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Unconventional monetary policy and bank risk taking
No full textWe analyze the presence of bank risk taking associated with unconventional monetary policy in the United States between 2008 and 2015 using corporate syndicated loan data at the bank-firm level. We measure monetary policy using the identification-through-heteroskedasticity approach with a VAR model. To identify the risk-taking channel we control for time-varying heterogeneity in credit demand and supply. Our results indicate that accommodating monetary conditions are associated with overall lower loan spreads. However, the spread reduction is lower for riskier firms, suggesting that there is no risk taking behavior in the syndicated loan market during the UMP period
Flexible multivariate Hill estimators
No full textDominicy et al. (2017) introduce a family of Hill estimators for elliptically distributed and heavy tailed random vectors. They propose to use the univariate Hill to a norm of order h of the data. The norms are homogeneous functions of order one. We show that the family of estimators can be generalized to homogeneous functions of any order and, more importantly, that ellipticity is not required. Only multivariate regular variation is needed, as it is preserved under well-behaved homogeneous functions. This enables us to have flexibility in terms of the estimator and the underlying distribution. Consistency and asymptotic normality are shown, and a Monte Carlo study is conducted to assess the finite sample properties under different asymmetric and heavy tailed multivariate distributions. We illustrate the estimators with an application to 10 years of daily data of paid claims from property insurance policies across 15 regions of Belgium.Matias Heikkila gratefully acknowledges financial support from Magnus Ehrnrooth Foundation, Finland
Trust transfer and partner selection in interfirm relationships
No full textDespite third parties being important conduits of trust, little is known about the mechanisms and conditions relevant to their influence on trust formation and partner selection in interfirm relationships. In this study, we experimentally examine how varying levels of third-party information shape the trust that buyer managers have in a potential supplier firm, and how this trust affects subsequent selection decisions. In addition, we investigate when this information is most influential, by accounting for the moderating impact of the focal firm’s own prior experience. As expected, both neutral and favorable third-party information are able to elicit trust, yet with different effects on competence and goodwill trusting beliefs. These trusting beliefs, in turn, are positively associated with the likelihood of the supplier to be selected. Notably, we find third-party effects over and above the effects resulting from own prior experience. Overall, by investigating differences with regard to the origin and content of information and the specific type of trust, this study advances a more nuanced understanding of the partner selection process.We acknowledge the funding received from the Intercollegiate Center for Management Science to support this researc
Controversy Without Conflict: How Group Emotional Awareness and Regulation can Prevent Conflict Escalation
Get PDFWe investigate whether group emotional awareness can prevent the escalation of controversy into conflict in project teams. We propose that group emotional awareness mitigates the impact of initial task conflicts on the development of group emotion regulation. This, in turn, prevents the escalation of task into relationship conflicts. We test our proposed model through a longitudinal design on project teams over the duration of a 3-month project, from the onset of their work together till the completion of the project. Group emotional awareness mitigates the impact of high levels of initial task conflict on the development of emotion regulation: the latter lacks conditions to develop when group emotional awareness is low and groups experience task conflict and can only develop under high emotional awareness conditions. Once in place, group emotional regulation reduces the likelihood of task conflicts escalating to relationship conflicts
Front End Transfers of Digital Innovations in a Hybrid Agile‐Stage‐Gate Setting
No full textThe hybrid Agile-Stage-Gate model encourages a collaborative instead of transactional approach to front end work on digital innovations.
Digital innovation transfers are distinctly different from technology transfers and, therefore, require a re-think of a firm’s existing innovation processes and performance measurements.
Manager should take into account that there are three different transfer practices that either facilitate (i.e., transfer management) or inhibit (i.e., transfer scope and synchronization) front end transfers of digital innovations.
Establishing champions across the important organizational interface of Research and Development is crucial in realizing front end transfers of digital innovations.Digital innovations often follow a more fluid innovation process and, therefore, require different ways of managing the front end of innovation. Agile as alternative to established front end management practices is often suggested, potentially combined with Stage‐Gate, in what is called a hybrid Agile‐Stage‐Gate model, to reap the benefits from both. Implementing the hybrid model in the front end is however not sufficient for firms with separate Research and Development departments to succeed. In such organizations digital innovations still need to be transferred from Research, where the front end work on digital innovations takes place, to the Development department, where formal development actually starts. Yet, such front end transfers have been described as inefficient and ineffective. Realizing digital innovation front end transfers is likely even more challenging because of their fluid definition. In the absence of extant theory on front end transfers in such a setting, this research uses a case study approach to analyze the front end transfer experiences of the Research department of a firm in the lighting industry that is undergoing a transformation from traditional to digital lighting. The in‐depth analysis of triangulated data on eight front end projects shows that Research struggles to transfer digital innovations to Development, because transfer practices in terms of management, scope, and synchronization, turn out to be inherently challenging in a hybrid Agile‐Stage‐Gate setting. Specifically, the results reveal that each transfer practice plays an intricate role in either facilitating (i.e., transfer management) or inhibiting (i.e., transfer scope and synchronization) front end transfers of digital innovations. The discovery of these opposing forces has important implications for novel theorizing on the use of Agile in the front end of digital innovation, transfer practices from Research to Development in a hybrid setting, as well as for theorizing about digital innovation management
The correlation structure of anomaly strategies
No full textWe consolidate a large number of mean-significant anomalies into cluster portfolios. More than a third of cluster portfolios remain significant under the Hou et al. (2020) five-factor model — the best performing among six benchmark models tested. A best-first search yields nine factors that subsume all cluster portfolios as well as all significant anomalies, demonstrating the feasibility of a parsimonious description of average realised returns. The expected growth factor (EG) and a cluster portfolio linked to accruals are prominent factors that improve pricing performance. The search-generated model produces a monthly maximum squared Sharpe ratio of 0.51, considerably higher than current benchmark models
Change management by negation: Exploring the power of the rejected
No full textOrganisation and management science has been, ever since its inauguration, overly desperate to find the 'one best way of organising'. The basic fundament of that quest was the attempt to define an organisation positively, namely by what it is. Until today, this starting point has not proven to be successful; this way has not decided to disclose its ability to instruct the theory and practice of organisation yet. This article argues that this positive, ontological way to define organisations and its major results like change management has led Organization and Management Theory (OMT) into a rather blurry state. OMT and especially change management would become much more instructive again if it started defining its objects negatively, by what they are not. After showing the pitfalls of the positive fiction in OMT, the article presents a negative way to instruct, especially change management. This profit will be demonstrated by introducing the concept of the tetralemma
A 2020 perspective on “The building of online trust in e-business relationships”
No full textThis research commentary discusses the perspectives offered in the article “The building of trust in online relationships.” The update argues that the creation of online trust is essential to support effective e-commerce transactions and interorganizational relationships. This goes beyond the advantages that buyers and sellers perceive to have become available through the digitalization of transaction-making. For this reason, we call for new kinds of research that goes beyond what the literature has presented before, to include new kinds of data, such as the digital traces of speech and communication. We also advocate more experimental research on consumer perceptions of organizational trustworthiness, including the use of functional magnetic resonance imaging (FMRI) of the brain to gain a more complete understanding of consumer information and perception processing, and their effects on their decision-making
Patient-Level Effectiveness Prediction Modeling for Glioblastoma Using Classification Trees
No full textOBJECTIVES: Little research has been done in pharmacoepidemiology on the use of machine learning for exploring medicinal treatment effectiveness in oncology. Therefore, the aim of this study was to explore the added value of machine learning methods to investigate individual treatment responses for glioblastoma patients treated with temozolomide.
METHODS: Based on a retrospective observational registry covering 3090 patients with glioblastoma treated with temozolomide, we proposed the use of a two-step iterative exploratory learning process consisting of an initialization phase and a machine learning phase. For initialization, we defined a binary response variable as the target label using one-by-one nearest neighbor propensity score matching. Secondly, a classification tree algorithm was trained and validated for dividing individual patients into treatment response and non-response groups. Theorizing about treatment response was then done by evaluating the tree performance.
RESULTS: The classification tree model has an area under the curve (AUC) classification performance of 67% corresponding to a sensitivity of 0.69 and a specificity of 0.51. This result in predicting patient-level response was slightly better than the logistic regression model featuring an AUC of 64% (0.63 sensitivity and 0.54 specificity). The tree confirms confounding by age and discovers further age-related stratification with chemotherapy-treatment dependency, both not revealed in preceding clinical studies. The model lacked genetic information confounding treatment response.
CONCLUSIONS: A classification tree was found to be suitable for understanding patient-level effectiveness for this glioblastoma-temozolomide case because of its high interpretability and capability to deal with covariate interdependencies, essential in a real-world environment. Possible improvements in the model's classification can be achieved by including genetic information and collecting primary data on treatment response. The model can be valuable in clinical practice for predicting personal treatment pathways.This work was supported by the Vlerick Business School Academic Research Fund. The funding agreement ensured the authors' independence in designing the study, interpreting the data, and publishing the report
Multi-mode schedule optimisation for incentivised projects
No full textThis research presents a novel quantitative methodology to optimise the scheduling of subcontracted projects from the perspective of the contractor. Specifically, the scenario where the contractor’s remuneration is performance dependent is investigated. Based on the incentive methodology introduced by Kerkhove and Vanhoucke (2016), a novel mixed integer programming formulation as well as a greedy local search heuristic to solve the contractor’s problem are presented and tested in a computational experiment. For this experiment, a database containing 3,150 contract-project combinations with diverse structures has been created. The results from this experiment demonstrate the efficiency of the MIP formulation even for larger problem instances, as well as the influence of the project and contract structure on the contractor’s earnings