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This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

The purpose of this study, thermal radiation and viscous dissipation impacts on double diffusive convection on peristaltic transport of Williamson nanofluid due to induced magnetic field in a tapered channel is examined. The study of propulsion system is on the rise in aerospace research. In spacecraft technology, the propulsion system uses high-temperature heat transmission governed through thermal radiation process. This study will help in assessment of chyme movement in the gastrointestinal tract and also in regulating the intensity of magnetic field of the blood flow during surgery.

The brief mathematical modelling, along with induced magnetic field, of Williamson nanofluid is given. The governing equations are reduced to dimensionless form by using appropriate transformations. Numerical technique is manipulated to solve the highly nonlinear differential equations. The roll of different variables is graphically analyzed in terms of concentration, temperature, volume fraction of nanoparticles, axial-induced magnetic field, magnetic force function, stream functions, pressure rise and pressure gradient.

The key finding from the analysis above can be summed up as follows: the temperature profile decreases and concentration profile increases due to the rising impact of thermal radiation. Brownian motion parameter has a reducing influence on nanoparticle concentration due to massive transfer of nanoparticles from a hot zone to a cool region, which causes a decrease in concentration profile· The pressure rise enhances due to rising values of thermophoresis and thermal Grashof number in retrograde pumping, free pumping and copumping region.

To the best of the authors’ knowledge, a study that integrates double-diffusion convection with thermal radiation, viscous dissipation and induced magnetic field on peristaltic flow of Williamson nanofluid with a channel that is asymmetric has not been carried out so far.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

The study presents the case of an automotive component, which illustrates practical relevance.

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

Particular attention is given to the viscous damping force parameter, stiffness parameter, rigidity parameter, and Brinkman number and plotted their graph for thermal distribution, momentum profile and concentration profile.

In the field of engineering, biologically inspired propulsion systems are getting the utmost importance. Keeping in view their developmental progress, the present study was made. The theoretical analysis explores the effect of heat and mass transfer on non-Newtonian Sisko fluid with slip effects and transverse magnetic field in symmetric compliant channel. Using low Reynolds number, so that the authors neglect inertial forces and for keeping the pressure constant during the flow, channel height is used largely as compared to the ratio of wavelength. The governing equations of fluid flow problem are solved using the perturbation analysis.

Results are considered for thickening, thinning and viscous nature of fluid models. It is found that the velocity distribution profile is boosted for increasing values of the Sisko fluid parameter and porous effect, while thermal profile is reducing for Brinkman number (viscous dissipation effects) for all cases. Moreover, shear-thicken and shear-thinning behavior of non-Newtonian Sisko fluid is also explained through the graphs.

Hear-thicken and shear-thinning behavior of non-Newtonian Sisko fluid is also explained through the graphs.

This study aims to evaluate the role of personality in digital library systems (DLS) adoption intention among Generation Z (Gen-Z) students. The study uses the unified theory of acceptance and use of technology-2 and the five-factor model to investigate personality’s influence on Gen-Z’s DLS adoption intention.

The study is a descriptive causal investigation based on primary data collected through a self-administered survey using pre-validated tools. The study uses structural equation modeling to investigate personality dimensions’ direct and moderating effect on the dependent, independent variables and their relation.

The study results indicate that personality has no significant influence on Gen-Z’s DLS adoption, suggesting the ubiquity and inevitability of technology in current times. Also, only performance expectancy had a considerable impact on DLS adoption among Gen-Z going to college – a deviation from past studies where multiple independent variables have influenced DLS adoption when examined from different technology adoption model angles.

The current research is done on Gen-Z, and thus the results are ideographic to the cohort.

The results of the study can be used to effectively design and communicate technology-enabled information solutions among the Cohort.

The results of the study help better understand the factors affecting the technology adoption intentions of Gen-Z. Such understanding can help in better design and implementation of technology-enabled solutions for the cohort, maximizing such system adoption and its effective and efficient utilization.

The study explores the impact of personality on DLS adoption intentions, hitherto unexplored. The research also focuses on Gen-Z – a cohort born in a technology-enabled world whose attitude and preferences towards technology might differ. The study’s findings will help understand the influence of personality on DLS adoption among the Gen-Z and can be used to design, promote and evaluate such systems.

The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.

In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.

The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.

This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.

The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to investigate the moderating effect of green self-identity on customers' post-service failure behavioral intentions.

A self-administered questionnaire was distributed to 327 participants who had experienced service failure while dining in green restaurants. The study draws upon the prevailing literature to examine the relationship among the constructs using structural equation modeling (SEM).

The findings of the study have confirmed that service failure has an adverse effect on customers' revisit intention toward the green restaurants. However, customers with green self-identity appear less anxious about service failure as findings indicate customers revisit green restaurant even after service failure.

The study provides a clear indication to the managers of the green restaurants that a better understanding of service failure attributions may facilitate in preventing service failure in a prompt and reasonable manner. It will not only contribute to building the brand reputation, but also ensure that customers stay with the brand for a longer duration.

The study is unique in a way that it is the first of its type to establish a relationship between service failure attributions and customer satisfaction in the emerging South Asian market, such as India in the context of green restaurants. Besides, this is the only study to use green self-identity as a moderator between the relationships of customer satisfaction and revisit intention.

This study presents a mathematical approach and model that can be useful to investigate the thermal performance of fluids with microstructures via hybrid nanoparticles in conventional fluid. It has been found from the extensive literature survey that no study has been conducted to investigate buoyancy effects on the flow of Maxwell fluid comprised of hybrid microstructures and heat generation aspects through the non-Fourier heat flux model.

Non-Fourier heat flux model and non-Newtonian stress–strain rheology with momentum and thermal relaxation phenomena are used to model the transport of heat and momentum in viscoelastic fluid over convectively heated surface. The role of suspension of mono and hybrid nanostructures on an increase in the thermal efficiency of fluid is being used as a medium for transportation of heat energy. The governing mathematical problems with thermo-physical correlations are solved via shooting method.

It is noted from the simulations that rate of heat transfer is much faster in hybrid nanofluid as compare to simple nanofluid with the increasing heat-generation coefficient. Additionally, an increment in the thermal relaxation time leads to decrement in the reduced skin friction coefficient; however, strong behavior of Nusselt number is shown when thermal relaxation time becomes larger for hybrid nanofluid as well as simple nanofluid.

According to the literature survey, no investigation has been made on buoyancy effects of Maxwell fluid flow with hybrid microstructures and heat generation aspects through non-Fourier heat flux model. The authors confirm that this work is original, and it has neither been published elsewhere nor is it currently under consideration for publication elsewhere.

Achieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.

An integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.

The results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.

A new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.