Management: Innovation

Business is said to consist of four elements: Principles, Models, Rules and Behaviours, the first constrains the company scope, the third the procedures, both being static elements. The interplay (feedback) between changing models and behaviours however is what drives innovation – the exploration of adjacent new possibilities. This is a step at a time mode of innovation, yet rules actually prevent these improvements which, it is shown, derive largely from the staff breaking rules. After looking more closely at complexity concepts (see later), the importance of language and metaphor is considered, especially the need for free format communications (stories) between employees. The knowledge and ideas thus exchanged are considered far more valuable to the company, in the new thinking, than any time wasted. This leads on to applications of the co-evolution metaphor central to complexity thinking, stressing that the future is no longer predictable from the past. The importance of ideas in defining company possibilities, and the need for a high ratio of information (ideas) to infrastructure (events), brings us to the successful franchise system, said to be the current best model of CAS thinking in action. This highlights the importance of independent feedback between control levels in achieving adaptation, plus the superiority of information flow over infrastructure change. The ramifications of understanding and challenging our basic assumptions (including principles) in order to make the necessary paradigm shift cannot be stressed enough, otherwise we merely tinker with the parts. Anyway, these serve to illustrate the benefits of devolving power and decision making to individuals or groups in the company (who form purposeful agents in the CAS). The self-organization that then occurs allows the rule transcendence (going beyond routine) necessary to generate that flexibility crucial to success in a modern co-evolutionary environment. The point that such emergence takes time is well made, and highlights one possible problem in the management of such complexity based systems – impatience. Another problem is the ability of staff to adopt such lateral, divergent thinking (the creative basis of adjacent innovation), and this requires that the employees change their mindset also, to embrace and not abuse the new freedoms. This both necessitates and will drive a society wide change, following the same devolution of power – complexity thinking isn't a change just to company behaviour, but to overall lifestyle. Many of the concepts are presented in a guru style, as claimed ‘truths', without justification, and this lack of depth means that inadequate background is given to many of the complexity terms used (e.g. attractor, fractal, fitness), so much so that their true relevance could be missed by the intended business audience. For example, the important idea of crossover, the re-combination of old ideas in new ways to cause step jumps in performance, with stress being placed instead on mutation style evolution (a move to an adjacent point on the fitness landscape). Additionally the emphasis on breaking down barriers, and the resultant freedom and unpredictability, neglects the spontaneously appearance of new dynamic barriers (by self-organization effects), which can prevent the feared chaos dissolving the business. On a more detailed level, there is inadequate mention of the many computer programs using complexity techniques available (outside the Santa Fe environment), which could help businesses gradually introduce this style of thinking, targeting specific existing problems (e.g. using Genetic Algorithms, Neural Networks, Fuzzy Logic, Artificial Life and Cellular Automata techniques). Those seeking a more in depth knowledge of general complexity ideas should therefore look elsewhere, but considerable scope is still provided here for the remodelling of overall business structures, along the lines of the organic complexity paradigms recommended. It would have been nice to have seen simulations used to give quantitative comparisons between the new, complexity, assumptions and the old (in the style of Epstein & Axtell's ‘Growing Artificial Societies'). It is not specific enough however, in my opinion, to convince old style managers to alter their ways. The implications that they must give up power, status and possibly reward for unpredictable ‘cognitive' gains is unlikely to appeal to closed minds, unless a suitable ‘bottom-line' accountant focus is given, emphasising a point that the book itself makes – that new thinking must be phrased in terms of the old concepts to make an impact. It is suggested that there are different types of patterns found in the organizational structure of a group. The patterns are referred to as paradigms. Closed Paradigm The structure is a traditional hierarchy of authority (similar to a CC team). This kind of team is good at creating software that is similar to its previous experience and it is less likely to be imaginative. Random Paradigm The team is not strictly centered and depends upon the members of team to be responsible for their tasks. When innovation or technological breakthrough is required, teams following the random paradigm will excel. Unfortunately, this type of team will not always excel if everything is completely organized. Open Paradigm The open paradigm is a combination of the closed and random paradigms. It structures the team so that there is control of tasks similar to the closed paradigm and has the attempts at innovation found in a random paradigm. Work is performed collaboratively with heavy communication and consensus-based decision making. This type of team structure is appropriate for teams that must deal with complex problems. Unfortunately, it may not be well suited for many people. Synchronous Paradigm This depends on the modularity of the entire project that is being solved. The problem can be broken down into smaller parts where team members work on a section independently. There is not much communication required among members. Such patterns, when changed to another pattern, can be called paradigm shifts, and form the underlying structure for talking about the future. They are pervasive and would be included in the driving forces as well as scenarios. They are the â€Å"unwritten rules† of how the emerging society might function.).   

Is there a correlation between happiness and sociability Essay Example

Is there a correlation between happiness and sociability Essay Example Is there a correlation between happiness and sociability Essay Is there a correlation between happiness and sociability Essay The aim of this investigation was to discover whether there is a correlation between happiness and sociability. The experimental hypothesis was that there would be a significant correlation between happiness and sociability, because most of the background research indicated that this would be the case. A total of 20 participants were used from college that were selected using a casual sample. The results were in terms of numerical scores and were analysed using the Spearman Rank Order Correlation Coefficient, and were found not to be significant at the 0.05 level of significance for a one tailed test. The results for the mean (11.3 (happiness), 7.7 (sociability)), median (12 (happiness), 7.5 (sociability)) and mode (14 (happiness), 5 (sociability)) reflected this with there being fairly significant differences between the results for happiness, and those for sociability. The range (14 (happiness), 12 (sociability)) showed that the data for both sets of scores was skewed. The conclusi on was that the results were inconclusive, as most evidence pointed to there being a positive correlation between happiness and sociability.Introduction:To be able to gain a better understanding of what this questionnaire is about the terms happiness and sociability need to try and be defined, so it can be seen what is actually being measured.Definitions of Sociability:The tendency to have and make personal relationships'(*1)Ability to engage in an appropriate range of social relationships.'(*2)Definition of Happiness:Having, taking, or demonstrating pleasure or satisfaction'(*3)glad, content, happy'(*4)There is lots of evidence that points towards happiness and sociability being related. These quotes show this relationship:Social science surveys have universally concluded that people claim to be most happy with friends and family, or just in the company of others(*5).This shows how people who socialise are likely to get a feeling of happiness; therefore, in theory the more sociable a person, the happier they should be.Relationships make us extremely happy when they go well, and very depressed when they dont work out(*5).This shows how the breakdown of social relationships can be the cause of unhappiness, but these relationships can also cause a person to be happy when they are going well.Happiness, along with health and mental health, is increased by presence of certain social relationships and depressed by those losing these(*6).This demonstrates how social relationships can not only affect a persons happiness, but also their health.Horowitz et al., 1982, and Weeks et al., 1980(*6) concluded that lonely people become depressed, and Horowitz et al. also concluded that lonely people also feel excluded, alienated and angry. This demonstrates how those who dont socialise very much may become unhappy.Reich and Zautra, 1981 (*6) have shown that increases in social contact lead to increases in happiness, therefore suggesting that the results to our questionnaire ar e likely to show that the more sociable a person is the more likely they are to be happy, and visa versa.Wessman and Ricks, 1966 (*6) conducted an experiment between happy students and unhappy students. Their findings showed that the students who had the better relationships with other students were the happier ones, whilst those students who were unhappy their social relations were often sources of anxiety, anger and guilt that led to cautious withdrawal and empty isolation. This study demonstrates well how the happiness of a person can affect their sociability, although it is not clear how Wessman and Ricks measured the students happiness.For this investigation we have comprised a questionnaire with questions taken from Eysncks (*7) Personality questionnaire, which has been accepted in terms of reliability and validity.Campbell, Converse and Rodgers, 1976 (*5) compiled the following table taken from an American national sample survey of 2164 people in 1971 showing what peoplethoug ht were the main sources of satisfaction in everyday life:Source of satisfactionMean importance ratingFamily lifeMarriageFinancial situationHousingJobFriendshipHealthLeisure activities1.461.442.942.102.192.081.372.79From this table we can see that two of the things that people regard as being among the most important sources of satisfaction are friendship and leisure activities which are both associated to sociability, showing that being sociable can cause happiness. We can also see that a persons financial situation gives them the most satisfaction in everyday life. If a person is financially secure then they can afford to participant in leisure activities, and meet new people.Aims: The aim of this investigation is to see if there is a positive correlation between how happy a person is and how sociable they are.Experimental hypothesis: There will be a significant positive correlation between happiness and sociability, as measured by questionnaire.This hypothesis has been decided up on because past research, such as that done by Horowitz et al. (1982), Reich and Zautra (1981), and Wessman and Ricks (1966) indicates that this hypothesis should be true.Null hypothesis: There will be no significant correlation between happiness and sociability, as measured by questionnaire.*1 The Penguin Dictionary of Psychology*2 A Students Dictionary of Psychology Second Edition*3 Readers Digest Universal Dictionary*4 Collins mini Gem English Dictioary*5 Flow the Psychology of Happiness*6 The Psychology of Happiness*7 Know your own PersonalityMethod:A correlation was used so that it could be discovered if there is a relationship between happiness and sociability.The two variables being investigated were happiness and sociability.Participants were given a pre-prepared questionnaire (see Appendix item 1) that contained a mixture of both questions related to sociability and questions related to happiness selected from Eysencks personality questionnaire. There were 18 questions re lated to each of the variables, plus 14 unrelated questions randomly mixed together to try to stop the participant from guessing the nature of the questionnaire.To analyse the data the Spearmans RHO test was used, at the 0.05 significance level (see Appendix item 6).In total we used 20 participants, 10 female and 10 male. Participants were taken from the local 6th form college, BHASVIC, and were selected using a casual sample. Participants were approached and asked if they wouldnt mind filling in a questionnaire for a Psychology project.. Once they had agreed each participant was given an A4 questionnaire (see Appendix item 1) with 50 YES, MAYBE, or NO answers to be circled with instructions at the top and debriefing at the bottom. They were also given a pen. Once all the results had been collected back the results were scored using Eysencks scoring system (see Appendix item 2) and they were then analysed using the Spearmans Rank Order Correlation Coefficient (see Appendix item 6).R esults: (For table of results see Appendix Item 3)(For workings of results see Appendix Item 4)Mean for Happiness = 11.3Mean for Sociability = 7.7Median for Happiness = 12Median for Sociability = 7.5Mode for Happiness = 14Mode for Sociability = 5Range for Happiness = 14Range for Sociability = 12Statistical Analysis:The Spearmans Rank Order Correlation Coefficient calculated value of -0.0004 at the 0.05 significance level is less than the critical value of 0.377, therefore the results are not significant and the null hypothesis cannot be rejected. This means our correlation did not show a relationship between how happy a person is and how sociable they are. This is reflected in the results of the mean, median and mode, with there being fairly significant gaps between the results of happiness and sociability. This means that the middle points for the sociability scores, and the happiness scores were far apart in each of the descriptive statistics done for averages.Both the ranges for happiness and for sociability were very far apart, with the range for happiness being 14, and the range for sociability being 12. The range shows that the spread of each of the results for sociability and happiness were far apart, with their being 14 points between the highest score for sociability and the lowest score, and there being 12 points between the highest score for happiness and the lowest score.As can be seen from the scattergraph there is not a clear relationship between the scores for happiness and those for sociability. It can be seen that some results do support our hypothesis of a positive correlation between happiness and sociability, but most of the results do not. Trying to draw a line of best fit through this graph would be nearly impossible.Discussion:The evidence that is shown in the introduction all supports our experimental hypothesis. This includes the research conducted by Horowitz et al. (1982) and Weeks et al. (1980) that lonely people become depressed, b y Reich and Zautra (1981) that increases in social contact lead to increases in happiness, and also the research done by Wessman and Ricks (1966) that students who had the better relationships with other students were the happier . Our results do not support our experimental hypothesis, or the evidence shown in the introduction, therefore it is hard to draw a conclusion. The null hypothesis could not be rejected because the result for the Spearmans Rank Order Correlation Coefficient showed that our results were not significant. The mean, median and mode reflected this, as there were large gaps between the mean, median and mode for happiness and sociability. The range shows that there were big gaps between the scores in the happiness section, and in the sociability section. This clearly shows that there was skewed data.As can be seen from the scattergraph there is no clear relationship between happiness and sociability, although some of the results do show this, but there may be fact ors that affected our results.This data all shows that just because a person is sociable, it doesnt mean that they are happy as well.Summary:Our results did not support our experimental hypothesis, therefore the null hypothesis has not been rejected, meaning that there might well not be a correlation between happiness and sociability.To get a better idea as to whether our experimental hypothesis is correct a far more representative sample would have to be used.Limitations of the design and Modifications:One reason as to why our results may not have been significant may be due to the questionnaire. However much care is taken over the wording of the questions, even if they are seen to be reliable and valid (as Eysencks questions are), different respondents may interpret the questions differently, meaning we may not have got answers to the questions we intended to get. The questions we used were only a sample from Eysencks questions, and therefore this may have affected the results. Wh en using a questionnaire there is little opportunity for the researcher to quantify what the question actually means. It may also be the case the respondents may interpret the terms in the questions differently. For example people may have different ideas as to what happy or sociable actually means (as the definitions in the introduction were merely a guide).Respondents to the questionnaire may not have given full and accurate answers. They may answer the questions in a way that makes themselves look good, or in a way in which they think the researcher wishes them to answer.The layout of the questions and the answers on the questionnaire did not line up due to limited space, therefore the respondents may have possibly got confused as to which question went with which answer. This may have affected our results.It is hard to measure the degree of happiness from person to person from a simple questionnaire, such as the one we conducted. More detailed questions would have to be asked in which the respondent could give their own answers. Problems would also arise from this as it is hard to define happiness.This study was conducted using only a small amount of participants, therefore not being very valid. This could be a reason as to why the results for our study did not support our experimental hypothesis, despite all of the evidence in the introduction supporting the experimental hypothesis. The age of the participants in our sample may have differed from those that were used in the background research that I conducted and this may have affected the results.The environment in which the participant filled in the questionnaire may have affected the results. If the room was too warm, too cold, too noisy, or to crowded it may have meant that the participant rushed their answers, or misread the questions. If the participant didnt have much time they may have rushed because they needed to get somewhere else.Further Study:In this study an equal amount of males and female s were used, but a comparison of the two was not conducted. This could be done to see if there is a difference in the happiness and sociability of males and females.The sample size could be increased to see if the result found in this study would be the same, this could also then include many different ages to see if age affected the results. Samples could be taken from different areas from the country, and also from other countries to test if this would affect the results.Instead of using questionnaires, interviews could be conducted to collect the data, this way the questions could be clarified.People in solitude could be studied to see if they consider themselves to be happy.Different sources of happiness could be explored, for example the financial situation a person is in or their health.Implications:Implications of this study, from the results that we obtained from our questionnaire, could be that those who are in solitude, such as people in prison should not suffer from unhap piness. These results could well mean that happiness is just a state of mind, and not affect by your sociability, as some people enjoy being on their own. This is reflected in the quote happiness, happiness, the greatest gift that I possess taken from a well-known song.Our study did not show a correlation between happiness and sociability, but if we were to assume that the evidence shown in the introduction was correct, then those who suffer from unhappiness could be placed into more social situations to try and improve their happiness.References:Michael Argyle The Psychology of Happiness (1987) Methuen and Co. LtdCollins mini Gem English Dictionary (1986)H.J Eysenck Know Your own Personality (1975) Maurice Temple SmithRichard Gross et. al Psychology-A New Introduction-Study Guide (1999) Hodderand StoughtonArthur S. Reber The Penguin Dictionary of Psychology (1985) Penguin GroupVivian Shackleton and Clive Fletcher Individual differences Theories andApplications (1984) Methuen and Co. LtdPeter Stratton and Nicky Hayes A Students Dictionary of Psychology-secondedition (1993) Edward ArnoldReaders Digest Universal Dictionary (1987)Appendix:Item 1: Sample QuestionnaireItem 2: Score sheet for questionnaireItem 3: Explanation of score sheetItem 4: Table of resultsItem 5: Workings for mean, median and modeItem 6: Workings for Spearmans Rank OrderCorrelation CoefficientAppendix Item 4 Table of ResultsParticipant numberScore for happiness(out of 18)Score for sociability(out of 18)1234567891011121314151617181920161076398111414141212915617141712551055641432211121397811814Appendix item 5: workings for mean, median and modeMEAN:Happiness:= 3+6+6+7+8+9+9+10+11+12+12+12+14+14+14+14+15+16+17+1720= 11.3Sociability:= 2+2+3+4+5+5+5+5+6+7+8+8+9+10+11+11+12+13+14+1420= 7.7MEDIAN:Happiness:= 3, 6, 6, 7, 8, 9, 9, 10, 11, 12, 12, 12, 14, 14, 14, 14, 15, 16, 17, 17= 12Sociability:= 2, 2, 3, 4, 5, 5, 5, 5, 6, 7, 8, 8, 9, 10, 11, 11, 12, 13, 14, 14= 7.5MODE:Happiness:= 3, 6, 6, 7, 8, 9, 9, 10, 11, 12, 12, 12, 14, 14, 14, 14, 15, 16, 17, 17= 14Sociability:= 2, 2, 3, 4, 5, 5, 5, 5, 6, 7, 8, 8, 9, 10, 11, 11, 12, 13, 14, 14= 5Range:Happiness:= 17 3= 14Sociability:=14 2= 12ContentsAbstract..1Introduction1Method4Results5Discussion..7References.9Appendices10Is there aCorrelationbetween Happinessand Sociability?Appendix item 3: Explanation of score sheet for questionnaire.The questions highlighted in pink are questions relating to happiness.The questions highlighted in yellow are questions relating to sociability.The questions crossed out are unrelated questions.On the answers the YES , MAYBE , or NO answers that are circled are the desired answers, meaning a person is happy/sociable. If a participant circles one of these answers on their copy of the questionnaire they are awarded one point, to either happiness or sociability depending on what the question was (whether highlighted in pink or yellow) related to. For example, if a participant was to answer NO to Question 1 (Do you think that people really dont care what happens to you?) the participant would be awarded one point on their happiness tally.The scoring system has been done in accordance with Eysencks scoring system to ensure the results were as valid and reliable as possible.

Free Essays on Methadone

Methadone-A Treatment? Methadone is a synthetic opiate. It was first synthesized by a German chemist during World War II and used as an analgesic. Methadone produces almost identical effects of that of morphine, but chemically they are very different. Methadone is used as a detoxification treatment for heroin addicts. It is also used to manage pain in cancer patients. Methadone belongs in the drug family opiates. It is grouped with such drugs as opium, morphine, codeine, and heroin. Opiates date back more than 3,000 years. Papyrus of Thebes, one of our earliest written records, gave instructions for the use of opium in the treatment of pain. (Hutchings, 1992) Opiates come from the milky juice of the poppy plant, in fact, the word opium comes from the Greek word for vegetable juice. Traces of poppy juice being used to alleviate pain can be found back to the third century B.C. By the 16th century though, the medicinal uses of opium were widely known across Europe. It was even written in 1680 â€Å"Among the remedies which it has pleased almighty God to give to man to relieve his suffering, none so universal and so efficacious as opium.† (Hutchings, 1992) During the 1800’s opium was so readily available it could even be purchased at the local grocery stores. Due to death rates increasing due to opium use, and rising drug-related crime rates, restrictions were implemented on the sale and use of opium in England in 1868. During the 19th century the United States caught on and they started importing opium for use as an aspirin. Physicians openly distribute the drug. You could also purchase opium in the grocery store, general, pharmacies, and even mail order. Many over-the-counter medicines, from teething medicines, to painkillers, could be purchased that contained opium. During the mid to late 19th century opium was very common. Opium dens, places where people would go, usually locat... Free Essays on Methadone Free Essays on Methadone Methadone-A Treatment? Methadone is a synthetic opiate. It was first synthesized by a German chemist during World War II and used as an analgesic. Methadone produces almost identical effects of that of morphine, but chemically they are very different. Methadone is used as a detoxification treatment for heroin addicts. It is also used to manage pain in cancer patients. Methadone belongs in the drug family opiates. It is grouped with such drugs as opium, morphine, codeine, and heroin. Opiates date back more than 3,000 years. Papyrus of Thebes, one of our earliest written records, gave instructions for the use of opium in the treatment of pain. (Hutchings, 1992) Opiates come from the milky juice of the poppy plant, in fact, the word opium comes from the Greek word for vegetable juice. Traces of poppy juice being used to alleviate pain can be found back to the third century B.C. By the 16th century though, the medicinal uses of opium were widely known across Europe. It was even written in 1680 â€Å"Among the remedies which it has pleased almighty God to give to man to relieve his suffering, none so universal and so efficacious as opium.† (Hutchings, 1992) During the 1800’s opium was so readily available it could even be purchased at the local grocery stores. Due to death rates increasing due to opium use, and rising drug-related crime rates, restrictions were implemented on the sale and use of opium in England in 1868. During the 19th century the United States caught on and they started importing opium for use as an aspirin. Physicians openly distribute the drug. You could also purchase opium in the grocery store, general, pharmacies, and even mail order. Many over-the-counter medicines, from teething medicines, to painkillers, could be purchased that contained opium. During the mid to late 19th century opium was very common. Opium dens, places where people would go, usually locat...

Haikouichthys - Facts and Figures

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Nike Case Study Analysis Essay Example | Topics and Well Written Essays - 750 words

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The connectionist model theory Essay Example | Topics and Well Written Essays - 500 words

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Health and Wellness Essay Example | Topics and Well Written Essays - 1250 words

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