Multi-motive information systems continuance model (MISC)

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Alternate name(s)

MISC model or The MISC

Main dependent construct(s)/factor(s)

Intention to continue / system continuance intention

Main independent construct(s)/factor(s)

Hedonic expectations, intrinsic expectations, extrinsic expectations, hedonic disconfirmation, intrinsic disconfirmation, extrinsic disconfirmation, attitude, satisfaction, hedonic performance, intrinsic performance, extrinsic performance, design expectations fit, ease of use, design aesthetics.

Motivation for MISC / Why IS researchers can benefit from using it

Motivation for use of the theory: Information systems designers and publishers are keenly interested in how to retain users. Accordingly, information systems researchers are eager to supply theories to explain and predict users’ intentions to continue to use information systems. Now, many different theoretical approaches have been taken to predict continuance intentions, however, these existing models often focus on users’ extrinsic motivations, such as desires for productivity, efficiency, and general utility, but fail to fully explain the range of intrinsic and extrinsic motivations that influence continuance intentions. Intrinsic motivations in particular have been shown to be a strong predictor of meaningful user outcomes, such as continuance intentions, as well as satisfaction, and perceived performance Differentiating between users’ intrinsic and extrinsic motives—and the stimuli that fulfill these motives—is particularly relevant for encouraging positive user interactions. These ideas are also highly pertinent to the newer idea of gamification that is starting revolutionize systems design. To identify key differences between intrinsic and extrinsic motivators, several studies have extended extrinsic motivation models or created new models to address users’ intrinsic motivations. However, models predicting intrinsic motives of system use often ignore extrinsic motives. As far as we know, no study has proposed a model that can account for the effects that these normally conflicting motives have on a user’s satisfaction, continuance intentions, and evaluations of system performance.

Additionally, most studies do not conceptualize the different types of intrinsic motivation – for example, hedonic motives like pleasure versus intrinsic motives like learning – and they do not measure the successful fulfillment of intrinsic motivations independently of that of extrinsic motivations. Existing models also often fail to account for user expectations, which are a key component of all interactions and are directly predicted by motivations. So, to address the issue of nomological completeness, researchers must also consider the role of expectations in system interactions. The existing underdeveloped constructs and models potentially confound research on system use and thus make such studies difficult to interpret or at least difficult to generalize across various types of systems and interactions. This gap in the literature also holds back the theoretical and empirical advancement of gamification and information systems design.

As a result, the MISC model is a comprehensive model for explaining and predicting how a range of motives and expectations influences user satisfaction and continuance intentions for multiple types of information systems that have been designed with various intents. Among many other findings, initial empirical research by Lowry et al. (2015) reveals that design-related constructs affect performance beliefs differently depending on system intent and user motives and expectations. This suggests that system designers can leverage the MISC model to learn where to focus their efforts as they design specific systems with specific intents. Nevertheless, they show that a user’s motives do not always match the intent of a system’s design, which increases the need for systems to be designed to accommodate multiple motives. 36. Additionally, many findings are consistent across all types of systems, suggesting that certain design constructs are universally essential. The MISC model also provides a foundation for extending a wide range of research in human-computer interaction and for revisiting prior research to examine the effects of multiple types of motivation in established systems-use theories.

Concise description of theory

The multi-motive information systems continuance model (or MISC), explains and predicts the discrete cognitive processes through which systems fulfill a range of motives and expectations and how this fulfillment leads to continuance intentions. The MISC model also accounts for design-related constructs that have the potential to contribute to or confound any study on system use, namely: design aesthetics, perceived ease of use, and design-expectations fit.

The MISC model is built upon expectation disconfirmation theory, or EDT, and the Bhattacherjee and Premkumar (2004) model. Theories and literature around EDT are plentiful. Sometimes referred to as met-expectations, expectancy violation, or expectation-disconfirmation, these theoretical models concern whether an experience conforms to one’s expectations or if those expectations are disconfirmed or violated. Most studies using an expectancy-confirmation or expectancy-disconfirmation paradigm argue that an individual’s expectations largely determine his or her overall satisfaction with something, such as a person, service, or product – and in our context, an online interaction with a user interface. While accounting for satisfaction, the MISC focuses on system continuance intention as the primary phenomenon of interest.

  • Expectations” refers to one’s beliefs about future events. By nature, the human mind projects and considers future scenarios to anticipate required actions, for both physical and social survival.
  • Disconfirmation” is the extent to which an event is evaluated as either exceeding or falling short of expectations.
  • Positive disconfirmation” results when perceived performance exceeds expectations, thereby causing satisfaction.
  • Whereas, “negative disconfirmation” occurs when performance falls below expectations, causing dissatisfaction.

To address several limitations of using EDT for systems use, MISC adds three more expectations as predictors of disconfirmation, and by including multiple motivation-related factors to the model. The MISC model leverages Design Expectations Fit (DEF), Ease of Use, and Design Aesthetics as additional predictors of Disconfirmation.

  1. DEF is the extent to which the design of the software matches the expected interaction. For example, if, prior to using some software, you expect to be able to have fun interactions with it, but the software is designed for productivity rather than fun, then the DEF is low. In this case, the DEF would be much higher if you had expected to interact productively with the software. Applications with designs that match the expectations of the user will be preferred to those which do not match the users’ expectations.
  2. Ease of use is a common construct in information systems research that represents the degree to which you believe using a system will be free of effort. Applications that are easy to use will be preferred over those that require more effort.
  3. Design Aesthetics refers to the appropriateness and professionalism of the user interface. Aesthetic, or appealing, interfaces are more likely to be preferred over unappealing ones.

Beyond these three new predictors of disconfirmation, the MISC further addresses issues with EDT by splitting beliefs and disconfirmations into their naturally occurring disparate parts, including Hedonic, Intrinsic, and Extrinsic components. When people learn about a new software or information system, they may have expectations or beliefs that fit into one of these three categories. For example, they may expect the software to be pleasurable on some level, uplifting to a certain degree, and, to some extent, useful for accomplishing something.

In all existing models, these three different components are conceptually combined or ignored, resulting in the observed poor ability to predict disconfirmation. Since MISC separates them, it is able to predict hedonic disconfirmations with hedonic expectations (or beliefs), intrinsic disconfirmations with intrinsic expectations, and extrinsic with extrinsic. Taken together, these should also predict evaluations of the interactions far better, as well as the user’s intention to continue using the software. Initial empirical tests by Lowry et al. (2015) indicate this is the case.

Diagram/schematic of theory

MISC figure1.JPG

Figure 1. Overview of the Multimotive Information Systems Continuance Model (MISC), from Lowry et al. 2015, p. 525.

Video companion on the theory

The following video companion on Youtube describes the development of MISC, empirical results of testing the MISC, and its several potential contributions to research and practice:

Originating author(s)

Paul Benjamin Lowry, James Eric Gaskin, Gregory D. Moody

Seminal articles

Paul Benjamin Lowry, James Eric Gaskin, and Gregory D. Moody (2015). “Proposing the multimotive information systems continuance model (MISC) to better explain end-user system evaluations and continuance intentions,” Journal of the Association for Information Systems (JAIS), vol. 16(7), pp. 515–579 (

Originating area

Information systems (native theory)

Level of analysis


IS and non-IS articles that use the theory

Paul Benjamin Lowry, James Eric Gaskin, and Gregory D. Moody (2015). “Proposing the multimotive information systems continuance model (MISC) to better explain end-user system evaluations and continuance intentions,” Journal of the Association for Information Systems (JAIS), vol. 16(7), pp. 515–579 (

Jin-Liang Wang, Hai-Zhen Wang, James Gaskin, Li-Hui Wang, “The role of stress and motivation in problematic smartphone use among college students,” Computers in Human Behavior, Volume 53, December 2015, Pages 181-188, ISSN 0747-5632,

Links from this theory to other theories

EDT (or expectation confirmation theory), Hedonic-motivation system adoption model (HMSAM), Technology acceptance model

External links


Original Contributor(s)

Paul Benjamin Lowry