EVES (Mobility and Energy Use for Different Shopping Situations)

Private consumption is associated with a substantial amount of energy use and GHG emissions, all above in the areas of passenger and freight traffic. EVES identifies the factors which affect this energy use und shows how it can be reduced by purposefully applied policies and personal action.

EVES develops a model of individual shopping decisions – from the choice of product and shopping situation to the travel decision and actual act of shopping. Individual shopping and travel decisions result in shopping mobility and different market shares of shopping situations. For six shopping situations and six product groups energy balances are calculated and compared, taking into account energy consumption from passenger transportation, delivery transportation, storage and operation of shops. Scenarios generalize the results from the investigation area (the urban agglomeration of Graz and the Ökoregion Kaindorf) to Austria. Moreover, they show impacts of price incentives or regulatory policies.

Methodological Approach

Different models will be applied which are structured from the micro to the macro level, and from the current situation to the future:

• The decision model is based on data of a standardized survey of n=800 households in the investigation area. Individual decision patterns are analyzed using structural equation models.
• The energy balances of shopping situations will be calculated with rucksack factors from different data bases (ecoinvent, ProBas, GEMIS) and supplemented by data from the literature as well as from companies in the investigation area. The amounts of CO₂e-emissions caused will be determined on the basis of energy balances and details about the energy carriers used.
• Scenarios will be developed by the project team and validated in a stakeholder workshop. Primary and secondary impacts are quantified by a General Computable Equilibrium model which considers all retroactive effects simultaneously.

Expected Results

The scenarios depict possible future shopping structures. The results provide a basis for decision making for policy options that support a sustainable energy use. Possible impacts of such policies are identified.