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Operations management.

This case can be used in a core course in production and operation management; process management and courses like design and planning of operations at the graduate level, preferably during or after the basic operations module of the course. The case focuses on the use of a process analysis that decomposes the problem into a number of easily solvable sub-problems, each of which could be distinctly analyzed and solved. The case can also be effectively utilized in elective courses on process reengineering, concurrent engineering/management, process management, capacity planning, etc. Ideally, this case can be discussed for 75 to 90 minutes.

The case describes the situation facing the operations supervisor, Sunil Mehta, of A-CAT Corp. in Vidarbha Region, Maharashtra, India. A-CAT Corp. was a mid-sized manufacturer and distributor of domestic electrical appliances, largely catering to the price-sensitive rural population. The firm operated two medium-sized facilities in one of the remote districts in Vidarbha, and these manufacturing units had been in operation since 1986. A-CAT manufactured a relatively wide range of electrical appliances for household use. Typical products from its stable included TV signal boosters, transformers, FM radio kits, electronic ballasts, battery chargers, voltage regulators, etc. The voltage regulators manufactured by A-CAT were used for many different purposes, although the focus was on its flagship product, VR500. The issue at hand for Sunil Mehta, operations supervisor at A-CAT, was to get data and act right; more often than not, this boiled down to critical information which everyone in the firm kept collecting but were too busy to use and utilize. The challenge was to select the right kind of data needed from the data-deluge that the company had in their databases. The eluding objective was to use it for the betterment of the firm. The challenge was to utilize the data that the workers and other operators kept logging in and, in the process of doing so, came up with some solutions to the problems faced on the operational front.

The case teaching and learning objectives are as following: to grasp the basics of process and process parameters; to understand the interrelationship between capacity, utilization, efficiency and productivity of a process; and to carry out process capacity analysis in assessing the performance of the firm on different metric drivers. The case also provides a very good foundation for understanding process parameters in a simple and lucid manner. To make right computations and not to use the terms and terminology in “cook book” or “strait jacketed” manner, students need to realize the parameters and their understanding changes from situation to situation.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 9: Operations and Logistics.

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

The purpose of this paper is twofold: to incorporate the symbolic relationships among the attributes of customer requirements (CRs) and engineering characteristics (ECs) as well as to factor in the values numerically to enhance the prioritization process for an improved, comprehensive quality function deployment (QFD) analysis. The aim is to develop the concept of assimilating and factoring in the often-ignored interrelationships among CRs and ECs utilizing the weighted average method for the CR and EC correlations with overall calculations.

After a brief literature review of the methods utilized, the research paper discusses the framework for the correlation triangle challenge and introduces a novel mathematical solution utilizing triangle values in conjunction with computed initial raw weights for CRs and initial priority scores for ECs. The capability and applicability of the proposed model are demonstrated with a real-life example.

Through the proposed technique, the roof and the interrelationship triangle's signs and symbols are translated into numerical values for each permutation of ECs and CRs, and then the prioritization values are processed and finalized. The proposed model successfully modifies and removes vagueness from an otherwise overlooked part of the QFD process.

The illustrated case study aptly proves that the proposed methodology yields more revealing and informative outcomes for engineers and designers, thus adding much-needed reliability to the outcome and its analysis. The validation conducted through the rank comparison endorses the premise, and the results obtained reflect the strength and accuracy of the progressive QFD as a product planning tool.

The research article proposes a fresh and unique QFD approach that solves typical procedural complications encountered in a regular QFD. Whereas the traditional methods neglect the interrelationships among CRs and ECs, this new methodology employs them in an improved, numerical way by incorporating them in quantitative analysis, which leads to judicious and improved decision-making.

The main aim of the existing study is to assess work-home interaction which is a challenge to human resource management (HRM).

The existing research is primary in nature. The sample size of the study is 285. The responses obtained from structured questionnaire. The qualitative data collected from secondary sources. For quantitative analysis various statistical tools have been applied, namely, Cronbach Alpha test, Correlation analysis and Regression analysis. The variables understudy was work environment, training opportunities, career opportunities, pay structure and technology factors.

As the recent pandemic continues to spread, all institutions should essentially remain alert and adaptable to new circumstances. HRM was essential throughout the pandemic, but now more than ever HR professionals must go above and beyond to meet the demands of organizations. The purpose of this study was to illuminate some of the most significant HR concerns that have surfaced in the aftermath of recent pandemics.

Employees' perspectives on work and life have shifted as a result of the added stress brought on by pandemic. So, businesses should provide crucial care to their workers' spirits and also HR professionals should pay close attention to their concerns and address the same thoughtfully.

The research adds to the current literature by illuminating the additional HR difficulties that have emerged in the wake of the global epidemic. More research may reveal additional significant HR difficulties, but these are a good place to start.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

Nanosized honeycomb-configured materials are used in modern technology, thermal science and chemical engineering due to their high ultra thermic relevance. This study aims to scrutinize the heat transmission features of magnetohydrodynamic (MHD) honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts.

Mass, energy and momentum preservation laws are assumed to find the mathematical model. A set of unified ordinary differential equations with nonlinear behavior is used to express the correlated partial differential equations of the established models, adopting a reasonable similarity adjustment. An approximate convergent numerical solution to these equations is evaluated by the shooting scheme with the Runge–Kutta–Fehlberg (RKF45) technique.

The impression of pertinent evolving parameters on the temperature, fluid velocity, entropy generation, skin friction coefficients and the heat transference rate is explored. Further, the significance of the irreversibility nature of heat transfer due to evolving flow parameters are evaluated. It is noted that the heat transference rate performance is improved due to the imposition of the allied magnetic field, Joule dissipation, heat absorption, squeezing and thermal buoyancy parameters. The entropy generation upsurges due to rising magnetic field strength while its intensification is declined by enhancing the porosity parameter.

The uniqueness of this research work is the numerical evaluation of MHD honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts. Furthermore, regression models are devised to forecast the correlation between the rate of thermal heat transmission and persistent flow parameters.

This study aims to investigate the impact of various audit committee (AC) characteristics on the performance of Indian commercial banks. Additionally, it also analyses the non-linear relationship of AC size and AC chairman tenure with bank performance.

A panel data approach has been used in this study. The authors have used the fixed-effect estimation technique to examine the relationship between AC characteristics and bank performance during the period 2009–2010 to 2016–2017.

The authors find that the professional financial education of the AC chairman and members positively affects bank performance. the frequency of the AC meetings and audit chair busyness bears an inverse relationship with performance. The findings are more or less consistent across the various bank performance measures and subsamples classified based on the time period and ownership of the banks.

This study provides insights to policy regulators and policymakers who are entrusted with the establishment of ACs in the banks in light of the ongoing regulatory reforms.

The study is among one of the early studies, which study the relationship between AC characteristics and bank performance in the light of recent regulatory reforms. It also extends the existing study by considering both public and private banks operating in India.

In India, many promotional policies and educational institutions have focused on entrepreneurship education (EE) for the development of future entrepreneurs. Through the survey from a region of Uttar Pradesh (UP), India, this paper aims to study the young community’s entrepreneurial attitude (EA) towards entrepreneurship.

The data was collected from a young community of various universities and colleges in different regions of UP, India to find out that “Does the EE help in developing a positive EA among young community towards entrepreneurship”. Firstly, 23 interviews have been conducted to explore about EE and EA. Further data was collected from 341 respondents through a structured questionnaire and undertaken done with the descriptive analysis: exploratory factor analysis and multiple regression method to explore the result of this study.

After the analysis, it was found that EE played an important role in developing EA of the young community towards entrepreneurship. All the coefficients in the regression model are positive, which means that all the factors of EE (awareness, enterprise knowledge and practical skills) have a positive impact on EA (affective, cognitive and behavioural).

This study provides a futuristic direction to various academic institutes and government organizations on how they prepare future entrepreneurs by inculcating EA among them. Creative minds generate innovative products and services, create jobs, alleviate poverty and maintain the GDP of a nation.

To the best of the authors’ knowledge, this is the first study to identify the relationship between EE and EA with the help of qualitative and quantitative analyses.

Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making.

Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose.

The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets.

Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return.

The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.