Anna Sidorova

Uncovering the intellectual core of the information systems discipline

What is the intellectual core of the information systems discipline? This study uses latent semantic analysis to examine a large body of published IS research in order to address this question. Specifically, the abstracts of all research papers over the time period from 1985 through 2006 published in three top IS research journals-MIS Quarterly, Information Systems Research, and Journal of Management Information Systems-were analyzed. This analysis identified five core research areas: (1) information technology and organizations; (2) IS development; (3) IT and individuals; (4) IT and markets; and (5) IT and groups. Over the time frame of our analysis, these core topics have remained quite stable. However, the specific research themes within each core area have evolved significantly, reflecting research that has focused less on technology development and more on the social context in which information technologies are designed and used. As such, this analysis demonstrates that the information systems academic discipline has maintained a relatively stable research identity that focuses on how IT systems are developed and how individuals, groups, organizations, and markets interact with IT.

Business intelligence success: The roles of BI capabilities and decision environments

This study examines the role of the decision environment in how well business intelligence (BI) capabilities are leveraged to achieve BI success. We examine the decision environment in terms of the types of decisions made and the information processing needs of the organization. Our findings suggest that technological capabilities such as data quality, user access and the integration of BI with other systems are necessary for BI success, regardless of the decision environment. However, the decision environment does influence the relationship between BI success and capabilities, such as the extent to which BI supports flexibility and risk in decision making.

Business process research: a cross‐disciplinary review

Purpose – The paper aims to provide a comprehensive overview of business processes (BPs) literature by identifying and discussing key BP‐related research themes and suggesting directions for future research.Design/methodology/approach – Latent semantic analysis was used to analyze the abstracts of academic articles related to BP. Over 2,700 articles that use the term “business process (BP)” in their title, abstract or keywords were identified through electronic journals database EBSCOHost and examined.Findings – The results clearly indicate growing interest in BP research during the past 20 years. The key research themes can be classified into core and associated BP research. Core BP research deals with four cornerstones of BP change: BP design, information technology, BP implementation, and ongoing BP management. The associated BP research lies on the intersection of BP and other research areas such as total quality management, supply chain management, e‐commerce, etc.Research limitations/implications – ...

Factors influencing business intelligence (BI) data collection strategies: An empirical investigation

This paper examines external pressures that influence the relationship between an organizations business intelligence (BI) data collection strategy and the purpose for which BI is implemented. A model is proposed and tested that is grounded in institutional theory, research about competitive pressure, and research about the purpose of BI. Two data collection strategies (comprehensive and problem driven) and three BI purposes (insight, consistency, and transformation) are examined. Findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI.

Business Intelligence (BI) Success And The Role Of BI Capabilities

Business intelligence (BI) has become the top priority for many organizations who have implemented BI solutions to improve their decision-making process. Yet, not all BI initiatives have fulfilled the expectations. We suggest that one of the reasons for failure is the lack of an understanding of the critical factors that define the success of BI applications, and that BI capabilities are among those critical factors. We present findings from a survey of 116 BI professionals that provides a snapshot of user satisfaction with various BI capabilities and the relationship between these capabilities and user satisfaction with BI. Our findings suggest that users are generally satisfied with BI overall and with BI capabilities. However, the BI capabilities with which they are most satisfied are not necessarily the ones that are the most strongly related to BI success. Of the five capabilities that were the most highly correlated with overall satisfaction with BI, only one was specifically related to data. Another interesting finding implies that, although users are not highly satisfied with the level of interaction of BI with other systems, this capability is highly correlated with BI success. Implications of these findings for the successful use and management of BI are discussed. Copyright

The influence of website dimensionality on customer experiences, perceptions and behavioral intentions: An exploration of 2D vs. 3D web design

Abstract As online retailers seek to attract customers through innovative electronic storefront designs, some are experimenting with three-dimensional (3D) websites. This study examines the influence of website dimensionality on cognitive absorption, perceived ease of use, and, indirectly, perceived website usefulness and intentions to buy online using the website. Findings indicate that shopping websites using 3D environments are associated with lower perceived ease of use and lower cognitive absorption, compared to traditional 2D websites. The effect of website dimensionality on cognitive absorption is moderated by user experience. The implications of the study for research and practice are discussed.

The Dual Micro/macro Informing Role of Social Network Sites: Can Twitter Macro Messages Help Predict Stock Prices?

Introduction Emergence and proliferation of social media is one of the most significant trends of the 2000s. Starting with the establishment of Friendster in 2003 as the first large-scale social networking site (Boyd, 2006), a mere 8 years has seen the Internet territory explode with a variety of Social Networking Sites (SNS) which cater to different user categories and are tailored for different purposes. The widespread adoption and popularity of these websites has generated interest from consumers, companies, and researchers alike. Consumers have discovered the value of social network sites and are flocking to them in droves. Social networking sites as a whole almost doubled in unique visitors per month from around 115 million in July of 2007, to just over 200 million in April of 2011 according to one measure (MarketingProfs.com, 2011), and as of June 2012, unique visits to social networking sites have increased by 6% every year (Perez, 2012). Companies are striving to capitalize on the trend of consumer engagement in a variety of ways. Some are using SNS to find new customers (Kulikowski, 2011), to market to existing customers and build their brand (R2Integrated, 2010), and as a new avenue for customer communication for many top U.S. companies (Farfan, 2011). An emerging group of financial traders is closely monitoring SNS for information, crowd pulse, and connection with each other (Harris & Rogers, 2011). The majority of research on SNS is focused on use, adoption, privacy and security issues of SNS (Fogel & Nehmad, 2009; Shen & Khalifa, 2010). SNS generate large volumes of data which in aggregate contain useful information about views and opinions of SNS users. Several studies have investigated the ways to interpret and utilize the information contained in SNS-generated data (e.g., Naaman, Becker, & Gravano, 2011; Taraszow, Aristodemou, Shitta, Laouris, & Arsoy, 2010). This suggests that SNS play a dual role. On the one hand they provide infrastructure for individual informers to deliver messages to individual clients. On the other hand, due to a largely public nature of the individual message exchange, SNS themselves serve as informers providing aggregate information to clients. The goal of this paper is to introduce and validate a framework for understanding the dual role of SNS as platforms for exchanging micro messages and as macro informers. To validate the micro/macro informing framework, we examine if Twitter can serve as a macro informer to the stock market. By applying text mining techniques to SNS messages for the purpose of stock market prediction, this paper represents transdisciplinary research in the fields of information systems and finance, and thus contributes to the goal of Informing Science transdiscipline to reward and encourage research that crosses disciplinary boundaries (Cohen, 2009). In the next section we provide a brief overview of key types of SNS and discuss prior work related to mining the information from SNS sites. We then formally introduce the micro/macro informing framework. We continue with our research methodology and present the results of our analysis. We conclude with a discussion of implications for practice and research. Overview The term social networking site generally refers to those websites and their derived applications that deliver innovative online communication within and among a persons various social networks. SNS typically share a common set of features which include a profile (representation and/or description) for each user, the means to build and manage a personal relational network (i.e., friends, family, acquaintances, etc.), and access to creative methods to communicate with members of their relational network and the online community (Magro, Ryan, Sharp, & Ryan, 2008). SNS have grown in popularity at a tremendous rate in the past several years. Facebook, which has emerged as the dominant SNS, reported 900 million active users in April of 2012 (Goldman, 2012). …

The Effect of Network Characteristics on Online Identity Management Practices

ABSTRACT As online social networking permeates all aspects of personal and professional lives, users of social networking sites (SNSs) are more motivated than ever to manage their online identities to project a favorable impression of themselves to online audiences. This research builds on the boundary management perspective to gain a better understanding of online identity management practices by examining the relationship between characteristics of the online social network, including cognitive homogeneity and social tie variety and the use of identity management practices such as segmentation and self-enhancement. The proposed research model is tested using survey data. The findings suggest cognitive homogeneity is positively related to the use of both identity management practices, segmentation and self-enhancement, whereas social tie variety is positively related to segmentation, but not self-enhancement practices. We conclude with implications of the study results for research and practice, as well as a discussion of directions for future research.

The effect of business process configurations on user motivation

Purpose – The purpose of this paper is to understand how business process configurations influence motivation among process participants. Design/methodology/approach – An experiment was conducted in which business process rules complexity, work backlog, and case distribution method were manipulated. Participant motivation and its antecedents were measured using a survey. Findings – The study finds that business process configurations influence the motivation of process participants through their effect on perceived competence. Increasing business process rules complexity reduces competence. The effect of case distribution method on competence depends on backlog. Sequential distribution undermines competence in the presence of backlog, and enhances competence when backlog is absent. However, batch distribution results in higher competence in the presence of backlog than in its absence. Research limitations/implications – The study confirms the applicability of self-determination theory for analyzing the ef...

Improving Decision Quality: The Role of Business Intelligence

ABSTRACT This exploratory study provides a validated, parsimonious research model of antecedents of the perception of the quality of decisions made using business intelligence support. Findings provide insight into little investigated avenues such as the role of problem space complexity in perceived decision quality as well as indicate a more complex interplay among the antecedents of decision quality than heretofore examined. For example, results suggest that there may be a tipping point for which information quality and use of the system support higher perceived decision quality. In addition, these findings provide a direction for future research to generate deeper, more meaningful contributions in our collective understanding of how business intelligence (BI) serves to improve the quality of decision-making.