Individual Innovativeness Scale (IIS-20)

Description

The Individual Innovativeness Scale (IIS-20) is a self-report psychometric instrument developed to assess the degree of individual innovativeness, defined as a person’s general predisposition to accept, adopt, or resist new ideas, practices, technologies, and changes. The original scale was developed by Hurt, Joseph, and Cook (1977) and has become a widely used instrument for examining innovativeness as an individual characteristic.

The IIS-20 consists of 20 items that assess different aspects of an individual’s orientation toward innovation, including willingness to try new things, tendency to seek novel solutions, adaptability to new circumstances and technologies, resistance to change, and perceptions of the risks associated with innovation.

Individual innovativeness is closely related to the Diffusion of Innovations theory, particularly to differences in how quickly and willingly people adopt new ideas. From this perspective, innovativeness does not refer exclusively to the creation of original ideas. It also includes receptiveness to change, willingness to experiment, openness to unfamiliar approaches, and the capacity to function effectively in changing environments.

The IIS-20 may be applied in fields such as:

  • Organizational Psychology
  • Human Resource Management
  • Entrepreneurship
  • Education
  • Technology Adoption
  • Innovation Management
  • Consumer Behavior
  • Digital Transformation
  • Organizational Change Research

The flexibility of the instrument allows it to be used in academic studies as well as in applied organizational and educational settings where researchers or professionals seek to assess individuals’ readiness to adopt new technologies, practices, or working methods.

Objective

The primary objective of the IIS-20 is to provide a systematic assessment of the degree to which an individual demonstrates an innovative orientation and a positive predisposition toward change.

More specifically, the scale can be used to:

  • Assess willingness to adopt new ideas and practices.
  • Examine receptiveness to technological and organizational change.
  • Evaluate the tendency to seek novel solutions and alternative approaches.
  • Assess adaptability to unfamiliar situations.
  • Investigate resistance to change.
  • Examine the relationship between innovativeness and occupational performance.
  • Study the acceptance and adoption of new technologies.
  • Evaluate educational or organizational interventions designed to strengthen an innovative culture.

Understanding individual innovativeness can contribute to change management, the development of new strategies, and performance improvement. It can also support research on the relationship between innovativeness, adaptability, and attitudes toward change.

Scoring

The IIS-20 includes 20 Likert-type items. Scoring should follow the instructions of the specific version being administered, as the original scale contains both positively and negatively worded items.

Therefore, the relevant negatively phrased items must be reverse scored before the total score is calculated. This step is essential because simply summing all responses without checking item direction may produce an inaccurate estimate of individual innovativeness.

In general:

  • Higher scores indicate greater individual innovativeness and stronger receptiveness to new ideas and change.
  • Lower scores indicate greater caution, reluctance, or resistance toward innovation.

Score interpretation should be based on the official scoring procedure and normative categories of the version used rather than on arbitrary cutoff values.

Data Analysis and Applications

Statistical analysis of IIS-20 data may include descriptive, psychometric, and inferential procedures, depending on the aims of the study. The source material specifically highlights factor analysis, reliability assessment, and correlations with variables such as job performance and technology adoption.

Descriptive Statistics

Initial analysis may include:

  • Mean
  • Median
  • Standard Deviation
  • Minimum and Maximum values
  • Range
  • Frequencies and Percentages

These indicators provide an overall profile of individual innovativeness within the study sample.

Reliability Analysis

The internal consistency of the IIS-20 may be evaluated using:

  • Cronbach’s Alpha
  • McDonald’s Omega
  • Corrected Item–Total Correlations
  • Split-Half Reliability
  • Test–Retest Reliability

The assessment of internal consistency, particularly through Cronbach’s alpha, is a central part of the psychometric evaluation of the scale.

Validity Assessment

The structure and validity of the IIS-20 may be examined through:

  • Exploratory Factor Analysis (EFA)
  • Confirmatory Factor Analysis (CFA)
  • Convergent Validity
  • Discriminant Validity
  • Criterion-related Validity

Validation across different populations and cultural settings is especially important to ensure that the instrument maintains satisfactory psychometric properties in diverse contexts.

Group Comparisons

Individual innovativeness may be compared across demographic, educational, or occupational groups using:

  • Independent Samples t-test
  • Paired Samples t-test
  • Analysis of Variance (ANOVA)
  • Multivariate Analysis of Variance (MANOVA)
  • Mann–Whitney U Test
  • Kruskal–Wallis Test
  • Analysis of Covariance (ANCOVA)

Correlation Analysis

The IIS-20 may be examined in relation to variables such as:

  • Job performance
  • Creativity
  • Entrepreneurial orientation
  • Adaptability
  • Resistance to change
  • Technology acceptance
  • Digital skills
  • Organizational commitment
  • Self-efficacy
  • Intention to adopt innovations

Associations may be evaluated using Pearson or Spearman correlation coefficients, depending on the distribution and measurement level of the data.

Predictive Modeling

For more complex research questions, the following techniques may be used:

  • Linear Regression
  • Multiple Regression
  • Hierarchical Regression
  • Logistic Regression
  • Structural Equation Modeling (SEM)

These analyses can be used to determine whether individual innovativeness predicts technology adoption, adjustment to organizational change, occupational behavior, or related outcomes.

References

  • Goldsmith, R. E., & Hofacker, C. F. (1991). Measuring Consumer Innovativeness. Journal of the Academy of Marketing Science, 19(3), 209–221.
  • Hurt, H. T., Joseph, K., & Cook, C. D. (1977). Scales for the Measurement of Innovativeness. Human Communication Research, 4(1), 58–65.
  • Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.