Transdisciplinary systems approach to realization of digital transformation

Hashmi, Muhammad Adnan; Mo, John P.T.; Beckett, Ronald C.

doi:10.1016/j.aei.2021.101316

Cited by 15 publications

(4 citation statements)

References 76 publications

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“…From a technical perspective, system integration is a common issue for technical effectiveness [40,41]. The two main dimensions involving business and technology are also confirmed by Hashmi et al [42] to accommodate the digital transformation of industries. Based on these works, the preliminary framework employs the principles of BI to ensure that the use of different BIM applications fits the human-computer hybrid information processing in BIM-based AECO practices.…”

Section: Preliminary Frameworkmentioning

confidence: 79%

Justifying the Effective Use of Building Information Modelling (BIM) with Business Intelligence

Yuan

et al. 2022

Buildings

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Although building information modelling (BIM) is a widely acknowledged information and communication technology (ICT) in the architecture, engineering, construction, and operation (AECO) industry, its implementation is hindered by the hybrid practice of BIM and non-BIM information processing, and sometimes, it fails to add value to the AECO business. It is crucial to define, on a scientific base, how to ensure the effective use of BIM regarding the various conditions in which to apply BIM in AECO practices. Although several studies have investigated similar topics, very few have focused on the adoption of distinct BIM applications over the conventional practice from the perspective of business intelligence (BI) as a theoretical framework to justify the effective value of BIM use in the AECO. This study proposes a framework relying on BI principles to justify effective BIM use and explicates the contextual factors in AECO practices. The data were acquired from a three-round Delphi survey. The framework suggests that effective BIM use in AECO practices should follow the two principles of BI: achieving technical effectiveness and realizing business value. The pursuit of technical effectiveness should consider business objectives, business issues, business sustainability and regulatory eligibility, and the realization of business value involves willingness to adopt BIM, human-computer interoperability, visualization-based data quality and sources, data processing and system integration, and application maturity. This study provides a new perspective by which to address the issue of the technological iteration in the current hybrid BIM and non-BIM practice and could help to improve BIM implementation in the AECO industry.

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Section: Preliminary Frameworkmentioning

confidence: 79%

Justifying the Effective Use of Building Information Modelling (BIM) with Business Intelligence

Yuan

et al. 2022

Buildings

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“…Such general topics indicated DT research in this period is at an infancy stage of clarifying the concepts and basic elements that constitute DT. Since 2013, the implementation of DT in industry field had rapidly emerged as the key focus of DT studies, especially in the manufacturing, educational and healthcare sectors [such as 108,109,111,112,118,133,140]. In the same period, digital platforms were also brought out for their values in accoupling with digital technologies to enable DT [61,62,63,103,114].…”

Section: Sep Analysismentioning

confidence: 99%

“…Again, this limitation makes us invite researchers for another line of research about how capabilities enabling DT might differ based on contextual factors in practice. For example, a recent study in this journal [140] has developed a transdisciplinary system design to describe a generic model applicable to any industry sector going through a DT.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Çetindamar

Min

et al. 2021

Advanced Engineering Informatics

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Digital transformation (DT) is prevalent in businesses today. However, current studies to guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly what DT is and the capabilities needed to enable it successfully. With the aim of filling the gaps, this paper presents a novel bibliometric framework that unearths clues from scientific articles and patents. The framework incorporates the scientific evolutionary pathways and hierarchical topic tree to quantitatively identify the DT research topics' evolutionary patterns and hierarchies at play in DT research. Our results include a comprehensive definition of DT from the perspective of bibliometrics and a systematic categorization of the capabilities required to enable DT, distilled from over 10,179 academic papers on DT. To further yield practical insights on technological capabilities, the paper also includes a case study of 9,454 patents focusing on one of the emerging technologies -artificial intelligence (AI). We summarized the outcomes with a four-level AI capabilities model. The paper ends with a discussion on its contributions: presenting a quantitative account of the DT research, introducing a process based understanding of DT, offering a list of major capabilities enabling DT, and drawing the attention of managers to be aware of capabilities needed when undertaking their DT journey.

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“…Neste contexto, Sistemas transdisciplinares com numerosos processos interconectados(HASHMI et al, 2021), tal como o conjunto de domínios da TD apresentados na Tabela 01, podem ser considerados Sistemas de Sistemas. 2020).…”

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A importância da ciência de dados como facilitador de tomadas de decisão na gestão das cadeias de abastecimento

Silveira de Oliveira

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This research studies the phenomenon of Digital Transformation (DT) by investigating a SYSTEM consisting of four disciplines: Supply Chain Management (SCM), Knowledge Management, Artificial Intelligence (AI) and Data Science (DSc). The hypotheses of the research are: (H1) the profiles of absorption of the knowledge of the SYSTEM, in different countries, are similar when there is a common knowledge base absorbed in these countries; and (H2): the profiles of application of knowledge about the SYSTEM, among countries that share a common basis of this knowledge, are similar. The study categorized into domains the factors that influence DT. A method was developed that combines questionnaire formulation techniques and sampling of very large populations, with more than 5,000 individuals. A questionnaire was sent to 13,479 rigorously selected individuals to study a target population of 37,592 professionals registered on LinkedIn. The 844 valid responses from 60 countries show that companies worldwide make decisions in SCM based on DSc processes that use AI practices to address the Big Data generated by Stakeholders. We conclude that the stage of absorption and application of the measured knowledge is similar in the countries studied. In the context of the Knowledge Economy society, without rigid barriers capable of preventing the transfer of knowledge, the implications of this mechanism include the consolidation of a common knowledge base between countries and the consolidation of similar levels of maturity related to the application of this knowledge. An additional contribution is that the method, which follows a clear sequence of tasks, provides the expected values for the Sampling Rate, Return Rate and Sample Error in surveys with very large target population on LinkedIn. Consequently, it is possible to reverse situations such as the drop-in response rate, low selectivity of the target population and little representativeness of very large populations. The method can be applied in surveys, transdisciplinary or not, of various areas of science, strengthening the credibility of the conclusions elaborated from the results obtained. Additionally, the Sampling and Results Matrix (SRM), a key element of the methodology, is a valuable tool for the academic benchmark, organizing the same indicators present in different studies and stimulating the standardization of interpretations of results by the scientific community.

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Transdisciplinary systems approach to realization of digital transformation

Cited by 15 publications

References 76 publications

Justifying the Effective Use of Building Information Modelling (BIM) with Business Intelligence

Justifying the Effective Use of Building Information Modelling (BIM) with Business Intelligence

Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

A importância da ciência de dados como facilitador de tomadas de decisão na gestão das cadeias de abastecimento

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