Does marketing analytics capability boost firms' competitive marketing performance in data-rich business environment?

Abstract

PurposeFew well-documented studies have explained the importance of researching firms' marketing analytics capability (FMAC). In spite of its significance, there is scant attention to conceptualising and empirically investigating FMAC and its consequences in a data-driven business context. Thus, this study aims to develop and test a conceptual model that relates FMAC and its repercussions in the data-rich business environment.Design/methodology/approachThis study analysed the data from 250 managers amongst large and medium-sized manufacturing and service-intensive firms. Furthermore, this research performed an empirical study by using operationalised questionnaire survey method to verify the hypotheses and reach its theoretical and managerial implications. Structural equation modelling with maximum-likelihood estimation method was applied to verify the validity of the proposed research model.FindingsMultivariate analysis results show that FMAC significantly influences firms' competitive marketing performance (FCMP) with the presence of holistic marketing decision-making (HMDM) as a mediator. Moreover, adoption of artificial intelligence (AAI) enhances the relationship of FMAC-HMDM and FMAC-FCMP linkages.Practical implicationsThis study analyses how FMAC can enhance FCMP and contributes to resource-based views and technological capability theories. From a managerial perspective, guidelines are provided for marketers to adopt advance technologies, such as AI, to optimise FMAC and HMDM to achieve competitive marketing performance.Originality/valueBelieving that “how to be competitive in marketing performance under data-rich-environment”, this research is the first to use the data of a firm manager to facilitate the understanding of FMAC, which provides a new direction for improving marketing performance. In addition, HMDM and AAI are also proposed for firms to optimise FCMP.

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

“…Table 1 presents each construct’s measurement questions and references to support the theoretical framework. The instrument was designed and developed based on a five-point Likert scale (1 = “strongly disagree”; 2 = “disagree”; 3 = “neutral”; 4 = “Agree”; 5 = “Strongly Agree”), which has been widely used by researchers in business management research in the past ( Chatterjee et al, 2021a ; Chaudhuri et al, 2021 ; Chen and Chen, 2021 ; Denicolai et al, 2021 ; Mostafiz et al, 2021 ; Rahman et al, 2021 ).…”

“…We focus on the firm capability in creating value because AIC can enhance the firm’s capabilities and improve firm performance ( Chatterjee et al, 2021a ). RBV is frequently used to demonstrate the association among firm resources, capabilities, and performance ( Barney, 1991 ; Chen and Lin, 2021 ; Hossain et al, 2021 ; Rahman et al, 2021 ). Therefore, this study will utilize the RBV in the following processes.…”

“…Combined with RBV, we define AIC of e-commerce firms as the ability of firms to build, integrate, and utilize AI-based related resources ( Łapińska et al, 2021 ; Mikalef and Gupta, 2021 ). Effective and efficient implementation of AI in firms, on the other hand, requires significant infrastructural resources (tangible resources; Bag et al, 2021c ; Chatterjee et al, 2021a ), which includes financial support ( Łapińska et al, 2021 ), data ( Herhausen et al, 2020 ; Hwang and Kim, 2021 ), hardware devices and software ( Zhang et al, 2020 ), and technical support ( Rahman et al, 2021 ). The majority of the businesses across E-commerce companies are throughout the Internet, and thus they have a natural advantage in acquiring data resources ( Wang and Fan, 2021 ).…”

“…Companies can also develop AIC while enhancing the formation and use of AIM systems ( Metawa et al, 2021 ). The implementation of artificial intelligence management systems needs to be driven by various resources of AIC ( Rahman et al, 2021 ). Firms can automate management activities with the help of AI technologies, and firms with AIC can advance AIM ( Bag et al, 2020a ).…”

“…Big data can enhance AIC ( Ghasemaghaei, 2021 ) and decision-making for more profitable business outcomes ( Denicolai et al, 2021 ). The AI-related business management systems are essential factors in optimizing business performance ( Rahman et al, 2021 ). Despite the great potential of AI technologies to facilitate firm performance, the current publications rarely focus on the firm creativity, artificial intelligence management (AIM), and artificial intelligence-driven decision making (AIDDM) in the relationship between the two (research gap 2).…”