本論文延伸過去的品牌標誌變更的研究，以採集實體的圖檔數據的方式來更深入的探討及分析標示變更對消費著的影響，圖檔的數據採集主要分為三大塊分別為標籤，標誌，及屬性並以變數的形式運用在廣義估計方程式 Generalized Estimating Equation (GEE)建構成研究模型來分析。此外，本研究也針對因分析的變更標誌採集了網路上消費著對此變更的回應加以分析，分析果顯示標籤及屬性的變更對消費著喜好上占有極大的正負面引響力及關連性，本研究希望可以透過提供此資訊來幫助未來的企業及設計顧問在考量品牌的標示更新及變更設計時作為重要的參考。

This thesis extends the scope of quantitative investigation on rebranding specifically focusing on exploring the topic of logo change. The research was examine in a quantitative manner through extracting numerical data in terms of image entities. A machine learning application was used to evaluate the logos and outputs the image entities of web, logo, properties and relative label that is further use as a variable to generate a GEE model. The result of the investigation suggested that label and color property considered to be the most significance factors in influencing consumer preference especially with label text possessing the most significant values followed by label font and color property both with inverse effect. Cooperate and brand consultant should really consider these indicated factors while modifying their logos.

Abstract ................................ ................................ ................................ .......................... I
Table of Contents ................................ ................................ ................................ ......... III
List of Tables................................ ................................ ................................ ................. V
1. Introduction................................ ................................ ................................ ................ 1
2. Literature Review................................ ................................ ................................ ....... 3
2.1 Google Vision API ................................ ................................ ............................... 3
2.1.1 What is Google vision API?................................ ................................ .......... 3
2.1.2 How Cloud Vision API works................................ ................................ ....... 3
2.1.3 Cloud Vision API features................................ ................................ ............. 4
2.1.4 Past Studies using Google Cloud API................................ ........................... 5
2.2 Logo ................................ ................................ ................................ ..................... 5
2.2.1 Effectiveness of logo................................ ................................ ..................... 6
2.2.2. Logo visual equity................................ ................................ ........................ 7
2.2.3 Effects of colours on logos ................................ ................................ ........... 7
2.2.4 Logo aesthetics................................ ................................ .............................. 8
2.3 Logo change................................ ................................ ................................ ....... 10
2.3.1 Reasons for logo change ................................ ................................ ............. 10
2.3.2 Impact of logo change................................ ................................ ................. 12
3. Methodology ................................ ................................ ................................ ............ 13
3.1 Logos selection ................................ ................................ ................................ .. 13
3.2 Data collection and Sample size ................................ ................................ ........ 13
3.3 Consumer Review ................................ ................................ .............................. 14
3.4 Analysis Method ................................ ................................ ................................ 15
4. Results................................ ................................ ................................ ...................... 18
5. Conclusion and Discussion ................................ ................................ ...................... 21
IV
5.1 Limitations and Future Research ................................ ................................ ....... 22
References................................ ................................ ................................ .................... 24
Appendix................................ ................................ ................................ ...................... 27
6.1 Quantitative Research: 50 brand logos studied in this research ........................ 27
6.2 Google Vision API: Image labels return ................................ ............................ 27
6.3 Google Vision API: Image web return ................................ ............................... 28
6.4 Google Vision API: Image properties return................................ ...................... 28
6.6 Consumer Review ................................ ................................ .............................. 29

List of Tables
Figure 1: Google Vision API (Google Cloud, 2019) ................................ ................. 3
Figure 2: High in natural and harmony ................................ ................................ ..... 9
Figure 3: High in natural low in harmony ................................ ................................ .9
Figure 4: Low investment logos ................................ ................................ ................ 9
Figure 5: Poorly designed logos ................................ ................................ ................ 9
Figure 6: Overall model showing the process of data collection to data analysis... 14
Figure 7: GEE model information ................................ ................................ ........... 16
Figure 8: Basis descriptive statistic model ................................ .............................. 16
Figure 9: GEE model parameter estimates ................................ .............................. 18
Figure 10: Categorical variable information ................................ ........................... 19
Figure 11: Goodness of fit ................................ ................................ ....................... 19

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