Measuring the Return on Information Technology: A Knowledge-Based Approach for Revenue Allocation at the Process and Firm Level

This paper proposes an approach for measuring the return on Information Technology (IT) investments. A review of existing methods suggests the difficulty in adequately measuring the returns of IT at various levels of analysis (e.g., firm or process level). To address this issue, this study aims to develop a method for allocating the revenue and cost of IT initiatives at any level of analysis using a common unit of measurement. Following the knowledge-based view (KBV), this paper proposes an analytic method for measuring the historical revenue and cost of IT investments by estimating the amount of knowledge necessary to generate a common unit of output from any business process. The amount of required knowledge is operationalized using the ¡®average learning time\u27 measure. The proposed operationalization is illustrated with a practical case example. The proposed KBV approach is extended specifically for IT resources, allowing us to assess the Return on IT (ROIT) using a typical productivity ratio (similar to ROI or ROA) that accurately captures the true business value of IT (despite any complementarities) at virtually any level of analysis

Tutorial on Latent Growth Models for Longitudinal Data Analysis

This tutorial introduces Latent Growth Modeling (LGM) as a promising new method for analyzing longitudinal data when interested in understanding the process of change over time. Given the need to go beyond cross-sectional models in IS research, explore complex longitudinal IS phenomena, and test Information Systems (IS) theories over time, LGM is proposed as a complementary method to help IS researchers propose time-dependent hypotheses and make longitudinal inferences about IS theories. The tutorial leader will explain the importance of theorizing patterns of change over time, how to propose longitudinal hypotheses, and how LGM can help test such hypotheses. All three tutorial facilitators will describe the tenets of LGM and offer guidelines for applying LGM in IS research including framing time-dependent hypotheses that can be readily tested with LGM. The three tutorial facilitators will also explain how to use LGM in SAS 9.2 with a hands-on application that will attempt to model the complex longitudinal relationship between IT and firm performance using longitudinal data from Fortune 1000 firms. The tutorial facilitators will also draw comparisons with other existing methods for modeling longitudinal data and they will also discuss the advantages and disadvantages of LGM for identifying longitudinal patterns in data

FIT DOES MATTER! AN EMPIRICAL STUDY ON PRODUCT FIT UNCERTAINTY IN ONLINE MARKETPLACES

This paper examines the antecedents and consequences of product uncertainty in online marketplaces by conceptualizing the dimensions of product uncertainty - description uncertainty (identifying product characteristics), performance uncertainty (inferring product‟s future performance) and fit uncertainty (matching product‟s characteristics with buyer‟s needs), with the focus on product fit uncertainty. It also theorizes the distinction, relationship, and effects of the three dimensions of product uncertainty. Finally, it proposes a set of IT artifacts to reduce product fit uncertainty. The hypotheses are tested with survey and website transaction data from 274 buyers in Taobao, the largest online marketplace in China. The results first demonstrate the distinction between three dimensions of product uncertainty, show that relative to description and performance uncertainty, only fit uncertainty has significant effect on price premiums, satisfaction, product returns, and repurchase intentions, and support the effects of the use of IT artifacts, such as instant messenger, product forums, and decision support tools on reducing fit uncertainty. Implications for research, theory and practice are discussed

Does Online Reputation Matter? An Empirical Investigation of Reputation and Trust in Online Auction Markets

Trust is an essential component of buyer-seller relationships, especially for online transactions. Appropriate feedback mechanisms help buyers build trust towards reputable sellers. Drawing from sociology and economics, we show that buyers pay a price premium to transact with reputable sellers, especially for expensive products. To empirically examine the relationship between feedback and price premiums, we collected data for 19 products from 702 completed online auctions from the auction site of ebay.com (www.ebay.com). Results showed a significant correlation between feedback and price premiums for all products. This correlation became increasingly significant for more expensive products. This paper contributes to a better understanding of the value of reputation and trust in EC

Latent Growth Modeling in IS Research: Basic Tenets, Illustration, and Practical Guidelines

This paper introduces Latent Growth Modeling (LGM) as a feasible method for analyzing longitudinal data to understand the process of change over time. Given the need to go beyond cross-sectional models, explore longitudinal Information Systems (IS) phenomena, and test IS theories over time, LGM is proposed as a complementary method to help IS researchers propose and evaluate time-centric hypotheses and make longitudinal inferences. The paper first describes the basic tenets of LGM and offers guidelines for using LGM in IS research, including framing hypotheses with time as a central component and implementing LGM models to test these hypotheses. The application of LGM in IS research is illustrated by modeling the longitudinal relationship between two IT variables (IT infrastructure and IT labor) and firm performance with 2001-2004 data from Fortune 1000 firms. Comparisons with other methods for analyzing longitudinal data reveal the advantages of LGM for studying time-dependent relationships and growth patterns

Does the Adoption of EMR Systems Inflate Medicare Reimbursements?

The adoption of EMR systems has been argued to lead to physicians “upcoding” their patients to inflate insurance reimbursements. In this paper, we examine if the adoption of the Clinical Physician Order Entry (CPOE) system is associated with an increase in the complexity of the patients\u27 case mix that hospitals report (termed upcoding ). We make use of a staggered roll-out of the Recovery Audit Program to combat upcoding as a natural experiment to assess the impact of the adoption of the CPOE systems on the case mix that a hospital reports. We find that on average the adoption of CPOE systems is associated with an increase in the reported case mix of hospitals, and that the Audit program has had an effect on reducing the case mix that hospitals report to Medicare for reimbursement. Implications for preventing inflated reimbursements due to upcoding are discussed

Incorporating Social Presence in the Design of the Anthropomorphic Interface of Recommendation Agents: Insights from an fMRI Study

Recommendation agents (RAs) are regularly used in online environments to give consumers advice on products. Since social components of human-like RAs (humanoid avatars) are important components in their adoption and use, this study focuses on how the design of the anthropomorphic interface of RAs in terms of social demographics, namely ethnicity and gender, can enhance the RA’s social presence to facilitate their adoption. Since social presence has been shown in the literature to predict the adoption and use of RAs, we examine whether match or mismatch in terms of the anthropomorphic RA’s ethnicity and gender can enhance the user’s social interaction with an RA. To overcome concerns of social desirability bias and political correctness when users assess the social presence of RAs that vary in their ethnicity and gender, we conducted a functional Magnetic Resonance Imaging (fMRI) study to complement a traditional behavioral experiment. Our goal was to explain prior behavioral findings that showed that ethnicity (as opposed to gender) match is associated with higher social presence, particularly among women. Specifically, brain activity was captured in an fMRI scanner while users who varied on their ethnicity and gender to either match or mismatch the ethnicity and gender of four RAs evaluated each of the RAs on their social presence. Besides contributing to the neuroscience literature by identifying the brain activations that relate to social presence, the fMRI results shed light on the nature of social presence and explain earlier behavioral findings by showing gender differences in the neural correlates of social presence in terms of ethnicity and gender match and mismatch. Implications on designing anthropomorphic interfaces to embody social demographics to enhance social presence are discussed

Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces

The Internet interface poses a difficulty for buyers in evaluating products online, particularly physical experience and durable goods, such as used cars. This increases buyers' product uncertainty, defined as the buyer's perceived estimate of the variance in product quality based on subjective probabilities about the product's characteristics and whether the product will perform as expected. However, the literature has largely ignored product uncertainty and mostly focused on mitigating buyer's seller uncertainty. To address this void, this study aims to conceptualize the construct of product uncertainty and propose its antecedents and consequences in online auction marketplaces. First, drawing upon the theory of markets with asymmetric information, we propose product uncertainty to be distinct from, yet affected by, seller uncertainty. Second, based on auction pricing theory, we propose that product uncertainty and seller uncertainty negatively affect two key success outcomes of online marketplaces: price premium and transaction activity. Third, following information signaling theory, we propose a set of product information signals to mitigate product uncertainty: (1) online product descriptions (textual, visual, multimedia); (2) third-party product certifications (inspection, history report, warranty); (3) auction posted prices (reserve, starting, buy-it-now); and (4) intrinsic product characteristics (book value and usage). Finally, we propose that the effect of online product descriptions and intrinsic product characteristics on product uncertainty is moderated by seller uncertainty. The proposed model is supported by a unique dataset comprised of a combination of primary (survey) data drawn from 331 buyers who bid upon a used car on eBay Motors, matched with secondary transaction data from the corresponding online auctions. The results distinguish between product and seller uncertainty, show the stronger role of product uncertainty on price premiums and transaction activity compared to seller uncertainty, empirically identify the most influential product information signals, and support the mediating role of product uncertainty. This paper contributes to and has implications for better understanding the nature and role of product uncertainty, identifying mechanisms for mitigating product uncertainty, and demonstrating complementarities between product and seller information signals. The model's generalizability and implications are discussed

An Empirical Investigation on the Role of IT Materiality in Multidisciplinary Innovation

Knowledge needs to traverse through social and cognitive boundaries as it is transformed from information to innovation. Little is known, however, regarding what, if any, role various IT material constraints and affordances play in supporting multidisciplinary innovations involving the complexities of heterogeneous knowledge. The notion of affordance has been used in Human Computer Interaction (HCI) to describe the action opportunities afforded by IT functionalities. By IT materiality, we refer to a set of “features that provide opportunities for and constraints on actions” (Leonardi and Barley 2008). We propose and empirically test a model to address this gap by drawing from the concepts of affordance, social structure theory, and the design of IT functionalities. We hypothesize that the impact of cognitive heterogeneity on innovation performance will be mediated by knowledge coordination and perspective taking. Further, we hypothesize that this relationship will be moderated by the material affordances of IT

Leveraging Rich Communication Tools: Evidence of Online Trust and Guanxi in China

Driven by the evolution of consumer-to-consumer (C2C) online marketplaces, we examine the role of communication tools (i.e., an instant messenger, internal message box and a feedback system), in facilitating dyadic online transactions in the Chinese C2C marketplace. Integrating the Chinese concept of guanxi with theories of social translucence and social presence, we introduce a structural model that explains how rich communication tools influence a website’s interactivity and presence, subsequently building trust and guanxi among buyers and sellers, and ultimately predicting buyers’ repurchase intentions. The data collected from 185 buyers in TaoBao, China’s leading C2C online marketplace, strongly support the proposed model. We believe that this research is the first formal study to show evidence of guanxi in online C2C marketplaces, and it is attributed to the role of communication tools to enhance a website’s interactivity and presence