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Climate warming, agricultural intensity, and urban growth are main forces triggering land degradation in advanced economies. Being active over different spatial and temporal scales, they usually reflect—at least indirectly—the impact of additional factors, such as wellbeing, demographic dynamics, and social development, on land quality. Using descriptive statistics and a multiple regression analysis, we analyzed the impact of these three processes comparatively over a decadal scale from 1960 to 2020 at the provincial level (Nuts-3 sensu Eurostat) in Italy. We enriched the investigation with a short-term forecast for 2030, based on four simplified assumptions grounded on a purely deterministic approach. Land degradation was estimated adopting the Environmental Sensitive Area Index (ESAI) measured at the spatio-temporal scale mentioned above. Computing on multiple observations at nearly 300,000 locations all over Italy, provinces were regarded as representative spatial units of the territorial pattern of land degradation. Between 1960 and 1990, the three predictors (climate, agriculture, and urbanization) explained a relatively high proportion of variance, suggesting a modest role for any other (unobserved) factor. All of these factors were found to be highly significant predictors of land degradation intensity across provinces, the most impactful being farming intensity. The highest adjusted-R2 coefficient was observed in both 1990 and 2000, and suggests that the three predictors still reflect the most powerful drivers of land degradation in Italy at those times, with a marginal role for additional (unobserved) factors. The impact of farming intensity remained high, with the role of urbanization increasing moderately, and the role of climate aridity declining weakly between 2000 and 2010. In more recent times (2010 and 2020), and in future (2030) scenarios, the adjusted R2 diminished moderately, suggesting a non-negligible importance of external (unobserved) factors and the rising role of spatial heterogeneity. The climate factor became progressively insignificant over time, while increasing the role of urbanization systematically. The impact of farming intensity remained high and significant. These results underlie a latent shift in the spatial distribution of the level of land vulnerability in Italy toward a spatially polarized model, influenced primarily by human pressure and socioeconomic drivers and less intensively shaped by biophysical factors. Climate aridity was revealed to be more effective in the explanation of land degradation patterns in the 1960s rather than in recent observation times. [ABSTRACT FROM AUTHOR]

To date, the studies on managerial loss aversion have produced contradictory findings, making it impossible to: (i) identify the ultimate impact of managerial loss aversion on the value that organisations create for themselves and for their stakeholders, and (ii) mitigate the effect of managerial loss aversion to improve corporate value creation. With the aim of filling this gap, the authors of this paper first performed a Systematic Literature Review (SLR), resulting in 65 relevant papers. The 65 papers were then analysed through a Thematic Analysis (TA), which was aimed at isolating and revising the single effects of managerial loss aversion on the corporate value creation process. Once it became clear when and how managerial loss aversion leads to negative impacts on corporate value creation (such as suboptimal investments in corporate social responsibility, short-term-oriented budget expenditures, illegal corporate conduct in favourable contexts, and low demand for audit quality), a novel theoretical framework was built. This framework proposes some preliminary approaches to mitigate these detrimental effects. In particular, future empirical research may operationalise potential debiasing strategies, derived from critical analysis of the literature, to reduce managerial loss aversion in different business settings, thereby improving corporate value creation. [ABSTRACT FROM AUTHOR]