Old Dominion University
  • Norfolk, Virginia, United States
Recent publications
Innovation in the public sector plays an important role in improving the quality of public services and addressing economic and societal challenges. Most of the previous research on innovations has focused on the private sector. How organizations may achieve ambidexterity for innovations in the public sector characterized by unique constraints has been largely underexplored. Platforms have emerged as key components in organizations’ approaches to innovation. Using an empirical study in a public sector organization, this study identifies a platform-based approach that can be used to achieve ambidexterity in balancing exploitative and exploratory innovations in the public sector. Organizations facing constraints pertaining to structure, risk, and value may benefit from considering their product/service development, process management, and value formulation through this approach. This study also identifies practices in platform development, appropriation, and control that contributed to the success of the platform-based approach.
We examine the effect of hedging with different derivative instruments on the market value of firms run by CEOs with different risk preferences – based on a noble dataset over five years. We focus on the interest rate, commodity, and foreign exchange derivatives and find striking similarities in the hedging intensities of risk-seeking and risk-averse CEOs. Our findings show that when the average firm experiences an extreme (three-standard-deviation) change in interest rates, commodity prices, or foreign exchange rates, its derivatives portfolio creates only modest gains, regardless of CEO risk preferences. These findings are consistent with the view that hedging is just an insurance policy, not a value-increasing strategy. Our results suggest that CEOs, irrespective of their different risk preferences, are unwilling to forgo wealth-creating projects to hedge corporate risks.
The ability of vegetated coastal ecosystems to sequester high rates of “blue” carbon over millennial time scales has attracted the interest of national and international policy makers as a tool for climate change mitigation. Whereas focus on blue carbon conservation has been mostly on threatened rural seascapes, there is scope to consider blue carbon dynamics along highly fragmented and developed urban coastlines. The tropical city state of Singapore is used as a case study of urban blue carbon knowledge generation, how blue carbon changes over time with urban development, and how such knowledge can be integrated into urban planning alongside municipal and national climate change obligations. A systematic review of blue carbon studies in Singapore was used to support a qualitative review of Singapore’s blue carbon ecosystems, carbon budget, changes through time and urban planning and policy. Habitat loss across all blue carbon ecosystems is coarsely estimated to have resulted in the release of ∼12.6 million tonnes of carbon dioxide since the beginning of the 20th century. However, Singapore’s remaining blue carbon ecosystems still store an estimated 568,971 – 577,227 tonnes of carbon (equivalent to 2.1 million tonnes of carbon dioxide) nationally, with a small proportion of initial loss offset by habitat restoration. Carbon is now a key topic on the urban development and planning agenda, as well as nationally through Singapore’s contributions to the Paris Agreement. The experiences of Singapore show that coastal ecosystems and their blue carbon stocks can be successfully managed along an urban coastline, and can help inform blue carbon science and management along other rapidly urbanizing coastlines throughout the tropics.
The incorporation of different types of crop straw may lead to distinct forms and chemical structures of soil organic matter (SOM), which are closely associated with the communities of soil microorganisms in agricultural ecosystems. However, the relationships between the physiochemical composition of SOM and soil microbial communities in response to the incorporation of different types of crop straw remain largely unknown. In this study, we sought to gain insights into these relationships based on a long-term (10 year) field experiment, in which we examined the effects of five treatments [no fertilizer (control), mineral fertilizer (F), mineral fertilizer and wheat straw return (WF), mineral fertilizer and maize straw return (MF), and mineral fertilizer with wheat and maize straw (WMF)]. Using advanced solid-state ¹³carbon (C) nuclear magnetic resonance and high-throughput sequencing techniques, we investigated the associations between SOM physical fractions and chemical composition and the compositions of soil fungal and bacterial communities Our observations indicated that compared with treatment MF, the long-term incorporation of wheat straw increased the proportions of carbohydrate carbons in light-fraction and coarse-particulate organic matter (cPOM), which were significantly correlated with soil bacterial community composition. Long-term maize straw incorporation was found to increase the proportions of course and fine-POM fractions relative to the WF treatment, as well as the proportions of their aromatic carbons, which were significantly correlated with soil fungal community composition. Collectively, the findings of this study revealed that bacterial and fungal communities are characterized by two distinct responses to wheat and/or maize straw incorporation, which are strongly associated with the physical fractions and chemical structure of SOM, particularly in the case of POM. These findings provide valuable insights for understanding the associations between soil microbial communities and SOM fractions following crop straw incorporation, which will contribute to the development of optimal strategies for crop straw management.
Salespeople are aware that many customers have negatively stereotyped the sales profession. Consequently, salespeople may become defensive and fearful about how customers perceive them. This phenomenon is called ‘stereotype threat.’ Stereotype threat from customers may be triggered by many stimuli, such as verbal or nonverbal behavior from the focal group (i.e., customers), comments from coworkers, or information from the media. We argue that similarity with customers and sales managers should reduce stereotype threat. Using a survey of professional salespeople, the results show that salespeople are less likely to experience stereotype threats when they perceive themselves to be similar to their managers, but contrary to expectations, not when they feel similar to customers. The results also show that stereotype threat increases anxiety, which can reduce organizational commitment. However, help-focused coping from others in the sales organization will help salespeople cope with their anxiety. The implications of this research will help sales managers reduce stereotype threat and help salespeople cope with this phenomenon.
Academic research on influencer marketing is becoming more prevalent. The majority of this research, though, takes the perspective of a sponsoring brand, advising companies on how best to partner with an influencer to reap brand benefits. As influencers are also brands, research is needed to aid influencers with their own brand management strategies. Thus, we examine influencers as brands, exploring activism efforts by influencers. Results from three studies show that while activism positively affects consumers’ attitudes toward the influencer, expectations for future activism activities also increase. Furthermore, improved consumer attitudes are predicated upon continued support. Specifically, failure to meet activism expectations results in reduced perceptions of authenticity and attitudes, suggesting that activism as a means to benefit the influencer is only effective if it is continued. Implications for influencers and traditional brands and contributions to theory are discussed.
The performance of a driving automation system (DAS) can influence the human drivers' trust in the system. This driving-simulator study examined how different types of DAS failures affected drivers' trust. The automation-failure type (no-failure, takeover-request, system-malfunction) was manipulated among 122 participants, when a critical hazard event occurred. The dependent measures included participants’ trust ratings after each of seven drives and their takeover performance following the hazard. Results showed that trust improved before any automation failure occurred, demonstrating proper trust calibration toward the errorless system. In the takeover-request and system-malfunction conditions, trust decreased similarly in response to the automation failures, although the takeover-request condition had better takeover performance. For the drives after the automation failure, trust was gradually repaired but did not recover to the original level. This study demonstrated how trust develops and responds to DAS failures, informing future research for trust repair interventions in designing DASs.
The integration of blockchain with various business scenarios in cyber physical systems, where resilience is critical for the stability of system operation, can provide decentralized, constant validation and a consistent view of the system state. However, there are significant managerial and cybersecurity challenges in the integration process. The physical elements in the industrial infrastructure are heterogeneous with limited communication and computation capabilities. This paper aims to investigate the blockchain assured innovative business models in the power grid as a distributed industrial network and explore the blockchain consensus design that enables a state-aware power grid with high scalability. Following design science and interdisciplinary research methodology, a multi-level technical framework is developed to explore the blockchain integration strategies, specifically with a customized Proof of Stake consensus, as a case study. Technical evaluation is performed to reveal the performance improvement and the resilience of the business models in the detection of false data injection attacks.
Background Biochar ozonization was previously shown to dramatically increase its cation exchange capacity, thus improving its nutrient retention capacity. The potential soil application of ozonized biochar warrants the need for a toxicity study that investigates its effects on microorganisms. Results In the study presented here, we found that the filtrates collected from ozonized pine 400 biochar and ozonized rogue biochar did not have any inhibitory effects on the soil environmental bacteria Pseudomonas putida, even at high dissolved organic carbon (DOC) concentrations of 300 ppm. However, the growth of Synechococcus elongatus PCC 7942 was inhibited by the ozonized biochar filtrates at DOC concentrations greater than 75 ppm. Further tests showed the presence of some potential inhibitory compounds (terephthalic acid and p -toluic acid) in the filtrate of non-ozonized pine 400 biochar; these compounds were greatly reduced upon wet-ozonization of the biochar material. Nutrient detection tests also showed that dry-ozonization of rogue biochar enhanced the availability of nitrate and phosphate in its filtrate, a property that may be desirable for soil application. Conclusion Ozonized biochar substances can support soil environmental bacterium Pseudomonas putida growth, since ozonization detoxifies the potential inhibitory aromatic molecules. Graphical Abstract
How efficient is the targeting of foreign aid to populations in need? A long literature has focused on the impacts of foreign aid, but much rarer are studies that examine how such aid is allocated within countries. We examine the extent to which donors efficiently respond to exogenous budget shocks by shifting resources toward needier districts within a given country, as predicted by theory. We use recently geocoded data on the World Bank’s aid in 23 countries that crossed the lower-middle income threshold between 1995 and 2010 and thus experienced sharp aid reductions. We measure locations’ need along a number of dimensions, including nighttime lights emissions, population density, conflict exposure, and child mortality. We find little evidence that aid project siting is increasingly concentrated in worse-off areas as budgets shrink; the only exception appears to be a growing share of funding in more conflict-affected areas. We further analyze the relationship of health aid to child mortality measures in six key countries, again finding little evidence of efficient responses to budget shocks. Taken together, these results suggest that large efficiency gains may be possible in the distribution of aid from the World Bank and other donors.
The harmful algal genus Alexandrium has characteristically been found in temperate and subtropical regions; however recent evidence suggests global warming may be expanding its range into high latitude waters. Alexandrium cysts have previously been documented in the Chukchi Sea and we hypothesize that Alexandrium may be expanding further into the Arctic due to distribution by the Beaufort shelfbreak jet. Here we document the presence of Alexandrium catenella along the Alaskan Beaufort Sea shelf, marking an expansion of its known range. The observations of A. catenella were made using three different methods: FlowCAM imaging, 18S eukaryotic sequencing, and real-time quantitative PCR. Four occupations of a shelf/slope transect spanned the evolution of a strong wind-driven upwelling event over a 5-day period. A nearby mooring provided the physical context for the event, revealing that enhanced easterly winds reversed the Beaufort shelfbreak jet to the west and induced upwelling of colder, denser water onto the outer shelf. A. catenella sequences dominated the surface phytoplankton community at the onset of the upwelling event. This signal vanished during and after the event, likely due to a combination of alongstream advection, cross-stream advection, and wind mixing. These results suggest contrasting physical processes that are both subject to global warming amplification, delivery of warm waters via the Beaufort shelfbreak jet and upwelling, may control the proliferation of this potential harmful alga into the Arctic.
The design of a security scheme for beamforming prediction is critical for next-generation wireless networks (5G, 6G, and beyond). However, there is no consensus about protecting beamforming prediction using deep learning algorithms in these networks. This paper presents the security vulnerabilities in deep learning for beamforming prediction using deep neural networks in 6G wireless networks, which treats the beamforming prediction as a multi-output regression problem. It is indicated that the initial DNN model is vulnerable to adversarial attacks, such as Fast Gradient Sign Method , Basic Iterative Method , Projected Gradient Descent , and Momentum Iterative Method , because the initial DNN model is sensitive to the perturbations of the adversarial samples of the training data. This study offers two mitigation methods, such as adversarial training and defensive distillation, for adversarial attacks against artificial intelligence-based models used in the millimeter-wave (mmWave) beamforming prediction. Furthermore, the proposed scheme can be used in situations where the data are corrupted due to the adversarial examples in the training data. Experimental results show that the proposed methods defend the DNN models against adversarial attacks in next-generation wireless networks.
Drug discovery and drug repurposing often rely on the successful prediction of drug-target interactions (DTIs). Recent advances have shown great promise in applying deep learning to drug-target interaction prediction. One challenge in building deep learning-based models is to adequately represent drugs and proteins that encompass the fundamental local chemical environments and long-distance information among amino acids of proteins (or atoms of drugs). Another challenge is to efficiently model the intermolecular interactions between drugs and proteins, which plays vital roles in the DTIs. To this end, we propose a novel model, GIFDTI, which consists of three key components: the sequence feature extractor (CNNFormer), the global molecular feature extractor (GF), and the intermolecular interaction modeling module (IIF). Specifically, CNNFormer incorporates CNN and Transformer to capture the local patterns and encode the long-distance relationship among tokens (atoms or amino acids) in a sequence. Then, GF and IIF extract the global molecular features and the intermolecular interaction features, respectively. We evaluate GIFDTI on six realistic evaluation strategies and the results show it improves DTI prediction performance compared to state-of-the-art methods. Moreover, case studies confirm that our model can be a useful tool to accurately yield low-cost DTIs. The codes of GIFDTI are available at https://github.com/zhaoqichang/GIFDTI .
The purpose of this paper is to describe the formative design, development, and evaluation of a three-dimensional collaborative virtual learning environment (3D CVLE) called the Museum of Instructional Design. The 3D CVLE was designed to support the classroom activities of doctoral students enrolled in an instructional design and technology program with an emphasis on providing synchronous discourse and applied design opportunities. The development of the MID was led by an iterative three-phased learner experience design process based on the Successive Approximation Model that included (1) preparation, (2) iterative design, and (3) iterative development. The findings from this paper will provide insight into how formative learner experience design processes can lead to the development of a 3D CVLE.
Unlabelled: The global COVID-19 pandemic has disrupted the lives of workers and taken its toll on health and well-being. In line with recent calls for more inductive and abductive occupational health science research, we exploratorily meta-analyzed workers' COVID-19 distress, defined as psychological and psychosomatic strain contextualized to experiencing the virus and pandemic broadly. We identified many existing COVID-19 distress measures (e.g., Fear of COVID-19 Scale by Ahorsu et al., International Journal of Mental Health and Addiction, 2020; Coronavirus Anxiety Scale by Lee, Death Studies, 44(7), 393-401, 2020a) and correlates, including demographic variables (viz., gender, marital status, whether worker has children), positive well-being (e.g., quality of life, perceived social support, resilience), negative well-being (e.g., anxiety, depression, sleep problems), and work-related variables (e.g., job satisfaction, burnout, task performance). Additionally, we found preliminary evidence of subgroup differences by COVID-19 distress measure and country-level moderation moderators (viz., cultural values, pandemic-related government response) as well as COVID-19 distress's incremental validity over and above anxiety and depression. The findings-based on k = 135 independent samples totaling N = 61,470 workers-were abductively contextualized with existing theories and previous research. We also call for future research to address the grand challenge of working during the COVID-19 pandemic and ultimately develop a cumulative occupational health psychology of pandemics. Supplementary information: The online version contains supplementary material available at 10.1007/s41542-022-00131-x.
This article examines the durable, yet largely overlooked, claims of Bahu Begam (1727–1815) to dynastic wealth and authority in the Awadh nawabi (1722–1856), a North Indian Mughal ‘successor state’ and an important client of the East India Company. Chief consort ( khass mahal ) to Nawab Shuja-ud-Daula (r. 1754–75) and mother to his successor Nawab Asaf-ud-Daula (r. 1775–97), Bahu Begam played a well-documented role in the regime’s tumultuous politics, particularly during Warren Hastings’s tenure as the Company’s governor-general (1773–85) and his later parliamentary impeachment. But despite her prominent political influence, little attention has been paid to the substance of her persistent claims to proprietorship over revenue rights and the immense fortune in her custody, as well as her broader assertions of authority over Awadh’s male rulers. Taking those claims seriously, this article contends that the begam rooted her arguments in notions of natural deference to maternal authority and generational seniority, evolving dynastic traditions of co-sharing sovereignty and fiscal resources, and her particular history as a principal financier of the Awadh regime. In so doing, the article argues that the begam’s claims reflect the shifting conceptual language of late-Mughal Persianate political discourse and the ambivalent position of elite women as dynastic financiers and state-builders in early colonial South Asia.
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6,447 members
Andrew Collins
  • Department of Engineering Management and Systems Engineering
Sebastian Erich Kuhn
  • Department of Physics
Alvin Holder
  • Department of Chemistry and Biochemistry
Michael Stacey
  • Frank Reidy Research Center for Bioelectrics
Barbara Hargrave
  • School of Medical Diagnostic and Translational Services
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