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The purpose of this paper is to measure the effect of rake angle on cutting forces on the rake face of single point cutting tool with two cutting conditions. The experimental setup has been developed to measure the cutting forces. The study aims to put forward the optimum cutting condition, which improves the product quality, surface finish, productivity and tool life.

The load cell-based tool dynamometer has been developed to measure the cutting forces. The experiments have performed on the mild steel bar of hardness 60 BHN. The friction and the normal forces have measured in dry cutting condition and with rust-X cutting fluids. The cutting forces for these two cutting conditions have calculated with constant depth of cut, speed and feed with different rake angles in the range of degrees 6, 7, 8, 9, 10, 11, 12, 15 and 20.

The experimental observations shows the variations of friction and normal forces with different cutting conditions and parameters. It shows the friction force on rake face increase and the normal force on the rake face decreases with increase the rake angle.

The observations has done only for mild steel of hardness 60 BHN. It can also be perform on different materials and for different cutting conditions.

The experimental setup developed in this research can be used in the manufacturing industry. It can help to decide and maintain the optimum cutting conditions.

The observations have been made on an experimental setup, which fulfills the actual working/cutting conditions as per the use in industries.

The purpose of this research is to identify and analyse the perceived risk factors affecting the safety of electric two-wheeler (E2W) riders in urban areas. Given the exponential growth of the global E2W market and the notable challenges offered by E2W vehicles as compared to electric cars, the study aims to propose a managerial framework, to increase the penetration of E2W in the emerging market, as a reliable, and sustainable mobility alternative.

The perceived risk factors of riding E2Ws are relatively scanty, especially in the context of emerging economies. A mixed-method research design is adopted to achieve the research objectives. Four expert groups are interviewed to identify crucial safety risk E2W factors. The grey-Delphi technique is used to confirm the applicability of the extracted risk factors in the Indian context. Next, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is employed to reveal the causal-prominence relationship among the perceived risk factors. The dominance and prominence scores are used to perform Cause and Effect analysis and estimate the triggering risk factors.

The finding of the study suggests that reckless adventurism, adverse road conditions, individual characteristics and distraction caused by using mobile phones, as the topmost triggering risk factors that impact the safety of E2Ws drivers. Similarly, reliability on battery performance low velocity and heavy traffic conditions are found to be some of the critical safety factors.

E2Ws are anticipated to represent the future of sustainable mobility in emerging nations. While they provide convenient and quick transportation for daily urban commutes, certain risk factors are contributing to increased accident rates. This research analyses these risk factors to offer a comprehensive view of driver and rider safety. Unlike conventional measures, it considers subjective quality and reliability parameters, such as battery performance and reckless adventurism. Identifying the most significant causal risk factors helps policymakers focus on the most prominent issues, thereby enhancing the adoption of E2Ws in emerging markets.

We have proposed an integrated framework that uses grey theory with Delphi and DEMATEL to analyse the safety risk factors of driving E2W vehicles considering the uncertainty. In addition, the amalgamation of Delphi and DEMATEL helps not only to identify the pertinent safety risk factors, but also bifurcate them into cause-and-effect groups considering the mutual relationship between them. The framework will enable practitioners and policymakers to design preventive strategies to minimize risk and boost the penetration of E2Ws in an emerging country, like India.

In the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).

A hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.

The study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.

The study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.

The literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

This study aims to explore the constituents of artificial intelligence (AI)-augmented knowledge management (AIKM) capability and its impact on clinical performance (CP) in the health-care sector. It further examines the mediating role of absorptive capacity (Abs Cap) and discusses the implications of these findings for marketing strategies, highlighting how enhanced CP through AIKM can lead to more effective and patient-centered marketing approaches.

This research uses a mixed-method design. A qualitative study through semi-structured interviews was conducted to explore the facets of AIKM. The synthesis of qualitative findings infused with the relevant literature to develop a hypothesized model of AKM, Abs cap and CP metrics (e.g. diagnostic accuracy, patient satisfaction and treatment effectiveness). A survey of health-care professional in India was conducted to assess the proposed model by using structural equation modeling (PLS-SEM).

The results demonstrate a significant positive relationship between AIKM and CP. Moreover, Abs Cap mediates this relationship partially, highlighting its crucial role in translating improved knowledge access and analysis enabled by AI into enhanced clinical outcomes.

The findings suggest that health-care organizations should invest in developing AIKM alongside strengthening Abs cap to maximize the positive impact of AI on CP and ultimately improve patient care. Future research can explore specific AIKM components and Abs cap facets influencing different aspects of CP.

This study represents a pioneering effort to conceptualize AIKM within the health-care context and empirically establish it as a higher-order factor. The inclusion of marketing strategies underscores the potential of AIKM not only in improving clinical outcomes but also in transforming health-care marketing. The mediating role of Abs Cap emphasizes the importance of organizational structures and processes that facilitate the absorption and utilization of knowledge, thereby contributing to both clinical and marketing excellence.

The purpose of this study is to present the tool life optimization of carbide-coated ball nose milling inserts when high-speed milling of Inconel 718 under cryogenic CO₂ condition. The main aims are to analyze the influence level of each cutting parameter on the tool life and to identify the optimum parameters that can lengthen the tool life to the maximum.

The experimental layout was designed using Box–Behnken RSM where all parameters were arranged without combining their highest and lowest values of each factor at the same time. A total of 29 milling experiments were conducted. Then, a statistical analysis using ANOVA was conducted to identify the relationship between the controlled factors on tool life. After that, a predictive model was developed to predict the variation of tool life within the predetermined parameters.

Results from the experimental found that the longest tool life of 22.77 min was achieved at Vc: 120 m/min, fz: 0.2 mm/tooth, ap: 0.5 mm and ae: 0.2 mm. ANOVA suggests the tool life of 23.4 min can be reached at Vc: 120.06 m/min, fz: 0.15 mm/tooth, ap: 0.66 mm and ae: 0.53 mm. All four controlled factors have influenced the tool life with the feed rate and radial depth of cut (DOC) as the major contributors. The developed mathematical model accurately represented the tool life at an average error of 8.2 per cent when compared to the actual and predicted tool life.

These experimental and statistical studies were conducted using Box–Behnken RSM method under cryogenic CO₂ condition. It is a proven well-known method. However, the cooling method used in this study is a new technique and its effects on metal cutting, especially in the milling process of Inconel 718, has not yet been explored.

This study aims to identify the constituents of internal flexibility in health-care organizations for achieving sustainability. The study incorporates resources-based theory and resource-dependence theory to illustrate how health-care organizations exhibit internal flexibility to redress environmental uncertainties and maximize organizational responsiveness.

This paper conducts a case study in a health-care organization to explore how health-care organizations acquire several resources for attaining internal flexibility. A survey of health-care professionals was conducted to assess the relationships using partial least squares-structural equation modeling.

In the present study, the dimensions of internal flexibility in health-care organizations are identified. This study also established internal flexibility as a higher-order factor and explained its underlying aspects as a value-laden perspective on sustainability.

The study was conducted in the public health-care context in India. The framework needs to be tested in another context. The sample size for the study was limited to health-care experts, which could be extended to include the customer’s perspective.

The study contributes to the body of knowledge by identifying the specific dimensions of internal flexibility and explains as a higher-order factor. It enhances the understanding of sustainability from a flexibility perspective of the firm.

The purpose of this paper is to identify the constituents of cause-related marketing (CRM) capabilities in the context of an emerging market healthcare sector, by incorporating the resource-based view alongside the dynamic capability perspective. Moreover, the authors aim to illustrate how the typologies of CRM capabilities help to achieve service innovation whilst taking into consideration the role of service flexibility (SF) and service climate.

The authors develop a research framework through a representative and novel case study in the Indian healthcare market by utilizing and analyzing the subject-specific literature. Furthermore, a quantitative survey of healthcare professionals was conducted to assess the relationships utilizing PLS–SEM.

After identifying the constituents of CRM capabilities, the study confirms the mediating mechanism of SF between CRM capabilities and service innovation. Furthermore, findings from the study suggest that service climate positively moderates the relationship between CRM capability and SF.

The study was conducted in the emerging country healthcare market of India. Thus, the generalizability of the framework needs to be tested in a similar or contrasting context. Furthermore, the sample size for the study was limited to healthcare professionals, and the customer’s perspective was missing.

This paper is a first step to identify the specific dimensions of CRM capability and explain it as a higher-order factor. The study further provides an integrative framework that includes CRM capability, service innovation, SF and service climate. More specifically, it enhances the understanding of the constituents of the CRM capabilities and their influence on service innovation.

This study aims to examine the impact of big data management on green service production (GSP) and environmental performance (ENPr) while considering green HRM practices (GHRM) in healthcare emergencies.

The authors collected primary data from major healthcare organizations in India by surveying healthcare professionals. The data analysis through structural equation modelling (PLS-SEM) reveals several significant relationships to extricate the underlying dynamics.

Grounded in the theories of service production and natural resource-based view (NRBV), this study conceptualizes GSP with its three dimensions of green procurement (GP), green service design (GSD) and green service practices (GSPr). The study conducted in India's healthcare sector with a sample size limited to healthcare professionals serving in COVID-19 identifies the positive and significant impact of big data management on GSP and ENPr that organizations seek to deploy in such emergencies. The findings of the study explain the moderating effects of GHRM on GSP-ENPr relationships.

The study was conducted in the healthcare sector in India, and its sample size was limited to healthcare professionals serving in COVID-19. The practical ramifications for healthcare administrators and policymakers are suggested, and future avenues of research are discussed.

This paper develops a holistic model of big data analytics, GP, GSD, GSPr, GHRM and ENPr. This study is a first step in investigating how big data management contributes to ENPr in an emergency and establishing the facets of GSP as a missing link in this relationship, which is currently void in the literature. This study contributes to the theory and fills the knowledge gap in this area.

This research aims to examine the impact of friction stir processing (FSP) treatment on an aluminum alloy, especially the AD31T alloy derived from the Al-Fe-Mg-Si system. The aim is to assess the influence of different processing techniques on the microstructure and physical and mechanical characteristics of the material, with a specific focus on structural and bulk imperfections inside the stir zone (SZ).

The study demonstrates that augmenting the linear velocity of the tool within the 25–100 mm/min range results in significant enhancements. The enhancements include a decrease in the heat-affected zone (HAZ), a reduction in the extent of volume defects inside the SZ and a more uniform deformation. The microstructural analysis results are corroborated by data acquired from microhardness and electrical conductivity studies, confirming the beneficial influence of modifying the tool’s linear velocity on the material parameters.

This study provides significant observations on the changes in microstructure and the generation of flaws throughout the process of FSP of AD31T alloy. These results have practical implications for improving the characteristics of the alloy and optimizing the production conditions.

All samples exhibit a distinct reduction in electrical conductivity within the initial third of the sample, aligning with the transitional region between the base metal (BM) and the HAZ. This underscores the importance of understanding the transitional zones during FSP.

This paper aims to focus on the utilisation of pre- and probiotics for oral care and the state of knowledge at this time.

Pre- and probiotics describe beneficial carbohydrates and microbiota, respectively, for optimal gut health. Carbohydrates provide energy selectively for the gut-friendly bacteria. The use of both carbohydrates and bacteria is, however, being expanded into other areas of the body – including the skin, vagina and oral cavity – for health-related applications.

There is increased interest in both pre- and probiotics for oral care products. The importance of oral microflora and their selective substrates is discussed against a background of contemporary oral care approaches. The issues and benefits are discussed in this review.

It is clear that consumption of prebiotics and probiotics may play a role as potential prophylactic or therapeutic agents for reducing the presence of organisms in the mouth associated with tooth decay. To confirm a beneficial effect of pre- and probiotics further in vivo studies involving healthy human volunteers should be considered.