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The purpose of this paper is to investigate two current transformation processes in the construction industry: the adoption of a novel material, cross-laminated timber (CLT), and the enhancement of digital transformation. This paper depicts the actors and interaction in the business network that is emerging around CLT construction and, in particular, how digital transformation (that is, the deployment of Construction 4.0 solutions) occurs in this business network.

Digital transformation is a relatively new phenomenon in CLT construction, and the authors, therefore, adopt a qualitative inductive research approach and rely on semi-structured interviews.

The findings of this paper suggest that it is critical for actors to adopt an interorganizational perspective in CLT construction, instead of only focusing on internal operations. An interorganizational perspective supports successful CLT construction, as well as the deployment of Construction 4.0 solutions. This will bring about the benefits of digital transformation in the construction industry.

This paper investigates the network created around CLT construction in Finland but more generally illustrates the change toward Construction 4.0 solutions.

For managers, this paper explicates the importance of networking, instead of focusing on the internal development of the company, when adopting novel solutions emerging from both construction and information technology-related advancements.

Stability and traditions are characteristic of the construction industry. New technical solutions and materials, together with calls for sustainability, have challenged the traditional ways of constructing, and for example, the development of CLT construction has led to an emergence of new business networks. This material-related process and the ongoing digital transformation of business form an interesting context for an empirical-based analysis of changing interaction and networks. This paper gives the first insights into how digital transformation can benefit the evolution of the network.

Despite the technological paradigm shift presented to the architecture, engineering, construction and operations sector (AECO), the full-fledged acceptance of the building information modelling (BIM) methodology has been slower than initially anticipated. Indeed, this study aims to acknowledge the need for increasing supportive technologies enabling the use of BIM, attending to available human resources, their requirements and their tasks.

A complete case study is described, including the development process centred on design science research methodology followed by the usability assessment procedure validated by construction projects facility management operational staff.

Results show that participants could interact with BIM using openBIM processes and file formats naturally, as most participants reached an efficiency level close to that expected for users already familiar with the interface (i.e. high-efficiency values). These results are consistent with the reported perceived satisfaction and analysis of participants’ discourses through 62 semi-structured interviews.

The contributions of the present study are twofold: a proposal for a virtual reality openBIM framework is presented, particularly for the semantic enrichment of BIM models, and a methodology for evaluating the usability of this type of system in the AECO sector.

The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process.

A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights.

The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector.

The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry.

The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.

Buildings and their use is a complex process from design to occupation. Buildings produce huge volumes of data such as building information modelling (BIM), sensor (e.g. from building management systems), occupant and building maintenance data. These data can be spread across multiple disconnected systems in numerous formats, making their combined analysis difficult. The purpose of this paper is to bring these sources of data together, to provide a more complete account of a building and, consequently, a more comprehensive basis for understanding and managing its performance.

Building data from a sample of newly constructed housing units were analysed, several properties were identified for the study and sensors deployed. A sensor agnostic platform for visualising real-time building performance data was developed.

Data sources from both sensor data and qualitative questionnaire were analysed and a matrix of elements affecting building performance in areas such as energy use, comfort use, integration with technology was presented. In addition, a prototype sensor visualisation platform was designed to connect in-use performance data to BIM.

This work presents initial findings from a post occupancy evaluation utilising sensor data. The work attempts to address the issues of BIM in-use scenarios for housing sector. A prototype was developed which can be fully developed and replicated to wider housing projects. The findings can better address how indoor thermal comfort parameters can be used to improve housing stock and even address elements such as machine learning for better buildings.

This study aims to facilitate consistency of information in building information modelling (BIM) and address the current BIM gaps through the perspectives of the productization concept and product structure (PS).

The study follows a conceptual research approach in conjunction with a single case study. First, the previous studies on BIM implementation, productization and PS are reviewed. Further, a case study is used to analyse the current state of productization in the construction sector and develop a functional PS for construction.

A Part-Phase-Elements Matrix is proposed as a construction-specific PS to facilitate consistency in information and to enhance BIM. The proposed matrix provides new avenues to facilitate consistent information exchange through the interconnection between conceptual PS and standard building objects library, and encourage collaborative communication between stakeholders.

This study explores the core of the productization concept and PS as means to facilitate consistency of information and thus address the current gaps in BIM. This as building projects progressively move towards systematic modular and prefabricated construction where the flow of reliable information about product and construction offerings becomes increasingly important.

Technological change drives transformation in most sectors of the economy. Industry 4.0 technologies have been applied at different stages of a building’s lifecycle. However, limited studies exist on their application in real estate facilities management (REFM). This study aims to assess the existing knowledge on the topic to suggest further research directions.

Scopus-indexed literature from 2013 to 2023 was examined and visualised using VOSviewer software to output quantitative (descriptive) results. Content analysis was used to complement the quantitative findings.

Findings indicated a concentration of research in China, Norway and Italy. The knowledge areas included three clusters: lifecycle integration and management, data curation and management and organisational and management capabilities. The benefits, challenges and support strategies were highlighted.

More collaboration is needed across countries and territories on technology integration in REFM. Future research using alternative methodologies is recommended, with a focus on adopting and non-adopting REFM organisations. Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

The study reveals the knowledge base on technology use in REFM. It adds to the evidence base on innovation and technology adoption in REFM.

The purpose of this study is to identify the key data categories and characteristics defined by asset information requirements (AIR) and how this affects the development and maintenance of an asset information model (AIM) for a blockchain-based digital twin (DT).

A mixed-method approach involving qualitative and quantitative analysis was used to gather empirical data through semistructured interviews and a digital questionnaire survey with an emphasis on AIR for blockchain-based DTs from a data-driven predictive analytics perspective.

Based on the analysis of results three key data categories were identified, core data, static operation and maintenance (OM) data, and dynamic OM data, along with the data characteristics required to perform data-driven predictive analytics through artificial intelligence (AI) in a blockchain-based DT platform. The findings also include how the creation and maintenance of an AIM is affected in this context.

The key data categories and characteristics specified through AIR to support predictive data-driven analytics through AI in a blockchain-based DT will contribute to the development and maintenance of an AIM.

The research explores the process of defining, delivering and maintaining the AIM and the potential use of blockchain technology (BCT) as a facilitator for data trust, integrity and security.

Political Corporate Social Responsibility (CSR), based on ideas about deliberative democracy, have been criticised for increasing corporate power and democratic deficits. Yet, deliberative ideals are flourishing in the corporate world in the form of dialogues with a broad set of stakeholders and engagement in wider societal issues. Extractive industry areas, with extensive corporate interventions in weak regulatory environments, are particularly vulnerable to asymmetrical power relations when businesses engage with society. This paper aims to illustrate in what way deliberative CSR practices in such contexts risk enhancing corporate power at the expense of community interests.

This paper is based on a retrospective qualitative study of a Canadian oil company, operating in an Albanian oilfield between 2009 and 2016. Through a study of three different deliberative CSR practices – market-based land acquisition, a grievance redress mechanism and dialogue groups – it highlights how these practices in various ways enforced corporate interests and prevented further community mobilisation.

By applying Laclau and Mouffe’s theory of hegemony, the analysis highlights how deliberative CSR activities isolated and silenced community demands, moved some community members into the corporate alliance and prevented alternative visions of the area to be articulated. In particular, the close connection between deliberative practices and monetary compensation flows is underlined in this dynamic.

The paper contributes to critical scholarship on political CSR by highlighting in what way deliberative practices, linked to monetary compensation schemes, enforce corporate hegemony by moving community members over to the corporate alliance.

German (corporate-) real estate management departments have been facing the challenge of poor data quality for years. This holds them back from generating efficiency potentials via the use of new methods from the field of digitalisation and from coping with the increasing requirements from the ESG context. The purpose of this paper is to explore why German (corporate-) real estate managements (do not) share data with their real estate service providers to address the data quality challenge and identify possible solutions.

To answer the research question, the reasoned action approach, an established theory from psychology for predicting human behaviour, is used. The relationships between the constructs are determined using linear regression. The study participants are almost exclusively from Germany.

The organisational milieu (perceived behavioural control) has a significant impact on the behaviour of sharing data with real estate service providers. Especially the change of contractual arrangements (data-driven contracts) seems to be crucial for the improvement of information logistics.

To the best of the author’s knowledge, for the first time, the reasoned action approach is used within the German real estate industry to predict organisational behaviour in the context of digitalisation.

This study aims to access, analyze and highlight opportunities and problems of the Indian pharmaceutical sector in the broader national health-care industry. The recent changes in the field, at the institutional and corporate levels, have placed India in the spotlight of the global pharmaceutical market, but several threats and weaknesses could limit this expansion.

Descriptive and inferential analyses have been based on empirical data extracted from authenticated data sources. Subsequently, a narrative strengths, weaknesses, opportunities and threats analysis was performed based on the results of prior investigations and on qualitative data that were retrieved from a marketing intelligence examination to generate an overall scenario analysis.

Indian pharmaceutical companies have faced several challenges on various fronts. In the home market, drug prices are controlled by the drug price control order; therefore, there is strong pressure on revenues and subsequently on costs. In the international market, threats derived from pharmaceutical multinational companies are emerging as tough obstacles to overcome.

More focus on patents for innovative drugs is required, instead of concentrating primarily on generic drugs. There is a need for policymakers to work on the sustainability and development of the industry, while the companies must redesign their orientation toward enhancing innovation capabilities. In addition, at the level of corporate strategy, firms should establish collaborations and alliances and expand their industrial marketing vision.

This study provides a global overview of the potential growth and development of the Indian pharmaceutical sector, comparing it with internal trends and external competition. The most relevant contribution of the research relies on the shift to innovative production that Indian companies must adopt (after years of focusing only on generic drugs), and in this vein, appropriate industrial marketing solutions are indispensable.