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Статті в журналах з теми "Risk inventory"

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Автор: Grafiati

Опубліковано: 23 червня 2021

Оновлено: 7 лютого 2022

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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 (October 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 confirmed the RTI’s good model–data fit via three further separate confirmatory factor analyses. In Study 2 (n = 518) and in Study 3 (n = 290), concurrent validity was also confirmed via associations with other related traits (sensation seeking, behavioral activation, behavioral inhibition, impulsivity, self-esteem, extraversion, and conscientiousness). In Study 4 (n = 365), predictive validity was confirmed via associations with mean accidents and mean close calls in the high-risk domain. Finally, in Study 4, the self-report version of the inventory was significantly associated with an informant version of the inventory. The measure will allow researchers and practitioners to investigate risk taking as a variable that is conceptually distinct from participation in a high-risk sport.

2

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

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3

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

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4

Bianco, Marco, and Andrea Gamba. "Inventory and Corporate Risk Management." Review of Corporate Finance Studies 8, no. 1 (November 6, 2018): 97–145. http://dx.doi.org/10.1093/rcfs/cfy007.

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5

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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6

Brooks, LeRoy D. "Inventory Policy Incorporating Systematic Risk." Engineering Economist 33, no. 3 (January 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 (October 2, 2009): 73–83. http://dx.doi.org/10.1080/01960070902903995.

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8

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

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9

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

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10

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

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11

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

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12

Zhang, Jiahua, Shu-Cherng Fang, and Yifan Xu. "Inventory centralization with risk-averse newsvendors." Annals of Operations Research 268, no. 1-2 (July 18, 2017): 215–37. http://dx.doi.org/10.1007/s10479-017-2578-0.

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13

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

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14

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

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15

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

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16

Beechem, Michael. "Beechem Risk Inventory for Late-Onset Alcoholism." Journal of Drug Education 27, no. 4 (December 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 feels the intensity of the loss at the moment (i.e., in the “here and now”). An additional feature of the inventory illustrates a simplified procedure to compute the respondent's unresolved loss-grief level through use of a 5-point Likert scale.

17

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

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18

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

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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 (August 10, 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 waste inventory of waste-producing companies and proposes a risk evaluation system for safely dealing with hazardous waste inventory, which expands the scope of inventory safety management and provides guidance to companies on developing appropriate measures to ensure hazardous waste inventory safety. First, the risk evaluation index system for hazardous waste inventory is constructed from equipment, management level, nature of hazardous waste and operational aspects. Then, the best worst method (BWM) is employed to calculate the criteria weights and the technique for order performance by similarity to ideal solution (TOPSIS) is employed to rank the alternatives. Finally, risk evaluation on four waste-producing companies was conducted using the developed method. The results show that Case Company 4 has the greatest risk of hazardous waste inventory, which should be reduced by improving storage method and the amount of hazardous waste. It was found that the proposed evaluation system was effective for hazardous waste inventory safety risk assessments and that the designed index system could assist companies improve their hazardous waste inventory management.

20

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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21

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 inventory plan and work with the contingency supplier. We develop a system dynamics method to simulate the operations in this production-inventory system to identify the approximately optimal order-up-to-level inventory policies. We find that the virtual dual production-inventory strategy can be the optimal contingency policy to deal with supplier dynamic disruption risks. Furthermore, for disruption risk with low frequency and long duration, the manufacturer should increase the safety inventory level before the disruption. Otherwise, it should increase the safety inventory level in every cycle.

22

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 temporary shrinkage. Two scenarios of reducing inventory shrinkage are presented. In the first scenario, the retailer conducts physical inventory audits to identify the discrepancy. In the second scenario, the retailer deploys an automatic tracking technology, radiofrequency identification (RFID), to reduce inventory shrinkage. With the CVaR criterion, we propose optimal policies for the two scenarios. We show monotonicity between the retailer’s ordering policy and his risk aversion degree. A numerical analysis provides managerial insights for risk-averse retailers considering investing in RFID technology.

23

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 risk-seeking retailer’s optimal inventory quantity, optimal inventory cost, supplier profit, retailer profit, and the profit of the entire water supply chain are derived. The validity of the equations is proved. The sensitivity analysis of the risk-seeking retailer’s optimal inventory decision-making is carried out. The risk level effects on the five dimensions, the retail price, wholesale price, unit shortage cost, unit inventory cost, and unit residual value, are displayed through numerical simulation. The optimal inventory quantity and optimal inventory cost of the risk-seeking retailer are obtained.

24

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 price uncertainty leads the firm to decrease inventory. Besides, the risk-averse behaviour leads the firm to reduce its stocking quantity.

25

Zhu, Xuechang, Qigang Yuan, and Wei Zhang. "Inventory leanness, risk taking, environmental complexity, and productivity." Journal of Manufacturing Technology Management 29, no. 7 (November 5, 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 relationship between inventory leanness and productivity. The authors then demonstrate the role of risk taking in mediating this relationship. Furthermore, the authors find that environmental complexity not only negatively moderates the relationship between inventory leanness and productivity, but also negatively moderates the relationship between risk taking and productivity. Practical implications Managers should not be excessively pursuing inventory leanness improvements, so as not to damage the ability to increase productivity. Originality/value This paper may be the first study to empirically demonstrate the moderating effect of environmental complexity and the mediating effect of risk taking on the inverted U-shaped relationship between inventory leanness and productivity.

26

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

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27

Colon, Célian, Åke Brännström, Elena Rovenskaya, and Ulf Dieckmann. "Fragmentation of production amplifies systemic risks from extreme events in supply-chain networks." PLOS ONE 15, no. 12 (December 28, 2020): e0244196. http://dx.doi.org/10.1371/journal.pone.0244196.

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Climatic and other extreme events threaten the globalized economy, which relies on increasingly complex and specialized supply-chain networks. Disasters generate (i) direct economic losses due to reduced production in the locations where they occur, and (ii) to indirect losses from the supply shortages and demand changes that cascade along the supply chains. Firms can use inventories to reduce their risk of shortages. Since firms are interconnected through the supply chain, the level of inventory hold by one firm influences the risk of shortages of the others. Such interdependencies lead to systemic risks in supply chain networks. We introduce a stylized model of complex supply-chain networks in which firms adjust their inventory to maximize profit. We analyze the resulting risks and inventory patterns using evolutionary game theory. We report the following findings. Inventories significantly reduce disruption cascades and indirect losses at the expense of a moderate increase in direct losses. The more fragmented a supply chain is, the less beneficial it is for individual firms to maintain inventories, resulting in higher systemic risks. One way to mitigate such systemic risks is to prescribe inventory sizes to individual firms—a measure that could, for instance, be fostered by insurers. We found that prescribing firm-specific inventory sizes based on their position in the supply chain mitigates systemic risk more effectively than setting the same inventory requirements for all firms.

28

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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29

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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30

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

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31

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

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32

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

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33

Djemame, Karim, Benno Barnitzke, Marcelo Corrales, Mariam Kiran, Ming Jiang, Django Armstrong, Nikolaus Forgó, and Iheanyi Nwankwo. "Legal issues in clouds: towards a risk inventory." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1983 (January 28, 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 legal issues surrounding risk assessment in cloud computing. Specifically, it analyses risk regarding data protection and security, and presents the requirements of an inherent risk inventory. The usefulness of such a risk inventory is described in the context of the OPTIMIS project.

34

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

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35

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 (December 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 factorization technique. When ω(x) is constant, no specific assumptions will be made on the service requirement distribution. However, in the linear case, we need some algebraic hypotheses concerning the Laplace–Stieltjes transform of the service requirement distribution. Throughout the paper, we also study a closely related model arising from insurance risk theory.

36

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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37

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

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38

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.

39

Rosenbloom, Tova. "RISK EVALUATION AND RISKY BEHAVIOR OF HIGH AND LOW SENSATION SEEKERS." Social Behavior and Personality: an international journal 31, no. 4 (January 1, 2003): 375–86. http://dx.doi.org/10.2224/sbp.2003.31.4.375.

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This study was aimed at achieving a better understanding of the role of the mediation of risk valuation between personality and risk-taking behavior. A sample of 55 females and 20 males completed the Sensation Seeking Scale (SSS) and self-report inventory of risk-taking in one session and a risk evaluation inventory in another session. The results show a positive correlation between risk taking and sensation seeking and a negative correlation between risk evaluation and sensation seeking. High sensation seekers are found to be higher in risk taking than in risk evaluation while the low sensation seekers are higher in risk evaluation than in risk taking. The meaning and possible implications of these results to the relationship between risk taking and sensation seeking are discussed.

40

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 (June 7, 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 the significant trend and intercept. The optimal demand is decreased during more risk as a deterioration variable to reduce the quantity in the stock. The initial demand is stationary after a first lag and the demand is stationary.Keywords: initial inventory; optimal of first run-time; EOQ (Economic Ordering Quantity); total cost function (TC). AbstrakPenelitian ini mengadopsi inventori dengan dua gudang penyimpanan, penentuan pada waktu run (run-time) awal, dan model deteriorating VAR (Vector Auto Regression). Nilai optimal EOQ dalam interval horizon berhingga ditentukan dengan pertimbangan kritis. Inventori dengan dua gedung yang tidak stasioner, yaitu inventori dan inventori awal tidak stasioner pada level, tetapi stasioner setelah perbedaan lag seperti halnya pada permintaan (permintaan dan permintaan awal). Hasil dari model yang diajukan menunjukkan nilai orde yang optimal dan waktu run awal yang optimal, total biaya optimal sebagai integrasi dari orde pertama dengan tren dan intercept yang signifikan. Permintaan optimal mengalami penurunan ketika lebih banyak risiko sebagai variabel deteroriating untuk mengurangi jumlah dalam stok. Permintaan awal menunjukkan stasioner setelah perbedaan lag pertama dan permintaan juga stasioner.Kata kunci: inventori awal; optimal run-time awal; EOQ (Economic Ordering Quantity); fungsi biaya total.

41

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 (April 15, 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 the retailer acts as a follower determining its pledged quantity. In the second one, the bank capital market is perfectly competitive. Lagrange multiplier method is adopted to solve the optimization.FindingsThe optimal strategies in inventory financing scheme in two scenarios are derived. Only when the initial stock is relatively high, the retailer pledges part of the initial stock. Retailer's risk aversion reduces its pledged quantity and performance. The strategic default reduces its profit. When it is relatively high, the bank refuses to offer the loan.Practical implicationsAnalytical inventory and financing strategies are specified to help retailers and banks to better understand the interaction of finance and operations management and to better respond to multi-risk.Originality/valueNew results and managerial insights are derived by incorporating partially endogenous strategic default and risk aversion into inventory financing, which enriches the interfaces of operations management and finance.

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Bagley, Penelope L., Beau Grant Barnes, and Nancy L. Harp. "Evaluating Risk and Processing Integrity Controls over Spreadsheets: An Educational Case." Issues in Accounting Education 34, no. 3 (April 1, 2019): 21–40. http://dx.doi.org/10.2308/iace-52426.

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ABSTRACT This case requires students to create a spreadsheet inventory, assess the risk related to each spreadsheet inventoried, and perform internal control testing on the spreadsheet deemed to be of the highest risk. Completing the case will benefit students in many ways. First, the case will familiarize students with creating a spreadsheet inventory. Second, it will familiarize students with the risks associated with spreadsheet errors by requiring them to evaluate and consider such risks. Third, the case will provide students with practice in evaluating spreadsheet controls and detecting spreadsheet errors. Finally, the case will increase students' awareness of the pervasiveness and potentially negative impact that spreadsheet errors can have on financial reporting.

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Range, Lillian M., and Linda Starling Lewis. "Life Orientation Inventory: A method of assessing suicide risk." Journal of Psychoeducational Assessment 10, no. 3 (September 1992): 296–97. http://dx.doi.org/10.1177/073428299201000310.

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Jaques, Nicholas, and Chris Morgan. "Adapting the Analytical Hierarchy Process to Identify Inventory Risk." International Journal of Logistics Management 15, no. 2 (July 2004): 93–105. http://dx.doi.org/10.1108/95740930480000354.

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Barone, David F., Glenn R. Caddy, Alan D. Katell, Frank B. Roselione, and Richard A. Hamilton. "The Work Stress Inventory: Organizational Stress and Job Risk." Educational and Psychological Measurement 48, no. 1 (March 1988): 141–54. http://dx.doi.org/10.1177/001316448804800117.

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Degiorgio, Lisa. "Examining Equivalency of the Driver Risk Inventory Test Versions." Measurement and Evaluation in Counseling and Development 48, no. 4 (October 2015): 297–305. http://dx.doi.org/10.1177/0748175615578736.

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Kao, Wei-Feng. "Risk supply chain culture and creative product inventory policy." Journal of Statistics and Management Systems 21, no. 5 (August 6, 2018): 901–15. http://dx.doi.org/10.1080/09720510.2018.1492892.

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Scheiner, A., M. Sexton, and Kimberly Wiesen. "Prediction of Developmental Outcome Using a Perinatal Risk Inventory." Pediatric Physical Therapy 6, no. 1 (1994): 42. http://dx.doi.org/10.1097/00001577-199400610-00023.

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Berman, Oded, Dmitry Krass, and M. Mahdi Tajbakhsh. "On the Benefits of Risk Pooling in Inventory Management." Production and Operations Management 20, no. 1 (January 2011): 57–71. http://dx.doi.org/10.1111/j.1937-5956.2010.01134.x.

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