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Facilities management (FM) plays a key role in the performance of businesses to ensure the comfort of users and the sustainable use of natural resources over operation and maintenance. Nevertheless, reactive maintenance (RM) services are characterised by delays, waste and difficulties in prioritising services and identifying the root causes of failures; this is mostly caused by inefficient asset information and communication management. While linking building information modelling and the Internet of Things through a digital twin has demonstrated potential for improving FM practices, there is a lack of evidence regarding the process requirements involved in their implementation. This paper aims to address this challenge, as it is the first to statistically characterise RM services and processes to identify the most critical RM problems and scenarios for digital twin implementation. The statistical data analytics approach also constitutes a novel practical approach for a holistic analysis of RM occurrences.

The research strategy was based on multiple case studies, which adopted university campuses as objects for investigation. A detailed literature review of work to date and documental analysis assisted in generating data on the FM sector and RM services, where qualitative and statistical analyses were applied to approximately 300,000 individual work requests.

The work provides substantial evidence of a series of patterns across both cases that were not evidenced prior to this study: a concentration of requests within main campuses; a balanced distribution of requests per building, mechanical and electrical service categories; a predominance of low priority level services; a low rate of compliance in attending priority services; a cumulative impact on the overall picture of five problem subcategories (i.e. Building-Door, Mechanical-Plumbing, Electrical-Lighting, Mechanical-Heat/Cool/Ventilation and Electrical-Power); a predominance of problems in student accommodation facilities, circulations and offices; and a concentration of requests related to unlisted buildings. These new patterns form the basis for business cases where maintenance services and FM sectors can benefit from digital twins. It also provides a new methodological approach for assessing the impact of RM on businesses.

The findings provide new insights for owners and FM staff in determining the criticality of RM services, justifying investments and planning the digital transformation of services for a smarter provision.

This study represents a unique approach to FM and provides detailed evidence to identify novel RM patterns of critical service provision and activities within organisations for efficient digitalised data management over a building’s lifecycle.

This study aims to improve the use of digitalization in facilities management (FM) for shopping complex facilities in the post-COVID-19 era. The resumption of economic activities, especially in shopping complexes, poses challenges for FM with throngs of shoppers. To tackle these challenges, enhanced and innovative FM practices are necessary.

The study used a qualitative research approach, incorporating case studies, interviews, observations and documentation. It focused on super-regional shopping complexes in the Klang Valley, Malaysia, selecting two complexes for qualitative data collection. Supplementary data were gathered from various sources, including government policy publications, websites, books, journal papers and archival records.

The research provides valuable insights into FM innovations and the application of FM digitalization in shopping complexes after the COVID-19 pandemic. It also addresses challenges faced by FM teams during this period. Recommendations for implementing FM digitalization in super-regional shopping complexes post-COVID-19 include developing skilled personnel, defining appropriate work scopes, strategies and policies, using cost-effective software, and increasing occupant awareness. The involvement of outsourced service providers is advised, emphasizing their understanding of the organization’s business model and innovative approaches.

The findings offer new perspectives on the characteristics of FM digitalization in the commercial sector during business disruptions caused by the pandemic. The proposed strategies are grounded in real industry implementations, aiming to enhance the FM digitalization approach for improved business performance.

This paper aims to empirically investigate how knowledge coordination is carried out within and across expert teams in the outsourcing service desk context from the standpoint of the information and communication technologies (ICT) provider.

The authors draw on an embedded case study to unravel the mechanisms used by expert teams to achieve knowledge coordination. Data collection included semi-structured interviews and document analysis over eight months.

Four groups of coordination mechanisms were found according to their nature and role in helping MESA achieve its organizational goals. The authors also identified how this set of mechanisms responds to the task-resource dependency and how it evolves over time to provide reliable ICT services. Furthermore, the analysis of four knowledge coordination dimensions inside each group uncovers the complexity of coordination in the studied context, with the “who” dimension being predominant across the groups. The analysis further reveals that the content (what) and mode of coordination (how) of each group respond to elements in the knowledge coordination process relevant for the different stages of the ICT service delivery process.

The case study addresses how people in outsourced services coordinate their knowledge to manage the interdependencies among the involved organizations and thus, achieving their goals. This study extends previous research that had analyzed the consequences of knowledge coordination for providers and customers by delving into the mechanisms used in this process from the provider’s point of view.

While the three lines model (TLM) provides an organizational structure to execute risk and control duties, research and practice show limitations in the model's implementation. These limitations result in governance issues. Such issues, together with control weaknesses, could be addressed by leveraging properties of distribution, transparency, and immutability of blockchain technology. To this end, in this paper the authors propose a conceptual control framework based on blockchain technology to augment control practice.

The design of the resulting blockchain-based control framework (BBCF) and its prototype, based on the design science research methodology (DSRM), is presented and discussed in terms of the potential impact in the context of the identified problems within the TLM.

One potential outcome of BBCF could be to redefine the scope and boundaries of some of the activities in audit and control practices from a more static to a more dynamic and prospective role. In a larger context of improving governance practices, the BBCF could set the path for a more inclusive and participatory interaction between the different governance actors of an organization.

However, this assumes that blockchain is more widely adopted despite its complexity and rigidity.

BBCF covering both a conceptual model design and a reference implementation provides an innovation in audit and control. BBCF could include all relevant stakeholders who have an interest in corporate governance and control activities, including the regulators.

The contribution intends to serve both as a starting point for discussing the evolution of audit and control practice based on blockchain technology, as well as an initial actionable prototype for experimentation and further development.

The UAE is among the fastest-growing facilities management (FM) markets globally. Nevertheless, conclusive evidence on this market is scarce in the literature. Therefore, this paper aims to provide an in-depth insight into the FM market in the UAE.

Fourteen interviewees were purposively selected to provide insight into FM status through their field experiences. A SWOT analysis of their answers held place.

Interviewees revealed that the main trends of FM in the UAE include interests in sustainability, integration of technology, health and safety, outsourcing FM, switching to total facilities management (TFM), and performance management systems use. Besides, the quality of the service in the FM market is driven by the real-estate boom, services sophistication, the increasing awareness of FM and focus on the quality of services. Furthermore, the interviews found that the recruitment of poorly skilled labors can threaten the FM market to meet the allocated budget, misperception of FM, the value of money, the lack of continuous follow-up with recent advancements in technologies and the lack of performance measurement models.

This paper highlights the major trends, drivers and threats of the FM market in the UAE, and the implications of its findings can direct FM organizations and researchers in their practices.

Cloud computing services gained huge attention in recent years and many organizations started moving their business data traditional server to the cloud storage providers. However, increased data storage introduces challenges like inefficient usage of resources in the cloud storage, in order to meet the demands of users and maintain the service level agreement with the clients, the cloud server has to allocate the physical machine to the virtual machines as requested, but the random resource allocations procedures lead to inefficient utilization of resources.

This thesis focuses on resource allocation for reasonable utilization of resources. The overall framework comprises of cloudlets, broker, cloud information system, virtual machines, virtual machine manager, and data center. Existing first fit and best fit algorithms consider the minimization of the number of bins but do not consider leftover bins.

The proposed algorithm effectively utilizes the resources compared to first, best and worst fit algorithms. The effect of this utilization efficiency can be seen in metrics where central processing unit (CPU), bandwidth (BW), random access memory (RAM) and power consumption outperformed very well than other algorithms by saving 15 kHz of CPU, 92.6kbps of BW, 6GB of RAM and saved 3kW of power compared to first and best fit algorithms.

The proposed multi-objective bin packing algorithm is better for packing VMs on physical servers in order to better utilize different parameters such as memory availability, CPU speed, power and bandwidth availability in the physical machine.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

The purpose of this paper is to explain how enterprise resource planning (ERP) implementation evolves by cloud computing in different industries with different delivery models of cloud ERP. This paper also investigates infrastructure as a service (IaaS) as a delivery approach for cloud ERP. Case research on IaaS is rarely found in the literature. In addition, this paper intends to reveal how this transformation from on-premises to the cloud would influence the ERP implementation process.

A multiple-case study is conducted to identify the different deployed models of cloud ERP systems in the implementation projects. The influences of emerging cloud computing technology on ERP implementation are investigated by interviewing consultants related to the projects.

The findings illustrate that not only software as a service (SaaS) but also IaaS and platform as a service cloud computing services are widely applied in cloud ERP implementation. This study also indicates that certain technical limitations of cloud ERP might have a positive effect on the outcome of ERP implementation.

This study investigates how cloud computing influences ERP implementation from different aspects. The result identifies both SaaS and IaaS as two different approaches widely adopted in cloud ERP implementation. Besides, this study has discussed in-depth and analyzed these two cloud ERP paradigms in five factors, including functionality, performance, portability, security, cost and customization. The classification and suggestions are original to the literature.

This paper aims to explore key management actions for implementing security on the cloud, which is a critical issue as many organizations are moving business processes and data on it. The cloud is a flexible, low cost and highly available technology, but it comes with increased complexity in maintaining the cloud consumer’s security. In this research, a model was built to assist strategic decision-makers in choosing from a diverse range of actions that can be taken to manage cloud security.

Published research from 2010 to 2022 was reviewed to identify alternatives to management actions pertaining to cloud security. Analytical hierarchical process (AHP) was applied to rate the most important action(s). For this, the alternatives, along with selection criteria, were summarized through thematic analysis. To gauge the relative importance of the alternatives, a questionnaire was distributed among cloud security practitioners to poll their opinion. AHP was then applied to the aggregated survey responses.

It was found that the respondents gave the highest importance to aligning information security with business needs. Building a cloud-specific risk management framework was rated second, while the actions: enforce and monitor contractual obligations, and update organizational structure, were rated third and fourth, respectively.

The research takes a general view without catering to specialized industry-based scenarios.

This paper highlights the role of management actions when implementing cloud security. It presents an AHP-based multi-criteria decision-making model that can be used by strategic decision-makers in selecting the optimum mode of action. Finally, the criteria used in the AHP model highlight how each alternative contributes to cloud security.

This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing research data that maintains the data’s accuracy and makes it available for reuse. It requires controlled data management.

The study uses a qualitative approach. Data collection was carried out through a focus group discussion in September–October 2022, interviews and document analysis. The informants came from four institutions in Indonesia.

The findings reveal that the national research repository has implemented data curation, albeit not optimally. Within the case study, one of the university repositories diligently curates its humanities data and has established networks extending to various ASEAN countries. Both the national archive repository and the other university repository have implemented rudimentary data curation practices but have not prioritized them. In conclusion, the readiness of the national research repository and the university repository stand at the high-capacity stage, while the national archive repository and the other university repository are at the established and early stages of data curation, respectively.

This study examined only four repositories due to time constraints. Nonetheless, the four institutions were able to provide a comprehensive picture of their readiness for DH data curation management.

This study provides insight into strategies for developing DH data curation activities in institutional repositories. It also highlights the need for professional development for curators so they can devise and implement stronger ownership policies and data privacy to support a data-driven research agenda.

This study describes the preparations that must be considered by institutional repositories in the development of DH data curation activities.