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The determination of the measurement uncertainty is relevant for all measurement processes. In production engineering, the measurement uncertainty needs to be known to avoid erroneous decisions. However, its determination is associated to high effort due to the expertise and expenditure that is needed for modelling measurement processes. Once a measurement model is developed, it cannot necessarily be used for any other measurement process. In order to make an existing model useable for other measurement processes and thus to reduce the effort for the determination of the measurement uncertainty, a procedure for the migration of measurement models has to be developed.

This paper presents an approach to migrate measurement models from an old process to a new “similar” process. In this approach, the authors first define “similarity” of two processes mathematically and then use it to give a first estimate of the measurement uncertainty of the similar measurement process and develop different learning strategies. A trained machine-learning model is then migrated to a similar measurement process without having to perform an equal size of experiments.Similarity assessment and model migration

The authors’ findings show that the proposed similarity assessment and model migration strategy can be used for reducing the effort for measurement uncertainty determination. They show that their method can be applied to a real pair of similar measurement processes, i.e. two computed tomography scans. It can be shown that, when applying the proposed method, a valid estimation of uncertainty and valid model even when using less data, i.e. less effort, can be built.

The proposed strategy can be applied to any two measurement processes showing a particular “similarity” and thus reduces the effort in estimating measurement uncertainties and finding valid measurement models.

Significant research has shown that gender and social class relationships can be problematic within the context of water-based leisure activities such as surfing, windsurfing, and sailing (Olive et al., 2016; Wheaton, 2003). More specifically, it has been argued that sailing is traditionally practiced and dominated by upper-class males who can determine social codes that exclude and devalue others (Créac'h & Sébileau, 2004). We develop these critical ideas about broader water sport activity through the lens of family involvement within the context of an international comparative qualitative study of sailing projects based within secondary schooling sites in California and France. A key line of analysis involved investigating how various forms of capital (Bourdieu, 1979) were reproduced through gendered and social class hierarchies. We found that parents played key roles in reinforcing gendered stereotypes and divisions that were operating in youths' daily practices and competitions (middle school and high school). Additionally, our data show that sailing was regularly utilized by families to maintain upper-class values and distinctive social status (Friedman, 2013). Thirty interviews and 113 hours of field observations with stakeholders such as coaches, teachers, youths (14 to 17 years old), and their parents frame these various lines of analysis around sailing activity.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

This paper aims to explore the increasing importance of the intraorganizational dimension of the sales role (IDSR) based on service-ecosystem theory. Specifically, it examines how firms can improve interactions both internally and with external actors and stakeholders to both create and sustain advantageous “thin crossing points” (Hartmann et al. 2018). Academic research on sales ecosystems has yet to fully harness the rich insights and potential afforded by the crossing-point perspective.

After developing and unpacking the paper’s guiding conceptual framework (Figure 1), the authors focus on crossing points and the diversity of interactions between the contemporary sales force and its many stakeholders. They examine the sales literature, identify opportunities for thinning sales crossing points and propose dozens of research questions and needs.

The paper examines the importance of improving interactions both within and outside the vendor firm to thin crossing points, further develops the concept of the “sales ecosystem” and contributes a series of important research questions for future examination.

The paper focuses on applying “thick” and “thin” crossing points, a key element of Hartman et al. (2018). The primary limitation of the paper is that it focuses solely on the crossing-points perspective and does not consider other applications of Hartman et al. (2018).

This work informs managers of the need to improve interactions both within and outside the firm by thinning crossing points. Improving relationships with stakeholders will improve many vendor firm and customer outcomes, including performance.

Integrating findings from the literature, the authors propose a conceptual framework to encompass the entire diversity of idiosyncratic interactions as well as long-term relationships the sales force experiences. They discuss the strategic importance of thinning crossing points as well as the competitive disadvantages, even peril, “thick” crossing points create. They propose an ambitious research agenda based on dozens of questions to drive further examination of the IDSR from a sales-ecosystem perspective.

The aim of this study is to explore and elucidate the influence of polygamy on the succession dynamics of family businesses in the Arab world, offering insights that may be underrepresented or overlooked in traditional, Western-focused literature.

This article adopts a perspective-based approach, focusing on delving into the amalgamation of polygamous family structures and their implications on the operation and continuation of family-run businesses.

Polygamy, while often primarily perceived as a cultural or religious tradition, wields substantial influence over various business facets. Notably, its presence can significantly shape business continuity, the methodologies behind succession planning and the overarching framework of corporate governance within Arab family businesses.

This article offers a unique Middle Eastern lens, highlighting the underexplored intersection of polygamy and business succession. It strives to bridge the knowledge gap by addressing topics potentially sidelined in mainstream Western business research.

Retailers increasingly endeavour to implement artificial intelligence (AI) innovations, such as humanoid social robots (HSRs), to enhance customer experience. This paper investigates the interactive effect of HSR intelligence and consumers' speciesism on their perceptions of retail robots as sales assistants.

Three online experiments testing the effects of HSRs' intellectual intelligence on individuals' perceived competence and, consequently, their decision to shop at a retail store that uses HSRs as sales assistants are reported. Furthermore, the authors examine whether speciesism attenuates these effects such that a mediation effect is likely to be observed for individuals low in speciesism but not for those with high levels of speciesism. Data for all studies were collected on Prolific and analysed with SPSS to perform a logistic regression and PROCESS 4.0 (Hayes, 2022) for the mediation and moderated-mediation analysis.

The findings show that the level of speciesism moderates the relationship between HSR intellectual intelligence and perceived competence such that an effect is found for low but not for high HSR intelligence. When HSR intellectual intelligence is low, individuals with higher levels of speciesism (vs low) rate the HSR as less competent and display lower HSR acceptance (i.e. customers' decision to shop using retail robots as sales assistants).

This research responds to calls in research to adopt a human-like perspective to understand the compatibility between humans and robots and determine how personality traits, such as a person's level of speciesism, may affect the acceptance of AI technologies replicating human characteristics (Schmitt, 2019). To the best of the authors' knowledge, the present research is the first to examine the moderating role of speciesism on customer perceptions of non-human retail assistants (i.e. human-like and intelligent service robots). This study is the first to showcase that speciesism, normally considered a negative social behaviour, can positively influence individuals' decisions to engage with HSRs.

Customer service conversations are becoming increasingly digital and automated, leaving service encounters impersonal. The purpose of this paper is to identify how customer service agents and conversational artificial intelligence (AI) applications can provide a personal touch and improve the customer experience in customer service. The authors offer a conceptual framework delineating how text-based customer service communication should be designed to increase relational personalization.

This paper presents a systematic literature review on conversation styles of conversational AI and integrates the extant research to inform the development of the proposed conceptual framework. Using social information processing theory as a theoretical lens, the authors extend the concept of relational personalization for text-based customer service communication.

The conceptual framework identifies conversation styles, whose degree of expression needs to be personalized to provide a personal touch and improve the customer experience in service. The personalization of these conversation styles depends on available psychological and individual customer knowledge, contextual factors such as the interaction and service type, as well as the freedom of communication the conversational AI or customer service agent has.

The article is the first to conduct a systematic literature review on conversation styles of conversational AI in customer service and to conceptualize critical elements of text-based customer service communication required to provide a personal touch with conversational AI. Furthermore, the authors provide managerial implications to advance customer service conversations with three types of conversational AI applications used in collaboration with customer service agents, namely conversational analytics, conversational coaching and chatbots.

Global supply chains are increasingly becoming more prone to high-impact disruptions, which has been fairly evident with the coronavirus disease 2019 (COVID-19) pandemic. The capacity to address disruptions is essential for the survival of any organization. Coping with increasing complexity and uncertainties requires a systemic view of supply chains. Furthermore, a comprehensive understanding of the governance structure and timely decision-making are critical in times of disruptions. Although several aspects of supply chain resilience (SCRES) are broadly studied in the literature, the relationship between supply chain orientation (SCO), decentralization in decision-making and SCRES is an understudied area.

This study takes a longitudinal approach to address this research gap with a comprehensive meta-analytic review to explore the relationships between the constructs of interest through the lenses of contingency and dynamic capability theories. Furthermore, 2 surveys with sample sizes of 250 and 200 were conducted with supply chain professionals to test the research framework before and after the pandemic to compare the findings.

Structural Equation Modeling (SEM) analysis indicates a positive relationship between SCO and decentralization and between decentralization and SCRES. The post-COVID-19 analysis further validates the influence of agility, collaboration and situational awareness related to decentralization and resilience. More importantly, capabilities have a higher impact on resilience during the pandemic than before.

The results entreat organizations to attain decentralized decision-making vis-à-vis dedicated functional teams charged with reacting timely to disruptions. The teams should be empowered to leverage their knowledge and experiences regardless of their position in the hierarchy.

Although SCRES is an active research stream, the structural aspects of SCRES and its relationship with SCO are understudied. Therefore, this research puts forth a research framework and empirically tests hypotheses that frame the relationship between SCO, decentralization and resilience outcomes in pre- and post-COVID environments.