Exploring Complementarities of Productive IT use through Methodological Complementarism


  • Natallia Pashkevich
  • Darek Haftor


complementarity systems approach, individual IT-enabled productivity, knowledge worker, methodological complementarism, online experiment, quasi-randomized field experiment


Factors affecting productivity and particularly IT‑enabled productivity increase have been and still remain the major concern for many business sectors. While previously researchers investigated what factors and their complementary relationships affect organizational productivity, organizational economists came to the conclusion that an organization cannot be regarded anymore as a black box since it is not an organization per se that conducts the very work but its resources with the basic elements being a single worker and a single IT system. Currently, it is proposed that we understand organizational internal mechanisms and their functioning for productivity through the lens of complementarity theory and maintain that when factors are synchronized correctly they can bring significant productivity increase. Identification of the complementarity factors and their synchronization bring, however, a major challenge for research methodology. Unlike conventional studies where a few variables independent of each other cause a reaction to dependent variables, in the context of complementarities, the assumption is closer to the real‑world experiences where a set of factors interact with each other to affect one or several dependent variables. The present paper addresses this difficulty of researching complementary factors for an individual knowledge worker and their productivity. The approach taken here is to use multiple and different research methods in a complementary manner, so that the results from each study of the same kind of phenomenon uncover new insights that cannot be derived from any such single study. The results from this multi‑method approach demonstrate new insights into the interplay between the studied factors that condition the productivity of knowledge workers and show the importance of analysing a complex phenomenon with complementary research methods.



1 Oct 2018