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Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects

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Abstract

New developments in the fields of artificial intelligence or robotics are receiving considerable attention from businesses, as they promise astonishing gains in process efficiency—sparking a surge of corporate investments in new, digital technologies. Yet, firms did not become per se more productive, as labor productivity growth in various industrial nations has decelerated in recent years. The fact that the adoption of innovative technologies is not accompanied by productivity increases has already been observed during the dawn of the computer age and became known as Solow’s Paradox. Thus, this paper takes stock of what is known about the Solow Paradox, before incorporating the findings into the debate of the current productivity slowdown. Based on an in-depth review of 86 empirical studies at the firm level, this paper uncovers various reasons for the emergence of the Solow Paradox, debates its following reversal marked by the occurrence of excess returns and deduces a model of factors influencing the returns on IT investments. Based on these insights, four overarching explanations of the modern productivity paradox namely adjustment delays, measurement issues, exaggerated expectations and mismanagement are discussed, whereby mismanagement emerges as a currently neglected, but focal issue.

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Notes

  1. For an excellent discussion of parametric and non-parametric approaches, see Cardona et al. (2013).

  2. Because of this broad definition, the terms IT and information and communication technology (ICT) are used interchangeably within this work.

  3. The search process was last updated on 20 February 2019.

  4. Rational managers should invest in an input factor until an additional unit of the input creates no more value than its costs, resulting in a net marginal product of zero. Therefore, if the marginal returns outweigh the marginal costs, the difference is referred to as an excess marginal product or excess return (see Lehr and Lichtenberg 1999).

  5. Weil (2007) further disaggregated IT-Investments into infrastructural, informational, transactional and strategic ones.

  6. These categories are quite similar to the ones proposed by Brynjolfsson (1993), but contain different sub-categories.

  7. Meaning a “faster automation than socially desirable” (Acemoglu and Restrepo 2019, p. 210).

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  1. Chair of Business Economics, Management Accounting and Control, University of Passau, Innstraße 27, 94032, Passau, Germany

    Stefan Schweikl & Robert Obermaier

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Schweikl, S., Obermaier, R. Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects. Manag Rev Q 70, 461–507 (2020). https://doi.org/10.1007/s11301-019-00173-6

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