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The purpose of this paper is to investigate the performance of bio-based lubricants (BBL), namely, palm mid-olein (PMO) enriched with an antioxidant agent, tertiary-butylhydroquinone (TBHQ) and a viscosity improver, ethylene-vinyl acetate (EVA), in journal bearing (JB) applications.

Samples of the BBL were prepared by blending it with TBHQ and EVA at various blending ratios. The oxidative stability (OS) and viscosity of the BBL samples were examined using differential scanning calorimetry and a viscometer, respectively. Meanwhile, their performance in JB applications was evaluated through the use of a JB test rig with a 0.5 length-to-diameter ratio at various operating conditions.

It was found that the combination of PMO + TBHQ + EVA demonstrated a superior oil film pressure and load-carrying capacity, resulting in a reduced friction coefficient and a smaller attitude angle compared to the use of only PMO or VG68. However, it was observed that the addition of TBHQ and EVA to the PMO did not have a significant impact on the minimum oil film thickness.

The results would be quite useful for researchers generally and designers of bearings in particular.

This study used PMO as the base stock, and its compatibility with TBHQ and EVA was investigated in terms of its OS and viscosity. The performance of this treated BBL was evaluated in a hydrodynamic JB.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0363/

The purpose of this paper is to define the local integration rate and how it is calculated to assess its relevance as a national performance indicator for the Moroccan automotive industry.

The research methodology first followed a systematic review approach through the analysis of published research articles and academic works. This study then followed a qualitative approach based on semi-structured interviews with various actors in the Moroccan automotive industry. Finally, the findings of this work were reinforced by a case study to analyze the supply chain of a locally produced vehicle.

The results indicate that the local integration rate as calculated today overestimates the performance of the automotive industry and does not systematically guarantee a significant creation of value added.

Due to the confidentiality of the data in terms of turnover, payroll and purchase prices as well as the large number of suppliers in the different supply chains of the car manufacturer, the case study focused on only one of the six existing ecosystems.

On the basis of research work on the Moroccan automotive industry as well as interviews with various actors, the local integration rate is unanimously considered as a viable performance indicator. This study has not only led us to the method of calculating this rate by the Ministry of Industry but also demonstrated its limitations while proposing a new method of calculation to increase the value added.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

When it comes to discovering the leaders of the future, how can hiring organizations build a more sensitive talent radar to pick up signals of early-stage talent? What do upcoming leaders need to do to appear on that radar? What kind of search strategy is needed to find the exceptional candidate? Based on dozens of interviews with talent development specialists, we present 11 characteristics that emerge as keys to success. We present a case that illustrates why executive search is high stakes-game of responsible positions, and examine why talent alone is no guarantee of success.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018) and in English (online) by the Amrop Partnership (2021) as “Destination Boardroom 2: The Talent Radar.”

The aim of this paper is to analyse the role of communities of practice (CoP) as knowledge-sharing tools in family small and medium-sized enterprises (SMEs). In this context, CoPs that jointly involve family and non-family members are expected to act as knowledge-sharing tools.

This paper employs a multiple case study methodology, analysing the cases of six small companies in different sectors and countries over a period of 8 years. Both primary and secondary data are used.

The results show the role CoPs play in involving family and non-family members in empowering knowledge-sharing initiatives. A CoP's role in knowledge sharing depends on the presence (or lack) of a family leader, the leadership approach, the degree of cohesion around shared approaches and values within the CoP, and the presence of multiple generations at work.

This paper contributes to the literature on knowledge sharing in family businesses, by exploring for the first time the role of the CoP as a knowledge-sharing tool, depending on families' involvement in the CoP.

Industry 4.0 is exacerbating the need for offsite construction (OSC) adoption, and this rapid transformation is pushing the boundaries of construction skills towards extensive modernisation. The adoption of this modern production strategy by the construction industry would redefine the position of OSC. This study aims to examine whether the existing skills are capable of satisfying the needs of different OSC types.

A critical literature review evaluated the impact of transformative technology on OSC skills. An existing industry standard OSC skill classification was used as the basis to develop a master list that recognises emerging and diminishing OSC skills. The master list recognises 67 OSC skills under six skill categories: managers, professionals, technicians and trade workers, clerical and administrative workers, machinery operators and drivers and labourers. The skills data was extracted from a series of 13 case studies using document reviews and semi-structured interviews with project stakeholders.

The multiple case study evaluation recognised 13 redundant skills and 16 emerging OSC skills such as architects with building information modelling and design for manufacture and assembly knowledge, architects specialised in design and logistics integration, advanced OSC technical skills, factory operators, OSC estimators, technicians for three dimensional visualisation and computer numeric control operators. Interview findings assessed the current state and future directions for OSC skills development. Findings indicate that the prevailing skills are not adequate to readily relocate construction activities from onsite to offsite.

To the best of the authors’ knowledge, this research is one of the first studies that recognises the major differences in skill requirements for non-volumetric and volumetric OSC types.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

This study aims to define a “technological statecraft” concept to distinguish tech-based measures/sanctions from an array of economic measures ranging from restrictions of rare earth elements and natural gas supplies to asset freezes under the wider portfolio of economic statecraft. This concept is practically intended to reveal the USA’s “logic of choice” in its employment of technology as an efficient instrument to deal with China in the context of the great power rivalry.

This study follows David A. Baldwin’s statecraft definition and conceptualization methodology, which relies on “means” rather than “ends.” In addition to Baldwin and as an incremental contribution to his economic statecraft analysis, this study also combines national political economy with statecraft analysis with a particular focus on the utilization of technological measures against China during the Trump administration.

The US rationale for choosing technology, namely, emerging and foundational technologies, in its rivalry against China is caused at least by two factors: the nature of the external challenge and the characteristics of the US innovation model based largely on radical innovations. To deal with China, the USA practically distinguished the role of advanced technology and followed a grammer of technological statecraft as depicted in the promulgated legal texts during the Trump administration.

Despite a growing volume of literature on economic statecraft and technological competition, studies focusing on countries’ “logic of choice” with regard to why and under what conditions they choose financial, technological or commodity-based sanctions/measures/controls are lacking. Inspired from Baldwin’s account on the “logic of choice” from among alternative statecrafts (i.e. diplomacy, military, economic statecraft, and propaganda). This study will contribute to the literature with a clear lens to demonstrate the “logic of choice” from among a variety of economic statecraft measures in the case of the US technological statecraft toward China.

Process orientation is important for improving organizational performance. The process view is considered a key enabler of digital transformation, and thus management control systems (MCS) are expected to incorporate this view. However, the existing body of knowledge is fragmented, as different process approaches are often considered independently following a reductionist view of control practices. This paper aims to provide recommendations for further research as well as guidance for practice by a systematic review of the state of research of MC for process orientation. It is based on both a comprehensive view to MC using an MCS package approach and a comprehensive view of process orientation.

A systematic literature review addressing major types of process orientation approaches was performed by applying the comprehensive MC framework of Malmi and Brown. The results were synthesized and propositions were developed.

All components of the MC framework, as well as MCS packages, are highly relevant for process orientation. Propositions regarding configurations of MC for process orientation show directions for future research. However, comprehensive considerations of packages and of individual components, especially cultural controls, remain scarce in the literature.

To the best of the authors‘ knowledge, this paper is the first of its kind to provide a comprehensive, structured overview of MC for process orientation, applying a nonreductionist view, based on an MCS Package approach, and consolidating the so far fragmented view of different process approaches.