Infollution (Information Pollution) Management, Filtering Strategy, Scalable Workforce, and Organizational Learning: A Conceptual Study

  • Qaisar Iqbal 1School of Management, Universiti Sains
  • Shaohua Yang Graduate School of Business, Universiti Sains,
  • Rashid Nawaz University of Education
  • Yifeng Lin Newcastle University, United Kingdom & School of Business and Administration, Fuzhou University of International Studies and Trade
DOI: https://doi.org/10.22610/imbr.v10i4.2641
Keywords: Scalable workforces, organisational learning, information pollution, infollution management, agile organisation

Abstract

Information generation is increasing rapidly on a global scale. The exponential advancement in information technology and communication has accentuated the problem of effective information management. Yet, employees’ cognitive ability to process information has not increased in parallel with information generation. With the exponential rise of information, information pollution (infollution) emerges as a problem on an exponential basis. Infollution is among the greatest challenges of the 21st century. Nevertheless, based on information processing theory and dynamic capability, researchers have conceptualised that agile organisations can cope with information pollution by promoting scalable workforce and organisational learning. By employing coping strategies, filtering has been hypothesised as moderating the association of scalable workplace and organisational learning with infollution management. This research will extend the literature in the domain of information management and agile organisations. It will be particularly useful for information processors to identify quality information for improved decision-making. 

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Published
2019-01-14
How to Cite
Iqbal, Q., Yang, S., Nawaz, R., & Lin, Y. (2019). Infollution (Information Pollution) Management, Filtering Strategy, Scalable Workforce, and Organizational Learning: A Conceptual Study. Information Management and Business Review, 10(4), 1-7. https://doi.org/10.22610/imbr.v10i4.2641
Issue
Vol 10 No 4 (2018)
Section
Research Paper

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