From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management

Leung, Eric Ka Ho; Lee, Carmen Kar Hang; Ouyang, Zhiyuan

doi:10.1016/j.ijpe.2021.108353

Cited by 40 publications

(22 citation statements)

References 42 publications

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“…Organizations can create IoT-based solutions that meet evolving customer demands and provide predictive maintenance capabilities, enabling them to stay ahead of competitors in their industry (Manavalan & Jayakrishna, 2019). Leung et al (2022) argue that IoT adoption can streamline operations and optimize resource allocation. This allows organizations to redirect resources, including human capital and investments, toward innovation initiatives that hold the most promise for success.…”

Section: Iot Adoption and Innovation Organizational Predictormentioning

confidence: 99%

Big data and IoT adoption in shaping organizational citizenship behavior: The role of innovation organizational predictor in the chemical manufacturing industry

Nuryanto,

Basrowi,

Quraysin

2024

10.5267/j.ijdns

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This research aims to investigate the relationships between Big Data and Internet of Things (IoT) adoption and employee behavior in the chemical manufacturing industry, specifically focusing on the mediating role of organizational innovation. The research methodology employs a quantitative approach that involves employee surveys, statistical analysis, and mediation testing. The primary findings reveal that Big Data adoption significantly enhances Organizational Innovation, contributing positively to Organizational Citizenship Behavior (OCB) among employees. Conversely, IoT adoption has a significant positive impact on Organizational Innovation but does not directly influence OCB. The relationship between IoT adoption and OCB is mediated by Organizational Innovation, highlighting the pivotal role of innovation as an intermediary in influencing employee behavior. The practical implications of this research suggest that organizations in the chemical manufacturing industry should strategically integrate Big Data and IoT technologies to foster innovation and elevate OCB. Leadership support and employee training are crucial. Study limitations include industry specificity, self-reported data, and static analysis. Future research should diversify samples and use longitudinal methods. Recommendations: embrace tech with innovation focus, train leaders, and deepen understanding of tech, innovation, and behavior.

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Section: Iot Adoption and Innovation Organizational Predictormentioning

confidence: 99%

Big data and IoT adoption in shaping organizational citizenship behavior: The role of innovation organizational predictor in the chemical manufacturing industry

Nuryanto,

Basrowi,

Quraysin

2024

10.5267/j.ijdns

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“…Influenced by the concept of digital twin technology, an increasing number of logistics and distribution companies are conducting research toward building a fine-grained digital supply chain system [20], [21]. In the field of intelligent distribution, Leung et al [22] constructed a multi-level framework based on the digital twin to enhance the construction of digital logistics. Based on the above research, this paper will be focusing on drawing on the system concept of digital twins further study the digital logistics based on the refined supply chain and will explore the intelligent logistics scheduling model.…”

Section: Introductionmentioning

confidence: 99%

An Auxiliary Model of Intelligent Logistics Distribution Management for Manufacturing Industry Based on Refined Supply Chain

Han

et al. 2023

IEEE Access

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In the context of Industry 4.0 and based on the demand of digital logistics construction of industrial enterprises, this paper integrates the concept of digital twin into Refined Logistics Supply Chain construction. Considering the constraints of multi-distribution center, heterogeneous vehicle performance, distribution cost, quasi-shipment certificate and humanized management, Refined Logistics Supply Chain System (RLSCS) and cross-regional scheduling optimization model of logistics vehicles with multidistribution center were established. The designed model can minimize the transportation cost, reduce the transportation time, and improve the vehicle load rate. An adaptive elite honey badger target algorithm based on cubic mapping mechanism (IHBA), is designed to solve the model. Further, performance evaluation by optimizing test functions, the convergence performance of IHBA algorithm was demonstrated. Finally, the simulation experiment is carried out according to the actual business data and it is compared to eight other optimistic algorithms. The experimental results show that the proposed algorithm is more effective and more robust, and the related models and algorithms can provide research basis for industrial products digital supply chain system.INDEX TERMS Industry 4.0, refined supply chain, multi-objective constraint, logistics distribution, honey badger algorithm, cubic mapping mechanism.

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“…Currently, the warehouse operations face challenges of excess stock, real-time occupational safety monitoring, low traceability, low connectivity, low visibility, spacerelated issues, extra procedures, delays in information, damaged product, product return and backorder pressures (Baker and Canessa, 2009;Leung et al, 2022;Md Mashud et al, 2021;Staudt et al, 2015). Kumar et al (2021) recently discussed the seven important focus areas needed to develop and ensure the warehouse's effectiveness: design, operation, planning, controlling, performance measures, automation and warehouse sustainability.…”

Section: Introductionmentioning

confidence: 99%

Digital twin-based warehouse management system: a theoretical toolbox for future research and applications

Maheshwari

Kamble

Kumar

et al. 2023

IJLM

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PurposeThe digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.Design/methodology/approachThe current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.FindingsThe study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.Originality/valueThis study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

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From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management

Cited by 40 publications

References 42 publications

Big data and IoT adoption in shaping organizational citizenship behavior: The role of innovation organizational predictor in the chemical manufacturing industry

Big data and IoT adoption in shaping organizational citizenship behavior: The role of innovation organizational predictor in the chemical manufacturing industry

An Auxiliary Model of Intelligent Logistics Distribution Management for Manufacturing Industry Based on Refined Supply Chain

Digital twin-based warehouse management system: a theoretical toolbox for future research and applications

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