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Alexander G. Nikolaev

Bio: Alexander G. Nikolaev is an academic researcher from University at Buffalo. The author has contributed to research in topics: Social network & Population. The author has an hindex of 17, co-authored 65 publications receiving 909 citations. Previous affiliations of Alexander G. Nikolaev include Northwestern University & State University of New York System.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors demonstrate the potential benefits of crowdsourcing last mile delivery by exploiting a social network of the customers and show that using friends in social networks to assist in last-mile delivery greatly reduces delivery costs and total emissions while ensuring speedy and reliable delivery.
Abstract: This paper demonstrates the potential benefits of crowdsourcing last mile delivery by exploiting a social network of the customers. The presented models and analysis are informed by the results of a survey to gauge people’s attitudes toward engaging in social network-reliant package delivery to and by friends or acquaintances. It is found that using friends in a social network to assist in last mile delivery greatly reduces delivery costs and total emissions while ensuring speedy and reliable delivery. The proposed new delivery method also mitigates the privacy concerns and not-at-home syndrome that widely exist in last mile delivery.

165 citations

Journal ArticleDOI
TL;DR: A routing model for repositioned trucks is used to show that the proposed optimization model and the latter heuristic approach, called the iterative price adjustment scheme (IPAS), reduce the overall operating cost while partially or fully obviating the need for a manual repositioning operation.

102 citations

Journal ArticleDOI
TL;DR: Examining studies using social network analysis (SNA) in the health care workforce and assessing factors contributing to social network and their relationships with care processes and patient outcomes found the level of technical sophistication in these studies tended to be low.

78 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the impact of hand-held cell phone use on driving safety based on historical automobile-accident-risk-related data and statistics, which would be of interest to transportation policy-makers.
Abstract: As of November 2008, the number of cell phone subscribers in the US exceeded 267 million, nearly three times more than the 97 million subscribers in June 2000. This rapid growth in cell phone use has led to concerns regarding their impact on driver performance and road safety. Numerous legislative efforts are under way to restrict hand-held cell phone use while driving. Since 1999, every state has considered such legislation, but few have passed primary enforcement laws. As of 2008, six states, the District of Columbia (DC), and the Virgin Islands have laws banning the use of hand-held cell phones while driving. A review of the literature suggests that in laboratory settings, hand-held cell phone use impairs driver performance by increasing tension, delaying reaction time, and decreasing awareness. However, there exists insufficient evidence to prove that hand-held cell phone use increases automobile-accident-risk. In contrast to other research in this area that uses questionnaires, tests, and simulators, this study analyzes the impact of hand-held cell phone use on driving safety based on historical automobile-accident-risk-related data and statistics, which would be of interest to transportation policy-makers. To this end, a pre-law and post-law comparison of automobile accident rate measures provides one way to assess the effect of hand-held cell phone bans on driving safety; this paper provides such an analysis using public domain data sources. A discussion of what additional data are required to build convincing arguments in support of or against legislation is also provided.

64 citations

Journal ArticleDOI
TL;DR: A variation of entropy centrality is defined based on a discrete, random Markovian transfer process and allows for varying locality in centrality analyses, thereby distinguishing locally central and globally central network nodes.

60 citations


Cited by
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Journal ArticleDOI

6,278 citations

01 Jan 1996

1,282 citations

DatasetDOI
01 Jan 1992
TL;DR: In this paper, the effect of outliers on reaction time analyses is evaluated and the power of different methods of minimizing the effect on the analysis of variance (ANOVA) is discussed.
Abstract: The effect of outliers on reaction time analyses is evaluated. The first section assesses the power of different methods of minimizing the effect of outliers on analysis of variance (ANOVA) and makes recommendations about the use of transformations and cutoffs. The second section examines the effect of outliers and cutoffs on different measures of location, spread, and shape and concludes using quantitative examples that robust measures are much less affected by outliers and cutoffs than measures based on moments. The third section examines fitting explicit distribution functions as a way of recovering means and standard deviations and concludes that unless fitting the distribution function is used as a model of distribution shape, the method is probably not worth routine use.

460 citations

Journal Article

383 citations