Rejection Decisions Research Articles

Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components

Background: The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. Our goal is to develop an application that can make real-time decisions to maximize total performance while adapting to the dynamic nature of incoming orders. We formulate the DVRP as a vehicle routing problem where new customer requests arrive dynamically, requiring immediate acceptance or rejection decisions. Methods: This study leverages reinforcement learning (RL), a machine learning paradigm that operates via feedback-driven decisions, to tackle the DVRP. We present a detailed RL formulation and systematically investigate the impacts of various state-space components on algorithm performance. Our approach involves incrementally modifying the state space, including analyzing the impacts of individual components, applying data transformation methods, and incorporating derived features. Results: Our findings demonstrate that a carefully designed state space in the formulation of the DVRP significantly improves RL performance. Notably, incorporating derived features and selectively applying feature transformation enhanced the model’s decision-making capabilities. The combination of all enhancements led to a statistically significant improvement in the results compared with the basic state formulation. Conclusions: This research provides insights into RL modeling for DVRPs, highlighting the importance of state-space design. The proposed approach offers a flexible framework that is applicable to various variants of the DVRP, with potential for validation using real-world data.

Modeling drivers’ dilemma at unsignalized T-intersections under mixed traffic conditions: A case study from India

Objective At unsignalized T-intersections, right turning drivers from major or minor roads have to accept or reject the available gap and cross the intersection. Poor judgment may arise risk of collision with the major road conflicting vehicles. Subject drivers intending to cross the intersection encounter wide range of gaps. Drivers accept large gaps and reject small gaps. However, drivers experience dilemma over a wide range of gaps. This study aims to examine dilemma experienced by the right turning drivers by modeling gap acceptance and rejection decisions for estimating dilemma zone boundaries on major road. Methods Videographic method was considered for collecting traffic movement data at unsignalized T-intersections. Traffic video data was collected at three specific unsignalized T-intersections with varying degree of channelization. After this, accepted and rejected gaps with different traffic characteristics of offending vehicles (subject drivers) and conflicting vehicles such as speed, distance, vehicle type, etc. for right turning movements were extracted from the video data to analyze gap acceptance and rejection decisions of the drivers and estimate dilemma zone boundaries. Results Gap decisions (acceptance or rejection) were modeled using Generalized Linear Model (GLM) as a function of conflicting vehicle type, speed, and distance from the intersection along with degree of channelization for major and minor roads. The results showed that gap rejection probability increased with increment in conflicting vehicle’s speed and decrement in conflicting vehicle’s distance from the intersection. Dilemma zone boundaries were obtained using developed GLM models by estimating the conflicting vehicle distance from the intersection for 90% and 10% gap rejection probabilities. Dilemma zone boundaries were observed to shift farther from the intersection with increase in vehicle speed and vehicle size. The analysis revealed that subject drivers experienced more dilemma while accepting a gap from major road as compared to minor road. Conclusions This study showed that channelization plays a major role in mitigating dilemma of the subject drivers. Overall, the study identified dilemma zone boundaries for unsignalized T-intersections which may assist the right turning subject drivers to cross the intersection safely.

Publishing in Hospitality and Tourism Journals

This study aims to identify the criteria reviewers use to determine whether to accept or reject empirical manuscripts and to define which criteria are more significant. In this exploratory study, which utilizes qualitative research methods, 16 members of the Scientific Committee of the National Tourism Congress of Turkiye were asked to identify the primary areas they focus on when reviewing a manuscript. The data was analyzed using content analysis to determine the most significant criteria. The study identifies six criteria for acceptance and seven for rejection. The most important criterion for acceptance is the appropriateness and adequacy of the research method, while the most crucial criterion for rejection is methodological weakness. Other criteria influencing the reviewers' acceptance or rejection decisions focus on similar issues. The critical factor that distinguishes them is how the manuscript meets the requirements established by the reviewers. The study provided recommendations for future researchers.

Trial- vs. cycle-level detrending in the analysis of cyclical biomechanical data

Biomechanical time series may contain low-frequency trends due to factors like electromechanical drift, attentional drift and fatigue. Existing detrending procedures are predominantly conducted at the trial level, removing trends that exist over finite, adjacent time windows, but this fails to consider what we term ‘cycle-level trends’: trends that occur in cyclical movements like gait and that vary across the movement cycle, for example: positive and negative drifts in early and late gait phases, respectively. The purposes of this study were to describe cycle-level detrending and to investigate the frequencies with which cycle-level trends (i) exist, and (ii) statistically affect results. Anterioposterior ground reaction forces (GRF) from the 41-subject, 8-speed, open treadmill walking dataset of Fukuchi (2018) were analyzed. Of a total of 552 analyzed trials, significant cycle-level trends were found approximately three times more frequently (21.1%) than significant trial-level trends (7.4%). In statistical comparisons of adjacent walking speeds (i.e., speed 1 vs. 2, 2 vs. 3, etc.) just 3.3% of trials exhibited cycle-level trends that changed the null hypothesis rejection decision. However 17.6% of trials exhibited cycle-level trends that qualitatively changed the stance phase regions identified as significant. Although these results are preliminary and derived from just one dataset, results suggest that cycle-level trends can contribute to analysis bias, and therefore that cycle-level trends should be considered and/or removed where possible. Software implementing the proposed cycle-level detrending is available at https://github.com/0todd0000/detrend1d.

Coordinating scheduling and rejection decisions in a two-machine flow shop scheduling problem

We study a two-machine flow shop scheduling problem where any operation can be rejected at a certain cost. A solution for such a problem requires two sets of decisions. The first involves the partition of the set of operations into two subsets: the set of operations that are accepted for scheduling in the shop, and the set of rejected operations. The second decision involves scheduling the set of accepted operations in the shop. The objective is to find a solution that minimizes the sum of the makespan and the total rejection cost. We prove that the problem is NP-hard even if all processing operations have identical processing times and identical rejection costs on either one of the two machines. We show, however, that the problem is fixed parameterized tractable with respect to a parameter that combine the number of different processing times on both machines with the number of different rejection costs on one out of the two machines. We also provide a pseudo-polynomial time algorithm for the problem, which we then convert into a fully polynomial time approximation scheme. This is achieved by dividing the problem into a set of subproblems and deriving a fully polynomial time approximation scheme for each one of them, separately. Finally, we present an integer linear programming formulation of the problem and two simple 2-approximation algorithms.

Dynamic container slot allocation for a liner shipping service

In this paper, we study a dynamic container slot allocation problem (DCSAP) for a liner container shipping company that aims to make an acceptance or rejection decision to each dynamically arriving container slot booking request. To capture the dynamic arrival feature and real-time acceptance/rejection decision of the booking request, we formulate the DCSAP as a dynamic programming (DP) model with the objective of maximizing the total revenues generated by accepted container booking requests over the entire booking horizon. Due to the well-known curse of dimensionality of solving a DP model, we develop a series of models to transform the intractable DP model into a solvable approximate linear programming (ALP) model. We further propose a spatiotemporal-heterogeneity-based (STH-based) decomposition preprocessor by identifying the spatiotemporal property of the DCSAP before solving the ALP model. Extensive numerical experiments are conducted to assess the applicability of the developed research methodology.

Online multiple hypothesis testing.

Modern data analysis frequently involves large-scale hypothesis testing, which naturally gives rise to the problem of maintaining control of a suitable type I error rate, such as the false discovery rate (FDR). In many biomedical and technological applications, an additional complexity is that hypotheses are tested in an online manner, one-by-one over time. However, traditional procedures that control the FDR, such as the Benjamini-Hochberg procedure, assume that all p-values are available to be tested at a single time point. To address these challenges, a new field of methodology has developed over the past 15 years showing how to control error rates for online multiple hypothesis testing. In this framework, hypotheses arrive in a stream, and at each time point the analyst decides whether to reject the current hypothesis based both on the evidence against it, and on the previous rejection decisions. In this paper, we present a comprehensive exposition of the literature on online error rate control, with a review of key theory as well as a focus on applied examples. We also provide simulation results comparing different online testing algorithms and an up-to-date overview of the many methodological extensions that have been proposed.

Augmented reality and indoor positioning based mobile production monitoring system to support workers with human-in-the-loop

With the increasing demand for product customization, the exponential increase in large-scale and small-batch production orders has yielded new challenges for the capacity of traditional production lines. Due to the information redundancy and complex production process on the production site of the factory, the traditional monitoring system is incapable of meeting the information interaction requirements between the factory management level and the executive level. Meanwhile, the traditional augmented reality (AR) based on image recognition is not suitable in the complex industrial environments. To address the gap, we propose a novel mobile production monitoring system (AIMPMs) with human-in-the-loop control by leveraging the cutting-edge AR and indoor positioning technique. In the proposed system, Ultra-wideband (UWB) and Inertial Measurement Unit (IMU) fusion indoor positioning technology is proposed, which provides accurate indoor positioning information for the production factors in the factory. Subsequently, we build the lightweight indoor map for positioning that can serve as the location reference and path planning, and a nearest-neighbor decision algorithm with double rejection decision (NN-DRD) is proposed to match the positioning features to trigger virtual monitoring information. Finally, the AIMPMs is applied in a hydraulic cylinder factory to verify its enforceability and effectiveness, and the human factors evaluation model and index system are constructed to evaluate two systems, (1) the mobile monitoring system based on positioning information, and (2) the mobile monitoring system based on image recognition, respectively. The experimental results indicate that after the application of AIMPMs, the physiological and mental fatigue of the production personnel is immensely decreased. Therefore, the system realizes a smarter and highly humanized human-machine interaction mode with human-in-the-loop control.

Should the Board Have Control over Shareholder Proposals? Evidence from China

Abstract This Article empirically investigates the impacts of the board’s rejection of shareholder proposals on corporate value and the appropriate approach to regulation. The study utilizes a dataset of such incidents in China, where the board enjoys significant discretion in rejecting proposals due to the inadequacy of legal enforcement mechanisms. The findings provide suggestive evidence that the market reacts negatively to the announcement of proposal rejections, leading to a significant decline in a firm’s stock value. The most adverse effects are associated with rejections of director nomination proposals and blockholder-sponsored proposals. The inclusion of external legal opinions can help alleviate these adverse consequences. Additionally, the research uncovers that while the two stock exchanges in China demonstrate overall competence in identifying harmful rejection decisions, the effectiveness of their regulatory actions via comment letters is hindered by the inherent weakness of the soft law approach. Drawing upon these results, this study posits that the critical value of the shareholder proposal regime lies in providing a low-cost approach for dissident shareholders to replace poorly performing management and facilitating the constructive engagement of large shareholders and the management. Furthermore, it is recommended that China establish an SEC-style review process for board rejection decisions, with the exchanges as the ultimate authority permitting the exclusion of shareholder proposals.

Plagiarism detection in manuscripts submitted to the <i>Journal of Surgical Sciences</i> between 2020 and 2021: a case study

The aim of this study was to share our experience with plagiarism detection in manuscripts submitted to the <i>Journal of Surgical Sciences</i>, a Romania-based medical journal, between 2020 and 2021. We analyzed similarity score reports from 200 articles submitted consecutively for publication between 2020 and 2021 generated by PlagScan, a software tool for plagiarism detection. The similarity score ranged from 0% to 92.4%, and 45 articles presented scores over 25.0%. According to PlagScan’s results, more than half of the submitted articles had a similarity score of more than 10% and one-third of them had a similarity score above 20%. Among submitted manuscripts with a similarity score of less than 20%, a larger proportion of the original research and review manuscripts than case reports used more than 10 sources. All articles with a similarity score below 20% were evaluated qualitatively before the final decision of rejection.

Prevention of multiple whole blood donations by an individual at the same month through the creation of a national Deferred Donor Registry (DDR)

IntroductionThe Colombian National Institute of Health administers the National Information System of Haemovigilance (SIHEVI-INS). Today, SIHEVI-INS constitutes a national blood donor and recipient database, which contains a national deferred donor registry (DDR), allowing blood banks to take acceptance or rejection decisions of a potential donor in real time. The study aimed to determine the rate of people who have made more than one whole blood donation monthly in Colombia, violating the national guideline of intervals between donations (three months for men and four for women), since DDR implementation. MethodsWe detected the unique personal identification number of people who, in 30 calendar days, made more than one whole blood donation at any of the 83 blood banks set up in Colombia. There were three comparison periods: 01/01/2018–08/31/2019 (launch of SIHEVI-INS and first national feedback); 09/01/2019–12/31/2020 (second feedback) and 01/01/2021–09/30/2022 (massive incorporation of web services). ResultsFor the first period, blood banks accepted 18.0 donations per 1000 people. There was a rate of 28.8 people/10,000 donations who had donated whole blood twice within 30 days. In the second period, there were 17.0 donations/1000 people and a rate of 2.1 people/10,000 donations (OR:14.0 CI95 %:12.2–16.0). For the last period, there were 18.2 donations/1000 people and a rate of 0.9 individuals/10,000 donations (OR:31.3 CI95 %:26.6–36.9, p < 0.001). ConclusionDDR reduced by 31 times the acceptance of blood donors who made more than one whole blood donation in the same month. It was necessary to provide periodic feedback and promote web service implementation to reduce this risky behavior.

Decision rules for egg-color-based rejection by two cavity-nesting hosts of the brown-headed cowbird.

Hosts of obligate avian brood parasites often evolve defense mechanisms to avoid rearing unrelated young. One common defense is egg rejection, for which hosts often rely on eggshell color. Most research has assumed that hosts respond to perceived color differences between their own eggs and parasite eggs regardless of the particular color; however, recent experiments have found that many hosts respond more strongly to brown foreign eggs than to equally dissimilar blue eggs. Yet, none of these prior studies tested a brown-egg-laying species and, with only one exception, all were conducted in open nests where light levels are considered sufficient for effective color-based egg discrimination. Here, we explored how two cavity-nesting hosts of the parasitic brown-headed cowbird (Molothrus ater) - the blue-egg-laying eastern bluebird (Sialia sialis) and the brown-egg-laying house wren (Troglodytes aedon) - respond to experimental eggs painted six distinct colors ranging from blue to brown. Rejection responses of both hosts were best predicted by perceived differences in color between the model egg and their own eggs. Specifically, we found that house wrens preferentially rejected eggs bluer than their own eggs. However, although we found that bluebirds relied on perceived differences in color for their egg rejection decisions, further tests are needed to determine whether they preferentially rejected brown eggs or simply responded to absolute perceived differences in color. These findings demonstrate that these cavity-nesting birds treat perceived color differences in distinct ways, which has important implications on the coevolutionary arms races and the interpretation of avian-perceived color differences.

May Artificial Intelligence Be a Co-Author on an Academic Paper?

Dear Colleagues,&#x0D; Recently, for an article submitted to the European Journal of Therapeutics, it was reported that the paper may have been written with artificial intelligence support at a rate of more than 50% in the preliminary examination made with Turnitin. However, the authors did not mention this in the article’s material method or explanations section. Fortunately, the article’s out-of-date content and fundamental errors in its methodology allowed us no difficulty making the desk rejection decision.&#x0D; On the other hand, similar situations that we may encounter later caused us to discuss how we would decide when the artificial intelligence support of the articles was written. The general opinion that we have adopted and currently available in the literature is that if artificial intelligence is used while writing an article, how artificial intelligence is used in the methodology should be written in detail.&#x0D; Moreover, we encountered a much more exciting situation during our evaluation. In a few academic studies, we have seen that artificial intelligence is added as a co-author. On July 06, 2023, in the Web of Science, using the advanced search, we found four articles with the author name ChatGPT [1]. We have determined that ChatGPT is the author in one of these articles [2] and the Group Author in three [3-5].&#x0D; Lee [6] stated that although artificial intelligence tools are much more advanced than search engines, they cannot be an author regarding research ethics because they cannot take responsibility for what they write. Similarly, Goto and Katanoda [7] stated that it is the author’s responsibility to confirm that the texts written by ChatGPT are correct. However, Pourhoseingholi et al. [8] reported that keeping up with technology is inevitable. Additionally, they said that“this action will be more fruitful and practical in extended dimensions when international institutes like ICMJE or COPE come up with the appropriate adjustments and establish robust criteria to scheme the AI authorship”.&#x0D; Most probably, the use of artificial intelligence applications in scientific articles and whether it can be a co-author in these papers will be discussed soon.&#x0D; We encourage interested authors to submit their ideas to our journal as a letter to the editor.&#x0D; Yours sincerely,

How honey bees make fast and accurate decisions.

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

What Makes Your Business Model (Un)investable?

This paper seeks to find out what makes a business model uninvestable. In particular, the study explores the reasons for venture capitalists’ rejection decisions on entrepreneurs’ proposals. The study digs into rejected cases in the American Shark Tank TV show as the source of secondary data. Data is transcribed, coded, synthesised, narratives are built, and storytelling techniques are applied to present the findings. The study deviates from the mainstream research on business models, based on primary data. In doing so, the study bridges between the business model research and communication sciences.

Gender and early career status: variables of participation at an international marine science conference

Abstract Conference participation is an important part of academic practice and contributes to building scientific careers. Investigating demographic differences in conference participation may reveal factors contributing to the continued under-representation of women in marine and ocean science. To explore the gender and career stage dimensions of participation in an international marine science conference, preferences of presentation type (oral/poster) as well as acceptance and rejection decisions were investigated using 5-years of data (2015–2019) from an International Marine Science Conference. It was found that early career scientists were more likely to be women, while established scientists were more likely to be men. Although overall, gender did not show a significant effect on the decisions to “downgrade” requests for oral presentations to poster presentations, early career scientists were significantly more likely to be downgraded than established scientists. Given that more women were often early career scientists, more women than men had their presentations downgraded. Other indicators and evidence from conference prize-giving and recognition awards point to a gender gap remaining at senior levels, highlighting the need for further actions as well as monitoring and researching conference participation from a gender perspective.

Analyzing survey data in marketing research: A guide for academics and postgraduate students

ABSTRACT Numerous marketing scholars have been overly loyal to seminal (and out-dated) analytical processes when using surveys. If this continues, these individuals may receive rejection decisions, as the standards of the so-called publishing game have increased. Accordingly, from an Associate Editor perspective, this commentary provides a contemporary guide (with thirteen stages) on how survey data can be effectively analyzed. This covers a series of basic techniques (like treating missing values, presenting profiling information about samples, and undertaking descriptive statistical analyses), alongside describing some scale purification tools and several complex procedures (e.g., running tests for various forms of reliability and validity, addressing common method variance, and testing for endogeneity bias). Then, some conclusions and methodological recommendations are offered to help authors to advance theory and practice with robust survey data. It is anticipated that these discussion points will facilitate debates among readers of the Journal of Strategic Marketing (and beyond) about the analysis of survey data.

Development and evaluation of M + 1-way classification mechanism realized through identifying foreign patterns

In this study, we are concerned with a new design methodology of M + 1-way classification mechanism. The intent is to reduce the cost of error prediction caused by insufficient evidence. The study is motivated by the notion of three-way decisions, which has been successfully used in various application areas to build human-centric systems. In contrast to traditional multiple classifications, one additional class is added into the proposed architecture to represent the reject decision made on foreign patterns, which exhibit significant differences compared to the patterns used for constructing the classification models. A collection of information granules is constructed on the basis of available experimental evidence to form a compact and interpretable representation of the feature space occupied by the native patterns. The patterns located outside the regions occupied by these information granules are identified and filtered out prior to classification while only the native patterns are subject to classification. The proposed methodology leads to a human-centric and human-interactive construct in which the rejected patterns need further processing. Different distance functions are utilized in the construction of information granules. The performance of the proposed architecture is evaluated involving one synthetic dataset and a collection of publicly available datasets.

How to Review a Paper.

How to Review a Paper.

Who is more willing to engage in social rejection? The roles of self-esteem, rejection sensitivity, and negative affect in social rejection decisions

ABSTRACT How do self-schemas and their consequences guide would-be-rejectors? When making decisions about whether to reject, individuals consider the difficulty and emotional consequences of rejecting, and both considerations are likely to involve self-schemas. In three preregistered studies, we examine the roles of self-esteem, rejection sensitivity, and symptoms of depression and anxiety in rejection decisions. In an initial set of studies (N1a = 214, N1b = 264), participants forecast their willingness to reject and their emotional responses in friendship (Study 1a) and romantic (Study 1a-1b) vignettes. In Study 2 (N2 = 259), participants who recently rejected rated that experience on the same measures. Correlates of negative self-schema were associated with negative emotions. Self-esteem, rejection sensitivity, and general distress were associated with forecasted difficulty rejecting, but only anxiety and general distress were associated with retrospectively reported increased difficulty. Taken together, psychological distress may decrease willingness to reject in a way that participants cannot predict.