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This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis.

This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations.

The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks.

This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector.

This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.

Three-dimensional (3D) printed parts usually have poor surface quality due to layer manufacturing’s “stair casing/stair-stepping”. So post-processing is typically needed to enhance its capabilities to be used in closed tolerance applications. This study aims to examine abrasive flow finishing for 3D printed polylactic acid (PLA) parts.

A new eco-friendly abrasive flow machining media (EFAFM) was developed, using paper pulp as a base material, waste vegetable oil as a liquid synthesizer and natural additives such as glycine to finish 3D printed parts. Characterization of the media was conducted through thermogravimetric analysis and Fourier transform infrared spectroscopy. PLA crescent prism parts were produced via fused deposition modelling (FDM) and finished using AFM, with experiments designed using central composite design (CCD). The impact of process parameters, including media viscosity, extrusion pressure, layer thickness and finishing time, on percentage improvement in surface roughness (%ΔRa) and material removal rate were analysed. Artificial neural network (ANN) and improved grey wolf optimizer (IGWO) were used for data modelling and optimization, respectively.

The abrasive media developed was effective for finishing FDM printed parts using AFM, with SEM images and 3D surface profile showing a significant improvement in surface topography. Optimal solutions were obtained using the ANN-IGWO approach. EFAFM was found to be a promising method for improving finishing quality on FDM 3D printed parts.

The present study is focused on finishing FDM printed crescent prism parts using AFM. Future research may be done on more complex shapes and could explore the impact of different materials, such as thermoplastics and composites for different applications. Also, implication of other techniques, such as chemical vapour smoothing, mechanical polishing may be explored.

In the biomedical field, the use of 3D printing has revolutionized the way in which medical devices, implants and prosthetics are designed and manufactured. The biodegradable and biocompatible properties of PLA make it an ideal material for use in biomedical applications, such as the fabrication of surgical guides, dental models and tissue engineering scaffolds. The ability to finish PLA 3D printed parts using AFM can improve their biocompatibility, making them more suitable for use in the human body. The improved surface quality of 3D printed parts can also facilitate their sterilization, which is critical in the biomedical field.

The use of eco-friendly abrasive flow finishing for 3D printed parts can have a positive impact on the environment by reducing waste and promoting sustainable manufacturing practices. Additionally, it can improve the quality and functionality of 3D printed products, leading to better performance and longer lifespans. This can have broader economic and societal benefits.

This AFM media constituents are paper pulp, waste vegetable oil, silicon carbide as abrasive and the mixture of “Aloe Barbadensis Mill” – “Cyamopsis Tetragonoloba” powder and glycine. This media was then used to finish 3D printed PLA crescent prism parts. The study also used an IGWO to optimize experimental data that had been modelled using an ANN.

Organizations today strive to differentiate themselves from others with the help of various tools. Aaker’s brand personality model is one of them. It comprises five components namely, sincerity, excitement, sophistication, competence and ruggedness. This model has been tested and supported by various scholars in the past. Similarly, it also attracted a lot of criticism especially in terms of generalizability across countries and cultures. The purpose of this paper is twofold: first, to study Aaker’s model from an Islamic perspective; second, considering the dearth of brand personality knowledge in the services sector, to develop Islamic Banks’ Brand Personality (IBBP) model.

To propose IBBP model, traits in Aaker’s model have been investigated in the light of selected Quranic verses and sayings of Prophet Muhammad (ahadith). Later on, content validation was conducted as a pilot study with experts from the relevant fields.

Findings exhibit that Quran and hadith clearly elaborate and support majority dimensions of the existing model. Importantly, three new dimensions, namely, trustworthiness, justice and Shariah compliance, were added to develop a comprehensive IBBP model. Once the dimensions of IBBP model were finalized, the underlying items were content validated from 12 experts. Most of the items were approved; some were recommended for amendments and a few items were eliminated.

This research contributes to the branding as well as bank marketing literature as it is the first Islamic banks’ brand personality framework. With the help of IBBP model, Islamic banks can create a better brand image, use advertising strategies effectively and ultimately retain existing and attract more potential customers.

This research elaborates the personality traits of Muslim consumer market. Following IBBP model, financial needs of Muslim consumer market can be catered effectively.

The IBBP model being first of its kind is significant for Islamic banking industry as it reflects dimensions that are supported by the Quran and hadith, and therefore suits Muslim customer market.

The purpose of the current study is to examine the implications of the implementation of Goods and Service Tax (GST) on the revenue efficiency of the sub-national governments in India. Furthermore, the study aims to compare the revenue efficiency of the Indian states for the pre-GST and post-GST periods in India.

The study has used the annual revenue of value-added tax (VAT)/GST of the Indian states for the period ranging from 2012–2013 to 2020–2021 for the pre- and post-GST periods. The empirical results are based on the panel regression model for examining the implications of GST adoption on the Indian states.

The analysis shows that the implementation of GST in India has negatively impacted the revenue efficiency of the Indian states. Moreover, the results affirm that the contribution of the service sector to the state's Net State Domestic Product (NSDP), credit-deposit ratio (CDR) and outstanding net bank credit (ONBC) ratio of schedule commercial banks (SCBs) positively and states' dependency on central transfers (DCT) negatively impact the tax revenue efforts of the state governments. Furthermore, the GST adoption has a greater impact on the revenue efficiency of the minor states in comparison to major states which may widen the inter-state disparity gap as GST revenue constitutes a major share in the Own Tax Revenue (OTR) of the Indian states in aggregate.

The current study will act as a guide for government, policymakers and for the sitting of the fifteenth finance commission in India for future policy formulation on GST and compensation to the Indian states. Similarly, this study can be used as a base for conducting future studies on the implications of GST at the national, sub-national, and international levels.

Previous studies on the implications of GST are theoretical and conceptual. There is hardly any study at the national or sub-national level that has focused on the implications of GST on the revenue efficiency of the Indian states.

Taking an evidence from social exchange theory, this research examines the mediating role of affective commitment in the correlation between internal branding, employee engagement and job satisfaction. The moderating role of work environment on the link between internal branding and affective commitment is also studied in this research.

The data were collected by using well-structured research measures from 215 employees working in the BPO sector of India (Punjab and Chandigarh). The hypotheses were developed, and the conceptual model was validated by applying structural equation modeling. The data were analyzed by using two statistical packages, namely SPSS and AMOS.

The findings suggest that internal branding has a significant positive relationship with employee engagement, job satisfaction and affective commitment. The mediating effect of affective commitment on the relationship between internal branding and employee engagement was full, whereas on the relationship between internal branding and job satisfaction, it was partial. Work environment also moderated the relationship of internal branding with affective commitment.

The current study offers significant lessons to management thinkers, human resource (HR), organizational branding and marketing manager. However, BPO sector should be aware about the critical role played by internal branding to enhance affective commitment, employee engagement and job satisfaction of the employees. The role of affective commitment is also taken into account to study the effect of internal branding on employee engagement and employee's job satisfaction. For itself, internal branding cannot be considered as in isolation and is doubtful to be efficacious if the work environment is not encouraging to an employee as well as to the brand values.

This study offers significant lessons to management thinkers, HR, organizational branding and marketing manager. However, BPO sector should be aware about the critical role played by internal branding to enhance employee engagement, job satisfaction and affective commitment of the employees. An important role of affective commitment is also taken into account to study the effect of internal branding on employee engagement and employee's job satisfaction. For itself, internal branding cannot be considered as in isolation and is doubtful to be efficacious if employees are not provided an encouraging work environment.

Existing researches on internal branding are theoretical in nature and overlook the empirical impact of internal branding on employee engagement, job satisfaction and affective commitment from the BPO employees' perspective. The study also offers an empirical examination of potential mediator and moderator for internal branding.

This study aims to synthesize the existing literature with insights gained from interviews conducted with regulatory experts. The objective is to analyse the challenges associated with incorporating cryptocurrencies into regulatory frameworks and to explore constraints in the regulatory institutionalization of cryptocurrencies.

The study methodology consists of two steps. The first step is to identify regulatory constraints in the literature review and in the next step, interviews are conducted with officials of the State Bank of Pakistan (SBP). The study used a qualitative case study methodology, in which a single case (regulatory constraint) was selected as a unit of analysis.

The findings show that lack of traceability, legal status, lack of governmental control due to decentralization, difficulty enforcing laws, volatility, lack of skills with regulators and difficulty integrating cryptocurrencies into the current financial system are the main obstacles to the introduction of a regulatory framework. Thus, on a broader conceptual level, the findings can be grouped into opportunism, lack of strategic capability and fragmented global laws.

This study could inform global cryptocurrency regulation discussions, sharing a developing country’s views on balancing the government, central banks, the financial sector and public interests. This could guide countries to consider cryptocurrency adoption in similar situations. This could affect the cryptocurrency market, impacting demand, supply and investor trust in Pakistan.

The study has implications for policy making officials. The research aims to offer valuable insights to the SBP and other regulatory authorities, helping them identify potential risks and create an effective regulatory framework for cryptocurrencies.

The study has implications for society in knowing about the volatile nature of cryptos and anonymity of their issuers, which poses regulatory constraints. This then implies its harmfullness to its traders and the huge losses that may arise from their trading due to its volatile nature.

This study contributes to the literature on the constraints, responsibilities and consultation framework of cryptocurrency regulations.

Automatic DNA-binding protein (DNA-BP) classification is now an essential proteomic technology. Unfortunately, many systems reported in the literature are tested on only one or two datasets/tasks. The purpose of this study is to create the most optimal and universal system for DNA-BP classification, one that performs competitively across several DNA-BP classification tasks.

Efficient DNA-BP classifier systems require the discovery of powerful protein representations and feature extraction methods. Experiments were performed that combined and compared descriptors extracted from state-of-the-art matrix/image protein representations. These descriptors were trained on separate support vector machines (SVMs) and evaluated. Convolutional neural networks with different parameter settings were fine-tuned on two matrix representations of proteins. Decisions were fused with the SVMs using the weighted sum rule and evaluated to experimentally derive the most powerful general-purpose DNA-BP classifier system.

The best ensemble proposed here produced comparable, if not superior, classification results on a broad and fair comparison with the literature across four different datasets representing a variety of DNA-BP classification tasks, thereby demonstrating both the power and generalizability of the proposed system.

Most DNA-BP methods proposed in the literature are only validated on one (rarely two) datasets/tasks. In this work, the authors report the performance of our general-purpose DNA-BP system on four datasets representing different DNA-BP classification tasks. The excellent results of the proposed best classifier system demonstrate the power of the proposed approach. These results can now be used for baseline comparisons by other researchers in the field.