such as allocating users to appropriate instruction for more effective training.
The Learning Organization Vol. 15, Issue 6, p. 486 – 494
Purpose – This article aims to examine international studies of knowledge management (KM) and organizational learning (OL).
Design/methodology/approach – The approach takes the form of a literature review of KM and OL research that focuses on a business or businesses located outside traditional Western economies.
Findings – There is a need to increase research that examines KM and OL existing in different and multiple countries. Additionally, cultural factors should be included in KM and OL research analysis.
Research limitations/implications – The limitation is that the only practical empirical evidence is supplied through the highlighted articles in the literature review.
Originality/value – The article shows that, in order to increase the application of KM and OL research world-wide, national culture and other geopolitical influences need to be represented in KM and OL models and measurement instruments.
Gregg, Dawn G. and Walczak, Steven
MIS Quarterly, Vol. 32, Issue 3, p. 653-670
Businesses can choose who they want to be online. Product and company attributes that are directly perceivable in the real world can be manipulated to make a favorable impression on online buyers. This study examines whether creating a more professional online e-image can signal consumers about unobservable product or company quality, and whether this signal influences their willingness to transact with the company, and ultimately the prices they are willing to pay for the company’s goods and services. An empirical study is presented that examines two new online auction businesses utilizing different company names and auction listing styles to sell items in parallel over the course of one year. The findings suggest that increasing the quality of an auction business’s e-image does increase consumers’ willingness to transact with the business, and increases prices received at auction. The study also demonstrates the ability to use eBay as an experimental laboratory for testing a variety of hypotheses about purchasing behavior online.
Organizational Research Methods Vol. 10, Issue 4, p. 710-712
The article reviews the book “Neural Networks in Organizational Research: Applying Pattern Recognition to the Analysis of Organizational Behavior,” by David Scarborough and Mark John Somers.
Kellogg, Deborah L. and Walczak, Steven
Interfaces Vol. 37, Issue 4, p. 355-369
The scheduling of nursing staff is a long-standing problem with myriads of research models published by academia. The exploratory research that we discuss examines the models that academia has produced and the models that hospitals have actually used. We use data from many sources, including research articles, e-mail and telephone surveys, an industry database, and a software source catalog. Only 30 percent of systems that research articles discuss are implemented, and there is very little academic involvement in systems that third-party vendors offer. We examine causes for the research-application gap and discuss directions for future academic research to make it more applicable.
Gregg, Dawn G. and Walczak, Steven
IEEE Transactions on Systems, Man and Cybernetics, Part C. Vol. 37 Issue 1 pp. 109-125
The World Wide Web is an increasingly important data source for business decision making; however, extracting information from the Web remains one of the challenging issues related to Web business intelligence applications. To use heterogeneous Web data for decision making, documents containing relevant data must be located and the data of interest within the documents must be identified and extracted. Currently most automatic information extraction systems can only cope with a limited set of document formats or do not adapt well to changes in document structure, as a result, many real-world data sources with complex document structures cannot be consistently interpreted using a single information extraction system. This paper presents an adaptive information extraction system prototype that combines multiple information extraction approaches to allow more accurate and resilient data extraction for a wide variety of Web sources. The Amorphic Web information extraction system prototype can locate data of interest based on domain-knowledge or page structure, can automatically generate a wrapper for a data source, and can detect when the structure of a Web-based resource has changed and act on this to search the updated resource to locate the desired data. The prototype Amorphic information extraction system demonstrated improved information extraction accuracy when compared with traditional data extraction approaches.
Walczak, Steven, Gregg, Dawn G. and Berrinberg, Joy
Journal of Electronic Commerce Research Vol. 7, Issue 4, p. 199-220
The purpose of this investigation is to identify factors in the decision making processes used by online auction sellers to select their online auction sales channel. Examining these decision factors will aid in creating a model of online auction seller channel evaluation mechanisms including economic and social factors and may be used by online auction services and intermediaries to maximize their market potential by increasing the perceived value of the various economic or social factors influencing seller outlet selection. An exploratory survey analysis is used to identify the components that online seller’s use for online channel selection.
Gregg, Dawn G. & Walczak, Steven
Communications of the ACM Vol. 49, Issue 5, p. 78-84
Extracting information from Web pages for internal applications is difficult. An effective Web information extraction system needs to interpret a wide variety of HTML pages and adapt to changes without breaking. An information extraction system should recognize different Web page structures and act on this knowledge to modify the information extraction techniques employed. In addition, the system should be customizable for a variety of domains and data-object types. This paper examines the characteristics of effective Web information extraction systems. This paper also presents a prototype adaptive Web information extraction system for building intelligent systems for mining information from Web pages.
Gregg, Dawn G. & Walczak, Steven
Decision Support Systems, Vol. 41 Issue 2, pp. 449-471
Online auctions are proving themselves as a viable alternative in the C2C and B2C marketplace. Several thousand new items are placed for auction every day and determining which items to bid on or when and where to sell an item are difficult questions to answer for online auction participants. This paper presents a multi-agent Auction Advisor system designed to collect data related to online auctions and use the data to help improve the decision making of auction participants. A simulation of applied Auction Advisor recommendations and a small research study that used subjects making real purchases at online auctions both indicate that online auction buyers and sellers achieve tangible benefit from the current information acquired by and recommendations made by the Auction Advisor agents.
Walczak, Steven & Parthasarathy, Madhavan
Information Systems and E-Business Management Vol. 4, Issue 1, p. 49 – 70
The internet and world wide web are an increasingly important resource, both as a market and as an information source, to both individual users and business entities. An estimated 120 million active web users exist in the United States alone. Access to these electronic marketplaces and information sources is accomplished through either a direct internet connection or through a service provider. Internet service providers (ISPs) enable internet and web access for most of these users either via dial-up modems (62.2 percent), or DSL connections (17 percent). Customers of ISPs frequently switch or discontinue service. The model selection perspective is used to extend previous work in this area through the development of a multi-agent system with neural network wrappers. The nonparametric (neural network) agents identify over 92 percent of those users that either stop or change service, which is a 15 percent increase over previous models.
The Learning Organization Vol. 12 Issue: 4 pp. 330 – 339.
Purpose – To propose and evaluate a novel management structure that encourages knowledge sharing across an organization.
Design/methodology/approach – The extant literature on the impact of organizational culture and its link to management structure is examined and used to develop a new knowledge sharing management structure. Roadblocks to implementing a new management structure and methods for overcoming these impediments are discussed. The efficacy of the proposed management structure is evaluated empirically by examining its effect on organizations that have implemented portions of the proposed structure.
Findings – The foundational ideas behind the proposed knowledge management organizational structure and the structure itself have been implemented in parts at various organizations located both in the USA and internationally. While the full management structure model has not been evaluated, the portions implemented in various organizations have enabled these organizations to assume leading roles in their respective industries.
Research limitations/implications – The proposed knowledge sharing management structure has not been fully implemented under controlled circumstances. The empirical evaluation is performed on portions of the proposed model, thus the full impact of the proposed management structure may well exceed the described benefits and additional structural-shift roadblocks may limit the realization of the proposed benefits.
Practical implications – The proposed knowledge sharing management structure gives managers a practical way to approach cross organizational knowledge sharing, which is frequently identified as a theoretical benefit of knowledge management. Means for diminishing or circumventing recognized impediments to organizational change are described to further facilitate the implementation of the proposed cross-organizational knowledge sharing structure.
Originality/value – The proposed knowledge sharing management structure is organized around knowledge-based teams of knowledge workers, but further extends this concept to include larger knowledge groups to transform an organization into a knowledge-based organization. If an organization’s functional structure can be successfully transformed, then this enables the maximization of competitive advantage realized through knowledge management initiatives, more specifically through knowledge sharing. Upper level management, who are responsible for organizational change are the primary audience, though the principals described may be implemented through a more grass roots approach by lower level management.