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Consumers by and large today look for economic growth and benefits without compromising on socio-environmental well-being. Having said that, it is imperative to note that consumers' consciousness may not essentially lead to sustainable purchases. This chapter aims to examine the role of both sustainable purchase intention and post-purchase dissonance in the relationship between consumers' sustainability consciousness and consumers' evangelism. With the increased role of social media pervading our lives, trusted sources' recommendations play a significant role in co-creating products. Thus, research on consumers' evangelism (especially sustainability-conscious consumers) would help marketers develop successful strategies. This study expands to the extant literature on sustainability-conscious consumers vis-a-vis consumer evangelism. We collected responses from 227 respondents to examine hypotheses, by means of structural equation modelling (SEM). The study indicates sustainable purchase intention does mediate the relationship between sustainability-conscious consumers and consumer evangelism. On the other hand, we also note that post-purchase dissonance is not a significant moderating construct between sustainability-conscious consumers and consumer evangelism.

This study aims to implement an improved version of the Chimp algorithm (IChimp) for load frequency control (LFC) of power system.

This work was adopted by IChimp to optimize proportional integral derivative (PID) controller parameters used for the LFC of a two area interconnected thermal system.

The supremacy of proposed IChimp tuned PID controller over Chimp optimization, direct synthesis-based PID controller, internal model controller tuned PID controller and recent algorithm based PID controller was demonstrated.

IChimp has good convergence and better search ability. The IChimp optimized PID controller is the proposed controlling method, which ensured better performance in terms of converging behaviour, optimizing controller gains and steady-state response.

The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control.

For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system.

The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value.

Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

The current research prioritizes the dimensions of a higher-order customer engagement construct in the tourism destination context in order of their relative importance as perceived by tourists to provide meaningful insights to the tourism industry player.

Data was collected from 429 tourists' from selected tourist destinations. Exploratory factor analysis (EFA) was used for data analysis using SPSS. The scale items were prioritized through hybrid evidence-based modeling using the RIDIT-GRA (Relative to an Identified Distribution and Grey Relational Analysis, respectively) approach.

The prioritization of customer engagement scale items is done through RIDIT analysis and is verified through GRA. The rankings of two independent methodologies show a 93% correlation, thereby ensuring the ranking's robustness.

Prioritizing customer engagement scale items may assist destination managers in strategy formulation to ensure tourists' high-level loyalty transcending purchase. The findings help develop key response areas (KRA's) for effective destination brand management.

Such precedence analysis of customer engagement scale items has not been done in the tourism studies yet. Also, the present study verified the results by incorporating two independent methodologies, thus providing more valid results.

Over the years, despite the best efforts to evaluate service quality through multiple techniques, the connotation between service deliverance and consumer expectation remains sporadic. In the quest to quantify service quality from an innovative perspective, the current study has leveraged consumer-perceived experiences to unveil the novel intricacies of healthcare quality.

Anchoring on the dimensions of patient experience (PX), field data were collected from 244 patients at different private hospitals operating across India. Further, this study incorporated a fuzzy analytic hierarchy process (F-AHP) to evaluate consumer preferences and prioritised the dimensions of PX in three categories of Indian hospitals, namely nursing homes (NHs), mid-tier corporate hospitals (MCHs) and top-tier corporate hospitals (TCHs).

The results establish a performance ranking by demonstrating that MCHs outperform the rest alternatives on the grounds of perceived experiences. Tukey's honestly significance difference (HSD) test was executed to confirm the heterogeneity among the participants' preferences across three different hospital categories. The results reveal that for most of the alternatives, the mean scores of the criterion were statistically significantly different.

In healthcare studies, PX dawned as an entity with an ability to propel healthcare quality in a better way than the classical techniques did. The study's findings present a comprehensive picture of a care delivery system by identifying relatively significant dimensions of PX, hence improving the quality quotients by adjusting healthcare offerings in alignment with consumer expectations and organisational strategies.

By examining the impact of the day of the week during the COVID-19 pandemic and the subsequent economic recession, it is possible to provide insights into market behaviour during volatile times that can be furnished to investors and policymakers for informed decisions.

This study investigates the day-of-the-week effect on the Colombo Stock Exchange (CSE), with particular emphasis on the variations in this effect during the COVID-19 pandemic and the subsequent economic crisis.

The study applies the Exponential Generalised Autoregressive Conditional Heteroskedasticity (EGARCH) model, allowing for the evaluation of asymmetric responses to positive and negative shocks. The data span from January 2006 to December 2022 and are segmented into different periods: the entire sample, war and post-war periods, the COVID-19 pandemic and the economic crisis period, each reflecting distinct market conditions.

The study uncovers a significant day-of-the-week effect on the CSE. Mondays and Tuesdays typically show a negative effect, while Thursdays and Fridays display a positive impact. However, this pattern shifts notably during the COVID-19 pandemic, with all weekdays exhibiting significant positive impact, and varies further across different waves of the pandemic. The economic crisis period also shows unique weekday effects, particularly before and after an important political event.