George L. Zheng

Employees in organizations are frequently subject to performance goals such as sales or publication targets. However, often employees do not know what actions will allow them to meet these goals. To perform such tasks effectively, employees need to explore to quickly learn from experience which among the available alternatives offers the higher reward potential, so that they can concentrate subsequent efforts on exploiting it. Prior work models such explore-exploit problems as an adaptive learning process, where employees sequentially sample various options and learn from feedback. However, we currently do not know how performance goals influence this adaptive learning process. We argue that performance goals influence the adaptive learning process by modifying how feedback is perceived. Individuals subject to challenging goals are more likely to interpret feedback from poor alternatives as failures. Therefore, they quickly develop high belief strength that the inferior alternative is worse than the superior alternative, enabling them to reduce “useless exploration,” but also making them slow to adapt to environmental shocks. We test our predictions in a series of laboratory experiments and find that decision makers subject to challenging goals exploit more (relative to those with moderate goals). We also show that such an exploitation focus, while beneficial in stable environments, is detrimental in unstable ones. Our finding that challenging performance goals improve performance in learning tasks stands in contrast to prior findings that such goals inhibit performance in search tasks, an insight that warrants further study to improve our understanding of goal setting in the knowledge economy. History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory. Funding: K. Srikanth was supported by SMU Seed Funding Grant for the initial version of this paper. Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2019.13311 .

Campus energy management increasingly demands a controlled and managed process for achieving the aims of cost control and operation effectiveness. A mature decision making process is driven by data gathering, analysis and reporting, as advocated by business intelligence (BI), which already has had broad impact on enterprises. The BI process has been widely adopted by universities in a number of areas already, including student services (enrollment) but less so in supporting areas like energy management. This paper describes an initial effort to apply BI practices to manage energy (starting with electric power) consumption on campuses, beginning with a needs assessment to develop an effective energy usage data gathering (in real-time), modeling, analysis and reporting process on our own campus. We provide details on how the situation was at the beginning of our four-month project, and on the improvements we were able to make to the campus' energy management process.