Proposition and Validation of Retention Model for Managers in Select Indian Private Sector Banks

Purpose- Focusing on private banking industry in Delhi (India), the study intent to identify the direct and indirect influence of select individual, internal (organizational) and external (environment) variables on retention of bank managers. Three retention models for banking industry with the said variables had been hypothesized and tested to find that most appropriate model. Design/Methodology/Approach - The required data of 301 lower and middle level managers was finalized using stratified random sampling. The managers examined for the study were with minimum two years of experience in the same bank. The study was conducted in two phases- (i) Significant determinants of retention were identified using multiple and hierarchical regression analysis, (ii) Involving only significant determinants three retention models were created and tested using Structural equation modelling (SEM). Findings- SEM result of best fit model suggests that perceived alternative employment opportunities, perceived organizations prestige, perceived competitiveness of pay, pay and benefits satisfaction, career advancement opportunities, work-life balance, and job satisfaction have significant effect on retention of managers and the result is consistent with regression analysis of the work. Moreover, final model showed retention acting as mediator between other variables and retention, though the indirect effect was found to be very weak. Practical Implications- The findings of the study will be serviceable for the banks want to keep those managers who had already spend a good amount of time in the bank. Originality/Value- Rather than including two or three predictors, the current work has considered determinants of retention from various dimensions. The study extended its area by making an effort to involve only those who retained in the organization for two years and can actually have an opinion on the matter or factors affecting their stay.

Development and Validation of Retention Models in Supercritical Fluid Chromatography for Impregnation Process Design

The retention factor is the key quantity for the thermodynamic analysis of the retention mechanism in chromatographic experiments. In this work, we measure retention factors for moderately polar solutes on four silica-based porous matrices as stationary phases by supercritical fluid chromatography. Elution of the solutes is only possible with binary mixtures of supercritical carbon dioxide (sc-CO2) and modifier (methanol) due to the low polarity of pure sc-CO2. The addition of modifiers makes the retention mechanism more complex and masks interactions between solute and stationary phase. In this work, we develop and validate several retention models that allow the obtaining of retention factors in modifier-free sc-CO2. Such models pave the way for quantifying adsorption interactions between polar solutes and non-swellable porous matrices in pure sc-CO2 based on retention data obtained in sc-CO2/modifier mixtures. The obtained information will thereby facilitate the understanding and design of impregnation processes, which are often performed in modifier-free conditions.

A methodology for the formulation of water retention models in deformable soils

This paper presents a novel approach to soil–water retention modelling that is based on the analysis of the material pore network. The approach postulates the existence of a differential coupling function, which relates the variation of water ratio to the variation of void ratio at constant suction. Distinct differential coupling functions have been considered, and the most general option has been integrated in a closed-form relationship between water ratio and void ratio with a suction-dependent integration constant, whose expression describes the isochoric retention behaviour. Four alternative expressions of the suction-dependent integration constant have been proposed resulting in four different, but equivalent, models linking degree of saturation, void ratio and suction. Each model predicts the variation of degree of saturation by means of four parameters, namely two parameters accounting for the effect of void ratio and two parameters accounting for the effect of suction. The models have been calibrated against laboratory data from soils with distinct particle size distributions and have shown accurate predictions of degree of saturation at different levels of suction and void ratio. Validation against additional data has also indicated that the models can extrapolate the soil behaviour to stress paths and suction levels beyond those considered during calibration.

An adaptive approach for estimation of transition probability matrix in the interacting multiple model filter

The traditional Interacting Multiple Model (IMM) filters usually consider that the Transition Probability Matrix (TPM) is known, however, when the IMM is associated with time-varying or inaccurate transition probabilities the estimation of system states may not be predicted adequately. The main methodological contribution of this paper is an approach based on the IMM filter and retention models to determine the TPM adaptively and automatically with relatively low computational cost and no need for complex operations or storing the measurement history. The proposed method is compared to the traditional IMM filter, IMM with Bayesian Network (BNs) and a state-of-the-art Adaptive TPM-based parallel IMM (ATPM-PIMM) algorithm. The experiments were carried out in an artificial numerical example as well as in two real-world health monitoring applications: the PRONOSTIA platform and the Li-ion batteries data set provided by NASA. The Retention Interacting Multiple Model (R-IMM) results indicate that a better prediction performance can be obtained when the TPM is not properly adjusted or not precisely known.

VSR Models of Change as Normative Practical Theory

This chapter offers a counterpoint to increasingly complex computational models of evolutionary change processes at higher levels of analysis. It explores the value of internal VSR (Variation-Selection-Retention) models as practical tools for managers. Individual change agents may actively and deliberately influence each of the three core internal processes and their balance and connect them with external VSR processes. Individuals may shape the organization’s current and potential future contexts beyond mere external adaptation to creation of novel future states. Broadening traditional assumptions of top-down rational decision-making, we include the potential of human imagination, and emotions of individuals and groups as engines of change as improvements to existing internal VSR models. A normative theory of internal VSR processes offers a practical tool for day-to-day operations of agents interested in understanding and affecting organization change. We encourage academics to bring renewed enthusiasm to teaching internal VSR models of change to practicing managers.

Undergraduate Research Communities for Transfer Students

Transfer students face many challenges integrating into a 4-year college that affect their retention and success, yet very little research has documented how to create wraparound programming to support them. There remains a need to establish retention models that are adaptable and can serve a variety of students and institutions. The Learning Environment and Academic Research Network (LEARN) Consortium, a partnership of Florida Atlantic University, University of Central Florida, and Western Carolina University whose focus is on engagement in undergraduate research, addressed this need by developing and testing T-LEARN, a new model for a sustainable science, technology, engineering, and mathematics (STEM) retention program specifically for transfer students who have transitioned to a university setting after receiving their associate’s degree at a community college. The new model was developed by adapting a successful retention model for 1st-year students at the University of Central Florida centered around three main pillars: (1) academics/research, (2) mentoring, and (3) community building. In this paper, we describe the development of the T-LEARN model, outline the adaptations made to accommodate the specific needs of transfer students, and present 3 years of implementation data we analyzed to determine what factor(s) most impact transfer student retention and success. Our findings indicate that T-LEARN students’ involvement in research during their 1st year was the most significant factor within the T-LEARN program that contributed to their academic success. Additionally, the majority of these students had continued to do research with the same LEARN program faculty mentor 1 year after the program ended.

Comparison of the Fitting Performance of Retention Models and Elution Strength Behaviour in Hydrophilic-Interaction and Reversed-Phase Liquid Chromatography

Hydrophilic interaction liquid chromatography (HILIC) is able to separate from polar to highly polar solutes, using similar eluents to those in the reversed-phase mode (RPLC) and a polar stationary phase, where water is adsorbed onto its surface. It is widely accepted that multiple modes of interaction take place in the HILIC environment, which can be far more complex than the interactions in an RPLC column. The behaviour in HILIC should be adequately modelled to predict the retention with optimisation purposes and improve the understanding on retention mechanisms, as is the case for RPLC. In this work, the prediction performance of several retention models is studied for seven HILIC columns (underivatised silica, and silica containing diol, amino and sulfobetaine functional groups, together with three columns recently manufactured with neutral, anionic, and cationic character), using uracil and six polar nucleosides (adenosine, cytidine, guanosine, thymidine, uridine, and xanthosine) as probe compounds. The results in HILIC are compared with those that were offered by the elution of several polar sulphonamides and diuretics analysed with two C18 columns (Chromolith Speed ROD and Zorbax Eclipse XDB). It is shown that eight retention models, which only consider partitioning or both partitioning and adsorption, give similar good accuracy in predictions for both HILIC and RPLC columns. However, the study on the elution strength behaviour, at varying mobile phase composition, reveals similarities (or differences) between RPLC and HILIC columns of diverse nature. The particular behaviour for the HILIC and RPLC columns was also revealed when the retention, in both modes, was fitted to a model that describes the change in the elution strength with the modifier concentration.