Cargando…
Big data and business analytics adoption and use : a step toward transforming operations and production management? /
Big data analytics (BDA) is defined as a holistic approach to managing, processing and analyzing the 5V data-related dimensions (i.e., volume, variety, velocity, veracity and value) to create actionable insights for delivering sustained value, measuring performance and establishing competitive advan...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Bingley] :
[Emerald Group Publishing Limited],
2017.
|
| Colección: | International journal of operations & production management ;
v. 37, no. 1. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_ocn973325251 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 170221s2017 enk o 000 0 eng d | ||
| 040 | |a N$T |b eng |e rda |e pn |c N$T |d IDEBK |d EBLCP |d N$T |d YDX |d N$T |d OCLCF |d OCLCQ |d OCLCO |d OCLCQ |d OCLCO |d OCLCL |d OCLCQ | ||
| 019 | |a 973532332 |a 973774662 |a 973809327 |a 973913881 |a 974031495 |a 974362128 |a 974444318 |a 974565331 | ||
| 020 | |a 9781787142855 |q (electronic bk.) | ||
| 020 | |a 178714285X |q (electronic bk.) | ||
| 020 | |z 9781787142848 | ||
| 029 | 1 | |a AU@ |b 000068480857 | |
| 035 | |a (OCoLC)973325251 |z (OCoLC)973532332 |z (OCoLC)973774662 |z (OCoLC)973809327 |z (OCoLC)973913881 |z (OCoLC)974031495 |z (OCoLC)974362128 |z (OCoLC)974444318 |z (OCoLC)974565331 | ||
| 050 | 4 | |a HD30.215 | |
| 072 | 7 | |a BUS |x 082000 |2 bisacsh | |
| 072 | 7 | |a BUS |x 041000 |2 bisacsh | |
| 072 | 7 | |a BUS |x 042000 |2 bisacsh | |
| 072 | 7 | |a BUS |x 085000 |2 bisacsh | |
| 082 | 0 | 4 | |a 658.4033 |2 23 |
| 049 | |a UAMI | ||
| 245 | 0 | 0 | |a Big data and business analytics adoption and use : |b a step toward transforming operations and production management? / |c guest editors, Samuel Fosso Wamba, Eric W.T. Nagai, Frederick Riggins, and Shahriar Akter. |
| 264 | 1 | |a [Bingley] : |b [Emerald Group Publishing Limited], |c 2017. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a International journal of operations & production management ; |v volume 37, number 1 | |
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed March 8, 2017). | |
| 520 | |a Big data analytics (BDA) is defined as a holistic approach to managing, processing and analyzing the 5V data-related dimensions (i.e., volume, variety, velocity, veracity and value) to create actionable insights for delivering sustained value, measuring performance and establishing competitive advantages (Fosso Wamba et al., 2015). BDA has captured the imagination of both practitioners and scholars for its high operational and strategic potentials across various industries including marketing, financial services, insurance, retailing, healthcare, and manufacturing. For example, manufacturing firms including GE, Rolls Royce and Ford have been successfully using BDA for maintenance (e.g., engine failures) and supplier risk management (Jobs et al., 2015). BDA has also improved business intelligence on the behaviour of customers as well as consumer profiling (European Commission, 2013). As such, the extant literature identifies big data as the "next big thing in innovation" (Gobble, 2013, p.64), "the fourth paradigm of science" (Strawn, (2012), or "the next frontier for innovation, competition, and productivity" (Manyika et al., 2011, p.1). The papers comprise seven standalone research articles. Five articles are published in this issue: Kache and Seuring (2017), Matthias et al. (2017), Sykes et al. (2017), Mehmood et al. (2017), and Ramanathan et al. (2017). The remaining articles are published in IJOPM regular issues and are Aloysius et al. (2016), and Chong et al. (2016). | ||
| 505 | 0 | |a Cover ; Editorial board ; Guest editorial ; Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management; Making sense of Big Data -- can it transform operations management? ; Big data breaches and customer compensation strategies; Exploring the influence of big data on city transport operations: a Markovian approach ; Role of social media in retail network operations and marketing to enhance customer satisfaction | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Decision making |x Data processing. | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Prise de décision |x Informatique. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Industrial Management. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Management. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Management Science. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Organizational Behavior. |2 bisacsh | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Decision making |x Data processing |2 fast | |
| 700 | 1 | |a Wamba, Samuel Fosso, |e editor. | |
| 758 | |i has work: |a Big data and business analytics adoption and use (Text) |1 https://id.oclc.org/worldcat/entity/E39PCYwM8KwfbcTM8VM9RJmR4y |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 830 | 0 | |a International journal of operations & production management ; |v v. 37, no. 1. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4810481 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL4810481 | ||
| 938 | |a EBSCOhost |b EBSC |n 1470837 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis37676748 | ||
| 938 | |a YBP Library Services |b YANK |n 13511952 | ||
| 994 | |a 92 |b IZTAP | ||