|
Elektron tijoratda katta ma'lumotlar tahlili: tizimli ko'rib chiqish va kelajakdagi tadqiqotlar uchun kun tartibi-ilova: Elektron tijoratda katta ma'lumotlar tahlilining (BDA) aniq jihatlari
|
səhifə | 5/11 | tarix | 23.04.2023 | ölçüsü | 119,05 Kb. | | #106749 |
| dissertatsiya uchun1-ilova: Elektron tijoratda katta ma'lumotlar tahlilining (BDA) aniq jihatlari
Study
|
Potential research areas
|
Definition
|
Purpose
|
Davenport (2006)
|
E-commerce functions: production and operations (e.g., supply chain flows), marketing (e.g., promotion), human resources (e.g., employee performance), finance (e.g., controlling fraud), and research and development (R&D).
|
BDA refers to based’ analysis making.
|
‘quantitative fact- aiding decision
|
Analytics advantage.
|
to
|
gain
|
competitive
|
Davenport
|
and
|
E-commerce functions: finance (e.g., merger &
|
BDA refers to the use of data,
|
Analytics to help build distinctive
|
Harris (2007b)
|
|
acquisition), manufacturing, R&D, human resources
(e.g., hire, retain, and promote the best people),
|
statistical and quantitative analysis
through explanatory and predictive
|
capabilities in an intensely
competitive business environment.
|
|
|
marketing (e.g., identifying profitable and loyal
|
models for facilitating fact-based
|
|
|
|
customers), and supply chain (e.g., lowest possible
|
management decisions and actions.
|
|
|
|
inventory without compromising stockouts).
|
|
|
Bose (2009)
|
E-commerce functions including: marketing (direct marketing, customer segmentation, pricing), supply chain (choice of channel partners), and finance (customer profitability analysis).
|
BDA refers to a group of tools used in combination to gain insights in order to direct, optimize, and
automate decision making for achieving organizational goals.
|
Assisting business managers to effectively understand the drivers behind advanced analytics implementation.
|
Shanks et al. (2010)
|
Functional areas including: production and operations (sales forecasts, production plans, order deliveries) and marketing (customer attrition, customer profitability, response rate of marketing campaigns,
differential pricing, etc.).
|
BDA refers to data interpretation to generate insights that improve decision making, and optimize business processes.
|
Technology and capabilities using analytics lead to value-creating actions to improve firm performance and competitive
advantage.
|
Manyika et al. (2011)
|
All e-commerce functions including: operations, and the supply chain.
|
marketing,
|
BDA creates value by creating transparency, discovering needs, exposing variability, and improving
performance.
|
Potential value of big data for organizations and the economy, outlining the ways to capture that
value.
|
LaValle et al. (2011)
|
All e-commerce functions including: marketing (loyalty/retention/defection), finance (e.g., budgeting, revenue growth, cost efficiency), human resources management (workforce planning/allocation), operations and production.
|
BDA is about insights—descriptive, predictive, and prescriptive—to deliver actions that are closely linked to business strategy and to organizational processes that take place at the right time.
|
Insightful evidence to help organizations understand the opportunity provided by information and advanced analytics.
|
Agarwal and Weill (2012)
|
Data in conjunction with emotion significantly strengthen the firm’s analytical ability for marketing (e.g., customer empowerment), human resources (e.g., employee empowerment), and supply chain (channel
|
Dostları ilə paylaş: |
|
|