Research on investment decision-making model from the perspective of “Internet of Things + Big data”

2020 ◽  
Vol 107 ◽  
pp. 286-292 ◽  
Author(s):  
Chenghao Sun
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Investment Decision ◽  
Investment Decision Making ◽  
Decision Making Model

The influence of big data analytics management capabilities on supply chain preparedness, alertness and agility

2019 ◽  
Vol 32 (2) ◽  
pp. 297-318 ◽  
Author(s):  
Santanu Mandal
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Investment Decision ◽  
Big Data Analytics ◽  
Content Type ◽  
Investment Decision Making ◽  
Management Capabilities ◽  
The Impact

Purpose The importance of big data analytics (BDA) on the development of supply chain (SC) resilience is not clearly understood. To address this, the purpose of this paper is to explore the impact of BDA management capabilities, namely, BDA planning, BDA investment decision making, BDA coordination and BDA control on SC resilience dimensions, namely, SC preparedness, SC alertness and SC agility. Design/methodology/approach The study relied on perceptual measures to test the proposed associations. Using extant measures, the scales for all the constructs were contextualized based on expert feedback. Using online survey, 249 complete responses were collected and were analyzed using partial least squares in SmartPLS 2.0.M3. The study targeted professionals with sufficient experience in analytics in different industry sectors for survey participation. Findings Results indicate BDA planning, BDA coordination and BDA control are critical enablers of SC preparedness, SC alertness and SC agility. BDA investment decision making did not have any prominent influence on any of the SC resilience dimensions. Originality/value The study is important as it addresses the contribution of BDA capabilities on the development of SC resilience, an important gap in the extant literature.

Project investment decision based on VIKOR interval intuitionistic fuzzy set

2021 ◽  
pp. 1-9 ◽  
Author(s):  
Caichuan Wang ◽  
Jiajun Li
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Investment Decision ◽  
Intuitionistic Fuzzy Set ◽  
Reference Value ◽  
Intuitionistic Fuzzy Sets ◽  
Project Investment ◽  
Intuitionistic Fuzzy ◽  
Investment Decision Making ◽  
Decision Making Model

The decision on the investment project is to analyze the feasibility and rationality of the project plan from multiple angles. However, due to the limitations of the actual project investment decision-making, this paper proposes a group decision making method based multifunctional intuitively fuzzy VIKOR interval sets. Firstly, according to the established investment decision-making model, the first round of preliminary candidate project schemes is selected. According to the definition of interval intuitionistic fuzzy sets and the traditional VIKOR method, established the research method of this article, and the project investment decision-making model based on VIKOR interval intuitionistic fuzzy sets is established. Finally, the project schemes are sorted according to the closeness degree of schemes. The results show that when sorting each candidate by Qi value, A4 >  A3 >  A2 >  A1 can be obtained. Because Q4 = 0, Q3 = 0.31, the condition q3-q4 >  0.25 is satisfied. It is concluded that the method can not only meet the needs of actual decision-making, but also has strong operability and practicability. The research results have reference value and guiding significance for project investment decision-making, and can promote the sustainable development of the project.

scholarly journals Decision-Making and Coordination of a Three-Stage Book Supply Chain considering Big Data Information Cost

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Pan Liu
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Supply Chain ◽  
Investment Decision ◽  
Supply Chain Coordination ◽  
Book Publisher ◽  
Investment Decision Making ◽  
Pricing Rules ◽  
The Cost ◽  
Investment Models

In the Big Data era, Big Data Information (BDI) has been used in the book supply industry. Data Company as an important BDI supplier should be included in a book supply chain. Thus, to explore the investment decision-making problems of BDI and its effects on the coordination and pricing rules of book supply chain, a three-stage book supply chain with one book publisher, one retailer, and one Data Company was chosen. Meanwhile, four benefit models about BDI investment were proposed and analyzed in the environments of symmetry information and asymmetric information. A revenue sharing contract was used to achieve book supply chain coordination. Findings: whether the book publisher and the retailer were suitable to invest in BDI, it was influenced by the cost improvement coefficient. With the ascent of the cost improvement coefficient, benefits of supply chain members will reduce, and, in different investment models, their prices show different change trends with the cost improvement coefficient.

scholarly journals Investment Decision-Making and Coordination of Supply Chain: A New Research in the Big Data Era

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Pan Liu ◽  
Shu-ping Yi
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Supply Chain ◽  
Investment Decision ◽  
Supply Chain Coordination ◽  
Chain Model ◽  
Market Demand ◽  
Investment Decision Making ◽  
Decentralized Decision Making ◽  
Data Environment

In a Big Data environment, in order to study the decision-making problem of Big Data information investment and the effects of using Big Data information to improve industry cost on supply chain coordination, firstly the importance of Data Company in supply chain was analyzed, and the original supply chain model was built. Meanwhile, some changes of consumer behavior were analyzed in a Big Data environment. Based on these, the market demand function and the benefit model of stakeholder were built and analyzed. Findings:(1)The first finding is whether an enterprise was suitable for gaining Big Data to improve its costs, which was determined by the cost improvement coefficient; namely, it was related to the ability of excavating and using the value of Big Data.(2)Whether the supply chain was the decentralized decision-making and the centralized decision-making, the thresholds of acquisition costs on Big Data information were equal. Moreover, the maximum value that they could undertake was same.(3)Meanwhile the fact that the quantity discount contract could achieve a win-win outcome for supply chain members was proved. The discount coefficient was related to consumers’ behavior preference in a Big Data environment.

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