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Article
Publication date: 22 December 2021

Majid Parchamijalal, Saeed Moradi and Mohsen Zabihi Shirazi

Claim formation is a fact and a regular occurrence in construction industry projects and often leads to a waste of money and time for organizations. Organizations can…

Abstract

Purpose

Claim formation is a fact and a regular occurrence in construction industry projects and often leads to a waste of money and time for organizations. Organizations can, however, reduce and control claims by promoting an integrated claim management system and improving productivity in the results of the claims. Establishing a claim management office is one of the ways to help organizations achieve this.

Design/methodology/approach

Based on library research, expert opinion and analysis of organizations' contracts as case studies and identifying the root causes of the claim, this paper proposes a claim management office maturity model and determines its levels.

Findings

This paper proposes a claim management office maturity model and also determines its levels. The general structure of this model is based on three parameters: “characteristics of each level,” “requirements of each level” and “transition period of each level” in five levels, where the first level is the most basic level and level five is the highest level of the implementation of a claim management office in the organization.

Originality/value

It can be clearly emphasized that this research is one of the first research studies that has dealt with the issue of claim management office in the construction industry and has proposed the model of maturity and development of claim management office in the organization. The use of numerous and experienced experts in achieving the results and case organizations to develop this research has increased the value and credibility of this research. This study also helps to improve the level of claim management in construction industry organizations so that these organizations can implement each level of claim management maturity model in the organization according to their competence and need for claim management. And by implementing it correctly, solve or reduce the problems of claim management in the organization and their projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 31 May 2021

Loay Salhieh and Waed Alswaer

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.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 14 June 2021

Sergey Yablonsky

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity

Abstract

Purpose

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity models (MMs) are the recognized tools to identify strengths and weaknesses of certain domains of an organization. They consist of multiple, archetypal levels of maturity of a certain domain and can be used for organizational assessment and development. In the case of AI, quite a few numbers of MMs have been proposed. Generally, the links between AI technology, AI usage and organizational performance stay unclear. To address these gaps, this paper aims to introduce the complete details of the AI maturity model (AIMM) for AI-driven platform companies. The associated AI-Driven Platform Enterprise Maturity framework proposed here can help to achieve most of the AI-driven platform companies' objectives.

Design/methodology/approach

Qualitative research is performed in two stages. In the first stage, a review of the existing literature is performed to identify the types, barriers, drivers, challenges and opportunities of MMs in AI, Advanced Analytics and Big Data domains. In the second stage, a research framework is proposed to align company value chain with AI technologies and levels of the platform enterprise maturity.

Findings

The paper proposes a new five level AI-Driven Platform Enterprise Maturity framework by constructing a formal organizational value chain taxonomy model that explains a vast group of MM phenomena related with the AI-Driven Platform Enterprises. In addition, this study proposes a clear and precise description and structuring of the information in the multidimensional Platform, AI, Advanced Analytics and Big Data domains. The AI-Driven Platform Enterprise Maturity framework assists in identification, creation, assessment and disclosure research of AI-driven platform business organizations.

Research limitations/implications

This research is focused on the basic dimensions of AI value chain. The full reference model of AI consists of much more concepts. In the last few years, AI has achieved a notable drive that, if connected appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in machine learning, especially in deep neural networks, the entire community stands in front of the barrier of explainability. Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models in industry. Our prospects lead toward the concept of a methodology for the large-scale implementation of AI methods in platform organizations with fairness, model explainability and accountability at its core.

Practical implications

AI-driven platform enterprise maturity framework can be used for better communicate to clients the value of AI capabilities through the lens of changing human-machine interactions and in the context of legal, ethical and societal norms.

Social implications

The authors discuss AI in the enterprise platform stack including talent platform, human capital management and recruiting.

Originality/value

The AI value chain and AI-Driven Platform Enterprise Maturity framework are original and represent an effective tools for assessing AI-driven platform enterprises.

Article
Publication date: 24 November 2020

Hadi Balouei Jamkhaneh and Abdol Hamid Safaei Ghadikolaei

The aim of this study is to develop a framework for measuring of service supply chain (SSC) maturity process.

Abstract

Purpose

The aim of this study is to develop a framework for measuring of service supply chain (SSC) maturity process.

Design/methodology/approach

The main framework of the SSC maturity was developed by reviewing the concepts and models of SSC, business excellence, maturity and supply chain performance evaluation. Then, the maturity level of each excellence criterion was defined in the proposed model by using the excellence criteria for SSC and the concept of Plan, Do, Check and Act (PDCA) cycle in combination with the process survey tools maturity model. Based on the excellence criteria and their maturity levels, a questionnaire was designed to practically measure the proposed framework.

Findings

The concepts and features of maturity levels defined for each of the excellence criteria were used to implement and operationalize the proposed framework and evaluate the SSC processes.

Practical implications

Through the assessment of the existing status of SSC processes, the findings allow managers to reach a better understanding of the strengths and weaknesses of such processes. Then, some opportunities are provided for improving each excellence criterion to enhance the performance of each process.

Originality/value

In fact, this study provides guidelines for organizations to measure their progress and performance and improve their management systems. The main advantages of the proposed SSC measurement framework include self-assessment facilitation, calculation of criteria scores and development of uses. The proposed model, like quality and productivity awards, can pave the way for increased competitiveness of the service industry.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 1
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 31 March 2021

Rhoda Ansah Quaigrain and Mohamed Hassan Issa

A review of the literature revealed a lack of coherent frameworks for implementing disability management, particularly within the construction industry. This study…

Abstract

Purpose

A review of the literature revealed a lack of coherent frameworks for implementing disability management, particularly within the construction industry. This study involved developing the construction disability management maturity model (CDM3) to assess the maturity of disability management (DM) practices in construction organisations.

Design/methodology/approach

In its current form, the model assessed twelve indicators using a series of questions representing relevant best practices for each indicator and five different maturity levels. An analytical hierarchical process was conducted using eight construction and DM experts to determine the weights of importance of these different indicators. The model was then applied to evaluate ten construction companies in Manitoba, Canada.

Findings

The results revealed that the indicators of “Return to Work”, “Disability and Injury Prevention”, and “Senior Management Support” practises were the most heavily weighted and, thus, the most important. Companies' DM performance was observed, on average, to be at the quantitatively managed level. “Senior Management Support” and “Disability Injury Prevention” practices were observed to be the most mature indicators on average, revealing a potential relationship between the most important and most mature indicators.

Research limitations/implications

The sample size of companies evaluated is a key limitation in that it does not permit for the generalisation of the results.

Practical implications

This study provided a framework for benchmarking the DM performance of construction organisations.

Originality/value

No similar maturity model has been developed to date to assess DM in construction, making the CDM3 the first of its kind to evaluate a construction organisation's existing DM practices against best practises.

Details

International Journal of Workplace Health Management, vol. 14 no. 3
Type: Research Article
ISSN: 1753-8351

Keywords

Article
Publication date: 28 December 2020

Kerem Elibal and Eren Özceylan

The purpose of this paper is to conduct a systematic literature review for industry 4.0 maturity modeling research studies to obtain a clear view of the current…

Abstract

Purpose

The purpose of this paper is to conduct a systematic literature review for industry 4.0 maturity modeling research studies to obtain a clear view of the current state-of-the-art. Identifying characteristics of the studies; gaps, limitations and highlighted features has been aimed to guide future research studies.

Design/methodology/approach

The study includes a systematic literature review conducted on Scopus, IEEE Xplore and Web of Science databases and 90 publications have been reviewed. A novel qualitative taxonomy has been constructed which aims to reduce the cognitive load of the readers.

Findings

While industry 4.0 maturity modeling is an emerging concept and taking researchers’ attraction, review studies are still in infancy. Current review papers are inadequate in getting a clear idea about the concept, especially from the perspective of guiding future researchers. By the conducted approach of classification conducted in this paper, it has been seen that there are some challenges for improving the industry 4.0 maturity modeling.

Research limitations/implications

Findings represented in this study can serve academicians and practitioners to develop and/or improve industry 4.0 maturity models.

Originality/value

The study includes a novel classification for the reviewed papers. Constructed taxonomy is among the first and tabular representations instead of prose analogy that aims to simplify the review of papers.

Article
Publication date: 28 September 2010

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.

3213

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.

Details

Supply Chain Management: An International Journal, vol. 15 no. 6
Type: Research Article
ISSN: 1359-8546

Keywords

Open Access
Article
Publication date: 31 December 2019

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…

1539

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.

Details

Journal of Intellectual Capital, vol. 21 no. 2
Type: Research Article
ISSN: 1469-1930

Keywords

Article
Publication date: 21 August 2019

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.

Details

Business Process Management Journal, vol. 26 no. 1
Type: Research Article
ISSN: 1463-7154

Keywords

Article
Publication date: 15 July 2020

Aras Okuyucu and Nilay Yavuz

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…

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.

Details

Transforming Government: People, Process and Policy, vol. 14 no. 4
Type: Research Article
ISSN: 1750-6166

Keywords

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