The last three decades have witnessed a huge amount of research exploring the linkage between companies' sustainability performance (SP), sustainability disclosure and financial performance (FP). Researchers have applied various methods and techniques to investigate this relationship, yet the results remain equivocal. In this article, we look inside this black box by considering various manifestations of sustainability practices and investigating their link with FP. We apply a manual content analysis technique to analyse the sustainability reports of the 100 best‐performing US firms. Our results reveal that fragmentation in the results is caused by the SP measurement. Additionally, we note that the interlinkages between different SP dimensions and sub‐dimensions are weak and somewhat contradictory. The results help draw important policy implications for the development of an SP reporting framework.

We aim to investigate the impact of the adoption of an Enterprise Risk Management (ERM) system on the enterprise value and to discover which are the determinants of this choice. Several economic actors have decided to face the current economic and financial complexity shifting from a Traditional silo-based Risk Management approach (TRM) to a more comprehensive one, the so called Enterprise Risk Management (ERM). Some academics have tried to investigate the effects of the ERM implementation on firm value, mainly focusing on the financial industry. The results are still controversial. Moreover, there is no empirical evidence about the adoption of ERM programs among non-financial companies. The aim of our study is double: first, we try to understand if the ERM implementation affects firm value on a sample of 200 European companies, belonging to both financial and non-financial industries; second, we test which are the determinants of the adoption of an ERM system. We do this performing a fixed effects panel regression analysis (goal 1) and a fixed effects logistic analysis (goal 2). We find a positive statistically significant relation between the ERM adoption and firm value. As for the probability that a firm engages in an ERM protocol, we find that size, the company beta and profitability (ROA) are the statistically significant determinants. JEL Classifications: G32, L22, L25,

We aim to investigate the impact of the adoption of an Enterprise Risk Management (ERM) system on the enterprise value and to discover which are the determinants of this choice. Several economic actors have decided to face the current economic and financial complexity shifting from a Traditional silo-based Risk Management approach (TRM) to a more comprehensive one, the so called Enterprise Risk Management (ERM). Some academics have tried to investigate the effects of the ERM implementation on firm value, mainly focusing on the financial industry. The results are still controversial. Moreover, there is no empirical evidence about the adoption of ERM programs among non-financial companies. The aim of our study is double: first, we try to understand if the ERM implementation affects firm value on a sample of 200 European companies, belonging to both financial and non-financial industries; second, we test which are the determinants of the adoption of an ERM system. We do this performing a fixed effects panel regression analysis (goal 1) and a fixed effects logistic analysis (goal 2). We find a positive statistically significant relation between the ERM adoption and firm value. As for the probability that a firm engages in an ERM protocol, we find that size, the company beta and profitability (ROA) are the statistically significant determinants. JEL Classifications: G32, L22, L25,

We study how the investor profile influences the asset allocation recommendations of professional advisors. We find the investor's perceived risk attitude influences more the mix of risky assets, whereas the socioeconomic variables influence more the cash percentage. The recommendations are consistent with a diversification behavior driven by actual asset correlations. These findings support the utility of investor advisory that may help enhance the risk and return trade-off. The main drawback of the recommendations may consist in the degree of customization that is limited by the small number of investor characteristics actually influencing the asset allocation. JEL Classification: G11

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