Search results for: picking%20process

Authors: Michelo Obrey

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Traditionally, mutual funds have long been esteemed as stand-alone entities in the U.S. However, the prevalence of the fund families’ affiliation to financial conglomerates is eroding this striking feature. Mutual fund families' affiliation with financial conglomerates can potentially be an important source of superior performance or cost to the affiliated mutual fund investors. On the one hand, financial conglomerates affiliation offers the mutual funds access to abundant resources, better research quality, private material information, and business connections within the financial group. On the other hand, conflict of interest is bound to arise between the financial conglomerate relationship and fund management. Using a sample of U.S. domestic equity mutual funds from 1994 to 2017, this paper examines whether fund family affiliation to an investment bank help the affiliated mutual funds deliver superior performance through private material information advantage possessed by the investment banks or it costs affiliated mutual fund shareholders due to the conflict of interest. Robust to alternative risk adjustments and cross-section regression methodologies, this paper finds that the investment bank-affiliated mutual funds significantly outperform those of the mutual funds that are not affiliated with an investment bank. Interestingly the paper finds that the outperformance is confined to holding return, a return measure that captures the investment talent that is uninfluenced by transaction costs, fees, and other expenses. Further analysis shows that the investment bank-affiliated mutual funds specialize in hard-to-value stocks, which are not more likely to be held by unaffiliated funds. Consistent with the information advantage hypothesis, the paper finds that affiliated funds holding covered stocks outperform affiliated funds without covered stocks lending no support to the hypothesis that affiliated mutual funds attract superior stock-picking talent. Overall, the paper findings are consistent with the idea that investment banks maximize fee income by monopolistically exploiting their private information, thus strategically transferring performance to their affiliated mutual funds. This paper contributes to the extant literature on the agency problem in mutual fund families. It adds to this stream of research by showing that the agency problem is not only prevalent in fund families but also in financial organizations such as investment banks that have affiliated mutual fund families. The results show evidence of exploitation of synergies such as private material information sharing that benefit mutual fund investors due to affiliation with a financial conglomerate. However, this research has a normative dimension, allowing such incestuous behavior of insider trading and exploitation of superior information not only negatively affect the unaffiliated fund investors but also led to an unfair and unleveled playing field in the financial market.

Keywords: mutual fund performance, conflicts of interest, informational advantage, investment bank

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Authors: Gary Peach, Furqan Hameed

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Musaimeer outfall tunnel is one of the longest storm water tunnels in the world, with a total length of 10.15 km. The tunnel will accommodate surface and rain water received from the drainage networks from 270 km of urban areas in southern Doha with a pumping capacity of 19.7m³/sec. The tunnel is excavated by Tunnel Boring Machine (TBM) through Rus Formation, Midra Shales, and Simsima Limestone. Water inflows at high pressure, complex mixed ground, and weaker ground strata prone to karstification with the presence of vertical and lateral fractures connected to the sea bed were also encountered during mining. In addition to pre-tender geotechnical investigations, the Contractor carried out a supplementary offshore geophysical investigation in order to fine-tune the existing results of geophysical and geotechnical investigations. Electric resistivity tomography (ERT) and Seismic Reflection survey was carried out. Offshore geophysical survey was performed, and interpretations of rock mass conditions were made to provide an overall picture of underground conditions along the tunnel alignment. This allowed the critical tunnelling area and cutter head intervention to be planned accordingly. Karstification was monitored with a non-intrusive radar system facility installed on the TBM. The Boring Electric Ahead Monitoring(BEAM) was installed at the cutter head and was able to predict the rock mass up to 3 tunnel diameters ahead of the cutter head. BEAM system was provided with an online system for real time monitoring of rock mass condition and then correlated with the rock mass conditions predicted during the interpretation phase of offshore geophysical surveys. The further correlation was carried by Samples of the rock mass taken from tunnel face inspections and excavated material produced by the TBM. The BEAM data was continuously monitored to check the variations in resistivity and percentage frequency effect (PFE) of the ground. This system provided information about rock mass condition, potential karst risk, and potential of water inflow. BEAM system was found to be more than 50% accurate in picking up the difficult ground conditions and faults as predicted in the geotechnical interpretative report before the start of tunnelling operations. Upon completion of the project, it was concluded that the combined use of different geophysical investigation results can make the execution stage be carried out in a more confident way with the less geotechnical risk involved. The approach used for the prediction of rock mass condition in Geotechnical Interpretative Report (GIR) and Geophysical Reflection and electric resistivity tomography survey (ERT) Geophysical Reflection surveys were concluded to be reliable as the same rock mass conditions were encountered during tunnelling operations.

Keywords: tunnel boring machine (TBM), subsea, karstification, seismic reflection survey

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: Yulia V. Krasavtseva, Tatiana V. Kornilova

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Risk-taking behaviors are not only dictated by cognitive components but also involve emotional aspects. Anticipatory emotions, involving both cognitive and affective mechanisms, are involved in decision-making in general, and risk-taking in particular. Affective reactions are prompted when an expectation or prediction is either validated or invalidated in the achieved result. This study aimed to combine predictions, anticipatory emotions, affective reactions, and personality traits in the context of risk-taking behaviors. An experimental online method Emotion and Prediction In a Casino (EPIC) was used, based on a casino-like roulette game. In a series of choices, the participant is presented with progressively riskier roulette combinations, where the potential sums of wins and losses increase with each choice and the participant is given a choice: to 'walk away' with the current sum of money or to 'play' the displayed roulette, thus accepting the implicit risk. Before and after the result is displayed, participants also rate their emotions, using the Self-Assessment Mannequin [Bradley, Lang, 1994], picking a picture, representing the intensity of pleasure, arousal, and dominance. The following personality measures were used: 1) Personal Decision-Making Factors [Kornilova, 2003] assessing risk and rationality; 2) I7 – Impulsivity Questionnaire [Kornilova, 1995] assessing impulsiveness, risk readiness, and empathy and 3) Subjective Risk Intelligence Scale [Craparo et al., 2018] assessing negative attitude toward uncertainty, emotional stress vulnerability, imaginative capability, and problem-solving self-efficacy. Two groups of participants took part in the study: 1) 98 university students (Mage=19.71, SD=3.25; 72% female) and 2) 94 online participants (Mage=28.25, SD=8.25; 89% female). Online participants were recruited via social media. Students with high rationality rated their pleasure and dominance before and after choices as lower (ρ from -2.6 to -2.7, p < 0.05). Those with high levels of impulsivity rated their arousal lower before finding out their result (ρ from 2.5 - 3.7, p < 0.05), while also rating their dominance as low (ρ from -3 to -3.7, p < 0.05). Students prone to risk-rated their pleasure and arousal before and after higher (ρ from 2.5 - 3.6, p < 0.05). High empathy was positively correlated with arousal after learning the result. High emotional stress vulnerability positively correlates with arousal and pleasure after the choice (ρ from 3.9 - 5.7, p < 0.05). Negative attitude to uncertainty is correlated with high anticipatory and reactive arousal (ρ from 2.7 - 5.7, p < 0.05). High imaginative capability correlates negatively with anticipatory and reactive dominance (ρ from - 3.4 to - 4.3, p < 0.05). Pleasure (.492), arousal (.590), and dominance (.551) before and after the result were positively correlated. Higher predictions positively correlated with reactive pleasure and arousal. In a riskier scenario (6/8 chances to win), anticipatory arousal was negatively correlated with the pleasure emotion (-.326) and vice versa (-.265). Correlations occur regardless of the roulette outcome. In conclusion, risk-taking behaviors are linked not only to personality traits but also to anticipatory emotions and affect in a modeled casino setting. Acknowledgment: The study was supported by the Russian Foundation for Basic Research, project 19-29-07069.

Keywords: anticipatory emotions, casino game, risk taking, impulsiveness

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Authors: Valentina Dolmova

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What consumers choose to buy and who voters select on election days are two questions that have captivated the interest of both academics and practitioners for many decades. The importance of understanding what influences the behavior of those groups and whether or not we can predict or control it fuels a steady stream of research in a range of fields. By looking only at the past 40 years, more than 70 thousand scientific papers have been published in each field – consumer behavior and political psychology, respectively. From marketing, economics, and the science of persuasion to political and cognitive psychology - we have all remained heavily engaged. The ever-evolving technology, inevitable socio-cultural shifts, global economic conditions, and much more play an important role in choice-equations regardless of context. On one hand, this makes the research efforts always relevant and needed. On the other, the relatively low number of cross-field collaborations, which seem to be picking up only in more in recent years, makes the existing findings isolated into framed bubbles. By performing systematic research across both areas of psychology and building a parallel between theories and factors of influence, however, we find that there is not only a definitive common ground between the behaviors of consumers and voters but that we are moving towards a global model of choice. This means that the lines between contexts are fading which has a direct implication on what we should focus on when predicting or navigating buyers and voters’ behavior. Internal and external factors in four main categories determine the choices we make as consumers and as voters. Together, personal, psychological, social, and cultural create a holistic framework through which all stimuli in relation to a particular product or a political party get filtered. The analogy “consumer-voter” solidifies further. Leading academics suggest that this fundamental parallel is the key to managing successfully political and consumer brands alike. However, we distinguish additional four key stimuli that relate to those factor categories (1/ opportunity costs; 2/the memory of the past; 3/recognisable figures/faces and 4/conflict) arguing that the level of expertise a person has determines the prevalence of factors or specific stimuli. Our efforts take into account global trends such as the establishment of “celebrity politics” and the image of “ethically concerned consumer brands” which bridge the gap between contexts to an even greater extent. Scientists and practitioners are pushed to accept the transformative nature of both fields in social psychology. Existing blind spots as well as the limited number of research conducted outside the American and European societies open up space for more collaborative efforts in this highly demanding and lucrative field. A mixed method of research tests three main hypotheses, the first two of which are focused on the level of irrelevance of context when comparing voting or consumer behavior – both from the factors and stimuli lenses, the third on determining whether or not the level of expertise in any field skews the weight of what prism we are more likely to choose when evaluating options.

Keywords: buyers’ behaviour, decision-making, voters’ behaviour, social psychology

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Authors: Varinder Kaur Gambhir, Neema Gupta, Sonal Tickoo Chaudhuri

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Bengaluru, a rapidly growing metropolis in India, with a population of 12.5 million citizens, generates 5,757 metric tonnes of solid waste per day. Despite their invaluable contribution to waste management, society and the economy, waste pickers face significant stigma, suspicion and contempt and are left with a sense of shame about their work. In this context, BBC Media Action was funded by the H&M Foundation to develop a 3-year multi-phase social media campaign to shift perceptions of waste picking and informal waste pickers amongst the Bengaluru population. Research has been used to inform project strategy and adaptation, at all stages. Formative research to inform campaign strategy used mixed methods– 14 focused group discussions followed by 406 online surveys – to explore people’s knowledge of, and attitudes towards waste pickers, and identify potential barriers and motivators to changing perceptions. Use of qualitative techniques like metaphor maps (using bank of pictures rather than direct questions to understand mindsets) helped establish the invisibility of informal waste pickers, and the quantitative research enabled audience segmentation based on attitudes towards informal waste pickers. To pretest the campaign idea, eight I-GDs (individual interaction followed by group discussions) were conducted to allow interviewees to first freely express their feelings individually, before discussing in a group. Robert Plucthik’s ‘wheel of emotions’ was used to understand audience’s emotional response to the content. A robust monitoring and evaluation is being conducted (baseline and first phase of monitoring already completed) using a rotating longitudinal panel of 1,800 social media users (exposed and unexposed to the campaign), recruited face to face and representative of the social media universe of Bengaluru city. In addition, qualitative in-depth interviews are being conducted after each phase to better understand change drivers. The research methodology and ethical protocols for impact evaluation have been independently reviewed by an Institutional Review Board. Formative research revealed that while waste on the streets is visible and is of concern to the public, informal waste pickers are virtually ‘invisible’, for most people in Bengaluru Pretesting research revealed that the creative outputs evoked emotions like acceptance and gratitude towards waste-pickers, suggesting that the content had the potential to encourage attitudinal change. After the first phase of campaign, social media analytics show that #Invaluables content reached at least 2.6 million unique people (21% of the Bengaluru population) through Facebook and Instagram. Further, impact monitoring results show significant improvements in spontaneous awareness of different segments of informal waste pickers ( such as sorters at scrap shops or dry waste collection centres -from 10% at baseline to 16% amongst exposed and no change amongst unexposed), recognition that informal waste pickers help the environment (71% at baseline to 77% among exposed and no change among unexposed) and greater discussion about informal waste pickers among those exposed (60%) as against not exposed (49%). Using the insights from this research, the planned social media intervention is designed to increase the visibility of and appreciation for the work of waste pickers in Bengaluru, supporting a more inclusive society.

Keywords: awareness, discussion, discrimination, informal waste pickers, invisibility, social media campaign, waste management

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