Short answer

Design omni-channel strategies that leverage localized fulfillment and pickup points to minimize transportation emissions, making Click & Collect the preferred model.

Field
Sustainability
Source
International Journal of Logistics Systems and Management (2019)
Method
Activity-based modelling and simulation
Evidence
Strong effect

Optimizing logistics for omni-channel apparel purchasing, specifically through Click & Collect models, can significantly reduce environmental impact by minimizing transportation distances. This sustainability research insight is drawn from a 2019 study published in International Journal of Logistics Systems and Management. Using Activity-based modelling and simulation, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Design omni-channel strategies that leverage localized fulfillment and pickup points to minimize transportation emissions, making Click & Collect the preferred model.

Study
SustainabilityHigh ImpactStrong effect

Omni-channel apparel logistics: Click & Collect reduces environmental impact by prioritizing customer proximity

Optimizing logistics for omni-channel apparel purchasing, specifically through Click & Collect models, can significantly reduce environmental impact by minimizing transportation distances.

International Journal of Logistics Systems and Management · 2019

01

Key Findings

  • 01Mobile Shopping in Store (MSiS) is less sustainable than Click & Collect (C&C).
  • 02Transportation is a major contributor to the environmental impact in both MSiS and C&C.
  • 03Customer proximity to the store is the most critical factor influencing environmental impact for both models.
  • 04Customer profile and location (urban vs. extra-urban) are significant factors, especially for MSiS.
02

Application

Design takeaway

Design omni-channel strategies that leverage localized fulfillment and pickup points to minimize transportation emissions, making Click & Collect the preferred model.

How to apply

When designing or evaluating omni-channel retail systems, model the environmental impact of different logistics scenarios, paying close attention to customer travel distances and the efficiency of pickup versus in-store mobile shopping.

Project actions

  • 01When researching omni-channel strategies, consider the environmental impact of different logistics options.
  • 02Use modelling to compare the sustainability of various purchasing methods, like Click & Collect versus home delivery.
03

Method & Evidence

AimTo quantitatively model and assess the environmental impact of omni-channel apparel purchasing, focusing on the logistics of 'Click & Collect' and 'Mobile Shopping in Store' models.
MethodActivity-based modelling and simulation
ProcedureDeveloped an activity-based model to assess the environmental impact of two omni-channel purchasing processes (Click & Collect and Mobile Shopping in Store) from both retailer and customer perspectives. Applied the model to a representative apparel industry case and conducted sensitivity analyses.
ContextApparel industry, omni-channel retail, logistics, environmental impact assessment

Variables

IV["Purchasing model (Click & Collect vs. Mobile Shopping in Store)","Customer-store distance","Customer location (urban/extra-urban)"]
DV["Environmental impact (e.g., CO2 emissions from transport)"]
CV["Apparel industry context","Retailer and customer perspectives considered","Logistics activities"]
04

Strengths & Limitations

Strengths

  • +Provides a quantitative model for assessing omni-channel sustainability.
  • +Considers both retailer and customer perspectives.
  • +Identifies key factors influencing environmental impact.

Limitations

The environmental impact can vary greatly depending on the specific transportation methods used by customers and retailers, as well as the energy efficiency of stores.

Reliability & validity

The study's reliability would depend on the consistency of the activity-based model and the data used. Validity is supported by comparing results to existing e-commerce sustainability research, but the specific context of omni-channel models might introduce new variables.

Think critically

How might the environmental impact of 'Mobile Shopping in Store' be mitigated to approach the sustainability of 'Click & Collect'?

05

Design Principles

"Minimize transportation externalities by optimizing logistics to customer proximity in omni-channel retail."

As consumer purchasing habits evolve towards blended online and physical retail experiences, understanding the environmental footprint of these new models is crucial. Designers and businesses must consider the lifecycle impact of their logistics strategies to align with sustainability goals and consumer expectations.

06

What This Means for Your Design

When people buy clothes online and pick them up from the store (Click & Collect), it's better for the environment than when they use their phones in the store to buy things. This is because the travel distance is usually shorter for Click & Collect.

How to use in your project

  • 1.Reference this study when discussing the environmental impact of e-commerce and omni-channel logistics in your design project.
  • 2.Use the findings to justify the selection of a more sustainable logistics model for your product or service.
07

Add to My Project

08

Quick Cite

Paragraph starter

This research highlights that omni-channel apparel purchasing, particularly through 'Click & Collect' models, offers a more sustainable logistical approach compared to 'Mobile Shopping in Store' due to reduced transportation requirements. The proximity of the customer to the retail point is a critical factor in minimizing environmental impact, suggesting that strategic placement of fulfillment centres and retail outlets is essential for eco-conscious design in the apparel sector.

09

Source

International Journal of Logistics Systems and Management

Modelling the environmental impact of omni-channel purchasing in the apparel industry: the role of logistics

journal · 2019

View source

Questions About This Research

What does the research say about omni-channel apparel logistics: click & collect reduces environmental impact by prioritizing customer proximity?
Design omni-channel strategies that leverage localized fulfillment and pickup points to minimize transportation emissions, making Click & Collect the preferred model. Evidence: International Journal of Logistics Systems and Management (2019).
Why does "Omni-channel apparel logistics: Click & Collect reduces environmental impact by prioritizing customer proximity" matter for design?
As consumer purchasing habits evolve towards blended online and physical retail experiences, understanding the environmental footprint of these new models is crucial. Designers and businesses must consider the lifecycle impact of their logistics strategies to align with sustainability goals and consumer expectations.
How can designers apply this research?
Design omni-channel strategies that leverage localized fulfillment and pickup points to minimize transportation emissions, making Click & Collect the preferred model.
What were the main findings?
Mobile Shopping in Store (MSiS) is less sustainable than Click & Collect (C&C).. Transportation is a major contributor to the environmental impact in both MSiS and C&C.. Customer proximity to the store is the most critical factor influencing environmental impact for both models.. Customer profile and location (urban vs. extra-urban) are significant factors, especially for MSiS.
What research method was used?
Activity-based modelling and simulation.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2019 journal from International Journal of Logistics Systems and Management.
What should I do differently in my next project?
When designing or evaluating omni-channel retail systems, model the environmental impact of different logistics scenarios, paying close attention to customer travel distances and the efficiency of pickup versus in-store mobile shopping.
What are the limitations?
The model's accuracy is dependent on the quality of input data regarding customer behaviour, transportation modes, and energy consumption. Generalizability to all apparel markets may vary.