Start Date
16-8-2018 12:00 AM
Description
Business analytics is increasingly advocated as an important strategic information technology (IT) investment for marketing (Wang & Hajli, 2017). Nevertheless, most of practitioners are still struggling to make progress with business analytics even though many big data success stories released from IT vendors such as IBM and SAP have reported that this technology has the potential to harvest data-driven insights, support strategic marketing, and improve innovation. Indeed, business analytics systems are an expensive and risky undertaking (Watson, 2014). Business analytics involves the various analytics techniques (e.g., descriptive analytics and predictive analytics), process, and analytical people embedded in transformation of data that used to support decision-making processes and organizational practices (Davenport & Harris, 2007; Watson, 2014). Therefore, in this research we look at big data analytics from marketing perspective to explore the effective use of data aggregation tools on customer agility, leading to new product development. In addition, we will consider effective user of data analysis tools as another big data analytics tool and will explore the effect of that on customer agility leading to new product success. The following model is our research model to construct a quantitative research. Our plan is to collect data through questionnaire and use SEM with PLS method to analysis our data.
Recommended Citation
Tajvidi, Mina; Hajli, Nick; and Wang, YiChuan, "Big Data Analytics for New Product Success (Product Innovation)" (2018). AMCIS 2018 Proceedings. 75.
https://aisel.aisnet.org/amcis2018/TREOsPDS/Presentations/75
Big Data Analytics for New Product Success (Product Innovation)
Business analytics is increasingly advocated as an important strategic information technology (IT) investment for marketing (Wang & Hajli, 2017). Nevertheless, most of practitioners are still struggling to make progress with business analytics even though many big data success stories released from IT vendors such as IBM and SAP have reported that this technology has the potential to harvest data-driven insights, support strategic marketing, and improve innovation. Indeed, business analytics systems are an expensive and risky undertaking (Watson, 2014). Business analytics involves the various analytics techniques (e.g., descriptive analytics and predictive analytics), process, and analytical people embedded in transformation of data that used to support decision-making processes and organizational practices (Davenport & Harris, 2007; Watson, 2014). Therefore, in this research we look at big data analytics from marketing perspective to explore the effective use of data aggregation tools on customer agility, leading to new product development. In addition, we will consider effective user of data analysis tools as another big data analytics tool and will explore the effect of that on customer agility leading to new product success. The following model is our research model to construct a quantitative research. Our plan is to collect data through questionnaire and use SEM with PLS method to analysis our data.