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The purpose of this paper is to develop optimal estimation procedures for the stress-strength reliability (SSR) parameter R = P(X > Y) of an inverse Pareto distribution (IPD).

We estimate the SSR parameter R = P(X > Y) of the IPD under the minimum risk and bounded risk point estimation problems, where X and Y are strength and stress variables, respectively. The total loss function considered is a combination of estimation error (squared error) and cost, utilizing which we minimize the associated risk in order to estimate the reliability parameter. As no fixed-sample technique can be used to solve the proposed point estimation problems, we propose some “cost and time efficient” adaptive sampling techniques (two-stage and purely sequential sampling methods) to tackle them.

We state important results based on the proposed sampling methodologies. These include estimations of the expected sample size, standard deviation (SD) and mean square error (MSE) of the terminal estimator of reliability parameters. The theoretical values of reliability parameters and the associated sample size and risk functions are well supported by exhaustive simulation analyses. The applicability of our suggested methodology is further corroborated by a real dataset based on insurance claims.

This study will be useful for scenarios where various logistical concerns are involved in the reliability analysis. The methodologies proposed in this study can reduce the number of sampling operations substantially and save time and cost to a great extent.

The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

The purpose of this paper is to implement a closed loop regulated bidirectional DC to DC converter for an application in the electric power system of more electric aircraft. To provide a consistent power supply to all of the electronic loads in an aircraft at the desired voltage level, good efficiency and desired transient and steady-state response, a smart and affordable DC to DC converter architecture in closed loop mode is being designed and implemented.

The aircraft electric power system (EPS) uses a bidirectional half-bridge DC to DC converter to facilitate the electric power flow from the primary power source – an AC generator installed on the aircraft engine’s shaft – to the load as well as from the secondary power source – a lithium ion battery – to the load. Rechargeable lithium ion batteries are used because they allow the primary power source to continue recharging them whenever the aircraft engine is running smoothly and because, in the event that the aircraft engine becomes overloaded during takeoff or turbulence, the charged secondary power source can step in and supply the load.

A novel nonsingular terminal sliding mode voltage controller based on exponential reaching law is used to keep the load voltage constant under any of the aforementioned circumstances, and its performance is contrasted with a tuned PI controller on the basis of their respective transient and steady-state responses. The former gives a faster and better transient and steady-state response as compared to the latter.

This research gives a novel control scheme for incorporating an auxiliary power source, i.e. rechargeable battery, in more electric aircraft EPS. The battery is so implemented that it can get regeneratively charged when primary power supply is capable of handling an additional load, i.e. the battery. The charging and discharging of the battery is carried out in closed loop mode to ensure constant battery terminal voltage, constant battery current and constant load voltage as per the requirement. A novel sliding mode controller is used to improve transient and steady-state response of the system.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Utilising the stimulus-organism-response (S-O-R) theoretical framework, this study investigated how destination attachment and overall satisfaction mediate the linkage between memorable tourism experiences and customer-based destination brand equity (CBDBE).

The authors study presents a model that illustrates how memorable tourism experiences can influence CBDBE by impacting tourists' attachment and overall satisfaction with a destination. The model was tested using empirical data obtained through a survey of 382 Indian domestic tourists. The data were analysed using the SPSS AMOS (Statistical Package for Social Sciences Analysis of a Moment Structures) programme.

This study validates the accuracy and effectiveness of the suggested conceptual model, demonstrating significant linkage between the variables of the study. Accordingly, it was observed that positive memorable tourism experiences have a notable impact on the development of attachment and satisfaction with the tourist destination forming strong CBDBE.

The study's primary managerial recommendation is that, to achieve sustainable competitive advantage, destination management organisations should give priority to memorable experiences and positive emotions instead than only concentrating on product-centred marketing. Second, destination managers must mould their business models based on the link between memorable tourism experiences, destination attachment, satisfaction and CBDBE.

Perhaps, the authors' research is one of the earliest to explore the relationship between tourists' overall satisfaction, attachment to a destination and memorable experiences and how they impact customer-based brand equity (CBBE) for a specific urban hill station destination.

This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

This study aims to examine the impact of the structural linkages between memorable tourism experiences, destination attachment, tourists’ satisfaction and customer-based destination brand-equity on tourists’ storytelling intentions.

The authors proposed a conceptual model that examines how memorable experiences contribute to tourists’ sense of attachment to a destination, which can lead to their willingness to share their trip stories. Using partial least square estimation, the authors analysed the conceptual model through data generated by a survey of 448 Indian domestic tourists.

Study confirms the validity and usefulness of the conceptualized model, as it shows significant correlations between the key variables. Specifically, the authors found that positive and memorable tourism experiences significantly affect tourists’ attachment and their satisfaction with destinations. As a result, tourists who form a strong customer-based destination brand equity are more likely to develop storytelling intentions.

To the best of the authors’ knowledge, current study is the earliest to explore the association between memorable tourism experiences, tourist satisfaction, attachment, customer-based brand equity and how they impact storytelling intentions of tourists.

This paper aims to examine the impact of social capital and self-efficacy in the performance of producer organizations. It also tests the mediating influence of self-efficacy in the relationship of social capital and performance of producer organizations.

The study used data from a survey of 226 members of farmer producer organizations (FPO) in India. The model was tested through structural equation modeling wherein all hypotheses were tested using “R” studio.

The findings reveal that social capital and self-efficacy play a significant role in predicting the performance of FPO. It was found that in the process of social capital influencing the performance of FPO, self-efficacy plays a significant role as a partial mediator with a mediating effect of approximately 69.28%.

The study considered only one antecedent while identifying the reasons for perceived performance of FPOs. Hence, further studies of the various other constructs such as attitude, subjective norms, etc., may be considered.

No previous work has examined the mediating role of self-efficacy in the relationship between social capital and perceived performance of FPO. This study is possibly the only one that joins two streams of thought – social capital and self-efficacy – to examine the performance of FPO.

Since the outbreak of the COVID-19 pandemic, the demand for online services has risen, with e-payment emerging as a prominent option for customers seeking faster and more convenient transactions to complete their online purchases. Nevertheless, e-payment adoption in Egypt remains a challenge that requires further investigation. Thus, this study aims to investigate the factors influencing online customers’ attitudes and intentions towards adopting e-payment for online transactions, social influence, perceived ease of use, perceived usefulness, perceived trust, structural assurance and perceived privacy/security risk.

The data were gathered from 302 customers in Egypt and structurally analysed based on partial least squares structural equation modelling (PLS-SEM).

The findings revealed that social influence, perceived usefulness and perceived trust are significant antecedents of attitude. Furthermore, perceived usefulness, perceived trust, perceived privacy/security risk and attitude directly influence behavioural intention. Structural assurance and perceived trust directly influence perceived privacy/security risk. Moreover, perceived usefulness, perceived trust and attitude were found to have several mediating roles.

This study adds new empirical evidence from a developing country regarding the adoption of e-payment among online customers. In addition, its findings can help the government, practitioners and policymakers understand how to promote customers’ positive attitudes and encourage their intentions towards using e-payment.

The findings of this study can contribute to the digital transformation strategy in Egypt by providing insights into enhancing online shoppers’ attitudes and intentions towards e-payment adoption. This, in turn, can boost Egyptian e-commerce and the country's digital economy as a whole.