Purpose The purpose of this paper is to investigate whether implementing certain innovation strategies and adopting a portfolio of innovations improve the relationship between supplier integration (SI) and operational performance (OP). Design/methodology/approach The authors test several research hypotheses by using a data set of 173 firms. Data were collected by interviewing managers, presidents and directors, from ten European countries and across nine different industries. The authors use structural equation modeling to estimate the relationships between SI and OP. The authors apply multi-group analysis to test the effects of certain innovation strategies and a portfolio of innovations on these relationships. Findings The authors show that SI improves internal OP but has no direct effect on external OP. The latter can only be improved through well-performing internal operations. The adoption of an incremental product innovation strategy improves the relationship between internal and external OP and leads to more effective SI. Other types of innovations do not help in improving the impact of SI on OP. Finally, the adoption of a portfolio of innovations does not enhance the influence of SI on OP. Thus, firms should focus on a small number of innovations rather than expanding their innovation portfolio to improve the effectiveness of SI on OP. Practical implications When firms aim to improve the impact of SI on OP, they should concentrate on incremental product innovations. Other strategies obtained by combining process, incremental and radical innovations are not adequate for that purpose. An expanded portfolio of innovations does not improve the effect of supplier innovation on OP. Originality/value This research suggests how the impact of SI on OP can be improved by adopting certain innovation strategies and without diversifying the portfolio of innovation projects.

This paper investigates a supply chain governed by a flat penalty service‐level contract in which missing the target fill rate can lead to costly operational disruption. We focus on near‐miss bias: (1) the preference for near‐miss events, that is, risky production quantities that reach the target but narrowly avoid disruption; and (2) riskier decision‐making due to such preferences. We propose a reference‐dependent behavioral model that explains the near‐miss bias. The findings of a laboratory experiment show that production quantities are evaluated based on realized profits and are below the optimal model prediction. Contracts associated with lower perceived severity, that is, the ratio of flat penalty to wholesale price, result in lower production quantities than those with higher perceived severity, even though the standard model does not predict any effect. A structural estimation analysis indicates that the behavioral model performs better than the standard model in terms of predictive accuracy and goodness of fit. Our analysis provides insights for managers who design supply chain contracts in settings with considerable risk of disruption due to a shortage of critical parts.

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