Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

Department of General Management

Knowing about the future returns attract every investor. Investors can take appropriate decisions once they know what would be the future returns based on their investments. To know the returns, the earlier studies have proposed basic models like Efficient Marker Hypothesis and Random Walk Model, whereas these theories have their own limitations in predicting the direction of the stock and the next day value of the stock. Later with the evolution of Machine learning and Deep Learning Techniques, there were many experiments which were made to study the stock markets. The present research paper aims at applying the Deep Learning technique of Artificial Neural Network to predict the direction of the stock index. The data consist of daily open price, close price, high price, low price and volume of NIFTY 50, S&P 500, New York Stock Index, Korean Stock Index, Dow Jones Index and Shanghai Stock Index from Jan 2015 to May 2020. The open price of the index is fed as input to the Artificial Neural Network. The model is evaluated on different performance metrics of Accuracy, Precision, Recall and F1-Score.

World University root node

VIT Business School

Vellore Campus

Fulltext

Predicting stock market movements using artificial neural networks

Psychological reactance gained scholarly attention and is continued to be explored across various disciplines ever since Brehm proposed reactance theory in 1966. Proliferation of intrusive marketing and promotion efforts across communication channels induce negative reactions from significant number of consumers. Little effort has been made in reviewing and consolidating the results of previous literature in the context of consumer reactance. To address this research gap the current study systematically reviewed the existing literature and has attempted to classify consumer reactance variables by using the stimulus–organism–response (S–O–R) framework. A conceptual framework was then built to explain the interrelationships between these three key S–O–R elements of consumer reactance. Lastly the implications for practitioners’ and researchers’ have been discussed. Propositions for future research are put forward. © 2020, Springer Nature Switzerland AG.

Management Review Quarterly

Toward an integrated model of consumer reactance: a literature analysis

Purpose: The objective of the paper is to identify and model the relevant enablers related to the issue of adoption and implementation of project-based learning (PjBL) in higher educational institutions. Design/methodology/approach: The present study has developed an integrated model using interpretive structural modeling (ISM) and the Fuzzy Matrice d' Impacts Croises Multiplication Appliqué an Classement (FMICMAC) approach, which helps to identify and classify the important enablers and reveal the direct and indirect effects of each enabler on the PjBL implementation in higher educational institutions. Findings: The paper has identified the key enablers and presented an integrated model using ISM and FMICMAC. The result shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and strategic importance, while another group consists of those enablers that have high dependence and are the resultant actions. Research limitations/implications: The study proposes a scientific way to model the relevant enablers to implementation of PjBL. This would help higher educational institutions to prioritize the enablers as these are hierarchically structured. The model is based on the experts' opinions, which may be biased, influencing the final output of the structural model. Originality/value: Enablers are building blocks for the adoption of PjBL. The study presents an integrated model using ISM and FMICMAC to identify and categorize various key enablers of PjBL adoption in higher education institutions. The results will help higher educational institutions to focus on the right enablers for the successful implementation of PjBL in their programs. © 2021, Emerald Publishing Limited.

International Journal of Quality and Reliability Management

Modeling the enablers of project-based learning: an ISM-Fuzzy MICMAC approach

There has been a growing concern about the performance measures based on traditional accounting information such as return on equity (ROE), return on capital employed (ROCE), return on net worth (RONW), earning per shares (EPS), net operating profit after taxes (NOPAT) and return on investment (ROI). These measures although widely used fail to capture the shareholders’ value creation/destruction as a result of management actions. The concept of economic value added (EVA) and market value added (MVA) have gained popularity all over the world particularly in the USA, the UK and European countries. EVA and MVA are finding acceptance as internal and external performance measures because these two measures are consistent with the organizational objective of shareholders’ value creation. Due to its popularity, a lot of research work has been conducted in the late 1990s covering diverse issues on EVA and MVA. In the light of the above, the present study made an attempt to calculate EVA as well as MVA and to analyze whether Apollo Tyres is creating or destroying shareholders’ wealth during the study period.

Department of Production, Operations, Systems and Quantitative Methods

South Asian Journal of Business and Management Cases

Is Apollo Tyres Creating or Destroying Shareholders’ Wealth?

This research is about the usage of Disruptive technology in recruitment process in the current scenario and the study is made with reference to recruitments that happen in IT Industries&nbsp;

International Journal of Advanced Science and Technology

Disruptive Technology Factors influencing digital recruitment Practices

How corporate Identity helps in creating brands and attracts the customers. This helps a lot in making consumer decisions and this paper is done on Royal Enfield&nbsp;

Test Engineering and Management

Corporate Identity: Relevance in Transformation of Logos in FMCGs

Striving to keep up the competition, small and medium enterprises (SMEs) in India have been deploying many process improvement measures. This paper is designed to analyse Kaizen events with a few live case studies on energy conservation to enhance industry's margins. When corresponding events are practiced in SMEs, it shall also support Government of India's mission in meeting energy conservation targets apart from market competition. This paper is based on case study research design methodology from industries. Case studies are deployed for collecting data on energy savings. Tools adopted in the studies are based on Lean-Kaizen structure. Carbon emissions are assumed from international conventions on energy. Case studies leading to reduction of energy sources like, LPG, diesel and coal and, reduction electricity are tabulated. This paper dedicated on energy conservation deploying Kaizen events is one of the first initiatives. Copyright © 2020 Inderscience Enterprises Ltd.

International Journal of Services and Operations Management

An empirical study on Kaizen events in Indian small and medium enterprises

Vibrio parahaemolyticus is a major seafood-borne pathogen causing significant economic losses in aquaculture systems. Therefore, application of phage encoded enzymes, particularly endolysin, as a new strategy for effective biocontrol and therapeutic agent against bacterial diseases. In the present study, we synthesized endolysin gene (Vplys60) of bacteriophage qdv001 and biochemically characterized by expressing in Pichia pastoris X-33. In addition to, we also investigated the anti-biofilm and anti-vibriosis activity of Pichia-expressing Vplys60 against vibrio challenged in vivo aquaculture model, Artemia franciscana. The result indicated that the predicted molecular size of Pichia expressed Vplys60 was approximately 28 kDa as verified by SDS-PAGE and zymogram. Vplys60 manifested stable activity over broad range of pH (6–10), temperatures (37–75 °C) and salinity (100–600 mM NaCl). Biochemical and in silico analysis revealed that addition of calcium ion (Ca2+) enhanced the lytic activity of Vplys60 whereas other metal ions inhibited the activity. Additionally, calcium-dependent Vplys60 has showed a strong amidase activity by cleaving the peptidoglycan of V. parahaemolyticus. Our data also showed that Vplys60 (75 μg/ml) significantly inhibits biofilm formation (91.6%) and significantly reduced the bacterial population. The in vivo challenge study showed enhanced survival rate in combination with reduced vibrio load in Artemia after administration of Pichia-expressing Vplys60. © 2019 Elsevier B.V.

Department of English

School of Social Sciences & Languages

VIT Unitversity

Department of Energy and Power Electronics

School of Electrical Engineering

Department of Biotechnology

School of Bio Sciences and Technology

International Journal of Biological Macromolecules

Recombinant engineered phage-derived enzybiotic in Pichia pastoris X-33 as whole cell biocatalyst for effective biocontrol of Vibrio parahaemolyticus in aquaculture

The environment in which supply chain (SC) operate keeps changing and so does the SC, making uncertainty as it's trait. SC agility is the key attribute which defines the capability to respond efficiently and effectively to such changes in order to achieve desired performance and achieve sustainable source of competitive advantage. The purpose of this study is to identify the enablers to achieve agility in automotive aftermarket SC and further modelling these enablers to understand their driving power, dependence and strategic importance. In phased approach, this article defines the various attributes of the automotive aftermarket SC which impacts its agility based on literature review and expert interviews and establishes interaction among the variables. Interpretive structural modelling (ISM) is used to present a hierarchy-based model and the mutual relationships among these enablers. ISM is supported with MICMAC analysis to determine the driving and dependence power among variables. Based on the results from the model of ISM, this paper also proposes the conceptual model and poses hypothesis for achieving SC agility and its impact on SC performance. In concluding remarks, paper provides commentary on the managerial implications, limitation of the current study along with future research directions. © 2020 Inderscience Enterprises Ltd.

International Journal of Value Chain Management

Modelling the enablers to explore the driving power, dependence and strategic importance in achieving SC agility

The stock market index forecasting is quite a popular topic in the present economy. There are many micro and macro-economic factors which influence the stock prices. With the emergence of machine learning techniques, algorithmic trading became most popular in forecasting the stock prices. There are many traditional machine learning techniques like ARMA, ARIMA which are used to forecast the stock market index. However these techniques consider trends and patterns involved in the data. Since the stock market data is a time series and irregular in nature there will be some noise involved. The present research paper studies the forecasting of stock market index by applying Hidden Markov models which considers the hidden states within the stock market index and traditional ARIMA model. HMM considers the posterior probabilities on different hidden states using Expectation Maximization algorithm. The data considered for the study includes 5 different stock market index Dow Jones, NIFTY 50, S P 500, New York Stock Index (NYSE) and KOSPI. The data includes daily prices of Low, High, Close, Open, Volume for a period of 5 years that is 2014-2019 which accounts to approximately 1380 data points. In HMM model the closing price of the index is considered for determining the transition states and posterior probabilities at 2, 3, 4 and 5 hidden states. Akaike Information Criteria (AIC) and Bayesian information Criterion (BIC) are used to determine the states from HMM. The research paper studies the direction of the market the closing price of the stock index considering HMM. The paper is divided into 5 parts which include Part 1: Introduction, Part 2: Past study, Part 3: Machine Learning Algorithms, Part4: Data Analysis using HMM and Part 5: Results and Conclusion. © 2020 IEEE.