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Journal of the Academy of Marketing Science
Erschienen in: Journal of the Academy of Marketing Science 5/2021

16.01.2021 | Original Empirical Research

Knowledge structure in product- and brand origin–related research

verfasst von: Saeed Samiee, Brian R. Chabowski

Erschienen in: Journal of the Academy of Marketing Science | Ausgabe 5/2021

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Abstract

Scholarly research regarding origins of products and brands is deep-rooted within international marketing, with an extraordinary following as evidenced by the large body of literature that is continuing to evolve. Our goal in this research is to examine this domain, generically referred to as the country-of-origin (CO) literature, and identify the most influential contributions and their corresponding topics that form the intellectual foundations of this knowledge domain. Using citation and co-citation analyses, we develop a spatial representation of the CO literature via multidimensional scaling with two concurrent goals of unfolding the literature’s knowledge structure as the basis for proposing a conceptual framework and identifying new research directions in the field. Our database consists of 482 articles, extracted from the Web of Science, that contain 33,194 citations through 2019. We develop a managerially relevant conceptual approach based on the results of our co-citations–based CO knowledge structure to unfold new research directions and expand the boundaries of the CO literature in fruitful directions.
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Fußnoten
1
We define origin-related scholarly research as projects in which location plays a central role. Country of origin is the common term associated with this stream of research. The term was originally associated with country of manufacture (i.e., source country), however, as the literature matured, numerous derivative aspects of location such as country of assembly, country of design, country of brand (i.e., brand origin), and country image were also investigated. In all cases, CO is the common identifier (keyword) used in published works.
 
2
Common definitions associated with this literature include: CO (the source country for a product), country of manufacture (where a product is substantially manufactured), country of assembly (country in which components are assembled into a final product), country of design (nation in which a product is designed), BO (location of the headquarters of the firm owning a brand), CI and its variations including destination and place image (perceptions and beliefs held by customers regarding a nation or location). As would be expected in a large body of knowledge, there are minor variations in definitions across publications. For example, Lu et al. (2016) define CI as an alternative to CO encompassing general CI and CO of a product, as well as place and destination image. In contrast, Han (1989) and Bilkey and Nes (1982) define CI as “consumers’ general perceptions of quality for products made in a given country,” that is, CO.
 
3
Two domain-related patterns of CO studies are worth noting as they have a potential impact in the development of the field and the corresponding knowledge areas that have influenced projects. First, the vast majority of CO studies (about 80% of those appearing in leading journals) consist of single-country samples of informants, with the remainder focused on comparative and cross-cultural investigations (Samiee and Leonidou 2013). Second, in terms of regions referenced in these investigations, initially attention was largely turned to countries situated in North America and Europe (24% and 28%, respectively). However, Asian countries have been more frequently used during the 1990s and since 2000 (32%), which collectively makes Asia the most-studied region.
 
4
Though other approaches besides co-citation analysis have been proposed and deemed relevant in portraying knowledge structure (cf. citation proximity analysis), access to available data of sufficient scale to implement such methods in the IM literature makes the task impractical to accomplish (Gipp and Beel 2009; Liu and Chen 2011). Rather, this study, by maintaining its focus on the article as the level of investigation, uses established bibliometric principles to analyze the knowledge structure and retain the data most closely to traditional co-citation networks.
 
5
WOS is a comprehensive source with wide coverage and inclusiveness of the vast proportion of electronically available published works (over 26,352 journals) which enables researchers to access large amounts of data (Clarivate Analytics 2020). The WOS database is commonly used in a range of bibliometric studies in business (e.g., Cornelius et al. 2006; Ramos-Rodríguez and Ruíz-Navarro 2004; Schildt et al. 2006).
 
6
Exact syntax is available from the authors upon request.
 
7
The marketing and IB journals with bibliometric data for this study were: Advances in Consumer Research, Asia Pacific Journal of Management, (Columbia) Journal of World Business, European Journal of Marketing, Industrial Marketing Management, International Business Review, International Journal of Advertising, International Journal of Research in Marketing, International Marketing Review, Journal of Advertising, Journal of Advertising Research, Journal of Business & Industrial Marketing, Journal of Business Research, Journal of Consumer Psychology, Journal of Consumer Research, Journal of International Business Studies, Journal of International Management, Journal of International Marketing, Journal of Macromarketing, Journal of Marketing, Journal of Marketing Research, Journal of Public Policy & Marketing, Journal of Retailing, Journal of Services Marketing, Journal of the Academy of Marketing Science, Management International Review, Marketing Letters, Marketing Science, and Psychology & Marketing.
 
8
It should be noted that many other network-related approaches to examining knowledge structure provide an overwhelming level of data without sufficient analysis and relation to established theoretical bases. In fact, there are some bibliometrics researchers who claim a network analysis tool such as VOS is superior to MDS with very large datasets (van Eck et al. 2010). However, as MDS is acknowledged as better for smaller datasets such as the one for the present study (Zupic and Čater 2015), others are more pragmatic and state that different approaches are appropriate for specific circumstances (Hook 2017). In the end, the main driver of using MDS as employed in this study is that it provides a balance between data analysis and linkages to established research concepts. And, as one of the main purposes of this study is to conduct a detailed research-focused study, MDS was chosen as the most apt to complete the task.
 
9
Several other proximity metrics might be applied in this line of inquiry. However, these approaches are independent of our MDS results and their use would result in considerably different and unrelated conclusions. As a result, the standardized Euclidean distance measures are directly related to the co-citation data analyzed as pivotal to this study. Thus, we selected standardized Euclidean distances for grouping specific publications.
 
10
Other network analysis–based approaches have been used in the literature to accomplish similar tasks. However, such tools do not provide for the exclusion of data deemed unnecessary to the study. As such, since our analysis does not include book reviews, editorial content, method-related articles, as well as other content not specific to the knowledge structure of the CO literature, these applications were deemed inappropriate.
 
11
Web Appendix 1a, which runs through 2018, was the original basis for analysis in this study. However, as a result of the review process, data through 2019, appearing in Web Appendix 1b, for this part of the study was requested for comparison.
 
12
It is worth noting that our proposed integrative framework incorporated recent concepts from the knowledge structure as mentioned in the Results section, regardless of whether they were a part of a research group or a research clique. Nevertheless, membership in groups and cliques demonstrate closer proximity of topics by virtue of researchers’ joint reliance on these works as influential knowledge nodes.
 
13
Burrell (2002, 2003) demonstrates that works cited early after their publication will continue to be referenced (i.e., “success-breeds-success”) and infrequently cited articles are unlikely to be among the discipline’s thought leaders. Keeping with precedence, we thus examined citation frequencies and the distribution of CO publication during the past decade. Leveraging Chabowski et al. (2013), we determined a minimum average citation cut-off point of 1.75 per year for inclusion of influential recent CO works.
 
14
A possible starting point for resolving tensions in the CO literature is to conduct a comprehensive review study of CO-related hypotheses examined, including links between studies’ variables used. We acknowledge the recommendation of the associate editor and the contribution of an anonymous reviewer aimed at addressing this issue.
 
15
For example, some CO studies have proposed that firms manage or even change country perceptions by reinforcing positive CO stereotypes or, in general, improve negative ones (e.g., Micevski et al. 2020; Knight and Calantone 2000). Analogous to product repositioning, changing an image or CO stereotype requires reinforcement over long periods, which is not a luxury most managers can afford, in addition to requiring a substantial communications budget. Other research recognizes that, on the one hand, bias is likely to vary from region to region while, on the other hand, proposing firms to take into account negative bias/animosity in selecting overseas suppliers, potentially leading to a chaotic supplier selection for firms operating in dozens of nations with varying CO biases (e.g., Klein et al. 1998).
 
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Metadaten
Titel
Knowledge structure in product- and brand origin–related research
verfasst von
Saeed Samiee
Brian R. Chabowski
Publikationsdatum
16.01.2021
Verlag
Springer US
Erschienen in
Journal of the Academy of Marketing Science / Ausgabe 5/2021
Print ISSN: 0092-0703
Elektronische ISSN: 1552-7824
DOI
https://doi.org/10.1007/s11747-020-00767-7

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