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The purpose of the paper is to explore the impact of board size on the accounting returns and asset quality of Indian banks.

This paper uses ordinary least squares regression, robust regression and panel data methods for estimation, based on data collected for a sample of 29 Indian banks that are listed on the National Stock Exchange (NSE) and form part of the NSE-500 index over a period of eight financial years 2009-2016. The data pertaining to the board size of the sample banks is collected from the annual reports of banks, whereas the data relating to return on assets (ROA) and ratio of the gross non-performing assets to total assets and control variables (bank age and bank size) is extracted from ACE Equity database.

This paper concludes that the size of the governing board has a positive impact on the accounting returns (measured through ROA) of the Indian banks. Further, board size is observed to be insignificant in determining the asset quality of Indian banks.

This paper contributes to the literature and practitioners in a number of ways. First, to the best of the authors’ knowledge, this is the first study on the impact of board size on the accounting returns and asset quality of Indian banks. The findings of the study contribute new theoretical insights to the body of knowledge on the influence of the size of the board, which may be useful for future researchers. Second, banks may enhance their financial performance by taking cognizance of the findings of this study. Finally, equity investors may make use of the findings of this article in deciding on whether to invest in a bank’s stock/lend to the bank based on board size of the bank.

In gearbox fault diagnosis, identifying the fault type and severity simultaneously, as well as the compound fault containing multiple faults, is necessary.

To diagnose multiple faults simultaneously, this paper proposes a multichannel and multi-task convolutional neural network (MCMT-CNN) model.

Experiments were conducted on a bearing dataset containing different fault types and severities and a gearbox compound fault dataset. The experimental results show that MCMT-CNN can effectively extract features of different tasks from vibration signals, with a diagnosis accuracy of more than 97%.

Vibration signals at different positions and in different directions are taken as the MC inputs to ensure the integrity of the fault features. Fault labels are established to retain and distinguish the unique features of different tasks. In MCMT-CNN, multiple task branches can connect and share all neurons in the hidden layer, thus enabling multiple tasks to share information.

This study investigated the micro–macro link in the hospitality and tourism (H&T) sector, specifically considering whether the gender diversity, independence and board attendance rates of H&T firms' boards, alongside the moderation effect of board policies, played a significant role in tourism sector performance.

The 2011–2018 data were retrieved from the World Bank and the Thomson Reuters Eikon databases, and fixed effects panel regression was conducted.

While female directors were a significant driver of tourism sector performance in terms of tourist arrivals and tourism receipts, independent directors were effective in improving tourist arrivals only. Furthermore, moderation analyses demonstrated the inefficacy of board policies in enhancing these directors' contributions to the sector's development. Moreover, the findings revealed the inefficiency of board meetings.

Concerning the efficacy of board policies, the results suggest that firms' boards should review and revise their policies. Surprisingly, while board-diversity policies made no difference to female directors' role in the sector's development (although females were influential), board-independence policies produced unexpected results. In the absence of a board-independence policy, independent directors are influential, but if a policy exists, they are not.

Although prior firm-level studies tested whether board characteristics enhanced firms' performance in the H&T sector, they did not investigate whether board characteristics promoted tourism sector performance. Moreover, the moderating effect of board policies on boards' structures and tourism sector performance has not yet been examined.

The objective of this study is threefold–first, to develop a Regional Competitiveness Index (RCI) for measuring competitiveness of sub-national regions for India; second, to test this index for its ability to explain regional growth, which validates usage and applicability of this index; and third, to further investigate if the competitiveness of states is in turn caused by economic growth, i.e. it is tested if there is a bidirectional causality between competitiveness and regional growth.

The data of indicators used in the index are from sources available freely in public domain. The competitiveness index is constructed using equal weightage supported by principal component analysis (PCA) technique. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMMs) is used for this dynamic regression estimation.

Based on RCI score, states have been ranked and through rank analysis, the authors observe the performance status of these sub-national regions and are able to categorize them as improving, no change or deteriorating in regional competitiveness. Using the GMM estimation, the association between RCI and economic growth is found to be significant at 10% level. This shows that regional competitiveness as captured through the RCI score is able to explain regional economic growth and economic disparity among the sub-national units. Further, that RCI score is found to Granger-cause growth, while growth does not lead to better RCI scores. This establishes the usefulness of RCI as an important policy variable to compare states and provide direction for sectoral reforms.

The limitations of the study include (1) broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment, and (2) data constraints as it is a longitudinal study. The study implies that the composite index could capture differences in regional competitiveness explaining regional economic disparity and that competitiveness causes higher economic growth and not vice versa.

The RCI score can prove to be a useful indicator of economic performance of different states and can be used by national and state policymakers to compare and assess regional disparity among different states. The pillar-wise scores will be useful for in-depth study of weakness and strength of the sub-national territories.

Construction of an RCI for sub-national territories and analysis of panel data for longitudinal study of ten years is unique in the regional competitiveness literature.

Fixture layout design is concerned with immobilization of the workpiece (engine mount bracket) during machining such that the workpiece elastic deformation is reduced. The fixture holds the workpiece through the positioning of fixturing elements that causes the workpiece elastic deformation, in turn, leads to the form and dimensional errors and increased machining cost. The fixture layout has the major impact on the machining accuracy and is the function of the fixturing position. The position of the fixturing elements, key aspects, needed to be optimized to reduce the workpiece elastic deformation. The purpose of this study is to evaluate the optimized fixture layout for the machining of the engine mount bracket.

In this research work, using the finite element method (FEM), a model is developed in the MATLAB for the fixture-workpiece system so that the workpiece elastic deformation is determined. The artificial neural network (ANN) is used to develop an empirical model. The results of deformation obtained for different fixture layouts from FEM are used to train the ANN and finally the empirical model is developed. The model capable of predicting the deformation is embedded to the evolutionary optimization techniques, capable of finding local and global optima, to optimize the fixture layouts and to find the robust one.

For efficient optimization of the fixture layout parameters to obtain the least possible deformation, ant colony algorithm (ACA) and artificial bee colony algorithm (ABCA) are used and the results of deformation obtained from both the optimization techniques are compared for the best results.

A MATLAB-based FEM technique is able to provide solutions when the repeated modeling and simulations required i.e. modeling of fixture layouts (500 layouts) for every variation in the parameters requires individual modeling and simulation for the output requirement in any FEM-based software’s (ANSYS, ABACUS). This difficulty is reduced in this research. So that the MATLAB-based FEM modeling, simulation and optimization is carried out to determine the solutions for the optimized fixture layout to reach least deformation.

Many a time the practicability of the machining/mechanical operations are difficult to perform costly and time-consuming when more number of experimentations are required. To sort out the difficulties the computer-based automated solution techniques are highly required. Such kind of research over this study is presented for the readers.

A MATLAB-based FEM modeling and simulation technique is used to obtain the fixture layout optimization. ANN-based empirical model is developed for the fixture layout deformation that creates a hypothesis for the fixture layout system. ACA and ABCA are used for optimizing the fixture layout parameters and are compared for the best algorithm suited for the fixture layout system.

The purpose of this paper is to propose a general model for locating and clamping workpieces of complex geometry with two skewed holes under multiple constraints.

Numerous constraints related to application of the proposed model are discussed as prerequisite to design of fixture solution. Based on theoretical model, a fixture was designed and successfully tested in experimental investigation. Experimental results were also verified using FEM simulations.

This study showed that, opposed to conventional approach, novel solution results in significantly smaller fixture dimensions, while providing greater stability. Insertion of mandrels and supports element sub-assemblies into the workpiece holes significantly increases workpiece stiffness through an increased moment of inertia, while the internal support elements largely diminish the problem of thin wall deformation in the workpiece.

The fixture designed in this case was actually used in industrial application to accommodate a thin-walled casting of gearbox housing, where it proved to be a very stable framework. It can be used in industry without any major readjustments.

According to available literature, this work is the first successful implementation of a fixture solution in which the problem of multiple constraints is solved by attaching centering elements, support sub-assemblies, and other fixture elements to the internal workpiece walls, and then locating them in the second part of the fixture.

The purpose of this paper is to evaluate the effect of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃) nanoparticles-reinforced pure aluminium (Al) on the mechanical properties of hybrid aluminium matrix nanocomposites (HAMNCs).

The HAMNCs were fabricated via a vacuum die-assisted stir casting route by a two-step feeding method. The varying weight percentages of TiO₂ and Y₂O₃ nanoparticles were added as 2.5, 5, 7.5 and 10 Wt.%.

Scanning electron microscope images showed the homogenous dispersion of nanoparticles in Al matrix. The tensile strength by 28.97%, yield strength by 50.60%, compression strength by 104.6% and micro-hardness by 50.90% were improved in HAMNC1 when compared to the base matrix. The highest values impact strength of 36.3 J was observed for HAMNC1. The elongation % was decreased by increasing the weight percentage of the nanoparticles. HAMNC1 improved the wear resistance by 23.68%, while increasing the coefficient of friction by 14.18%. Field emission scanning electron microscope analysis of the fractured surfaces of tensile samples revealed microcracks and the debonding of nanoparticles.

The combined effect of TiO₂ and Y₂O₃ nanoparticles with pure Al on mechanical properties has been studied. The composites were fabricated with two-step feeding vacuum-assisted stir casting.

This paper aims to explore the role of retention strategies and psychological contract (PC) factors in private hospitals.

The current study is an empirical research. The study was conducted by receiving responses from a sample size of 190 respondents who participated in the Doctors and Nurses’ survey.

The study results show the relationship between PC and the retention strategies of employees in hospitals. The research found that employees try to be committed to the hospital due to the image of the hospital and career development opportunities. Creating a sense of commitment among the employees towards their job and organisation, making to feel pride in the job, creating an attitude among the employees, a willingness to advocate the benefits and advantages and satisfaction among the employee towards the job and organisation.

With a population of more than one million employees (Doctors and Nurses) in the Indian health-care sector, the sample needs to be more adequate. However, these limitations present scope for future studies on this topic bearing on the aspiration for generalisation of the findings on the entire population.

The study has strong practical implications in strengthening the relationships by identifying the factors of PC and influencing the retention strategies of health-care professionals in the hospital.

This research explores the changing dynamics of the Indian health-care sector. Health-care professionals may perceive and react differently to the retention strategies and policies of the HR system in the health-care sector and have more expectations of PC fulfilment that enhance their capability to use professional skills and resources in the realisation of their organisational goals.

In this conceptual paper, anchoring on the Hindu philosophical doctrine of karma, this study models the impact of salesperson’s karma orientation (KO) (a relatively new construct), in alleviating his/her job burnout. This study also explores the moderating impact of thought self-leadership (TSL).

This study theorizes the impact of KO on salesperson’s burnout by integrating the job demand–resource model with spirituality and TSL literatures.

Using multi-dimensional construct of KO, this study proposes several research propositions to theorize the impact of each of the four dimensions (i.e. work as selfless action, work as duty towards others, detachment from work-related rewards and equanimity under environmental influences) on three aspects of job burnout (i.e. emotional exhaustion, depersonalization and reduced personal accomplishment). Additionally, this study also theorizes the moderating impact of TSL on the above-mentioned relationships.

Organizations can adopt the karma doctrine for designing new sales jobs that provide higher meaningfulness and a greater sense of purpose to their salespeople, going beyond extrinsic rewards such as money. Higher KO among the business to business salespersons would lead them to derive higher intrinsic motivation to make karmic investments with their customers knowing that their good deeds with customers would eventually lead to good rewards for themselves, reducing their burnout, while also enhancing their well-being.

The paper makes an original theoretical contribution by theorizing the impact of Hindu philosophy of karma on salesperson’s job burnout, and hence well-being and eventual impact on organizational effectiveness.