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Data quality and information loss in standardised interpolated path analysis: Quality measures and guidelines

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  • Lenz, Annika
  • Kaya, Muhammed
  • Melzer, Philipp
  • Schmid, Andreas
  • Witt, Josepha
  • Schoop, Mareike

Abstract

Standardised interpolated path analysis (SIPA) is a method to investigate negotiation processes making different negotiation histories comparable. Due to its interpolation approach, researchers employing SIPA must take data quality and potential information loss into account to maximise the method's explanatory power. This paper presents quality measures and applies them to two negotiation datasets for deriving meaningful boundaries. Using these quality measures enables researchers to compare SIPA across segmentations, variables, and datasets also providing outlier analysis.

Suggested Citation

  • Lenz, Annika & Kaya, Muhammed & Melzer, Philipp & Schmid, Andreas & Witt, Josepha & Schoop, Mareike, 2019. "Data quality and information loss in standardised interpolated path analysis: Quality measures and guidelines," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2019, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    • Handle: RePEc:zbw:hohdps:082019
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    References listed on IDEAS

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    1. P. V. (Sundar) Balakrishnan & Jehoshua Eliashberg, 1995. "An Analytical Process Model of Two-Party Negotiations," Management Science, INFORMS, vol. 41(2), pages 226-243, February.
    2. Michael Filzmoser & Patrick Hippmann & Rudolf Vetschera, 2016. "Analyzing the Multiple Dimensions of Negotiation Processes," Group Decision and Negotiation, Springer, vol. 25(6), pages 1169-1188, November.
    3. Eva-Maria Pesendorfer & Sabine T. Koeszegi, 2006. "Hot Versus Cool Behavioural Styles in Electronic Negotiations: The Impact of Communication Mode," Group Decision and Negotiation, Springer, vol. 15(2), pages 141-155, March.
    4. Katharina J. Srnka & Sabine t. Koeszegi, 2007. "From Words to Numbers: How to Transform Qualitative Data into Meaningful Quantitative Results," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 59(1), pages 29-57, January.
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