Search results

This paper aims to develop a real-time pothole detection system to improve mapping, localization and path planning, reducing vehicle instability and accident risks. Efficient mapping, accurate localization and optimal path planning stand as prerequisites to realizing accident-free navigation. Despite their significance, existing literature often overlooks the real-time detection of potholes, which poses a considerable risk, particularly during nighttime operations. Potholes contribute to vehicle imbalance, trajectory tracking errors, abrupt braking, wheel skidding, jerking and steering overshoot, all of which can lead to accidents.

Unmanned vehicles constitute a critical domain within robotics research, necessitating reliable autonomous navigation for their optimal functioning. This research paper addresses the gap in current methodologies by leveraging a Convolutional Neural Network (CNN)-based approach to detect potholes, facilitating the generation of an efficient environmental map. Furthermore, a hybrid solution is proposed, integrating an improved Ant Colony Optimization (ACO) algorithm with modified Bezier techniques, complementing the CNN approach for accident-free and time-efficient unmanned vehicle navigation. The conventional Bezier technique is enhanced by incorporating new control points near sharp turns, mitigating rapid trajectory convergence and ensuring collision-free paths.

The hybrid solution, combining CNN with path smoothing techniques, is rigorously tested in various real-time scenarios. Experimental results demonstrate that the proposed technique achieves a 100% reduction in collisions in favorable conditions, a 4.5% decrease in path length, a 100% reduction in sharp turns and a significant 23.31% reduction in total time lag compared to state-of-the-art techniques such as conventional ACO, ACO+ Bezier and ACO+ midpoint Bezier, Improved ACO, hybrid ACO+ A*.

The proposed technique provides a proficient solution in the field of unmanned vehicles for accident-free time efficient navigation in an unstructured environment.

The purpose of this study is to represent an attempt to empirically capture the impact of disinvestment on the financial and operating performance of 26 Bombay Stock Exchange (BSE) listed central public sector enterprises (CPSEs) in India which got divested through stock market mechanism during the time period of 2000–2014.

Through ratio analysis different ratios such as return on assets, return on equity, net income efficiency, debt equity, dividend payout and employment levels have been computed. Pre- and post disinvestment performance of these firms is examined through Wilcoxon signed-rank test. The present research endeavors to examine the impact of disinvestment through random effect panel data models in order to control the effect of other firm specific variables.

The overall results of the study indicate statistically significant fall in profitability ratios. The empirical results have not witnessed positive effect of disinvestment on the profitability of the CPSEs; rather, this effect has found to be negative. The possible reasons behind these negative results could be poor pre disinvestment financial health of CPSEs, negative rate of return on capital employed by PSEs and inefficiency which need to be tested empirically by future researchers.

The fact that government-owned firms are typically less proficient or at least less gainful than private-owned firms is widely hypothesized. Therefore, the disinvestment policy aims at dropping the participation of the public sector in the economic actions of the country in order to support the private sector. The present study is a first of its kind to study the impact of disinvestment on the profitability of the firms, which got divested through stock market mechanism since the year 2000 by applying both univariate and multivariate analysis.

The present study aims to examine the short-term effect of disinvestment oriented IPOs and FPOs on the stock market performance of Indian central public sector enterprises (CPSEs), which divested their equity between 2000 and 2017.

The analysis of stock price reaction is conducted for listing dates only in the case of IPOs and three different dates in the case of FPOs through the event study methodology. The three-event dates related to FPOs are public notification date (PND), issue announcement date (IAD) and price band date (PBD).

Overall empirical analysis indicates that investor sentiments are generally insignificant prior to and posts the PND (first date). The second major date of announcement that is (IAD) is new information in the market and returns are found to be significantly negative across both the periods that is before and after IAD. Thus, the analysis depicts strongly negative investor sentiments in the case of IAD. These results are further substantiated by negatively significant CAR (cumulative abnormal returns) values for both the pre and post-event windows of PBD as well.

Empirical analysis concludes that investors do not stand a chance to gain abnormal returns through initiating positions in the stocks of CPSEs during the alternative event dates analyzed.

Since the year 2000, disinvestment through public offering has gathered momentum, and this mode accounts for approximately 62% of the collective disinvestment funds generated by the government of India till now. But there have been very limited research studies on the market performance of disinvested CPSEs. This analysis provides new empirical evidence for the market reactions of retail investors in response to the sale of equity by the Indian government in CPSEs.

This paper presents a systematic literature review of the various aspects of reverse logistics (RL) and closed-loop supply chains (CLSC) in implementing and achieving circular economy (CE) motives. CE is identified as a method of embracing imperishability into the economic structure, helping shift from a linear to a condition leading to ecological and social benefits.

Systematic literature was used to review a total of 80 peer-reviewed articles are included in the study and covers different concepts related to the implementation of CE, such as cost-saving, network design, sustainable RL, waste management and extended producer responsibility.

The findings reveal that the research in the domain is in a growing phase, and in recent years, a lot of attention has been given by researchers across the globe. However, further research is required in crucial areas for the adoption of CE, such as retail reverse logistics, pharmaceutical industries and resource recycling industry.

The study discusses the business needs and solutions for industries. Key enablers and barriers are listed along with the main activities involved in each sector in CLSC. Managers can design a pathway to decide which lever to use to overcome a particular challenge.

The work contributes theoretically by developing research themes in RL and CLSC practices applied to CE. It also provides theoretical and practical implications of the study, which can be used as a signboard for further research.

The study attempts to develop a multi-product multi-period (MPMP) aggregate production plan (APP) to fulfill the customers' demand in terms of throughput and lead time for achieving market competence.

This research proposes an integrated Fuzzy analytical hierarchy process (FAHP), multi-objective linear programming (MOLP), and simulation approach. Initially, FAHP is used to select the essential objectives a firm desires to achieve. Adopting the MOLP, an APP is formulated for the firm under study. Later, the simulation model of a firm is created in a discrete-event simulation (DES) software Arena© to evaluate the applicability of the proposed APP. A comparative analysis of the manufacturing performance levels (namely throughput, lead time, and resource utilization) achieved through the implication of an existing production plan and proposed APP is conducted further.

The findings from the study depict that the proposed MOLP-based APP can satisfy the customers' requirement (namely throughput and lead time) and improve the level of resource utilization compared with the firm's existing production plan.

The proposed research facilitates researchers and practitioners to understand the process of developing MOLP-based MPMP APP and analyzing its applicability through simulation technique to be utilized for developing APP at their firm.

An integrated FAHP-MOLP-simulation framework is the novel contribution to the literature on production planning. It can be extended to solve strategic, tactical, and operational problems in different domains like service, healthcare, supply chain, logistics, and project management.

According to the efficient market hypothesis, a company's advertising expenditures are fully reflected in its stock price. If so, then future abnormal stock returns should not be correlated to advertising spending. Nonetheless, this chapter explores the impact of advertising spending on the abnormal stock returns using portfolio sort based on both the advertising intensity and change in advertising intensity. Using data from 2000 to 2019, the results suggest that larger advertising intensity is coupled with negative abnormal stock returns in India. The study suggests that market is penalizing the firms for spending more on advertising. Hence, it suggests that advertising budgets should be allocated with caution by marketing managers.

Industry 4.0 with artificial intelligence (AI), the Internet of Things, and automation are giving way to Industry 5.0 which places emphasis on workers' well-being, people, and society. The new era accentuates interaction between humans and smart machines to drive prosperity and induce sustainable contribution of industry to society. It must build a resilient economy to cope with future uncertainties or external shocks. Moreover, the sustainability effort of companies demanded by consumers, employees, shareholders, governments, and civil society requires sustainability transformation of business strategies. Applying sustainability principles in product design implies the consideration of a product's entire life cycle. Technologies accelerate sustainable production and support using natural resources efficiently taking into consideration planetary boundaries. This condition also makes for a novel perception of products, including financial products. Under the current circumstances of a volatile, uncertain, complex, and ambiguous environment, the focus on consumers and recognition of their dominance play a pivotal role in business models to maintain customer relationships. Thus, the digital, sustainable, human-centric industry is emerging. This chapter deals with digital products to enable twin transition and accomplish a sustainable business strategy simultaneously. It examines the reciprocal reinforcement of sustainability and digitalization and discusses the impact of digital sustainability on products. In this sense, this chapter also outlines the business contribution to sustainable development through digitalization. Finally, a holistic model for a hypothetical financial remittance product is offered to demonstrate how a digital product can contribute to sustainable development.

Introduction: The government has taken many initiatives for the overall growth of India after liberalisation and remarkably performed to make India an emerging economy. Due to changes in macroeconomic conditions, investment in companys’ shares includes the possibility of bearing high risk, which cannot be eliminated but, to some extent, minimised. The persistence of risks motivates investors to invest in different available options of investment. Gearing measures, a company’s financial leverage, represent the risk afforded within the company’s capital structure.

Purpose: The research aims to identify the risk-return analysis of financial geared stocks of Nifty 50 companies in India, which have debt equity ratios of more than 1.

Methodology: Convenience and cluster sampling techniques were used to identify companies with debt equity ratios of more than 1. The considered time period is 2010–2019.

Findings: This research found capital structure ratios, debt equity ratio, and total debt ratio. The total equity ratio does not have any visible effect on any of the dependent variables, i.e., Return on equity (ROE), Return on Assets (ROA), Earnings per share (EPS), Return on capital employed (ROCE). It explains the impact of high-levered firms’ performance on profitability and functioning. The study highlights that highly geared companies do not significantly impact the ROA, proving Modigliani and Miller’s (1958) irrelevant theory.

This study prioritizes the supply chain risks (SCRs) and determines risk mitigation strategies (RMSs) for the Indian apparel industry to mitigate the shock of the COVID-19 pandemic disruption.

Initially, 23 SCRs within the apparel industry are identified through an extant literature review. Further, a fuzzy analytical hierarchy process (FAHP) is utilized to prioritize the SCRs considering the epidemic situations to understand the criticality of SCRs and determine appropriate RMSs to mitigate the shock of SCRs during COVID-19.

This study prioritized and ranked the SCRs within the Indian apparel industry based on their severity during the COVID-19 disruption. Results indicate that the demand uncertainty and pandemic disruption risks are the most critical. Based on the SCRs, the present work evaluated and suggested the flexibility and postponement mitigation strategies for the case under study.

This study has novel implications to the existing literature on supply chain risk management in the form of the FAHP framework. Supply chain practitioners from the other industrial sectors can extend the proposed FAHP framework to assess the SCRs and identify suitable mitigation strategies. The results aid the practitioners working in an apparel industry to benchmark and deploy the proposed RMSs in their firm.

The present study is a unique and earlier attempt to develop a quantitative framework using FAHP to evaluate and determine the risk mitigation strategy for managing the SCRs during the coronavirus epidemic.