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Article
Publication date: 1 January 1992

Suresh K. Goyal and S.G. Deshmukh

Gives a critical review of the existing literature on just‐in‐timemanufacturing. Suggests a relevant literature classification scheme,followed by subsections on each class and…

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Abstract

Gives a critical review of the existing literature on just‐in‐time manufacturing. Suggests a relevant literature classification scheme, followed by subsections on each class and offers critical comments. Also identifies the possible research portfolios after an explanation of the gap existing between theory and practice.

Details

International Journal of Operations & Production Management, vol. 12 no. 1
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 23 November 2021

Ruchi Tyagi and Suresh Vishwakarma

The Electric Vehicles Initiative (EVI) is a multi-government policy forum devoted to speed up the introduction and adoption of electric vehicles (EVs) worldwide. EVI key themes…

593

Abstract

Purpose

The Electric Vehicles Initiative (EVI) is a multi-government policy forum devoted to speed up the introduction and adoption of electric vehicles (EVs) worldwide. EVI key themes for sustainable development include energy-efficient transportation with e-mobility (drive-by science and technology), reduced greenhouse gas emissions, decreased oil dependence and improved local air quality. India's transport sector contributes around 142 million tons of CO2 every year, with road transport contributing 123 million tons.

Design/methodology/approach

Review methodology forms a basis for knowledge development, creating guidelines for policy and practice. Quality assessment of review articles is by using mixed methods appraisal tool (MMAT).

Findings

The research trends on Sustainable Development Goal (SDG) technological and social aspects highlight the critical role of technology in economic and social development, emphasising infrastructure development and communication of government policy and rewards for awareness and end-user acceptance.

Originality/value

The scenario brings a school of thought if it is equally important to address a social perspective to improve India's perception and acceptance of technology-enabled EVs.

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Book part
Publication date: 29 May 2023

Sagar Suresh Gupta and Jayant Mahajan

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to…

Abstract

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.

Details

Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalised Economy
Type: Book
ISBN: 978-1-83753-416-6

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Article
Publication date: 1 January 2025

Gargi Raj

This study aims to evaluate how biases among retail investors – such as mental accounting, overconfidence and herd behaviour – affect their investment choices, while also…

69

Abstract

Purpose

This study aims to evaluate how biases among retail investors – such as mental accounting, overconfidence and herd behaviour – affect their investment choices, while also examining how demographics, specifically, age, gender and income moderate these effects.

Design/methodology/approach

This paper uses quantitative method for collecting data through questionnaire from 385 Indian investors investing actively in stock market. The relationship was tested using partial least squares structural equation modelling through SmartPLS 4.0. To analyse the moderating role of demographics, multi-group analysis with percentile bootstrapping approach was performed.

Findings

The results reveal the varying effect of each bias on investment decision. The evidence proves the presence of herd behaviour, overconfidence and mental accounting while making investment decisions. Furthermore, age and gender was found to be moderating the effect of biases and investment decision of Indian investors. Also, the results imply that female investors are more prone to herd behaviour compared to their male counterparts.

Research limitations/implications

The study confirms that investors often deviate from complete rationality, with their investment decisions constrained by available resources, information and cognitive processing abilities, consistent with the theory of bounded rationality. The findings offer practical insights for financial advisors, educators, investors, government agencies and regulators to enhance investment decision-making practices.

Originality/value

This study offers new perspectives on the impact of behavioural biases on investment decisions. Particularly, the study enhances the understanding of investment patterns and contributes to the behavioural finance literature by addressing the interplay between demographics and investor behaviour in a rapidly growing economy.

Details

International Journal of Accounting & Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1834-7649

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Article
Publication date: 16 August 2022

Saumyaranjan Sahoo, Satish Kumar, Mohammad Zoynul Abedin, Weng Marc Lim and Suresh Kumar Jakhar

Deep learning (DL) technologies assist manufacturers to manage their business operations. This research aims to present state-of-the-art insights on the trends and ways forward…

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Abstract

Purpose

Deep learning (DL) technologies assist manufacturers to manage their business operations. This research aims to present state-of-the-art insights on the trends and ways forward for DL applications in manufacturing operations.

Design/methodology/approach

Using bibliometric analysis and the SPAR-4-SLR protocol, this research conducts a systematic literature review to present a scientific mapping of top-tier research on DL applications in manufacturing operations.

Findings

This research discovers and delivers key insights on six knowledge clusters pertaining to DL applications in manufacturing operations: automated system modelling, intelligent fault diagnosis, forecasting, sustainable manufacturing, environmental management, and intelligent scheduling.

Research limitations/implications

This research establishes the important roles of DL in manufacturing operations. However, these insights were derived from top-tier journals only. Therefore, this research does not discount the possibility of the availability of additional insights in alternative outlets, such as conference proceedings, where teasers into emerging and developing concepts may be published.

Originality/value

This research contributes seminal insights into DL applications in manufacturing operations. In this regard, this research is valuable to readers (academic scholars and industry practitioners) interested to gain an understanding of the important roles of DL in manufacturing operations as well as the future of its applications for Industry 4.0, such as Maintenance 4.0, Quality 4.0, Logistics 4.0, Manufacturing 4.0, Sustainability 4.0, and Supply Chain 4.0.

Details

Journal of Enterprise Information Management, vol. 36 no. 1
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 30 August 2023

Sneha Badola, Aditya Kumar Sahu and Amit Adlakha

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore…

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Abstract

Purpose

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Design/methodology/approach

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

Findings

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

Research limitations/implications

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

Originality/value

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

Details

Qualitative Research in Financial Markets, vol. 16 no. 3
Type: Research Article
ISSN: 1755-4179

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Article
Publication date: 8 January 2018

Ashima Goyal and Abhishek Kumar

The purpose of this paper is to estimate the relationship between the current account (CA) and fiscal deficit (FD), and the real exchange rate for India, for the managed float…

337

Abstract

Purpose

The purpose of this paper is to estimate the relationship between the current account (CA) and fiscal deficit (FD), and the real exchange rate for India, for the managed float period 1996 Q2 to 2015 Q4, after controlling for output growth and oil shocks. It also examines the cyclicality of the CA, the size of each shock, and assesses whether aggregate demand, forward-looking smoothing, or supply shocks dominate outcomes.

Design/methodology/approach

The authors use several variants of structural vector autoregression (SVAR), implemented with quarterly Indian data, to control for effects of oil prices, and the output cycle, and then see how FD shocks affect the current account deficit (CAD) and the real exchange rate. For robustness, the authors tried different identifications, changed variable definitions, added new variables, or substituted with other variables. The cyclicality issue is addressed by examining the effect of growth shocks. The relative size of each shock is assessed through co-movement decompositions of the forecast errors. Responses to shocks help identify dominant influences on India’s CAD.

Findings

The CAD is found to be countercyclical. A FD shock raises the CAD, but high impact growth shocks and large variance oil shocks lead to overall divergence of the deficits. There is some support for the aggregate demand channel, but it is moderated by supply shocks and compositional effects. Consumption is sticky rather than forward-looking.

Originality/value

The paper contributes to the literature by including supply shocks, compositional effects, cyclicality, real interest and exchange rate in a theoretically and empirically consistent way for the analysis of twin deficits. The large empirical literature on twin deficits in EMs has not yet done this. There is no study using quarterly data in an SVAR allowing the dynamic relationship between the variables to be explored. The extensions bring in the supply side and compositional effects qualify the working of both the channels, with empirical exercises supporting theoretical predictions.

Details

Journal of Economic Studies, vol. 45 no. 1
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 28 February 2023

Natalia García-Fernández, Manuel Aenlle, Adrián Álvarez-Vázquez, Miguel Muniz-Calvente and Pelayo Fernández

The purpose of this study is to review the existing fatigue and vibration-based structural health monitoring techniques and highlight the advantages of combining both approaches.

375

Abstract

Purpose

The purpose of this study is to review the existing fatigue and vibration-based structural health monitoring techniques and highlight the advantages of combining both approaches.

Design/methodology/approach

Fatigue monitoring requires a fatigue model of the material, the stresses at specific points of the structure, a cycle counting technique and a fatigue damage criterion. Firstly, this paper reviews existing structural health monitoring (SHM) techniques, addresses their principal classifications and presents the main characteristics of each technique, with a particular emphasis on modal-based methodologies. Automated modal analysis, damage detection and localisation techniques are also reviewed. Fatigue monitoring is an SHM technique which evaluate the structural fatigue damage in real time. Stress estimation techniques and damage accumulation models based on the S-N field and the Miner rule are also reviewed in this paper.

Findings

A vast amount of research has been carried out in the field of SHM. The literature about fatigue calculation, fatigue testing, fatigue modelling and remaining fatigue life is also extensive. However, the number of publications related to monitor the fatigue process is scarce. A methodology to perform real-time structural fatigue monitoring, in both time and frequency domains, is presented.

Originality/value

Fatigue monitoring can be combined (applied simultaneously) with other vibration-based SHM techniques, which might significantly increase the reliability of the monitoring techniques.

Details

International Journal of Structural Integrity, vol. 14 no. 2
Type: Research Article
ISSN: 1757-9864

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Article
Publication date: 15 November 2018

Simarjit Kaur, Suresh Rajabhau Bhise, Amarjeet Kaur and K.S. Minhas

The present study was carried out to standardize the method for preparation of naturally carbonated fermented paneer whey beverage by incorporating pineapple and strawberry fruit…

196

Abstract

Purpose

The present study was carried out to standardize the method for preparation of naturally carbonated fermented paneer whey beverage by incorporating pineapple and strawberry fruit juice and to check their suitability in the beverage by evaluating the organoleptic characteristics and shelf life of product.

Design/methodology/approach

Beverage was inoculated with yeast culture Clavispora lucitaniae at 0.5 per cent v/v and fermented at 35 ± 1°C for 36 h aerobically. Standardization of total soluble solids (TSS) (16, 15, 14, 13 and 12oBrix) and juice concentration (15, 20, 25 and 30 per cent) of beverage was done on the basis of organoleptic evaluation, and the beverage with TSS 12oB and 30 per cent juice was selected best for further storage study. Two types of beverages were prepared: paneer whey beverage blended with pineapple juice and paneer whey beverage blended with strawberry juice, and were stored at refrigerated (4 ± 1oC) and ambient (25 ± 5oC) conditions. Effect of storage on physico-chemical, microbiological and sensory attributes were studied periodically after every 15 days for 90 days of storage period.

Findings

There was significant decrease in brix:acid ratio (p = 0.0008) from 12.0 to 9.3, total sugar (p = 0.017) from 10.8 to 6.8, ascorbic acid (p = 0.002) from 17.8 to 9.3 mg/100 mL and lactose (p = 0.037) from 3.1 to 0.6 per cent content over 90 days of ambient storage period. Total yeast count increased during the initial stages of fermentation and started declining after 60 days of storage. The alcohol production started after 15 days and reached 0.7 per cent after 90 days for paneer whey beverages blended with strawberry juice. The more variations were found in the physico-chemical and microbiological properties of the beverage at ambient storage than refrigeration storage. Highest score for color, flavor, mouthfeel and overall acceptability was found on third days, which decreased further during the storage. The comparative study of the paneer whey beverage blended with strawberry juice stored at ambient and refrigeration temperature showed that maximum decrease was found for score of appearance/color, flavor, mouthfeel and overall acceptability at ambient temperature as compared to refrigeration temperature. Beverage stored at refrigeration temperature was found more acceptable than the beverage which was stored at ambient temperature irrespective of all types of beverages.

Originality/value

The refrigerated beverage was found more acceptable up to 90 days, whereas beverage stored under ambient conditions was found acceptable up to 60 days. The products so obtained had naturally produced CO2, and little alcohol content added effervescence, sparkle, tangy taste and flavoring characteristics.

Details

Nutrition & Food Science, vol. 49 no. 4
Type: Research Article
ISSN: 0034-6659

Keywords

Available. Open Access. Open Access
Article
Publication date: 4 July 2023

Stutee Mohanty, B.C.M. Patnaik, Ipseeta Satpathy and Suresh Kumar Sahoo

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

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Abstract

Purpose

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

Design/methodology/approach

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Findings

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Research limitations/implications

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

Practical implications

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

Originality/value

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

Details

Arab Gulf Journal of Scientific Research, vol. 42 no. 3
Type: Research Article
ISSN: 1985-9899

Keywords

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