George M. Marakas

The Multilevel and Multifaceted Character of Computer Self-Efficacy: Toward Clarification of the Construct and An Integrative Framework for Research

Despite the recent empirical interest and advances in research with regard to the construct of computer self-efficacy (CSE), the results obtained to date have, in some cases, been either equivocal or contradictory. We suggest that such results may be attributable to a general lack of attention to the dynamic, multileveled, and multifaceted nature of the computer self-efficacy construct. We offer examples from the extant CSE literature suggesting weaknesses in existing measures of the construct as well as issues associated with manipulations and the need for control of antecedent and consequent factors directly associated with CSE. The objectives of this paper are: (1) to provide a thorough review of the extant literature related to CSE; (2) to present an integrated model of empirical findings, constructed from a wide variety of disciplines, that comprehensively defines the multifaceted nature of task-specific CSE in terms of its antecedent, consequent, and moderating factors; (3) to present a conceptual model of CSE at the general versus task-specific level; and (4) to use the two models of CSE to proffer guidelines for both measurement and manipulation of the construct. Through our review of the CSE literature, we offer several thoughts regarding the nature of the empirical results obtained to date. The combined objectives serve as a basis for establishing a foundation upon which future research investigating the CSE construct can be based.

Differential social attributions toward computing technology: An empirical investigation

A debate exists as to whether social cues should be intentionally designed into the user interface. Some have argued that such interfaces will improve comfort with the interface, create a more natural interaction and improve productivity, although others have argued that these interfaces will lead individuals to ascribe characteristics and responsibilities to computing technology that it does not have. Despite the debate, limited research has focused on the impact these interfaces have on how people ascribe responsibility to computing technology. Drawing from social psychology, empirical work regarding social responses toward computing technology, and attribution theory, this research empirically tests a model developed by Marakas et al. [2000. A theoretical model of differential social attributions toward computing technology: when the metaphor becomes the model. International Journal of Human Computer Studies 52, 719-750] which identifies and explains several of the factors that contribute to differential social attributions toward computing technology. Using data from 240 students and professionals, results from a laboratory study indicate that attributions toward computing technology are influenced by an individuals core self-evaluations, their generalized beliefs about the social role of computing technology and the nature of the computer interface used. Specifically, the results provide support for the argument that certain individuals do indeed attribute independent agency to computing technology and respond accordingly, and that this propensity is magnified when exposed to a computer with a distinctly social interface. Implications for both the applied and academic research communities are discussed.

Revisiting bias due to construct misspecification: different results from considering coefficients in standardized form

Researchers in a number of disciplines, including Information Systems, have argued that much of past research may have incorrectly specified the relationship between latent variables and indicators as reflective when an understanding of a construct and its measures indicates that a formative specification would have been warranted. Coupled with the posited severe biasing effects of construct misspecification on structural parameters, these two assertions would lead to concluding that an important portion of our literature is largely invalid. While we do not delve into the issue of when one specification should be employed over another, our work here contends that construct misspecification, but with a particular exception, does not lead to severely biased estimates. We argue, and show through extensive simulations, that a lack of attention to the metric in which relationships are expressed is responsible for the current belief in the negative effects of misspecification.

Comparing conceptual modeling techniques: a critical review of the EER vs. OO empirical literature

The empirical literature comparing entity relationship and object-oriented modeling techniques, while vibrant, has often yielded equivocal findings. This review employs Normans (1986) Theory of Action to distinguish between model creation and comprehension studies, and applies and extends the theoretical framework proposed by Gemino and Wand (2004) to highlight and detail several issues that may need further exploration if consistent results in this stream are to be realized. Specifically, this paper explores why and how issues of ontological foundation, training, equivalence of conceptual models, and modeling practices may result in differences between alternative modeling techniques. A comprehensive picture of this literature is provided and a number of potential avenues for future research are proposed.

Beliefs about the social roles and capabilities of computing technology: development of the computing technology continuum of perspective

Using data from 1216 students and professionals, this research developed a new construct focusing on beliefs about the social role and capabilities of computing technology, the computing technology continuum of perspective (CP). Results indicated that individuals have different beliefs about the social role and capabilities of computing technology along four dimensions, including beliefs about: 1) intelligence; 2) socialness; 3) control; 4) control of rights. Results further indicated that an individuals CP was related to gender, experience with computers, as well as locus of control, self-esteem, neuroticism and general computer self-efficacy. Implications are drawn for future research investigating various beliefs about the social role and capabilities of computing technology.

Omission of Causal Indicators: Consequences and Implications for Measurement

ABSTRACT One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant causal indicator does not affect downstream estimates relating the focal latent variable to other variables in the model, which challenges the current stance in the literature. Further, we argue that this occurrence presents a fundamental challenge to the causal-indicator literature, in that the lack of negative consequences is not consistent with the tenet that latent variables derive their meaning from the set of causal indicators included in a research model. Rather, though causal indicators help identify the focal latent variable, its meaning is derived from its position as a common factor of other downstream variables—latent or observed—to which it is related.

Measurement of composite reliability in research using partial least squares: some issues and an alternative approach

The accurate estimation of reliability is of great importance to the conduct and interpretation of empirical research as it is used to judge the quality of reported research, often plays a role in publication decisions, and is a key element of meta-analytic reviews. When employing partial least squares (PLS) as the method of analysis, the reliability of the composites involved in the model is typically the parameter examined. In this research, we describe the existence of three important issues concerning the accuracy of composite reliability estimation in PLS analysis: the assumption of equal indicator weights, the bias in loading estimates, and the lack of independence between indicator loadings and weights. We subsequently present an alternative approach to correct these issues. Using a Monte Carlo simulation we provide a demonstration of both the effects of these issues on research decisions and the improved accuracy of the alternative method.

Exploring Choice as an Antecedent to Behavior: Incorporating Alternatives into the Technology Acceptance Process

In this paper, the authors conduct a study to explore the evaluation and choice between candidate software applications. Using business professionals, technology adoption is investigated by presenting participants with an alternative choice set using software applications relevant to the professional domain of the subjects. Results from this study, focusing on models of intentions, provide evidence to suggest the underlying process by which choice behaviors are determined and demonstrate the value of incorporating choice into models of technology adoption, particularly in situations where selection is made from a set of candidate technologies, such as in an organizational adoption decision. In addition, theoretically derived models of comparison processes are examined to develop further understanding into how individuals arrive at a specific choice behavior. A second study is conducted to further validate the obtained results. Implications for future research into the processes leading to adoption of information technologies are also presented.

A Rejoinder to Rigdon et al. 2014

We appreciate the interest shown by Rigdon et al. [Rigdon EE, Becker J-M, Rai A, Ringle CM, Diamantopoulos A, Karahanna E, Straub DW, Dijkstra TK 2014 Conflating antecedents and formative indicators: A comment on Aguirre-Urreta and Marakas. Inform. Systems Res. 254:780-784.] in our recent work and for the time and effort spent in carefully considering it and offering their comments and concerns. In what follows, and within the limitations of a short rejoinder, we offer our response to their comments, highlighting points of agreement and noting where more research is necessary.

Exploring the Psychological Determinants of Perceived Ease of Use and Usefulness

The question of why individuals adopt a particular information system is an important issue in IS research. While extensive prior research has established that the Technology Acceptance Model (TAM) does a good job of predicting a users intention to adopt an information system through the constructs Perceived Ease of Use (PEOU) and Perceived Usefulness (PU), relatively little attention has been paid to the antecedents associated with the formation of these perceptions. Understanding the determinants of PEOU and PU is essential for providing actionable recommendations for practice in order to influence ultimate system use. This paper reports on an exploratory study investigating the effect of various antecedent variables on PEOU and PU for technologies of varying complexity. The intention is to converge on an experimental model that focuses on the salient variables.