大数据分析的成功应用:价值链流程层面的视角

IF 4.5 3区 管理学 Q1 BUSINESS
Ramzi El-Haddadeh, Adam Fadlalla, Nitham M. Hindi
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引用次数: 0

摘要

目的尽管有关大数据分析(BDA)如何改变企业并提高其能力的言论甚嚣尘上,但通过成功采用大数据分析来认识其战略价值的做法仍有待加强。设计/方法/途径基于资源的理论为开发概念性 BDA 流程价值链采用模型提供了视角。对 369 家小型、中型(SMEs)和大型组织采用了两阶段回归-人工神经网络相结合的方法,以验证组织成功采用 BDA 的关键价值链流程层面驱动因素。研究结果研究结果表明,组织成功采用 BDA 的主要驱动因素是产品和服务流程层面的价值,组织规模不同,驱动因素也不同。大型组织主要从外部价值链的角度采用 BDA,而中小型组织则从内部价值链的角度采用 BDA。因此,建议企业认识到自己的组织动态和确切规模,以制定正确的战略,成功采用 BDA。研究局限性/影响本研究有助于了解内部和外部价值链驱动因素在影响中小型企业和大型企业如何成功采用 BDA 方面的作用。因此,需要仔细研究组织的独特属性,包括其规模。通过对这些要素的调查,本研究揭示了必须如何精心打造这种创新能力和竞争力,以帮助创造可持续的竞争优势。对于大型企业来说,与中小企业相比,创新资源往往比较丰富。因此,它们可以对成本和相关风险进行有效管理。通过考虑已确定的与价值链相关的采用成功因素,企业应能更好地评估自身能力,同时为采用 BDA 做好准备。原创性/价值本研究从流程级价值链的角度,为研究界和企业界提供了基于经验的见解,帮助他们了解在组织中成功采用大数据所需的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big data analytics adoption success: value chain process-level perspective

Purpose

Despite the considerable hype about how Big Data Analytics (BDA) can transform businesses and advance their capabilities, recognising its strategic value through successful adoption is yet to be appreciated. The purpose of this paper is to focus on the process-level value-chain realisation of BDA adoption between SMEs and large organisations.

Design/methodology/approach

Resource-based theory offered the lens for developing a conceptual BDA process-level value chain adoption model. A combined two-staged regression-artificial neural network approach has been utilised for 369 small, medium (SMEs) and large organisations to verify their critical value chain process-level drivers for successful organisational adoption of BDA.

Findings

The findings revealed that organisational BDA adoption success is driven predominantly by product—and service-process-level value, with distinctive discrepancies dependent on the organisation’s size. Large organisations primarily embrace BDA for their external value chain dimensions, while SMEs encompass its internal value chain cues. As such, businesses will be advised to acknowledge their organisational dynamics and precise size to develop the right strategies to adopt BDA successfully.

Research limitations/implications

The study advances the understanding of the role of internal and external value chain drivers in influencing how BDA can be successfully adopted in SMEs and large organisations. Thus, appreciating the organisation’s unique attributes, including its size, will need to be carefully examined. By investigating these elements, this research has shed new light on how developing such innovative capabilities and competencies must be carefully crafted to help create a sustainable competitive advantage.

Practical implications

For an organisational positioning, acknowledging the role of internal and external value chain drivers is critical for implementing the right strategies for adopting BDA. For larger businesses, resources for innovation often can be widely available compared to SMEs. As such, they can manage their costs and associated risks resourcefully. By considering the identified value-chain-related adoption success factors, businesses should be better positioned to assess their competencies while being prepared to adopt BDA.

Originality/value

The study offers the research and business community empirical-based insights into the strategies needed to successfully adopt big data in an organisation from a process-level value chain perspective.

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来源期刊
CiteScore
8.60
自引率
9.80%
发文量
58
期刊介绍: Business processes are a fundamental building block of organizational success. Even though effectively managing business process is a key activity for business prosperity, there remain considerable gaps in understanding how to drive efficiency through a process approach. Building a clear and deep understanding of the range process, how they function, and how to manage them is the major challenge facing modern business. Business Process Management Journal (BPMJ) examines how a variety of business processes intrinsic to organizational efficiency and effectiveness are integrated and managed for competitive success. BPMJ builds a deep appreciation of how to manage business processes effectively by disseminating best practice. Coverage includes: BPM in eBusiness, eCommerce and eGovernment Web-based enterprise application integration eBPM, ERP, CRM, ASP & SCM Knowledge management and learning organization Methodologies, techniques and tools of business process modeling, analysis and design Techniques of moving from one-shot business process re-engineering to continuous improvement Best practices in BPM Performance management Tools and techniques of change management BPM case studies.
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