At Your Service on the Table: Impact of Tabletop Technology on Restaurant Performance

References

• Albright S, Winston WL (2014) Business Analytics: Data Analysis & Decision Making (Nelson Education, Ontario, Canada).Google Scholar
• Allon G, Federgruen A, Pierson M (2011) How much is a reduction of your customers’ wait worth? an empirical study of the fast-food drive-thru industry based on structural estimation methods. Manufacturing Service Oper. Management 13(4):419–563.Google Scholar
• Aral S, Brynjolfsson E, Van Alstyne M (2012) Information, technology, and information worker productivity. Inform. Systems Res. 23(3-part-2):849–867.Google Scholar
• Argote L, Epple D (1990) Learning curves in manufacturing. Science 247(4945):920–924.Crossref, Google Scholar
• Baertlein L (2017) Chipotle says hackers hit most restaurants in data breach. Reuters (May 26), http://www.reuters.com/article/us-chipotle-cyber-idUSKBN18M2BY.Google Scholar
• Bavafa H, Hitt LM, Terwiesch C (2018) The impact of e-visits on visit frequencies and patient health: Evidence from primary care. Management Sci. 64:(12):5461–5480.Google Scholar
• Bertrand M, Duflo E, Mullainathan S (2004) How much should we trust differences-in-differences estimates? Quart. J. Econom. 119(1):249–275.Google Scholar
• Bresnahan TF, Brynjolfsson E, Hitt LM (2002) Information technology, workplace organization, and the demand for skilled labor: Firm-level evidence. Quart. J. Econom. 117(1):339–376.Crossref, Google Scholar
• Brynjolfsson E, Hitt LM (1996) Paradox lost? Firm-level evidence on the returns to information systems spending. Management Sci. 42(4):541–558.Link, Google Scholar
• Brynjolfsson E, Hitt LM (2000) Beyond computation: Information technology, organizational transformation and business performance. J. Econom. Perspect. 14(4):23–48.Crossref, Google Scholar
• Brynjolfsson E, Hitt LM (2003) Computing productivity: Firm-level evidence. Rev. Econom. Statist. 85(4):793–808.Crossref, Google Scholar
• Campbell D, Frei F (2010) Cost structure, customer profitability, and retention implications of self-service distribution channels: Evidence from customer behavior in an online banking channel. Management Sci. 56(1):4–24.Link, Google Scholar
• Card D, Krueger AB (2000) Minimum wages and employment: A case study of the fast-food industry in New Jersey and Pennsylvania. [reply] Amer. Econom. Rev. 90(5):1397–1420.Crossref, Google Scholar
• CBInsights (2017) The future of dining: 89+ startups reinventing the restaurant in one infographic. CBInsights (April 29), https://www.cbinsights.com/research/restaurant-tech-market-map-company-list/.Google Scholar
• Chuang HH, Oliva R, Perdikaki O (2016) Traffic-based labor planning in retail stores. Production Oper. Management 25(1):96–113.Crossref, Google Scholar
• Chwelos P, Benbasat I, Dexter AS (2001) Empirical test of an edi adoption model. Inform. Systems Res. 12(3):304–321.Link, Google Scholar
• Dewan S, Kraemer KL (2000) Information technology and productivity: Evidence from country-level data. Management Sci. 46(4):548–562.Link, Google Scholar
• Dewan S, Min C (1997) The substitution of information technology for other factors of production: A firm level analysis. Management Sci. 43(12):1660–1675.Link, Google Scholar
• Gandhi P, Khanna S, Ramaswamy S (2016) Which industry are the most digital (and why)? Harvard Bus. Rev. (April 1), https://hbr.org/2016/04/a-chart-that-shows-which-industries-are-the-most-digital-and-why.Google Scholar
• Gao F, Su X (2018) Omnichannel service operations with online and offline self-order technology. Management Sci. 64(8):3469–3970.Link, Google Scholar
• Gatignon H, Robertson TS (1989) Technology diffusion: An empirical test of competitive effects. J. Marketing 53:35–49.Crossref, Google Scholar
• Gray PH, MeGray DB (2004) Knowledge sourcing effectiveness. Management Sci. 50(6):821–834.Link, Google Scholar
• Hansen BB (2004) Full matching in an observational study of coaching for the SAT. J. Amer. Statist. Assoc. 99(467):609–618.Crossref, Google Scholar
• Hitt LM, Brynjolfsson E (1996) Productivity, business profitability, and consumer surplus: Three different measures of information technology value. Management Inform. Systems Quart. 20(2):121–142.Crossref, Google Scholar
• Hitt LM, Tambe P (2016) Health Care information technology, work organization, and nursing home performance. ILR Rev. 69(4):834–859.Crossref, Google Scholar
• Iacovou CL, Benbasat I, Dexter AS (1995) Electronic data interchange and small organizations: Adoption and impact of technology. Management Inform. Systems Quart. 19(4):465–485.Crossref, Google Scholar
• Jerath K, Kumar A, Netessine S (2015) An information stock model of customer behavior in multichannel customer support services. Manufacturing Service Oper. Management 17(3):368–383.Link, Google Scholar
• Kandel E, Lazear EP (1992) Peer pressure and partnerships. J. Political Econom. 100(4):801–817.Crossref, Google Scholar
• Kimes SE, Robson SKA (2004) The impact of restaurant table characteristics on meal duration and spending. Cornell Hotel Restaurant Admin. Quart. 45(4):333–346.Crossref, Google Scholar
• Kimes SE, Thompson GM (2004) Restaurant revenue management at Chevys: Determining the best table mix. Decision Sci. 35(3):371–392.Crossref, Google Scholar
• Kuziemko I, Buell RW, Reich T, Norton MI (2014) Last-place aversion: Evidence and redistributive implications. Quart. J. Econom. 129(1):105–149.Crossref, Google Scholar
• Landsberger HA (1957) Hawthorne Revisited: A Plea for an Open City (Cornell University, Ithaca, NY).Google Scholar
• Lapré MA, Mukherjee AS, Van Wassenhove LN (2000) Behind the learning curve: Linking learning activities to waste reduction. Management Sci. 46(5):597–611.Link, Google Scholar
• Lee MK, Verma R, Roth A (2015) Understanding customer value in technology-enabled services: A numerical taxonomy based on usage and utility. Service Sci. 7(3):227–248.Link, Google Scholar
• Lorden A, Pant G (2015) 17th annual restaurant technology study. Accessed August 12, 2019, https://hospitalitytech.com/2015-restaurant-technology-study.Google Scholar
• Lu SF, Lu LX (2017) Do mandatory overtime laws improve quality? Staffing decisions and operational flexibility of nursing homes. Management Sci. 63(11):3531–3997.Link, Google Scholar
• Lu SF, Rui H, Seidmann A (2017) Does technology substitute for nurses? Staffing decisions in nursing homes. Management Sci. 64(4):1842–1859.Link, Google Scholar
• Mani V, Kesavan S, Swaminathan JM (2015) Estimating the impact of understaffing on sales and profitability in retail stores. Production Oper. Management 24(2):201–218.Google Scholar
• Mas A, Moretti E (2009) Peers at work. Amer. Econom. Rev. 99(1):112–145.Crossref, Google Scholar
• Meyer D (2008) Setting the Table: The Transforming Power of Hospitality in Business (Harper Paperbacks, New York).Google Scholar
• Miller AR, Tucker CE (2011) Can healthcare information technology save babies? J. Political Econom. 119(2):289–324.Crossref, Google Scholar
• Mogavero D, A’agnese J (2016) The Underground Culinary Tour: How the New Metrics of Today’s Top Restaurants Are Transforming How America Eats (Crown Business, New York).Google Scholar
• National Restaurant Association (2017) Restaurant industry pocket factbook, National Restaurant Association, Washington, DC.Google Scholar
• Pierce L, Snow DC, McAfee A (2015) Cleaning house: The impact of information technology monitoring on employee theft and productivity. Management Sci. 61(10):2299–2319.Link, Google Scholar
• Rajan B, Seidmann A, Dorsey E (2013) The competitive business impact of using telemedicine for the treatment of patients with chronic conditions. J. Management Inform Systems 30(2):127–158.Crossref, Google Scholar
• Ren F, Dewan S (2015) Industry-level analysis of information technology return and risk: What explains the variation? J. Management Inform. Systems 32(2):71–103.Crossref, Google Scholar
• Roels G, Su X (2013) Optimal design of social comparison effects: Setting reference groups and reference points. Management Sci. 60(3):606–627.Link, Google Scholar
• Schultze U, Orlikowski WJ (2004) A practice perspective on technology-mediated network relations: The use of Internet-based self-serve technologies. Inform. Systems Res. 15(1):87–106.Link, Google Scholar
• Shafer SM, Nembhard DA, Uzumeri MV (2001) The effects of worker learning, forgetting, and heterogeneity on assembly line productivity. Management Sci. 47(12):1581–1732.Link, Google Scholar
• Singh S (2015) Future of automotive aftermarket and car servicing: Consumers will have more channels to shop around. Forbes (June 2), https://www.forbes.com/sites/sarwantsingh/2015/06/02/future-of-automotive-aftermarket-and-car-servicing-consumers-will-have-more-channels-to-shop-around/#327f019827f8.Google Scholar
• Staats BR, Dai H, Hofmann D, Milkman KL (2016) Motivating process compliance through individual electronic monitoring: An empirical examination of hand hygiene in healthcare. Management Sci. 63(5):1271–1656.Google Scholar
• Susskind AM, Curry B (2016) An examination of customers’ attitudes about tabletop technology in full-service restaurants. Service Sci. 8(2):203–217.Link, Google Scholar
• Tambe P, Hitt LM (2012) The productivity of information technology investments: New evidence from it labor data. Inform. Systems Res. 23(3-part-1):599–617.Google Scholar
• Tan TF, Netessine S (2014a) The implications of worker behavior for staffing decisions: Empirical evidence and best practices. Cornell Hospital Quart. 55(3):277–286.Crossref, Google Scholar
• Tan TF, Netessine S (2014b) When does the devil make work? An empirical study of the impact of workload on worker productivity. Management Sci. 60(6):1351–1616.Link, Google Scholar
• Tan TF, Netessine S (2019) When you work with a Superman, will you also fly? An empirical study of the impact of coworkers on performance. Management Sci. 65(8):3449–3947.Google Scholar
• Tan TF, Staats B (2017) Behavioral drivers of routing decisions: Evidence from restaurant table assignment. Working paper, Cox Business School, Dallas, TX.Google Scholar
• Thompson GM (2004) Planning-interval duration in labor-shift scheduling. Cornell Hotel Restaurant Admin. Quart. 45(2):145–157.Crossref, Google Scholar
• Thompson GM (2007) Restaurant capacity effectiveness: Leaving money on the tables. Cornell Hospitality Report 7(7):6–13.Google Scholar
• Xu Y, Armony M, Ghose A (2017) The interplay between online reviews and physician demand: An empirical investigation. Working paper, Gies College of Business, Champaign, IL.Google Scholar
• Xue M, Hitt LM, Chen P (2011) Determinants and outcomes of Internet banking adoption. Management Sci. 57(2):291–307.Link, Google Scholar
• Yu Q, Shunko M, Mankad S (2017) A quality value chain network: Linking supply chain quality to customer lifetime value. Research paper, Kelley School of Business, Bloomington, IN.Google Scholar