MIS 9003 – Prof. Min-Seok Pang

Week 11 – Labor

Bloom et al 2014 -Siddharth Bhattacharya

The paper talks about how information technology is a decentralizing force, whereas communication technology is a centralizing force. The paper argues that these technologies have at least two distinct components, information technology (IT) and communications technology (CT). The paper studies the differential impact on the organization of firms of these two types of technology (information versus communication) and applies this framework in a world with two types of decisions, production and nonproduction ones. Results show that, technologies that lead to falling information costs for nonproduction decisions (like ERP) tend to empower plant managers (relative to the headquarters), and technologies that lead to falling information costs for production decisions (like CAD/CAM) tend to empower workers relative to plant managers. In other words, a technology that lowers information costs increases the autonomy of the lower-level agent (a worker in the production case, a plant manager in the nonproduction case), whereas a technology that lowers communication costs reduces this autonomy. The study relies on a new data set that combines plant-level measures of organization and ICT hardware and software adoption across the United States and Europe as part of a large international management survey. For identification, the authors rely on simple conditional correlations between the different ICT measures and the multiple dimensions of the organization of the firm. Instrumental variables show increased robustness of the results. The work solves the conundrum in literature that takes s information technology (IT) and communication technology (CT) into a single homogeneous category and shows that e impact of IT and CT on the organization of firms, and ultimately income inequality, will be quite different depending on the type of technology used.

Week 11 – Pierce et al. 2015 – Joe

Lamar Pierce, Daniel C. Snow, Andrew McAfee (2015) Cleaning House: The Impact of Information Technology Monitoring on Employee Theft and Productivity. Management Science 61(10):2299-2319.

Employee theft and fraud are widespread problems in firms, with workers stealing roughly $200 billion annually from U.S. firms to supplement their income. A growing empirical literature clarifies when and how theft and other misconduct occur but says little about the overall impact of firms’ use of forensics to monitor and reduce theft. This paper examines how firm investments in technology-based employee monitoring impact both misconduct and productivity by addressing three important yet unresolved questions: 1) is employee monitoring indeed effective in reducing theft, as economics suggests, or does monitoring demotivate and constrain employees and thus negate gains from theft reductions? 2) do possible gains from monitoring result from changing worker behavior or from replacing unethical workers with more honest ones? 3) if increased monitoring indeed reduces theft by existing workers, then through which mechanisms does productivity in other tasks change and what is the overall impact to the firm?

The paper initiates with phenomenon-driven questions while exploring the underlying mechanisms of economics, phycology, and behavior aspects using theft and sales data from 392 restaurant locations from five firms. After using a restaurant-level and individual worker-level Differences-in-Differences model, the authors find significant treatment effects in reduced theft and improved productivity. More, they dig more on the mechanism identification: the majority of productivity improvement and theft reduction is due to behavioral changes among existing workers rather than selection effects due to managers replacing problem workers revealed by the IT system. Furthermore, the authors explore the deeper mechanism: economic multi-tasking, cognitive multi-tasking, motivation from fairness or perceived increases of general oversight. Their results cast significant doubt on both the cognitive and economic multitasking mechanisms, and provide mixed evidence on fairness concerns. Although we cannot directly test for perceptions of increased productivity monitoring, this explanation seems most consistent with our results. Implications are also discussed.

Week 11 – Reading Summary – Tambe and Hitt (2014) – Xi Wu

Tambe, P., & Hitt, L. M. (2014). Job Hopping, Information Technology Spillovers, and Productivity Growth. Management Science, 60(2), 338–355.

Like earlier general-purpose technology such as electricity or the steam engine, researchers argued that information technology (IT) investments generate productivity “spillovers” among firms, and the movement of IT workers among firms is believed to be an important mechanism by which IT-related innovations diffuse throughout the economy. In this paper, the authors use employee microdata obtained from an online resume database to test the hypothesis that firms benefit from the IT investment of other firms because the flow of specialized technical know-how among organizations facilitates the implementation of new IT innovations.

Based on the literature on the impact of R&D spillovers and IT investment on productivity, this study modeled the knowledge available to the focal firm as the weighted sum of the knowledge of other firms in the sample, and the transfer of IT-related knowledge occurs through the mobility of workers. Two IT investment measures are applied: IT capital stock-based measure and IT labor-based measure. The external IT pool measure is computed as the IT intensity of other firms. OLS and Fixed Effect model are used to support the hypothesis of productivity spillover effect through the IT labor flow. This study also compares the benefits through IT labor flow with that through the IT investments of geographically proximate firms, the estimators indicate that regional spillovers appear to be driven by IT labor flows, and IT labor flows appear to be an important source of spillovers even outside a fixed region.

This study is the first to analyze how IT labor flows drive IT spillovers and, to investigate this issue using microdata on labor mobility.  It suggests that a substantial amount of variation in IT returns can be explained by productivity spillovers generated by IT labor flows.


Week 11 -Reading Summary – Leting Zhang

Atasoy, H., Banker, R. D., & Pavlou, P. A. (2016). On the Longitudinal Effects of IT Use on Firm-Level Employment. Information Systems Research, 27(1), 6-26.

This study examines how IT use affect firm-level employment, more specifically, how web and enterprise applications differentially play a role in the firm’s employment, how firm size, the average skill level of its employees,  industry technology intensity, as moderators influence IT impacts on employment.

In the theory part, the paper specifies three mechanisms behind this impact: productivity gains, make versus buy decisions, labor complementarity versus substitution. then differentiating enterprise applications and web applications, because the implementation of enterprise applications require more investments and organizational change, so it takes more time to materialize them compared to web applications. Next, it illustrates moderator’s role, specifically, the materialization of IT is more slowly in larger firms; IT use would have a stronger role in employment for firms with high level of skills and firms in the high-tech industry.

This study uses a firm-level survey from TurkStat which has several advantages, compared to other commonly used datasets, it is more representative, more granular and it covered smaller firms. Fixed effects model is used to examine the relationship between IT usage and employment. It also uses several strategies to deal with endogeneity, including using a series of control variables, analyzing the timing of changes in IT use and employment, and generalized propensity score. The results are robust.

The paper has several conclusions. Firstly, there is a positive relationship between IT use and firm-level employment on average; furthermore, the effect of enterprise applications is lagged, but the use of web application materialize in the current year; the longitudinal impact led by the use of enterprise application  is more salient in larger firms with higher average wages in high-tech industries, while the current effects of the use of web application are more pronounced in small firms. It provides several implications for public policy.

Week 12 Reading Summary (HK)

Bloom, N., Garicano, L., Sadun, R., & Van Reenen, J. (2014). The distinct effects of information technology and communication technology on firm organization. Management Science, 60(12), 2859-2885.

Information Communication Technologies (ICTs) have radically impacted industries and the roles of various employees. However, this impact has not been uniform across industries, positions, etc. For example, ICTs have rendered Ambassadors mute because technology now makes it relatively easy to be in contact with the actual country leaders regardless of geographic distance. On the other hand, nurses’ responsibilities and capabilities have grown immensely due to ICTs as it allows them to be able to accomplish tasks previously requiring doctors or superiors. Bloom, Caricano, Sadun, and Van Reenen (2014) propose that the differing impact of ICTs could be due to its dual-component nature; effectively, due to differences in information technologies (ITs) and communication technologies (CTs).

ITs allow employees at lower levels to make impactful decisions, such as the case with nurses, due to the increase in information readily available to them. Effectively, ITs, specifically ERPs for non-product related decisions and CAD/CAM for product decisions, allow lower level employees to gain access to information traditionally only available to high level employees at little to no costs. Furthermore, these technologies widen the manager’s span of control. On the other hand, CTs, such as intranets, lead to more centralization as it is easier to communicate and in theory could render more decisions or more verifications to higher level employees. That being said, results considering CTs are more ambiguous than those for the ITs. Overall, Bloom et al. (2014) were able to draw these conclusions by combining the CEP management and organization survey and the Harte-Hanks ICT panel to create a comprehensive dataset that spanned industries and countries. Overall, these findings help to explain the contradictory impacts of ICTs by highlighting the distinct components of ITs and CTs and their differing impacts.

Paper Summary-Jack Tong

Atasoy, H., Banker, R.D. and Pavlou, P.A., 2016. On the Longitudinal Effects of IT Use on Firm-Level Employment. Information Systems Research27(1), pp.6-26.

It is a critical question to understand how IT investment could affect the firm-level employment with argument that whether IT investment would replace human labor with automation or improve workers’ productivity, and the authors examine the longitudinal role of IT use in the firm’s total number of employees. The dataset covers firms with different sizes in various industries from Turkey and captures the firm-level applications of different enterprise software and systems such as ERP, CRM and web applications.

The empirical specifications exploit both within-firm and between-firm variations to show the positive effect of IT use on firm-level employment, which varies across IT applications over time. Interestingly, they find that the effects of the use of enterprise applications materialize after two years, whereas the effects of the use of Web applications are realized in the current year. The authors also explore the moderating role of different factors such as firm size, industry technology density, and average salary rate. They find that long-term effects of the use of enterprise applications on firm-level employment are more pronounced in larger firms, with higher average wages, and in high-technology industries.