Measuring Adaptive Behaviour in a Retail Planning Context; A Multi-Stakeholder Conjoint Measurement Experiment

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Measuring Adaptive Behaviour in a Retail Planning
ContextA Multi-Stakeholder Conjoint Measurement
Experiment

• Ingrid Janssen
• Co-authors Aloys Borgers Harry Timmermans
• June 2010

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Agenda

• Introduction
• Retail planning in the Netherlands
• Multi-actor decision making
• Approach
• Online conjoint experiment
• Multiple stakeholders
• Choice modelling
• Model specification
• Results
• Conclusion

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Introduction

• Retail planning Multi-Stakeholder decision
  making
• Planning philosophy From plan-driven to
  market-driven
• Introduction Nota Ruimte
• Development planning
• No strict rules for new out-of-town retail
  locations
• Responsibility planning decisions delegated to
  local governments
• Regional governments have a steering role
• Dominant retail development industry

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Introduction
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Introduction

• Retail planning in the Netherlands
• Retail planning nowadays is a result of
  negotiations between multiple actors
• Developers
• Retailers
• Local governments
• To understand the behavioral aspects underlying
  (retail) planning decisions there is a need for
  multi-actor approaches.
• Focus adaptive behavior

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Approach

• Suitable approach A conjoint experiment in
  combination with choice modelling
• Experiment deciding on the expansion of retail
  supply in an imaginary city.
• Three stakeholders involved developers, local
  governments, retailers.
• How conjoint analysis.
• Alternatives are pre-specified
• References
• Borgers Timmermans (1993) -gt household
  decisions
• Hensher et. al. (2007) -gt freight distribution
  decisions

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Research objectives

• The aim of the experiment is
• to understand the preferences of different
  stakeholder groups regarding the planning of
  out-of-town retail facilities.
• to measure adaptive behaviour between agents
  involved in retail planning, as one of the
  behavioural aspects.

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Extended conjoined experiment

• Design choice task
• Decision problem How to expand retail supply in
  the imaginary city Shop City?
• Possible expansions
• Toys and Sporting Goods
• Home Electronics and Media
• Fashion
• Restaurant
• Characteristics Shop City
• Middle sized Dutch city
• Market position non-daily retail supply Shop
  City is weak compared to other cities in region.
• Accessibility of both peripheral is equal.

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Extended conjoined experiment
Attributes Attributes Levels
1 Toys and sporting goods (2.500 m2) Peripheral location sport stadium Peripheral location furniture strip Inner city
2 Home electronics and media (5.000 m2) Peripheral location sport stadium Peripheral location furniture strip Inner city
3 Fashion (7.500 m2) Peripheral location sport stadium Peripheral location furniture strip Inner city
4 Restaurant (1.000 m2) Peripheral location sport stadium Peripheral location furniture strip No restaurant
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Research approach (part II)
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Data collection

• Response

Invitation by personal letter Invitation by personal e-mail Invitation by letter to organization Invitation by e-mail to organization Visited website Completed questionnaire
Developers 163 147 0 0 unknown 67
Retailers 88 68 185 160 unknown 36
Planners 132 216 62 0 unknown 67
Total 383 431 247 160 266 170
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Model specification

• Random utility theory
• Each alternative i, has a utility (Ui). This
  utility consists of a structural (Vi) and a
  random (ei) component

(1)
(2)
where Xik represents characteristic k of
alternative i and ßk is the parameter for
characteristic k. ß0 is the utility of the both
retail plans are not acceptable-option.

• ßk represent the main effects. However,
  interaction effects and adaptation effects have
  to be introduced.

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Model specification

• The formula for the structural utility can be
  extended

(3)

• where
• ß0 represents the utility of the both
  alternatives are not acceptable option
• ßk parameters measure the main effects
• ?k parameters measure the interaction effects
• ak parameters measure the adaptation effects

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Model estimation

• Multinimial Logit models were estimated using
  maximum likelihood procedures.
• Only parameters at the 5 significance level were
  included.
• For each stakeholder group (developer, retailer,
  planner) separate models were estimated.

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Estimated parameters MNL-model
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Findings

• All stakeholders do not prefer to locate fashion
  on a peripheral retail location.
• Since X0 is significant but negative for all
  stakeholders, respondents are really willing to
  make a choice.
• Different type of interaction variables are of
  significant importance.
• Developer is most willing to adapt his preference
  to the opinion of other stakeholders.
• The retailer is the least sensitive for the
  opinion of other stakeholders
• Planners utility of the location of toyssport
  on a furniture strip turns positive when both
  other stakeholders are in favour.
• Goodness-of-fit (Rho2) is satisfying for
  developers and planners.

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Conclusions

• The experiment showed that adaptive behaviour in
  retail planning decision plays an important role.
• By extending the traditional random utility model
  with parameters that measure adaptive behaviour,
  this behavioural aspect can be incorporated.
• Applying Mixed Logit models will lead to even
  more valid models (the Rho2 will increase).
• Further research estimating for heterogeneity
  within each group of stakeholders based on
  respondent characteristics.