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Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake [email protected] Martin Weiss University of Pittsburgh [email protected]
15

Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake [email protected] Martin Weiss.

Dec 19, 2015

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Page 1: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

Strategic Options for Managing Technology Evolution in the Wireless Industry

Hak-Ju KimUniversity of Houston – Clear [email protected]

Martin Weiss University of [email protected]

Page 2: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

2

Introduction

Technology transitions are a way of life for wireless firms Various technology adoption paths exist

for firms migrate to 3G How can we frame this decision using

real options? The US is a good laboratory, since

multiple technologies exist

Page 3: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

3

Research Issues

1G 2G 3G

At a given point in time, t, the number of 3G subscribers =

(1) new to market +(2) migrated from 1G +(3) migrated from 2G

TAssuming that (1) Firm A uses 1G + 2G (i.e., Cingular-AT&T, Verizon) (2) Firm B uses 2G (i.e., Sprint, T-Mobile, Nextel) (3) Firm C uses 3G (potential firms)

t

• What is a firm’s migration strategy for 3G ?• How to measure the value of technology migration?

• What is a firm’s migration strategy for 3G ?• How to measure the value of technology migration?

Page 4: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

4

Wireless Market

World Wireless Industry

0

200

400

600

800

1,000

1,200

Year

Su

bsc

rib

ers(

Mill

ion

)

Total

GSM

CDMA

TDMA

Analog

World Wireless Industry

0

200

400

600

800

1,000

1,200

Year

Su

bsc

rib

ers(

Mill

ion

)

Total

GSM

CDMA

TDMA

Analog

US Wireless Industry

0.0020.0040.0060.0080.00

100.00120.00140.00160.00

Year

Su

bsc

rib

ers(

Mill

ion

)

Total

GSM

CDMA

TDMA

Analog

US Wireless Industry

0.0020.0040.0060.0080.00

100.00120.00140.00160.00

Year

Su

bsc

rib

ers(

Mill

ion

)

Total

GSM

CDMA

TDMA

Analog

World Wireless Market Share

0.00

0.20

0.40

0.60

0.80

1.00

Years

Mar

ket

Sh

ares CDMA

GSM

TDMA

Analog

World Wireless Market Share

0.00

0.20

0.40

0.60

0.80

1.00

Years

Mar

ket

Sh

ares CDMA

GSM

TDMA

Analog

US Wireless Market Share

0.00

0.20

0.40

0.60

0.80

1.00

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Year

Ma

rke

t S

ha

re (

%)

CDMA

GSM

TDMA

Analog

US Wireless Market Share

0.00

0.20

0.40

0.60

0.80

1.00

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Year

Ma

rke

t S

ha

re (

%)

CDMA

GSM

TDMA

Analog

Page 5: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

5

US Wireless Industry

VerizonCingular-AT&T

Sprint PCS

T-Mobile Nextel

AMPS O O

iDEN(integrated

Digital

Enhanced

Network)

TDMA O

GSM O O

CDMA O O

Page 6: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

6

Technology Migration Options

Cingular-AT&T

Verizon

Page 7: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

7

Research Design

OldTechnology

(i.e.,1G or 2G)

NewTechnology

(i.e., 2G or 3G)

Scenario I:Inter-Generational

Technology Migration

OldTechnology(i.e., TDMA)

Revolutionarychange

(i.e., CDMA)

Scenario II: Intra-Generational

Technology MigrationEvolutionary

change(i.e., GSM)

• Strategy:- Short-term Perspective: Single-step Technology Choice- Long-term Perspective: Multi-stage Technology Choice

• Strategy:- Short-term Perspective: Single-step Technology Choice- Long-term Perspective: Multi-stage Technology Choice

Page 8: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

8

Technology Options and Scenarios

Single-step Migration Scenarios Inter-Generational Migration

Analog => TDMA, Analog =>GSM, Analog => CDMA TDMA => cdma2000, TDMA => WCDMA GSM => cdma2000, GSM => WCDMA CDMA => cdma2000, CDMA => WCDMA

Intra-Generational Migration TDMA => GSM TDMA => CDMA GSM => CDMA

Multi-stage Migration Scenarios GSM-based Migration

Analog => TDMA => GSM => WCDMA CDMA-based Migration

Analog => CDMA => cdma2000

Page 9: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

10

Results (Inter-Generational)Value Curve (Analog=>GSM, US)

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Value Curve (Analog=>GSM, US)

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Value Curve (Analog=>CDMA, US)

-0.8000

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

0.8000

1998 1999 2000 2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Value Curve (Analog=>CDMA, US)

-0.8000

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

0.8000

1998 1999 2000 2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Value Curve (Analog=>TDMA, US)

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

1998 1999 2000 2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Value Curve (Analog=>TDMA, US)

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

1998 1999 2000 2001 2002 2003 2004

Year

Val

ue

OV

Premium

Net Value

Desirable to migrate into new technology, but the timing is different for each technology

Desirable to migrate into new technology, but the timing is different for each technology

Page 10: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

11

Results (Intra-Generational)

Value Curve (TDMA=>GSM, US)

-0.3000

-0.2000

-0.1000

0.0000

0.1000

0.2000

0.3000

Year

Val

ue

OV

Premium

Net Value

Value Curve (TDMA=>GSM, US)

-0.3000

-0.2000

-0.1000

0.0000

0.1000

0.2000

0.3000

Year

Val

ue

OV

Premium

Net Value

Value Curve (TDMA=>CDMA, US)

-0.2000

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

Year

Va

lue OV

Premium

Net Value

Value Curve (TDMA=>CDMA, US)

-0.2000

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

Year

Va

lue OV

Premium

Net Value

Value Curve (GSM=>CDMA, US)

-0.4000

-0.3000

-0.2000

-0.1000

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

Year

Va

lue OV

Premium

Net Value

Value Curve (GSM=>CDMA, US)

-0.4000

-0.3000

-0.2000

-0.1000

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

Year

Va

lue OV

Premium

Net Value

Value Curve (TDMA=>GSM, World)

-1000.0000

-500.0000

0.0000

500.0000

1000.0000

1500.0000

Year

Val

ue

OV

Premium

NOV

Value Curve (TDMA=>GSM, World)

-1000.0000

-500.0000

0.0000

500.0000

1000.0000

1500.0000

Year

Val

ue

OV

Premium

NOV

Page 11: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

12

Results (Intra-generational)

• US TDMA carriers should migrate to CDMA

• In reality some carriers choose the GSM migration path

• Result of sensitivity to data • World data vs. US data

Page 12: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

13

Results (towards 3G)

Value Curve (GSM=>WCDMA, US)

-0.2000

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

2004 2005 2006 2007 2008 2009 2010

Year

Val

ue

OV

Premium

Net value

Value Curve (GSM=>WCDMA, US)

-0.2000

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

0.2500

2004 2005 2006 2007 2008 2009 2010

Year

Val

ue

OV

Premium

Net value

Desirable to migrate toward 3G, but not now…

Yet carriers are making investments today Consequence of using market data

Value Curve (CDMA=>cdma2000, US)

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

2004 2005 2006 2007 2008 2009 2010

Year

Val

ue

OV

Premium

Net Value

Value Curve (CDMA=>cdma2000, US)

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

2004 2005 2006 2007 2008 2009 2010

Year

Val

ue

OV

Premium

Net Value

Page 13: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

14

Summary

Several migration paths are possible – no optimum path exists Several migration paths are possible – no optimum path exists

GSM(9.5Kbps)

Analog

TDMA

CDMA(14.4Kbps)

cdma2000(2.4Mbps)

WCDMA(2Mbps)0.4741

(2003)

0.1924(2004)

0.6978(2004) 0.4654

(2003)

0.1972(2003)

0.0372(2010)

0.1928(2010)

0.0289(2010)

0.1840(2010)

(?)

(?)

Page 14: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

15

Discussion

Applied real options theory to mobile network transitions

Model is very sensitive to data

Page 15: Strategic Options for Managing Technology Evolution in the Wireless Industry Hak-Ju Kim University of Houston – Clear Lake kimhak@uhcl.edu Martin Weiss.

16

Summary of the study

Assessed technology migration option in the US wireless industry Used the real options approach Discussed the US wireless carriers’ technology

migration strategies Used macro market data

Provided a reasonable data set for theory development

Better data would produce more useful results Techniques can be adapted for use

elsewhere