QFD Application In Cross-border E-commerce Third Party Logistics Provider Selection

The rapid growth of Indonesia’s food and beverage industry has increased the need for innovative and environmentally friendly packaging, especially for takeaway drinks. This study aims to develop a cup holder design to replace plastic bags by integrating customer needs using the Quality Function Deployment (QFD) method. QFD was chosen because it can translate the Voice of Customer (VoC) into measurable technical specifications through the House of Quality (HoQ) matrix. The research used a descriptive quantitative approach with 30 café customers selected through purposive sampling. Validity testing using the Pearson Product Moment showed that 11 out of 20 statements were valid (r > 0.36), and the reliability test achieved a Cronbach’s Alpha value of 0.870, indicating high consistency. The results of the VoC and HoQ analysis identified eleven important customer needs such as capacity, ease of use, material strength, design, and price efficiency. Three alternative cup holder designs were evaluated using the Pugh Matrix, and the best concept scored +4, featuring a kraft paper material with 300 gsm thickness, moisture resistance, ergonomic shape, and the ability to hold four cups while displaying café branding. This design improves customer comfort, strengthens brand image, and reduces plastic waste. The study demonstrates how QFD can effectively link customer preferences to engineering design, offering a practical example for small and medium cafés to develop sustainable packaging that supports both product functionality and environmental responsibility.

Aircraft conceptual design is the very beginning of aircraft design process in which one or several aircraft configurations are created to meet the top-level requirements of aircraft. The aim of this paper is to build a more traceable, structured and systematic process of aircraft conceptual design by use of Quality Function Deployment (QFD) method. The conceptual design of a narrow body commercial aircraft is used as an example to illustrate application of the QFD. The top-level requirements of the commercial aircraft are defined. The conceptual design activities such as initial sizing of aircraft, wing configuration design, fuselage configuration design, and empennage configuration design are accomplished using House of Quality (HOQ). During initial sizing of aircraft, the top-level requirements of aircraft are converted into the requirements for aerodynamics, propulsion and weight with the aid of HOQ and constraint analysis. During configuration designs of the wing, fuselage and empennage, their requirements are identified based on the top-level requirements and output of the initial sizing, and consist of requirements of aerodynamics, structure, control, safety, operation, cost and etc. Several HOQs representing the relationships between the requirements and the configuration design parameters are created. After that, the configuration design parameters are selected with the aid of the HOQ and relevant design knowledges. By use of the QFD, aircraft conceptual design activities are represented by a number of the HOQ and the design process of configuration parameters is traceable through the HOQ. It is concluded that the QFD-based aircraft conceptual design is more traceable, structured and systematic than the traditional method.

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.

PurposeThe purpose of this paper is to report case studies conducted in a company in Italy that produces packaging systems, in comparison with a Brazilian company within a similar industrial sector. The paper compares those two cases in terms of quality function deployment (QFD) usage and discusses the lessons learned from the cases.Design/methodology/approachCase‐based research was employed. Data were mostly gathered through semi‐structured interviews with engineers and managers involved with product development. Direct observation and archival data were also used to extract more evidence towards triangulation. Then, the aggregation of results was done a posteriori.FindingsQFD implementation process was found to be similar in both companies but with some differences in terms of managerial aspects of product development, e.g. gathering the voice of customer and a more extensive use of other matrices besides the “house of quality”.Research limitations/implicationsThe study was limited in two companies. Although one of the purposes was to analyse if there are contextual differences between those two cases, this study was unable of verifying the context of QFD application. In addition, the study findings are not generalisable to other similar plants.Practical implicationsThe research shows the importance of QFD implementation and similarities between the cases, in addition to contributing to application by identifying relevant aspects of its introduction. It enables practitioners to use the findings on factors that should be taken into consideration when applying QFD.Originality/valueBesides the comparison between two companies, the paper discusses the innovation on QFD projects in one of the companies. In addition, the empirical results found grounding in existing theory to some extent.

The objective of this paper is to develop the tool of halal food control by applying Quality Function Deployment (QFD). The modification of House of Quality (HOQ) matrix in QFD model are necessary to be conducted in order to fit the proposed QFD model with halal food control in the company. The proposed QFD model is composed of three HOQ matrices. The matrix 1 describes the relationship between attributes of halal assurance system and product process. The matrix 2 represent the relationship between attributes of halal assurance system and the halal critical. Finally, matrix 3 explains the relationship between product process and halal critical. The case study in chicken meat processing company is used to test the applicability and how to work the proposed QFD model for halal food control.

The fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is an attractive tool for measuring complex phenomena based on uncertain data. The original version of the method assumes that the object assessments in terms of the adopted criteria are expressed as triangular fuzzy numbers. One of the crucial stages of the fuzzy TOPSIS is selecting the fuzzy conversion scale, which is used to evaluate objects in terms of the adopted criteria. The choice of a fuzzy conversion scale may influence the results of the fuzzy TOPSIS. There is no uniform approach in constructing and selecting the fuzzy conversion scale for the fuzzy TOPSIS. The choice is subjective and made by researchers. Therefore, the aim of the article is to present a new, objective approach to the construction of fuzzy conversion scales based on Item Response Theory (IRT) models. The following models were used in the construction of fuzzy conversion scales: Polychoric Correlation Model (PM), Polytomous Rasch Model (PRM), Rating Scale Model (RSM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), Graded Response Model (GRM), Nominal Response Model (NRM). The usefulness of the proposed approach is presented on the example of the analysis of a survey’s results on measuring the quality of professional life of inhabitants of selected communes in Poland. The obtained results indicate that the choice of the fuzzy conversion scale has a large impact on the closeness coefficient values. A large difference was also observed in the spreads of triangular fuzzy numbers between scales based on IRT models and those used in the literature on the subject. The use of the fuzzy TOPSIS with fuzzy conversion scales built based on PRM, RSM, PCM, GPCM, and GRM models gives results with a greater range of variability than in the case of fuzzy conversion scales used in empirical research.

PurposeThe purpose of this study is to provide a decision support tool to deal with the problem of seting priorites among patients competing for limited health care resources. Limited resources and unlimited demands prevent health-care services to be provided to all those in need. This became publicity evident with the current Covid-19 pandemic. Although controversial, health care rationing has always existed and is now inevitable. Setting priorities becomes then inevitable. How to define those priorities is a complex and yet irresolvable issue mainly because it involves several and conflicting criteria, translated into efficiency and equity considerations. This is why multi-criteria decision analysis (MCDA) was introduced to health care as an appropriate decision-support framework for solving complex problems.Design/methodology/approachThis paper proposes the application of two combined approaches – analytic hierarchy process (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and AHP-VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), as decision support tools to rank patients with competing needs in a more effective and equitable way. A rationing scenario involving four patients, differentiated by personal characteristics and health conditions, is used to illustrate, test and compare the applicability of both approaches. After extraction of the relative weights of the prioritization criteria involved in the hypothetical scenario from paired wise comparison methods, TOPSIS and VIKOR priority setting methods were designed.FindingsResults suggest that patients ranking from both combination approaches are similar and in accordance with the order made directly by health-care professionals. Therefore, the relative weights computed by AHP in combination with TOPSIS and/or VIKOR methods could be used with suitable applicability by health-care decision-makers.Originality/valueThis study is the first attempt to apply a combination of MCDA methods to patients’ prioritization context and the first to cross previous studies to deepen and consolidate the research.

Application of AHP, TOPSIS, and TFNs to plant selection for phytoremediation of petroleum-contaminated soils in shale gas and oil fields

In software defect prediction systems, choosing the best data mining classification algorithm is essential for efficient decision-making. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for ranking classification algorithms according to several criteria is assessed in this study. Classifiers were evaluated and ranked using the AR1 and JM1 datasets using a structured multi-criteria decision-making (MCDM) methodology. According to the results, Lazy-IBK continuously performs better than other classifiers, demonstrating how well TOPSIS finds the top-performing models. Furthermore, the comparative study of classification algorithms shows how reliable the approach is when taking into account variables like scalability, accuracy, and computational efficiency. According to the results, TOPSIS considerably enhances classifier selection when it comes to software defect prediction, resulting in data mining applications that make better-informed and impartial decisions. Key Words: MCDM, Software Defect Prediction, TOPSIS

A research on the cutting database system based on machining features and TOPSIS

<p>One common multi-criteria decision making (MCDM) technique is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is frequently applied in several application fields. Finding an ideal and an anti-ideal solution, which are then utilized to determine the distances between the alternatives and the ideal solution, is the foundation of the TOPSIS approach. The method then ranks the alternatives according to their closeness to the ideal solution. TOPSIS is able to handle both quantitative and qualitative criteria, however, the method can be sensitive to the weight of the criteria, and the ranking results can be influenced by the choice of the reference alternatives. This paper provides an overview of the TOPSIS method, its applications, main characteristics and limitations. The paper also provides step-by-step instructions on how to apply the TOPSIS method, including the determination of the criteria weights, the construction of the decision matrix, and the calculation of the TOPSIS scores.</p>

The importance of disaster logistics and its share in the logistics sector are increasing significantly. Most disasters are difficult to predict; therefore, a set of measures seems to be necessary to reduce the risks. Thus, disaster logistics needs to be designed with the pre-disaster and post-disaster measures. These disasters are experienced intensely in Turkey and the importance of these measures becomes more evidential. Therefore, accurate models are required to develop an effective disaster preparedness system. One of the most important decisions to increase the preparedness is to locate the centres for handling material inventory. In this context, this paper analyses the response phase designing the disaster distribution centres in Turkey at the provincial level. AHP (Analytical Hierarchy Process) based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and goal programming model integration is used to decide alternative locations of distribution centres. TOPSIS method is employed for ranking the locations, which is based on hazard scores, total area, population, and distance to centre. Two conflicting objectives are first proposed in the goal programming formulation, in which maximization of the TOPSIS scores and minimization of the number of distribution centres covering all demands named set covering model are included. Although Gecimli has the highest priority with 0.8 p score in the TOPSIS ranking, Altincevre (0.77) and Buzlupınar (0.75) ensure both the TOPSIS score and coverage of the demand nodes. The results from this paper confirm that the computational results ensure disaster prevention insights especially in regions with limited data.

To resolve environmental and social problems and traffic congestion, a sustainability evaluation of transportation infrastructure should be done for current and proposed situations. The aim of the present investigation is to evaluate the sustainability of infrastructure project on system interchange and assess their results with respect to sustainable development indicators. Based on interviews with experts, intensive observation, and development infrastructure related to the case study, six proposed scenarios are proposed to improve traffic condition of the Sheikhfazolah-Yadegar interchange in Tehran. The proposed scenarios are modeled and calibrated in AIMSUN 8.0, then the value of all indicators are determined through an indirect and direct procedure by AIMSUN results. A technique for order of preference by similarity to ideal solution (TOPSIS) method is used to integrate the results of proposed indicators. Although the weight of each indicator specifies its effect in sustainability evaluation, changes intensity of indicator value was not applied in sustainability evaluation by the previous methods of multi-criteria decision analysis (MCDA). In this study, for the first time, a simplified approach is defined and used to evaluate sustainable development of all scenarios that can apply the effect of changes intensity in sustainability evaluation. This method is named the applied effect of changes intensity in each indicator (AECIEI). According to the purposes of Tehran vision in 2025, all proposed scenarios are ranked based on TOPSIS results and the simplified approach, and then results of these methods are compared.

The concept of socio-economic development refers to the qualitative and quantitative measure of progress. The main objective of the study was to assess the level of socio-economic development of thirty-one counties of Wielkopolska province in 2014. A synthetic indicator based on TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), a multi-criteria decision analysis method, was used in the analysis. The statistical data were taken from the Local Data Bank of the Central Statistical Office. The counties were classified into four groups depending on their level of development. The study revealed that the most developed county of Wielkopolska province was Poznań county, while Koło county was the least developed. The socio-economic development in most counties of Wielkopolska province was at a medium level in 2014.

PurposeThis study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems.Design/methodology/approachIn this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based partial and general coverage of suppliers makes the number of orders of products more realistic. In this model, the weights of suppliers are determined by fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, as a multi-criteria decision analysis method, in the objective function. Also, the authors consider the parameters related to delays as triangular fuzzy numbers.FindingsA small-sized numerical example is provided to clearly show the proposed model. The exact epsilon constraint method is used to solve this given multi-objective combinatorial optimization problem. Subsequently, the sensitivity analysis is conducted to testify the proposed model. The obtained results demonstrate the validity of the proposed multiple objectives mixed integer mathematical programming model and the efficiency of the solution approach.Originality/valueIn real-life situations, supplier selection parameters are uncertain and incomplete. Hence, the fuzzy set theory is used to tackle uncertainty. In this paper, a multi-objective supplier selection problem is formulated taking into consideration the coverage of suppliers and suppliers’ weights. Integrating coverage of suppliers to select and allocate the order to them can be mentioned as the main contribution of this study. The proposed model considers the delay from suppliers as fuzzy parameters.