Critique of Quantitative Methods - Essay Example

Critique of Quantitative Methods Journal Paper Table of Contents Table of Contents 2 Introduction 3 Brief of current theory and empiricalresearch 3 The nature of sample used in the study and an appraisal of its fit 4 Description and meaning of the Most Significant Statistics used in the paper 5 Confirmatory Factor Analysis 5 Confirmatory Fit Index 6 Root-Mean-Square Error of Approximation 6 Cronbach’s Alpha 7 Mean 7 Standard Deviation 8 Correlation 8 Conclusion 8 Reference List 10 Introduction Silke Astrid Eisenbeib and Sabine Boerner in the article ‘A Double-Edged Sword: Transformational Leadership and Individual Creativity’ authored during 2013 in the British Journal of Management reflect on the negative aspects of transformational leadership. The authors highlight that though the aspect of transformational leadership has gained the needed popularity in the management circle in casting a positive influence on the performance of the organizational, yet it also casts a negative influence on enhancing the dependency of the people concerned in generating creative solutions. A key research gap relating to the contribution of transformational leadership in enhancing the dependency of the followers on the transformational leader in taking creative and innovative decisions is potentially highlighted in the paper. The authors argued that though the dimension of transformational leadership is considered effective in stimulating the behavioural and thinking process of organizational people yet the charisma of the transformational leaders is observed to augment the level of dependency of the individuals which in turn affects their creative thinking. Transformational leadership thus is researched in the paper as a dual faceted management style in that it contributes in both stimulating the thinking process of individuals and also in enhancing their dependency on the leader (Eisenbeib & Boerner, 2013). Brief description of current theory and empirical research The empirical research carried out in the journal article provides a description of the current theory related to four different aspects outlined as follows. Initially the concept of transformational leadership is dealt as that which contributes in influencing and motivating the people in an organization to generate needed productivity. The discussion relating to the concept of transformational leadership reflects an inconsistent approach such that where a number of authors relate transformational leadership style as a synonym of charismatic leadership others opine that though the two leadership styles reflect due commonality yet charisma is viewed only as a part of transformational leadership but not the whole. Further the aspect of transformational leadership is identified in the empirical research as such that contributes in enhancing the parameter of creativity of the followers. The transformational leader is identified as a person that contributes in the identification of loopholes and thereby in helping to generate needed changes. Acting as a change maker and also in generating new vision and mission objectives the transformational leader is held to motivate the people to adapt new and creative ideas and work in a motivated fashion to help fulfil such objectives. An incoherent and inconsistent approach is observed in this direction in that the aspect of transformational leadership is observed to generate an insignificant and negative impact on the potential of employee creativity. Empirical research conducted along a large number of organizations reflects that the impact of transformational leadership is insignificant and also negative relating to employee creativity. The idea of transformational leadership as enhancing the dependency rate relating to the followers as identified by the authors based on the empirical studies is thereby held to reduce the growth of creative pursuits in that the people would endeavour to unquestionably follow their superiors in meeting of stated objectives. A transformational leader is also observed to restrict the growth of innovative thought and actions relating to their subordinates in areas where the same fails to match with their personal opinions. This reflects due uncertainty relating to the potential of transformational leadership in augmenting employee creativity (Eisenbeib & Boerner, 2013). The nature of sample used in the study and an appraisal of its fit It is observed that the random sampling method is used relating to the study such that the same contributes in selecting the total size of 416 different respondents from a large group of different companies operating along varied sectors like high-tech, medical engineering, electronics and also relating semiconductor, software, chemistry and biology sectors. Use of the random sampling method is considered effective for the study such that the same contributes in generating equal opportunity to the respondents for being ideally represented. The use of the Simple Random Sampling generates potential advantages such that it contributes in effectively and easily aligning the sample for the research activity. Further the use of simple random sampling is considered effective relating to the research such that it helps in generalizing the responses gained from the different respondents to rightly contribute in meeting the research objectives (Black, 2011). Description and meaning of the Most Significant Statistics used in the paper The statistical tools that were employed in a significant manner relating to the research activity can be essentially briefed as follows. Confirmatory Factor Analysis The Confirmatory Factor Analysis is used to help in the identification of different factors that owe responsibility in varying and co-varying a set of different parameters. Confirmatory Factor Analysis (CFA) requires the researcher to specify at an earlier occasion the different parameters to help in constructing the factor model like factor loadings, variances involved, communalities and the residuals to be gained. Further the incorporation of CFA related to a research paper requires the development of an empirical and conceptual background to help in guiding the formulation of the factor model. CFA as a specialised form of factor analysis gains larger use relating to social research an activity such that it aims in evaluating the consistency of measures relating to different factors to that of the researcher’s understanding of the same. The use of CFA gains efficacy in evaluating the manner in which the results gained tend to match the hypotheses framed relating to the research. Use of CFA is generated in the initial phase of the research such that the same contributes in assessing the model generated for carrying out the research activity. Owing to the above attributes, CFA is used as an effective strategy for construction and analysis of different equations and models (Child, 2006). Confirmatory Fit Index Confirmatory Fit Index tends to gain usage to help in validating the fitness of a model compared to a more restricted baseline model. Confirmatory Fit Index is one such example of Confirmatory Fit Indices of which the other examples are like Tucker-Lewis Index (TLI) and also the non-normed fit index (NNFI). Confirmatory Fit Index (CFI) contributes in comparing the constructed model with potential alternatives relating to the Null Hypotheses. CFI is also commonly known as the Bentler Comparative Fit Index. In a more specific sense, CFI is used in comparing the fitness of a model or equation created related to the research issue to a more independent type of model such that in which the variables are taken to appear in an uncorrelated form. Chi-Square Index is considered as an effective example of CFI such that it contributes in evaluating the differences between covariance matrices of observed and predicted type. Thus CFI contributes in evaluating the effectiveness of the targeted or created model compared to that of the independent model. Values tending to 1 relating to CFI are considered to be more appropriate and acceptable. The measures or results of CFI are observed to be less sensitive relating to the sample size relating to the research. Other researchers opine that the CFI measures reflect an element of biasness which thereby limits its efficacy (Harrington, 2008). Root-Mean-Square Error of Approximation The Root-Mean-Square Error of Approximation (RMSEA) is considered as a substitute model used for evaluating the significance of the research model such that the use of the chi-square tests get limited relating to large sample sizes. The RMSEA is considered as an ideal measure of effectiveness of fit of statistical models such that the goal of the sample population duly constructed is to bear a close approximation to the hypothesized model. The statistical tool does not however reflect exact fit in that the sample population is large in nature compared to smaller sample sizes. RMSEA as a statistical tool gains efficacy such that the same contributes in reducing the errors emanating from the approximation of the population sample to the targeted model (Millsap, 2012). Cronbach’s Alpha Cronbach’s Alpha is used as a statistical method that contributes in evaluating the level of consistency or reliability of the different items relating to a specified group. The tool that is used for measuring the level of consistency is popularly known as the Simple Cronbach’s Alpha and is denoted by the Greek letter Alpha. The utility of the Cronbach’s Alpha is gained such that it helps in understanding the manner in which a set of variables or factors tend to measure a specific construct. The value of Cronbach’s Alpha tends to be higher such that the level of correlation between the different variables tends to increase. Values for Cronbach Alpha tend to range from 0 to 1 such that in case of research related to Social Sciences the value of Cronbach Alpha of 0.7 is considered as effective. Cronbach Alpha values measuring above 0.9 are not considered valid such that it aims at narrowing down the scope of the research activity (Andrew et al., 2011). Mean Mean of a set of variables is considered as a significant statistical measure pertaining to Descriptive Statistics such that it indicates on the centralised position of a data distribution. The estimation of a statistical mean is considered as an effective descriptive statistical tool such that it indicates the direction of responses gained from the respondents relating to the different parameters or factors. Thus a higher mean value gained relating to a specific factor indicates on the potential of positive responses gained from the different respondents. Further the estimation of mean gains popularity relating to descriptive statistics owing to its easiness of calculation. Standard Deviation Standard Deviation is considered as another effective method relating to descriptive statistics in that it contributes in understanding the degree to which the different observations tend to vary along the mean. Estimation of standard deviation gains success only for such variables for which the mean can be rightly calculated. Thus estimation of mean serves as a background to the calculation of standard deviation. Standard Deviation thus contributes in observing and evaluating the position of an observation relating to the arithmetic mean (Kohler & Kreuter, 2005). Correlation Correlation Analysis serves as an effective statistical tool such that it helps in evaluating the degree of association between two or more variables. The coefficient of correlation tends to range from -1 to +1 such that a high degree of correlation gained indicates an effective relationship between the different variables. Coefficient of Correlation tending to +1 indicates positive correlation between the variables while that tending to -1 reflects on a negative correlation or association between the different variables. Similarly the coefficient of correlation reflecting a figure of zero tends to generate a null correlation which indicates the absence of an effective association between the variables. Graphically the association or correlation between the variables is indicated as a scatter diagram where the trend line reflects on the linear relationship between the variables (Sharma, 2005). Conclusion The research analysis relating to the impact of transformational leadership in reducing the creativity of the employees in an organization can also be effectively conducted in a qualitative fashion through the use of the NVIVO 10 Software. Research activity relating to the above direction would tend to focus on the designing of unstructured questionnaire which would be used for conducting of interviews relating to a focused group. The focused group relating to the new method can be rightly constituted through the use of a non-probability sampling method like the use of Quota Sampling method which would take a certain quota of managers and employees relating to different organizations. Responses gained from respondents relating to a sample size of 20 would be fed in the software to help in reflecting the frequency of specific words and phrases used while generating the inferences to the questions. Words or phrases grouped serve as the categorisation or unitisation of the data in several packets thereby contributing to generate needed inferences in a summarized fashion. Use of word tree diagram can also be made to further contribute in the ease of understanding of the inferences generated (Bazeley, 2007). Reference List Andrew, D.P.S., Pedersen, P.M. & McEvoy, C.D., 2011. Research Methods and Design in Sport Management. United States : Human Kinetics. Bazeley, P., 2007. Qualitative Data Analysis with NVivo. United Kingdom: SAGE. Black, K., 2011. Business Statistics: For Contemporary Decision Making. United Kingdom : John Wiley and Sons. Child, D., 2006. The Essentials of Factor Analysis. United States : A&C Black. Eisenbeib, S.A. & Boerner, S., 2013. A Double-edged Sword: Transformational Leadership and Individual Creativity. British Journal of Management, 24, pp.54-68. Harrington, D., 2008. Confirmatory Factor Analysis. United Kingdom: Oxford University Press. Kohler, U. & Kreuter, F., 2005. Data Analysis Using Stata. United States: Stata Press. Millsap, R.E., 2012. Statistical Approaches to Measurement Invariance. New York: Routledge. Sharma, A.K., 2005. Text Book Of Correlations And Regression. United States: Discovery Publishing House. Read More