@article {Johnson2020,
	title = {The benefits of eHRM and AI for talent acquisition},
	journal = {Journal of Tourism Futures},
	year = {2020},
	abstract = {Purpose : The hospitality and tourism industry faces a number of workforce challenges, especially the high turnover rates and associated replacement costs associated with continually identifying and hiring new employees. The purpose of this paper is to discuss how hospitality and tourism organizations can use electronic human resource management (eHRM) and artificial intelligence (AI) to help recruit and select qualified employees, increase individual retention rates and decrease the time needed to replace employees. Specifically, it discusses how e-recruiting and e-selection and AI tools can help hospitality and tourism organizations improve recruiting and selection outcomes. Design/methodology/approach: Research on eHRM, AI, employee recruitment and employee selection are applied to the hospitality and tourism industry and insights for how eHRM and AI can be applied to the industry are discussed. Findings: eHRM and AI have the potential to transform how the hospitality and tourism industry recruit and select employees. However, care must be taken to ensure that the insights gained and the decisions made are well received by employees and lead to better employee and organizational outcomes. Research limitations/implications: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry. Originality/value: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.},
	keywords = {artificial intelligence, e-HRM, e-recruiting, e-selection, eHRM, Electronic human resource management, Employee selection, Recruitment, Selection},
	issn = {2055592X},
	doi = {10.1108/JTF-02-2020-0013},
	author = {Johnson, Richard D and Stone, Dianna L and Lukaszewski, Kimberly M}
}
@article {2019,
	title = {Behavioural artificial intelligence: An agenda for systematic empirical studies of artificial inference},
	journal = {AI \& SOCIETY},
	year = {2019},
	month = {Jun-12-2020},
	issn = {0951-5666},
	doi = {10.1007/s00146-019-00928-5},
	author = {Pedersen, Tore and Johansen, Christian}
}
@book {2019,
	title = {Benefits and risks of artificial intelligence tools in workplaces},
	volume = {11581},
	year = {2019},
	pages = {292 - 315},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-22215-4},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-22216-1_22},
	author = {Moore, Phoebe V.},
	editor = {Duffy, Vincent G.}
}
@conference {2019,
	title = {Beyond Dyadic Interactions: Considering Chatbots as Community Members},
	booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems  - CHI {\textquoteright}19},
	year = {2019},
	pages = {1-13},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Glasgow, Scotland UK},
	isbn = {9781450359702},
	doi = {10.1145/3290605},
	author = {Seering, Joseph and Luria, Michal and Kaufman, Geoff and Hammer, Jessica}
}
@article {2019,
	title = {Blame the boss, not the robot},
	journal = {New Labor Forum},
	volume = {28},
	year = {2019},
	month = {Oct-05-2020},
	pages = {66 - 69},
	issn = {1095-7960},
	doi = {10.1177/1095796019837947},
	author = {Smith, Zachary}
}
@article {2019,
	title = {Bots Coordinating Work in Open Source Software Projects},
	journal = {Computer},
	volume = {52},
	year = {2019},
	month = {Jan-09-2019},
	pages = {52 - 60},
	issn = {0018-9162},
	doi = {10.1109/MC.2018.2885970},
	author = {Hukal, Philipp and Berente, Nicholas and Germonprez, Matt and Schecter, Aaron}
}
@article {2019,
	title = {A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence},
	journal = {California Management Review},
	volume = {61},
	year = {2019},
	month = {Sep-08-2019},
	pages = {5 - 14},
	issn = {0008-1256},
	doi = {10.1177/0008125619864925},
	author = {Haenlein, Michael and Kaplan, Andreas}
}
@article {2018,
	title = {{\textquoteleft}The beginning of a wave{\textquoteright}: A.I. Tiptoes into the workplace},
	journal = {The NewYork Times},
	year = {2018},
	keywords = {AI, impacts},
	url = {https://www.nytimes.com/2018/08/05/technology/workplace-ai.html},
	author = {Steve Lohr}
}
@article {2018,
	title = {Beyond r\&d: The role of embodied technological change in affecting employment},
	year = {2018},
	keywords = {Innovation; R\&D; Embodied Technological Change; Employment; GMM-SY},
	issn = {2284-0400},
	url = {https://ideas.repec.org/p/ssa/lemwps/2018-15.html},
	author = {Gabriele Pelleegrino and Mariacristina Piva and Marco Vivarelli}
}
@article {2018,
	title = {Boundary spanning at the science{\textendash}policy interface: the practitioners{\textquoteright} perspectives},
	journal = {Sustainability Science},
	volume = {13},
	year = {2018},
	month = {Jan-07-2018},
	pages = {1175 - 1183},
	issn = {1862-4065},
	doi = {10.1007/s11625-018-0550-9},
	author = {Bednarek, A. T. and Wyborn, C. and Cvitanovic, C. and Meyer, R. and Colvin, R. M. and Addison, P. F. E. and Close, S. L. and Curran, K. and Farooque, M. and Goldman, E. and Hart, D. and Mannix, H. and McGreavy, B. and Parris, A. and Posner, S. and Robinson, C. and Ryan, M. and Leith, P.}
}
@article {2017,
	title = {Big data and organizational design {\textendash} the brave new world of algorithmic management and computer augmented transparency},
	journal = {Innovation},
	volume = {19},
	year = {2017},
	month = {Feb-01-2017},
	pages = {23 - 30},
	issn = {1447-9338},
	doi = {10.1080/14479338.2016.1252043},
	author = {Schildt, Henri}
}
@book {2017,
	title = {Big Data in Organizations and the Role of Human Resource Management},
	year = {2017},
	url = {https://www.jstor.org/stable/j.ctv9hj9z6.1},
	author = {Peter Lang}
}
@proceedings {9999,
	title = {Blending machine and human learning processes},
	year = {2017},
	abstract = {<p>Citizen science projects rely on contributions from volunteers to achieve their scientific goals and so face a dilemma: providing volunteers with explicit training might increase the quality of contributions, but at the cost of losing the work done by newcomers during the training period, which for many is the only work they will contribute to the project. Based on research in cognitive science on how humans learn to classify images, we have designed an approach to use machine learning to guide the presentation of tasks to newcomers that help them more quickly learn how to do the image classification task while still contributing to the work of the project. A Bayesian model for tracking this learning is presented.</p>},
	doi = {10.24251/HICSS.2017.009},
	url = {http://hdl.handle.net/10125/41159},
	attachments = {https://waim.network/sites/crowston.syr.edu/files/training\%20v3\%20to\%20share_0.pdf},
	author = {Kevin Crowston and Carsten {\O}sterlund and Lee, Tae Kyoung}
}
@book {2015,
	title = {The big move toward big data in employment},
	series = {Employment\& Labor Law Solutions Worldwide},
	year = {2015},
	publisher = {Littler Mendelson, P.C.},
	organization = {Littler Mendelson, P.C.},
	url = {https://www.littler.com/files/wp_big_data_8-04-15.pdf},
	author = {Aaron Crews}
}
@article {2014,
	title = {Beyond motivation: Job and work design for development, health, ambidexterity, and more},
	journal = {Annual Review of Psychology},
	volume = {65},
	year = {2014},
	month = {Mar-01-2014},
	pages = {661 - 691},
	issn = {0066-4308},
	doi = {10.1146/annurev-psych-010213-115208},
	author = {Parker, Sharon K.}
}
@article {918,
	title = {Beyond Big Data},
	year = {2013},
	url = {http://people.ischool.berkeley.edu/~hal/Papers/2013/BeyondBigDataPaperFINAL.pdf},
	author = {Hal R. Varian}
}
@article {2013,
	title = {Beyond convergence of Nano-Bio-Info-Cognitive technologies},
	year = {2013},
	month = {07/2013},
	url = {http://www.wtec.org/NBIC2/Docs/FinalReport/Pdf-secured/NBIC2-FinalReport-WEB.pdf},
	author = {Mihail C. Roco and William S. Bainbridge and Bruce Tonn and George Whitesides}
}
@article {RN2496,
	title = {Bringing work back in},
	journal = {Organization Science},
	volume = {12},
	number = {1},
	year = {2001},
	pages = {76{\textendash}95},
	type = {Journal Article},
	doi = {10.1287/orsc.12.1.76.10122},
	author = {Stephen R. Barley and Kunda, Gideon}
}
