Future Performance Research Articles

Behavioral Beliefs about Acts of Academic Dishonesty: A study with Brazilian accounting students

This study seeks to identify, with the support of the Theory of Planned Behavior (TPB), individual behavioral beliefs that determine academic dishonesty behaviors. Qualitative research was conducted with Brazilian students and revealed their perceptions on academic dishonesty behaviors. According to the results, students perceive that fraud can lead to a better academic performance and less effort or time spent on academic tasks, but it can also result in punishment and embarrassment when it’s perceived by faculty, as well as impair learning and concerns about their future professional performance. The research contributes to the construction of an instrument for collecting and measuring beliefs, which can be considered as a relevant contribution to the literature and to understanding fraudulent behaviors.

A practical guide to improve sleep and performance in athletes

Sleep is vital for optimal mental and physical health. For athletes, optimizing sleep is becoming a popular strategy to enhance athletic performance. Athletes often complain of sleep problems including insufficient sleep and insomnia symptoms and are also at a higher risk for sleep disordered breathing. Sleep disorders and insufficient sleep can contribute to excessive sleepiness, daytime dysfunction, and performance problems. In contrast, better sleep provides benefits for physical health and athletic performance. For athletes, multiple factors can contribute to insufficient sleep. Sport-specific factors include frequent travel across time zones, competition and training schedules, high training loads, and sleeping in an unfamiliar environment. Non-sport-related factors include work, social, and family commitments; attitudes and sleeping beliefs; individual characteristics, such as chronotype or preference for morning or evening; and lifestyle choices. Fortunately, there are strategies that can be implemented to improve sleep in athletes including (a) education and emphasis on the importance of sleep; (b) sleep screening; providing extra sleep opportunities like (c) banking sleep and (d) napping; improving sleep hygiene like (e) proper light exposure; (f) a good pre-sleep routine; (g) a conducive sleep environment; (h) a strategy for supplementation; (i) utilizing circadian timing adjustments; and (j) jet lag management. Increased recognition of the importance of sleep from sport professionals and screening for sleep disorders and disturbances will be key for future athlete health, well-being, and performance.

197 Evaluating the Associations Between Piglet’s Characteristics at Birth and Growth Performance During Lactation Period on Piglets from Hyperprolific Sows

Abstract This study aimed to identify the impact of birth body weight (BBW) and average daily gain (ADG) during the first week (ADG07) on the weaning body weight (WBW) of piglets from hyperprolific sows, as well as to evaluate the role played by other perinatal factors against the ADG07 and WBW. A total of 1,398 piglets [(Landrace x Yorkshire) x Pietrain] born from 87 sows between first and tenth parity (mean ± SD: 3.7 ± 2.2) were used. Each farrowing was monitored to record birth order (BO), birth time (BT), BBW, sex (SX), rectal temperature (RT), and total number of piglets born. Vitality score (VS) was established by monitoring udder stimulation and number of completed circles around the enclosure. At day 1 of life, litters were equalized to 15 piglets (62.17 ± 19.44 % BBW > 1.15 kg piglets; 37.83 ± 19.44 % BBW ≤ 1.15 kg piglets per litter). Piglets were individually weighed after litter equalization, at day 7, and at weaning (26.1 ± 0.45 d). Linear mixed models were fitted to the two study outcomes (ADG07 and WBW) and all possible explanatory variables. The adoptive sow was used as the random effect. Stepwise backward elimination of fixed effects was done to obtain optimized models. Differences between optimized models with or without fixed effects interactions were tested by ANOVA. The individual impact of BBW and ADG07 on WBW was analyzed with individual linear mixed models including only the explanatory variable to be studied (BBW or ADG07). The interaction BBW x RT (P < 0.001) fitted the best model for ADG07 prediction (Marginal R-sq = 0.22). Concerning the BBW, despite being a significant predictor (P < 0.001), it did not explain a great fraction of the variation of ADG07 (R-sq = 0.21). Increments of 100 g in BBW were associated with ADG07 increments of 8.9 g/d. The WBW final model (Marginal R-sq = 0.64) had BBW (P < 0.001), ADG07 (P < 0.001), and VS (P = 0.03) as significant predictors. Individual linear mixed models showed that ADG07 was a better predictor than BBW on WBW (R-sq = 0.59 vs. 0.31). Interaction BBW x ADG07 was significant (P < 0.001), indicating that ADG07 had a greater impact on WBW in piglets with low BBW. Regarding VS, piglets with the best VS at birth had better WBW compared with piglets with the least VS at birth (7.06 ± 1.92 vs. 6.47 ± 1.87 kg). These results suggest that growth performance during the first week has at least an equivalent influence as BBW on WBW, giving an early-life window of opportunity to apply strategies to improve the future performance of the piglets. The VS and RT have a significant role in ADG07 and WBW models.

How to improve quality investing

In this article, we evaluate the relationship between quality investing combined with Economic Moat, ESG (Environmental, Social and Governance) and analyst opinions over the period 2014–2020 based on a data set comprising 803 US stocks. Performance is evaluated using several metrics (returns and alphas). Our results show that quality stocks measured by return on invested capital (ROIC) exhibit superior performance. The incorporation of competitive advantages allows a better discrimination among the classic high-quality strategies. Investment in stocks with quality and high ESG entails the payment of a premium but buying quality companies with Economic Moat makes up for this negative aspect. The results show how quality companies that have competitive advantages obtain a better future performance and are recognized by the market with a higher valuation. However, the markets may take time to recognize this value since the incorporation of the average Price-to-Price target (Analyst consensus) increases the future performance. JEL classification: G11; G14; G23

Machine learning and fund characteristics help to select mutual funds with positive alpha

Machine-learning methods exploit fund characteristics to select tradable long-only portfolios of mutual funds that earn significant out-of-sample annual alphas of 2.4% net of all costs. The methods unveil interactions in the relation between fund characteristics and future performance. For instance, past performance is a particularly strong predictor of future performance for more active funds. Machine learning identifies managers whose skill is not sufficiently offset by diseconomies of scale, consistent with informational frictions preventing investors from identifying the outperforming funds. Our findings demonstrate that investors can benefit from active management, but only if they have access to sophisticated prediction methods.

Limits to Hole Mobility and Doping in Copper Iodide.

Over one hundred years have passed since the discovery of the p-type transparent conducting material copper iodide, predating the concept of the "electron-hole" itself. Supercentenarian status notwithstanding, little is understood about the charge transport mechanisms in CuI. Herein, a variety of modeling techniques are used to investigate the charge transport properties of CuI, and limitations to the hole mobility over experimentally achievable carrier concentrations are discussed. Poor dielectric response is responsible for extensive scattering from ionized impurities at degenerately doped carrier concentrations, while phonon scattering is found to dominate at lower carrier concentrations. A phonon-limited hole mobility of 162 cm2 V-1 s-1 is predicted at room temperature. The simulated charge transport properties for CuI are compared to existing experimental data, and the implications for future device performance are discussed. In addition to charge transport calculations, the defect chemistry of CuI is investigated with hybrid functionals, revealing that reasonably localized holes from the copper vacancy are the predominant source of charge carriers. The chalcogens S and Se are investigated as extrinsic dopants, where it is found that despite relatively low defect formation energies, they are unlikely to act as efficient electron acceptors due to the strong localization of holes and subsequent deep transition levels.

R&D grants and medical innovation

This paper examines the relationship between government-funded R&D grants in the US and pharmaceutical firm innovation. We find a positive and robust relationship between grant receipt, future patents, and medical innovations. The strength of the relationship between R&D grants and pharmaceutical innovation is attenuated by firm lobbying but strengthened by industry competition, geographic dispersion, and leverage. Investors recognize the unequal value added by grant receipt. R&D grant receipt also impacts future financial performance and sales growth. Our results indicate that the relationship between R&D and innovation is more nuanced than previously identified.

Waterproofing Performance Evaluation and Grading Methods for Lowest Level Floor Slabs and Positive-Side Walls of Residential Underground Structures

In Korea, large-scale apartment projects often give rise to disputes among residents, which have prompted implementation of the “Apartment Performance Rating System” by the Ministry of Land, Infrastructure, and Transport. In addition, disputes related to leakage defects in apartment structures are increasing, especially in underground spaces of joint residential complexes. This study aims to identify waterproofing materials and methods for specific underground structure components through experimental evaluations and to assign waterproofing performance ratings similar to existing apartment house grades. These performance ratings will serve as foundational data to prevent leakage in joint residential complexes. This study proposes composite and self-adhesive sheet waterproofing as effective methods, emphasizing the significance of sheet waterproofing materials for excellent performance. The need for improved waterproofing materials to address long-term permeability issues is also highlighted. This research provides essential data for future waterproofing performance ratings; therefore, contributing to construction quality and safety in joint residential complexes.

Modeling novice law enforcement officers’ interaction with in-vehicle technology

Cognitive performance models have been used in several human factors domains such as driving and human-computer interaction. However, most models are limited to expert performance with rough adjustments to consider novices despite prior studies suggesting novices' cognitive, perceptual, and motor behaviors are different from experts. The objective of this study was to develop a cognitive performance model for novice law enforcement officers (N-CPM) to model their performance and memory load while interacting with in-vehicle technology. The model was validated based on a ride-along study with 10 novice law enforcement officers (nLEOs). The findings suggested that there were no significant differences between the N-CPM and observation data in most cases, while the results of the benchmark model were different from that of N-CPM. The model can be applied to improve future nLEO's patrol mission performance through redesigning in-vehicle technologies and training methods to reduce their workload and driving distraction.

Reading Comprehension: An Essential Process for the Development of Critical Thinking

People have the right to receive a quality of education that promotes, among other things, reading comprehension and the development of critical thinking. In Ecuador, there is a need to implement strategies and design educational programs to encourage and facilitate the development of these skills. This research focuses on the relationship between reading comprehension and the development of critical thinking, with a particular interest in the education of high school students in Ecuador. This research aims to analyze the relationship between reading comprehension and critical thinking, based on the experiences of a sample of high school students of both genders, aged between 12 and 16 years, from five schools in different regions of Ecuador. The study adopts a quantitative, retrospective, and correlational approach. The surveys, administered to a sample of students, showed that teachers actively encourage reading and implement timely educational strategies and teaching methods to develop critical thinking, recognizing its crucial role in future professional performance.

Nonprofessional Investor Judgments: Linking Dependent Measures to Constructs

ABSTRACTThere is limited evidence on the construct validity of the dependent measures commonly used in the literature on nonprofessional investor judgments. In this paper, we first survey the literature to understand the types of dependent measures typically used by researchers. We then conduct factor analyses to uncover linkages between dependent measures and the constructs underlying these nonprofessional investor judgments. Our results suggest that, while the wide variety of dependent measures can appear on their face to represent many nuanced economic constructs, these measures capture three distinct factors. These factors relate to nonprofessional investors’ (1) expectations regarding future firm performance and value, (2) holistic perceptions of the firm, and (3) evaluations of the risk associated with investing in the firm. Next, we provide recommendations for selecting, analyzing, and reporting dependent measures in future research. Finally, we provide directions for future research to further our understanding of the judgments made by investors.

Are they worth it? – An evaluation of predictions for NBA ‘Fantasy Sports’

Abstract‘Fantasy Sports’ - an internet-based game in which participants chose virtual teams of real professional athletes - has recently gained in popularity. Various firms provide projections regarding athletes’ future performance to help participants choose their virtual teams. We evaluate such forecasts based on 1658 projections regarding NBA basketball of four selected projection providers that were collected in February 2022. We calculate standard measures of forecast quality and find that the use of professional forecasts reduces the errors made in naïve forecasts, but only to a moderate extent. Applying regression-based tests of forecast efficiency, we find that the predictions are inefficient and, in some cases, even biased. Third, pairwise comparisons of the accuracy of the providers suggest notable differences among such providers in the short run. We use a simple optimization algorithm to choose a virtual team for each match day and feed it with the forecasts of the providers. Subsequently, we rank the providers according to the score obtained by these teams. We find small, although in one case significant, long-run differences between the providers, among whom each provides better accuracy than that of a naïve projection based on these athletes’ past performances. Finally, we simulate one-on-one competition among various forecast providers to ascertain the long-term profitability of their services. Given the small magnitude of the detected differences, our results, in brief, raise doubts as to whether the forecasts provided are worth the money.

Paid medical malpractice claims: How strongly does the past predict the future?

AbstractWhen does the past predict the future? In financial markets, warnings that “past results are no guarantee of future performance” are ubiquitous. But in multiple fields (including professional sports, insurance, and criminal law), it is widely believed that the past is a useful guide to the future. Does that insight apply to medical malpractice (“med mal”)? Using a novel dataset (which includes detailed data on all licensed physicians and all paid claims in Illinois over a 25‐year period), we study whether past paid med mal claims, physician characteristics, and specialty predict future paid med mal claims. After controlling for other factors, physicians with a single prior paid claim have a fourfold higher risk of future claims than physicians with zero prior paid claims. The more prior paid claims a physician has, the higher the likelihood of a future paid claim. Multiple factors (male gender, having an MD, attending a non‐U.S. medical school, practicing in a high‐claim‐risk specialty, and mid‐career status [6–15 prior years of experience]) predict a higher likelihood of having one or more paid med mal claims.

Enhancing school buildings energy efficiency under climate change: A comprehensive analysis of energy, cost, and comfort factors

Incorporating future weather predictions into building assessments is essential for enhancing resilience, energy efficiency, cost savings, comfort, and sustainable infrastructure development in response to climate change. This study investigates the interplay between climate change and building performance, primarily focusing on energy usage, cost implications, and occupant comfort. It examines how future weather conditions impact school buildings in different climates, analyzing energy, cost, and comfort aspects. The research underscores the significance of tailored climate adaptation strategies for various regions and emphasizes considering future performance, even for highly energy-efficient buildings. Employing a comprehensive simulation-based approach, the study implements and validates future weather data in a Turkish school building, incorporating envelope improvements and photovoltaic applications to boost energy efficiency. A distinctive feature is the rigorous validation of future weather predictions against current measured data, facilitating a regional-level assessment of climate change effects on building energy consumption. The study's novelty lies in its detailed evaluation of climate change's multifaceted impacts on buildings, innovative future climate data validation, and contribution to a more localized and climate-specific approach to addressing building energy-cost-comfort performance. Findings reveal that in hot climates, there is a potential for nearly doubling primary energy consumption, global costs, and CO2 emissions in the future for both cost-optimal and nearly zero-energy scenarios. Consequently, the savings would decrease from 53-63 % to 13–30 %. In contrast, in cold climates, the impact on these parameters differs slightly, with reduced primary energy consumption and CO2 emissions but higher global costs. Notably, a building retrofitted to a high energy efficiency level may experience a substantial increase in future energy consumption and global costs, approaching the levels of currently inefficient buildings.

Contrarians, Extrapolators, and Stock Market Momentum and Reversal

We document considerable cross-investor variation in survey expectations about aggregate stock market returns. Although most investors are extrapolators who expect higher returns after a good market performance, some are contrarians who expect lower returns after a good performance. More notably, compared with extrapolators, contrarians have less persistent expectations that are corrected more quickly. We then develop a dynamic equilibrium model accounting for these differences in expectations and find that the equilibrium stock price exhibits short-term momentum and long-term reversal as in the data. Furthermore, we test the key predictions of our model linking the observable differences in extrapolators’ and contrarians’ expectations to aggregate stock market momentum and future stock performance and find supportive evidence for our model mechanism. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4960 .

Response speed enhanced fine-grained knowledge tracing: A multi-task learning perspective

The primary objective of knowledge tracing (KT) is to trace learners’ changing knowledge states and predict their future performance by analyzing their learning trajectories. One of the fundamental assumptions underpinning KT is that estimating knowledge states is roughly equivalent to predicting future performance. However, this assumption has not been extensively explored in most studies, particularly in relation to the consistency between observable performance and latent knowledge state. To address this challenge, we propose a novel response speed enhanced fine-grained knowledge tracing (FKT) method. FKT leverages response speed through response time and integrates speed prediction as an additional task within a multi-task learning framework. Through this framework, FKT can separate representations of different knowledge state in the feature space, thereby facilitating fine-grained knowledge tracing. Moreover, we divide the task of predicting learner performance into three procedures: obtaining historical knowledge state, inferring future latent traits, and forecasting future performance. To this end, we formalize each learner’s response interaction as a time cell and develop an encoder–decoder–predictor framework for KT. To enhance the accuracy of performance prediction, we introduce a time-distance attention mechanism and knowledge proficiency component and provide two multi-task objective functions. Our experimental results on four real-world datasets demonstrate the superiority of future performance prediction and good interpretability of FKT.

The impact of cryptocurrencies capitalization on banking deposits variability in the UAE: evidence from the NARDL approach

PurposeThis study aims to analyze the effect of cryptocurrency capitalization market development on bank deposits variability in the United Arab Emirates (UAE) spanning the period 2005M1–2020M4 using the novel nonlinear autoregressive distributive lag (NARDL).Design/methodology/approachThe study employs the NARDL recently developed by Shin et al. (2014) to estimate the long and short-run relationships between the variables rather than the widely known ARDL (Pesaran et al., 2001), which suffers from a complex structure in the estimation equation that usually includes lags and differences in both short and long terms. The implementation of NARDL required several proceedings after plotting the descriptive data, commencing with unit root tests, selection of lag length, estimating the long-and-short variables coefficients, heteroscedasticity test and Wald test for symmetries.FindingsThe long-run estimations of the positive and negative asymmetric coefficients indicate that cryptocurrencies capitalization has a negative impact on bank deposits in the UAE. Further, the short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decrease bank deposits.Research limitations/implicationsThe study has applied to the UAE spanning the period 2005M1–2020M4 using the NARDL.Practical implicationsThe short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decreases bank deposits, which means that the increase in the magnitude of cryptocurrencies capitalization stimulates depositors and speculators to adjust their portfolios towards contracting their deposits in banks to invest partially in cryptocurrencies, on the other hand, the decline in cryptocurrencies capitalization process spur depositors and speculators to reduce their deposits for purchasing cryptocurrencies at lower prices.Social implicationsThe study infers that individuals and businesses are cautious when investing in cryptocurrencies, and they need more certainty and trust to include these types of assets in their portfolios. The fluctuation in cryptocurrencies capitalization prompts speculators to change their deposits according to the cryptocurrencies' prices.Originality/valueThis study explores the short-and long-run asymmetric impacts of cryptocurrencies capitalization development on bank deposits volatility in the UAE, based on a NARDL, for providing a manifest depiction of whether the cryptocurrencies industry might be a threat to conventional banking system performance in the potential future.

Differences in Burnout Aspects in Croatian Nursing Students – A Cross-Sectional Study

Introduction: Burnout syndrome is a growing concern among nursing students, potentially impacting their academic success and future professional performance. This study aimed to explore the prevalence of burnout syndrome in Croatian nursing students and examine the associations between burnout and demographic features (age, gender, year of study, part-time or full-time study). Methods: A quantitative cross-sectional study was conducted with 423 nursing students from the University of Applied Health Sciences, Zagreb, and the Faculty of Health Sciences, Rijeka. The Maslach Burnout Inventory (MBI); MBI human services survey was used to assess burnout levels. Results: Nursing students at the Faculty of Health Sciences, Rijeka, experienced higher burnout levels than those at the University of Applied Health Sciences, Zagreb (χ2 = 10.214, ss = 2, p = 0.006). Significant associations were found between burnout levels and age, gender, year of study, and enrolment status. Specifically, younger students, female students, and full-time students reported higher levels of emotional exhaustion (EE). 2nd-year students reported lower EE than their first and 3rd-year peers. Conclusions: This study underscores the importance of recognizing and addressing the unique needs and stressors faced by different subgroups of nursing students. Tailored interventions and support systems are essential for alleviating burnout and promoting well-being in nursing students. Further research, including longitudinal studies, is required to better understand burnout progression and to inform the development of effective strategies for reducing burnout in nursing education.

Associations among post-partum rumen fill and motility, subclinical ketosis and fertility in Holstein dairy cows

This prospective observational study aimed to investigate the association of rumen fill and motility in post-partum Holstein cows with their future reproductive performance and subclinical ketosis (SCK). The study population consisted of two independent data sets: the first (DS1) included 237 cows from 6 herds and the second one (DS2) 709 cows from 9 herds. Rumen Fill Score (RFS) was transformed into a 3 level-trait, representing very low, low and adequate dry matter intake, respectively. A binary Rumen Contraction Score (RCS) was defined as: 0: <2 contractions/2 min, impaired rumen motility and 1: ≥2 contractions/2 min, normal rumen motility. A combined binary trait based on RFS and RCS (RFCS) was also established, representing unsatisfactory and satisfactory rumen function. Three SCK traits were defined, based on 3 different thresholds, SCK_I: BHB≥1,000 mmol/L, SCK_II: BHB≥1,100 mmol/L and SCK_III: BHB≥1,200 mmol/L. Scores were assessed and blood samples collected on day 7 (DS1) or day 8 (DS2), postpartum. Kaplan-Meier survival analysis, multivariable Cox proportional hazards models and Generalized Linear Mixed Models were performed to evaluate the association of rumen and SCK traits with reproduction. Herd, parity, calving season and several postparturient diseases were also included as potential explanatory variables. Mean days from calving to pregnancy after the 1st artificial insemination (AI) and from calving to pregnancy (all AIs) were shorter for levels of rumen traits representing adequate DMI and normal rumen motility; in most cases these differences were statistically significant in both datasets. Cows with adequate DMI and normal rumen motility (only in DS2) had greater hazard (hazard ratio [HR] = 1.84 and 1.61, for RFS and RFCS, respectively) and odds (odds ratio [OR] = 2.49 and 1.98, for RFS and RFCS, respectively) for pregnancy at 1st AI. Assessment of the association of examined rumen traits with hazard and odds for pregnancy at all AIs yielded statistically significant results in both datasets. For RFS, RCS and RFCS, HRs ranged from 1.57 to 3.31 and ORs from 1.95 to 4.83. No statistically significant associations with hazard and odds for pregnancy at 1st or all AIs were detected, for any of the 3 SCK traits, in either dataset. Overall, the combined RFCS trait constantly identified more than twice the number of cows with future reproductive problems than a positive SCK blood test.

Nonlinear dynamics and chaos control of circular dielectric energy generator

The current study focuses on the nonlinear dynamics of the dielectric elastomer generator (DEG). To begin with, we will go through DEG’s operating principles, parameters, materials, and deformation modes. On this basis, the dynamical modeling for the nonlinear behavior of the DEG system is described, and the second-order nonlinear ordinary differential equation representing radially symmetric motion is derived using Hamilton’s variational principle. A static applied electric field allows the DEG system to attain two equilibrium states: thick and thin. The effects of the stiffening phenomenon on the dynamics of the DEG system are investigated. The system converges to a stable equilibrium point under constant loads, and the convergence position and velocity are closely related to both the initial states. Subjected to periodic loads, certain phenomena such as quasiperiodicity and chaos are detected, and the chaotic phenomena are explored using the bifurcation diagram and 0-1 chaos test. Furthermore, parametric studies are carried out using numerical analyses to demonstrate the influence of load amplitude and external frequency on the dynamics of the DEG system. Once the DEG enters the chaotic regime, the chaotic zone is transformed into a stable manifold using established chaos control techniques such as system parameter change and parametric perturbation. However, because these techniques require changes in system design, we proposed a chaos control by using a non-linear controller, specifically, adaptive integral backstepping sliding mode control (AIBSMC) as one demonstrative candidate. The controller also enables the DEG system to follow motion along a predefined trajectory. The current work may be expected to substantially impact the future design and performance of energy harvesters.