Onward and upward? An empirical investigation of gender and promotions in Information Technology Services

The shaky ascent of women up the organizational ladder is a critical factor that may contribute to the lack of women in information technology (IT). In this study, we examine the effect of gender on the likelihood of employee promotions. We further examine whether women get an equal lift in promotion likelihood from performance improvements, work experience, and training as men. We analyze archival promotion data, as well as demographic, human capital, and administrative data for 7,004 employees at a leading IT services firm located in India for the years 2002–2007 and for multiple levels of promotion. We develop robust econometric models that consider employee heterogeneity to identify the differential effect of gender and performance on promotions. We find that, contrary to expectations, women are more likely to be promoted, on average. However, looking deeper into the heterogeneous main effects using hierarchical Bayesian modeling reveals more nuanced insights. We find that, ceteris paribus, women realize less benefit from performance gains than men, less benefit from tenure within the focal firm, but more benefit from training than men. These results suggest that despite the disparity in returns to performance and experience improvements, women can rely on signaling mechanisms such as training to restore parity in promotions. We find that the effects of gender and performance vary with the level of employee promotion; although not as much as men, women benefit more from performance gains at higher organizational levels. Our findings suggest several actionable managerial insights that can potentially make IT firms more inclusive and attractive to women

Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Journey predictive energy management strategy for a plug-in hybrid electric vehicle

The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonisation of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialisation. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Further, recent studies suggest the use of \intelligent transport" infrastructure to include a predictive element to the energy management strategy to achieve reductions in emissions. The thesis addresses the problem of determining the links between component-sizing, real-world usage and energy management strategies for a PHEV. The objective is to develop an integrated framework in which the advantages of predictive energy management can be realised by component downsizing for a PHEV. The study is spilt into three sections. The first part presents the framework by which the predictive element can be included into the PHEV's energy management strategy. Second part describes the development of the PHEV component models and the various energy management strategies which control the split in energy used between the engine and the battery. In this section a new control strategy is presented which integrates the predictive element proposed in the first part. Finally, in the third section an optimisation framework is presented by which the size of the components within the PHEV are reduced due to the lower energy demands of the new proposed energy management strategy. The first part of the study presents a framework by which the energy consumption of a vehicle may be predicted over a route. The proposed energy prediction framework employs a neural network and was used o_-line for estimating the real-world energy consumption of the vehicle so that it can be later integrated within the vehicles energy management control system. Experimental results show an accuracy within 20%-30% when comparing predicted and measured energy consumptions for over 800 different real-world EV journeys … [cont.]

The Business Meeting: A Cross-cultural Experiential Learning Activity

This paper presents a simulation designed to help students learn about the challenges and necessary skills for conducting business in cross-cultural settings. The exercise involves assigning participants to two fictitious cultural groups, each with its own norms and expectations. Participants interact with members of the other culture in accordance with the instructions provided in order to negotiate successfully. This experiential learning activity allows students to reflect on their cross-cultural skills in a simulated business setting. An assessment of the exercise conducted in classroom setting indicated evidence of its effectiveness

Polygalacturonase production by Aspergillus nomius MR103 in solid state fermentation using Agro-industrial wastes

The present study was aimed at polygalacturonase production from Aspergillus nomius MR103 under solid state fermentation. A total of 57 fungal strains were obtained from mangrove soils collected from Gilakaladindi and Malakayalanka of Krishna District Andhra Pradesh. For the isolation of fungi these Soil samples were serially diluted and plated on pectin agar media plates.  Among them, the isolate which showed maximum polygalacturonase activity was selected for this study. This strain was identified as A. nomius MR 103 by 18S rRNA sequences analysis. Pectin rich agro-industrial wastes like apple peel, citrus peel, orange peel, wheat bran, rice bran and sugarcane bagasse were used as substrates for polygalacturonase production by A. nomius MR 103. This strain was inoculated into the nutrient broth containing agro industrial wastes under solid state fermentation and amount of Polygalacturonase production was estimated. Maximum enzyme production of 4.83 IU/mg was recorded at pH 7.0 and temperature 35?C after 7 days of incubation, when orange peels were used as substrate.  Addition of carbon and nitrogen sources to orange peel media improved the Polygalcturonase production. Sucrose as carbon and peptone as nitrogen sources were proved  to be the best for  maximum production of Polygalcturonase by A. nomius MR 103 on orange peel substrate. Utilization of agro-industrial by-products provided the establishment of a cost-efficient and sustainable process for enzyme production.&nbsp

Power Quality Improvement Using Series Active Power Filter Based On Gravitational Search Algorithm

This paper proposes a heuristic control of the series active power filter for power quality enhancement. In this context, the series active filter is better utilized as a voltage source controller contrary to its conventional usage as variable impedance. The present-day utility system as a linear model is unsatisfactory and the steps are laid down to discuss utility system as a nonlinear model. This paper deals power quality disturbances like voltage sag/swell, voltage error and THD with robust heuristic algorithms like the gravitational search algorithms (GSA) and it is further compared with firefly (FF) algorithm. The harmonic reduction in the source current and mitigation of sags/swells in the load voltage is carried out with optimal tuning of the PI controller. The series active power filter as a harmonic suppressor with a specific reference controlled strategy is discussed in this paper. The synchronous reference frame (SRF) theory is used to generate the reference voltage signals required for compensation. The hysteresis band current controller (HBCC) is used to perform the switching operation of Voltage Source Inverter. Simulations are carried out in the MATLAB/SIMULINK environment

Power Quality Improvement Based On PSO Algorithm Incorporating UPQC

The usage of the term power quality is increasing day by day with extensive usage of large capacity loads and nonlinear loads. The major power quality issues are voltage disturbances and current disturbances in the present-day power systems. Today, with the advent of power semiconductor devices these power quality issues are solved to a great extent. The unified power quality conditioner is one such power semiconductor device which utilizes active filtering methodology to deal with the concerned power quality issues. Here an attempt is made to control and generate the reference currents and voltages for a unified power quality conditioner with the optimal tuned synchronous reference frame theory. The particle swarm optimization is employed to evolve gains of the proportional-integral controller. The unified power quality conditioner is a combination of shunt and series voltage source converters. The hysteresis band current controller for series and the pulse width modulation current controller for the shunt active filter are used for generation of gating pulses required by the switches of the voltage source converters in the unified power quality conditioner. The performance evaluation of multi-objective convergence fitness function (dealing: the voltage sag, the source current variations, and the load voltage variations) with unified power quality conditioner based on particle swarm optimization algorithm is performed. The efficacy of the proposed work is validated by conducting simulations in MATLAB/SIMULINK software environment.

Sustained Post-Mating Response in Drosophila melanogaster Requires Multiple Seminal Fluid Proteins

Successful reproduction is critical to pass genes to the next generation. Seminal proteins contribute to important reproductive processes that lead to fertilization in species ranging from insects to mammals. In Drosophila, the male's accessory gland is a source of seminal fluid proteins that affect the reproductive output of males and females by altering female post-mating behavior and physiology. Protein classes found in the seminal fluid of Drosophila are similar to those of other organisms, including mammals. By using RNA interference (RNAi) to knock down levels of individual accessory gland proteins (Acps), we investigated the role of 25 Acps in mediating three post-mating female responses: egg production, receptivity to remating and storage of sperm. We detected roles for five Acps in these post-mating responses. CG33943 is required for full stimulation of egg production on the first day after mating. Four other Acps (CG1652, CG1656, CG17575, and CG9997) appear to modulate the long-term response, which is the maintenance of post-mating behavior and physiological changes. The long-term post-mating response requires presence of sperm in storage and, until now, had been known to require only a single Acp. Here, we discovered several novel Acps together are required which together are required for sustained egg production, reduction in receptivity to remating of the mated female and for promotion of stored sperm release from the seminal receptacle. Our results also show that members of conserved protein classes found in seminal plasma from insects to mammals are essential for important reproductive processes