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The study aims to explore the available academic literature on the decision-making frameworks used in additive manufacturing management (AMM).

This research formulates a systematic literature review to determine the research trend of the decision-making framework in AMM. Further, the theory, context, characteristics, and methodology (TCCM) framework is used to identify the research gaps and suggest future research directions.

The systematic literature review (SLR) delves into overarching research themes within decision-making frameworks in AMM. Additionally, it uncovers trends in article publication, geographical distribution, methodologies utilized, and industry applications. This review not only reveals research gaps but also proposes directions for future exploration.

The key novelty of this research lies in revealing the five most contributing themes of decision-making frameworks in AMM, with the highest contributing theme being AM process selection, followed by part selection for AM. This finding enables decision-makers to make informed decisions to address similar problems while exploring AM technology. Moreover, this research introduces an AM part fabrication roadmap inspired by the literature review. Lastly, the paper highlights key research gaps for future research.

The purpose of this study is to identify the critical components of the reverse logistics (RL) disposition decision‐making process and suggest a decision framework that may guide future investigation and practice.

The authors utilized a problem‐driven content analysis methodology. RL literature from 2000 through 2010 was content analyzed to determine which components may impact a firm's RL disposition decision.

The authors extrapolated seven RL disposition decision components from a compilation of 60 variables identified in the literature. Practical implications and suggestions for future research are offered, and a RL disposition decision‐making framework is presented.

Although methodological techniques were carefully followed, the nature of a content analysis may be subject to author bias. Future investigation and use of the framework presented will verify the findings presented here.

This study identifies seven components that should be considered when deciding which RL disposition alternative should be adopted and integrates these components into a decision‐making framework. Supply chain professionals who refer to this framework during the decision process will benefit from a more comprehensive analysis of potential RL disposition alternatives.

Congruent with recent assertions suggesting that RL research is evolving from an operational‐level focus to a holistic business process approach for maximizing value recovery, this study synthesizes operational‐level research to develop a practical framework for RL disposition decision‐making.

This paper aims to present a strategic framework for make‐or‐buy (MoB) decision‐making process and a case study based on the framework. This framework can be applied to all the scenarios of MoB decision‐making that includes making decisions for new components and reevaluating the decisions for presently in‐sourced or outsourced components.

Based on this study of an Indian Automobile Company and review of the literature the paper proposes a strategic framework for MoB decision‐making. Unlike previous academic attempts, where a framework is developed first based on the existing theories followed by illustration through case studies, our approach starts with a case study, the paper then proposes a framework that best suits the company's need. Later the paper discusses the specific features of the framework that makes it applicable to other manufacturing sectors.

The sourcing decision‐making for any firm is a complex and dynamic process where, after stipulated period firms have to reevaluate their decisions. Existing frameworks treat both fresh and reevaluated decisions alike. It is found that the need for a framework with separate provision for outsourcing decision reevaluation. The paper identifies partial outsourcing as a strategic option to avoid supplier opportunism. It also explicitly suggests the exact decision point where risk evaluation is necessary during MoB decision‐making process.

The proposed framework takes a detailed and critical look at actual outcomes in terms of costs, competences and risk. Three important considerations adopted from the literature and incorporated in the proposed framework, makes it unique: provision for reevaluating the MoB decision, consideration of partial outsourcing as a strategic option other than purely making or buying, identification of decision points where risk evaluation is necessary.

Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM.

Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed.

In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified.

The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required.

The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.

The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

This study aims to predict artificial intelligence (AI) technology development and the impact of AI utilization activity on companies, to identify AI strategies dealing with the broad innovation activity of AI, and to construct the strategic decision-making framework of AI strategies for a small- and medium-sized enterprise (hereafter SME), to improve strategic decision-making practices of AI strategy in SMEs.

This study used the multiple methods on the design of two data collection stages. The first stage is an expertise-based approach. It organized the three groups of expert panels and conducted the Delphi survey on them in combination with the brainstorming of technology, innovation and strategy in the fourth industrial revolution. The second stage is in the complement approach of expertise-based results. It used the literature review to involve the analysis of academic and practical papers, reports and audio materials relating to technology development, innovation types and strategies of AI. Additionally, it organized the four semi-structured interviews. Finally, this study used the mind-map and decision tree to conduct each analysis and synthesize each analytical result.

This study identifies the precondition and four paths of AI technological development classifying into specialized AI, AI convergence with other technologies, general AI and AI control methods. It captures the impact of non- and technological innovation through AI on companies. Second, it identifies and classifies the six types of AI strategy: the bystander, capability-building, capability-holding, management-enhancing, market-enhancing and new-market-creating strategy. By using the decision tree, it constructs the strategic decision-making framework containing six AI strategies. Actionable points, strategic priorities and relevant instruments are suggested.

The strategic decision-making framework covering from AI technology development to utilization in a SME can help understand the strategic behaviours in SMEs. The typology of six AI strategies implies the broad innovation behaviours in SMEs. It can lead to further research to understand the pattern of strategic and innovation behaviour on AI.

This practical study can help executives, managers and engineers in SMEs to develop their strategic practices through the strategic decision framework and six AI strategies.

This practical study elicits the six types of AI strategy and constructs the strategic decision-making framework of six AI strategies from AI technology development to utilization. It can contribute to improving the practices of strategic decision-making in SMEs.

This study explored in-service educators' experience of using the Wisconsin Assistive Technology Initiative (WATI) for assistive technology (AT) decision-making within Singapore schools.

The study adopted a qualitative design. Eight educators across both mainstream and special education schools were introduced to the WATI framework which they subsequently employed as a trial experience for a student under their care. Written feedback gathered from participants was analysed to identify common issues and themes regarding the use of the WATI framework for AT decision-making.

The comprehensive consideration of a broad scope of different factors, provision of a structured process for AT decision-making, as well as a common language for use by different stakeholders emerged as key benefits of implementing the WATI. Challenges encountered include administrative struggles in gathering different stakeholders together, time and resource constraints and difficulties in loaning AT devices for trial use.

Based on educators' feedback, recommendations to facilitate the adoption of the WATI for AT decision-making within Singapore schools are discussed and considered. This study also highlights the need for greater AT instruction within both preservice and in-service teacher preparation programmes in Singapore.

Schools in Singapore currently rarely adopt any frameworks in place to guide educators through a systematic process of AT consideration. It is anticipated that this study will spearhead and drive the adoption of systematic frameworks such as the WATI for better AT decision-making within Singapore schools.

The peer review history for this article is available at: https://publons.com/publon 10.1108/JET-03-2021-0015

The purpose of this study is to build a proposal for an integrated analysis / evaluation / decision / implementation framework to suit entrepreneurial companies intending to redefine their strategic behaviours and their competitive schemes in the global environment.

A conceptual approach, based on theoretical perspectives relating to globalisation-based management and decision-making of entrepreneurs, is adopted.

The paper presents a conceptual framework useful for supporting entrepreneurial decisions for global strategies, drawing on an integrated analysis of external environment and internal components, with a specific focus on the entrepreneur's characteristics in terms of cognitive and emotional profiles. It is suggested to adopt a logical process aimed at identifying which strategic levers are available for entrepreneurial players to implement their strategies.

Entrepreneurial decision-making may benefit from an integrated framework which helps entrepreneurs, who aim to compete in the global marketplace, to explore and exploit all the key factors useful to defining their strategies.

There is a lack of decision-making frameworks that put the entrepreneur at the centre and, at the same time, present a potential balance between the external factors (globalisation drivers and local opportunities) and the resources and competences required to manage risks and difficulties of the global environment (internal factors). The originality of the proposed framework consists in filling this gap. Moreover, this framework can be useful for “re-born global” or “global-again” firms that are currently a neglected typology of studied firms.

This purpose of this paper is to provide insight through analysis of the data collected from a pilot study, into the decision-making process used by organizations in cybersecurity investments. Leveraging the review of literature, this paper aims to explore the strategic decisions made by organizations when implementing cybersecurity controls, and identifies economic models and theories from the economics of information security, and information security investment decision-making process. Using a survey study method, this paper explores the feasibility for development of a strategic decision-making framework that may be used when evaluating and implementing cybersecurity measures.

A pilot study was conducted to evaluate the ways in which decisions are made as it relates to cybersecurity spending. The purpose of the pilot study was to determine the feasibility for developing a strategic framework to minimize cybersecurity risks. Phase 1 – Interview Study: The qualitative approach focused on seven participants who provided input to refine the survey study questionnaire. Phase 2 – Survey Study: The qualitative approach focused on information gathered through an online descriptive survey study using a five-point Likert scale.

The literature review identified that there is limited research in the area of information security decision making. One paper was identified within this area, focusing on the research completed by Dor and Elovici [22]. This exploratory research demonstrates that although organizations have actively implemented cybersecurity frameworks, there is a need to enhance the decision-making process to reduce the number and type of breaches, along with strengthening the cybersecurity framework to facilitate a preventative approach.

The partnership research design could be expanded to facilitate quantitative and qualitative techniques in parallel with equal weight, leveraging qualitative techniques, an interview study, case study and grounded theory. In-depth data collection and analysis can be completed to facilitate a broader data collection which will provide a representative sample and achieve saturation to ensure that adequate and quality data are collected to support the study. Quantitative analysis through statistical techniques (i.e. regression analysis) taking into account, the effectiveness of cybersecurity frameworks, and the effectiveness of decisions made by stakeholders on implementing cybersecurity measures.

This exploratory research demonstrates that organizations have actively implemented cybersecurity measure; however, there is a need to reduce the number and type of breaches, along with strengthening the cybersecurity framework to facilitate a preventative approach. In addition, factors that are used by an organization when investing in cybersecurity controls are heavily focused on compliance with government and industry regulations along with opportunity cost. Lastly, the decision-making process used when evaluating, implementing and investing in cybersecurity controls is weighted towards the technology organization and, therefore, may be biased based on competing priorities.

The outcome of this study provides greater insight into how an organization makes decisions when implementing cybersecurity controls. This exploratory research shows that most organizations are diligently implementing security measures to effectively monitor and detect cyber security attacks. The pilot study revealed that the importance given to the decisions made by the CIO and Head of the Business Line have similar priorities with regard to funding the investment cost, implementing information security measures and reviewing the risk appetite statement. This parallel decision-making process may potentially have an adverse impact on the decision to fund cybersecurity measures, especially in circumstances where the viewpoints are vastly different .

Cybersecurity spend is discussed across the literature, and various approaches, methodologies and models are used. The aim of this paper is to explore the strategic decision-making approach that is used by organizations when evaluating and implementing cybersecurity measures. Using a survey study method, this paper explores the feasibility for development of a strategic decision-making framework that may be used when evaluating and implementing cybersecurity measures.