| Literature DB >> 35600559 |
Abstract
Co-location has been a relevant topic in the international business literature, yet the extant literature focuses on the co-location of research and development (R&D) and production activities and overlooks marketing value activities. Marketing innovation is an agile and effective way to respond to crises such as the COVID-19 pandemic, and many manufacturers in global value chains aim to upgrade functionally following the trajectory of the OEM-ODM-OBM. Thus, this study proposes the co-location of marketing activities as a flexible and organizational learning strategy for manufacturing upgrades, and explores the antecedents of marketing co-location in foreign direct investment (FDI) decisions. The proposed research framework was examined using survey data from 343 Taiwanese manufacturing firms in China, which were drawn from a database compiled by Taiwan's Ministry of Economic Affairs in 2020. The results show that the breadth of international experience, linkage to R&D, marketing as a primary knowledge source in the host country, upgrading for local demands, and new product development for global supply are all positively associated with the co-location of marketing and production functions. Additionally, it was found that there was a negative association between FDIs that had been impacted by COVID-19 and marketing co-location. The findings provide valuable theoretical, practical, and strategic insights into how firms should manage their global value chains with respect to marketing co-location in case of another crisis.Entities:
Keywords: COVID-19 crisis; Co-location; Local linkages for knowledge; Marketing innovation; Resilience
Year: 2022 PMID: 35600559 PMCID: PMC9107328 DOI: 10.1016/j.jbusres.2022.04.060
Source DB: PubMed Journal: J Bus Res ISSN: 0148-2963
Fig. 1The conceptual framework.
Descriptive Statistics and Correlation Matrix.
| Variable | Mean | S.D. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Co-location decision | 0.504 | 0.501 | 1.000 | ||||||||||
| 2 | Breadth of internationalization | 2.035 | 1.277 | 0.082 | 1.000 | |||||||||
| 3 | Depth of internationalization | 6.362 | 12.112 | 0.022 | 0.389** | 1.000 | ||||||||
| 4 | R&D linkage | 0.566 | 0.496 | 0.084 | −0.018 | 0.033 | 1.000 | |||||||
| 5 | Marketing linkage | 0.810 | 0.392 | 0.428** | −0.051 | 0.047 | −0.064 | 1.000 | ||||||
| 6 | Upgrading for local demands | 0.583 | 0.494 | 0.262** | 0.056 | 0.024 | −0.025 | 0.330** | 1.000 | |||||
| 7 | Upgrading for NPD for global supply | 0.324 | 0.469 | 0.112* | −0.068 | −0.062 | 0.003 | 0.017 | 0.016 | 1.000 | ||||
| 8 | Firm size | 0.729 | 0.445 | 0.130* | 0.320** | 0.202** | 0.034 | −0.061 | 0.003 | −0.055 | 1.000 | |||
| 9 | R&D intensity | 0.134 | 0.224 | 0.207** | −0.003 | −0.031 | 0.081 | 0.106* | 0.013 | 0.057 | 0.119* | 1.000 | ||
| 10 | Intra-industry FDI | 0.974 | 0.160 | −0.090 | 0.047 | −0.060 | 0.077 | −0.033 | −0.028 | 0.036 | −0.018 | 0.015 | 1.000 | |
| 11 | COVID-19 pandemic | 0.184 | 0.388 | −0.117* | −0.007 | 0.021 | 0.051 | −0.020 | −0.072 | −0.022 | 0.018 | 0.029 | −0.016 | 1.00 |
Note: SD stands for standard deviation. Sample size: 343; Co-location cases: 173; Non-colocation cases: 170. ∗Significant at the 0.05 level; ∗∗significant at the 0.01 evel.
Logistic Results for the Marketing and Production Co-location Decision.
| Independent variable | Model 1 | Model 2 | Model 3 | Model 4 | ||||
|---|---|---|---|---|---|---|---|---|
| Coefficients | P-value | Coefficients | P-value | Coefficients | P-value | Coefficients | P-value | |
| Intercept | 0.850 | 0.315 | 0.767 | 0.367 | −2.386** | 0.033 | −2.689** | 0.014 |
| Breadth of internationalization | – | – | 0.109* | 0.078 | 0.212* | 0.067 | 0.203* | 0.084 |
| Depth of internationalization | – | – | −0.003 | 0.758 | −0.013 | 0.235 | −0.012 | 0.284 |
| R&D linkage | – | – | – | – | 0.627** | 0.016 | 0.634** | 0.016 |
| Marketing linkage | – | – | – | – | 3.397*** | 0.000 | 3.155*** | 0.000 |
| Upgrading for local demands | – | – | – | – | – | – | 0.599** | 0.027 |
| Upgrading for NPD for global supply | – | – | – | – | – | – | 0.580** | 0.039 |
| COVID-19 pandemic | −0.701** | 0.018 | −0.701** | 0.019 | −0.799** | 0.016 | −0.772** | 0.021 |
| Firm size | 0.513** | 0.043 | 0.430 | 0.110 | 0.632** | 0.032 | 0.638** | 0.034 |
| R&D intensity | 2.036*** | 0.000 | 2.057*** | 0.000 | 1.648** | 0.010 | 1.656** | 0.011 |
| Intra-industry FDI | −1.370* | 0.100 | −1.433* | 0.087 | −1.791* | 0.072 | −1.819* | 0.061 |
| Log-likelihood | –223.571 | –222.974 | −183.516 | −178.754 | ||||
| Restricted Log-likelihood | −237.736 | −237.736 | −237.736 | −237.736 | ||||
| Chi Square | 28.331 | 29.525 | 108.441 | 117.965 | ||||
| Significance level | 0.0000*** | 0.0000*** | 0.0000*** | 0.0000*** | ||||
| Cox & Snell R2 | 0.079 | 0.082 | 0.271 | 0.291 | ||||
| Correct classification rate (%) | 61.20 | 61.80 | 71.10 | 73.50 | ||||
Note: Dependent variables: Co-location = 1; Non-colocation = 0.
*Significant at the 0.10 level; ∗∗significant at the 0.05 level; ∗∗∗significant at the 0.01 level.