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This paper aims to improve decision making in credit portfolio management through analytical data-mining methods, which should be used as data availability and data quality of credit portfolios increase due to (semi-)automated credit decisions, improved data warehouses and heightened information needs of portfolio management.

To contribute to this fact, this paper elaborates credit portfolio analysis based on cluster analysis. This statistical method, so far mainly used in other disciplines, is able to determine “hidden” patterns within a data set by examining data similarities.

Based on several real-world credit portfolio data sets provided by a financial institution, the authors find that cluster analysis is a suitable method to determine numerous multivariate contract specifications implying high or, respectively, low profit potential.

Nevertheless, cluster analysis is a statistical method with multiple possible settings that have to be adjusted manually. Thus, various different results are possible, and as cluster analysis is an application of unsupervised learning, a validation of the results is hardly possible.

By applying this approach in credit portfolio management, companies are able to utilize the information gained when making future credit portfolio decisions and, consequently, increase their profit.

The paper at hand provides a unique structured approach on how to perform a multivariate cluster analysis of a credit portfolio by considering risk and return simultaneously. In this context, this procedure serves as a guidance on how to conduct a cluster analysis of a credit portfolio including advices for the settings of the analysis.

Suggests that youth unemployment is seen in East Germany as a critical life event because not only may it “scar” individuals’ careers but there is the fear that it may be a cause of other social problems such as criminal and racist behaviour. Bases the study on event‐history and optimal‐matching analysis. Considers seven hypotheses about the impact of unemployment on social mobility career transitions. Findings suggest that unemployment can raise those chances of upward, downward and lateral mobility.

As a strand in industrialization movement in architecture, engineering and construction (AEC) industry, prefabricated construction (PC) has gained widespread popularity due to high efficiency, energy saving, low environmental impacts, safety and other advantages of PC. Well-managed supply chain can further leverage the advantages of PC. However, there is a lack of more systematically overview of the prefabricated construction supply chain (PCSC). This paper aims to comb the current status and look into the future direction of PCSC by reviewing the existing research.

In total, 131 articles related to prefabricated construction supply chain management (PCSCM) from 2000 to 2022 have been collated to (1) conduct a bibliometric analysis by using VOSviewer, including the literature sources, keywords co-occurrence, co-authorships, authorship citation and country active in the field of PCSCM; (2) classify and summarize the status of research in PCSCM through qualitative discussion and (3) point out the future research directions.

In total, 131 articles are carried out for bibliometric analysis and in-depth qualitative discussion, the visualization maps and the main research themes in the field of PCSCM are obtained. The results show that supply chain intelligentization and informatization are hot topics. Finally, future research directions that should be paid attention to in the field of PCSCM are pointed out.

This study can help project managers understand the current status and problems of PCSC operations and provide a basis for future management decisions.

Compared with previous studies, this study adds the dimension of “article authorship” to the quantitative analysis and discusses the research themes in the field of PCSCM in a comprehensive manner. In addition, this paper deeply discusses the main research topics from both the specific contents and research methods adopted.

Action design research (ADR) has become widely accepted as a prominent research method within information systems when managing design-oriented research projects. One purpose of the ADR method is to provide methodological guidance for the building of IT artefacts. However, several scholars have reported a lack of guidance of method support at the micro level. This article aims to complement the macro level of the ADR method by integrating prescriptive method support at the micro level.

A qualitative approach including direct content analysis. An empirical ADR project was analysed in order to identify method support that could be integrated into the ADR method.

Method support at the micro level was identified for all the stages of the ADR method. The method support consists of procedural support, guiding concepts, and various techniques for the documentation of project tasks stated in the ADR method.

The contribution to theory consists of aspects concerning the integration of macro and micro levels: relationships between normative and prescriptive support, continuous focus shifts, and method completeness.

The contribution to practice consists of explicit suggestions for method support that could be integrated into the ADR method.

This study extends previously provided knowledge by offering empirical evidence concerning theoretical constructions consisting of explicit relationships between ADR tasks and integrated method support, and elaboration on the integration of macro and micro levels.

Building on recent research that emphasizes the role of managers as central in the adoption and implementation of management ideas, the purpose of this paper is to explore the reasons why managers may vary in their responses toward these ideas.

Drawing on a cognitive perspective, the research uses a repertory grid approach to analyze survey data from 189 managers.

Rather than stressing only the role of organizational context, the paper indicates the likelihood that more invariant mental models shaped by especially position and disposition play an important role in explaining the way managers view and eventually implement management ideas.

The findings indicate the significance of cognitive factors in explaining managers’ attitudes toward ideas, and advance the understanding of the variety in managers’ responses toward these ideas, particularly in implementation trajectories.

The purpose of this paper is to explore a conceptual model on the influence of corporate social responsibility (CSR) “fit” on organizational attractiveness among job applicants under the boundary conditions of chief executive officer (CEO) activism and CSR credibility.

The study is based on archival research, largely reviewing extant in CSR and drawing propositions based on existing theory.

Paper draws propositions based on CSR fit, credibility and CEO activism. The paper asserts the influence of CSR fit on organizational attractiveness among job applicants. It further explains moderated mediating mechanism through which CSR fit influences organizational attractiveness among job applicants.

Recruitment has primarily explored the role of CSR in attracting potential job candidates. This paper presents the role of CSR “fit,” an aspect not explored before in recruitment. This paper also introduces the role of CEO activism in recruitment.

Construction 4.0 technology is a novel innovative technology that has been proved to enhance project performance. However, information on the concept's awareness, adoption readiness and challenges in developing economies is still scanty. The purpose of the study is to appraise awareness, adoption readiness and challenges of Construction 4.0 technologies in Nigeria to bring to the fore the state of art of these innovative technologies in the study area.

The study used a convenient sampling technique to select 129 construction professionals (architects, engineers and quantity surveyors) in Osun State, Nigeria, who provided data for the study through a closed-ended structure questionnaire survey. The quantitative data supplied were analysed using frequency, percentile, Cronbach's alpha, mean score (MS) analysis and analysis of variance (ANOVA).

The overall awareness level of construction professionals in the study area about Construction 4.0 technologies is at a moderate level (MS = 3.03). The analysis of each component of the Construction 4.0 technologies shows that BIM (MS = 3.69) has the highest level of awareness, while augmented reality (MS = 2.51) has the least awareness level. More results show a significant difference in the opinion of the respondents, a significant difference in the respondents on 36% of the components of Construction 4.0 technologies. The adoption readiness of the Nigerian construction industry (NCI) to Construction 4.0 technologies is at an initial level (MS = 2.86). However, the 3D printing (MS = 3.36) and augmented reality (MS = 2.49) have the highest and lowest adoption readiness ratings, respectively. There is no significant difference in how respondents ranked the NCI adoption readiness on 73% of the components of Construction 4.0 technologies. The main challenges of Construction 4.0 technologies in the study area are lack of standardisation (MS = 4.02), lack of investment in research and development and cost of implementation (MS = 3.87) each. The result shows that there is perfect unanimity in the way respondents ranked the challenges of Construction 4.0.

The study provided information on the status quo of Construction 4.0 technologies in the NCI to enhance improvement in practice and the attendant project delivery.

The study attempted to bring to the fore the state of the art on awareness, adoption readiness and challenges of Construction 4.0 technologies in Nigeria. The study's information will be valuable to improve project delivery.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.