Journal of the Association for Information Systems

Understanding Online Health Information Use: The Case of People with Physical Disabilities

Huigang Liang et al. — Wed, 28 Jun 2017 12:42:10 PDT

In this paper, we study the online health information use behavior of people with physical disabilities. Drawing on rational choice theory and IS success model, we develop a contextualized research model to explain how individuals’ level of physical disability moderates the effects of object- and outcome-based beliefs. We empirically tested the model with survey data from 243 online users with physical disabilities. The results show that perceived benefit enhances, whereas perceived risk reduces, online health information use. Information quality and system quality increase perceived benefit and mitigate perceived risk. In addition, we found that accuracy, completeness, currency, and transparency of online health information predict information quality, whereas accessibility, navigability, and readability of online health information predict system quality. More importantly, we found that physical disability weakens the effect of information quality on perceived risk, strengthens the effect of system quality on perceived risk, and strengthens the effect of perceived benefits on information use. This research contributes to the IS literature by focusing on the minority group of people with physical disabilities and providing an in-depth understanding of their online health information use behavior.

Evaluating Business Process Maturity Models

Amy Van Looy et al. — Wed, 28 Jun 2017 12:42:05 PDT

Maturity models have become important aids to support process improvement. However, researchers have frequently criticized the many business process maturity models (BPMMs) for differing in quality, which creates a demand for comparing and evaluating these models. This paper describes a well-founded, ranked, and weighted set of critical criteria for BPMMs that are most important to prospective users. The paper also demonstrates how this set can serve as a standard or guideline for designing BPMMs. In evaluating the used sample of BPMMs against the set of criteria, we reveal gaps and shortcomings of current BPMMs, make suggestions for raising the quality of BPMMs, and highlight future research avenues.

Examining Real Options Exercise Decisions in Information Technology Investments

Sarah Shafiq Khan et al. — Fri, 26 May 2017 19:48:47 PDT

Researchers have advocated real options thinking (ROT) for evaluating and managing risky IT investments to account for managerial decision flexibility. Effective ROT is a three-step process that requires managers to recognize, value, and exercise options embedded in IT projects. Prior research has illustrated the existence of managerial bias in the recognizing and valuing real options. However, little research has examined real options exercise decisions. Hence, we use prospect theory to examine whether IT managers demonstrate systematic biases while exercising real options in IT projects and portfolios. We also study whether one can control or mitigate such biases. We found evidence of biased (suboptimal) real option exercise decisions in IT projects and in IT portfolios. However, we found differences in biased decision making between a single project and a portfolio scenario. We also found that project scale and real option type influenced vulnerability of a project to biased decision making. In addition, simplifying the presentation of the net effects of real options exercise decisions can help reduce bias, especially for large project portfolios. We discuss the implications of these results on theory and practice.

Heuristic Principles and Differential Judgments in the Assessment of Information Quality

Ofer Arazy et al. — Fri, 26 May 2017 19:48:43 PDT

Information quality (IQ) is a multidimensional construct and includes dimensions such as accuracy, completeness, objectivity, and representation that are difficult to measure. Recently, research has shown that independent assessors who rated IQ yielded high inter-rater agreement for some information quality dimensions as opposed to others. In this paper, we explore the reasons that underlie the differences in the “measurability” of IQ. Employing Gigerenzer’s “building blocks” framework, we conjecture that the feasibility of using a set of heuristic principles consistently when assessing different dimensions of IQ is a key factor driving inter-rater agreement in IQ judgments. We report on two studies. In the first study, we qualitatively explored the manner in which participants applied the heuristic principles of search rules, stopping rules, and decision rules in assessing the IQ dimensions of accuracy, completeness, objectivity, and representation. In the second study, we investigated the extent to which participants could reach an agreement in rating the quality of Wikipedia articles along these dimensions. Our findings show an alignment between the consistent application of heuristic principles and inter-rater agreement levels found on particular dimensions of IQ judgments. Specifically, on the dimensions of completeness and representation, assessors applied the heuristic principles consistently and tended to agree in their ratings, whereas, on the dimensions of accuracy and objectivity, they not apply the heuristic principles in a uniform manner and inter-rater agreement was relatively low. We discuss our findings implications for research and practice.

Brownie: A Platform for Conducting NeuroIS Experiments

Anuja Hariharan et al. — Fri, 28 Apr 2017 20:25:30 PDT

In the NeuroIS field, experimental software needs to simultaneously present experimental stimuli to participants while recording, analyzing, or displaying neurophysiological measures. For example, a researcher might record a user’s heart beat (neurophysiological measure) as the user interacts with an e-commerce website (stimulus) to track changes in user arousal or show a user’s changing arousal levels during an exciting game. In this paper, we identify requirements for a NeuroIS experimental platform that we call Brownie and present its architecture and functionality. We then evaluate Brownie via a literature review and a case study that demonstrates Brownie’s capability to meet the requirements in a complex research context. We also verify Brownie’s usability via a quantitative study with prospective experimenters who implemented a test experiment in Brownie and an alternative software. We summarize the salient features of Brownie as follows: 1) it integrates neurophysiological measurements, 2) it incorporates real-time processing of neurophysiological data, 3) it facilitates research on individual and group behavior in the lab, 4) it offers a large variety of options for presenting experimental stimuli, and 5) it is open source and easily extensible with open source libraries. In summary, we conclude that Brownie is innovative in its potential to reduce barriers for IS researchers by fostering replicability and research collaboration and to support NeuroIS and interdisciplinary research in cognate areas, such as management, economics, or human-computer interaction.

Representing Crowd Knowledge: Guidelines for Conceptual Modeling of User-generated Content

Roman Lukyanenko et al. — Fri, 28 Apr 2017 20:25:25 PDT

Organizations’ increasing reliance on externally produced information, such as online user-generated content (UGC) and crowdsourcing, challenges common assumptions about conceptual modeling in information systems (IS) development. We demonstrate UGC’s societal importance, analyze its distinguishing characteristics, identify specific conceptual modeling challenges in this setting, evaluate traditional and recently proposed approaches to modeling UGC, propose a set of conceptual modeling guidelines for developing IS that harness structured UGC, and demonstrate how to implement and evaluate the proposed guidelines using a case of development of a real crowdsourcing (citizen science) IS. We conclude by considering implications for conceptual modeling research and practice.

An Extensive Examination of Regression Models with a Binary Outcome Variable

Suneel Babu Chatla et al. — Fri, 28 Apr 2017 20:25:21 PDT

Linear regression is among the most popular statistical models in social sciences research, and researchers in various disciplines use linear probability models (LPMs)—linear regression models applied to a binary outcome. Surprisingly, LPMs are rare in the IS literature, where researchers typically use logit and probit models for binary outcomes. Researchers have examined specific aspects of LPMs’ but not thoroughly evaluated their practical pros and cons for different research goals under different scenarios. We perform an extensive simulation study to evaluate the advantages and dangers of LPMs, especially with respect to big data, which is now common in IS research. We evaluate LPMs for three common uses of binary outcome models: inference and estimation, prediction and classification, and selection bias. We compare its performance to logit and probit under different sample sizes, error distributions, and more. We find that coefficient directions, statistical significance, and marginal effects yield results similar to logit and probit. In addition, LPM estimators are consistent for the true parameters up to a multiplicative scalar. This scalar, although rarely required, can be estimated assuming an appropriate error distribution. For classification and selection bias, LPMs are on par with logit and probit models in terms of class separation and ranking and is a viable alternative in selection models. LPMs are lacking when the predicted probabilities are of interest because predicted probabilities can exceed the unit interval. We illustrate some of these results by modeling price in online auctions using data from eBay.

Political Maneuvering During Business Process Transformation: A Pluralist Approach

Sune D. Müller et al. — Wed, 29 Mar 2017 17:14:51 PDT

For years, managers have tried to improve organizational performance through business process transformation (BPT), and their experiences have informed IS research and practice. Although extant theory acknowledges the political nature of these dynamic transformation initiatives, researchers have yet to empirically investigate and theorize how organizational politics impacts BPT behaviors and outcomes. Drawing on a pluralist methodology, we present an embedded case study of a company-wide BPT project across four business units at the high-tech firm Terma. First, we apply different perspectives on organizational politics to develop detailed accounts of each business unit's response to the transformation initiative, which reveals four distinct patterns of BPT politics: “applying the hammer”, “struggling to engage”, “walking the talk”, and “keeping up appearances”. Next, we combine the empirical findings with extant literature to theorize how transformation agents and process users engage in politics during BPT implementation. As a result, our research leverages a pluralist approach to show how alternative political perspectives and forms of politics can help managers maneuver BPT initiatives in their roles as transformation agents and process users.

Management Misinformation Systems: A Time to Revisit?

Kalle Lyytinen et al. — Wed, 29 Mar 2017 17:14:47 PDT

In this essay, we revisit Ackoff’s (1967) classic “Management Misinformation Systems” and its five myths. The paper appeared at the dawn of the information systems (IS) field and shattered popular assumptions about designing and using IS. The paper shaped the direction and scope of scholarly discourse around information systems; in contrast to dominant claims at that time, he argued that managers swam in the abundance of irrelevant information, were victims of poor modeling and, consequently, poor understanding of their own decisions, participated in destructive communication due to conflicting goals, and had a poor understanding of how systems worked. Despite the passage of 50 years (and many revolutions in information technology), researchers in the IS field still regard Ackoff’s arguments as valid and rarely debate them. Yet, given the new information-rich environments and our nearly limitless capability to collect and analyze data, we may need to reexamine these arguments to correctly frame information systems’ contemporary effects on managerial decision making. We scrutinize Ackoff’s five assumptions in light of today’s IT and data-rich environments and identify key tenets that will reframe the disciplinary discourse concerning the effects of information systems. We identify significant shifts in research on decision making including the role of abduction, data layering and options, and intelligence augmentation. We honor the extraordinary legacy of Ackoff’s remarkable paper as an IS scholar by shaping the field’s future inquiries in the spirit of the original paper.

The Online Waiting Experience: Using Temporal Information and Distractors to Make Online Waits Feel Shorter

Younghwa (Gabe) Lee et al. — Wed, 29 Mar 2017 17:14:42 PDT

Research on how to manage the online waiting experience has begun to emerge but has primarily focused on the use of distracting cues for online wait management (e.g., text and images that distract the user from the wait). The use of temporal information in waiting webpages (e.g., text and images that convey the duration of the wait) has received little attention from the information systems literature, and we have limited understanding about how the two types of cues (temporal information and distractors) affect wait time estimation. We address this gap by developing a theoretical model of how these cues affect the waiting experience and perceived waiting time. We tested the model with a 2 x 2 x 2 x 2 controlled lab experiment and 1025 participants using progress bar treatments that included temporal information (spatial and text description of the wait time duration) and distractors (progress bar animation and accelerated filling of the progress bar) with both short and long wait conditions. We found that the two types of cues reduced perceived waiting time through different nomological paths. Temporal cues reduced perceived uncertainty about the wait, while distractor cues directed attention away from the wait, increasing perceived enjoyment and wait time distortion. Further, the enhanced waiting experience reduced the perceived waiting time. Further, these cues were effective in managing the online waiting experience with both short and long waits.

Challenging Dominant Frames in Policies for IS Innovation in Healthcare through Rhetorical Strategies

Roberta Bernardi et al. — Tue, 28 Feb 2017 15:04:42 PST

Information systems (IS) innovation in healthcare is a contested area often characterized by complex and conflicted relationships among different stakeholders. In this paper, we provide a systematic understanding of the mechanisms through which various actors translate competing visions about health sector reforms into policy and action and, thus, generate contradictions in IS innovation. We argue that we can learn more about the source of such contradictions by examining how competing frames can affect IS innovation in healthcare. We adopt frame theory and rhetorical strategies analysis in the case of health sector reforms in Kenya and focus specifically on the deployment of health information systems (HIS). We make several contributions. First, we demonstrate that policy actors’ adherence to the interests and values represented in a frame is important in determining the choice of a rhetorical strategy and its influence on policy transformation and IS innovation. Second, we develop an understanding of how technology mediates the rhetorical strategies of different actors. In particular, we demonstrate the role of technology in giving continuity to frames, which affects policy change and IS innovation.

An Integrated Temporal Model of Belief and Attitude Change: An Empirical Test With the iPad

David Xu et al. — Tue, 28 Feb 2017 15:04:38 PST

Bhattacherjee and Premkumar (2004) propose a temporal model of belief and attitude change to understand fluctuating patterns of information technology (IT) usage. However, they overlook the role of perceived enjoyment in the process of temporal IT usage. Perceived enjoyment has become an increasingly important part of how consumers assess technology. Thus, we build on Bhattacherjee and Premkumar’s model (BP model) and propose a new model by investigating the comparative role of perceived usefulness (PU) and perceived enjoyment (PE) for explaining temporal changes in users’ beliefs and attitudes toward IT usage. We name our proposed model the integrated temporal model (ITM). Through an empirical study of iPad usage in a classroom setting at three different stages, we found that 1) the effect of PE on PU was stronger at the pre-usage (vs. post-usage) stage and that its effect was stronger at the initial-usage (vs. later-usage) stage; 2) while PE has a stronger effect than PU on attitude at both pre-usage and initial-usage stages, that was not the case at the later-usage stage; instead, the effect of PU on attitude was stronger at the later-usage (vs. initial-usage) stage; 3) the effect of disconfirmation on modified PU and PE was stronger at the initial (vs. later) stage, while the effect of PU and PE expectation on modified PU and PE was weaker at the initial (vs. later) stage. Our study extends the BP model to IT with hedonic elements (i.e., the iPad) and is the first of its kind to empirically examine the combined and relative impact of PU and PE on the temporal usage of IT with hedonic elements in the classroom setting.

Use of Online Social Networking Services from a Theoretical Perspective of the Motivation-Participation-Performance Framework

Mohammad Salehan et al. — Tue, 28 Feb 2017 15:04:35 PST

Social networking services (SNS) are platforms to form and manage personal connections and create a foundation for human relationships. Intending to identify why, how, and for what outcome users use SNS, this study contributes to the body of knowledge on SNS by analyzing how motivation, participation, and performance are related to each other in the SNS context. Drawing on a theoretical perspective of the motivation-participation-performance framework, we identify four significant why motivations (i.e., vertical social, horizontal social, hedonic, and utilitarian motivations), two main ways (how) of participation (i.e., sharing and collaboration), and two ultimate benefits (for what outcome) of SNS use (i.e., personal and job performance). The analyzed results of empirical data collected from SNS users indicate that the identified motivations significantly influence participation in sharing and collaboration activities on SNS and that SNS participation significantly affects personal and professional/job-related performance. This study contributes to theory by providing a multidimensional view of SNS use, its predictors, and its consequences.

Software Piracy in the Presence of Open Source Alternatives

Fernando S. Machado et al. — Tue, 31 Jan 2017 09:32:31 PST

We develop a model to investigate the manner in which the pricing, profitability, and protection strategies of a seller of a proprietary digital good respond to changing market conditions. Specifically, we investigate how product piracy and the presence of open source software alternatives (such as Open Office) impact the optimal strategy of a seller of proprietary software (such as Microsoft Office). In contrast to previous literature, we show that firms may make more (rather than less) effort to control piracy when network externalities are strong. In addition, we show that the level of network externalities amplifies losses incurred by an incumbent due to high-quality pirated goods. Therefore, for products characterized by high network externalities (such as software), sellers need to try to maintain a large perceived quality gap between their product and illegal copies. Further, we demonstrate that the appearance of an OSS alternative leads the incumbent to reduce both price and the level of piracy control. Although high-quality pirated goods are detrimental to profits in the absence of OSS, they may actually limit the incumbent’s losses and the need to adjust price and protection strategies due to the introduction of an OSS alternative. Thus, an incumbent may find it easier to compete with OSS in the presence of product piracy. Finally, highly correlated intrinsic valuation between an incumbent and OSS products require smaller adjustments to price and piracy controls and leads to muted impact on incumbent profit.

Got Phished? Internet Security and Human Vulnerability

Sanjay Goel et al. — Tue, 31 Jan 2017 09:32:28 PST

A leading cause of security breaches is a basic human vulnerability: our susceptibility to deception. Hackers exploit this vulnerability by sending phishing emails that induce users to click on malicious links that then download malware or trick the victim into revealing personal confidential information to the hacker. Past research has focused on human susceptibility to generic phishing emails or individually targeted spear-phishing emails. This study addresses how contextualization of phishing emails for targeted groups impacts their susceptibility to phishing. We manipulated the framing and content of email messages and tested the effects on users’ susceptibility to phishing. We constructed phishing emails to elicit either the fear of losing something valuable (e.g., course registrations, tuition assistance) or the anticipation of gaining something desirable (e.g., iPad, gift card, social networks). We designed the emails’ context to manipulate human psychological weaknesses such as greed, social needs, and so on. We sent fictitious (benign) emails to 7,225 undergraduate students and recorded their responses. Results revealed that contextualizing messages to appeal to recipients’ psychological weaknesses increased their susceptibility to phishing. The fear of losing or anticipation of gaining something valuable increased susceptibility to deception and vulnerability to phishing. The results of our study provide important contributions to information security research, including a theoretical framework based on the heuristic-systematic processing model to study the susceptibility of users to deception. We demonstrate through our experiment that several situational factors do, in fact, alter the effectiveness of phishing attempts.

Communicating Personal Health Information in Virtual Health Communities: An Integration of Privacy Calculus Model and Affective Commitment

Nima Kordzadeh et al. — Tue, 31 Jan 2017 09:32:24 PST

Health consumers such as patients and caregivers often join virtual health communities (VHCs) to seek and provide health-related information and emotional support. To do so, they converse with other individuals in platforms such as public discussion boards and blogs. During these online conversations, people may communicate their personal health information (PHI) to others. A potential driver for this form of revealing PHI is the immediate positive outcomes that it can provide for contributors and the community. PHI disclosure, however, can entail privacy risks and concerns for community members, which may ultimately hamper their participation in those communities. Moreover, one’s emotional attachment to a VHC (namely, affective commitment) may influence one’s PHI sharing behaviors in that community. Thus, to understand how various factors impact communicating PHI in public VHC discussions, we drew on the privacy calculus model and the notion of affective commitment, developed a theoretical model, and empirically tested the model. To do so, we administered a survey to individuals from three different populations including students, faculty, and staff at a large university and visitors to clinics. We performed a set of hierarchical moderated multiple regressions on the dataset. The results revealed that privacy concerns along with expected personal and community-related outcomes of communicating PHI affected willingness to communicate PHI in public VHC discussions. The results, however, refuted the hypothesized direct and moderating effects of affective commitment on willingness to share PHI in these virtual platforms. The findings of this study provide contributions to research and practice.

Understanding the Role of IS and Application Domain Knowledge on Conceptual Schema Problem Solving: A Verbal Protocol Study

Vijay Khatri et al. — Wed, 28 Dec 2016 20:34:25 PST

One of the most neglected areas of information systems research is the role of the domain to which researchers apply IS methods, tools, and techniques; that is, the application domain. For example, little prior information systems (IS) or related research has examined how IS and application domain knowledge (ISDK and ADK, respectively) influence how individuals solve conceptual schema problem-solving tasks. In this research, we investigate the effects of both ISDK and ADK on two types of conceptual schema problem-solving tasks: schema based and inferential. We used verbal protocol analysis to explore the roles that ISDK and ADK play in the problem-solving processes participants use when addressing these tasks. We found that, for the two types of conceptual schema problem-solving tasks, ADK and ISDK have similar effects on problem-solving processes. That is, we found that, for schema-based problem-solving tasks, participants used focused (depth-first) processes when the application domain was familiar as did participants with greater IS domain knowledge. We also found that, for inferential problem-solving tasks, participants used exploratory (breadth-first) processes when the application domain was familiar as did participants with greater IS domain knowledge. We then show how cognitive psychology literature on problem solving can help explain the effects of ISDK and ADK and, thus, provide the theoretical foundation for analyzing the roles of each type of knowledge in the process of IS problem solving.

Enhancing Analysts’ Mental Models for Improving Requirements Elicitation: A Two-stage Theoretical Framework and Empirical Results

Padmal Vitharana et al. — Wed, 28 Dec 2016 20:34:20 PST

Research has extensively documented the importance of accurate system requirements in avoiding project delays, cost overruns, and system malfunctions. Requirement elicitation (RE) is a critical step in determining system requirements. While much research on RE has emerged, a deeper understanding of three aspects could help significantly improve RE: 1) insights about the role and impacts of support tools in the RE process, 2) the impact of using support tools in multiple stages of the RE process, and 3) a clear focus on the multiplicity of perspectives in assessing RE outcomes. To understand how using support tools could improve RE, we rely on the theoretical lens of mental models (MM) to develop a dynamic conceptual model and argue that analysts form mental models (MMs) of the system during RE and these MMs impact their outcome performance. We posit that one can enhance analysts’ MMs by using a knowledge-based repository (KBR) of components and services embodying domain knowledge specific to the target application during two key stages of RE, which results in improved RE outcomes. We measured the RE outcomes from user and analyst perspectives. The knowledge-based component repository we used in this research (which we developed in collaboration with a multi-national company) focused on insurance claim processing. The repository served as the support tool in RE in a multi-period lab experiment with multiple teams of analysts. The results supported the conceptualized model and showed the significant impacts of such tools in supporting analysts and their performance outcomes at two stages of RE. This work makes multiple contributions: it offers a theoretical framework for understanding and enhancing the RE process, develops measures for analysts’ mental models and RE performance outcomes, and shows the process by which one can improve analysts’ RE performance through access to a KBR of components at two key stages of the RE process.

Culture, Conformity, and Emotional Suppression in Online Reviews

Yili Hong et al. — Wed, 30 Nov 2016 11:23:54 PST

In this study, we examine consumers’ cultural background as an antecedent of online review characteristics. We theoretically propose and empirically examine the effect of cultural background (specifically individualism (versus collectivism)) on consumers’ tendency to conform to prior opinion and review texts’ emotionality. We also examine how conformity and emotionality relate to review helpfulness. We test our hypotheses using a unique dataset that combines online restaurant reviews from TripAdvisor with measures of individualism/collectivism values. We found that consumers from a collectivist culture were less likely to deviate from the average prior rating and to express emotion in their reviews. Moreover, individuals perceived those reviews that exhibited high conformity and intense emotions to be less helpful. We also present several important implications for managing online review platforms in light of these findings, which reflect the previously unidentified drivers of systematic differences in the characteristics of online reviews.

Overconfidence in Phishing Email Detection

Jingguo Wang et al. — Wed, 30 Nov 2016 11:15:11 PST

This study examines overconfidence in phishing email detection. Researchers believe that overconfidence (i.e., where one’s judgmental confidence exceeds one’s actual performance in decision making) can lead to one’s adopting risky behavior in uncertain situations. This study focuses on what leads to overconfidence in phishing detection. We performed a survey experiment with 600 subjects to collect empirical data for the study. In the experiment, each subject judged a set of randomly selected phishing emails and authentic business emails. Specifically, we examined two metrics of overconfidence (i.e., overprecision and overestimation). Results show that cognitive effort decreased overconfidence, while variability in attention allocation, dispositional optimism, and familiarity with the business entities in the emails all increased overconfidence in phishing email detection. The effect of perceived self-efficacy of detecting phishing emails on overconfidence was marginal. In addition, all confidence beliefs poorly predicted detection accuracy and poorly explained its variance, which highlights the issue of relying on them to guide one’s behavior in detecting phishing. We discuss mechanisms to reduce overconfidence.