2019
DOI: 10.1108/imds-09-2018-0403
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Dynamic property of consumer-based brand competitiveness (CBBC) in human interaction behavior

Abstract: Purpose The purpose of this paper is to identify potential competitive relationships among brands by analyzing the dynamic clicking behavior of consumers. Design/methodology/approach Consumer sequential online click data, collected from JD.com, is used to analyze the dynamic competitive relationship between brands. It is found that the competition intensity across categories of products can differ considerably. Consumers exhibit big differences in purchasing time of durable-like goods, that is, the purchasin… Show more

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Cited by 9 publications
(4 citation statements)
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References 42 publications
(48 reference statements)
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“…Furthermore, the study provides a new basis to encourage researchers like Zuo et al (2019) to penetrate deeper into the complex nature of the relationships conceptualised, thereby providing a salient avenue for further empirical research. This research has provided a framework to examine the role of two important variables -marketing orientation and strategic orientation of operations -in the context of business customers.…”
Section: Implications and Future Researchmentioning
confidence: 99%
“…Furthermore, the study provides a new basis to encourage researchers like Zuo et al (2019) to penetrate deeper into the complex nature of the relationships conceptualised, thereby providing a salient avenue for further empirical research. This research has provided a framework to examine the role of two important variables -marketing orientation and strategic orientation of operations -in the context of business customers.…”
Section: Implications and Future Researchmentioning
confidence: 99%
“…Visually drawn from Figure 6, the two areas shaped by the red scatters for segment 1 (consisting of 1,750 unique products) and those shaped by the green for segment 2 (264 correspondingly) are much larger than the blue area for segment 3 (only 145 products). Statistically, 6.7 percent of the products in segment 3 account for 78.68 percent of product sales in the whole market, while most products present very little competition, which is close to the 80/20 rule, verifying the known Pareto principle in e-commerce (Fujiwara et al, 2004;Zuo et al, 2019).…”
Section: Visualizing Competitive Product Market Structurementioning
confidence: 52%
“…According to Table 1, the average number of times consumers repurchase products in category 2 is twice that of category 1, while the number of browses for category 1 products is more than twice that of category 2. Different categories of products have different attribute factors and consumption frequencies, so there is a difference in the number of consumers' browses and repurchases (e.g., Zuo et al, 2019). Therefore, according to consumers' browsing and purchasing information, we can see these categories are different.…”
Section: Datamentioning
confidence: 99%