The Valuation of Information Technology Investments by Real Options Analysis

2009 ◽  
Vol 12 (04) ◽  
pp. 611-628 ◽  
Author(s):  
Kuo-Jung Lee ◽  
David S. Shyu ◽  
Miao-Ling Dai
Keyword(s):  
Information Technology ◽  
Real Options ◽  
Cost Savings ◽  
Price Volatility ◽  
Closed Form Expression ◽  
Optimal Timing ◽  
Real Options Analysis ◽  
It Investments ◽  
Output Price ◽  
Information Technology Investments

This study establishes a dynamic model under real options analysis to analyze the optimal timing decision of information technology (IT) investments when the output price for firms is stochastic and benefits of IT investments are arisen from the increasing output price, increasing sale, and cost savings. We derive the closed form expression of the timing of IT investments and furthermore prove that IT investments rise at an increasing rate in economic booms and fall in economic busts. This study finds that increasing (decreasing) price volatility will delay (advance) the timing of IT investments. Increasing IT investments, however, may not delay the timing of IT investments. In addition, the decreasing (increasing) efficiency and increasing (decreasing) depreciation of IT investments will delay (advance) the timing of IT investments.

Modeling Customer-Related IT Diffusion

2011 ◽  
pp. 251-263
Author(s):  
Shana L. Dardan ◽  
Ram L. Kumar ◽  
Antonis C. Stylianou
Keyword(s):  
Information Technology ◽  
Data Collection ◽  
Diffusion Model ◽  
Technology Diffusion ◽  
Empirical Support ◽  
Event Studies ◽  
It Investments ◽  
It Diffusion ◽  
Information Technology Investments ◽  
Bayesian Prior

This study develops a diffusion model of customer-related IT (CRIT) based on stock market announcements of investments in those technologies. Customer-related IT investments are defined in this work as information technology investments made with the intention of improving or enhancing the customer experience. The diffusion model developed in our study is based on data for the companies of the S&P 500 and S&P MidCap 400 for the years of 1996-2001. We find empirical support for a sigmoid diffusion model. Further, we find that both the size and industry of the company affect the path of CRIT diffusion. Another contribution of this study is to illustrate how data collection techniques typically used for fi- nancial event studies can be used to study information technology diffusion. Finally, the data collected for this study can serve as a Bayesian prior for future diffusion forecasting studies of CRIT.

Revisiting the Impact of Information Technology Investments on Productivity

2011 ◽  
pp. 296-322
Author(s):  
Myung Ko ◽  
Jan Guynes Clark ◽  
Daijin Ko
Keyword(s):  
Information Technology ◽  
Predictor Variable ◽  
Value Added ◽  
It Investments ◽  
Interaction Variable ◽  
Information Technology Investments ◽  
Technology Investments ◽  
The Impact ◽  
The Relationship

This article revisits the relationship between IT and productivity, and investigates the impact on information technology (IT) investments. Using the MARS techniques, we show that although IT Stock is the greatest predictor variable for productivity (Value Added), it is only significant as an interaction variable, combined with Non-IT Capital, Non-IT Labor, Industry, or Size.

scholarly journals Information Technology Investments And Aggregate Productivity

2016 ◽  
Vol 32 (4) ◽  
pp. 995-1008
Author(s):  
Paul Moon Sub Choi ◽  
Hakyoul Choe
Keyword(s):  
Information Technology ◽  
Financial Markets ◽  
Capital Allocation ◽  
Aggregate Productivity ◽  
It Investments ◽  
Relative Contribution ◽  
Information Technology Investments ◽  
Country Analysis ◽  
Cross Country ◽  
Empirical Implications

Earlier studies have shown positive and large impacts of information technology (IT) investments on aggregate products in the nascent stage. However, this causal inference may not be applicable in the adult regime with a diminishing marginal productivity. We conduct a 52 cross-country analysis on a 15 year data of IT capital stocks, rather than flows as used in the literature. Controlling for country and time effects, the empirical implications of our study are as follows: First, the IT investment intensity positively affects aggregate productivity controlling for labor, assets, and financial markets. Second, the relative contribution has decreased as the law of diminishing returns predicts. Lastly, software and services have gained more capital allocation on relative terms in exchange for less on hardware. This finding contrasts with the existing argument that the hardware-software mix is time-constant due to substitution.

scholarly journals Information technology investments and supply chain governance

2014 ◽  
Vol 18 (2) ◽  
pp. 217-235 ◽  
Author(s):  
Pietro Cunha Dolci ◽  
Antonio Carlos Gastaud Maçada
Keyword(s):  
Information Technology ◽  
Supply Chain ◽  
Supply Chain Performance ◽  
Extensive Literature ◽  
Final Model ◽  
It Investments ◽  
Information Technology Investments ◽  
Supply Chain Governance ◽  
And Performance ◽  
Shed Light

The aim of this research is to propose a model that relates information technology (IT) investments, supply chain governance (SCG) and performance together. For this purpose, a pilot study involving both a qualitative and a quantitative stage was conducted. The qualitative analysis, consisting of an extensive literature review and two case studies conducted in six major, globally-relevant Brazilian companies, led to the development of an initial model. This model was refined during the quantitative stage that involved 38 executives from large national companies. IT was found to be one of the main drivers of SCG influencing companies' supply chain performance. The final model consists of 5 constructs and 26 elements. Regarding the SCG constructs: (a) a new element 'formal contracts', emerged in the 'contractual SCG' construct; (b) the element 'cooperation' was not confirmed in the 'relational SCG' construct; (c) the element 'transparency' was considered an important element in the 'transactional SCG' construct. Five new elements emerged in the 'IT investment' construct. Market aspects were highlighted as being relevant in the 'supply chain performance' construct. Thus, the model includes elements that can be analyzed in order to shed light on how IT investments influence SCG and supply chain performance.

Use of Information Technology Investment Management to Manage State Government Information Technology Investments

2009 ◽  
pp. 1-22
Author(s):  
David Van Over
Keyword(s):  
Information Technology ◽  
State Government ◽  
Significant Proportion ◽  
Government Information ◽  
It Investments ◽  
Technology Investment ◽  
Information Technology Investments ◽  
Information Technology Investment ◽  
High Level ◽  
Business Requirements

The expenditures of funds on IT has continued to expand and a significant proportion of the expenditures are hidden, unaccounted for, or never evaluated in terms of the business value derived from the expenditure. This chapter focuses on the methods and means of creating a linkage between business requirements and the IT investments that can address those requirements. An ITIM framework is proposed, which addresses three key elements of ITIM: what decisions are to be made, who should make the decisions, and how decisions are to be made and monitored. ITIM is a management process that provides for the identification (pre selection), selection, control, and evaluation of business driven IT investments across the investment lifecycle. ITIM uses structured processes to minimize risks and maximize return on investments. Additionally, a high-level ITIM implementation plan is discussed.

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