Online leasing problem with price fluctuations under the consumer price index

Feng, Xin; Xu, Yinfeng; Ni, Guanqun; Dai, Yunchuan

doi:10.1007/s10878-018-0305-7

Cited by 11 publications

(6 citation statements)

References 14 publications

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“…The consumer price index (CPI) is the fluctuation trend of the price level of goods and services purchased by residents [1]. The purpose of compiling the CPI is to analyze and study the impact of price changes on socioeconomic development and residents' living standards [2]. In recent years, with the increasing economic pressure, how to analyze the influencing factors of CPI scientifically and intuitively has become a hot issue.…”

Section: Introductionmentioning

confidence: 99%

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Advancing the comprehension of consumer price index and influencing factors: insight into the mechanism based on prediction machine learning models

Cui,

Rong,

Zhang

2023

AEMR

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The consumer price index (CPI) is an important indicator to measuring inflation or deflation. Its changes are closely related to residents' lives, and also affect the direction of national macroeconomic policy formulation. In recent years, the combination of economics with mathematical models such as machine learning and macro-statistics has gradually become a hot topic. In this paper, the impact of different types of CPI on China's overall CPI was discussed. Machine learning prediction and correlation analysis of various types of influencing factors and CPI. The machine learning model of the regression decision tree process predicted CPI more accurately. Spearman correlation analysis showed that CPI was mainly positively related to goods and services, living, medical care, food, tobacco and alcohol, clothing and so on, while CPI was mainly negatively related to the transport and communication of residents.

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Section: Introductionmentioning

confidence: 99%

“…The main formulas of the above three models are shown in eqs. ( 1) and (2). In addition, the Spearman correlation analysis matrix was used to study the correlation between various influencing factors.…”

Section: Introductionmentioning

confidence: 99%

Advancing the comprehension of consumer price index and influencing factors: insight into the mechanism based on prediction machine learning models

Cui,

Rong,

Zhang

2023

AEMR

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“…Generally speaking, to decide if leasing is a profitable financing option, the decision maker should know both the price and the usage time of the resources [12,13]. However, in practice, the usage time is often impossible to be known in advance.…”

Section: Introductionmentioning

confidence: 99%

“…In all of the above literature, the resource price is assumed to be unchanged. The online leasing problem considering time-varying prices is investigated in [13,[37][38][39][40][41][42][43]. Irani and Ramanathan [37] considered a situation in which the resource price lies in a predetermined interval [1, M] while the rental fee remained unchanged.…”

Section: Introductionmentioning

confidence: 99%

“…Bienkowski [38] considered another online leasing problem where the prices on two consecutive days differed by at most 1. After that, the online leasing problem with price fluctuation bounded by CPI is studied in [13,39,40], in which the ratio between prices on two consecutive days was strictly less than a given upper bound. In addition, online leasing problems with depreciable resources are investigated in [41][42][43].…”

Section: Introductionmentioning

confidence: 99%

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Competitive Analysis of the Online Leasing Problem for Scarce Resources

Chen

Feng

2023

IJERPH

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The leasing activities of enterprises are of positive significance for promoting a green and low-carbon economy. For scarce resources that can easily go into tight supply states due to changes in the external market environment, the sudden change of their price is a common phenomenon in the leasing market. This paper provides an online leasing model based on the characteristics of scarce resources in which the resource might have a sudden price surge, and the length of its usage time cannot be known in advance. An online leasing strategy ON was then developed to achieve the minimum possible acquisition cost for the scarce resource. This strategy was proven to be the optimal online strategy through competitive analysis. Computational experiments were conducted to evaluate the performance of the proposed online strategy. Furthermore, sensitivity analysis of the problem parameters shows that increasing resource reserves and reducing the price-to-rent ratio are effective ways to improve the performance of enterprise leasing operation management for scarce resources.

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Online leasing problem with price fluctuations and the second-hand transaction

Feng

Chu

2020

J Comb Optim

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Online leasing problem with price fluctuations under the consumer price index

Cited by 11 publications

References 14 publications

Advancing the comprehension of consumer price index and influencing factors: insight into the mechanism based on prediction machine learning models

Advancing the comprehension of consumer price index and influencing factors: insight into the mechanism based on prediction machine learning models

Competitive Analysis of the Online Leasing Problem for Scarce Resources

Online leasing problem with price fluctuations and the second-hand transaction

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