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Article
Publication date: 23 October 2023

Haoze Cang, Xiangyan Zeng and Shuli Yan

The effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high…

Abstract

Purpose

The effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high volatility and uncertainty of the crude oil futures price, a matrixed nonlinear exponential grey Bernoulli model combined with an exponential accumulation generating operator (MNEGBM(1,1)) is proposed in this paper.

Design/methodology/approach

First, the original sequence is processed by the exponential accumulation generating operator to weaken its volatility. The nonlinear grey Bernoulli and exponential function models are combined to fit the preprocessed sequence. Then, the parameters in MNEGBM(1,1) are matrixed, so the ternary interval number sequence can be modeled directly. Marine Predators Algorithm (MPA) is chosen to optimize the nonlinear parameters. Finally, the Cramer rule is used to derive the time recursive formula.

Findings

The predictive effectiveness of the proposed model is verified by comparing it with five comparison models. Crude oil futures prices in Cushing, OK are predicted and analyzed from 2023/07 to 2023/12. The prediction results show it will gradually decrease over the next six months.

Originality/value

Crude oil futures prices are highly volatile in the short term. The use of grey model for short-term prediction is valuable for research. For the data characteristics of crude oil futures price, this study first proposes an improved model for interval number prediction of crude oil futures prices.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 12 March 2024

Yanping Liu, Bo Yan and Xiaoxu Chen

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of…

Abstract

Purpose

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

Design/methodology/approach

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

Findings

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

Practical implications

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

Originality/value

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 9 June 2023

Umar Farooq Sahibzada, Nadia Aslam Janjua, Muhammad Muavia and Suhaib Aamir

The purpose of this study is to examine the link between knowledge-oriented leadership (KOL) and organizational performance (OP) at Higher Education Institutions (HEIs) both…

Abstract

Purpose

The purpose of this study is to examine the link between knowledge-oriented leadership (KOL) and organizational performance (OP) at Higher Education Institutions (HEIs) both directly and indirectly through service innovation and knowledge-sharing quality.

Design/methodology/approach

This research used Smart PLS 4.0 to model structural equations using a sample comprising 237 academic staff from HEIs in China.

Findings

According to the study data, KOL has a negligible direct influence on organizational performance. The link between KOL and OP, on the other hand, is entirely mediated by the quality of knowledge sharing quality and service innovation.

Practical implications

The study results validate universities' experience with KOL and propose ways for academics at higher education institutions to prioritize the quality of knowledge sharing and service innovation, which in turn helps organizations function better in a volatile environment.

Originality/value

Despite the growing relevance of knowledge-oriented leadership in higher education, little research has been conducted to examine the mediating impact of numerous factors in the link between KOL and OP. The present research examines the link between knowledge-oriented leadership, the quality of knowledge sharing, service innovation and the performance of higher education institutions. The current study scientifically investigates the link between KOL and OP and offers insight into the existing literature by examining the mediating role of KSQ and SI.

Details

Journal of Organizational Effectiveness: People and Performance, vol. 11 no. 1
Type: Research Article
ISSN: 2051-6614

Keywords

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