WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Journal of Engineering Management Rese...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

disarray/array the political system wh...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

with those stated in the characteristi...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

3.2 Technique for Order Preference by ...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

inflation, information technology, pur...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Uyun, S., Riadi, I. (2011), A Fuzzy To...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Appendix 3: Updated PEC’s Characterist...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Appendix 5: Political Characteristics ...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

Appendix 6: Economic Characteristic Ta...
WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION

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Delphi, Entropy and TOPSIS Analysis of Political, Economic and Cultural Characteristics that Affect Textile and Apparel Industry

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Delphi, Entropy and TOPSIS Analysis of Political, Economic and Cultural Characteristics that Affect Textile and Apparel Industry

  1. 1. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION Journal of Engineering Management Research MAY 2013 VOL.1, No,3 Delphi, Entropy and TOPSIS Analysis of Political, Economic and Cultural Characteristics that Affect Textile and Apparel Industry. Akyene Tetteh School of Management Science and Engineering, 1882 Yan’an Road West, 200051 P.R. China, Donghua University, Accepted 8 May 2013 Abstract Textiles and apparel industry sprung up industrialization but political system, economic system and cultural environment characteristics may affect its survival positively or negatively. This paper uses Delphi Method for forecasting in a different fashion to analyze some characteristics of political system, economic system and cultural environment to ascertain how they affect the textiles and apparel industry. The Delphi method exercise in this paper consists of 3 steps and 2 questionnaires format coupled with analysis and consensus. The paper further employed two multiple criteria decision making methods Entropy and TOPSIS to analyze the Delphi result. It was realized that political system dummy is economic system but not cultural environment. The textiles and apparel industry suffers negatively/positively if government disarray/array the political system which intend affect the economic system negatively/positively but does not affect the cultural environment. The textiles and apparel industry can fuse their cultural practice into their company strategy for efficient and effective productivity. Keywords: Delphi Method, Entropy, TOPSIS, Textile and Apparel, Political, Economic and Cultural Characteristics. 1. Introduction Textiles and apparel industry sprung up industrialization, which can be traced back to 1733 when John Kay made a shuttle that speed back and forth on wheels. His invention led to another invention in which we now have heavy machines which can cut and sew apparel in some modern factories today. Most nations derive foreign exchange from exporting textiles and apparel to other countries which boost their GDP growth. United States imports of textiles and apparel in 2010 totaled to $93.3 billion with China being number one exporter (Kim 2011).The textile and apparel industry growth can be hindered/promoted by political benefits (peace, good governments laws, good education system, effective and efficient economy, etc.), economic benefits (good land turner system, labor, good access to capital, low inflation, good exchange rate, etc.) and cultural environment (belief system, language, dressing, food, dance, etc.). This paper seeks to find which of these three conditions hinders/promotes growth of textiles and apparel industry using Delphi Method. The Delphi method is essentially defined as “a method for measuring consensus among group of experts”. The method is used to analyze the characteristics of each condition (Political, Economic and Cultural (PEC)) in no order of priority. The paper further employed two multiple criteria decision making methods (Entropy and TOPSIS) to analyze the Delphi result. The paper found that, political system dummy is economic system but not cultural environment. The textiles and apparel industry suffers negatively/positively if government 70
  2. 2. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION disarray/array the political system which intend affect the economic system negatively/positively but does not affect the cultural environment. The textiles and apparel industry can fuse their cultural practice into their company strategy for efficient and effective productivity. The rest of the paper is organized as follows; section 2 covers Delphi method, questionnaires and Delphi method steps whiles section 3 describes the methodology. Section 4 touches on results discussion and finally section 5 conclude with conclusion and limitations. 2. Delphi Method The Delphi method was developed at Rand Corporation by Olaf Helmer, the Delphi method is based on expert opinion 24. This was necessary because the existing methods of forecasting were insufficient to generate the report wanted because historical data for this subject were unavailable. In such cases, when a reliable forecast must be issued by qualitative means, the Delphi Method is generally preferred. The Delphi method is a structured technique used to generate forecasting in business, technology, science, education, health and other fields. The traditional Delphi Method aims to identify a consensus from the experts, on the research problem under consideration. Delphi Method is essentially defined 25 as “a method for measuring consensus among group of experts”. The method is a long-range forecasting method of aggregating the forecast of experts on multidisciplinary issues, it is an interactive process for soliciting and collating opinions on a particular topic, through a set of carefully designed sequential questionnaires with a summarized feedback of opinions derived from earlier responses 26. The Delphi methodology has it strength and weakness. Some of its strengths are: can produce agreements when other methods may not be possible, time for reflection, improving the strength of opinion, learning and motivating experience for participants, and participants have an equal say whiles its weakness are: can be extremely time consuming for participants, ambiguity regarding panel size and consensus levels required, fatigue tendency and care needed to avoid facilitator bias. This paper is the first paper to use Delphi Method of forecasting in a different fashion to analyze the characteristics of government, economic and cultural environment affecting textile and apparel industries. 2.1 Questionnaires The questionnaires were coin from the characteristics of political systems, economics systems and cultural environment that affect the textiles and apparel industry. These characteristics that affect textiles and apparel industries were listed and analyzed one by one. The questionnaires come in three (3) folds. The first questionnaire aimed at capturing more characteristics of PEC as per the one stated in appendix 1. The second analyze each characteristics of PEC by grade: points 1 represent strong disagreement whiles 7 points indicates a strong agreement (i.e. 1≡ 20% to 7≡ 95%). The entire questionnaires are displayed in appendix 2a to 2c. 2.2 Delphi Method Application and Steps The essence of the Delphi Method is to use the assessment of opinions and predictions made by a number of experts; it is an interactive process used to collect and distil the judgment of experts using a series of questionnaires in a number of stages 27. The Delphi Method comprises several steps involving participants, who may or may not meet face to face. The Delphi research team (DRT) comprise of 7 PHD scholars, made of three males and four females: 7 where chosen in case of any dead heat. Each classification political, economic and cultural environment was analyzed based on their characteristics and reports were taken as per their characteristics table. The DRT grade each PEC characteristics on 1 to 7 points. The DRT took two weeks to deliberate on each classification characteristics affecting textiles and apparel industry. After these deliberations all the analysis by each steps on PEC’s characteristics affecting textile and apparel industry were arranged in a table form (shown in appendix 5, 6 and 7) for further analysis using entropy and TOPSIS. Delphi method steps for each PEC’s: Step 1, (Individual Analysis): Each DRT member was giving questionnaire 1 (appendix 2) to compare 24 James A. & Mona J Fitzsimmons “Service Management Operations, Strategy and Information Technology”, 2002. 25 Burns et al. 26 Tam et al., (2006) 27 Skulmoski et al. (2007) 71
  3. 3. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION with those stated in the characteristics table in appendix 1. This was amide to extract more characteristics of each PEC’s from the individual analyst. They proceeded to the second questionnaire by awarding grade to each PEC’s and in step 1 each DRT member did independent analysis (not meeting face to face). Step 2 (Group Analysis): The 7 DRT members were divided into two groups (i.e. 3:4 per group). Each group skips questionnaire 1 but all the additional characteristics raised by each individual analyst were amalgamated into the updated PEC characteristics table shown in appendix 3. The groups proceed with questionnaire 2 and award grades and to each updated PEC characteristics. Step 2 is far different from step one since most of the grades were awarded by intense deliberation, debate and consensus reaching. Step 3 (DRT Analysis): This stage the 7 DRT members did the analysis of the each PEC characteristics together. They also skip questionnaire 1 and deal attentively with questionnaire 2 grading the updated PEC characteristics. This step is time consuming and needs a lot of patient in terms of deliberations and approving each grade. In concluding their task they gather all the various steps works and formed a PEC characteristics table (appendix 5, 6 and 7) by finding the mean average of each PEC characteristics analyzed in each step. 3. Methodology Multiple criteria decision making method (MCDM) is a decision making analysis method which has being developed since 1970. A decision making problem is the process of finding the best option from all feasible alternatives. A MCDM problem can be concisely expressed in a matrix format as: Where A1, A2, A3… Am are possible alternatives among which decision makers have to choose, C1, C2, C3… Cn are criteria with which alternatives performance are measured, Xij is the performance value alternatives Ai with respect to criterion Cj and wj is the weight of criterion Cj. Two MCDM related methods are discussed below. 3.1 Entropy Entropy is a concept use to measure information that is the average amount of information (Ding and Shi, 2005). In this paper we calculate the Delphi analysis index weight by using entropy. Entropy method of weight calculation is highly reliable, free of decision makers’ biasness and can be easily adopted (Zou et al. 2005). If a decision matrix B shown above with m alternatives and n indicators entropy steps of weight calculation are as follows: In matrix B, feature weight pij is of the ith alternatives to the jth factor, The output entropy ej of the jth factor becomes, Variation coefficient of the jth factor gj can be defined by the following equation, Note that the larger gj is the higher the weight should be. Calculate the weight of entropy wj, 72
  4. 4. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION 3.2 Technique for Order Preference by Similarity to Ideal Solution Method (TOPSIS) Hwang and Yoon (1981) developed the techniques for order preference by similarity to ideal solution (TOPSIS) method to rank alternative over multiple criteria. TOPSIS finds the best alternatives by minimizing the distance to the ideal solution and maximizing the distance to the nadir or negative-ideal solution (Jahanshahloo et al 2006). Several researchers have used TOPSIS in evaluating several MCDM (Tetteh 2012, Kou et al. 2011, Dai and Wang 2011, Uyun and Riadi 2011, Shahanaghi and Yazdian 2008, Chen 2000) problems. TOPSIS six steps listed below: Calculate the normalized decision matrix A. The normalized value aij is calculated as; Calculate the weighted normalized decision matrix, Were wj is the weight of the ith criterion and Calculate the ideal solution V+ and the negative ideal solution V-, Calculate the separation measures, using the m-dimensional Euclidean distance, Calculate the relative closeness to the ideal solution Where The larger Yi is, the closer the alternative is to the ideal solution. The larger TOPSIS value, the better the alternative. 4. Results Discussion 4.1 Political System Political system (democracy, communist, religious, etc.) in nations was not of great interest in this research since this research was interested in the benefits political system provides for textile and apparel industry to function effectively and efficiently. Individual analysis, group analysis and 7 DRT members analysis were grouped together into a table format by finding their average of each political characteristic (appendix 5) for entropy and TOPSIS analysis. Entropy analysis were used to obtained the various weight for each analysis (ten in number) and the result were shown in appendix 5a. TOPSIS followed entropy analysis to rank political characteristics and TOPSIS top five characteristics are: effective economy, peace, good education system, fight against corruption and government laws (appendix 5b). Thou TOPSIS analysis ranked peace number two top characteristics, the 7 DRT members’ final conclusions were in every political system, what textiles and apparel industry valued most is peace since without peace whatever production the industry creates cannot see the light of profit. 4.2 Economic System The same procedure used for political system were administered to economic system in terms of how economic benefit affect textiles and apparel industry (entropy weight, appendix 6a) but an interesting revelation cropped up: for any economic system to function effectively and efficiently it depends on the political system of the day. The DRT realized that the political system puppet is economic system. This revelation is proved in the TOPSIS analysis of political system characteristics were effective economy were ranked number one. TOPSIS rank for economic characteristics are: 73
  5. 5. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION inflation, information technology, purchasing power of money, capital and exchange rate (appendix 6b). 4.3 Cultural Environment Under cultural environment the panel proceeded with the same analysis as per that of political system and economic system. The DRT members realized that cultural environment cannot be influenced by any political system or economic system. Entropy weight analysis is shown in appendix 7a and TOPSIS top five rank characteristics that affect textiles and apparel industry are; language, attitude, food, belief system, color perception and religion (appendix 7b). Conclusion and Limitations This paper has utilized Delphi method of forecasting in another fashion to analyzed political system, economic system and cultural environment that affect textile and apparel industry. After Delphi analysis we used two MCDM entropy and TOPSIS to further analyze each PEC’s characteristics after all the Delphi steps were arranged in a table format. From our analysis we can conclude that in any country, political party in power controls the economic and political system. If the government manipulates the political and economic system in any conventional/unconventional fashion it affects textiles and apparel industry in a positive/negative way. Textiles and apparel industry should fuse their cultural system into their organization structure since political and economic systems cannot manipulate its effective usage in their organization system. The limitations of this paper are: (i) small DRT member size, (ii), consensus difficulty and (iii) time frame for DRT members’ discussion on each issue were not enough. References Asplet, M., Cooper M. (2000), Cultural Designs in New Zealand Souvenir Clothing, Tourism Management, Vol. 21, pp. 307-312. Burns T., Fiander M., Bernard A. (2000), A Delphi approach to characterizing relapse as used in UK clinical practice, International Journal of Social Psychiatry, vol. 46, no. 3. Dai L. and Wang J., (2011), Evaluation of the Profitability of Power Listed Companies Based on Entropy Improved TOPSIS Method”, Science Direct, Vol. 15, pp. 4728 – 4723. Ding S., and Shi Z., (2005), Studies on Incident Pattern Recognition Based on Information Entropy”, Journal of Information Science, Vol. 31, No. 6, pp. 497-294. Fitzsimmons J. A., Fitzsimmons M. J. (2001), Service Management Operation, Strategy and Information Technology, pp. 260. Hwang C.L., and Yoon K., (1981), Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag: New York. Jahanshahloo G.R., Hosseinzadeh L. F., and Izadikhah M. (2006), Extension of the TOPSIS Method for Decision-Making, Applied Mathematics and Computation, Vol. 181, No. 2, pp.1544 – 1551. Kim, G, (2011) U.S. Textile and Apparel Trade Policy Update, Deputy Assistant Secretary for Textiles and Apparel International Trade Administration U.S. Department of Commerce USA-ITA. Kou G., Wu, W., Zhao, Y., Peng, Y., Nti, E. Y., Shi, Y. (2011), A Dynamic Assessment Method for Urban Eco-environmental Quality Evaluation, Journal of Multi-Criteria Decision Analysis, Vol. 18, pp. 23-38. Lazăr, C., Lazăr, M. (2008), Seria Delphi - The Highest Qualitative Forecast Method, Ştiinţe Economice, Vol. LX, No. 1, pp. 31-31. Peng, Y., (2000), “Management Decision Analysis”, Peking: Science Publication. Shahanaghi, K. and Yazdian, S. A. (2009), Vendor Selection Using a New Fuzzy Group TOPSIS Approach, Journal of Uncertain System, Vol. 3, No. 3, pp. 221-231. Skulmoski, G., Hartman, F., Krahn, J. (2007), The Delphi Method for Graduate Research, Journal of Information Technology Education, vol.6. Tam, L. W. H., Mills, J. (2006), Proceedings of the Asia –Pacific Conference on Library & Information Education & Practice, Singapore. Tetteh, A. (2012), Cell Phone Evaluation Base on Entropy and TOPSIS, Interdisciplinary Journal of Research in Business, Vol. 1, No. 12, pp. 9-15. 74
  6. 6. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION Uyun, S., Riadi, I. (2011), A Fuzzy Topsis Multiple-Attribute Decision Making for Scholarship Selection, Telkomnika, Vol. 9, No. 1, pp. 37-46. Zou Z, Sun J, and Ren G., (2005), Study and Application on the Entropy Method for Determination of Weight of Evaluating Indicators in Fuzzy Synthetic Evaluation for Water Quality Assessment, ACTA Scientiae Circumstantiae, Vol. 25, No. 4, pp. 552 – 556. Acknowledgement I wish to thank the entire PhD colleagues for participating in this analysis. My regards also goes to two anonymous reviewers for their constructive and helpful comments. Appendix Appendix 1, Characteristics of PEC Affecting Textile and Apparel Industry Political System Economic System Cultural Environment Peace Land Belief System Government Laws Labor Language Basic needs Provision (Water, Capital Attitudes Electricity, fuel and other) Good Education System Inflation Religion Effective Economy Exchange Rate Food High Efficiency and Promptly Entrepreneurship Music Effective Reaction to Emergency Situations Fight Against Corruption Roads, Railways, Aviation Dance Right to Vote Ports and Harbor Ornaments Right of Association Information, Technology Appendix 2a: Questionnaires to capture more PEC’s Characteristics Questions 1. Do you agree that all the characteristics listed in appendix 1 affect PEC’s? 2. If No, list other characteristics that affect PEC. Appendix 2b: PEC’s Characteristics Affecting Textile and Apparel Industry Questions 1 1. 2. 3. 4. 5. 2 Yes GRADES 3 4 5 No 6 7 How do you value peace in a Nations? How do you value peace in textile and apparel production? How does peace in a Nation affect textile and apparel industry? How does peace affect the profit of textile and apparel industry? How does peace propel the Textile and apparel industry? Note: 1. Strong Disagreement; 2. Disagreement; 3. Disagree Somewhere; 4. Uncertain; 5. Agree Somewhere; 6. Agree; and 7. Strong Agreement 75
  7. 7. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION Appendix 3: Updated PEC’s Characteristics Affecting Textile and Apparel Industry Political System Economic System Cultural Environment Peace Land Belief System Government Laws Labor Language Basic needs Provision (Water, Capital Attitudes Electricity, fuel and other) Good Education System Inflation Religion Effective Economy Exchange Rate Food High Efficiency and Promptly Entrepreneurship Music Effective Reaction to Emergency Situations Fight Against Corruption Roads, Railways, Aviation Dance Right to Vote Ports and Harbor Ornaments Right of Association Information, Technology Color Perception Tax system Interest rate Factory Incentives Import / Export duties Purchasing Power of Money Appendix 4: Delphi Method Steps Delphi Research Team (7 PHD Scholars) Expert 1 Expert 2 Expert 3 FIRST ROUND FIRST ROUND FIRST ROUND Expert 4 FIRST ROUND Expert 5 Expert 6 Expert 7 FIRST ROUND FIRST FIRST ANSWERS FIRST ROUND QUSTIONS SECOND ROUND SECOND ROUND SECOND ROUND SECOND ROUND SECOND ROUND SECOND ROUND SECOND ROUND ANSWERS SECOND ROUND QUSTIONS THIRD ROUND THIRD ROUND THIRD ROUND THIRD ROUND THIRD ROUND ANSWERS THIRD ROUND QUSTIONS 76 THIRD ROUND THIRD ROUND
  8. 8. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION Appendix 5: Political Characteristics Table. PhD 1 PhD 2 PhD 3 PhD 4 PhD 5 PhD 6 PhD 7 Group 1 Group 2 DRT Good Education System -0.20046 -0.19512 -0.21436 -0.20523 -0.21296 -0.21894 -0.21203 -0.24702 -0.20430 -0.20627 Government Laws -0.22291 -0.24203 -0.20398 -0.20755 -0.20763 -0.21778 -0.22437 -0.21358 -0.21968 -0.21301 Effective Economy -0.22319 -0.22115 -0.21646 -0.23061 -0.21239 -0.21217 -0.20399 -0.23117 -0.20220 -0.20836 Peace -0.22449 -0.23139 -0.19641 -0.21059 -0.20787 -0.20744 -0.21371 -0.23431 -0.20940 -0.22046 Factory Incentive -0.19788 -0.22854 -0.19922 -0.20882 -0.20245 -0.20957 -0.21912 -0.22361 -0.21943 -0.21094 High Efficiency and Prompt Action -0.22344 -0.21133 -0.22473 -0.22868 -0.22230 -0.22464 -0.21912 -0.20903 -0.22460 -0.22071 Fight Against Corruption -0.22838 -0.21359 -0.23394 -0.20755 -0.20613 -0.20982 -0.24218 -0.20903 -0.23260 -0.23089 Right to Vote -0.22037 -0.21359 -0.22691 -0.23166 -0.23042 -0.22987 -0.21374 -0.20602 -0.22204 -0.21579 Right of Association -0.21000 -0.21861 -0.21898 -0.22327 -0.23071 -0.20772 -0.21943 -0.20602 -0.21461 -0.22071 Tax System -0.21755 -0.21109 -0.22124 -0.22091 -0.23016 -0.22727 -0.21646 -0.20602 -0.22460 -0.22834 Basic Needs Provision -0.22627 -0.20672 -0.23672 -0.22014 -0.23120 -0.23038 -0.21097 -0.20602 -0.22204 -0.22071 Ej 0.99877 0.99803 0.99794 0.99880 0.99846 0.99904 0.99884 0.99748 0.99900 0.99928 dj 0.00123 0.00197 0.00206 0.00120 0.00154 0.00096 0.00116 0.00252 0.00100 0.00072 wj 0.08577 0.13713 0.14343 0.08366 0.10699 0.06687 0.08075 0.17564 0.06967 0.05010 Appendix 5a: Political Characteristics data after Normalization, Entropy value and variation coefficient. PhD 1 PhD 2 PhD 3 PhD 4 PhD 5 PhD 6 PhD 7 Group 1 Group 2 DRT Good Education System 4.46421 4.32995 4.86180 4.28347 4.57403 4.61405 4.49267 5.55087 4.27491 4.22012 Government Laws 5.34167 6.26880 4.47276 4.36483 4.38284 4.57214 4.95073 4.29202 4.83334 4.45475 Effective Economy 5.35322 5.34167 4.94317 5.23184 4.55322 4.37339 4.21066 4.92326 4.20210 4.29202 Peace 5.40789 5.78208 4.20210 4.47276 4.39140 4.21066 4.55322 5.04254 4.45475 4.72451 Factory Incentive 4.36996 5.65711 4.30148 4.40941 4.20210 4.28347 4.75198 4.64404 4.82388 4.38194 High Efficiency and Prompt Action 5.36367 4.94317 5.27375 5.15446 4.92326 4.82388 4.75198 4.13876 5.02263 4.73396 Fight Against Corruption 5.57287 5.03309 5.66070 4.36483 4.32995 4.29202 5.67225 4.13876 5.34167 5.12201 Right to Vote 5.23661 5.03309 5.36367 5.27375 5.24229 5.02263 4.55412 4.03938 4.92326 4.55412 Right of Association 4.82388 5.23661 5.04254 4.94317 5.25384 4.22012 4.76333 4.03938 4.64404 4.73396 Tax System 5.12201 4.93371 5.13246 4.85325 5.23184 4.92326 4.65350 4.03938 5.02263 5.02263 Basic Needs Provision 5.48295 4.76333 5.78208 4.82388 5.27375 5.04254 4.45475 4.03938 4.92326 4.73396 Appendix 5b: Political Characteristics separation measure Si+, Si- , relative closeness Yi and ranking Si+ SiYi Ranking Good Education System 0.02119 0.01909 0.92002 3 Government Laws 0.02092 0.01731 0.84469 5 Effective Economy 0.01684 0.01643 0.99182 1 Peace 0.01880 0.01759 0.95329 2 Factory Incentive 0.02134 0.01334 0.63851 9 High Efficiency and Prompt Action 0.02103 0.01451 0.70434 8 Fight Against Corruption 0.02123 0.01782 0.85724 4 Right to Vote 0.02171 0.01592 0.74925 7 Right of Association 0.02215 0.01364 0.62956 11 Tax System 0.02242 0.01390 0.63393 10 Basic Needs Provision 0.02263 0.01777 0.80331 6 77
  9. 9. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION Appendix 6: Economic Characteristic Table. Appendix 6a: Economic Characteristics data after Normalization, Entropy value and variation coefficient. PhD 1 PhD 2 PhD 3 PhD 4 PhD 5 PhD 6 PhD 7 Group 1 Group 2 DRT Land -0.21905 -0.19661 -0.19629 -0.19596 -0.20569 -0.20320 -0.19927 -0.20667 -0.21386 -0.21373 Labor -0.20905 -0.20735 -0.21109 -0.21076 -0.21306 -0.19760 -0.19696 -0.20691 -0.21410 -0.19887 Capital -0.19922 -0.21515 -0.21109 -0.20003 -0.22061 -0.18897 -0.21395 -0.22491 -0.22688 -0.21625 Road, Rail, Aviation -0.22925 -0.19309 -0.19472 -0.19076 -0.21079 -0.19165 -0.20803 -0.20970 -0.20910 -0.20379 Interest Rate -0.18784 -0.22042 -0.20347 -0.20251 -0.21332 -0.20058 -0.21472 -0.22183 -0.21806 -0.18818 Inflation -0.19897 -0.20760 -0.20152 -0.20496 -0.19827 -0.23577 -0.19462 -0.19097 -0.19452 -0.20645 Exchange Rate -0.20394 -0.22264 -0.21391 -0.22773 -0.18238 -0.22000 -0.19978 -0.21169 -0.20396 -0.21142 Entrepreneurship -0.21641 -0.19615 -0.20850 -0.19845 -0.19655 -0.22000 -0.19978 -0.20200 -0.20396 -0.21373 Information and Technology -0.19681 -0.20516 -0.21264 -0.21996 -0.22114 -0.22277 -0.20285 -0.19301 -0.18730 -0.21142 Port and Habor -0.20902 -0.20999 -0.21109 -0.21027 -0.18667 -0.20091 -0.20803 -0.21441 -0.21923 -0.20645 Import/Export -0.20878 -0.19772 -0.20826 -0.21237 -0.21355 -0.19286 -0.20204 -0.20225 -0.20396 -0.21142 Purchasing Power of Money -0.20281 -0.21023 -0.21109 -0.20788 -0.21796 -0.20399 -0.24007 -0.19721 -0.18507 -0.20134 Ej 0.99849 0.99888 0.99951 0.99869 0.99802 0.99734 0.99806 0.99866 0.99802 0.99925 dj 0.00151 0.00112 0.00049 0.00131 0.00198 0.00266 0.00194 0.00134 0.00198 0.00075 wj 0.10019 0.07435 0.03280 0.08714 0.13100 0.17628 0.12846 0.08914 0.13102 0.04962 Appendix 6b: Political Characteristics separation measure Si+, Si- , relative closeness Yi and ranking. Si+, SiYi Ranking Land 0.66852 8 0.01478 0.64418 11 0.02015 0.87477 4 0.02463 0.01559 0.64861 10 Interest Rate 0.02137 0.01729 0.82654 6 Inflation 0.02227 0.02099 0.96359 1 Exchange Rate 0.02128 0.01763 0.84581 5 Entrepreneurship 0.02062 0.01617 0.80056 7 Information and Technology 0.02113 0.01943 0.93899 2 Port and Harbor 0.02251 0.01460 0.66298 9 Import/Export 0.02503 0.01305 0.53427 12 Purchasing Power of Money 0.02145 0.01963 0.93514 3 0.02251 Labor 0.02348 Capital 0.02358 Road, Rail, Aviation 0.01472 78
  10. 10. WORLD ACADEMIC JOURNAL OF BUSINESS & APPLIED SCIENCES-MARCH-SEPTEMBER 2013 EDITION PhD 1 PhD 2 PhD 3 PhD 4 PhD 5 PhD 6 PhD 7 Group 1 Group 2 DRT 5.03309 5.03309 4.73396 4.54467 4.37339 6.01328 4.46331 5.24229 5.54918 4.62261 5.25175 4.74342 4.55412 4.66206 4.68197 4.73396 4.83334 5.12201 4.38194 6.12814 5.03309 4.83334 4.54467 4.56268 4.80334 4.88171 4.63459 5.13246 5.42591 5.00309 5.90345 4.92326 4.45475 4.45475 4.37339 5.78208 4.96118 4.55412 5.00309 4.98109 4.96307 4.85325 4.84280 4.64404 4.79179 5.05299 5.77052 4.65350 4.69052 4.55412 5.12201 4.73396 4.54467 4.37339 4.19355 5.55087 4.73396 5.13246 5.06056 4.83811 5.24229 5.12201 4.63459 4.64404 4.20210 5.33121 4.63459 5.12201 5.08445 5.46782 5.13246 4.63459 4.45475 4.36483 4.38284 5.67225 4.55412 5.23184 5.89462 4.69052 5.22139 4.83334 4.45475 4.21066 4.46421 6.01328 4.31004 4.82388 5.38645 5.02741 Appendix 7: Cultural Characteristic Table. Appendix 7a: Cultural Characteristics data after Normalization, Entropy value and variation coefficient. PhD 1 PhD 2 PhD 3 PhD 4 PhD 5 PhD 6 PhD 7 Group 1 Group 2 DRT Belief System -0.23952 -0.24890 -0.24855 -0.24558 -0.24111 -0.25736 -0.23545 -0.25041 -0.25375 -0.23286 Language -0.24516 -0.24100 -0.24339 -0.24898 -0.25020 -0.22570 -0.24600 -0.24731 -0.22264 -0.27058 Dance -0.23952 -0.24350 -0.24311 -0.24611 -0.25363 -0.22969 -0.24042 -0.24758 -0.25074 -0.24330 Religion -0.26086 -0.24595 -0.24046 -0.24292 -0.24111 -0.25209 -0.24949 -0.23178 -0.23993 -0.24271 Ornaments -0.23767 -0.24404 -0.25159 -0.24847 -0.25331 -0.23419 -0.26986 -0.23460 -0.23146 -0.23091 Music -0.24184 -0.24074 -0.24311 -0.24048 -0.23557 -0.24663 -0.24323 -0.24758 -0.24145 -0.23885 Attitude -0.24492 -0.25124 -0.24572 -0.24847 -0.23584 -0.24126 -0.24042 -0.24731 -0.24207 -0.25518 Food -0.24211 -0.23793 -0.24046 -0.24022 -0.24140 -0.24952 -0.23811 -0.25014 -0.26189 -0.23477 Color Perception -0.24439 -0.24350 -0.24046 -0.23547 -0.24384 -0.25736 -0.23088 -0.23934 -0.24976 -0.24394 Ej 0.99944 0.99980 0.99983 0.99976 0.99945 0.99844 0.99847 0.99946 0.99840 0.99813 dj 0.00056 0.00020 0.00017 0.00024 0.00055 0.00156 0.00153 0.00054 0.00160 0.00187 wj 0.06360 0.02230 0.01978 0.02761 0.06179 0.17634 0.17361 0.06120 0.18163 0.21214 Appendix 7b: Cultural Characteristics separation measure Si+, Si- , relative closeness Yi and ranking. Si+, SiYi Ranking Belief System 0.02695 0.01973 0.75174 6 Language 0.02526 0.02318 0.94077 1 Dance 0.02505 0.01484 0.60722 8 Religion 0.02192 0.01712 0.79838 5 Ornaments 0.02845 0.01860 0.67229 7 Music 0.02493 0.01372 0.56404 9 Attitude 0.02080 0.01719 0.84334 2 Food 0.02548 0.02087 0.83990 3 Color Perception 0.02447 0.01936 0.81039 4 79

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