Indian study shows high-performance work systems (HPWS) mediate the relationship between business strategy and employees’ intention to leave

Purpose This paper examines the relationship between business strategies and employees’ intention to leave (ITL), through the mediating role of high-performance work system (HPWS). Design/methodology/approach To test their hypotheses, the authors used self-administered questionnaires. They drew up a list of 600 organizations of different nature and structure operating in India that were listed by the Federation of Indian Chambers and Industry. They approved 192 organizations and sent the surveys to 960 executives. They aimed to receive a minimum of one response from an HR executive and two from non-HR executives from each one. In the end, they received 572 useable responses. Findings The study found that high-performance work systems (HPWS) mediate the relationship between business strategy and employees’ intention to leave (ITL). The two effective approaches were “quality management” and “innovation strategy”, both of which reinforced the adoption of HPWS. But a third approach, a “cost-reduction strategy”, was not shown to be positively correlated with HPWS. Another important finding was that the influence on ITL did not vary across the types, or ownership structures, of the firms. Originality/value The data has lessons for HR departments. First, it shows it is advantageous for firms hoping to retain more employees to invest in HPWS that are consistent with the values of their organizations. A second practical finding is that firms need to take into account the Indian context. A third lesson is HR practitioners should make strong efforts to communicate the goals of the HPWS to employees The study also shows firms adopting cost-reduction strategies should focus more on treating employees as resources.

Alert Optimization of the PLUM Earthquake Early Warning Algorithm for the Western United States

ABSTRACT We determine an optimal alerting configuration for the propagation of local undamped motion (PLUM) earthquake early warning (EEW) algorithm for use by the U.S. ShakeAlert system covering California, Oregon, and Washington. All EEW systems should balance the primary goal of providing timely alerts for impactful or potentially damaging shaking while limiting alerts for shaking that is too low to be of concern (precautionary alerts). The PLUM EEW algorithm forward predicts observed ground motions to nearby sites within a defined radius without accounting for attenuation, avoiding the earthquake source parameter estimation step of most EEW algorithms. PLUM was originally developed in Japan where the alert regions and ground motions for which alerts are issued differ from those implemented by ShakeAlert. We compare predicted ground motions from PLUM to ShakeMap-reported ground motions for a set of 22 U.S. West Coast earthquakes of magnitude 4.4–7.2 and evaluate available warning times. We examine a range of prediction radii (20–100 km), thresholds used to issue an alert (alert threshold), and levels of impactful or potentially damaging shaking (target threshold). We find optimal performance when the alert threshold is close to the target threshold, although higher target ground motions benefit from somewhat lower alert thresholds to ensure timely alerts. We also find that performance, measured as the cost reduction that a user can achieve, depends on the user’s tolerance for precautionary alerts. Users with a low target threshold and high tolerance for precautionary alerts achieve optimal performance when larger prediction radii (60–100 km) are used. In contrast, users with high target thresholds and low tolerance for precautionary alerts achieve better performance for smaller prediction radii (30–60 km). Therefore, setting the PLUM prediction radius to 60 km balances the needs of many users and provides warning times of up to ∼20 s.

Recent Industrial Application and Perspectives of Rheo-Diecast Process in China

The Rheo-diecast process has been rapidly developed and increasingly used in China in the recent 5 years. The high solid fraction (solid content close to 50%) rheo-diecast components were commercially used in the transportation markets mainly because of lightweight. The mechanical properties of the high solid fraction rheo-diecast components are obviously superior than that of the conventional liquid diecast parts. The defects such as oxide, gas entrapment, shrinkage porosities are well prevented in the high solid fraction rheo-diecast parts. The high solid fraction rheo-diecast parts can be fully T6 heat treated. A comparison between high solid fraction rheo-diecast part and conventional liquid diecast part will be described in detail. The low solid fraction (solid content 5-20%) rheo-diecast components were widely used in the 5G communication markets. The future perspectives of Rheo-diecast process will be described at last. 1. Cost reduction. 2. Production consistency. 3. New Rheo-diecast alloys development. 4. Numerical simulation of Rheological filling.

Cost and Emissions Reduction in CO2 Capture Plant Dependent on Heat Exchanger Type and Different Process Configurations: Optimum Temperature Approach Analysis

The performance of a plate heat exchanger (PHE), in comparison with the conventional shell and tube types, through a trade-off analysis of energy cost and capital cost resulting from different temperature approaches in the cross-exchanger of a solvent-based CO2 capture process, was evaluated. The aim was to examine the cost reduction and CO2 emission reduction potentials of the different heat exchangers. Each specific heat exchanger type was assumed for the cross-exchanger, the lean amine cooler and the cooler to cool the direct contact cooler’s circulation water. The study was conducted for flue gases from a natural-gas combined-cycle power plant and the Brevik cement plant in Norway. The standard and the lean vapour compression CO2 absorption configurations were used for the study. The PHE outperformed the fixed tube sheet shell and tube heat exchanger (FTS-STHX) and the other STHXs economically and in emissions reduction. The optimal minimum temperature approach for the PHE cases based on CO2 avoided cost were achieved at 4 °C to 7 °C. This is where the energy consumption and indirect emissions are relatively low. The lean vapour compression CO2 capture process with optimum PHE achieved a 16% reduction in CO2 avoided cost in the cement plant process. When the available excess heat for the production of steam for 50% CO2 capture was considered together with the optimum PHE case of the lean vapour compression process, a cost reduction of about 34% was estimated. That is compared to a standard capture process with FTS-STHX without consideration of the excess heat. This highlights the importance of the waste heat at the Norcem cement plant. This study recommends the use of plate heat exchangers for the cross-heat exchanger (at 4–7 °C), lean amine cooler and the DCC unit’s circulation water cooler. To achieve the best possible CO2 capture process economically and in respect of emissions reduction, it is imperative to perform energy cost and capital cost trade-off analysis based on different minimum temperature approaches.

A Cost Model for 3D Woven Preforms

Lack of cost information is a barrier to acceptance of 3D woven preforms as reinforcements for composite materials, compared with 2D preforms. A parametric, resource-based technical cost model (TCM) was developed for 3D woven preforms based on a novel relationship equating manufacturing time and 3D preform complexity. Manufacturing time, and therefore cost, was found to scale with complexity for seventeen bespoke manufactured 3D preforms. Two sub-models were derived for a Weavebird loom and a Jacquard loom. For each loom, there was a strong correlation between preform complexity and manufacturing time. For a large, highly complex preform, the Jacquard loom is more efficient, so preform cost will be much lower than for the Weavebird. Provided production is continuous, learning, either by human agency or an autonomous loom control algorithm, can reduce preform cost for one or both looms to a commercially acceptable level. The TCM cost model framework could incorporate appropriate learning curves with digital twin/multi-variate analysis so that cost per preform of bespoke 3D woven fabrics for customised products with low production rates may be predicted with greater accuracy. A more accurate model could highlight resources such as tooling, labour and material for targeted cost reduction.

Assessment of Hanging Type Grain Cleaner Drudgery Reducing Tool by Farm Women

The study was undertaken to assess ergonomically efficiency of hanging type wheat graincleaner, carried out in adopted villages under On Farm Testing (OFT) and Front LineDemonstration (FLD) program conducted by KVK, Mandsaur (M.P.). Total Fifteen farmwomen were selected to assess the physiological workload to compare the impact ofimproved technology over conventional practice for hanging type grain cleaner. Physiologicalparameters i.e. HR, energy expenditure, cardiac cost reduction and physiological costreduction etc., were measured during operations. The results revealed that hanging typegrain cleaner has proved proficient on time and output parameters. The average cardiaccost of work was decreased by 82.29 per cent while using hanging type grain cleaner forwheat. Drudgery reduction was found 83.96 per cent and it saved time by 89.10 per centwhen compared to traditional practice. The physiological cost of work and energyexpenditure in terms of heart rate were observed to be lower while performing activitieswith hanging type grain cleaner as compared to the traditional practice.

Healthcare Data Analytics using Power BI

Innovations in computer technologies have revolutionized attention in recent years. Data analytics has emerged as a promising tool for determination problems in various health care connected disciplines. The effective utilization of knowledge mining in deeply noticeable fields like e-business, promoting and retail has prompted application in completely different businesses and divisions. Among these components merely finding is the medical services. Medical services organizations can reduce down on medical services expense and furnish better consideration with the help of predictive analysis. Enormous information likewise helps in diminishing medicine mistakes by improving budgetary and regulatory execution, and decrease readmission. The paper aims at systematic collection of patient-related healthcare data ,analyse through Microsoft Power BI after some transformations of data and determine major disciplines to improve the patient engagement, health system management, diagnosis and cost reduction.

Precisely controlled synthesis of Co/N species contained porous carbon for oxygen reduction reaction via anion-exchanging and CO2 activation

For wide use and cost reduction of proton-exchange-membrane fuel cells (PEMFCs), the development of trandition-metal-doped porous carbon (THPCs) electrocatalysts for the oxygen reduction reaction (ORR) is urgently needed. Herein, we...

Artificial Neural Networks in Medicine

Artificial neural networks (ANNs) have proven to be efficacious for modeling decision problems in medicine, including diagnosis, prognosis, resource allocation, and cost reduction problems. Research using ANNs to solve medical domain problems has been increasing regularly and is continuing to grow dramatically. This chapter examines recent trends and advances in ANNs and provides references to a large portion of recent research, as well as looking at the future direction of research for ANN in medicine.