مقاله انگلیسی رایگان در مورد تحلیل داده ها و عملکرد شرکت: پلت فرم B2C آنلاین – الزویر ۲۰۱۸

elsevier

 

مشخصات مقاله
ترجمه عنوان مقاله تحلیل داده ها و عملکرد شرکت: یک مطالعه تجربی در پلت فرم B2C آنلاین
عنوان انگلیسی مقاله Data analytics and firm performance: An empirical study in an online B2C platform
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۱۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) scopus – master journals – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF) ۳٫۸۹۰ در سال ۲۰۱۷
شاخص H_index ۱۳۵ در سال ۲۰۱۸
شاخص SJR ۱٫۶۲۸ در سال ۲۰۱۸
رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت کسب و کار، مدیریت عملکرد، مدیریت فناوری اطلاعات
نوع ارائه مقاله ژورنال
مجله / کنفرانس اطلاعات و مدیریت – Information & Management
دانشگاه  School of Business – Nanjing University – Nanjing – China
کلمات کلیدی تحلیل داده ها، ارزش کسب و کار، انواع محصولات، شدت رقابت، پلت فرم آنلاین
کلمات کلیدی انگلیسی Data analytics, Business value, Product variety, Competitive intensity, Online platform
شناسه دیجیتال – doi
https://doi.org/10.1016/j.im.2018.01.004
کد محصول E9381
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
۱ Introduction
۲ Theoretical background
۳ Hypotheses development
۴ Research methodology
۵ Data analysis and results
۶ Discussion
References

بخشی از متن مقاله:
ABSTRACT

Data analytics has become an increasingly eye-catching practice in both the academic and the business communities. The importance of data analytics has also prompted growing literature to focus on the design of data analytics. However, the boundary conditions for data analytics in creating value have been largely overlooked in the literature. The objective of this article therefore is to examine the business value of data analytics usage and explore how such value differs in different market conditions. We rely on an online B2C platform as our empirical setting and obtain several important insights. First, both demand-side and supply-side data analytics usage has a positive effect on the performance of merchants. Second, when merchants’ product variety is high, the influence of usage toward demand-side data on performance is strengthened, whereas such impact is weakened for supply-side data analytics. Third, when competitive intensity is high, the performance implication of demand-side data analytics usage is strengthened, whereas such impact is not strengthened for supply-side data analytics. This study contributes by advancing the overall understanding of business value of data analytics.

Introduction

With dramatic advancement in data collecting, storage, and processing technologies in recent decades, organizations worldwide are exploring new data-enabled ways to compete and win—transforming themselves to take advantage of the vast array of available data to improve decision-making and performance [1–۳]. These new opportunities have led many managers to rely less on business decision-making process and more on data itself in their decision-making [4,5]. Data analytics, therefore, has become an increasingly eye-catching practice in both academic and the business communities, and industry studies have highlighted this significant development. For example, on the basis of a survey of over 4000 information technology (IT) professionals from 93 countries and 25 industries, the IBM Tech Trends Report [6] identified business analytics as one of the four major technology trends in the 2010s. In a survey of the state of data analytics by Bloomberg Businessweek [7], 97% of companies with revenues exceeding US$100 million were found to use some form of data analytics [8]. The importance of data analytics has also prompted growing literature to focus on the design of data analytics for generating knowledge and intelligence to support decision-making and strategic objectives [3,9,10]. For example, Bardhan et al. [11] demonstrated that using health IT-related data could help hospitals save millions of dollars by avoiding costly readmission-related penalties. Martens et al. [9] examined the use of massive, fine-grained data on consumer behavior to improve predictive models for targeted marketing. Guo et al. [3] proposed a system framework for extracting representative information from intra-organizational blogging platforms. The puzzle, however, is why not all firms have implemented this practice? The stream of IT business value research points that value creation process of technological innovations in a firm cannot depart from how to use them [12,13]. For example, Devaraj and Kohli [14] posited and proved that the actual usage of technology is a key variable to explain the impact of IT application on organizational performance.

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