The maturity of maturity model research: A systematic mapping study

Maturity models assess the prevailing capability level and proffer the necessary capabilities for effective adoption in a systematic roadmap. This is considered essential to achieve diffusion of the emerging technologies. The paper provides a guide to maturity model development in the digitisation era. This study adopted scientometrics and meta-synthesis to critically review and provide guidance on maturity model development. Firstly, bibliographic data was collected from the Scopus database and analysed using Scientometrics. Secondly, developed BIM maturity models were critically reviewed. The study identified areas of maturity model deployment and the industries of deployment. It also identified the present areas of deployment of maturity models. The second aspect critically reviewed selected BIM maturity models through stated parameters and outlined the necessary criteria for maturity model development. Maturity model is widely adopted to achieve optimisation and proper assessment in various industries. The study identified the industries where it is deployed and identified the areas of maturity model deployment in the digitisation era. In addition, it was observed that some existing BIM maturity models do not conform to the various requirements expected of a maturity model. The study is unique in the methods adopted to achieve its results. Also, it identified the areas of maturity model deployment. The study is helpful as it provides the criteria for maturity model development hereafter, while also helping BIM users choose among the existing BIM maturity models. The study is crucial for proper maturity model development in the digitisation era.

Maturity models are valuable instruments for IT managers because they allow the assessment of the current situation of a company as well as the identification of reasonable improvement measures. Over the last few years, more than a hundred maturity models have been developed to support IT management. They address a broad range of different application areas, comprising holistic assessments of IT management as well as appraisals of specific subareas (e. g. Business Process Management, Business Intelligence). The evergrowing number of maturity models indicates a certain degree of arbitrariness concerning their development processes. Especially, this is highlighted by incomplete documentation of methodologies applied for maturity model development. In this paper, we will try to work against this trend by proposing requirements concerning the development of maturity models. A selection of the few well-documented maturity models is compared to these requirements. The results lead us to a generic and consolidated procedure model for the design of maturity models. It provides a manual for the theoretically founded development and evaluation of maturity models. Finally, we will apply this procedure model to the development of the IT Performance Measurement Maturity Model (ITPM3).

The fourth industrial revolution and accompanying digital transformation has progressed dramatically in recent years. The new digital revolution, mostly known as Industry 4.0, introduces impressive changes in the way enterprises and organizations are operating in a globalized world and altering the well-established lifestyle of a society. Therefore, it is of utmost importance to identify the current capabilities of companies in the context of Industry 4.0. Current literature on Industry 4.0 maturity and assessment models underlies the importance of a proper development strategy with exact steps to perform. Design principles address the issue of systematizing the measurable and attainable steps for further development. The present study contributes towards the identification of the research gap in the presence of core Industry 4.0 design principles during the development of maturity models. The analysis of 12 chosen maturity models by eight core design principles was provided. This research can serve as a starting point for the development of a complex strategic roadmap and thereby to provide a successful transition from traditional manufacturing into Industry 4.0.

Maturity models are widespread in research and in particular, IT practitioner communities. However, theoretically sound, methodologically rigorous and empirically validated maturity models are quite rare. This systematic mapping paper focuses on the challenges faced during the development of maturity models. More specifically, it explores the literature on maturity models and standard guidelines to develop maturity models, the challenges identified and solutions proposed. Our systematic mapping revealed over six hundred articles on maturity models. Extant literature reveals that researchers have primarily focused on developing new maturity models pertaining to domain-specific problems and/or new enterprise technologies. We find rampant re-use of the design structure of widely adopted models such as Nolan’s Stage of Growth Model, Crosby’s Grid, and Capability Maturity Model (CMM). We also identify three dominant views of maturity models and provide guidelines for various approaches to constructing maturity models with a standard vocabulary. We finally propose using process theories and configurational approaches to address the main theoretical criticisms with regard to maturity models and conclude with some recommendations for maturity model developers.

The systematic mapping study (SMS) is a relatively new method of generating new information from existing studies. First defined as a methodology in 2007, it offers a method to filter existing information to produce novel insight into the observed research domain, and pinpoint new directions of research. In this study, the systematic mapping study method was utilized to determine how SMS as a method has spread and was utilized during the first decade since its conceptualization. In general, it was found that the SMS method is still at its early phase in utilization, and is mainly used in software engineering and healthcare studies, but also in several other scientific domains. SMS research and the scientific outputs rely on transparent protocols when conducting the actual search and identification process, and so far, the applied protocol and research procedure correlates strongly with the application domain; different domains have their own protocols. The SMS method can be recommended, for example, when the aim is to gain knowledge on how a specific topic is studied and where there are research gaps. There are still areas that are debated or where successful implementation is difficult, the biggest problems being the amount of work it requires and possible lack of quality analysis of the articles.

Organizations in various industries have widely developed the artificial intelligence (AI) maturity model as a systematic approach. This study aims to review state-of-the-art studies related to AI maturity models systematically. It allows a deeper understanding of the methodological issues relevant to maturity models, especially in terms of the objectives, methods employed to develop and validate the models, and the scope and characteristics of maturity model development. Our analysis reveals that most works concentrate on developing maturity models with or without their empirical validation. It shows that the most significant proportion of models were designed for specific domains and purposes. Maturity model development typically uses a bottom-up design approach, and most of the models have a descriptive characteristic. Besides that, maturity grid and continuous representation with five levels are currently trending in maturity model development. Six out of 13 studies (46%) on AI maturity pertain to assess the technology aspect, even in specific domains. It confirms that organizations still require an improvement in their AI capability and in strengthening AI maturity. This review provides an essential contribution to the evolution of organizations using AI to explain the concepts, approaches, and elements of maturity models.

PurposeThis study aims to propose a novel maturity model development framework based on design science theory utilizing qualitative and quantitative methods for empirical evidence and develops a descriptive digital transformation maturity model by using the proposed framework.Design/methodology/approachDesign science theory is deeply explored and extended to propose a novel maturity model development approach, including robust and rigorous validation processes. Thus, three consecutive discussion sessions and evaluations with experts are carried out iteratively to evolve and saturate the efficiency and utility of the maturity model, and consensus among experts at each session is validated by the intra-class correlation (ICC) coefficient. Furthermore, the Wilcoxon signed rank test is utilized to test whether there is a difference between consecutive sessions. Finally, prototype testing as a pilot study and two case studies in the manufacturing industry are carried out to validate the applicability of the developed maturity model.FindingsA 3-phase maturity model development framework that includes the activities and outcomes in each phase emerge based on the design science theory. The comparative literature analysis and discussion sessions resulted in six dimensions, ten sub-dimensions, 39-capability items that circumscribe the digital transformation concept and five maturity levels that demonstrate conceptual consistency and a measurement tool for self-assessment. In addition, prototype testing and case studies show that the developed maturity model can measure the company's maturity level. Finally, it is proven that the digital transformation maturity model is developed by following the proposed maturity model development framework.Practical implicationsThe maturity model draws a framework for practitioners that facilitate an initial roadmap and enhance the adoption rate, and it motivates the practitioners for frequent and efficient assessments, thus helping the continuous improvement of the digital transformation journey.Originality/valueThe originality of this paper lies in proposing a novel maturity model development framework based on design science and presents the activities and validation methods for this purpose. Furthermore, a comprehensive and rigorously validated digital transformation maturity model is developed based on the proposed framework.

Aim/Purpose: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics.

PurposeThe purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability.Design/methodology/approachNineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions.FindingsThe five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance.Practical implicationsResearchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories.Originality/valueCompared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

Background: Maturity models have been developed to assist organizations to enhance software quality, and the software engineering community has proposed numerous types of these, most of them based on CMM, ISO/IEC 15504 and CMMI-DEV. The great proliferation of maturity models leads to a need for systematic approaches to build them. Aim: To discover and analyze the existing methods and recommended practices for developing maturity models. Method: A systematic literature review (SLR) was conducted. Results: 1500 papers were returned as a result of the searches, from which 23 were chosen as candidates, and 7 of these, published between 2005 and 2010, were eventually selected as primary studies. Conclusions: The proposal of methods for maturity models development is an emerging topic in literature. Most published maturity models are based on practices and success factors from projects that showed good results in an organization or industry, but which lack a sound theoretical basis and methodology. The proposed methods highlight as main activities: to establish goals for maturity model development, to design model architecture, to set out capability levels and dimensions, to and pilot testing. However, the creation of an assessment questionnaire and specific activities for maintenance are poorly supported. The SLR results have served to propose a method for developing maturity models that is focused on product quality characteristics.

This paper presents a systematic mapping study based on literature and industrial survey related to assistive technologies for people with dementia. The world population of the ageing people is increasing both in developed and developing countries, so does the number of people with dementia. Consequently assistive technologies are getting much importance from academic researchers and industry as an aid for people with dementia. Assistive technologies are helping people with dementia to perform activities which otherwise are not possible for them without external help. Systematic mapping studies are popular in other fields like software engineering, yet this methodology is mostly ignored in assistive technology research. Literature survey indicates that there is no systematic mapping study conducted so far on assistive technologies for people with dementia. Thus, we are motivated to conduct this systematic mapping study on assistive technologies for people with dementia. As per the study nature, we carried out a thorough literature and industrial survey. The results indicates that current available assistive technologies can be classified into five major types i.e. robotics, health monitoring, prompts and reminders, communication and software. There is rich literature available on first three categories while communication and software based assistive technologies need more attention, whereas the industrial focus is mostly on health monitoring and software based assistive technologies. The mapping study results emphasize the need for industry to invest more efforts in communication and software based assistive technologies.

The aim of this paper is the scientific development of a maturity model concerning the digital transformation of companies within the manufacturing industry’s supply chain. The rather “broad” and dispersed “mega-trend” of digitalization is expected to play an increasingly important role for companies as well as for the (digital) supply chain of the future. Such a model comprises the objective of addressing fundamental components, complementary innovations and relevant terminologies, like smart products, Cyber-Physical Systems (CPS) and Big Data Analytics. Scientific rigor is achieved through conducting grounded theory research and in-depth interviews as methods of data collection and evaluation. Furthermore, relevant aspects concerning the development and construction of maturity models are discussed, before a suitable and scientifically elaborated maturity model concerning digitalization emerges from the course of investigation and its value for economic practice as well as for the scientific community is specified.

Quality attribute traceability (QAT), as a sub-discipline of software traceability, ensures that quality attributes are considered in all phases of software development. QAT is one of the most critical and challenging research areas in requirement engineering. In recent years, several studies have been conducted on quality attribute traceability. However, researchers in this field have problems to identifying the research status of this field due to the lack of a comprehensive secondary study that reveals research trends and gaps. Evidence-based software engineering (EBSE) proposes systematic mapping study (SMS) and systematic literature review (SLR) methods for secondary studies on software engineering. In this paper we use the semantically enhanced SMS method in the QAT research area. In order to improve SMS, we introduce a concept classification approach. In this approach by using a QAT domain ontology, the keywords classification process is improved. The most important innovation of this study is the presentation of the QAT research tree. This research tree has been created by gathering research topics identified in this field along with existing gaps. Identified research topics include “QAT Approach,” “QAT Development,” “QAT Model,” “QAT Framework,” and “QAT Algorithm”. The results also indicate that “QAT Frameworks” is a research trend, and most recent studies have focused on this topic. On the other hand, “Trace Maintenance” and “Trace Integrity” are the research gaps in this field. In this article, active researchers, journals, conferences and countries in the field of QAT are also introduced. We also introduce a set of tools that facilitate the SMS process.

Software project management is a relatively recent discipline that emerged during the second half of the 20th century (Kwak, 2003). Many of the software project management methodologies available today were developed in Western/European countries and research showed that there was a need to formalise a software project management framework for developing countries, in particular Africa (Muriithi & Crawford, 2003). Based on surveys and discussions with software professionals, a methodology for software project management is being proposed. The methodology is based on a maturity model as Mauritius is faced with a shortage in skilled professionals. So far, few organisations in Mauritius have been found to be using software project management methodologies developed in Western/European countries. Most maturity models, for example Capability Maturity Model Integration (CMMI) and Kerzner’s maturity model, have five maturity levels. The trend is towards the development of maturity models that have fewer maturity levels. For example, the Organisational Project Management Maturity Model (OPM3) and Prince 2 Maturity Model have been developed with three maturity levels.

Usability evaluation methods for the web: A systematic mapping study