Feeling Watched: The Impact of Tip Visibility on Customer Engagement and Firms’ Financial Outcomes: An Abstract

Tipping, Disrupted: The Multi-Stakeholder Digital Tipped Service Journey

“…Sample calculations on paper receipts generally increase tip amounts (Karniouchina, Verma, and Mishra 2008;Seiter, Brownlee, and Sanders 2011), while service quality suggestions reduce tip variance (Strohmetz and Rind 2001). Recent research on digital payment screens finds that higher (vs. lower) levels of default tip suggestions result in higher tip amounts (Alexander, Boone, and Lynn 2021;Chandar et al 2019), though they may also reduce repatronage and cause customers to refuse tip requests (Haggag and Paci 2014;Warren et al 2021b). Except for research on tip guidelines, prior research has largely overlooked the technologies used to collect tips.…”

“…Using a digital POS system at a café alters customer-employee interactions and incorporates additional stakeholders. First, because payment screens are often mounted on counters, they are less discreet than paper bills, which can cause paying customers to feel like they are being observed (Warren, Hanson, and Yuan 2021a). This feeling could result from the presence of ambient customers, who paying customers may or may not know, from the employee processing the payment, or from ambient employees.…”

“…10-20% vs. 20-30%). Tip default level may be the most impactful, as it positively affects tip amounts (Haggag and Paci 2014) and negatively affects downstream customer responses (Warren, Hanson, and Yuan 2021b). Tipping software can include special tipping options, such as "no tip" and "0%," which may result in different outcomes (Bluvstein Netter and Raghubir 2022), or "custom" tip options, which often require extra steps to select.…”

“…A final employee-firm interaction of note is how firms use ratings to evaluate and distribute work to employees, particularly how tipped service platforms use ratings to allocate work to gig workers. Employees need to consider not only how to best elicit tips from customers but also how to elicit positive evaluations, which may or may not correlate with tip amounts (Warren, Hanson, and Yuan 2021b). Extending this suggests that some employees may pursue ratings-optimization strategies while others try to optimize tips, and that these optimization strategies vary across service platforms.…”

“…Research focusing on tip interactions should examine how these stakeholders balance competing personal and inter-stakeholder goals within the tip-selecting process. For example, employees may seek to pressure customers into providing higher tips, such as by observing while customers select tip amounts (Dyussembayeva et al 2022; Warren, Hanson, and Yuan 2021a), though employees may also feel that doing so is unfair or goes against their personal service ethics, similar to employees who experience discomfort when instructed to touch customers (Luangrath, Peck, and Gustafsson 2020). In another example, tipping platforms may need to balance customer interests in easy and choice-enabling formatting and employee interests in formats that increase tip income by presenting a limited set of high percentage default options.…”