Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment
Abstract
:1. Introduction
- What logistics service quality dimensions do India Post customers in southern India prioritize?
- How aligned are these customer priorities with the internal service focus of India Post?
2. Literature Review
3. Methodology
3.1. AHP and QFD
Comparative Analysis of Design and Decision-Making Frameworks
4. Results
4.1. Prioritization of Logistics Service Quality Dimensions by Customers
4.2. Prioritization of Service Parameters from the Point of View of India Post
4.3. Normalization
4.4. Consistency Check
4.5. Identification of Important Service Parameters Using QFD
● | Strong relationship. |
○ | Medium relationship. |
▽ | Weak relationship. |
- Xi = the priority of the row item (customer need priority in the house of quality)
- aij = the strength of the relationship
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
LSQ | Logistics service quality |
AHP | Analytical Hierarchy Process |
QFD | Quality Function Deployment |
B2C | Business-to-consumer |
B2B | Business-to-business |
C2C | Consumer-to-consumer |
VoC | Voice of the customer |
IQ | Information quality |
OP | Ordering procedures |
OQ | Order release quantities |
TM | Timeliness |
OA | Order accuracy |
OC | Order condition |
OD | Order discrepancy handling |
PQ | Personnel contact quality |
CR | Consistency ratio |
CI | Consistency index |
RI | Random consistency index |
HOQ | House of quality |
FSD | Fast sorting and distribution |
TTA | Transit time analysis |
CSI | Core system integration |
NI | Network integration |
DRC | Disaster-relief centers |
SC | Scan compliance |
MMT | Multi-model transport integration |
CM | Change management |
DQM | Dynamic queue management system |
Appendix A
Service Parameter | Definition |
---|---|
Fast sorting and dispatching process | The sorting process will begin as soon as the articles reach the office in which it will show the names of post offices and R.M.S. (Railway Mail Services) sections for which mail bags are to be made up and for which labelled bundles are usually prepared, and the compartments of the sorting case will be arranged and labelled accordingly. The mail bag together with the parcel bag (if any), will then be dispatched after sorting. |
Transit time analysis | Transit time is the amount of time required for moving goods from one point to another. For India Post, it is the time taken for an item from being delivered to a post office to the time it is delivered to the addressee. Transit time analysis is performed to analyze how much time it takes for a parcel to reach the customer and to identify the reasons for the delay. |
Core system integration | Core system integration (CSI) aims at computerizing through one central platform for all the postal, mail, and counter operations of the post offices, apart from implementing the computerization of the finance and accounts and HR functions of the department. A total of 511 divisions (499 postal and RMS divisions and 12 independent head post offices/GPOs) have been rolled out in CSI. |
Network integration | Networking of all 155,531 post offices covering the remotest parts of the country will enable the tracking and tracing of all kinds of accountable mail and parcels in the country, in addition to providing real-time information to facilitate customer feedback and management functions. |
Disaster-recovery centers | Disaster-recovery centers aim to help the organization to resolve data loss and recover system functionality so that it can resume its operations. Developing a plan for recovering a network becomes more complicated as the complexity of the network increases. It is important to detail the step-by-step recovery procedure, test it properly, and keep it updated. |
Scan compliance KPI | It provides the actual number of scans available against prescribed scans and identifies the number of articles with full scans. This is being performed to reduce the flow of mail between different centers and to ensure consistency and reliability. It includes a booking scan, closing scan, bag-receiving scan at the sorting hub, bag-opening scan at the sorting hub, bag closing scan at the sorting hub, bag dispatch scan at the sorting hub, bag-receiving scan at the destination sorting hub, bag-opening scan at the destination sorting hub, bag-closing scan at the destination sorting hub, bag-dispatch scan at the destination sorting hub, bag-receiving scan at the delivery PO, and a final delivery scan for town delivery (TD) and non–town delivery (NTD). |
Multi-model transport integration | In India Post, consignments are transmitted by road, rail, or air depending upon the requirements of the customer. As a result, the integration of various modes of transport is essential for prompt delivery. |
Change management | The change management aims to prepare all the employees of the department to enable them to function effectively in the IT environment. Training activities are given by the department on its own. |
Dynamic queue management system (DQMS) | The Department of Post has also installed DQMS in 263 post offices with the objective of reducing waiting time, increasing processing capacity, reducing miscommunications among customers, and matching customer needs and service, to give a comfort level to the staff and customers, to track staff performance based on reports, and to monitor customer flow. |
N | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
---|---|---|---|---|---|---|---|---|---|---|
RI | 0 | 0 | 0.58 | 0.9 | 1.1.2 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 |
FSD | TTA | CSI | NI | DRC | SC | MMT | CM | DQMS | |
---|---|---|---|---|---|---|---|---|---|
FSD | 1 | 0.33 | 0.14 | 0.12 | 2 | 0.11 | 3 | 7 | 0.5 |
TTA | 3 | 1 | 1 | 0.5 | 5 | 0.17 | 4 | 9 | 3 |
CSI | 7 | 1 | 1 | 1 | 9 | 0.5 | 7 | 9 | 4 |
NI | 8 | 2 | 1 | 1 | 7 | 1 | 4 | 6 | 5 |
DRC | 0.5 | 0.2 | 0.11 | 0.14 | 1 | 0.12 | 1 | 5 | 0.33 |
SC | 9 | 6 | 2 | 1 | 8 | 1 | 6 | 9 | 4 |
MMT | 0.33 | 0.25 | 0.14 | 0.25 | 1 | 0.17 | 1 | 2 | 0.25 |
CM | 0.14 | 0.11 | 0.11 | 0.17 | 0.2 | 0.11 | 0.5 | 1 | 0.14 |
DQMS | 2 | 0.33 | 0.25 | 0.2 | 3 | 0.25 | 4 | 7 | 1 |
Service Parameter | Row Total | Normalized Weight |
---|---|---|
Fast sorting and distribution | 0.616191 | 0.04 |
Transit time analysis | 1.72846 | 0.13 |
Core system integration | 2.712072 | 0.20 |
Network integration | 2.875484 | 0.21 |
Disaster-relief centers | 0.406775 | 0.03 |
Scan compliance | 3.851794 | 0.28 |
Multi-model transport | 0.397084 | 0.03 |
Change management | 0.196833 | 0.01 |
Dynamic queue management system | 0.960072 | 0.07 |
Total | 13.74476 | 1 |
Service Parameters | Maximum Eigen Value | |
---|---|---|
Fast sorting and distribution | 0.451 | 0.451/0.045 = 10.058 |
Transit time analysis | 1.212 | 1.212/0.126 = 9.636 |
Core system integration | 1.863 | 1.863/0.197 = 9.442 |
Network integration | 2.055 | 2.055/0.209 = 9.822 |
Disaster-relief centers | 0.285 | 0.285/0.030 = 9.641 |
Scan compliance | 2.860 | 2.860/0.280 = 10.207 |
Multi-model transport integration | 0.278 | 0.278/0.029 = 9.636 |
Change management | 0.153 | 0.153/0.014 = 10.661 |
Dynamic queue management system | 0.667 | 0.667/0.070 = 9.547 |
FSD | TTA | CSI | NI | DRC | SC | MMT | CM | DQMS | |
---|---|---|---|---|---|---|---|---|---|
FSD | 1 | 0.33 | 0.11 | 2 | 7 | 0.5 | 3 | 4 | 0.5 |
TTA | 3 | 1 | 0.33 | 7 | 9 | 5 | 6 | 9 | 1 |
CSI | 9 | 3 | 1 | 5 | 9 | 2 | 7 | 9 | 2 |
NI | 0.5 | 0.14 | 0.2 | 1 | 3 | 0.25 | 3 | 8 | 0.2 |
DRC | 0.14 | 0.11 | 0.11 | 0.33 | 1 | 0.12 | 1 | 2 | 0.12 |
SC | 2 | 0.2 | 0.5 | 4 | 8 | 1 | 4 | 8 | 0.5 |
MMT | 0.33 | 0.17 | 0.14 | 0.33 | 1 | 0.25 | 1 | 3 | 0.2 |
CM | 0.25 | 0.11 | 0.11 | 0.12 | 0.5 | 0.12 | 0.33 | 1 | 0.14 |
DQMS | 2 | 1 | 0.5 | 5 | 8 | 2 | 5 | 7 | 1 |
Service Parameter | Row Total | Normalized Weight |
---|---|---|
Fast sorting and distribution | 1.0480 | 0.076 |
Transit time analysis | 2.9484 | 0.214 |
Core system integration | 4.0696 | 0.295 |
Network integration | 0.7175 | 0.052 |
Disaster-relief centers | 0.2934 | 0.021 |
Scan compliance | 1.6725 | 0.121 |
Multi-model transport integration | 0.4179 | 0.030 |
Change management | 0.2156 | 0.016 |
Dynamic queue management system | 2.4156 | 0.175 |
Total | 13.798 | 1 |
Service Parameters | Maximum Eigen Value | |
---|---|---|
Fast sorting and distribution | 0.733 | 0.733/0.076 = 9.654 |
Transit time analysis | 2.198 | 2.198/0.214 = 10.285 |
Core system integration | 3.016 | 3.016/0.295 = 10.226 |
Network integration | 0.524 | 0.524/0.052 = 10.074 |
Disaster-relief centers | 0.202 | 0.202/0.021= 9.505 |
Scan compliance | 1.175 | 1.175/0.121 = 9.695 |
Multi-model transport integration | 0.284 | 0.284/0.030 = 9.363 |
Change management | 0.156 | 0.156/0.016 = 10.015 |
Dynamic queue management system | 1.621 | 1.621/0.175 = 9.262 |
FSD | TTA | CSI | NI | DRC | SC | MMT | CM | DQMS | |
---|---|---|---|---|---|---|---|---|---|
FSD | 1 | 0.11 | 0.2 | 0.12 | 4 | 0.17 | 2 | 3 | 0.5 |
TTA | 9 | 1 | 3 | 7 | 9 | 3 | 8 | 9 | 6 |
CSI | 5 | 0.33 | 1 | 3 | 5 | 0.5 | 7 | 8 | 4 |
NI | 8 | 0.14 | 0.33 | 1 | 6 | 0.5 | 5 | 7 | 4 |
DRC | 0.25 | 0.11 | 0.2 | 0.17 | 1 | 0.12 | 0.5 | 2 | 0.33 |
SC | 6 | 0.33 | 2 | 2 | 8 | 1 | 5 | 8 | 6 |
MMT | 0.5 | 0.12 | 0.14 | 0.2 | 2 | 0.2 | 1 | 3 | 0.5 |
CM | 0.33 | 0.11 | 0.12 | 0.14 | 0.5 | 0.12 | 0.33 | 1 | 0.14 |
DQMS | 2 | 0.17 | 0.25 | 0.25 | 3 | 0.17 | 2 | 7 | 1 |
Service Parameter | Row Total | Normalized Weight |
---|---|---|
Fast sorting and distribution | 0.5596 | 0.039 |
Transit time analysis | 5.0677 | 0.349 |
Core system integration | 2.4129 | 0.166 |
Network integration | 1.7516 | 0.121 |
Disaster-relief centers | 0.3218 | 0.022 |
Scan compliance | 2.9152 | 0.201 |
Multi-model transport integration | 0.4646 | 0.032 |
Change management | 0.2284 | 0.016 |
Dynamic queue management system | 0.8110 | 0.056 |
Total | 14.5328 | 1 |
Service Parameter | Maximum Eigen Value | |
---|---|---|
Fast sorting and distribution | 0.386 | 0.386/0.039 = 10.029 |
Transit time analysis | 3.570 | 3.570/0.349 = 10.238 |
Core system integration | 1.619 | 1.619/0.166 = 9.751 |
Network integration | 1.258 | 1.258/0.121 = 10.441 |
Disaster-relief centers | 0.214 | 0.214/0.022 = 9.651 |
Scan compliance | 1.917 | 1.917/0.201 = 9.558 |
Multi-model transport integration | 0.300 | 0.300/0.032 = 9.381 |
Change management | 0.157 | 0.157/0.016 = 9.996 |
Dynamic queue management system | 0.538 | 0.538/0.056 = 9.645 |
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Source | Projected CAGR (2023–2030) |
---|---|
Cognitive Market Research (2024) | 4.6% |
Statista (2024) | 4.8% |
McKinsey & Company (2023) | 4.5–5.0% |
IBISWorld (2024) | 4.7% |
Parameters of Logistics Service Quality | Definition |
---|---|
Timeliness | Whether orders arrive at the customer location as promised |
Information quality | The usefulness of the information the consumer can obtain from the personnel of the courier and even from the couriers |
Ordering procedures | Efficiency and effectiveness of the procedure followed by the organization in making a delivery to the customer |
Personnel contact quality | Interaction between customers and courier personnel |
Order accuracy | Precision of how the items will arrive to the hands of the customer |
Order condition | Lack of damage to orders |
Order discrepancy handling | How well the courier services address any discrepancies in products after they arrive |
Order release quantities | Alternative options given by the courier services in sending a different quantity of goods |
Model | Key Features | Suitability for This Study |
---|---|---|
Design Thinking | Empathy-driven, iterative, human-centric | Moderate—good for ideation, not prioritization |
Kano Model | Classifies customer preferences into categories | Complementary but not comprehensive |
AHP-QFD (Selected Model) | Prioritizes and translates customer needs into technical requirements | High—aligns directly with study objectives |
Value Engineering | Systematic approach to improving value by analyzing function and cost | Low—less applicable to LSQ |
TRIZ | Problem-solving based on patterns of invention | Low—good for innovation, not prioritization |
Agile/Scrum | Iterative product development methodology | Low—not aligned with postal service context |
Weight | 8 | 7 | 6 | 5 | 4 | 3 | 2 | 1 | Weighted Average Score |
---|---|---|---|---|---|---|---|---|---|
LSQ Dimensions | Rank 1 | Rank 2 | Rank 3 | Rank 4 | Rank 5 | Rank 6 | Rank 7 | Rank 8 | |
IQ | 26 | 27 | 17 | 90 | 45 | 15 | 21 | 14 | 4.824 |
OP | 20 | 28 | 37 | 18 | 15 | 95 | 27 | 15 | 4.243 |
OD | 30 | 24 | 14 | 13 | 24 | 19 | 28 | 103 | 3.408 |
PQ | 16 | 35 | 83 | 23 | 29 | 40 | 17 | 12 | 4.973 |
OQ | 21 | 14 | 24 | 25 | 91 | 27 | 20 | 33 | 4.129 |
TM | 91 | 33 | 21 | 35 | 21 | 15 | 19 | 20 | 5.675 |
OA | 19 | 20 | 11 | 27 | 11 | 29 | 96 | 42 | 3.365 |
OC | 32 | 74 | 48 | 24 | 19 | 15 | 27 | 16 | 5.384 |
Intensity | Definition |
---|---|
1 | Equal importance |
3 | Moderate importance |
5 | Strong importance |
7 | Very strong importance |
9 | Extreme importance |
2, 4, 6, 8 | Intermediate values |
Service Parameter | Geometric Mean of Normalized Weights | Ranks |
---|---|---|
Fast sorting and distribution (FSD) | 0.051 | 6 |
Transit time analysis (TTA) | 0.211 | 2 |
Core system integration (CSI) | 0.213 | 1 |
Network integration (NI) | 0.109 | 4 |
Disaster-relief centers (DRC) | 0.024 | 8 |
Scan compliance (SC) | 0.190 | 3 |
Multi-model transport integration (MMT) | 0.030 | 7 |
Change management (CM) | 0.015 | 9 |
Dynamic queue management system (DQM) | 0.088 | 5 |
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James, N.; Kumar, A.K.P.; Nathan, R.J. Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment. Economies 2025, 13, 120. https://doi.org/10.3390/economies13050120
James N, Kumar AKP, Nathan RJ. Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment. Economies. 2025; 13(5):120. https://doi.org/10.3390/economies13050120
Chicago/Turabian StyleJames, Nisa, Anish K. P. Kumar, and Robert Jeyakumar Nathan. 2025. "Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment" Economies 13, no. 5: 120. https://doi.org/10.3390/economies13050120
APA StyleJames, N., Kumar, A. K. P., & Nathan, R. J. (2025). Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment. Economies, 13(5), 120. https://doi.org/10.3390/economies13050120