scholarly journals Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

2021 ◽  
Vol 17 (33) ◽  
pp. 47-63
Author(s):  
Isabel Cristina Arango-Palacio
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Competitive Advantage ◽  
Sources Of Information ◽  
Intelligent Software ◽  
Searching Method

La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución. Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.

Facilitating artificial intelligence powered supply chain analytics through alliance management during the pandemic crises in the B2B context

2021 ◽  
Vol 96 ◽  
pp. 135-146
Author(s):  
Rameshwar Dubey ◽  
David J. Bryde ◽  
Constantin Blome ◽  
David Roubaud ◽  
Mihalis Giannakis
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Alliance Management

Unlocking the Supply Chain to Build Competitive Advantage

2000 ◽  
Vol 11 (2) ◽  
pp. 1-8 ◽  
Author(s):  
Brian Walker ◽  
David Bovet ◽  
Joseph Martha
Keyword(s):  
Supply Chain ◽  
Competitive Advantage

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

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