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Departing from the existing strategy perspective that demonstrates the short-term myopia resulting from analyst and financial market pressures, we argue and show that in certain industries, analyst pressures can also push a firm towards eschewing options to convert more uncertain and risky longer term R&D into relatively stable short-term earnings. Using pharmaceutical industry as our focal context and a robust research design that accounts for the endogeneity of analyst coverage, we show that greater analyst scrutiny reduces the likelihood that a firm will demonstrate intent to license out its technologies in order to obtain royalty payments. Additional examination of contingent firm characteristics provides further clarity on the nature of this mechanism.
Fintechs’ Business Model Evolution in the UK
University of Warwick Pinar Ozcan,
University of Oxford
In this study, we look at business model evolution of data-driven new ventures in UK banking (fintechs), with special attention to data access methods they used before and after a regulatory change that established APIs as the market standard for data access. We collected data through semi-structured interviews and used multiple cases to build the theory inductively. The findings show that market characteristics forced B2C entrants to add or completely pivot to different B2B models both to quickly access mass data and to ensure profitability. Furthermore, although the regulatory change required the use of new technology for data access, old technology persisted due to poor implementation of APIs, insufficiency of regulation in covering different types of data, and global non-standardization in data access methods.
Innovation Failures & Breakthroughs: Are Technological and Economic Value Extremes the Same?
Innovations laying at the extremes of value distribution, breakthrough and failures, can have tremendous consequences on firms’ competitiveness. Despite the well-known association between technological value and market estimation of economic value, we do not know yet if this holds for extreme innovations. Using economic value data as proposed by Kogan et al. (2017), I document that technologically high-impact inventions are seldom (7,6%) economic breakthroughs as estimated by the market. Technological failures are rarely evaluated as (6,1%) economic failures. Reasons for this are either (ii) errors in market prediction of future technological value or (ii) economic value captures dynamics not reflected in technological value. Applying basic regressions and supervised machine learning algorithms, I identify determinants of market misvaluation of innovation extremes and explain the divergence.