Valuation of Procurement Flexibility in the Machinery and Equipment Industry Using the Real Option Approach

Kleinert, Alexander; Stich, Volker

doi:10.1007/978-3-642-15509-3_3

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Despite their differences, the studies by Benaroch et al (2010), Wu et al (2001), and Klaus et al (2014) have an essential property in common with our objective: Due to the trend toward highly individualized products, we consider a company that applies an MTO approach with no production of stock, which is similar to those authors' application context of ITservices that cannot be physically stored. In the context of manufacturing, we found only one other paper that uses ROA to evaluate temporal capacity expansion of companies with MTO approaches: Kleinert and Stich (2010) address companies in the machinery and equipment industry that source subcomponents from suppliers. As unforeseen problems might occur during the manufacturing process, these authors recommend that such companies consider the purchase of additional expansion options from their suppliers.…”

Section: Investment Evaluation Methodsmentioning

confidence: 99%

Evaluating investments in flexible on-demand production capacity: a real options approach

Freitag

Häfner

Pfeuffer

et al. 2019

Bus Res

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Ongoing digitalization of production accelerates trends like mass customization, ever shorter lead times, and shrinking product life cycles. Thereby, industrial companies face increasingly volatile demand that complicates an appropriate production capacity planning. On the other hand, the comprehensive digitalization of production environments favors, amongst others, the dynamic integration of flexible external on-demand production capacity provided by specialized external capacity providers (ECPs). To enable the usage of on-demand production capacity, industrial companies may require significant upfront investments (e.g., for inter-organizational information systems, planning and organizational processes, employee training). The objective of this paper is to develop a model that evaluates such enabling upfront investments from the perspective of a manufacturing company. To consider flexibility of action, we apply real options analysis in a discrete-time binomial tree model and weigh these so-called expansion options to related cash outflows. In addition, we evaluate our model by means of a simulation and sensitivity analyses and derive insights for both researchers and practitioners. The insights gained by our model present a profound economic basis for investment decisions on upfront investments in flexible on-demand production capacity.

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Section: Investment Evaluation Methodsmentioning

confidence: 99%

Evaluating investments in flexible on-demand production capacity: a real options approach

Freitag

Häfner

Pfeuffer

et al. 2019

Bus Res

View full text Add to dashboard Cite

show abstract

“…Private information that the other companies do not possess is very important to implement one's own optimal actions in the supply chain coordination. Due to the high uncertainty in manufacturing process, a method to increase the flexibility needs to be used (Kleinert and Stich 2010). One method increasing suppliers' flexibility that has been used in recent years is ROA (Lander and Pinches 1998).…”

Section: Research Questionsmentioning

confidence: 99%

Production Flexibility of Real Options in Daily Supply Chain

Kume

Fujiwara

2015

Glob J Flex Syst Manag

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Production or its investment of carton soft drink is relatively lower in cost than that of the canned, glass bottled, or plastic bottled soft drink. However, as the shelf life is shorter than other packaging systems, it is difficult to carry its inventory and then to produce daily by order. In particular, at the final batch in daily production, it is unavoidable to discard the excess drink over the minimum volume necessary for final one batch processing. Hence, this paper's research question is how some flexible before and behind shift of order timing can reduce such kinds of discard based on an agreement with the customer.A key phrase is 'Virtual Inventory' by flexible demand timing shift for a buffer between supply and demand without any physical inventory for discard reduction. The methodology to the above research questions is real options analysis for a flexible shift decision of demand timing. This paper's objective is to build a two-stage supply-chain model for call and put options for positive and negative daily production flexibility to ''real demand'', draw an option selection policy to each gap between supply and demand, apply a sensitivity analysis to find critical conditional and decision variables at a decision tree, and confirm the effectiveness of this scheme by using practical demand data. Thus, timing option can be considered as Virtual Inventory by its buffer function between supply and demand in daily demand production. The next challenge is smart and flexible risk management to uncertain demand with clear seasonal variation.

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Scheduling Flexible Demand in Cloud Computing Spot Markets

et al. 2019

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The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper, the authors apply real options analysis (ROA), which is an established valuation method designed to capture the flexibility of action under uncertainty. They adapt and compare multiple discrete-time approaches that enable cloud customers to quantify and exploit the monetary value of their short-term temporal flexibility. The paper contributes to the field by guaranteeing cloud job execution of variable-time requests in a single cloud spot market, whereas existing multi-market strategies may not fulfill requests when outbid. In a broad simulation of scenarios for the use of Amazon EC2 spot instances, the developed approaches exploit the existing savings potential up to 40 percent-a considerable extent. Moreover, the results demonstrate that ROA, which explicitly considers time-of-day-specific spot price patterns, outperforms traditional option pricing models and expectation optimization.

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Valuation of Procurement Flexibility in the Machinery and Equipment Industry Using the Real Option Approach

Cited by 3 publications

References 14 publications

Evaluating investments in flexible on-demand production capacity: a real options approach

Evaluating investments in flexible on-demand production capacity: a real options approach

Production Flexibility of Real Options in Daily Supply Chain

Scheduling Flexible Demand in Cloud Computing Spot Markets

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