Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
2.3
Journals
Mathematics
Special Issues
Applied Statistics in Management Sciences
share announcement

Applied Statistics in Management Sciences

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 6903

Special Issue Editors

Prof. Dr. Chia-Ding Hou

E-Mail Website
Guest Editor
Department of Statistics and Information Science, Fu Jen Catholic University, New Taipei City 242062, Taiwan
Interests: genetic statistics; simultaneous statistical inference
Dr. Rung-Hung Su

E-Mail Website
Guest Editor
Department of Statistics and Information Science, Fu Jen Catholic University, New Taipei City 242062, Taiwan
Interests: practical application of statistics; quality management and control; inventory management; industrial management

Special Issue Information

Dear Colleagues,

Applied statistics is a type of of data analysis and is devoted to identifying reliable solutions based on analysis and estimation results. This Special Issue seeks high-quality studies focusing on the practice of statistical techniques in enabling the development of scientific decisions in management. We recommend that mathematical modeling, statistical skills, programming, algorithms, deep learning, and simulation are applied to make decisions that are more routed in science. An application example is provided to illustrate the practicality and applicability of the proposed method. Some managerial insights are also discussed. Novel applications from all fronts of management will also be considered. Topics include, but are not limited to, the following:

  • Marketing management;
  • Production management;
  • Inventory management;
  • Quality management and control;
  • Financial management;
  • Operations research;
  • Supply chain management;
  • Education policy;
  • Public health policy;
  • Environment and energy policy.

Prof. Dr. Chia-Ding Hou
Dr. Rung-Hung Su
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • applied statistics
  • management sciences
  • decision-making
  • data analysis
  • deep learning

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

20 pages, 1873 KiB  
Article
An Investigation of Subsidy Policies on Recycling and Remanufacturing System in Two-Echelon Supply Chain for Negative Binomial Distribution
by Yi-Ta Hsieh, Chiu-Yen Shen, Yung-Fu Huang and Ming-Wei Weng
Mathematics 2025, 13(8), 1303; https://doi.org/10.3390/math13081303 - 16 Apr 2025
Viewed by 143
Abstract
This study investigates a two-stage production–inventory model with subsidy policies for paper cup recycling. The model includes remanufacturers, recyclers, and consumers, taking into account their preferences for different recycling channels. The negative binomial distribution of investment fund w is introduced and briefly studied. [...] Read more.
This study investigates a two-stage production–inventory model with subsidy policies for paper cup recycling. The model includes remanufacturers, recyclers, and consumers, taking into account their preferences for different recycling channels. The negative binomial distribution of investment fund w is introduced and briefly studied. The influence of various subsidy strategies on the optimal pricing, profit, and recycling volume of the reverse supply chain is discussed. Numerical simulations show that increased consumer recycling preferences positively impact the recycling volume and profit. When subsidies are limited, subsidizing remanufacturers leads to higher recycling volumes, while subsidizing consumers results in higher profits at lower-to-middle subsidy levels. The findings suggest that policymakers can leverage different subsidy strategies to effectively manage the paper cup recycling supply chain and promote sustainability by incentivizing key stakeholders to participate in the recycling process. For example, subsidizing remanufacturers can increase the overall recycling volume by making it more financially viable for them to collect and process used cups, while subsidizing consumers can boost their participation and willingness to properly dispose of cups for recycling, leading to higher profits for the reverse supply chain. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

17 pages, 4290 KiB  
Article
Predictive Maintenance for Cutter System of Roller Laminator
by Ssu-Han Chen, Chen-Wei Wang, Andres Philip Mayol, Chia-Ming Jan and Tzu-Yi Yang
Mathematics 2025, 13(8), 1264; https://doi.org/10.3390/math13081264 - 11 Apr 2025
Viewed by 277
Abstract
In the era of Industry 4.0, equipment maintenance is shifting toward data-driven strategies. Traditional methods rely on usage time or cycle counts to estimate component lifespan. This often causes early replacement of parts, leading to increased production costs. This study focuses on the [...] Read more.
In the era of Industry 4.0, equipment maintenance is shifting toward data-driven strategies. Traditional methods rely on usage time or cycle counts to estimate component lifespan. This often causes early replacement of parts, leading to increased production costs. This study focuses on the cutter system of a roller laminator used in printed circuit board (PCB) manufacturing. An accelerometer is used to collect vibration signals under normal and abnormal states. Fast Fourier transform (FFT) is used to convert time-domain data into the frequency domain, then key statistical features from critical frequency bands are extracted as independent variables. The study applies logistic regression (LR), random forest (RF), and support vector machine (SVM) for predictive modeling of the cutting tool’s condition. The results show that the prediction accuracies of these models are 87.55%, 93.77%, and 94.94%, respectively, with SVM performing the best. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

29 pages, 3060 KiB  
Article
Applying Multi-Task Deep Learning Methods in Electricity Load Forecasting Using Meteorological Factors
by Kai-Bin Huang, Tian-Shyug Lee, Jonathan Lee, Jy-Ping Wu, Leemen Lee and Hsiu-Mei Lee
Mathematics 2024, 12(20), 3295; https://doi.org/10.3390/math12203295 - 21 Oct 2024
Viewed by 1621
Abstract
The steady rise in carbon emissions has significantly exacerbated the global climate crisis, posing a severe threat to ecosystems due to the greenhouse gas effect. As one of the most pressing challenges of our time, the need for an immediate transition to renewable [...] Read more.
The steady rise in carbon emissions has significantly exacerbated the global climate crisis, posing a severe threat to ecosystems due to the greenhouse gas effect. As one of the most pressing challenges of our time, the need for an immediate transition to renewable energy is imperative to meet the carbon reduction targets set by the Paris Agreement. Buildings, as major contributors to global energy consumption, play a pivotal role in climate change. This study diverges from previous research by employing multi-task deep learning techniques to develop a predictive model for electricity load in commercial buildings, incorporating auxiliary tasks such as temperature and cloud coverage. Using real data from a commercial building in Taiwan, this study explores the effects of varying batch sizes (100, 125, 150, and 200) on the model’s performance. The findings reveal that the multi-task deep learning model consistently surpasses single-task models in predicting electricity load, demonstrating superior accuracy and stability. These insights are crucial for companies aiming to enhance energy efficiency and formulate effective renewable energy procurement strategies, contributing to broader sustainability efforts and aligning with global climate action goals. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

15 pages, 2050 KiB  
Article
Elevating Wafer Defect Inspection with Denoising Diffusion Probabilistic Model
by Ping-Hung Wu, Thi Phuong Hoang, Yen-Ting Chou, Andres Philip Mayol, Yu-Wei Lai, Chih-Hsiang Kang, Yu-Cheng Chan, Siou-Zih Lin and Ssu-Han Chen
Mathematics 2024, 12(20), 3164; https://doi.org/10.3390/math12203164 - 10 Oct 2024
Cited by 1 | Viewed by 1795
Abstract
Integrated circuits (ICs) are critical components in the semiconductor industry, and precise wafer defect inspection is essential for maintaining product quality and yield. This study addresses the challenge of insufficient sample patterns in wafer defect datasets by using the denoising diffusion probabilistic model [...] Read more.
Integrated circuits (ICs) are critical components in the semiconductor industry, and precise wafer defect inspection is essential for maintaining product quality and yield. This study addresses the challenge of insufficient sample patterns in wafer defect datasets by using the denoising diffusion probabilistic model (DDPM) to produce generated defects that elevate the performance of wafer defect inspection. The quality of the generated defects was evaluated using the Fréchet Inception Distance (FID) score, which was then synthesized with real defect-free backgrounds to create an augmented defect dataset. Experimental results demonstrated that the augmented defect dataset significantly boosted performance, achieving 98.7% accuracy for YOLOv8-cls, 95.8% box mAP for YOLOv8-det, and 95.7% mask mAP for YOLOv8-seg. These results indicate that the generated defects produced by the DDPM can effectively enrich wafer defect datasets and enhance wafer defect inspection performance in real-world applications. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

19 pages, 3268 KiB  
Article
Obtaining Conservative Estimates of Integrated Profitability for a Single-Period Product in an Own-Branding-and-Manufacturing Enterprise with Multiple Owned Channels
by Rung-Hung Su, Chia-Ding Hou and Jou-Yu Lee
Mathematics 2024, 12(13), 2080; https://doi.org/10.3390/math12132080 - 2 Jul 2024
Viewed by 1082
Abstract
The achievable capacity index (ACI) is a simple and efficient approach for estimating the profitability of newsboy-type products, wherein profitability is defined as the probability of achieving the target profit by optimizing the order quantity. At present, the ACI is applicable to single [...] Read more.
The achievable capacity index (ACI) is a simple and efficient approach for estimating the profitability of newsboy-type products, wherein profitability is defined as the probability of achieving the target profit by optimizing the order quantity. At present, the ACI is applicable to single retail stores (i.e., single demand) but not to multiple sales channels (i.e., multiple demand). This paper presents an integrated achievable capacity index (IACI) by which to measure the aggregate profitability of multiple mutually independent channels under normally distributed demand. An unbiased IACI estimator is also developed, to which is applied the Taylor expansion to approximate its sampling distribution, wherein the sizes, means, and variances of demand differ in each channel. Furthermore, overestimates due to sampling error are avoided by deriving the lower confidence bound for the IACI. This paper also provides generic tables to aid managers seeking conservative estimates of profitability. The applicability of the proposed scheme is demonstrated numerically using a real-world example involving an own-branding-and-manufacturing (OBM) enterprise with multiple owned channels. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

17 pages, 5891 KiB  
Article
Lifetime Distribution for a Mixed Redundant System with Imperfect Switch and Components Having Phase–Type Time-to-Failure Distribution
by Myung-Ki Baek and Heungseob Kim
Mathematics 2024, 12(8), 1191; https://doi.org/10.3390/math12081191 - 16 Apr 2024
Viewed by 1004
Abstract
Recently, a mixed redundancy was introduced among the redundant design strategies to achieve a more reliable system within the equivalent resources. This study deals with a lifetime distribution for a mixed redundant system with an imperfect fault detector/switch. The lifetime distribution model was [...] Read more.
Recently, a mixed redundancy was introduced among the redundant design strategies to achieve a more reliable system within the equivalent resources. This study deals with a lifetime distribution for a mixed redundant system with an imperfect fault detector/switch. The lifetime distribution model was formulated using a structured continuous Markov chain (CTMC) and considers the time-to-failure (TTF) distribution of a component as a phase-type distribution (PHD). The model’s versatility and practicality are enhanced because the PHD can represent diverse degradation patterns of the components exposed to varied operating environments. The model provides accurate reliability for a mixed redundant system by advancing the approximate reliability function suggested in previous studies. Furthermore, the model would be useful in system design and management because it provides information such as the nth moment of the system’s lifetime distribution. In numerical experiments on some examples, the mixed redundancy was confirmed to devise a more reliable system than the existing active and standby redundancies, and the improvement effect increased as the number of redundant components decreased. The optimal structure for maximizing the expected lifetime of the system changes depends on the reliability of the components and fault detector/switch. Full article
(This article belongs to the Special Issue Applied Statistics in Management Sciences)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop