Archivio istituzionale della Ricerca - Bocconi
Not a member yet
30225 research outputs found
Sort by
Energizing change: how policies and experience drive research and development
No full textGiven the significance of firm research and development (R&D) investment in supporting successful technological shifts, this paper asks whether policy incentives can drive firms to invest in R&D. We use data from the U.S. electric utilities industry, a setting in which most state governments have enacted renewable portfolio standards (RPSs) mandating renewable electricity. We examine whether these policies also motivate firms to increase investment in R&D. We find a positive relationship between RPSs and R&D investment but primarily among firms with previous experience generating renewable electricity. Notably, electric utility firms focus their investments on external R&D rather than on internal R&D projects. By highlighting how policy incentives for technological change and firm technological experience work together to stimulate R&D efforts, this research deepens our understanding of technological search
Denunzia di gravi irregolarità, titolarità dell’aliquota del capitale sociale e legittimazione ad agire
No full textLa nota commenta il provvedimento di Trib. Napoli, Sez. Impr., 25 giugno 2025 in tema di qualificazione della quota di partecipazione nel capitale sociale ai fini della proposizione da parte del socio della denunzia di gravi irregolarità dell'art. 2409 c.c. Nel commento si critica la qualifica di tale requisito alla stregua della legittimazione ad agire in base alla affermazione della natura di giudizio a contenuto oggettivo del procedimento de quo
When colleagues compete outside the firm
Get PDFCollaboration among employees
is the bedrock of an organization, but we suggest that it
can be undermined by their extra‐organizational affilia-
tions. We point to the hidden but common constella-
tion of two coworkers who are also affiliated with
organizations that compete with one another. We
hypothesize that such colleagues collaborate less with
one another when performing on behalf of their shared
employer. Using data from professional soccer, we
provide empirical evidence. We outline implications
for research on extra‐organizational affiliations, intra-
organizational collaboration, competition and rivalry,
and social networks
Persuasion and gender: experimental evidence from two political campaigns
Get PDFWe investigate differential responses by gender to competitive persuasion in political
campaigns. We implemented a survey and a field experiment during two mayoral elections in Italy. Eligible voters were exposed to a positive or negative campaign by an opponent. The survey experiment used on-line videos and slogans. The field experiment used door-to-door canvassing. In both experiments, gender differences emerge. Females vote more for the opponent and less for the incumbent when exposed to positive—as opposed to negative—campaigning. Males do the opposite. These differences cannot be explained by gender identification, ideology, or other voters’ observable attributes
Assessing the influence of ESG washing on bank reputational exposure: a cross‐country analysis
Get PDFThe study investigates the effects of ESG washing on banks' reputational exposure. We define ESG washing as a disparity between a bank's environmental and social disclosure level and the practical implementation of the relative measures. The analysis involves an international sample of 120 banks operating across 35 countries from 2014 to 2020. The results evidence a different effect based on the pillar considered: the higher the inconsistency on environmental issues, the higher a bank's reputational exposure. Conversely, higher levels of disclosure compared to performance on social issues appear to reduce reputational exposure. In addition, citizen movements and the country's legal system play a significant role in amplifying or mitigating a bank's reputational exposure. Our findings offer insight into the phenomenon of ESG washing in the banking industry, supporting the need for more verified information across countries and all economic sectors
Sustainable governance: board sustainability experience and the interplay with board age for firm sustainability
No full textThe growing emphasis on sustainability in the business landscape has prompted scholars and industry practitioners to explore the role of corporate governance, particularly the board of directors, in promoting corporate sustainability. Companies are called upon to operate ethically and to redefine their objectives beyond mere economic pursuits to create social impacts that contribute to sustainability challenges. Corporate governance plays a key role in this regard, as it defines the purpose and ethical orientation of the firm, thereby shaping its sustainability. While previous research has primarily focused on observable board characteristics, this study delves into a critical yet underexplored aspect of sustainable boards, i.e., the sustainability experience. Drawing on the upper echelon and resource dependency theories, our research examines how the sustainability experience of board members influences a firm's sustainability performance, investigating the moderating effect of board age. We analyzed European listed companies from 2014 to 2020, and our findings show that the effect of board sustainability experience on firm performance is contingent on board age. Specifically, our results show that younger boards amplify the positive effect of sustainability experience, while for older boards, this effect diminishes, up to the point of being completely mitigated, highlighting a potential misalignment between sustainability efforts and ethical business conduct. This study is pioneering in investigating the joint effects of board sustainability experience and board age on a firm's sustainability, thus, providing valuable contributions to theory and practical recommendations for firms in director recruitment, as well as recommendations for regulatory practices
View selection in multi-view stacking: choosing the meta-learner
No full textMulti-view stacking is a framework for combining information from different views (i.e. different feature sets) describing the same set of objects. In this framework, a base-learner algorithm is trained on each view separately, and their predictions are then combined by a meta-learner algorithm. In a previous study, stacked penalized logistic regression, a special case of multi-view stacking, has been shown to be useful in identifying which views are most important for prediction. In this article we expand this research by considering seven different algorithms to use as the meta-learner, and evaluating their view selection and classification performance in simulations and two applications on real gene-expression data sets. Our results suggest that if both view selection and classification accuracy are important to the research at hand, then the nonnegative lasso, nonnegative adaptive lasso and nonnegative elastic net are suitable meta-learners. Exactly which among these three is to be preferred depends on the research context. The remaining four meta-learners, namely nonnegative ridge regression, nonnegative forward selection, stability selection and the interpolating predictor, show little advantages in order to be preferred over the other three
The unseen targets of hate: a systematic review of hateful communication datasets
Get PDFMachine learning (ML)-based content moderation tools are essential to keep online spaces free from hateful communication. Yet ML tools can only be as capable as the quality of the data they are trained on allows them. While there is increasing evidence that they underperform in detecting hateful communications directed towards specific identities and may discriminate against them, we know surprisingly little about the provenance of such bias. To fill this gap, we present a systematic review of the datasets for the automated detection of hateful communication introduced over the past decade, and unpack the quality of the datasets in terms of the identities that they embody: those of the targets of hateful communication that the data curators focused on, as well as those unintentionally included in the datasets. We find, overall, a skewed representation of selected target identities and mismatches between the targets that research conceptualizes and ultimately includes in datasets. Yet, by contextualizing these findings in the language and location of origin of the datasets, we highlight a positive trend towards the broadening and diversification of this research space