Systematic Approach to A New Service Ideas Conceptualisation: Quantitative Decision Making

Drejeris, Rolandas; Drejerienė, Eglė

doi:10.5755/j01.ee.28.3.14752

Cited by 5 publications

(4 citation statements)

References 21 publications

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“…Decision making with uncertain quality is a living optimization problem both in the field of production like automotive industry (Ouisse & Cogan, 2010), food processing (Curt et al, 2007), petrochemical industry (Moradi-Aliabadi & Huang, 2016), TV panel manufacturing (Tang & Hsu, 2015) and creating of high-tech/high-value products (Batkovskiy et al, 2016) and services (Jiang & Seidmann, 2014;Drejeriene & Drejeris, 2017). The economics of decisions includes other special application fields, like evaluation of the factors determining risk of growing current account deficit (Garšviene & Cibulskiene, 2017) or the modelling of financial market volatility (Chin et al, 2016).…”

Section: Figure 3 Classification Of Articles Considering the Used Kementioning

confidence: 99%

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Economic aspects of decision making in production processes with uncertain component quality

Bányai

2019

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Production and service processes always introduce discrepancies between real and expected parameters. Accurate modelling of uncertainties in manufacturing processes has great impact on logistics related factors. In this representation, instead of a deterministic analysis of manufacturing processes with uncertain quality of components, decision making is described with stochastic decision trees. The objective of this work is to show how to include the uncertain quality of components into the optimization of manufacturing processes. This paper proposes a new decision tree model with stochastic parameters that can determine the optimal operations depending on the quality of components to be assembled. After a careful literature review, this paper introduces a model to formulate the problem of decision making in manufacturing and assembly processes depending on the quality of produced batches of components. The model seeks the optimal pre-assembly operation, like testing or repairing while taking into account specific costs, prior and posterior probabilities and likelihoods. Next, we demonstrate an enhanced stochastic decision tree with cumulative hypergeometric probability distributions to find the minimum of expected cost based objective function. Numerical results demonstrate how the proposed model supports the decision making process and increase the efficiency, flexibility and reliability of the manufacturing process.

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Section: Figure 3 Classification Of Articles Considering the Used Kementioning

confidence: 99%

“…After this reduction, we got 49 articles. We added 4 other articles selected through separate search (Aghdaie et al, 2013;Korponai et al, 2017;Banyaine Toth et al, 2017;Drejeriene & Drejeris, 2017), so the final list for classification and evaluation from the point of view of scientific results includes 53 articles.…”

Section: Introductionmentioning

confidence: 99%

Economic aspects of decision making in production processes with uncertain component quality

Bányai

2019

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“…The product is primarily created to satisfy the customers' needs and desires; therefore, knowledge about their requirements is crucial. New product development literature indicates that the voice of the customer should be taken into account at each stage of the NPD process to create competitive product innovation (Drejeriene & Drejeris, 2017;Kahn, Barczak, Nicholas, Ledwith, & Perks, 2012). Customers can serve as a source of new ideas and product improvement that can be implemented in the process of NPD, thereby enhancing product innovativeness (De Luca & Atuahene-Gima, 2007;Joshi, 2016).…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

Different sources of market information and product innovativeness

Dąbrowski

2018

EBR

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: The purpose of this study is to identify whether the gathering of market information from different sources -i.e. from customers, competitors and other entities -is related to product innovativeness. The relationships proposed so far have not been empirically investigated but they can have important theoretical and practical implications for product innovation. To achieve the purpose of the paper data concerning 287 new products were used by applying confirmatory factor analysis and structural equation modelling. The findings indicate that the obtaining of market information from customers and market entities, other than customers and competitors, has a positive impact on product innovativeness, but there was no such relationship in the case of gathering information from competitors.

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“…However, this kind of information is a crucial resource when developing new products. The voice of the customer, or even broadly the voice of the market, has to be taken into account at each stage of the new product development process, so the new product can meet customers' needs and desires better than competing products (Barczak, Griffin, & Kahn, 2009;Cooper, Edgett, & Kleinschmidt, 2004;Drejeriene & Drejeris, 2017;Kahn et al, 2012). Managers' decisions about product functions and attributes, and about marketing activities pursued during commercialization (e.g.…”

Section: Introductionmentioning

confidence: 99%

Sources of Market Information, Its Quality and New Product Financial Performance

Dąbrowski

2018

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While we observe a growing interest in the role of market information in new product development (NPD), existing research has still largely ignored the quality of market information that is a crucial issue in the era of the information society. What does affect the quality of market information in new product development projects, and how does this quality influence the financial performance of new products? In this paper, we address these questions and hypothesize that sources of information (e.g. customers, competitors) influence the quality of market information, and this quality affects new product financial performance through market predictability as a mediator. We test these hypotheses using data of about 287 new product projects of medium-high and high technology firms from Poland. Our findings indicate that the key sources that influence market information quality are customers and competitors. More intensive collection of market information from these two sources, and especially from customers, will result in this information being of a higher quality. Surprisingly, gathering market information from other market entities (e.g. suppliers, distributors) has no effect on the quality of market information. We also find that an important consequence of high quality market information available in NPD is high new product financial performance. Additionally, market information quality positively influences market predictability that, in turn, has a positive impact on new product performance. Our results support a partial mediation effect of market predictability between the quality of market information and NPD financial performance. Based on these findings, the author discusses the theoretical and managerial implications of this work and proposes paths for future research.

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Systematic Approach to A New Service Ideas Conceptualisation: Quantitative Decision Making

Cited by 5 publications

References 21 publications

Economic aspects of decision making in production processes with uncertain component quality

Economic aspects of decision making in production processes with uncertain component quality

Different sources of market information and product innovativeness

Sources of Market Information, Its Quality and New Product Financial Performance

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