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Case Study of Diffusion Models of
Mobile Industry in Greece
2018.10.24
Madeleine
Diffusion models of telecommunication
分析動機與目的:
• 個案探討的工具較偏向總經預測非個經預測 (整個pie)
• 了解diffusion of innovation -> 客戶對科技採納程度的分類,並依照
Rogers 的 S型擴散(成長)創新理論, 5種類客戶分布跟定義
• 2008 3G 情境類比現今,依據擴散模型做需求預估,比較擴散模型結果
個案分析步驟 :
1 Introduction
2 Mobile telecommunications sector in Greece—market overview
3 Diffusion models for mobile telecommunications
4 Model evaluation and results
4.1 Methodology for diffusion analysis – critical mass
4.2 Models evaluation and comparison – training data and real
data、MAPE
5 Conclusion
一、個案摘要 -希臘電信業市場狀況
60.3%
52.0%
34.6% 35.9%
14.5%
37.6% 37.6%
39.7%
33.5% 27.0% 18.8%
0.8%
7.6%
1996 1998 2002 2005
Vodafone (ex.
Panafon)
CosmOTE TIM (ex.
Telestet)
Q-Telecom
1. 驗證希臘電信用戶擴散(成長)率(the diffusion rate),證明S型(S-
shaped,sigmoid patterns)科技擴散(成長)模型適用於行動通訊/電信業
2. 希臘電信業擴散(成長)流程提供了滲透率幾個有趣的面向,像擴散(成長)速度、
競爭運營商數量兩者的相關性及其他社經、法規的面向
3. 以2G擴散(成長)流程的參數研究結果,個案分析所使用到選擇適當模型的技
巧(MAPE),可運用此分析方法來預估希臘或任何地方下一代電信網路的潛
在市場擴散(成長)型態
寡頭
市場
二、 電信業擴散(成長) 模型
2G >> 3G VS 4G >> 5G
從2000年開始,通信業界就在呼喊3G,但喊了幾年,直到2007、2008年才開始真正普
及,原因是3G的崛起,從iPhone開始
Bass Model
Fisher-Pry Model
Gompertx Model
S-shaped Model
FLOG Model
Box-Cox
三、技術採用生命週期
Technology Adoption LifeCycle
1957年Iowa State College 為分析玉米種子採購行為所提出。起先,該概念的提出並未獲
得許多迴響,一直要等到1962年Everett Rogers出版《創新的擴散》(Diffusion of
Innovations)一書後,才逐漸獲得學研界的重視。
落後者(laggards)
16% - neighbours
and friends are main
info sources, fear of
debt(落伍者)
晚期大眾(late majority)
34% - skeptical, traditional,
lower socio-economic
status (傳統百姓)
創新者(innovators)2.5% -
venturesome, educated,
multiple info sources,
greater propensity to take
risk (冒險家)
早期大眾(early
majority)34% -
deliberate, many
informal social
contacts (深思熟慮者)
早期採用者(early
adopters)13.5% -
social leaders,
popular, educated
(意見領袖)
critical
mass
臨界質量;臨界人數;群聚效應;
也是一個社會動力學的名詞,用來描述在一個社會系統裡,某件事情的存在已達
至一個足夠的動量,使它能夠自我維持,並為往後的成長提供動力 .
關鍵在算出反趨點/反曲點
S型擴散(成長)創新反趨點/反曲點,Bass 可以算出來
• 如果已經有很多用戶了,就會有越來越多用戶
• 如果現在沒有用戶,就沒人想成為該組織/公司的用戶
Bass重點,p、q、M
p : 原來就會用的用戶 (innovator)
q : network externality (imitator)
M -- the potential market (the
ultimate number of adopters)
p -- coefficient of
innovation
q -- coefficient of
imitation
Source : http://www.bassbasement.org/BassModel/Default.aspx
the Bass model, its parameters are estimated by
nonlinear least squares (NLS) regression,
Differentiation
微分, 再微分囉
• 𝜹, coefficient of diffusion
• the diffusion speed and
correlates the diffusion
rate with the actual and
maximum penetration.
• Y(t) , population that has
already adopted the
service
• Y(t) represents the total
penetration at time t.
• S, the saturation
level of the specific
technology (the
• maximum expected
adoption level)
• S-Y(t), the remaining
market potential
represented by
四、模型 : A differential equation for the
aggregated S-type diffusion models
模型比較
Ra-squared : the adjusted coefficient of multiple determination
Population in 2005, 10,964,000
S.E. standard error of estimate
Withheld sample : real data
Training data : historical data
五、結論
• 根據估算結果 𝐩 ≈ 𝟎. 𝟎𝟎𝟏 且 𝒒 ≈0.63,顯示希臘是 imitators的市場
• 所有模型都預測飽和度大於100%,主因是企業用戶、預付卡..等等,MO提供具吸引力的促案造成
churn effect
• Bass模型的計算統計誤差非常高,模型不適合此特定的數據集估計和預測。Gompertz模型未能成
功估算早期數據,因顯示出較高絕對錯誤,但在接下來的幾年提供準確的估計。Logistic家族模型
非常可靠地收斂實際數據,具較低的計算錯誤;根據本份分析報告,希臘在2003已達市場飽和及
被視為成熟到可以接受新一代的電信科技,Vodafone and Wind (ex. TIM Hellas)為了有更好的
ARPU已積極準備提供HSDPA (3.5G)
• 雖然3G (GSM)在希臘市場算比較慢推出,當時仍是寡頭市場,但創新擴散/成長仍邁向市場飽和,
主要是受採用者和非採用者之間的互動‘wordof-mouth’process (Bass, 1969),特別是在初期,
競爭對手的數量跟吸引用戶的密集和具說服力的營銷策略有關。到1998年,用戶數較前一年成長
一倍,固網電信商OTE在1997-1998電信市場起飛時加入,稍後2002第四家 MO Q-Telecom也進
入,即使在一個相當飽和的市場,希臘電信產業展現出市場潛力。
• 電信業是網路效應典型例子,此外,就競爭而言,希臘證明Geroski(2000)“過多的競爭會減緩
擴散”,但用戶數仍會隨時間而增加,關鍵因素是新技術(如3G和4G)的採用是最初的用戶/創新
者所影響的速度和擴散的範圍。
• 其他進一步的研究包括預付卡跟月付型的用戶選擇行為大不同,也有探討行、固網間的補貼或替代,
最後一個最重要的基本因子是價格,根據希臘這個個案,在過去的3 - 4年中,價格下降約54%,
而未來的趨勢將和其他歐洲國家一樣,行網成長,固網依舊。
• backup
Diffusion of mobile telephony in Greece
1994-2005
• population would face an annual growth of about 0.2% (page 8)
衡量預測精準度

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Case study of diffusion models of mobile industry in Greece

  • 1. Case Study of Diffusion Models of Mobile Industry in Greece 2018.10.24 Madeleine
  • 2. Diffusion models of telecommunication 分析動機與目的: • 個案探討的工具較偏向總經預測非個經預測 (整個pie) • 了解diffusion of innovation -> 客戶對科技採納程度的分類,並依照 Rogers 的 S型擴散(成長)創新理論, 5種類客戶分布跟定義 • 2008 3G 情境類比現今,依據擴散模型做需求預估,比較擴散模型結果 個案分析步驟 : 1 Introduction 2 Mobile telecommunications sector in Greece—market overview 3 Diffusion models for mobile telecommunications 4 Model evaluation and results 4.1 Methodology for diffusion analysis – critical mass 4.2 Models evaluation and comparison – training data and real data、MAPE 5 Conclusion
  • 3. 一、個案摘要 -希臘電信業市場狀況 60.3% 52.0% 34.6% 35.9% 14.5% 37.6% 37.6% 39.7% 33.5% 27.0% 18.8% 0.8% 7.6% 1996 1998 2002 2005 Vodafone (ex. Panafon) CosmOTE TIM (ex. Telestet) Q-Telecom 1. 驗證希臘電信用戶擴散(成長)率(the diffusion rate),證明S型(S- shaped,sigmoid patterns)科技擴散(成長)模型適用於行動通訊/電信業 2. 希臘電信業擴散(成長)流程提供了滲透率幾個有趣的面向,像擴散(成長)速度、 競爭運營商數量兩者的相關性及其他社經、法規的面向 3. 以2G擴散(成長)流程的參數研究結果,個案分析所使用到選擇適當模型的技 巧(MAPE),可運用此分析方法來預估希臘或任何地方下一代電信網路的潛 在市場擴散(成長)型態 寡頭 市場
  • 4. 二、 電信業擴散(成長) 模型 2G >> 3G VS 4G >> 5G 從2000年開始,通信業界就在呼喊3G,但喊了幾年,直到2007、2008年才開始真正普 及,原因是3G的崛起,從iPhone開始 Bass Model Fisher-Pry Model Gompertx Model S-shaped Model FLOG Model Box-Cox
  • 5. 三、技術採用生命週期 Technology Adoption LifeCycle 1957年Iowa State College 為分析玉米種子採購行為所提出。起先,該概念的提出並未獲 得許多迴響,一直要等到1962年Everett Rogers出版《創新的擴散》(Diffusion of Innovations)一書後,才逐漸獲得學研界的重視。 落後者(laggards) 16% - neighbours and friends are main info sources, fear of debt(落伍者) 晚期大眾(late majority) 34% - skeptical, traditional, lower socio-economic status (傳統百姓) 創新者(innovators)2.5% - venturesome, educated, multiple info sources, greater propensity to take risk (冒險家) 早期大眾(early majority)34% - deliberate, many informal social contacts (深思熟慮者) 早期採用者(early adopters)13.5% - social leaders, popular, educated (意見領袖) critical mass
  • 6. 臨界質量;臨界人數;群聚效應; 也是一個社會動力學的名詞,用來描述在一個社會系統裡,某件事情的存在已達 至一個足夠的動量,使它能夠自我維持,並為往後的成長提供動力 . 關鍵在算出反趨點/反曲點 S型擴散(成長)創新反趨點/反曲點,Bass 可以算出來 • 如果已經有很多用戶了,就會有越來越多用戶 • 如果現在沒有用戶,就沒人想成為該組織/公司的用戶 Bass重點,p、q、M p : 原來就會用的用戶 (innovator) q : network externality (imitator) M -- the potential market (the ultimate number of adopters) p -- coefficient of innovation q -- coefficient of imitation Source : http://www.bassbasement.org/BassModel/Default.aspx the Bass model, its parameters are estimated by nonlinear least squares (NLS) regression,
  • 7. Differentiation 微分, 再微分囉 • 𝜹, coefficient of diffusion • the diffusion speed and correlates the diffusion rate with the actual and maximum penetration. • Y(t) , population that has already adopted the service • Y(t) represents the total penetration at time t. • S, the saturation level of the specific technology (the • maximum expected adoption level) • S-Y(t), the remaining market potential represented by 四、模型 : A differential equation for the aggregated S-type diffusion models
  • 8. 模型比較 Ra-squared : the adjusted coefficient of multiple determination Population in 2005, 10,964,000 S.E. standard error of estimate Withheld sample : real data Training data : historical data
  • 9. 五、結論 • 根據估算結果 𝐩 ≈ 𝟎. 𝟎𝟎𝟏 且 𝒒 ≈0.63,顯示希臘是 imitators的市場 • 所有模型都預測飽和度大於100%,主因是企業用戶、預付卡..等等,MO提供具吸引力的促案造成 churn effect • Bass模型的計算統計誤差非常高,模型不適合此特定的數據集估計和預測。Gompertz模型未能成 功估算早期數據,因顯示出較高絕對錯誤,但在接下來的幾年提供準確的估計。Logistic家族模型 非常可靠地收斂實際數據,具較低的計算錯誤;根據本份分析報告,希臘在2003已達市場飽和及 被視為成熟到可以接受新一代的電信科技,Vodafone and Wind (ex. TIM Hellas)為了有更好的 ARPU已積極準備提供HSDPA (3.5G) • 雖然3G (GSM)在希臘市場算比較慢推出,當時仍是寡頭市場,但創新擴散/成長仍邁向市場飽和, 主要是受採用者和非採用者之間的互動‘wordof-mouth’process (Bass, 1969),特別是在初期, 競爭對手的數量跟吸引用戶的密集和具說服力的營銷策略有關。到1998年,用戶數較前一年成長 一倍,固網電信商OTE在1997-1998電信市場起飛時加入,稍後2002第四家 MO Q-Telecom也進 入,即使在一個相當飽和的市場,希臘電信產業展現出市場潛力。 • 電信業是網路效應典型例子,此外,就競爭而言,希臘證明Geroski(2000)“過多的競爭會減緩 擴散”,但用戶數仍會隨時間而增加,關鍵因素是新技術(如3G和4G)的採用是最初的用戶/創新 者所影響的速度和擴散的範圍。 • 其他進一步的研究包括預付卡跟月付型的用戶選擇行為大不同,也有探討行、固網間的補貼或替代, 最後一個最重要的基本因子是價格,根據希臘這個個案,在過去的3 - 4年中,價格下降約54%, 而未來的趨勢將和其他歐洲國家一樣,行網成長,固網依舊。
  • 11. Diffusion of mobile telephony in Greece 1994-2005 • population would face an annual growth of about 0.2% (page 8)