scholarly journals Integration of BIM and advanced digital technologies to the end of life decision-making process: a paradigm of future opportunities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aurora Abruzzini ◽  
Sepehr Abrishami
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Conceptual Framework ◽  
End Of Life ◽  
Digital Technologies ◽  
Learning Technologies ◽  
Digital Data ◽  
Decision Making Process ◽  
Content Type ◽  
Building Information

Purpose At the end of a building’s lifecycle, there are several limitations to the decision-making process (DMP). There is a lack of data available from the building’s history, the difficulty in assessing the condition of a building and the variety of stakeholders’ needs that have to be satisfied. The purpose of this paper is to answer the question: how would end-of-life (EOL) DMP change when buildings will have been digitally built? The answer will be illustrated through a conceptual framework. Design/methodology/approach A qualitative analysis of the existing literature has been performed to identify the elements within building information modelling (BIM) and advanced digital technologies that could be of support to the DMP. The findings have been collected and summarised in a conceptual framework that has been validated and enhanced through online interviews with industry experts. Findings The enhanced framework has identified that BIM technology would bring the benefit of providing the initial digital data source, from which machine learning and data analytics would then extract the relevant data needed to measure accurately the criteria during the analysis of the EOL options put on the table. Originality/value The findings of this research could contribute to developing the software modules making the bridge between BIM and machine learning technologies, to implement them in the EOL DMP.

A conceptual framework for wisdom-based decision-making process in audit profession

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hoang To Loan Nguyen
Keyword(s):  
Decision Making ◽  
Grounded Theory ◽  
Conceptual Framework ◽  
Research Process ◽  
Decision Making Process ◽  
Ethical Orientation ◽  
Content Type ◽  
External Auditors ◽  
Wise Decision ◽  
Knowledge Assimilation

PurposeWisdom is considered as crucial in decision-making in both management and auditing practice. This research aims to investigate the concept of wisdom in auditing, thereby empirically exploring the determinants of wisdom in audit decision-making and explaining inter-relations among these determinants.Design/methodology/approachThis study employs grounded theory methodology that is based on in-depth interviews with twenty-seven practicing auditors who are audit partners, managers, seniors and assistants of auditing firms. Guided by the grounded theory, data collection and data analyses were conducted simultaneously to look into the new insights of the research phenomenon. The coding process was constantly compared until the research's theoretical saturation is reached after four rounds. At the end of the research process, the study conducted a survey to confirm the proposed framework as well as examine the inter-relationships between the defined determinants.FindingsResults suggest developing a conceptual framework to interpret wisdom-based decision-making process in auditing. A wise process of audit decision-making is defined as an integrated exercise of multiple determinants including knowledge assimilation, judgmental ability and ethical orientation. The research also explains and examines the potential interrelationships among these determinants in the audit decision-making process.Practical implicationsWisdom is a valuable tacit ability for all external auditors. The development of wise decision-making abilities of auditors should be considered an integral part of multiple virtues including knowledge and judgmental and ethical aspects.Originality/valueThe contributions of this study are original and significant because it proposes a new approach to explain for the audit decision-making process and enhances better understandings of the concept of wisdom in auditing practices and its roles in audit decision-making.

scholarly journals Building information modelling to support maintenance management of healthcare built assets

Facilities ◽  
2019 ◽  
Vol 37 (7/8) ◽  
pp. 415-434 ◽  
Author(s):  
Nadeeshani Wanigarathna ◽  
Keith Jones ◽  
Adrian Bell ◽  
Georgios Kapogiannis
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Conceptual Framework ◽  
Asset Management ◽  
Building Information Modelling ◽  
Content Type ◽  
Information Modelling ◽  
Wide Range ◽  
Building Information ◽  
Use Phase

Purpose This paper aims to investigate how digital capabilities associated with building information modelling (BIM) can integrate a wide range of information to improve built asset management (BAM) decision-making during the in-use phase of hospital buildings. Design/methodology/approach A comprehensive document analysis and a participatory case study was undertaken with a regional NHS hospital to review the type of information that can be used to better inform BAM decision-making to develop a conceptual framework to improve information use during the health-care BAM process, test how the conceptual framework can be applied within a BAM division of a health-care organisation and develop a cloud-based BIM application. Findings BIM has the potential to facilitate better informed BAM decision-making by integrating a wide range of information related to the physical condition of built assets, resources available for BAM and the built asset’s contribution to health-care provision within an organisation. However, interdepartmental information sharing requires a significant level of time and cost investment and changes to information gathering and storing practices within the whole organisation. Originality/value This research demonstrated that the implementation of BIM during the in-use phase of hospital buildings is different to that in the design and construction phases. At the in-use phase, BIM needs to integrate and communicate information within and between the estates, facilities division and other departments of the organisation. This poses a significant change management task for the organisation’s information management systems. Thus, a strategically driven top-down organisational approach is needed to implement BIM for the in-use phase of hospital buildings.

Evolution of national heritage inventories for Scotland and Wales

2016 ◽  
Vol 6 (2) ◽  
pp. 113-127 ◽  
Author(s):  
Peter McKeague ◽  
David Thomas
Keyword(s):  
Decision Making ◽  
Digital Technologies ◽  
Renewable Resource ◽  
Building Blocks ◽  
Evidence Base ◽  
Digital Data ◽  
Content Type ◽  
National Heritage ◽  
Access To Knowledge ◽  
The Impact

Purpose – The purpose of this paper is to present a review of the origins and development of national inventories in Scotland and Wales from paper-based records to digital databases. The impact of digital technologies on data management and dissemination is considered. Design/methodology/approach – Exploring the evolution of historic environment inventories in Scotland and Wales highlights the common issues faced and solutions adopted. In considering the longue durée, the durability and flexibility of information is highlighted. Findings – Inventories may combine locational, descriptive and visual material to help document a fragile, finite and non-renewable resource. They provide the evidence base for decision making and stewardship in managing change, stimulating interest in and valuing the historic environment. Contribution to recognised inventories should be a requirement for activities documenting the historic environment. Digital technologies shape the expectations of a modern inventory and associated digital archives, with emphasis placed on the repurposing of inventory contents so that they can better contribute to an information network serving multiple audiences. Social implications – Transformation from paper records to digital data has radically enhanced and democratised access to knowledge about the historic environment. Digital delivery helps place heritage data within mainstream societal activities and fosters public interest and engagement in the historic environment. Originality/value – Inventories are the foundation building blocks of informed decision making. Digital technologies have transformed these resources to help place the historic environment within mainstream societal activities and interest.

Decision-making framework with double-loop learning through interpretable black-box machine learning models

2017 ◽  
Vol 117 (7) ◽  
pp. 1389-1406 ◽  
Author(s):  
Marko Bohanec ◽  
Marko Robnik-Šikonja ◽  
Mirjana Kljajić Borštnar
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Decision Making ◽  
Organizational Learning ◽  
Decision Making Process ◽  
Organizational Setting ◽  
Business Decision ◽  
Content Type ◽  
Industry Standard ◽  
General Explanation

Purpose The purpose of this paper is to address the problem of weak acceptance of machine learning (ML) models in business. The proposed framework of top-performing ML models coupled with general explanation methods provides additional information to the decision-making process. This builds a foundation for sustainable organizational learning. Design/methodology/approach To address user acceptance, participatory approach of action design research (ADR) was chosen. The proposed framework is demonstrated on a B2B sales forecasting process in an organizational setting, following cross-industry standard process for data mining (CRISP-DM) methodology. Findings The provided ML model explanations efficiently support business decision makers, reduce forecasting error for new sales opportunities, and facilitate discussion about the context of opportunities in the sales team. Research limitations/implications The quality and quantity of available data affect the performance of models and explanations. Practical implications The application in the real-world company demonstrates the utility of the approach and provides evidence that transparent explanations of ML models contribute to individual and organizational learning. Social implications All used methods are available as an open-source software and can improve the acceptance of ML in data-driven decision making. Originality/value The proposed framework incorporates existing ML models and general explanation methodology into a decision-making process. To the authors’ knowledge, this is the first attempt to support organizational learning with a framework combining ML explanations, ADR, and data mining methodology based on the CRISP-DM industry standard.

Measuring intellectual capital in a firm belonging to a strategic alliance

2015 ◽  
Vol 16 (1) ◽  
pp. 174-198 ◽  
Author(s):  
Stefania Veltri ◽  
Andrea Venturelli ◽  
Giovanni Mastroleo
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Intellectual Capital ◽  
Strategic Alliances ◽  
Strategic Alliance ◽  
Empirical Work ◽  
Organizational Level ◽  
Decision Making Process ◽  
Content Type ◽  
Scant Attention

Purpose – The purpose of this paper is to propose a method to measure intellectual capital (IC) in firms involved in strategic alliances, an area that has received scant attention in the literature, as existing research is focused mainly on organizational level mainly and increasingly on macro-level unit such as regions or nations. There are very few works at the meso-level (i.e. alliances, clusters), and the paper aims to fill this void, by providing researchers and practitioners with a tool capable of combining measurement and management aims, developed at organizational level with the active participation of the researchers. Design/methodology/approach – The method of analysis is based on a model formalized through a fuzzy expert system (FES). The FES are able to merge the capabilities of an expert system to simulate the decision-making process with the vagueness typical of human reasoning, maintaining the ability to still have a numeric value as a response. Its construction requires the participation of experts, whose knowledge of the problem is accumulated in the form of blocks of rules. These features make it possible to formalize the decision-making process related to the IC valuation, handling qualitative and quantitative variables, and exploring the cognitive mechanisms underlying this process. Findings – The outcome of the application is a system designed to measure the intangible performance deriving from participation in a strategic alliance using FES. This study contributes to the broadening of the research community’s understanding regarding the alternative measurement of IC created within strategic alliances. Research limitations/implications – To the best of the authors’ knowledge, IC literature lacks methods expressly designed to measure the incremental value of IC originating from collaboration among firms. From a measurement perspective, the results may be regarded as valuable proof that IC performance within strategic alliances can be measured quantitatively. Practical implications – On the management side, the possibility of retracing the determinants of different IC intermediate indicators composing the final IC index allows strategic alliances managers to use this information for decision-making purposes. Originality/value – To the best of the authors’ knowledge this is the first study applying FES to measure IC in a firm belonging to a strategic alliance. In the authors’ opinion, fuzzy logic methodology, recently applied in empirical work designed to evaluate IC, represents a reliable methodology because of the “fuzzy” nature of IC.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

Integration between knowledge management and business process management and its impact on the decision making process in the construction sector: a case study of Jordan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sami Wasef Abuezhayeh ◽  
Les Ruddock ◽  
Issa Shehabat
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Decision Makers ◽  
Decision Making Process ◽  
Construction Sector ◽  
Content Type

Purpose The purpose of this paper is to investigate and explain how organizations in the construction sector can enhance their decision-making process (DMP) by practising knowledge management (KM) and business process management (BPM) activities. A conceptual framework is developed that recognises the elements that impact DMP in terms of KM and BPM. The development of this framework goes beyond current empirical work on KM in addition to BPM as it investigates a wider variety of variables that impact DMP. Design/methodology/approach A case study is undertaken in the context of the construction industry in Jordan. A theoretical framework is developed and assessment of the proposed framework was undertaken through a questionnaire survey of decision-makers in the construction sector and expert interviews. Findings The outcomes of this research provide several contributions to aid decision-makers in construction organizations. Growth in the usage of KM and BPM, in addition to the integration between them, can provide employees with task-related knowledge in the organization’s operative business processes, improve process performance, promote core competence and maximise and optimise business performance. Originality/value Through the production of a framework, this study provides a tool to enable improved decision-making. The framework generates a strong operational as well as theoretical approach to the organizational utilization of knowledge and business processes.

Evaluation of barriers in the adoption of halal certification: a fuzzy DEMATEL approach

2019 ◽  
Vol 14 (1) ◽  
pp. 153-174 ◽  
Author(s):  
Shahbaz Khan ◽  
Mohd Imran Khan ◽  
Abid Haleem
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Specific Region ◽  
Integrative Approach ◽  
Decision Making Process ◽  
Management Support ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Certification System ◽  
Expert’S Opinion

PurposeHigher level of customer satisfaction for halal products can be achieved by the effective adoption of halal certification through assessment and accreditation (HCAA). There are certain issues that seem detrimental towards the adoption of HCAA. The purpose of this paper is to identify the major barriers towards the adoption of HCAA and evaluate inter-relationships among them for developing the strategies to mitigate these barriers.Design/methodology/approachThe barriers towards the adoption of HCAA are identified through an integrative approach of literature review and expert’s opinion. The inter-relationship among the identified barriers is evaluated using fuzzy-based decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique, which categorises them into influential and influenced group.FindingsThe evaluation of inter-relationship among barriers using fuzzy DEMATEL indicates four influencing barriers and six influenced barriers towards the adoption of HCAA. Further, findings suggest an extensive government, and management support is vital in terms of commitment, resources and actions to realise the benefits attributed with HCAA.Research limitations/implicationsThe inter-relationship among barriers is contextual and based on the perception of experts which may be biased as per their background and area of expertise. This study pertains to a specific region and can be extended to the generalised certification system.Originality/valueThe empirical base of the research provides the inter-relationship among the barriers towards the adoption of HCAA which can be effectively used as input in the decision-making process by producers, manufacturers and distributor. The policy maker can analyse the cause group and effect group of barriers to formulate policies that would help in the adoption of HCAA.

Decision making, distributed leadership and the objective knowledge growth framework

2019 ◽  
Vol 34 (2) ◽  
pp. 217-231
Author(s):  
Stephanie Chitpin
Keyword(s):  
Decision Making ◽  
Distributed Leadership ◽  
School Leaders ◽  
Decision Makers ◽  
Decision Making Process ◽  
Objective Knowledge ◽  
Content Type ◽  
Education Leaders ◽  
Knowledge Growth ◽  
Analytical Approaches

Purpose The purpose of this paper is to know the extent to which a decision-making framework assists in providing holistic, comprehensive descriptions of strategies used by school leaders engaging with distributed leadership practices. The process by which principals and other education leaders interact various school-based actors to arrive at a distributed decision-making process is addressed through this paper. The position taken suggests that leadership does not reside solely with principals or other education leaders, but sustains the view that the actions of various actors within a school setting contribute to fuller and more comprehensive accounts of distributed leadership. Design/methodology/approach While the application of rational/analytical approaches to organizational problems or issues can lead to effective decisions, dilemmas faced by principals are often messy, complex, ill-defined and not easily resolved through algorithmic reason or by the application of rules, as evidenced by the two stories provided by Agnes, a third-year principal in a small countryside elementary school in a small northeastern community, and by John, a novice principal in a suburb of a large Southwestern metropolitan area. Findings The value of the objective knowledge growth framework (OKGF) process is found in its ability to focus Agnes’s attention on things that she may have overlooked, such as options she might have ignored or information that she might have resisted or accepted, as well as innumerable preparations she might have neglected had she not involved all the teachers in her school. Research limitations/implications The implementation of the OKGF may appear, occasionally, to introduce unnecessary points along this route and may not be laboriously applied to all decision-making situations. However, the instinctively pragmatic solutions provided by this framework will often produce effective results. Therefore, in order to reduce potentially irrational outcomes, the systematic approach employed by the OKGF is preferable. The OKGF must be managed, implemented and sustained locally if it is to provide maximum benefits to educational decision makers. Practical implications Given the principals’ changing roles, it is abundantly clear that leadership practice can no longer involve just one person, by necessity, and it is becoming increasingly difficult to imagine how things could have been accomplished otherwise. Expecting the principal to single-handedly lead efforts to improve instruction is impractical, particularly when leadership may be portrayed as what school principals do, especially when other potential sources of leadership have been ignored or treated as secondary or unimportant because that leadership has not emanated from the principal’s office (Spillane, 2006). In this paper, the authors have striven to reveal how a perspective of distributed leadership, when used in conjunction with the objective knowledge growth framework, can be effective in assisting principals in resolving problems of practice. Social implications Different school leaders of varying status within the educative organization benefit from obtaining different answers to similar issues, as evidenced by John’s and Agnes’s leadership tangles. Lumby and English (2009) differentiate between “routinization” and “ritualization.” They argue, “They are not the same. The former erases the need for human agency while the latter requires it” (p. 112). The OKGF process, therefore, cannot provide school leaders with the “right” answers to their educative quandaries, simply because any two school leaders, facing the same issues, may utilize differing theories, solutions, choices or options which may satisfy their issues in response to their own individual contextual factors. Similarly, in a busy day or week, school leaders may be inclined to take the shortest distance between two points in the decision-making process; problem identification to problem resolution. Originality/value Should the OKGF process empower decision makers to obtain sound resolutions to their educative issues by assisting them in distancing themselves from emotions or confirmation biases that may distract them from resolving school problems, its use will have been worthwhile.

scholarly journals Data competence maturity: developing data-driven decision making

2018 ◽  
Vol 11 (2) ◽  
pp. 139-158 ◽  
Author(s):  
Thomas G. Cech ◽  
Trent J. Spaulding ◽  
Joseph A. Cazier
Keyword(s):  
Decision Making ◽  
Secondary Education ◽  
Data Science ◽  
Data Driven ◽  
Decision Making Process ◽  
Maturity Model ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Development Data ◽  
Education Performance

Purpose The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education. Findings The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process. Practical implications Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes. Originality/value This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

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