Early stage SME bankruptcy: does the local banking market matter?

Small Business Economics - This paper investigates the role of local context, with regard to the effect of local financial development and banking concentration, on a firm’s probability of...     

约翰·霍普金斯大学：中国需要新的增长动力？

“得过且过”的古话似乎并不适用于中国的经济增长。尽管过去25年，中国的经济增长屡创纪录，但外界普遍认为，它过于依赖固定投资作为经济增长的动力了。     

Leveraging purchase regularity for predicting customer behavior the easy way

The valuation of future customer activity is a mainstay of any organization seeking to efficiently manage its customer portfolio. In the area of customer-base analytics, the ongoing race for predictive power has yielded a large corpus of research to assist managers in this respect. Approaches in the tradition of stochastic models have been particularly successful because they rely only on easy-to-compute key metrics and integrate them within a parsimonious probability-modeling framework. Recent advances in this field have demonstrated that incorporating the timing regularity of past purchases can improve predictive accuracy relative to purely recency/frequency-based approaches. This paper expands that idea and introduces generalizations of a well-established probability model, the BG/NBD (Fader et al., 2005a), by replacing the exponential with a more flexible Erlang-k interarrival timing process. The resulting model variants are capable of leveraging regularity while retaining almost the same level of data requirements and algorithmic efficiency. Using extensive simulation studies and six data sets covering a wide range of empirical settings the authors demonstrate substantial improvements in predictive accuracy against the baseline models and performance gains close to or on par with a more complex model alternative. The availability of efficient and easily accessible implementations of the new model variants in the R-package BTYDplus allows marketing analysts to apply them in large-scale scenarios of data-rich environments on a continuous basis.     

Determinants and Value of Enterprise Risk Management: Empirical Evidence From the Literature

The development of an enterprise risk management (ERM) program enables companies to manage corporate risks in a holistic manner as opposed to the silo‐based perspective in traditional risk management frameworks. One main question in this regard is what factors drive the implementation of an ERM system in companies and whether ERM programs can actually create value once implemented. This article addresses these questions by conducting a comparative assessment of empirical evidence from the literature regarding the determinants of ERM and its value once implemented. In doing so we are able to illustrate differences in model specifications and the underlying data. Our literature study shows that particularly the company size and the level of institutional ownership are significantly positively related to the implementation of ERM in most empirical studies and, furthermore, that ERM generally has a (significant) positive impact on corporate value and performance (to a different extent and depending on the focus of the studies). However, geographic and/or industrial restrictions regarding the underlying data sets partly limit the generalization of the empirical results.     

Critical Illness Insurances: Challenges and Opportunities for Insurers

Since the first introduction of critical illness insurance in 1983 in South Africa, the product has successfully spread to some insurance markets, especially in Asian and Anglophone countries, but market penetration remains low in other countries. For this reason and because of the increasing relevance of dread diseases, the aim of this article is to provide a first comprehensive overview of challenges and opportunities associated with critical illness products for insurers. Toward this end, we first present the various product designs, as well as the developments that have taken place within the market before comparing this form of coverage to alternative insurance products in order to better assess the market potential. Based on these assessments, we thoroughly discuss the major challenges and opportunities within the market from the insurer's perspective.     

Networks and geography in the economics of knowledge flows. A comment

This paper proposes a comment on the article by M. A. Maggioni and T. E. Uberti within this issue. It focuses on one main question: can we say that the literature on Networks and Geography has reached the initial objective assigned to it: “Demonstrate that networks and geography are the necessary ingredients for every study of the innovative process at any level of analysis: from individual agents, to institution/organization, from the regional to the national and international level”? The answer to this question is presented following three main steps: (1) How do geographical positioning and network positioning interact to impact the innovative performance? (2) What is the influence of the geography on the networking strategies (cooperation choices)? (3) What is the influence of the network upon geographical strategies (location choices)? The conclusion is that the field described by Mario Maggioni and Erika Uberti is, as their paper shows, fast expanding and already has a history and appreciable results. It still clearly appears however that much still remains to be done if the potentiality offered by the cross-use of spatial and network analysis when dealing with knowledge diffusion and its impact on innovation is to be fully exploited. No doubt that the important advances accomplished during these last years in the collecting of data related to localized relationships will provide the necessary incentives to develop the still greatly lacking micro-econometric analyses.