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The purpose of this study to identify and optimize the machining of polyvinyl butyral (PVB) material for industrial uses. The research is based on input machining parameters of rotary ultrasonic machining for better understand the output response surface roughness (SR) property of polyvinyl butyral (PVB) by using the Taguchi approach. The grey relational grade analysis (GRG) is also implemented to resolve the complex interrelationship of SR data for optimization and predicting and validate the results.

In experimental work, the input parameters, namely, concentration, abrasives, power rate, grit size, tool material and hydrofluoric (HF) acid has been selected. The experiment’s design was created using MINITAB Software; the L27 orthogonal array was selected for the experimentation. SR was examined with the GRG technique for process optimization. On the other hand, for single parameter optimization analysis of variance (ANOVA) has been used.

ANOVA optimization technique gives the best result on concentration (40%) of abrasive (Al2O3+SiC+B4C), power rate (40%), grit size (600), HF acid (1.5%) and tool material (D2 alloy) are the optimal parameters to provide the slightest degree of SR. GRG optimization of multi-response parameter setting: 40% concentration, SiC+B4C mixed abrasive slurry, 40% of power rating, 280 grit size, 0.5% HF acid and high-speed tool steel tool material gives better results. The SR of PVB glass material improved by 20% after grey relational analysis.

There are several practical applications in a variety of material processing sectors, including metallurgy, machinery, electronics and transportation. These real-world applications have produced substantial and discernible economic benefits.

The analytical and optimization results will be used in the various material processing sectors, including metallurgy, machinery, electronics and transportation.

The ANOVA and grey theory approaches offer the reader a primary picture of the machining research and process parameter optimization. Combined abrasive slurry of Al₂O3+SiC+B₄C with a high power-rating exhibits lower SR. Similarly, grit size is vital; larger grits produce better SR. Ra – 0. 611 m is the lowest SR value at the hole found in trial 25 after the experimentation.

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.

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.

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.

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.

This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Environmental pollution and corresponding adverse health impacts have now become a significant concern for the entire planet. In this regard, analysts and experts are continually formulating policies to reduce environmental pollution and improve natural ecological conditions. To aid in coping with the ecological predicament, a framework has been developed in the present study to inspect the adverse environmental impacts and related health issues of coal mining.

The parameters for this study have been identified through a review of the literature and finalized 23 critical parameters of air, water, land and soil, and noise related to coal mining by consultation with experts from industry and academia. Finally, the parameters have been categorized in accordance with the level of threat they pose to the environment by assigning weight using the Bradley–Terry model considering attitudinal data acquired by a questionnaire survey.

It is found that coal mining has a relatively higher impact on four attributes of “air pollution” (suspended particulate matter [SPM], respiratory particulate matter [RPM], sulfur dioxide [SO₂] and oxides of nitrogen [NO_x]), followed by “land and soil pollution” (deforestation and surface structure diversion), “noise pollution” (vehicle movement) and “water pollution” (water hardness, total solids (TSS/TDS) and iron content). It is also found that raising the air concentration of SPM and RPM results in increased respiratory and cardiopulmonary mortality. Therefore, reducing dust concentrations into the air generated during coal mining is recommended to reduce air pollution caused by coal mining, which will reduce contamination of water and land and soil.

The model built in this study is a hypothesized model that relied on the experts' opinions considering the parameters of coal production only. However, the parameters related to the usage of coal and its consequences have been excluded. Further, only industrial and academic experts were considered for this study; however, they excluded local people, coal mining personnel, policy authorities, etc. Therefore, the study findings might differ in real circumstances. The research can further be reproduced by considering the parameters related to the use of coal and its consequences, considering the opinions of the local people, coal mining personnel and policy authorities.

Categorizing the parameters according to the threat they pose to the environment due to coal mining can help the decision-maker develop an effective policy to reduce environmental pollution due to coal mining by considering the parameters on a priority basis. In addition, the results further help the decision-makers to assess the environmental impact of coal mining and take necessary action.

The study has developed a framework using the Bradley–Terry model to categorize the environmental parameters of coal mining to develop effective environmental policies, which are original and unique in nature.

This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.

The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.

The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.

The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.

The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.

Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

In recent years, scholarly focus has shifted towards exploring the applications of disruptive technologies in professional services. These studies emphasise the need for further research in this domain. This research aims to comprehensively review the existing literature on the uses of blockchain, artificial intelligence (AI) and machine learning (ML) algorithms in professional services such as higher education, healthcare, financial securities firms and smart energy consulting. The rapid innovation and advancement in technology have led to substantial improvements in work efficiency and productivity. As industries transition towards sustainability and digitalisation, the role of energy-efficient systems becomes important in shaping smart factory designs and in further implementations. The uses of AI and other disruptive technologies for business operations not only boost production efficiency but also enhance customer satisfaction. Central to this transformation are strategies like deep learning and data/text mining, which facilitate the shift from conventional manufacturing practices to smart manufacturing. Apart from smart energy systems, the fields of higher education, healthcare and financial securities are witnessing a surge in the applications of AI, ML algorithms and blockchain technology and their contributions in emerging service economy. This study undertakes a comprehensive investigation into various factors associated with the application of disruptive technologies, evaluating their impact on the operational efficiency of professional service firms (PSFs). Through this research, we aim to identify gaps in the current literature and will suggest the directions for future research.

This study explores the significance of homestays in India as a tool for sustainable tourism, community development and cultural immersion. It begins by outlining the evolution of tourism in India and the rise of homestays, emphasising their role in providing authentic local experiences. This chapter describes the characteristics of homestays and their cultural relevance in India, showcasing their growth across diverse regions. Case studies illustrate the positive impact of homestays on local communities. The literature review explores global perspectives on homestays, highlighting their contribution to reducing rural poverty and supporting community-based tourism. The research design employs secondary data to analyse the distribution of homestays in Indian states. The analysis section interprets the data, revealing patterns influenced by factors such as tourism promotion, cultural appeal and community involvement. The discussion emphasises the shift in traveller preferences towards immersive experiences and acknowledges challenges associated with homestays, such as quality concerns and regulatory issues. The study concludes by advocating for strategic development, supportive policies and awareness campaigns to ensure the authenticity and sustainability of homestay experiences. Overall, the research provides insights for stakeholders aiming to leverage homestays for sustainable tourism growth in India.

This study aims to focus on examining the impact of transformational leadership on employee creativity to enhance organizational innovation through mediating effect of intrinsic motivation and the moderating effect of organizational culture on the relationship between employee creativity and organizational innovation in Indian automobile industries.

Responses were collected from engineers, managers and R&D professionals from car manufacturing and R&D units from southern India through a structured questionnaire. The data were analyzed using IBM SPSS version 20. The validity of the constructs and the theoretical model were confirmed by applying structural equation modeling approach using IBM SPSS Amos version 20.

Empirical findings proved that transformational leadership has a positive effect on employee creativity, as mediated by intrinsic motivation. Studies also revealed that employees tend to exhibit higher creative potential when they are exposed to a higher degree of distinct shared assumptions, values and beliefs, which governs their behavior in an organization.

As research was carried out in Indian automobile manufacturing and R&D units, it cannot be generalized across the broader range of sectors and international environment.

This research is unique in its attempt to empirically test the moderating effect of organizational culture in enhancing organizational innovation in Indian automobile industry.