The paper investigates the innovation ecosystem alignment of ASEAN countries, based on the Global Competitiveness Report 2019 and Global Innovation Report 2019. Of interest are issues on institutions, human capital and research, infrastructure, market sophistication, and business sophistication. The results show the comparative strengths and weaknesses of each ASEAN economy. The information is suggestive to policymaker and private sectors if any measurement is required to close these gaps or to leverage their innovation ecosystem.
E-commerce growth enforces the courier business to focus on developing a new business model decision. This paper aims to explore a suitable new business idea for courier business if the Data Analytics (DA) can be advantageous, using small courier company as a case study. The study investigates Logistics Service Provider (LSP) activities and the Gap Analysis and SWOT analysis were conducted to explore Data Analytics (DA) opportunity. Then, the alternative business models were pre-screened by the requirements of company, i.e. reasonable investment cost and the opportunity in using Data Analytics (DA). Ansoff Matrix is used to classify the alternative of new service idea into two segments; 1) offer development, i.e. Market development, and 2) New business development, i.e. Service development and Diversification. Fuzzy Analytic Hierarchy Process (FAHP) is used to select suitable business idea by weighted summation on five of Data Analytics (DA) accommodation criteria, i.e. company capability; the ability performs of demand; vision, strategy, and desire of executive, investment strategy and customer data opportunity. The business models that are mostly desirable are 1) Suppliers-Consignees recommendation, 2) Fulfillment service model and 3) Sourcing model. These three models were elaborated and discussed in the perspectives of company and customer. Additionally, this research proposes several challenges in Data Analytics (DA) related in logistics activity, key decision criteria and methods of idea selection implemented guidelines for logistics business practice.
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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