Big Data and Firm Performance: An Outside-in Approach

被引:5
作者
Jaber, Faten [1 ]
Abbad, Muneer [2 ]
机构
[1] Oxford Brookes Univ, Oxford, England
[2] Community Coll Qatar, Doha, Qatar
关键词
Big data analytics; CRM; market information processing; customer relationship; performance; strategy; resources; MARKET ORIENTATION; DATA ANALYTICS; CAPABILITIES; MANAGEMENT; RESOURCES; FRAMEWORK; STRATEGY; QUALITY; ASSETS;
D O I
10.1080/08874417.2021.1927240
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Little research has been undertaken into how marketing capabilities can leverage on big data analytics to improve firm performance. This study investigates whether ancustomer relationship management (CRM) linking capabilities can leverage big data analytics and organizational resources to improve firm performance. Structural equation modeling was used to analyze data collected from 315 employees in Jordanian companies. The results indicate that big data analytics presented through the amalgamation of data, technology, and human skills have a strong impact on CRM linking capabilities. Also, market information processing capabilities combining customer-focus and inter-functional coordination for knowledge interpretation also have a positive effect on CRM linking capabilities. CRM linking consequently has a positive impact on multi-dimensional firm performance. This study contributes to the field of big data through its adoption of an outside-in approach that integrates a range of capabilities into an integrative framework that delineates the process of successful big data.
引用
收藏
页码:850 / 862
页数:13
相关论文
共 83 条
[41]  
Hair J. F., 2010, Multivariate data analysis: A global perspective, DOI DOI 10.1016/J.IJPHARM.2011.02.019
[42]   Mediating effects of individual market orientation on the link between learning orientation and job performance [J].
Hamzah, Muhammad Iskandar ;
Othman, Abdul Kadir ;
Hassan, Faridah .
JOURNAL OF BUSINESS & INDUSTRIAL MARKETING, 2020, 35 (04) :655-668
[43]   Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications [J].
Hazen, Benjamin T. ;
Boone, Christopher A. ;
Ezell, Jeremy D. ;
Jones-Farmer, L. Allison .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 154 :72-80
[44]   A new criterion for assessing discriminant validity in variance-based structural equation modeling [J].
Henseler, Jorg ;
Ringle, Christian M. ;
Sarstedt, Marko .
JOURNAL OF THE ACADEMY OF MARKETING SCIENCE, 2015, 43 (01) :115-135
[45]  
Hooley G., 1998, J STRATEG MARK, V6, P97, DOI DOI 10.1080/09652549800000003
[46]   The performance impact of marketing resources [J].
Hooley, GJ ;
Greenley, GE ;
Cadogan, JW ;
Fahy, J .
JOURNAL OF BUSINESS RESEARCH, 2005, 58 (01) :18-27
[47]  
HUNT SD, 1995, J MARKETING, V59, P1, DOI 10.1177/002224299505900201
[48]  
Jaber F, 2017, J STRATEG MARK, V25, P475, DOI 10.1080/0965254X.2016.1149212
[49]   Innovation, organizational learning, and performance [J].
Jimenez-Jimenez, Daniel ;
Sanz-Valle, Raquel .
JOURNAL OF BUSINESS RESEARCH, 2011, 64 (04) :408-417
[50]  
John G., 2015, STRATEGIC DATA BASED