Big data-driven business model innovation by traditional industries in the Chinese economy

S. Cheah, Shenghui Wang
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引用次数: 51

Abstract

Purpose This study aims to construct mechanisms of big data-driven business model innovation from the market, strategic and economic perspectives and core logic of business model innovation. Design/methodology/approach The authors applied deductive reasoning and case analysis method on manufacturing firms in China to validate the mechanisms. Findings The authors have developed an integrated framework to deduce the elements of big data-driven business model innovation. The framework comprises three elements: perspectives, business model processes and big data-driven business model innovations. As we apply the framework on to three Chinese companies, it is evident that the mechanisms of business model innovation based on big data is a progressive and dynamic process. Research limitations/implications The case sample is relatively small, which is a typical trade-off in qualitative research. Practical implications A robust infrastructure that seamlessly integrates internet of things, front-end customer systems and back-end production systems is pivotal for companies. The management has to ensure its organization structure, climate and human resources are well prepared for the transformation. Social implications When provided with a convenient crowdsourcing platform to provide feedback and witness their suggestions being implemented, users are more likely to share insights about their use experience. Originality/value Extant studies of big data and business model innovation remain disparate. By adding a new dimension of intellectual and economic resource to the resource-based view, this paper posits an important link between big data and business model innovation. In addition, this study has contributed to the theoretical lens of value by contextualizing the value components of a business model and providing an integrated framework.
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大数据驱动中国经济传统产业的商业模式创新
目的本研究旨在从市场、战略和经济角度以及商业模式创新的核心逻辑构建大数据驱动的商业模式创新机制。设计/方法论/方法作者将演绎推理和案例分析方法应用于中国制造企业,以验证其机制。研究结果作者开发了一个综合框架来推断大数据驱动的商业模式创新的要素。该框架包括三个要素:视角、商业模式流程和大数据驱动的商业模式创新。当我们将该框架应用于三家中国公司时,很明显,基于大数据的商业模式创新机制是一个渐进和动态的过程。研究局限性/影响案例样本相对较小,这是定性研究中的典型权衡。实际意义一个无缝集成物联网、前端客户系统和后端生产系统的强大基础设施对公司来说至关重要。管理层必须确保其组织结构、气候和人力资源为转型做好充分准备。社会影响当提供一个方便的众包平台来提供反馈并见证他们的建议得到实施时,用户更有可能分享关于他们使用体验的见解。独创性/价值对大数据和商业模式创新的外部研究仍然不同。通过在基于资源的观点中增加知识和经济资源的新维度,本文提出了大数据与商业模式创新之间的重要联系。此外,本研究通过将商业模式的价值组成部分置于情境中并提供一个综合框架,为价值的理论视角做出了贡献。
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来源期刊
CiteScore
3.40
自引率
4.20%
发文量
17
期刊介绍: The Journal of Chinese Economic and Foreign Trade Studies (JCEFTS) negotiates China''s unique position within the international economy, and its interaction across the globe. From a truly international perspective, the journal publishes both qualitative and quantitative research in all areas of Chinese business and foreign trade, technical economics, business environment and business strategy. JCEFTS publishes high quality research papers, viewpoints, conceptual papers, case studies, literature reviews and general views. Emphasis is placed on the publication of articles which seek to link theory with application, or critically analyse real situations in terms of Chinese economics and business in China, with the objective of identifying good practice in these areas and assisting in the development of more appropriate arrangements for addressing crucial issues of Chinese economics and business. Papers accepted for publication will be double–blind peer-reviewed to ensure academic rigour and integrity.
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