Cross-functional multiple informant empirical research: Minimizing problems in data analysis

Research output: Contribution to conferencePaper

Abstract

Inter-functional research carries unique problems and challenges which include data collection, management, and analysis. This paper discusses these issues in the context of a cross-functional empirical study using a multiple-informant design. A process is presented to manage the data at the input, processing, and output phases of a research project. Although the process was developed for investigation into the manufacturing - marketing interface, it may be generalized to ease the analytical problems and therefore expand the frontiers of cross-functional research.

Original languageEnglish (US)
Pages1003-1005
Number of pages3
Publication statusPublished - Dec 1 1997
EventProceedings of the 1997 Annual Meeting of the Decision Sciences Institute. Part 1 (of 3) - San Diego, CA, USA
Duration: Nov 22 1997Nov 25 1997

Other

OtherProceedings of the 1997 Annual Meeting of the Decision Sciences Institute. Part 1 (of 3)
CitySan Diego, CA, USA
Period11/22/9711/25/97

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All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Hardware and Architecture

Cite this

Parente, D. (1997). Cross-functional multiple informant empirical research: Minimizing problems in data analysis. 1003-1005. Paper presented at Proceedings of the 1997 Annual Meeting of the Decision Sciences Institute. Part 1 (of 3), San Diego, CA, USA, .