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Factors Affecting Operating Performance of Global Third-Party Payment Companies
|關鍵字:||第三方支付;全球科技指數;企業績效;Panel Data分析;Panel Logit模型;Third-Party Payment;Global Technology Index;Firm Performance;Panel Data Analysis;Panel Logit Model||Project:||應用經濟論叢, Issue 104, Page(s) 31-92||摘要:||
晚近第三方支付業務正於全球風起雲湧，而台灣終於在2015年通過了眾所期盼的第三方支付專法「電子支付機構管理條例」，許多業者更早已摩拳擦掌積極搶進第三方支付業務；然企業要如何成功經營第三方支付業務實值得深究。爰此，本研究旨在利用全球科技指數變數與總體經濟變數，並結合企業特性變數探討影響第三方支付企業成功經營之因素。本文使用8個國家篩選之33家第三方支付樣本企業，以Panel Data與Panel Logit模型進行實證分析。由Panel Data的實證結果可知全球科技指數中之固定寬頻網路用戶或國際互聯網用戶越多，生物辨識技術越提升，ICT綜合價格越下降，固定寬頻網路月租費越下降，則第三方支付企業績效顯著越高，而總體經濟變數中之實質GDP與S&P全球股票指數越高，則第三方支付企業績效顯著越高。最後，Panel Logit模型的實證結果則發現固定寬頻網路用戶、生物辨識技術與企業規模則對第三方支付企業虧損機率具顯著負向影響，而實質GDP與公司成立年數對第三方支付企業虧損機率具顯著正向影響。
In recent years, enterprises from all parts of the world actively engage in third-party payment business. Meanwhile, Taiwan has eventually passed the highly anticipated law that concerns third-party payment, the Payment Processing Institutions Act, in 2015. Now many of them are actively providing platforms of third-party payment for customers, but how these enterprises could make it as successful as PayPal and Alipay is still the question. This study aimed at finding out 33 sample firms in 8 countries for the impacts of global technology index and macroeconomics variables, combining with firm characteristics, on the operation of the global third-party payment providers by using Panel Data Model and Panel Logit Model. And as for the global technology index in Panel Data results, the increase of fixed broadband user population and internet user population, the improvement of biometrics technology, or the decrease of ICT price basket and monthly fee of fixed broadband significantly contribute to the higher performance of the third-party payment companies. For the macroeconomics variables in Panel Data results, we found that both real GDP and S&P global stock index have significantly positive impacts on business performance of the third-party payment companies. For Panel Logit results, fixed broadband user population, biometrics technology, and firm size have significantly negative impacts on the loss probability of the third-party payment companies, but both real GDP and companies' founded years have significantly positive impacts on the loss probability of the third-party payment companies.
|Appears in Collections:||應用經濟論叢 第104期|
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