Obtaining collaboration benefits: the role of collaboration-specific investment and absorptive capacity in China

This study examines the role of collaboration-specific investment and absorptive capacity on the attainment of interorganizational collaboration benefits. Grounded in the extended resource-based view, and using survey data from Chinese executives, we study the driver for, and test the impacts of, collaboration-specific investment and organizational learning on collaboration performance. Our findings indicate that resource similarity between the collaborative partners affects the level of collaboration-specific investment and learning, and demonstrate an approach that firms can use to obtain both abnormal common and private benefits from participation in an interorganizational collaboration. Specifically, the findings suggest that collaboration-specific investment has a direct effect on the enhancement of absorptive capacity and attainment of common and private collaboration benefits. Furthermore, due to the direct effect of absorptive capacity on attainment of collaboration benefits, commitment of collaboration-specific investment has an indirect effect on the attainment of common and private collaboration benefits. This study is the first to apply both the competence-capability framework and extended resource-based view to study interorganizational collaboration. In fact, this study aims to determine mechanisms for a collaboration-participating firm to obtain more benefit, whether common or private. Our findings provide support for the importance of learning capability as a factor in the acquisition of collaboration benefits.     

Does a central clearing counterparty reduce liquidity needs?

This study investigates whether and how central clearing influences the overall liquidity needs in a network of financial obligations. Utilizing the approach of flow network theory, we show that the effect of adding a central clearing counterparty (CCP) is decomposed into two effects: central routing, and central netting effects. Each effect can produce different liquidity needs according to different liquidity scenarios. The analysis indicates that adding a CCP in times of financial distress successfully reduces the overall liquidity needs if and only if the netting efficiency of the CCP is sufficiently high. Furthermore, once the economy is no longer in financial distress, higher netting efficiency of the CCP could conversely increase the overall liquidity needs. The results have implications for the effectiveness of CCPs in mitigating systemic risk in times of financial distress, and their operating costs once the distress has passed.     

Role of search for domain knowledge and architectural knowledge in alliance partner selection

Research Summary: The literature on technological alliances emphasizes that search for knowledge drives alliance formation. However, in conceptualizing technological knowledge, prior work on alliances has not made a distinction between domain knowledge—knowledge that firms possess in distinct technological domains—and architectural knowledge—knowledge that firms possess about how to combine elements from different technological domains. We argue that firms seek partners that are similar in domain knowledge to deepen their knowledge, and partners that are dissimilar in architectural knowledge to broaden their knowledge. Our results indicate that the likelihood of alliance formation increases when two firms are similar in domain knowledge and dissimilar in architectural knowledge. Further, our results show that these effects are positively moderated by the degree of decomposability of a firm's knowledge base. Managerial Summary: In dynamic environments, companies need to continually deepen and broaden their technological knowledge, and they often look for alliance partners who can provide them that knowledge. For knowledge deepening, companies are more likely to form alliances with those companies that have expertise in similar technological fields. For knowledge broadening, they are more likely to form alliances with those companies that have expertise in the same technological fields, but have different recipes for combining knowledge from those fields. Furthermore, a company with a modular knowledge base is more likely to seek a partner that has expertise in similar technological fields or whose recipes for combining knowledge from different technological fields are different from the recipes it has.     

The role of social proximity in professional CEO appointments: Evidence from caste/religion‐based hiring of CEOs in India

Research Summary: The role of homophily in CEO appointments at the largest corporations is an important subject in corporate governance. This subject is particularly important in a country like India where a multitude of religions, castes, and communities form its social fabric. We test for the role of homophily in professional CEO appointments in India by empirically examining the preference for same caste/religion CEOs by the largest firms. Using a unique dataset, assembled by detailed identification of castes/religions from family names and counterfactuals obtained through the Coarsened Exact Matching technique, we find that caste/religion plays a crucial role in CEO selection as a source of information (positive discrimination). The evidence is not consistent with its use to pursue taste‐based preferences (negative discrimination). Managerial Summary: We test for the role of homophily in the appointments of CEOs in India by empirically examining the preference for same caste/religion CEOs by the largest firms. We find that caste/religion plays an important role in CEO selection, i.e., as a form of information or “positive discrimination.” The evidence is not consistent with its use to pursue taste‐based preferences or “negative discrimination.”     

Modularization of hybrid censoring schemes and its application to unified progressive hybrid censoring

In this paper, a structural analysis of hybrid censoring models is presented. This new modularization approach to hybrid censoring models enables a convenient derivation of distributional results. For instance, it allows to derive the exact distribution of the MLEs under an exponential assumption for very complex hybrid scenarios. In order to illustrate the benefit of this idea, we apply it to four new unified progressive hybrid censoring schemes. They are extensions of already proposed unified Type-I/II/III/IV hybrid censoring schemes to progressively Type-II censored data. The resulting analysis shows that the modularization approach provides a powerful, efficient, and elegant tool to study even more complex hybrid censoring models.     

Inference for the two-parameter bathtub-shaped distribution based on record data

Here we consider the record data from the two-parameter of bathtub-shaped distribution. First, we develop simplified forms for the single moments, variances and covariance of records. These distributional properties are quite useful in obtaining the best linear unbiased estimators of the location and scale parameters which can be included in the model. The estimation of the unknown shape parameters and prediction of the future unobserved records based on some observed ones are discussed. Frequentist and Bayesian analyses are adopted for conducting the estimation and prediction problems. The likelihood method, moment based method, bootstrap methods as well as the Bayesian sampling techniques are applied for the inference problems. The point predictors and credible intervals of future record values based on an informative set of records can be developed. Monte Carlo simulations are performed to compare the so developed methods and one real data set is analyzed for illustrative purposes.     

Multi-level and mixed-level <Emphasis Type="Italic">k</Emphasis>-circulant supersaturated designs

Supersaturated designs (SSDs) constitute an important class of fractional factorial designs that could be extremely useful in factor screening experiments. Most of the existing studies have focused on balanced designs. This paper provides a new lower bound for the \(E(f_{NOD})\)-optimality measure of SSDs with general run sizes. This bound is a generalization of existing bounds since it is applicable to both balanced and unbalanced designs. Optimal multi and mixed-level, balanced and nearly balanced SSDs are constructed by applying a k-circulant type methodology. Necessary and sufficient conditions are introduced for the generator vectors, in order to pre-ensure the optimality of the constructed k-circulant SSDs. The provided lower bounds were used to measure the efficiency of the generated designs. The presented methodology leads to a number of new families of improved SSDs, providing tools for directly constructing optimal or nearly-optimal k-circulant designs by just checking the corresponding generator vector.     

Stochastic comparisons of coherent systems

The study of stochastic comparisons of coherent systems with different structures is a relevant topic in reliability theory. Several results have been obtained for specific distributions. The present paper is focused on distribution-free comparisons, that is, orderings which do not depend on the component distributions. Different assumptions for the component lifetimes are considered which lead us to different comparison techniques. Thus, if the components are independent and identically distributed (IID) or exchangeable, the orderings are obtained by using signatures. If they are just ID (homogeneous components), then ordering results for distorted distributions are used. In the general case or in the case of independent (heterogeneous) components, a similar technique based on generalized distorted distributions is applied. In these cases, the ordering results may depend on the copula used to model the dependence between the component lifetimes. Some illustrative examples are included in each case.     

The multiple filter test for change point detection in time series

A framework for the detection of change points in the expectation in sequences of random variables is presented. Specifically, we investigate time series with general distributional assumptions that may show an unknown number of change points in the expectation occurring on multiple time scales and that may also contain change points in other parameters. To that end we propose a multiple filter test (MFT) that tests the null hypothesis of constant expectation and, in case of rejection of the null hypothesis, an algorithm that estimates the change points.The MFT has three important benefits. First, it allows for general distributional assumptions in the underlying model, assuming piecewise sequences of i.i.d. random variables, where also relaxations with regard to identical distribution or independence are possible. Second, it uses a MOSUM type statistic and an asymptotic setting in which the MOSUM process converges weakly to a functional of a Brownian motion which is then used to simulate the rejection threshold of the statistical test. This approach enables a simultaneous application of multiple MOSUM processes which improves the detection of change points that occur on different time scales. Third, we also show that the method is practically robust against changes in other distributional parameters such as the variance or higher order moments which might occur with or even without a change in expectation. A function implementing the described test and change point estimation is available in the R package MFT.