Pallavi P. Deshmukh, Prakash A. Mahanwar and Sunil S. Sabharwal
Urethane Acrylate Oligomer with 100% solids was synthesised and characterised in order to study the application in electron beam curing with varying ratio of Trimethylol propane…
Abstract
Purpose
Urethane Acrylate Oligomer with 100% solids was synthesised and characterised in order to study the application in electron beam curing with varying ratio of Trimethylol propane triacrylate (TMPTA). The purpose of this paper is to study effect of TMPTA addition on the crosslink density and different coating properties.
Design/methodology/approach
Polyester polyol was synthesised by reacting single diacid, adipic acid (AA), with Pentaerythritol (PENTA) and 1,6‐hexanediol (HD). Further, Urethane acrylate resin was synthesised by using Isophorone diisocyanate (IPDI), hydroxy ethyl acrylate (HEA) and Polyester polyol. The polyester polyol and urethane acrylate oligomer were characterised by 1H NMR, 13C NMR, FTIR and GPC. Further, TMPTA was added as a crosslinker to the urethane acrylate oligomer and cured by electron beam radiation. The cured UA films having varying concentration of TMPTA were employed to evaluate thermal property, contact angle analysis, mechanical and chemical properties.
Findings
The obtained results showed improvement in their chemical properties, mechanical properties, thermal properties and water contact angle at 20% of TMPTA iconcentration. The TMPTA also reduced the dose required for the curing.
Research limitations/implications
The resin can be synthesised from different isocyanates as TDI, MDI and HMDI, etc. The study can also be done with different multi or mono functional monomers such as methacrylate, hexanediol diacrylate, ethylene glycol diacrylate, etc.
Practical implications
The paper provides the better solution to reduce the cost of the electron beam radiation required for the curing.
Social implications
The method presented in the paper could be very useful for controlling environmental pollution; as the conventional method of curing releases volatile organic compounds (VOC).
Originality/value
In this paper, urethane acrylate and TMTPA cured with electron beam are shown to offer good coating properties. A high‐solid urethane acrylate coating would find numerous industrial applications in surface coatings.
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Pallavi Pradeep Khobragade and Ajay Vikram Ahirwar
The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year…
Abstract
Purpose
The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India.
Design/methodology/approach
Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location.
Findings
Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region.
Practical implications
Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model.
Originality/value
The findings provide valuable results to be considered for controlling air pollution in the region.
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Ashulekha Gupta and Rajiv Kumar
Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types…
Abstract
Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.
Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.
Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.
Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.
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Durgesh Agnihotri, Kushagra Kulshreshtha, Vikas Tripathi and Pallavi Chaturvedi
The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to…
Abstract
Purpose
The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to investigate the moderating effect of green self-identity on customers' post-service failure behavioral intentions.
Design/methodology/approach
A self-administered questionnaire was distributed to 327 participants who had experienced service failure while dining in green restaurants. The study draws upon the prevailing literature to examine the relationship among the constructs using structural equation modeling (SEM).
Findings
The findings of the study have confirmed that service failure has an adverse effect on customers' revisit intention toward the green restaurants. However, customers with green self-identity appear less anxious about service failure as findings indicate customers revisit green restaurant even after service failure.
Practical implications
The study provides a clear indication to the managers of the green restaurants that a better understanding of service failure attributions may facilitate in preventing service failure in a prompt and reasonable manner. It will not only contribute to building the brand reputation, but also ensure that customers stay with the brand for a longer duration.
Originality/value
The study is unique in a way that it is the first of its type to establish a relationship between service failure attributions and customer satisfaction in the emerging South Asian market, such as India in the context of green restaurants. Besides, this is the only study to use green self-identity as a moderator between the relationships of customer satisfaction and revisit intention.