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Showing 2 results for Bibliometrics
Class-Based Storage: Bibliometric analysis for Research Mapping
Nur Iftitah, Qurtubi Qurtubi, Muchamad Sugarindra,
Volume 34, Issue 4 (12-2023)
Abstract
This research aims to determine the scope and pattern of research and understand trends in class-based storage research, to deliver the latest research on the topic of class-based storage for future studies.  This study is based on data derived from several journal publications, limited only to publication years of 2012 to 2023. Harzing's Publish or Perish and VOSviewer software were used in data collection. Therefore, 980 articles were obtained based on keywords and processed by using bibliometric analysis. From the results of bibliometric research on the topic of class-based storage, identification of trends and patterns on research growth is obtained, analyzing renewal, obsolescence, and distribution of references, estimating productivity, author, year of publication, most-contributed publishers, and collaboration among authors who discussing interrelated topics. This research shows that in bibliometric studies in class-based storage literature, by involving analysis through keywords contained in titles and abstracts, as well as various analyses of years of publication, most publications are able to deepen and expand the literature in the previous class-based storage-related research. So that the findings in terms of assessment techniques and relationships can be used as information for future researchers in such fields of study. Research on bibliometrics is the main reference, especially in the arrangement of facility layout and warehouse management. The originality provided by this study lies in the presentation of differences and similarities between current researchers and previous researchers and the processing of publication databases based on class-based storage journals. So that all published information on the topic of class-based storage in the last 10 years (2012-2023) could become a basis and reference for further research.

Behavioral Finance biases: A Comprehensive Review on regret approach studies in portfolio optimization
Amirmohammad Larni-Fooeik, Hossein Ghanbari, Seyed Jafar Sadjadi, Emran Mohammadi,
Volume 35, Issue 1 (3-2024)
Abstract
In the ever-evolving realm of finance, investors have a myriad of strategies at their disposal to effectively and cleverly allocate their wealth in the expansive financial market. Among these strategies, portfolio optimization emerges as a prominent approach used by individuals seeking to mitigate the inherent risks that accompany investments. Portfolio optimization entails the selection of the optimal combination of securities and their proportions to achieve lower risk and higher return. To delve deeper into the decision-making process of investors and assess the impact of psychology on their choices, behavioral finance biases can be introduced into the portfolio optimization model. One such bias is regret, which refers to the feeling of remorse that can induce hesitation in making significant decisions and avoiding actions that may lead to unfavorable investment outcomes. It is not uncommon for investors to hold onto losing investments for extended periods, reluctant to acknowledge mistakes and accept losses due to this behavioral tendency. Interestingly, in their quest to sidestep regret, investors may inadvertently overlook potential opportunities. This research article aims to undertake an in-depth examination of 41 publications from the past two decades, providing a comprehensive review of the models and applications proposed for the regret approach in portfolio optimization. The study categorizes these methods into accurate and approximate models, scrutinizing their respective timeframes and exploring additional constraints that are considered. Utilizing this article will provide investors with insights into the latest research advancements in the realm of regret, familiarize them with influential authors in the field, and offer a glimpse into the future direction of this area of study.  The extensive review findings indicate a growth in the adoption of the regret approach in the past few years and its advancements in portfolio optimization.

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