Adoption of artificial intelligence and big data analytics: an organizational readiness perspective of the textile and garment industry in Bangladesh

IF 4.5 3区 管理学 Q1 BUSINESS
Md Khalid Hossain, Aashish Srivastava, Gillian Christina Oliver, Md Ekramul Islam, Nayma Akther Jahan, Ridoan Karim, Tanjila Kanij, Tanjheel Hasan Mahdi
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引用次数: 0

Abstract

Purpose

The purpose of this paper is to investigate the organizational readiness perspective of adopting artificial intelligence and big data analytics in the textile and garment industry in Bangladesh along with identifying the associated factors.

Design/methodology/approach

The research uses a qualitative method using semi-structured interviews with representatives of business organizations and stakeholders of Bangladesh’s textile and garment industry.

Findings

The research reveals that the textile and garment industry in Bangladesh currently has low organizational readiness to adopt artificial intelligence and big data analytics. This is due to moderate knowledge- and leadership-readiness along with low human-, finance- and engagement-readiness of most of the business organizations. The readiness aspects interplay with each other and need to be improved holistically.

Practical implications

Considering the significant global and national importance of Bangladesh’s textile and garment industry, gaining insights into the industry’s current state of readiness for adopting artificial intelligence and big data analytics would offer valuable assistance to both national and global economies and may enhance economic outcomes.

Originality/value

Since no exploratory study was conducted to understand the organizational readiness aspects of adopting artificial intelligence and big data analytics of the globally significant textile and garment industry in Bangladesh, the paper analyzes five key aspects of such readiness and offers a basis for conducting similar studies in other emerging economies.

采用人工智能和大数据分析:孟加拉国纺织服装业的组织准备视角
本文旨在调查孟加拉国纺织服装行业采用人工智能和大数据分析的组织准备程度,并确定相关因素。研究采用定性方法,对孟加拉国纺织服装行业的商业组织代表和利益相关者进行了半结构化访谈。研究结果表明,孟加拉国纺织服装行业目前采用人工智能和大数据分析的组织准备程度较低。这是因为大多数企业组织在知识和领导力方面的准备程度一般,而在人力、财务和参与方面的准备程度较低。实践意义考虑到孟加拉国纺织和服装行业在全球和国内的重要地位,深入了解该行业目前采用人工智能和大数据分析的准备状态,将为国家和全球经济提供有价值的帮助,并可能提高经济成果。原创性/价值由于没有开展探索性研究来了解孟加拉国具有全球重要性的纺织和服装行业在采用人工智能和大数据分析方面的组织准备情况,本文分析了此类准备情况的五个关键方面,并为在其他新兴经济体开展类似研究提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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