This paper discusses the issue of formative constructs in information systems research. Researchers often mistakenly treat formative constructs as reflective, leading to errors in measurement models. Formative constructs are defined by their items, which describe and define the construct, rather than being affected by it. Reflective constructs, on the other hand, are affected by the underlying construct. The paper argues that researchers must properly specify formative constructs to ensure valid scientific results. It discusses the implications of misspecifying formative constructs, including Type I and Type II errors, and provides a roadmap for researchers to correctly specify formative constructs. The paper also discusses how to address formative constructs within a research model after they are specified. The paper highlights the importance of distinguishing between formative and reflective constructs and provides decision rules for identifying them. It also discusses the challenges of specifying formative constructs and the need for better understanding and dissemination of knowledge on this topic. The paper concludes that researchers must be aware of the potential for measurement model misspecification and take steps to ensure the validity of their constructs.This paper discusses the issue of formative constructs in information systems research. Researchers often mistakenly treat formative constructs as reflective, leading to errors in measurement models. Formative constructs are defined by their items, which describe and define the construct, rather than being affected by it. Reflective constructs, on the other hand, are affected by the underlying construct. The paper argues that researchers must properly specify formative constructs to ensure valid scientific results. It discusses the implications of misspecifying formative constructs, including Type I and Type II errors, and provides a roadmap for researchers to correctly specify formative constructs. The paper also discusses how to address formative constructs within a research model after they are specified. The paper highlights the importance of distinguishing between formative and reflective constructs and provides decision rules for identifying them. It also discusses the challenges of specifying formative constructs and the need for better understanding and dissemination of knowledge on this topic. The paper concludes that researchers must be aware of the potential for measurement model misspecification and take steps to ensure the validity of their constructs.