SlideShare a Scribd company logo
1 of 11
1
Research Ideas
An Investigation of Geographical
Information System in Retail Marketing
2
GIS
• GIS is essential for solving business planning problems
having spatial dimensions
• Developed due to dissatisfaction with socio-economic
groupings
– ‘mass’ marketing ‘niche’ marketing: requires more spatially
disaggregated information about both consumers and competitors.
– The growing establishment of customer databases.
– For competitive advantage and business effectiveness
3
Current Developments
• The business planning segment is presently the fastest growing share
of the GIS market. One reason is that over 80% of business data has
spatial nature (Wallick, 1984)
• Advent of more powerful, cheaper IT is driving product development
and adoption.
• GIS plays a greater role in decision making process for merchandise
and service retail firms.
• Now many GIS systems (OR) models, often industry specific
• The most exciting challenges in location analysis relate to planning for
retail and service firms.
4
How marketers can take the
advantage of GIS
• Better processing spatial data, thus constituting an
information industry that can generate wealth by adding
value.
– Trade area delineation: population within a certain area.
– Geodemographics: analysing patterns of demand across one area
and from one area to another.
– Direct estimation: deriving demand structures for areas.
• Sometimes “a map is worth than thousands of words”
5
Current issues
• Technology is too complex to be understood by end-users
• Modelling procedures are severely lacking
• inefficiencies regarding decision making
• Furthering corporate acceptance of geographic principles
6
Technology is too complex to
understand regarding to end-users
• A fairly simple command structure with a graphical
interface and the ability to answer complex spatial
questions.
– Powerful and flexible analysis capabilities combined with ease
use.( a few button and an answer)
7
Modelling procedures are severely
lacking
• Current models:
– Analogue techniques
– Regression techniques
– Catchment area analysis
– Spatial interaction models
– Location-allocation and optimisation models
– Trial and error
• Integration of these models into a spatial decision support
system(SDSS), aimed to increase the spatial analytical
functions of GIS, are not yet clear.
• Most of these models has its own drawbacks.
8
Drawbacks
• Analogue techniques:success is dependent on whether similar sites are found across town or across
the country. Effective modelling depends on whether trading characteristics can be transferred from
geographical locations. New markets with unusual demographics and competitive profiles may not
match any markets in the analog base(Buxton, 1993)
• Regression techniques: it does not consider interaction at a spatial level. It evaluates sites in
isolation without considering competition or the affects of the corporations networks of stores and
distribution on future store revenues.
• Location-allocation and optimisation models: this technique does not take into consideration any
form of competition other than from its own network sites
• The above models including catchment area analysis and spatial interaction models only consider
existing outlets within a market and rarely have a flat playing field where there are no existing
outlets.
• Trial and error approach: the technique is highly subjective and relies on the experience of key
individuals. In many instances it is a very time consuming and expensive technique. It also may be
impractical to visit al potentially feasible sites.
9
Inefficiencies regarding decision
making
• There is a limited degree of attention to examine the
societal context which influence the efficiencies of GIS in
business decision making.
– Collaboration, organisational communication relating to GIS
adoption in business firms.
– Users insights and qualifications
– The consideration of data accessibility, data protection when
adopting GIS in decision making system.
10
Furthering corporate acceptance of
geographic principles
• Does geodemographic modelling lead to redlining or other forms of
geographical exclusion or, on the other hand, more efficient niche
marketing and better, specialised location and investment decisions?
• To what extent GIS is an integral component of the formulation,
implementation, and evaluation of any marketing strategy plan.
• What are the implications of widespread use of spatial interaction and
location-allocation models in corporate geography for competition,
and for corporate welfare.
11
Why carry out this research
• To date, no many systematic, theoretically grounded study of GIS
implementation across multiple private-sector organisation has been
published.
• An in depth understanding and investigation of the above problems so
as to identify the most cost effective and successful marketing strategy
for businesses regarding GIS application.
• A modelling will be designed based on the data collected and applied
with the collaboration retail industry, thus to identify the usefulness
and efficiencies of GIS into decision making.

More Related Content

Similar to proposal[1]

Benefits and implementation of geography within business intelligence
Benefits and implementation of geography within business intelligenceBenefits and implementation of geography within business intelligence
Benefits and implementation of geography within business intelligenceDidier ROBERT
 
Key innovative market trends for your policy administrative system
Key innovative market trends for your policy administrative systemKey innovative market trends for your policy administrative system
Key innovative market trends for your policy administrative systemAccenture Insurance
 
Ramco cement BI Case Study
Ramco cement BI Case StudyRamco cement BI Case Study
Ramco cement BI Case StudyAbhishek Sinha
 
Retail Stores Network: Optimal Size & Geographical Distribution
Retail Stores Network: Optimal Size & Geographical DistributionRetail Stores Network: Optimal Size & Geographical Distribution
Retail Stores Network: Optimal Size & Geographical DistributionSotiris Athanassopoulos
 
Yellowfin Location Intelligence Best Practices Webinar
Yellowfin Location Intelligence Best Practices WebinarYellowfin Location Intelligence Best Practices Webinar
Yellowfin Location Intelligence Best Practices WebinarYellowfin
 
URISA’s Local Government GIS Capability Maturity Model
URISA’s Local Government GIS Capability Maturity ModelURISA’s Local Government GIS Capability Maturity Model
URISA’s Local Government GIS Capability Maturity ModelGreg Babinski
 
HUMAN AND ORGANIZATIONAL ISSUE- GIS
HUMAN AND ORGANIZATIONAL ISSUE- GISHUMAN AND ORGANIZATIONAL ISSUE- GIS
HUMAN AND ORGANIZATIONAL ISSUE- GISTanvir Rashed
 
Geomarketing analyses for business by GEPOL
Geomarketing analyses for business by GEPOLGeomarketing analyses for business by GEPOL
Geomarketing analyses for business by GEPOLGepol Sp. z o. o.
 
Atlas How Site Selectors are Using GIS to Evaluate Communities
Atlas How Site Selectors are Using GIS to Evaluate CommunitiesAtlas How Site Selectors are Using GIS to Evaluate Communities
Atlas How Site Selectors are Using GIS to Evaluate CommunitiesAtlas Integrated
 
Community Systems - How Site Selectors Use Geographic Information Systems
Community Systems - How Site Selectors Use Geographic Information SystemsCommunity Systems - How Site Selectors Use Geographic Information Systems
Community Systems - How Site Selectors Use Geographic Information SystemsBen Wright
 
Jean michel viola masterclass 14th of june
Jean michel viola masterclass 14th of juneJean michel viola masterclass 14th of june
Jean michel viola masterclass 14th of juneArmina Stepan
 
Challenges in adapting predictive analytics
Challenges  in  adapting  predictive  analyticsChallenges  in  adapting  predictive  analytics
Challenges in adapting predictive analyticsPrasad Narasimhan
 
Augmented Analytics Market Outlook
Augmented Analytics Market OutlookAugmented Analytics Market Outlook
Augmented Analytics Market OutlookAman Soni
 
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Data Science Society
 

Similar to proposal[1] (20)

Benefits and implementation of geography within business intelligence
Benefits and implementation of geography within business intelligenceBenefits and implementation of geography within business intelligence
Benefits and implementation of geography within business intelligence
 
Market pulse
Market pulseMarket pulse
Market pulse
 
Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic ...
Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic ...Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic ...
Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic ...
 
Key innovative market trends for your policy administrative system
Key innovative market trends for your policy administrative systemKey innovative market trends for your policy administrative system
Key innovative market trends for your policy administrative system
 
s&r6ch02-isorg.ppt
s&r6ch02-isorg.ppts&r6ch02-isorg.ppt
s&r6ch02-isorg.ppt
 
Ramco cement BI Case Study
Ramco cement BI Case StudyRamco cement BI Case Study
Ramco cement BI Case Study
 
Retail Stores Network: Optimal Size & Geographical Distribution
Retail Stores Network: Optimal Size & Geographical DistributionRetail Stores Network: Optimal Size & Geographical Distribution
Retail Stores Network: Optimal Size & Geographical Distribution
 
Tourism marketing
Tourism marketingTourism marketing
Tourism marketing
 
Bdml ecom
Bdml ecomBdml ecom
Bdml ecom
 
Yellowfin Location Intelligence Best Practices Webinar
Yellowfin Location Intelligence Best Practices WebinarYellowfin Location Intelligence Best Practices Webinar
Yellowfin Location Intelligence Best Practices Webinar
 
URISA’s Local Government GIS Capability Maturity Model
URISA’s Local Government GIS Capability Maturity ModelURISA’s Local Government GIS Capability Maturity Model
URISA’s Local Government GIS Capability Maturity Model
 
HUMAN AND ORGANIZATIONAL ISSUE- GIS
HUMAN AND ORGANIZATIONAL ISSUE- GISHUMAN AND ORGANIZATIONAL ISSUE- GIS
HUMAN AND ORGANIZATIONAL ISSUE- GIS
 
Geomarketing analyses for business by GEPOL
Geomarketing analyses for business by GEPOLGeomarketing analyses for business by GEPOL
Geomarketing analyses for business by GEPOL
 
Atlas How Site Selectors are Using GIS to Evaluate Communities
Atlas How Site Selectors are Using GIS to Evaluate CommunitiesAtlas How Site Selectors are Using GIS to Evaluate Communities
Atlas How Site Selectors are Using GIS to Evaluate Communities
 
Community Systems - How Site Selectors Use Geographic Information Systems
Community Systems - How Site Selectors Use Geographic Information SystemsCommunity Systems - How Site Selectors Use Geographic Information Systems
Community Systems - How Site Selectors Use Geographic Information Systems
 
Jean michel viola masterclass 14th of june
Jean michel viola masterclass 14th of juneJean michel viola masterclass 14th of june
Jean michel viola masterclass 14th of june
 
Challenges in adapting predictive analytics
Challenges  in  adapting  predictive  analyticsChallenges  in  adapting  predictive  analytics
Challenges in adapting predictive analytics
 
Augmented Analytics Market Outlook
Augmented Analytics Market OutlookAugmented Analytics Market Outlook
Augmented Analytics Market Outlook
 
Product flyer
Product flyerProduct flyer
Product flyer
 
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
Disruptive as Usual: New Technologies and Data Value Professor Severino Mereg...
 

More from Chen Zunqiu

Net Promoter Score
Net Promoter ScoreNet Promoter Score
Net Promoter ScoreChen Zunqiu
 
Presentation noanimation
Presentation noanimationPresentation noanimation
Presentation noanimationChen Zunqiu
 
the elements of data analytic style checklisti
the elements of data analytic style checklistithe elements of data analytic style checklisti
the elements of data analytic style checklistiChen Zunqiu
 
New Opportunity for Urban Analysis
New Opportunity for Urban AnalysisNew Opportunity for Urban Analysis
New Opportunity for Urban AnalysisChen Zunqiu
 
MortalityRateComp
MortalityRateCompMortalityRateComp
MortalityRateCompChen Zunqiu
 
Producing Smoothed Prostate Mortality Map, Iowa
Producing Smoothed Prostate Mortality Map, IowaProducing Smoothed Prostate Mortality Map, Iowa
Producing Smoothed Prostate Mortality Map, IowaChen Zunqiu
 
Members’ distribution of Infectious diseases network[edited1]
Members’ distribution of Infectious diseases network[edited1]Members’ distribution of Infectious diseases network[edited1]
Members’ distribution of Infectious diseases network[edited1]Chen Zunqiu
 
Maps for Peds MRSA SSTI
Maps for Peds MRSA SSTIMaps for Peds MRSA SSTI
Maps for Peds MRSA SSTIChen Zunqiu
 

More from Chen Zunqiu (13)

Net Promoter Score
Net Promoter ScoreNet Promoter Score
Net Promoter Score
 
Presentation noanimation
Presentation noanimationPresentation noanimation
Presentation noanimation
 
the elements of data analytic style checklisti
the elements of data analytic style checklistithe elements of data analytic style checklisti
the elements of data analytic style checklisti
 
Presentation1
Presentation1Presentation1
Presentation1
 
Presentation2
Presentation2Presentation2
Presentation2
 
figures
figuresfigures
figures
 
New Opportunity for Urban Analysis
New Opportunity for Urban AnalysisNew Opportunity for Urban Analysis
New Opportunity for Urban Analysis
 
PCSA
PCSAPCSA
PCSA
 
MortalityRateComp
MortalityRateCompMortalityRateComp
MortalityRateComp
 
Producing Smoothed Prostate Mortality Map, Iowa
Producing Smoothed Prostate Mortality Map, IowaProducing Smoothed Prostate Mortality Map, Iowa
Producing Smoothed Prostate Mortality Map, Iowa
 
Members’ distribution of Infectious diseases network[edited1]
Members’ distribution of Infectious diseases network[edited1]Members’ distribution of Infectious diseases network[edited1]
Members’ distribution of Infectious diseases network[edited1]
 
Maps for Peds MRSA SSTI
Maps for Peds MRSA SSTIMaps for Peds MRSA SSTI
Maps for Peds MRSA SSTI
 
Eric_Chen_final
Eric_Chen_finalEric_Chen_final
Eric_Chen_final
 

proposal[1]

  • 1. 1 Research Ideas An Investigation of Geographical Information System in Retail Marketing
  • 2. 2 GIS • GIS is essential for solving business planning problems having spatial dimensions • Developed due to dissatisfaction with socio-economic groupings – ‘mass’ marketing ‘niche’ marketing: requires more spatially disaggregated information about both consumers and competitors. – The growing establishment of customer databases. – For competitive advantage and business effectiveness
  • 3. 3 Current Developments • The business planning segment is presently the fastest growing share of the GIS market. One reason is that over 80% of business data has spatial nature (Wallick, 1984) • Advent of more powerful, cheaper IT is driving product development and adoption. • GIS plays a greater role in decision making process for merchandise and service retail firms. • Now many GIS systems (OR) models, often industry specific • The most exciting challenges in location analysis relate to planning for retail and service firms.
  • 4. 4 How marketers can take the advantage of GIS • Better processing spatial data, thus constituting an information industry that can generate wealth by adding value. – Trade area delineation: population within a certain area. – Geodemographics: analysing patterns of demand across one area and from one area to another. – Direct estimation: deriving demand structures for areas. • Sometimes “a map is worth than thousands of words”
  • 5. 5 Current issues • Technology is too complex to be understood by end-users • Modelling procedures are severely lacking • inefficiencies regarding decision making • Furthering corporate acceptance of geographic principles
  • 6. 6 Technology is too complex to understand regarding to end-users • A fairly simple command structure with a graphical interface and the ability to answer complex spatial questions. – Powerful and flexible analysis capabilities combined with ease use.( a few button and an answer)
  • 7. 7 Modelling procedures are severely lacking • Current models: – Analogue techniques – Regression techniques – Catchment area analysis – Spatial interaction models – Location-allocation and optimisation models – Trial and error • Integration of these models into a spatial decision support system(SDSS), aimed to increase the spatial analytical functions of GIS, are not yet clear. • Most of these models has its own drawbacks.
  • 8. 8 Drawbacks • Analogue techniques:success is dependent on whether similar sites are found across town or across the country. Effective modelling depends on whether trading characteristics can be transferred from geographical locations. New markets with unusual demographics and competitive profiles may not match any markets in the analog base(Buxton, 1993) • Regression techniques: it does not consider interaction at a spatial level. It evaluates sites in isolation without considering competition or the affects of the corporations networks of stores and distribution on future store revenues. • Location-allocation and optimisation models: this technique does not take into consideration any form of competition other than from its own network sites • The above models including catchment area analysis and spatial interaction models only consider existing outlets within a market and rarely have a flat playing field where there are no existing outlets. • Trial and error approach: the technique is highly subjective and relies on the experience of key individuals. In many instances it is a very time consuming and expensive technique. It also may be impractical to visit al potentially feasible sites.
  • 9. 9 Inefficiencies regarding decision making • There is a limited degree of attention to examine the societal context which influence the efficiencies of GIS in business decision making. – Collaboration, organisational communication relating to GIS adoption in business firms. – Users insights and qualifications – The consideration of data accessibility, data protection when adopting GIS in decision making system.
  • 10. 10 Furthering corporate acceptance of geographic principles • Does geodemographic modelling lead to redlining or other forms of geographical exclusion or, on the other hand, more efficient niche marketing and better, specialised location and investment decisions? • To what extent GIS is an integral component of the formulation, implementation, and evaluation of any marketing strategy plan. • What are the implications of widespread use of spatial interaction and location-allocation models in corporate geography for competition, and for corporate welfare.
  • 11. 11 Why carry out this research • To date, no many systematic, theoretically grounded study of GIS implementation across multiple private-sector organisation has been published. • An in depth understanding and investigation of the above problems so as to identify the most cost effective and successful marketing strategy for businesses regarding GIS application. • A modelling will be designed based on the data collected and applied with the collaboration retail industry, thus to identify the usefulness and efficiencies of GIS into decision making.