A1 Journal article (refereed), original research

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

Publication Details
Authors: Sintonen Sanna, Tarkiainen Anssi, Cadogan John W., Kuivalainen Olli, Lee Nick, Sundqvist Sanna
Publisher: Emerald: 24 month embargo
Publication year: 2016
Language: English
Related Journal or Series Information: International Marketing Review
Volume number: 33
Issue number: 3
Start page: 454
End page: 482
Number of pages: 29
ISSN: 0265-1335
eISSN: 1758-6763
JUFO-Level of this publication: 1
Open Access: Not an Open Access publication


Purpose– The purpose of this paper is to focus on the case where – by design – one needs to impute cross-country cross-survey (CCCS) 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. The 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 (IEO) data. Three variations of the input data are tested: first, imputation based on all the data available for the measurement model; second, imputation based on the set of items based on the invariance structure of the joint items shared across the two groups; and third, 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– Considering multiple imputation, the present exploratory study suggests that there are several concerns and issues that should be taken into account when planning CCCSs (or split questionnaire or sub-sampling designs). Even if there are several advantages available for well-implemented CCCS designs such as shorter questionnaires and improved response rates, these concerns lead us to question the appropriateness of the CCCS approach in general, due to the need to impute across the samples.
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. The authors demonstrate the consequences of the various imputation strategy choices taken by using a real example of a two-country sample. The exploration may have significant implications to international marketing researchers and the paper offers stimulus for further research in the area.

Last updated on 2018-19-10 at 08:49