Arpita Agnihotri, Saurabh Bhattacharya and Satya Prasad V.K.
The purpose of this study is to examine the impact of multiple brand celebrity endorsement strategies on firms’ performance and different attributes associated with celebrities on…
Abstract
Purpose
The purpose of this study is to examine the impact of multiple brand celebrity endorsement strategies on firms’ performance and different attributes associated with celebrities on firms’ performance. In this regard, the present study specifically explores the role of celebrity reputation and experience, as well as social media as a promotion platform in influencing the economic effectiveness of multiple brand endorsement strategies, i.e. proportion of brands endorsed in a firms’ brand portfolio.
Design/methodology/approach
Study is based on instrumental variable regression analysis approach and is conducted in one of the emerging markets, i.e. India.
Findings
The findings indicate that firms’ market valuations increase as its proportion of brands endorsed by celebrities increases. Furthermore, popularity reputation of celebrity also influences market valuation, and relationship is positively moderated by celebrity’s experience.
Originality/value
Extant studies have considered one endorsement news of a firm at a time. However, how total proportion of firms’ brand endorsed by celebrities impacts its performance has not been investigated. Furthermore, impact of celebrity traits has been examined only in consumer behavior studies and has been rarely investigated in context of firms’ economic performance.
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Khader Zelani Shaik, P. Siddaiah and K. Satya Prasad
Planar periodic metallic arrays behave as artificial magnetic conductor (AMC) surfaces when placed on a grounded dielectric substrate, and they introduce a zero-degree reflection…
Abstract
Purpose
Planar periodic metallic arrays behave as artificial magnetic conductor (AMC) surfaces when placed on a grounded dielectric substrate, and they introduce a zero-degree reflection phase shift to incident waves. The antenna designers have new challenges while designing the AMC structure. The steps followed in designing the structure are as follows: 1) Designing the antenna, aimed to operate at millimetric wave frequencies, (2) Designing the AMC at desired frequencies, (3) Integrating the antenna design and AMC to resonate at millimetric wave frequencies and (4) Validate the output parameters of the antenna to be suitable for Internet of Things (IoT) applications.
Design/methodology/approach
The antenna is integrated with artificial material known as high impedance surface (HIS) for performance enhancement. A miniaturized, multiband, enhanced gain, AMC-integrated CPW-fed antenna is proposed and aimed to operate at millimetric wave frequencies, which is most suitable for IoT applications. The developed antenna operates at an extremely high range (30–300 GHz), i.e. from 40 to 60 GHz with the return loss values at lesser than −20 dB, and gain is greater than 10. The antenna is developed and simulated by using HFSS software.
Findings
An extensive research study has been carried out to develop a low profile, high gain and optimized antenna. The first two steps are separately designing the antenna and the AMC unit cell at the desired frequencies. The third step is finding the antenna or AMC radiating parts responsible for each resonant frequency by analysing the surface current distribution. CPW fed along with AMC integration has made the antenna feasible to achieve the extremely high frequency (EHF) range, i.e. 40–60 GHz, which is highly adoptable in IoT applications.
Originality/value
The result represented that the developed antenna is resonating at EHF rank with high gain and good imped matching when it is being compared with the previous models and has only CPW fed without having AMC structure integration. It is evident that the antenna which has only CPW fed has resonated at lower frequency than EHF range and justified output characteristics. But when it is embedded with the AMC structure, it resonates at the EHF range, which makes the antenna highly suitable for IoT applications, with more accuracy and high data rate possibility.
Khader Zelani Shaik, Siddaiah P. and K. Satya Prasad
Millimeter wave spectrum represents new opportunities to add capacity and faster speeds for next-generation services as fifth generation (5G) applications. In its Spectrum…
Abstract
Purpose
Millimeter wave spectrum represents new opportunities to add capacity and faster speeds for next-generation services as fifth generation (5G) applications. In its Spectrum Frontiers proceeding, the Federal Communications Commision decided to focus on spectrum bands where the most spectrums are potentially available. A low profile antenna array with new decoupling structure is proposed and expected to resonate at higher frequency bands, i.e. millimeter wave frequencies, which are suitable for 5G applications.
Design/methodology/approach
The presented antenna contains artificial magnetic conductor (AMC) surface as decoupling structure. The proposed antenna array with novel AMC surface is operating at 29.1GHz and proven to be decoupling structure and capable of enhancing the isolation by reducing mutual coupling as 8.7dB between the array elements. It is evident that, and overall gain is improved as 10.1% by incorporating 1x2 Array with AMC Method. Mutual coupling between the elements of 1 × 2 antenna array is decreased by 39.12%.
Findings
The proposed structure is designed and simulated using HFSS software and the results are obtained in terms of return loss, gain, voltage standing wave ratio (VSWR) and mutual coupling. The S-Parameters of each stage of design is tabulated and compared with each other to prove the decoupling capability of AMC surface in antenna arrays.
Originality/value
The proposed structure is designed and simulated using HFSS software, and the results are obtained in terms of return loss, gain, VSWR and mutual coupling. The S-Parameters of each stage of design is tabulated and compared with each other to prove the decoupling capability of AMC surface in antenna arrays.
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Krishna Mohan A., Reddy P.V.N. and Satya Prasad K.
In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best…
Abstract
Purpose
In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The purpose of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG and Harris are used for the process of feature extraction. The authors’ proposed method will give the best results when compared with other existing methods.
Design/methodology/approach
The visual tracking of many real-world applications such as robotics, smart monitoring systems, independent driving and human-computer interactions are a major and current research problem in the field of computer vision. This refers to the automated trajectory prediction of an arbitrary target object, often given in the first frame in a bounding box while moving about in successive video frames. In the community of visual tracking or object tracking, DCF has gained more importance. Discriminative trackers strive to train a classifier that differentiates the target item from the background. The fundamental concept is to train a correlation filter that creates high responses around the target and low responses elsewhere. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG and Harris are used for the process of feature extraction. Through experimental analysis, the authors have evaluated several performance assessment metrics such as accuracy, precision, F-measure and specificity. The authors’ proposed method will give the best results when compared with other existing methods.
Findings
This process involved DCF which gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique for tracking the objects and these results will be used for identifying the action of the object.
Originality/value
The main theme exists in the process is to identify the tracking motion of the object by using convolution regression with varied features. This method proves that it will provide better results when compared to state of art methods.
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Krishna Mohan A, Reddy PVN and Satya Prasad K
In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best…
Abstract
Purpose
In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG & Harris are used for the process of feature extraction. The proposed method will give the best results when compared to other existing methods.
Design/methodology/approach
This paper introduces the concept and research status of tracks; later the authors focus on the representative applications of deep learning in visual tracking.
Findings
Better tracking algorithms are not mentioned in the existing method.
Research limitations/implications
Visual tracking is the ability to control eye movements using the oculomotor system (vision and eye muscles working together). Visual tracking plays an important role when it comes to identifying an object and matching it with the database images. In visual tracking, deep learning has achieved great success.
Practical implications
The authors implement the multiple tracking methods, for better tracking purpose.
Originality/value
The main theme of this paper is to review the state-of-the-art tracking methods depending on deep learning. First, we introduce the visual tracking that is carried out manually, and secondly, we studied different existing methods of visual tracking based on deep learning. For every paper, we explained the analysis and drawbacks of that tracking method. This paper introduces the concept and research status of tracks, later we focus on the representative applications of deep learning in visual tracking.
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Van Thi Hong Do and Long Thanh Do
While consumers are increasingly concerned about the environment and commit themselves to environmental protection, they are still reluctant to act. This phenomenon, to date, has…
Abstract
Purpose
While consumers are increasingly concerned about the environment and commit themselves to environmental protection, they are still reluctant to act. This phenomenon, to date, has remained a puzzle and gained much attention from practitioners and researchers. As a contribution to the understanding of the phenomenon, this study aims to examine the role of downward social comparison as an explanation for the inconsistency of the relationships between two types of pro-environmental attitudes, namely attitudes toward the environment and attitudes toward sustainable consumption, and two sustainable consumption behaviors including electricity-saving behavior and unneeded consumption reduction.
Design/methodology/approach
Hierarchical multiple regressions were employed to test the hypotheses with survey data from 381 consumers in a large city in a Southeast Asian country.
Findings
The regression results support our expectation that downward social comparison negatively moderates the relationships between the two attitude variables and the two sustainable consumption behaviors.
Originality/value
Our findings provide some insights into the complexity of the attitude-behavior relationship and offer some practical recommendations for governments and policymakers in designing more effective behavioral interventions for the sustainability of human society.
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Vasishta Bhargava, Satya Prasad Maddula, Swamy Naidu Venkata Neigapula, Md. Akhtar Khan, Chinmaya Prasad Padhy and Dwivedi Yagya Dutta
This paper aims to model the aerodynamic flow characteristics of NACA0010 for various angle of attacks including stall for incompressible flows using panel methods. This paper…
Abstract
Purpose
This paper aims to model the aerodynamic flow characteristics of NACA0010 for various angle of attacks including stall for incompressible flows using panel methods. This paper also aims to quantify the surface pressure distribution on streamlined bodies and validate the results with analytical Jukouwski method and inverse panel methods that can predict the aerodynamic flow behaviour using the geometric iteration approach.
Design/methodology/approach
The 2 D panel method was implemented in Qblade software v.06 which uses the fundamental panel method which rely on source strengths and influence coefficients to determine the velocity and pressure fields on the surface. The software implements the boundary layer or viscous effects to determine the influence on aerodynamic performance at various angles of attack. Jukouwski method is also evaluated for predicting aerodynamic characteristics and is based on the geometric iteration approach. Then complex aerodynamic flow potentials are determined based on the source strengths which are used to predict the pressure and velocity fields.
Findings
At low to moderate angles of attack, panel and Jukouwski methods predict similar results for surface pressure coefficients comparable to Hess and Smith inverse method. In comparison to panel method, results from the Jukouwski mapping method predicted the pressure coefficient conservatively for the same free stream conditions. With increase in Reynolds number, lift coefficient and aerodynamic performance improved significantly for un-tripped aerofoil when stall angle is approached when compared to tripped aerofoil.
Practical implications
This study demonstrated that panel methods have higher efficacy in terms of computational time or resources and thus can provide benefits to many real-world aircraft or aerospace design applications.
Originality/value
Even though panel and Jukouwski methods have been studied extensively in the past, this paper demonstrates the efficacy of both methods for modelling aerodynamic flows that range between moderate to high Reynolds number which are critical for many aircraft applications. Both methods have been validated with analytical and inverse design methods which are able to predict aerodynamic flow characteristics for simple bluff bodies, streamlined aerofoils as well as bio-inspired corrugated aerofoils.
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The paper underpins an advanced domestic manufacturing that comes with some advanced employment specialization status of individual industries as the key determinant of foreign…
Abstract
Purpose
The paper underpins an advanced domestic manufacturing that comes with some advanced employment specialization status of individual industries as the key determinant of foreign direct investment (FDI) and considers how FDI in the food processing industry in India relates to this focal point.
Design/methodology/approach
This paper investigates how inward FDI inflows relate to domestic investment and revival in the industry using Auto Regressive Distributed lags (ARDL) model over the period 2000–2017. The model allows for different specifications to study whether FDI is responsible for the revival or the prior revival induces the FDI.
Findings
The results show the lack of proper advanced specialized employment status of the food processing industry. FDI in food processing is mainly guided by exports and imports opportunities and FDI plays no role in the revival of advanced growth in the industry. This finding explains why FDI in the industry is predominantly service sector oriented.
Originality/value
The paper underlines (1) the proper conceptualization of human capital as an important determinant of FDI; (2) reinterpretation of Kaldor's technical progress function that uncovers how employment dynamics embedded in intermediate goods specializations play a key role in supporting a higher pace of investment (and FDI); (3) labor costs' importance should involve not only the wage rate but also the advantages that a specialized employment base and (4) FDI in manufacturing demands a greater policy focus on developing domestic bases of intermediate goods specializations.
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B.V.K. Satya Sai, K.N. Seetharamu and P.A. Aswathanarayana
Presents a numerical study on heat transfer by natural convection in porous media in vertical enclosures with side wall heating. The model for porous media includes inertia terms…
Abstract
Presents a numerical study on heat transfer by natural convection in porous media in vertical enclosures with side wall heating. The model for porous media includes inertia terms and also the Brinkman extension in addition to the Darcy resistance term. A semi‐implicit finite element scheme based on operator splitting method is adopted for solving the time‐dependent system of equations. The first half of the investigations is confined to the low permeability regime where Darcy law holds good. Presents the results for annular and rectangular cavities and proposes correlations for two types of boundary conditions, namely constant wall temperature case and uniform wall heat flux case. In the second half of the investigations, the scheme is applied in a high permeability regime, where the validity of Darcy law becomes questionable. Employs plane rectangular cavities with the two types of boundary conditions mentioned earlier. Highlights the influence of Rayleigh number (Ra) and Darcy number (Da) as separate parameters and proposes correlations for a square cavity for the first time in terms of Ra and Da as separate parameters. Discusses a qualitative study of the effect of aspect ratio on heat transfer as the permeability changes.
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The present paper aims to highlight how manufacturing expansions under conditions of increasing returns, which involve the growth of intermediate goods specializations, support…
Abstract
Purpose
The present paper aims to highlight how manufacturing expansions under conditions of increasing returns, which involve the growth of intermediate goods specializations, support advanced service employment. In addition, the increasing use of manufacturing products in services highlights additional, new service sector employment opportunities.
Design/methodology/approach
This paper investigates (1) the manufacturing and service interactions and (2) the investment behaviour in manufacturing using Auto-Regressive Distributed lags (ARDL) and Vector Autoregressive (VAR) models. The models allow for different specifications to study whether investment behaviour in manufacturing supports dynamic manufacturing and service interactions.
Findings
The results underpin how Kaldorian manufacturing as an engine of growth is still relevant in Indian growth and is key to achieving higher advanced employment, export-orientation and services and manufacturing nexus outcomes. What matters, though, is that manufacturing investments are to be guided mainly by intermediate goods specializations. The slowdown of these specializations, explaining the slowdown of manufacturing investment, is therefore, a concern.
Originality/value
A reinterpretation of manufacturing as an engine of growth in which primacy is given to investment behaviour in technical progress functions that can support the growth of specializations in manufacturing and such specialized service employment.