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Early contractor involvement (ECI) faces many barriers because it differs from traditional business practices. Public owners, especially, face a major challenge because they must comply with international and national legislation. The purpose of this paper is to develop a framework that illustrates the various approaches that public project owners can take to implement ECI.

In addition to a literature review, three groups of case studies were carried out. The case studies were based on 54 semi-structured in-depth interviews with key personnel from 21 Norwegian public projects and document study.

In all, 25 approaches to ECI were identified during the research. Twelve of these were used in the cases studied.

There are several approaches to ECI that are suitable for public owners. However, the contractor’s contribution depends on which approach is implemented and how it is implemented.

As original contribution, this study presents a novel framework that defines options for implementing ECI in public projects. Furthermore, this paper provides insights on how ECI can be implemented in public projects based on Norwegian experiences. Although the empirical data of the study is limited to Norwegian public projects, this study contributes to knowledge about how to implement ECI internationally.

The paper aimed to identify the extent of the implementation of merit criteria in the selection of senior bureaucratic officials in Egypt.

The design of the study is both descriptive in the theoretical part and quantitative in the applied one. The study is based on a literature review and adopts an analytical approach to clarify the related concepts. Besides, an empirical study to investigate the correlations in practice, based on a sample of 380 senior officials to obtain the primary data.

The results of the study reveal that there are no statistically significant differences between the respondents' perspectives towards the implementation of merit criteria in selecting senior officials. This means that merit criteria are not always applied, but sometimes. Moreover, the results showed no statistically significant differences between the respondents' perspectives towards the implementation of merit criteria attributed to gender and age, while there were differences attributed to educational qualification and experience. The study recommended the necessity of adhering to the provisions of the civil service system and reconsidering the procedures of competitive examinations and interviews.

With respect to the Middle East, very limited studies have focused on the implementation of the merit system in recruitment. There is a lack of research and academic articles on this topic (Budhwar and Mellahi, 2016; Afiouni et al., 2014). The study addresses this gap in research and provides several recommendations that may improve the implementation of the merit system in Egypt. Moreover, this study adds to the limited literature on this topic in the Middle East.

Higher education institutions have undergone a transformation over the past few decades, from loosely coupled systems to more centrally managed organizations. Central to this ongoing development is the increasing competition for resources and reputation, driving higher education institutions to rationalize their structures and practices. In our study, we focused on changes in job advertisements for professorships in Germany from 1990 to 2010. Findings showed that the requirements stipulated by universities for professorial positions have become increasingly differentiated (and measurable) over time. In this context, competitive aspects, such as third-party funding, international orientation, or publications, have particularly come to the fore and grown significantly in importance. We discuss these findings in light of an increasing managerialization of higher education institutions, which has a direct effect on collegiality. We argue that the differentiation of professorial job profiles leads to even more formalized appointment processes and may push collegial governance into the background.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Societies depend on interconnected infrastructures that are becoming more complex over the years. Multi-disciplinary knowledge and skills are essential to develop modern infrastructures, requiring close collaboration of various infrastructure owners. To effectively manage and improve inter-organizational collaboration (IOC) in infrastructure construction projects, collaboration status should be assessed continually. This study identifies the assessment criteria, forming the foundation of a tool for assessing the status of IOC in interconnected infrastructure projects.

A systematic literature study and in-depth semi-structured interviews with practitioners in interconnected infrastructure construction projects in the Netherlands are performed to identify the criteria for assessing the status of IOC in infrastructure construction projects, based on which an assessment tool is developed.

The identified assessment criteria through the literature and the practitioner’s perspectives results in the designing and development of a collaboration assessment tool. The assessment tool consists of 12 criteria and 36 sub-criteria from three different categories of collaborative capacity: individual, relational, and organizational.

The assessment tool enables practitioners to monitor the status of IOC between infrastructure owners and assists them in making informed decisions to enhance collaboration. The assessment tool provides the opportunity to assess and analyze the status of collaboration based on three categories (i.e., individual, relational, and organizational).

Cruise tourism is the fastest-growing segment of the shipping and port industry. This study aims to develop an analytic model to assess the key criteria and sub-criteria influencing four cruise port's development in Taiwan.

Based on the literature review, four criteria and 13 sub-criteria are developed and analysed by fuzzy analytic hierarchy process (FAHP). Four cruise ports include Kaohsiung, Keelung, Taichung and Hualien ports. The 26 relevant field experts (including cruise operators, governmental officials and academics) were invited to provide information for assessing the sub-criteria in the model.

The results indicate that port infrastructure and facilities are the most important criterion, followed by port-city development plans, port geography and climate and port regulations and services. In addition, the three most important sub-criteria overall are the onshore tourism programme, the city’s historical and cultural features and the green port hinterland transport system. Also, Keelung port is ranked as the best port, followed by Kaohsiung, Taichung and Hualien.

As Asia is an important cruise market in the world (ranked as third) and passenger number in Taiwan has achieved the top two in Asia, denoting Taiwan is a good market to develop an evaluation model of cruise ports. The findings present a holistic picture of the relative importance of the various criteria associated with cruise port development and raise issues related to cruise port marketing and the economic and environmental sustainability of ports and their hinterlands.

The objective of the study is to develop a methodology to strategically rank store locations using criteria such as population, store site characteristics, economic considerations, competition and so on to select the most optimal retail convenience store location.

A case of National Capital Region, India, for a 24-h convenience store was considered for the study and the major criteria that affect the performance of a convenience store are identified, such as population characteristics, economic criteria, competition, consumer accessibility, store size, total cost, site attractiveness and security. Fuzzy AHP is utilized to find the weightage for each criteria and a combination of fuzzy TOPSIS and grey relational analysis (GRA) is applied to rank the alternative using these criteria weight. Further, results obtained are compared with results from fuzzy TOPSIS and fuzzy VIKOR methods. Sensitivity analysis is also performed for ensuring the robustness of the framework.

It is observed that outcomes do not change under various settling coefficient values, demonstrating that the methodology is very robust. The developed framework will be quite useful to diverse retailers looking to expand and generate substantial profits.

A large sample size of number of locations encourages generalization of results. Strategic ranking of the selected locations is carried out on a few selected criteria. The study was limited by the designated geographical area.

The study contributes to the few available articles on convenience store selection using combination of fuzzy AHP, fuzzy TOPSIS and GRA for a developing country.

Supplier segmentation provides companies with suitable policies to control each segment, thereby saving time and resources. Sustainability has become a mandatory requirement in competitive business environments. This study aims to develop a clustering-based approach to sustainable supplier segmentation.

The characteristics of the suppliers and the aspects of the purchased items were considered simultaneously. The weights of the sub-criteria were determined using the best-worst method. Then, the K-means clustering algorithm was applied to all company suppliers based on four criteria. The proposed model is applied to a real case study to test the performance of the proposed approach.

The results prove that supplier segmentation is more efficient when using clustering algorithms, and the best criteria are selected for sustainable supplier segmentation and managing supplier relationships.

This study integrates sustainability considerations into the supplier segmentation problem using a hybrid approach. The proposed sustainable supplier segmentation is a practical tool that eliminates complexity and presents the possibility of convenient execution. The proposed method helps business owners to elevate their sustainable insights.