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This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

The factors for higher education institutions’ (HEIs) project management failure have been studied for several years. One of the issues is a lack of tools to combine their knowledge infrastructure capabilities (KIC) with project management (PM) to examine these infrastructures and monitor maturity. There are several project management maturity (PMM) models available. However, there are just a few empirical studies that support the three knowledge infrastructure capabilities and PMM integrations. As a result, the current research aims to suggest a new conceptual model, KIC-knowledge management (KM), and assess a research model that includes the three knowledge infrastructure capabilities as a prerequisite to elevate the PMM.

Partial least squares structural equation modeling (PLS-SEM) is used to evaluate the proposed research model. The study’s hypotheses were also examined using a sample of 352 respondents from PM departments at ten Yemeni public universities.

The study found that if the three key knowledge infrastructure capabilities integrate into the PMs, then it will help HEIs to perform project tasks more effectively and efficiently. Also, it will improve the PM maturity level if all the three capabilities positively effect PMM.

The study findings cannot be generalized to other industries because the collected date were with the Yemeni public universities’ context. Also, the new proposed model can be assessed in various sectors to increase the validity of the model. One more thing, future academics can conduct qualitative research study to validate again the proposed model.

Project managers can develop and improve their organization’s effectiveness and performance by focusing on these findings and using the developed model. Also, the findings of this study can be used as a benchmark for evaluating initiatives and knowledge-based governmental entities.

It is an opportunity for knowledge-based governmental entities particularly and other organizations to elevate most of projects to achieve a supreme level of maturity. Also, this study will assist employees to understand the relationship between KICs and projects within HEIs in Yemen.

This paper is among the first to empirically study the impact of the three knowledge infrastructure capabilities toward PMM. It links between two important domains: KM and PM.

Digital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.

This study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.

The results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.

This paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.

Building Information Modeling (BIM) capabilities have been studied at the individual, project, organizational, and even industry levels to ensure the realization of BIM value in the architectural, engineering, construction, and operation industry. However, limited research has focused on a project owner organization perspective to investigate owner BIM capabilities that are required to ensure effective project management and delivery. This present study aims to propose an indicator framework to evaluate owner BIM capabilities at the organizational level.

Leveraging the existing literature on BIM capabilities and synthesizing insights from the resource-based view and information technology capabilities research, this study conceptualizes the BIM capabilities of project owner organizations and offers a framework of indicators for measurement. Semi-structured interviews with BIM experts and a questionnaire survey were conducted to identify key indicators affecting owner BIM capabilities. A six-dimensional structural equation model with 29 indicators was then established.

The findings highlight the multidimensionality of owner BIM capabilities and show that process capabilities play a crucial role in enhancing owner BIM capabilities, while technical capabilities are considered as the least important aspect.

The study sheds light on the key role of project owner organizations in ensuring BIM value and suggests that project owners focus more on the organizational processes of introducing BIM in managing projects.

This study reconceptualizes owner BIM capabilities drawing on the idea of resource-based view and information technology capabilities and highlights the important dimensions and indicators of owner BIM capabilities at the organizational level.

This study aims to develop a maturity model designed for assessing the current state of digitization in accounting firms.

The authors have developed this index where the maturity levels are defined from the life cycle theory. For the items of a maturity measure, the authors have adopted a multimethodological approach. That approach allows to identify 27 measurement items to cover the three dimensions of audit, reporting and taxation.

This research proposes a diagnostic tool specific to accounting firms. The authors have tested this index in the Tunisian context. The results show that there are two types of accounting firms. This study found the first firm in the embryonic phase and the other in the growth phase. This points out the active role of Tunisian accounting firms in technology integration.

This study highlights the integration of technology in the accounting field. Specifically, it aims to address technology management in accounting firms by measuring the degree of digitization of accounting firms. This research projects the use of information technologies (artificial intelligence, cloud, big data, etc.) in auditing, reporting and taxation.

On a practical level, this research provides an organizational diagnostic tool to assess the status of their accounting firms in terms of digitization. This will motivate practitioners to make frequent assessments, thus contributing to continuous improvement toward digitization.

The theoretical foundation of this research is based on the theory of the life cycle of technologies. This study is using this theory to identify and describe the current phase of the organization. And that is by indicating the overall scores on the technological capabilities of the accounting firms.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

Industry 4.0 is characterised by systemic transformations occurring exponentially, encompassing an array of dynamic processes and technologies. To move towards a more sustainable future, it is important to understand the nature of this transformation. However, construction enterprises are experiencing a capacity shortage in identifying the transitional management steps needed to navigate Industry 4.0 better. This paper presents a maturity model with the acronym “Smart Modern Construction Enterprise Maturity Model (SMCeMM)” that provides direction to construction enterprises.

It adopts an iterative procedure to develop the maturity model. The attributes of Industry 4.0 maturity are obtained through a critical literature review. The model is further developed through knowledge elicitation using modified Delphi-based expert forums and subsequent analysis through qualitative techniques. The conceptual validity of the model is established through a validation expert forum.

The research defines maturity characteristics of construction enterprises across five levels namely ad-hoc, driven, transforming, integrated and innovative encompassing seven process categories; data management, people and culture, leadership and strategy, automation, collaboration and communication, change management and innovation. The maturity characteristics are then translated into assessment criteria which can be used to assess how mature a construction enterprise is in navigating Industry 4.0.

The results advance the field of Industry 4.0 strategy research in construction. The findings can be used to access Industry 4.0 maturity of general contractors of varying sizes and scales and generate a set of recommendations to support their macroscopic strategic planning.

This study aims to develop and test an original conceptual framework that examines the role of various factors borrowed from three theories (i.e. Institutional Theory, Resource-Based View and Diffusion of Innovation) in adopting Human Resource Analytics (HRA).

A new conceptual framework (research model) is developed based on previous research and coherent theoretical arguments. Its factors are classified using the Technology–Organization–Environment (TOE) framework. Research hypotheses are tested using primary data collected from 152 managers of Greek organizations. Empirical data are analyzed using the “Structural Equation Modelling” (SEM) technique.

The technological and organizational context proved extremely important in enhancing Organizational Analytics Maturity (OAM) and HRA adoption, while the environmental context did not. Relative advantage and top management support were found to significantly impact the adoption of HRA, while Information Technology (IT) infrastructure, human resource capabilities and top management support are crucial for increasing OAM. Overall, the latter is the most important factor in enhancing HRA adoption.

This study contributes to the limited published research on HRA adoption while at the same time it can be used as a guideline for future research. The novel findings offer insights into the factors impacting OAM and HRA adoption.

The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

Identifying the criteria that effectively drive innovation in universities is critical to assessing their innovation maturity level, and hence, planning for the improvements required to reach a target level. This paper aims to propose a three-phase approach to develop a multidimensional maturity assessment framework used by university decision-makers to determine their level of innovation readiness.

First, a systematic collection of evaluation criteria from the literature is conducted. The results are mapped into different categories in a hierarchical and multidimensional way, and validated by experts. The second phase aims to identify the critical factors and their priorities, which are determined using analytic network process (ANP). To facilitate that, a panel of thirteen experts is formed and questionnaires are sent to rank the importance of the criteria and their elements. Finally, a maturity assessment tool is developed to complement the framework, allowing decision-makers to determine the level of innovation maturity with respect to each dimension and the overall position.

Results revealed three clusters, eight criteria and 26 subcriteria related to innovation in universities. The findings about the relative importance of the various attributes are reflected in the developed assessment tool and taken into consideration in the maturity indices computation approach.

To the best of the authors’ knowledge, this is the first attempt to develop a comprehensive list of innovation success drivers in universities and to use this list to design an innovation maturity assessment framework