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Industry 4.0 has received significant attention in today's competitive business market, necessitating a restructuring of functional domains in nearly every manufacturing organization. A comprehensive strategy to improve performance in preparation for Industry 4.0 implementation necessitates several steps, one of which is the establishment of performance outcomes (POs). The aim of this paper is to identify and rank the POs realized due to the adoption of Industry 4.0 enablers.

Based on an extensive literature review and inputs received from experts, a comprehensive list of enablers and the POs was prepared and finalized. This paper proposes a framework based on hybrid solution methodology, namely Neutrosophic Analytical Hierarchy Process (N-AHP) and Neutrosophic Combined Compromise Solution (N-CoCoSo), to rank the POs realized due to the adoption of Industry 4.0 enablers. The N-AHP methodology has been adopted to calculate the relative weights of the Industry 4.0 enablers. In comparison, the N-CoCoSo method has been adopted to rank the POs of Industry 4.0.

The proposed framework is applied to an Indian manufacturing organization to test the organization's practical applicability. Additionally, sensitivity analysis is also carried out to check the steadiness of the proposed framework. The findings of this study revealed that “Improved responsiveness to market conditions in today's competitive business environment” is the top-ranked PO of Industry 4.0, followed by “Enhanced competitiveness and better market share”, “Better product quality, through smart management of production process” and “Reduction in manufacturing waste and environmental sustainability” which could be realized due to adoption of its enablers.

This research would aid practitioners by enhancing the practitioners' capacity to understand and prioritize the various POs resulting from implementing Industry 4.0 enablers. Embracing a clear strategic plan will further assist practitioners in improving the efficiency of Industry 4.0 implementation.

Previous literature has only addressed the relationship between Industry 4.0 enablers and POs in a limited way. This paper attempts to compile a comprehensive list of Industry 4.0 enablers relevant to manufacturing organizations in order to fill this knowledge and research gap.

Several studies have examined the relationship between service quality and willingness to pay in many industries. However, this relationship has not been explored through the lens of customer perceived value and their willingness to pay for improving and sustaining water service. This study aims to examine the impact of technical and functional service quality dimensions on customer perceived value and assess the influence of customer perceived value and socio-economic factors on customers' willingness to pay for improving and sustaining the water service.

Technical service quality includes core water service such as water delivery and maintenance, while functional service quality refers to the appearance of facilities, employees’ dress, and communication. SERVQUAL questionnaire responses were collected from 333 Palestinian household customers. Cronbach’s alpha was conducted to measure internal consistency and convergent validity. Path analysis was utilized to evaluate a causal diagram by examining the relationships among the constructs.

The results showed that technical and functional service quality and relative price explain 52% of the customer perceived value variation. Additionally, the results revealed that customer perceived value, technical service quality, and relative price significantly impact the customer’s willingness to pay for improving and sustaining service. In contrast, the functional service quality and socio-economic factors have insignificant effects. These predictors explain 60% of the customer’s willingness to pay for improving and sustaining service.

The study suggests that water providers should prioritize improving and sustaining technical service quality to increase customer willingness to pay. Furthermore, they should be aware that other factors, such as employee appearance and politeness, are less influential in driving customers’ willingness to pay.

The study presents a water service improvement model that utilizes data from a developing country to assess the influence of perceived customer value, along with its dimensions, on the willingness to pay for improving and sustaining water service quality.