Big data approaches and outcome of information asymmetry: opportunities for future research

Abstract

The purpose of this paper is to advocate reorientation of current managerial practices in the light of growing reliance on Big Data strategies by contemporary firms, to make them more consumer-centric in nature. Big data strategies by their very nature and modalities lead to heightened levels of information asymmetry which by default have the capacity to disempower the very user that contributes towards the data driven insights. The fundamental driver for writing this paper is not to criticise big data strategies per se, but to suggest; it is merely a tool which can be equally used for consumer entrapment, as well as consumer empowerment. This paper wishes to contribute to the intellectual debate among academics, policy maker, and practitioners alike; en-route for a type of big data-driven managerial orientation that balances the consumers' right to market-based transparency, and the enterprise's need for economic viability.

A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy

“…Okwechime et al ( 2018 ) have made use of the 4I model in deploying and integrating ‘Big Data’ and ‘Smart Cities’ from the organizational learning perspective. Mandlik and Kadirov ( 2018 ) studied the ‘Big Data’ ecosystem at the micro-level (Individual behavior), meso-level (Network of firms), and the macro-level (Institutional, Socio-political). The conceptual framework proposed for ‘Data Science’ success, connects the construct ‘Resources’ as the business input leading to ‘Strategic Business Value’ as the outcome.…”

“…‘Data Science Strategy’ by its very nature leads to asymmetric information in the technology market (Mandlik and Kadirov 2018 ). In equity markets, information on firms’ investment in ‘Data Science’ leads to positive stock market reactions.…”

Opportunities for Research in Air Transportation

“…From an economic perspective, however, questions arise concerning the ways in which data are gathered and subsequently used. For example, is it exploiting consumers who find themselves at an informational disadvantage to the air transportation service providers (Mandlik and Kadirov 2018)? It also may add to an already considerable bias toward that which can be counted, to hark back to the opening quote, and a continued discounting of softer information and data.…”