Search results

1 – 10 of over 101000
To view the access options for this content please click here
Article
Publication date: 14 September 2021

Paula Rodrigues, Ana Pinto Borges and Ana Daniela Ferreira Antunes de Sousa

This study, based on craft beer brands, aims (1) to explain the importance of four brand authenticity dimensions (continuity, originality, reliability and naturalness) in…

Abstract

Purpose

This study, based on craft beer brands, aims (1) to explain the importance of four brand authenticity dimensions (continuity, originality, reliability and naturalness) in consumers' perceptions of brand image; (2) to verify if the brand–consumer emotional relationship (brand love) is enhanced by the consumer's perceptions of the brand's image; (3) to verify if the consumer's perceptions of the brand's image increase brand satisfaction; and (4) to verify if brand satisfaction increases brand love.

Design/methodology/approach

Data were collected from consumers of different craft beer brands to evaluate the assumptions underlying the proposed conceptual model. In total, 175 questionnaire responses were used, and the model was estimated through structural equation modelling (SEM) with partial least squares (PLS).

Findings

The results confirmed that brand authenticity is a strong antecedent of the brand image of craft beers, and that brand image affects both consumer brand satisfaction and brand love. The effect of brand satisfaction on brand love has also been confirmed. Craft beer brands should aim to attract more fan-consumers, i.e. consumers who seek an emotional relationship that manifests itself in affection, beauty, well-being and long-term commitment. Fan-consumers give their hearts/love and recommend the brand.

Originality/value

The paper tries to fill two gaps in the literature. First, we make the initial empirical application of the Bruhn et al. (2012) scale and verify its adequacy in this context. Second, this is the first time that the model's design has been validated. The results allow us to confirm that authenticity is an antecedent of brand image, and its simultaneous impact on the consumer's brand love for, and satisfaction with, craft beer brands.

Details

EuroMed Journal of Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1450-2194

Keywords

To view the access options for this content please click here
Article
Publication date: 10 September 2021

Ying-Yi Deng and Yi-Chun Yang

Few studies have explored how to foster green customer citizenship behavior. Therefore, the aim of this study was to understand the factors influencing green customer…

Abstract

Purpose

Few studies have explored how to foster green customer citizenship behavior. Therefore, the aim of this study was to understand the factors influencing green customer citizenship behavior in a restaurant context.

Design/methodology/approach

This study proposes a conceptual model, based on previous studies, hypothesizing that green attributes transparency engenders green brand image and green trust, which together facilitate green customer citizenship behavior. The authors used structural equations modeling with data collected from 312 consumers in Taiwan to do the analysis.

Findings

The findings indicate that green attributes transparency plays a strong role in determining green brand image and green trust, which enhance green customer citizenship behavior. Managerial implications to aid businesses in developing strategies to enhance their ability to foster green citizenship behavior among its consumers for competitive advantage is also provided, together with an outline of the limitations of the study.

Originality/value

This study used the concept of stimulus–organism–response to test the stimuli of green attributes transparency to enhance customer citizenship behavior mediated by green brand image and green trust. This study makes two theoretical contributions. First, this study extended the concept of attributes transparency, brand image, trust and customer citizenship behavior to a green context. The authors developed a research framework and confirmed that green attributes transparency facilitate green brand image and green trust, which contribute to green customer citizenship behavior. Second, there is no prior study exploring the relationship between green attributes transparency, green brand image, green trust and green customer citizenship behavior. The empirical support for the model developed in this study is based on empirical data of Taiwan restaurant consumers.

Details

British Food Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0007-070X

Keywords

To view the access options for this content please click here
Article
Publication date: 3 September 2021

G. Jaffino and J. Prabin Jose

Forensic dentistry is the application of dentistry in legal proceedings that arise from any facts relating to teeth. The ultimate goal of forensic odontology is to…

Abstract

Purpose

Forensic dentistry is the application of dentistry in legal proceedings that arise from any facts relating to teeth. The ultimate goal of forensic odontology is to identify the individual when there are no other means of identification such as fingerprint, Deoxyribonucleic acid (DNA), iris, hand print and leg print. The purpose of selecting dental record is for the teeth to be able to withstand decomposition, heat degradation up to 1600 °C. Dental patterns are unique for every individual. This work aims to analyze the contour shape extraction and texture feature extraction of both radiographic and photographic dental images for person identification.

Design/methodology/approach

To achieve an accurate identification of individuals, the missing tooth in the radiograph has to be identified before matching of ante-mortem (AM) and post-mortem (PM) radiographs. To identify whether the missing tooth is a molar or premolar, each tooth in the given radiograph has to be classified using a k-nearest neighbor (k-NN) classifier; then, it is matched with the universal tooth numbering system. In order to make exact person identification, this research work is mainly concentrate on contour shape extraction and texture feature extraction for person identification. This work aims to analyze the contour shape extraction and texture feature extraction of both radiographic and photographic images for individual identification. Then, shape matching of AM and PM images is performed by similarity and distance metric for accurate person identification.

Findings

The experimental results are analyzed for shape and feature extraction of both radiographic and photographic dental images. From this analysis, it is proved that the higher hit rate performance is observed for the active contour shape extraction model, and it is well suited for forensic odontologists to identify a person in mass disaster situations.

Research limitations/implications

Forensic odontology is a branch of human identification that uses dental evidence to identify the victims. In mass disaster circumstances, contours and dental patterns are very useful to extract the shape in individual identification.

Originality/value

The experimental results are analyzed both the contour shape extraction and texture feature extraction of both radiographic and photographic images. From this analysis, it is proved that the higher hit rate performance is observed for the active contour shape extraction model and it is well suited for forensic odontologists to identify a person in mass disaster situations. The findings provide theoretical and practical implications for individual identification of both radiographic and photographic images with a view to accurate identification of the person.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

Content available
Article
Publication date: 2 September 2021

Mattias Jacobsson and Beata Jałocha

The aim of this article is to give an overview of the development and current state of projectification research. The inquiry was driven by a threefold research question…

Abstract

Purpose

The aim of this article is to give an overview of the development and current state of projectification research. The inquiry was driven by a threefold research question: How has projectification been understood and defined over time, what has the trajectory of the development been and what are the main trends and emerging ideas?

Design/methodology/approach

The article is an integrative literature review of research done on the notion of projectification to date. An interdisciplinary, integrative literature review was conducted using Scopus and Web of Science as primary sources of data collection. The full data set consists of 123 journal articles, books, book chapters and conference contributions. With the data set complete, a thematic analysis was conducted.

Findings

Among other things, the review outlines the development and scope of projectification research from 1995 until 2021 and discusses four emerging images of projectification: projectification as a managerial approach, projectification as a societal trend, projectification as a human state and projectification as a philosophical issue. These characteristics emphasize some common features of each of the images but also imply that the way projectification is understood changes depending on the paradigmatic perspective taken by the researcher, the time and place in which the observation was made and the level of observation.

Originality/value

The authors have outlined and discussed four images of projectification – projectification as a managerial approach, projectification as a societal trend, projectification as a human state and projectification as a philosophical issue – where each image represents a special take on projectification with some prevalent characteristics. By doing this, the authors provide a systematic categorization of research to date and thus a basis upon which other researchers can build when furthering the understanding of projectification at large.

Details

International Journal of Managing Projects in Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8378

Keywords

To view the access options for this content please click here
Article
Publication date: 23 September 2021

Wahyu Rahmaniar, W.J. Wang, Chi-Wei Ethan Chiu and Noorkholis Luthfil Luthfil Hakim

The purpose of this paper is to propose a new framework and improve a bi-directional people counting technique using an RGB-D camera to obtain accurate results with fast…

Abstract

Purpose

The purpose of this paper is to propose a new framework and improve a bi-directional people counting technique using an RGB-D camera to obtain accurate results with fast computation time. Therefore, it can be used in real-time applications.

Design/methodology/approach

First, image calibration is proposed to obtain the ratio and shift values between the depth and the RGB image. In the depth image, a person is detected as foreground by removing the background. Then, the region of interest (ROI) of the detected people is registered based on their location and mapped to an RGB image. Registered people are tracked in RGB images based on the channel and spatial reliability. Finally, people were counted when they crossed the line of interest (LOI) and their displacement distance was more than 2 m.

Findings

It was found that the proposed people counting method achieves high accuracy with fast computation time to be used in PCs and embedded systems. The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

Practical implications

The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

Originality/value

The proposed method can count the number of people entering and exiting a room at the same time. If the previous systems were limited to only one to two people in a frame, this system can count many people in a frame. In addition, this system can handle some problems in people counting, such as people who are blocked by others, people moving in another direction suddenly, and people who are standing still.

Details

Sensor Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0260-2288

Keywords

To view the access options for this content please click here
Article
Publication date: 24 August 2021

Rajakumar Krishnan, Arunkumar Thangavelu, P. Prabhavathy, Devulapalli Sudheer, Deepak Putrevu and Arundhati Misra

Extracting suitable features to represent an image based on its content is a very tedious task. Especially in remote sensing we have high-resolution images with a variety…

Abstract

Purpose

Extracting suitable features to represent an image based on its content is a very tedious task. Especially in remote sensing we have high-resolution images with a variety of objects on the Earth's surface. Mahalanobis distance metric is used to measure the similarity between query and database images. The low distance obtained image is indexed at the top as high relevant information to the query.

Design/methodology/approach

This paper aims to develop an automatic feature extraction system for remote sensing image data. Haralick texture features based on Contourlet transform are fused with statistical features extracted from the QuadTree (QT) decomposition are developed as feature set to represent the input data. The extracted features will retrieve similar images from the large image datasets using an image-based query through the web-based user interface.

Findings

The developed retrieval system performance has been analyzed using precision and recall and F1 score. The proposed feature vector gives better performance with 0.69 precision for the top 50 relevant retrieved results over other existing multiscale-based feature extraction methods.

Originality/value

The main contribution of this paper is developing a texture feature vector in a multiscale domain by combining the Haralick texture properties in the Contourlet domain and Statistical features using QT decomposition. The features required to represent the image is 207 which is very less dimension compare to other texture methods. The performance shows superior than the other state of art methods.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 6 August 2021

Valli Bhasha A. and Venkatramana Reddy B.D.

The problems of Super resolution are broadly discussed in diverse fields. Rather than the progression toward the super resolution models for real-time images, operating…

Abstract

Purpose

The problems of Super resolution are broadly discussed in diverse fields. Rather than the progression toward the super resolution models for real-time images, operating hyperspectral images still remains a challenging problem.

Design/methodology/approach

This paper aims to develop the enhanced image super-resolution model using “optimized Non-negative Structured Sparse Representation (NSSR), Adaptive Discrete Wavelet Transform (ADWT), and Optimized Deep Convolutional Neural Network”. Once after converting the HR images into LR images, the NSSR images are generated by the optimized NSSR. Then the ADWT is used for generating the subbands of both NSSR and HRSB images. The residual image with this information is obtained by the optimized Deep CNN. All the improvements on the algorithms are done by the Opposition-based Barnacles Mating Optimization (O-BMO), with the objective of attaining the multi-objective function concerning the “Peak Signal-to-Noise Ratio (PSNR), and Structural similarity (SSIM) index”. Extensive analysis on benchmark hyperspectral image datasets shows that the proposed model achieves superior performance over typical other existing super-resolution models.

Findings

From the analysis, the overall analysis of the suggested and the conventional super resolution models relies that the PSNR of the improved O-BMO-(NSSR+DWT+CNN) was 38.8% better than bicubic, 11% better than NSSR, 16.7% better than DWT+CNN, 1.3% better than NSSR+DWT+CNN, and 0.5% better than NSSR+FF-SHO-(DWT+CNN). Hence, it has been confirmed that the developed O-BMO-(NSSR+DWT+CNN) is performing well in converting LR images to HR images.

Originality/value

This paper adopts a latest optimization algorithm called O-BMO with optimized Non-negative Structured Sparse Representation (NSSR), Adaptive Discrete Wavelet Transform (ADWT) and Optimized Deep Convolutional Neural Network for developing the enhanced image super-resolution model. This is the first work that uses O-BMO-based Deep CNN for image super-resolution model enhancement.

To view the access options for this content please click here
Article
Publication date: 30 August 2021

Richard Huaman-Ramirez and Dwight Merunka

This paper aims to model and estimate how celebrity chief executive officers (CEOs) credibility (i.e. expertise, trustworthiness, attractiveness) is related to their brand…

Abstract

Purpose

This paper aims to model and estimate how celebrity chief executive officers (CEOs) credibility (i.e. expertise, trustworthiness, attractiveness) is related to their brand image (i.e. functional, sensory/visual). This paper further examines the effects of consumer materialism on both celebrity CEOs’ credibility and the image of their brand.

Design/methodology/approach

A total of 260 participants knowledgeable of CEOs and their corresponding brands completed an online questionnaire in a cross-sectional study. The data were analyzed through covariance-based structural equation modeling.

Findings

Celebrity CEOs’ expertise and attractiveness are positively related to both functional and sensory/visual images of their brands. Results also demonstrate the positive effect of materialism on both celebrity CEOs’ credibility and brand image.

Research limitations/implications

The research was conducted in one country (France) using a cross-sectional design. Additional studies in other settings or countries should be carried out to establish the generalizability of results and strengthen causality inferences.

Practical implications

CEOs need to understand and manage their key role as celebrities, given the direct influence they may have on consumer brand perceptions and behavior.

Originality/value

This study refines the relationship between celebrity CEOs’ credibility and brand image. It is the first to introduce and validate the effect of consumer materialism on the perception of celebrity CEOs.

Details

Journal of Consumer Marketing, vol. 38 no. 6
Type: Research Article
ISSN: 0736-3761

Keywords

To view the access options for this content please click here
Article
Publication date: 10 August 2021

Hirak Jyoti Hazarika, S. Ravikumar and Akash Handique

This paper aims to present a novel DSpace-based medical image repository system planned explicitly for storing and retrieving clinical images using digital imaging and…

Abstract

Purpose

This paper aims to present a novel DSpace-based medical image repository system planned explicitly for storing and retrieving clinical images using digital imaging and communication in medicine (DICOM) metadata standards. DSpace institutional repository software is widely used in an academic environment for accessing and mainly storing text-related files. DICOM images are particular types of images embedded with much system-generated metadata and organised using DICOM metadata standards.

Design/methodology/approach

The present paper talks about institutional repository software (DSpace) in archiving DICOM images. In the current study, the authors have tried to integrate the DICOM metadata standard with DSpace, which was compatible with Dublin Core (DC) and open archives initiative – protocol for metadata harvesting (OAI-PMH). After combining the DICOM standard with DSpace and the repository tested with a sample of 5,000 images, the retrieval results using various DICOM tags was very satisfactory. This study paves for the use of open source software (OSS) in storing and retrieving medical images.

Findings

The author has provided the DSpace software to recognised DICOM (.dcm) files in the first stage. In the second stage, a patch was developed to identify the DICOM metadata standard in Dspace, which has inbuilt DC metadata standards. Finally, in the third stage, retrieval efficiency was tested with a 5,000 .dcm image using the DICOM tag and the results were very fruitful.

Research limitations/implications

A major limitation of this study was the size of the data (5,000 DICOM images) with which the authors have tested the system. The system scalability has to be tested on various fronts like on cloud and local servers with different configurations, for which a separate study has to be done.

Practical implications

Once this system is in place, DICOM users can stock, retrieve and access the image from the Web platform. Furthermore, this proposed repository will be the warehouse of various DICOM images with reasonable storage costs.

Originality/value

In addition to exploring the opportunities of free open source software (FOSS) implementation in medical science, this study includes issues related to the performance of an open-source repository for retrieving and preserving medical images. It created and developed Open Source DICOM Medical Image Library with DICOM metadata standard with the help of DSpace. Thus, the study will generate value for library professionals and medical professionals and FOSS vendors to understand the medical market in the context of FOSS.

Details

Collection and Curation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9326

Keywords

To view the access options for this content please click here
Article
Publication date: 11 August 2021

Wienand Kölle, Matthias Buchholz and Oliver Musshoff

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of…

Abstract

Purpose

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

Design/methodology/approach

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

Findings

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

Originality/value

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

Details

Agricultural Finance Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0002-1466

Keywords

1 – 10 of over 101000