Health Insurance Competition: The Effect of Group Contracts

In countries like the US and the Netherlands health insurance is provided by private firms. These private firms can offer both individual and group contracts. The strategic and welfare implications of such group contracts are not well understood. Using a Dutch data set of about 700 group health insurance contracts over the period 2007-2008, we estimate a model to determine which factors explain the price of group contracts. We find that groups that are located close to an insurers’ home turf pay a higher premium than other groups. This finding is not consistent with the bargaining argument in the literature as it implies that concentrated groups close to an insurer’s home turf should get (if any) a larger discount than other groups. A simple Hotelling model, however, does explain our empirical results.health insurance;health-plan choice;managed competition

Theoretical lenses and domain definitions in innovation research

Purpose - This study aims to scrutinize the meaning and domain of "innovation" by providing an extensive theory-driven review of the new product literature in marketing, management and engineering. The overall objective is to classify the recent literature on innovation and to illustrate theoretically derived discourses in the study of innovation. Design/methodology/approach - The paper organizes this literature by providing typologies of discourses, which define innovation. Based on our review of 238 articles from a comprehensive set of journals publishing innovation research, we propose a theoretical divide in the innovation literature. Findings - Theoretical underpinnings, namely adoption/diffusion theory versus the resource-based/contingency theory view, form one dimension of the typology. Jointly considered with the other two dimensions - level of analysis and customer vs firm perspective - a framework is formed of the different discourses and conceptualisations in the innovation literature. Originality/value - Past researchers have always proposed a definition of innovation that was embedded in a typology of innovation types; in contrast, the paper allows the theoretical discourses to unveil meanings of innovation and associated constructs (and hence it starts with theory specification, not construct definition). It argues for starting with theory as the basic division and proposes a theory driven typology. Through its theoretical genesis, the paper wishes to create a shared understanding among academics and practitioners of what constitutes innovation and constructs within the related theoretical net. © Emerald Group Publishing Limited

New product success: Is it really controllable by managers in highly turbulent environments?

This research proposes and tests a model of direct and indirect effects linking four antecedents to new product success: (1) a proactive strategic orientation along with enabling (2) organic organizational structures should lead to more (3) innovativeness and (4) market intelligence. Innovativeness and market intelligence should in turn lead to greater new product success. The relationships among the four antecedents are not hypothesized to be moderated by environmental turbulence because their domain is intraorganizational. However, the relationships from intraorganizational constructs to new product success are hypothesized to be moderated by environmental turbulence because success depends in part on the environment in which the new product must compete. The model was tested using a sample composed of 202 small business units of manufacturers on the Fortune 500. The sample was heavily involved in new product development: Their average annual research and development budget was $360.4 million, and approximately 8.2% of sales came from products introduced in the last five years. A two-group structural equation model analysis supports the moderation model overall and reveals the pattern of direct, indirect, and total effects. The results show that innovativeness (but not market intelligence) directly predicts new product success when turbulence is high, whereas market intelligence (but not innovativeness) directly engenders new product success in low turbulence. Environmental turbulence also affects the total indirect impact of strategy proactiveness and organizational organicity on new product success. These indirect effects operate through innovativeness and market intelligence as complete mediators. © 2008 Product Development & Management Association

The Euclid Archive Processing and Data Distribution Systems: A Distributed Infrastructure for Euclid and Associated Data

The Euclid Archive System is an ambitious information system, which sits at the heart of the Euclid Science Ground Segment. It is a joint development between the Euclid Consortium and the ESAC Science Data Centre. It encompases both Euclid data and the large volume of associated ground based data (e.g. KiDS, DES and LSST). The Euclid Science Ground Segment consists of the Euclid Science Operations Centre and ten national Science Data Centres. The large data volumes demand that data transfer is minimized and that the processing is taken to the data. This is supported by the Euclid Archive Data Processing System and the Euclid Archive Distributed Data System. The Data Processing System consists of a central metadata repository, which contains the information necessary to process any data item and full data lineage of any data product created. The Distributed Data System provides a cloud solution with a node at each of the national Science Data Centres, which controls data storage and transfer. It supports a large number of storage types, including POSIX, iRODS, gridftp and Xrootd. No limitations are placed on the storage implemented at an individual SDC. Further more, the user of the system needs no knowledge of where data is located. Jobs will be started at the most appropriate locations, or data transferred as necessary

The Euclid Archive Processing and Data Distribution Systems: A Distributed Infrastructure for Euclid and Associated Data

The Euclid Archive System is an ambitious information system, which sits at the heart of the Euclid Science Ground Segment. It is a joint development between the Euclid Consortium and the ESAC Science Data Centre. It encompases both Euclid data and the large volume of associated ground based data (e.g. KiDS, DES and LSST). The Euclid Science Ground Segment consists of the Euclid Science Operations Centre and ten national Science Data Centres. The large data volumes demand that data transfer is minimized and that the processing is taken to the data. This is supported by the Euclid Archive Data Processing System and the Euclid Archive Distributed Data System. The Data Processing System consists of a central metadata repository, which contains the information necessary to process any data item and full data lineage of any data product created. The Distributed Data System provides a cloud solution with a node at each of the national Science Data Centres, which controls data storage and transfer. It supports a large number of storage types, including POSIX, iRODS, gridftp and Xrootd. No limitations are placed on the storage implemented at an individual SDC. Further more, the user of the system needs no knowledge of where data is located. Jobs will be started at the most appropriate locations, or data transferred as necessary

The Euclid Archive Processing and Data Distribution Systems: A Distributed Infrastructure for Euclid and Associated Data

The Euclid Archive System is an ambitious information system, which sits at the heart of the Euclid Science Ground Segment. It is a joint development between the Euclid Consortium and the ESAC Science Data Centre. It encompases both Euclid data and the large volume of associated ground based data (e.g. KiDS, DES and LSST). The Euclid Science Ground Segment consists of the Euclid Science Operations Centre and ten national Science Data Centres. The large data volumes demand that data transfer is minimized and that the processing is taken to the data. This is supported by the Euclid Archive Data Processing System and the Euclid Archive Distributed Data System. The Data Processing System consists of a central metadata repository, which contains the information necessary to process any data item and full data lineage of any data product created. The Distributed Data System provides a cloud solution with a node at each of the national Science Data Centres, which controls data storage and transfer. It supports a large number of storage types, including POSIX, iRODS, gridftp and Xrootd. No limitations are placed on the storage implemented at an individual SDC. Further more, the user of the system needs no knowledge of where data is located. Jobs will be started at the most appropriate locations, or data transferred as necessary

The Role of the Euclid Archive System in the Processing of Euclid and External Data

Euclid is an ESA M2 mission which will create a 15,000 square degrees space-based survey: the Euclid Archive System (EAS) is a core element of the Science Ground Segment (SGS) of Euclid. The EAS follows a data-centric approach to data processing, whereby the Data Processing System (DPS) is responsible for the centralized metadata storage and the Distributed Storage System (DSS) supports the distributed storage of data files. The EAS-DPS implements the Euclid Common Data model and along with the EAS-DSS provides numerous services for Euclid Consortium users and SGS subsystems. In addition, the EAS-DPS assists in the preparation of Euclid data releases which are copied to the third EAS subsystem, the ESA developed Science Archive System (SAS) where they become available to the wider astronomical community. The EAS-DPS implements the object-oriented Euclid Common Data Model using a relational DBMS for the storage. The EAS-DPS supports the tracing of the lineage of any data item in the system, provides services for the data quality assessment and the data processing orchestration. The EAS-DSS is a distributed storage system which is based on a set of storage nodes located in each of the ten Science Data Centers of the Euclid SGS. The storage nodes supports a wide range of solutions from local disk, using a unix filesystem, to iRODS nodes or Grid storage elements. In this paper the architectural design of EAS-DPS and EAS-DSS are reviewed: the interaction between them and tests of the already implemented components are described