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The official journal of the International Society for Business and Industrial Statistics, Applied Stochastic Models in Business and Industry (ASMBI), is inviting contributions for a special issue devoted to fusion inference for problems in business and industry. Fusion inference, sometimes called fusion learning, is the use of statistical methods for combining results from different studies. Meta-analysis is a well-known example of fusion inference. Combining reliability data across different test environments is another example. Fusion inference is of vital importance in light of the increasing trend to collect data from heterogeneous sources. Papers should present either innovative methodologies fusion inference, or forceful applications of existing methods. All submissions will go through the standard, selective review process of ASMBI. Submissions are possible until July 31, 2016 through the website http://mc.manuscriptcentral.com/asmb Please follow the ASMBI author submission guidelines given on the ASMBI website and click on the box about submissions for special issues, mentioning "Data Fusion" when requested. The Guest Editors of the special issue are Daniel R. Jeske ([log in to unmask]) and Min-ge Xie ([log in to unmask]). For any information about the ASMBI journal, please contact the Editor-in-Chief: Fabrizio Ruggeri ([log in to unmask]). -- Fabrizio Ruggeri fabrizio AT mi.imati.cnr.it CNR IMATI tel +39 0223699532 Via Bassini 15 fax +39 0223699538 I-20133 Milano (Italy) web.mi.imati.cnr.it/fabrizio You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.