Big data-driven strategic orientation in international marketing

Abstract

PurposeBig data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.Design/methodology/approachThe study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.FindingsThe findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.Research limitations/implicationsThe study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.Originality/valueThe study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.

Development of formats for the implementation of the intelligent business model of trade enterprises

“…The results of the literature review [13][14][15][16][17][18] show that the intellectual activities under modern business conditions determine the competitiveness of existing business models of enterprises and are a key resource for their development. Awareness of the level of intellectual activity of the enterprise is of great importance in the justification and implementation of strategic development directions [16,[19][20][21][22].…”

Scientometric and Bibliometric Analysis in Analytical Marketing Research

“…It is exploratory in nature and consists of five phases: formulation, identification, selection, confirmation, analysis and thematic synthesis (Velt et al, 2020;Diodato & Gellaty, 2013;Araya-Castillo et al, 2021). Formulation is based on posing research questions (Quinn et al, 2016;Paschen et al, 2020;Akter et al, 2021), taking into account the most important issues related to analytical marketing, which are:…”

An innovative big data framework for exploring the impact on decision-making in the European Mediterranean healthcare sector

“…, 2020). This is evident when there is a focus on the abundance of unstructured data available for automated decisions and to formulate strategies by grabbing evidence-based opportunities (Akter et al. , 2021; Akhtar et al.…”

“…Therefore, big data enable and support the ability of doctors and practitioners to take smarter decisions early in healthcare (Nazir et al, 2020;Chen et al, 2020). This is evident when there is a focus on the abundance of unstructured data available for automated decisions and to formulate strategies by grabbing evidence-based opportunities (Akter et al, 2021;Akhtar et al, 2019). A predominant amount of critical healthcare big data is held in an unstructured or a semi-structured way.…”

“…However, to achieve automated decision-making (Akter et al, 2021;Akhtar et al, 2019), advanced systems such as ML and AI techniques are needed to processes these high volumes of big data in real time. However, as there is still a lack of the right level of software and hardware support, until now, the meaning of big data is still vague.…”