K. Venkataravana Nayak, J.S. Arunalatha, G.U. Vasanthakumar and K.R. Venugopal
The analysis of multimedia content is being applied in various real-time computer vision applications. In multimedia content, digital images constitute a significant part. The…
Abstract
Purpose
The analysis of multimedia content is being applied in various real-time computer vision applications. In multimedia content, digital images constitute a significant part. The representation of digital images interpreted by humans is subjective in nature and complex. Hence, searching for relevant images from the archives is difficult. Thus, electronic image analysis strategies have become effective tools in the process of image interpretation.
Design/methodology/approach
The traditional approach used is text-based, i.e. searching images using textual annotations. It consumes time in the manual process of annotating images and is difficult to reduce the dependency in textual annotations if the archive consists of large number of samples. Therefore, content-based image retrieval (CBIR) is adopted in which the high-level visuals of images are represented in terms of feature vectors, which contain numerical values. It is a commonly used approach to understand the content of query images in retrieving relevant images. Still, the performance is less than optimal due to the presence of semantic gap among the image content representation and human visual understanding perspective because of the image content photometric, geometric variations and occlusions in search environments.
Findings
The authors proposed an image retrieval framework to generate semantic response through the feature extraction with convolution network and optimization of extracted features using adaptive moment estimation algorithm towards enhancing the retrieval performance.
Originality/value
The proposed framework is tested on Corel-1k and ImageNet datasets resulted in an accuracy of 98 and 96%, respectively, compared to the state-of-the-art approaches.
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Robert Detmering, Anna Marie Johnson, Claudene Sproles, Samantha McClellan and Rosalinda Hernandez Linares
– The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.
Abstract
Purpose
The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.
Design/methodology/approach
Introduces and annotates English-language periodical articles, monographs and other materials on library instruction and information literacy published in 2013.
Findings
Provides information about each source, discusses the characteristics of current scholarship and describes sources that contain unique scholarly contributions and quality reproductions.
Originality/value
The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.
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Andreas Kakouris, Vasilis Athanasiadis and Eleni Sfakianaki
Acknowledging the importance of both lean thinking (LT) and Industry 4.0 (I4.0) for successful business performance and organisational success, the present study investigates the…
Abstract
Purpose
Acknowledging the importance of both lean thinking (LT) and Industry 4.0 (I4.0) for successful business performance and organisational success, the present study investigates the critical success factors (CSFs) for the concurrent implementation of both approaches, a field not yet significantly explored.
Design/methodology/approach
The study conducts two systematic literature reviews (SLRs), one on LT and the other one on I4.0 to map out the CSFs for the effective implementation of each approach. These CSFs are subsequently prioritised with the use of a Delphi Study. Finally, from the set of the common CSFs recognised through the two approaches, a more condensed list is put forward as the first step towards achieving a successful synergy between LT and I4.0.
Findings
The study’s findings suggest the most important CSFs and determine their definition in the context of a concurrent implementation of LT and I4.0. This can provide managers and practitioners with the awareness of crucial factors, enabling them to take the necessary steps for planning and implementing both approaches.
Practical implications
A concise set of CSFs for the concurrent implementation of both LT and I4.0 has been identified, which can be viewed as a starting point for providing top executives and managers with useful insights into enhanced business efficiency and performance. This study furthermore contributes to the overall body of knowledge on LT and I4.0.
Originality/value
The scholarly literature that explores a common set of CSFs for the concurrent implementation of LT and I4.0 is limited. This gap significantly enhances the importance of the present research, contributing to a better understanding amongst both academics and practitioners of the key supporting factors for the integration of the two approaches.
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Harshad Sonar, Vivek Khanzode and Milind Akarte
The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and…
Abstract
Purpose
The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and to establish the hierarchical relationship among them.
Design/methodology/approach
The methodology includes three phases, namely, identification of factors through systematic literature review (SLR), interviews with experts to capture industry perspective of AM implementation factors and to develop the hierarchical model and classify it by deriving the interrelationship between the factors using interpretive structural modeling (ISM), followed with the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis.
Findings
This research has identified 14 key factors that influence the successful AM implementation in the Indian manufacturing sector. Based on the analysis, top management commitment is an essential factor with high driving power, which exaggerates other factors. Factors, namely, manufacturing flexibility, operational excellence and firm competitiveness are placed at the top level of the model, which indicates that they have less driving power and organizations need to focus on those factors after implementing the bottom-level factors.
Research limitations/implications
Additional factors may be considered, which are important for AM implementation from different industry contexts. The variations from different industry contexts and geographical locations can foster the theoretical robustness of the model.
Practical implications
The proposed ISM model sets the directions for business managers in planning the operational strategies for addressing AM implementation issues in the Indian manufacturing sector. Also, competitive strategies may be framed by organizations based on the driving and dependence power of AM implementation factors.
Originality/value
This paper contributes by identification of AM implementation factors based on in-depth literature review as per SLR methodology and validation of these factors from a variety of industries and developing hierarchical model by integrative ISM-MICMAC approach.
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Anilkumar Malaga and S. Vinodh
The objective of the study is to identify and analyse drivers of smart manufacturing using integrated grey-based approaches. The analysis facilitates industry practitioners in the…
Abstract
Purpose
The objective of the study is to identify and analyse drivers of smart manufacturing using integrated grey-based approaches. The analysis facilitates industry practitioners in the identification of preference of drivers through which smart manufacturing can be implemented. These drivers are explored based on existing literature and expert opinion.
Design/methodology/approach
Modern manufacturing firms have been adopting smart manufacturing concepts to sustain in the global competitive landscape. Smart manufacturing incorporates integrated technologies with a flexible workforce to interlink the cyber and physical world. In order to facilitate the effective deployment of smart manufacturing, key drivers need to be analysed. This article presents a study in which 25 drivers of smart manufacturing and 8 criteria are analysed. Integrated grey Technique for Order Preference by Similarity to Ideal Solution (grey TOPSIS) is applied to rank the drivers. The derived ranking is validated using “Complex Proportional Assessment – Grey” (COPRAS-G) approach.
Findings
In total, 25 drivers with 8 criteria are being considered and an integrated grey TOPSIS approach is applied. The ranking order of drivers is obtained and further sensitivity analysis is also done.
Research limitations/implications
In the present study, 25 drivers of smart manufacturing are analysed. In the future, additional drivers could be considered.
Practical implications
The study presented has been done with inputs from industry experts, and hence the inferences have practical relevance. Industry practitioners need to focus on these drivers in order to implement smart manufacturing in industry.
Originality/value
The analysis of drivers of smart manufacturing is the original contribution of the authors.
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Tâmara Machado Fagundes da Silva, Luciano Costa Santos and Cláudia Fabiana Gohr
Studies addressing barriers to implement lean production (LP) from the perspective of risk management (RM) have not been so usual in the literature. Re-interpreting barriers to…
Abstract
Purpose
Studies addressing barriers to implement lean production (LP) from the perspective of risk management (RM) have not been so usual in the literature. Re-interpreting barriers to lean as potential risks that should be avoided or mitigated, this paper aims to identify and categorise risks in the implementation of LP to propose a framework, which provides an overview of risks that negatively influence this process.
Design/methodology/approach
Through a systematic literature review exploring papers in the Web of Knowledge database, 69 papers were selected. A descriptive analysis was first carried out to identify the evolution in the number of papers, usual terminologies, research methods, analytic tools and the RM phases approached by each paper. After that, an in-depth study of the paper sample was conducted to find risk factors and categories.
Findings
The authors found a list of 61 risk factors. Then, considering the sources of the identified risk factors, six broad categories of risks were defined, namely, top management risks, human resources risks, lean knowledge risks, technical risks, supply chain risks and cultural risks. The authors also defined 34 subcategories, resulting in a risk classification framework.
Research limitations/implications
Based on the review, the authors identified literature gaps and provided a research agenda. A noteworthy research limitation is that the authors only selected papers about LP, so the authors might have missed some potential risks in lean implementation that may arise from other-related areas. Thus, the exploration of lean risks adopting other perspectives may constitute a promising pathway for further research.
Practical implications
The classification framework may help practitioners and researchers in risk identification, evaluation and mitigation. It can also enable the creation of response plans to risks in lean production implementation, as it indicates the potential risks that may be faced along with this process.
Originality/value
This study contributed to add the perspective of RM to the literature on lean implementation. The introduction of RM concepts and tools may generate more robust models of lean implementation. Therefore, the classification framework may represent a starting point to produce new knowledge about this research topic.
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Sarita Prasad, Milen Baltov, Neelakanteswara Rao A. and Krishnanand Lanka
The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).
Abstract
Purpose
The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).
Design/methodology/approach
In this study, the interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for enablers. Also, the interpretive ranking process (IRP) was used to analyse and rank enablers with reference to performance variables. For the ISM approach, a structural self- integration matrix was developed with the help of experts’ suggestions and opinions. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship amongst enablers. A total of nine experts were chosen for collecting the primary data in which seven experts belong to the industry and two experts were academicians. The dominant relationship amongst the enablers was analysed through IRP modelling.
Findings
A total of 11 enablers were identified for the purpose of this study. The model shows that “leadership and commitment by management”, “human resource management”, “customer relation management”, “supplier relation management” and “information technology system” are the most significant enablers for lean implementation in Bulgarian SMEs as these are positioned at the bottom levels in ISM model. MICMAC analysis shows that five enablers fall in the independent factor, two enablers in linkage factor and four enablers in the dependant factor while there is no enabler in the autonomous factor. ISM and IRP models show that “continuous improvement” is an essential enabler for the successful implementation of lean in Bulgarian SMEs. This study also helps to explain the comparative analysis of ISM and IRP, which indicates that IRP is a more robust modelling approach than ISM, as it incorporates the relationship of enablers with performance variables.
Research limitations/implications
ISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study.
Practical implications
This study supports the professionals/experts to prioritise and manage enablers at strategic and tactical levels while implementing lean manufacturing practices in Bulgarian SMEs. The models developed in the study will be helpful for practitioners to understand and analyse the interdependence of enablers for lean manufacturing implementation.
Originality/value
This study helps to identify and prioritise enablers that affect lean manufacturing adoption using ISM and IRP approaches. Literature shows that numerous authors have used the ISM approach but the use of IRP approach is limited. The models were developed in the study, totally dependent on data collected from the experts to ensure their real-life validity.
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The present study aims to examine the influence of stakeholders on green marketing strategy (GMS). Marketing literature recognizes that stakeholders play a significant role in…
Abstract
Purpose
The present study aims to examine the influence of stakeholders on green marketing strategy (GMS). Marketing literature recognizes that stakeholders play a significant role in influencing organizations and markets, but has not targeted a single integrated approach to examine the relationship between stakeholder management and GMS.
Design/methodology/approach
This research comprised several phases, including the development of a typology of GMS, an analysis of how managers prioritize stakeholders, a study of the influence of stakeholders on GMS, and an analysis of the influence of the organizational context on managers' perception of the stakeholders. The hypotheses were validated using multivariate correlational techniques.
Findings
The study identified the stakeholders associated with GMS and their impact on the strategy adopted by the firms, and established how this is moderated by the firm's own economic sector and organizational characteristics.
Research limitations/implications
Future studies might replicate and extend the research in other industries and countries to ascertain whether environmental concerns have different effects in other contexts.
Practical implications
The surveys on GMS and stakeholder perception undertaken in the present survey are a potential source of information for managers – because they can be used as a self‐diagnostic tool to determine if a firm's attitude to the environment is reactive or proactive.
Originality/value
Results show that the organizational “greening” process is not a linear, one‐dimensional progression, rather an uneven process in which several GMS profiles prioritize different stakeholders. The results also reveal that underlying perceptual, behavioral, and organizational factors influence GMS implementation.
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José M. Moneva and Eduardo Ortas
The aim of this paper is to evaluate the significance of the link between corporate environmental and financial performance in order to show managers how an adequate management of…
Abstract
Purpose
The aim of this paper is to evaluate the significance of the link between corporate environmental and financial performance in order to show managers how an adequate management of environmental factors could contribute to the financial success of the firm.
Design/methodology/approach
The paper analyses the environmental and financial performance of a sample of 230 European companies. Under the stakeholder approach, the commitment to environmental performance is analysed and linked with the firms' financial improvement. The paper proposes a partial least squares model (PLS) for measuring corporate environmental and financial performance that seems to be the first time which has been applied in the field.
Findings
The results support the idea that enterprises which obtained higher rates of environmental performance show better financial performance levels in the future.
Research limitations/implications
The lack of a long series of environmental performance data for organisations is an obstacle for a broader analysis. This research shows the usefulness of the multivariate modelling for analysing the environmental and financial performance of businesses.
Practical implications
In practice, this research may show managers the need of taking into account the environmental management factors when configuring the strategic policy of the firm and how environmental management can impact to the financial success of the firms.
Originality/value
The use of PLS modelling for measuring environmental and financial performance theoretical concepts and considering a sample of European companies for the empirical analysis.
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Wei-Mon Yan, Hsu-Yang Teng, Chun-Han Li and Mohammad Ghalambaz
The electromagnetic field and cooling system of a high power switched reluctance motor (SRM) are studied numerically. The geometry of the motor and its main components are…
Abstract
Purpose
The electromagnetic field and cooling system of a high power switched reluctance motor (SRM) are studied numerically. The geometry of the motor and its main components are established using a computer-aided design software in the actual size. This study aims to evaluate the resulting thermal losses using the electromagnetic analysis of the motor.
Design/methodology/approach
In the electromagnetic analysis, the Joule’s loss in the copper wires of the coil windings and the iron losses (the eddy currents loss and the hysteresis loss) are considered. The flow and heat transfer model for the thermal analysis of the motor including the conduction in solid parts and convection in the fluid part is introduced. The magnetic losses are imported into the thermal analysis model in the form of internal heat generation in motor components. Several cooling system approaches were introduced, such as natural convection cooling, natural convection cooling with various types of fins over the motor casing, forced conviction air-cooled cooling system using a mounted fan, casing surface with and without heat sinks, liquid-cooled cooling system using the water in a channel shell and a hybrid air-cooled and liquid-cooled cooling system.
Findings
The results of the electromagnetics analysis show that the low rotational speed of the motor induces higher currents in coil windings, which in turn, it causes higher copper losses in SRM coil windings. For higher rotational speed of SRM, the core loss is higher than the copper loss is in SRM due to the higher frequency. An air-cooled cooling system is used for cooling of SRM. The results reveal when the rotational speed is at 4,000 rpm, the coil loss would be at the maximum value. Therefore, the coil temperature is about 197.9°C, which is higher than the tolerated standard temperature insulation material. Hence, the air-cooled system cannot reduce the temperature to the safe temperature limitation of the motor and guarantee the safe operation of SRM. Thus, a hybrid system of both air-cooled and liquid-cooled cooling system with mounting fins at the outer surface of the casing is proposed. The hybrid system with the liquid flow of Re = 1,500 provides a cooling power capable of safe operation of the motor at 117.2°C, which is adequate for standard insulation material grade E.
Originality/value
The electromagnetic field and cooling system of a high power SRM in the presence of a mounted fan at the rear of the motor are analyzed. The thermal analysis is performed for both of the air-cooled and liquid-cooled cooling systems to meet the cooling demands of the motor for the first time.