Social Responsibility and Business Ethics Assignment

Social Responsibility and Business Ethics - Assignment Example Being the owner of a manufacturing company which is involved in the business of producing goods and selling it in the market, the primary goal or objective of the company is to earn profits out of the products sold. However, social responsibility and business ethics are two vital tasks which have to be undergone by the company to create a perfect balance between the profit making motive and being a good corporate citizen. Critical analysis of these two aspects has been discussed in this study. CSR can be defined as the means operating a business by an organization which meets or even exceeds the legal, ethical, public and commercial expectations which the society has from the organization. According to the requirements of CSR, every company is needed to have some obligations towards its society and environment at large (Kotler, & Lee, 2008, p.3). CSR serves several purposes. It helps to ensure that the business processes are conducted by the organizations in an ethical way in accordance with the interests of the community. It helps in responding in a positive way towards the emerging priorities in the society. It serves for the purpose of developing willingness amongst the organizations to act beyond the regulatory confrontation. It also helps in maintaining a balance between interests of the shareholders of the company and the wider community. CSR helps in the development of the corporate organizations into good corporate citizens in the society. Social responsibility of the corporate organizations can be considered to have four dimensions. One is the economic perspective which is the responsibility of the organizations to earn profits and generate wealth for the owners of the company. Legal is another aspect of CSR which implies that all the business organizations have the responsibility to act in accordance with the existing laws and are to comply with those laws.  

Psychiatric Disorders, Diseases, and Drugs Essay Example for Free

Psychiatric Disorders, Diseases, and Drugs Essay There are five main psychiatric disorders and they are schizophrenia, depression, mania, anxiety disorders, and Tourette syndrome. Psychiatric disorders are â€Å"disorders of psychological function sufficiently sever to require treatment† Pinel, J. P. J. (2011). The main fact about these psychiatric disorders is that they are difficult to diagnose. They use the DSM-IV-TR to diagnose patients that is the Diagnostic and Statistical Manual of the American Psychiatric Association. The first psychiatric disorder is Schizophrenia, this disorder is â€Å"the splitting of psychic functions† Pinel, J. P. J. (2011). This is a disease that breaks down the emotion, thought, and action, which is chaos or madness. Schizophrenia is divided into five different categories and they are disorganized, paranoid, residual, and undifferentiated. Each of these have their own set of symptoms, but schizophrenia affects a person’s behavior, logic, and emotions. There is positive symptoms and negative symptoms of schizophrenia. The positive symptoms are delusions, hallucinations, inappropriate affect, incoherent speech or thought, and odd behavior. The negative symptoms are affective flattening, alogia, avolition, and anhedonia. There was a neurodevelopmental theory of schizophrenia during the 20th-century two famines a Dutch and a Chinese famine had mother who were diagnosed with schizophrenia and these two by adults would most likely have it as well. The first antischizophrenic drug was chlorpromazine. This drug helps agitated patients and the severity of schizophrenic symptoms. Later reserpine was given, which is an active ingredient of the snakeroot plant. This was given to patients with schizophrenia, but was taken off for treatment because it caused a huge incline in blood pressure that could be fatal. Through these two together, the discovery of Parkinson’s disease came about. The dopamine theory of schizophrenia is caused† by too much dopamine and, conversely, that antischizophrenic drug exert their effects by  decreasing dopamine levels Pinel, J. P. J. (2011). People who suffer from schizophrenia have a decent amount of brain damage. The next ones are affective disorders, which include depression and mania. Everyone has depression at one time or another and it becomes stressful to you, your body, and even people around you. There is anhedonia â€Å"loss of the capacity to experience pleasure† Pinel, J. P. J. (2011). This is people who fall into despair for no apparent reasons, it just happens. When this happens, it causes them to slowly slip away from life and their normal daily routines and can be quite deadly to them if they fall too much. If this happens for more than two weeks then they might diagnose them with clinical depression, or major depressive disorder. The second affective disorder is mania, which is almost the total opposite of depression. Mania is â€Å"characterized by overconfidence, impulsivity, distractibility, and high energy. Depression and Mania are also under mood swings category. People who show mild mania might be talkative, energetic, impulsive, positive, and extremely confident. At this point, in a person’s mania they can do there day to day activities nicely but when it becomes extreme it can become a huge problem for them and possibly others around them. If there, mania becomes too extreme they will feel like nothing can stop them and it can get in the way of the many things that they are achieving in their lives. For people who are depressive they might experience episodes of mania and if they do experience mania they are known to suffer from bipolar affective disorder. The ones who do not suffer from mania are under unipolar affective disorder. Depression is under two categories and these are negative experience (reactive depression) and depression for no apparent reason (endogenous depression). Four main drugs are treatment for affective disorders and these are monoamine oxidase inhibitors, tricyclic antidepressants, selective monoamine reuptake inhibitors, and mood stabilizers. MAO inhibitors have several side effects and the most dangerous is called the cheese effect. Cheese, wine, and pickles all contain what they call tyramine and it causes high blood pressure when mixed with the MAO inhibitors. Tricyclic antidepressants don’t cause any major side effects and is safer compare to MAO inhibitors. SSRIs and Prozac don’t have many side effects and they help with other psychological disorders other than just  depression. They help with lack of self-esteem, fear of failure, excessive sensitivity to criticism, and inability to experience pleasure. They even help with the rates of suicides. The last one is mood stabilizers, which are antidepressant drugs, and they act against depression without increasing mania, or they act against mania without increasing depression (Bourin Prica, 2007). Mood stabilizers are very effective and help with epilepsy. Lithium is what calms a patient in the mood stabilizers, but they cause extreme nausea as well or major sickness. All in all the best treatment for depression is lamotigine, and the best for treating mania is lithium and carbamazepine. Monoamine theory of depression â€Å"holds that depression is associated with underactivity at serotonergic and noradrenergic synapses† Pinel, J. P. J. (2011). A nice remedy or alternative for coping with depression and is trying to stay motivated and exercise. Light exercises can help keep you calm and get used to your life again and keep you healthy after all the stress you have been put through already from all the stress. This helps because you release feel good brain chemicals, rude immune system chemicals, increase body temperature, gain confidence, takes your mind off worries, and cope in a healthy way (Mayo Clinic, 2013). Anxiety disorders relate to stress a lot. Anxiety disorders that are severe in patients make it hard to cope with day-to-day activities and they can’t function normally. People who have this have feelings of anxiety, which might include fear, worry, and despondency. When they get these type of symptoms it can lead to rapid heartbeat, high blood pressure, nausea, breathing difficulty, sleep disturbances, and high glucocorticoid levels. There is five classes of anxiety disorders and they are generalized anxiety disorders, phobic anxiety disorders, panic disorders, obsessive-compulsive disorders, and posttraumatic stress disorders. There are three types of treatments for these disorders and they are benzodiazepines, serotonin agonists, and antidepressants. Benzodiazepines, which are Librium and valium, are the usual medicines prescribed for treatment and they help as sleep aids, anti convulsants, and muscle relaxants. The side effects include sedation, ataxia, tremor, nausea, and a withdrawal reaction, which causes rebound anxiety. These drugs are also very addictive and sold illegally if not prescribed to the right people who really need them for short periods.  Serotonin agonists buspirone is used a decent amount in the treatment for anxiety disorders. This drug helps with producing anxiolytic, which is anti-anxiety, and it helps by not producing ataxia, muscle relaxation, and sedation. The side effects that it does cause are nausea, headache, and insomnia. Tourette syndrome is the last one to talk about, it is a psychiatric disorder, and its different from the other three already discussed which include schizophrenia, affective disorders, and anxiety. The main symptom of Tourette’s is the tics. Tourette syndrome is a disorder in which they call the tics, which is involuntary, repetitive, stereotyped movements or vocalizations. This disorder happens in younger people or young adults. Sudden jerks and eye movements are usually the first signs and eventually it worsens, as they get older. The common complex motor tics include hitting, touching objects, squatting, and hopping, twirling, and sometimes-lewd gestures. The common verbal tics include inarticulate sounds such as barking, coughing, grunting, uttering obscenities, repetition of another’s words, and the repetition of one’s own words. People with this disorder can live normal lives if they have supportive and understanding people around them. It can get in the way of making friends and even getting a job if people don’t understand their condition. The first of the treatments for this disorder is family, friends, the patient, and teachers be educated on the condition. The second part of the treatment is finding out the emotional problems such as anxiety or depression, after this the treatment will be taken for the patient symptoms. One treatment is neuroleptics, which reduce tics by about 70% if the patient can be given the drug. The side effects are weight gain, fatigue, and dry mouth. Comprehensive behavioral intervention for Tics (CBIT) is something that is new and it’s a behavioral therapy for TS and chronic tic disorders. This includes habit reversal and other strategies, which include education about tics and relaxation techniques. This is a very effective program that starts when the child is young and even adults and they try to find better ways for the kids and adults to fit in, in any type of situation including in school and jobs (Centers for Disease Control and Prevention , 2013). References: Centers for Disease Control and Prevention . (2013). Tourette Syndrome (TS). Retrieved from http://www.cdc.gov/ncbddd/tourette/treatments.html Mayo Clinic. (2013). Depression (major depression). Retrieved from http://www.mayoclinic.com/health/depression-and-exercise/MH00043 Pinel, J. P. J. (2011). Biopsychology (8th ed.). Boston, MA: Pearson.

Effort Estimation Model

Effort Estimation Model Effort Estimation Model for each Phase of Software Development Life Cycle Information Technology Abstract Assessment of main risks of software development discloses that major threat of delays are caused by poor effort / cost estimation of the project. Low / poor cost estimation is the second highest priority risk [1]. This risk can affect four out of total five phases of software development life cycle i.e. Analysis, Design, Coding and Testing. Hence targeting this risk alone may reduce the over all risk impact of the project by fifty percent. Architectural designing of the system is great activity which consumes most of the time in SDLC. Obviously effort is put to produce the design of the system. It is evident that none of the existing estimation models try to calculate the effort put on designing of the system. Although use case estimation model uses the use case points to estimate the cost. But what is the cost of creating use cases? One reason of poor estimates produced by existing models can be negligence of design effort/cost. Therefore it shall be well estimated to prevent any cost overrun of the project. We propose a model to estimate the effort in each of these phases rather than just relying upon the cost estimation of the coding phase only. It will also ease the monitoring of project status and comparison against planned cost and actual cost incurred so far at any point of time. Key Words: Effort estimation, software development life cycle, Risk Mitigation, Project Planning. Section 1:Back Ground and Motivation Existing estimation techniques such as Functions point estimation and use case estimation rely upon the artifacts generated in earlier phase. These artifacts (i.e. Use case diagrams, class diagrams, sequence diagrams, activity diagrams, state chart diagrams etc) depict the architectural design of the entire system. These diagrams are not generated out of a blue or are not instantly available without putting any effort. Standard task set and the percentage of work duration associated with it decomposes the ratio of effort put in each phase. Activity Standard Work Effort% Definition Phase Business Requirements 6% Functional Specifications 10% Delivery Phase Detailed Design 14% Code and Unit Test 40% System Testing 20% User Acceptance Testing 10% Total Effort 100% Table 1 Standard Task Set Work Duration %age [4] It is evident in Table 1 that although major ratio (i.e. 40%) of work effort is put in code and unit test phase. The rest 60 percent effort is put in different areas of the project development life cycle. Hence this signifies the importance of estimating cost for these phases of software development life cycle. Usually the effort estimation is done after the analyses phase when the project reaches into coding stage. The cost / effort is measured in terms of line of codes for each functionality to be incorporated into the software. Therefore it is very clear to understand that only 40 % (i.e. as shown in table 1) of the total software development effort is estimated. Whereas this estimation is delayed until all the analyses and design has completed. We have adapted a different approach and suggest that effort estimation shall be carried out for each phase of the development process. We propose this model to avoid the risk of low cost estimation as earliest as possible in the development process. Current software cost estimation methods first try to know the size of the software to be built. Based upon this size the expected effort to be put is measured. Estimated effort further is utilized to calculate the duration (i.e. Time required) and cost (monetary/human resources) of the project. Calculating the size of project is the foremost logical step to be taken in order to estimate the effort. If we do not know the distance to be travelled we can not estimate the cost and duration per mileage. Therefore we also first measure the size of the entire project. We know that there are mainly three categories of software projects i.e. Organic mode: These are relatively small, simple SW projects (application programs e.g. Thermal analysis program) Embedded mode: System programs which are developed within tight HW, SW and operational constraints (flight control SW for aircraft). Semi-detached mode: An intermediate level (size and complexity, utility programs) SW projects with mixed experience, mixed requirements. It can be mixture of organic and embedded software as well. Therefore these categories of the software project would effect the estimation of each phase. We propose the modular approach to be adapted for the development efforts so that even large scale enterprise information systems can also be decomposed into a mix of several modules of organic, semi detached, and embedded system. Therefore the focus can be put in individual module accordingly. Following are the sections which individually discuss the methods to estimate the expected effort to be put in each phase of software development life cycle. Section 2: Measuring the Size of each project We do not try to measure the size of the project as a whole rather focus on measuring the size of each phase i.e. Analyses, design, coding and testing phases. This can provide us different milestones in the road map of project development. Our main objective is to suggest the estimation methods for analysis, design and testing phasing. We do not focus much on coding phase, as we would refer to the already done work for this phase. We estimate the size of each phase based on the artifacts and project products which are produced in that particular phase. E.g. the analyses phase produces the detailed user requirements document (use cases etc), design phase produces the class diagram, database Model i.e. E-R diagram, Sequence diagrams, activity diagrams etc. based upon these deliverables in each phase the time and effort to produce these are estimated. Figure 1 shows the step wise flow chart of entire project planning process. After the identification of project scope/objectives, characteristics and infrastructure, the identification of all the activities is done. This identification of activities at early stage may provide the strong basis to estimate the size of each individual phase of software development process. As this involves the work break down structure to be defined and can identify the product / deliverable of each phase. Figure also shows that based on this identification of each activity the cost and risk are estimated for each activity. As this is part of project planning. Therefore we can obtain this information in the most earliest phase of project planning and do not need to wait for longer duration as have to wait in existing cost estimation models to estimate the cost of construction of the software. Hence early stage activity identification can help us to estimate the cost/effort for each phase i.e. analysis, design, coding and testing. Figure 1. Step wise Project Planning [3] Moreover the responsibility of the analysis and design of the system goes to the systems analyst. Generally system is viewed in terms of a collection of sub systems therefore each sub system analysis and design is the responsibility of any individual analyst. Hence the human resource need is very clear for analysis and design phase. But when team work is done in coding and testing phases then more stressed has to be put to estimate the required human resources. Bruegge defines the following work products to be generated in each phase of software development life cycle. Figure 2 Software Life Cycle Activities. [6] Bruegge describes and decomposes the overall system model and design into three types of design models i.e. Analysis model Object Design model Behavioral model Section 3: Requirement Elicitation Analyses Phase Size and Effort Estimation In earlier phase of the development process the scope is defined. This may also provide an intuitive vision of project size to the experienced project managers. Unified Process for software development defines the work products in different phases. [2] During the analyses phase we propose Inception points to be identified and estimated. Inception points refer to the points which must be analyzed about in context of the interest of each stakeholder. As use cases represent the points of some business operation or systems functionality, which needs to be clearly understood and modeled therefore we call them inception points. We must know the accurate number of inception points and the effort needed to develop those points. Unified process for software development describes the following main work products in Inception phase. Definition of the problem Identification of all stakeholders Identification of Functional / non functional requirements Validation of requirements [2] Therefore all the main inception points can be clearly identified. Inception point will mainly focus around the identification of the users / stakeholders (possible actors functionality needed) and requirements. The size can be estimated for this phase by estimating the requirements. This can further be utilized to estimate the cost to build the use cases for each requirement. We suggest that the elicitation of requirements may consume effort / cost relevant to the number of requirements and user present. No of Requirements No of Users Project Size Less than 25 1-10 Small 25 50 11-50 Average 50 above 50 above Large Table 2 Project size based on no of requirements. Table 2 can signifies the need to enumerate each requirement, moreover each requirement will produce a use case and would also identify all its possible actors. Hence this can produce the effort needed to build those use cases which need to be documented in the software requirement specification document. Use cases can also be weighted to measure their complexity. So that the size can be determined and the time taken to create those use cases can be determined. No of Processing Points No of Actors No of > Use case Time taken to develop No of Person 1-3 1-2 1-2 3 Hours 1 4-5 3-5 3-5 5 Hours 1 5 + 5 + 5 + 7 Hours 1 Table 3 Use Case Types We have categorized the use cases based upon the number of processing points. actors, and the extension use cases which emerge from that particular use case. We conducted a survey to get the opinion from experienced software engineers and project managers in different software houses. We had distributed the questionnaire which primarily contained the questions to ask about the time needed to develop different types of use case as described in the table 3. We have processed the survey data and have obtained the average time for each category of the use case. Hence we can sum up the total number of inception points and can multiply them by the number of hours required for each type of use case. Summing up the time required in hours for each type of use case can then further give us the total number of hours required to build inception points. Section 4:Design Phase Size and Effort Estimation Object design model and behavioral model are produced during the design phase. We can estimate the size of each model alone and can sum the effort to obtain the total design phase effort. We can identify the Design Points, therefore we can add the weight associated to each design point and hence can measure the size and effort of that particular design point. This gives the lower level granularity to perceive the effort and size of each possible system feature to be designed. Hence further gives us tighter grip on the project progress. Following can be the possible design points: Entity classes Boundary classes Control classes System decomposition System integration Aggregation / composition of objects Generalization / specialization of objects Object interaction Interfaces Application logic 4.1Object Design Model Size and Effort The main artifact of the Object model is class diagram. Class diagram is comprised of several entity, control and boundary classes. If Entity Relationship diagram has already been produced then the effort can be lessened as persistent object are already been identified. Further more each type of classes need to be designed very carefully as control classes depict all the processing and interaction responsibilities among the classes. Where as boundary classes are responsible for the interfacing with either other system components, users, or external system for electronic data interchange. We declare each class to be a design point. A class in the system primarily depicts a systems object which interacts with other objects in systems environment. Hence a class does not dangle into a void but have solid connections and interactions with other classes that must be very accurately and rightly designed. Therefore we can categorize the class based on the complexity of their design. A class would be difficult to design if it has many associations , aggregations, generalizations, functionalities, overloading, overriding etc. Table 4 depicts the parameters to judge the complexity ratio of any class to be designed therefore the effort would be relevant to the complexity ratio. Complexity Ratio No of Associations No of Interactions No of Methods No of Interfaces Time Required (Hours) Low None None 1-5 1 2 2 Medium Single Single 5-10 2 5 5 High Multiple Multiple 10-20 5 10 8 Table 4: class categories for design complexity Our conducted survey tells us that based upon the complexity ratio any class can take 2, 5, or 8 hours for designing. Remember that this time is for design of the class but coding can take extra effort in the coding phase. Therefore if we can obtain the total number of design points and multiply them with the hours required to get the total hours required for the entire class diagram. 4.2Behavioral Model Size and Effort Behavioral model comprises of different diagrams which depicts the state, interaction of different classes with each other and the sequence of activities performed in the system to achieve any objective or perform business function. These diagrams are sequence diagram and state transition diagrams mainly. We declare each of these diagrams to be the design point as it is very essential to trace the possible states of the system so that a good design can be obtained. Whereas the sequence diagrams is the most sophisticated diagram that shows the complete step by step functionality and participating classes. But if the functionality of the existing system has been well understood then creation of sequence diagrams become easier. Our surveyed data reveals the facts that each of these diagrams can be different in complexity level i.e. low, medium, high. Parameters involved for determining the complexity level are summarized in table 5 below. Complexity Ratio State Chart No of States No of Transitions / Events No of Activity of State No of Actions associated with states Time Required (Hours) 1-5 1-5 1-5 1-5 3 5-10 5-7 5-7 5-7 5 10-15 7-10 7-10 7-10 8 Sequence Diagram NO of Classes No of Actors No of Events No of Control, boundary Entity Objects Time Required (Hours) 1-5 1-5 1-5 1-5 3 5-10 5-7 5-7 5-7 5 10-15 7-10 7-10 7-10 8 Table 5 Complexity parameters for behavioral model diagrams We perceive each of such diagrams as design point and can sum up the total number of hours required for each to obtain the total size and effort estimate to develop behavioral model. 4.3Data Model Size and Effort Mainly an objective is set to achieve an Entity Relationship diagram to depict the over all database design for the entire software system. E-R diagram itself involves several steps to be carried out. The size of database model itself may relate to the type of software project. Embedded software may not be using any large data base but may work using few files available in the read only memory. Whereas organic and semi detached software projects may require the data to be accessed from large databases. Complexity further increases when database has to be distributed. For the time being we do not discuss about distributed databases and leave it for our future work. Therefore we aim to estimate the size of conventional database to be built. The following table 4 summarizes the parameters that would affect the size of the database. Complexity Ratio No of Entities No of Relationships No of Aggregations Normalization Degree Query Joins Low 10-20 5-10 1-5 1-3 10-15 Medium 20-35 10-20 5-10 1-3 15-25 High 35-50 20-40 10-20 1-5 25-50 Table 6: Complexity parameters and Ratio to develop E-R Model The larger the number of entities to be designed, larger the database size increases. It is time consuming task to identify the persistent objects (i.e. entities) in the system. Then to design its attribute set. Different types of attributes i.e. composite, derived and multi-valued attributes are difficult to design and to decide that which entity would be the best suitable place for any particular attribute. Based upon the complexity ratio we had conducted a survey to know that how much time and personnel is required to build the E-R model. We have analyzed the data and got the average time and no of personnel required to develop E-R model. Complexity Ratio Days Required Personnel Required Low 7 10 1 2 Medium 10 25 1 3 High 25 40 1 5 Table 7: Required Effort for E-R model We have considered the flexibility range in the commencement of the activities as well, therefore have concluded the time and personnel requirement in to range of lower and upper limit. Section 5.Coding phase Size and Effort estimate Much work has been done to focus at the code phase effort and size estimation. Mainly Constructive Cost Model and Use case Point method strive hard to achieve this objective. But still there is room for the refinement. But as our main objective was to talk about the other phases e

Truman Capotes In Cold Blood Essay -- In Cold Blood Essays

1. Title: â€Å"In Cold Blood.† 2. Author plus biographical background information: Truman Capote, one of America’s most famous writers was born in New Orleans in 1924 and died in California in 1984. He wrote both fiction and non- fiction stories. (for example this book, â€Å" In cold blood†) short stories, novels, travel writing, profiles, reportage, memoirs, plays and films. 3. Number of pages: 336 4. Theme (s): - Murder - Feelings 5. The Clutter family. Herb Clutter: He’s the father of the murdered family. He’s forty-eight yr. old. Herb is a normal man, who makes a living with the farm he owns. His social contacts in the neighborhood and the people of Holcomb community are very good, people love to talk with him and Mr. Clutter is a member of the agricultural society. Mrs. Clutter: She’s the mother of the family, and loves miniature things. She has two kids, a girl named Nancy and a boy named Kenyon. The daughter is very much loved in town by boys who like to hang out with her, but she already has a boyfriend named Bobby Rupp. Nancy has another love, and that’s her old fat horse named Babe. The brother of Nancy is Kenyon, he’s a boy who likes to fish and hunt. Chase coyotes on his â€Å"Coyote wagon†, just a normal boy. Perry and Dick. Perry Smith is a very quiet person who had a lousy childhood, which affected his behavior in worse form. He seems to be a quite decent person to talk with, but he’s very easily influenced. In the end you feel a little sorry for him because Truman Capote describes him as a person who had a very difficult childhood. Perry was the person who killed the Clutters by shooting their brains out with a .12-gauge shotgun. He’s feel’s no sorry for the crime he has committed. But he also says he liked Mr. Clutter, and thought he was a very nice man. Then there is his companion named Richard (Dick) Hickock. He’s the one who comes with the idea of robbing the Clutter family and to kill any people in the house on the moment of the robbery. When they’re looking for the safe of Mr. Clutter, they find out that there isn’t any safe in the office of Mr. Clutter. They decide to tie the family up and kill them. Dick doesn’t dare to pull the trigger so Perry has to do the dirty work. Dick first was planning to rape Nancy Clutter, but Perry kept him from doing that. People who are sexually obsessed make him mad. In the story you’ll know ... ...about what they’ve done. But they are very pissed of the fact that there was so little money in the house ( they only got 40 $ ). They decide to go to Mexico to flee and hide for the police, who are starting an investigation on the Clutter murder case. The whole city of Holcomb is shocked by the killing of the loved family and everybody is scared. Perry and Dick stay in Mexico for a while but then they want to return to the states again, they decide to hitchhike back to the USA. Then Floyd Wells, a former cellmate of Dick. Dick told Wells that he was planning to kill the Clutters and leave no witnesses. Floyd Wells reads about the murder and tips the police of the possible murderers. Dick and Perry stole a car when they were back in the US, they also pass out false cheques and spent the money on a holiday in Miami. Then they travel to Las Vegas where the police catch them. They are questioned about the murder and they finally make a full confession. They spent the rest of their time in jail until they have to go to court to hear their punishment. The jury as the judge decides to give them the dead penalty by hanging. Eventually both of the men are hanged on April 14 1965. Truman Capote's In Cold Blood Essay -- In Cold Blood Essays 1. Title: â€Å"In Cold Blood.† 2. Author plus biographical background information: Truman Capote, one of America’s most famous writers was born in New Orleans in 1924 and died in California in 1984. He wrote both fiction and non- fiction stories. (for example this book, â€Å" In cold blood†) short stories, novels, travel writing, profiles, reportage, memoirs, plays and films. 3. Number of pages: 336 4. Theme (s): - Murder - Feelings 5. The Clutter family. Herb Clutter: He’s the father of the murdered family. He’s forty-eight yr. old. Herb is a normal man, who makes a living with the farm he owns. His social contacts in the neighborhood and the people of Holcomb community are very good, people love to talk with him and Mr. Clutter is a member of the agricultural society. Mrs. Clutter: She’s the mother of the family, and loves miniature things. She has two kids, a girl named Nancy and a boy named Kenyon. The daughter is very much loved in town by boys who like to hang out with her, but she already has a boyfriend named Bobby Rupp. Nancy has another love, and that’s her old fat horse named Babe. The brother of Nancy is Kenyon, he’s a boy who likes to fish and hunt. Chase coyotes on his â€Å"Coyote wagon†, just a normal boy. Perry and Dick. Perry Smith is a very quiet person who had a lousy childhood, which affected his behavior in worse form. He seems to be a quite decent person to talk with, but he’s very easily influenced. In the end you feel a little sorry for him because Truman Capote describes him as a person who had a very difficult childhood. Perry was the person who killed the Clutters by shooting their brains out with a .12-gauge shotgun. He’s feel’s no sorry for the crime he has committed. But he also says he liked Mr. Clutter, and thought he was a very nice man. Then there is his companion named Richard (Dick) Hickock. He’s the one who comes with the idea of robbing the Clutter family and to kill any people in the house on the moment of the robbery. When they’re looking for the safe of Mr. Clutter, they find out that there isn’t any safe in the office of Mr. Clutter. They decide to tie the family up and kill them. Dick doesn’t dare to pull the trigger so Perry has to do the dirty work. Dick first was planning to rape Nancy Clutter, but Perry kept him from doing that. People who are sexually obsessed make him mad. In the story you’ll know ... ...about what they’ve done. But they are very pissed of the fact that there was so little money in the house ( they only got 40 $ ). They decide to go to Mexico to flee and hide for the police, who are starting an investigation on the Clutter murder case. The whole city of Holcomb is shocked by the killing of the loved family and everybody is scared. Perry and Dick stay in Mexico for a while but then they want to return to the states again, they decide to hitchhike back to the USA. Then Floyd Wells, a former cellmate of Dick. Dick told Wells that he was planning to kill the Clutters and leave no witnesses. Floyd Wells reads about the murder and tips the police of the possible murderers. Dick and Perry stole a car when they were back in the US, they also pass out false cheques and spent the money on a holiday in Miami. Then they travel to Las Vegas where the police catch them. They are questioned about the murder and they finally make a full confession. They spent the rest of their time in jail until they have to go to court to hear their punishment. The jury as the judge decides to give them the dead penalty by hanging. Eventually both of the men are hanged on April 14 1965.

Macbeth Quotes

Violence Quotes Lady Macbeth Come, you spirits That tend on mortal thoughts, unsex me here, And fill me from the crown to the toe top-full Of direst cruelty! make thick my blood; Stop up the access and passage to remorse, That no compunctious visitings of nature Shake my fell purpose, nor keep peace between The effect and it! Come to my woman's breasts, And take my milk for gall, you murdering ministers, (1. 5. 46-54) Macduff I shall do so, But I must also feel it as a man. I cannot but remember such things were That were most precious to me. 4. 3. 261-264) Macbeth From this moment The very firstlings of my heart shall be The firstlings of my hand. And even now, To crown my thoughts with acts, be it thought and done! The castle of Macduff I will surprise, Seize upon Fife, give to the edge o' the sword His wife, his babes, and all unfortunate souls That trace him in his line. (4. 1. 168-176) Ambition Quotes Macbeth My thought, whose murder yet is but fantastical, Shakes so my single s tate of man that function Is smother'd in surmise, and nothing is But what is not. (1. 3. 60-163) Lady Macbeth Glamis thou art, and Cawdor; and shalt be What thou art promised: yet do I fear thy nature; It is too full o' the milk of human kindness To catch the nearest way: thou wouldst be great; Art not without ambition, but without The illness should attend it: (1. 5. 15-20) Banquo My noble partner You greet with present grace and great prediction Of noble having and of royal hope, That he seems rapt withal. To me you speak not. If you can look into the seeds of time, And say which grain will grow and which will not,Speak then to me, who neither beg nor fear Your favors nor your hate. (1. 3. 61-68) Guilt Quotes Lady Macbeth Naught's had, all's spent, Where our desire is got without content. ‘Tis safer to be that which we destroy Than by destruction dwell in doubtful joy. (3. 2. 6-9) Macbeth Will all great Neptune's ocean wash this blood Clean from my hand? No. This my hand wi ll rather The multitudinous seas incarnadine, Making the green one red. (2. 2. 81-84) Wake Duncan with thy knocking! I would thou couldst! (2. 2. 96) Macbeth Quotes Violence Quotes Lady Macbeth Come, you spirits That tend on mortal thoughts, unsex me here, And fill me from the crown to the toe top-full Of direst cruelty! make thick my blood; Stop up the access and passage to remorse, That no compunctious visitings of nature Shake my fell purpose, nor keep peace between The effect and it! Come to my woman's breasts, And take my milk for gall, you murdering ministers, (1. 5. 46-54) Macduff I shall do so, But I must also feel it as a man. I cannot but remember such things were That were most precious to me. 4. 3. 261-264) Macbeth From this moment The very firstlings of my heart shall be The firstlings of my hand. And even now, To crown my thoughts with acts, be it thought and done! The castle of Macduff I will surprise, Seize upon Fife, give to the edge o' the sword His wife, his babes, and all unfortunate souls That trace him in his line. (4. 1. 168-176) Ambition Quotes Macbeth My thought, whose murder yet is but fantastical, Shakes so my single s tate of man that function Is smother'd in surmise, and nothing is But what is not. (1. 3. 60-163) Lady Macbeth Glamis thou art, and Cawdor; and shalt be What thou art promised: yet do I fear thy nature; It is too full o' the milk of human kindness To catch the nearest way: thou wouldst be great; Art not without ambition, but without The illness should attend it: (1. 5. 15-20) Banquo My noble partner You greet with present grace and great prediction Of noble having and of royal hope, That he seems rapt withal. To me you speak not. If you can look into the seeds of time, And say which grain will grow and which will not,Speak then to me, who neither beg nor fear Your favors nor your hate. (1. 3. 61-68) Guilt Quotes Lady Macbeth Naught's had, all's spent, Where our desire is got without content. ‘Tis safer to be that which we destroy Than by destruction dwell in doubtful joy. (3. 2. 6-9) Macbeth Will all great Neptune's ocean wash this blood Clean from my hand? No. This my hand wi ll rather The multitudinous seas incarnadine, Making the green one red. (2. 2. 81-84) Wake Duncan with thy knocking! I would thou couldst! (2. 2. 96)

New Developments in Technology Management

The teaching of technology management has a long history in business schools. However, the nature and focus of such curricula have changed in recent years, due to several trends. The rise of a knowledge-based economy has brought greater attention to the management and commercialization of intellectual property (Markman, Siegel, & Wright, 2008).Questions regarding the appropriate business models to foster successful commercialization have been further complicated by the rise of â€Å"open-source† innovation (e. g. , Linux, a software company that has captured substantial market share). And new institutions (e. g. , incubators and science parks; Phan, Siegel, & Wright, 2005) and new organizational forms (e. g. , research joint ventures [RJVs], and technology alliances) have emerged that may also have profound effects on technology management education.Nonprofit institutions, most notably universities and federal laboratories, have become much more aggressive in protecting and ex ploiting their intellectual property (Siegel & Wright, 2007). Such institutions, es324 Copyright of the Academy of Management, all rights reserved. Contents may not be copied, emailed, posted to a listserv, or otherwise transmitted without the copyright holder’s express written permission. Users may print, download or email articles for individual use only. pecially universities, are also working much more closely with industry and government.These trends and growing involvement of government and nongovernmental institutions in innovation and commercialization have led to growing international recognition of the narrowness of technology management education as it is practiced today. Some business and engineering schools have responded to these developments by designing new courses and curricula related to technological entrepreneurship. Some countries with centralized educational systems (e. g. , Japan, Singapore, and Ireland) are graduating â€Å"bilingual engineers† with capabilities in technology and business.Yet, this trend of marrying technology with management education is still far from being in the mainstream. Another important development in stimulating and changing the nature of the demand for technology management education is the rise of knowledge and intellectual property management as a professional field. In many countries, national governments have supported these initiatives by en- 2009 Phan, Siegel, and Wright 325 acting legislation to facilitate public–private research partnerships, technology transfer (through patenting and licensing) from universities to firms (e. g. , the Bayh–Dole Act of 1980), and collaborative research.For example, the EU, China, and Singapore have established technology-based venture funds to stimulate the development of technologybased start-up companies. In the United States, the national â€Å"public sector venture capital† for technology-based new ventures, the Small Business Inn ovation Research (SBIR) program and numerous state-level programs with similar goals (e. g. , Ben Franklin Technology Partners, Pennsylvania, and the Massachusetts Technology Development Corporation) have propelled technology transfer issues to the forefront of university technology management curricula.Government is also providing subsidies for research joint ventures involving universities and firms (e. g. , the Commerce Department’s Advanced Technology Program/Technology Innovation Program), shared use of expertise and laboratory facilities (e. g. , the National Science Foundation’s Engineering Research Centers and Industry– University Cooperative Research Centers), and programs to promote management and entrepreneurship education among scientists and engineers (e. g. the Science Enterprise Challenge in the U. K. ). These and other trends discussed here have led to experimentation and innovation in technology management pedagogy and content, which is the focu s of this special issue. For example, it is obvious that the rise in collaborative research and commercialization has important educational implications, since it implies that team-work has become more important in science and engineering, especially when both innovation and commercialization are involved.This has resulted in the increasingly popular use of real-life team projects as the primary method of delivering discovery-based learning. Our purpose in this special issue is to assess the implications of these trends for technology management curricula in business schools. In spring 2008, we issued an open Call for Papers on the Academy of Management website, the Social Science Research Network, and other venues. We received 38 manuscripts, which were reviewed according to AMLE standards for the Research & Reviews section.Papers were also solicited for the Essays, Dialogues, & Interviews and Exemplary Contribution sections, which were subject to the usual peer-review process. Bas ed on the results, we selected several manuscripts for inclusion which are summarized in Table 1. The remainder of this essay is organized as fol- lows: First, we describe recent public policy changes, which have promoted university– industry partnerships, collaborative research, and technology transfer from universities and federal labs to the private sector.Then, we discuss the educational implications of these trends, drawing on some of the lessons learned from the papers in special issue. Finally, we outline an agenda for additional research on technology management education. PUBLIC POLICY INITIATIVES INFLUENCING TECHNOLOGY MANAGEMENT In recent decades, we have witnessed rapid growth in the incidence of a variety of research partnerships and technology commercialization involving corporations, universities, nonprofit organizations, and government agencies.This growth can be attributed to three policy initiatives: †¢ Policies promoting the transfer of technology from universities and federal labs to firms †¢ A large increase in the incidence of public– private partnerships †¢ Relaxation of antitrust enforcement related to collaborative research Examples of such technology partnerships are research joint ventures, strategic alliances and networks involving high-technology organizations, industry consortia (e. g. SEMATECH), cooperative research and development agreements (CRADAs) involving federal labs and firms, engineering research centers (ERCs), and industry– university cooperative research centers (IUCRCs) sponsored by the U. S. National Science Foundation, federally funded research and development centers, science parks and high-technology incubators (many of which are located at universities), and licensing and sponsored research agreements involving universities, government laboratories, firms, and university-based start-ups. Table 2 summarizes the key U. S. egislation promoting government– university œindustry partnerships, collaborative research, and technology transfer/commercialization. The most important legislation in this regard is the Bayh–Dole Act of 1980, which dramatically changed the rules of the game with respect to the ownership of intellectual property rights of technologies emerging from federal research grants. Bayh–Dole conferred the right to universities to patent and claim the scientific discoveries arising from U. S. government-funded research, instituted a uniform patent policy across federal agencies, and lifted numerous restrictions on technology licensing.As a result of this legis- 326 Academy of Management Learning & Education September TABLE 1 Summary of Papers Authors Barr, Baker, Markham, & Kingon Key Research Question Discovering how to teach technological entrepreneurship skills that will help bridge the â€Å"valley of death† in COT between creation of technology and emergence of a commercial venture. Theory/Framework Van Burg et al. (2008) science-based design framework of five factors critical to enhance science-based start-ups; cognitive theory; theory of planned action.Data/Methods Analysis of development of a COT program for MBA, PhD, and master’s students at North Carolina State over 14year period. Findings/Conclusions Enactive mastery experiences have to be perceived as authentic and real to have desired effect; importance of loosely structured handson engagement; program needs to be real, intensive, interdisciplinary and iterative; need to create temporal checkpoints, decenter business plans, to structure large blocks of time, to emphasize and balance team diversity, generate technology flow, beware of idiosyncratic heuristics.Significant positive effects of the program on student perceptions of the multidisciplinary capabilities needed to operate in a technological business environment. Thursby, Thursby, & Fuller What are the benefits and challenges of integrated approaches to graduate edu cation in technological entrepreneurship? Theory of the Firm—Economic Approach to Evaluation. Austin, Nolan, & O’Donnell How to design a student experience in technology management that addresses the learning cycle more completely, while maintaining very high levels of student engagement. Experiential learning theory.Ordered logit analysis of program assessment data including pre- and postsurveys and a control group relating to a NSF-sponsored integrated program at Georgia Tech and Emory University involving PhD, MBA, and JD students. Programs at universities in two countries, MNC executives, and open enrollment course at a business school; combination of case and traditional lecture-based approaches; narrative approach based on monomyth; student course feedback and follow-up 1 year later. Verzat, Byrne, & Fayolle Boni, Weingart, & Evenson What teaching methods can be used to create entrepreneurial engineers that have a keen sense of teamwork?Are games an appropriate p edagogical device to meet the specific learning needs of engineering students? Can games help engineering students learn about teamwork? How to teach skills of creating disruptive innovations and develop new business opportunities through blending entrepreneurial thought and action, design thinking, and team building. Education science and team process; Kirkpatrick’s 4level hierarchy of evaluation. Use of team games in a traditional elitist French teaching context that emphasizes individual learning; evaluation data collected from 111 groups on initial reaction to the game and interviews 3 months later.Approach works at multiple student levels with same materials but emphasis differs across groups; able to use with introductory and capstone courses; approach acts as a leveler in class as all can engage with the ‘story’; issues concerning integration of supplementary materials, lack of ‘closure’ in each class, use of fictionalized cases. Games rated a positive reaction from students despite being an informal departure from normal formal approach; real learning outcome in exposing students to importance of team working.Disruptive innovation, entrepreneurial leadership, design thinking, and team building. Capstone course for MBA Entrepreneurship in Organizations & Design master’s students at Carnegie Mellon involving team teaching; Multidisciplinary teams of designers, technologists, and business student entrepreneurs. It is important to blend three perspectives for effective commercialization of innovation: (1) entrepreneurial thought and action, (2) design thinking, and (3) teambuilding.A key feature of this project-based course is the collaboration between MBA students and School of Design students, which leads to the development of new business opportunities. (table continues) 2009 Phan, Siegel, and Wright 327 TABLE 1 Continued Authors Clarysse, Mosey, & Lambrecht Key Research Question What are implications for developm ents in technology management education of contemporary challenges such as globalization, open innovation, and the need for corporate renewal (and venturing)? Theory/Framework Technology management skills provision.Data/Methods Qualitative analysis based on interviews with 10 technology management education demand- and supply-side actors in universities, consultancies, and corporations across Europe. Findings/Conclusions Technology Management Educations is a dynamic field moving from traditional MBA focused programs towards more entrepreneurial ‘bootcamps’, from a case study oriented teaching style towards a mentoring approach and from an emphasis upon general business towards working across disciplines yet being sensitive to underlying technologies; a shift from general to specific skills; Linkages between business schools and technology chools is an important element of this change. Courses in IP management, management of industrial R&D, systems architecture and engin eering could only be offered by transfer to School of Engineering; traditional professional degrees can be enhanced by integrating management of technology programs into core engineering curriculum; advantages of offering part-time courses for those in employment.Need to find a subtle balance between traditional didactic courses, presentations of leading edge research, workshops and meetings with practitioners, field studies and involvement in real projects through internships (including outside France); need for faculty to have close links with industry both domestically and abroad; important use of concurrent teaching modes. Hang, Ang, Wong, & Subramanian How can management of technology programs & curricula be designed to meet the needs of a small newly developed Asian country?Action learning as a foundation for curriculum design in technology intensive technology management programs. Qualitative analysis of transfer of MSc in Management of Technology from business school to a sc hool of engineering in Singapore Mustar How to develop a highly selective technology management course for students in a leading French engineering school, in an institutional and country environment traditionally resistant to the notion of entrepreneurship, that develops their entrepreneurial skills but which goes beyond an introductory course on how to start a business.How to combine the acquisition of knowledge and the development of skills. How to develop their entrepreneurial skills and their ability to take responsibilities. How to encourage imagination, creativity, involvement, and risk taking. Qualitative analysis of the case of innovation and entrepreneurship in Mines Paris-Tech, a leading French engineering school. lation, U. S. research universities established technology transfer offices to manage and protect their intellectual property.The Stevenson–Wydler Act, enacted in the same year as Bayh–Dole and then extended in 1986, required federal labs to adopt technology transfer as part of their mission and also authorized cooperative research and development agreements (CRADAs) between the labs and private organizations. The National Cooperative Research Act (NCRA) of 1984 and the National Cooperative Research and Production Act (NCRPA) of 1993, promoted collabo- 328 Academy of Management Learning & Education September TABLE 2 Key U. S.Legislation Promoting Government–University–Federal Lab–Industry Partnerships, Collaborative Research, Technology Transfer/Commercialization Legislation Bayh–Dole Act of 1980 Key Aspects of Legislation Transferred ownership of intellectual property from federal agencies (which sponsor most basic research) to universities; Spurred the growth of university technology transfer offices, which manage university patenting and licensing. Required federal labs to adopt technology transfer as a part of their mission; Authorized cooperative research and development agreements (CRADAs) be tween federal labs and private organizations.Created the Small Business Innovation Research (SBIR) and the Small Business Technology Transfer (STTR) programs, which require each federal agency to allocate a percentage (now 2. 5%) of their research budget to small business research with commercial potential. NCRA and NCRPA actively encouraged the formation of research joint ventures and joint production ventures among U. S. firms. Institutions Affected by Legislation Universities; teaching hospitals; firms Stevenson–Wydler Technology Innovation Act of 1980; Federal Technology Transfer Act of 1986 Federal labs; firms Small Business Innovation Development Act of 1982Universities; small firms; venture capital firms National Cooperative Research Act (NCRA) of 1984; National Cooperative Research and Production Act (NCRPA) of 1993 Omnibus Trade and Competitiveness Act of 1988; America COMPETES Act (2007) Firms; universities The 1988 act established the Advanced Technology Program (A TP), a public–private research program. In 2007, the America COMPETES Act created the successor to ATP, the Technology Innovation Program (TIP). Firms; universities rative research by eliminating antitrust concerns associated with joint research even when these projects involved firms in the same industry.The NCRA created a registration process, later expanded by the National Cooperative Research and Production Act (NCRPA) of 1993, under which research joint ventures (RJVs) can disclose their research intentions to the Department of Justice. The most notable research joint venture established via the NCRA registration process was SEMATECH (SEmiconductor MAnufacturing TECHnology), a not-for-profit research consortium, which provided a pilot manufacturing facility, where member companies could improve their semiconductor manufacturing process technologies.Other legislation created two key publicly funded technology programs: (1) the Small Business Innovation Research (SBIR) and the Small Business Technology Transfer (STTR) programs, which require each federal agency to allocate a percentage (now 2. 5%) of their research budgets to small businesses with commercial promise, and (2) the Advanced Technology Program (ATP), a public– private research program, which funds collaborative research on generic technologies. In 2007, the America COMPETEs Act created the successor to ATP, the Technology Innovation Program (TIP).Universities are actively involved in both programs, working closely with large firms on ATP/ TIP research projects, as well as with small companies on SBIR/STTR, sometimes founding these firms. As a result, many technology management curricula in the United States are now infused with a public policy dimension that was previously missing. Table 3 presents global evidence on key policy changes relating to the legislative and support environment for technology commercialization in five nations: France, Germany, Italy, Singapore, and the Un ited Kingdom.For example, according to Meyer (2008), Austria, Denmark, Finland, Germany, Italy, and Japan have adopted â€Å"Bayh–Dole like† legislation, emphasizing a â€Å"patent-centered† model of university and national laboratory technology transfer. The United Kingdom and Israel have always had a system of university-owned 2009 TABLE 3 Legislative and Support Environment for Technology Commercialization in France, Germany, Italy, Singapore, and the U. K. Germany 1999 Public researchers receive the right to be the owner of their IP.This is the opposite of the Bayh–Dole Act, but oftentimes the university makes a formal contract on an individual basis to give the IP rights to the university. 2002 Employer Invention Law: Invention belongs to the employer not to the professor. 2000–2006 Restructuring of various laws to make it easier to commercialize technology from universities, get part of the royalties as an academic, take equity in start-ups, etc. Italy Singapore U. K. No formal Bayh–Dole Act. In the case of UK public research organizations the IP is owned by the institution and the royalties associated with the IP are distributed between the relevant parties.The distribution of royalties is organized on an institutional basis. Milestone France I. University Ownership of Intellectual Property Arising From Federal (National) Research Grants (e. g. , Bayh–Dole Act in U. S. ) Not relevant as all IP belongs to universities/public research institutes following the â€Å"code intellectuelle de la propriete. † II. Other Key Changes 1999 Innovation Act gives the possibility to academics who are civil servants to participate as a partner or a manager in a new company and to take equity (previously illegal for civil servants).This Act encourages the creation of new start-up firms by students. 2002 Decree that regulates and increases the personal income an academic can receive from IP (50%). Phan, Siegel, and W right III. Financial Support 1999 11 (pre-) seed capital funds created to invest in innovative start-ups and take equity (investment in 150 spinoffs in 8 yrs). Creation of the annual National Competition for the creation of technologically innovative startups (grant from 45,000 to 450,000 Euros); 12,927 projects have been presented between 1999 and 2007: 1,879 have been funded.Creation of 29 incubators between 1999 and 2007; they hosted 1993 projects giving birth to 1,239 new firms. Between 1999 and 2007, these 3 schemes have benefited 1,760 new firms (taking into account that a company can benefit from different schemes). Around 50% are academic spin-offs. 2000 EXIST: public program that assists spin-offs through preseed capital and management support. 2002 EEF-Fund: Researchers can receive a scholarship to start a spin-off. 2002 22 TTOs established which take care of IP management. 999 National Research Commission created, which annually funds about 5-10 proposals for spin-offs, a mounting to 30,000 Euro, on average. 2005 Quantica Fund. First interuniversity seed capital fund (a form of public–private partnership) is created. 2005 Italian University technology transfer offices have to join together in groups of four and bid for money (100,000 Euro/university) to sponsor their day-today operations. 1963 Forms tripartite macroeconomic structure of industry, labor, and government as basis for funding innovation and economic development. 001–2008 National initiative to focus on microelectronics, biotechnology, nanotechnology, materials science, healthcare and life sciences as part of national innovation initiative. The right to commercialize IP are assigned to the faculty. 2001 Economic Development Board charged with the implementation of the 5-Year Science and Technology Plan which includes initiatives to target key technology sectors, attract foreign investment and human capital, and accelerate technological entrepreneurship and technology commerc ialization.Agency for Science, Technology and Research or A*STAR) created to fund and create infrastructure of industry– university joint research efforts in strategic technology sectors. 2005 The government’s funding plan is to increase R&D expenditure to 3% of GDP by 2010, from the 2004 R&D expenditure of $2. 5 billion US (about 2. 25% of GDP). 2007 Public sector R&D budgets more than doubled to $13. 55 US billion from 2005, comprised of $5 billion US for the National Research Foundation (NRF), $5. 4 billion US for the Public Research Institutes housed in the Agency for Science, Technology and Research (A*STAR). 1. 05 billion US for academic (universitybased) research. $2. 1 billion US for the Economic Development Board (EDB) to promote private sector R&D. 1970 onward Various schemes to promote collaborative projects between universities and industry, including Knowledge Transfer Networks. 1998–2004 Higher education reaches out to business and the community to provide funding to establish corporate liaison offices and collaborative projects. 1998 University Challenge Funds (UCFs): Universities were granted funds to support spin-off and limited incubation support. 001 onward HEIF (Higher Education Innovation Fund) provides permanent flow of funding to support & develop universities’ capacity to act as drivers of growth in the knowledge economy (various rounds up to 2008). (table continues) 329 330 TABLE 3 Continued Germany Italy Singapore UK Milestone France In 2005, six â€Å"Maisons de l’entrepreneuriat† in different universities have been created. They aim at facilitating the promotion of the entrepreneurial spirit and mind-set and â€Å"sensitization† to the new business start-up or new activities.Academy of Management Learning & Education Science Enterprise Challenge funding (1991/2001), to encourage culture open to entrepreneurship required for successful knowledge transfer from science base. Teaching ent repreneurship to support the commercialization of science and technology to produce graduates and postgraduates better able to engage in enterprise. Establish a network of UK universities specializing in teaching and practice of commercialization and entrepreneurialism in science and technology. 005 Medici Fellowship Scheme, pilot providing 50 fellowships over 2 years focusing on commercialization of biomedical research; fellows required to have significant prior research; local training in host institution in finance, marketing, IP, & business strategy; fellows encouraged to develop links with practitioners; postpilot further funding obtained to extend remit to include engineering researchers from 2007–2009; analogous schemes subsequently created by Research Councils and Regional Development Agencies and from 2007–2009 mainly focused in life sciences.Regional Development Agencies providing broad spectrum of assistance to develop more productive links between universit ies and industry. 2007–2011 Technology Strategy Board strategic plan envisages investing ? 1 billion of public funds plus matched funds from industry over 2008-2011, in doubling number of innovation platforms, a strategic review of Knowledge Transfer Networks, doubling number of Knowledge Transfer Partnerships, developing strategy to rapidly commercialize new and emerging technologies, piloting a new Small Business Research Initiative.September Information sources: Clarysse et al. (2007); Mustar & Wright (2009); and Koh & Phan (In Press). 2009 Phan, Siegel, and Wright 331 intellectual property. An increase in funding for technological entrepreneurship in many countries (see Table 3) has also stimulated greater interaction among firms, universities, and national labs, as well as the rise of intellectual property management curricula and courses at these institutions (for detailed comparison of France and the U. K. , see Mustar & Wright, 2009).EDUCATIONAL IMPLICATIONS OF THESE TRENDS The end result of these global trends is an increased emphasis on collaborative research, commercialization of intellectual property, entrepreneurship, venture capital, and research centers dedicated to emerging technologies, such as Organic LEDs, nanotechnology, biotechnology, materials science, MEMS, and so on. Such trends have brought new issues and perspectives, propelling the role of education to the forefront of discourse (e. g. , the recent AMLE special issue on entrepreneurship education).Conventional technology management and management of innovation curricula have focused largely on understanding the technology and innovation strategies of multinational firms (Nambisan & Willemon, 2003). There has been, until recently, less emphasis on start-up and entrepreneurial technology-based firms. The differences can be significant. For example, in the traditional curriculum, the role of teamwork, especially linking interdisciplinary teams of agents (scientists, technology ma nagers, and entrepreneurs) and institutions (firms, universities, government agencies) have not been stressed.That is, the individual and institutional levels of analyses have been ignored, such that technology management education curricula have been confined to how organizations respond to technological challenges. The developments in technology management education considered in this special issue can be seen as a response to the challenges leveled at business schools to be relevant to the practice of management (Pfeffer & Fong, 2002, 2004; Starkey, Hatchuel, & Tempest, 2004).At the same time, such programs that reside in business schools, when detached from the engineering and science faculties of their universities, run the risk of treating the technology component as a special case of general management. Our review of the literature and the lessons learned from this special issue suggest that a fully matured technology management program should treat technology with a capital â€Å"T† rather than the small one it has been to date. To accomplish this design goal, business schools eed to appoint program directors with strong boundary-spanning skills that can link up with technology-based units on and off campus by colocating or partnering with such institutions. We note that the challenge of integration is not easily solved. Over the years, business schools in the United States and United Kingdom have chosen to remain independent from the rest of their universities. This was partially enabled by the largesse of endowments in the 1980s and 1990s pouring in from private foundations and industrialists seeking to establish their names in perpetuity.Clarysse, Mosey, and Lambrecht (this issue) hypothesize that this is not a wise strategy for business schools administering technology management curricula. The authors conclude that business schools should expand their educational mission to include the education of engineering and science professors and res earchers, and the training of postgraduate science and engineering students, since these individuals are more likely to choose an industry or technology-specific master’s degree, instead of a traditional MBA.More generally, business schools need to have a stronger connection to schools of engineering and the sciences, and other technology-orientated organizations in the areas of medicine, public health, and pharmacy, as well as science-based business incubators and science parks. While acknowledging Clarysse et al. ’s points, we are concerned that each of these institutions has different paradigms, norms, standards, and values, as well as diverse languages and codes. Thus, it may be necessary to develop a shared syntax of boundary objects that include repositories, standardized forms, objects and models (Carlile, 2002).These communication devices enable individuals in business schools and technologybased schools to learn about their differences and dependencies, as wel l as jointly to evolve their knowledge bases about how things work â€Å"on the other side. † Hence, the recruitment and development of boundary spanners (such as program managers, center directors, or interdisciplinary faculty members) who can communicate across schools are important to facilitate such integration (see e. . , the Medici Scheme, Table 3). Another concern regarding the optimal design of technology management curricula arises in relation to the overall configuration of business schools. Ambos, Makela, Birkinshaw, and D’Este (2008) have argued that for universities to be effective at technology commercialization there is a need for ambidexterity in the organizational structures of these traditional research and teaching institutions.Similarly, with respect to technology 332 Academy of Management Learning & Education September management education, business schools must make their organizations more porous, for example, through the hiring and promotion of faculty with science and engineering degrees. Such ambidexterity configurations will enable business schools to more tightly bind the traditional business disciplines to science and engineering disciplines. The papers in this pecial issue challenge the proposition of Suddaby and Greenwood (2001), who asserted that business schools can sustain demand for new managerial knowledge through the education and accreditation of a continuing stream of management students. While it is true that there has been substantial growth in demand for courses in entrepreneurship and innovation in MBA and undergraduate programs, the ability of business schools to deliver these programs beyond an introductory level is open to debate, especially when faculty in such schools traditionally lack exposure to the hard sciences and technology disciplines.A third concern in the design of technology management curricula raised herein is the notion of avoiding polar extremes in content coverage, which are emphasiz ing theoretically rigorous, but highly abstract research or stressing practical content based on â€Å"war stories† and conventional wisdom. Placing too much emphasis on practical experience may have negative consequences since the mental models that such pedagogies create can quickly become obsolete, particularly in light of the fast evolving technologies the curricula are supposed to address (Locke & Schone, 2004).In ? other words, practice-oriented technology management curricula may inspire students to become more entrepreneurially oriented, but without the concomitant development of critical thinking skills, such as the ability to assess risks and recognize the inevitable downsides of entrepreneurial activity. Technology management curricula that are light on practice, however, can produce students who may find the challenge of boundary spanning, a key skill for successful technology managers, too great to scale.Van Burg, Romme, Gilsing, and Reymenk (2008) have outlined a design science-based model for the development of academic spin-offs that is grounded in both theory and practice. As noted by Barr, Baker, Markham, and Kingon (this issue), new developments in technology management education stress the importance of active involvement (experiential learning) models that are authentic and real. Many technology management curricula mimic those of entrepreneurship, in that they include a ealthy dose of business plan writing, ostensibly as products of courses on commercialization and opportunity search. There is considerable debate over the usefulness of business plans in practice, even though venture capitalists and banks demand them. Indeed, Barr, Baker, Markham, and Kingon (this issue) challenge the effectiveness of teaching the preparation of a business plan. They suggest that it is preferable to deemphasize the writing of a plan because it tends to restrict creativity and the search for more appropriate solutions.Yet, as a pedagogical tool, we t hink that business plans, when used appropriately, can be a useful way to garner a student’s attention on a comprehensive set of issues that should be considered when commercializing an invention. A shift is taking place from traditional technology management curricula toward more entrepreneurially based courses that require interdisciplinary skills. As part of this development, there is a need for interdisciplinary team-learning activities to be a central part of curriculum development in technology management education.Team composition needs to be addressed carefully to enable participants to gain full benefits. Thursby, Thursby, and Fuller (this issue) present an interesting example of teams of law, business, science, and engineering students converging to commercialize innovations developed at Emory University and the Georgia Institute of Technology. Developments in technology management education also pose major faculty recruitment challenges. Many business school facult y members do teaching, research, and service (including consulting) that is focused on large corporations.Traditional business school academics typically lack the appropriate context-specific business creation skills that are increasingly demanded as central to technology management education (Wright, Piva, Mosey, & Lockett, 2008). As noted in Barr, Baker, Markham, and Kingon (this issue), the recruitment of adjunct faculty members should be focused on those who can serve as mentors to students. There is also a need to consider recruitment and training of faculty who can act as boundary spanners.The time-consuming nature of developing interdisciplinary curricula raises a concern about possible conflicts with the promotion-and-tenure process, which also needs to be addressed in recruitment and retention. AGENDY FOR FURTHER RESEARCH ON TECHNOLOGY EDUCATION To build on the findings of this special issue, we identify a number of areas for further research. 2009 Phan, Siegel, and Wright 333 These are summarized in Table 4, where we identify a series of research questions relating to institutional issues, the interaction between education and practice, the advancement of business schools, and evaluation.Universities typically have well-established conventions and practices concerning the management of their activities. The traditional academic culture of the university (the classic â€Å"ivory tower†) embodies a system of values that opposes the commercialization of research through company creation. When university administration is decentralized, with no mechanism for integration, links between business schools and technologyoriented units of universities may be weak or in- formal.This suggests a need for the development and implementation of clear and well-defined strategies, processes, and policies regarding new venture formation and approaches to technology management education that incorporate entrepreneurial activities. Institutional frictions and thei r impact upon intraorganization knowledge transfer are wellknown (Szulanski, 1996). These frictions in the interactions between different elements of the university may frustrate the development of interdisciplinary technology management curricula.Transferring personnel across organizational boundaries has been identified as an important mechanism to effect knowledge transfer (Inkpen & Tsang, TABLE 4 Research Agenda Institutional Issues How do incentive systems for faculty encourage the time-intensive development of effective technology management courses? What institutional challenges constrain the cross-disciplinary development of technology management education? What are resource implications for universities attempting to develop interdisciplinary technology management education?Interaction Between Education and Practice How can technology management education processes be transferred to promote the creation and development of spin-offs? How can universities develop integration processes among technology management education and technology transfer offices, incubators, and science parks? How can business schools enhance (effective) engagement with leading-edge technological entrepreneurs? Advancement of Business Schools How can the necessary specific skills now required for technology management education be developed within business schools?Do business schools have the requisite career structures for faculty involved in technology management education? (e. g. , adjunct, nontenure track faculty). What is the role of business school faculty in contributing to the development of technology management education? Evaluation Issues How effective are different developments in technology management education? Is it possible to have a valid control group in evaluation of technology management education? From a corporate perspective (since many students are sponsored by companies), how effective are technology management programs?What are the most appropriate metho ds for evaluating the effectiveness of technology management education? What decision making processes are most effective in promoting interdisciplinary teaching and research, and integration in technology management education (top-down vs. bottom-up)? Does development of technology management education represent a need to reevaluate the whole position of business schools within universities, or is there a need for ambidexterity? What are the roles of different competitors within the segments of the broad technology management space?What challenges arise in addressing â€Å"language barriers† between business school and technology/ engineering faculty and how can they be overcome? What is the best way to train technology managers who must engage in boundary spanning among industry, the entrepreneurial community, academia, and government? What challenges arise in integrating research with new developments in technology management education? Is it possible to build evaluation i nto the design of technology management education programs, so we can identify â€Å"best practices† and benchmark comparable programs? 34 Academy of Management Learning & Education September 2005). Universities may need to consider the facilitation of exchanges of staff between schools or the development of faculty with boundary-spanning skills. Academics may identify more closely with their discipline than with the business school or university and may seek to marginalize â€Å"tribes† from â€Å"outside disciplines† (Becher & Trowler, 2001). This concern is especially salient if the objective is to integrate research with new developments in technology management education.Differences in language and goals between business schools and science- and technology-based departments exacerbate these problems. Business schools may also lack credibility with conventional, â€Å"pure† scientists, who perceive them as professional schools with little research tra dition. This may be a major issue in universities with strong science departments and weak business schools (Wright et al. , 2008). However, even this effect is likely to vary between disciplines, as some departments, for example, engineering and medicine, may be closer in the sense of being professional schools than the pure science departments.It may also be important to focus on the role of technology managers within the university. Siegel, Waldman, and Link (2003) found that the key impediment to effective university technology transfer tended to be organizational in nature. In a subsequent field study (Siegel, Waldman, Atwater, & Link, 2004), the authors found there are deficiencies in the technology transfer office and other areas of the university involved in technology commercialization with respect to marketing skills and entrepreneurial experience.This finding has been confirmed with more systematic data by Markman, Phan, Balkin, and Gianodis (2004), who explained this res ult by reporting that universities were not actively recruiting individuals with such skills and experience. Instead, representative institutions appear to be focusing on expertise in patent law and licensing or technical expertise. To develop effective curricula, the expertise that business school faculty need to interact with science and technology departments may be discipline specific.Yet the background of business school faculty typically makes it difficult for them to convey sufficiently context-specific material for different groups of technologists. To this end, Siegel and Phan (2005) suggest the creation of formal training programs for university personnel on the issue of technology management. Thursby, Thursby, and Fuller (this issue) report that an integrated graduate program on technological entrepreneurship has a positive impact on student perceptions of the multidisciplinary capabil- ties needed to operate in a technologically oriented business environment. Taking a pa ge from Souitaris, Zerbinati, and Al-Laham (2007), who drew on the theory of planned behavior to demonstrate that entrepreneurship programs raised risktaking attitudes and inspired entrepreneurial intention among students, we suggest that technology management curricula can similarly inspire students to think creatively about how they can convert science to commercial ventures by immersing them in the experience of technology and opportunity evaluation early on in the program.Authors of evaluation studies need to find ways of incorporating the measurement of postprogram outcomes, such as new venturing and career trajectories, through more longitudinal studies. More specifically, it would be extremely useful to build evaluation into the design of such programs, so that we can identify â€Å"best practices† and benchmark comparable programs as we do for other types of programs. A critical methodological issue in evaluation concerns whether it is possible to have a viable contro l group for such a study. The papers in this special issue represent a number of different institutional contexts worldwide.A final question one can ask, after reading these papers, is whether there are developments that suggest a convergence in program design towards a universal model, or are we likely to experience a wide variation due to adaptations to the local contexts? Locke and Schone (2004) highlight ? important differences in the interaction between business schools and industry in Europe compared to those in the United States. They suggest that the relations between business school faculty and other scientists have traditionally been stronger in the United States than in the United Kingdom and France.Further, subjects taught in business schools in France, the United Kingdom, and the United States tend to be close to praxis, and professors have usually had practical experience. To contrast, in Germany management education has always been strongly oriented toward science, wi th academics having little business experience/ contact with industry; this pattern appears to have persisted despite pressure for convergence to an Anglo-Saxon business school model (Muller-Camen & Salzgeber, 2005).Mustar (this issue) and Verzat, Byrne, and Fayolle (this issue) illustrate the challenges of introducing entrepreneurial elements to the traditional approach to technology and engineering training in France. Hang, Ang, Wong, and Subramanian (this issue) argue that there was a need to design a program to meet the needs of a small newly developed Asian country. In sum, while the elements of technology man- 2009 Phan, Siegel, and Wright 335 agement curricula appear to be very similar, in part driven by the institutional hegemony of U. S. ased models, there is some indication of local adaptation in pedagogy, delivery mechanisms, and sequencing of content, based on government initiatives, types of corporations that employ the local graduates of such programs, and the capabili ties of the universities delivering them. REFERENCES Ambos, T. , Makela, K. , Birkinshaw, J. , & D’Este, P. 2008. When does university research get commercialized? Creating ambidexterity in research institutions. Journal of Management Studies, 45: 1424 –1447. Becher, T. , & Trowler, P. R. 2001. Academic tribes and territories.Buckingham: The Society for Research into Higher Education and Open University Press. Carlile, R. 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Journal of Product Innovation Management, 25: 114 –128. Wright, M. , Piva, E. , Mosey, S. , & Lockett, A. 2009. Academic entrepreneurship and the role of business schools. Journal of Technology Transfer. Phillip Phan is professor and vice dean for Faculty and Research at The Johns Hopkins University Carey Business School.Between 2000 and 2007, he was the Warren H. Bruggeman ’46 and Pauline Urban Bruggeman Distinguished Professor of Management at Rensselaer Polytechnic Insti tute. Phil is associate editor for the Journal of Business Venturing, the Journal of Financial Stability, and the Journal of Technology Transfer. His most recent books are Theoretical Advances in Family Enterprise Research (InfoAge Press); Entrepreneurship and Economic Development in Emerging Regions (Edward Elgar); and Taking Back the Boardroom: Thriving as a Director in the 21st Century (Imperial College Press).Donald Siegel is dean of the School of Business and professor of management at the University at Albany, SUNY. Don is editor of the Journal of Technology Transfer, associate editor of 336 Academy of Management Learning & Education Journal of Business Venturing, Journal of Productivity Analysis, and Academy of Management Learning & Education. His most recent books are Innovation, Entrepreneurship, and Technological Change (Oxford University Press); and the Handbook of Corporate Social Responsibility (Oxford University Press).He has received grants or fellowships from the Slo an Foundation, National Science Foundation, NBER, American Statistical Association, W. E. Upjohn Institute for Employment Research, and the U. S. Department of Labor. Professor Siegel is a member of the Advisory Committee to the Secretary of Commerce on â€Å"Measuring Innovation in the 21st Century Economy. † Mike Wright has been professor of financial studies at Nottingham University Business School since 1989 and director of the Centre for Management Buy-out Research since 1986.He has written over 25 books and more than 250 papers in academic and professional journals on management buy-outs, venture capital, habitual entrepreneurs, corporate governance, and related topics. He served two terms as an editor of Entrepreneurship Theory and Practice (1994 –1999) and is currently a consulting editor of Journal of Management Studies and an associate editor of Strategic Entrepreneurship Journal. Mike is also program chair of the Academy of Management Entrepreneurship Divisi on. His latest books include Academic Entrepreneurship in Europe and Private Equity and Management Buyouts. September