Samhita Mangu, Thillai Rajan Annamalai and Akash Deep
The use of public–private partnership (PPP) approaches for developing infrastructure has been well recognized. The allocation of risk between public authority and private sector…
Abstract
Purpose
The use of public–private partnership (PPP) approaches for developing infrastructure has been well recognized. The allocation of risk between public authority and private sector differs among the different types of PPP projects. The objective of the paper is to analyze the factors that influence the type of PPP and the performance of different types of PPP contracts.
Design/methodology/approach
A unique data set of 202 national highway PPP projects from India, comprising 154 toll and 48 annuity projects formed the basis of the study.
Findings
There are significant differences between toll and annuity PPP projects. The former are longer, are implemented in better developed states but are also characterized by higher cost over-runs. The latter are characterized by higher debt–equity ratio.
Practical implications
Mitigating revenue risk can significantly enhance the debt capacity of the projects, thereby reducing the overall cost of capital. To make toll roads attractive for bidders, they have to be developed as longer stretches. Toll projects that are immediately ready for development at the time of award would reduce cost overruns of toll projects and sustain the interest of private developers.
Originality/value
Comparison of toll and annuity PPP road projects has never been done previously. The unique data set used in this study highlights the differences in characterization and performance for both the project types. The study provides evidence support to “intuition” and enables policymakers to choose the right form of PPP to realize their objectives.
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Robert Owsiński, Kevin Moj, Cyprian Lachowicz, Mariusz Prażmowski, Akash Nag, Munish Kumar Gupta and Radim Halama
Computer tomography (CT) is widely used in engineering applications, allowing for precise structural analysis of materials and components, enabling the measurement of internal…
Abstract
Purpose
Computer tomography (CT) is widely used in engineering applications, allowing for precise structural analysis of materials and components, enabling the measurement of internal properties and features, which is crucial for assessing their quality and durability. Therefore, the purpose of this study is to analyze the fatigue fracture surface features of titanium alloy (Ti-6Al-4V) under different loading configurations and structure orientations using computational micro-tomography.
Design/methodology/approach
In this work, the specimens were fabricated by selective laser melting (SLM) and subjected to fatigue tests to analyze the effects of different printing parameters on mechanical properties and microstructural features. The comprehensive methodology included metallographic testing, fatigue life testing, fractographic analysis and CT analysis, followed by microhardness measurements, providing a detailed assessment of internal defects and their impact on fatigue performance.
Findings
The fatigue test results showed better fatigue life for samples printed with Y orientation followed by X and Z orientation. The measurement values were fitted to obtain mean variable values of A as 6.522, 10.831 and 6.747 and values of m as −0.587, −2.318 and −0.771 for samples printed with X, Y and Z orientation for the Basquin’s equation to determine fatigue life. CT analysis revealed that the mean equivalent defect diameters were 0.0506, 0.0496 and 0.0513 mm and mean defect volume of 0.000714, 0.000467 and 0.000534 mm3 for X, Y and Z orientation samples, respectively.
Originality/value
The novel aspect of this study is to investigate the effect of extreme SLM process parameters on the durability of the material subjected to complex multiaxial loading conditions, including nonproportional fatigue loading.
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Satyajit Ghosh, Karan Kochhar, Akash Sharma, Shreyaan Kaushal, Jatin Agrawal, Anshul Garg, Arnav Kumar and Yash Dugar
The Government of India is proposing the setting up of several new smart cities in the sub-continent. Being an over-populated country, space is at a premium. In congested areas…
Abstract
Purpose
The Government of India is proposing the setting up of several new smart cities in the sub-continent. Being an over-populated country, space is at a premium. In congested areas high-rise buildings afford a solution. The purpose of this paper is to present new research involving architecture and computational fluid dynamics (CFDs) must be done at the screening stage of design plans before new cities are laid out. This is achieved in the present study involving a university residential campus with a population of 29,000 comprising of an assortment of high-rise buildings in complex terrain.
Design/methodology/approach
This paper uses a combination of instrument-fitted drone measurements – (equipped with a barometer, and sensors for obtaining temperature, relative humidity and altitude) along with a computational fluid dynamical analysis to yield deep insights into the ventilation patterns around an assortment of building forms.
Findings
This study was conducted in a residential complex in the campus of the Vellore Institute of Technology (VIT) India. Based on the deciphered wind velocity pattern, a human thermal comfort study was also conducted. It was concluded that the orientation of the buildings play a pivotal role in enhancing the ventilation rates inside a building. It was observed that a dominant eddy spanning a radius of approximate 34 meters was responsible for much of the air changes within the rooms – the smaller eddies had an insignificant role. This method of ascertaining eddy structures within a study area comprising of an assortment of buildings is essential for accurate prescriptions of glazing ratios on building facades.
Research limitations/implications
The main research implications pertain to the use of smart ventilation methods in built up environments. The study shows how large eddies drive the momentum transfer and the air changes per hour with rooms in high-rise buildings in complex terrain. In monsoon-driven flows, there are well set preferred directions of wind flow and this enables the characterization of the fully eddy structure in the vicinity of tall buildings. Another research implication would be the development of new turbulence closure models for eddy structure resolution for flow around complex building forms.
Practical implications
This study introduces a novel protocol at the planning stage of the upcoming residential complexes in proposed smart cities in the sub-continent. The results may well inform architects and structural engineers and help position and orient buildings in confined spaces and also ascertain the optimal glazing ratio, which affects the ventilation pattern.
Social implications
The results from this study can be used by town planners and architects in urban conurbations in the developing world. The results may well help lower heating ventilation and airconditioning loads. Energy-efficient buildings in developing countries are necessary because most of these have rapidly growing GDPs with a concomitant increase in energy consumption.
Originality/value
This novel study combining instrument mounted drone and CFDs shows for the first time how architects and town planners with a limited budget position and orient a group of buildings in a complex terrain.
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Shailendra Kumar and Akash Chaurasia
The study attempts to investigate the relationship between emotional biases (loss aversion bias, overconfidence bias, and regret aversion bias) and investment decisions through a…
Abstract
Purpose
The study attempts to investigate the relationship between emotional biases (loss aversion bias, overconfidence bias, and regret aversion bias) and investment decisions through a meta-analysis approach.
Design/methodology/approach
A meta-correlation analysis was done using sample size and correlation (r) data from several relevant studies that look at how emotional biases (loss aversion bias, regret aversion bias, and overconfidence bias) affect investment decisions. Additionally, beta coefficients (ß) were also converted to correlation coefficients (r) from six studies.
Findings
This study analysed 31 empirical studies and found a significant positive correlation between emotional biases and investment decisions [loss aversion bias (r = 0.492), regret aversion bias (r = 0.401), and overconfidence bias (r = 0.346)]. We set the statistical significance threshold at 0.05.
Research limitations/implications
The review covered 31 online research publications that showed significant heterogeneity, possibly influenced by various methodological, population, or other factors. Furthermore, the use of correlational data restricts the ability to establish causation.
Originality/value
This is a novel attempt to integrate the results of various studies through meta-analysis on the relation between these emotional biases (loss aversion, overconfidence, and regret aversion) and investment decisions.
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Anamika Saharan, Akash Saharan, Krishan Kumar Pandey and T. Joji Rao
The low level of financial literacy among young adults is a pressing concern at both individual and country levels. Therefore, there is a dire need to understand the best-worst…
Abstract
Purpose
The low level of financial literacy among young adults is a pressing concern at both individual and country levels. Therefore, there is a dire need to understand the best-worst antecedents of financial literacy and how they influence each other.
Design/methodology/approach
A two-phased multicriteria decision-making (MCDM) technique consisting of best-worst method and interpretive structural modeling (BWM-ISM) was employed for pair-wise comparison, assigning weights, ranking and establishing the relationship among antecedents of financial literacy.
Findings
Results suggest that use of Internet (SF1), role of financial advisors (SF3) and education level of individuals (DS7) are top ranked antecedents, whereas masculinity/feminity, language and power distance in society are the least ranked antecedents of financial literacy. Findings will help both academicians and practitioners focus on the key factors and make efforts to increase financial literacy by minimizing resource usage.
Originality/value
The current study provides clarity among antecedents of financial literacy by following BWM-ISM approach for the first time in the financial literacy context.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0746
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Rahul Priyadarshi, Akash Panigrahi, Srikanta Routroy and Girish Kant Garg
The purpose of this study is to select the appropriate forecasting model at the retail stage for selected vegetables on the basis of performance analysis.
Abstract
Purpose
The purpose of this study is to select the appropriate forecasting model at the retail stage for selected vegetables on the basis of performance analysis.
Design/methodology/approach
Various forecasting models such as the Box–Jenkins-based auto-regressive integrated moving average model and machine learning-based algorithms such as long short-term memory (LSTM) networks, support vector regression (SVR), random forest regression, gradient boosting regression (GBR) and extreme GBR (XGBoost/XGBR) were proposed and applied (i.e. modeling, training, testing and predicting) at the retail stage for selected vegetables to forecast demand. The performance analysis (i.e. forecasting error analysis) was carried out to select the appropriate forecasting model at the retail stage for selected vegetables.
Findings
From the obtained results for a case environment, it was observed that the machine learning algorithms, namely LSTM and SVR, produced the better results in comparison with other different demand forecasting models.
Research limitations/implications
The results obtained from the case environment cannot be generalized. However, it may be used for forecasting of different agriculture produces at the retail stage, capturing their demand environment.
Practical implications
The implementation of LSTM and SVR for the case situation at the retail stage will reduce the forecast error, daily retail inventory and fresh produce wastage and will increase the daily revenue.
Originality/value
The demand forecasting model selection for agriculture produce at the retail stage on the basis of performance analysis is a unique study where both traditional and non-traditional models were analyzed and compared.
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Akash K. Gupta, Rahul Yadav, Malay K. Das and Pradipta K. Panigrahi
This paper aims to present the implementation of a multi-layer radiation propagation model in simulations of multi-phase flow and heat transfer, for a dissociating methane hydrate…
Abstract
Purpose
This paper aims to present the implementation of a multi-layer radiation propagation model in simulations of multi-phase flow and heat transfer, for a dissociating methane hydrate reservoir subjected to microwave heating.
Design/methodology/approach
To model the induced heterogeneity due to dissociation of hydrates in the reservoir, a multiple homogeneous layer approach, used in food processes modelling, is suggested. The multi-layer model is incorporated in an in-house, multi-phase, multi-component hydrate dissociation simulator based on the finite volume method. The modified simulator is validated with standard experimental results in the literature and subsequently applied to a hydrate reservoir to study the effect of water content and sand dielectric nature on radiation propagation and hydrate dissociation.
Findings
The comparison of the multi-layer model with experimental results show a maximum difference in temperature estimation to be less than 2.5 K. For reservoir scale simulations, three homogeneous layers are observed to be sufficient to model the induced heterogeneity. There is a significant contribution of dielectric properties of sediments and water content of the reservoir in microwave radiation attenuation and overall hydrate dissociation. A high saturation reservoir may not always provide high gas recovery by dissociation of hydrates in the case of microwave heating.
Originality/value
The multi-layer approach to model microwave radiation propagation is introduced and tested for the first time in dissociating hydrate reservoirs. The multi-layer model provides better control over reservoir heterogeneity and interface conditions compared to existing homogeneous models.
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R. Dhanalakshmi, Dwaraka Mai Cherukuri, Akash Ambashankar, Arunkumar Sivaraman and Kiran Sood
Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart…
Abstract
Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.
Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.
Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.
Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.
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The purpose of this paper is to contextualise the architect–client relationship and evaluate the factors responsible for its deterioration, and then define the impact of these…
Abstract
Purpose
The purpose of this paper is to contextualise the architect–client relationship and evaluate the factors responsible for its deterioration, and then define the impact of these factors on the future needs of architects and clients, including how such knowledge can help emerging architects to develop an understanding of the profession at an early stage. It will attempt to reveal new insights and build consensus around issues, such as functionality and aesthetics, per cent-based fee structure, conflict of interest amongst architects, contractors and clients.
Design/methodology/approach
A combination of qualitative online survey, semi-structured interviews and online focus group discussions under the comprehensive umbrella of the case study method has been used to construct a pragmatic framework. The data collection was focused on revealed preferences rather than stated preferences, in terms of likes and dislikes, in a standard survey.
Findings
Overall, this paper strengthens the idea that the predicament of the profession and the marginalisation of architects is due to their detachment from clients. The findings suggest that the fee structure might be a major source of discontent and there is an urgent need for alternative routes of procurement, particularly for private residential clients. While most clients prefer functionality over aesthetics and want architects to be affordable, they are more willing to invest their trust in architects who can deliver from concept to completion.
Research limitations/implications
The arguments contested in this paper attempt to demystify the dynamics that are at play during the construction stage. It looks at power sharing, responsibilities and silent hierarchies that transpire between architects, clients and contractors, particularly in private residential projects.
Originality/value
The main recommendation of this paper is that to secure the future of the architecture profession emerging architects need to be trained more in client-centric skills than design-centric aptitude.