Bridging Individual and Organisational Knowledge The Appeal to Tacit Knowledge in Knowledge
学术英语(社科)Unit1-8 Text A译文
学术英语课文翻译Unit1人们如何做出决策理性的人认为在保证金1.经济学家通常假设人是理性的。
理性的人们系统地,有目的地做最好的,他们可以实现他们的目标,考虑到可用的机会。
当你学习经济学,你会遇到公司决定雇佣多少工人,有多少他们的产品生产和销售利润最大化。
你也会遇到那些决定花多少时间工作和买什么商品和服务产生的收入来实现最高水平的满意度。
2.理性的人知道生活中的决策很少是黑白的，但通常是灰色的。
在吃饭的时候，你面对的不是空腹或是像猪一样进食，而是吃额外的一匙土豆泥。
当考试开始时，你的决定不是介于两者之间，而是让他们减少或学习一天24小时，而不是花更多的时间复习笔记而不是看电视。
经济学家用“边际变化”这个术语来描述对现有的行动计划的调整。
请记住，边际意味着“边缘如此边缘的变化是在你正在做的边缘周围的调整”。
理性的人往往通过比较边际收益和边际成本来做出决定。
3.例如，考虑一家航空公司决定向待机乘客收取多少费用。
假设撒德躺在横跨美国的200座飞机上，航空公司损失100,000英镑。
在这种情况下，每个座位的平均成本是1,000美元/ 200美元，这是500美元。
有人可能会得出这样的结论：航空公司不应该售出票价低于500美元的机票。
事实上，一家理性的航空公司通常可以通过考虑利润率来提高利润。
想象一下，一架飞机即将起飞，有10个空座位，候机旅客在门口等候，将支付300美元的座位。
航空公司应该把票卖掉吗？当然应该。
如果飞机有空座位，增加一个乘客的成本很小。
乘飞机的平均成本是S500，边际成本仅仅是额外的乘客将消耗的花生袋和苏打水的成本。
只要备用乘客支付超过边际成本，售票是有利可图的。
4.边际决策有助于解释一些令人费解的经济现象。
这里有一个经典的问题：为什么水这么便宜，而钻石这么贵？人类需要水来生存，而钻石是不必要的；但出于某种原因，人们愿意付出更多的钻石比一杯水。
原因是一个人愿意支付任何好处是基于一个额外单位的好处会产生边际效益。
biddinggame
17© Shreekant W Shiralkar 2016S. W. Shiralkar, IT Through Experiential Learning , DOI 10.1007/978-1-4842-2421-2_3C ontext:C ollaborative Learning and Collective Understanding of E RPDuring our school days, my friends and I frequently engaged in discussing specific topics from our textbooks. Each one of us comprehended a specific aspect of the larger subject, and when we shared understanding or knowledge of the topic, we found that our collective understanding helped us raise each individual’s understanding much faster and deeper than individually struggling to comprehend the subject. Later, we even formalized the process during the examination period as we found the process helping learn quickly. During my college days, we practiced the technique further by forming study groups, and when having difficulty understanding a topic, we broke it into subtopics and distributed among the group for learning parts individually and then collectively sharing it with the rest of the group. The process helped each one of us in comprehending knowledge which appeared difficult and complex to us as individuals. The results of learning through a process of discussion were impressive and gave me insight into a few aspects of the concept formally known as “cooperative learning,” which defines the process of learning together rather than being passive individual receivers of knowledge (e.g., teacher lecturing and students hearing). This process allows learners to use cognitive skills of questioning and clarifying, extrapolating and summarizing.I n one of my assignments, I was engaged to train the top management of an organization on ERP and the impact of its implementation. I anticipated that it would be a huge challenge to engage top executives in this training, as most would have had some understanding already, and applying a conventional training process risked losing their attention if my co-trainer or I fell short of their expectations. While individually each top executive may have had generic knowledge of ERP , they certainly lacked comprehensive knowledge, and more specifically a seamless collective understanding of the subject, without any gaps due to individual interpretations or exposures. The task, therefore, was multifaceted: on one hand, I had to get them interested in learning aspects of which they lacked knowledge, and on the other, I had to encourage them to share their individual understandings of the subject, facilitating development of a collective learning.CHAPTER 3 ■ BIDDING GAME18F or a top executive, it is expected that he or she needs to take calculated risks inalmost every key decision, whether it’s bidding for a large contract or establishing price point while taking a privately held organization for public trading. The process of bidding involves awareness of collective knowledge of capability, assessment about competition, and expertise to apply judgment based on rational (and some irrational) criteria. In the knowledge-driven economy, the contributions of each employee, regardless of level, add up to the collective capability of the organization.W ith a view to facilitate collective learning in the shortest possible time for these top executives, I conceived a “Bidding Game” that leveraged cooperative learning to teach the ERP solution and the impact of its implementation in one session. The result in of Bidding Game was outstanding.T his is the premise of the game that will be explained in this chapter. The game also helps induce elements of social skills like effective communication and interpersonal and group skills in learning an otherwise abstract and complex subject.T he Bidding Game is a game played by all the participants divided into two or more teams. Teams compete on the strength of their collective knowledge of the subject. The game concludes after the collective learning on a specific subject is acquired to the appropriate level on all the essential aspects. The game format provides encouragement to each participant to contribute his or her knowledge of the subject and helps the team to win. A notional value attached to the correct and complete response helps measure the level of knowledge among participants. The competition is premised on the accuracy of the initial bid, which adds a flavor of bidding.F igure 3-1will help you visualize the setting created for the participants of the Bidding Game.F igure 3-1.I nstructor inviting b idsCHAPTER 3 ■ BIDDING GAME19In a hall, participants will be seated in a U-shaped arrangement, facing the projector screen. The hall will have two whiteboards on either side of the projector screen. One of the whiteboards will be titled “Knowledge Bid” and will display the bids by participating t eams.T he second whiteboard will record the actual earnings or the SCORE for each of the teams. The projector screen will be used to publish the question for each of the bid, and the instructor will allow the teams to respond in sequence and will record the score on the whiteboard on the basis of the accuracy and completeness of response by the team (Figure 3-2).F igure 3-2.I nstructor inviting response to q uestion In designing the Bidding Game, the elements of competition and encouraging discussion on each aspect form the core theme. The competitive aspect triggers speed, the game element induces interest without force or pressure, and finally discussions and sharing of knowledge facilitate desired coverage of the subject—for instance, technical nuances and features offered by new technology and/or processes, channelling an accelerated Learning and Collective Understanding new technology and/or p rocesses .B idding Game Design To design the Bidding Game, I recommend ensuring that the pace of learning is accelerated gradually, and that learning begins with basic aspects and moves on to the advanced and complex aspects in sequence instead of beginning with complex subjects and then concluding with basics. In the design of the sequence, care has to be exercised in segregating the basic and must-learn aspects from the “nice-to-know” aspects, andCHAPTER 3 ■ BIDDING GAME20design should ensure accomplishing learning of basic and must-learn ones whileprovisioning for nice-to-know types based on the interest and appetite of the participants. Design the sequence in such a way that initially the participant need to spend less time and are encouraged toward the game and competition, while later parts of the sequence should ensure that participants spend more time in discussions and staying ahead of competition.T he objective—rapid development of collective learning of technology and/or new processes—necessitates a short duration of the Bidding Game.L et us now examine the task-level details of the Bidding Game beginning with preparation/planning, recommended rules, and then the process for its execution,including steps to consolidate learning after conclusion. An overview of the entire game is depicted in Figure 3-3 .C omplete details of the activities in the process flow are described in detail in the following sections.P reparation/Planning •D ivide the subject into 20 subtopics that cover the subject comprehensively. • C reate a question for each of the subtopics.•C reate a sequence of questions in a way that gradually raises the level of knowledge. •S egment the questions into three levels: Rookie, Advanced, and Expert.•A ssign different values to questions from the three sets, for example, $100 per question from the Rookie level, $200 perquestion from the Advanced level, and $300 per question from the Expert level. •D evelop a clear rule set for the Bidding Game that can be used to explain the game to the participants.F igure 3-3.B idding Game p rocess flowCHAPTER 3 ■ BIDDING GAME • H ave a scoreboard that displays the bid value of the team and alsotheir score during the progress of the game (use the whiteboardmarker pens).• H ave a large clock for monitoring time and identify assistants forkeeping time and recording the score.R ecommended Rules• T he winner is chosen on the basis of two parameters: high scoreas well as that which is closest to its bid.• E ach wrong or incomplete response has a loss of value (i.e.,negative marking); for example, a $50 penalty for each wrong orincomplete response.• $50 is deducted from the value of a passed-over question or apartly answered question.• T he completeness of the response to a question can be challengedby competing teams to apply penalty and reduce the score.• T here’s a limit of 5 minutes for responding to each question. Eachround could begin sequence in a way that provides a fair chanceto all the teams.O nce all the preparation is completed, the game can begin.E xecution1. A ll the participants are told the context and rationale for thegame (i.e., what ERP is and the importance of each of themhaving a collective understanding of the subject, which wouldmaximize benefit from its implementation). Also, it shouldbe explained how playing a game such as this can increaseindividual understanding much faster and more deeply thanindividually struggling to comprehend the subject in isolation.2. P articipants are divided into teams. Team formation canbe done in any way that generates nearly equal numbers ofparticipants for each team (dividing the room, counting off bytwos, etc.)3. T he instructor/quiz master (QM) invites bids from each of theteams, which are recorded on the whiteboard for everyone tosee.4. T he instructor launches the first question on the screen andinvites the first team to take its chance, while the timekeepermonitors the time taken by the responding team.21CHAPTER 3 ■ BIDDING GAME225. O n the basis of correctness and completeness of the response,the instructor assigns a score to the team, which is recordedon the second whiteboard.6. I n case the question is passed to the second team and they areable to respond correctly and completely, the reduced score isrecorded.7. I n case the question is not answered or is incompletelyresponded by any of the teams, the instructor shares the correctand complete answer and the subject is discussed and clarified.8. T he process continues until the subject is completely covered.9. T he instructor tallies the scores for the teams and announcesthe winner on the basis of the high score and the bid a ccuracy .O nce the game is over, observations from experience are collected and crystallized inlearning in the next section.C onclusion• T he learning gained through the game needs to be articulatedand consolidated. Debrief is a process that will aid in articulatinglearning that participants gained during the game.• T he process of debrief begins with each participant sharinglearning, specifically something that has changed theirunderstanding about the subject during the game.• E ach participant would have learned something new, be it a verybasic addition to earlier knowledge of the subject or very complexinformation that the participant hadn’t ever known before.• T he individual learnings are recorded on a whiteboard, whichhelps in crystallizing and consolidating collective understandingon the subject.• O nce the game is over, the learning can be consolidated bypresenting additional material by way of slides, videos, and so on.S ample ArtifactsW ith a view to facilitate the immediate application of the approach in the chapter, a sample list of questions on ERP and Big Data along with an illustrative score sheet with result, are provided in the following section. The correct responses from multiple choices, are identified in bold.CHAPTER 3 ■ BIDDING GAMES ample Question Cards:ERP1. W hat is the extended form of ERP?a. E nterprise Retail Processb. E nterprise Resource Planningc. E arning Revenue and Profitd. N one of the above2. R eal time in the context of ERP relates to which of thefollowing?a. T ime shown in the computer system synchs with yourwatchb. P rocesses/events happen per transaction at the sameinstantc. B oth of the aboved. N one of the above3. W hat does “SOA” stand for in relation to ERP systemarchitecture?a. S ervice-Oriented Architectureb. S ystem of Accountsc. S tatement of Accountd. N one of the above4. W hich of these is not a packaged ERP?a. S APb. O raclec. W indowsd. J D Edwards5. I n the context of packaged ERP, do “Customization” and“Configuration” refer to the same process, or are theydifferent?a. S ameb. D ifferentc.D on’t know23CHAPTER 3 ■ BIDDING GAME246. M aterials Management in ERP helps to/esnure ?a. I ncrease of inventoryb. I nventory is well balancedc. B oth of the aboved. N one of the above7. S ales and Distribution Module in ERP helps in which of thefollowing?a. I ncreased customer serviceb. R educed customer servicec. B oth of the aboved. N one of the above8. F inancial and Controlling Module in ERP helps in which ofthe following?a. E valuating and responding to changing businessconditions with accurate, timely financial datab. E asy compliance with financial reporting requirementsc. S tandardizing and streamlining operationsd. A ll of the abovee. N one of the above9. G ain from implementation of ERP results in which of thefollowing?a. I mproved business performanceb. I mproved decision makingc. I ncreased ability to plan and growd. A ll of the aboveS ample Question Cards:B ig Data1. W hat is Big Data?a. D ata about big thingsb. D ata which is extremely large in size (in petabytes)c. D ata about datad. N one of the aboveCHAPTER 3 ■ BIDDING GAME2. W hich are not characteristics of Big Data?a. V olumeb.V elocityc. V irtualityd.V ariety3. W hich are key inputs for Big Data?a.I ncreased processing powerb. A vailability of tools and techniques for Big Datac. I ncreased storage capacitiesd. A ll of the above4. W hich are applications of Big Data?a. T argeted advertisingb.M onitoring telecom networkc. C ustomer sentimentsd. A ll of the above5. W hich tools are used for Big Data?a. N oSQLb. M apReducec. H adoop Distributed File Systemd. A ll of the above6. S ocial media and mobility are key contributors to Big Data:true or false?a. T rueb. F alse7. W hich is not a term related to Big Data?a. D atabasesMongoDBb. D ata T riggerc. P igd. S PARK25CHAPTER 3 ■ BIDDING GAME26B enefit Assessment After consolidation of the learning, it’s recommended to conduct a benefit assessment exercise to measure the gains from application of the game-based approach. Theassessment could be in form of a written quiz on the subject with multiple-choice answers.。
《跨文化交际语篇分析法》详解
“There is a taxi at the door.” →different way of being “at” the door→ the taxi at some distance at the door in a roadway or a driveway The difference lies in what we know about men and taxis and how they wait “at” doors.
a. walking down the street and stop a stranger to ask —— “It’s 2:00” —— “Thank you”
b. in a elementary school classroom teacher “ What time is it?” —— “It’s 2:00” —— “Very good, Frankie.” c. A husband and a wife are at dinner in the home of friends wife: “ What time is it ?” =“ Don’t you think it is time we were leaving?”
《与陌生人交际——跨文化交流方法》William
B. Gudykunst /Young Yun Kim，2007， 上海外语教育出版社
4. Dynamics of Intercultural Communication 《跨文化交际动力》
Carley H. Dodd，2006年 上海外语教育出版社
2. Sentence-level ambiguity in language
The meaning in sentence resides not in the sentence alone but in the situation in which it is used as well. Example: “What time is it?”
论教学中的缄默知识_卢尚建
2010年第1期(总第270期)GLOBAL EDUCATIONVol.39 No1,2010 论教学中的缄默知识卢尚建 【摘要】 在教学中存在着大量不容忽视的缄默知识,它来源于实际的教学、生活中的观察和体验,具有片断性、离散性、情境性等特征。
教学中的缄默知识存在两种功能,一是有利于教师进行教学和学生进行学习的正向功能,二是阻碍教师进行有效的教学和学生进行有效学习的负向功能。
研究缄默知识对于教学具有重要的启示作用:更新教学中的传统知识观念,使教学中缄默知识显性化,在实践中形成和应用缄默知识。
【关键词】 教学 知识 缄默知识 【作者简介】 卢尚建/西北师范大学教育学院博士生 (兰州730070) 英国物理化学家和思想家波兰尼(Polanyi)在20世纪50年代末提出:“人类有两种知识,通常所说的知识是用书面文字或地图、数学公式来表述的,这只是知识的一种形式。
还有一种知识是不能系统表述的,例如我们有关自己行为的某种知识。
如果我们将前一种知识称为显性知识的话,那么我们就可以将后一种知识称为缄默知识。
”[1]波兰尼在这里所说的缄默知识(tacit know ledge)与隐性知识(implicit know ledge)应当是同一概念,即指“只可意会不可言传的”知识。
波兰尼从认识论角度把人类的知识做出严格的逻辑分析,使人类对外部世界和自身内部世界的认识又向前迈进了一步。
一、教学中缄默知识的存在及其特征(一)教学中缄默知识的存在在教学中,若对大量存在的缄默知识进行分类,就涉及到分类的标准。
按不同的标准分类就会有不同的类型。
根据缄默知识在教学中存在的主体不同可以划分为教师拥有的缄默知识和学生拥有的缄默知识。
假如按照缄默知识的内容性质进一步划分,有教师的缄默学科知识、教师的缄默教学知识、学生的缄默学科知识和学生学习方法方面的缄默知识。
传统的教学,教师往往只重视对显性的学科知识的教学,简单地认为教学就是把学科的概念、原理、规律和方法传递给学生,在学生的头脑里就自然而然有了这些显性的学科知识。
跨文化管理
简答题A1. （评估风险的方法）Four methods of analyzing economic risk:1) The quantitative approach定量分析This measure is arrived by assigning different weights to economic variables in order to produce a composite index复合指标used to monitor the country’s creditworthiness over time and to make comparison with other countries.A drawback of this approach is that it does not make into account different stages of development among the countries it compares.2) The qualitative approach 定性分析It evaluates a country’s economic ris k by assessing the competence能力of its leaders and analyzing the types of policies they are likely to implement执行.This approach entails使成为必要a subjective（个人的）assessmen t by the researcher in the process of interviewing those leaders and projecting the future directions of economy.3) The checklist approachRelies on a few easily measureable and timely criteria 标准believed to reflect or indicate changes in the creditworthiness of the country.4) A combination of both approachesNot any single approach can provide a comprehensive economic risk profile of a country, so they use a combination of approaches.A2. 经济风险（economic risks）A country’s level of economic development generally determines its economic stability and, therefore, its relative risk to a foreign firm. A country’s ability or intention to meet its financial obligation determines its economic risk. The economic risk incurred by a foreign corporation usually falls into one of two main categories.The government abruptly changes its domestic monetary or fiscal policiesThe government decides to modify its foreign-investment policiesThe latter situation would threaten the company’s ability to repatriate（遣返）its earnings and would create a financial or interest-rate risk. Furthermore, the risk of exchange-rate volatility（挥发性）results in currency translation exposure (货币换算风险) to the firm when the balance sheet of the entire corporation is consolidated 统一的and may cause a negative cash flow from the foreign subsidiary.A3. Project GlOBE Culture Dimensions (文化维度)GLOBE: Global Leadership Organizational Behavior Effectivenessgender differentiation, uncertainty avoidance（不确定规避）, power distance, institutional collectivism versus individualism, and in-group collectivism.1) Assertiveness: This dimension refers to how much people in a society areexpected to be tough(坚韧的), confrontational（对抗的）, and competitive versus modest and tender（脆弱的）.Highly assertive: Greeze, Austria and Germany (value competition and a can-do attitude)Less assertive: New Zealand Sweden瑞典and Japan (prefer warm and cooperate relations and harmony)2)Future orientation:this dimension refers to the level of importance a society attaches（依附）to future-oriented behaviors such as planning and investing in the future.High: Netherlands, Switzerland and Singapore (are inclined to save for the future and have a longer time horizon for decisions)Low: Poland, Russia and Argentina (tend to plan more in the shorter term and place more emphasis on instant gratification)3) Performance orientation: this dimension measures the importance of performance improvement and excellence（优秀）in society and refers to whether or not people are encouraged to strive（争取）for continued improvement.High: Singapore, Hong Kong SAR, New Zealand and the United States (tend to take initiative and have a sense of urgency and the confidence to get things done)Low: Russia, Argentina, Greeze and Italy (they hold other priorities ahead of performance, such as tradition, loyalty, family and background and they associate competition as defect)4)Humane orientation: this dimension measures the extent to which a society encourages and rewards people for being fair, altruistic（无私的）, generous, caring, and kind.High: Philippines, Ireland, Malaysia, and Egypt. (focus on sympathy and support for weak, paternalism and patronage are important, and people are usually friendly and tolerant and value harmony)Low: Spain, France and former West Germany (give more importance to power and material possessions, as well as self-enhancement)A4.p.115 Comparative Management in Focus Communicating with ArabsAt the core of Middle Eastern culture are friendship, honor, religion, and traditional hospitality.中东文化的核心是友谊、荣誉、宗教以及传统的热情。
49编号博士研究生英语精读-翻译及原文（中科院）
第1课知识的悖论The Paradox of KnowledgeThe greatest achievement of humankind in its long evolution from ancient hominoid ancestors to its present status is the acquisition and accumulation of a vast body of knowledge about itself, the world, and the universe. The products of this knowledge are all those things that, in the aggregate, we call "civilization," including language, science, literature, art, all the physical mechanisms, instruments, and structures we use, and the physical infrastructures on which society relies. Most of us assume that in modern society knowledge of all kinds is continually increasing and the aggregation of new information into the corpus of our social or collective knowledge is steadily reducing the area of ignorance about ourselves, the world, and the universe. But continuing reminders of the numerous areas of our present ignorance invite a critical analysis of this assumption.In the popular view, intellectual evolution is similar to, although much more rapid than, somatic evolution. Biological evolution is often described by the statement that "ontogeny recapitulates phylogeny"--meaning that the individual embryo, in its development from a fertilized ovum into a human baby, passes through successive stages in which it resembles ancestral forms of the human species. The popular view is that humankind has progressed from a state of innocent ignorance, comparable to that of an infant, and gradually has acquired more and more knowledge, much as a child learns in passing through the several grades of the educational system. Implicit in this view is an assumption that phylogeny resembles ontogeny, so that there will ultimately be a stage in which the accumulation of knowledge is essentially complete, at least in specific fields, as if society had graduated with all the advanced degrees that signify mastery of important subjects.Such views have, in fact, been expressed by some eminent scientists. In 1894 the great American physicist Albert Michelson said in a talk at the University of Chicago:While it is never safe to affirm that the future of Physical Science has no marvels in store even more astonishing than those of the past, it seems probable that most of the grand underlying principles have been firmly established and that further advances are to be sought chiefly in the rigorous application of these principles to all the phenomena which come under our notice .... The future truths of Physical Science ate to be looked for in the sixth place of decimals.In the century since Michelson's talk, scientists have discovered much more than the refinement of measurements in the sixth decimal place, and none is willing to make a similar statement today. However, many still cling to the notion that such astate of knowledge remains a possibility to be attained sooner or later. Stephen Hawking, the great English scientist, in his immensely popular book A Brief History of Time (1988), concludes with the speculation that we may "discover a complete theory" that "would be the ultimate triumph of human reason--for then we would know the mind of God." Paul Davies, an Australian physicist, echoes that view by suggesting that the human mind may be able to grasp some of the secrets encompassed by the title of his book The Mind of God (1992). Other contemporary scientists write of "theories of everything," meaning theories that explain all observable physical phenomena, and Nobel Laureate Steven Weinberg, one of the founders of the current standard model of physical theory, writes of his Dreams of a Final Theory (1992).Despite the eminence and obvious yearning of these and many other contemporary scientists, there is nothing in the history of science to suggest that any addition of data or theories to the body of scientific knowledge will ever provide answers to all questions in any field. On the contrary, the history of science indicates that increasing knowledge brings awareness of new areas of ignorance and of new questions to be answered.Astronomy is the most ancient of the sciences, and its development is a model of other fields of knowledge. People have been observing the stars and other celestial bodies since the dawn of recorded history. As early as 3000 B.C. the Babylonians recognized a number of the constellations. In the sixth century B.C., Pythagoras proposed the notion of a spherical Earth and of a universe with objects in it chat moved in accordance with natural laws. Later Greek philosophers taught that the sky was a hollow globe surrounding the Earth, that it was supported on an axis running through the Earth, and chat stars were inlaid on its inner surface, which rotated westward daily. In the second century A.D., Ptolemy propounded a theory of a geocentric (Earth-centered) universe in which the sun, planets, and stars moved in circular orbits of cycles and epicycles around the Earth, although the Earth was not at the precise center of these orbits. While somewhat awkward, the Ptolemaic system could produce reasonably reliable predictions of planetary positions, which were, however, good for only a few years and which developed substantial discrepancies from actual observations over a long period of time. Nevertheless, since there was no evidence then apparent to astronomers that the Earth itself moves, the Ptolemaic system remained unchallenged for more than 13 centuries.In the sixteenth century Nocolaus Copernicus, who is said to have mastered all the knowledge of his day in mathematics, astronomy, medicine, and theology, became dissatisfied with the Ptolemaic system. He found that a heliocentric system was bothmathematically possible and aesthetically more pleasing, and wrote a full exposition of his hypothesis, which was not published until 1543, shortly after his death. Early in the seventeenth century, Johannes Kepler became imperial mathematician of the Holy Roman Empire upon the death of Tycho Brahe, and he acquired a collection of meticulous naked-eye observations of the positions of celestial bodies chat had been made by Brahe. On the basis of these data, Kepler calculated that both Ptolemy and Copernicus were in error in assuming chat planets traveled in circular orbits, and in 1609 he published a book demonstrating mathematically chat the planets travel around the sun in elliptical orbits. Kepler's laws of planetary motion are still regarded as basically valid.In the first decade of the seventeenth century Galileo Galilei learned of the invention of the telescope and began to build such instruments, becoming the first person to use a telescope for astronomical observations, and thus discovering craters on the moon, phases of Venus, and the satellites of Jupiter. His observations convinced him of the validity of the Copernican system and resulted in the well-known conflict between Galileo and church authorities. In January 1642 Galileo died, and in December of chat year Isaac Newton was born. Modern science derives largely from the work of these two men.Newton's contributions to science are numerous. He laid the foundations for modem physical optics, formulated the basic laws of motion and the law of universal gravitation, and devised the infinitesimal calculus. Newton's laws of motion and gravitation are still used for calculations of such matters as trajectories of spacecraft and satellites and orbits of planets. In 1846, relying on such calculations as a guide to observation, astronomers discovered the planet Neptune.While calculations based on Newton's laws are accurate, they are dismayingly complex when three or more bodies are involved. In 1915, Einstein announced his theory of general relativity, which led to a set of differential equations for planetary orbits identical to those based on Newtonian calculations, except for those relating to the planet Mercury. The elliptical orbit of Mercury rotates through the years, but so slowly that the change of position is less than one minute of arc each century. The equations of general relativity precisely accounted for this precession; Newtonian equations did not.Einstein's equations also explained the red shift in the light from distant stars and the deflection of starlight as it passed near the sun. However, Einstein assumed chat the universe was static, and, in order to permit a meaningful solution to the equations of relativity, in 1917 he added another term, called a "cosmological constant," to the equations. Although the existence and significance of a cosmological constant is stillbeing debated, Einstein later declared chat this was a major mistake, as Edwin Hubble established in the 1920s chat the universe is expanding and galaxies are receding from one another at a speed proportionate to their distance.Another important development in astronomy grew out of Newton's experimentation in optics, beginning with his demonstration chat sunlight could be broken up by a prism into a spectrum of different colors, which led to the science of spectroscopy. In the twentieth century, spectroscopy was applied to astronomy to gun information about the chemical and physical condition of celestial bodies chat was not disclosed by visual observation. In the 1920s, precise photographic photometry was introduced to astronomy and quantitative spectrochemical analysis became common. Also during the 1920s, scientists like Heisenberg, de Broglie, Schrodinger, and Dirac developed quantum mechanics, a branch of physics dealing with subatomic particles of matter and quanta of energy. Astronomers began to recognize that the properties of celestial bodies, including planets, could be well understood only in terms of physics, and the field began to be referred to as "astrophysics."These developments created an explosive expansion in our knowledge of astronomy. During the first five thousand years or more of observing the heavens, observation was confined to the narrow band of visible light. In the last half of this century astronomical observations have been made across the spectrum of electromagnetic radiation, including radio waves, infrared, ultraviolet, X-rays, and gamma rays, and from satellites beyond the atmosphere. It is no exaggeration to say chat since the end of World War II more astronomical data have been gathered than during all of the thousands of years of preceding human history.However, despite all improvements in instrumentation, increasing sophistication of analysis and calculation augmented by the massive power of computers, and the huge aggregation of data, or knowledge, we still cannot predict future movements of planets and other elements of even the solar system with a high degree of certainty. Ivars Peterson, a highly trained science writer and an editor of Science News, writes in his book Newton's Clock (1993) that a surprisingly subtle chaos pervades the solar system. He states:In one way or another the problem of the solar system's stability has fascinated and tormented asrtonomers and mathematicians for more than 200 years. Somewhat to the embarrassment of contemporary experts, it remains one of the most perplexing, unsolved issues in celestial mechanics. Each step toward resolving this and related questions has only exposed additional uncertainties and even deeper mysteries.Similar problems pervade astronomy. The two major theories of cosmology,general relativity and quantum mechanics, cannot be stated in the same mathematical language, and thus are inconsistent with one another, as the Ptolemaic and Copernican theories were in the sixteenth century, although both contemporary theories continue to be used, but for different calculations. Oxford mathematician Roger Penrose, in The Emperors New Mind (1989), contends that this inconsistency requires a change in quantum theory to provide a new theory he calls "correct quantum gravity."Furthermore, the observations astronomers make with new technologies disclose a total mass in the universe that is less than about 10 percent of the total mass that mathematical calculations require the universe to contain on the basis of its observed rate of expansion. If the universe contains no more mass than we have been able to observe directly, then according to all current theories it should have expanded in the past, and be expanding now, much more rapidly than the rate actually observed. It is therefore believed that 90 percent or more of the mass in the universe is some sort of "dark matter" that has not yet been observed and the nature of which is unknown. Current theories favor either WIMPs (weakly interacting massive particles) or MACHOs (massive compact halo objects). Other similar mysteries abound and increase in number as our ability to observe improves.The progress of biological and life sciences has been similar to that of the physical sciences, except that it has occurred several centuries later. The theory of biological evolution first came to the attention of scientists with the publication of Darwin's Origin of Species in 1859. But Darwin lacked any explanation of the causes of variation and inheritance of characteristics. These were provided by Gregor Mendel, who laid the mathematical foundation of genetics with the publication of papers in 1865 and 1866.Medicine, according to Lewis Thomas, is the youngest science, having become truly scientific only in the 1930s. Recent and ongoing research has created uncertainty about even such basic concepts as when and how life begins and when death occurs, and we are spending billions in an attempt to learn how much it may be possible to know about human genetics. Modern medicine has demonstrably improved both our life expectancies and our health, and further improvements continue to be made as research progresses. But new questions arise even more rapidly than our research resources grow, as the host of problems related to the Human Genome Project illustrates.From even such an abbreviated and incomplete survey of science as this, it appears that increasing knowledge does not result in a commensurate decrease in ignorance, but, on the contrary, exposes new lacunae in our comprehension and confronts us with unforeseen questions disclosing areas of ignorance of which wewere not previously aware.Thus the concept of science as an expanding body of knowledge that will eventually encompass or dispel all significant areas of ignorance is an illusion. Scientists and philosophers are now observing that it is naive to regard science as a process that begins with observations that are organized into theories and are then subsequently tested by experiments. The late Karl Popper, a leading philosopher of science, wrote in The Growth of Scientific Knowledge (1960) chat science starts from problems, not from observations, and chat every worthwhile new theory raises new problems. Thus there is no danger that science will come to an end because it has completed its task, clanks to the "infinity of our ignorance."At least since Thomas Kuhn published The Structure of Scientific Revolutions (1962), it has been generally recognized that observations are the result of theories (called paradigms by Kuhn and other philosophers), for without theories of relevance and irrelevance there would be no basis for determining what observations to make. Since no one can know everything, to be fully informed on any subject (a claim sometimes made by those in authority) is simply to reach a judgment that additional data are not important enough to be worth the trouble of securing or considering.To carry the analysis another step, it must be recognized that theories are the result of questions and questions are the product of perceived ignorance. Thus it is chat ignorance gives rise to inquiry chat produces knowledge, which, in turn, discloses new areas of ignorance. This is the paradox of knowledge: As knowledge increases so does ignorance, and ignorance may increase more than its related knowledge.My own metaphor to illustrate the relationship of knowledge and ignorance is based on a line from Matthew Arnold: "For we are here as on a darkling plain...." The dark chat surrounds us, chat, indeed, envelops our world, is ignorance. Knowledge is the illumination shed by whatever candles (or more technologically advanced light sources) we can provide. As we light more and more figurative candles, the area of illumination enlarges; but the area beyond illumination increases geometrically. We know chat there is much we don't know; but we cannot know how much there is chat we don't know. Thus knowledge is finite, but ignorance is infinite, and the finite cannot ever encompass the infinite.This is a revised version of an article originally published in COSMOS 1994. Copyright 1995 by Lee Loevinger.Lee Loevinger is a Washington lawyer and former assistant attorney general of the United States who writes frequently for scientific c publications. He hasparticipated for many years as a member, co-chair, or liaison with the National Conference of Lawyers and Scientists, and he is a founder and former chair of the Science and Technology Section of the American Bar Association. Office address: Hogan and Hartson, 555 Thirteenth St. NW, Washington, DC 20004.人类从古类人猿进化到当前的状态这个长久的进化过程中的最大成就是有关于人类自身、世界以及宇宙众多知识的获得和积聚。
动态知识管理(野中郁次郎)
SECI,Ba and Leadership:a Uni®ed Model of Dynamic Knowledge CreationIkujiro Nonaka,Ryoko Toyama and Noboru KonnoDespite the widely recognised importance of knowledge as a vital source of competitive advantage,there is little understanding of how organisations actually create and manage knowledge dynamically.Nonaka,Toyama and Konno start from the view of an organisation as an entity that creates knowledge continuously,and their goal in this article is to understand the dynamic process in which an organisation creates,maintains and exploits knowledge.They propose a model of knowledge creation consisting of three elements:(i)the SECI process,knowledge creation through the conversion of tacit and explicit knowledge;(ii)`ba ',the shared context for knowledge creation;and (iii)knowledge assets,the inputs,outputs and moderators of the knowledge-creating process.The knowledge creation process is a spiral that grows out of these three elements;the key to leading it is dialectical thinking.The role of top management in articulating the organisation's knowledge vision is emphasised,as is the important role of middle management (`knowledge producers')in energising ba .In summary,using existing knowledge assets,an organisation creates new knowledge through the SECI process that takes place in ba ,where new knowledge,once created,becomes in turn the basis for a new spiral of knowledge creation.=2000Elsevier Science Ltd.All rights reserved.As Alvin Tof¯er said,we are now living in a `knowledge-based society',where knowledge is the source of the highest quality power.1In a world where markets,products,technologies,competitors,regulations and even societies change rapidly,con-tinuous innovation and the knowledge that enables such inno-vation have become important sources of sustainable competitive advantage.Hence,management scholars today con-sider knowledge and the capability to create and utilise knowl-edge to be the most important source of a ®rm's sustainable Long Range Planning 33(2000)5±34/locate/lrp 0024-6301/00/$-see front matter #2000Elsevier Science Ltd.All rights reserved.PII:S 0024-6301(99)00115-6Ikujiro Nonaka is Professor and Dean of the Japan Advanced Institute of Science and Technology,Graduate School of Knowledge Science,Japan.Corresponding address:Japan Advanced Institute of Science and Technology,GraduateSchool of Knowledge Science,competitive advantage.2The raison d'e Ãtre of a ®rm is to con-tinuously create knowledge.Yet,in spite of all the talk about `knowledge-based management'and in spite of the recognition of the need for a new knowledge-based theory that differs ``in some fundamental way''3from the existing economics and or-ganisational theory,there is very little understanding of how organisations actually create and manage knowledge.This is partly because we lack a general understanding of knowledge and the knowledge-creating process.The `knowledge management'that academics and business people talk about often means just `information management'.In the long tra-dition of Western management,the organisation has been viewed as an information processing machine that takes and processes information from the environment to solve a pro-blem and adapts to the environment based on a given goal.This static and passive view of the organisation fails to capture the dynamic process of knowledge creation.Instead of merely solving problems,organisations create and de®ne problems,develop and apply new knowledge to solve the problems,and then further develop new knowledge through the action of problem solving.The organisation is not merely an information processing machine,but an entity that creates knowledge through action and interaction.4It interacts with its environment,and reshapes the environment and even itself through the process of knowledge creation.Hence,the most important aspect of understanding a ®rm's capability concern-ing knowledge is the dynamic capability to continuously create new knowledge out of existing ®rm-speci®c capabilities,rather than the stock of knowledge (such as a particular technology)that a ®rm possesses at one point in time.5With this view of an organisation as an entity that creates knowledge continuously,we need to re-examine our theories of the ®rm,in terms of how it is organised and managed,how it interacts with its environment,and how its members interact with each other.Our goal in this article is to understand the dynamic process in which an organisation creates,maintains and exploits knowledge.The following sections discuss basic concepts related to the organisational knowledge-creating pro-cess,how such a process is managed,and how one canlead Figure 1.Knowledge created through a spiral Tatsunokuchi,Ishikawa 932-1292,Japan.Ryoko Toyama is AssistantProfessor at the JapanAdvanced Institute of Scienceand Technology,GraduateSchool of Knowledge Science,Japan.Noboru Konno is President ofColumn,Inc.,Tokyo,Japan.6SECI,Ba and Leadershipsuch a knowledge-creating process.Knowledge is created in the spiral that goes through two seemingly antithetical concepts such as order and chaos,micro and macro,part and whole, mind and body,tacit and explicit,self and other,deduction and induction,and creativity and control.We argue that the key in leading the knowledge-creating process is dialectical thinking,which transcends and synthesises such contradictions (see Figure1).What is knowledge?In our theory of the knowledge-creating process,we adopt the traditional de®nition of knowledge as`justi®ed true belief'.However,our focus is on the`justi®ed'rather than the`true' aspect of belief.In traditional Western epistemology(the theory of knowledge),`truthfulness'is the essential attribute of knowl-edge.It is the absolute,static and non-human view of knowl-edge.This view,however,fails to address the relative,dynamic and humanistic dimensions of knowledge.Knowledge is dynamic,since it is created in social inter-actions amongst individuals and organisations.Knowledge is context-speci®c,as it depends on a particular time and space.6 Without being put into a context,it is just information,not knowledge.For example,`1234ABC Street'is just information. Without context,it does not mean anything.However,when put into a context,it becomes knowledge:``My friend David lives at1234ABC Street,which is next to the library.''Knowl-edge is also humanistic,as it is essentially related to human action.Knowledge has the active and subjective nature rep-resented by such terms as`commitment'and`belief'that is dee-ply rooted in individuals'value rmation becomes knowledge when it is interpreted by individuals and given a context and anchored in the beliefs and commitments of indi-viduals.Hence,knowledge is relational:such things as`truth', `goodness'and`beauty'are in the eye of the beholder.As Alfred North Whitehead stated,``there are no whole truths;all truths are half-truths''.7In this study,we consider knowledge to be``a dynamic human process of justifying personal belief toward the`truth'''.8There are two types of knowledge:explicit knowledge and tacit knowledge.Explicit knowledge can be expressed in formal and systematic language and shared in the form of data,scien-ti®c formulae,speci®cations,manuals and such like.It can be processed,transmitted and stored relatively easily.In contrast, tacit knowledge is highly personal and hard to formalise.Sub-jective insights,intuitions and hunches fall into this category of knowledge.Tacit knowledge is deeply rooted in action,pro-cedures,routines,commitment,ideals,values and emotions.9It `indwells'in a comprehensive cognisance of the human mind and body.10It is dif®cult to communicate tacit knowledge to others,since it is an analogue process that requires a kind of `simultaneous processing'.the key in leading the knowledge-creating process is dialectical thinkingLong Range Planning,vol3320007Western epistemology has traditionally viewed knowledge as explicit.However,to understand the true nature of knowledge and knowledge creation,we need to recognise that tacit and explicit knowledge are complementary,and that both types of knowledge are essential to knowledge creation.Explicit knowl-edge without tacit insight quickly loses its meaning.Written speech is possible only after internal speech is well developed.11Knowledge is created through interactions between tacit and explicit knowledge,rather than from tacit or explicit knowledge alone.The knowledge-creating processKnowledge creation is a continuous,self-transcending process through which one transcends the boundary of the old self into a new self by acquiring a new context,a new view of the world,and new knowledge.In short,it is a journey ``from being to becoming''.12One also transcends the boundary between self and other,as knowledge is created through the interactions amongst individuals or between individuals and their environ-ment.In knowledge creation,micro and macro interact with each other,and changes occur at both the micro and the macro level:an individual (micro)in¯uences and is in¯uenced by the environment (macro)with which he or she interacts.To understand how organisations create knowledge dynami-cally,we propose a model of knowledge creation consisting of three elements:(i)the SECI process,the process of knowledge creation through conversion between tacit and explicit knowl-edge;(ii)ba ,the shared context for knowledge creation;and (iii)knowledge assetsÐthe inputs,outputs,and moderator of the knowledge-creating process.The three elements ofknowl-Figure 2.Three elements of the knowledge-creating process8SECI,Ba and Leadershipedge creation have to interact with each other to form the knowledge spiral that creates knowledge(see Figure2).In the following sections,we discuss each of these three elements.The SECI process:four modes of knowledge conversion An organisation creates knowledge through the interactions between explicit knowledge and tacit knowledge.We call the interaction between the two types of knowledge`knowledge conversion'.Through the conversion process,tacit and explicit knowledge expands in both quality and quantity.13There are four modes of knowledge conversion.They are:(1)socialisa-tion(from tacit knowledge to tacit knowledge);(2)externalisa-tion(from tacit knowledge to explicit knowledge);(3)combination(from explicit knowledge to explicit knowledge); and(4)internalisation(from explicit knowledge to tacit knowl-edge).SocialisationSocialisation is the process of converting new tacit knowledge through shared experiences.Since tacit knowledge is dif®cult to formalise and often time-and space-speci®c,tacit knowledge can be acquired only through shared experience,such as spend-ing time together or living in the same environment.Socialisa-tion typically occurs in a traditional apprenticeship,where apprentices learn the tacit knowledge needed in their craft through hands-on experience,rather than from written man-uals or textbooks.Socialisation may also occur in informal social meetings outside of the workplace,where tacit knowledge such as world views,mental models and mutual trust can be created and shared.socialisation also occurs beyond organis-ational boundaries.Firms often acquire and take advantage of the tacit knowledge embedded in customers or suppliers by interacting with them.ExternalisationExternalisation is the process of articulating tacit knowledge into explicit knowledge.When tacit knowledge is made explicit, knowledge is crystallised,thus allowing it to be shared by others,and it becomes the basis of new knowledge.Concept creation in new product development is an example of this conversion process.Another example is a quality control circle, which allows employees to make improvements on the manu-facturing process by articulating the tacit knowledge accumu-lated on the shop¯oor over years on the job.The successful conversion of tacit knowledge into explicit knowledge depends on the sequential use of metaphor,analogy and model. CombinationCombination is the process of converting explicit knowledge into more complex and systematic sets of explicit knowledge. Explicit knowledge is collected from inside or outside the or-ganisation and then combined,edited or processed to form When tacit knowledge is made explicit, knowledge is crystallisedLong Range Planning,vol3320009new knowledge.The new explicit knowledge is then dissemi-nated among the members of the organisation.Creative use ofcomputerised communication networks and large-scale data-bases can facilitate this mode of knowledge conversion.Whenthe comptroller of a company collects information fromthroughout the organisation and puts it together in a contextto make a®nancial report,that report is new knowledge in thesense that it synthesises knowledge from many different sourcesin one context.The combination mode of knowledge conver-sion can also include the`breakdown'of concepts.Breakingdown a concept such as a corporate vision into operationalisedbusiness or product concepts also creates systemic,explicitknowledge.InternalisationInternalisation is the process of embodying explicit knowledgeinto tacit knowledge.Through internalisation,explicit knowl-edge created is shared throughout an organisation and con-verted into tacit knowledge by individuals.Internalisation isclosely related to`learning by doing'.Explicit knowledge,suchas the product concepts or the manufacturing procedures,hasto be actualised through action and practice.For example,training programmes can help trainees to understand an organ-isation and themselves.By reading documents or manualsabout their jobs and the organisation,and by re¯ecting uponthem,trainees can internalise the explicit knowledge written insuch documents to enrich their tacit knowledge base.Explicitknowledge can be also embodied through simulations or exper-iments that trigger learning by doing.When knowledge is internalised to become part of individ-uals'tacit knowledge bases in the form of shared mentalmodels or technical know-how,it becomes a valuable asset.This tacit knowledge accumulated at the individual level canthen set off a new spiral of knowledge creation when it isshared with others through socialisation.The following list summarises the factors that characterisethe four knowledge conversion modes.Factors that constitute the knowledge-conversion process14.Socialisation:from tacit to tacit*Tacit knowledge accumulation:managers gather infor-mation from sales and production sites,share experienceswith suppliers and customers and engage in dialogue withcompetitors.*Extra-®rm social information collection(wandering out-side):managers engage in bodily experience through man-agement by wandering about,and get ideas for corporatestrategy from daily social life,interaction with externalexperts and informal meetings with competitors outsidethe®rm.10SECI,Ba and Leadership*Intra-®rm social information collection(wanderinginside):managers®nd new strategies and market opportu-nities by wandering inside the®rm.*Transfer of tacit knowledge:managers create a work en-vironment that allows peers to understand craftsmanshipand expertise through practice and demonstrations by amaster..externalisation:from tacit to explicit*Managers facilitate creative and essential dialogue,the useof`abductive thinking',the use of metaphors in dialoguefor concept creation,and the involvement of the industrialdesigners in project teams..Combination:from explicit to explicit*Acquisition and integration:managers are engaged inplanning strategies and operations,assembling internaland external data by using published literature,computersimulation and forecasting.*Synthesis and processing:managers build and create man-uals,documents and databases on products and servicesand build up material by gathering management®gures ortechnical information from all over the company.*Dissemination:managers engage in the planning and im-plementation of presentations to transmit newly createdconcepts..Internalisation:from explicit to tacit*Personal experience;real world knowledge acquisition:managers engage in`enactive liasing'activities with func-tional departments through cross-functional developmentteams and overlapping product development.They searchfor and share new values and thoughts,and share and tryto understand management visions and values throughcommunications with fellow members of the organisation.*Simulation and experimentation;virtual world knowledgeacquisition:managers engage in facilitating prototypingand benchmarking and facilitate a challenging spirit withinthe organisation.Managers form teams as a model andconduct experiments and share results with the entiredepartment.As stated above,knowledge creation is a continuous processof dynamic interactions between tacit and explicit knowledge.Long Range Planning,vol33200011Such interactions are shaped by shifts between different modes of knowledge conversion,not just through one mode of inter-action.Knowledge created through each of the four modes of knowledge conversion interacts in the spiral of knowledge cre-ation.Figure 3shows the four modes of knowledge conversion and the evolving spiral movement of knowledge through the SECI (Socialisation,Externalisation,Combination,Internalis-ation)process.It is important to note that the movement through the four modes of knowledge conversion forms a spiral ,not a circle.In the spiral of knowledge creation,the interaction between tacit and explicit knowledge is ampli®ed through the four modes of knowledge conversion.The spiral becomes larger in scale as it moves up through the ontological levels.Knowledge created through the SECI process can trigger a new spiral of knowledge creation,expanding horizontally and vertically across organis-ations.It is a dynamic process,starting at the individual level and expanding as it moves through communities of interaction that transcend sectional,departmental,divisional and even or-ganisational anisational knowledge creation is a never-ending process that upgrades itself continuously.This interactive spiral process takes place both intra-and inter-organisationally.Knowledge is transferred beyond organis-ational boundaries,and knowledge from different organisations interacts to create new knowledge.15Through dynamic inter-action,knowledge created by the organisation can trigger the mobilisation of knowledge held by outside constituents such as consumers,af®liated companies,universities or distributors.For example,an innovative new manufacturing process may bring about changes in the suppliers'manufacturing process,which in turn triggers a new round of product and process in-novation at the organisation.Another example is the articula-tion of tacit knowledge possessed by customers that they themselves have not been able to articulate.A product worksas Figure 3.The SECI process 12SECI,Ba and Leadershipthe trigger to elicit tacit knowledge when customers give mean-ing to the product by purchasing,adapting,using,or not pur-chasing it.Their actions are then re¯ected in the innovation process of the organisation,and a new spiral of organisational knowledge creation starts again.Figure 4shows how the organ-isation interacts with outside constituents to create knowledge.It should be also noted that knowledge creation is a self-transcending process,in which one reaches out beyond the boundaries of one's own existence.16In knowledge creation,one transcends the boundary between self and other,inside and outside,past and present.In socialisation,self-transcendence is fundamental because tacit knowledge can only be shared through direct experiences which go beyond individuals.17For example,in the socialisation process people empathise with their colleagues and customers,which diminishes barriers between individuals.In externalisation,an individual transcends the inner-and outer-boundaries of the self by committing to the group and becoming one with the group.Here,the sum of the individuals'intentions and ideas fuse and become inte-grated with the group's mental world.In combination,new knowledge generated through externalisation transcends the group in analogue or digital signals.In internalisation,individ-uals access the knowledge realm of the group and the entire or-ganisation.This again requires self-transcendence,as one has to ®nd oneself in a larger entity.Ba :shared context in motion for knowledge creation Knowledge needs a context to be created.Contrary to the Car-tesian view of knowledge,which emphasises the absoluteand Figure 4.Creating knowledge with outside constituentsLong Range Planning,vol 33200013context-free nature of knowledge,the knowledge-creating pro-cess is necessarily context-speci®c in terms of who participates and how they participate.Knowledge needs a physical context to be created:``there is no creation without place''.18`Ba '(which roughly means `place')offers such a context.Based on a concept that was originally proposed by the Japanese philoso-pher Kitaro Nishida 19and was further developed by Shimizu,20ba is here de®ned as a shared context in which knowledge is shared,created and utilised.In knowledge creation,generation and regeneration of ba is the key,as ba provides the energy,quality and place to perform the individual conversions and to move along the knowledge spiral.21In knowledge creation,one cannot be free from context.Social,cultural and historical contexts are important for indi-viduals,11as such contexts provide the basis for one to interpret information to create meanings.As Friedrich Nietzsche argued,``there are no facts,only interpretations''.Ba is a place where information is interpreted to become knowledge.Ba does not necessarily mean a physical space.The Japanese word `ba 'means not just a physical space,but a speci®c time and space.Ba is a time±space nexus,or as Heidegger expressed it,a locationality that simultaneously includes space and time.It is a concept that uni®es physical space such as an of®ce space,virtual space such as e-mail,and mental space such as shared ideals.The key concept in understanding ba is `interaction'.Some of the research on knowledge creation focuses mainly on indi-viduals,based on the assumption that individuals are the pri-mary driving forces of creation.For example,quoting Simon's ``All learning takes place inside individual human heads'',Grant claims that knowledge creation is an individual activity and that the primary role of ®rms is to apply existing knowl-edge.22However,such an argument is based on a view of knowledge and human beings as static and inhuman.As stated above,knowledge creation is a dynamic human processthat Figure 5.Ba as shared context in motion 14SECI,Ba and Leadershiptranscends existing boundaries.Knowledge is created through the interactions amongst individuals or between individuals and their environments,rather than by an individual operating alone.Ba is the context shared by those who interact with each other,and through such interactions,those who participate in ba and the context itself evolve through self-transcendence to create knowledge(see Figure5).Participants of ba cannot be mere onlookers.Instead,they are committed to ba through action and interaction.Ba has a complex and ever-changing nature.Ba sets a boundary for interactions amongst individuals,and yet its boundary is open.As there are endless possibilities to one's own contexts,a certain boundary is required for a meaningfulshared context to emerge.Yet ba is still an open place where participants with their own contexts can come and go,and the shared context(ba)can continuously evolve.By providing a shared context in motion,ba sets binding conditions for the participants by limiting the way in which the participants view the world.And yet it provides participants with higher view-points than their own.Ba lets participants share time and space,and yet it trans-cends time and space.In knowledge creation,especially in socialisation and externalisation,it is important for participants to share time and space.A close physical interaction is import-ant in sharing the context and forming a common language among participants.Also,since knowledge is intangible, unbounded and dynamic and cannot be stocked,ba works as the platform of knowledge creation by collecting the applied knowledge of the area into a certain time and space and inte-grating it.However,as ba can be a mental or virtual place as well as a physical place,it does not have to be bound to a cer-tain space and time.The concept of ba seemingly has some similarities to the concept of`communities of practice'.23Based on the appren-ticeship model,the concept of communities of practice argues that members of a community learn through participating in the community of practice and gradually memorising jobs. However,there are important differences between the concepts of communities of practice and ba.While a community of practice is a living place where the members learn knowledge that is embedded in the community,ba is a living place where new knowledge is created.While learning occurs in any com-munity of practice,ba needs energy to become an active ba where knowledge is created.The boundary of a community of practice is®rmly set by the task,culture and history of the community.Consistency and continuity are important for a community of practice,as it needs an identity.In contrast,the boundary of ba is¯uid and can be changed quickly as it is set by the participants.Instead of being constrained by history,ba has a`here and now'quality.It is constantly moving;it is cre-ated,functions and disappears according to need.Ba constantly changes,as the contexts of participants or the membership of ba has a`here and now'qualityba change.In a community of practice,changes mainly take place at the micro (individual)level,as new participants learn to be full participants.In ba ,changes take place at both the micro and the macro level,as participants change both them-selves and ba itself.While the membership of a community of practice is fairly stable,and it takes time for a new participant to learn about the community to become a full participant,the membership of ba is not ®xed;participants come and go.Whereas members of a community of practice belong to the community,participants of ba relate to the ba .There are four types of ba :that is,originating ba ,dialoguing ba ,systemising ba and exercising ba ,which are de®ned by two dimensions of interactions (see Figure 6).One dimension is the type of interaction,that is,whether the interaction takes place individually or collectively.The other dimension is the media used in such interactions,that is,whether the interaction is through face-to-face contact or virtual media such as books,manuals,memos,e-mails or teleconferences.Each ba offers a context for a speci®c step in the knowledge-creating process,though the respective relationships between each single ba and conversion modes are by no means exclusive.Building,main-taining and utilising ba is important to facilitate organisational knowledge creation.Hence,one has to understand the different characteristics of ba and how they interact with each other.The following sections describe the characteristics of each ba .Originating ba Originating ba is de®ned by individual and face-to-face inter-actions.It is a place where individuals share experiences,feel-ings,emotions and mental models.It mainly offers a context for socialisation,since an individual face-to-face interaction is the only way to capture the full range of physical senses and psycho-emotional reactions,such as ease or discomfort,which are important elements in sharing tacit knowledge.Originating ba is an existential place in the sense that it is the world where an individual transcends the boundary between self and others,by sympathising or empathising with others.Fromoriginating Figure 6.Four types of ba。
解构知识管理
解构知识管理开篇治理大年夜师德鲁克认为："２１世纪的组织，最有价值的资产是组织内的常识工作者和他们的临盆力。
" 在现今的信息时代里，常识已成为最重要的财宝来源，而常识工作者确实是最有生命力的资产，组织和小我的最重要义务将是对常识进行治理。
经由一段时刻的进修，本人整顿出一些关于常识治理的脉络，欲望能和存眷常识治理的同伙共享。
什么是常识常识是用于临盆的信息（有意义的信息）。
－－1998年，世界银行《1998年世界成长申报－常识促进成长》常识的分类隐性常识(Tacit Knowledge)是高度个性化同时难于格局化的常识，主不雅的明白得、直觉和预感都属于这一类。
显性常识(Explicit Knowledge)是能用文字和数字表达出来，轻易以硬数据的情势交换和共享，比如编辑整顿的法度榜样或者广泛原则。
常识的转换隐性常识转换为显性常识小我常识转换为组织常识常识在哪里此主题相干图片如下：什么是常识治理APCQ（美国临盆力和质量中间）对常识治理的定义是：常识治理应当是组织一种有意识采取的计策，它包管能够或许在最须要的时刻将最须要的常识传送给最须要的人。
如许能够赞助人们共享信息，并进而将之经由过程不合的方法付诸实践，最终达到进步组织事迹的目标。
斯威比（Karl E. Sveiby）从熟悉论的角度对常识治理的定义是：常识治理是应用组织的无形资产制造价值的艺术。
常识治理的来源斯威比（Karl E. Sveiby)博士，于1986年用瑞典文出版了《常识型企业》，使他成为常识治理理论与实践的"瑞典活动"的思惟源泉。
1987年，他和英国常识治理专家汤姆·劳埃德合著出版了《常识型企业的治理》一书，提出一整套常识型企业治理理论和有用方法，成为常识型企业治理的开山之作。
1990年，斯威比出版了《常识治理》一书，是世界上第一部以"常识治理"为题的著作。
什么缘故须要常识治理常识成为最重要的财宝来源形成竞争优势须要常识治理企业的可连续成长须要常识治理优化企业经营须要常识治理信息技巧的成长催生常识治理常识治理的构成元素此主题相干图片如下：常识治理的架构此主题相干图片如下：常识治理的计策把常识治理作为组织经营计策常识转移和最优实践活动以客户为重点的常识计策建立组织成员对常识的义务感无形资产治理计策技巧立异和常识制造计策材料来源：美国临盆力与质量研究中间常识治理的流程此主题相干图片如下：常识治理体系的构造层次此主题相干图片如下：常识治理体系的技巧要素一个完美的常识治理体系应当具备以下七种技巧要素：门户技巧搜刮引擎动技巧协作技巧E-Learning技巧贸易智能技巧内容治理技巧集成技巧常识治理的重要技巧此主题相干图片如下：常识过程图定义：常识过程图(Knowledge Storyboard)，是指在企业的营业轮回中，支撑流程所需的常识以及介入个中的人的图表。
人力资源开发teamwork英文正稿
1.1Compare different learning stylesKolb recognized that people tend to have a preference for a particular phase of the cycle, which he identified as a preferred learning style.Honey and Mumford also noted that ‘people vary not just in their learning skills but also in their learning styles. Why otherwise might two people, matched for age, intelligence and need, exposed to the same learning opportunity, react so differently?’Honey and Mumford formulated a popular classification of learning styles in terms of the attitudes and behaviours which determine an individual’s preferred way of learning.Learning styles are different ways that a person can learn. It's commonly believed that most people favor some particular method of interacting with, taking in, and processing stimuli or information. Psychologists have proposed several complementary taxonomies of learning styles. But other psychologists and neuroscientists have questioned the scientific basis for some learning style theories. A major report published in 2004 cast doubt on most of the main tests used to identify an individual's learning style.ActivistActivists involve themselves fully in new experiences. They are open-minded and enthusiastic about new things – but easily bored by long-term implementation and consolidation: act first and think about consequences later. They prefer to tackle problems by brainstorming. They easily get involved with others – but tend to centre activities on themselves.ReflectorReflectors like to stand back to observe and ponder new experiences, preferring to consider all angles and implications, and to analyse all available data, before reaching any conclusions or making any moves. When they do act, it is from awareness of the big picture. They tend to adopt a low profile, taking a back seat in meeting and discussions – though listening and observing others carefully and tend to have a slightly distant, tolerant, unruffled air.TheoristsTheorists are keen on basic assumptions, principles, theories, models and systems thinking. They are detached and analytical and like to analyse and synthesise facts and observations into coherent theories. They think problems through systematically and logically. They are interested in maximizing certainty, and so tend to be rigidly perfectionist and uncomfortable with subjectivity, ambiguity, lateral thinking and flippancy.PragmatistReflectors are eager to try out ideas, theories and technique to see if they work in practice. They like to get on with things, acting quickly and confidently on ideas that attract them-and tending to be impatient with ruminating and open-ended discussion. They are down to earth: enjoying practical decisions and responding to problems and opportunities ‘as a challenge’.Hang and Li Xiaochun are activists. Fan Jiaxin is theorist. Today our team will take reflector as an example and make some sample analysis.Reflectors like back then reflect on experience and examine them from different angles. They like to collect data, both their own data and the data obtained from others. They like to fully consider before make any conclusion.Taking our team member Lu Chen as an example, when she completed teamwork. Lu Chen is a reflector. When the team members are talking about how to finish the team work, she will not be particularly intense in group discussion. She will be quietly thinking and analysis topic in this time. After thinking and listened to the team members’ideas, she can consider put forward a perfect answer. Usually, this answer will be accepted by team members. This is the advantage of learning style. But it also has disadvantage. For example, in class, the teacher asks Lu Chen a question suddenly. Under the condition of no advance preparation, she will be nervous and incoherent.As a result, we've come to the conclusion that reflectors learning the best and the worst situation.Following activities are the best situations for reflectors:●Require or encourage them to observe and think of these activities●They listen and watch team work in the event. Sitting back in a meeting or at themovies●Allow them to have time to prepare before taking any action●They can hard study to find out the truth●they can make a decision under the condition of no pressure and no timelimitationFollowing activities are the worst situations for reflectors:●They were forced to be leadership or president●They involved in some situation need action without plan●Let them to react immediately and produce spontaneous ideas●Complete event under time constraints or pressure●Provided data is not enough to support the conclusion1.2 Explain the role of the learning curve and the importance of transferring learning to the workplaceThe role of the learning curveA learning curve is a graph showing the relationship between the time spent in learning and the level of competence attained. Hence, it describes the progress and variable pace of learning. It is common for people to say that they are on a steep learning curve when they have to acquire a lot of new knowledge or skills in a short period of time.The learning curve may be used in three ways:●To suggest typical patterns in the acquisition of a given skill or type of skill: thepace of skill acquisition, the standard at which performance levels out; the point at which performance plateaus.●To illustrate the progress of a given trainee’s learning/proficiency during thetraining progress, in order to monitor the progress and pace of training and to make allowances for different rates of learning and the steepness of the curve where necessary.●To plan the size of the chunks to be taught in one serving or stage of learning, thelength of practice periods before moving to the next stage and so on.A standard learning curve is initially steep, levelling out towards proficiency. However, in practice this will depend on the design of the learning program and the motivation and aptitude of the learner. The curve for the acquisition of skills typically shows one or more plateaus, reflecting the trainee’s need to consolidate wha t he has learned so far, to correct some aspects of performance to regain motivation and focus after the initial effort, or to establish habitual or unconscious competence in one skill prior to moving on to a new area. Momentum then gathers again, until the trainee reaches proficiency level, where the curve will level off unless there is an injection of new equipment or methods, or fresh motivation, to lift output again.Here is the learning curve:Level ofProficiencyLearning timeAs you can see, the chart is steepest at the beginning, when a person first starts learning. The beginner gains knowledge quickly, learning in just a few minutes. There is more to learn, but he will never learn as quickly as she did at the beginning of her lesson.It is known to all that learning curves can be quite complex, going down as well as up: for example, if the trainee is unable to practice or apply newly acquired skills and forgets, or refuses to accept new areas of conscious incompetence which emerge in the course of training. An up-and-down transition curve is common in cases where an individual changes jobs or work methods, or makes the transition from a non-managerial to a managerial position.the importance of transferring learning to the workplace：In my opinion, learning plays very important role in workplace. In the following text, I will discuss the importance of transferring learning to the workplace from 2 terms.Firstly, the importance for ourselves.Learning is the ladder of human progress. In the school, the knowledge we learn not only includes the knowledge in books, but also includes the following 4 aspects:1.Learning to survive. We need to learn to developing after surviving, survival and development, and striving for survival and development.2.Learning to communicate. We need to learn to adapt to the complex relationships.3.Learning to learn. We need to learn to master the art of learning.4.Learning skills.Only making the above 4 aspects achieving mastery through a comprehensive can we enter the society and our jobs with confidence.Secondly, the importance for enterprises.T he development of human is the strong power for enterprises’ development, and the most important power source of the development of human is learning. Only through learning and applying knowledge and skills got by learning to the development of the enterprise can make an enterprise get substantial progress and development. For example, high school teachers may improve their teaching ability by listening to other outstanding teachers' classes and learning the way of teaching. Again, for example, the mechanics may try to complete their work more efficiently through apprenticing other richly experienced old mechanics and learning their methods.In an enterprise, there will always have some people who prefer learning, and there also have some people who do not prefer learning. The development of the enterprise depends on those who prefer learning. When the development of the enterprise can't keep up with the development of people who prefer learning, these people might leave. And, in turn, those who can't keep up with the development of the enterprise will eventually be eliminated by enterprise. An individual's own development depends largely on whether it is interested in the industry because onlywhen it is interested in this work, it would find pleasure in work and find its insufficient in work that let it try to learn together way. When all become a virtuous cycle, work and life will be full of fun. In one word, learning is also a driving force for the development of the society.1.3Assess the contribution of learning styles and theories when planning anddesigning a learning eventMost people will clearly have a strong preference for a given learning style. The ability to switch between different styles is not one that we should assume comes easily or natural to many people.People who have a clear learning style preference will tend to learn more effectively if learning is orientated according to their preference. For example, assimilators will not be comfortable being thrown in at the deep end without notes and instructions, accommodators are likely to become frustrated if they are forced to read lots of instructions and rules and are unable to get hands-on experience as soon as possible. Tension can develop where there are differences in learning style between educators and students.Where possible it is helpful if workplace educators can identify the students learning style and provide opportunities that work to their strength, however the aim for the students is to engage in learning across different learning styles and develop abilities across a range of techniques rather than just their preferred styles.Students need to be able to adapt to the presenting situation, and develop their preferred as well as non-preferred learning styles.Learning StyleUnderstanding the way that you learn, your learning style, will help you select your learning activities to ensure you learn most effectively. This does not mean that you cannot learn from activities that are not specifically suited to your own style, in fact selecting activities outside your normal style will help you develop your learning skills.Educational ImplicationsBoth Kolb's learning stages and cycle could be used by teachers to critically evaluate the learning provision typically available to students, and to develop more appropriate learning opportunities.Educators should ensure that activities are designed and carried out in ways that offer each learner the chance to engage in the manner that suits them best. Also, individuals can be helped to learn more effectively by the identification of their lesser preferred learning styles and the strengthening of these through the application of the experiential learning cycle.Ideally, activities and material should be developed in ways that draw on abilities from each stage of the experiential learning cycle and take the students through the whole process in sequence.It is not possible to put forward a simple definition of learning, because dispite intensive scientific and practical work on the subject, there are different ways ofunderstanding how the process works, what it involves, and what we mean when we say that a person knows something. Whichever approach it is based on, learning theory offers certain useful propositions foe the design of effective training programmers.There are three basic theories how learning works. One of the basic theories is that The behaviourist ( or stimulus-response):The behaviourist (our stimulus-response) approach. Behaviourist psychology is based on empirical epistemology (the belief that the human mind operates purelyon infomation gained from the senses by experiences and concentrates on observable behaviour,since thought processes are neccery amenable to scientific study.Such as:(1) the individual should be motivated to learn. The purpose and benefits of a learning activity should be made clear, according to the individual's motives or goals: reward, challenge, competence or whatever. Organisational support is critical to the effectiveness of its member’s learning(2) clear goals and objectives should be set, so that each task has some meaning. This will help trainees in the control process that leads to learning, providing targets against which performance will constantly be measured and agjusted. Motivation to learn will be enhanced if the individual has been involved in setting his or her own learning goals.(3) learning should be structured and paced to allow learning processes to take place effectively and progressively. Each stage of learning should present a challene , without overloading trainees so that they lose confidence and the ability to assimilate information.(4) exposure to learning materials and interactive input(from learning software and /or from coaches or facilitatoes)enriches the cognitive process and encourages the internalisation of learning. Case-studies, probelm solving exercises and so on engage the purposive process of learning.(5) there should be timely, relevant feedback on performance and progress(6) positive and negative reinforcement should be judiciously used(7) active participation in the learning experience(for example, in action learning or discovery learning)is generally more effective than passive reception.1.1written by Luchen and Fanjiaxin1.2written by Qiaofei and Huating1.3written by Lixiaochun and Wenghang。
Lecture3： Professional Identities
Reflecting on Personality:
Researchers largely agree that there are five core traits that
interact to form human personality, now known commonly as ‘The Big Five’ (McCrae and Costa 1987; 1997). Although there is some disagreement on what these factors should be called, the most commonly used terms are: Extraversion Neuroticism Conscientiousness Openness Agreeableness
Ibarra argues that an understanding of one’s own professional identity is important because it defines how we see ourselves and how others perceive us within our professional role. Any incongruence between what the role demands and what we see as our (professional) identity can lead to problems with fulfilling that role.
Professional identity has been defined by Schein (1978) as: ‘The relatively stable and enduring constellation of attributes, beliefs, values, motives and experiences in terms of which people define themselves in a professional role’
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Bridging Individual and Organisational Knowledge:The Appeal to Tacit Knowledgein Knowledge Management Theory
Christiaan MAASDORPDepartment of Information ScienceStellenbosch University, South Africachm2@sun.ac.za
Abstract:This paper is a contribution to conceptual clarity with respect to KnowledgeManagement theory. It provides a conceptual analysis of aspects of the notion oftacit knowledge. The analysis consists of positioning the notion of tacitknowledge in two frameworks - conceptual and contextual. The appeal to tacitknowledge as a basis for a Knowledge Management epistemology is reviewed inthe conceptual framework. Positioning the notion in the contextual framework,the appeal to tacit knowledge as a link between individual and organisationalknowledge is analysed. The paper suggests that the contextual framework shouldtake preference, and concludes that the notion of tacit knowledge offers aconceptual tool that bridges individual and organisational knowledge. For thisreason the notion has continued currency, despite its limitations as anepistemological basis for Knowledge Management.
1. The Double Bind for KM theory: Conceptual and Contextual.The paper starts from the assumption that Knowledge Management theory is in a double bind. Onthe one hand, it faces a conceptual problem related to the slippery nature of the concept ofknowledge. On the other hand, it faces a contextual problem related to the phenomenon oforganisation - the context in which that knowledge is made productive through knowledgemanagement practices. This presents Knowledge Management theory with two issues: firstly, thelack of a coherent theory of knowledge in Knowledge Management (because of the shifting natureof the concept knowledge); secondly, problematic levels of analysis for Knowledge Managementtheories (because of the tension between individual and organisational knowledges).
Many writers have turned to the distinction between tacit/explicit knowledge to serve as the basisfor a Knowledge Management epistemology. However, this turn towards the tacit dimension isconsidered by many to be problematic. Objections range from noting that the concept is often ill-applied, that it does not consider the very particular context in which the concept was originallyused and consequently, that the full implications of the concept is rarely properly integrated into aKnowledge Management framework1; to reservations about the use of a subjective conception ofknowledge in Knowledge Management2. Hence, the usefulness of the concept has to be questioned.
The paper will focus on the underlying reasons for the appeal to the notion of tacit knowledge inKnowledge Management theory. In particular my question is: assuming that the objections to theusefulness of the notion of tacit knowledge for a Knowledge Management epistemology carry someweight, can a rationale be advanced for its continued usefulness? It seems to me that the answer tothis question is a prerequisite for a more coherent Knowledge Management epistemology.
The paper has several limitations. Firstly, the aim is not to offer an improved, coherent theory ofknowledge for Knowledge Management. Secondly, no attempt will be made to provide anexhaustive overview of the use of the tacit/explicit dichotomy in Knowledge Managementliterature. Thirdly, the reinterpretation of tacit knowledge will not be evaluated in terms of theextent to which it takes the implications and intention of the concept into account3. Lastly, theconcept of tacit knowledge will not be analysed in full either. Familiarity with the basic ideasunderpinning the distinction between tacit and explicit knowledge will largely be assumed.Therefore, questions concerning the difference, relation between and structure of tacit and explicitknowledge will not be central to this paper.
Instead, the reasons for the appeal to tacit knowledge will be dealt with by positioning it in twoframeworks: The first part positions the question within the framework of the (traditional) theory ofknowledge discourse – that is the conceptual implications of the notion of tacit knowledge. Thesecond part positions the question within a levels of analysis framework4 – thus as a contextualissue.
1 Brohm (1999); Kinghorn & Maasdorp (1999)
2 Schreinemakers & Essers (1997); Stewart (1997)
3 The shortcomings of current use of the concept of tacit knowledge in Knowledge Management literature have already