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The purpose of the paper is to develop a mathematical model that describes group learning processes with and without worker turnover.

Based on an extensive literature review, fundamental characteristics of group learning processes are first identified and then incorporated into a group learning curve (GLC). The developed GLC is then validated by fitting to empirical data.

The results show that the behaviour of the developed model is in conformance with the characteristics identified in the literature. A comparison with two other learning curves that have frequently been discussed in the literature shows that the GLC developed in this paper is a good mathematical representation of group learning processes.

The model developed in this paper enables practitioners to predict performance improvement in groups.

The paper is one of the first to propose a mathematical formulation of a GLC.

The purpose of this paper is to present an original model for the production-recycling-reuse of plastic beverage bottles.

It is assumed that discarded two-liter plastic polyethylene terephthalate (PET) bottles are collected from the market. The bottles are then sorted into non-contaminated and contaminated streams. The non-contaminated PET bottles are either remanufactured or used as regrind mixed with virgin PET to produce new bottles to satisfy varying demand. The contaminated bottles are either sold to industries using low-grade plastic or disposed of in a landfill. Numerical studies are used to illustrate the behaviour of the model, with an emphasis on exploring the reduction of total system cost and the amount of bottles going into a landfill.

Numerical analyses conducted on the model found that the amount of bottles collected had the largest influence on the outcome of the total system unit time cost. Alternative materials to PET are surveyed and used to demonstrate a significant reduction in the cost of landfill disposal due to their more rapid degradation in the landfill.

Several areas for future work are highlighted. Potential modifications to the model could focus on accommodating bottles made of material other than plastic, incorporating the effects of learning on manual tasks, and on accommodating shortages or excess inventory.

The model incorporates several unique aspects, including accounting for the cost of land use and associated environmental damage through the calculation of a present value that is charged to the manufacturer.

The purpose of this paper is to present a mathematical model that illustrates the trade‐offs between sustainability, demand, costs, and profit in a supply chain with a single supplier and a single manufacturer.

It is assumed that a single product is produced and sold on a market where demand is sensitive to price and quality. Sustainability is treated as a quality attribute and is measured in terms of the levels of scrap and emissions generated in the supply chain. It is assumed that the emissions and scrap can be controlled by varying production rates or by investing in production processes. The impact of cooperative and non‐cooperative behaviour between the supplier and the manufacturer is explored. Numerical studies are used to illustrate the behaviour of the model.

The analysis shows that the supplier and the manufacturer can attract additional customers by controlling scrap and emissions. The behaviour of the supplier and the manufacturer are dictated by the decision criteria, such as changes in the level of sustainability, used by customers to evaluate the product. It is shown that the profit of the system is higher and that the level of quality is lower in the case of cooperation than in the case of non‐cooperation.

Several areas for future work are highlighted. The study of alternative demand functions, linking sustainability to a monetary component, including additional players, and incorporating additional sustainability indicators all offer possibilities for extending the model.

There is an identified need for analytical models that consider sustainability in the supply chain. The results are especially important for companies operating in markets where customers perceive the sustainability of a product as a quality criterion.

Scheduling of aircraft maintenance operations is a gap in the literature. Maintenance times should be determined close to the real-life to schedule aircraft maintenance operations effectively. The learning effect, which has been studied extensively in the machine scheduling literature, has not been investigated on aircraft maintenance times. In the literature, the production times under the learning effect have been examined in numerous studies but for merely manufacturing and assembly lines. A model for determining base and line maintenance times in civil aviation under the learning effect has not been proposed yet. It is pretty challenging to determine aircraft maintenance times due to the various aircraft configurations, extended maintenance periods, different worker shifts and workers with diverse experience and education levels. The purpose of this study is to determine accurate aircraft maintenance times rigorously with a new model which includes the group learning effect with the multi-products and shifts, plateau effect, multi sub-operations and labour firings/rotations.

Aircraft maintenance operations are carried out in shifts. Each maintenance operation consists of many sub-operations that are performed by groups of workers. Thus, various models, e.g. learning curve for maintenance line (MLC), MLC with plateau factor (MPLC), MLC with group factor (MGLC) were developed and used in this study. The performance and efficiency of the models were compared with the current models in the literature, such as the Yelle Learning model (Yelle), single learning curve (SLC) model and SLC with plateau factor model (SLC-P). Estimations of all these models were compared with actual aircraft maintenance times in terms of mean absolute deviation (MAD), mean absolute percentage error (MAPE) and mean square of the error (MSE) values. Seven years (2014–2020) maintenance data of one of the top ten maintenance companies in civil aviation were analysed for the application and comparison of learning curve models.

The best estimations in terms of MAD, MAPE and MSE values are, respectively, gathered by MGLC, SLC-P, MPLC, MLC, SLC and YELLE models. This study revealed that the models (MGLC, SLC-P, MPLC), including the plateau factor, are more efficient in estimating accurate aircraft maintenance times. Furthermore, MGLC always made the closest estimations to the actual aircraft maintenance times. The results show that the MGLC model is more accurate than all of the other models for all sub-operations. The MGLC model is promising for the aviation industry in determining aircraft maintenance times under the learning effect.

In this study, learning curve models, considering groups of workers working in shifts, have been developed and employed for the first time for estimating more realistic maintenance times in aircraft maintenance. To the best of the authors’ knowledge, the effect of group learning on maintenance times in aircraft maintenance operations has not been studied. The novelty of the models are their applicability for groups of workers with different education and experience levels working in the same shift where they can learn in accordance with their proportion of contribution to the work and learning continues throughout shifts. The validity of the proposed models has been proved by comparing actual aircraft maintenance data. In practice, the MGLC model could efficiently be used for aircraft maintenance planning, certifying staff performance evaluations and maintenance trainings. Moreover, aircraft maintenance activities can be scheduled under the learning effect and a more realistic maintenance plan could be gathered in that way.

The purpose of this paper is to develop a multi-item economic production quantity (EPQ) strategy under grey environment and space constraint. Since the “demand” cannot be predicted with certainty, it is assumed that data behave under grey environment and compare the proposed inventory model with other studies using crisp or fuzzy environments.

This paper is to optimise the cycle time and total cost of the multi-item EPQ inventory model. For this purpose, the Lagrangian coefficient is used to solve the constrained optimisation problem. The grey relational analysis approach and grey data are applied in developing the EPQ inventory model.

The results are compared with the analysis using crisp and fuzzy data. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The results of the study demonstrate that crisp data outperform the other two data in all scales problems in terms of cycle time and cost; grey data perform better in all scales problems than fuzzy data.

The contribution of this research is the use of grey data in developing the EPQ inventory model with space constraint.

The purpose of this paper is to review the literature on logistics and supply chain costs to provide an analysis of sources of publication, citations and authorship using bibliometric analysis techniques (VOSviewer and CitNetExplorer tools).

A review of 756 articles published during the period 2014 to 2019 referenced in the Scopus database was performed. The review was limited to articles published in English and directly related to logistics and supply chain costs.

The research identified more than 2,000 authors representing more than 5,000 keywords and 10,000 references from a total of 155 journals investigated. A critical synthesis of the resulting data revealed several insights about various aspects of studies in this field. For instance, the review identified a scarcity of academic publications in three key areas, namely “supply chain,” “optimization” and “transportation”, which are concepts focused on the total supply chain.

This research highlights important areas of attention for both researchers and practitioners considering costs associated with logistics and supply chain operations and strategies. The results can also help identify thematic areas, journals and topics for future research. The paper identifies and proposes research areas to contribute to the literature when challenges to investigating logistics and supply chain costs are discussed.

To contribute to the design of the energy service companies (ESCOs)' environment in the Mediterranean countries, mainly focusing on the constraints this company's environment face and the actions that can fulfil its needs and aims, taking also into consideration the opportunities and threats emerging from the energy liberalization and climate change.

The methodology that was followed (based in a large part on the context of two projects targeted to the Mediterranean region and funded by the European Commission) incorporated four steps, the desk analysis for energy efficiency potential in the Mediterranean, the data collection, the assessment of the constraints and the final assessment of the ESCOs' environment.

Provides information regarding the current status of ESCOs' development, in the dimensions of the ESCOs' environment (political/legal, economical/financial, social/cultural and technological), both in the European Union (EU) (Cyprus, France, Greece, Italy, Malta and Spain) and non‐EU (Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Syria, Tunisia and Turkey) Mediterranean countries.

There are no papers investigating the activation environment of ESCOs in a coherent and integrated way in the Mediterranean. This paper provides to decision makers a supportive framework for policy design and formulation of policy priorities for ESCOs development in the region.

This paper examines the interaction of human capital and CRM on the performance of SMEs in Yemen.

The study used a quantitative approach in investigating the interacting effect of human capital on the relationship between CRM and SMEs' performance in Yemen. The PLS-SEM analysis was performed to test the hypotheses.

It was observed that key customer focus, technology-based CRM and CRM knowledge management were effective drivers of SME performance, but not CRM organization tools. It was also ascertained that human capital has no moderating effect on the key customer focus and knowledge management relationships with performance, although it does moderate the relationships between performance and CRM organization and technology-based CRM respectively.

Because this study is limited to manufacturing SMEs in Yemen, the results cannot be generalized to other types of industry such as services, whose structure and vision differ from those of manufacturing SMEs. While the current results may be appropriate for SMEs in other developing countries, the researcher believes they are unsuitable for SMEs in advanced economies with different financial structures and employee and management cultures.

The empirical insights of this study are valuable for the owners, managers and professionals in the SMEs manufacturing sector in developing countries, to enrich their organizational performance through CRM adoption, while considering the moderating effect of human capital.

This is the first empirical work to confirm way the main drivers of human capital, including in the analysis the impact of CRM dimensions and SME performance, in the context of the manufacturing sector. In support of an original conceptual model, the insights contribute to the literature on CRM, SMEs in the manufacturing sector, human capital and emerging economies.

This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the emerging themes in addressing volatility, uncertainty, complexity and ambiguity (VUCA).

The biblioshiny technique based on the bibliometrix R package was used to draw journal papers’ performance and scientific contributions by displaying distinctive features from the bibliometric method used in prior studies. The data was extracted from the Web of Science (WOS) and Scopus databases.

Since the 1990s, ERM publication has gained momentum, and it is generally categorised into four main themes. Studies by Miller (1992) and Bromiley et al. (2015) scored the highest in global and local citations, respectively. However, the Economic Outlook ranked first in quality of publications while the Journal of Risk and Insurance topped in quantity of publications. Collaborative research mainly exists between two authors, and the dynamic number of collaborative networks is evident in the USA.

This study is limited by the filtered keywords used to generate the search on journal papers’ in WOS and Scopus. It is imperative to have more comprehensive and rigorous analytics on ERM research to enable a direction for future research. Finally, ERM implementation better equips firms to mitigate risk in a VUCA environment.

This study attempts to fill a vacuum of ERM literature, specifically in business economics, in addressing VUCA. Moreover, it covers a comprehensive predetermined period of from its inception in 1983 until 2022.

With rising environmental concerns, recent years have witnessed a significant surge of academic and corporate interest in green supply chain coordination (GSCC). This is evident from the rise in channel coordination literature focused toward the elimination of sub-optimal in the green supply chain (GSC). This paper seeks to summarize the model-based research on coordination in GSCs with the help of a framework developed specifically for this paper. The purpose of this paper is to present an in-depth analysis of the widely used models in the area.

A review of literature is presented in this paper to examine the underlying concepts peculiar to GSCC. A classification framework is developed to present an exhaustive survey of commonly used concepts.

Around 90 percent of the papers on GSCC come from game theory (GT) application, which explicitly utilizes coordination through contracts. The review concludes prospective area of research in GSCC. The study posits that there exists a potential of creating a more rational and efficient coordination strategies to improve GSC’s operational performance, with the view of the optimum distribution of resources and better environmental management.

To the best of authors’ knowledge, this is the first state-of-the-art review of GSCC literature focused primarily on mathematical model-based literature. This review identifies various methodological and content-oriented characteristics of GSCC. The paper also opens avenues of future research.