Logistic Service Improvement Parameters for Postal Service Providers Using Analytical Hierarchy Process and Quality Function Deployment

Abstract

Postal services have re-emerged across numerous emerging economies worldwide as essential logistics providers, harnessing their vast coverage and dependability in the face of expanding e-commerce platforms and technological innovations. This study investigates India Post, one of the largest postal networks globally, to determine the key logistics service parameters prioritized by customers in southern India. Quantitative data obtained from 255 India Post end-users were evaluated using the logistics service quality (LSQ) scale, assessing eight dimensions including information quality, timeliness, ordering procedure, order accuracy, order condition, personal contact quality, order discrepancy handling, and order release quantities. The Analytical Hierarchy Process (AHP) ranked these elements, while Quality Function Deployment (QFD) bridged customer expectations with service improvements. The findings highlight the need to improve sorting and distribution processes to meet customer demands for timely, high-quality delivery. By refining logistics efficiency, this study provides suggestions and recommendations for boosting satisfaction and profitability, shedding light on service-led economic advancement for postal services in emerging economies. These insights equip postal service providers to cultivate loyalty and maintain competitiveness within the dynamic logistics landscape.

1. Introduction

The global postal sector is a longstanding pillar of global communication and commerce, traditionally focused on delivering letters and parcels, connecting people and businesses alike (Kováčiková et al., 2023). This is not confined to the exchange of mail alone, but also to communication and logistics networks. Advancements in technology, however, have forced a paradigm shift in the way national posts operate, generate revenue, and operate profitably. Hence, the most important challenge for the industry is maintaining sustainability in reach, coverage, and innovation.

The Universal Postal Union (UPU) conducted an extensive study covering 174 countries worldwide, utilizing the Integrated Index for Postal Development (2IPD) to assess the complexities of global postal progress. According to the State of the Postal Sector 2024 report, released on 17 December 2024, by the UPU, this study reveals that disparities in postal development between nations continue to exacerbate economic disadvantages, particularly as the postal sector’s role in e-commerce and logistics grows. The report highlights how countries with lower 2IPD scores, evaluated across reliability, reach, relevance, and resilience, struggle to leverage postal networks for economic growth, widening the gap with higher-performing nations like Switzerland and Germany, which topped the 2024 rankings.

Parcel and logistics services have emerged as vital frontiers in the global postal industry, driven by the e-commerce boom, with their revenue share rising from 11% in 2005 to 32% in 2021 and projected to reach 36% by 2025, according to trends observed in the International Post Corporation (IPC) Global Postal Industry Report 2024 (International Post Corporation, 2024) which notes a 6.8% parcel volume increase in 2023 alone. This rapid growth, further supported by Cognitive Market Research (2024) estimating the parcel delivery market at USD 468.2 billion in 2023 with a 4.6% CAGR through 2030, highlights the sector’s expanding role, creating both enhanced last-mile solutions and challenges, such as intensified competition and operational costs, for postal operators worldwide. A comparative analysis with other market analysts reveals a strong convergence in growth expectations. Statista (2024) projects a CAGR of approximately 4.8% for the same period, reflecting similar optimism. McKinsey & Company (2023) reports a long-term annual growth rate of 4.5–5% for the parcel and last-mile delivery segment. IBISWorld (2024) also forecasts steady growth, estimating a CAGR of 4.7% over the next five years. These consistent growth projections from multiple sources validate the strategic importance of the logistics segment within the postal sector. Table 1 below presents a comparative summary of these CAGR estimates.

Couriers and postal operators offer a crucial role in the global logistics infrastructure which is necessary to achieve specifically target 9.1 and 9.4 in the United Nation’s Sustainable Development Goal Number 9 (SDG9).

SDG 9 aims to build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation. This goal is particularly relevant to research focused on improving logistics service quality in postal systems, as it underscores the importance of enhancing infrastructure and fostering innovation in the postal and logistics sectors. Strengthening logistics services contributes to the development of more efficient and reliable infrastructure, which is essential for economic growth and connectivity, especially in rural and underserved regions. Additionally, the research aligns with the following targets under SDG 9:

Target 9.1: Develop quality, reliable, sustainable, and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all.

Target 9.4: Upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes.

In the global ranking, Switzerland leads the table. It is noteworthy that performance is a significant factor. The Asia-Pacific region has improved its performance from the previous ranking but still lags far behind Europe. Service delivery and customer satisfaction play vital roles in the ranking mechanisms. Logistics service quality has become very important, as the revenue from this operation is growing rapidly.

India Post was selected for this study because of its extensive and unparalleled reach across the vast and diverse geographical landscape of India. As one of the largest postal networks in the world, India Post provides a unique case for examining logistics service improvement parameters, given its significant role in delivering postal and financial services, especially in rural and remote areas. Its long-standing history, wide range of services, and ongoing modernization efforts make it an ideal subject for analyzing and enhancing the efficiency and effectiveness of national postal services. India Post, established in 1854, is a government-operated postal system functioning under the Department of Posts within the Ministry of Communications, Government of India. As a public sector entity, it has historically maintained a dominant position in the Indian postal ecosystem. In the traditional postal service segment such as letter mail, money orders, and rural postal services, India Post primarily operates as a monopoly, being the sole provider due to government control and regulatory protections. However, with the liberalization of the logistics and courier sector, several private players such as Blue Dart, DTDC, and Delhivery have entered the market, particularly in urban and semi-urban regions. In this broader logistics and parcel delivery segment, India Post faces considerable competition, and the market structure reflects characteristics of monopolistic competition or oligopoly. Despite this, India Post continues to hold a competitive edge, especially in rural areas, owing to its extensive network, universal service obligations, and integration with government schemes, which collectively distinguish it within the evolving postal and logistics landscape.

There is no other public utility in India that has touched the common man like India Post. While advancements in digital communication and technology have reduced the routine reliance on traditional postal services among the general population, the resurgence of India Post has been facilitated by the rapid growth of e-commerce, which demands robust logistics and supply chain capabilities. Leveraging its extensive network, nationwide coverage, and institutional reliability, India Post has repositioned itself as a critical player in last-mile delivery and logistics support, particularly in underserved and rural regions. India Post has been the primary service provider in India when it comes to traditional postal services and number one in the world with the largest network (India Post, 2021). With the advent of technology and better communication methodologies, traditional postal services such as letters, post, and telegrams have taken a back seat. The banking and financial service industry has undergone a plethora of changes, which has also reduced the need for money orders and other financial services through India Post. This has pushed India Post to identify or modify existing services, enhance efficiency, and enter new business domains by exploiting the large network and coverage it has established.

The e-commerce revolution in India mandated that large players could leverage the logistics aspects of business. Millions of orders are placed daily on various online portals that need to be delivered from the manufacturer to the customer. Moreover, the development of reverse logistics has boosted the requirement for reliable and efficient logistics players who can provide services at the lowest possible cost. The major challenges include speed, efficiency, accuracy, and cost. As e-commerce drives a surge in parcel volumes, postal service providers need to streamline their operations to manage the growing demand while maintaining high service quality (Baláž et al., 2024).

The Department of Post in India faces intense competition from private courier services, and to emerge as a leader in the mailing and courier sector, it must undertake substantial changes in its services and technology (Sangeetha & Subatra, 2023; Kavitha et al., 2023; Noordin et al., 2012). Understanding customer requirements is paramount for India Post to enhance its services and to ensure customer satisfaction. While India Post enjoys a strong brand image, it needs to focus on improving various dimensions of service quality to attain customer satisfaction and establish its services as indispensable. This entails a comprehensive approach that concentrates on balanced growth across all services to retain existing customers and attract new ones.

From a literature review, this study identifies various aspects of logistics service quality that are relevant to India Post. Subsequently, customers of India Post were surveyed to assess and prioritize the identified dimensions of service quality according to their perceived importance.

The study identified the service parameters associated with these quality dimensions by conducting interviews with experts in India Post. Following this, three senior officials were consulted to determine the order of priority for these service parameters using the Analytical Hierarchy Process (AHP) (e Costa & Vansnick, 2008). Subsequently, an analysis was carried out using Quality Function Deployment (QFD) (Loya et al., 2023) to assess which service parameters demanded the most attention from India Post. In this analysis, the priorities assigned to service quality dimensions by India Post customers were treated as customer requirements and assigned importance ratings. This facilitated a comparison of the disparity in the prioritization of service parameters between customers and India Post, ultimately pinpointing the areas that require the highest level of attention.

The voice of the customer (VoC) helps us to understand realistic customer expectations and improve the service quality provided by organizations (Rajendran et al., 2023; Griffin & Hauser, 1993). It helps to map the needs, requirements, and perceptions of customers about various products and services. The AHP model was created by Saaty (1970), who found its application in solving multi-criteria decision-making problems (Basílio et al., 2022) where the pairwise comparison of criteria results in proportional weights of criteria. This helps to attribute a rank to each criterion. The AHP was used in this study to evaluate the weight of the nine service parameters in measuring the priorities. The opinions and subjective evaluations of experts are objective and, thus, more reliable. Its application has been reported in numerous fields such as portfolio selection, corporate planning, transportation planning, and student admission (James et al., 2023) and supplier selection (Joseph & James, 2018). Quality Function Deployment (QFD) is a “systematic approach employed to ascertain and accurately translate consumer demands and preferences into specific technical requirements, manufacturing processes, and precise production planning” (Zhou et al., 2022; Bossert, 2021; Revelle et al., 1998), and central to QFD is the “house of quality, a graphical matrix incorporating six key elements: the voice of the customer, technical response, relationship, benchmarks, correlations, and technical assessment”.

Effective communication between industry stakeholders, customers, and management representatives is crucial for gathering essential information. The house of quality (Figure 1) serves as the initial phase in the QFD process (Vairaktarakis, 1999), resembling a house’s structural framework, emphasizing customer needs and aligning the design and development process with customer preferences, ultimately reducing the time to market.

The pivotal relationship between service parameters and specific customer requirements can be established through QFD, which also entails evaluating and comparing results to enhance the product’s intended purpose. Following the identification of all the requirements, the critical question revolves around determining the necessary product/service design to meet these requirements and facilitate trade-off decisions. QFD serves as a method to link consumer wants and needs to design objectives, employing quality as a pivotal assurance mechanism during the product development phase.

The study of logistics service quality is crucial for India Post, as it operates in a highly competitive sector where enhancing service quality is essential for boosting customer loyalty (Naz et al., 2021).

Despite growing academic interest in LSQ, limited research has explored how customer expectations are systematically translated into service improvement strategies within public postal systems. This study addresses this gap by identifying the logistics service parameters that India Post customers in southern India value most and aligning these with internal service planning using an integrated AHP-QFD framework.

This study is guided by the following research questions:

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?

By analyzing the voice of the customer and refining its service parameters, India Post can provide quality services that maximize customer value. The findings of this study will not only have practical significance in improving India Post’s logistics services but also contribute to the organization’s competitiveness in a global courier services market that is experiencing transformative changes due to the surge in e-commerce and evolving customer needs.

2. Literature Review

Logistics has always supported production and consumption, and its functions are viewed as a cost by traditional courier service providers. This view began to shift in the 1990s, and logistics functions are now considered more as a “tool leading to greater customer satisfaction and loyalty” (Do et al., 2023; Lin et al., 2023; Mentzer et al., 2001). Service quality is the evaluation of the general quality of the services provided to customers. It results from customers’ perceptions of how well the service meets their expectations in comparison to the actual performance of the service (Parasuraman et al., 1985). Eight dimensions of service quality (Table 2) in logistics sector were identified by Rafiq and Jaafar (2007), viz. “information quality (IQ), ordering procedures (OP), order release quantities (OQ), timeliness (TM), order accuracy (OA), order condition (OC), order discrepancy handling (OD), and personnel contact quality (PQ)”.

In the evolving landscape of global postal and courier services, logistics service quality (LSQ) has emerged as a critical determinant of customer satisfaction and loyalty. Recent studies underscore the significance of key LSQ dimensions—such as reliability, responsiveness, and empathy—in influencing customer perceptions and behaviors. For instance, Tang et al. (2022) found that reliability, responsiveness, and empathy significantly impact customer satisfaction in courier services, with empathy being the most influential factor. Similarly, Gulc (2021) identified reliability, responsiveness, and technical quality as pivotal in shaping customer satisfaction within the e-commerce courier sector.

Widely adopted and cited parameters of logistics service quality are as follows:

Various multi-criteria decision-making approaches are used for product design, redesign, and incorporating customer voices in product development. When combined with QFD, AHP is considered the best approach for resolving subjective choice problems that involve placing the customer’s voice first and transferring it to the engineering, manufacturing, production, and supplier quality specifications (Fehlmann & Glenn, 2016).

The AHP-QFD approach not only improves the quality of the final product (Apichonbancha et al., 2024; Buakum et al., 2024; Li et al., 2023; Kapuria & Karmaker, 2018), but it is also an effective method that can be used in diverse service scenarios, such as education, to identify different teaching methods (Lam & Zhao, 1998) and techniques and evaluate their effectiveness in achieving educational objectives and streamlining student admission in higher-education institutions (James et al., 2023). Köksal and Eğïtman (1998) used the integrated AHP-QFD strategy to raise the standard of instruction. Killen et al. (2005) presented the idea of strategic planning using QFD, which offers an outline and justification for the main steps in the planning process. The study also demonstrates the application of strategic QFD in locating and addressing consumer prospects as well as in identifying and optimizing internal capabilities. When applied to strategic planning, QFD maintains the integrity of the VOC and produces creative solutions to realize an organization’s goals (Maritan & Panizzolo, 2009). Additionally, recent studies (Liu et al., 2024; Paltayian et al., 2024; Hariri et al., 2023; Çetin & Ucler, 2023) contend that this integrated approach immediately results in service design and enhancement, the adoption of policies for implementation, and performance control.

3. Methodology

In this study, critical service parameters are identified for a national postal service provider. This is achieved by translating customer requirements into the desired service parameters and determining the priority that both the postal service provider and customers assign to these parameters. The robustness of this integrated approach has been validated in several studies (Paltayian et al., 2024; Hariri et al., 2023; Çetin & Ucler, 2023; Sharma & Tripathy, 2023), as the conceptual and procedural frameworks remain consistent. The main aim of this research was to determine the most crucial service parameters of India Post, focusing on logistics service quality (LSQ) as perceived by customers.

A non-probability purposive sampling technique was adopted to ensure that respondents had relevant experience with India Post’s logistics services. A total of 255 customers who had availed of the logistics services of India Post within the previous six months were surveyed across selected post offices and customer service points in southern India. The inclusion criteria required that participants be above 18 years of age and have firsthand experience using India Post’s parcel or courier services.

Respondents were approached in person, and data were collected using an offline structured questionnaire. Participation was voluntary, and oral informed consent was obtained from each participant prior to data collection. To reduce potential sampling bias, efforts were made to include a diverse mix of users from urban and semi-urban locations.

The questionnaire was developed based on the logistics service quality (LSQ) scale proposed by Mentzer et al. (1999) and included 24 items grouped under eight key dimensions: information quality, timeliness, ordering procedure, order accuracy, order condition, personal contact quality, order discrepancy handling, and order release quantities.

Each item was measured using a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Respondents were also asked to rank these eight dimensions in order of perceived importance. Additionally, responses were gathered from India Post officials using an AHP matrix, to prioritize service parameters. Interviews with three key officials from different departments of India Post were conducted to gain insights into any potential differences in service parameter priorities between customers and the organization itself.

Subsequently, Quality Function Deployment (QFD) was employed to identify the service parameters that required the most attention from India Post (Loya et al., 2023). In this approach, the service quality dimensions prioritized by customers were treated as customer requirements and assigned corresponding importance weights. This enabled a comparative analysis between the priorities of India Post customers and those of the service provider, thereby highlighting critical areas where attention and improvement are most needed.

In traditional QFD applications, companies must identify customer expectations and their relative importance (external variables) to determine the internal service parameters that should receive the most resources. However, this study focuses on starting with the quality dimensions deemed important by customers and translating these into specific service parameters. Once the service provider identifies and prioritizes these parameters, a comparative analysis can be conducted to assess any discrepancies between the importance attributed by the organization and the customer. This approach enhances the focus on critical service parameters, ultimately leading to improved customer satisfaction.

The data collection process, conducted offline using straightforward and non-sensitive questions, adhered to the ethical standards set by the 1964 Helsinki Declaration, minimizing potential risks or discomfort to participants. Informed oral consent was obtained from all participants, and as the research employed a non-intrusive quantitative approach with anonymized data, without collecting personal or sensitive information, ethical board approval was not required. All responses were treated with strict confidentiality and used solely for academic purposes, ensuring compliance with established ethical standards.

3.1. AHP and QFD

Comparing two items (objectives) in relation to one another in terms of their relative relevance, preference, or likelihood is called pairwise comparison (goal). Pairwise comparisons were made to determine the priority. To prioritize the service parameters, three stakeholders of India Post were asked to perform a pairwise comparison of the nine service parameters: fast sorting and dispatching process, core system integration, transit time analysis, disaster-management facility, scan compliance, fast sorting and distribution, network integration, mail transport integration, change management, and dynamic queue management system.

The QFD was used to translate customer requirements into service parameters. Customer requirements are captured as customers’ voices by prioritizing the LSQ dimensions. Every LSQ dimension must be translated into a service parameter that the organization must focus on. Discussions with experts from India Post helped to identify the corresponding service parameters pertaining to the services rendered by India Post. Volume VII of the Postal Manual (India Post, 2022) also serves as a reference to identify the service parameters, the definitions of which are given in Table A1 in Appendix A.

Comparative Analysis of Design and Decision-Making Frameworks

To substantiate the selection of the integrated AHP-QFD methodology, this section provides a critical comparative analysis through Table 3, of the established design and decision-making frameworks frequently employed in service quality enhancement and product development research.

Each service design and decision-making model offers unique strengths that cater to specific contexts and problem structures. For instance, Design Thinking emphasizes empathy and user-centered innovation, making it ideal for exploratory problem-solving and creative ideation (Schlott, 2024), but it lacks the structured prioritization mechanisms necessary for complex multi-criteria decisions. The Kano Model effectively classifies customer requirements based on satisfaction (Madzík et al., 2024) impact but does not provide guidance on how to translate these into operational parameters. TRIZ and Axiomatic Design are powerful in solving engineering design problems through systematic innovation and functional decomposition, respectively (Rong et al., 2024), yet they require high technical expertise and may not be easily adaptable to service-oriented contexts. Agile and Scrum frameworks excel in iterative development and flexibility (Natarajan & Pichai, 2024) but are less suited for strategic planning involving structured analysis of customer needs. Value Engineering (VE)/Value Analysis (VA) focuses on maximizing value by balancing function and cost (Jazzaa, 2024), though it can overlook qualitative customer preferences. In contrast, the AHP-QFD integrated approach offers a balanced methodology that combines the quantitative rigor of multi-criteria decision-making with a structured mechanism to translate customer expectations into actionable service design priorities. However, it may be resource-intensive in terms of data collection and expert involvement. This study adopts the AHP-QFD framework due to its ability to systematically prioritize service quality dimensions and align them with organizational improvements, which is particularly relevant in logistics service contexts like that of India Post.

A SWOT analysis of the AHP-QFD integrated approach reveals a strategic balance of methodological strengths and contextual limitations. The strengths of this method lie in its structured and systematic framework for decision-making, enabling the quantification and prioritization of customer requirements (via AHP) and their effective translation into technical or service parameters (via QFD). This ensures alignment between customer expectations and organizational actions (Apichonbancha et al., 2024). Its weaknesses, however, include the intensive data requirements, reliance on expert judgment for pairwise comparisons, and the potential for inconsistency in subjective evaluations. In terms of opportunities, the method’s adaptability across diverse industries—including logistics, manufacturing, and healthcare—presents potential for broader application, especially in enhancing service quality in public sector organizations. Additionally, advancements in decision-support tools and software can streamline its implementation. However, threats may arise from the emergence of more agile or AI-driven decision-making models that promise quicker iterations and real-time adaptability, potentially challenging the continued dominance of traditional hierarchical frameworks like AHP-QFD in fast-paced environments.

4. Results

Of the 57.3% male and 42.7% female respondents, the majority of them fall between 18 and 30 years of age (30.2%), followed by the age groups of 45–60 years (25.9%), 30–45 years (22.7%), and finally those above 60 years (21.2%). This shows that the 18–30 and 45–60 age groups mostly avail of the services of India posts.

4.1. Prioritization of Logistics Service Quality Dimensions by Customers

The weighted average score (Table 4) of the LSQ dimensions revealed that the majority of the customers looked for timeliness (5.675), which was given the highest priority, followed by order condition (5.384), personal contact quality (4.973), information quality (4.824), ordering procedure (4.243), order release quantities (4.129), order discrepancy handling (3.408), and order accuracy (3.365).

4.2. Prioritization of Service Parameters from the Point of View of India Post

To prioritize the service parameters, three senior officials of India Post were asked to perform a pair wise comparison using the Analytical Hierarchy Process (AHP) of the nine service parameters: fast sorting and dispatching process, core system integration, transit time analysis, disaster-management facility, scan compliance, fast sorting and distribution, network integration, mail transport integration, change management, and dynamic queue management system (Table A3, Table A6 and Table A9, in Appendix A). This process unveiled the hierarchy of importance that India Post places on the service parameters.

Table 5 describes the “linguistic variables and their corresponding numerical values” (Saaty, 1980). Pairwise comparison of service parameters by each of the three stakeholders was performed, followed by calculation of the normalized weights (Table A4, Table A7 and Table A10 in Appendix A), and consistency checks were carried out.

4.3. Normalization

To normalize the weights, the sum of each column was computed, and each column was divided by the corresponding sum to obtain a value of less than 1.

When the total weight of the service parameters is greater than 1, the weight of the parameters is normalized by dividing the total weight by each of the service parameters to obtain a value less than 1.

4.4. Consistency Check

To ascertain the accuracy of the weights allocated through expert judgment, must be determined. Hence, consistency ratio (CR) checking is necessary; typically, a value of less than 0.1 indicates that the weights are consistent. The following formula was used to determine the consistency ratio (CR):

CR = CI/RI, where CI is the consistency index and RI is the random consistency index (Table A2, Appendix A).

CI = (λmax − n)/n − 1, λmax = average of the normalized weight of the criteria, n = number of comparisons. λmax is found as the maximum eigen value (Table A5, Table A8 and Table A11).

As the value of the CI obtained is <0.1, the degree of consistency is well satisfied, and hence the weights are valid. As the pairwise comparison was performed by multiple respondents, the geometric mean of the ranks of each service parameter was taken (Table 6).

The ranking of the service parameters from the most important to the least important by the three stakeholders was computed by taking the geometric mean of the normalized weights. The results show that core system integration (0.213) has the highest priority, followed by transit time analysis (0.211), scan compliance (0.190), network integration (0.109), dynamic queue management system (0.088), fast sorting and distribution (0.051), multi-model transport integration (0.030), and change management (0.015).

4.5. Identification of Important Service Parameters Using QFD

QFD offers “a structured decision-making process for converting customer requirements into quantifiable service specifications and disseminating a culture of quality within the organization, allowing for customer satisfaction” (Alsaadi et al., 2018). Here, customer requirements are captured by identifying priorities attached to various dimensions of logistics service quality. Service specifications corresponding to logistics quality dimensions were identified and prioritized.

The most frequently utilized component of the QFD is the House of Quality (HOQ). A mixture of sub-matrices, the HOQ matrix, obtains its name from its appearance as a house. Its purpose is to boost customer satisfaction by providing clients with the desired services.

The House of Quality was set up with the dimensions of the logistics service quality and service parameters. On the left side of the matrix, logistical service quality dimensions and the corresponding ranks given by customers are placed. The service parameters identified and ranked by India Post using AHP were placed at the top and middle of the house.

In the next step, customer requirements and service parameters are compared. For this comparison, a 1-3-9 scale was used, where 1 was the weakest, 3 was the middle, and 9 was a strong relationship. Instead of numbers, symbols are used to represent this strength.

●	Strong relationship.
○	Medium relationship.
▽	Weak relationship.

At the top of the house of quality matrix, the interrelations between each service parameter are performed and are indicated using symbols where (+) represents a positive correlation, (−) indicates a negative relationship, and where there is no symbol, it is represented as no correlation. To calculate the importance rating, the percentage of the importance rating is multiplied by the relationship score for each customer need. All values for each column of the service parameters were added, and the sum was written at the bottom of the table. This represents the total importance of each service parameter. The totals were added to the importance rating. Each rating was divided by the total score. The requirements with the highest importance ratings or percentages are the service parameters that India Post should prioritize or invest more in.

The absolute weight sum of service parameters are calculated as follows:

(1)$Wj=\sum _{i=1}^{n}Xiaij$

where,

Xi = the priority of the row item (customer need priority in the house of quality)

aij = the strength of the relationship

The HOQ matrix (Figure 2) indicates that the most important service parameters that are vital to improving the logistics services of India Post in order to meet customer requirements are fast sorting and distribution followed by scan compliance, transit time analysis, network integration, multi-model transport integration, core system integration, dynamic queue management system, change management, and disaster-relief centers.

However, according to the prioritization of the officials of India Post, the most important service parameter is core system integration followed by transit time analysis, scan compliance, network integration, dynamic queue management system, fast sorting and distribution, and multi-model transport integration, and the least prioritized is change management.

It is observed that the most important service parameter for meeting customer requirements optimally is fast sorting and distribution, which was not prioritized by the officials of India Post. This shows that there is a gap in the understanding of the requirements of customer needs. The priority given by India’s post-service parameters is not in line with the priorities attributed by customers.

Customers should be considered the most valuable asset, and ensuring timely and quality service to customers is the pre-requisite for retaining the present market share of India Post. To enhance the quality of logistics services, it is essential to focus on delivery timeliness, ensuring that customers receive goods according to a predetermined schedule (Restuputri et al., 2021). The Department of Post must assess its logistical performance compared to that of its competitors and make the necessary adjustments.

5. Discussion

This study presents an integrated AHP-QFD methodology to translate the voice of the customer into the desired service parameters, which helps the organization to deliver high-quality services. A critical comparison of Table 4 and Table 6, along with the HOQ matrix (Figure 2), reveals a distinct misalignment between customer expectations and the prioritization of service parameters by India Post officials. While customers place the highest value on “fast sorting and distribution” to ensure timely deliveries, officials consider “core system integration” to be of the utmost importance. This divergence highlights a strategic gap in the organization’s understanding of end-user needs.

The relatively lower emphasis by officials on sorting and distribution efficiency—which customers perceive as most vital—indicates an urgent need to recalibrate internal priorities. Failure to do so may result in customer dissatisfaction and declining competitiveness. Aligning internal processes with customer priorities is crucial for enhancing logistics service quality and sustaining relevance in the evolving postal logistics landscape. The results show that to satisfy the customer requirements of timely delivery and quality in services, it has to ensure fast sorting and distribution together with other parameters such as scan compliance, transit time analysis, network integration, multi-model transport integration, core system integration, dynamic queue management system, change management, and disaster-relief centers. However, it was also found that there is a mismatch between assessing customer requirements and the prioritization of service parameters by India Post, which can have a significant impact on customer satisfaction levels. Modern-day businesses depend on customer loyalty and customer lifetime value. It is especially important for business organizations to capture the voices of customers. The voice of the customer provides deep insight into the cognitive and affective domains of consumer decision-making.

Logistics play a vital role in the procurement, delivery, and ease of purchase of most businesses. The global courier services market is witnessing significant changes, primarily driven by increasing demand for parcel delivery across various sectors, including B2C, B2B, and C2C. Private courier providers are adapting to these changes by offering new models and technologies to meet customers’ evolving needs and by optimizing costs. In this context, India Post faces the challenge of staying competitive among technologically advanced private competitors. To achieve this, it must focus on enhancing its service parameters to satisfy and retain customers. This study aims to help India Post to understand customer attitudes toward its logistics services, which will aid in making necessary improvements. In today’s digital era, customer expectations and preferences have shifted, and customers have a plethora of alternatives at their fingertips. Thus, India Post must adapt to these changing dynamics to secure its position as a leader in the current market.

Recent studies in logistics and postal services have highlighted the importance of digital transformation and innovation in enhancing service quality and customer satisfaction. A current published study by Baláž et al. (2024) emphasized the role of the Internet of Things (IoT) in improving postal service efficiency, which aligns with our findings on the need for fast sorting and distribution. As companies strive to stay competitive in today’s global marketplace, they are increasingly turning to PTL systems to boost efficiency, responsiveness, and customer focus (Abdu, 2024). Similarly, the integration of advanced technologies such as AI and machine learning in logistics can significantly enhance operational efficiency and customer experience (Do et al., 2023). These technological advancements can help India Post to address the gaps identified in this study and improve its service quality.

Moreover, the role of postal services in regional economic development cannot be overstated. The Universal Postal Union (UPU) has highlighted the critical role of postal networks in promoting financial and digital inclusion, particularly in rural and underserved areas (Universal Postal Union, 2024). By leveraging its extensive network, India Post can drive regional development through improved logistics, e-commerce facilitation, and digital inclusion. This aligns with the findings of this study, which emphasize the need for India Post to enhance its service parameters to meet customer expectations and contribute to regional economic growth.

To remain relevant in a fast-evolving digital logistics ecosystem, India Post must proactively embrace emerging technologies and modernize its operational backbone. Some of the critical technological challenges and innovation areas that require immediate attention include logistics and distribution automation, digitalization of traditional services, and the integration of artificial intelligence (AI) and data analytics for predictive performance tracking and customer behaviour analysis. Strengthening cybersecurity infrastructure is essential to protect customer data and build trust, particularly as mobile and app-based services expand.

Furthermore, enhancing rural connectivity is vital for ensuring equitable access, especially as India Post aims to promote financial inclusion through fintech solutions. E-commerce and marketplace integration can also position India Post as a key enabler of small business growth in underserved regions. IT modernization, cloud migration, and robust KPI tracking systems will provide the organization with real-time insights for agile decision-making and service improvement. These advancements may also necessitate departmental restructuring and capacity-building initiatives to align internal competencies with the demands of a tech-enabled service environment.

Incorporating these innovations aligns with global best practices and supports India Post’s broader mandate of contributing to the socio-economic, cultural, and financial development of India’s regional economies. This strategic transformation can create positive externalities by fostering digital inclusion, improving rural livelihoods, and enhancing the logistics infrastructure critical for a connected and competitive India.

While the study employed the Analytic Hierarchy Process (AHP) and ensured internal consistency using the consistency ratio (CR), further model robustness checks such as sensitivity analysis, subgroup comparisons, or simulations (e.g., Monte Carlo or bootstrapping) were not undertaken. These techniques can provide additional insights into the stability and variability of prioritization outcomes in response to changes in the input data. However, as the present study aimed primarily at exploring and prioritizing service quality parameters within a structured decision-making framework rather than building predictive or inferential models, such methods were beyond its intended scope. Future research could integrate these analytical extensions to enhance model robustness and explore how variations in stakeholder input affect the final rankings.

In conclusion, this study contributes to the understanding of logistics service quality in the context of national postal services. The findings highlight the importance of aligning service parameters with customer expectations to enhance satisfaction and loyalty. By comparing these results with recent findings from high-impact marketing, economics, postal, and logistics research journals, we provide a comprehensive view of the current landscape and offer practical recommendations for India Post to optimize its services. Future research should explore the implementation and impact of the recommended service improvements and continuously monitor customer satisfaction levels to ensure sustained success.

6. Conclusions

This study addresses the need to enhance postal services and competitiveness amidst private courier competition, while also acknowledging the broader shift in the global courier market driven by changing customer demands and e-commerce growth. India Post was selected for this study for the gathering of research data due to its large capacity, history, and prominence. By analyzing and acting upon customer feedback and leveraging its established network, India Post can position itself as a leader and ensure customer satisfaction in the evolving landscape, where customer choices are more diverse and dynamic than ever before. In contemporary digital landscapes, customer anticipation and choices have evolved significantly, with a multitude of alternatives that are easily accessible. Therefore, it is imperative for postal service providers to adjust to these evolving dynamics to maintain their leadership position in the present market scenario.

The successful implementation of technology-driven enhancements in India Post also hinges on the innovative capacity and digital readiness of consumers. Technological efficiency cannot be achieved in isolation; it must be complemented by a user base that is capable of adopting and utilizing digital tools effectively. This study suggests that India Post should consider a geographically targeted strategy, initiating pilot programs in regions with high levels of digital literacy and infrastructure readiness to introduce technologically advanced services such as mobile-based platforms, real-time tracking, and AI-powered support systems. Simultaneously, in areas with lower levels of digitalization, the organization should collaborate with public and private partners to invest in digital literacy programs, infrastructure development, and user education. Such a dual-pronged approach can help to bridge the digital divide, ensuring that innovation is inclusive and that all segments of the population can benefit from the modernization of postal and logistics services.

Future research could involve assessing the suggested implementation and impact of the recommended service improvements to postal service providers. This would include monitoring customer satisfaction levels post-implementation, analyzing any operational challenges faced during the changes, and identifying further areas for refinement. Additionally, exploring advancements in technology and logistics practices to continuously enhance service parameters would be crucial for courier and logistics service providers to remain competitive in the evolving global courier services market. This also relates to the need to enhance the reliability of such logistics and courier delivery networks to ensure uninterrupted supply, especially when it comes to the food supply chain and other essential goods’ delivery to consumers. Courier and postal services that are delivered without interruption would provide a backbone for a clear delivery network for essential items as well, especially during critical time periods such as natural disasters or crisis, when the food supply chain would be critical for people affected by the crisis. Postal and courier service providers have the leverage to play a critical role during times of need to serve the people when they have established a supply chain network connecting people from vast geographical distances with their resilient end-to-end connectivity.

Author Contributions

Conceptualization, N.J.; Methodology, A.K.P.K. and R.J.N.; Software, N.J. and A.K.P.K.; Validation, N.J. and A.K.P.K. Formal analysis, A.K.P.K.; Investigation, N.J. and A.K.P.K.; Resources, R.J.N.; Data curation, N.J.; Writing—original draft, N.J. and A.K.P.K.; Writing—review & editing, R.J.N.; Visualization, N.J.; Supervision, R.J.N.; Project administration, R.J.N.; Funding acquisition, R.J.N. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The data collection process, conducted offline using straightforward and non-sensitive questions, adhered to the ethical standards set by the 1964 Helsinki Declaration, minimizing potential risks or discomfort to participants. Informed oral consent was obtained from all participants, and as the research employed a non-intrusive quantitative approach with anonymized data, without collecting personal or sensitive information, ethical board approval was not required. All responses were treated with strict confidentiality and used solely for academic purposes, ensuring compliance with established ethical standards.

Informed Consent Statement

Informed oral consent was obtained from all participants.

Data Availability Statement

The data supporting the findings of this study are not publicly available to ensure the confidentiality of participant responses and adherence to ethical standards. Data access can be provided upon reasonable request, subject to approval from the corresponding author, and in accordance with the privacy and ethical guidelines.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

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

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1 House of quality.

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Figure 2 House of quality matrix of India Post (source: self-computed for this study).

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Table 1

Comparative CAGR estimates for the global parcel delivery market (2023–2030).

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%

(Source: Compiled from various sources).

Table 2

Parameters of logistics service quality.

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

Source: (Mentzer et al., 1999) and (Rafiq & Jaafar, 2007).

Table 3

Comparative analysis of design and decision-making frameworks.

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

Source: compiled by the authors.

Table 4

Perception of customers towards the logistical service quality dimension.

Weight	8	7	6	5	4	3	2	1	WeightedAverageScore
LSQDimensions	Rank1	Rank2	Rank3	Rank4	Rank5	Rank6	Rank7	Rank8
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

(Source: computed for this study).

Table 5

Scale of relative importance.

Intensity	Definition
1	Equal importance
3	Moderate importance
5	Strong importance
7	Very strong importance
9	Extreme importance
2, 4, 6, 8	Intermediate values

(Source: Saaty, 1980).

Table 6

Ranks of service parameters.

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

(Source: self-computed for this study).

Appendix A

Table A1

Service parameters of India Post.

Service Parameter	Definition
Fast sorting anddispatching 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.

Table A2

Random consistency index.

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

Source: (Saaty, 1980).

Table A3

Pairwise comparison matrix of stakeholder 1.

	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

Table A4

Normalized weight for stakeholder 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

Table A5

Maximum eigen value of stakeholder 1.

Service Parameters	${\displaystyle \sum _{\mathit{j}=1}^{\mathit{n}}}\mathit{a}\mathit{i}\mathit{j}\mathbf{\ast }\mathit{e}\mathit{j}1$	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

Table A6

Pairwise comparison matrix for stakeholder 2.

	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

Table A7

Normalized weight for stakeholder 2.

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

Table A8

Maximum eigen value of stakeholder 2.

Service Parameters	${\displaystyle \sum _{\mathit{j}=1}^{\mathit{n}}}\mathit{a}\mathit{i}\mathit{j}\mathbf{\ast }\mathit{e}\mathit{j}1$	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

Table A9

Pairwise comparison matrix for stakeholder 3.

	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

Table A10

Normalized weight for stakeholder 3.

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

Table A11

Maximum eigen value for stakeholder 3.

Service Parameter	${\displaystyle \sum _{\mathit{j}=1}^{\mathit{n}}}\mathit{a}\mathit{i}\mathit{j}\mathbf{\ast }\mathit{e}\mathit{j}1$	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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