2015
DOI: 10.2139/ssrn.2688097
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When You Work with a Super Man, Will You Also Fly? An Empirical Study of the Impact of Coworkers on Performance

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Cited by 5 publications
(4 citation statements)
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“…Second, our paper joins the growing literature in operations that uses detailed micro-level production and service data to study how environmental, social, and psychological factors can impact individual worker productivity. Recent studies have demonstrated operational policies such as scheduling and staffing (Chan et al 2014;Dai et al 2015;Huckman and Staats 2011), monitoring and transparency (Bernstein 2012;Buell et al 2016;Staats et al 2016;Tan and Netessine 2015), performance recognition (Gubler et al 2016;Song et al 2016), and workflow (Kuntz et al 2014;Staats and Gino 2012;Tan and Netessine 2014) can all profoundly impact worker performance. Even environmental factors outside managerial control, such as weather (Lee et al 2014), are being revealed as determinants of individual and group productivity.…”
Section: Introductionmentioning
confidence: 99%
“…Second, our paper joins the growing literature in operations that uses detailed micro-level production and service data to study how environmental, social, and psychological factors can impact individual worker productivity. Recent studies have demonstrated operational policies such as scheduling and staffing (Chan et al 2014;Dai et al 2015;Huckman and Staats 2011), monitoring and transparency (Bernstein 2012;Buell et al 2016;Staats et al 2016;Tan and Netessine 2015), performance recognition (Gubler et al 2016;Song et al 2016), and workflow (Kuntz et al 2014;Staats and Gino 2012;Tan and Netessine 2014) can all profoundly impact worker performance. Even environmental factors outside managerial control, such as weather (Lee et al 2014), are being revealed as determinants of individual and group productivity.…”
Section: Introductionmentioning
confidence: 99%
“…Hence peer performance is unlikely to affect primary worker productivity. Prior work examining peer effects notes that observability is a key driver of productivity (Bandiera, Barankay, & Rasul, 2010;Mas & Moretti, 2009;Tan & Netessine, 2015), and workers, in general, given our field setting, cannot easily observe other harvesters. Second, workers are unlikely to discuss their performance after the shift.…”
Section: Base Specificationmentioning
confidence: 99%
“…Various aspects of work structure-including task design, specialization, interdependence, work scheduling and sequencing-have been found to impact important outcomes, such as productivity and quality (Kc & Terwiesch, 2009;Narayanan, Balasubramanian, & Swaminathan, 2009;Song, Tucker, & Murrell, 2015;Staats & Gino, 2012). The scheduling of labor has proven to be a significant consideration for ensuring prolonged successful performance: who works, with whom they work, and when they work are important structural factors that can lead to positive performance outcomes (Huckman, Staats, & Upton, 2009;Kesavan, Staats, & Gilland, 2014;Song & Tucker, 2016;Tan & Netessine, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…Our casual dining data provide a valuable empirical setting to study whether and how a router deviates from a rule that he/she is instructed to follow and to evaluate such discretionary deviation. First, waiters are a heterogeneous group, with varying sales and speed skills (Tan and Netessine ). These variations allow us to understand how server‐related factors may contribute to a router’s discretionary assignment preferences.…”
Section: Empirical Setting Data and Variablesmentioning
confidence: 99%