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Cross-country cross-survey design in international marketing research: the role of input data in multiple imputation

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journal contribution
posted on 2015-06-05, 08:50 authored by S. Sundqvist, S. Sintonen, O. Kuivalainen, A. Tarkiainen, Nick Lee, John Cadogan
Purpose – The present paper focuses on the case where – by design – one needs to impute cross-country cross-survey data (situation typical for example among multinational firms who are confronted with the need to carry out comparative marketing surveys with respondents located in several countries). Importantly, while some work demonstrates approaches for single-item direct measures, no prior research has examined the common situation in international marketing where the researcher needs to use multi-item scales of latent constructs. Our paper presents problem areas related to the choices international marketers have to make when doing cross-country / cross-survey research and provides guidance for future research. Design/methodology/approach – Multi-country sample of real data is used as an example of cross-sample imputation (292 New Zealand exporters and 302 Finnish ones) the international entrepreneurial orientation data. Three variations of the input data are tested: A) imputation based on all the data available for the measurement model, B) imputation based on the set of items based on the invariance structure of the joint items shared across the two groups, and C) imputation based both on examination of the invariance structures of the joint items and the performance of the measurement model in the group where the full data was originally available. Findings – Based on distribution comparisons imputation for New Zealand after completing the measurement model with Finnish data (Model C) gave the most promising results. Consequently, using knowledge on between country measurement qualities may improve the imputation results, but this benefit comes with a downside since it simultaneously reduces the amount of data used for imputation. None of the imputation models leads to the same statistical inferences about covariances between latent constructs than as the original full data, however. Research limitations / Implications - The present exploratory study suggests that there are several concerns and issues that should be taken into account when planning cross-country cross-surveys. These concerns arising from current study lead us to question the appropriateness of the cross-country cross-survey approach in general although in general advantages exist. Further research is needed to find the best methods. Originality / value – The combination of cross-country and cross-survey approaches is novel to international marketing, and it is not known how the different procedures utilized in imputation affect the results and their validity and reliability. We demonstrate the consequences of the various imputation strategy choices taken by using a real example of a two-country sample. Our exploration may have significant implications to international marketing researchers and the paper offers stimulus for further research in the area.

History

School

  • Business and Economics

Department

  • Business

Published in

International Marketing Review

Volume

33

Issue

3

Pages

454 - 482

Citation

SUNDQVIST, S. et al., 2016. Cross-country cross-survey design in international marketing research: the role of input data in multiple imputation. International Marketing Review, 33 (3), pp. 454-482.

Publisher

© Emerald Group Publishing Limited

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2016-05-09

Notes

This paper was published in the journal International Marketing Review and the definitive published version is available at http://dx.doi.org/10.1108/IMR-11-2014-0348.

ISSN

0265-1335

Language

  • en

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