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This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

This study aims to analyze and synthesize the design features of existing digital transformation maturity models with a developed classification scheme and propose a generic maturity model development wireframe based on design science research.

A systematic literature review is conducted on digital transformation maturity models in peer-reviewed journals, including the Emerald Insight, Science Direct, Scopus, Taylor & Francis and Web of Science databases, which resulted in 21 studies. A concept-centric tabular approach is used to analyze the studies, and intersectional demonstrations are used to synthesize the findings regarding the design features.

The classification scheme derived from the tabular concept-centric approach and iteratively evolved results in three main and 25 subcategories related to the design features. Analysis and synthesis of the studies reveal the granularity of the existing digital transformation maturity models concerning the design features. Furthermore, considering the design features in the classification scheme, a generic maturity model development wireframe is proposed to guide the researchers.

The generic maturity model development wireframe and the classification scheme that represents the design features of existing maturity models guide the researchers for the maturity model development roadmap.

The existing literature review studies do not focus on the design feature of digital transformation maturity models within a systematic literature review perspective. A unique classification scheme derived from the tabular concept-centric approach aims to analyze the granularity level of the existing models. Furthermore, the generic maturity model development wireframe includes the guidelines and recommendations of design science studies and presents a roadmap for maturity model researchers.

The purpose of this paper is to originally present the generic analytical models of memelement and inverse memelement with time-dependent memory effect.

The variable order forward Grünwald–Letnikov fractional derivative and the memristor and inverse memristor models proposed by Fouda et al. have been adopted as the basis. Both analytical and numerical studies have been conducted. The applications to the candidate practical memristor and inverse memelements have also been presented.

The generic analytical models of memelement and inverse memelement with time-dependent memory effect, the simplified ones for DC and AC signal-based analyses and the equations of crucial parameters have been derived. Besides the well-known opposite relationships with frequency, the Lissajous patterns of memelement and inverse memelement also use the opposite relationships with the time. The proposed models can be well applied to the practical elements.

To the best of the authors’ knowledge, for the first time, the models’ memelement and inverse memelement with time-dependent memory effect have been presented. A new contrast between these elements has been discovered. The resulting models are applicable to the practical elements.

The purpose of this paper is to propose a new method that allows to compare the magnetic pressures of different pulse width modulation (PWM) strategies in a fast and efficient way.

The voltage harmonics are determined using the double Fourier integral. As for current harmonics and waveforms, a new generic model based on the Park transformation and a dq model of the machine was established taking saturation into consideration. The obtained analytical waveforms are then injected into a finite element software to compute magnetic pressures using nodal forces.

The overall proposed method allows to accelerate the calculations and the comparison of different PWM strategies and operating points as an analytical model is used to generate current waveforms.

While the analytical expressions of voltage harmonics are already provided in the literature for the space vector pulse width modulation, they had to be calculated for the discontinuous pulse width modulation. In this paper, the obtained expressions are provided. For current harmonics, different models based on a linear and a nonlinear model of the machine are presented in the referenced papers; however, these models are not generic and are limited to the second range of harmonics (two times the switching frequency). A new generic model is then established and used in this paper after being validated experimentally. And finally, the direct injection of analytical current waveforms in a finite element software to perform any magnetic computation is very efficient.

This study aims at presenting deeper insights regarding the understanding and application of the quality costs (CoQ) in the automotive manufacturing industry. The empirical research included three general determinants: reasons for, difficulties during and benefits from implementing quality costs, as well as two specific determinants: measuring and evaluating quality cost elements.

The empirical research methodology employs the expert evaluation method – the Delphi method, using a survey questionnaire comprising a total of 200 questions, and answered by 9 companies.

The survey results showed that companies do recognize the reasons for implementing quality costs as a need arising from the quality management standards, the lack of knowledge of quality costs by employees and management as the biggest difficulty while the biggest benefit includes the quality costs enhance the company competitiveness. The costs competence and qualification, the quality management system costs, the costs for improvement, the production control costs, the input control costs, the new measuring and control equipment calibration costs, the costs related to scrap, repairs and product finishing are the most significant elements of the quality costs.

This study is limited by the small number of surveyed companies from the automotive cluster.

The proposed quality costs model provides to the management to conceive CoQ elements as possible drivers in the improvement process of product quality. The structure and the nature of the CoQ elements is expected to advance the process of detailing the quality costs elements.

The novelty of this paper refers to development of a generic quality cost model, whose relevance is confirmed by the structuring of the model with elements published in literature and validating in research companies.

Competencies are significant predictors of employee outcome. Nowadays, new technologies are changing maintenance processes and workflow. The role of employees and their competencies will therefore undergo decisive changes in the future. Therefore, a well-designed competency model for maintenance departments is important. The purpose of this paper is to develop a maintenance 4.0 competency model applicable to all industrial sectors by adapting it to the specificities of each sector.

The research methods consist of a comprehensive literature review on the main characteristics of the competency model and the individual competencies needed for the maintenance 4.0 employees. Interviews were conducted in order to validate and prioritize the required competencies for maintenance 4.0 employees identified in the literature.

The maintenance 4.0 competency model combines the required competencies in maintenance 4.0 and crosses the three hierarchical levels: managers, engineers and technicians. These competencies are organized in terms of four categories: technical, personal, social and methodological. In addition, a degree of importance for each competency is assigned as very important, moderately important and slightly important. As a result, this study identified the essential competencies for maintenance 4.0 stakeholders, where 12 competencies are considered very important for maintenance 4.0 technicians, 19 for engineers and 18 for managers.

This work has some limitations. First, although the articles related to competencies and their classification were selected very carefully, it is difficult to eliminate the probability of overlooking publications. Second, the limitation of the study is based on the difficulty of implementing the model in a case study, given that a minority of industrial companies have implemented maintenance 4.0 technologies in Morocco.

This work has practical implications for both individuals and institutions (companies and academies) to cope with new competency requirements in maintenance 4.0. Organizations can use the model in the recruitment process and for the identification of training needs. The results of the research will also contribute to identifying the scope of competencies of the maintenance 4.0 actors (engineer, manager and technician), which, in practice, contributes to the creation of requirements for the candidates applying for a job in the maintenance department. Additionally, educational institutions should make the necessary changes to their curricula to suitably prepare students for the required maintenance 4.0 competencies.

The social implications of the article result from the contribution to the development of maintenance competencies. Individuals can use this model for their own personal development. Furthermore, companies can use this model to define job profiles for vacancies in M4.0. Therefore, using the model for training program implementation has a positive effect on employee job satisfaction and employees ’morale.

This research develops a novel maintenance 4.0 competency model by categorizing the maintenance workforce into three hierarchical levels: managers, engineers and technicians. In addition, the competency requirement is prioritized to three degrees: very important, moderately important and slightly important. According to the previous studies conducted on maintenance 4.0 and employees' competencies, this study revealed that no research has developed a competency model for maintenance 4.0. Hence, this model is unique, generic and integrative since it presents the most relevant competencies for the three hierarchical levels. Moreover, this work combines the results of the literature review and the experts' returns. This model can be useful in the recruitment of new maintenance employees, the evaluation of their performance and the identification of training needs to cope with new changes in maintenance competencies.

Despite considerable research on the subject, there is still some misunderstanding about what characterizes successful project delivery in construction projects. Evaluating project delivery success is crucial for organizations since it enables them to prepare for future growth through more effective project management mechanisms and rank the organization's projects for continuous improvement. There is considerable disagreement over a set of success criteria that can be applied to all kinds of projects when evaluating project delivery success, making it a complicated procedure for practitioners and scholars. This research seeks to alleviate the problem by validating and testing a systematic project delivery success model (3D integration model) in the Australian construction industry. The aim is to establish a dependable approach built upon prior research and reliable in evaluating delivery success for any project type.

Based on a novel project delivery success model, this research applies a case study methodology to analyse 40 construction projects undertaken by a single Australian project management consultancy. The research utilizes a mixed-method research approach and triangulates three sets of data. First, the project delivery success (PDS) scores of the projects are calculated by the model. Second, a qualitative analysis targeting the performance of the same projects using a different system called the performance assessment review (PAR) scores was obtained. These culminate in two sets of ranking. The third step seeks validation of results from the head of the partnering organization that has undertaken the projects.

The findings of this study indicate that the 3D integration model is accurate and reliable in measuring the success of project delivery in construction projects of various sizes, locations and durations. While the model uses six key performance indicators (KPIs) to measure delivery success, it is evident that three of these may significantly improve the likelihood of PDS: value, speed and impact. Project managers should focus on these priority aspects of performance to generate better results.

Restrictions inherent to the case study approach are identified for this mixed-method multiple-case study research. There is a limitation on the sample size in this study. Despite the researcher's best efforts, no other firm was willing to share such essential data; therefore, only 40 case studies could be analysed. Nonetheless, the number of case studies met the literature's requirements for adequate units for multiple-case research. This research only looked at Australian construction projects. Thus, the conclusions may not seem applicable to other countries or industries. The authors investigated testing the PDS in the construction sector. It can assist in improving efficiency and resource optimization in this area. Nonetheless, the same technique may be used to analyse and rank the success of non-construction projects.

Despite the research conducted previously on the PDS of construction projects, there is still confusion among researchers and practitioners about what constitutes a successful project delivery. Although several studies have attempted to address this confusion, no consensus on consistent performance metrics or a practical project success model has been formed. More importantly, (1) the ability to measure success across multiple project types, (2) the use of triple bottom line (TBL) to incorporate sustainability in evaluating delivery success and (3) the use of a complexity measurement tool to adjust delivery success scores set the 3D integration model apart from others.

Project management skills are important for today’s engineers, as they get involved in various project-based employment roles. The purpose of this paper is to discuss a learning model to provide project management knowledge through scaffolding and project-based learning (PjBL) methods in the project engineering course.

This paper discusses a generic learning model that includes how scaffolding and project-based methods are integrated to provide project management skills to the students. The paper uses the survey method to collect and analyze data on the applicability of the model.

Statistical analysis of the collected data shows that the respondents positively perceive the value of the learning model to gain project management knowledge and skills. The response shows that the model is useful not only to the current students but also the graduates who use project management skills in their employment.

The learning model can be used by the instructors to provide project management skills to undergraduate and graduate students from all education disciplines.

This paper focuses on the development of a unique learning model, and artifacts used by the students and the instructors for interactive learning and gaining skills on project management.

The purpose of this study is to examine the impact of educational service quality (ESQ) on student academic performance via the mediating role of student satisfaction.

To serve the study’s purpose, the study adopted a quantitative research approach. Three public universities representing 30% of the ten public universities located in the Southern part of Ethiopia participated in the study. Questionnaires were the main tools for gathering data. The adapted questionnaire, consisting of 116 items was administered to 400 randomly selected regular undergraduate graduating class students. The quantitative data collected via questionnaire were analyzed using descriptive and advanced inferential statistics.

The quantitative findings revealed that there is a statistically positive association between overall education service quality and students’ satisfaction (r = 0.712). The findings proved that the facets of education service quality accounted for 71.2% of the variations in students’ satisfaction in the universities. The quantitative findings further showed that the education service quality has a statistically indirect effect on students’ academic performance via the mediating role of students’ satisfaction (test statistic = 31.5311573, std. error = 0.00122536 and p-value = 0). The findings further confirmed that the overall education service quality accounted for 12.7% of the variations in students’ academic performance via student satisfaction in the universities.

The present study was conducted in public universities located in the Southern part of Ethiopia. The findings and conclusions of the study may not be generalizable to all Ethiopian public universities. Future researchers and scholars should conduct their study in all Ethiopian public universities by taking a representative sample from the Ethiopian public universities.

The present finding suggests that an improvement in ESQ leads to students’ satisfaction and that could contribute to boosting their academic performance. The findings of the present may help the practitioners who measure higher education service quality by providing how the provision of ESQ indirectly influences the student’s academic performance in the universities.

The findings of this study confirmed that the facets of ESQ are associated with students’ satisfaction and this, in turn, indirectly influences their academic performance. Student academic performance is one of the key indicators of quality education, and it has its influences on the social, political and economic development of a country. The findings of the present research provide valuable insights to higher education management bodies, higher quality assurance agencies and the Federal Ministry of Education to learn the indirect effect of ESQ on students’ academic performance and take necessary measures to improve the Ethiopian higher education quality.

The contributions of ESQ in the higher education sector are enormous. However, the existing service quality literature in higher education mainly focuses on the interrelation among service quality, student satisfaction, loyalty and behavioral intentions. Little is known about the indirect influence of ESQ on student academic performance (one of the key indicators of quality education), principally in Ethiopian higher education, the place of current research. The present study showed the indirect impact of ESQ on student academic performance in Ethiopian public universities. The study, therefore, suggests that university management bodies should actively monitor the quality of their services and commit themselves to boosting students’ learning outcomes.

Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify, select, manage and optimize the associated decision variables (e.g. capacity, number and speed) for trucks and loaders equipment to minimize cost and time objectives.

This paper addresses an innovative multiobjective and multivariable mathematical optimization model to generate a Pareto-optimality set of solutions that offers insights of optimal tradeoffs between minimizing earthmoving activity’s cost and time. The proposed model has three major stages: first, define all related decision variables for trucks and loaders and detect all related constraints that affect the optimization model; second, derive the mathematical optimization model and apply the multiobjective genetic algorithms and classify all inputs and outputs related to the mathematical model; and third, model validation.

The efficiency of the proposed optimization model has been validated using a case study of earthmoving activities based on data collected from the real-world construction site. The outputs of the conducted optimization process promise the model’s originality and efficiency in generating optimal solutions for optimal time and cost objectives.

This model provides the decision-maker with an efficient tool to select the optimal design variables to minimize the activity's time and cost.