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The fourth industrial revolution has necessitated the integration of sustainability and customer centricity into modern manufacturing systems, thereby emphasising their significance. However, the production process itself is characterised by inherent uncertainties. Hence, this paper primarily focuses on the multi-objective flexible job shop rescheduling problem with uncertain processing time and new job insertions. Two fuzzy constraints are incorporated: fuzzy processing time and fuzzy due date, which aim to model the uncertainty of processing time and ensure flexibility in meeting deadlines. The objective function aims to optimise both customer satisfaction and energy consumption. To address two types of rescheduling problems: time delay caused by fuzzy features and new job insertions, this paper is dedicated to providing a hybrid adaptative rescheduling strategy that combines a satisfaction-driven policy with two specific rescheduling methods. Moreover, an enhanced version of the non-dominated sorting genetic algorithm II (NSGA-II) is developed, incorporating population initialisation rules and multiple genetic operators to obtain solutions of superior quality. Experimental studies have demonstrated the impact of time delay caused by fuzzy features on customer satisfaction. The proposed hybrid adaptative rescheduling strategy and methods exhibit significant improvements in rescheduling plan performance under uncertain environments. [ABSTRACT FROM AUTHOR]

Evoking simplicity in marketing communications has become popular among marketing practitioners, but little is known about its effects on consumers and firms. The current work focuses on consumers' perceptions of the simplicity or complexity of brands and a previously overlooked consequence of those perceptions. Results from six experiments and analysis of a proprietary customer satisfaction dataset from Consumer Reports (N = 147,600) show that when consumers think brands are simple, they judge them to be less likely to experience product or service failures. Although these lower risk judgments could be positive for brands, they can also lead consumers to punish simpler brands more in the event of failures. Results also suggest that consumers' simplicity/complexity perceptions reflect the dimensionality of their mental representations of brands, and the relationship between simplicity and lower risk is attenuated when additional brand dimensionality is framed in terms of redundancy. The findings cast doubt on the degree to which evoking simplicity is a uniformly positive marketing strategy and encourage practitioners to more thoughtfully consider simplicity's implications for consumer and firm welfare. [ABSTRACT FROM AUTHOR]

Key driver analysis (statistically inferred importance analysis) is commonly implemented to understand what customer satisfaction attributes are most important in driving overall customer satisfaction. Building on prior research, this article suggests that dominance analysis and relative weight analysis are the most appropriate statistical techniques for conducting key driver analysis, yet relative weight analysis is the more feasible choice. A process is put forth so that research practitioners can conduct key driver analysis with relative weight analysis implementing a two-step approach. The two-step approach should be used when the key driver analysis contains a large number of attributes, which are theoretically redundant and highly correlated. [ABSTRACT FROM AUTHOR]

With the service level playing an increasingly essential role in the service-oriented manufacturing (SOM) supply chain, the distribution network design can be heavily affected by the customer behaviour based on their satisfaction of services. In this paper, we consider the service level for service time and delivery quantity separately. A novel mixed integer non-linear programming model is proposed to design the multi-period distribution network from a fourth-party logistics (4PL) perspective. The customer satisfaction based on prospect theory is maximised while considering the investment budget and the service level. A scenario-based linear reformulation is proposed to find the optimal solution when the problem scale is small. For a large-scale problem, we propose an individual-driven Q-learning based memetic particle swarm optimisation algorithm. Numerical experiments are conducted to demonstrate the effectiveness and efficiency of the proposed algorithm. Furthermore, the impact of service modes, different customer behaviour, and customer satisfaction evaluation periods on distribution network is investigated. We find that the length of evaluation periods leads to differences in customer satisfaction due to different perceptions of 'small loss' and 'big gain' by boundedly rational customers. [ABSTRACT FROM AUTHOR]

ChatGPT and generative artificial intelligence (Gen-AI) are transforming firms and supply chains. However, the empirical literature reporting the benefits, challenges, and outlook of these nascent technologies in operations and supply chain management (OSCM) is limited. This study surveys current projects and perceptions of these technologies in US (n = 119) and UK (n = 181) supply chains. We found that projects range from proof-of-concept to full implementation, with a main focus on operational gains, such as improved customer satisfaction, cost minimisation, and process efficiencies. The main challenges concern data, technological and organisational issues. Expected benefits are dominated by cost savings and enhanced customer experience, but also include increased automation and sustainability. Industries were found to cluster around six groups according to perceived benefits and implementation challenges. Our findings contribute to the emerging literature on Gen-AI use in OSCM, and to management practice by mapping the benefits, challenges, outlook, and maturity level of Gen-AI projects in supply chains. [ABSTRACT FROM AUTHOR]

For more than 20 years, the consumer–brand relationship (CBR) subfield has flourished with scores of constructs being employed. We provide an epistemological examination of its 14 most commonly measured relational constructs (e.g. Brand Love, Self-Brand Connection) collected from 767 research articles, reflecting 1,753 scales and approximately 9,200 items. We demonstrate that constructs overlap an average of 43% across all journals and 21% in top journals due to assessing highly similar or synonymous ideas (i.e. jangle). We use a combination of text and cluster analyses to show that measures of allegedly the same construct are polysemic, having an average of 5.3 different meanings (i.e. jingle). The results document in the CBR subfield the types of measurement inconsistencies and ambiguities that have sown confusion and frustration in other academic fields. We discuss the roots of these problems and offer recommendations aimed at helping scholars to improve measurement practices and to limit the presence of jingle and jangle in the CBR subfield. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is increasingly embedded into service firms' operations. However, production systems and operations management scholars have not yet examined if AI-empowered service operations are positively judged by service customers. To bridge this gap, this study draws on the three-factor theory of customer satisfaction applied to online review data, to capture the effect of AI-empowered service operations on overall customer satisfaction, operationalised by means of online review ratings. Based on text analytics techniques applied to a sample of more than 50,000 TripAdvisor ORs covering 35 international hotels in Asia and America, we develop a penalty–reward contrast analysis. The findings reveal that the effects of customer interaction with mechanical AI on customer satisfaction with service operations are asymmetric: positive customer interaction with mechanical AI positively and significantly influences overall customer satisfaction with AI-empowered service operations, whereas negative customer interaction with mechanical AI does not significantly alter customer satisfaction. Taken together, these findings suggest that mechanical AI constitutes a key element of resilient AI-empowered service operations. [ABSTRACT FROM AUTHOR]

With heightened uncertainties and risks in the fluctuating business environment, existing studies have concentrated on elucidating how service organizations leverage human resource practices to adapt to and survive such unforeseen and disruptive threats. However, how such practices could serve the strategic objective of cultivating a sustainably thriving workforce across different situations is not well understood. Thriving is a core transitional state that fosters positive behaviors, such as creative customer‐related problem‐solving. Applying social information processing theory, we propose and test a model by exploring how organizations that engage in thriving‐oriented human resource management (HRM) encourage employees to take responsibility and promote constructive change, thereby activating their creative problem‐solving behaviors. Specifically, we theorize and develop measures to promote thriving‐oriented HRM in Study 1. In Study 2, we collected multisource and multi‐wave data from 296 frontline service employees and 45 supervisors in China. Our findings reveal that thriving‐oriented HRM is positively related to felt responsibility for change, which ultimately encourages creative problem‐solving. We also show that the threat imposed by a crisis, that is, the COVID‐19 pandemic, strengthens the positive relationship between thriving‐oriented HRM and felt responsibility for change. Our study contributes to the HRM literature, especially on thriving‐oriented HRM and employee perception, and has practical implications for service organizations in the uncertain context. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the determinants of sport consumers' mobile ticketing adoption by the technology readiness constructs and quality–satisfaction–behavioral intentions framework. A total of 295 participants were included in the analysis. Data analysis was performed using structural equation modeling and PROCESS macro. A content analysis was conducted to provide further insight into the proposed model using open-ended responses. The findings indicate that consumers' technology readiness alone was not a positive driver of mobile ticketing but suggest a role for technology readiness in promoting mobile ticketing, combined with service quality, satisfaction, and online ticket purchasing. The importance and originality of this study are that it confirms the sport context as a unique and effective vehicle in advancing existing knowledge of consumers' ticket consumption behavior via self-service technology across various disciplines. Also, the findings can be used to set out recommendations for policy or practice aimed at facilitating and sustaining mobile ticketing consumption. [ABSTRACT FROM AUTHOR]

For automobile manufacturers, reducing vehicle interior noise is essential for increasing customer satisfaction and vehicle quality. Windshield wipers are one of the major components that generate such noises, and faulty wipers could negatively affect passengers' psychological and physiological perceptions while driving. Thus, identifying faulty wipers during the manufacturing process would improve the driving experience and vehicle and road safety as well as reduce driver distraction. However, the existing windshield wiper noise-detection process is entirely manual, relies upon human subjectivity, and is time-consuming. Accordingly, this paper develops a novel automated windshield wiper fault-detection system. First, a novel binarization approach is used to effectively binarize the transformed spectrograms of sound signals from windshield wiper operation to segment nAoisy regions. Then, a new matrix-factorisation approach called orthogonal binary singular value decomposition is proposed to decompose binarized mel spectrograms into uncorrelated binary eigenimages to extract meaningful features and identify faulty wipers. Then, the $ k $ k -nearest neighbour classifier is utilised to classify the extracted features into normal or faulty windshield wipers. Finally, to demonstrate the effectiveness of the proposed system, it was validated on real-life windshield wiper reversal and squeal noise datasets, where it outperformed existing methods and achieved accuracies of 95% and 94%, respectively. [ABSTRACT FROM AUTHOR]

Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more seamless and comprehensive implementation of the knowledge-based decision-making process. New models that provide a competitive edge must be created by combining the Lean paradigm with the new technologies of Industry 4.0. This paper presents novel computer-based vision models for automated detection and classification of damaged packages from intact packages. In high-volume production environments, the package manual inspection process through the human eye consumes inordinate amounts of time poring over physical packages. Our proposed three different computer-based vision approaches detect damaged packages to prevent them from moving to shipping operations that would otherwise incur waste in the form of wasted operating hours, wasted resources and lost customer satisfaction. The proposed approaches were carried out on a data set consisting of package images and achieved high precision, accuracy, and recall values during the training and validation stage, with the resultant trained YOLO v7 model. [ABSTRACT FROM AUTHOR]

Net Promoter Score (NPS) is one of the most popular customer feedback metrics (CFMs) with benefits and limitations. One limitation is that prior research has shown that NPS is not better in explaining outcome variables such as sales growth or churn than other CFMs. Most prior research, however, has not considered combinations of CFMs, CFMs related to the antecedents of customer satisfaction, and CFMs with affective components. Therefore, we argue that NPS should be supplemented with other CFMs, e.g., emotions. In an empirical investigation in the mobile phone industry, we choose Net Emotional Value (NEV) to measure of emotions. We show that a combination of NPS and NEV leads to a better explanation of two out of three outcome variables compared to using NPS only or NEV only. We also illustrate how emotional profiles and driver analyses can be used to identify the most relevant emotions of Detractors, Passives, and Promoters and conclude with limitations and potential for further research. [ABSTRACT FROM AUTHOR]

The Net Promoter Score (NPS) is a popular metric for measuring customer loyalty and is claimed by Reichheld to predict a company's growth. However, various academic studies provide controversial results regarding its reliability and prediction powers. This study analyzes how respondents answer the likelihood-to-recommend (LTR) question in different predescribed and validated situations. One thousand participants are presented with situation descriptions that consist of previous and recent experiences with a bank and are asked how they would respond to the LTR question after such an experience. The results indicate that respondents do not always give a high score for good experiences, and a low score for bad experiences. However, with a high number of respondents, the different answering approaches even out, and the NPS results are higher for good than for bad experiences. Additionally, we notice that whereas negative experiences are evaluated as low by all respondents, Generation X and Boomers tend to give lower scores for neutral and positive experiences. Those with lower income and basic education give lower scores for neutral experiences. The recent experience influences the customer's likelihood of recommending more than the previous experiences with the company. [ABSTRACT FROM AUTHOR]

Although the lay appeal of the Net Promoter Score (NPS) is undeniable, scholars have noted concerns over its use based on conceptual and empirical grounds. We address these concerns through an examination of three research questions: (1) To what extent do NPS responses correspond to actual word-of-mouth behaviors? (2) Do NPS responses exhibit measurement invariance across key demographic groupings? (3) How well does NPS perform (as opposed to customer satisfaction scores) as a predictor of financial performance? Study results show that NPS scores correspond to reported word-of-mouth exposure for most, but not all, product categories; NPS responses are invariant across demographic groupings; and that when examined separately, both customer satisfaction and NPS are significant predictors of differences in financial performance, but customer satisfaction explains slightly more variance. We discuss the managerial and theoretical implications arising from these results. [ABSTRACT FROM AUTHOR]

Despite scholarly critiques, use of the Net Promoter Score (NPS®) continues to grow in popularity among firms. Even researchers who criticize NPS recognize its potential for predicting desirable customer behaviors and revenue growth. However, a firm's goal in measuring NPS is not to simply assess it, but to be empowered to improve that score. This goal begs an important question: Does a "net promoter" study provide the insights that a firm needs to improve their NPS? The critical, but untested, assumption in NPS use is that the insights gained from open-ended customer comments in a net promoter study can be used to set improvement priorities that will increase future NPS likely-to-recommend ratings. Through two distinct studies, one in a business-to-business context with auto dealership decision-makers and one in a business-to-consumer context with vehicle repair customers, we investigate this assumption. Our results reveal that the critical untested assumption of a net promoter study is questionable. The convergence is low to moderate between open-ended priorities from a net promoter study and predictors of the standard 'likely-to-recommend' NPS question. We also find that the convergence between customers' open-ended priorities and their stated and derived priorities from closed-ended responses is higher for NPS detractors and passives than promoters, but it is still only moderate. The strength of this convergence of priorities is also impacted by the wording of the questions used to elicit customers' open-ended priorities. Firms using open-ended comments to set priorities should ask customers, especially detractors, to identify areas for improvement. In addition, they should supplement open-ended customer feedback with closed-ended questions to get customers' performance ratings in relation to their specific needs. [ABSTRACT FROM AUTHOR]

The Net Promoter Score (NPS) is a popular management tool that is used in a variety of ways by firms, not-for-profits, and government. This study firstly provides an overview of the various ways in which the NPS is used. It then canvasses four concerns raised by researchers, authors and commentators about the NPS. These relate to (1) its presumed link to business growth, (2) the assumption that low NPS scores indicate negative word of mouth, (3) the weak association between stated likelihood to recommend and actual recommending, and (4) the claim that NPS is a superior metric to customer satisfaction. The evidence pertaining to those concerns is examined. The study then discusses another problem with the NPS that many practitioners are aware of, but has not been studied. The problem is that the counting method used to calculate the NPS introduces additional variation in scores compared to mean average likelihood-to-recommend scores. This additional variation occurs both across brands in a study, as well as for the same brand over survey waves. This variation is likely to be difficult for market research providers, or those who commission NPS work, to explain. The study concludes with alternative courses of action for NPS users. [ABSTRACT FROM AUTHOR]

Post-sale customer care (PSCC) outsourcing is an effective supply chain strategy to reduce costs, but traditional outsourcing methods cannot ensure consumers' belief in PSCC quality, harming the firms' competitive strategy. To ensure consumer satisfaction through transparency, this article examines evolving supply chain strategies of leveraging blockchain to outsource PSCC operations of competing manufacturers to third-party agents. Based on consumers' beliefs and blockchain adoption cost, manufacturers have two choices; to outsource the PSCC operations with or without blockchain, resulting in multiple outsourcing strategies. Results show that the consumers' belief in one manufacturer's outsourcing strategy has detrimental effects on the stance of another manufacturer. Moreover, the blockchain cost and consumers' beliefs dictate the manufacturers' strategies for PSCC outsourcing, resulting in a 'quadruple zone of strategic fit', where both manufacturers adopt blockchain or neither adopt blockchain, or one adopts while the other does not. Interestingly, despite the low or zero blockchain cost, both manufacturers will outsource without blockchain if their traditional business models satisfy consumers. The extended analysis reveals contradictory results that manufacturers should outsource more often with blockchain to facilitate consumers when a long-term warranty is offered, or the product has a higher failure rate, even though, overall these factors increase costs. [ABSTRACT FROM AUTHOR]

The effect of voice technology on how consumers search for information online is explored. Results from a field survey of consumer experiences with voice-assisted search, three controlled experiments involving dictated (vs. typed) Google searches, and a supplemental experiment (N  = 10,385) find that vocalizing (vs. typing) a query leads consumers to provide more specific, detailed descriptions of what they are seeking, which in turn yield search results that they are more satisfied with. This occurs because consumers tend to be more concerned about communicating clearly when engaging with voice technology, which prompts them to think more about how they want to convey their query before saying it out loud (vs. typing it). This increased forethought leads consumers to provide more detailed descriptions of what they are searching for in vocalized queries, such as by including brand names and intended purposes of use. Finally, the increased specificity of vocalized (vs. typed) queries results in search returns that better satisfy consumers' search goals. Implications for research on consumer–technology interactions, as well as for marketers and consumers, are discussed. [ABSTRACT FROM AUTHOR]

Nanotechnology has a wide scope in various fields as an interdisciplinary science and provides innovative tools in the medical, industrial, agricultural, and food sectors. The unique properties of nanomaterials as compared to the conventional bulk materials because of their small size in the nanoscale have attracted researchers to explore their potential, especially in agriculture and food diagnostics. With the increasing concern over the protection of agricultural products from various threats and to increase agricultural yield, nanotechnology has proven to be an essential tool. The earlier detection of the adversely affecting factors like pathogens, undesirable chemicals, and adverse soil conditions can help in treatment well in time and prevent the undue loss of agricultural yield as well as adverse effects on the environment. Likewise, safe and contamination-free food products are the demand in the food industry not only for enhancement of shelf life of products and maintenance of nutrient quality but also for consumer satisfaction and health. Various nanomaterials have been used to sense these factors to provide eco-friendly and economic diagnostics. In this study, applications of various nanomaterials in the agriculture and food industry have been reviewed in terms of their use as nano-based sensors and biosensors to diagnose soil conditions, soil nutrients, pesticides, and pathogens in plants and food products. In addition, the role of nano-based sensors and biosensors in detecting the presence of various adulterants including heavy metals and other contaminants has also been summarised. [ABSTRACT FROM AUTHOR]

Background: High-quality absorbent products with effective performance characteristics help maintain user dignity and normalise incontinence. Aim: The study evaluated the most important performance characteristics of newly developed MoliCare Premium Pants. Methods: Fifty-two adults with incontinence in Germany were surveyed for their views and levels of satisfaction with various performance features of the tested absorbent incontinence product via a computer-assisted personal interview. Findings: All features of the product received positive feedback from all respondents. More than 94% of participants 'agreed' that the new design performed very well on each characteristic; 98% of users were 'highly satisfied' and 'satisfied' with the MoliCare product. Conclusions: The new design performed particularly well with regard to different performance aspects. The redesigned MoliCare Premium Pants with innovative features is suitable specifically for individuals with incontinence and can help them continue a normal lifestyle independently without feeling embarrassed due to their continence problem. [ABSTRACT FROM AUTHOR]

Background: Dates are highly perishable fruits, and maintaining their quality during storage is essential for both commercial viability and consumer satisfaction. One effective strategy for preserving their nutritional and functional properties is through drying, which reduces moisture content and inhibits microbial growth while concentrating essential nutrients. This study compared the impact of three drying methods (sun drying, hot air oven drying, and cabinet drying) on the chemical, functional, and microbial properties of date flour. The flesh of two date varieties, Amber and Sukkari, was processed by washing, drying at 65°C, milling, and sieving to obtain fine flour, which was then subjected to analysis. Results: The results revealed that fat (5.35 ± 0.07%), protein (10.50 ± 0.00%), and crude fiber (8.57 ± 0.59%) contents were higher in hot‐air oven‐dried amber date fruit. Moisture (12.94 ± 0.63%), ash (2.37 ± 0.03%), and vitamin C (0.024 ± 0.00 mg/100 g) contents were reported to be higher in sun‐dried Sukkari date due to the slower drying process and exposure to lower drying temperatures during sun drying, which allows for minimal thermal degradation of heat‐sensitive compounds like vitamin C. Oven‐dried Amber date powder displayed greater water absorption (1.10 mL/g) and solubility (66.60%). In terms of microbial analysis, both hot air oven‐dried Amber and Sukkari dates had the lowest total viable count (1.19 × 105 and 9.45 × 104 CFU/mL, respectively). Conclusion: Hot air oven drying is a suitable method for drying date fruit as it results in the highest retention of protein, fiber, and ash content while also maintaining low moisture levels, reducing microbial growth, and improving shelf life. [ABSTRACT FROM AUTHOR]

The retail payments market is developing, and the implementation of digital payments has been one of the trends in consumer finance worldwide. This is the first study to jointly examine the perception of digital payment methods and financial services' role, for consumers with and without disabilities. First, based on a nationwide survey on Internet users in Poland, the authors compared the popularity of selected financial services among consumers, then the perception of characteristics of payment methods. The results revealed that consumers with disabilities use a wide range of payment services, and they are included in digital finance. Moreover, contactless payment cards are used by consumers with disabilities even more often than by consumers on average. The results suggest that the control over finances make digital payments an important empowering tool for consumers with disabilities. Finally, the paper provides recommendations for the banking sector, on strategies for offering digital financial services. Points of Interest: This paper examines the potential of new cashless payment methods as an empowering and assistive technologies for consumers with disabilities. The research found that consumers with disabilities use a wide range of payment services, and contactless payment cards are used by them even more often than by non-disabled people. People with disabilities also perceive payment cards as giving great control over their personal finance. This suggest that new payment methods might be their assistive and empowering tool of everyday life. Consequently, the research recommends that entities designing new payment methods should meet the needs of people with disabilities, because they could be improving their shopping and banking experience with appropriate adjustments. [ABSTRACT FROM AUTHOR]

Quality management plays a crucial role in manufacturing industry as it directly impacts product quality and customer satisfaction. Traditional manufacturing industries have begun incorporating deep learning models to manage production quality. However, existing studies often focus on algorithmic models that require high computing power, while practical industrial applications often suffer from a lack of labelled data. This article proposes a novel and lightweight machine-learning-based quality detection model to address this issue. The proposed model tackles quality detection by efficiently detecting the local maxima of the scale space in input images using a Hessian matrix detection method, eliminating the need for continuous computation of multilayer Gaussian difference images. Additionally, image processing techniques are employed to augment the training data, enabling the model to achieve high accuracy even with limited datasets. Experimental results demonstrate that the proposed model outperforms alternative methods in terms of both accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The energy crisis and environmental pollution are receiving increasing attention from governments and communities. This study researches energy-aware remanufacturing systems. Remanufacturing aims to reuse valuable resources from end-of-life products and produce as-new products. Since remanufacturing systems involve a series of disassembly, processing and assembly operations, remanufacturing schedule integrates disassembly, processing and assembly shops. A multi-objective scheduling of remanufacturing systems is proposed, considering workstation use, energy consumption and customer satisfaction simultaneously. A chance-constrained programming model is established to minimize makespan and energy consumption while satisfying total tardiness requirements. A hybrid method is developed, using group teaching optimization and a discrete event simulation system, which can seek and evaluate potentially favourable solutions. The approach is validated on a group of test instances using well-known methods. The results reveal that this method can find non-dominated solutions with well-converged and well-diversified performance, verifying its advantages in providing informed decisions for managers and engineers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has irreversibly altered consumer shopping patterns, engendering a paradigm shift in business-consumer dynamics. Leveraging geospatial tools enables businesses to pinpoint customer travel patterns, forecast demand, and augment both efficiency and customer satisfaction. This study introduces innovative GIS and spatial marketing methodologies to amass and analyze geospatial data, thereby enhancing business operations and customer engagement in southern United States cities. We devised a heatmap detailing the travel and nocturnal locations of Walmart patrons during pandemic, utilizing geolocational data to assist businesses in refining market segmentation and identifying target demographics. Our research reveals significant shifts in consumer behavior due to the pandemic, underscoring an immediate necessity for businesses to acclimate to these evolutions. Providentially, geolocational data emerges as an indispensable asset for retailers, facilitating a competitive stance through meticulous customer base analysis—crucial for discerning consumer necessities and apprehending societal tendencies. [ABSTRACT FROM AUTHOR]