{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T10:13:07Z","timestamp":1776507187029,"version":"3.51.2"},"reference-count":84,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2017,6,5]],"date-time":"2017-06-05T00:00:00Z","timestamp":1496620800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BPMJ"],"published-print":{"date-parts":[[2017,6,5]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Big data analytics (BDA) helps service providers with customer insights and competitive information. It also empowers customers with insights about the relative merits of competing services. The purpose of this paper is to address the research question, \u201cHow does big data analytics enable frontline employees (FLEs) in effective service delivery?\u201d<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The research develops schemas to visualise service contexts that potentially benefit from BDA, based on the literature drawn from BDA and FLEs streams.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The business drivers for BDA and its level of maturity vary across firms. The primary thrust for BDA is to gain customer insights, resource optimisation and efficient operations. Innovative FLEs operating in knowledge intensive and customisable settings may realise greater value co-creation.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>There exists a considerable knowledge gap in enabling the FLEs with BDA tools. Managers need to train, orient and empower FLEs to collaborate and create value with customer interactions. Service-dominant logic posits that skill asymmetry is the reason for service. So, providers need to enhance skill levels of FLEs continually. Providers also need to focus on market sensing and customer linking abilities of FLEs.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Social implications<\/jats:title>\n<jats:p>Both firms and customers need to be aware of privacy and ethical concerns associated with BDA.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>Knitting the BDA and FLEs research streams, the paper analyses the impact of BDA on service. The research by developing service typology portrays its interplay with the typologies of FLEs and BDA. The framework portrays the service contexts in which BD has major impact. Looking further into the future, the discussion raises prominent questions for the discipline.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/bpmj-12-2015-0182","type":"journal-article","created":{"date-parts":[[2017,4,28]],"date-time":"2017-04-28T07:40:33Z","timestamp":1493365233000},"page":"623-644","source":"Crossref","is-referenced-by-count":32,"title":["Does big data analytics influence frontline employees in services marketing?"],"prefix":"10.1108","volume":"23","author":[{"given":"Saradhi","family":"Motamarri","sequence":"first","affiliation":[]},{"given":"Shahriar","family":"Akter","sequence":"additional","affiliation":[]},{"given":"Venkat","family":"Yanamandram","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"78-83","key":"key2020120705083388500_ref001","first-page":"128","article-title":"Making advanced analytics work for you","volume":"90","year":"2012","journal-title":"Harvard Business 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