Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/139989
|
| Title: | 產業演化與生態系策略研究 - 以無人駕駛車產業之演化及智慧相機之生態系策略為例
Industrial evolution and its ecosystem strategy - Case study of smart camera’s ecosystem strategy along the self-driving car’s industry evolution |
| Authors: | 梁志宏
Liang, Chih-Hung |
| Contributors: | 尚孝純
Shang, Shari S.C.
梁志宏
Liang, Chih-Hung |
| Keywords: | 產業演化
生態系策略
自動駕駛
無人駕駛車
智慧相機
Industrial evolution
Ecosystem strategy
Autonomous driving
Self-driving vehicle
Smart camera |
| Date: | 2022 |
| Issue Date: | 2022-05-02 15:01:59 (UTC+8) |
| Abstract: | 新興產業的演化同時也帶動產業之生態系的進化，生態系內的個別參與者如何辨識產業演化模式並採取適當策略，使自身順應產業演化得以生存，並進而成為俱相對優勢的參予者，為本研究想探索的核心議題。本研究以無人駕駛車產業的演化及其生態系內的智慧相機為例，透過產業的實際演化過程分析生態系參予者應採取之演化策略。
本研究透過釐清產業生態系內個別關鍵參予者所提供的價值，解析生態系內各關鍵角色及其所屬之分工位置。同時，定位智慧相機與其他參與者的相互關係，理解生態系內參予者間之行為邏輯及互動誘因。以此為基礎，透過賽局模型分析產業演化過程中之因果關係，從中萃取出其演化模式，並據此建構出智慧相機於演化過程中應採取之生態系策略。
生態系的「共生關係」及賽局理論的「價值網關係」為本研究據以解析生態系參予者間之行為邏輯及互動誘因的主要工具。共生關係協助生態系參予者借用環境資源達成生存目的，而價值網關係促使參予者採取適當策略創造生存優勢。
賽局分析部分，本研究採用競合策略所用之賽局模型，分析無人駕駛車產業演化過程中改變產業進程的八個關鍵事件，透過該模型，演繹關鍵事件對後續產業演化所產生之影響，並從中萃取出演化過程之因果關係及演化模式。
本研究發現產業之演化如同生物之進化，即是不斷地尋找生命的出路。而產業演化過程中持續出現的「互補性技術」及「階段性區隔市場」即為產業及其生態系在順應演化過程中，尋找出路的具體表現。二者在演化過程中協助產業及其參予者突破限制，並產生演化所需之推拉動能。生態系參予者應妥善運用此二樞鈕所提供之槓桿，作為其生態系策略之核心，創造自身於演化過程中之相對優勢。
Industrial evolution unfolds along with its ecosystem development. How an individual participant in the ecosystem can identify the evolution patterns and apply suitable strategy to survive well in the process and furthermore to develop its advantage along the path is what this research is aiming to explore. By looking into the example of self-driving industry’s evolution and smart camera in its ecosystem, this study attempts to extract an applicable strategy guideline to help the ecosystem participant to live along and grow stronger toward the realization of a market that is being newly developed.
The research takes four steps to reach the goal. Firstly. It deconstructs the industry and its ecosystem into key participants, clarifies the value and labor division that each participant provides among the entire network. Then, by mapping the relationship between the smart camera and other participants, it tries to find out the related behavioral motivation among the ecosystem members. Upon this basis, this research furthermore uses the gaming theory to figure out the causal relationship amid the evolution dynamic and extract common patterns accordingly. At last, this research formulates the strategy guideline for the participant like smart camera to obtain its viability and potency toward the realization of self-driving vehicle.
Symbiosis for the ecosystem and Value-Network for gaming theory are the two perspectives this research uses to get insights into what drives the behavior and related motivation in the ecosystem during evolution. Symbiosis explains how the individual exploits the environmental resources for viability. Value-Network supports to take proper strategy to obtain the potency.
This research applies the gaming theory that’s commonly used in the “co-opetition” to analyze eight critical events that were considered to have changed the evolutional path in the self-driving industry. Through this analysis, it infers what the likely consequences the events would bring about in the following evolution and extracts the causal relationship and evolutional patterns amid the dynamics.
This research discovered that industrial evolution shares the same pattern as biological evolution, i.e. “Life will keep finding its way out”. The repeating emergence of “complementary technologies” and “interim segmental markets” is how the industrial evolution embodies this pattern. It supports the industry and its ecosystem to break through hurdles and generates the momentum needed in the evolutional process. The participant in ecosystem should therefore take good leverage of the two pivots as the core of its ecosystem strategy and obtain advantage over the evolution toward its realization. |
| Reference: | 中文文獻
1. 方謙、李仕奇，(2019）。長鞭效應的成因與減緩措施。學術論壇，2月號，219-220。
2. 吳思華著，(2000），策略九說。台北：城邦文化。
3. 李薇，（2011）。學習型競合關係運行機制的系統動力學研究。企業戰略，第四期，22-24。
4. 李郁怡，（2013）。重造創新生態系統。哈佛商業評論，9月號，數位版。
5. 周信輝，王逸萍，（2021）。遵循「SVA架構」，4 大法則打造商業生態系統。哈佛商業評論，12月號，數位版。
6. 姚艷紅、宋緒萍更、陳歡歡，（2020）。競合關係、組織慣例更新與突破式創新。科技進步與對策，37卷24期，1-9。
7. Adam M. Brandenburger, Barry Nalebuff著，黃婉華、馮勃翰譯，（2015），競合策略。台北：雲夢千里文化。
8. 陳明哲，（2022）。動態競爭。台北：元照出版。
9. 張彥文，（2019）。釐清五個觀念，成功創造生態系統。哈佛商業評論，9月號，數位版。
10. 楊陽、焦鄭珊、孫顯斌，（2018）。產業演化的動力模型與經驗研究。產經評論，11月第六期，92-103。
英文文獻
1. In the Ecosystem Economy, What’s Your Strategy, July 10, 2021, https://hbr.org/2019/09/in-the-ecosystem-economy-whats-your-strategy
2. James F Moore, (1997). The Death of Competition, New York: Harper Paperback.
3. Levels of Driving Automation, January 23, 2022, https://www.sae.org/news/2019/01/sae-updates-j3016-automated-driving-graphic
4. Marco Iansiti and Roy Levien, (2004). The Keystone Advantage, Boston: Harvard Business Review Press.
5. Marco Iansiti and Karim R. Lakhani, (2020). Competing in the Age of AI, Boston: Harvard Business Review Press.
6. Platforms, Communities, and Business Ecosystems: Lessons Learned about Technology Entrepreneurship in an Interconnected World, July 12, 2021, https://timreview.ca/article/655
7. Self-driving car, January 23, 2022, https://en.wikipedia.org/wiki/Self-driving_car
8. The New-Market Conundrum, July 13, 2021, https://hbr.org/2020/05/the-new-market-conundrum
9. Timeline: Milestones in ADAS Before 2010, August 14, 2021, https://www.adaptautomotive.com/articles/51-timeline-milestones-in-adas-before-2010
10. Vehicle-to-everything, January 23, 2022, https://en.wikipedia.org/wiki/Vehicle-to-everything |
| Description: | 碩士
國立政治大學
經營管理碩士學程(EMBA)
109932083 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0109932083 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202200398 |
| Appears in Collections: | [經營管理碩士學程EMBA] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 208301.pdf | | 2067Kb | Adobe PDF2 | 103 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
