Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach

We investigate a novel database of 10,217 extreme operational losses from the Italian bank UniCredit. Our goal is to shed light on the dependence between the severity distribution of these losses and a set of macroeconomic, financial, and firm‐specific factors. To do so, we use generalized Pareto regression techniques, where both the scale and shape parameters are assumed to be functions of these explanatory variables. We perform the selection of the relevant covariates with a state‐of‐the‐art penalized‐likelihood estimation procedure relying on L₁‐penalty terms. A simulation study indicates that this approach efficiently selects covariates of interest and tackles spurious regression issues encountered when dealing with integrated time series. Lastly, we illustrate the impact of different economic scenarios on the requested capital for operational risk. Our results have important implications in terms of risk management and regulatory policy.     

Reviewing systematic literature reviews: ten key questions and criteria for reviewers

Management Review Quarterly - Systematic literature review articles are important for synthesizing knowledge in management and business research. However, to date, we lack clear guidelines how to...     

The benefits and implementation of performance transparency: The why and how of letting your customers ‘see through’ your business

While some organizations swear by the benefits of transparency and are eager to learn and implement transparency practices, many managers are still reluctant or even afraid to use them. Our research reveals that only a few innovative companies have taken steps to leverage a potentially useful form of transparency: the provision of accessible and objective information to customers (e.g., sharing unbiased benchmark data, publishing unfiltered customer comments, or providing candid product reviews that may praise but also criticize the company’s products). Our study also shows that many companies remain wary and view greater calls for transparency as a challenge to be managed rather than an opportunity to be traded upon. This is partly due to limited research into the performance benefits of giving customers access to objective information, and lack of practical guidelines on how to actually implement it. This article addresses these shortcomings. First, we investigate whether performance transparency leads to customer outcomes that can be profitable for an organization and, second, we analyze the characteristics of successful transparency initiatives in a wide range of industries. Our research shows that customers exhibit more trust and are willing to pay a premium to deal with transparent businesses. Also, it uncovers seven effective strategies to leverage transparency. This article provides convincing empirical evidence for the benefits of performance transparency and the ways in which management may implement it successfully.     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

New ventures in Cleantech: Opportunities,capabilities and innovation outcomes

Facing the challenge of climate change, innovations that imply environmental benefits create business opportunities for entrepreneurs. This paper analyzes innovation capabilities of startups in Cleantech and how the innovation outcomes of those startups develop over time. Based on the Mannheim Foundation Panel and applying propensity score matching, a cohort of 567 Cleantech startups is analyzed and compared with a control cohort of non‐Cleantech startups. We find that startups in Cleantech have, on average, higher technological capabilities compared with all other startups. Our econometric evidence shows that Cleantech startups are more likely to combine existing technology in a novel way. Finally, we find that Cleantech startups develop more market novelties in subsequent years when compared with their control group peers.     

Structures,strategizing, and contested territories: A structuration perspective on strategy development in employer branding

This study examines strategy development in employer branding based on structuration theory, focusing on the interplay between employer branding structures and the (inter)actions of employer branding strategists. To analyse this interplay, this paper draws upon a series of strategy meetings in an employer branding project of a multinational construction company. This study adds to the current debate on employer branding by advancing the understanding of the structural embeddedness of strategizing in employer branding. Furthermore, the study proposes that strategy development shifts employer branding engagements into contested territory due to various and contradictory structures strategists need to deal with.     

Taking agricultural technologies to scale: experiences from a vegetable technology dissemination initiative in Tanzania

One of the widely suggested approaches to meet the increasing food demand of a substantially growing world population is sustainable intensification. We present a unique agricultural research and scaling programme in Tanzania, focusing on the key elements necessary for results related to: gender analysis; private sector engagement; social capital; improvement and adaptation; and programme performance monitoring and evaluation. Since 2014, more than 6000 farmers have benefited from either the adaptive research or the scaling component of the programme. Preliminary impact analysis results from six pilot locations indicate that programme participants realized significantly higher yields compared to non-participants. In addition to productivity improvements, introducing resistant and drought-tolerant elite vegetable varieties improved the resilience of the existing farming systems. Finally, considering the needs of both male and female participants had a positive impact on technology adoption rates and reach.