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Introduction
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August 2015 - July 2016
August 2010 - present
Publications
Publications (47)
The editorial process at our leading information systems journals has been pivotal in shaping and growing our field. But this process has grown long in the tooth and is increasingly frustrating and challenging its various stakeholders: editors, reviewers, and authors. The sudden and explosive spread of AI tools, including advances in language model...
Construct-based models have become a mainstay of management and information systems research. However, these models are likely overfit to the data samples upon which they are estimated, making them risky to use in explanatory, prescriptive, or predictive ways outside a given sample. Empirical researchers currently lack tools to analyze why and how...
Construct-based models have become a mainstay of management and information systems research. However, these models are likely overfit to the data samples upon which they are estimated, making them risky to use in explanatory, prescriptive, or predictive ways outside a given sample. Empirical researchers currently lack tools to analyze why and how...
Advances in reinforcement learning and implicit data collection on large-scale commercial platforms mark the beginning of a new era of personalization aimed at the adaptive control of human user environments. We present five emergent features of this new paradigm of personalization that endanger persons and societies at scale and analyze their pote...
In 2021, the third edition of our introductory book A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) was published (Hair, Hult, Ringle, & Sarstedt, 2022). The book covers the latest developments in the ield, including recent advances in model evaluation (e.g., inference testing in discriminant validity assessment, predictive...
Researchers in information systems have studied how nonintentional elements of our psychology such as personality, addiction, and even sheer habit, can waylay us from our original purpose of using information technology. This study seeks to reintegrate these elements to present a holistic framework comparing Internet addiction with Internet habit i...
Computational statistics is now an increasingly popular method of analysis for researchers that combines a vast array of algorithms, statistical methods, and the power of functional coding. The R programming language, in particular, has benefitted from this development alongside of traditional graphical user interface (GUI) software. Today, it has...
Mediation occurs when a third variable, referred to as a mediator construct, intervenes between two other directly related constructs. More precisely, a change in the exogenous construct results in a change of the mediator construct, which in turn changes the endogenous construct. The mediator analysis evaluates the factors related to the cause–eff...
Structural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS r...
When moderation is present, the strength and even the direction of a relationship between two constructs depend on a third construct (i.e., the moderator). In other words, the strength of the relationship between two constructs changes as the levels of the moderator construct change. As an example, the relationship between customer satisfaction and...
The goal of reflective measurement model assessment is to ensure the reliability and validity of the construct measures and therefore provides support for the suitability of their inclusion in the path model. This chapter introduces the key criteria that are relevant in reflective measurement model assessment: indicator reliability, internal consis...
Structural model assessment in PLS-SEM focuses on evaluating the significance and relevance of path coefficients, followed by the model’s explanatory and predictive power. In this chapter, we discuss the key metrics relevant to structural model assessment in PLS-SEM. We also discuss model comparisons and introduce key criteria for assessing and sel...
SEMinR is a software package developed for the R statistical environment (R Core Team, 2021). The package includes a user-friendly syntax for creating and estimating structural equation models using estimators such as partial least squares. In this chapter, we introduce the syntax to create, estimate, and report structural equation models using SEM...
PLS-SEM is the preferred approach when formatively specified constructs are included in the PLS path model. In this chapter, we discuss the key steps for evaluating formative measurement models. These include the assessment of (1) convergent validity, (2) indicator collinearity, and (3) statistical significance and relevance of the indicator weight...
Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and meas...
Datasets with induced emotion labels are scarce but of utmost importance for many NLP tasks. We present a new, automated method for collecting texts along with their induced reaction labels. The method exploits the online use of reaction GIFs, which capture complex affective states. We show how to augment the data with induced emotion and induced s...
SEMinR brings a friendly syntax to creating and estimating structural equation models (SEM). The syntax allows applied practitioners of SEM to use terminology that is very close to their familiar modeling terms (e.g., reflective, composite, interactions) instead of specifying underlying matrices and covariances. SEM models can be estimated either u...
The use of crowdworkers in NLP research is growing rapidly, in tandem with the exponential increase in research production in machine learning and AI. Ethical discussion regarding the use of crowdworkers within the NLP research community is typically confined in scope to issues related to labor conditions such as fair pay. We draw attention to the...
We present an overview of the EmotionGIF2020 Challenge, held at the 8th International Workshop on Natural Language Processing for Social Media (SocialNLP), in conjunction with ACL 2020. The challenge required predicting affective reactions to online texts, and included the EmotionGIF dataset, with tweets labeled for the reaction categories. The nov...
Structural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS r...
Sarcasm detection is an important task in affective computing, requiring large amounts of labeled data. We introduce reactive supervision, a novel data collection method that utilizes the dynamics of online conversations to overcome the limitations of existing data collection techniques. We use the new method to create and release a first-of-its-ki...
This study seeks to develop and test a theory-driven model of technology addiction within the context of smartphone use. Drawing on incentive-sensitisation theory, we proposed a nomological network that centres on a second-order factor of smartphone addiction from a psychological perspective. We empirically evaluated the proposed model against long...
Purpose
The purpose of this study is to clarify theory and identify factors that could explain the level of fintech continuance intentions with an expectation confirmation model that integrates self-efficacy theory.
Design/methodology/approach
With data collected from 753 fintech users, this study applies partial least square structural equation m...
Methodological research in Partial Least Squares Path Modeling (PLS-PM), a construct-based modeling technique, has seen a flurry of efforts to introduce predictive analytic methods. However, there is still confusion about how prediction can be applied to refine theory and integrate with this traditionally inferential technique. We feel that predict...
Habit and addiction are two distinct drivers of information technology (IT) use that nonetheless bear increasing resemblance in how they are conceptualized and modeled in the information systems (IS) literature. The purpose of this study is to aid the further growth of these heretofore-independent streams of research by developing a comparative fra...
Rapid growth in the availability of behavioral big data (BBD) has outpaced the speed of updates to ethical research codes and regulation of data privacy and human subjects' data collection, storage, and use. The introduction of the European Union's (EU's) General Data Protection Regulation (GDPR) in May 2018 will have far-reaching effects on data s...
With the Internet permeating every aspect of daily life, organizations of all types are increasingly concerned about the degree to which their employees are cyberloafing by shirking their work responsibilities to surf the Internet, check e-mail, or send text messages. Although technological interventions against cyberloafing have been shown to be e...
Apart from the theoretic explanations offered by our empirical models, practitioners are also interested in the practical implications that they can apply to future cases. Being able to provide predictive diagnoses is an increasingly important issue linking theory and pracice, and empirical researchers in hospitality and tourism should heed the cal...
Partial least squares path modeling (PLS-PM) has become popular in various disciplines to model structural relationships among latent variables measured by manifest variables. To fully benefit from the predictive capabilities of PLS-PM, researchers must understand the efficacy of predictive metrics used. In this research, we compare the performance...
Generating predictions from PLS models is a recent and novel addition to the research and practice of structural equation modeling. Shmueli et al. (2016) gave us an explicit understanding of what prediction should entail in the context of PLS. That study also demonstrated how to generate predictions using the measurement items and structure of the...
The major challenge for social networking services (SNS) has been in getting users to exhibit prosocial behavior by active participation in creating and sharing content. We seek to integrate and reconcile the varying, and sometimes conflicting, explanations of prosocial behaviors at SNS. Rooted in postadoption behavior and commitment theory, our st...
Open-source modules are software libraries that allow other developers to freely download and use them, and even to collaboratively contribute back with bugfixes or enhancements. For example, consider a Ruby programming language developer who creates a module that converts any data serialized in XML format into a native data structure for the Ruby...
Despite the growing interest in predictive analytics using PLS models, there are no practical studies that demonstrate the application of predictive PLS modeling. This study reexamines an established empirical model and reanalyzes it through the lens of predictive analytics. In implementing predictive PLS procedures in recent literature, we uncover...
Attempts to introduce predictive performance metrics into partial least squares (PLS) path modeling have been slow and fall short of demonstrating impact on either practice or scientific development in PLS. This study contributes to PLS development by offering a comprehensive framework that identifies different dimensions of prediction and their ef...
Attempts to introduce predictive performance metrics into Partial Least Squares (PLS) path modeling have been slow and fall short of demonstrating impact on both practice and scientific development in PLS. This study contributes to PLS development by offering a comprehensive framework that identifies different dimensions of prediction and their eff...
Online communities are new social structures dependent on modern information technology, and they face equally modern challenges. Although satisfied members regularly consume content, it is considerably harder to coax them to contribute new content and help recruit others because they face unprecedented social comparison and criticism. We propose t...
Cloud computing is a new information technology (IT) paradigm that promises to revolutionize traditional IT delivery through reduced costs, greater elasticity, and ubiquitous access. On the surface, adopting cloud computing requires a firm to address many of the same concerns they face in adopting any enterprise IT. However, cloud technologies also...
Researchers have been closely studying how information technology services became a routine part of our lives. Studies have found that users who routinely use online services either consciously develop loyalty or automatically develop a habit. But many studies now mix the elements of conscious and automatic use despite the great differences in thes...
The highly competitive and rapidly changing market for online services is becoming increasingly effective at locking users in through the coercive effects of switching costs. Although the information systems field increasingly recognizes that switching costs plays a big part in enforcing loyalty, little is known about what factors users regard as s...
Security researchers agree that security control is a difficult to observe credence quality of online services that Internet users cannot easily assess through research or experience. Yet there is evidence that users form perceptions of security control that strongly determine how much trust they put in online services. This study investigates whet...