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Case study
Publication date: 17 October 2012

S. Ramesh Kumar and Arun Bhattacharyya

Entrepreneurship in emerging markets; the planning of survival and competition strategies of small businesses run by entrepreneurs against well established larger brands.

Abstract

Subject area

Entrepreneurship in emerging markets; the planning of survival and competition strategies of small businesses run by entrepreneurs against well established larger brands.

Study level/applicability

The case can be used at the post graduate level in principles of marketing, entrepreneurship or emerging markets courses.

Case overview

The case looks at the antecedents and process of transformation of a small-scale firm into a marketing-oriented organization, through the lens of holistic marketing. The case focuses on a small-scale Bangalore based Indian company, Vishaal Natural Food Products (I) Pvt. Ltd that had used the concept of marketing orientation and holistic marketing to effectively make use of the advantages of its “smallness” and the characteristics of its entrepreneurial setup.

Expected learning outcomes

How can an entrepreneur survive in a dynamic environment? How should the company conceptually finalize its growth avenues? How can holistic marketing have an impact on the entire functioning of the organization when radical changes to handle the environmental changes, are made? How does the concept of holistic marketing which in textbooks fits in with the complexities of large corporations when they plan their strategies, have an impact on the functioning of these small businesses. The case delves into the conceptual linkages posed by these questions.

Supplementary materials

Teaching notes are available, please consult your librarian for access.

Details

Emerald Emerging Markets Case Studies, vol. 2 no. 8
Type: Case Study
ISSN: 2045-0621

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Article
Publication date: 20 November 2020

S. Madhu and M. Balasubramanian

The purpose of this study is for solving many issues in production that includes processing of complex-shaped profile, machining of high-strength materials, good surface…

Abstract

Purpose

The purpose of this study is for solving many issues in production that includes processing of complex-shaped profile, machining of high-strength materials, good surface finish with high-level precision and minimization of waste. Among the various advanced machining processes, abrasive jet machining (AJM) is one of the non-traditional machining techniques used for various applications such as polishing, deburring and hole making. Hence, an overview of the investigations done on carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GRFP) composites becomes important.

Design/methodology/approach

Discussion on various approaches to AJM, the effect of process parameters on the glass fiber and carbon fiber polymeric composites are presented. Kerf characteristics, surface roughness and various nozzle design were also discussed.

Findings

It was observed that abrasive jet pressure, stand-off distance, traverse rate, abrasive size, nozzle diameter, angle of attack are the significant process parameters which affect the machining time, material removal rate, top kerf, bottom kerf and kerf angle. When the particle size is maximum, the increased kinetic energy of the particle improves the penetration depth on the CFRP surface. As the abrasive jet pressure is increased, the cutting process is enabled without severe jet deflection which in turn minimizes the waviness pattern, resulting in a decrease of the surface roughness.

Research limitations/implications

The review is limited to glass fiber and carbon fiber polymeric composites.

Practical implications

In many applications, the use of composite has gained wide acceptance. Hence, machining of the composite need for the study also has gained wide acceptance.

Social implications

The usage of composites reduces the usage of very costly materials of high density. The cost of the material also comes down.

Originality/value

This paper is a comprehensive review of machining composite with abrasive jet. The paper covers in detail about machining of only GFRP and CFRP composites with various nozzle designs, unlike many studies which has focused widely on general AJM of various materials.

Details

World Journal of Engineering, vol. 18 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

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Article
Publication date: 8 July 2021

M. Balasubramanian and S. Madhu

The purpose of this study is to bring out the machining characteristics of abrasive jet machining on carbon fibre reinforced thermoplastic composites utilized in aerospace…

Abstract

Purpose

The purpose of this study is to bring out the machining characteristics of abrasive jet machining on carbon fibre reinforced thermoplastic composites utilized in aerospace and biomedical applications. Biocompatibility materials such as carbon fibres and polyether thermoplastics, like polyether ether ketone (PEEK) are widely used in trauma and orthopaedic surgery. Due to the heterogeneity, layered construction of reinforcing phase bonds with a resin matrix and abrasiveness of the reinforcing fibre, traditional drilling of carbon fibre-reinforced composites (CFRPs) are always challenging task.

Design/methodology/approach

An investigation is carried out using abrasive jet machine for drilling PEEK filled with 30 Wt.% carbon fibre (CF 30) using threaded and unthreaded nozzle to study the effect of abrasive jet process variables on surface roughness (Ra) and delamination factor (DF). Pressure (P) and stand-off distance (SOD) as important technological abrasive jet factors were evaluated. It is found that higher abrasive jet pressure and minimum SOD maybe selected to achieve minimum delamination.

Findings

The study further reported that the threaded nozzle minimized the surface roughness by 43% and delamination factor up to 12%.

Originality/value

This study of experimenting and observing the machining characteristics of CF30 by using a threaded nozzle is being tried for the first time and the results are deliberated.

Details

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

Keywords

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Article
Publication date: 8 June 2021

M. Balasubramanian and S. Madhu

The purpose of the study is to machine the composites at lower machining time with higher accuracy without causing delamination.

Abstract

Purpose

The purpose of the study is to machine the composites at lower machining time with higher accuracy without causing delamination.

Design/methodology/approach

Abrasive jet machining is the technology appropriate for machining composite materials to obtain good dimensional accuracy without causing de-lamination. The central composite design was followed in deciding the number of experiments to be carried out.

Findings

The influence of abrasive jet machining process parameters on machining time, material removal rate (MRR) and kerf characteristics were investigated. The experimental results proved the newly designed internal threaded nozzle increased MRR, thereby reducing the machining time.

Originality/value

Machining of glass fibre reinforced polymer (GFRP) is one of the challenging tasks given its non-linear and in-homogeneous properties. In this investigation, newly developed threaded and unthreaded nozzles in machining were used for making holes on the GFRP composites.

Details

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

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Article
Publication date: 7 March 2016

Ekaterina Arshavskaya

Significant effort has been made to support pre-service and novice teacher learning in the K-12 context. Less attention has been paid to promoting pre-service and novice…

Abstract

Purpose

Significant effort has been made to support pre-service and novice teacher learning in the K-12 context. Less attention has been paid to promoting pre-service and novice second language teacher learning via collaboration with peers and more expert educators at the university level. In order to facilitate this type of teacher collaboration, a mentoring project was incorporated into the existing practicum of a Master of Arts in Teaching English as a Second Language (ESL) program at a US University. The purpose of this paper is to examine the nature of the mentoring experiences of four ESL mentor-pre-service teacher pairs in the US University context.

Design/methodology/approach

For this research project, eight teachers – four mentor-pre-service teacher pairs – participated as pairs in mentoring sessions focussed on activities such as co-planning, co-teaching, and co-reflecting on teaching. Informed by a sociocultural perspective on teacher learning (Vygotsky, 1978), this study presents case studies of all four pairs in order to demonstrate the complex nature of mentoring. The data analysis focussed on the content of the teachers’ interactions and their perceptions of the mentoring experience.

Findings

The study traced the developmental trajectories of the participating teachers over one 15-week academic semester. The study uncovered some critical contradictions that the participants encountered during the mentoring experience, thus pointing to its complexity. The study also uncovered the varied nature of mentoring: whereas in one pair the mentor acted as a more expert other (Vygotsky, 1978), in another pair, the mentoring relationship was more reciprocal.

Practical implications

This study showed that pre-service teachers can develop further through mentoring. Such mentoring can help teachers gain confidence and share teaching strategies. At the same time, the study revealed certain challenges associated with introducing a mentoring project in a pre-service teacher practicum. It is recommended that program faculty as a whole read the rich dialogues produced by participating teachers engaged in relationships focussed on collaborative learning, thereby discovering a foundation for revisions that go beyond individual teaching practices to the programmatic level.

Originality/value

This study’s principal contribution to the field is that it showcases the complex nature of mentoring experiences and the ways in which they differ from each other.

Details

International Journal of Mentoring and Coaching in Education, vol. 5 no. 1
Type: Research Article
ISSN: 2046-6854

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Article
Publication date: 1 December 2005

Michael E. Drew, Tony Naughton and Madhu Veeraragavan

In this article we compare the performance of the traditional CAPM with the multi factor model of Fama and French (1996) for equities listed in the Shanghai Stock…

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Abstract

In this article we compare the performance of the traditional CAPM with the multi factor model of Fama and French (1996) for equities listed in the Shanghai Stock Exchange. We also investigate the explanatory power of idiosyncratic volatility and respond to the claim that multi factor model findings can be explained by the turn of the year effect. Our results show that firm size, book to market equity and idiosyncratic volatility are priced risk factors in addition to the theoretically well specified market factor. As far as the turn of the year effect is concerned we reject the claim that the findings are driven by seasonal factors.

Details

Managerial Finance, vol. 31 no. 12
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 20 October 2021

Jayalaxmi Anem, G. Sateeshkumar and R. Madhu

The main aim of this paper is to design a technique for improving the quality of EEG signal by removing artefacts which is obtained during acquisition. Initially…

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Abstract

Purpose

The main aim of this paper is to design a technique for improving the quality of EEG signal by removing artefacts which is obtained during acquisition. Initially, pre-processing is done on EEG signal for quality improvement. Then, by using wavelet transform (WT) feature extraction is done. The artefacts present in the EEG are removed using deep convLSTM. This deep convLSTM is trained by proposed fractional calculus based flower pollination optimisation algorithm.

Design/methodology/approach

Nowadays' EEG signals play vital role in the field of neurophysiologic research. Brain activities of human can be analysed by using EEG signals. These signals are frequently affected by noise during acquisition and other external disturbances, which lead to degrade the signal quality. Denoising of EEG signals is necessary for the effective usage of signals in any application. This paper proposes a new technique named as flower pollination fractional calculus optimisation (FPFCO) algorithm for the removal of artefacts from EEG signal through deep learning scheme. FPFCO algorithm is the integration of flower pollination optimisation and fractional calculus which takes the advantages of both the flower pollination optimisation and fractional calculus which is used to train the deep convLSTM. The existed FPO algorithm is used for solution update through global and local pollinations. In this case, the fractional calculus (FC) method attempts to include the past solution by including the second order derivative. As a result, the suggested FPFCO algorithm approaches the best solution faster than the existing flower pollination optimization (FPO) method. Initially, 5 EEG signals are contaminated by artefacts such as EMG, EOG, EEG and random noise. These contaminated EEG signals are pre-processed to remove baseline and power line noises. Further, feature extraction is done by using WT and extracted features are applied to deep convLSTM, which is trained by proposed fractional calculus based flower pollination optimisation algorithm. FPFCO is used for the effective removal of artefacts from EEG signal. The proposed technique is compared with existing techniques in terms of SNR and MSE.

Findings

The proposed technique is compared with existing techniques in terms of SNR, RMSE and MSE.

Originality/value

100%.

Details

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

Keywords

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Article
Publication date: 3 May 2021

Bharat Singh Patel, Murali Sambasivan, R. Panimalar and R. Hari Krishna

The purpose of this study is to categorize and analyse the drivers and barriers of Lean Manufacturing (LM) and subsequently, based on the structural model develop a house…

Abstract

Purpose

The purpose of this study is to categorize and analyse the drivers and barriers of Lean Manufacturing (LM) and subsequently, based on the structural model develop a house of lean management which will give an idea to the academicians and practitioners about the factors that are critical to implement lean practices in an organization.

Design/methodology/approach

A list of drivers and barriers was prepared based on the literature review and opinions from experts. Total Interpretive Structural Modelling (TISM) was utilized to build a structural hierarchy of the drivers and barriers of LM. The structural hierarchy was utilized to build the house of lean management.

Findings

Based on the hierarchy developed, the elements (drivers and barriers) of LM are classified into three groups: bottom-level, middle-level and top-level elements. To develop a house of lean management, bottom-level of elements were considered as a foundation, middle-level elements were considered as pillars and top-level elements were considered as a beam. Finally, foundation, pillars and beam of the house were used to support the roof (which is value to customers and profitability to firm).

Practical implications

The outcome of this research can assist researchers as well as practitioners to enhance the significant drivers and to reduce the impact of hazardous barriers for the better implementation of lean practices.

Originality/value

This research is a novel approach, as it visibly demonstrates both the drivers and barriers, examines the interrelationships among them in order and shows them pictorially as the house of lean management.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 2 January 2018

Anan Zhang, Cong He, Maoyi Sun, Qian Li, Hong Wei Li and Lin Yang

Noise abatement is one of the key techniques for Partial Discharge (PD) on-line measurement and monitoring. However, how to enhance the efficiency of PD signal noise…

Abstract

Purpose

Noise abatement is one of the key techniques for Partial Discharge (PD) on-line measurement and monitoring. However, how to enhance the efficiency of PD signal noise suppression is a challenging work. Hence, this study aims to improve the efficiency of PD signal noise abatement.

Design/methodology/approach

In this approach, the time–frequency characteristics of PD signal had been obtained based on fast kurtogram and S-transform time–frequency spectrum, and these characteristics were used to optimize the parameters for the signal matching over-complete dictionary. Subsequently, a self-adaptive selection of matching atoms was realized when using Matching Pursuit (MP) to analyze PD signals, which leading to seldom noise signal element was represented in sparse decomposition.

Findings

The de-noising of PD signals was achieved efficiently. Simulation and experimental results show that the proposed method has good adaptability and significant noise abatement effect compared with Empirical Mode Decomposition, Wavelet Threshold and global signal sparse decomposition of MP.

Originality/value

A self-adaptive noise abatement method was proposed to improve the efficiency of PD signal noise suppression based on the signal sparse representation and its MP algorithm, which is significant to on-line PD measurement.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 18 December 2019

Huy Duc Dang, Au Hai Thi Dam, Thuyen Thi Pham and Tra My Thi Nguyen

The purpose of this paper is twofold: to explain access to formal and informal credit in agriculture of Vietnam; and to compare the effectiveness between regular…

Abstract

Purpose

The purpose of this paper is twofold: to explain access to formal and informal credit in agriculture of Vietnam; and to compare the effectiveness between regular econometrics and machine learning techniques.

Design/methodology/approach

The multinomial logit (MNL) regression model and the random forest (RF) technique are employed for comparison purposes. To avoid heteroskedasticity, the robust covariance matrix is computed to estimate the sandwich estimator which in turn provides an asymptotic covariance matrix for biased estimators. Additionally, multicollinearity is tested among independent variables with variance inflation factors less than 3. Adequacy approach and sensitivity analysis are used to determine relevant levels of predictors. For models comparison, statistical evaluation metrics including Cohen’s κ, mean absolute error, root mean squared error and relative absolute error are employed.

Findings

The discrepancy between sensitivity analysis and adequacy approach revealed that MNL is more compatible for explaining determinants of credit participation. Due to insignificant differences in the evaluation metrics between models, the winner of choice is undetermined. Among other determinants, collateral, farmsize, income, procedure, literacy and all risk variables stand out to be critical factors when deciding borrowing schemes. While financially literate farmers tend to acquire loans from both sources, borrowing decisions against different risk sources depend on risk type and famers’ own desire to borrow.

Originality/value

Results of the MNL model are more consistent with literatures, which reinforce the role of collateral in the local credit scheme. Besides, financial literacy and farmers’ perception on different risk sources also influence how farmers’ borrowing strategies vary among sources.

Details

Agricultural Finance Review, vol. 80 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

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