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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.

This 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 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.

A 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.

The 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.

The 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.

This study explores the influencing factors of the enterprise resource planning (ERP) readiness stage on project success immediately after go-live from the project manager’s perspective.

The influencing factors of the ERP readiness stage are explored through the literature and expert review sessions and are embedded in Kotter’s change management model. A survey-based empirical study is conducted among ERP project managers in Turkey in 2019 utilizing principal component analysis and multiple regression analysis to reveal the direct relation of influencing factors and project success.

Results show that the proposed model explains 65.179% of the variation with four components. The association of components through regression analysis reveals that project planning and management, employee commitment and change management directly relate to the ERP project success. Yet, surprisingly top management support is not directly correlated. Therefore, the results suggest that influencing factors of such long projects are to be evaluated by the stages of the project life cycle.

This research is limited to the project managers’ perspective in Turkey and the readiness stage of the project life cycle.

The objectives of this research serve as a guideline for ERP project managers to consider the success factors in terms of ERP project phases. This ensures that the project manager allocates optimum resources to the right factors at the right time.

Despite numerous studies in the ERP readiness stage, this study opens new ways of future research while filling several gaps. First, the ERP readiness phase is discussed with a theoretical approach through Kotter’s change management model. Second, the influencing factors of the ERP readiness stage on ERP project success from the project manager’s perspective are explored, and factor structures are revealed. Then, the association of the factors with ERP project success of “immediately after go-live” is empirically tested.

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.

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.

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.

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.

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.

Micro and small enterprises (MSEs) represent 99% of Peruvian firms, contribute 42% of Peru's Gross Domestic Product, and employ half of the country's labor force. Despite their relevance for the Peruvian Economy, they have low survival rates and are characterized by low productivity and processes inefficiencies. This chapter explores whether the adoption of Business and Supply Chain Management (SCM) practices influences MSEs' performance. We conducted a field study using data from 50 MSEs located in Piura, Peru, specifically from trade, service, and manufacturing sectors. We used the data collection guidelines from the MIT GeneSys to measure the firms' adoption of Business and SCM practices. Our results show that MSEs with higher adoption of Financial Planning, Supply Chain Planning, Supplier Relationship Management, Marketing, Procurement, and Stock Control practices are more likely to have higher revenue (i.e., sales). In addition, a multiple regression analysis reveals that while SCM practices do not seem to directly explain productivity growth in MSEs (as business practices do), they, however, seem to influence the performance of business practices, and, thus, have an indirect effect on the productivity growth of MSEs.