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Awards can propel academic careers. They also reflect the culture and values of the scientific community. But do awards incentivize greater transparency, inclusivity, and openness in science? Our cross-disciplinary survey of 222 awards for the "best" journal articles across all 27 SCImago subject areas revealed that journals and learned societies administering such awards generally publish little detail on their procedures and criteria. Award descriptions were brief, rarely including contact details or information on the nominations pool. Nominations of underrepresented groups were not explicitly encouraged, and concepts that align with Open Science were almost absent from the assessment criteria. At the same time, 10% of awards, especially the recently established ones, tended to use article-level impact metrics. USA-affiliated researchers dominated the winner's pool (48%), while researchers from the Global South were uncommon (11%). Sixty-one percent of individual winners were men. Overall, Best Paper awards miss the global calls for greater transparency and equitable access to academic recognition. We provide concrete and implementable recommendations for scientific awards to improve the scientific recognition system and incentives for better scientific practice. Research awards are an integral part of the universal "prestige economy" in science, but do they incentivize greater transparency, inclusivity, and openness? This study uses cross-disciplinary data to explore the level of transparency of publicly available award descriptions and assessment criteria, asking whether such awards contribute to or propagate existing reproducibility crises and inequities in science. [ABSTRACT FROM AUTHOR]

Since its onset, scholars have characterized social media as a valuable source for data collection since it presents several benefits (e.g. exploring research questions with hard-to-reach populations). Nonetheless, methods of online data collection are riddled with ethical and methodological challenges that researchers must consider if they want to adopt good practices when collecting and analyzing online data. Drawing from our primary research project, where we collected passive online data on Reddit, we explore and detail the steps that researchers must consider before collecting online data: (1) planning online data collection; (2) ethical considerations; and (3) data collection. We also discuss two atypical questions that researchers should also consider: (1) how to handle deleted user-generated content; and (2) how to quote user-generated content. Moving on from the dichotomous discussion between what is public and private data, we present recommendations for good practices when collecting and analyzing qualitative online data. [ABSTRACT FROM AUTHOR]

Research across a wide array of fields has established the organizational importance of fair treatment and why it should be a primary consideration of supervisors. As such, scholars have begun to unpack characteristics of organizations, supervisors, and employees that may promote fair treatment. Although this literature has been informative and is growing, we know little about how the dyadic interplay between leaders and followers—and, in particular, how both parties' perceptions of that joint interplay—may facilitate or hinder views of fairness. The lack of clarity on this phenomenon is particularly problematic when one considers that there are several features of dyadic relationships within work units that—by their nature—work against the facilitation of fair treatment (e.g., supervisors inevitably provide some employees more/less information, support, and attention than others because they cannot establish high-quality exchange relationships with every employee). Drawing from common threads found in theories of fairness and role theory surrounding expectation alignment, we posit that the key to facilitating views of fair treatment at any level of relationship quality is for supervisors and employees to "see eye to eye" on LMX quality-LMX agreement. We further theorize that each party's views of fair treatment flowing from LMX agreement (within the dyad) will ultimately result in leaders being more efficacious about their fairness-related abilities and employees performing at higher levels (beyond the dyad). Results of three field studies (and two supplemental preregistered experiments) largely support our theorizing and further show that fair treatment can result in a self-reinforcing positive fairness-efficacy spiral for supervisors. Funding: This research was partially funded by the University of Georgia's Institute for Leadership Advancement Research Scholar Award. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.15475. [ABSTRACT FROM AUTHOR]

A method is proposed to compute more precise standard errors for marketing A/B tests. Incrementality experiments compare customers exposed to a marketing action designed to increase sales with those randomly assigned to a control group. These experiments suffer from noisy responses, which make precise estimation of the average treatment effect (ATE) and marketing return difficult. We develop a model that improves the precision by estimating separate treatment effects for three latent strata defined by potential outcomes in the experiment—customers who would buy regardless of ad exposure, those who would buy only if exposed to ads, and those who would not buy regardless. The overall ATE is estimated by averaging the strata-level effects, and this produces a more precise estimator of the ATE over a wide range of conditions typical of marketing experiments. Analytical results and simulations show that the method decreases the sampling variance of the ATE most when (1) there are large differences in the treatment effect between latent strata and (2) the model used to estimate the strata-level effects is well identified. Applying the procedure to five catalog experiments shows a reduction of 30%–60% in the variance of the overall ATE. This leads to a substantial decrease in decision errors when the estimator is used to determine whether ads should be continued or discontinued. History: Olivier Toubia served as the senior editor. Funding: This work was supported by Adobe Systems [Adobe Digital Experience Research Award]. R. Berman was supported by the United States-Israel Binational Science Foundation [Grant 2020022] and the Wharton Dean's Research Fund, and E. M. Feit was supported by the Dean's Fellowship from LeBow College of Business. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mksc.2022.0297. [ABSTRACT FROM AUTHOR]

Trade-Offs in Dynamic Allocation Problems Food rescue organizations often receive donations to allocate to food pantries or families. Donations are unpredictable, and goods are often perishable; as a result, allocations have to be made within a short time frame after arrival without knowledge of future arrivals. It is important that donations go to organizations that are able to use them; at the same time, organizations that serve different communities should be treated equitably. In "Fair and Efficient Online Allocations," Benadè, Kazachkov, Procaccia, Psomas, and Zeng study fairness-efficiency trade-offs in such online allocation problems. Against adversarial arrivals, no algorithm can provide nontrivial guarantees for both these objectives simultaneously. When item values are drawn from (potentially correlated) distributions, there is no trade-off, and a simultaneously fair and efficient algorithm is presented. We study trade-offs between fairness and efficiency when allocating indivisible items online. We attempt to minimize envy, the extent to which any agent prefers another's allocation to their own, while being Pareto efficient. We provide matching lower and upper bounds against a sequence of progressively weaker adversaries. Against worst-case adversaries, we find a sharp trade-off; no allocation algorithm can simultaneously provide both nontrivial fairness and nontrivial efficiency guarantees. In a slightly weaker adversary regime where item values are drawn from (potentially correlated) distributions, it is possible to achieve the best of both worlds. We give an algorithm that is Pareto efficient ex post and either envy free up to one good or envy free with high probability. Neither guarantee can be improved, even in isolation. En route, we give a constructive proof for a structural result of independent interest. Specifically, there always exists a Pareto-efficient fractional allocation that is strongly envy free with respect to pairs of agents with substantially different utilities while allocating identical bundles to agents with identical utilities (up to multiplicative factors). Funding: A. Psomas is supported in part by the National Science Foundation [Award CCF-2144208] and Google [the AI for Social Good Award and the Research Scholar Award]. This work was partially supported by the National Science Foundation [Grants IIS-2147187, IIS-2229881, and CCF-2007080] and the Office of Naval Research [Grant N00014-20-1-2488]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2022.0332. [ABSTRACT FROM AUTHOR]

Background: Undertaking Patient and Public Involvement (PPI) when developing health and social care research grant applications is critical. However, researchers may not have any funding to undertake PPI when developing grants. In response, the National Institute for Health and Care Research- Research Design Service for Yorkshire and the Humber in the United Kingdom, provided Public Involvement Fund Awards of up to £600 to fund PPI activity when researchers were developing grant applications. Researchers provided post-activity reports about how they utilised the Public Involvement Fund. These reports were analysed with the aim of evaluating the usefulness of the Public Involvement Fund and to provide learning about supporting researchers to undertake PPI when developing grants. Methods: The project was a qualitative document analysis of 55 reports. Initially a researcher coded four reports and three Public Contributors provided feedback. Researchers coded the remaining reports and identified key findings. A workshop was held with the three Public Contributors to develop the findings. Results: Researchers accessing the Public Involvement Fund award were generally early career researchers or clinicians who did not have other sources of funding for pre-grant PPI input. Researchers felt the award was useful in enabling them to conduct PPI, which strengthened their grant applications. Some researchers found that the award limit of £600 and guidance encouraging expenditure within three months, made it difficult to undertake PPI throughout the full grant development process. Instead, the majority of researchers consulted Public Contributors on one or two occasions. Researchers struggled to recruit diverse members or run group sessions due to the time pressures of grant deadlines. Researchers wanted training on undertaking PPI alongside the financial support. Conclusions: Researchers, especially early career researchers found having a Public Involvement Fund award instrumental in enabling them to undertake PPI when developing grant applications. It would be beneficial for similar schemes to be widely available. Schemes need to provide sufficient funding to enable meaningful PPI and allow researchers to hold the award for long enough to facilitate involvement during the whole grant development process. Researchers continue to need training on undertaking PPI. Plain English summary: Undertaking Patient and Public Involvement (PPI) when developing health and social care research grant applications is important. This ensures that patients have a voice in deciding what topics are researched. However, researchers often do not have funding to undertake PPI when developing grants. In response, a regional research advice service in the United Kingdom established a small grant scheme (up to £600) to fund PPI activity. This was called the Public Involvement Fund (PIF). Researchers developing health and social care grant applications could apply. After spending the funding, researchers wrote reports to explain how they used the Public Involvement Fund and the challenges they faced. We analysed 55 reports submitted over a three-year period to understand researchers' experiences of the fund. Researchers found the funding critical in enabling them to undertake PPI. Many felt their grants were improved from consulting Public Contributors. For example, helping them to decide a topic, changing their research method or choosing a questionnaire. However, researchers sometimes struggled to recruit Public Contributors, particularly when the research was not about a specific health condition. Researchers wanted to be able to have the award for long enough to enable them to involve Public Contributors throughout the whole grant development process. Alongside funding, researchers also need specific training about undertaking PPI when developing grants. For example, how to recruit representative Public Contributors quickly. It is recommended that similar schemes to the PIF are available to enable researchers to fund PPI activities when developing grant applications. [ABSTRACT FROM AUTHOR]

The stock option-implied volatility skew reflects both the structural risk characteristics of the underlying company and the short-term information flow about the stock price movement. This paper builds a semistructural, cross-sectional option pricing model to separate the structural risk contributions from the information flow. The model identifies two structural risk sources that contribute to the cross-sectional variation of the skew: the company's business cyclicality and its default risk. The model can explain as much as 44% of the cross-sectional variation in implied volatility skew and is particularly informative during and after recessions. The remaining skew variation reflects mainly short-term information flow and can be used to construct stock portfolios with much better investment performance and without hidden structural risk exposures. This paper was accepted by Agostino Capponi, finance. Funding: L. Wu gratefully acknowledges support by a grant from the City University of New York PSC-CUNY Research Award Program. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4872. [ABSTRACT FROM AUTHOR]

We study structured multiarmed bandits, which is the problem of online decision-making under uncertainty in the presence of structural information. In this problem, the decision-maker needs to discover the best course of action despite observing only uncertain rewards over time. The decision-maker is aware of certain convex structural information regarding the reward distributions; that is, the decision-maker knows that the reward distributions of the arms belong to a convex compact set. In the presence of such structural information, the decision-maker then would like to minimize his or her regret by exploiting this information, where the regret is its performance difference against a benchmark policy that knows the best action ahead of time. In the absence of structural information, the classical upper confidence bound (UCB) and Thomson sampling algorithms are well known to suffer minimal regret. However, as recently pointed out by Russo and Van Roy (2018) and Lattimore and Szepesvari (2017), neither algorithm is capable of exploiting structural information that is commonly available in practice. We propose a novel learning algorithm that we call "DUSA," whose regret matches the information-theoretic regret lower bound up to a constant factor and can handle a wide range of structural information. Our algorithm DUSA solves a dual counterpart of the regret lower bound at the empirical reward distribution and follows its suggested play. We show that this idea leads to the first computationally viable learning policy with asymptotic minimal regret for various structural information, including well-known structured bandits such as linear, Lipschitz, and convex bandits and novel structured bandits that have not been studied in the literature because of the lack of a unified and flexible framework. Funding: N. Golrezaei was supported in part by the Young Investigator Program (YIP) Award from the Office of Naval Research (ONR) [Grant N00014-21-1-2776] and the MIT Research Support Award. This paper was accepted by Chung Piaw Teo, Optimization [ABSTRACT FROM AUTHOR]

European sports policies have focused on the implementation of public instruments and policy measures, aiming to encourage EU member states to promote and improve sports habits, while simultaneously tackling high levels of sedentary lifestyle among Europeans. Despite these efforts, data concerning the various measures is quite limited, making it impossible to assess the real impact on the population, particularly in the case of the European Cities of Sport. This award has been held since 2007 and has already distinguished 193 cities; however, current knowledge does not allow researchers to theorise about its multiple impacts as a strategic policy instrument for the local development of sport in Europe, thus constituting a gap within sports management research. In order to further this knowledge, we explored European reality over a decade (2013–2022), analysing nine awards of Portuguese cities. We employed qualitative methods for documentary analysis of public information and descriptive statistics for data analysis. The results show that over 2 600 multidisciplinary events were organised, among which 402 had an international character (15%), an average of 50 sports disciplines per edition, 359 events related to culture and education, and involved over 1 000 000 participants, with an overall investment of over €39 million. This research now allows a theoretical-scientific and operational referential pattern of key indicators to be established for future European ECS applications, while demonstrating an encouraging relationship, from a sports perspective and economically, between public investment made and estimated return, thus contributing to better political decisions and to the positive implications of increasing public investment in sport. [ABSTRACT FROM AUTHOR]

Social media is commonly used by governments to disseminate information related to transparency and institutional promotion, but its potential for the dissemination of cultural resources is often overlooked. This research proposes a strategy for adopting social media to achieve cultural dissemination in the municipality of Lamas, Peru, which has tourism potential and has been awarded the "Best Tourism Villages" seal of the World Tourism Organisation. Methodologically, we propose a case study at a propositional exploratory level. We start by determining the current state of dissemination of tangible and intangible resources, as well as the practical use of social media, through a survey of 20 officials. The results reveal that crafts are the most widely disseminated tangible resource in the municipality (according to 55% of officials), and intangible resources are occasionally disseminated (50%). We also find that Facebook is the only digital channel used to disseminate cultural information. In this context, we formulate a strategy for adopting social media to improve cultural dissemination, which consists of six phases: (i) forming a work team, (ii) preparing a budget plan, (iii) strengthening capacities, (iv) taking inventory of cultural resources, (v) coordinating community interests and (vi) preparing a cultural dissemination plan. The findings can contribute to formulating public initiatives for the institutionalisation of social media in governments for the purposes of preserving, promoting and guaranteeing the accessibility of cultural heritage. [ABSTRACT FROM AUTHOR]

We study combinatorial auctions with interdependent valuations, where each agent i has a private signal si that captures her private information and the valuation function of every agent depends on the entire signal profile, s=(s1,...,sn). The literature in economics shows that the interdependent model gives rise to strong impossibility results and identifies assumptions under which optimal solutions can be attained. The computer science literature provides approximation results for simple single-parameter settings (mostly single-item auctions or matroid feasibility constraints). Both bodies of literature focus largely on valuations satisfying a technical condition termed single crossing (or variants thereof). We consider the class of submodular over signals (SOS) valuations (without imposing any single crossing-type assumption) and provide the first welfare approximation guarantees for multidimensional combinatorial auctions achieved by universally ex post incentive-compatible, individually rational mechanisms. Our main results are (i) four approximation for any single-parameter downward-closed setting with single-dimensional signals and SOS valuations; (ii) four approximation for any combinatorial auction with multidimensional signals and separable-SOS valuations; and (iii) (k + 3) and (2 log(k) + 4) approximation for any combinatorial auction with single-dimensional signals, with k-sized signal space, for SOS and strong-SOS valuations, respectively. All of our results extend to a parameterized version of SOS, d-approximate SOS, while losing a factor that depends on d. Funding: A. Eden was partially supported by NSF Award IIS-2007887, the European Research Council (ERC) under the European Union's Seventh Framework Programme [FP7/2007-2013]/ERC Grant Agreement 337122, by the Israel Science Foundation [Grant 317/17], and by an Amazon research award. M. Feldman received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [Grant Agreement 866132], by the Israel Science Foundation [Grant 317/17], by an Amazon research award, and by the NSF-BSF [Grant 2020788]. The work of K. Goldner was supported partially by NSF awards DMS-1903037 and CNS-2228610 and a Shibulal Family Career Development Professorship. A. R. Karlin was supported by the NSF-CCF [Grant 1813135]. [ABSTRACT FROM AUTHOR]

The journal announces that the article "The Hidden Cost of Prayer: Religiosity and the Gender Wage Gap” by Traci Sitzmann and Beth (E.M.) Campbell won the 2021 AMJ Best Paper Award and the article "Health Care’s Grand Challenge: Stimulating Basic Science on Diseases that Primarily Afflict the Poor" by Keyvan Vakili and Anita (A.M.) McGahan won the 2022 AMJ Research Impact Award.

Information systems age ungracefully. Once-modern systems aging into unmaintainable, buggy, meltdown-prone albatrosses is a widespread phenomenon that has received limited research attention. The received wisdom is that degenerative deterioration can be combated with refactoring or architectural improvements to their existing code. We conceptualize this phenomenon as system atrophy, and corroborate its existence by analyzing the code of over 1,300 systems as they underwent 19 million changes over 25 years. Such atrophy in systems has bread-and-butter consequences for organizations that rely on them. We show that it stunts the evolution of systems, makes them more bug-prone, and disengages developers. Atrophy in existing systems also makes it for organizations to implement other new systems because there are harder to integrate with them and cannibalize resources left over after their costlier upkeep. We then develop the idea that little increments in the modularity of their underlying code as a system evolves provide a powerful antidote to such atrophy. However, this antidote gradually loses its potency as a system ages further. Contrary to the popular belief, architectural improvements slow down atrophy but do not stop it. Our findings suggest that organizations must plan to eventually phase out these information systems, rather than just hoping to maintain them. For practice, we offer new insights on managing the tradeoff between evolution and atrophy; and how organizations can extract more useful life from aging systems. A pervasive, unbroached phenomenon is how once-modern systems age into unmaintainable albatrosses. We conceptualize this phenomenon from first-principles as system atrophy. We construct a trace data set from 190 million lines of evolving code in 1,354 systems spanning 25 years to corroborate it. Our middle-range theory introduces system atrophy into the conversation on information systems evolution, showing how small increments in modularity slow atrophy but lose potency with age. Atrophy eventually stunts systems, increases bugginess, and disengages developers. History: Yulin Fang, Senior Editor; Ning Su, Associate Editor. Funding: H. Safadi acknowledges support from the Terry-Sanford Research Award. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1218. [ABSTRACT FROM AUTHOR]

Benefit–cost analyses are critical to support U.S. agencies' programmatic decision making. These analyses are particularly challenging when one of the benefits is adversary deterrence. This paper presents a framework for calculating the value of deterrence related to countermeasures implemented to mitigate an attack by an adaptive adversary. We offer an approach for partitioning the benefit of countermeasures into three components: (1) threat reduction (deterrence), (2) vulnerability reduction, and (3) consequence mitigation. The benefit of a countermeasure is measured by the expected value of countermeasure implementation (EVCI) attributable to a specific countermeasure. It is based on the concept of expected value of imperfect control, defined as the difference in the expected values of alternatives with and without countermeasures. The EVCI represents all the benefits of implementing the countermeasure and is derived from three sources: (1) changes in attack probability (threat reduction from deterrence), (2) changes in detection probability (vulnerability reduction), and (3) changes in the distribution of attack outcomes (consequence mitigation). We partition the EVCI and estimate the portion attributable to each of these three sources to quantify the unique benefit of each. We provide two applications of the partitioning methodology using examples from the published literature that examine countermeasures designed to protect commercial aircraft against man-portable air defense systems. The proposed framework provides an approach for explicitly accounting separately for deterrence, vulnerability reduction, and consequence mitigation in benefit–cost analyses. It provides quantifiable insights into how countermeasures reduce terrorism risk. Funding: This material is based upon work supported by the U.S. Department of Homeland Security under [Grant Award 22STESE00001-02-00]. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security. This award was made to Northeastern University and the University of Southern California is a sub-awardee. This work was also supported by the National Science Foundation [Grant 2027296] awarded to Decision Research. [ABSTRACT FROM AUTHOR]

In this paper, we consider a personalized assortment planning problem under inventory constraints, where each arriving customer type is defined by a primary item of interest. As long as that item is in stock, the customer adds it to the shopping cart, at which point the retailer can recommend to the customer an assortment of add-ons to go along with the primary item. This problem is motivated by the new "recommendation at checkout" systems that have been deployed at many online retailers, and it also serves as a framework that unifies many existing problems in online algorithms (e.g., personalized assortment planning, single-leg booking, and online matching with stochastic rewards). In our problem, add-on recommendation opportunities are eluded when primary items go out of stock, which poses additional challenges for the development of an online policy. We overcome these challenges by introducing the notion of an inventory protection level in expectation and derive an algorithm with a 1/4-competitive ratio guarantee under adversarial arrivals. Funding: This work was supported by the Adobe Data Science Research Award and the Alibaba Innovation Research Award. L. Xin was partly supported by the National Science Foundation (NSF) [Award CMMI-1635160], X. Chen was supported by the NSF [CAREER Award IIS-1845444]. W. Ma and D. Simchi-Levi were supported by the Accenture and MIT Alliance in Business Analytics. [ABSTRACT FROM AUTHOR]

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Purpose: Quality awards are widely considered symbols of successful quality management. The purpose of this paper is to empirically test the effects of the China Quality Award (CQA) on firms' performance. The study further explores how the benefits due to CQA are affected by contextual factors. Design/methodology/approach: Using the data of CQA winners from 2001 to 2016, the event study method is applied to analyze the abnormal performance of winners. Furthermore, multiple regression models are proposed to evaluate the effects of contextual factors on the relationship between the award and profitability. Findings: The findings show that CQA has positive impacts on profitability and fixed asset efficiency but not on labor productivity. Besides, state-owned firms and firms with high innovation intensity obtain more profitability benefits than others. Originality/value: This is the first study to explain the relationship between quality awards and firm performance from a theoretical perspective, providing new insights into the quality management and performance literature. Furthermore, this study deepens the understanding of the relationship between quality awards and performance and reveals new implications. Some of the contextual factors examined, such as innovation intensity, are considered for the first time in quality award research. [ABSTRACT FROM AUTHOR]

This paper investigates a model-free algorithm of broad interest in reinforcement learning, namely, Q-learning. Whereas substantial progress had been made toward understanding the sample efficiency of Q-learning in recent years, it remained largely unclear whether Q-learning is sample-optimal and how to sharpen the sample complexity analysis of Q-learning. In this paper, we settle these questions: (1) When there is only a single action, we show that Q-learning (or, equivalently, TD learning) is provably minimax optimal. (2) When there are at least two actions, our theory unveils the strict suboptimality of Q-learning and rigorizes the negative impact of overestimation in Q-learning. Our theory accommodates both the synchronous case (i.e., the case in which independent samples are drawn) and the asynchronous case (i.e., the case in which one only has access to a single Markovian trajectory). Q-learning, which seeks to learn the optimal Q-function of a Markov decision process (MDP) in a model-free fashion, lies at the heart of reinforcement learning. When it comes to the synchronous setting (such that independent samples for all state–action pairs are drawn from a generative model in each iteration), substantial progress has been made toward understanding the sample efficiency of Q-learning. Consider a γ-discounted infinite-horizon MDP with state space S and action space A : to yield an entry-wise ε-approximation of the optimal Q-function, state-of-the-art theory for Q-learning requires a sample size exceeding the order of | S ‖ A | (1 − γ) 5 ε 2 , which fails to match existing minimax lower bounds. This gives rise to natural questions: What is the sharp sample complexity of Q-learning? Is Q-learning provably suboptimal? This paper addresses these questions for the synchronous setting: (1) when the action space contains a single action (so that Q-learning reduces to TD learning), we prove that the sample complexity of TD learning is minimax optimal and scales as | S | (1 − γ) 3 ε 2 (up to log factor); (2) when the action space contains at least two actions, we settle the sample complexity of Q-learning to be on the order of | S ‖ A | (1 − γ) 4 ε 2 (up to log factor). Our theory unveils the strict suboptimality of Q-learning when the action space contains at least two actions and rigorizes the negative impact of overestimation in Q-learning. Finally, we extend our analysis to accommodate asynchronous Q-learning (i.e., the case with Markovian samples), sharpening the horizon dependency of its sample complexity to be 1 (1 − γ) 4 . Funding: Y. Chen is supported in part by the Alfred P. Sloan Research Fellowship, the Google Research Scholar Award, the Air Force Office of Scientific Research [Grant FA9550-22-1-0198], the Office of Naval Research (ONR) [Grant N00014-22-1-2354], and the National Science Foundation (NSF) [Grants CCF-2221009, CCF-1907661, DMS-2014279, IIS-2218713, and IIS-2218773]. Y. Wei is supported in part by the Google Research Scholar Award and the NSF [Grants CCF-2106778, DMS-2147546/2015447, and CAREER award DMS-2143215]. Y. Chi is supported in part by the ONR [Grants N00014-18-1-2142 and N00014-19-1-2404] and the NSF [Grants CCF-1806154, CCF-2007911, CCF-2106778, ECCS-2126634, and DMS-2134080]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2023.2450. [ABSTRACT FROM AUTHOR]

The article announces the winners of the 2024 GODORT Awards. Marie Concannon receives the James Bennett Childs Award for her significant contributions to the field of documents librarianship, particularly her work with the website Prices and Wages by Decade. Celina McDonald and Patricia Kenly are awarded the Bernadine Abbott Hoduski Founders Award for their respective contributions to federal and state documents librarianship. Kennesaw State University Libraries and the Bentley Rare Book Museum receive the ProQuest/ GODORT/ ALA "Documents to the People" Award for their collaboration on a Constitution Week event. Aimée Quinn is granted the NewsBank/ Readex/ GODORT/ ALA Catharine J. Reynolds Research Grant for her project on the demise of government information during the 45th presidency. Finally, the Margaret T. Lane / Virginia F. Saunders Memorial Research Award is given to the book "What Can U.S. Government Information Do for Me?" for its outstanding research on government information resources. [Extracted from the article]

PharmEvo Research Forum, in collaboration with the Pakistan Cardiac Society, recently launched Shark Tank Cardiology, an initiative aimed at encouraging postgraduates in the field of cardiology to participate in research awards. The competition, held at CARDIOCAN23 in Sukkur, showcased the enthusiasm of young cardiologists from various cities in Pakistan. However, it also highlighted the lack of mentoring and deficiencies in their training. The participants were required to present their proposals within a strict time limit, but many struggled to do so effectively, indicating a need for better training in presentation skills. The winners of the competition were awarded cash prizes, and special recognition was given to percussionists who participated. The event was seen as an opportunity to promote research culture and encourage young cardiologists in their academic pursuits. [Extracted from the article]

A growing body of research documents that audiences reward organizations perceived to be authentic with positive evaluations. In the current work, we adopt a mixed-methods approach—using data collected from Glassdoor.com and two experiments—to establish that perceptions of authenticity are elicited by perceived congruence between an organization's stated values (i.e., the values it claims to hold) and its lived values (i.e., values members perceive as embodied by the organization), which in turn lead to more positive organizational evaluations. We then explore the conditions under which audiences are less likely to respond favorably to organizational authenticity, finding that the positive effects of stated-lived value congruence on evaluations are attenuated when audiences have a lower preference for stated values. Although scholars have often explored whether and how organizations can successfully make themselves appear authentic to reap rewards, our findings suggest that the perceived authenticity that results from stated-lived value congruence may not prove fruitful unless the audience holds a higher preference for an organization's stated values. History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory. Funding: This research was supported by the Interdisciplinary Research Award from the Management and Organizations Department at the Kellogg School of Management and by the Michael-Lee Chin Institute for Corporate Citizenship Research Grant from the Rotman School of Management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1578. [ABSTRACT FROM AUTHOR]

The article discusses the issue of low participation in awards, grants, and fellowships offered by the Association of Plastic Surgeons of India (APSI). The author highlights that there are few applicants for these opportunities, and sometimes there is only one applicant for multiple awards. The author suggests that this lack of participation may be due to a lack of awareness or missed application deadlines. They propose several measures to improve participation, including providing a welcome kit for new members, making early announcements, proactive promotion by the executive council, and creating an information page on the APSICON website. The author emphasizes the importance of encouraging eligible members to apply for these opportunities to increase their value and benefit the association. [Extracted from the article]

We are pleased to announce that the MURAKAMI Suminao Award for Disaster Research and the JDR annual awards (the JDR Award for the Most Cited Paper, the JDR Award for the Most Downloaded Article, and the JDR Award for the Most Contributory Reviewer) of 2023 have been decided by the JDR editorial boards. The award ceremony was held on December 6, 2023 at Gakushikaikan, Tokyo, Japan. We congratulate the winners and sincerely wish for future success. MURAKAMI Suminao Award for Disaster Research 2023 Prof. Fumihiko Imamura (Tohoku University) JDR Award for the Most Cited Paper 2023 Ryohei Kato, Ken-ichi Shimose, and Shingo Shimizu Predictability of Precipitation Caused by Linear Precipitation Systems During the July 2017 Northern Kyushu Heavy Rainfall Event Using a Cloud-Resolving Numerical Weather Prediction Model JDR Vol.13 No.5 pp. 846-859, 2018 JDR Award for the Most Downloaded Article 2023 Chun-Hao Shao, Pei-Chun Shao, and Fang-Ming Kuo Stampede Events and Strategies for Crowd Management JDR Vol.14 No.7 pp. 949-958, 2019 JDR Award for the Most Contributory Reviewer 2023 Prof. Reo Kimura (University of Hyogo) [ABSTRACT FROM AUTHOR]

This paper reviews manufacturing progress in making materials that have the strength necessary to form the tether for the space elevator. These fall into two categories, nanotubes and 2D materials. The aim is to raise awareness of the properties of these new materials and the state of the art of manufacturing methods. A NASA Innovative Advanced Concepts (NIAC) space elevator feasibility study concluded in 2003 that the "space elevator could be built in the near future with acceptable risk and less funding than some current space programs". The key technology that needed development was the tether component. The study concluded that carbon nanotubes were the material of choice for the tether. Considerable effort has been invested in manufacturing carbon nanotubes. Publicly disclosed information reveals that the longest carbon nanotube made is 0.5 m. The current state of the art is to manufacture carbon nanotubes in bundles called forests. Waseda University has shown that these can be grown at lengths of 0.14 m, at speeds of 1 m in 186 h. One year after the NIAC feasibility study was published, a new class of materials was isolated for the first time. In 2004, graphene was isolated as the world's first two-dimensional material. In 2010 the Nobel prize was awarded to the researchers who isolated and characterised the material, discovering it to have a similar tensile strength to carbon nanotubes (130 GPa). In the past decade much academic and industrial research effort has resulted in the manufacture of graphene as a large area material that can be manufactured at speeds of 2 m per minute and lengths of up to 1 km. While the manufacture of tether-quality material still needs more development, the trajectory to a high-quality industrial product is clear. This paper will detail the current state of the art of manufacturing for these tether candidate materials. • There is considerable progress in manufacturing 2D materials suitable for a space elevator. • The emphasis is on single-crystal graphene and graphene super laminate. [ABSTRACT FROM AUTHOR]

Structure of Elective Module on Research Initiated by Undergraduate Medical Students. To the Editor, Research is an essential aspect of medical science and it needs to be adequately addressed in the undergraduate (UG) curriculum in India. [6] There was rampant plagiarism in UG medical work, around 59%.[7] I Abysmal funding i : Indian Council of Medical Research (ICMR) has recently increased its funding for UG medical research from 20,000 to 50,000, but the uptake of students as compared to applications remains extremely small. [Extracted from the article]

Problem definition: Employers across many sectors of the economy have been fast to adopt variable work scheduling policies. The cost of this flexibility for employers is usually borne by employees, for whom unstable work schedules create several disruptions. In the context of home healthcare, we examine how employer-driven volatility in nurses' schedules impacts their decision to voluntarily leave their job. Methodology/results: Using an instrumental variables approach, we causally identify the effect of schedule volatility on nurses' voluntary turnover. We begin by constructing an operational measure of schedule volatility using time-stamped work log data from one of the largest home health agencies in the United States. Because this measure may be endogenous to the worker's decision to quit, we instrument for schedule volatility using paid days off taken by other nurses in the same branch. We find that higher levels of schedule volatility substantially increase a worker's likelihood of quitting. Specifically, a one-standard-deviation increase in schedule volatility increases the average worker's propensity to quit on a given day by more than threefold. Translated into yearly terms, 30 days of high schedule volatility over the course of the year increases the average worker's probability of quitting that year by 20%. Our policy simulations of counterfactual scheduling policies suggest that excess schedule volatility can explain a significant portion of voluntary turnover, and some interventions have the potential to substantially reduce workers' daily propensity to quit. Managerial implications: This work contributes to the understanding of the extent to which employees value control over their own work schedules and are averse to volatile work schedules that are dictated by employers. Especially in the current environment where there is a growing emphasis on work-life balance and employee-driven flexibility, finding a way to support stable schedules could be important for employers to attract and retain workers. Funding: This work was supported by the National Research Service Award Postdoctoral Fellowship, the Wharton Dean's Research Fund, the Agency for Healthcare Research and Quality [T32 Grant 5T32HS26116], and the Claude Marion Endowed Faculty Scholar Award. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2023.1205. [ABSTRACT FROM AUTHOR]

The article features the 2023 Plasma awards by Association of Asia Pacific Physical Societies (AAPPS). Topics covered include the selection of Katsumi Ida as the 2023 Laureate of the Subrahmanyan Chandrasekhar Prize of Plasma Physics, and the selection of Takayuki Watanabe for the Plasma Innovation Prize. Also noted are recipients of the Young Researcher Award, the U30 Doctoral Scientist/Student Award, and the Poster Prize.

The document titled "SIOP Award Winners and New Fellows" announces the recipients of various awards and fellowships at the 2024 SIOP Annual Conference. The awards include the Dunnette Prize, Distinguished Scientific Contributions Award, Distinguished Service Contributions Award, Distinguished Early Career Contributions Award, Distinguished Teaching Contributions Award, SIOP Humanitarian Award, Wayne Cascio Scientist-Practitioner Award, and several others. Additionally, the document lists the winners of research grants, fellowships, scholarships, and conference awards. The document concludes by introducing the new SIOP Fellows for 2024. [Extracted from the article]

The article focuses on AlphaFold, an artificial intelligence (AI) system created by DeepMind, a British AI research lab and its groundbreaking achievement of winning the 2023 Albert Lasker Basic Medical Research Award for the pioneering contributions of developers like Demis Hassabis and John Jumper in the field. It mentions the implications of AlphaFold in deciphering protein structures, its transformative impact on various domains of biological research, and the innovative AI methodologies.

In the category of emerging physicians, Dr. Muhammad Hussain from Services Hospital in Lahore won the first prize, followed by Dr. Saif ur Rahman from DHQ, Faisalabad, who won the second prize, and Dr. Nousheen Iqbal from Aga Khan University, Karachi, Pakistan, who won the third prize. Pakistan Chest Society and PharmEvo Research Forum have made waves in the medical community by successfully organizing the first-ever Respiratory Research Award at the 4th National Chest Con on April 28-30, 2023, in Lahore. [Extracted from the article]

Hence, eleven physicians were selected for First, Second and Third position in different categories in some cases two physicians shared the prize, after they were evaluated by separate panel of Judges on second day of the conference i.e. March 12th 2023 and the prizes were presented in the evening at a special session. In order to promote research culture and encourage the young researchers, Pakistan Society of Internal Medicine (PSIM) had signed a Memorandum of Understanding with PharmEvo to present Research Awards to winners in the competition at the time of its annual conference. [Extracted from the article]

This paper studies how to integrate rider mode preferences into the design of on-demand multimodal transit systems (ODMTSs). It is motivated by a common worry in transit agencies that an ODMTS may be poorly designed if the latent demand, that is, new riders adopting the system, is not captured. This paper proposes a bilevel optimization model to address this challenge, in which the leader problem determines the ODMTS design, and the follower problems identify the most cost efficient and convenient route for riders under the chosen design. The leader model contains a choice model for every potential rider that determines whether the rider adopts the ODMTS given her proposed route. To solve the bilevel optimization model, the paper proposes an exact decomposition method that includes Benders optimal cuts and no-good cuts to ensure the consistency of the rider choices in the leader and follower problems. Moreover, to improve computational efficiency, the paper proposes upper and lower bounds on trip durations for the follower problems, valid inequalities that strengthen the no-good cuts, and approaches to reduce the problem size with problem-specific preprocessing techniques. The proposed method is validated using an extensive computational study on a real data set from the Ann Arbor Area Transportation Authority, the transit agency for the broader Ann Arbor and Ypsilanti region in Michigan. The study considers the impact of a number of factors, including the price of on-demand shuttles, the number of hubs, and access to transit systems criteria. The designed ODMTSs feature high adoption rates and significantly shorter trip durations compared with the existing transit system and highlight the benefits of ensuring access for low-income riders. Finally, the computational study demonstrates the efficiency of the decomposition method for the case study and the benefits of computational enhancements that improve the baseline method by several orders of magnitude. Funding: This research was partly supported by National Science Foundation [Leap HI Proposal NSF-1854684] and the Department of Energy [Research Award 7F-30154]. [ABSTRACT FROM AUTHOR]

How can governments invest in the public good of science in a way that accelerates advancement and encourages innovation at the frontier of science–all the while acknowledging that investing in science means investing in scientists? The Ruth L. Kirschstein National Research Service Award (NRSA) program is a research-training program administered by the National Institutes of Health (NIH) that makes such investments. This study examines the impact of NRSA postdoctoral fellowships on subsequent career outcomes using NIH administrative records on applicants for the fellowship from 1996 to 2008. It finds that fellowships increased the probability of receiving subsequent research awards from 4.0 to 6.3 percentage points and of achieving a major independent research award from 2.6 to 4.6 percentage points. The findings demonstrate that federally funded fellowships promote the retention of scientists in the biomedical research workforce. [ABSTRACT FROM AUTHOR]

Daniel Grimes is an Assistant Professor in the Institute of Molecular Biology at the University of Oregon, USA, and a recipient of the National Institutes of Health (National Institute of General Medical Sciences) MIRA Outstanding Research Award. His lab studies the consequences of ciliary mutations including left-right patterning defects and scoliosis, primarily in zebrafish. We spoke to Daniel over Zoom to hear more about his career path, his experience of becoming a group leader and the influence of Jurassic Park. [ABSTRACT FROM AUTHOR]

This essay presents collaborative research related to the National Endowment for the Humanities-Arts and Humanities Research Council grant-funded project Connecting Threads, a website that brings together academics and curators across the United Kingdom and the United States who seek to contribute to wider decolonization work in the humanities and engage communities whose contributions to global cultures of textiles and fashion have historically been ignored. The Connecting Threads research team uses the Dutch Textile Trade Project's data and web applications to deepen understanding of the Madras kerchief, a large checked cotton square cloth that circulated in Afro-diasporic communities in the Caribbean during the eighteenth and nineteenth centuries. [ABSTRACT FROM AUTHOR]

Copyright of Gaceta de la Real Sociedad Matematica Espanola is the property of Real Sociedad Matematica Espanola and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research was made possible by a Research Assistantship Grant awarded through the USC Upstate Office of Sponsored Awards and Research Support (SARS). In addition, the authors would also like to offer special thanks to Dr. Warren "Wren" Bareiss for providing vital comments that helped to strengthen this manuscript. [ABSTRACT FROM AUTHOR]

Adequately addressing the grand challenge of poverty requires addressing resource scarcity. However, efforts to provide resources as a means of poverty alleviation have met with mixed success. We explore what makes resource provision effective as a means of poverty alleviation. We adopt a resourcing perspective, which focuses on the relationship between potential resources and schemas, or shared understandings, that shape how resources are used. Consistent with prior research, we find that schemas shape how resources are used in practice. However, we also find that who can access the resources is as consequential as how they are used. In exploring this issue, we identify a new category of schemas related not to use but to access, which we refer to as access schemas. We define access schemas as shared understandings regarding who can appropriately access potential resources. We find that different social groups have distinct schemas regarding access, and we identify three mechanisms—precedence, complementarity, and scaffolding—that shape the way that access schemas are enacted in resource-scarce settings. Our study contributes to the literature on grand challenges by clarifying the link between resource provision and resource use. We also contribute to the literature on resourcing by uncovering mechanisms that shape schema enactment in the presence of conflicting access schemas held by different social groups. Funding: This work was supported by the Research Grants Council, University Grants Committee [GRF Grants PolyU 548210 and PolyU 549211], and International Development Research Centre [Doctoral Research Award 107473-99906075-074]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.1570. [ABSTRACT FROM AUTHOR]

The article describes a historical corpus which documents the 19th and early 20th century. The corpus was created as part of a research grant whose objective was to investigate the development of the aspectual system of Polish in the last 250 years against the background of Czech and Russian. An important resource for this investigation was a database of aspectual triplets, which, in turn, was based on materials such as text corpora. Since there was no large corpus of the 19th and early 20th century available, there was a need to bridge this gap. In the course of the project, such corpus was made and it is now publicly accessible with no restrictions. This comprehensive corpus contains over 12 million contemporary words. Its texts originate from major Polish virtual libraries. It is POS-tagged with a tagger dedicated for 19th century texts. A web-based concordancer, an adjusted version of ParaVoz, allows for querying the corpus. The queries may be constrained by metadata. [ABSTRACT FROM AUTHOR]

Dr. Aena Saeed from Ziauddin Medical Univesity, Dr. Abdul Wahab and Dr. Muhammad Idrees both from Hayatabad Medical Complex Peshawar won the first, second and third prize for best posters during CARDIOCON 2022. The winners in this category were Dr. Aena Saeed from Ziauddin Medical Univesity who won the first prize while Dr.Abdul Wahab and Dr. Muhammad Idrees both from Hayatabad Medical Complex won the second and third prizes respectively. Dr. Kanwal Fatima from NICVD Karachi wont the first prize, Dr. Kamran again from NICVD won second prize while third prize was won by Dr. Manzoor Khan from Khyber Teaching Hospital Peshawar. [Extracted from the article]

The winners were presented prizes by Prof. Abdus Samad an eminent interventional cardiologist along with Prof. Feroze Memon, Prof. M. Ishaq and Prof. Fasih Hashmi. Ishaq, Prof. Feroz Memon, Prof. Fasih Hashmi, Mr. Shaukat Ali Jawaid, Mr. Mohsin from PharmEvo and others. PharmEvo Research Forum had signed a Memorandum of Understanding with Pakistan Hypertension League to sponsor Hypertension Research Awards which were presented at the PHL Conference held at Hyderabad on second day of the conference October 29th 2022 for the first time. [Extracted from the article]

The 2022 Lasker-DeBakey Clinical Medical Research Award is presented to Yuk Ming Dennis Lo of the Chinese University of Hong Kong for the discovery of fetal DNA in maternal blood, leading to development of noninvasive prenatal testing for Down syndrome. [ABSTRACT FROM AUTHOR]

The foundational research recognized by this year's Lasker Basic Science Research Award "for discoveries concerning the integrins—key mediators of cell-matrix and cell-cell adhesion in physiology and disease" reaches back to the 1970s. [ABSTRACT FROM AUTHOR]