How market orientation contributes to innovation and market performance: the roles of business analytics and flexible IT infrastructure

Abstract

Purpose Market orientation (MO) (intelligence generation, intelligence dissemination and responsiveness) is known as one of the key concepts in marketing literature. Although prior research has widely focused on the meaning and application of MO, few attempts have been made to explore how market-oriented firms lead to innovation and market performance and what factors actually moderate this relationship. To fill this gap, the present study aims to explore the relationship between MO, innovation and market performance. This study also attempts to examine the intervening role of IT infrastructure, business analytics (BA) capabilities and market turbulence in the proposed model. Design/methodology/approach In this study, a questionnaire-based survey was undertaken to test the proposed hypotheses. To verify the proposed theoretical model, partial least squares (PLS)/structured equation modeling (SEM) was performed with 114 valid survey data. Findings Despite prior studies which postulated innovation performance as the final outcome of MO (Han et al., 1998; Song et al., 2015), this study focused on innovation performance as a mediating outcome which finally leads to market performance. The statistical results approve the putative relationship which means managers would be able to realize the paramount role of innovation as an integral part of achieving higher market performance. In addition, no support was found for the relationship between intelligence generation and responsiveness. This finding shows that not all obtained information can help managers in the decision-making process. Originality/value This study aims to enrich literature by developing a conceptual model to test the link between MO, innovation and market performance. The value of this study is to investigate the roles of flexible IT infrastructure, BA capabilities and market turbulence as the potential moderators in the proposed model. The results advance the understanding of the influence of BA capabilities on the link between intelligence dissemination and responsiveness. Findings also show innovation performance as remarkable and deemed valuable capability, leading to higher performance in marketing-related activities, particularly in highly turbulent markets.

A Nexus among Strategic Orientation, Social Network, Knowledge Sharing, Organizational Innovation, and MSMEs Performance

“…MSMEs businessmen are fully aware that today they are required to have a strategy that is right on track, which include resource and market aspects. This result also strengthens the prior research finding that resources orientation (Muafi et al, 2019;Obeidat, 2016;Zaied et al, 2015;Su et al, 2018;Islami et al, 2018) and market orientation (Ashrafi & Ravasan, 2018) can increase organizational innovation and organizational performance (Saunila, 2014;Aujirpongpan & Hareebin, 2020;Lee & Xuan, 2019;Huang & Ngoc, 2019).…”

“…Likewise, it must analyze the long-term marketing strategies of existing and potential competitors. The research result proves that there is a positive relationship between market orientation and organizational innovation (Ashrafi & Ravasan, 2018;Huhtala et al, 2014), especially SMEs performance (Saunila, 2014).…”

The role of business analytics capabilities in bolstering firms’ agility and performance

“…Past studies showed that the importance of firms' capability to extract environmental information to reveal new business opportunities and evolve/innovate consistently (Bose, 2009;Chae, 2014;Wang & Dass, 2017). The extracted data help managers find the most efficient way to uncover new business opportunities (Ashrafi & Zare Ravasan, 2018;Howson, 2007;Sivarajah, Kamal, Irani, & Weerakkody, 2017). Therefore, firms seek to develop innovative capability through various enterprise applications such as BA (March & Hevner, 2007).…”

Big Data Analytics and Firm Performance: A Systematic Review

“…Two of the three papers that did not use the term big data analytics are those of Ghasemaghaei, Hassanein and Turel [5] and Arnaboldi [55], who use the keyword data analytics. Another is that of Ashrafi and Zare Ravasan [6], who use the keyword business analytics. However, the authors of the present review included those papers because the contents of the studies fulfilled the objective of the current study.…”

“…Its results are intended to support scholars in precisely framing their studies by taking advantage of our stringent assurance procedure. The publications selected for review comprise those of (Mikalef, Pappas, Krogstie and Giannakos [1], Ghasemaghaei, Hassanein and Turel [5], Ashrafi and Zare Ravasan [6], Ardito, Scuotto, Del Giudice and Petruzzelli [8], Wamba and Mishra [10], Ji-fan Ren, Wamba, Akter, Dubey and Childe [16], Chen, Preston and Swink [31], Akter, Wamba, Gunasekaran, Dubey and Childe [32], Raguseo and Vitari [35], Mandal [36], Zhan, et al [37], Côrte-Real, et al [38], Gravili, et al [39], Gupta and George [40], Hughes [41], Vera-Baquero, et al [42], Popovič, et al [43], Kwon, et al [44], Wamba, et al [45], Wang and Hajli [46], Wang and Byrd [47], Wang, et al [48], Wang, et al [49], Müller, et al [50], Lai, et al [51], Rialti, et al [52], Mikalef, et al [53,54], Arnaboldi [55], Vidgen, et al [56], Cillo, et al [57], Saggi and Jain [58], Wamba, et al [59]). Figure 1 shows the distribution of the papers based on the WoS category.…”