A multi-dimensional construct of perceived information pollution in the era of rife infollution

Qaisar Iqbal*, Shaohua Yang, Rashid Nawaz, Khalid Iqbal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Purpose: This paper aims to evaluate employee’s perception regarding information pollution and determined the factors that lead to perceived infollution. In the case of this study, a four-dimensional scale of perceived infollution is presented. In addition, this study quantified information pollution in contrast to using the measurement tools of information quality. Design/methodology/approach: A sequential exploratory mixed-method design was used to validate the measurement scale. The population of the present study comprised of the employees who work in the operations and credit department of banking sector. In this study, a four-dimensional second-order scale of perceived information pollution with a total of 19 items or sub-dimensions managed to be developed using exploratory factor analysis and confirmatory factor analysis. Findings: The measurement scale confirmed that perceived information pollution in the context of workplace environment consisted of four dimensions, namely, intrinsic PIP, accessible PIP, contextual PIP and representational PIP where PIP stands for Perceived Information Pollution. Research limitations/implications: Management may use the four dimensions as a benchmark in revealing polluted information as well as enhancing information quality through information processing. Originality/value: This is the first attempt of exploring the dimensions and validating the measurement scale of perceived infollution.

Original languageEnglish
Pages (from-to)162-180
Number of pages19
JournalVINE Journal of Information and Knowledge Management Systems
Volume49
Issue number2
DOIs
StatePublished - 17 May 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Emerald Publishing Limited.

Keywords

  • Big data
  • Data quality
  • Exponential relationship
  • Information quality
  • Linear relationship
  • Rife infollution

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Library and Information Sciences
  • Management of Technology and Innovation

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