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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.

Deals with the construction of a strategic framework for improving the productivity of firms. Productivity improvement (PI) has become an important aspect of organizations striving for a major share in international markets. New productivity improvement strategies facilitate an increase in the awareness of PI in present day organizations and help to set‐up an appropriate framework for the management of productivity. Presents a strategic approach for improving productivity and guidelines for establishing productivity measurement criteria.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

The learning outcomes are as follows: to understand and examine the strategies that help platforms fight competition and manage networks; to analyse the role of platform governance in the management of the networks and partners’ trust; and to evaluate the strategic risks of disintermediation and multi-homing firms face while trying to sustain profits and capture value.

The case presents the dilemma faced by Deepinder Goyal, the young founder and CEO of Zomato in formulating the growth strategy for its food delivery platform, struggling to retain its market leadership position amid intensifying competition and other challenges during the COVID-19 pandemic. Zomato has become a public company with an IPO announced in mid of July 2021. Therefore, there is growing expectation for profitability among its shareholders and investors considering tailwinds of COVID-19 crisis, which have given the push towards adoption of food delivery among the customers. This has also resulted in increased competition in the industry. On other hand, there is growing dissatisfaction among its restaurant partners who have been hit hard by COVID-19 and struggling for survival. CEO Deepinder has to find how he will ensure the long-term growth for Zomato to tap the growing food delivery market in India and regain its restaurant partner’s trust.

The case is intended for post-graduate courses (MBA, PGDM) on digital business strategy or strategic management of technology-oriented businesses. The case can be used to understand the nature of competition and different strategies for platform-based businesses in the digital world. The case can also be used to study the role governance can play in efficient value creation and capture on the platform by the partner entities. Finally, the case also highlights how are platform businesses are coping with the Covid challenge. There are no specific prerequisites but knowledge on basic strategy concepts and platform business concepts will be good for better understanding. Level of difficulty is medium.

Teaching notes are available for educators only.

CSS 11: Strategy.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This study aims to review the extant literature on workplace disability inclusion in the organised sector in India and presents an integrated model based on emergent themes in indigenous studies.

The review is directed by the following foci: In what contexts was workplace disability inclusion in India empirically investigated? How was workplace disability inclusion examined (method)? What important themes emerge from the studies? Towards this, empirical scholarly studies in India, published between 2011–2019, is reviewed to identify the evolutionary trends.

Prominent themes have been identified at three levels – organization, group and individual. At an organization level, the focus is on inclusive strategy and practices. Country-specific contextual factors such as legislation, accessibility and external eco-system influence an organization’s inclusive strategy, which addresses how organizations engage with persons with disability (PwD), job mapping, accessibility and targeted recruitment. Inclusive practices span across various phases of the employee life cycle, namely, recruitment, onboarding, development and retention. At the group level, the themes highlight group boundaries, PwD-supervisor interaction, PwD-co-worker interaction and PwD-PwD interaction. At an individual level, PwD experiences are categorized as physical, job-related and psychological. Workplace treatment and experiences of PwD vary from discrimination to inclusion and along with other outcomes, are influenced by contextual factors.

This study contributes to the development of workplace disability inclusion theory, by presenting an integrated model of prominent themes, offering greater clarity and avenues for extending the literature. The paper discusses themes that can help organizations facilitate inclusion, thereby improving employment opportunities for PwD.

In a first, the study provides an integrated account of inclusion of PwD in organized sector in India.

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.

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.

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.

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