A linear goal programming approach to determining the relative importance weights of customer requirements in quality function deployment

Quality function deployment (QFD) is a planning tool used in new product development and quality management. It aims at achieving maximum customer satisfaction by listening to the voice of customers. To implement QFD, customer requirements (CRs) should be identified and assessed first. The current paper proposes a linear goal programming (LGP) approach to assess the relative importance weights of CRs. The LGP approach enables customers to express their preferences on the relative importance weights of CRs in their preferred or familiar formats, which may differ from one customer to another but have no need to be transformed into the same format, thus avoiding information loss or distortion. A numerical example is tested with the LGP approach to demonstrate its validity, effectiveness and potential applications in QFD practice.     

Application of the QFD as a design approach to ensure comfort in using hand tools: Can the design team complete the House of Quality appropriately?

Quality Function Deployment is proposed as an effective design method to integrate ergonomics needs and comfort into hand tool design because it explicitly addresses the translation of customer needs into engineering characteristics. A crucial step during QFD concerns the linking of engineering characteristics to customer needs in the House of Quality by the design team. It is generally assumed (looking at all the QFD success stories) that design teams can accurately predict the correlations between customer needs and engineering characteristics (also referred to as “Whats”/“Hows” correlations). This paper explicitly tests this assumption by comparing the “Whats”/“Hows” correlations estimated by a design team with those observed in a systematic user evaluation study, which has not been done before. Testing the assumption is important, because inaccurate estimates may lead to ergonomically ineffective (re)design of hand tools and a waste of company resources. Results revealed that the design team's correlation estimates were not as accurate as is generally assumed. Twenty-five percent of the estimates differed significantly with those observed in the user evaluation study. Thus, QFD is a useful method to assist design teams in designing ergonomically more comfortable hand tools, but only on the condition that the correlations between customer needs and engineering characteristics are validated, preferably by means of a systematic user evaluation study.     

Designing capacity-building in e-learning expertise: Challenges and strategies

This research study looks at how organizations in developing countries perceive the challenge of building capacity in e-learning expertise. Data was collected on six such organizations, and a range of perceived rationales and constraints were identified. The paper hypothesizes a four-part framework to define the e-learning capacity gaps that these circumstances appear to represent: the “instructional design capacity gap”, the “production capacity gap”, the “tutorial capacity gap” and the “community building gap”. The framework is used to re-examine the data to explore the ways in which the organizations’ e-learning activities might constitute strategic responses to the hypothesized capacity gaps.     

The relationships among service quality,perceived value,customer satisfaction,and post-purchase intention in mobile value-added services

The purposes of this study are to construct an instrument to evaluate service quality of mobile value-added services and have a further discussion of the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention. Structural equation modeling and multiple regression analysis were used to analyze the data collected from college and graduate students of 15 major universities in Taiwan. The main findings are as follows: (1) service quality positively influences both perceived value and customer satisfaction; (2) perceived value positively influences on both customer satisfaction and post-purchase intention; (3) customer satisfaction positively influences post-purchase intention; (4) service quality has an indirect positive influence on post-purchase intention through customer satisfaction or perceived value; (5) among the dimensions of service quality, “customer service and system reliability” is most influential on perceived value and customer satisfaction, and the influence of “content quality” ranks second; (6) the proposed model is proven with the effectiveness in explaining the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile added-value services.     

Assessing e-learning 2.0 system success

Traditional e-learning systems support “one-way” communication. Teachers provide knowledge for learners, but they are unable to use a student’s learning experiences to benefit the class as a whole. To address these problems, this study explores e-learning success factors via the design and evaluation of an e-learning 2.0 system. This study develops a theoretical model to assess user satisfaction and loyalty intentions to an e-learning system using communication quality, information quality, system quality, and service quality. The empirical results show that communication quality, information quality, and service quality significantly and positively affect user satisfaction and loyalty intentions to use the e-learning system for sharing experience, communicating with others, and getting feedback.     

Integrating conjoint analysis with quality function deployment to carry out customer-driven concept development for ultrabooks

A hybrid framework integrating conjoint analysis (CA) with quality function deployment (QFD) is presented to incorporate customer preferences into the process of product development. In particular, the proposed framework constitutes two sequential phases, namely, concept generation based on CA and prototype evaluation based on QFD. In addition, product features are characterized by customer requirements (CRs) and functional attributes (FAs). By means of DEMATEL (Decision Making and Trial Laboratory), the impacts of FAs on CRs are systematically identified to visualize their causalities. Instead of utilizing FAs, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is employed to assess potential prototypes in terms of CRs.     

A new integrated approach for engineering characteristic prioritization in quality function deployment

As a customer-driven quality improvement tool, quality function deployment (QFD) can convert customer requirements (CRs) into appropriate engineering characteristics (ECs) in product design and development. However, the conventional QFD method has been criticized for a variety of drawbacks, which limit its efficiency and potential applications. In this study, a new QFD approach integrating picture fuzzy linguistic sets (PFLSs) and the evaluation based on distance from average solution (EDAS) method is proposed for the determination of ranking order of ECs. The PFLSs are utilized to express the judgements of experts on the relationships among CRs and ECs. Then, the EDAS method is extended under picture fuzzy linguistic environment for the prioritization of the ECs identified in QFD. Moreover, a combined weighing method based on technique for order of preference by similarity to ideal solution (TOPSIS) and maximum entropy theory is established to calculate the weights of experts objectively. Finally, a product-service system design is provided to illustrate the effectiveness of the proposed QFD approach. The result shows that the manufacturer should pay more attention to “Meantime before failure”, “Warning feature” and “Quality of product manual”. Feedback from domain experts indicates that the integrated approach being proposed in this paper is more suitable for assessing and prioritizing ECs in QFD.     

Designing a sustainable supply chain using an integrated analytic network process and goal programming approach in quality function deployment

Sustainable supply chain management (SSCM) provides economic, social end environmental requirements in material and service flows occurring between suppliers, manufacturers and customers. SSCM structure is considered as a prerequisite for a sustainable success. Thus designing an effective SCM structure provides competitive advantages for the companies. In order to achieve an effective design of this structure, it is possible to apply quality function deployment (QFD) approach which is successfully applied as an effective product and system development tool. This study presents a decision framework where analytic network process (ANP) integrated QFD and zero-one goal programming (ZOGP) models are used in order to determine the design requirements which are more effective in achieving a sustainable supply chain (SSC). The first phase of the QFD is the house of quality (HOQ) which transforms customer requirements into product design requirements. In this study, after determining the sustainability requirements named customer requirements (CRs) and design requirements (DRs) of a SSC, ANP is employed to determine the importance levels in the HOQ considering the interrelationships among the DRs and CRs. Furthermore ZOGP approach is used to take into account different objectives of the problem. The proposed method is applied through a case study and obtained results are discussed.     

Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals

This paper provided a content analysis of studies in the field of cognition in e-learning that were published in five Social Sciences Citation Index (SSCI) journals (i.e. Computers and Education, British Journal of Educational Technology, Innovations in Education and Teaching International, Educational Technology Research & Development, and Journal of Computer Assisted Learning) from 2001 to 2005. Among the 1027 articles published in these journals from 2001 to 2005, 444 articles were identified as being related to the topic of cognition in e-learning. These articles were cross analyzed by published years, journal, research topic, and citation count. Furthermore, 16 highly-cited articles across different topics were chosen for further analysis according to their research settings, participants, research design types, and research methods. It was found from the analysis of the 444 articles that “Instructional Approaches,” “Learning Environment,” and “Metacognition” were the three most popular research topics, but the analysis of the citation counts suggested that the studies related to “Instructional Approaches,” “Information Processing” and “Motivation” might have a greater impact on subsequent research. Although the use of questionnaires might still be the main method of gathering research data in e-learning cognitive studies, a clear trend was observed that more and more studies were utilizing learners’ log files or online messages as data sources for analysis. The results of the analysis provided insights for educators and researchers into research trends and patterns of cognition in e-learning.     

An integrated approach for rating engineering characteristics’ final importance in product-service system development

Product-service system (PSS) approach has emerged as a competitive strategy to impel manufacturers to offer a set of product and services as a whole. A three-domain PSS conceptual design framework based on quality function deployment (QFD) is proposed in this research. QFD is a widely used design tool considering customer requirements (CRs). Since both product and services influence satisfaction of customer, they should be designed simultaneously. Identification of the critical parameters in these domains plays an important role. Engineering characteristics (ECs) in the functional domain include product-related ECs (P-ECs) and service-related ECs (S-ECs). ECs are identified by translating customer requirements (CRs) in the customer domain. Rating ECs’ importance has a great impact on achieving an optimal PSS planning. The rating problem should consider not only the requirements of customer, but also the requirements of manufacturer. From the requirements of customer, the analytic network process (ANP) approach is integrated in QFD to determine the initial importance weights of ECs considering the complex dependency relationships between and within CRs, P-ECs and S-ECs. In order to deal with the vagueness, uncertainty and diversity in decision-making, the fuzzy set theory and group decision-making technique are used in the super-matrix approach of ANP. From the requirements of manufacturer, the data envelopment analysis (DEA) approach is applied to adjust the initial weights of ECs taking into account business competition and implementation difficulty. A case study is carried out to demonstrate the effectiveness of the developed integrated approach for prioritizing ECs in PSS conceptual design.     

A new hesitant fuzzy QFD approach: An application to computer workstation selection

Computer workstation selection is a multiple criteria decision making problem that is generally based on vague linguistic assessments, which represent human judgments and their hesitancy. In this paper, a new fuzzy quality function deployment (QFD) approach is used to effectively determine the design requirements (DRs) of a computer workstation. Hesitant fuzzy linguistic term sets (HFLTS) are innovatively employed to capture the hesitancy of the experts in this approach. More precisely, the proposed new QFD approach is the first study that determines the importance of customer requirements (CRs), the relations between CRs and DRs and the correlations among DRs via HFLTS. Additionally, HFLTS based Analytic Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods are utilized in the computational steps to select the best computer workstation. A real industrial application is carried out to validate the implementation of the proposed approach.     

An integrated linguistic-based group decision-making approach for quality function deployment

Quality function deployment (QFD) is a well-known customer-driven approach for new or improved product/service design and development to maximize customer satisfaction. A typical QFD analysis process involves a series of group decision-making (GDM) processes, such as determination of the importance of customer requirements (CRs), the relationship between CRs and engineering characteristics (ECs), and the correlation among ECs. Properly handling these GDM processes is essential because it will significantly affect the prioritization of ECs, the target value setting of ECs, and the following deployment phases of QFD. Due to different personal experiences and/or lack of sufficient knowledge and information, decision-makers who participate in the QFD analysis process tend to provide their opinions by using different types and multi-granularity linguistic information, which are inherently vague and imprecise. Unlike most of the previous studies, which excessively rely on fuzzy approaches, this study proposes an integrated linguistic-based GDM approach, which can compute with words directly and avoid the risk of loss of information, to cope with multiple types and multi-granularity linguistic assessments given by a group of decision-makers in QFD activity process. Finally, a numerical example is taken to illustrate the applicability of the proposed approach. The linguistic-based approach can effectively manage the imprecise and vague input information in QFD and facilitate decision-making in product design and development.     

A new approach to quality function deployment planning with financial consideration

Quality function deployment (QFD) is becoming a widely used customer-oriented approach and tool in product design. Taking into account the financial factors and uncertainties in the product design process, this paper deals with a fuzzy formulation combined with a genetic-based interactive approach to QFD planning. By introducing new concepts of planned degree, actual achieved degree, actual primary costs required and actual planned costs, two types of fuzzy optimisation models are discussed in this paper. These models consider not only the overall customer satisfaction, but also the enterprise satisfaction with the costs committed to the product. With the interactive approach, the best balance between enterprise satisfaction and overall customer satisfaction can be obtained, and the preferred solutions under different business criteria can be achieved through human–computer interaction.Scope and PurposeQuality function deployment (QFD) that originated in Japan in the late 1960s is a concept and mechanism for translating the ‘voice of customer’ into product through various stages of product planning, engineering and manufacturing. It has become a widely used customer-oriented approach to facilitating product design by analysing customer requirements (CRs). Determination of the target levels for the technical attributes (TAs) of a product with a view to achieving a high level of overall customer satisfaction is an important activity in product design and development.Traditional methods for QFD planning are mainly subjective, ad hoc and heuristic. They can hardly achieve global optimisation, and most of these models barely take into consideration the correlation between TAs. Moreover, most of these methods are technically one-sided without considering the design budget. However, the financial factor is also an important factor and should not be neglected in QFD planning. In addition, owing to uncertainties involved in the decision process, these deterministic methods could not formulate and solve it effectively.Taking into consideration the financial factors and uncertainties in the product design process, this paper deals with fuzzy formulation combined with a genetic-based interactive approach to QFD planning. By introducing new concepts of planned degree, actual achieved degree, actual primary costs required and actual planned costs, two types of fuzzy optimisation models are discussed in this paper. These models consider not only the overall customer satisfaction, but also the enterprise satisfaction with the costs committed to the product. With the interactive approach, the best balance between enterprise satisfaction and overall customer satisfaction can be obtained, and the preferred solutions under different business criteria can be achieved through human–computer interaction.     

Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment

As a customer-driven tool, quality function deployment (QFD) is widely used in product planning or improvement to achieve higher product performance and customer satisfaction. QFD uses a matrix called the house of quality (HoQ) to translate customer requirements (CRs) into engineering characteristics (ECs). Constructing the HoQ, which includes determining the importance weights of CRs, the correlation matrix among ECs and the relationship matrix between CRs and ECs, is an important issue in the application of QFD. However, decision-makers (DMs) participating the construction of HoQ tend to give their individual judgments in multi-format or multi-granularity depending on their different knowledge, experience, culture and circumstance. Furthermore, these judgments are more difficult to assess with the precise quantitative forms due to the vagueness and uncertainty existed in the early stage of new product development. In this paper, a group decision-making approach incorporating with two optimization models (i.e. logarithmic least squares model and weighted least squares model) is proposed to aggregate these multi-format and multi-granularity linguistic judgments. Fuzzy set theory is utilized to address the uncertainty in the decision-making process. The proposed method is illustrated with a real-world case of horizontal directional drilling machine. The application indicates that the group decision-making method may be a promising tool for constructing the HoQ.     

Construction of house of quality for new product planning: A 2-tuple fuzzy linguistic approach

A house of quality (HOQ) diagram is used to analyze the critical factors involved in the quality function deployment (QFD) processes for the new product planning (NPP). The principal tasks of the QFD acting process comprise describing and scoring customer requirements (CRs); determining design requirements (DRs), the relationship between CRs and DRs, the correlations among CRs, and the correlations among DRs. Finally, the DRs can be scored by these assessments in NPP. This study proposes various methods of scoring the requirements of current and potential customers to reflect the knowledge and preference differences among different customers regarding CRs. The CR scores provided by different customers can be assessed by using linguistic, numerical, and interval values, or can be assessed using linguistic label sets with different granularity. A 2-tuple fuzzy linguistic computational approach is adopted to aggregate the CR importance scores obtained from customers by using various methods. In addition, to accurately rate the DRs, a modified relationship between CRs and DRs is proposed. The proposed HOQ construction model is practical because it prevents the loss of information during the QFD process for NPP. An example is used to demonstrate the applicability of the proposed model.     

Fuzzy cognitive map based quality function deployment approach for dishwasher machine selection

The traditional quality function deployment (QFD) approach deals with the weights of customer requirements (CRs), relationships among CRs and design requirements (DRs), correlation among DRs by using crisp values. This paper uses fuzzy numbers to improve the drawbacks of the traditional QFD method because fuzzy numbers enable to make consistent decisions in uncertain environment to decision makers. The existing papers handle a simple multiplication operation to calculate the correlation among CRs and the correlation among DRs. This study proposes fuzzy cognitive map (FCM) approach to calculate these correlations so that FCM is a successful method to handle the interactions among criteria. This paper contributes to the literature by integrating QFD approach and fuzzy cognitive map approach. The weights of DRs are defined in the result of the proposed QFD approach. These weights are used to evaluate the dishwasher machine alternatives in intuitionistic fuzzy VIKOR method. Intuitionistic fuzzy number (IFS) ensures to handle more information than type-1 fuzzy number to describe the fuzziness and the uncertainty of the real life world. Finally, the proposed approach has been implemented to a dishwasher machine selection in order to test its validity.     

Application of quality function deployment in the semiconductor industry: A case study

In quality function deployment (QFD), the voice of the customer (VOC) is the critical factor in developing and producing a product that will meet or exceed customer requirements. This study integrates quality function deployment (QFD), management techniques to optimise product-design investment, process improvement, and phase-into meet customer requirements and company goals. QFD uses systematic multi-level development and evaluation to translate customer requirements into the design of product characteristics and manufacturing processes that will satisfy the customer and minimise potential failure costs. ‘Process management’, which is one of the pivotal Six Sigma implementation criteria, is used to construct an ‘integrated product and process development’ (IPPD) model by product type to enhance the effectiveness of QFD. This model, combined with a company’s customer satisfaction strategy and QFD techniques, provides process management through built-in IPPD and appropriate changes in organisational culture. This paper presents a case study from the semiconductor industry to demonstrate the model’s applicability and suitability.     

Improving quality function deployment analysis with the cloud MULTIMOORA method

Quality function deployment (QFD) is a quality guarantee method extensively used in various industries, which can help enterprises shorten the product design period and enhance the manufacturing and managing work. The task of selecting important engineering characteristics (ECs) in QFD is crucial and often involves multiple customer requirements (CRs). In this paper, a modified multi‐objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method based on cloud model theory (called C‐MULTIMOORA) is developed to determine the ranking order of ECs in QFD. First, the linguistic assessments provided by decision makers are transformed into normal clouds and aggregated by the cloud weighted averaging operator. Then, the weights of CRs are determined based on a maximizing deviation method with incomplete weight information. Finally, the importance of ECs is obtained using the C‐MULTIMOORA method. An empirical case conducted in an electric vehicle manufacturing organization is provided together with a comparative analysis to validate the advantages of our proposed QFD model.     

An advanced queueing model to analyze appointment-driven service systems

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue (also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility and receives service. Important measures of interest include the size of the waiting list as well as the time spent in the waiting list. We develop a model to assess these performance measures. The model may be used to support strategic decisions concerning server capacity (e.g. how often should a server be online, how many customers should be served during each service session, etc.). The model is a vacation model that uses efficient algorithms and matrix analytical techniques to obtain waiting list performance measures.     

A study of the relationship between institutional policy,organisational culture and e-learning use in four South African universities

This article investigates the relationship between policy (conceptualised as goals, values and resources), organisational culture and e-learning use. Through both qualitative and quantitative research methods, we gathered data about staff and student perspectives from four diverse South African universities representing a selection of ICT in education policy types (Structured and Unstructured) and organisational cultural types of “collegium, bureaucracy, corporate and enterprise” (McNay, 1995). While our findings show a clear relationship between policy and use of ICTs for teaching and learning, organisational culture is found crucial to policy mediation and the way that e-learning use is embedded within the organisation. We conclude that although a Structured Corporate institutional type enables the attainment of a “critical mass” within e-learning, Unstructured Collegium institutions are better at fostering innovation. Unstructured Bureaucratic institutions are the least enabling of either top down or bottom up e-learning change.