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Journal articles on the topic 'Risk inventory'

Author: Grafiati

Published: 23 June 2021

Last updated: 29 July 2025

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1

Woodman, Tim, Matt Barlow, Comille Bandura, Miles Hill, Dominika Kupciw, and Alexandra MacGregor. "Not All Risks Are Equal: The Risk Taking Inventory for High-Risk Sports." Journal of Sport and Exercise Psychology 35, no. 5 (2013): 479–92. http://dx.doi.org/10.1123/jsep.35.5.479.

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Although high-risk sport participants are typically considered a homogenous risk-taking population, attitudes to risk within the high-risk domain can vary considerably. As no validated measure allows researchers to assess risk taking within this domain, we validated the Risk Taking Inventory (RTI) for high-risk sport across four studies. The RTI comprises seven items across two factors: deliberate risk taking and precautionary behaviors. In Study 1 (n = 341), the inventory was refined and tested via a confirmatory factor analysis used in an exploratory fashion. The subsequent three studies con

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2

Tapiero, Charles S., and Alberto Grando. "INVENTORY OUTSOURCING AND RISK MANAGEMENT." IFAC Proceedings Volumes 38, no. 1 (2005): 13–17. http://dx.doi.org/10.3182/20050703-6-cz-1902.01427.

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3

Tapiero, C. S., and A. Grando. "Supply risk and inventory outsourcing." Production Planning & Control 17, no. 5 (2006): 534–39. http://dx.doi.org/10.1080/09537280600777172.

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4

Chen, Xin, Melvyn Sim, David Simchi-Levi, and Peng Sun. "Risk Aversion in Inventory Management." Operations Research 55, no. 5 (2007): 828–42. http://dx.doi.org/10.1287/opre.1070.0429.

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5

Bianco, Marco, and Andrea Gamba. "Inventory and Corporate Risk Management." Review of Corporate Finance Studies 8, no. 1 (2018): 97–145. http://dx.doi.org/10.1093/rcfs/cfy007.

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6

Brooks, LeRoy D. "Inventory Policy Incorporating Systematic Risk." Engineering Economist 33, no. 3 (1988): 191–210. http://dx.doi.org/10.1080/00137918808966954.

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7

Oehlerts, Beth. "Inventory: Risk Identification and More." Library & Archival Security 22, no. 2 (2009): 73–83. http://dx.doi.org/10.1080/01960070902903995.

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8

Bartl, Ondrej. "Cost-Effective Inventory Control Under Risk." Communications - Scientific letters of the University of Zilina 2, no. 4 (2000): 16–28. http://dx.doi.org/10.26552/com.c.2000.4.16-28.

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9

Gaur, Vishal, and Sridhar Seshadri. "Hedging Inventory Risk Through Market Instruments." Manufacturing & Service Operations Management 7, no. 2 (2005): 103–20. http://dx.doi.org/10.1287/msom.1040.0061.

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10

Chod, Jiri. "Inventory, Risk Shifting, and Trade Credit." Management Science 63, no. 10 (2017): 3207–25. http://dx.doi.org/10.1287/mnsc.2016.2515.

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11

Tapiero, Charles S. "Value at risk and inventory control." European Journal of Operational Research 163, no. 3 (2005): 769–75. http://dx.doi.org/10.1016/j.ejor.2003.05.005.

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12

Stoikov, Sasha, and Mehmet Sağlam. "Option market making under inventory risk." Review of Derivatives Research 12, no. 1 (2009): 55–79. http://dx.doi.org/10.1007/s11147-009-9036-3.

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13

Ahmed, Shabbir, Ulaş Çakmak, and Alexander Shapiro. "Coherent risk measures in inventory problems." European Journal of Operational Research 182, no. 1 (2007): 226–38. http://dx.doi.org/10.1016/j.ejor.2006.07.016.

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14

Jammernegg, Werner, and Peter Kischka. "Risk preferences and robust inventory decisions." International Journal of Production Economics 118, no. 1 (2009): 269–74. http://dx.doi.org/10.1016/j.ijpe.2008.08.023.

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15

Wilt, Peter J., and Edmund P. Segner. "Risk vs. the Gas Inventory Charge." Natural Gas 4, no. 11 (2007): 22–25. http://dx.doi.org/10.1002/gas.3410041107.

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16

Zhang, Jiahua, Shu-Cherng Fang, and Yifan Xu. "Inventory centralization with risk-averse newsvendors." Annals of Operations Research 268, no. 1-2 (2017): 215–37. http://dx.doi.org/10.1007/s10479-017-2578-0.

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17

Yu, Wenfang, Guisheng Hou, and Baogui Xin. "Decision-Making Optimization of Risk-Seeking Retailer Managed Inventory Model in a Water Supply Chain." Discrete Dynamics in Nature and Society 2021 (April 26, 2021): 1–18. http://dx.doi.org/10.1155/2021/9943753.

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Water retailer managed inventory is a classical and inevitable inventory management mode in present economic society. Stochastic models can more clearly explain demand uncertainty and are closely related to water supply chains. Risk preferences are widely valued in behavioral operation management. Related to the risk preferences in inventory management, the research on risk aversion is dominant, while risk-seeking is insufficient. Based on the model assumptions, the risk-seeking retailer’s optimal decision-making inventory model with stochastic demand in a water supply chain is studied. The ri

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18

Zhu, Lijing, Ki-Sung Hong, and Chulung Lee. "Optimal Ordering Policy of a Risk-Averse Retailer Subject to Inventory Inaccuracy." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/951017.

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Inventory inaccuracy refers to the discrepancy between the actual inventory and the recorded inventory information. Inventory inaccuracy is prevalent in retail stores. It may result in a higher inventory level or poor customer service. Earlier studies of inventory inaccuracy have traditionally assumed risk-neutral retailers whose objective is to maximize expected profits. We investigate a risk-averse retailer within a newsvendor framework. The risk aversion attitude is measured by conditional-value-at-risk (CVaR). We consider inventory inaccuracy stemming both from permanent shrinkage and temp

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19

Deng, Fumin, Yanjie Li, Huirong Lin, Jinrui Miao, and Xuedong Liang. "A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation." International Journal of Environmental Research and Public Health 17, no. 16 (2020): 5765. http://dx.doi.org/10.3390/ijerph17165765.

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Hazardous waste can cause severe environmental pollution if not disposed of properly, which in turn can seriously affect the sustainable development of the entire ecology and will inevitably bring disaster to companies. However, because of limited available disposal capacity, it is often difficult to safely dispose of hazardous waste, meaning that it must be kept as passive inventory. For the passive inventory of hazardous waste, risk evaluation of safe operation of the inventory is crucial and urgently needs to be resolved. Based on this, this paper focuses on the risk management of hazardous

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20

Zhang, Huirong, Zhenyu Zhang, and Jiaping Zhang. "A Risk-Averse Newsvendor Model under Stochastic Market Price." Discrete Dynamics in Nature and Society 2021 (September 1, 2021): 1–9. http://dx.doi.org/10.1155/2021/9967359.

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The optimal inventory control is closely related to an enterprise’s operational efficiency, survival, and development. Market price uncertainty is introduced into the newsvendor model and the uncertainty’s impact on the firm's optimal stocking quantity is discussed. The results show that the impact of stochastic market price on the optimal stocking quantity under a given condition mainly depends on the magnitude of inventory cost. When the inventory cost is low, the market price’s uncertainty leads the firm to increase the stocking quantity. In contrast, when the inventory cost is high, market

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21

Beechem, Michael. "Beechem Risk Inventory for Late-Onset Alcoholism." Journal of Drug Education 27, no. 4 (1997): 397–410. http://dx.doi.org/10.2190/v49d-5le1-ch0w-kf5m.

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This group study features an at-risk inventory administered to ninety-six respondents. The principle purposes of this study were: 1) to design a “user-friendly” assessment tool to identify elderly persons who may be at risk for drinking problems and/or late-life alcoholism; and 2) to identify unresolved loss-grief issues that will need to be addressed in the treatment phase. For each of the loss items, the respondent indicates whether the loss occurred at “(A) Age Fifty-Four and Younger” or “(B) Age Fifty-Five and Older.” The respondent also subjectively indicates the extent to which he/she fe

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22

Wu, Qingyi, and Shuang Xie. "Supply chain coordination with inventory risk allocation." JUSTC 54, no. 8 (2024): 0806. http://dx.doi.org/10.52396/justc-2023-0134.

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Unlike the traditional decentralized channel, the drop-shipping channel entails a retailer relaying consumers' orders to the manufacturer, which proceeds to stock the orders and directly ship them to the consumers. This study explores supply chain coordination and product quality in drop-shipping and traditional channels. Specifically, we analyze the performance of both channels under wholesale price and revenue-sharing contracts. Our study yields several key findings. First, the revenue-sharing contract can coordinate both traditional and drop-shipping channels, effectively increasing supply

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23

Anvari, M., and M. Kusy. "Risk in inventory models: Review and implementation." Engineering Costs and Production Economics 19, no. 1-3 (1990): 267–72. http://dx.doi.org/10.1016/0167-188x(90)90051-i.

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24

Krishnan, Gopal V., Bin Srinidhi, and Lixin (Nancy) Su. "Inventory policy, accruals quality and information risk." Review of Accounting Studies 13, no. 2-3 (2008): 369–410. http://dx.doi.org/10.1007/s11142-008-9067-2.

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25

Zhu, Xuechang, Qigang Yuan, and Wei Zhang. "Inventory leanness, risk taking, environmental complexity, and productivity." Journal of Manufacturing Technology Management 29, no. 7 (2018): 1211–32. http://dx.doi.org/10.1108/jmtm-03-2018-0082.

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Purpose The purpose of this paper is to examine the effect of inventory leanness on productivity. In particular, the authors explore the moderating role of environmental complexity and the mediating role of risk taking. Design/methodology/approach In the mediated moderation analysis of the relationship among inventory leanness, risk taking, environmental complexity and productivity, the authors adopt the instrumental variable method to test the hypotheses based on data collected from 1,709 Chinese listed manufacturing firms. Findings The results show that there is an inverted U-shaped relation

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26

钟, 玉金. "Supply Chain Coordination with Inventory Level Dependent Demand and Inventory Risk Averse Retailer." Operations Research and Fuzziology 09, no. 01 (2019): 80–92. http://dx.doi.org/10.12677/orf.2019.91010.

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27

Markou, Panos, and Daniel Corsten. "Financial and Operational Risk Management: Inventory Effects in the Gold Mining Industry." Production and Operations Management 30, no. 12 (2021): 4635–55. https://doi.org/10.1111/poms.13448.

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Financial and operational risk management are central concepts at the intersection of finance, operations, and commodity risk management. Yet, empirical evidence on their effects on inventory is lacking. We use a fine-grained data set comprising the financial and operational risk management decisions of gold miners from 2003 to 2011 to empirically assess the effects of risk management on inventory. Faced with volatile gold prices, miners may manage (output) risk financially by committing to sell future gold production and lock in prices. They may also manage (input) co

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28

Alshami, Abdullah Mohammed, and Aniket Muley. "Economic Ordering Policy for VAR Deterioration Model with Non-stationary Two-warehouse Inventory and Demand." InPrime: Indonesian Journal of Pure and Applied Mathematics 2, no. 2 (2020): 79–86. http://dx.doi.org/10.15408/inprime.v2i2.15390.

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AbstractThis paper adopts the two-warehouse inventory, determination on the first run-time and VAR (Vector Auto Regression) deterioration model. The optimal EOQ in the interval of the finite horizon is determined under critical considerations. The non-stationary two-warehouse inventory, i.e. the inventory and initial inventory are non-stationary at level, but stationary after lag difference similar to demand (demand and initial demand). The output of the proposed model represented the optimal order quantity and optimal first run-time, the optimal total cost as integration of first order with t

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29

He, Juan, Xin Wang, and Zhong Hua Ma. "On Risk Factors of Inventory Finacing Based on Structural Equation Model." Applied Mechanics and Materials 58-60 (June 2011): 674–79. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.674.

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This paper analyses the risk factors of inventory finacing, establishes path diagram and the structural equation model on relations between inventory financing risk factors and makes the empirical analysis. The results indicate the operation status of the company and the characteristics of the inventory pledged have a significant effect on credit risk, and so of the level of company management on company operation.Based on this, banks should take relative measures while developing the inventory finacing.

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30

Borgonovo, E., and L. Peccati. "Financial management in inventory problems: Risk averse vs risk neutral policies." International Journal of Production Economics 118, no. 1 (2009): 233–42. http://dx.doi.org/10.1016/j.ijpe.2008.08.040.

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31

Boxma, Onno, Rim Essifi, and Augustus J. E. M. Janssen. "A queueing/inventory and an insurance risk model." Advances in Applied Probability 48, no. 4 (2016): 1139–60. http://dx.doi.org/10.1017/apr.2016.68.

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AbstractWe study an M/G/1-type queueing model with the following additional feature. The server works continuously, at fixed speed, even if there are no service requirements. In the latter case, it is building up inventory, which can be interpreted as negative workload. At random times, with an intensity ω(x) when the inventory is at level x>0, the present inventory is removed, instantaneously reducing the inventory to 0. We study the steady-state distribution of the (positive and negative) workload levels for the cases ω(x) is constant and ω(x) = ax. The key tool is the Wiener–Hopf factori

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32

Qin, Jiang, and Ping Qin. "Research on the Application of Risk-Oriented Audit in the Inventory Audit of Liquor Enterprises —— Take A Liquor Enterprise as an Example." International Journal of Global Economics and Management 4, no. 2 (2024): 421–28. http://dx.doi.org/10.62051/ijgem.v4n2.47.

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As a representative industry of China's national culture, the liquor industry has a huge industrial chain and a high degree of industrial relevance, and occupies an important position in China's economic market. Because the inventory of liquor enterprises is closely related to its operating results, coupled with the complexity of liquor inventory and the easy manipulation of value, it is easy to have problems in the evaluation and supervision session, leading to the increase of inventory audit risk. How to efficiently assess the risk and professional judgment of the inventory value of liquor e

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33

Deepika, O. "Inventory Backorder Prediction." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 763–66. http://dx.doi.org/10.22214/ijraset.2023.53461.

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Abstract: Product going to out of stock is a common problem in supply and chain scenario that comes under unpredictable risk in demand and supply. We aim to use Machine Learning predictive models in area of the business processes in decision making. By predicting products, backorder predictive models provides flexibility to decision authority, better clarity in the process, and helps in maintaining greater accuracy. The machine learning models that are tree based are chosen to predict material backordering. The backorders of products are predicted in this project by considering various models.

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34

Urohman, Taufiq, Alvian Jihad Suryana, and Maria Yovita R. Pandin. "Meta Analysis: Impact of Just in Time Implementation on Cost Efficiency and Profit." International Journal of Economic, Finance and Business Statistics 1, no. 2 (2023): 115–24. http://dx.doi.org/10.59890/ijefbs.v1i2.1107.

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Excessive inventory results in losses for the industry due to capital being held back, increased storage costs, incurring tax and inventory insurance costs, the risk of falling prices and quality, and giving rise to the potential for damage and theft. Inventory shortages can also cause losses because they can disrupt the production process. This research identified and analyzed 20 journals related to the implementation and impact of just in time implementation. Implementing just in time can reduce inventory costs, increase time efficiency and production costs so that producers can focus more o

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35

Urohman, Taufiq, Alvian Jihad Suryana, and Maria Yovita R. Pandin. "Meta Analysis: Impact of Just in Time Implementation on Cost Efficiency and Profit." Meta Analysis: Impact of Just in Time Implementation on Cost Efficiency and Profit 1, Vol. 1 No. 2 (2023): Desember 2023 (2024): 10. https://doi.org/10.59890/ijefbs.v1i2.1107.

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Excessive inventory results in losses for the industry due to capital being held back, increased storage costs, incurring tax and inventory insurance costs, the risk of falling prices and quality, and giving rise to the potential for damage and theft. Inventory shortages can also cause losses because they can disrupt the production process. This research identified and analyzed 20 journals related to the implementation and impact of just in time implementation. Implementing just in time can reduce inventory costs, increase time efficiency and production costs so that producers can focus more o

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36

Qin, Zheng, and Xiaochao Ding. "Risk Migration In Supply Chain Inventory Financing Service." Journal of Service Science and Management 04, no. 02 (2011): 222–26. http://dx.doi.org/10.4236/jssm.2011.42026.

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37

Djemame, Karim, Benno Barnitzke, Marcelo Corrales, et al. "Legal issues in clouds: towards a risk inventory." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1983 (2013): 20120075. http://dx.doi.org/10.1098/rsta.2012.0075.

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Cloud computing technologies have reached a high level of development, yet a number of obstacles still exist that must be overcome before widespread commercial adoption can become a reality. In a cloud environment, end users requesting services and cloud providers negotiate service-level agreements (SLAs) that provide explicit statements of all expectations and obligations of the participants. If cloud computing is to experience widespread commercial adoption, then incorporating risk assessment techniques is essential during SLA negotiation and service operation. This article focuses on the le

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38

Cigolini, R., and T. Rossi. "A note on supply risk and inventory outsourcing." Production Planning & Control 17, no. 4 (2006): 424–37. http://dx.doi.org/10.1080/09537280600650338.

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39

Zhang, F. "A note on supply risk and inventory outsourcing." Production Planning & Control 17, no. 8 (2006): 796–806. http://dx.doi.org/10.1080/09537280600834387.

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40

Hung, Kuo-Ting, and Sungmin Ryu. "Changing risk preferences in supply chain inventory decisions." Production Planning & Control 19, no. 8 (2008): 770–80. http://dx.doi.org/10.1080/09537280802550146.

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41

Yang, S. Alex, and John R. Birge. "Trade Credit, Risk Sharing, and Inventory Financing Portfolios." Management Science 64, no. 8 (2018): 3667–89. http://dx.doi.org/10.1287/mnsc.2017.2799.

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42

Yang, Hongsuk, and Linus Schrage. "Conditions that cause risk pooling to increase inventory." European Journal of Operational Research 192, no. 3 (2009): 837–51. http://dx.doi.org/10.1016/j.ejor.2007.10.064.

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43

Silbermayr, Lena, and Stefan Minner. "A multiple sourcing inventory model under disruption risk." International Journal of Production Economics 149 (March 2014): 37–46. http://dx.doi.org/10.1016/j.ijpe.2013.03.025.

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44

Liu, Hong, and Yajun Wang. "Market making with asymmetric information and inventory risk." Journal of Economic Theory 163 (May 2016): 73–109. http://dx.doi.org/10.1016/j.jet.2016.01.005.

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45

Chen, Yu, Liyuan Liu, Victor Shi, Yibin Zhang, and Jing Zhu. "The Optimization of a Virtual Dual Production-Inventory System under Dynamic Supply Disruption Risk." Complexity 2020 (December 24, 2020): 1–12. http://dx.doi.org/10.1155/2020/7067502.

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Major events such as the COVID-19 pandemic, Olympic Games, and G20 Summit bring about supplier disruption risks and challenges to supply chain management. To help deal with these risks, a virtual dual-sourcing production-inventory system can be deployed. In this paper, we study such a system which consists of a raw material supplier, a manufacturer, and a virtual dual-sourcing contingency supplier. The manufacturer needs to determine the production, procurement, and inventory plan of raw materials. When its supplier is interrupted, the manufacturer may need to adjust the production and invento

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46

Li, Tianyun, Weiguo Fang, Desheng Dash Wu, and Baofeng Zhang. "Inventory financing a risk-averse newsvendor with strategic default." Industrial Management & Data Systems 120, no. 5 (2020): 1003–38. http://dx.doi.org/10.1108/imds-08-2019-0417.

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PurposeThe paper aims to explore the optimal strategies of inventory financing when the risk-averse retailer has different objectives, in the presence of multi-risk, i.e. demand risk, non-operational risk and retailer's strategic default risk.Design/methodology/approachThis paper develops an inventory financing model consisting of a bank and a risk-averse retailer with strategic default. This paper considers two scenarios, i.e. the capital-constrained retailer cares about its profit or firm value. In the first scenario, the bank acts as a Stackelberg leader determining its interest rate, and t

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47

Dzreke, Simon Suwanzy, and Semefa Elikplim Dzreke. "The fragility of efficiency: How lean inventory strategies amplify supply chain crisis losses – a $2.3 trillion analysis of geopolitical shocks across 1,864 manufacturing firms." Frontiers in Research 2, no. 1 (2025): 45–66. https://doi.org/10.71350/30624533107.

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This research uncovers a critical vulnerability in global manufacturing: conventional lean inventory solutions excel under stable circumstances but markedly exacerbate losses during supply chain disturbances. A quantitative examination of more than 1,800 enterprises during 12 significant geopolitical events—including the Russia-Ukraine war, COVID-19 lockdowns, and the Suez Canal blockage—reveals that inadequate inventory buffers resulted in $2.3 trillion in preventable global losses. Regression research reveals that firms with Days Inventory Outstanding below sustainable norms had revenue decr

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48

Rahmaddial, Andre, and Suparno Suparno. "Inventory Control of Main Distribution Material (MDU) PB PD 1 Phase at PT PLN UP3 Banten Selatan." Journal Research of Social Science, Economics, and Management 4, no. 11 (2025): 2090–102. https://doi.org/10.59141/jrssem.v4i11.905.

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PT PLN UP3 Banten Selatan faces material shortages that delay customer connections, impacting service quality and regulatory compliance. This study aims to optimize inventory control for Main Distribution Unit (MDU) materials, focusing on 1-phase New Installation (PB) and Capacity Upgrade (PD) requests. The research compares current inventory practices with continuous review (s,S) and periodic review (R,s,S) systems to identify optimal inventory parameters. Risk management is addressed using the Multi-Criteria Decision Making (MCDM) framework, specifically the Analytical Hierarchy Process (AHP

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49

Xue, Shan, Ye Du, and Liang Xu. "Adaptive Market Making with Inventory Constraints via Online Learning." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 20 (2025): 21859–67. https://doi.org/10.1609/aaai.v39i20.35492.

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A market maker is a specialist who provides liquidity by continuously offering bid and ask quotes for a financial asset. The market maker’s objective is to maximize profit while avoiding the accumulation of a large position in the asset to control inventory risk. To achieve model-free results, online learning has been applied to design market-making strategies that make no assumptions on the dynamics of the limit order book and asset price. However, existing work primarily focuses on profit rather than inventory risk. To address this limitation, this paper develops market-making strategies wit

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50

Liu, Yingjun. "A Cross-Border e-Commerce Cold Chain Supply Inventory Planning Method Based on Risk Measurement Model." Mobile Information Systems 2022 (September 27, 2022): 1–9. http://dx.doi.org/10.1155/2022/6318373.

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Inventory planning results are less reliable when the statistical problem of supply chain risk factors is not considered. In conjunction with the risk measurement model, a cross-border e-commerce cold chain supply inventory planning method is proposed to effectively address the aforementioned issues. This paper aims to define the fundamental elements of the supply chain network, determine the supply chain's imbalance range, and develop a risk measurement model and also to calculate the ordering cost and storage cost, the storage cost, the cross-border e-commerce imbalance index based on the ri

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