E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future.

中文翻译：

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电子商务初创企业采用大数据分析的概念框架：基于案例的方法

电子商务初创企业已涉足新兴经济体，并且以显着更快的速度增长。大数据在其增长故事中起到了催化剂的作用。大数据分析（BDA）吸引了电子商务公司对工具进行投资，并获得了领先于其竞争对手的优势。电子商务初创企业采用这些BDA工具的过程一直是人们关注的领域，因为成功采用将导致更好的结果。本研究旨在开发一种解释性结构模型（ISM），它将作为有效实施BDA的框架。该研究使用混合多准则决策过程来开发框架并使用实际案例研究对其进行测试。对文献进行系统的审查并与专家进行讨论，探讨了采用BDA工具的11个促成因素。从行业专家那里收集了主要数据，以开发ISM框架，并使用模糊MICMAC分析对采用过程的推动因素进行了分类。然后使用案例研究对框架进行测试。进行主题聚类以开发一个简单的ISM框架，然后进行模糊分析网络过程（ANP）来讨论促成因素的关联和排名。结果表明，对相关数据的访问构成了框架的基础，将成为采用过程中最强大的推动力，而公司则将员工的技术技能视为最重要的推动力。还发现，在ISM和ANP中出现的促成因素的排名之间存在正相关。该框架有助于简化任何电子商务公司将来采用BDA所遵循的策略。