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1 – 10 of over 23000Edwin Juma Omol, Lucy Waruguru Mburu and Paul Anyango Abuonji
This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business…
Abstract
Purpose
This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business challenges to establishing a comparative analysis framework grounded in Resource Dependence Theory (RDT).
Design/methodology/approach
DMAM is based on positivist philosophy and objectivist epistemology, supported by Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). The methodology involves iterative development, from problem identification to creating a practical solution for assessing SMEs' digital maturity and guiding digitalization efforts.
Findings
DMAM offers a clear and specific methodology, distinguishing itself by addressing the unique needs of SMEs, particularly resource-dependent ones. The model’s development fills critical gaps in existing literature and provides a practical artifact for SMEs' digitalization.
Originality/value
DMAM is original in its focus on the specific needs of resource-dependent SMEs, offering actionable recommendations and addressing shortcomings in existing models. It serves as a foundational framework for SMEs' digital transformation, making a significant contribution to the digital maturity assessment literature.
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Batuhan Kocaoglu and Mehmet Kirmizi
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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Mehmet Kirmizi and Batuhan Kocaoglu
This study aims to analyze and synthesize the design features of existing digital transformation maturity models with a developed classification scheme and propose a generic…
Abstract
Purpose
This study aims to analyze and synthesize the design features of existing digital transformation maturity models with a developed classification scheme and propose a generic maturity model development wireframe based on design science research.
Design/methodology/approach
A systematic literature review is conducted on digital transformation maturity models in peer-reviewed journals, including the Emerald Insight, Science Direct, Scopus, Taylor & Francis and Web of Science databases, which resulted in 21 studies. A concept-centric tabular approach is used to analyze the studies, and intersectional demonstrations are used to synthesize the findings regarding the design features.
Findings
The classification scheme derived from the tabular concept-centric approach and iteratively evolved results in three main and 25 subcategories related to the design features. Analysis and synthesis of the studies reveal the granularity of the existing digital transformation maturity models concerning the design features. Furthermore, considering the design features in the classification scheme, a generic maturity model development wireframe is proposed to guide the researchers.
Research limitations/implications
The generic maturity model development wireframe and the classification scheme that represents the design features of existing maturity models guide the researchers for the maturity model development roadmap.
Originality/value
The existing literature review studies do not focus on the design feature of digital transformation maturity models within a systematic literature review perspective. A unique classification scheme derived from the tabular concept-centric approach aims to analyze the granularity level of the existing models. Furthermore, the generic maturity model development wireframe includes the guidelines and recommendations of design science studies and presents a roadmap for maturity model researchers.
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David Vance, Mingzhou Jin, Christopher Price, Sachin U. Nimbalkar and Thomas Wenning
The 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…
Abstract
Purpose
The 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/approach
Nineteen 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.
Findings
The 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 implications
Researchers 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/value
Compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.
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The purpose of this paper is to propose a maturity model to improve warehouse performance.
Abstract
Purpose
The purpose of this paper is to propose a maturity model to improve warehouse performance.
Design/methodology/approach
This paper will follow De Bruin et al’s (2005) suggested six relevant phases: scope, design, populate, test, deploy and maintain in developing the proposed maturity model. This study concentrates on the first five phases.
Findings
The proposed warehouse maturity model can be used as descriptive, benchmarking and a prescriptive with a road map for improvement.
Practical implications
The warehouse maturity model was proposed to let warehouse managers evaluate their practices and assess them by maturity level. Then, the proposed warehouse maturity model can be utilized to develop a set of plans for conducting projects to improve the warehouse practices, techniques and tools.
Originality/value
The proposed warehouse maturity model contributes to fill the shortages of maturity model addressing the warehouse environment. In particular, it provides a useful tool to establish the overall maturity level of a warehouse system. The proposed maturity model supports strategic decisions oriented toward improvement capabilities of the warehouse and to compete based on service level provided.
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Heriberto Garcia Reyes and Ronald Giachetti
This research aims to develop a supply chain maturity model so that Mexican firms can evaluate their current supply chain operations and develop an improvement road‐map.
Abstract
Purpose
This research aims to develop a supply chain maturity model so that Mexican firms can evaluate their current supply chain operations and develop an improvement road‐map.
Design/methodology/approach
The Delphi Method was used with 80 experts in Mexico. The Delphi Method gathers multiple perspectives on supply chain operations and delineates a path to reach a group consensus. The results lead to the specification of a supply chain maturity model S(CM)2. S(CM)2 is validated through experimentation and a pilot test to verify the ability of the model to help managers assess the supply chain processes of a firm by identifying their maturity level in each model viewpoint. A pilot test with a Mexican firm demonstrates the practical implementation of the model.
Findings
The research results in a meta‐model, called the supply chain maturity model S(CM)2, that describes supply chain maturity at five levels across multiple competency areas, and provides guidance to specify an improvement plan.
Research limitations/implications
The meta‐model was developed in Mexico and may not apply to the operations of supply chains in other countries. Additionally, the large scope of the meta‐model calls for further testing and refinement.
Practical implications
The research provides a means for firms to evaluate their supply chain operations and develop improvement plans.
Originality/value
The paper contributes by integrating the ideas of reference frameworks, capability maturity models, and improvement processes and demonstrates how a holistic meta‐model can be developed to evaluate supply chain operations.
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Bilge Yigit Ozkan, Marco Spruit, Roland Wondolleck and Verónica Burriel Coll
This paper presents a method for adapting an Information Security Focus Area Maturity (ISFAM) model to the organizational characteristics (OCs) of a small- and medium-sized…
Abstract
Purpose
This paper presents a method for adapting an Information Security Focus Area Maturity (ISFAM) model to the organizational characteristics (OCs) of a small- and medium-sized enterprise (SME) cluster. The purpose of this paper is to provide SMEs with a tailored maturity model enabling them to capture and improve their information security capabilities.
Design/methodology/approach
Design Science Research was followed to design and evaluate the method as a design artifact.
Findings
The method has successfully been used to adapt the ISFAM model to a group of SMEs within a regional cluster resulting in a model that is aligned with the OCs of the cluster. Areas for further investigation and improvements were identified.
Research limitations/implications
The study is based on applying the proposed method for the SMEs active in the transport, logistics and packaging sector in the Port of Rotterdam. Future research can focus on different sectors and regions. The method can be used for adapting other focus area maturity models.
Practical implications
The resulting adapted maturity model can facilitate the creation and further development of a base of common or shared knowledge in the cluster. The adapted maturity model can cut the cost of over implementation of information security capabilities for the SMEs with scarce resources.
Originality/value
The resulting adapted maturity model can facilitate the creation and further development of a base of common or shared knowledge in the cluster. The adapted maturity model can cut the cost of over implementation of information security capabilities for the SMEs with scarce resources.
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Marek Szelagowski and Justyna Berniak-Woźny
The purpose of this paper is to investigate whether the current business process management (BPM) maturity models meet the requirements of evaluating organizations in the…
Abstract
Purpose
The purpose of this paper is to investigate whether the current business process management (BPM) maturity models meet the requirements of evaluating organizations in the knowledge economy (KE) which manage processes in a dynamic way.
Design/methodology/approach
In this study, a content analysis of the OMG (2008) Business Process Maturity Model and ten research papers on the practical application of business process management maturity models was conducted. The nature of the study is descriptive and based solely on information from secondary data sources.
Findings
The research results reveal that the current BPM maturity models do not correspond with the knowledge-based organizations and take into account knowledge-intensive (usually dynamic) processes in a very limited way. That is why the adaptation of the current BPM maturity models to the KE is needed.
Originality/value
This paper contributes to the BPM theory and practice in two ways. First, it provides an enhanced insight into the requirements of the KE toward BPM and BPM maturity models by distinguishing between static and dynamic processes. Second, it formulates the recommendations on possible ways of adapting the current BPM maturity models to the requirements of the KE.
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Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the…
Abstract
Purpose
Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level.
Design/methodology/approach
A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al.’s Big Data maturity model and Kuraeva’s Big Data maturity model.
Findings
While Klievink et al.’s model is designed to evaluate Big Data maturity at the organizational level, Kuraeva’s model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government’s big data maturity such as legislative framework and national policy dimensions (strategic plans and actions).
Originality/value
This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. Based on the review, it provides insights about the development of integrated models to evaluate big data maturity in the public sector.
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