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The purpose of this paper is to address the issue of knowledge visualization and its connection with performance measurement from an epistemological point of view, considering quantification and measurement not just as technical questions but showing their relevant implications on the management decision-making of knowledge-based organizations.

This study proposes a theoretical contribution that combines two lines of research for identifying the three main meta-choices problems that arise in the multidimensional benchmarking of knowledge-based organizations. The first is the meta-choice problem related to the choice of the algorithm used (Iazzolino et al., 2012; Laise et al., 2015; Daraio, 2017a). The second refers to the choice of the variables to be included in the model (Daraio, 2017a). The third concerns the choice of the data on which the analyses are carried out (Daraio, 2017a).

The authors show the interplay existing among the three meta-choices in multidimensional benchmarking, considering as key performance indicators intellectual capital, including Human Capital, Structural Capital and Relational Capital, and performances, evaluated in financial and non-financial terms. This study provides an empirical analysis on Italian Universities, comparing the ranking distributions obtained by several efficiency and multi-criteria methods.

This study demonstrates the difficulties of the “implementation problem” in performance measurement, related to the subjectivity of results of the evaluation process when there are many evaluation criteria, and proposes the adoption of the technologies of humility related to the awareness that we can only achieve “satisficing” results.

Competition in the modern, knowledge-based economy is utterly pendant on innovation, rendering it indispensable in virtually every organisation. Knowledge workers, therefore, must remain vigilant, spanning novel ways to innovate. Given the relevance of innovation orientation (IO) in knowledge work, it is imperative to possess an extensive understanding of the concept. Therefore, this study aims to develop and validate a measurement scale to gauge employees’ IO.

Considering that the instruments now in existence exhibit insufficiency for measuring knowledge workers’ IO in its entirety, the mixed-method approach used in this study draws on both qualitative and quantitative findings across various studies, to address this problem. This study has been organised into five stages: item generation, scale purification, scale refinement, nomological validation and generalizability.

This study establishes and verifies a second-order, reflective–reflective IO measure founded on multiple samples, encompassing the dimensions of creative orientation, learning orientation, first-mover orientation, trust orientation and agility orientation. The resultant IO scale serves as a robust and reliable tool that is capable of being leveraged to explain, assess and enhance IO for knowledge workers.

The rigorous methodology used in this scale development procedure serves as a benchmark for prospective scale development methodologists. From a managerial stance, this study serves managers/leaders concerning how to foster an innovation-oriented work environment to uncover employees’ hidden innovators. Organisations can leverage this study to discover, cultivate and capitalise on knowledge workers’ IO.

Although there exists an abundance of research on IO viewed from an institutional standpoint, research centred on the IO of knowledge workers is scarce. To bridge this gap, this study has developed and validated a scale for measuring knowledge workers’ IO.