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User personality and resistance to mandatory information systems in organizations: a theoretical model and empirical test of dispositional resistance to change

  • Research Article
  • Published:
Journal of Information Technology

Abstract

This research is driven by the assumption made in several user resistance studies that employees are generally resistant to change. It investigates the extent to which employees’ resistance to IT-induced change is caused by individuals’ predisposition to resist change. We develop a model of user resistance that assumes the influence of dispositional resistance to change on perceptual resistance to change, perceived ease of use, and usefulness, which in turn influence user resistance behavior. Using an empirical study of 106 HR employees forced to use a new human resources information system, the analysis reveals that 17.0–22.1 percent of the variance in perceived ease of use, usefulness, and perceptual resistance to change can be explained by the dispositional inclination to change initiatives. The four dimensions of dispositional resistance to change – routine seeking, emotional reaction, short-term focus and cognitive rigidity – have an even stronger effect than other common individual variables, such as age, gender, or working experiences. We conclude that dispositional resistance to change is an example of an individual difference that is instrumental in explaining a large proportion of the variance in beliefs about and user resistance to mandatory IS in organizations, which has implications for theory, practice, and future research.

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Notes

  1. The depicted results represent participants’ actual answers. Participants who did not indicate their gender,. age and tenure are not visualized in the table.

  2. Please see Appendix B for a detailed description of effect sizes in structural equation modeling.

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Authors and Affiliations

  1. University of Bamberg, Information Systems and Services, Bamberg, Germany

    Sven Laumer, Christian Maier & Tim Weitzel

  2. German Graduate School of Management and Law (GGS), Heilbronn, Germany

    Andreas Eckhardt

Authors
  1. Sven Laumer
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  2. Christian Maier
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  3. Andreas Eckhardt
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  4. Tim Weitzel
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Corresponding author

Correspondence to Sven Laumer.

Appendices

Appendix A

Measurement items

Table A1

Table A1 Measurement Items
Full size table

Appendix B

Effect size

In general, effect size is a quantitative measure to determine the strength of a phenomenon (Kelley and Preacher 2012). Cohen’s f 2 is one possible measure of effect size in structural equation modeling. The general formula for f 2 can be defined as follows whereas R 2 incl is the coefficient of determination (R 2) of a variable including the impact of the phenomena of interest and R 2 excl is the coefficient of determination (R 2) of the same variable excluding the impact of the phenomena of interest (Cohen 1992). As suggested by Cohen (1988) a f 2 of 0.02, 0.15, and 0.35 can be classified as small, medium, and large effect sizes.

Formula 1: effect size

Using the formula we have calculated the effect size of dispositional resistance to change compared to other individual differences such as age, gender and experience. We first calculated the model using all predictors of perceived usefulness, perceived ease of use, and resistance to change. Than we exclude the dispositional resistance to change variables. On the basis of the two R 2 values for each variable we calculated the effect size using the above formula. We can observe a medium effect of dispositional resistance to change, and small or non-existing effect for the other control variables. Hence, we can conclude that dispositional resistance to change has a stronger effect on perceived usefulness, perceived ease of use, and resistance to change than age, gender, and experience.

Besides this general comparison, we also controlled for the effect size of each dispositional resistance to change dimension. These results are illustrated by Table B1 and reveal that emotional reaction has a stronger effect on the outcome variables compared with all other variables used. Hence, it is the dimension of dispositional resistance to change with the strongest effect on perceived usefulness, perceived ease of use, and resistance to change.

Table B1 Effect size of the IV on the DV
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Appendix C

Alternative conceptualizations

On the basis of the discussion of modeling dispositional resistance to change either as a dimension set, a multi-dimensional or a uni-dimensional construct, we concluded that a dimension set is most appropriate for our approach (see 0). However, as we also acknowledge different conceptualizations of dispositional resistance to change we provide the results of an evaluation of our research model using both a multi-dimensional and a uni-dimensional operationalization of dispositional resistance to change.

Dispositional resistance to change as a first-order formative second order reflective multidimensional construct

In order to conceptualize dispositional resistance to change in different ways we also modeled it as a first-order formative second order reflective multidimensional construct and recalculated the structural model validation. The choice of a first-order formative second order reflective operationalization is based on the guidelines provided by Polites et al. (2011). Figure C1 summarizes the evaluation of the first-order formative construct and illustrates the results of the structural model validation using a multi-dimensional constructs. Regarding path-coefficients dispositional resistance to change still has a significant impact in perceived ease of use, perceived usefulness, and resistance to change. Regarding the R 2, the values observed using the multi-dimensional construct are lower than those observed when using the dimension set. However, this is in line with prior research that constitutes that when using multi-dimensional constructs less variance in outcome variables can be observed than when using its individual dimensions (Edwards 2001).

Figure C1
figure 3

Dispositional resistance to change as a second order construct

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Dispositional resistance to change as a uni-dimensional construct

We also conceptualized dispositional resistance to change as a uni-dimensional construct and recalculated the structural model validation. On the basis of MacKenzie et al. (2005) it might be appropriate for studies not focusing on the different dimensions of a multi-dimensional construct or dimension set to substitute a multi-dimensional construct with a single measure per dimension. Hence, we also used only one indicator per dimension and recalculated the structural model validation. Table C1 illustrates the items used and the corresponding loadings. Figure C2 summarizes the results of the structural model validation. With regard to path-coefficients, dispositional resistance to change still has a significant impact in perceived ease of use, perceived usefulness, and resistance to change. Also using a uni-dimensional conceptualization reveals lower R2 compared with a dimension set.

Table C1 Items for a uni-dimensional construct of dispositional resistance to change
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Figure C2
figure 4

Dispositional resistance to change as a uni-dimensional construct

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Laumer, S., Maier, C., Eckhardt, A. et al. User personality and resistance to mandatory information systems in organizations: a theoretical model and empirical test of dispositional resistance to change. J Inf Technol 31, 67–82 (2016). https://doi.org/10.1057/jit.2015.17

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