数据质量有助于克服企鹅效应？以项目主数据池的案例.pdf

CAN DATA QUALITY HELP OVERCOME THE PENGUIN EFFECT? THE CASE OF ITEM MASTER DATA POOLS Madlberger, Maria, Webster University Vienna, Berchtoldgasse 1, A-1220 Vienna, Austria, madlberger@webster.ac.at. Abstract The diffusion of standards is characterized by network effects, path dependency, and the penguin effect. Particularly the latter, also referred to as excess inertia, is a frequent inhibitor of the adoption of standards, even if they could provide benefits. This is particularly true for item master data pools that suffer from little adoption in many industries as benefits can only accrue if many firms use them. At the same time, data pools show the potential to improve the quality of item master data by pooling the efforts on data quality assurance. This paper addresses the question whether an improvement of item master data quality can contribute to overcoming the penguin effect by data pools. The theoretical considerations are supplemented by an exploratory qualitative research among the leading retailers in the Austrianfood and drug sector. The findings suggest that data quality improvement can be one way to encourage the use of data pools and thus overcome the penguin effect in adoption. Keywords: Item Master Data, Data Quality, Data Pools, Global Data Synchronization Network, Penguin Effect, Excess Inertia, Standardization 1 Introduction The effectiveness of interorganizational information sharing strongly depends on the quality of the shared data (Hartono et al., 2010). This is particularly true for sharing of item master data, i.e., data on product attributes, such as identification data, size, weight, and price. Item master data is necessary for logistics processes in supply chains as they control the physical flow of goods, inventory management, transportation, and the space management in the retail outlets. It is al