Uncovering the worth of the past: the relationship between corporate museums' strategic orientation and dual performance

PurposeThe main aim of the study is to empirically investigate the relationship between strategic orientation and a dual conceptualization of performance (i.e. non-economic performance and economic performance) in the research context of corporate museums, which are owned and run by private companies. Furthermore, the study aims to explore the nature of the relationship between the dual performance, shedding light on the relevance of non-economic results for this peculiar category of museums.Design/methodology/approachThe study is based on survey data from 105 Italian corporate museums, which represent almost the entire population in the country (91%). A structural model was estimated using SmartPLS software in order to examine the direct and indirect effects of strategic orientation on corporate museums' non-economic and economic performance.FindingsThe findings show that only if corporate museums are able to achieve non-economic performance, creating value for the owning company and the local community, they can also have good results in economic terms. Thus, the non-economic performance acts as a mediator into the relationship between strategic orientation and economic performance.Originality/valueThe current work is a pioneer study for the empirical investigation of performance within corporate museums. The empirical model of the study, based on a dual conceptualization of performance and a mediation analysis, is completely innovative in this research context.

Efficient gene expression signature for a breast cancer immuno-subtype

Motivation and background The patient’s immune system plays an important role in cancer pathogenesis, prognosis and susceptibility to treatment. Recent work introduced an immune related breast cancer. This subtyping is based on the expression profiles of the tumor samples. Specifically, one study showed that analyzing 658 genes can lead to a signature for subtyping tumors. Furthermore, this classification is independent of other known molecular and clinical breast cancer subtyping. Finally, that study shows that the suggested subtyping has significant prognostic implications. Results In this work we develop an efficient signature associated with survival in breast cancer. We begin by developing a more efficient signature for the above-mentioned breast cancer immune-based subtyping. This signature represents better performance with a set of 579 genes that obtains an improved Area Under Curve (AUC). We then determine a set of 193 genes and an associated classification rule that yield subtypes with a much stronger statistically significant (log rank p-value < 2 × 10−4 in a test cohort) difference in survival. To obtain these improved results we develop a feature selection process that matches the high-dimensionality character of the data and the dual performance objectives, driven by survival and anchored by the literature subtyping.