The Problem with Standardizing International Market Research: A Case Study from B2B Services
Bibliographic record
Abstract
One of the key issues for multinational corporations (MNCs) is whether to standardize their marketing approach across all countries or adapt their practices to fit each country. In order to make this decision, MNCs must determine if their marketing approach is cross-culturally appropriate and equivalent from country to country. Unfortunately, recent research indicates that the vast majority of academic studies do not adequately address the cross-cultural equivalence issue. The primary purpose of this article is to illustrate the problem of using a standardized, global, B2B research approach. The second goal is to show how cross-cultural equivalence can be identified and managed. The firm in this study is a Fortune 100 MNC that provides facilities management services in over 100 countries. This article compares the cross-cultural equivalence of customer satisfaction survey data from the US and from Japan. The results show that about half of the items typically used to measure dimensions of product and service quality as drivers of customer satisfaction lack cross-cultural equivalence. The implication is that the use of a fully standardized approach to global research must be questioned.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".