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This study aims to examine the process of using simulation to select candidates from a pool of teacher-education-programme applicants, considering the applicants’ perspective. The population of applicants to teacher-education programmes has been the subject of numerous studies; however, only a minor portion of these examined the applicants’ perspective regarding the applicant-selection process. Furthermore, the process of using simulation as a tool for applicant selection to a teacher-education has not been studied yet.

This case study focuses on applicants’ experience of the simulation-based selection (SBS) and its potential advantages. A total of 188 applicants completed a reflection questionnaire and participated in interviews; 15 of them also participated in focus groups. The data were analysed using the thematic-cognitive method.

Data analysis revealed three major themes and nine subthemes, which represent the value of SBS from the applicants’ perspective in terms of social–interpersonal, cognitive–professional and emotional–personal skills.

Research findings may enable decision-makers in teacher-education programmes to improve the candidate selection process, which will lead to the absorption of suitable teachers on the one hand and prevent the integration of unsuitable candidates on the other.

This pioneering study contributes to our understanding of the applicant-selection process and offers practical recommendations for using SBS to enhance the quality of the selection process.

The author presents a comparative study of the three evolutionary economic schools, namely the Austrians, neo-Schumpeterians, and institutionalists. The comparison is based on an analysis of nine basic features of the evolutionary process and evolutionary approach, including a dynamical view of economic phenomena (seen from a historical perspective), a focus on far-from-equilibrium analysis, a proper and realistic perception of time, and a population perspective (to what extent emergent properties are results of interaction among economic agents). The relevant features of the evolutionary process are the heterogeneity and behavior of economic agents, the search for novelty based on a concept of economic agents’ hereditary information, a selection process (based on the concept of rivalry), spontaneity of development, and the presence of decision-making procedures (how economic agents make decisions, and to what extent their subjective values play a role). The goal of the comparative analysis is to estimate the level of “evolutionary content” of the three schools. My subjective evaluation suggests that only the Austrian school can be called entirely evolutionary. Slightly less evolutionary are the neo-Schumpeterians, and the least evolutionary are the institutionalists.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The purpose of this paper is to investigate the data profile of manufacturing small and medium enterprises (SMEs) with specific emphasis on understanding the data readiness of SMEs for discrete event simulation (DES) modelling.

Research was conducted through a review of literature and a survey research strategy of manufacturing SMEs.

This paper illustrates the data profile of manufacturing SMEs. Insight is provided on the types of data collected by SMEs, the collection methods used and how these data are stored by the SMEs. Additionally size and age effects are considered. Based on this data profile, conclusions are made regarding an indication of data readiness of manufacturing SMEs for DES modelling.

This research is focused specifically on manufacturing SMEs in Ireland, other countries and sectors are not investigated.

This paper provides owner-managers and senior management insight into the data profile of manufacturing SMEs and their potential for utilisation of DES for performance improvement and decision support.

This paper addresses the gaps that exist in the knowledge of the data profile of manufacturing SMEs and consequently the status of this profile with regard to the readiness of SMEs for DES modelling.

Traditional epidemic models, like the classical SIR, are fitted to real data using deterministic optimization techniques. As a consequence, their performances cannot be properly assessed and, more importantly, the estimates of the critical epidemic parameters (which are of dramatic importance in monitoring the epidemic evolution) cannot be complemented with the calculation of confidence intervals. The aim of the present work is to remove such limitations and to compare the results obtained using two stochastic versions of deterministic SIR models. We describe the two alternatives and the associated estimation procedures, and we apply the two methodologies to a set of COVID-19 data observed in Italy in the 2020 pandemic wave. Our estimates of the basic reproduction number are comparable with the official sources, but using our methods uncertainty can also be properly assessed.

In this paper, two popular multiple-criteria decision-making (MCDM) methods with hesitant fuzzy logic approach; hesitant fuzzy analytic hierarchy process (hesitant F-AHP) and hesitant fuzzy the technique for order preference by similarity to ideal solution (HF-TOPSIS) are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning (ERP) alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.

Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues (i.e. time loss, increased costs and a loss of market share). On the other hand, finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.

In this integrated approach, the hesitant F-AHP is used to determine the criteria weights, as the hesitant F-TOPSIS is utilized to rank ERP package alternatives. The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.

If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers, the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations. Therefore, the number of criteria and alternatives should be at reasonable numbers.

The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.

Furthermore, in literature, to the best of our knowledge, the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.

The purpose of this paper is to present a detailed literature review of the recent applications of the analytic hierarchy process (AHP) and analytic network process (ANP) group decision‐making methodologies.

Among more than 600 related papers published in the period 2005‐2009, a total of 232 application articles published in highly reputed international academic journals were selected and referenced in this paper. Papers were categorized according to application areas, subject titles, publication date, country of origin, academic journals, and integrated methodologies, and are summarized herein by various tables and charts.

The findings show that during the years 2005‐2009, use of the AHP technique has continued to increase exponentially. Moreover, it is expected that ANP will gain more popularity in the future, as the benefits of ANP become better understood. Applications of AHP have been dominant in manufacturing, followed by the environmental management and agriculture field, power and energy industry, transportation industry, construction industry, and healthcare. Other remarkable application fields include education, logistics, e‐business, IT, R&D, telecommunication industry, finance and banking, urban management, defense industry and military, government, marketing, tourism and leisure, archaeology, auditing, and the mining industry.

The study does not consider theoretical based AHP or ANP articles. Also the search excluded conference proceedings, masters' theses, and doctoral dissertations.

It is hoped that this study will guide practitioners in future work towards advancement of these techniques and will help the managers to select better decisions by making use of these methodologies.

The paper presents a comprehensive literature review of recent applications of AHP, and also ANP decision tools over the period 2005‐2009. Furthermore, the paper covers fuzzy AHP and fuzzy ANP extensions that are becoming popular methods in some application areas of traditional AHP and ANP.

For the crews and assets of the European Union’s (EU’s) Joint Operations available today, but a vast area in the Mediterranean Sea to monitor, detection of small boats and rafts in distress can take up to several days or even fail at all. This study aims to outline how an energy-autonomous swarm of Unmanned Aerial System can help to increase the monitored sea area while minimizing human resource demand.

A concept for an unattended swarm of solar powered, unmanned hydroplanes is proposed. A swarm operations concept, vehicle conceptual design and an initial vehicle sizing method is derived. A microscopic, multi-agent-based simulation model is developed. System characteristics and surveillance performance is investigated in this delimited environment number of vehicles scale. Parameter variations in insolation, overcast and system design are used to predict system characteristics. The results are finally used for a scale-up study on a macroscopic level.

Miniaturization of subsystems is found to be essential for energy balance, whereas power consumption of subsystems is identified to define minimum vehicle size. Seasonal variations of solar insolation are observed to dominate the available energy budget. Thus, swarm density and activity adaption to solar energy supply is found to be a key element to maintain continuous aerial surveillance.

This research was conducted extra-occupationally. Resources were limited to the available range of literature, computational power number and time budget.

A proposal for a probable concept of operations, as well as vehicle preliminary design for an unmanned energy-autonomous, multi-vehicle system for maritime surveillance tasks, are presented and discussed. Indications on path planning, communication link and vehicle interaction scheme selection are given. Vehicle design drivers are identified and optimization of parameters with significant impact on the swarm system is shown.

The proposed system can help to accelerate the detection of ships in distress, increasing the effectiveness of life-saving rescue missions.

For continuous surveillance of expanded mission theatres by small-sized vehicles of limited endurance, a novel, collaborative swarming approach applying in situ resource utilization is explored.

The purpose of this paper is to explore the use of a hybrid enterprise resource planning (ERP) system, combining an ERP system with enterprise social software (ESS). The study will provide a critical assessment of the implementation of this process technology.

Multiple case studies of organisations based in China were conducted to understand the use of ERP systems in different contexts. Following an evaluation of the context of each ERP implementation (within-case analysis) the research draws a cross-case conclusion that defines the nature of a hybrid ERP system and then synthesises the propositions related to the benefits and challenges of implementation.

The authors find that a hybrid ERP system is able to support efficiency in business process management and also provide a flexible response to changes in business requirements. It does this by allowing for the continued use of informal processes that cannot be incorporated into the ERP system.

This research indicates how ERP systems in conjunction with ESS can provide a flexible response to changing business requirements and increase collaboration within the organisation. Key lessons include the need to perform informal activities under the guidance of managers and provide clear boundaries for the implementation of informal activities.

This study has found that the use of case studies can provide a valuable insight into the use of a hybrid ERP system from the perspective of its use within the organisation as a work system that requires an assessment of the context within which organisational members perform their work.

The purpose of this paper aims to evaluate field repair within product-service system (PSS) models operated by multinational manufacturers in the Egyptian emerging market to better understand the unique characteristics of this evolving market and to identify differences compared to established markets.

Case research was conducted on multinational manufacturers providing field repair services in Egypt. The sample is made up of 12 companies across different industries using convenience and purposive sampling. Data were collected using structured interviews.

There is no common model for field repair PSSs provision in the Egyptian emerging market even within the same industry, which is influenced by several factors. One of these factors is the market type being emerging or established. However, some commonalities have been found between some industries such as computer, telecommunications and document processing. Yet, there is no structural difference in the supply networks used to provide field repair service offerings in the Egyptian emerging market compared to established markets with the trend of outsourcing evident as a main attribute of a PSS in emerging markets. The main differences between established and emerging markets are related to country, culture and customer factors, which are market-based. Among the main challenges and risks that internationalized manufacturers face in Egypt, is the low level of customer awareness.

Findings are limited to the studied cases and industries; yet, internationalized firms must deal with some unique challenges and difficulties in emerging markets.

This paper assesses PSS requirements and provides deeper insights for companies looking to provide or expand manufacturing-based offerings into the Egyptian emerging market.

This paper contributes to the evolving research on PSSs, particularly in emerging markets through identifying and describing different field repair PSS models in the Egyptian emerging market.