A multiple objective stochastic programming model for working capital management

Masri, Hatem; Abdulla, Yomna

doi:10.1016/j.techfore.2017.05.006

Cited by 23 publications

(20 citation statements)

References 28 publications

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“…Working capital management significantly contributes to firm value by maintaining a balance between risk and profitability [5,7,[9][10][11][12][13]. Depending upon managers' preferences, this balance may have a range of strategies including high risk-high profit (aggressive strategy) or low risk-low profit (conservative strategy) [14].…”

Section: Introductionmentioning

confidence: 99%

Moderating Effects of Firm Size and Leverage on the Working Capital Finance–Profitability Relationship: Evidence from China

et al. 2019

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We evaluated the moderating effects of firm size and leverage on the working capital finance (WCF)-profitability relationship among Chinese companies during 2000-2017. Applying the generalized method of moments (GMM) technique on panel data, we observed that firm size and leverage have strong moderating roles in the WCF-profitability relationship. We observed that small or low-leverage firms have an inverted U-shaped WCF-profitability relationship. However, this relationship is U-shaped for large or high-leverage firms. We report break-even points in these relationships that show the portion of short-term debt in working capital financing. The results reveal that the break-even point for all subgroups (small, large, low-leverage, and high-leverage firms) decreases compared to the break-even point of the full sample. This study shows how the break-even point of the WCF-profitability relationship shifts when a company expands or its leverage level changes. Managers can use this information for profit maximization.

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Section: Introductionmentioning

confidence: 99%

Moderating Effects of Firm Size and Leverage on the Working Capital Finance–Profitability Relationship: Evidence from China

et al. 2019

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“…Long-term debt has a positive impact on the company's liquidity as it is a source of funds that could enhance liquidity (Masri & Abdulla, 2018). In common-law systems, companies tend to have lower levels of working capital, less internal sourcing of working capital from retained profits, and more external sourcing from banks (Troilo, Walkup, Abe, & Lee, 2019).…”

Section: Hypotheses Developmentmentioning

confidence: 99%

The Implications of Debt Financing on Working Capital Management Efficiency: Evidence From Mena Emerging Markets

Alrahamneh

Chu

Hong

2020

IJIM

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This proposed study aims to examine how debt financing affects the working capital management (WCM) efficiency of firms in eight selected MENA countries over the period 2016-2020. This study discusses different theories of debt financing which include the trade-off theory, the pecking order theory, the market timing theory, and the agency theory (i.e., the agency theory of debt, equity, and free cash flow). Particularly, the study addresses how short-term debt, long-term debt, and total debt influence WCM efficiency. We hypothesize that there are positive relationships between the short-term debt (measured by the current ratio), the long-term debt (measured by the long-term debt to total assets ratio), and the total debt (measured by the total debt to total assets ratio) toward WCM (measured by cash conversion cycle). Firm’s specific characteristics such as the firm type, the firm size, firm’s sales growth, and tangibility were used as control variables for WCM. To achieve the study objectives, a sample of 718 non-financial listed companies on stock exchanges in countries of Bahrain, Egypt, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, and UAE will be used over the period 2016-2020. Secondary quantitative data will be collected from the annual financial statements of firms. The multiple regression model will be used to test the study hypotheses. This proposed paper originally contributes to the extant literature in several ways. First, there were limited studies of WCM in the MENA context and the current study provided a new insight that has not been investigated before in the MENA region. Thus, it bridges the gap in the literature. However, the majority of extant WCM literature emphasized the relationship between efficient WCM and firms profitability. Moreover, this paper contributes to developing efficient WCM practices and strategies that improve the financial performance of listed companies in the MENA region

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“…Thereafter, a large number of models were proposed by extending these work. Abdelaziz et al [26] assumed that the parameters related to the target obeyed the normal distribution and proposed a stochastic multi-objective programming portfolio model, then transformed it into an chance-constrained compromise programming model for solution; Li et al [27] used expectation value and variance as the composite quantitative indicators of random variables, and established the generalized expectation model of stochastic programming; for the uncertainties existed in inventory, transportation cost and demand in the recycling logistics network, Sazvar et al [28] proposed a stochastic programming model based on expected value; Masri et al [29] established a multi-objective stochastic programming model based on the retailer's optimal working capital level, and proposed multiple solution strategies based on chance constrained approach, a recourse approach and stochastic goal programming approach; Tong et al [30] used random variables to describe the target under uncertain demand, established a bi-level programming model of stochastic multi-objective logistics network design and further designed genetic algorithm (GA) based on stochastic simulation for solution; Fard et al [31] established a twostage stochastic multi-objective programming model for closedloop supply chain (CLSC) considering environmental factors and downside risk. Moreover, a number of memetic metaheuristics had been considered.…”

Section: Introductionmentioning

confidence: 99%

A Two-Stage Multi-objective Programming Model to Improve the Reliability of Solution

Jin¹,

Li²,

Feng³

et al. 2020

IJCIS

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Randomness is a common uncertainty encountered in practical multi-objectives decision-making. But it is always a challenge for decision-makers to process randomness in multi-objective programming problems. This paper takes the decision-making objectives as fuzzy events and aims to solve numerical multi-objective programming problems under random environment. We first analyze the effects of randomness on multi-objective decision-making results. With the expectation value and the probability of fuzzy events as quantitative index of randomness, we then establish a two-stage random multi-objective programming model based on reliability (i.e., TS-MOPM). Specifically, we give several probability calculation methods of fuzzy events with common distributions, and further present the corresponding calculation procedures for solving TS-MOPM. Finally, a case study is implemented to test the proposed model TS-MOPM. Theoretical analysis and case study indicate that our model has better interpretability and operability. The research results enrich the existing random multi-objective programming methods to some extent.

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A multiple objective stochastic programming model for working capital management

Cited by 23 publications

References 28 publications

Moderating Effects of Firm Size and Leverage on the Working Capital Finance–Profitability Relationship: Evidence from China

Moderating Effects of Firm Size and Leverage on the Working Capital Finance–Profitability Relationship: Evidence from China

The Implications of Debt Financing on Working Capital Management Efficiency: Evidence From Mena Emerging Markets

A Two-Stage Multi-objective Programming Model to Improve the Reliability of Solution

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