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Article
Publication date: 2 October 2019

Arpita Khare, Gaurav Awasthi and Rishi P. Shukla

Increased competition among different retail formats has led mall managers to focus on mall promotional activities to attract shoppers to malls. The purpose of this paper is to…

745

Abstract

Purpose

Increased competition among different retail formats has led mall managers to focus on mall promotional activities to attract shoppers to malls. The purpose of this paper is to understand Indian mall retailers views on mall events and its role in improving traffic, sales and mall image.

Design/methodology/approach

The current study used a qualitative to decipher mall retailers’ views regarding mall events. In total, 36 in-depth interviews of mall retailers across 13 metropolitan and non-metropolitan cities (Tier-I and Tier-II) were conducted to develop a comprehensive understanding of mall events organized by Indian mall managers.

Findings

The findings revealed that mall events were categorized under six different types: product launch events, events organized to promote the social cause, commemorate festivals, celebrity nights, events organized by retailers in malls and theme events. There were differences in the nature of events used by malls in bigger and smaller cities across India. The nature of mall events varied according to regional, cultural and lifestyle factors across the country.

Research limitations/implications

Mall managers can use the insights from the study on mall events for segmenting and targeting strategies. The different types of mall events can be used for improving footfall, sales and mall image. The study findings employ a grounded theory approach to understand mall retailers’ views on mall events. Future research can be directed toward understanding mall managers’ and consumers’ opinions about the relevance of mall events in improving footfall and profitability of malls.

Originality/value

Extant research has looked at mall events, their role and efficacy in a consolidated manner. The current study attempts to segregate the events organized by mall management into distinct categories and provide linkages of these categories concerning mall image and traffic.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 32 no. 2
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 1 March 2021

Gaurav Prashar and Hitesh Vasudev

In the present study, Al2O3 coatings were deposited on stainless steel AISI-304 material by using atmospheric plasma spraying technique to combat high temperature solid particle…

213

Abstract

Purpose

In the present study, Al2O3 coatings were deposited on stainless steel AISI-304 material by using atmospheric plasma spraying technique to combat high temperature solid particle erosion. The present aims at the performance analysis of Al2O3 coatings at high temperature conditions.

Design/methodology/approach

The erosion studies were carried out at a temperature of 400°C by using a hot air-jet erosion tester for 30° and 90° impingement angles. The possible erosion mechanisms were analyzed from scanning electron microscope (SEM) micrographs. Surface characterization of the powder and coatings were conducted by using an X-ray diffractometer, SEM, equipped with an energy dispersive X-ray analyzer. The porosity, surface roughness and micro-hardness of the as-sprayed coating were measured. This paper discusses outcomes of the commonly used thermal spray technology, namely, the plasma spray method to provide protection against erosion.

Findings

The plasma spraying method was used to successfully deposit Al2O3 coating onto the AISI 304 substrate material. Detailed microstructural and mechanical investigations were carried out to understand the structure-property correlations. Major findings were summarized as under: the erosive wear test results indicate that the plasma sprayed coating could protect the substrate at both 30° and 90° impact angles. The coating shows better resistance at an impact angle of 30° compared with 90°, which is related to the pinning and shielding effect of the alumina particle. The major erosion wear mechanisms of Al2O3 coating were micro-cutting, micro-ploughing, splat removal and detachment of Al2O3 hard particles.

Originality/value

In the current study, the authors have followed the standard testing method of hot air jet erosion test as per American society for testing of materials G76-02 standard and reported the erosion behavior of the eroded samples. The coating was not removed at all even after the erosion test duration i.e. 10 min. The erosion test was continued till 3 h to understand the evolution of coatings and the same has been explained in the erosion mechanism. The outcome of the present study may be used to minimize the high temperature erosion of AISI-304 substrate.

Details

World Journal of Engineering, vol. 18 no. 5
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 7 June 2021

Prabhdeep Singh and Rajbir Kaur

The purpose of this paper is to provide more accurate structure that allows the estimation of coronavirus (COVID-19) at a very early stage with ultra-low latency. The machine…

200

Abstract

Purpose

The purpose of this paper is to provide more accurate structure that allows the estimation of coronavirus (COVID-19) at a very early stage with ultra-low latency. The machine learning algorithms are used to evaluate the past medical details of the patients and forecast COVID-19 positive cases, which can aid in lowering costs and distinctively enhance the standard of treatment at hospitals.

Design/methodology/approach

In this paper, artificial intelligence (AI) and cloud/fog computing are integrated to strengthen COVID-19 patient prediction. A delay-sensitive efficient framework for the prediction of COVID-19 at an early stage is proposed. A novel similarity measure-based random forest classifier is proposed to increase the efficiency of the framework.

Findings

The performance of the framework is checked with various quality of service parameters such as delay, network usage, RAM usages and energy consumption, whereas classification accuracy, recall, precision, kappa static and root mean square error is used for the proposed classifier. Results show the effectiveness of the proposed framework.

Originality/value

AI and cloud/fog computing are integrated to strengthen COVID-19 patient prediction. A novel similarity measure-based random forest classifier with more than 80% accuracy is proposed to increase the efficiency of the framework.

Details

World Journal of Engineering, vol. 19 no. 1
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 1 August 2014

Nirmala Ratchagar and R. Kumar

The effect of magnetic field on unsteady convective diffusion in a couple stress fluid (blood) is studied using a time dependent dispersion model. This model is used to calculate…

44

Abstract

The effect of magnetic field on unsteady convective diffusion in a couple stress fluid (blood) is studied using a time dependent dispersion model. This model is used to calculate the mean concentration distribution of a solute, bounded by the porous layer and is expressed as a function of dimensionless axial distance and time. The magnetic field, arising as a body couple in the governing equations is shown to increase the axis dispersion coefficient. This is useful to the control of haemolysis caused by artificial organs implanted or extracorporeal. Dispersion coefficient and mean concentration are computed for different values of Hartmann number (M), Couple Stress Parameter (a) and Porous Parameter (σ).

Details

World Journal of Engineering, vol. 11 no. 4
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 1 July 2021

Rumi Iqbal Doewes, Rajit Nair and Tripti Sharma

This purpose of this study is to perfrom the analysis of COVID-19 with the help of blood samples. The blood samples used in the study consist of more than 100 features. So to…

176

Abstract

Purpose

This purpose of this study is to perfrom the analysis of COVID-19 with the help of blood samples. The blood samples used in the study consist of more than 100 features. So to process high dimensional data, feature reduction has been performed by using the genetic algorithm.

Design/methodology/approach

In this study, the authors will implement the genetic algorithm for the prediction of COVID-19 from the blood test sample. The sample contains records of around 5,644 patients with 111 attributes. The genetic algorithm such as relief with ant colony optimization algorithm will be used for dimensionality reduction approach.

Findings

The implementation of this study is done through python programming language and the performance evaluation of the model is done through various parameters such as accuracy, sensitivity, specificity and area under curve (AUC).

Originality/value

The implemented model has achieved an accuracy of 98.7%, sensitivity of 96.76%, specificity of 98.80% and AUC of 92%. The results have shown that the implemented algorithm has performed better than other states of the art algorithms.

Details

World Journal of Engineering, vol. 19 no. 2
Type: Research Article
ISSN: 1708-5284

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