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Article
Publication date: 3 May 2022

Abror Hoshimov, Anna Corinna Cagliano, Giulio Mangano, Maurizio Schenone and Sabrina Grimaldi

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system…

Abstract

Purpose

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

Design/methodology/approach

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

Findings

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

Research limitations/implications

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

Originality/value

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

Details

Journal of Facilities Management , vol. 22 no. 1
Type: Research Article
ISSN: 1472-5967

Keywords

Article
Publication date: 26 March 2024

Yingjie Ju, Jianliang Yang, Jingping Ma and Yuehang Hou

The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security…

60

Abstract

Purpose

The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security emergency industry demonstration base, on the profitability of local publicly traded companies. Additionally, the study investigates the significance of firms' blockchain strategies and technologies within this framework.

Design/methodology/approach

Using the differences-in-differences (DID) approach, this study evaluates the impact of China's national security emergency industry demonstration bases (2015–2022) on the profitability of local firms. Data from the China Research Data Service (CNRDS) platform and investor Q&As informed our analysis of firms' blockchain strategy and technology, underpinned by detailed data collection and a robust DID model.

Findings

Emergency industry demonstration bases have notably boosted enterprise profitability in both return on assets (ROA) and return on equity (ROE). Companies adopting blockchain strategies and operational technology see a clear rise in profitability over non-blockchain peers. Additionally, the technical operation of blockchain presents a more pronounced advantage than at the strategic level.

Originality/value

We introduced a new perspective, emphasizing the enhancement of corporate operational safety and financial performance through the pathway of emergency industry policies, driven by the collaboration between government and businesses. Furthermore, we delved into the potential application value of blockchain strategies and technologies in enhancing operational security and the emergency industry.

Details

Industrial Management & Data Systems, vol. 124 no. 4
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 4 February 2022

Anish Kumar, Sachin Kumar Mangla and Pradeep Kumar

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements…

1742

Abstract

Purpose

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

Design/methodology/approach

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

Findings

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Originality/value

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 2
Type: Research Article
ISSN: 1741-0401

Keywords

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