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Based on positive organizational scholarship, this study aims to examine the role of faculty engagement in mediating the relationship between quality of work-life (QWL) and organizational commitment. The paper also analyses how spiritual leadership moderates the relationship between QWL and faculty engagement.

The data was collected through structured questionnaires from undergraduate and postgraduate teachers working in various business schools across major cities in India. The sample was selected through the snowball sampling technique. The sample size was 486, and analysis was done through the structural equation modelling approach using the bootstrapping method.

Findings indicate that faculty engagement mediates the relationship between QWL and organizational commitment among teachers. Furthermore, results show that educational institutions that practice spiritual leadership support higher positive psychological and emotional states of engagement.

The paper provides an integrated model of engagement, commitment and QWL through a study of mediation and moderation effects and adds value to the psychology and workplace spirituality literature. There is the future scope for further generalizations of the model in different geographical contexts to analyse the influence of other leadership styles.

Furthermore, it would help educational institutions to design QWL strategies for engaging teachers psychologically, emotionally and cognitively by accelerating employees’ positive emotions and behaviours. Finally, the paper shows implications for developing the QWL strategies to create a committed and engaged workforce through spiritual leadership.

The paper contributes to the academic literature by investigating interrelationships among variables from a positive organizational scholarship perspective. The paper would help practitioners to comprehend the importance of spiritual leadership in educational institutions.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

The purpose of this study is to explore the effects of aerospike and hemispherical aerodisks on flow characteristics and drag reduction in supersonic flow over a blunt body. Specifically, the study aims to analyze the impact of varying the length of the cylindrical rod in the aerospike (ranging from 0.5 to 2.0 times the diameter of the blunt body) and the diameter of the hemispherical disk (ranging from 0.25 to 0.75 times the blunt body diameter). CFD simulations were conducted at a supersonic Mach number of 2 and a Reynolds number of 2.79 × 10⁶.

ICEM CFD and ANSYS CFX solver were used to generate the three-dimensional flow along with its structures. The flow structure and drag coefficient were computed using Reynolds-averaged Navier–Stokes equation model. The drag reduction mechanism was also explained using the idea of dividing streamline and density contour. The performance of the aero spike length and the effect of aero disk size on the drag are investigated.

The separating shock is located in front of the blunt body, forming an effective conical shape that reduces the pressure drag acting on the blunt body. It was observed that extending the length of the spike beyond a specific critical point did not impact the flow field characteristics and had no further influence on the enhanced performance. The optimal combination of disk and spike length was determined, resulting in a substantial reduction in drag through the introduction of the aerospike and disk.

To predict the accurate results of drag and to reduce the simulation time, a hexa grid with finer mesh structure was adopted in the simulation.

The blunt nose structures are primarily employed in the design of rockets, missiles, and re-entry capsules to withstand higher aerodynamic loads and aerodynamic heating.

For the optimized size of the aero spike, aero disk is also optimized to use the benefits of both.

This paper aims to propose a two-element dual fed ultra-wideband (UWB) multiple input multiple output (MIMO) antenna system with no additional decoupling structures. The antenna operates from 3.1 to 10.6 GHz. The antenna finds its usage in on-body wearable device applications.

The antenna system measures 63.80 × 29.80 × 0.7 mm. The antenna radiating element is designed by using a modified dumbbell-shaped structure. Jean cloth material is used as substrate. The isolation improvement is achieved through spacing between two elements.

The proposed antenna has a very low mutual coupling of S₂₁ < −20 dB and impedance matching of S₁₁ < −10 dB. The radiation characteristics are stable in the antenna operating region. It provides as ECC < 0.01, diversity gain >9.9 dB. The antenna offers low average specific absorption rate (SAR) of 0.169 W/kg. The simulated and measured results are found to be in reasonable match.

The MIMO antenna is proposed for on-body communication, hence, a very thin jean cloth material is used as substrate. This negates the necessity of additional material usage in antenna design and the result range indicates good diversity performance and with a low SAR of 0.169 W/kg for on-body performance. This makes it a suitable candidate for textile antenna application.

This study was carried out to analyze the importance of consumer preference data in forecasting demand in apparel retailing.

To collect preference data, 729 hypothetical stock keeping units (SKU) were derived using a full factorial design, from a combination of six attributes and three levels each. From the hypothetical SKU's, 63 practical SKU's were selected for further analysis. Two hundred two responses were collected from a store intercept survey. Respondents' utility scores for all 63 SKUs were calculated using conjoint analysis. In estimating aggregate demand, to allow for consumer substitution and to make the SKU available when a consumer wishes to buy more than one item in the same SKU, top three highly preferred SKU's utility scores of each individual were selected and classified using a decision tree and was aggregated. A choice rule was modeled to include substitution; by applying this choice rule, aggregate demand was estimated.

The respondents' utility scores were calculated. The value of Kendall's tau is 0.88, the value of Pearson's R is 0.98 and internal predictive validity using Kendall's tau is 1.00, and this shows the high quality of data obtained. The proposed model was used to estimate the demand for 63 SKUs. The demand was estimated at 6.04 per cent for the SKU cotton, regular style, half sleeve, medium priced, private label. The proposed model for estimating demand using consumer preference data gave better estimates close to actual sales than expert opinion data. The Spearman's rank correlation between actual sales and consumer preference data is 0.338 and is significant at 5 per cent level. The Spearman's rank correlation between actual sales and expert opinion is −0.059, and there is no significant relation between expert opinion data and actual sales. Thus, consumer preference model proves to be better in estimating demand than expert opinion data.

There has been a considerable amount of work done in choice-based models. There is a lot of scope in working in deterministic models.

The proposed consumer preference-based demand estimation model can be beneficial to the apparel retailers in increasing their profit by reducing stock-out and overstocking situations. Though conjoint analysis is used in demand estimation in other industries, it is not used in apparel for demand estimations and can be greater use in its simplest form.

This research is the first one to model consumer preferences-based data to estimate demand in apparel. This research was practically tested in an apparel retail store. It is original.

Industrial drives require appropriate control systems for reliable and efficient performance. With synchronous reluctance machines (SynRMs) slowly replacing the most commonly used induction, switched reluctance and permanent magnet machines, it is essential that the drive and its control be properly selected for enhanced performance. But the major drawback of synchronous reluctance motor is the presence of high torque ripple as its design is characterized by large number of variables. The solutions to reduce torque ripple include design modifications, choice of proper power electronic inverter and PWM strategy. But little has been explored about the power electronic inverters suited for synchronous reluctance motor drive to minimize torque ripple inherently by obtaining a more sinusoidal voltage. The purpose of this paper is to elaborate on the potential multilevel inverter topologies applicable to SynRM drives used in solar pumping applications.

The most significant field-oriented control using maximum torque per ampere algorithm for maximizing the torque production is used for the control of SynRM. Simulation results carried out using Matlab/Simulink are presented to justify the choice of inverter and its control technique for SynRM.

The five-level inverter drive gives lesser core or iron losses in the SynRMin comparison to the three- and two-level inverters due to lower Id current ripple. The five-level inverter reduces the torque ripple of the SynRM significantly in comparison to the three- and two-level inverter fed SynRM drives. The phase disposition-PWM control method used for the inverter shows the least total harmonic distortion (THD) levels in output voltage compared with the other level shifted PWM techniques.

Among the available topologies, a fitting topology is proposed for use for the SynRM drive to have minimal THD, minimal current and torque ripple. Additionally, this paper presents various modulation techniques available for the selected drive system and reports on a suitable technique based on minimal THD of output voltage and hence minimal torque ripple.

The design, fabrication and experimental validation of defected microstrip structure (DMS) are proposed to address the problem of near-end crosstalk (NEXT) and far-end crosstalk (FEXT) between the microstrip transmission lines in a printed circuit board.

The proposed DMS evolved with the combination of spur line (L-shaped DMS) and U-shaped DMS topologies. This technique reduces the strength of electromagnetic coupling and suppresses crosstalk by optimizing the capacitive and inductive coupling ratio between the linked microstrip lines. The practical inductance value is much more significant in DMS than in defected ground structures (DGS), but the capacitance value remains the same.

A DMS unit is etched on the aggressor microstrip line instead of the DGS circuit. Because there is no leakage via the ground plane and the circuit size is far smaller than with DGS, the enclosure issue is disregarded. DMS structures have a larger effective inductance and are resistant to electromagnetic interference. A tightly coupled transmission line structure with minimal separation between the coupled microstrip line is designed using DMS. Further research must be conducted to improve the NEXT, FEXT and spacing between the transmission lines.

Simulation and actual measurement results show that the proposed DMS structure can effectively suppress crosstalk by analysing the S-parameters, namely, S_12, S_13 and S_14, with measured values of 1.48 dB, 20.65 dB and 21.099 dB, respectively. The data rate is measured to be 1.34 Gbps as per the eye diagram characterization. The results show that the NEXT and FEXT are reduced by approximately 20 dB in the frequency range of 1–11 GHz for mixed signals. The substantial measured results in the vector network analyser coincide with the computer simulation technology microwave studio suite simulation results.

This study investigated the antecedents influencing purchase intentions of sustainable luxury products using the stimulus-organism-response (S-O-R) model.

The data were collected from 513 participants through surveys about recent purchases of sustainable luxury products. As part of this study, the authors visited luxury retail outlets in Hyderabad, Mumbai and Chennai, and AMOS version 23 was used to analyze the data.

Consumer trust and attitude (organism) are positively influenced by utilitarian, hedonic, epistemic, social and self-image (SEI) stimuli. Consumer trust and attitude (organism) have a significant impact on sustainable luxury purchase intention (response). In addition, escapism (ESC) moderated the organism–response relationship.

As a result of the findings regarding utilitarian, hedonistic, epistemic, social and SI aspects of luxury brands, practitioners can develop sustainable marketing strategies that will promote luxury brands.

This study contributes to the existing literature by examining the moderating role of entertainment (ENT) and ESC in the S-O-R model in terms of antecedents influencing the purchase intention of sustainable luxury products. Furthermore, this new model contributes by providing a deeper understanding of sustainable luxury shoppers' intentions in India through analyzing purchase intentions for sustainable luxury products.

The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.

The sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.

The study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.

The current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.

The study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.

Existing AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.

Financial mathematics is one of the most rapidly evolving fields in today’s banking and cooperative industries. In the current study, a new fractional differentiation operator with a nonsingular kernel based on the Robotnov fractional exponential function (RFEF) is considered for the Black–Scholes model, which is the most important model in finance. For simulations, homotopy perturbation and the Laplace transform are used and the obtained solutions are expressed in terms of the generalized Mittag-Leffler function (MLF).

The homotopy perturbation method (HPM) with the help of the Laplace transform is presented here to check the behaviours of the solutions of the Black–Scholes model. HPM is well known for its accuracy and simplicity.

In this attempt, the exact solutions to a famous financial market problem, namely, the BS option pricing model, are obtained using homotopy perturbation and the LT method, where the fractional derivative is taken in a new YAC sense. We obtained solutions for each financial market problem in terms of the generalized Mittag-Leffler function.

The Black–Scholes model is presented using a new kind of operator, the Yang-Abdel-Aty-Cattani (YAC) operator. That is a new concept. The revised model is solved using a well-known semi-analytic technique, the homotopy perturbation method (HPM), with the help of the Laplace transform. Also, the obtained solutions are compared with the exact solutions to prove the effectiveness of the proposed work. The different characteristics of the solutions are investigated for different values of fractional-order derivatives.