Qualitative analysis of big data in the service sectors

Huang, Chun‐Che; Liang, Wen‐Yau; Wen, Dan-Wei; Ting, Ping-Ho; Shen, Meng-Ying

doi:10.1080/02642069.2018.1509957

Cited by 3 publications

(1 citation statement)

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“…The Business Model Canvas developed by Osterwalder and Pigneur [19] defines how companies generate revenue and make a profit through the overall structures of process, customers, suppliers, channels, resources, and capabilities. The critical goal of service businesses is to understand customers and their behavior, necessitating identification of key consumer groups [20], while prioritizing the customer to allocate attention and resources to designated customer groups [13].…”

Section: Literature Reviewmentioning

confidence: 99%

Matching Consignees/Shippers Recommendation System in Courier Service Using Data Analytics

2020

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The purpose of this research was to create a Matching Consignees/Shippers Recommendation System (MCSRS). We used the association rule to identify product associations, the clustering technique to group shippers and consignees according to behaviors when receiving goods from similar shipper groups, and the decision tree to identify possible matches between shippers and consignees. Finally, Monte Carlo simulation was used to estimate potential revenue. The case study is a courier company in Thailand. The results showed that garment products and clothes were the products with the highest association. Shippers and consignees of these products were segmented according to recency, frequency, monetary factors, number of customers, number of product items, weight, and day. Three rules are proposed that enabled the assignment of 8 consignees to 56 shippers with an estimated increase in revenue by 36%. This approach helps decision-makers to develop an effective cost-saving new marketing, inclusive strategy quickly.

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Section: Literature Reviewmentioning

confidence: 99%