A natural experiment demonstrating knowledge asset impact on organizational performance

Purpose The purpose of this study is to more strongly demonstrate a relationship between effective management of knowledge and positive organizational performance outcomes. While assumed in the field, proof has been inconsistent and often unconvincing. This study fills several gaps in the literature. The knowledge management (KM)/performance link remains unsettled because of largely subjective and statistical approaches. This research is objective and experimental, allowing causal inferences. This study also establishes a useful KM metric useful in assessing not only knowledge assets but also real-world applications such merger and acquisition (M&A) evaluations. This study uses a longitudinal experimental design to better understand details of KM’s impact on performance outcomes. Design/methodology/approach Using a unique experimental design, a natural experiment, this study measures firm performance before and after a key event, a M&A action. Further, knowledge metrics are used to divide a sample of M&A firms, allowing prediction of post-stock price movements (financial performance outcomes) based on KM outcomes. A full census of over 2,000 M&A events were analyzed over the years 2003–2013, identifying knowledge metrics and stock prices from published financial statements. Findings A relationship was found between relative knowledge levels and a positive move in stock price, strongly suggesting a correlation between KM and financial performance. As a natural experiment, this study also provides evidence a causal relationship exists. Strong empirical data demonstrate that when a firm better manages knowledge, it can have a demonstrated positive impact on performance (stock price). Originality/value This study is unique in several ways. This study uses a natural experiment methodology not commonly applied to KM scholarship. This paper more convincingly establishes a relationship, causal, between KM and financial performance. It does so by using objective metrics rather than subjective self-reports from surveys. Interestingly, it suggests the direction of KM’s impact, as M&A events with a higher acquirer KM metric are more successful than those with a higher target KM metric. Finally, it demonstrates an investment strategy of interest to financial planners, predicting future stock prices based on current knowledge assets levels.