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Quality function deployment (QFD) is a methodology to translate the “voice of the customer” into engineering/technical specifications (HOWs) to be followed in designing of products or services. For the method to be effective, QFD practitioners need to be able to accurately differentiate between the final weights (FWs) that have been assigned to HOWs in the house of quality matrix. The paper aims to introduce a statistical testing procedure to determine whether the FWs of HOWs are significantly different and investigate the robustness of different rating scales used in QFD practice in contributing to these differences.

Using a range of published QFD examples, the paper uses a parametric bootstrap testing procedure to test the significance of the differences between the FWs by generating simulated random samples based on a theoretical probability model. The paper then determines the significance or otherwise of the differences between: the two most extreme FWs and all pairs of FWs. Finally, the paper checks the robustness of different attribute rating scales (linear vs non-linear) in the context of these testing procedures.

The paper demonstrates that not all of the differences that exist between the FWs of HOW attributes are in fact significant. In the absence of such a procedure, there is no reliable analytical basis for QFD practitioners to determine whether FWs are significantly different, and they may wrongly prioritise one engineering attribute over another.

This is the first article to test the significance of the differences between FWs of HOWs and to determine the robustness of different strength of scales used in relationship matrix.

The purpose of this paper is to introduce a solution to the problem of changing priorities of customer needs (CNs) in quality function deployment (QFD). Customer preferences and priorities are not very stable and they may change before products are ready for the market. Therefore, finding CNs accurately is a key to reach a higher level of customer satisfaction through improving products.

In the proposed model, a Markov chain is employed to model the changing priorities of CNs. The Markov chain finds a pattern of future CNs, the main inputs of QFD. The QFD method is applied to translate CNs into product requirements (PRs). The analytic network process (ANP) is attached to QFD to ensure that all the relations among the elements, inner and outer, are taken into consideration during the translation process. Thus, CNs are received and adjusted by a Markov chain.

The application of Markov chains for an ANP-QFD model develops an adequate method of finding a pattern of changing priorities of CNs. This pattern enables the ANP-QFD method to work independent of the initial CNs, and originates a Markovain ANP-QFD.

This study originates a stochastic ANP-QFD model. There have been several papers employing various tools and techniques such as the ANP or analytic hierarchy process for QFD to find accurate relations between PRs and CNs. While there are a few papers applying Markov chains to predict the future of the relations of QFD, there is no study which traces the changes in priorities of the CNs during the improvement process. This is addressed by applying a Markovian ANP-QFD. The model is validated through a case study.

Quality function deployment (QFD) is a planning methodology to improve products, services and their associated processes by ensuring that the voice of the customer has been effectively deployed through specified and prioritised technical attributes (TAs). The purpose of this paper is two ways: to enhance the prioritisation of TAs: computer simulation significance test; and computer simulation confidence interval. Both are based on permutation sampling, bootstrap sampling and parametric bootstrap sampling of given empirical data.

The authors present a theoretical case for the use permutation sampling, bootstrap sampling and parametric bootstrap sampling. Using a published case study the authors demonstrate how these can be applied on given empirical data to generate a theoretical population. From this the authors describe a procedure to decide upon which TAs have significantly different priority, and also estimate confidence intervals from the theoretical simulated populations.

First, the authors demonstrate not only parametric bootstrap is useful to simulate theoretical populations. The authors can also employ permutation sampling and bootstrap sampling to generate theoretical populations. Then the authors obtain the results from these three approaches. qThe authors describe why there is a difference in results of permutation sampling, bootstrap and parametric bootstrap sampling. Practitioners can employ any approach, it depends how much variation in FWs is required by quality assurance division.

Using these methods provides QFD practitioners with a robust and reliable method for determining which TAs should be selected for attention in product and service design. The explicit selection of TAs will help to achieve maximum customer satisfaction, and save time and money, which are the ultimate objectives of QFD.

The aim of this study is to examine the effect of financial leverage impact on customer satisfaction and marketing costs including research and development (R&D) and advertisement costs. Furthermore, the authors aim to investigate whether customer satisfaction as well as financial distress moderates the effect of financial leverage impact on customer satisfaction and marketing costs including R&D and advertisement costs.

The statistical population of this study consists of listed companies on the Tehran Stock Exchange manually obtained from different industries in 2017. Multivariate regression based on data compilation methodology is used to test research hypotheses.

The results indicate that financial leverage is negatively and significantly associated with customer satisfaction and this negative relationship is more pronounced in companies with lower sale growth. Furthermore, the authors' results suggest that customer satisfaction negatively (positively) and significantly affects firm value in companies with lower (higher)-financial leverage. The authors also demonstrate that there is no significant relationship between financial leverage caused by financial flexibility and firm value caused by customer's satisfaction (CS). The authors' findings also suggest that financial distress significantly affects the relationship between financial leverage and customer satisfaction. Finally, the authors' find that financial leverage significantly affects firms' R&D and advertisement costs.

Since the fundamental institutional assumptions underpinning the Western and even East Asia financial models are not valid in the institutional environment of Iran, the authors' findings could provide substantial implications for the authors' understanding of the relationship between finance and R&D costs and contribute substantially to customer satisfaction and firm value literature as well. The sample country of the present paper has recently experienced a spate of financial collapses that somewhat contributes, indirectly, to financial distress incurred by the Iranian firms. Moreover, R&D costs are growing among the Iranian quoted firms.

Since the fundamental institutional assumptions underpinning the Western and even East Asia financial models are not valid in the institutional environment of Iran, the authors' findings could provide substantial implications for our understanding of the relationship between finance and R&D costs and contribute substantially to customer satisfaction and firm value literature as well. The sample country of the present paper has recently experienced a spate of financial collapses that somewhat contributes, indirectly, to financial distress incurred by the Iranian firms. Moreover, R&D costs are growing among the Iranian quoted firms.

This study aims to revise the weights in the interrelationship matrix of the house of quality.

After determining customer requirements (CRs) and product design characteristics (PDCs), a house of quality (HoQ) has been developed and the interrelationships between CRs and PDCs have been determined and classified using the Kano model. The PDCs have been prioritized based on the classic HoQ and the revised HoQ. Finally the results have been compared and discussed. The television design of Entekhab Industrial Group, the largest producer of home appliance products in Iran has been selected as a case study.

Results indicated different sets of priorities derived from the two approaches. Particularly, the difference between the revised HoQ and the classic approach was due to the nonlinear relationship between CRs and PDCs.

This study was performed merely on a single product of a company, and the case study results cannot be generalized to all of the home appliance industries.

Developing the application of the Kano model in computing and revising the weights of the cells in the interrelationship matrix of HoQ is the main contribution of this paper.

Customer satisfaction refers to the extent to which customers are happy and satisfied with the products and services provided by a business. The purpose of this paper is twofold: first, to integrate lean tools in the analysis of customer satisfaction and, second, to examine its implications for research and practice.

The author proposes the combination of three lean tools in order to design a service quality system that has customer expectations (CEs) as the first input. These tools are quality function deployment (QFD), Hoshin Kanri planning process (HKPP) and benchmarking. The author uses a case study to show the functionality of these tools and the final design of a service quality system for a medical center.

Interaction between the service provider and the customer is the primary core activity for service-oriented businesses of different natures. A key relationship between trust in service quality and customer satisfaction cannot be ignored in interpersonal-based service encounters. However, there is a gap in the literature in terms of standardized lean-based procedures or methodologies that lead to improved customer satisfaction that are based directly on CEs.

Given the variety of the population, the authors developed several methodologies to standardize the customer responses. Using several total quality management tools, the standardization allows the authors to separate the different CEs. The gathering of customers’ expectations (voice of the customers) allows the companies to focus on the real problems expressed by the users of the service, increasing their loyalty and, most importantly in the field under study, the customer’s satisfaction with the service received.

For practitioners, this study helps with the use of lean tools such as QFD, benchmarking and HKPP and attempts to bridge such a gap with an evidence-based real case.

With the incorporation of all the customer needs, additional elements must be considered in the design of new services. Availability for all and sustainability play an important part of the CEs.

This paper presents a real application of QFD and Hoshin Kanri and how they may help the service organizations with future development.

The purpose of this paper is to present a literature review demonstrating that quality and its management are increasingly definable as a balancing act between value, risk and cost throughout the value stream, from product/service design to production and delivery, and purchaser decision-making. An original framework is presented showing this interplay across the value stream, referred to as the QVRC framework.

Content analysis is combined with bibliometric analytics, displayed via temporal graphs and citation networks. Reviewed literature is transdisciplinary, encompassing marketing, operations/quality and psychology sources. Core quality management methodologies are positioned on the framework illustrating their relative contribution to value, risk and cost management.

The QVRC framework is developed, and used as a basis for classifying models and methodologies associated with quality management. A set of propositions are developed, which, together with the framework, set an agenda for further research.

No literature review can capture the richness of discourses on terms as pervasive as value, risk and cost. This paper aims to present a systematic and reliable sampling of such literature.

The resulting model can be applied to management tools, and to products and services.

Researchers, particularly in marketing, have developed models of value, risk and cost in terms of products and services. However, delivering products that provide the appropriate value, risk and cost trade-off is an operations management problem. This is the first paper to combine value, risk and cost across the value stream showing how this interplay extends beyond product.