8 2-10 hkust chn

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Chinese translation. Using socially constructed data, parsed from data retrieved from online English-language press releases, network analysis shows patterns of organizational infrastructure. The cultivation approach to global investments into Chinese technology-based companies is contrasted with the harvesting approach of Chinese investments into the rest of the world. Critical implications for board interlocks and flows of information are discussed. Research conducted at Media X at Stanford University, by Martha G. Russell, Neil Rubens, Kaisa Still, Jukka Huhtamaki. Presented at Hong Kong University of Science and Technology, August 2, 2010.

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  • Please think of several patterns and outliers in bicicles picture.ASK AUDIENCE---So let me just mention a few:Color is one of the patters that jumps out right awayFor example there is a lot of aluminum colorsYellow bike jumps out as an outlierIf we look closer we may also notice that there is only one bike where the handles are greenOnly a few bikes have their seat covered with plasticBikes are more or less lined upThere is a bike that is facing the wrong way though----------Even in these small dataset there are so many patterns and outliersBut how many of them are interesting; that really depends.We try to find patterns that are novel; since telling people that bicycles tend to have two wheels is perhaps not so interesting.What is interesting also depends on the purpose;A person checking whether bicycles have permit for parking – is looking for a specific outliersWhen I look for my own bike; I have a different outlier in mindSo ability to spot things that are interesting is extremely important.Outliers are normally discarded in data mining …Because you are often trying to find a pattern, and outliers screw up things.In business, some outliers have become very successful as described in the following book.So we thing it is interesting to look not only for patterns but also for outliers
  • Can’t do data mining without the data; so we need data and the more the better – since then we can see patterns more clearly
  • Also when we have more dimensions it is easier to spot patterns
  • Now let me briefly describe a case of how we utilized the above mentioned principles.In our project we try to understand innovation, so have gathered the data on companies, people and money.What makes this data set different, besides its timeliness is the majority of data (thanks to social media) is about small companies having between 1 – 5 employees.A lot of innovation happens there so it is important to track.
  • This shows how we have evolved from the local/regional activities
  • This shows how the models of innovations have evolved reflecting the changes
  • We can also look at the companies by sector
  • At the core of this research we have what initially were called “regional technology-based economic development”– however each of the three parts has experienced changes, which calls for updating the whole concept
  • So far I have shown analysis based on the spatial distance;However the aspects of distance is changing;We don’t know where these people are physically located but they seem to be in the same space.
  • So the new maps may be based on the connections; rather than on distance.For this analysis we have utilized an open source tool called NodeXL
  • My name is Neil Rubens, I am not a journalist; I am a data miner – but I think in essense it is not so different.
  • It is rare that the data is simply brought to us on a silver platterWe have to try hard to actively acquire it
  • This map indicates the location of the companies. Size of circle indicates number of companies.For this part of analysis we have used Tableau Software.
  • 8 2-10 hkust chn

    1. 1. 使用社交网络分析在创新生态系统中协同创造价值创新生态系统网络Martha G Russell, Neil RubensAugust 2, 2010<br />
    2. 2. Media X 旨在推动斯坦福大学的行业及学院研究,加速其对社会信息和科技的影响力。<br />依靠分布在斯坦福校园各个学科部门,研究中心或是实验室的93位世界级别的的研究人员领军者,Media X促进对创新的根本性了解,帮助加快取得研究成果。<br />Media X的研究为会员公司提供了最新的科技的信息知识,从而帮助他们降低风险。斯坦福的思想领袖们的见解还帮助会员们具有开创性的洞悉,识别新兴的机会。<br />
    3. 3.
    4. 4.
    5. 5.
    6. 6. 创新产生于至少两个人之间。团队精神是必须的。总是有赢家和输家。<br />虽然人们可以随时随地地沟通,但对于复杂的全球性问题,一个人很难在某个时刻具备所有必须的洞察力,从而做出决定。<br />创新是社会性的<br />
    7. 7. 一场知识革命正在发生。<br />我们能学些什么去做得更好呢?<br />
    8. 8. http://www.innovation-ecosystems.org<br />创新生态系统网络<br /><ul><li>Martha G Russell, PhD, martha.russell@stanford.edu
    9. 9. Sr. Research Scholar, HSTAR Institute
    10. 10. Associate Director, Media X at Stanford University
    11. 11. Neil Rubens, PhD, neil@hrstc.org
    12. 12. Assistant Professor, Graduate School of Information Systems
    13. 13. University of Electro-Communications, Tokyo
    14. 14. Jukka Huhtamäki, jukka.huhtamaki@tut.fi
    15. 15. Researcher, Lecturer
    16. 16. Hypermedia Laboratory (HLab) of Tampere University of Technology (TUT).
    17. 17. Kaisa Still, PhD, kaisastill@yahoo.com
    18. 18. Knowledge Management Specialist
    19. 19. Beijing DT Electronic Technology Co., Ltd
    20. 20. Mario Gastel, mariogastel@zeelandnet.nl
    21. 21. Graduate student, Texas Advertising, UT Austin
    22. 22. Fulbright Scholar (2009-11)
    23. 23. Jiafeng (Camilla) Yu, camillayu@gmail.com
    24. 24. M.A. in Advertising in Planning Track
    25. 25. The University of Texas at Austin</li></li></ul><li>http://www.flickr.com/photos/ritavitafinzi/2192500407/<br />
    26. 26. “没有一种数据可以与拥有更多的数据媲美”<br />(Mercer at Arden. House, 1985)<br />“There is no data like more data” <br />(Mercer at Arden. House, 1985)<br />Tan, Steinbach, Kumar; 2004<br />2,000 个点<br />500 个点<br />8,000 个点<br />
    27. 27. 更多的维度:一把双刃剑<br />对数据的需求量增多<br />http://wissrech.ins.uni-bonn.de/research/projects/engel/engelpr2/pr2_thumb.jpg<br />能较容易地找出模式<br />http://www.iro.umontreal.ca/~bengioy/yoshua_en/research_files/CurseDimensionality.jpg<br />
    28. 28. 创新生态系统网络<br />创新生态系统指的是组织内部的,包括政治,经济,环境,科技的系统 – 是一个对于加速,维护和支持商业发展的有利的环境。<br />一个动态的创新生态系统的特点是会对人,知识信息和资源之间的协同关系不断做出调整,对不断发展的内因和外因做出极快的反应,从而促进和谐发展。<br />世界各地的发展商都想知道如何才能优化公共或私人对于加速创新的投资,达到最大的影响效果。<br />人们还没有完全了解如何利用本地资源吸引全球的投资,从而使本地区受益。而且,如何对中期进展进行评估也是急需解决的问题。IEN的目的就是为了填补这部分的空白。<br />
    29. 29. .<br />创新生态系统的数据库<br />35,000 companies include:<br />Sectors: Advertising, biotech, cleantech, consulting, ecommerce, enterprise, games_video, hardware, legal, mobile, network_hosting, public relations, search, security, semiconductor, software, web, other firms serving these.<br />Investment profiles from Ltd to public, financing rounds identified<br />Merger & Acquisition profiles<br />Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” <br />Technical Report. Media X, Stanford University, Feb.2010.<br />
    30. 30. # 公司数<br /># 人数<br />Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” <br />Technical Report. Media X, Stanford University, Feb.2010.<br />
    31. 31. 创新的地点<br />从地方到区域到虚拟共享空间<br />Innovation Acceleration<br />Networks<br />?<br />
    32. 32. 创新的模式<br />从组织到单独的用户到联网的个体<br />eClusters<br />?<br />
    33. 33. .<br />美国科技公司的数量<br />按行业划分,2009年12月<br />Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” <br />Technical Report. Media X, Stanford University, Feb.2010.<br />
    34. 34. 亟待更新<br />区域科技产业经济发展<br />“全球的商业地图被越来越多的区域集中化的公司群体,其相关的经济人和机构所占据。”<br />The Use of Data and Analysis as a tool for cluster policy, Green Paper on international best practices and perspectives prepared for the European Commission, November 2008<br />“有时一个产业群体中的成员分布于全球不同区域,但他们可以通过信息和通讯技术联系在一起... 所以人们会用“e-群体“去形容它们” <br />Danese, Filippini, Romano, Vinelli 2009<br />“科技化的趋势正在带动发达市场经济中产生更多的创新。”Baldwin & von Hippel November 2009, Harvard Business School Working Paper 10-038<br />“各地的政府部门在积极地采取措施,加强国家的创新体系。因为他们都意识到要想成为经济发展的领军者及加强国际竞争力,创新能力和商业化高科技产品的能力发挥着日益重要的作用。”Understanding Research, Science and Technology Parks: Global Best Practices, National Research Council of the National Academies, Report 2009<br />
    35. 35. 距离<br />过去<br />现在<br />
    36. 36. 新型的组织架构图<br />
    37. 37. 创新生态系统网络<br />创新生态系统指的是组织内部的,包括政治,经济,环境,科技的系统 – 是一个对于加速,维护和支持商业发展的有利的环境。<br />一个动态的创新生态系统的特点是会对人,知识信息和资源之间的协同关系不断做出调整,对不断发展的内因和外因做出极快的反应,从而促进和谐发展。<br />世界各地的发展商都想知道如何才能优化公共或私人对于加速创新的投资,达到最大的影响效果。<br />人们还没有完全了解如何利用本地资源吸引全球的投资,从而使本地区受益。而且,如何对中期进展进行评估也是急需解决的问题。IEN的目的就是为了填补这部分的空白。<br />
    38. 38. 新的地图应该是建立在各种联系上-而不是距离上。<br />
    39. 39. 清洁技术<br />Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,<br /> “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.<br />
    40. 40. 生物技术<br />Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,<br /> “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.<br />
    41. 41. 公关<br />Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,<br /> “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.<br />
    42. 42. 网络<br />Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,<br /> “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.<br />
    43. 43. 角色<br />首席技术官<br />投资者<br />首席市场官<br />创始人<br />Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,<br /> “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.<br />
    44. 44. 问题?<br /><ul><li>What interlock patterns characterize investments into technology-based companies being made by Chinese investment firms?
    45. 45. How are these patterns similar or different to those made by the rest of the world into China?</li></ul>http://4.bp.blogspot.com/_qFju91K89HM/SxRpABd1DTI/AAAAAAAABjw/6LaSJfjfk-I/s1600/Unexpected_Guests.jpg<br />http://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg<br />
    46. 46. 进出中国的投资环境<br />社交架构的数据,英文,开放式-在中国都是挑战。<br />创新生态系统数据库<br /><ul><li>323个科技产业公司,在中国拥有一个和多个办事地点
    47. 47. 42个中国投资公司,77个外商投资公司
    48. 48. 54亿美元的投资进入中国
    49. 49. 31亿美元的投资来自中国</li></ul>洞察:<br />进出中国的金融资源的流动<br />更多说明性而非描述性/观点性的结果<br />NodeXL, Tableau<br />Innovation Ecosystem Network<br />
    50. 50. 初步数据分析:<br />53% (113) 的中国企业属于eCIS行业<br />50 % (66) 的外商公司属于eCIS行业<br />进一步洞察:<br />流入和流出中国的投资模式及其不同的特点<br />具体: eCIS行业环境电子商务和电子安全系统=电子商务, 软件研究, 网络存取, 移动, 游戏和录影, 企业<br />Innovation Ecosystem Network<br />
    51. 51. 快速收获来自中国的投资(进行投资)<br />Innovation Ecosystem Network<br />
    52. 52. 慢慢耕耘进入中国的投资(获得投资)<br />Innovation Ecosystem Network<br />
    53. 53. 网络标准<br />Innovation Ecosystem Network<br />
    54. 54. 投资公司连接起的新兴中国商业群<br />Innovation Ecosystem Network<br />
    55. 55. 慢慢耕耘 / 快速收获的模式 – 价值共创<br />中国公司互锁在投资公司的层面上<br />Government-led investment firms<br />Knowledge of government guarantees<br />Investments in firms that return benefits to China<br />国际公司互锁在投资公司及公司层面上<br />机会网络及价值共创<br />http://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg<br />重要的发现<br />
    56. 56. http://www.flickr.com/photos/manpsing/2618332693/<br />http://www.fabcats.org/owners/feeding/info.html<br />被动获取<br />主动猎取<br />FURTHER RESEARCH<br />Personal relationships/opportunity networks <br />Time series analysis<br />Expansion of data <br />Chinese language press releases <br />Chinese business registries<br />
    57. 57. Innovation Ecosystems Network Regional Studies with Global Perspective<br />China, Norway, Finland<br />
    58. 58. .<br />Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” <br />Technical Report. Media X, Stanford University, Feb.2010.<br />
    59. 59. 讨论<br />数据,工具,问题<br />www.innocation-ecosystems.org<br />Innovation Ecosystem Network<br />
    60. 60. 参与到Media X中来<br /><ul><li>会员制
    61. 61. 访问学者
    62. 62. 研究方案
    63. 63. 专题讨论会
    64. 64. 研讨会
    65. 65. 夏季学院</li>

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