Nathan P. Podsakoff

TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.

TL;DR: The meaning of the terms "method" and "method bias" are explored and whether method biases influence all measures equally are examined, and the evidence of the effects that method biases have on individual measures and on the covariation between different constructs is reviewed.

TL;DR: New and existing techniques are integrated into a comprehensive set of recommendations that can be used to give researchers in MIS and the behavioral sciences a framework for developing valid measures.

TL;DR: Results indicated that OCBs are related to a number of individual-level outcomes, including managerial ratings of employee performance, reward allocation decisions, and a variety of withdrawal-related criteria, and some evidence that O CBs are causally related to these criteria is provided.

TL;DR: In this article, a comprehensive set of recommendations that can be used to give researchers in MIS and the behavioral sciences a framework for developing valid measures is presented. But the scale development and validation of constructs is still a challenging activity.