Process innovation and performance: the role of divergence
Authors: Mooi Erik , Rudd John , de Jong Ad 
Published: February 2020

PurposeProcess innovation is a key determinant of performance. While extant literature paints a clear picture of the drivers of process innovation, the effect of process innovation on performance has received little attention. This paper aims to examine how the divergence of process innovation impacts performance. Divergence concerns the extent to which the observed level of process innovation diverges from the expected level of process innovation. Positive divergence occurs when the observed level of process innovation is higher than expected while for negative divergence the opposite occurs. In turn, the authors consider how divergence acts as a driver of performance.Design/methodology/approachThe authors use survey and archival data from 5,594 firms across 15 countries. The authors analyze the data using an advanced two-step random-effects estimator that accounts for the multi-level data used.FindingsThe authors find negative divergence to reduce performance under high competitive intensity, whereas positive divergence is detrimental under high environmental uncertainty.Research limitations/implicationsThe authors present new and unique insights into the relationship between divergence and performance. The authors argue that each firm has an “ideal” level of process innovation, based on their resources and business environment, relative to which performance diminishes. Specifically, the authors argue that divergence from the firm’s expected level of process innovation is associated with the reduced performance during high environmental uncertainty or high competitive intensity. Furthermore, the authors argue that there can be “too much” process innovation. This nuance of the majority of prior empirical studies in this area suggests that more innovation is always better for firms. The more nuanced approach reveals that the process innovation-performance debate should not focus on more or less innovationper se, but on how innovation is constructed and supported.Practical implicationsSome argue the existence of an academia-practitioner gap, with both living in different worlds (Reibsteinet al., 2009). The findings suggest that theory is not only useful to practitioners but also has a crucial and central role regarding decisions relating to efficiency and effectiveness of scarce resources, in the field of process innovation. More specifically, the authors demonstrate that the prior study on process innovation seems to be useful in that relative to a theory-predicted level, divergence diminishes performance in the global sample of companies across a wide range of industries. In addition, the authors suggest that firms should not strive for more innovationper se. The findings suggest that positive divergence or too much innovation is detrimental for performance under environmental uncertainty, while negative divergence or too little innovation is harmful to performance under competitive uncertainty. Moreover, the divergence approach is also useful for comparing performance to that of other firms, typically referred to as benchmarking.Originality/valueThis paper is useful and important for managers and theory development as it provides insight into situations where a firm may have “too little” or “too much” process innovation. Thus, divergence advances understanding as, in contrast with the previous study, the authors do not suggest that more innovation is always better.