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1 – 10 of 12Shumank Deep, Sushant Vishnoi, Radhika Malhotra, Smriti Mathur, Hrishikesh Yawale, Amit Kumar and Anju Singla
Augmented Reality (AR) and Virtual Reality (VR) technologies possess the potential to transform the scenario of making real estate investment decisions through the immersive…
Abstract
Purpose
Augmented Reality (AR) and Virtual Reality (VR) technologies possess the potential to transform the scenario of making real estate investment decisions through the immersive experience they offer. From the literature it was observed that the research in this domain is still emergent and there is a need to identify the latent variables that influence real estate investment decisions. Therefore, by examining the effects of these technologies on investment decision-making, the purpose of the study is to provide valuable insights into how AR and VR could be applied to enhance customers' property buying experiences and assist in their decision-making process.
Design/methodology/approach
From an extensive review of the literature four latent variables and their measure were identified, and based on these a survey instrument was developed. The survey was distributed online and received 300 responses from the respondents including home buyers, developers, AEC professionals and real estate agents. To validate the latent variables exploratory factor analysis was used whereas to establish their criticality second-order confirmatory factor analysis was used.
Findings
From the results, the four latent constructs were identified based on standard factor loadings (SFL) that is Confident Value Perception (CVP, SFL = 0.70), Innovative Investment Appeal (IIA, SFL = 0.60), Trusted Property Transactions (TPT, SFL = 0.58) and Effortless Property Engagement (EPE, SFL = 0.54), that significantly influence investor decision-making and property purchase experience.
Originality/value
This study contributes to the literature on real estate investment decisions by providing empirical evidence on the role of AR and VR technologies. The identified key variables provided practical guidelines for developers, investors and policymakers in understanding and leveraging the potential of AR and VR technologies in the real estate industry.
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Pragati Agarwal, Sanjeev Swami and Sunita Kumari Malhotra
The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as…
Abstract
Purpose
The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.
Design/methodology/approach
The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.
Findings
The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.
Research limitations/implications
Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.
Practical implications
First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.
Originality/value
As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.
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Hatice Camgöz‐Akdağ and Mosad Zineldin
The aim of this research is to examine the major factors affecting patients' perception of cumulative satisfaction and to address the question whether patients in Istanbul…
Abstract
Purpose
The aim of this research is to examine the major factors affecting patients' perception of cumulative satisfaction and to address the question whether patients in Istanbul evaluate quality of health care to be similar or different to that of the Kazakhstani, Egyptian and Jordanian patients.
Design/methodology/approach
A conceptual model including behavioural dimensions of patient‐physician relationships and patient satisfaction has been used for approach. As the empirical research setting, this study concerns people who are or were patients once in Istanbul hospitals.
Findings
The questionnaire was taken from another research regarding Egyptian and Jordanian medical clinics. The same research was also done by the authors in Kazakhstan in 2008. A total of 48 items (attributes) of the newly developed five quality dimensions (5Qs) by the second author were identified to be the most relevant.
Practical implications
The results of this study can be used by the hospitals to reengineer and redesign creatively their quality management processes and the future direction of their more effective health care quality strategies.
Originality/value
A 5Qs model to measure the patients' satisfaction of medical care is proposed as for previous studies for Kazakhstanian, Egyptian and Jordanian hospitals. As mentioned previously the 5Qs model encompasses technical, functional, interaction, infrastructure and the atmosphere qualities and services. The results can be used by the hospitals to reengineer and redesign creatively their quality management processes and the future direction of their more effective health care quality strategies.
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Mosad Zineldin, Hatice Camgöz‐Akdağ and Valiantsina Vasicheva
This paper aims to examine the major factors affecting cumulative summation, to empirically examine the major factors affecting satisfaction and to address the question whether…
Abstract
Purpose
This paper aims to examine the major factors affecting cumulative summation, to empirically examine the major factors affecting satisfaction and to address the question whether patients in Kazakhstan evaluate healthcare similarly or differently from patients in Egypt and Jordan.
Design/methodology/approach
A questionnaire, adapted from previous research, was distributed to Kazakhstan inpatients. The questionnaire contained 39 attributes about five newly‐developed quality dimensions (5Qs), which were identified to be the most relevant attributes for hospitals. The questionnaire was translated into Russian to increase the response rate and improve data quality. Almost 200 usable questionnaires were returned. Frequency distribution, factor analysis and reliability checks were used to analyze the data.
Findings
The three biggest concerns for Kazakhstan patients are: infrastructure; atmosphere; and interaction. Hospital staff's concern for patients' needs, parking facilities for visitors, waiting time and food temperature were all common specific attributes, which were perceived as concerns. These were shortcomings in all three countries. Improving health service quality by applying total relationship management and the 5Qs model together with a customer‐orientation strategy is recommended.
Practical implications
Results can be used by hospital staff to reengineer and redesign creatively their quality management processes and help move towards more effective healthcare quality strategies.
Social implications
Patients in three countries have similar concerns and quality perceptions.
Originality/value
The paper describes a new instrument and method. The study assures relevance, validity and reliability, while being explicitly change‐oriented. The authors argue that patient satisfaction is a cumulative construct, summing satisfaction as five different qualities (5Qs): object; processes; infrastructure; interaction and atmosphere.
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Purpose of This Chapter: This study explores the positive chain effects of Employee-Centered CSR (ECCSR) in harmonizing the current challenges of The Great Resignation from the…
Abstract
Purpose of This Chapter: This study explores the positive chain effects of Employee-Centered CSR (ECCSR) in harmonizing the current challenges of The Great Resignation from the perspective of employees’ well-being.
Design / Methodology / Approach: The quantitative approach was used to test the proposed research model by using a self-responded questionnaire. Purposive judgemental sampling was applied to qualify the respondents based on the criteria that they are gainfully employed now and during the pandemic. The responses gathered were analyzed using structural equation modelling (SEM).
Findings: The findings show that ECCSR significantly and positively influences employees’ well-being, specifically workplace well-being (β = 0.793), social well-being (β = 0.761), psychological well-being (β = 0.712), and subjective well-being (β = 0.611). The PLSpredict results reveal that the proposed research model possesses the predictive relevance of ECCSR in reflecting the reality of employees’ well-being.
Research Limitations: The data were collected in the post-pandemic phase to capture the employees’ state of mind. Hence, the findings may not represent the normal business cycle challenges.
Practical Implications: The empirical evidence suggests that depressing organizations to consider implementing ECCSR for employees’ well-being which in turn enables the organizations to navigate through turbulent times a little easier.
Originality: The novelty of this study is attributed to the positive and detailed findings of ECCSR in the context of employee well-being for organizational resilience.
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Dinesh Kumar, Surjit Angra and Satnam Singh
This research outlines the development and characterization of advanced composite materials and their potential applications in the aerospace industry for interior applications…
Abstract
Purpose
This research outlines the development and characterization of advanced composite materials and their potential applications in the aerospace industry for interior applications. Advanced composites, such as carbon-fiber-reinforced polymers and ceramic matrix composites, offer significant advantages over traditional metallic materials in terms of weight reduction, stiffness and strength. These materials have been used in various aerospace applications, including aircraft, engines and thermal protection systems.
Design/methodology/approach
The development of design of experiment–based hybrid aluminum composites using the stir-casting technique has further enhanced the performance and cost-effectiveness of these materials. The design of the experiment was followed to fabricate hybrid composites with nano cerium oxide (nCeO2) and graphene nanoplatelets (GNPs) as reinforcements in the Al-6061 matrix.
Findings
The Al6061 + 3% nCeO2 + 3% GNPs exhibited a high hardness of 119.6 VHN. The ultimate tensile strength and yield strength are 113.666 MPa and 73.08 MPa, respectively. A uniform distribution of reinforcement particulates was achieved with 3 Wt.% of each reinforcement in the matrix material, which is analyzed using scanning electron microscopy. Fractography revealed that brittle and ductile fractures caused the failure of the fractured specimens in the tensile test.
Practical implications
The manufactured aluminum composite can be applied in a range of exterior and interior structural parts like wings, wing boxes, motors, gears, engines, antennas, floor beams, etc. The fan case material of the GEnx engine (currently using carbon-fiber reinforcement plastic) for the Boeing 7E7 can be another replacement with manufactured hybrid aluminum composite, which predicts weight savings per engine of close to 120 kg.
Originality/value
The development of hybrid reinforcements, where two or more types of reinforcements are used in combination, is also a novel approach to improving the properties of these composites. Advanced composite materials are known for their high strength-to-weight ratio. If the newly developed composite material demonstrates superior properties, it can potentially be used to replace traditional materials in aircraft manufacturing. By reducing the weight of aircraft structures, fuel efficiency can be improved, leading to reduced operating costs and environmental impact. This allows for a more customized solution for specific application requirements and can lead to further advancements in materials science and technology.
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Hingmire Vishal Sharad, Santosh R. Desai and Kanse Yuvraj Krishnrao
In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The…
Abstract
Purpose
In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.
Design/methodology/approach
In this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.
Findings
The performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.
Originality/value
This paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.
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Ravi Butola, N. Yuvaraj, Ravi Pratap Singh, Lakshay Tyagi and Faim Khan
This study aims to analyse the changes in mechanical and wear performance of aluminium alloy when yttrium oxide particles are incorporated. The microstructures are studied to…
Abstract
Purpose
This study aims to analyse the changes in mechanical and wear performance of aluminium alloy when yttrium oxide particles are incorporated. The microstructures are studied to analyse the change in the grain structures. Worn surfaces are observed via scanning electron microscope to study the wear mechanism in detail.
Design/methodology/approach
Stir casting is used to incorporate varying composition of yttrium particles, having an average particle size of 25 micrometer, in aluminium alloy 6063 matrix. Wear testing is carried out by DUCOM manufactured high temperature rotatory tribometer, and an indentation test is used for analysing the microhardness of the fabricated samples.
Findings
Microhardness of the material is increased with the increasing content of particulate addition. With the increasing content of reinforcement, more refined grains are produced. The load is transferred from the matrix to more rigid yttrium oxide particles. These factors contributed to escalated microhardness of the reinforced samples. Particulate addition enhanced the wear performance of the material; this might be attributed to increased microhardness and formation of an oxide layer.
Originality/value
Aluminium composites are finding wide applications in various industries, and there is always a requirement of material with enhanced tribological properties. Yttrium oxide particles exhibit improved mechanical properties, and their interaction with the aluminium matrix has not been studied much in the past. So, in this work, yttrium oxide incorporated aluminium matrix is studied.
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This case is meant for MBA/MS/executive MBA students.
Abstract
Study level/applicability
This case is meant for MBA/MS/executive MBA students.
Subject area
Entrepreneurship development, leadership.
Case overview
This case is about the successful entrepreneurial journey of Kiran Mazumdar-Shaw, founder of India-based biotechnology company Biocon Limited. Mazumdar-Shaw established Biocon in 1978 as a joint venture company. As a woman entrepreneur, Mazumdar-Shaw faced many challenges and setbacks during her initial days. She overcame these and took Biocon to new heights. Later, Mazumdar-Shaw decided to make a strategic shift in Biocon’s business model – going from manufacturing enzymes to biopharmaceuticals with the vision of making an impact on global health care by providing access to affordable, life-saving drugs.
Expected learning outcomes
The learning outcomes are as follows: understand the ecosystem of women entrepreneurs in developing countries; examine the challenges faced by women entrepreneurs in their entrepreneurial journey and how successful entrepreneurs convert challenges into opportunities; and analyze what entrepreneurial leadership is and understand how these leadership qualities play an important role in the success of entrepreneurial ventures.
Social implications
Mazumdar-Shaw was able to break through the gender barrier that was highly prevalent in Indian society then and successfully established her entrepreneurial venture in biotechnology, a discipline that was still nascent in the1970s. Though she has scaled great heights in the biotechnology area and developed her business, she has remained sensitive to the problems of those who are unable to get affordable medicines. Firmly believing that she should share the prosperity of the company with the poor and the marginalized, Mazumdar-Shaw, through her philanthropic venture, Biocon Foundation, started providing essential drugs at affordable prices to them.
Subject code
CCS 3: Entrepreneurship.
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