Talwinder Singh, Chandan Deep Singh and Rajdeep Singh
Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in…
Abstract
Purpose
Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.
Design/methodology/approach
The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.
Findings
From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.
Practical implications
Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.
Originality/value
This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/
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Jatin Goyal, Rajdeep Singh, Harpreet Kaur and Kanwaljeet Singh
The purpose of this study is to comprehend the efficiency levels of the Indian textile industry and also its sub-sectors in the light of changing global and national business…
Abstract
Purpose
The purpose of this study is to comprehend the efficiency levels of the Indian textile industry and also its sub-sectors in the light of changing global and national business environment. It is imperative to study the efficiency levels of textile industry for an emerging economy like India, where the industry contributes up to 13 per cent in export earnings, 10 per cent in total industrial production and 2 per cent in gross domestic product (GDP). The study holds an important place in the wake of phasing out of the quota regime existing under the Multi Fibre Agreement (MFA) and the rising competition being faced from countries such as Bangladesh, Vietnam and Cambodia.
Design/methodology/approach
The present study attempts to have an in-depth analysis of the efficiency levels in the Indian textile industry using meta-frontier data envelopment analysis, which is a non-parametric linear programming based frontier technique.
Findings
The findings highlight that the Indian textile industry is inefficient and has a huge scope of improvement in terms of efficiency. It also confirms the existence of different production functions among the sub-sectors of the industry. Among the different sub-sectors, the proximity of production frontier of readymade garments is the closest to meta-frontier followed by cotton and blended yarn, man-made fibre, cloth and others.
Practical implications
The findings bear strong implications for the policymakers in their attempt to regain the lost competitive position of the Indian textile industry and to enhance its contribution in the economy. As per the findings, policymakers should target the relatively inefficient sub-sectors of textile industry (cloth, man-made fibre, cotton and blended yarn) to infuse more efficiency in these sectors to enhance the market share of the Indian textile industry in the global textiles market.
Originality/value
The current study is a unique addition to the sparse literature on managing efficiencies in the textile industry, particularly of emerging economy like India. Looking at the methodological and geographical coverage of the previous work, it was found that no study has explored and analysed the efficiencies of the sub-sectors in the Indian textile industry using meta-frontier analysis. Therefore, this study will be the first of its kind which seeks to fill such gaps and intends to enrich the available literature.
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Rajdeep Kumar Raut, Rohit Kumar and Niladri Das
This study aims to explore and comprehend the reasons behind individual investors’ intention towards socially responsible investment (SRI) in the Indian stock market along with…
Abstract
Purpose
This study aims to explore and comprehend the reasons behind individual investors’ intention towards socially responsible investment (SRI) in the Indian stock market along with examining the validity of the theory of reasoned action (TRA) model to predict such phenomenon in the Indian context.
Design/methodology/approach
The TRA has been used as an underlying framework and has been extended by adding four variables, namely, moral norms, environmental concern, financial literacy and financial performance. The study used a self-administered questionnaire and adopted a convenience sampling method for a survey to collect the data from the individual investors from the capital cities of three states of India. Further, the collected data have been analysed using two-step structural equation modelling.
Findings
Results of this study indicate a significant impact of attitude, subjective norms, moral norms, financial literacy and financial performance on investors’ intention towards SRI; however, no significant relation was found between environmental concern and investors’ SRI intention. The multiple squared correlation (R2) shows that the final model could explain 71% of the variance in investors’ intention towards SRI, which signifies a successful implementation of TRA model along with new additions to predict investors’ decision-making behaviour for SRI. Moreover, investors are found to be highly concerned primarily about their financial goals and then for their personal obligation towards society as far as SRI is concerned.
Practical implications
This study reports significant and prominent importance of subjective norms in SRI which could be a strategic theme for the government and the policymakers to influence investors through their opinion leaders to promote SRI. The government should also increase its efforts to facilitate financial literacy among citizens.
Originality/value
Using the TRA model and four variables, namely, moral norms, environmental concern, financial literacy and financial performance addition to its original variables, this study extends the understandings of SRI which is perhaps the novelty of this paper because such examination of SRI has not been conducted, especially in the case of developing countries such as India.
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Manik Chandra and Rajdeep Niyogi
This paper aims to solve the web service selection problem using an efficient meta-heuristic algorithm. The problem of selecting a set of web services from a large-scale service…
Abstract
Purpose
This paper aims to solve the web service selection problem using an efficient meta-heuristic algorithm. The problem of selecting a set of web services from a large-scale service environment (web service repository) while maintaining Quality-of-Service (QoS), is referred to as web service selection (WSS). With the explosive growth of internet services, managing and selecting the proper services (or say web service) has become a pertinent research issue.
Design/methodology/approach
In this paper, to address WSS problem, the authors propose a new modified fruit fly optimization approach, called orthogonal array-based learning in fruit fly optimizer (OL-FOA). In OL-FOA, they adopt a chaotic map to initialize the population; they add the adaptive DE/best/2mutation operator to improve the exploration capability of the fruit fly approach; and finally, to improve the efficiency of the search process (by reducing the search space), the authors use the orthogonal learning mechanism.
Findings
To test the efficiency of the proposed approach, a test suite of 2500 web services is chosen from the public repository. To establish the competitiveness of the proposed approach, it compared against four other meta-heuristic approaches (including classical as well as state-of-the-art), namely, fruit fly optimization (FOA), differential evolution (DE), modified artificial bee colony algorithm (mABC) and global-best ABC (GABC). The empirical results show that the proposed approach outperforms its counterparts in terms of response time, latency, availability and reliability.
Originality/value
In this paper, the authors have developed a population-based novel approach (OL-FOA) for the QoS aware web services selection (WSS). To justify the results, the authors compared against four other meta-heuristic approaches (including classical as well as state-of-the-art), namely, fruit fly optimization (FOA), differential evolution (DE), modified artificial bee colony algorithm (mABC) and global-best ABC (GABC) over the four QoS parameter response time, latency, availability and reliability. The authors found that the approach outperforms overall competitive approaches. To satisfy all objective simultaneously, the authors would like to extend this approach in the frame of multi-objective WSS optimization problem. Further, this is declared that this paper is not submitted to any other journal or under review.
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Rajdeep Kumar Raut, Rohit Kumar and Niladri Das
Sustainable financial practices are integral to achieving the United Nation’s development goals that necessitates the collaborative efforts of both corporate and investors. This…
Abstract
Purpose
Sustainable financial practices are integral to achieving the United Nation’s development goals that necessitates the collaborative efforts of both corporate and investors. This study focuses on investors’ pro-environmental personal norms (PN) along with hedonic values on socially responsible investment (SRI) intentions, which could help in understanding investors’ responsiveness to corporate Environmental, Social and Governance efforts.
Design/methodology/approach
The sample for this study included 415 responses from young millennial investors, using a cross-sectional research design. A two-step structural equation model was used to analyze construct reliability and validity and to test the hypotheses and overall model predictability. The mediating role of ascribed responsibility (AR) between the awareness of consequence (AOC) and PNs was investigated.
Findings
These results indicate that AOC and AR substantially affect PNs. PNs based on AOC and AR was found to be significant but scored lower than hedonic considerations for SRI. In addition, the relationship between AOC and PNs exhibited a full mediation effect on AR.
Practical implications
These findings suggest that investors are environmentally conscious when aware of the repercussions of their actions. They feel accountable, even when making financial choices. Fund managers might include more environmentally responsible companies in their portfolios and the government could offer tax incentives to attract investors. The active economic participation of an increasing number of pro-environmental investors can improve the macroeconomic climate.
Originality/value
This is the first study to use the norm activation model for pro-environmental behavior in a financial setting. Most previous studies have focused on social norms to showcase individuals’ obligation and responsibility for a good cause. However, this study demonstrates the importance of personal moral obligation in shaping societal norms. Hedonism is a new dimension in the context of responsible investment.
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Rajdeep Kumar Raut, Niranjan Shastri, Akshay Kumar Mishra and Aviral Kumar Tiwari
This study aims to investigate factors that influence the attitudes and intentions of investors towards environmental, social and governance (ESG) stocks in the presence of…
Abstract
Purpose
This study aims to investigate factors that influence the attitudes and intentions of investors towards environmental, social and governance (ESG) stocks in the presence of perceived risk as a moderator.
Design/methodology/approach
Data was collected through an online survey method from 341 investors with more than three years of investing experience. Smart PLS was used to analyse the data using two-stage structural equation modelling. First, a measurement model was performed for construct reliability and validity, followed by path analysis (structural model) for hypothesis testing and overall model predictability.
Findings
The findings show that both environmental concern (altruistic value) and economic concern (egoistic value) are crucial for the attitude and intention of investors to invest in ESG-backed stocks; however, environmental concern was found to be a more significant predictor of their behaviour, showing evidence of pro-environmental values in the decision-making of utility-seeking individuals. No significant impact of perceived risk was evident as a moderator of the relationship between attitude and intention towards ESG stocks.
Practical implications
The study's findings have implications for fund managers, policymakers, and the government. Values as antecedents were found to be influential in shaping investors’ attitudes and intentions towards the environmental cause. Fund managers could include more ESG-compliant companies in their portfolios, and the government can play an important role in encouraging investors by providing financial incentives. Corporates should also take strategic steps to adopt green production processes to secure long-term, sustainable capital funding.
Originality/value
To the best of the authors’ knowledge, there has been no research done in the field of ESG investing that takes into account the values (both altruistic and egoistic) of investors as potential antecedents of their attitudes and intentions.
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Rajat Kumar Mudgal, Rajdeep Niyogi, Alfredo Milani and Valentina Franzoni
The purpose of this paper is to propose and experiment a framework for analysing the tweets to find the basis of popularity of a person and extract the reasons supporting the…
Abstract
Purpose
The purpose of this paper is to propose and experiment a framework for analysing the tweets to find the basis of popularity of a person and extract the reasons supporting the popularity. Although the problem of analysing tweets to detect popular events and trends has recently attracted extensive research efforts, not much emphasis has been given to find out the reasons behind the popularity of a person based on tweets.
Design/methodology/approach
In this paper, the authors introduce a framework to find out the reasons behind the popularity of a person based on the analysis of events and the evaluation of a Web-based semantic set similarity measure applied to tweets. The methodology uses the semantic similarity measure to group similar tweets in events. Although the tweets cannot contain identical hashtags, they can refer to a unique topic with equivalent or related terminology. A special data structure maintains event information, related keywords and statistics to extract the reasons supporting popularity.
Findings
An implementation of the algorithms has been experimented on a data set of 218,490 tweets from five different countries for popularity detection and reasons extraction. The experimental results are quite encouraging and consistent in determining the reasons behind popularity. The use of Web-based semantic similarity measure is based on statistics extracted from search engines, it allows to dynamically adapt the similarity values to the variation on the correlation of words depending on current social trends.
Originality/value
To the best of the authors’ knowledge, the proposed method for finding the reason of popularity in short messages is original. The semantic set similarity presented in the paper is an original asymmetric variant of a similarity scheme developed in the context of semantic image recognition.
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Alfredo Milani, Niyogi Rajdeep, Nimita Mangal, Rajat Kumar Mudgal and Valentina Franzoni
This paper aims to propose an approach for the analysis of user interest based on tweets, which can be used in the design of user recommendation systems. The extract topics are…
Abstract
Purpose
This paper aims to propose an approach for the analysis of user interest based on tweets, which can be used in the design of user recommendation systems. The extract topics are seen positively by the user.
Design/methodology/approach
The proposed approach is based on the combination of sentiment extraction and classification analysis of tweet to extract the topic of interest. The proposed hybrid method is original. The topic extraction phase uses a method based on semantic distance in the WordNet taxonomy. Sentiment extraction uses NLPcore.
Findings
The algorithm has been extensively tested using real tweets generated by 1,000 users. The results are quite encouraging and outperform state-of-the-art results and confirm the suitability of the approach combining sentiment and categorization for the topic of interest extraction.
Research limitations/implications
The hybrid method combining sentiment extraction and classification for user positive topics represents a novel contribution with many potential applications.
Practical implications
The functionality of positive topic extraction is very useful as a component in the design of a recommender system based on user profiling from Twitter user behaviors.
Social implications
The application of the proposed method in short-text social network can be massive and beyond the applications in tweets.
Originality/value
There are few works that have considered both sentiment analysis and classification to find out users’ interest. The algorithm has been extensively tested using real tweets generated by 1,000 users. The results are quite encouraging and outperform state-of-the-art results.
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Mahima Hada, Rajdeep Grewal and Gary L. Lilien
From the supplier firm's perspective, a referral is a recommendation from A (the referrer) to B (the potential customer) that B should, or should not, purchase from C (the…
Abstract
From the supplier firm's perspective, a referral is a recommendation from A (the referrer) to B (the potential customer) that B should, or should not, purchase from C (the supplier firm). Thus, as referrals are for a specific supplier firm, they should be viewed as part of the supplier firm's marketing and sales activities. We recognize three types of referrals – customer-to-potential customer referrals, horizontal referrals, and supplier-initiated referrals – that have critical roles in a potential customer's purchase decision. We develop the concept of referral equity to capture the net effect of all referrals for a supplier firm in the market. We argue that supplier firms should view referral equity as a resource that has financial value to the firm as it affects the firm's cash flows and profits. We offer strategies firms can use to manage referrals and build their referral equity and suggest a research agenda.