AI in operations management: applications, challenges and opportunities

Dogru, Ali K.; Keskin, Burcu B.

doi:10.1007/s42488-020-00023-1

Cited by 43 publications

(14 citation statements)

References 20 publications

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“…Online shopping equips e-retailers with a large quantum of data-related browsing patterns and shopping habits of consumers. This in turn allows them to design future promotions and product offerings while enabling them to manage their inventory efficiently (Dogru and Keskin, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, in healthcare, various online applications have enhanced efficiency in clinical operations like scheduling of surgeries, analyzing images with the objective of diagnosis and disease prognosis (Panch et al , 2018). The digitization and automation of manufacturing operations, fueled by big data and machine learning, has brought about a notable transformation and resulted in path-breaking manufacturing facilities like self-learning plants (Dogru and Keskin, 2020). Then there is the deployment of AI in retail operations.…”

Section: Literature Reviewmentioning

confidence: 99%

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Impact of artificial intelligence on employees working in industry 4.0 led organizations

Malik

Tripathi

Kar

et al. 2021

IJM

155

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PurposeThis study attempts to develop a practical understanding of the positive and negative employee experiences due to artificial intelligence (AI) adoption and the creation of technostress. It unravels the human resource development-related challenges with the onset of Industry 4.0.Design/methodology/approachSemi-structured interviews were conducted with 32 professionals with average work experience of 7.6 years and working across nine industries, and the transcripts were analyzed using NVivo.FindingsThe findings establish prominent adverse impacts of the adoption of AI, namely, information security, data privacy, drastic changes resulting from digital transformations and job risk and insecurity brewing in the employee psyche. This is followed by a hierarchy of factors comprising the positive impacts, namely, work-related flexibility and autonomy, creativity and innovation and overall enhancement in job performance. Further factors contributing to technostress (among employees): work overload, job insecurity and complexity were identified.Practical implicationsThe emerging knowledge economy and technological interventions are changing the existing job profiles, hence the need for different skillsets and technological competencies. The organizations thus need to deploy strategic manpower development measures involving up-gradation of skills and knowledge management. Inculcating requisite skills requires well-designed training programs using specialized tools and virtual reality (VR). In addition, employees need to be supported in their evolving socio-technical relationships, for managing both positive and negative outcomes.Originality/valueThis research makes the unique contribution of establishing a qualitative hierarchy of prominent factors constituting unintended consequences, positive impacts and technostress creators (among employees) of AI deployment in organizational processes.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Impact of artificial intelligence on employees working in industry 4.0 led organizations

Malik

Tripathi

Kar

et al. 2021

IJM

155

View full text Add to dashboard Cite

show abstract

“…Managers and employees should look for sustainable solutions when any problem arises. It increases perfection that is one of the competitive advantages ( Sony, 2019 ; Dogru and Keskin, 2020 ).…”

Section: Literature Analysismentioning

confidence: 99%

Achieving Operational Excellence Through Artificial Intelligence: Driving Forces and Barriers

2021

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This paper presents an in-depth literature review on the driving forces and barriers for achieving operational excellence through artificial intelligence (AI). Artificial intelligence is a technological concept spanning operational management, philosophy, humanities, statistics, mathematics, computer sciences, and social sciences. AI refers to machines mimicking human behavior in terms of cognitive functions. The evolution of new technological procedures and advancements in producing intelligence for machines creates a positive impact on decisions, operations, strategies, and management incorporated in the production process of goods and services. Businesses develop various methods and solutions to extract meaningful information, such as big data, automatic production capabilities, and systematization for business improvement. The progress in organizational competitiveness is apparent through improvements in firm’s decisions, resulting in increased operational efficiencies. Innovation with AI has enabled small businesses to reduce operating expenses and increase revenues. The focused literature review reveals the driving forces for achieving operational excellence through AI are improvement in computing abilities of machines, development of data-based AI, advancements in deep learning, cloud computing, data management, and integration of AI in operations. The barriers are mainly cultural constraints, fear of the unknown, lack of employee skills, and strategic planning for adopting AI. The current paper presents an analysis of articles focused on AI adoption in production and operations. We selected articles published between 2015 and 2020. Our study contributes to the literature reviews on operational excellence, artificial intelligence, driving forces for AI, and AI barriers in achieving operational excellence.

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“…Indeed, recent studies on AI have deepened our understanding of AI in the contexts of OSCM yet, scaling AI usage could encounter significant bottlenecks that remain under studied (Spanaki et al 2020). For example, failure to scale up from pilot implementations of AI applications can result in unclear business value as managers fail to estimate the potential impact of the pilot on the manufacturing processes and define success criteria accurately (Dogru and Keskin 2020).…”

Section: Evolution Of Ai In Modern Operations and Supply Chain Managementmentioning

confidence: 99%

Understanding the influential and mediating role of cultural enablers of AI integration to supply chain

Cadden

Dennehy

Mäntymäki

et al. 2021

International Journal of Production Research

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Artificial Intelligence (AI) has been claimed to offer transformational power across industries and sectors. To date, research has largely focused on the technical characteristics of AI and its influence on organisational capabilities. Despite the hype surrounding AI, there is a scarcity of rigorous research that examines the organisational and behavioural factors that foster AI integration in supply chains is lacking. This quantitative study addresses this gap in knowledge by developing a research hypothesis that examines the relationships between supply chain culture and AI. We extend the generalisability of culture to provide novel insights about AI-driven supply chains that have not been reported in previous studies. The findings demonstrate the influential role that cultural enablers have on the successful integration of AI technologies in supply chains, which has implications for operations and supply chain management.

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AI in operations management: applications, challenges and opportunities

Cited by 43 publications

References 20 publications

Impact of artificial intelligence on employees working in industry 4.0 led organizations

Impact of artificial intelligence on employees working in industry 4.0 led organizations

Achieving Operational Excellence Through Artificial Intelligence: Driving Forces and Barriers

Understanding the influential and mediating role of cultural enablers of AI integration to supply chain

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