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To ensure product quality within a manufacturing process, inspection processes are indispensable. One task of inspection planning is the selection of inspection characteristics. For optimization of costs and benefits, key characteristics can be defined by which the product quality can be checked with sufficient accuracy. The manual selection of key characteristics requires substantial planning effort and becomes uneconomic if many product variants prevail. This paper, therefore, aims to show a method for the efficient determination of key characteristics.

The authors present a novel Algorithm for the Selection of Key Characteristics (ASKC) based on an auto-encoder and a risk analysis. Given historical measurement data and tolerances, the algorithm clusters characteristics with redundant information and selects key characteristics based on a risk assessment. The authors compare ASKC with the algorithm Principal Feature Analysis (PFA) using artificial and historical measurement data.

The authors find that ASKC delivers superior results than PFA. Findings show that the algorithms enable the cost-efficient selection of key characteristics while maintaining the informative value of the inspection concerning the quality.

This paper fills an identified gap for simplified inspection planning with the method for the efficient selection of key features via ASKC.

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.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

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.

This chapter introduces classical ideas of leadership, from Homer's Iliad and Odyssey and Xenophon's Anabasis, posing questions that challenge the ethical and value-based stance of the contemporary literature on authentic leadership. Do leaders in all spheres need to be versatile in the classical sense? Is the use of ruses legitimate if they succeed? Do literature and history provide greater insight into the execution of leadership than conventional business school courses? Pieper urges researchers to investigate the qualities that a leader needs and the values espoused by proponents of authentic leadership and what coherent theory that recognises the leadership imperatives exemplified by the heroic classical accounts could replace the model of authentic leadership.

Purpose: Small and medium enterprises (SMEs) are the most significant contributors to maximum employment generation, the gross domestic product (GDP) of many countries, and the overall global economy. It is also evident that cyber threats are becoming a big challenge for SMEs, which is directly impacting global economy.

Methodology: Existing research inputs were accessed to understand current cyber threats for SMEs and their cybersecurity posture. Additionally, this research has collected the latest insights by taking direct inputs from SMEs and conducting a well-designed research survey. It has provided a few direct inputs to designing solutions for the SME segment. For analysis and recommendations, cybersecurity best practices and core cybersecurity concepts are considered at the centre of the solution.

Findings: Implementing existing cybersecurity standards or frameworks is not easy for SMEs, as they generally have limited resources and different priorities for their business when it comes to the implementation of any cybersecurity controls. Currently, many cybersecurity standards are not able to support the implementation of business domain-specific controls.

Practical implications: Along with the research findings shared in this chapter, as a resolution to the problems faced by SMEs, the authors will propose a new framework as a solution. This framework is designed using core concepts of cybersecurity such as confidentiality, integrity, and availability (CIA triad) as well as defence in depth (DiD) mechanisms in each layer of organisation. The authors will also share a high-level idea about how reliable artificial intelligence-based software can help identify recommended controls for particular SMEs.

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.