Unfortunately The Introduction Of Our New Product Will Be Delayed: An Exploratory Examination Of Factors That Influence A Firm To Announce Changes In Its New Product Plans

New product preannouncement research investigates formal and deliberate communications by a firm regarding its future new product introductions (e.g., types of new products, new product attributes, plans for distribution, planned launch date). However, previous studies have primarily focused on communication related to the firm’s intent to introduce a new product and largely ignored communications regarding changes in their status, such as launch delays as well as cancellation of the new product introduction. The goal of this study is to address this shortfall by examining antecedents factors  influencing a preannouncing firm (i.e., one that preannounces its new products) to also announce changes in to its new product introduction plans (NPCs); specifically, delays in the introduction of a new product or its cancellation. This topic is particularly relevant given the importance that recent studies have placed on the investigation of false new product preannouncements or bluffs, especially in the software industry where they are termed vaporware.  Furthermore, in the wake of the many recent high-profile corporate scandals (e.g., Enron and Tyco), a growing emphasis on corporate disclosure, particularly regarding performance shortfalls (e.g., new product delays and cancellations), also highlights the need for further research on corporate communication regarding changes to new product introduction plans.  Additionally, unlike most extant preannouncement research that attempts to examine differences between preannouncers and non-preannouncers, our study only examines firms that preannounce their new product introductions and then, goes further, by examining post-preannouncement behavior. In developing our framework, we propose five antecedents that motivate a preannouncing firm’s propensity, when the situation arises, to issue announcements regarding delays in a new product introduction or its cancellation. Additionally, we highlight the use of NPCs as strategic marketing communication tools that can continually inform and influence a wide range of target audiences (e.g., buyers, employees, supply chain participants, investors, and business media). The hypotheses are tested via factor score regression with a sample of 221 U.S. – based manufacturers. Our findings indicate that it is not the firm’s desire to communicate in a general sense through information sharing nor its concerns regarding competitors that motivates preannouncing firms to issue NPCs. Instead, the preannouncing firm’s desire to build its reputation, the innovativeness of its industry, and the degree to which buyers must make substantial pre-purchase investments are the main drivers of communication regarding changes to its new product introduction plans. As a set, these findings are particularly interesting as they indicate that the preannouncing firm’s desire to reduce uncertainty, often in its own favor, underlies its decision to issue NPCs

The Benefits of Using XML Technologies in Astronomical Data Retrieval and Interpretation

This paper describes a solution found during recent research that could provide improvements in the efficiency, reliability and cost of retrieving stored astronomical data. This solution uses XML Technologies in showing that when querying a variety of astronomical data sources a standardised data structure can be output into an XML query results Document. This paper shows the astronomical XMLSchema that has been partially developed in conjunction with simple custom supporting system software. It also discusses briefly possible future implications

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

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