Search results

Global building failures, such as the Grenfell Tower fire in London, UK, emphasised the need for trustworthy building handover information for safety. However, a notable gap remains in understanding how reliable handover information can ensure the safety of occupants. This study aims to investigate the use and essential quality of handover information to understand the effects of the quality of information on the management of commercial buildings.

Ninety-four participants from nine organisations who regularly use handover information to manage multiple commercial buildings participated in the semi-structured interviews. Qualitative thematic coding using interview transcripts was performed to identify the utilisation of handover information and its quality requirements.

This study reveals that as-built drawings and product information are predominately used to fulfil statutory obligations, comply with the organisation’s internal policies, evaluate asset valuation and make informed decisions about capital investment and operating expenses. The quality dimensions of “accuracy”, “timeliness”, and “completeness” are preferred in combination to achieve desired outcomes.

This study focused on using handover information in the management of commercial buildings. However, its results can offer valuable perspectives for improving its application across various sectors in the built environment.

The findings affirm the need for quality handover information for safety, compliance and efficient management in commercial buildings.

This research significantly contributes to the current knowledge of handover information in the building sector. Given the study findings, building owners are equipped to define specific handover information requirements and quality requisites.

How organisations interact with and respond to environmental pressures has been a long-term interest of organisational scholars. Still, it remains an under-theorised phenomenon from a project perspective. So far, there is limited understanding of how projects, which are composed by a constellation of organisations, “respond” to institutional pressures that are exerted on them. This research takes the perspective of projects as adopters/implementers of institutional pressures and analyses how they interact with, and respond to, such pressures. More specifically, this research explores how construction projects respond to the pressure of a Building Information Modelling (BIM) mandate.

Multiple in-depth case studies were conducted to explore the practical implementation of a BIM mandate in the UK and understand how the construction projects responded to the coercive pressures to implement a new policy mandate for process digitalisation. Multiple sources were employed for data collection and the data were analysed inductively. The findings identify a hybrid response comprising four distinct ways that projects might respond to an institutional pressure.

We find that projects decouple both from the content and from the intended purpose of a policy, i.e. there are two variance of a policy-practice decoupling phenomenon in projects. The findings also reveal the underlying conditions leading to decoupling.

We advance decoupling literature so that it better applies to the temporary, distributed and interdependent work conducted via projects. Second, we define decoupling in projects as a provisional and fragmented process of wayfinding through heterogeneous institutional spaces, and discuss the potential policy-practice assemblages in projects, influenced by how, if and when project members' activities decouple from the many and often contradicting institutional pressures they face. Third, we discuss how the qualitatively different forms of decoupling that we identified in our work may act as part of a legitimation process in ambiguous situations whereby projects might share a resemblance of conformity with institutional pressures when they are de facto only partially conforming to them.

Sustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors.

This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM.

This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.

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.

Building Information Modeling (BIM) capabilities have been studied at the individual, project, organizational, and even industry levels to ensure the realization of BIM value in the architectural, engineering, construction, and operation industry. However, limited research has focused on a project owner organization perspective to investigate owner BIM capabilities that are required to ensure effective project management and delivery. This present study aims to propose an indicator framework to evaluate owner BIM capabilities at the organizational level.

Leveraging the existing literature on BIM capabilities and synthesizing insights from the resource-based view and information technology capabilities research, this study conceptualizes the BIM capabilities of project owner organizations and offers a framework of indicators for measurement. Semi-structured interviews with BIM experts and a questionnaire survey were conducted to identify key indicators affecting owner BIM capabilities. A six-dimensional structural equation model with 29 indicators was then established.

The findings highlight the multidimensionality of owner BIM capabilities and show that process capabilities play a crucial role in enhancing owner BIM capabilities, while technical capabilities are considered as the least important aspect.

The study sheds light on the key role of project owner organizations in ensuring BIM value and suggests that project owners focus more on the organizational processes of introducing BIM in managing projects.

This study reconceptualizes owner BIM capabilities drawing on the idea of resource-based view and information technology capabilities and highlights the important dimensions and indicators of owner BIM capabilities at the organizational level.

The versatility of customer relationship management (CRM) systems has kept these technologies popular over the years. These solutions have been integrated into organizations of all sizes, from large corporations to small- and medium-sized enterprises. Similarly, CRM systems have also found applications in all types of industries and business sectors. All this has been the driving force behind the proliferation of CRM solutions around the world. In this chapter, the author not only reflects on the impact and democratization of CRM systems on business management and marketing strategies but also explores how these technologies can determine the company's income. In particular, the author presents an experiment that analyzes the extent to which the volume of annual investment in CRM solutions can be used to predict annual net income in a sample of companies. Using time series analysis and applying the autoregressive integrated moving average modeling technique, the researcher examines a sample of 10 companies from different industries, and countries, over a 20-year period. The results show the efficiency of the predictive models developed in nine of the 10 companies analyzed. The findings of this study allow us to conclude that there seems to be an association between the investments made in CRM solutions and the income of the companies that invest in these technologies.

The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and social good. A review related to diverse policy approaches of various countries remains a research gap, and hence the analysis in the paper is designed with the intention of developing a research framework and providing policy gaps for further exploration.

A systematic review of academic and non-academic literature on theoretical foundations, applications of NPD for economic and social good and NPD policies and regulations was conducted to identify the evaluation criteria. A total of 32 dimensions got identified for evaluation. As second step, content analysis was used for evaluation. A total of 13 documents from 6 countries and 1 geographical region were identified for evaluation. The documents were evaluated based on the 32 dimensions spread across 5 domains that facilitate data access and sharing for economic and societal benefit.

The analysis highlights three distinct emerging perspectives on data exchange: most policy and regulatory documents acknowledge the importance of identifying different types of NPD and accordingly describing the distinct roles and responsibilities of data actors for leveraging the data; the policy and regulatory frameworks clearly focus on increasing business opportunities, data sharing cooperation and innovation; and findings also demonstrate certain gaps in the policy frameworks such as a more comprehensive discussion on data access and sharing mechanisms, particularly data sandboxes and open data, and concrete norms and rigorous standards regarding accountability, transparency, ownership and confidentiality. Furthermore, policies and regulations may include appropriate incentive structures for data providers and users to ensure unhindered and sustainable access to data for the common good.

To the best of the authors’ knowledge, this paper represents one of the first research contributions evaluating global data policies focused on NPD in the context of its increasing use as a public good. The paper first identifies evaluation criteria for the analysis on public and social good, and, thus, provides a conceptual framework for future research. Additionally, the analysis identifies the broad domains of policy analysis on social and public good for data economics.

This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.

A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.

Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.

Implications are limited to the e-commerce B2C domain.

The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.

The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

The advent of Industry 4.0 (I4.0) and the requirements imposed on companies still need to be clarified. Companies still strive to understand I4.0 requirements and technological, organizational, operational and management challenges. Current literature on I4.0 underlies the importance of a roadmap with structured steps to achieve the benefits of I4.0, mainly focused on augmenting operational performance. Therefore, this paper proposes a roadmap to implement I4.0 focused on operational management concepts, mainly aiming to augment operational performance and bridge the gap between theory and practice regarding roadmaps focused on the operational management dimension.

This paper follows a research approach divided into the following stages: a literature review to analyze the I4.0 roadmaps and identify the main components of I4.0; development of the proposed I4.0 roadmap presented; field research to test the roadmap by collecting data from a manufacturing company in the automotive industry; validation of the roadmap through modeling and simulation.

The authors presented a production line design with real-time control, fast response, shop floor coordination and predictive capacity. The results prove that the proposed I4.0 roadmap augments operation performance in the investigated automotive company. The main results were work in process reduction, lead time reduction, output increase, real-time control, shop floor coordination and fast response.

The main novelty of the proposed roadmap is to move toward I4.0 implementation with a focus on the operational management dimension. The roadmap has an innovative combination of the two approaches – lean manufacturing and factory physics – a straightforward roadmap with only three steps: (1) requirements, (2) real-time control and (3) predictive capacity, a structured definition of the approaches and operational management concepts fundamental in each step.