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Article
Publication date: 4 December 2017

Subrata Kumar Mondal, Sangamesh Gondegaon and Hari Kumar Voruganti

This paper proposes a novel approach to impose the Neumann boundary condition for isogeometric analysis (IGA) of Euler–Bernoulli beam with 1-D formulation. The proposed…

Abstract

Purpose

This paper proposes a novel approach to impose the Neumann boundary condition for isogeometric analysis (IGA) of Euler–Bernoulli beam with 1-D formulation. The proposed method is for only IGA in which it is difficult to handle the Neumann boundary conditions. The control points of B-spline are equivalent to nodes in finite element method. With 1-D formulation, it is not possible to accommodate multiple degrees of freedom in IGA. This case arises in the analysis of beams. The paper aims to propose a way to work around this issue in a simple way.

Design/methodology/approach

Neumann boundary conditions, which are even-order derivatives (example: double derivative) of the primary variable, are inherently satisfied in the weak form. Boundary conditions with an odd number of derivatives (example: slope) are imposed with the introduction of a new penalty matrix.

Findings

The proposed method can impose a slope boundary condition for IGA of a beam using 1-D formulation.

Originality/value

From the literature, it can be observed that the beam is formulated in 1-D by considering it as either a rotation-free element or a 2-D formulation by considering shear strain along with the normal strain. The work represents 1-D formulation of a beam while considering the slope boundary condition, which is easy and effective to formulate, compared with the slope boundary conditions reported in previous works.

Details

World Journal of Engineering, vol. 14 no. 6
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 29 September 2020

Hari Hara Krishna Kumar Viswanathan, Punniyamoorthy Murugesan, Sundar Rengasamy and Lavanya Vilvanathan

The purpose of this study is to compare the classification learning ability of our algorithm based on boosted support vector machine (B-SVM), against other classification…

Abstract

Purpose

The purpose of this study is to compare the classification learning ability of our algorithm based on boosted support vector machine (B-SVM), against other classification techniques in predicting the credit ratings of banks. The key feature of this study is the usage of an imbalanced dataset (in the response variable/rating) with a smaller number of observations (number of banks).

Design/methodology/approach

In general, datasets in banking sector are small and imbalanced too. In this study, 23 Scheduled Commercial Banks (SCBs) have been chosen (in India), and their corresponding corporate ratings have been collated from the Indian subsidiary of reputed global rating agency. The top management of the rating agency provided 12 input (quantitative) variables that are considered essential for rating a bank within India. In order to overcome the challenge of dataset being imbalanced and having small number of observations, this study uses an algorithm, namely “Modified Boosted Support Vector Machines” (MBSVMs) proposed by Punniyamoorthy Murugesan and Sundar Rengasamy. This study also compares the classification ability of the aforementioned algorithm against other classification techniques such as multi-class SVM, back propagation neural networks, multi-class linear discriminant analysis (LDA) and k-nearest neighbors (k-NN) classification, on the basis of geometric mean (GM).

Findings

The performances of each algorithm have been compared based on one metric—the geometric mean, also known as GMean (GM). This metric typically indicates the class-wise sensitivity by using the values of products. The findings of the study prove that the proposed MBSVM technique outperforms the other techniques.

Research limitations/implications

This study provides an algorithm to predict ratings of banks where the dataset is small and imbalanced. One of the limitations of this research study is that subjective factors have not been included in our model; the sole focus is on the results generated by the models (driven by quantitative parameters). In future, studies may be conducted which may include subjective parameters (proxied by relevant and quantifiable variables).

Practical implications

Various stakeholders such as investors, regulators and central banks can predict the credit ratings of banks by themselves, by inputting appropriate data to the model.

Originality/value

In the process of rating banks, the usage of an imbalanced dataset can lessen the performance of the soft-computing techniques. In order to overcome this, the authors have come up with a novel classification approach based on “MBSVMs”, which can be used as a yardstick for such imbalanced datasets. For this purpose, through primary research, 12 features have been identified that are considered essential by the credit rating agencies.

Details

Benchmarking: An International Journal, vol. 28 no. 1
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 1 December 2005

Subashini Hari, Charles Egbu and Bimal Kumar

Popularity in knowledge management has, unfortunately, not been matched by parallel empirical research on the processes, challenges and benefits of knowledge capture in…

Abstract

Purpose

Popularity in knowledge management has, unfortunately, not been matched by parallel empirical research on the processes, challenges and benefits of knowledge capture in small and medium enterprises (SMEs) in the construction industry, given the fact that 99 per cent of firms in the UK construction industry can be classified as SMEs. This paper aims to discuss the output of a research study, which is focused on knowledge capture in SMEs in construction industry. The paper also aims to present and discuss a computer‐based awareness tool on knowledge capture underpinned by Kolb's experiential learning theory.

Design/methodology/approach

The empirical study involved a total of 51 professionals from 26 SMEs in the construction industry. Grounded theory approach was adopted. Also, a content analysis was considered.

Findings

The results show that there is lack of awareness of complex issues associated with an effective knowledge capture process as well as ensuing benefits for SMEs in the construction industry. The effective implementation of knowledge capture in SMEs is partly dependent on the vision and flair of the owner/partners of the organisation. It is also determined by culture, structure, people, finance and technology, which warrants a coherent and structured approach.

Originality/value

A computer‐based awareness tool which is underpinned by Kolb's experiential learning theory.

Details

Engineering, Construction and Architectural Management, vol. 12 no. 6
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 16 November 2015

Hari Kumar and Satish Raghavendran

Fostering employee engagement in large organizations is a formidable problem that gets even more challenging in a sluggish economy, when the standard lever of monetary…

Abstract

Purpose

Fostering employee engagement in large organizations is a formidable problem that gets even more challenging in a sluggish economy, when the standard lever of monetary incentives are not a viable option for boosting employee engagement and motivation. As the organization gets larger, building emotional connectedness or bonding becomes challenging as teams expand to operate in different time zones. The overwhelming pace of work in the modern workplace can also hamper bonding. Yet emotional connectedness, when present, serves as a catalyst in driving superior performance and employee loyalty. The culture of many large organizations discourages innovation and out-of-the-box thinking because their institutional structures encourage risk aversion. Even though large organizations are best positioned to absorb the ups and downs of intelligent risk-taking, their talent processes enforce conformity, legitimize mediocrity and penalize failed attempts at innovative thinking. Performance appraisals tend to promote employees who take the path of least resistance. Managers, of course, help perpetuate this risk-averse cycle of mediocrity. Either they have been conditioned to think only in a linear fashion or organizational systems perpetuate managerial insecurity at all levels. This insecurity manifests in several ways: managers may take credit for the work performed by a subordinate; shoot down ideas a subordinate may have; or deflect opportunities that a subordinate may get. Survival in such an environment is based on being average and staying within the system. As a result, the spirit of entrepreneurship is lost. The authors designed a creative and playful contest called “Maverick” to tackle employee engagement in large organizations. The contest deeper goals include: shifting culture and behavior, talent discovery, brand building and meaningful engagement. The impact of the program on a broader organizational culture parameters were assessed through a survey. The survey results validate the impact of the program.

Design/methodology/approach

The paper develops a conceptual approach that underlies the design of the Maverick program. Surveys were deployed to determine the perceived impact of the program on the broader culture.

Findings

The secret ingredient in employee engagement is gaining the “emotional share of wallet” of employees to drive meaningful, enduring organizational change. Emotional wallet share is the sweet spot that lies at the intersection of employees’ skill sets, their aspirations and the value they generate for the organization. Proactively identifying the sweet spot empowers an organization to capture employees’ emotional wallet share to identify enablers and catalysts that can unlock motivation and performance. The survey results indicate that the Maverick contest was perceived to have a positive impact on all the identified attributes. This is a testament to the program’s success as a pivotal driver of a positive organizational culture. Further, it validates that the Maverick contest identifies several levers that leaders can use to positively influence organizational culture.

Research limitations/implications

The organizations can adapt the proposed conceptual framework in designing meaningful programs to tackle employee engagement and motivation.

Practical implications

The paper provides a meaningful framework to tackle employee engagement in large organizations. The Maverick approach is of interest to leaders of large organizations that are struggling to increase employee engagement with limited resources and that wish to foster creativity to drive innovation. The program offers a compelling way for talented professionals to meaningfully contribute to their organization that is agnostic to their position in the hierarchy. It gives employees the freedom to strive without being paralyzed by fear of failure; the chance to build their personal brand and pride; and a safe environment in which they can question received wisdom and attempt an unconventional approach to problem-solving. It creates a playful environment to bust stress, foster innovation and encourage an entrepreneurial mindset.

Originality/value

This paper offers a superior alternative to the standard gamification solutions that are routinely applied to business situations. Gamification mechanics work effectively in roles that are transactional, instead of roles that demand autonomy, mastery and a sense of purpose. Maverick program is designed while being mindful of the intrinsic motivation of the professionals.

Details

Journal of Business Strategy, vol. 36 no. 6
Type: Research Article
ISSN: 0275-6668

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Article
Publication date: 10 May 2013

Hari Kumar and Satish Raghavendran

The conventional talent management approach views human relationships as transactional, akin to the commodities that traverse through the supply chain maze. In short

Abstract

Purpose

The conventional talent management approach views human relationships as transactional, akin to the commodities that traverse through the supply chain maze. In short, there is a quid pro quo relationship between wage and services, depriving any role for other non‐monetary influences on this relationship. This naïve view of human behavior has distracted the fundamental purpose of talent management – to unlock the value of talent to organizations. Two fundamental drivers that have challenged this transactional view espoused by HR include technology and advances in neuroscience. The technological advancements have created a demand for highly skilled professionals who value autonomy and meaningful engagement. This has brought employee engagement within the focus of managers – a topic that had less significance in earlier decades. The transactional view of workplace relationships has been challenged by discoveries of human behavior by neuroscience. Human beings are wired to have emotions and perceptions, and a workplace is no exception. Reframing the issue through a simple‐yet‐powerful framework, fundamentals of talent management can be restored, paving the way for a meaningful design of organizations. This paper seeks to address these issues.

Design/methodology/approach

Using rigorous in‐depth secondary research about current talent practices, the report offers a novel framework to unlock the drivers of employee's motivation and performance. The framework serves as a diagnostic leadership tool to identify breakdowns and foster a meaningful conversation to restore the organization back to equilibrium. A holistic alternative that is agnostic to the rank of the employee, job role, and geography offers promise over the current practice of dealing with employee issues in fragmented manner.

Findings

The proposed framework helps identify the sweet‐spot that lies at the intersection of three fundamental drivers; employee's preferences on the type of work, employee's core competency and activities that are value‐adding to the organization. The sweet‐spot is the employee's emotional wallet that the organizations must proactively capture to unlock the true drivers of motivation and performance. The proposed framework serves as a diagnostic tool to meaningfully tackle breakdowns and restore organizations to equilibrium. The sweet‐spot provides the clue to design an effective organizational structure, identify the enablers and catalyst that can unlock employee motivation and performance.

Practical implications

There is a compelling need for today's organizations to refocus their energies to unlock the value of their talent to drive higher performance and motivation. Deploying the proposed framework will empower organizations to capture the “share of emotional wallet” that is critical to drive higher levels of employee engagement and motivation. Smarter organizational structures and job role can be meaningfully designed.

Social implications

The proposed framework challenges conventional talent management views of human relationships as transactional akin to the commodities that traverse through the supply chain maze. This blind spot has deprived the organizations in unlocking the drivers of employee motivation and performance. Overcoming this blind spot empowers talent management to capture the emotional share of wallet instead of trying to perfect the delivery supply chain.

Originality/value

Despite new organizational complexities, the fundamental focus for talent management is to unlock the value of its resource. Despite the pristine appeal of this fundamental tenet of talent management, it is ironic that HR has drifted its focus from its core. Reframing the issue through a simple‐yet‐powerful framework, fundamentals of talent management can be restored, paving the way for a meaningful design of organizations. This is a paradigm shift for talent management to get back to basics of what really matters to the organizations.

Details

Journal of Business Strategy, vol. 34 no. 3
Type: Research Article
ISSN: 0275-6668

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Book part
Publication date: 28 August 2019

Vincent Mosco

Abstract

Details

The Smart City in a Digital World
Type: Book
ISBN: 978-1-78769-138-4

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Article
Publication date: 8 July 2020

M. Kaladhar

The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for…

Abstract

Purpose

The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.

Design/methodology/approach

In this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.

Findings

Optimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.

Originality/value

This work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.

Details

Multidiscipline Modeling in Materials and Structures, vol. 17 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

Content available
Article
Publication date: 1 December 2005

Ronald McCaffer

Abstract

Details

Engineering, Construction and Architectural Management, vol. 12 no. 6
Type: Research Article
ISSN: 0969-9988

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Book part
Publication date: 21 August 2017

Bryant Keith Alexander

This piece is a performative keynote address delivered at the 2016 International Congress of Qualitative Inquiry, University of Illinois Champaign-Urbana.1 The keynote…

Abstract

This piece is a performative keynote address delivered at the 2016 International Congress of Qualitative Inquiry, University of Illinois Champaign-Urbana. 1 The keynote showed clips from films on education that triggered critical memories of the author’s own educational experience as teacher/scholar/administrator. The keynote was thus a performative film autocritography. The title “Black Man/White Tower” serves as a trope of tensiveness and transgression at the nexus of thick intersectionalities in higher education.

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Article
Publication date: 3 July 2020

Anjani Kumar, Gaurav Tripathi and P. K. Joshi

New varieties of paddy are constantly being developed in India in order to sustain yield gains in the face of biotic and abiotic stresses. In this study, the authors…

Abstract

Purpose

New varieties of paddy are constantly being developed in India in order to sustain yield gains in the face of biotic and abiotic stresses. In this study, the authors attempt to identify the drivers for adoption of new varieties of paddy in India; the authors also estimate the impact on yield of the adoption of new paddy varieties.

Design/methodology/approach

Survey data consisted of the reported information from approximately 20,000 paddy farmers in India. The study employs Cragg's double-hurdle model to study the probability and intensity of adoption of new varieties; we use regression discontinuity design to estimate the change in yield due to adoption of new varieties.

Findings

The authors’ findings indicate that the adoption of new varieties of paddy in India varies significantly within and between regions; further, the adoption of new varieties is affected by a number of socioeconomic and demographic factors; the authors also find that the adoption of new varieties increases yield significantly.

Research limitations/implications

These are observational data and not based on the experiments. The authors relied on farmers' memory to recall the information.

Originality/value

The authors suggest the formulation of strategic policies that can cater to the needs of regions and states that are lagging behind in the adoption of new paddy varieties.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. 11 no. 3
Type: Research Article
ISSN: 2044-0839

Keywords

1 – 10 of 173