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In this study, the deployment of an integrated Quality Function Deployment (QFD) decision framework is presented to help cities design targeted strategies to become “smart”. Arguably smart cities leverage advanced technologies to enhance their smartness to improve everyday urban life. To this end, a QFD – Analytic Hierarchy Process – Analytic Network Process (QFD-AHP-ANP) framework is proposed to deliver guidance for selecting the appropriate mix of smart technologies based on the specific smart needs of each city.

The AHP and ANP methods are incorporated into QFD to enhance its methodological robustness in formulating the decision problem. AHP accurately captures and translates the “Voice of the Experts” into prioritized “Smart City” dimensions, while establishing inter-relationships between these dimensions and “Smart City Technologies”. Meanwhile, ANP explores tradeoffs among the technologies, enabling well-informed decisions. The framework’s effectiveness is evaluated through an illustrative application in the city of Thessaloniki.

Applying the framework to this real-world context confirms its practicality and utility, demonstrating its ability to particularize local, social, political, environmental and economic trends through the resulting mix of technologies in smart urban development strategies.

The importance of this study lies in several aspects. Firstly, it introduces a novel QFD decision framework tailored for smart city strategic planning. Secondly, it contributes to the operationalization of the smart city concept by providing guidance for cities to effectively adopt smart technologies. Finally, this study represents a new field of application for QFD, expanding its scope beyond its traditional domains.

The purpose of this paper is to provide an enhanced version of quality function deployment (QFD) that captures customers’ present and future preferences, accurately prioritizes product specifications and eventually translates them into desirable quality products. Under rapidly changing environments, customer requirements and preferences are constantly changing and evolving, rendering essential the realization of the dynamic role of the “Voice of the Customer (VoC)” in the design and development of products.

The proposed methodological framework incorporates a Multivariate Markov Chain (MMC) model to describe the pattern of changes in customer preferences over time, the Fuzzy AHP method to accommodate the uncertainty and subjectivity of the “VoC” and the LP-GW-AHP to discover the most important product specifications in order to structure a robust QFD method. This enhanced QFD framework (MMC-QFD-LP-GW-Fuzzy AHP) takes into consideration the dynamic nature of the “VoC” captures the actual customers’ preferences (WHATs) and interprets them into design decisions (HOWs).

The integration of MMC models into the QFD helps to handle the sequences of customers’ preferences as categorical data sequences and to consider the multiple interdependencies among them.

In this study, a MMC model is introduced for the first time within QFD, in an effort to extend the concept of listening to further anticipating to customer wants. Gaining a deeper understanding of current and future customers’ preferences could help organizations to design products and plan strategies that more effectively and efficiently satisfy them.

The purpose of this paper is to promote successful application of quality function deployment (QFD) combined with quantitative techniques in service organizations.

The paper assesses advantages and disadvantages of implementing the QFD method in service organizations. It discusses the integration of quantitative techniques with QFD in order to overcome some of the problems that organizations face in its application. The implementation of QFD along with AHP and ANP is studied within the bank sector. With the intention of completing the first House of Quality and thus prioritizing customers' bank selection criteria, a field survey was carried out with customers of a bank. Also, information from interviews with the bank's managers was utilized.

The real world illustration confirms the compatibility between QFD, AHP and ANP and demonstrates the applicability and ease of use of the proposed model.

A procedure is presented to help practitioners of this improved QFD framework deal with the challenges of quick response to dynamic shifts in customer needs by automating the House of Quality (HOQ). The paper could be useful to academics and practitioners in developing the integrated QFD‐AHP‐ANP method to design high quality services in various services.

The purpose of this paper is to promote the integration of quality function deployment (QFD) with quantitative methods in an attempt to enhance its effectiveness and resolve issues like the failure of prioritizing customer requirements and determining proper importance levels.

This paper discusses the combination of QFD with analytic hierarchy process‐analytic network process (AHP‐ANP) and DEAHP‐DEANP methodologies to prioritize selection criteria in a service context. DEAHP is a hybrid method, developed by Ramanathan. Data envelopment analysis (DEA) is embedded in the AHP methodology and potentially replaces the eigenvalue method. In this paper DEAHP is used for completing the relationship matrix of house of quality (HOQ). Furthermore, in accordance with the DEAHP method, a methodological framework for completing the roof matrix of HOQ is developed, based on DEA and ANP techniques‐DEANP. The implementation of QFD along with the above mentioned quantitative approaches is studied utilizing data from the Greek banking sector, and a comparative analysis is conducted.

The illustrative implementation offers support to the compatibility of the two alternative approaches demonstrating both applicability and ease of use. Results suggest that the QFD‐DEAHP‐DEANP methodology provides superior information since it offers more robust sensitivity analysis outcomes.

The novelty of this research lies in the innovative idea to use QFD in conjunction with DEAHP and in the development of the DEANP method. The proposed methodology is a valuable tool for identifying strategic opportunities and gaining sustainable advantage since it helps service providers to capture the mix of services that customers are expecting them to offer.