Information Technology Productivity
Zhang, D., Nault, B.R. and X. Wei. The Strategic Value of IT in Setting Productive Capacity. Information Systems Research, 30(4), December 2019, 1124-1144. PDF (last version of working paper)
Capacity is the maximum short run output with capital in place under normal operations, and capital investment increases capacity. Excess capacity can be used as an economic strategy for entry deterrence by lowering average costs over a greater range of output, and as an operations strategy providing value through flexibility to manage demand fluctuations and production disturbances. Our primary focus is to study the way that information technology (IT) can contribute to a strategy of holding excess capacity by comparing the relationship between IT capital and capacity with that of non-IT capital and capacity. Using production theory-based empirical analyses, we find that increases in IT capital yield almost four-fold greater expansion in capacity than do increases in non-IT capital. Thus, as both types of capital are constraints on capacity, for a strategy of holding excess capacity IT capital is a more valuable constraint to relax than non-IT capital. In addition, since the late 1990s, IT capital, and to a lesser extent non-IT capital, have reduced capacity utilization (output/capacity), meaning increasing levels of excess capacity are being held across manufacturing industries and utilities across the economy.
Zhang, D., Cheng, Z., Mohammad, H.Q., and B.R. Nault, “Information Technology Substitution Revisited,” Information Systems Research 26(3), September 2015, 480-495. PDF (last version of working paper)
Taking advantage of the opportunities created by the price adjusted performance improvement in IT depends in part on the ability of IT capital to substitute for other inputs in production. Studies in the IS literature as well as most economics training that examine substitution of IT capital for other inputs use the Allen elasticity of substitution (AES). We present a less-well-known measure for the elasticity of substitution, the Morishima Elasticity of Substitution (MES). In contrast to the AES which is misleading when there are three or more inputs – such as non-IT capital, labor and IT capital – the MES provides a substitution measure where the scale is meaningful, and the measure differs depending upon which price is changing. This is particularly important for IT capital as prices have been declining and there is evidence that IT capital can substitute for non-IT capital or labor in a qualitatively different way than non-IT capital and labor substitute for each other. Methodologically we also show the impact of imposing local regularity – for example, monotonicity of output from increases in inputs – that we do through Bayesian methods employed to estimate the underlying functions that are used to calculate various measures of substitution. We demonstrate the importance of the MES as an under-recognized measure of substitution and the impact of imposing local regularity using an economy-wide industry-level dataset covering 1998-2009 at the three digit NAICS level. Our MES results show that reductions in the price of IT capital increase the quantity of IT capital in use but are unlikely to change the input share of IT capital – the value of IT capital as a proportion of the value of all inputs, in contrast to major studies using the AES. In addition, estimates for both elasticities of substitution are more stable after imposing local regularity. Both of these advances – that is, the MES and imposing local regularity – have potential to impact future work on IT productivity, IT pricing, IT cost estimation and any type of analysis that posits the substitution of IT capital for non-IT capital or labor.
Kundisch, D., Mittal, N., and B.R. Nault, “Using Income Accounting as the Theoretical Basis for Measuring IT Productivity,” Information Systems Research , 25(3), September 2014, 449-467 PDF
We use the under-recognized income accounting identity to provide an important theoretical basis for using the Cobb-Douglas production function in IT productivity analyses. Within the income accounting identity we partition capital into non-IT and IT capital and analytically derive an accounting identity (AI)-based CobbDouglas form that both nests the three-input Cobb-Douglas and provides additional terms based on wage rates and rates of return to non-IT and IT capital. To empirically confirm the theoretical derivation, we use a specially constructed data set from a subset of the U.S. manufacturing industry that involve elaborate calculations of rates of return—a data set that is infeasible to obtain for most productivity studies—to estimate the standard Cobb-Douglas and our AI-based form. We find that estimates from our AI-based form correspond with those of the Cobb-Douglas, and our AI-based form has significantly greater explanatory power. In addition, empirical estimation of both forms is relatively robust to the assumption of intertemporally stable input shares required to derive the AI-based form, although there may be limits. Thus, in the context of future research the CobbDouglas form and its application in IT productivity work have a theoretically and empirically supported basis in the accounting identity. A poor fit to data or unexpected coefficient estimates suggests problems with data quality or intertemporally unstable input shares. Our work also shows how some returns to IT that do not show up in output elasticities can be found in total factor productivity (TFP)—the novel ways inputs are combined to produce output. The critical insight for future research is that many unobservables that have been considered part of TFP can be manifested in rates of return to IT capital, non-IT capital, and labor—rates of return that are separated from TFP in our AI-based form. Finally, finding that the additional rates of return terms partially explain TFP confirms the need for future IT productivity researchers to incorporate time-varying TFP in their models.
Cheng, Z., and B.R.Nault, "Relative Industry Concentration and Customer-Driven IT Spillovers," Information Systems Research, 23(2), June 2012, 340-355. PDF
We examine how one industry’s productivity is affected by the IT capital of its customers and how this effect depends on industries’ relative concentration. These customer-driven IT spillovers result from customers’ IT investments in various information systems that reduce transaction costs through information sharing and coordination and lead to more efficient production and logistics upstream. The magnitude of IT spillovers depends on relative industry concentration because customers in more concentrated industries relative to those of their suppliers are better able to retain the benefits from their IT investments. We model customer-driven effects based on production theory and empirically test the model using two industry-level data sets covering different and overlapping time periods (1987–1999 and 1998–2005), different scopes of the economy (manufacturing only versus all industries), and different levels of industry aggregation. We find that, given an increase in a downstream industry’s IT capital, there is a significant increase in downstream industry output as well as significant increases in upstream industry output. Moreover, the magnitude of IT spillovers is related to relative industry concentration: A 1% decrease in a customer’s relative industry concentration increases spillovers by roughly 1%. Thus, further increases in IT capital can be justified along the supply chain, and an industry’s relative concentration—which can reflect market power—in part determines the distribution of productivity benefits.
Han, K., Kauffman, R.J., and B.R. Nault, "Returns to Information Technology Outsourcing," Information Systems Research, 23(2), December 2011, 340-355. PDF
This study extends existing information technology (IT) productivity research by evaluating the contributions of spending in IT outsourcing using a production function framework and an economywide panel data set from 60 industries in the United States over the period from 1998 to 2006. Our results demonstrate that IT outsourcing has made a positive and economically meaningful contribution to industry output and labor productivity. It has not only helped industries produce more output, but it has also made their labor more productive. Moreover, our analysis of split data samples reveals systematic differences between high and low IT intensity industries in terms of the degree and impact of IT outsourcing. Our results indicate that high IT intensity industries use more IT outsourcing as a percentage of their output, but less as a percentage of their own IT capital, and they achieve higher returns from IT outsourcing. This finding suggests that to gain greater value from IT outsourcing, firms need to develop IT capabilities by intensively investing in IT themselves. By comparing the results from subperiods and analyzing a separate data set for the earlier period of 1987–1999, we conclude that the value of IT outsourcing has been stable from 1998 to 2006 and consistent over the past two decades. The high returns we find for IT outsourcing also suggest that firms may be underinvesting in IT outsourcing.
Mittal, N., and Nault, B.R., "Investments in Information Technology: Indirect Effects and Information Technology Intensity, " Information Systems Research, 20(1), March 2009, 140-154. PDF
Many studies measure the value of information technology (IT) by focusing on how much value is added rather than on the mechanisms that drive value addition. We argue that value from IT arises not only directly through changes in the factor input mix but also indirectly through IT-enabled augmentation of non-IT inputs and changes in the underlying production technology. We develop an augmented form of the CobbDouglas production function to separate and measure different productivity-enhancing effects of IT. Using industry-level data from the manufacturing sector, we find evidence that both direct and indirect effects of IT are significant. Partitioning industries into IT-intensive and non-IT-intensive, we find that the indirect effects of IT predominate in the IT-intensive sector. In contrast, the direct effects of IT predominate in the non-IT intensive sector. These results indicate structural differences in the role of IT in production between industries that are IT-intensive and those that are not. The implication for decision-makers is that for IT-intensive industries the gains from IT come primarily through indirect effects such as the augmentation of non-IT capital and labor.
Cheng, Z., and Nault, B.R., "Industry Level Supplier-Driven IT Spillovers," Management Science, 53(8), August 2007, 1199-1216. PDF
We model and estimate the effects to downstream productivity from information technology (IT) investments made upstream. Specifically, we examine how an industry’s productivity is affected by the IT capital stock of its suppliers. These supplier-driven IT spillovers occur because, due to competition in the supplying industry, quality benefits from suppliers’ IT investments can pass downstream. If the output deflators of supplying industries (consequently the intermediate input deflator of the using industries) do not capture the quality improvement from IT, then the output productivity of the supplying industries is mismeasured or misassigned. We develop and empirically test a model capturing these supplier-driven effects using data on 85 manufacturing industries at the three-digit SIC code level. We find that for a 10.5% increase in suppliers’ IT capital, the suppliers’ output increases by 0.63%–0.70%, which is more than covering the cost of the increase in suppliers’ IT capital. In addition, this increase in suppliers’ IT capital increases the average downstream industry’s output by $66–$72 million, thereby confirming substantial supplier-driven IT spillovers downstream. We also infer the magnitude of the measurement error of the price deflator of the intermediate input resulting from the failure to account for IT-related quality improvement, finding that the me.