109年科技管理學刊第25卷學刊第二期 民國一○九年三月
Volume 25, Number 1 March 2020(若需下載全完請登入會員)
標題Article：群眾募資平台動態預測之研究:以Kickstarter 平台為例
Research on Dynamic Prediction of Crowdfunding Platform:An Empirical Study of Kickstarter platform
作者Aurthor：歐宗殷、傅新彬、蘇勁達、林冠宇 Tsung-Yin Ou,Hsin-Pin Fu,Jin-Da Su,Guan-Yu Lin
中文摘要Chinese Abstract：
群眾募資是指一個創新的項目透過網路吸引大眾共同參與投資的過程,根據統計資料顯示,群眾募資僅 81%可以達到資金目標的 20%,其餘 19%連目標的 20%都達不到。本研究使用 C#和Python 程式撰寫爬蟲程式,蒐集國際知名 Kickstarter 群眾募資平台上科技類提案的動態數據,六個月(2019/2/1~2019/7/1)期間,每四個小時蒐集一次資料,然後使用 ARIMA、類神經網路、決策樹、支持向量機以及隨機森林建立群眾募資金額動態預測模型,以平均絕對百分比誤差(MAPE)作為預測模型的比較,可提前掌握那些專案較容易達成募資目標。各預測模型結果顯示,使用 ARIMA 在中高價提案有不錯的準確度,隨機森林在低價提案、中高價提案以及高價提案的表現最佳,而類神經網路則是在中低價提案的預測表現較佳,整體綜合評估仍是以隨機森林的預測表現最好。此一研究成果可以讓群眾募資的投資者對於募資專案的掌握度和可預期程度有所提升,而募資者除了專注於技術開發以及創意發想之外,更應該關注募資專案在平台上的回應以及經營,對於專案的募資成功率將有所提升,而平台經營者可以在網站的功能和服務上進行加值,提供更即時且更精準地提供專案分析和動態訊息服務給投資者和募資者。
關鍵字:群眾募資、動態預測、Kickstarter、決策樹、支持向量機、隨機森林
English Abstract：
Crowdfunding is defined as a project or business process requires investment, and
requires a large group of people to provide this investment. In the past few years, this
phenomenon has grown exponentially in the index, is seeking ways and means of
funding for entrepreneurs and designers. Statistics show that the vast majority of the
people have not been successful fund-raising activities, which is only 81% to 20%
funding target. Crowdfunding proposal of sorts, in addition to the commodity, content
creators, covered the public issues, campaigning, art, invention, design, and scientific
research, public disaster reconstruction can initiate fund-raising in fund-raising
platform.
This study uses C# and Python programs to write web crawlers and collects dynamic
data on technology proposals from the world's best-known Kickstarter crowdfunding
platform. The data collection period is six months (2019/2/1~2019/7/1). Dynamic data
is collected every four hours. After data consolidation and collation, ARIMA, neural
network, decision tree, vector support machine, and random forest are used to establish
a dynamic prediction model for the amount of funds raised. And the mean absolute
percent error (MAPE)of the predicted results is compared as a different prediction
model. According to the research results, it can be known in advance that those projects
are easier to achieve the goal of fundraising, and the follow-up proposers can put the
factors of past fundraising success into their own proposals to improve the success rate
of fundraising, and the sponsors can also use This research explores potential
innovative commodities and projects, and then invests in the commodity early to
develop cooperation and develop markets. Results show that ARIMA model has low
prediction error in mid-high price proposal; random forest prediction model has low
error in low price proposal, mid-high price proposal and high price proposal; neural
network is in the forecast mid-low price proposal. The overall is still the best prediction
error random forests than now.
The research results can help the investors who raise funds for the masses to improve
the mastery and predictability of fundraising projects. In addition to focusing on
technology development and creative ideas, fundraisers should pay attention to the
response and operation of the fundraising project on the platform, which will improve
the project's fundraising success rate. Platform operators can add value to the functions
and services of the website, providing project analysis and dynamic information
services to investors and fundraisers in a more timely and accurate manner.
Keywords: Crowdfunding, Dynamic prediction, Kickstarter, Decision Tree, Support Vector Machine, Random Forest
標題Article：再探大學研發技轉中心的代理人角色
Revisiting the Agent Roles of the Technology Transfer Office in University Commercialization
作者Aurthor：黃心怡、陳詩欣 Hsini Huang,Shih-Hsin Chen
中文摘要Chinese Abstract：
在美國杜拜法案的影響下,全球高等教育機構紛紛起而效尤,包括台灣也在 1999 年通過之科技基本法與數次後續的修法中,允許大學校院與大學教授可不受國有財產法之限制,就其政府補助之科研成果,申請專利並授權使用。然而,在大學商業化的過程中,學校結構內相關利害關係人的相互影響,仍是國內文獻甚少討論的議題。透過質性的研究方法,本研究旨在理解大學商業化過程中三個主要參與者:大學行政中心(校方)、技轉中心、科研發明者(大學教授)的不同角色,以及技轉中心作為一個雙重代理人所面對的不同期待、挑戰以及可能導致的負面行為。本研究有助於政策制定者了解大學商業化中不一致的組織目標可能帶來的負面影響。
關鍵字:大學商業化、雙重代理、技術移轉中心、制度邏輯不一致
English Abstract：
Under the influence of the U.S. Bayh-Dole Act, Taiwan followed the global
trend and legislated the “Fundamental Science and Technology Act” in 1999.
Over the period between 1999 and 2010, a series of laws was enacted to allow
university and academic scientists to privatize the outcomes of
government-funded research. However, there is little previous work on the
interrelationships among the three major players in university
commercialization activities: the university administration, the faculty, and the
Technology Transfer Office (TTO). Agency theory is considered as a useful
organizational theory to predict agent behavior in the Principal−Agent (P−A)
relations in the process of university commercialization. Drawing upon agency
theory, the dilemma and pitfalls of TTO as a dual agent are examined in this
qualitative study with 30 interviewees from 10 universities in Taiwan. The
results of this research have practical and theoretical implications for university
technology transfer policy and the limitation of the incentive system for TTOs
built within the universities.
Keywords: university entrepreneurship, principal−agent problems, technology transfer office, inconsistent institutional logics
標題Article：紡織雲服務系統使用及其對綠色供應績效之影響
The Usage of Textile Cloud Services System and its Impact on Green Supply Performance
作者Aurthor：楊學隆、楊亨利 Shiue-Lung Yang,Heng-Li Yang
中文摘要Chinese Abstract：
這項研究的目的是調查「綠色紡織雲服務系統」(GTCS)在台灣紡織行業中的使用和影響。這項研究以問卷調查法、PLS 統計分析分兩個階段進行:第一階段的樣本使用 GTCS 至少半年,第二階段的樣本使用 GTCS至少兩年。在第一階段,我們發現較高的知覺服務品質有助於使用者知覺有用、滿意度,進而對系統的持續使用。此外,知覺的環境法規壓力也對GTCS 的知覺有用有正向影響;不過信任是對系統的持續使用最重要的因素。在第二階段,我們發現原物料供應商對中央製造商的依賴和信任將增強共享資訊的意願。而若資訊共享程度高且資訊成熟度高,供應商將提高與 GCTS 的電子綠色控制的橋接程度,而進一步提高綠色供應績效。
關鍵字:雲端服務系統、綠色供應鏈、持續使用、紡織工業
English Abstract：
The purpose of this study is to investigate the usage and impacts of a Green
Textile Cloud Services System (GTCS) in Taiwan’s textile industry. Adopting
sample survey and PLS analysis, this study was conducted in two stages:
samples in the first stage have used GTCS at least half a year; samples in the
second stages had used GTCS at least two years. In the first stage, we found
that higher perceived service quality has a positive impact on perceived
usefulness, user satisfaction, and further increase continuance intention of the
system. Besides, perceived pressure of environmental regulations has a positive
effect on perceived usefulness of GTCS, and trust is the most important factor
for usage continuance. In the second stage, we found that dependence and trust
on central firm would enhance the willing to share information. With high
information sharing and suitable information maturity, suppliers would increase
the level of electronic green control bridging with GCTS, which would further
enhance green supply performance.
Keywords: Cloud services system; Green supply chain; Usage continuance;Textile industry