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This work aims to investigate the feasibility of recycling waste plastic (polyethylene terephthalate) as a coarse aggregate for producing blended cement concrete modified with fly ash and pond ash.

The low, medium and high controlled strength blended cement concrete modified with varied proportions of fly and pond ashes were produced. Manufactured sand and recycled plastic coarse aggregate (RPCA) replaced normal fine and coarse aggregates. Concrete samples were tested for workability, mechanical and durability characteristics. Microstructural analysis was performed on cement concrete blended with fly and pond ashes and compared to conventional concrete samples.

All concrete mixes showed better flowability with values greater than 200 mm. Besides, the maximum flow time was approximately 8 s. The wet density of blended cement concrete-RPCA-based concretes was approximately 30% lower than that of conventional concrete. The compressive strengths of the controlled strength mix at 7 and 28 days were within the specified ranges. While the conventional concrete had slightly higher permeability, the blended cement concrete-RPCA-based concretes had better thermal resistivity and lower thermal conductivity. The scanning electron microscopy analysis revealed the densification of the microstructure due to the filler effects of fly and pond ashes.

This study establishes the prospects of substituting RPCA with normal coarse aggregate in the production of controlled low-strength blended cement concrete, offering benefits of structural fill concrete, lower permeability and thermal conductivity, higher thermal resistivity and reduced density and shrinkage.

Developing nations are starting to take centre stage and are becoming more conscious of their economic potential in the tourism sector. Earlier, these countries were largely left out of the tourist sector. Today, the foreign exchange reserves of these nations are mostly derived from tourism and a nation's balance of payments derived through tourism supports international trade and stabilizes the economy. The chapter adopts a case study method to evaluate the prospects of inclusive growth through socio economic well-being. In the dynamic and constantly evolving tourism industry, it is imperative to make the growth more inclusive so that there is a balanced approach to long term sustainable development. When it comes to using traditional skills and cultural heritage to participate in this economic paradigm, rural artisans face both opportunities and challenges as the global tourism landscape undergoes evolving transformations. The study commences by closely examining the current market obstacles that rural artisans in the tourism industry face, which encompass a range of issues such as shifting consumer preferences, market saturation and the aftermath of external shocks like pandemics. The chapter indicates major obstacles impeding the integration of rural artisans into the tourism value chain by means of a thorough empirical analysis. In order to overcome the obstacles, the study investigates inclusive growth and how it might act as a spur to improve the socio-economic circumstances of rural craftsmen. The findings in the chapter distil best practices that promote inclusivity, empower local communities and support sustainable tourism development by looking at successful case studies and policy interventions.

Renewable energy sources and smart devices are options for those wishing to lessen their reliance on fossil fuels. Smart devices in the home also allow energy providers to remotely control energy use (RCEU). However, little is understood about consumer’s perceptions of RCEU programs. Based on the theory of planned behavior (TPB), it is proposed that environmental attitudes, environmental self-identity, green history, subjective norms and perceived behavioral control will predict differences in both purchase intentions and RCEU.

Data from 692 participants was collected via an online survey of energy consumers. The relationship between study variables was examined using regression analyses.

The results indicate that environmental attitude, environmental identity, green history and perceived behavioral control are positively related to both purchase intentions and RCEU. The results could have important implications for energy providers, practitioners, energy consumers and citizens interested in environmental issues.

As energy providers consider ways to better manage consumer energy use, RCEU has been used more frequently. However, understanding customer perceptions of RCEU is not well-established in the green energy literature. This paper contributes a first step towards the understanding of RCEU perceptions.

This study aims to investigate the machining performance of CVD-coated carbide tools by considering most crucial machinability aspects: cutting force, tool life, surface roughness and chip morphology in high-speed hard turning of AISI 4340 alloy steel under a sustainable minimum quantity lubrication (MQL) environment.

The purpose of this study is to analyze the performance of coated carbide tools under MQL environment therefore, machining tests were performed in accordance with the Taguchi L9 orthogonal array, accommodating the three crucial machining parameters such as cutting speed (V = 300–400 m/min), feed rate (F = 0.1–0.2 mm/rev) and depth of cut (DOC = 0.2–0.4 mm). The measured or calculated values obtained in each experimental run were validated for normality assumptions before drawing any statistical inferences. Taguchi signal-to-noise (S/N) ratio and analysis of variance methodologies were used to examine the effect of machining variables on the performance outcomes.

The quantitative analysis revealed that the depth of cut exerted the most significant influence on cutting force, with a contributing rate of 60.72%. Cutting speed was identified as the primary variable affecting the tool life, exhibiting a 47.58% contribution, while feed rate had the most dominating impact on surface roughness, with an overall contributing rate of 89.95%. The lowest cutting force (184.55 N) and the longest tool life (7.10 min) were achieved with low machining parameters at V = 300 m/min, F = 0.1 mm/rev, DOC = 0.2 mm. Conversely, the lowest surface roughness (496 nm) was achieved with high cutting speed, low feed rate and moderate depth of cut at V = 400 m/min, F = 0.1 mm/rev and DOC = 0.3 mm. Moreover, the microscopic examination of the chips revealed a serrated shape formation under all machining conditions. However, the degree of serration increased with an incremental raise with cutting speed and feed rate.

The study is limited to study the effect of machining parameters within the stated range of cutting speed, feed rate and depth of cut as well as other parameters.

Practitioners may consider to adopt this machining technique to create more sustainable working environment as well as eliminate the disposal cost of the used metal cutting fluid.

By applying this machining technique, diseases caused by metal cutting fluid to the mechanist will be significantly reduced, therefore creating better lifestyles.

Hard turning is commonly carried out with advanced cutting tools such as ceramics, cubic boron nitride and polycrystalline cubic boron nitride to attain exceptional surface finish. However, the high cost of these tools necessitates exploration of alternative approaches. Therefore, this study investigates the potential of using cost-effective, multilayer-coated carbide tools under MQL conditions to achieve comparable surface quality.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0013/

In recent times, ternary hybrid nanofluid has garnered attention from scientist and researchers due to its improved thermal efficiency. This study aims to delve into the examination of ternary hybrid nanofluid (Al₂O₃–Cu–TiO₂/water), particularly concerning axisymmetric flow over a nonlinearly permeable stretching/shrinking disk. In addition, the investigation of convective boundary conditions and thermal radiation effects is also considered within the context of the described flow problem.

Mathematical formulations representing this problem are reduced into a set of ordinary differential equations (ODEs) using similarity transformation. The MATLAB boundary value problem solver is then used to solve the obtained set of ODEs. The impact of considered physical parameters such as suction parameter, radiation parameter, nonlinear parameter, nanoparticle volumetric concentration and Biot number on the flow profiles as well as the physical quantities is illustrated in graphical form.

The findings revealed the thermal flux for the nonlinearly shrinking disk is approximately 1.33%, significantly higher when compared to the linearly shrinking disk. Moreover, the existence of dual solutions attributed to the nonlinear stretching/shrinking disk is unveiled, with the first solution being identified as the stable and reliable solution through temporal stability analysis.

Understanding ternary hybrid nanofluid behavior and flow has applications in engineering, energy systems and materials research. This study may help develop and optimize nanofluid systems like heat exchangers and cooling systems.

The study of flow dynamics across nonlinear stretching/shrinking disk gains less attention compared to linear stretching/shrinking geometries. Many natural and industrial processes involve nonlinear changes in boundary shapes or sizes. Understanding flow dynamics over nonlinear shrinking/stretching disks is therefore essential for applications in various fields such as materials processing, biomedical engineering and environmental sciences. Hence, this study highlights the axisymmetric flow over a nonlinear stretching/shrinking disk using ternary hybrid nanofluid composed of alumina (Al₂O₃), copper (Cu) and titania (TiO₂). Besides, this study tackles a complex problem involving multiple factors such as suction, radiation and convective boundary conditions. Analyzing such complex systems can provide valuable insights into real-world phenomena where multiple factors interact.

Plant cultivation holds a pivotal role in agriculture, necessitating precise disease identification for the overall health of plants. This research conducts a comprehensive comparative analysis between two prominent deep learning algorithms, convolutional neural network (CNN) and DenseNet121, with the goal of enhancing disease identification in tomato plant leaves.

The dataset employed in this investigation is a fusion of primary data and publicly available data, covering 13 distinct disease labels and a total of 18,815 images for model training. The data pre-processing workflow prioritized activities such as normalizing pixel dimensions, implementing data augmentation and achieving dataset balance, which were subsequently followed by the modeling and testing phases.

Experimental findings elucidated the superior performance of the DenseNet121 model over the CNN model in disease classification on tomato leaves. The DenseNet121 model attained a training accuracy of 98.27%, a validation accuracy of 87.47% and average recall, precision and F1-score metrics of 87, 88 and 87%, respectively. The ultimate aim was to implement the optimal classifier for a mobile application, namely Tanamin.id, and, therefore, DenseNet121 was the preferred choice.

The integration of private and public data significantly contributes to determining the optimal method. The CNN method achieves a training accuracy of 90.41% and a validation accuracy of 83.33%, whereas the DenseNet121 method excels with a training accuracy of 98.27% and a validation accuracy of 87.47%. The DenseNet121 architecture, comprising 121 layers, a global average pooling (GAP) layer and a dropout layer, showcases its effectiveness. Leveraging categorical_crossentropy as the loss function and utilizing the stochastic gradien descent (SGD) Optimizer with a learning rate of 0.001 guides the course of the training process. The experimental results unequivocally demonstrate the superior performance of DenseNet121 over CNN.

By following the “employee-centric” approach, this study aims at identifying the impact of high-performance work systems (HPWS) on specific employee attitudinal outcomes such as work engagement, job satisfaction and affective commitment in the Indian healthcare industry.

The target population for this study includes the nurses working in large private multi-specialty tertiary care hospitals in India. Partial Least Squares Structural Equation Modelling (PLS-SEM) techniques are used on a sample of 152 nurses working in two large specialty hospitals.

In the Indian healthcare industry context, the nurse's perception of HPWS has shown a significant positive effect on their attitudinal variables such as work engagement, job satisfaction and affective commitment. When checked for mediation of work engagement and job satisfaction variables in HPWS – affective commitment relationship, nurse's job satisfaction partially mediated the relationship, but nurse's work engagement has shown no mediation effect.

This is one of the pioneering studies conducted in the Indian healthcare industry context, especially on the nurse's sample in identifying the impact of high-performance work systems on their attitudinal outcomes. Underscoring the paucity of HPWS research in the Indian healthcare industry, this study's findings will be an addition to the HPWS literature and also to the nursing research in the Indian healthcare settings.

In the process of providing quality healthcare services, identifying the important healthcare attributes and their operational performance is crucial in the healthcare industry. Highlighting this, the authors have aimed to find the importance of certain healthcare attributes and their respective performance from the customers’ perspective in the Indian private tertiary healthcare facilities by conducting an importance-performance analysis (IPA).

For this study, the authors have derived 10 healthcare attributes from the literature and responses regarding their importance and performance were taken from 350 inpatients from 6 hospitals.

The analysis resulted in identification of the most and least important, high and low performing healthcare attributes as perceived by the patients. In terms of attribute importance, the doctors’ competencies and provision of safe and effective patient care have been ranked most important, whereas the doctors’ competencies and accessibility have been rated high in terms of performance. In addition, the importance ranks and performance scores helped in the development of a two-dimensional IPA grid.

The IPA grid helped in identifying the areas for improvement, hence determining the need for implementation of significant strategies in the process of cost-effective high-quality healthcare service provision.

There is a paucity of IPA studies with a focus on the Indian healthcare system in identifying and demonstrating the healthcare components that need to be addressed for improvement. Emphasizing the gap, this is one of the pioneering studies that captured various healthcare attributes’ importance and their respective performance from the lens of hospital inpatients, which helped in the development of an IPA grid by clearly outlining the areas that need attention, especially in the post-pandemic scenario.

Borrowing from the dynamic capabilities theory and augmented by the relational view, the study investigates the criticality of supply chain agility in delivering operational performance while understanding the determinant role of key cross-firm resources. Additionally, based on the contingency theory, the interactive influence of two critical context factors, supply uncertainty and product complexity, is examined to enrich the understanding of the contingent nature of the operational performance implications.

The study draws its conclusions from the survey data collected from a 152-respondent sample of executives from US manufacturing firms. The empirical data analyses using partial least square structural equation modeling (PLS-SEM) relate agility to operational performance enhancements while incorporating the moderating effects of contextual factors.

The study relates agility capability to operational performance enhancements, while resource specificity and resource complementarity emerge as significant determinants of the capability. Results on the contingent impact of contextual factors suggest differential influences of supply uncertainty and product complexity on the agility–performance relationship: while the former enhances, the latter detracts from the relationship.

The study’s contributions suggest theory extensions into supply chains as contexts, reinforcing the importance of market-responsive capabilities and the foundational nature of supply chains as repositories of vital cross-firm resources. The contingent nature of the agility–performance relationship accents the importance of market context factors.

After completion of the case study, the students will be able to explore the challenges involved in growing a business during its early stages inorganically, discuss the challenges faced by start-ups in their quest for growth in an emerging market, investigate the reasons behind the mergers and acquisitions, comprehend the issues in the merger of a start-up and a conventional bank, identify the various possible synergies out of the merger and examine the growth strategies that a troubled start-up such as Slice can follow to survive and expand its business operations.

The case study discusses the challenges that Slice, a modern fintech organization, and North East Small Finance Bank (NESFB) face due to the changing business and regulatory environment. After working tirelessly to earn the trust of India’s banking regulator, Slice got the approval for its merger with NESFB. While Slice and NESFB got a new lease of life after the approval of their merger, Rajan Bajaj, founder of Slice, needed to make the merger a success by leveraging on the strength of the combined entity and meeting all the lending and other regulatory requirements applicable to small finance banks.

This case study is suitable for MBA/MS/BBA/BS students.

Teaching notes are available for educators only.

CSS 11: Strategy.