Trends in retail inventory performance: 1982 – 2012

Johnston, Ahren

doi:10.1007/s12063-014-0090-0

Cited by 11 publications

(23 citation statements)

References 7 publications

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“…We note that H3 is supported in all papers that we have reviewed: Gaur et al (2005), Gaur and Kesavan (2008) and Johnston (2014) for the US and Kolias et al (2011) for the Greek retail industries; Rumyantsev and Netessine (2007) and Lee et al (2015) for the non-service US public firms across different industries:…”

Section: Hypothesis Developmentmentioning

confidence: 61%

“…The first three hypotheses relate inventory turnover to gross margin, capital intensity and sales surprise. As we briefly review in the second section, some of these hypotheses are presented and tested earlier in other empirical papers including Gaur et al (2005), Rumyantsev and Netessine (2007), Gaur and Kesavan (2008), Kolias et al (2011), Shan and Zhu (2013), Rajagopalan (2013), Johnston (2014) and Lee et al (2015). The fourth hypothesis relates inventory turnover to demand uncertainty as it is measured by the new metric we propose: MAPE of quarterly demand forecasts:…”

Section: Hypothesis Developmentmentioning

confidence: 99%

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Demand uncertainty and inventory turnover performance

Hançerlioğulları

Şen

Aktunc

2016

International Journal of Physical Distribution &Amp; Logistics Management

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Purpose-The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios. Design/methodology/approach-The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009. Findings-Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data. Practical implications-In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer's inventory performance against its competitors. Originality/value-The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.

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Section: Hypothesis Developmentmentioning

confidence: 61%

Section: Hypothesis Developmentmentioning

confidence: 99%

Demand uncertainty and inventory turnover performance

Hançerlioğulları

Şen

Aktunc

2016

International Journal of Physical Distribution &Amp; Logistics Management

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“…While risk pooling has been extensively analyzed for industrial and trading companies (e.g. Johnston 2014;Wiengarten et al 2017;Cachon and Terwiesch 2019), healthcare research on it still seems fragmented (see Table 2). Zepeda et al (2014Zepeda et al ( , 2016 and Stanger et al (2013) explicitly focus on risk pooling or pooling in short.…”

Section: Theoretical Background On Risk Pooling Methods In Healthcarementioning

confidence: 99%

Exploring risk pooling in hospitals to reduce demand and lead time uncertainty

Oeser

Romano

2020

Oper Manag Res

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Nearly every eighth German hospital faces an elevated risk of bankruptcy. An inappropriate use of inventory management practices is among the causes. Hospitals suffer from demand and lead time uncertainty, and the current COVID-19 pandemic worsened the plight. The popular business logistics concept of risk pooling has been shown to reduce these uncertainties in industry and trade, but has been neglected as a variability reduction method in healthcare operations research and practice. Based on a survey with 223 German hospitals, this study explores how ten risk pooling methods can be adapted and applied in the healthcare context to reduce economic losses while maintaining a given service level. The results suggest that in general risk pooling may improve the economic situation of hospitals and, in particular, inventory pooling, transshipments, and product substitution for medications and consumer goods are the most effective methods in the healthcare context, while form postponement may be unsuitable for hospitals due to the required efforts, delay in treatments, and liability issues. The application of risk pooling in healthcare requires willingness to exchange information and to cooperate, adequate IT infrastructure, compatibility, adherence to healthcare laws and regulations, and securing the immediate treatment of emergencies. Compared to manufacturing and trading companies, hospitals seem to currently neglect the variability reducing effect of risk pooling.

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“…The research on the management of perishable inventory almost started in the seventies of the past century [5,6,7,8,9]. Recent surveys on retail invetory can be found in [10]. Similar surveys on perishable inventory can be found in [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Period Age-Discriminated Perishable Inventory

Alrawabdeh

2021

Management Systems in Production Engineering

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In this paper, an extremely short shelf-life inventory of age-discriminated stochastic demand is considered. Age discriminated demand can be found in products of high circulation and short shelf-lives such as dairy products, packaged food, pharmaceutical products and medical products of short shelf lives. Simulation based optimization is considered to find the optimal order quantity. The model employs Discrete Event Simulation along with a modified simulated annealing algorithm. To validate the model and the optimization algorithm, the classical newsvendor problem is tested first, later, different experiments are carried out for different product lifetimes. In contrast to the classical newsvendor, this problem tackles a multi-period inventory of different ages and different demand distributions. The objective is to determine the optimal order quantity to satisfy the stochastic demand of all ages such that shortages and expirations are minimized. The results showed remarkable performance and outstanding minimum levels of shortage and expiration.

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Trends in retail inventory performance: 1982 – 2012

Cited by 11 publications

References 7 publications

Demand uncertainty and inventory turnover performance

Demand uncertainty and inventory turnover performance

Exploring risk pooling in hospitals to reduce demand and lead time uncertainty

Multi-Period Age-Discriminated Perishable Inventory

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