Bayesian Network Approach to Customer Requirements to Customized Product Model

Yang, Qin; Li, Zhirui; Jiao, Haisen; Zu-fang, Zhang; Weijie, Chang; Wei, Daozhu

doi:10.1155/2019/9687236

Cited by 7 publications

(6 citation statements)

References 19 publications

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“…Models that use BNs can make bidirectional inferences, capture the dependency between variables and manage uncertainties [38]. The BN´s theoretical basis is that if the probability of the initial node (variable) and the conditional probability among all nodes are determined, it is possible to quantify the distribution status of all nodes in the network [39]. A BN can be regarded as a compact representation of conjunction or joint probability distributions of a set of random variables (X1, X2, ..., Xn), as illustrated in Equation 1:…”

Section: The Proposed Approachmentioning

confidence: 99%

Adding Technology Sustainability Evaluation to Product Development: A Proposed Methodology and an Assessment Model

et al. 2021

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In the current world scenario, which is experiencing the arrival of new technologies, Industry 4.0, increased mobility and a pandemic environment, the achievement of sustainability demands proactive solutions. One of these actions includes the design of sustainable products. Several authors have studied the scientific discipline of Life Cycle Engineering (LCE), which encompasses environmental, social and economic dimensions. However, current LCE models have gaps, such as the need to incorporate a more holistic view, uncertainty and integrated analysis. In this context, the aim of this paper is to present a model to evaluate the technology sustainability (TS) dimension. The methodology of the present work involves a literature review, the development of a model with qualitative and quantitative data, and application in a case study. A structure was developed to include market, technical, and technology-scaling perspectives. The computational model uses hybrid Bayesian networks, based on probabilistic theory, and incorporates uncertainty using sustainability indicators. The model includes quantitative and qualitative variables derived from experts’ opinions. The results of applying the model to a real research project on manhole covers indicate that this analytical tool can support decision-making, allowing a new dimension to be incorporated into LCE analysis. Finally, the model allows LCE analysis to be applied in a variety of circumstances, such as strategy development or the selection of more sustainable products, as well as the evaluation of competing products.

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Section: The Proposed Approachmentioning

confidence: 99%

Adding Technology Sustainability Evaluation to Product Development: A Proposed Methodology and an Assessment Model

et al. 2021

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“…In previous research [29], the DBC method has been used, which allows for customers to participate in the process of product design, resulting in modification and adjustment of the product to the customers' requirements. Therefore, in the context of processing and determination of products' quality level, the main methods used have been Kansei (KE) [24,[30][31][32], Quality Function Deployment (QFD) [33][34][35][36], Kano [16,34,37,38], and the Bayesian Network (Naive Bayesian Classifier) [39][40][41][42][43]. These methods were also integrated [31,32,34,38,44].…”

Section: Introductionmentioning

confidence: 99%

“…In turn, the above-mentioned Bayesian network (i.e., the so-called Naive Bayesian Classifier), is a probabilistic classifier based on independent, conditional assumptions. Examples in the literature, e.g., [39][40][41][42][43], apply the Bayesian network to adjust the level of product quality to meet customers' requirements. Forecasting or prediction of products' quality level has been analyzed in which authors applied a hidden Markov chain model [16,33,36].…”

Section: Introductionmentioning

confidence: 99%

A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

Siwiec

Pacana

2021

Sustainability

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The main factor that conditions the success of organizations is the development of products oriented toward customer satisfaction. An additional attribute of organizations is the use of sustainable development rules. The use of these rules and the simultaneous desire to create high-quality products encourage organizations to apply different methods to, for example, eliminate waste. This study aimed to develop a method to determine the research sample size required to predict a product’s quality level, taking into account current customers’ expectations. This method was developed by modifying a procedure to determine the research sample size as part of the calculated estimator of the mean value in the general population. Based on the concept of product sustainability development, the goal of the developed method was to determine the number of potential customers (respondents) needed to provide product requirements, which were then processed and used to predict the quality level of the product. This method was applied to simultaneously test a number of hypotheses, determine the test power, and detect statistically significant differences for several relationships of the sample sizes and the test power. This was achieved using universal hypotheses and the popular alternative-punctual (MAP) method. Testing of the proposed method showed that it was able to predict the quality level of products based on current expectations of customers.

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“…Concurrently, a growing number of emerging studies have addressed issues involved in offering a customized product [10][11][12]. Scholars have shown that offering a customizable product is an independent strategy in a monopoly market [13] and a competitive market, rather than in the context of vertical line extensions.…”

Section: Introductionmentioning

confidence: 99%

“…Equilibrium outcomes when the low-quality firm expands the product line. + (6τ − 9)μ 3 − 15τμ 2 − 8τ 2 μ)/(12…”

mentioning

confidence: 99%

Vertical Line Extension Decisions in a Competitive Market with Consumers’ Need for Product Uniqueness

Wang

2020

Discrete Dynamics in Nature and Society

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One important reason for offering customized products is to satisfy consumers’ need for product uniqueness. In this paper, we take consumers’ unique preferences into account to examine how firms make decisions on vertical line extensions with introducing a customized product. This study develops the consumer’s utility function, which captures consumers’ behavioural and emotional factors, and the results show that the high-quality firm always introduces an upward extension without uniqueness sensitivity. However, introducing a downward extension may be more profitable especially when consumers have the high unique ness sensitivity. We also find that the upward extension of the high-quality firm does not intensify competition with the low-quality firm, but its downward extension will intensify the competition between two firms, whether with or without unique preferences. We also analyse the low-quality firm’s extension decisions when it faces a high-end competitor and find that the low-quality firm may change from introducing a downward extension to introducing an upward extension when intrafirm quality differentiation is small.

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Bayesian Network Approach to Customer Requirements to Customized Product Model

Cited by 7 publications

References 19 publications

Adding Technology Sustainability Evaluation to Product Development: A Proposed Methodology and an Assessment Model

Adding Technology Sustainability Evaluation to Product Development: A Proposed Methodology and an Assessment Model

A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

Vertical Line Extension Decisions in a Competitive Market with Consumers’ Need for Product Uniqueness

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