A weighted interval rough number based method to determine relative importance ratings of customer requirements in QFD product planning

Customer requirements (CRs) play a significant role in the product development process, especially in the early design stage. Quality function deployment (QFD), as a useful tool in customer-oriented product development, provides a systematic approach towards satisfying CRs. Customers are heterogeneous and their requirements are often vague, therefore, how to determine the relative importance ratings (RIRs) of CRs and eventually evaluate the final importance ratings is a critical step in the QFD product planning process. Aiming to improve the existing approaches by interpreting various CR preferences more objectively and accurately, this paper proposes a weighted interval rough number method. CRs are rated with interval numbers, rather than a crisp number, which is more flexible to adapt in real life; also, the fusion of customer heterogeneity is addressed by assigning different weights to customers based on several factors. The consistency of RIRs is maintained by the proposed procedures with design rules. A comparative study among fuzzy weighted average method, rough number method and the proposed method is conducted at last. The result shows that the proposed method is more suitable in determining the RIRs of CRs with vague information

Appliance to Predict the Quality of Hypothetically Modified Products

Customizing the quality of the product to change customer expectations is a necessary action in good, prospering organizations. In enterprises, the most beneficial solutions consider the future satisfaction of customer with the product. This issue is not easy and is not resolved; therefore, integration of different techniques was proposed as part of a single, coherent appliance. Therefore, the aim is to propose the appliance to predict the quality of hypothetically modified products. The appliance was developed by adequately selected and combined techniques, i.e., survey research with the Likert scale, AHP method (Analytic Hierarchy Process), Pareto rule (20/80), WSM method (Weighted Sum Model) and Naive Classifier Bayes. The concept of the proposed appliance concerns the possibility of determining important product attributes and possible combinations of feature states. Based on this, the quality levels were estimated, and then satisfaction with the hypothetical modifications of the product was predicted. The test was carried out on the vacuum cleaner. As a result, four combinations of product modifications were determined, which have been created based on hypothetical and actual attributes. Each modification was satisfying for the customer. Therefore, the proposed apparatus turned out to be effective in predicting customer satisfaction for the modified quality levels. Originality is to propose a new integration of different techniques to predict levels of quality product modification based on current product quality

Does maturity level influence the use of agile UX methods by digital startups? Evaluating design thinking, lean startup, and lean user experience

Context: Agile UX methods such as Design Thinking, Lean Startup, and Lean User Experience have been employed to deliver customer value and improve organizational performance. However, there is a lack of studies that assess how these tools are used at different stages of maturity of digital startups. Objective: The present study aims to compare the knowledge of graduated, incubated, and pre-incubated digital startups at university incubators concerning the use of Agile UX methods so that weaknesses and opportunities can be identified to provide co founders and scholars with new strategic insights. Method: Six reduced focus groups were conducted with 14 members of the six selected startups via multiple case studies. Answers were registered by researchers and then analyzed using an inductive process and codification. Results: The results indicated that digital startups had contact with consumers through market research, viability analysis, and product discontinuity. However, except for one startup, deficiencies in co-founders’ participation throughout developing products and services projects were identified. As far as the multiple case studies are concerned, Design Thinking and Lean Startup were employed by four of the startups, while two of them used the Lean User Experience method due to its higher maturity level. Conclusion: Although all Agile UX methods were employed, all six digital startups reported having made adaptations to the methods or to have used them only partially. Finally, it was concluded that the maturity level influences the Agile UX methods of each digital startup according to its nature and its stage of development in the market.Campus Lima Centr

Fusing incomplete preference rankings in design for manufacturing applications through the ZM II-technique

The authors recently presented a technique (denominated “ZM”) to fuse multiple (subjective) preference rankings of some objects of interest - in manufacturing applications - into a common unidimensional ratio scale (Franceschini, Maisano 2019). Although this technique can be applied to a variety of decision-making problems in the Manufacturing field, it is limited by a response mode requiring the formulation of complete preference rankings, i.e. rankings that include all objects. Unfortunately, this model is unsuitable for some practical contexts – such as decision-making problems characterized by a relatively large number of objects, field surveys, etc. – where respondents can barely identify the more/less preferred objects, without realistically being able to construct complete preference rankings. The purpose of this paper is to develop a new technique (denominated “ZMII”) which also “tolerates” incomplete preference rankings, e.g., rankings with the more/less preferred objects only. This technique borrows the underlying postulates from the Thurstone’s Law of Comparative Judgment and uses the Generalized Least Squares method to obtain a ratio scaling of the objects of interest, with a relevant uncertainty estimation. Preliminary results show the effectiveness of the new technique even for relatively incomplete preference rankings. Description is supported by an application example concerning the design of a coach-bus seat

Importance Calculation of Customer Requirements for Incremental Product Innovation

Incremental product innovation is achieved by finding and solving problems of existing products. The importance of customer requirements reflects the severity of existing product problems, which points out the direction for incremental product innovation. In this research, the calculation process of customer requirement importance mainly includes three steps. Firstly, from the perspective of customers, the improvement gap analytical method is used to obtain the improvement and original importance of customer requirements by measuring customer perceived satisfaction and dissatisfaction. Secondly, from the perspective of industry experts, an improved interval grey number ranking method is proposed to calculate the basic importance of customer requirements, which can deal with the inadequate problem of the data provided by experts due to the limited number of experts. Finally, a multi-dimensional vector cosine method, which avoids the interference of subjectivity of importance weight calculation to the final importance, is proposed to integrate the importance data provided by customers and experts. A case of a water purifier is considered to illustrate the validity of the proposed process. This research improves existing calculation methods and proposes an integrated calculation process from three dimensions to calculate the final importance of customer requirements effectively

An extended COPRAS model for multi-criteria decision-making problems and its application in web-based hotel evaluation and selection

Facilitation of suitable accommodation for different travellers is the prime concern of travel agencies. Travel agencies must keep themselves competitive and sustain a good pace of growth to continue raising profits by attracting and retaining as many tourists as possible through meeting their various prospective needs. To achieve this, the agencies must prepare well-organised data for hotels and destinations from a quality control perspective. Initially, the hotels are ranked and evaluated according to performance across several criteria from the tourists’viewpoint. The relative importance of each criterion is mainly subjective and depends on the assessor’s judgement. Additionally, hotels’ rankings vary across different websites, resulting in inconsistencies. To handle such inconsistencies and subjectivity, this paper presents a collective decision-making evaluation framework by integrating a weighted interval rough number (WIRN) method and a WIRN- based complex proportional assessment (COPRAS) model to evaluate and rank hotels. An empirical example and a real-world case study from the Indian tourism industry are presented to validate the applicability of the proposed framework. Finally, a comparison and sensitivity analysis are performed to examine the validity and robustness of the proposed model