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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.

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.