Nancy K. Lankton

Antecedents and determinants of information technology habit

IT researchers have recently distinguished habits from prior behavior frequency. We expanded this research by examining habits antecedents and investigating the simultaneous effect of habit and prior IT use on continued IT use. We found that the research model was relatively robust over four specific use activities of one software application. Indeed, prior IT use, satisfaction, and importance significantly influenced IT habits. Also, while prior IT use predicted continued IT use in the combined data set, habit only predicted continued IT use for activities with higher habit levels. Practical implications are discussed.

What does it mean to trust facebook?: examining technology and interpersonal trust beliefs

Researchers have recently studied technology trust in terms of the technological artifact itself. Two different kinds of trusting beliefs could apply to a website artifact. First, the trusting beliefs may relate to the interpersonal characteristics--competence, integrity, and benevolence. Second, they may relate to corresponding technology characteristics--functionality, reliability, and helpfulness. Since social networking websites like Facebook may demonstrate either interpersonal or technology trust characteristics, researchers may need to carefully choose the beliefs to model. Thus it is important to understand not only the conceptual meaning of these beliefs, but also whether human and technology trust beliefs are distinct. Using data collected from 362 university-student Facebook users, we test two second-order factor structures that represent alternative ways to model the three interpersonal and three technology trust beliefs. We find that the best-fitting measurement model depicts the three conceptually-related pairs of trust beliefs (competence-functionality, integrity-reliability, and benevolence-helpfulness) as three distinct second-order factors. This model outperformed the model splitting trusting beliefs into separate interpersonal and technology second-order factors. The results show people distinguish among three types of conceptually-related trust attributes, and that they trust Facebook as both a technology and a quasi-person. These second-order trust factors can be used in future research to better understand social networking trust and usage continuance intentions

Uncertainty and Industry Structure Effects on Managerial Intuition About Information Technology Real Options

Real options analysis is an important but costly tool for valuing many information technology (IT) investments. As a low-cost substitute for real options-based methods, firms often depend on managerial intuition, which sometimes approximates real options-based valuations and sometimes does not. Making good choices about how to value IT investments requires an understanding of why, and therefore when, intuitive judgment is more or less likely to be consistent with real options-based valuations. Field and survey studies have provided ex post observations of systematic variations in consistency by option type, but ex ante hypotheses explaining this variation have been rare. This study uses two behavioral economic theories to predict option-type-specific differences between intuitive judgments and real options prescriptions. Regret theory posits that individuals will value decision outcomes based on both the expected utility of payoffs and on anticipated regret for not having made an alternative decision. As a consequence, intuitive IT investment decisions are less aggressive as uncertainty increases (higher valuation of deferral options, lower valuation of growth options), in contrast to higher normative values for both real option types with higher uncertainty. Consistent with competitive behavior theories that predict overaggressive behavior to contest market behavior, intuitive IT investment decisions are more aggressive in the presence of a potential competitor (lower valuation of deferral and higher valuation of growth options), holding constant the normative value of the options. We present experimental evidence consistent with these predictions. An important implication of our results is that future research should not test for general consistency between intuitive judgment and real options theory, but should identify and explain systematic variation in consistency across option types and settings. Such variation is important in practice because it determines when intuitive judgment is and is not likely to be an adequate substitute for costly formal real options valuation. It also determines when training in real options concepts needs to be more intensive to overcome inconsistency with intuitive judgment, and when the outputs of formal real options valuation are likely to be unintuitive and thus not readily acceptable to managers with limited option theory training.

Incorporating trust-in-technology into Expectation Disconfirmation Theory

Continued use of strategic information systems is not always a given. This study proposes that users’ trust in the system may influence their satisfaction and continuance intention. While trust has been found to have strategic implications for understanding consumers’ technology usage, relatively little research has examined how trust’s influence operates over time. To gain insight into trust’s influence on strategic system usage over time and to explain how trust relates to satisfaction and continuance intention, we integrate trust-related constructs with the Complete Expectation Disconfirmation Theory (EDT) Model. Our results demonstrate that trust plays a central role in the EDT process and that the EDT process helps explain trust’s role more completely. The study shows that technology trusting expectations influence trusting intention through performance, disconfirmation, and satisfaction. We also show that technology trusting intention adds predictive power to EDT’s satisfaction construct as together they predict usage continuance intention. For research, our results provide a strong combined EDT and trust theory base for future studies that examine expectation management and system development projects. For practice, our study informs systems implementation strategies for technologies that have fewer human-like characteristics and more technology-like characteristics. Our findings underscore that managers need to adopt an EDT process-based view when seeking to build trust, satisfaction, and continuance intention in strategically important information systems.

Internet-based knowledge acquisition

Internet tools used as knowledge retrieval mechanisms can be beneficial for knowledge acquisition (KA). This study applies the concepts of decisional guidance and restrictiveness to three commonly used tools to predict perceived information overload, task quality, and task speed for tasks that differ in complexity. In an experimental setting we find that less restrictive pull systems (i.e., web directories and Google search) increased quality in high-complexity tasks over more restrictive push systems (i.e., listservs) and lowered perceived information overload in both low- and high-complexity tasks. In low-complexity tasks, subjects using predefined guidance (i.e., listservs and web directories) performed better and faster than those using participative guidance (i.e., Google search). In high-complexity tasks, participative guidance provided lower perceived information overload and higher task quality. Implications for research and practice are discussed. Highlights? In high-complexity tasks, less restrictive pull systems (i.e., web directories and Google search) increased quality and lowered perceived information overload over more restrictive push systems (i.e., listservs). ? In low-complexity tasks less restrictive pull systems lowered perceived information overload. ? In low-complexity tasks, predefined guidance (i.e., listservs and web directories) performed better and faster than those using participative guidance (i.e., Google search). ? In high-complexity tasks, participative guidance provided lower perceived information overload and higher task quality than predefined guidance.

Strategic implications of asynchronous healthcare communication

Asynchronous online communication technologies are likely to cause major changes in the way patients and their healthcare providers communicate. Initially, these technologies will be applied to undemanding communication uses, such as requesting prescription refills. In the longer term, however, the technologies may provide strategic benefits to healthcare innovators. In this paper, we project changes that we expect to accompany the advent of asynchronous healthcare communication and propose several strategic opportunities that these changes will create.

Research Note—Using Expectation Disconfirmation Theory and Polynomial Modeling to Understand Trust in Technology

Trust in technology is an emerging research domain that examines trust in the technology artifact instead of trust in people. Although previous research finds that trust in technology can predict important outcomes, little research has examined the effect of unmet trust in technology expectations on trusting intentions. Furthermore, both trust and expectation disconfirmation theories suggest that trust disconfirmation effects may be more complex than the linear expectation disconfirmation model depicts. However, this complexity may only exist under certain contextual conditions. The current study contributes to this literature by introducing a nonlinear expectation disconfirmation theory model that extends understanding of trust-in-technology expectations and disconfirmation. Not only does the model include both technology trust expectations and technology trusting intention, it also introduces the concept of expectation maturity as a contextual factor. We collected data from three technology usage contexts that differ in expectation maturity, which we operationalize as length of the introductory period. We find that the situation, in terms of expectation maturity, consistently matters. Using polynomial regression and response surface analyses, we find that in contexts with a longer introductory period (i.e., higher expectation maturity), disconfirmation has a nonlinear relationship with trusting intention. When the introductory period is shorter (i.e., expectation maturity is lower), disconfirmation has a linear relationship with trusting intention. This unique set of empirical findings shows when it is valuable to use nonlinear modeling for understanding technology trust disconfirmation. We conclude with implications for future research.

Distinguishing the effects of B2B information quality, system quality, and service outcome quality on trust and distrust

Abstract Successful business-to-business (B2B) data exchanges can help firms improve inter-organizational cooperation and operational practices, thereby increasing competitive advantage. However, data exchange quality and trust are not assured. Further, although researchers have examined how trust in the exchange partner relates to data exchange system success, both trust and distrust may be important to consider. Using two-factor theory and trust theory, we examine the differential impacts of information quality, system quality, and service outcome quality on trusting and distrusting beliefs. We also study whether trusting and distrusting beliefs have differential influences on relationship commitment and perceived risk. Results from a laboratory experiment show that information quality, a process (i.e., motivating) factor, more strongly influences trusting beliefs than distrusting beliefs, whereas service outcome quality, an outcome (i.e., hygiene) factor, more strongly influences distrusting beliefs. Also, while trusting beliefs has a significantly stronger influence on relationship commitment, trusting and distrusting beliefs have equivalent effects on perceived risk. Implications and ways to expand this research are discussed.

Facebook privacy management strategies: A cluster analysis of user privacy behaviors

Abstract Online privacy management research related to e-commerce mainly focuses on whether or not to disclose information. Online social networking on the other hand, offers a broader set of privacy management behaviors such as using vendor-provided privacy settings, limiting self-disclosures, and managing network size. While much prior research has examined these privacy behaviors individually, we investigate how Facebook users combine these behaviors to form privacy management strategies. Using communications privacy management and impression management theories we first develop four propositions about possible user strategies that combine differing levels of disclosure, network size, and privacy setting use. One strategy is the most public, whereas two others deviate from this public strategy by either limiting disclosures, or using privacy settings to restrict access. The final strategy is the most private. We then survey two samples of Facebook users (college students and the general population) about their privacy management behaviors, privacy perceptions, technology usage perceptions, and demographics. Using cluster analysis we find some support for all four propositions, and for an additional strategy that beginning users may employ. The findings also reveal intriguing differences among the privacy management strategies in terms of perceptions and demographics like privacy concern, usefulness, enjoyment, and age, gender, and experience. Implications for future research are discussed.

A Framework and Guidelines for Assessing and Developing Board-Level Information Technology Committee Charters

ABSTRACT: IT governance is important to the success of most business enterprises. One form of IT governance is the use of board-level IT committees. This study examines committee charters, which ar...