Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction
Issue:
Volume 4, Issue 2, March 2019
Pages:
41-56
Received:
23 July 2019
Accepted:
24 August 2019
Published:
16 September 2019
Abstract: Demand management research has always attracted considerable attention from academia and industry, covering almost all fields, including multiple disciplines, including philosophy, economics, mathematics, management, psychology, etc. This paper provides a systematic review of 110 peer-reviewed journal articles published from 2013 to 2018. The primary purpose is to study how companies design and plan optimal product sales decisions under different demand patterns. We passed to organize and analyze these 110 articles, summarizing the specific role of demand on the consumer goods supply chain, and the relationship to corporate sales decisions. We found that customer demand has driving force and starting point for suppliers to make product sales decisions in the field of consumer goods supply chain. The customer demand for products dramatically affects the degree of market segmentation and also determines the benefits of manufacturers and retailers. However, the existing research is only done under the uncertainty of demand and does not consider the three different demand patterns, real, false, and semi-real. Therefore, there is a significant theoretical gap in existing research. Our goal is to establish a theoretical bridge through the combing and review of relevant literature systems and to construct a conceptual model of the demand-oriented supply chain. This conceptual model will provide an essential reference for the direction of future research.
Abstract: Demand management research has always attracted considerable attention from academia and industry, covering almost all fields, including multiple disciplines, including philosophy, economics, mathematics, management, psychology, etc. This paper provides a systematic review of 110 peer-reviewed journal articles published from 2013 to 2018. The prima...
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Several Inequalities on Moment of Uncertain Variables
Issue:
Volume 4, Issue 2, March 2019
Pages:
57-62
Received:
26 July 2019
Accepted:
28 August 2019
Published:
21 September 2019
Abstract: An uncertain variable is a Borel measurable function whose domain is uncertainty space and range is the set of real numbers. However, for many reasons, like the difficult of collecting data, the value of an uncertain variable is usually not easy to measure accurately. Hence many scholars study the estimation range of the value of an uncertain variable, and usually to estimate the upper or lower bounds of the moment of an uncertain variable is the primary idea. Many inequalities are established to estimate the above bounds, but there are still some problems on the estimation of the moment of uncertain variables. For instance, the even-order moment of an uncertain variable cannot be uniquely calculated at present. So the aim of this paper is to estimate the upper or power bounds of the moment of uncertain variables or the uncertain measure of an event by establishing several new inequalities. Firstly, we extend the Lyapunov inequality on uncertain variable and this inequality gives the upper bound of the even-order moment of an uncertain variable, and as a corollary, the lower bound of the above even-order moment is given. Then the inequality of arithmetic-geometry is proved, which estimates the lower bound of the expected value of an uncertain variable. After that, two equivalent inequalities are given, which can be used to judge the existence of the expected value of a function of an uncertain variable. Finally, as for two independent and identically distributed uncertain variables, the weakly symmetric inequalities are investigated to estimate the upper and lower bounds of the uncertainty distributions of the difference of these uncertain variables which implies the uncertain measures of several events. The above inequalities extend the application range of uncertain variable.
Abstract: An uncertain variable is a Borel measurable function whose domain is uncertainty space and range is the set of real numbers. However, for many reasons, like the difficult of collecting data, the value of an uncertain variable is usually not easy to measure accurately. Hence many scholars study the estimation range of the value of an uncertain varia...
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