Wireless sensor networks and internet of things for E-services applied natural language processing and deep learning

Muam, Pascal; Skalna, Iwona; Pełech-Pilichowski, Tomasz

doi:10.21203/rs.3.rs-2322639/v1

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Furthermore, it is crucial to acknowledge that provisions pertaining to data privacy, such as the General Data Protection Regulation (GDPR), impose stringent responsibilities about the procurement, preservation, and use of customer data. Therefore, it is crucial to establish robust safeguards and adhere to compliance protocols [15].…”

Section: Challenges and Limitationsmentioning

confidence: 99%

Leveraging AI-Enhanced Robotic Process Automation for Retail Pricing Optimization: A Comprehensive Analysis

Venigandla,

Vemuri,

Thaneeru

et al. 2023

JKLST

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Pricing strategies are of paramount importance in the fiercely competitive retail sector, exerting a substantial influence on a company's financial performance and market standing. The amalgamation of artificial intelligence (AI) and robotic process automation (RPA) presents merchants with a potentially revolutionary opportunity to include and augment their pricing strategies via automation. The present research article investigates the field of AI-enhanced Robotic Process Automation (RPA) within the realm of retail pricing. It aims to analyses the impact of RPA on decision-making processes, operational efficiency, and overall organizational success. This research offers a thorough examination of pertinent scholarly works, empirical examples, and theoretical frameworks to investigate the advantages, challenges, and potential future trajectories associated with the utilization of artificial intelligence (AI) and robotic process automation (RPA) to augment pricing strategies in the retail sector.

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Section: Challenges and Limitationsmentioning

confidence: 99%

Leveraging AI-Enhanced Robotic Process Automation for Retail Pricing Optimization: A Comprehensive Analysis

Venigandla,

Vemuri,

Thaneeru

et al. 2023

JKLST

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show abstract

“…Figure 1 delineates the various stages essential for fostering effective cooperation within logistics frameworks, as corroborated by technical communities in game theory [20,21]. The utilization of wireless sensor networks, which monitor and record environmental conditions and transmit this data, has become increasingly significant [22]. These sensors' capabilities in tracking shipments and relaying critical data to management systems are integral to the efficacy of logistics operations.…”

Section: Steps Towards Cooperative Theory In Logistics During Covid-19mentioning

confidence: 99%

Strategic Application of Cooperative Game Theory in Mitigating Labor Shortages in Post-Pandemic Logistics: A Case Study of Poland

Munyeshuri,

Song,

Akoko

et al. 2023

JOSA

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The onset of the global pandemic has underscored the pivotal role of logistics, bolstered by information and communication technologies, in the resilience of supply chain networks. This study investigates the transformative impact of the COVID-19 pandemic on these networks, with a focus on the resultant operational challenges and labor shortages experienced in Poland -a critical hub in European supply chains. The research delves into how cooperative game theory can be strategically applied to address workforce deficits, particularly in sectors vital to Poland's economy, such as food and healthcare. In the context of reduced operations triggered by illness, fatalities, and preventive measures, including travel restrictions, this study elucidates the operational dynamics within supply chain networks through game theory frameworks. It scrutinizes the strategies implemented by major corporations, including Amazon, DHL, Post Office, KFC, and McDonald's, to navigate these challenges. The methodology encompasses an analysis of the network structure of supply chain game theory, tailored to the operational confines of Poland's logistics sector, acknowledging its role as Europe's breadbasket. The findings reveal various approaches to counteract labor shortages exacerbated by the pandemic, drawing parallels with similar challenges in regions like Africa, Asia, Ukraine, Turkey, and India. The study highlights the diverse impacts of workforce disruptions on commodity prices and the revenues of logistics companies within the supply network economy. These insights contribute to a broader understanding of the financial and operational implications of cooperative game theory in the context of global health emergencies. Conclusively, this research augments existing literature by demonstrating the applicability of cooperative game theory in addressing labor shortages under pandemic-induced constraints. It presents a comprehensive analysis of the strategies employed by key players in the logistics sector, offering valuable perspectives on mitigating operational disruptions in times of crisis.

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Wireless sensor networks and internet of things for E-services applied natural language processing and deep learning

Cited by 2 publications

References 23 publications

Leveraging AI-Enhanced Robotic Process Automation for Retail Pricing Optimization: A Comprehensive Analysis

Leveraging AI-Enhanced Robotic Process Automation for Retail Pricing Optimization: A Comprehensive Analysis

Strategic Application of Cooperative Game Theory in Mitigating Labor Shortages in Post-Pandemic Logistics: A Case Study of Poland

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