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Touch mode capacitive pressure sensors (TMCPS) offer superior sensitivity and linearity in comparison to normal mode CPS and have therefore seen substantial improvements in modeling and construction. This study aims to develop a sensor that is highly robust, with near-linear output characteristics, increased sensitivity and superior overload protection, making it an ideal choice for deployment in harsh industrial environments.

The proposed sensor design uses a substrate with a multi-step notch, introducing a new quadruple TMCPS and uses a small deflection model for mathematical analysis. Addition of a multi-step notch to traditional touch mode capacitive sensors results in quadruple touch regions which further enhances its operational range performance.

The simulation of diaphragm deflection in response to pressure is carried out by using COMSOL Multiphysics, whereas MATLAB is used for analytical simulations pertaining to variations in capacitance and capacitive sensitivity. Comparing with earlier models, there is a noticeable enhancement in capacitance, experiencing a fivefold increase. The achieved value stands at 50.1 pF, reflecting improved sensitivity for applied pressure ranging from 0 to 2 MPa.

In existing literature to improve the performance of the single TMCPS, a double-sided TMCPS has been developed. To enhance sensor performance, a substrate with a multi-step notch is proposed. The notch creates four touch regions with varying gap depths, resulting in increased capacitance and capacitive sensitivity.

The purpose of this research is to study the performance of piezoresistive pressure sensors using polysilicon as the piezoresistive material, which is typically used to measure pressure in high-temperature environments.

The performance of this sensor is enhanced by studying the influence of multi-turn configuration at which the piezoresistors are arranged. Different configurations are studied and compared by laying down their analytical solution.

The validation of analytical results is accomplished through finite element analysis using the software COMSOL Multiphysics. The best configuration, which uses a partial triple-turn configuration, was able to achieve a sensitivity of 116.00 mV/V/MPa over a simulated pressure range of 0 to 500 KPa.

The literature shows the study of single-turn and double-turn meander-shaped configuration of micro-electromechanical systems piezoresistive pressure sensor but multi-turn meander-shaped configuration using a square silicon diaphragm has not been reported. Its study has reflected promising results than its counterparts based on key performance parameters such as sensitivity and linearity and are more effective to be used for automotive, aviation, biomedical and consumer electronics applications.

The research fields of consumer behaviour and neurology are connected to the emerging subject of neuromarketing. The learning of how the human mind reacts to marketing stimulus is called neuromarketing, which integrates concepts from neuroscience and economics. It looks for the underlying brain mechanisms and affective states that shape the behaviour of consumers. Neuromarketers use methods like eye tracking, biometrics, brain imaging (fMRI and EEG) and eye tracking to try and understand how consumers make decisions, what grabs their attention and how they emotionally interact with companies, products and ads. Market grooming is the process of creating and manipulating the existing market towards a specific product, service or idea. It is the practice that helps the marketer to groom the product through various stages of marketing, be it market research, product development, advertising campaigns or creating favourable conditions for the product. All practices are performed to groom the market for a specific product, when they are combined with neuromarketing, it becomes a perfect blend for the success of product in the actual market. The study concludes that market grooming along with neuromarketing can present a significant potential for enhancing the understanding of consumer decision behaviour by increasing the validity and precision of assessing customer responses to marketing activities.

The purpose of this research is to identify the cross-functional factors and their impact after exploratory factor analysis (EFA), especially in B2B context and constructing a model to interpret and quantify the influences (sales performance score) specifically to the IT/ITES companies.

Getting answer for a corporate that where its current stand in the industry is important for the strategy making, especially for the sales team. Few academic researches charted direction toward cross-functional sales factors, but getting answer whether we can quantify that sales performance and identify what is the numeric benchmark value, is difficult. For the companies to understand the need to focus on which cross-functional factors and when, is also difficult.

After 1,079+ literature study, concluded with the 25 antecedents strongly used in previous studies and 8 more on after focused group study, pilot study and discussion with the industry leaders, 35 questions addressing 33 indicators collected in 10 months duration from 310 sales professionals, 90+ IT companies. Three samples were removed as outliers using “Mahalanobis Distance Test” for multivariate analysis, dropped two variables by “Missing value Not at Random” (MNAR). Final 15 determinants of cross-functional sales performance indicators forming four best factors with very high reliability after EFA to form a future formative model and sales performance score.

(1) In this study no moderator and mediator effect are analyzed. (2) This study is the precursor to the final model construction. (3) Business down due to recession, global pandemic, terrorism, earthquake, war etc. are not considered during this analysis and study. Only the cross-functional reasons for natural business down have been considered and analyzed. (4) Exact “Sales Performance Score (SPS)” should be calculated after model forming, adjusting and confirmatory factor analysis.

(1) The major implication of this study would be for IT/ITES companies. It will be very easy for them to quantify the sales performance and measure that scientifically. (2) There will be a way to measure, predict and take measurable actions in case sales performance of the company downfalls. (3) Also the impact will be known to the top management of the company well in advance so that they can make the proper strategy. This will be very useful in current situation when measuring business outcome and make strategy well in advance is of any company's utmost priority.

Focusing on these identified factors companies can improve its sales performance. The authors contribute in creating a statistical model and computing a sales performance score, based on the final factor loading values, would be unique and unprecedented to measure the current industry performance by quantifying its standard or benchmark value for better strategic support toward the achievement of targets.