Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-District in Guangzhou City, China

Round 1

Reviewer 1 Report

The paper combines AHP and Huff model to support the decision of which PPP point to activate.

Overall the paper is very well written and clear.

I have s few minor suggestions.

- In the introduction the authors write "Last-mile delivery, which is the terminal delivery in e-commerce". I'd say not only ecommerce, shipping in general.

- The authors write "Comparison of the quantity data is tedious and inefficient,

particularly in the cases with a high number of the criteria and alternatives."

I agree with the authors, especially when the number of alternatives grows. However I have a suggestion (perhaps for future work). Recently AHP methods have been provided where the matrix is allowed to have a sparse structure, i.e., to have missing entries. (Representing the criteria as nodes in a graph and the availability of a comparison as an edge joining two nodes, it is sufficient that the graph is connected to reconstruct the ranking). The authors may want to take a look at papers like:

Bozóki, Sándor, and Vitaliy Tsyganok. "The (logarithmic) least squares optimality of the arithmetic (geometric) mean of weight vectors calculated from all spanning trees for incomplete additive (multiplicative) pairwise comparison matrices." International Journal of General Systems 48.4 (2019): 362-381.

G. Oliva, R. Setola and A. Scala, “Sparse and Distributed Analytic Hierarchy Process", Automatica, vol. 85, pp. 211–220 (doi: 10.1016/j.automatica.2017.07.051).

Harker, Patrick T. "Incomplete pairwise comparisons in the analytic hierarchy process." Mathematical modelling 9.11 (1987): 837-848.

G. Oliva, R. Setola, A. Scala and P. Dell’Olmo, “Opinion-Based Optimal Group Formation”, Omega, vol. 89, pp. 164–176, 2019 (doi: 10.1016/j.omega.2018.10.008).

Also, the authors could consider different ways to obtain a ranking from the AHP data, e.g., logarithmic least squares, which in several cases has better performance that the eigenvector approach. 

- About Eq. 3: is the 8+1 in this equation intended to obtain Saaty's scale from 1 to 9?

It could be interesting to compare weights obtained in this paper for the criteria with a ranking that captures just the frequency of the preference (e.g., a normalization of the terms Si ).

Author Response

Dear Reviewer 1,

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled “Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-district in Guangzhou City, China,” with the manuscript ID ijgi-743392. We appreciate the time and effort that you have dedicated to providing your valuable feedback and insightful comments on the manuscript. We modified the manuscript accordingly.

Please check the detailed response by the attachment.

We look forward to hearing from you in due time regarding our submission and to respond to any further questions and comments you may have.

Sincerely,

The authors

Author Response File: Author Response.docx

Reviewer 2 Report

This study proposes a GIS-based hybrid model combining AHP and Huff model for identifying a suitable location for the attended parcel-pickup point (PPP) in a typical residential area-Shiweitang. The author use AHP to evaluate the relative importance of factors for calculating the attractiveness of the facilities, and apply the Huff model to predict the number of customers at the candidate facilities. The results indicate that the number of customers is the primary factor influencing the suitability of the location of PPP. The decision-makers can find the optimal facilities by the PPP service distance they need from the ranking fluctuations diagram. There are some interesting aspects to this paper, but I think there are few fundamental questions surrounding the research which need to be addressed.

• Results are not properly shown and explained:
• In Page 5, the author show that the purple area represents the service area of the four pre-existing PPPs in Figure 4. However, the location of four pre-existing PPPs in Figure 1 and the 300 m service area make me confused.
• In section 2.2.1, I doubt that the potential PPP facilities are not in line with reality, where most PPPs are franchised.
• In Page 6, “We divided the 32 facilities into 12 groups according to their distribution and mutual aggregation that are represented by red ellipses in Figure 4. In each group, we only selected one facility, represented by a green triangle, as a candidate facility”. I only find 12 purple ellipses and 12 red triangles.
• In Table 6, I recommend adjusting each criteria in a row.
• The references should be updated. Please check whether the following references are relevant and may be cited:

Aggregation of the Nearest Consistency Matrices with the Acceptable Consensus in AHP-GDM, Annals of Operations Research (2020), DOI: https://0-doi-org.brum.beds.ac.uk/10.1007/s10479-020-03572-1

Comparison of Judgment Scales of the Analytical Hierarchy Process — A New Approach， https://0-doi-org.brum.beds.ac.uk/10.1142/S0219622019500044

A Novel Hybrid Fuzzy AHP-GA Method for Test Sheet Question Selection，https://0-doi-org.brum.beds.ac.uk/10.1142/S0219622020500054

Author Response

Dear Reviewer 2,

Thank you for allowing us to submit a revised draft of our manuscript titled “Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-district in Guangzhou City, China”, with manuscript ID ijgi-743392. We appreciate the time and effort that you have dedicated to providing your valuable feedback and insightful comments on my manuscript. We modified the manuscript accordingly.

Please check the detailed response by the attachment.

We look forward to hearing from you in due time regarding our submission and to respond to any further questions and comments you may have.

Sincerely,

The authors

Author Response File: Author Response.docx