Jyrki Savolainen, Mikael Collan and Pasi Luukka
The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of…
Abstract
Purpose
The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of subjective market information with a new cycle reverting price process is proposed.
Design/methodology/approach
Subjective managerial estimates are included into stochastic metal price modeling by defining separately the following parameters of each price cycle phase: approximated length, approximated long-term price level and volatility. An net present value-based investment analysis model is applied together with Monte Carlo simulation.
Findings
It is plausible to combine managerial estimates about metal price trends and cycles with stochastic modeling for shorter term and to include the information into investment analysis. The results show that the difference between the proposed process and the commonly used mean reverting process is remarkable in terms of decision-making implications.
Originality/value
The proposed method allows the inclusion of more relevant information into the metal price modeling used in mining investment analysis. Results suggest that the cyclical nature of metal prices affects project value of metal mining projects, and it should be considered when making irreversible investment decisions. The proposed method can be generalized for any cyclical processes.
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The author warns that nowadays a company must learn to be “co-productive” with an app developer community, a supplier community, a content community, an advocacy community or a…
Abstract
Purpose
The author warns that nowadays a company must learn to be “co-productive” with an app developer community, a supplier community, a content community, an advocacy community or a customer ecosystem in order to stay competitive through continuous innovation. Leaders need new tools to promote informed decisions.
Design/methodology/approach
The article shows how companies monitoring dynamic ecosystem change can develop crowd-based reporting scorecards to guide decision making.
Findings
Increasingly it is the innovations and expertise of the ecosystem, not the talents and resources of the firm, that are crucial to its future wealth generation. But many of the consequences of ecosystem change are, in fact, unmanageable in any traditional sense. An experimental way to identify the uncertainty produced by a dynamic ecosystem offers decision support.
Practical implications
The uncertainty monitoring experiments described in this article can clarify the risk levels and the need for preparatory investments. They offer a high level view of the dynamics of the new market ecosystem environment.
Originality/value
This article offers cutting-edge insights for managers struggling to make decisions about investments related to the dynamic ecosystem of users, suppliers, partners and customers in their companies’ markets.
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The economic life of large investments necessitates constant dynamic managerial actions. To be able to act in an optimal way in the dynamic management of large investments…
Abstract
The economic life of large investments necessitates constant dynamic managerial actions. To be able to act in an optimal way in the dynamic management of large investments managers need to have constant access to information about the real time situation of the investment, as well as access to up‐to‐date information about changes in the business environment. Looks at how emerging soft computing technologies will help to provide a better support in such a context and then to frame a support system that will make an integrated application of the technologies. Introduces traditional and advanced methods for capital budgeting and investment decision making, then presents a process view of the real option framework based investment management, and develops a holistic framework for an agent‐facilitated capital budgeting system using a fuzzy real option approach. Discusses how intelligent agents can be applied to collect decision information, and to facilitate the integration of foresight information into capital budgeting process, and how the agents can be constructed. Finally, elaborates on the managerial implications of the proposed decision support technology.
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José M. Merigó, Salvador Linares-Mustarós and Joan Carles Ferrer-Comalat