臺灣博碩士論文加值系統

Nowadays fierce competition pushes any company to make decision faster and more accurate since any market changes can be more unpredictable. There then rises need to realize leading indicators of company performance to quickly evaluate the ongoing or planned strategies in a company; since it will give the managers to manage some decisions more accurately, fit, and reliable to the actual competition condition. This study proposes two new metrics as the leading indicators of company performance, namely advertising ‘reach’ and endorsement ‘likes’; and utilize best combination of marketing-mix elements to generate the highest profit for the company, with the profit being the lagging indicator of company performance. By using system dynamic approach and genetic algorithm to generate the highest profit of the company, this study will capture and utilize leading and lagging indicators that could be used to evaluate the performance of a company. This study uses the data from a small fashion company in Bandung, Indonesia. The result of the simulation that the higher the effectiveness of advertising and endorsement programs, the more they benefit the company in terms of Sales Volume and Number of Customers; while the higher the number of ‘reach’ and ‘likes’ will result in the bigger number of people aware of the existence of the brand.

Nowadays fierce competition pushes any company to make decision faster and more accurate since any market changes can be more unpredictable. There then rises need to realize leading indicators of company performance to quickly evaluate the ongoing or planned strategies in a company; since it will give the managers to manage some decisions more accurately, fit, and reliable to the actual competition condition. This study proposes two new metrics as the leading indicators of company performance, namely advertising ‘reach’ and endorsement ‘likes’; and utilize best combination of marketing-mix elements to generate the highest profit for the company, with the profit being the lagging indicator of company performance. By using system dynamic approach and genetic algorithm to generate the highest profit of the company, this study will capture and utilize leading and lagging indicators that could be used to evaluate the performance of a company. This study uses the data from a small fashion company in Bandung, Indonesia. The result of the simulation that the higher the effectiveness of advertising and endorsement programs, the more they benefit the company in terms of Sales Volume and Number of Customers; while the higher the number of ‘reach’ and ‘likes’ will result in the bigger number of people aware of the existence of the brand.

TABLE OF CONTENTS

ABSTRACT ii
ACKNOWLEDGEMENT iii
TABLE OF CONTENTS iv
LIST OF FIGURES viii
LIST OF TABLES x
CHAPTER 1 INTRODUCTION 1
1.1 Research Background 1
1.2 Research Questions 3
1.3 Research Objectives 3
1.4 Research Structure 3
CHAPTER 2 LITERATURE REVIEW 5
2.1 Performance Measurement System: Lagging vs. Leading Indicators 5
2.2 Constructs Review for Leading Indicators Development 7
2.2.1 Social Media Marketing 7
2.2.2 Brand Awareness 12
2.2.3 Brand Exposure 12
2.2.4 Advertisement in Social Media 13
2.2.5 Celebrity Endorsement in Social Media 14
2.2.6 Customer Engagement and Brand Post Popularity 15
2.2.7 Proposed Measure for Leading Indicators 15
2.3 Marketing Strategy: The Marketing Mix Elements 15
2.3.1. Product 16
2.3.2. Price 16
2.3.3. Place 16
2.3.4. Promotion 17
2.4 Proposed Measure for Lagging Indicators: Profit Optimization Approach 17
2.5 Theoretical Review of Modeling Approach 18
2.5.1 System Dynamics: A System Thinking Perspective 18
2.5.2 Genetic Algorithm 23
2.6 State of The Art and Research Position 25
CHAPTER 3 RESEARCH METHODOLOGY 33
3.1 Research Design 33
3.1.1. Problem Articulation (Boundary Selection) 34
3.1.2. Conceptual Model Development 34
3.1.3. Formulation of Dynamic Hypotheses 34
3.1.4. Formulation of Simulation Model 34
3.1.5. Model Testing 34
3.1.6. Scenarios Building 36
3.1.7. Scenarios Running 36
3.1.8. Comparison of scenarios 37
3.2 Object of The Study 37
3.3 Data Collection 37
3.4 Mathematical and Model Formulation for Profit Optimization Problem 37
3.5 Genetic Algorithm Structure 40
3.5.1. Initial Population 40
3.5.2. Fitness Evaluation 41
3.5.3. Crossover Mechanism 42
3.5.4. Mutation Mechanism 43
3.5.5. Stopping Criterion 44
3.6 System Dynamics Model Reference Used 44
3.6.1. Customer Model 45
3.6.2. Word-of-Mouth Model 46
3.6.3. Stock Model 47
CHAPTER 4 MODELS, FINDINGS, and ANALYSIS 48
4.1 Problem Articulation (Boundary Selection) 48
4.2 Conceptual Model Development 49
4.2.1 Summary of Interview Result 49
4.2.2 Additional Data Collection: Social Media Marketing Managers 52
4.2.3 Modification of Vensim PLE Models 53
4.3 Formulation of Dynamic Hypotheses 55
4.3.1. Model Boundary Chart 55
4.3.2. Causal-Loop Diagram 57
4.4 Formulation of Simulation Model 61
4.4.1. Gross Sales of Products Sub-model 62
4.4.2. Total Cost of Goods Sub-model 63
4.4.3. Revenue of Stores Sub-model 64
4.4.4. Total Overhead Cost Sub-model 65
4.4.5. Profit Sub-model 66
4.4.6. Seed Customers Sub-model 66
4.4.7. Customers Conversion Sub-model 67
4.4.8. People Aware Sub-model 69
4.5. Model Testing (Validation) 70
4.6. Formulation of Scenarios 72
4.7. Result of Simulation 76
4.7.1. Number of Customers 76
4.7.2. Sales Volume 77
4.7.3. Number of People Aware 78
4.7.4. Cumulative Profit 79
CHAPTER 5 CONCLUSION 81
5.1 Conclusion 81
5.2 Managerial Implication 82
5.3 Discussion, Limitation, and Suggestions for Future Research 82
REFERENCES 85
APPENDICES 93

REFERENCES

2016-2018 Research Priorities, Marketing Science Institute website, retrieved 7 December 2016 from http://www.msi.org/research/2016-2018-research-priorities//
Aaker, D. A. (1996). Measuring Brand Equity Across Products and Markets. California Management Review, 38(3), 102-120.
Anderson, C. H., and Vincze, J. W., 2006, Strategic marketing, 02 ed., pp. 392-400, New Delhi: Biztantra India.
Anggraeni, A., & Rachmanita. (2015). Effects of Brand Love, Personality and Image on Word of Mouth; the Case of Local Fashion Brands among Young Consumers. Paper presented at the 2nd Global Conference on Business and Social Science 2015, Bali, Indonesia.
Anjomshoae, A., Hassan, A., Kunz, N., Wong, K. Y., & Leeuw, S. d. (2017). Toward a dynamic balanced scorecard model for humanitarian relief organization’s performance management. Journal of Humanitarian Logistics and Supply Chain Management, 7(2), 194-218.
Assaf, A. G., Josiassen, A., Mattila, A. S., & Cvelbar, L. K. (2015). Does Advertising Spending Improve Sales Performance? International Journal of Hospitality Management, 48, 161-166. doi:http://dx.doi.org/10.1016/j.ijhm.2015.04.014
Baumann, C., Hamin, H., & Chong, A. (2015). The role of brand exposure and experience on brand recall - Product durables vis-a-vis FMCG. Journal of Retailing and Consumer Services, 23, 21-31.
Bednář, V. (2011). Marketing na sociálních sítích: Prosaďte se na Facebooku a Twitteru. 1st edition. Brno: Computer Press. 304 p.
Boateng, P., Chen, Z., Ogunlana, S., & Ikediashi, D. (2013). A system dynamics approach to risks description in megaprojects development. Organization, Technology & Management in Construction, 5 Retrieved from http://search.proquest.com/docview/1506147548?accountid=31562.
Brønn, C., & Brønn, P. S. (2015). A Systems Approach to Understanding How Reputation Contributes to Competitive Advantage. Corporate Reputation Review, 18(2), 69-86. doi:10.1075/crr.2015.5
Bruhn, M., Schoenmueller, V., & Schäfer, D. B. (2012). Are Social Media Replacing Traditional Media in Terms of Brand Equity Creation? Management Research Review, 35(9), 770-790. doi:10.1108/01409171211255948
Castronovo, C., Huang, L., 2012, Social Media in an Alternative Marketing Communication Model, Journal of Marketing Development and Competitiveness, 6(1): 117-131.
Chanthinok, K., Ussahawanitichakit, P., Jhundra-indra, P., 2015, Social Media Marketing Strategy and Marketing Outcomes – A Conceptual Framework, Proceedings of the Academy of Marketing Studies, 19(2): 35-52.
Chianasta, F. P., & Wijaya, S., 2014, The Impact of Marketing Promotion through Social Media on People’s Buying Decision of Lenovo in Internet Era – A Survey of Social Media Users in Indonesia, International Journal of Scientific and Research Publications, 4(1): 1-6.
Chen, K. C. (2004). Decision Support System for Tourism Development: System Dynamics Approach. The Journal of Computer Information System, 45(1), 104-112.
Chernicoff, W. (2015). A System Dynamics Approach to Implementing Consumer Experience in Technology Adoption Models. (Doctor of Philosophy), George Washington University. (3671461)
Chuang, K.-W. (2011). Building A System Dynamics Simulation Model in Support of ERP Project Implementation. (Doctor of Philosophy), Purdue University.
Colliander, J., & Marder, B. (2018). ‘Snap happy’ brands: Increasing publicity effectiveness through a snapshot aesthetic when marketing a brand on Instagram. Computers in Human Behavior, 78, 34-33.
Dissanayake,D M N S W. (2012). INTEGRATED COMMUNICATIONS, INTEGRATED MARKETING COMMUNICATIONS AND CORPORATE REPUTATION: EVIDENCES FROM DELL COMPUTER CORPORATIONS. Researchers World, 3(3), 26-33. Retrieved from http://search.proquest.com/docview/1034611842?accountid=31562
Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68.
Farooq, F., Jan, Z., 2012, The Impact of Social Networking to Influence Marketing through Product Reviews, International Journal of Information and Communication Technology Research, 2(8): 627-637.
Forrester J.W. (1991) 'System Dynamics and the Lessons of 35 Years', in The Systemic Basis of Policy Making in the 1990s, De Greene K.B. (ed.).
Ghafoor, F., & Niazi, M. A. (2016). Using social network analysis of human aspects for online social network software: A design methodology. Complex Adaptive Systems Modeling, 4(1), 1-19. doi:http://dx.doi.org/10.1186/s40294-016-0024-9
Goldsmith, R. E., Laffert, B. A., & Newell, S. J. (2013). The Impact of Corporate Credibility and Celebrity Credibility on Consumer Reaction to Advertisements and Brands. Journal of Advertising.
Gonzalez, L. (2006). Performance Measurement Using Systems Dynamics in an SME. (Master of Science), University of Alberta, Edmonton, Alberta. (978-0-494-22270-6)
Hakimi, D., Oyewola, D., Yahaya, Y., & Bolarin, G. (2016). Comparative Analysis of Genetic Crossover Operators in Knapsack Problem. Journal of Applied Science in Environment and Management, 20(3), 593-596.
He, W., Zha, S., Li, L., 2013, Social Media Competitive Analysis and Text Mining: A Case Study in the Pizza Industry, International Journal of Information Management, 33: 464-472.
Hesamamiri, R., & Bourouni, A. (2016). Customer Support Optimization using System Dynamics: A Multi-Parameter Approach. Kybernetes, 45(6), 900-914.
Hoffman, D. L., & Fodor, M. (2010). Can you measure the ROI of your social media marketing? MIT Sloan Management Review, 52(1), 41-49. Retrieved from http://search.proquest.com/docview/757349606?accountid=31562
Iannone, R., Martino, G., Miranda, S., & Riemma, S. (2015). Modeling Fashion Retail Supply Chain through Causal Loop Diagram. Paper presented at the International Federation of Automatic Control 2015.
Internet World Stats, 2018, Internet Users in the World by Geographic Regions, https://www.internetworldstats.com/stats.htm, online accessed June 2018.
Jackson, M. C., 2003, Systems Thinking: Creative Holism for Managers, Great Britain: John Wiley & Sons Inc.
Jones, S. K., and Schee, B. A. V., 2008, Creative Strategy in Direct and Interactive Marketing and Integrated Marketing Communication Instruction, DMEF 2008 Direct/Interactive Marketing Research Summit Competitive Paper Extended Abstract, (pp. 2-4).
Keller, K. L., 2009, Building Strong Brands in A Modern Marketing Communications Environment, Journal of Marketing Communications, 15(2-3): 139-155.
Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. Journal of Marketing, 57(1), 1-22.
Khoo, D., 2014, How has the internet changed consumers over the past 10 years and how can marketers best adapt, http://www.brandba.se/blog/2014/8/11/how-has-the-internet-changed-consumers-over-the-past-10-years-and-how-can-marketers-best-adapt, online accessed June 2018.
Kilgour, M., Sasser, S. L., & Larke, R., 2015, The Social Media Transformation process – Curating Content into Strategy, Corporate Communications: An International Journal, 20(3): 326-343.
Kim, J., Lee, C., & Elias, T. (2015). Factors affecting information sharing in social networking sites amongst university students. Online Information Review, 39(3), 290-309. Retrieved from https://search.proquest.com/docview/1686054694?accountid=31562
Kirkwood C.W. (2005a) “A Modelling Approach”, [online], Arizona State University, www.public.asu.edu/~kirkwood/sysdyn/SDIntro/ch-2.pdf.
Kohli, C., Suri, R., Kapoor, A., 2015, Will Social Media Kill Branding?, Business Horizons, 58: 35-44.
Kohli, A. S. (2005). A Dynamic Simulation Study to Assess the Impact of Collaboration on the Performance of a Supply Chain. (Doctor of Philosophy), University of Louisville, Louisville, Kentucky. (3172281)
Kowalksa, M., 2012, The internet impact on market behavior of young consumers, Journal of International Studies, 5, 1, pp. 101-106.
Kotler, P., & Keller, K. L. (2012). Marketing Management (pp. 812).
Kumar, V., & Mirchandani, R. (2012). Increasing the ROI of social media marketing. MIT Sloan Management Review, 54(1), 55-61. Retrieved from http://search.proquest.com/docview/1115278029?accountid=31562.
Kunc, M. (2008). Using systems thinking to enhance strategy maps. Management Decision, 46(5), 761-778. doi:http://dx.doi.org/10.1108/00251740810873752.
Lee, S. & Yoo, S. 2012, Return on Marketing Investment: Pizza Hut Korea’s Case. Management Decision, 50(9): 1661-1685.
Lin, X. (2015). Exploring the business value of social media by examining users' information sharing behaviors, evaluation of benefits, and usage continuance decision making (Order No. 3732726). Available from ProQuest Dissertations & Theses Global: The Sciences and Engineering Collection. (1735491453). Retrieved from https://search.proquest.com/docview/1735491453?accountid=31562
Londhe, B. R. (2014). Marketing Mix for Next Generation Marketing. Paper presented at the Symbiosis Institute of Management Studies Annual Research Conference 2013.
Luna-Reyes L.F. & Andersen D.L. (2003) 'Collecting and analyzing qualitative data for system dynamics: methods and models', System Dynamics Review, Vol.19, No.4, pp. 271-296.
McCann, M., & Barlow, A. (2015). Use and measurement of social media for SMEs. Journal of Small Business and Enterprise Development, 22(2), 273-287. Retrieved from http://search.proquest.com/docview/1682159162?accountid=31562.
Neuman, W. L., 2006, Social Research Methods, United States: Pearson
Perreault, W. D., & McCarthy, E. J. (2002). Basic Marketing: A Global-Managerial Approach (pp. 848).
Otto, P. (2002). Understanding The Misbehavior of Brand Strategies: A Dynamic Modeling Approach. (Doctor of Philosophy), University of Albany, New York. (3053062)
Pirttilä, O., Kärkkäinen, H., & Jussila, J. J. (2016). Evaluating the business impacts of social media use with System Dynamics and Agent-Based Modeling: A Literature Review. INTERNATIONAL JOURNAL OF VIRTUAL COMMUNITIES AND SOCIAL NETWORKING, 8(2). DOI: 10.4018/IJVCSN.20160401Pomirleanu, N., Schibrowsky, J. A., Peltier, J., & Nill, A. (2013). A review of internet marketing research over the past 20 years and future research direction. Journal of Research in Interactive Marketing, 7(3), 166-181. doi:http://dx.doi.org/10.1108/JRIM-01-2013-0006
Pride, W. M., and Ferrel, O. C., 2006, Marketing concepts and strategies, (12 ed., pp. 432-459), New Delhi: Biztantra India
Pye, G., & Warren, M. (2011). Modelling relational aspects of critical infrastructure systems. Paper presented at the 202-210. Retrieved from http://search.proquest.com/docview/1010346794?accountid=31562.
Samodra, A. B., & Mariani, M., 2013, Examining the Influence of Social Norms on the Intention to Use Social Networking Media: A Study of Generation Z in Indonesia, GSTF International Journal on Computing, 3(1): 126-129.
Schultz, Don E., Tannenbaum, Stanley I., and Lauterborn, Robert F., 1993, Integrated Marketing Communications: Putting It Together & Making It Work. NTC Books: Lin-colnwood.
Scott, L. M., 2001, On reflection: Philosophy for a new curriculum, Journal of Advertising Education, 5(1), 5-9.
Selvakumar, J. J., & Vikkraman, P. (2011). Impact of Advertising and Price Promotions on Brand Equity in Service Sector. Journal of Contemporary Research in Management, 51-65.
Shojaee, S., & Azman, A. b. (2013). An Evaluation of Factors Affecting Brand Awareness in the Context of Social Media in Malaysia. Asian Social Science, 9(17), 72-78. doi:10.5539/ass.v9n17p72
Srivastava, R., 2015, Measuring the Effectiveness of the Communication Strategy by Using the Brand Score Technique – A Conceptual Study, Journal of Asia Business, 9(2): 133-146.
Svatosová, V. (2012). Social media such as the phenomenon of modern business. Journal of Marketing Development and Competitiveness, 6(4), 1-23. Retrieved from http://search.proquest.com/docview/1315304118?accountid=31562
Tang, C., Mehl, M. R., Eastlick, M. A., He, W., & Card, N. A. (2016). A Longitudinal Exploration of the Relations between Electronic Word-of-Mouth Indicators and Firm’s Profitability: Findings from the Banking Industry. Journal of Information Management, 36, 1124-1132. doi:http://dx.doi.org/10.1016/j.ijinfomgt.2016.03.015
Tang, C. M. (2015). HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP) MODEL. International Journal of Cyber Society and Education, 8(2), 81-98. doi:http://dx.doi.org/10.7903/ijcse.1383
Toldos-Romero, M. de la P., & Orozco-Gómez, Ma. M., 2015, Brand Personality and Purchase Intention, European Business Review, 27(5): 462-476.
Treviño, L. K., den Nieuwenboer, N. A., Kreiner, G. E., and Bishop, D. G., 2013, Legitimating the legitimate: A grounded theory study of legitimacy work among Ethics and Compliance Officers, Organizational Behavior and Human Decision Processes, 123: 186-205
Turner-August, S. (2015). The relationship between social networking and self-esteem (Order No. 3667249). Available from ProQuest Dissertations & Theses Global: The Sciences and Engineering Collection. (1646844035). Retrieved from http://search.proquest.com/docview/1646844035?accountid=31562
Twine, C., & Ruckman, J. E., 2005, Fibre Brand Promotion and Consumer Product Awareness: Case Study of Tactel, Journal of Fashion Marketing and Management, 9(3): 330-341.
Vries, L. d., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of Brand Posts on Brand Fan Pages: An Investigation of the Effects of Social Media Marketing. Journal of Interactive Marketing, 26, 83-91. doi:10.1016/j.intmar.2012.01.003
Wahab, N. A., Hassan, L. F. A., Shahid, S. A. M., & Maon, S. N. (2016). The Relationship between Marketing Mix and Customer Loyalty in Hijab Industry: The Mediating Effect of Customer Satisfaction. Paper presented at the Fifth International Conference on Marketing and Retailing 2015.
Wallace, E., Buil, I., & Chernatony, L. d. (2014). Consumer Engagement with Self-Expressive Brands: Brand Love and WOM Outcomes. JOurnal of Product & Brand Management, 23(1), 33-42. doi:10.1108/JPBM-06-2013-0326
Yang, C., & Yeh, C. (2014). Application of system dynamics in environmental risk management of project management for external stakeholders. Systemic Practice and Action Research, 27(3), 211-225. doi:http://dx.doi.org/10.1007/s11213-013-9283-y.
Yin, R. K., 2003, Case Study Research Design and Methods Third Edition, Applied Social Research Methods Series, 5: 126-163.
Zielinski, D. (2012). Find social media's value. HRMagazine, 57(8), 53-55. Retrieved from http://search.proquest.com/docview/1030259950?accountid=31562.