Showing 5 results for Literature Review
Yahia Zare Mehrjerdi,
Volume 25, Issue 2 (5-2014)
Abstract
Abstract
Purpose of this paper: The purpose of this article is to review some of the most prominent applications of RFID in industries and to provide a comprehensive review of the work done from 1985 through 2007 and the research trend on that. The effectiveness of RFID and the challenges that it is facing with are also discussed. Some applications of radio frequency identification in supply chain are briefly reviewed and three large cases of radio frequency identification implementation in supply chain are discussed.
Design/methodology/approach: Provides some background on radio frequency identification, and a deep look at the researches conducted from 1985 through 2007. Articles are classified by the year of publications and each case is discussed very briefly. To obtain a good understanding of the level of the researches completed up to the end of 2007 a table and graph are used to demonstrate the summary of results.
Findings: In this research, author came up with 401 articles on RFID as all are listed in a table. The findings point to this fact that research on RFID has started to pick up on year 2002 with 16 publications and then reached to its pick at year 2005 with 112 publications, and then trend went down to 42 and then up to 51 publications for years 2006 and 2007, respectively.
Practical implications (if applicable):
What is original/value of paper: Due to the fact that a better management of a system is related to the full understanding of the technologies implemented, sufficient background on the radio frequency identification technology is provided and the types of researches conducted so far on this matter are briefly discussed.
Chaymae Bahtat, Abdellah El Barkany, Abdelouahhab Jabri,
Volume 34, Issue 2 (6-2023)
Abstract
The productivity and flexibility of current manufacturing systems (dedicated and flexible production systems) are no longer competitive as products are developed and brought to market in increasingly shorter cycles. As a result, a new generation of reconfigurable manufacturing systems (RMS) has emerged that should be responsive enough to cope with sudden market changes while maintaining excellent product quality at low prices. These systems could also leverage technologies at the heart of Industry 4.0, such as artificial intelligence and machine learning, the Internet of Things (IoT), and digital twins, to create a smart, dynamic, and most importantly, reconfigurable factory, dubbed the Reconfigurable Factory 4.0. This study provides an organized and up-to-date systematic review of the literature on reconfigurable manufacturing systems, from design to simulation, and from automation to the fourth industrial revolution (Industry 4.0) highlighting the application areas as well as the significant approaches and technologies that have contributed to the development of a Reconfigurable Factory 4.0.
Ag Kaifah Riyard Kiflee, Nornajihah Nadia Hasbullah, Faerozh Madli,
Volume 35, Issue 2 (6-2024)
Abstract
Over the years, the attention given to corporate social responsibility (CSR) and sustainability topics has received a lot of attention significantly and various new terms have been introduced. This result has sparked a wide-ranging and unspecified discussion, particularly in the fields of economics and business management. The presents of functional CSR and sustainability enable management to make better decisions for the benefit of the entire society. As a result, understanding the topic of interest and broadening research collaboration are critical for advancing research development. The purpose of this study is to identify global research trends in CSR and sustainability based on publication numbers, co-authorship, affiliated countries, and keyword co-occurrences. This study used RTools and Prisma for its analysis. The findings indicate a significant rise in the number of articles published in the field of corporate social responsibility and sustainability since 2015. The USA contributed more than half of the publications, with Italy and Spain following closely behind.
Daniel Atnafu, Shimelis Zewdie Werke,
Volume 35, Issue 2 (6-2024)
Abstract
The incorporation of sustainable practices becomes crucial as firms transition from Industry 4.0 to Industry 5.0. Therefore, this systematic review explores the relationship between the two sustainability approaches; Green Human Resource Management (GHRM) and Green Supply Chain Management (GSCM) using peer-reviewed studies from 2016-2023, retrieved from Scopus and Web of Science databases. 2016 marks the starting point as the first relevant paper emerged in the literature in that year. The PRISMA approach was used to identify relevant studies, resulting in the inclusion of 30 studies for analysis purposes. The study reveals a growing interest in understanding the relationship between GHRM and GSCM practices and their impact on sustainable performance. The majority of reviewed studies utilized quantitative survey methods, suggesting the need for future research utilizing qualitative and mixed methods for gaining deeper insights. The review indicates that most studies are conducted in emerging countries, and there is a significant gap in research on the relationship between GHRM and GSCM practices in other context. Finally, the study provides valuable insights for practitioners and researchers, emphasising the importance of integrating GHRM and GSCM practices for a sustainable competitive advantage.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (6-2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
