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This paper aims to identify the importance of individual variables in the corporate real estate (CRE) decision-making process.

Nine experts received a posed scenario of a changed business strategy requiring a CRE reduction in individual interviews. Based on their suggested response, a decision network was modelled for each expert using the causal network elicitation technique, incorporating the utilities for decision variables and importance weights for attributes and benefits. The decision model offers a graphical representation of decision-benefit links for the decisions CRE managers make in such a period of decline.

Perceived facilitators of CRE dynamic alignment were identified by calculating lift ratios on their perceived importance of the attributes they mentioned during the interviews as nodes in the network that link decisions to benefits. Facilitators included CRE metrics and workplace strategy, while capital expenditure and landlords inhibit alignment processes. The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process.

The research set a specific scenario for the experts to consider. That could be regarded as small but there was clear evidence of saturation of expert knowledge. Additional face-to-face interviews with the experts may have generated further details on the thought processes of the experts.

The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process. Thereby providing CRE decision-makers with key elements for a decision model.

The research technique, causal network elicitation technique, uses semi-structured interviews to create decision networks, which is a technique that has not been widely applied to CRE research. The research provides a granular view of what are important inhibitors or facilitators of dynamic alignment of CRE to business strategy.

The evolution of technologies has unleashed a wealth of challenges by generating massive amount of data. Recently, biological data has increased exponentially, which has introduced several computational challenges. DNA short read alignment is an important problem in bioinformatics. The exponential growth in the number of short reads has increased the need for an ideal platform to accelerate the alignment process. Apache Spark is a cluster-computing framework that involves data parallelism and fault tolerance. In this article, we proposed a Spark-based algorithm to accelerate DNA short reads alignment problem, and it is called Spark-DNAligning. Spark-DNAligning exploits Apache Spark ’s performance optimizations such as broadcast variable, join after partitioning, caching, and in-memory computations. Spark-DNAligning is evaluated in term of performance by comparing it with SparkBWA tool and a MapReduce based algorithm called CloudBurst. All the experiments are conducted on Amazon Web Services (AWS). Results demonstrate that Spark-DNAligning outperforms both tools by providing a speedup in the range of 101–702 in aligning gigabytes of short reads to the human genome. Empirical evaluation reveals that Apache Spark offers promising solutions to DNA short reads alignment problem.

While localized small-series production is a significant opportunity, various tensions challenge implementation in high-cost contexts. This paper explores how managers view and respond to different tensions in small-series production implementation by adopting a paradox-based perspective.

The paper presents a multiple case study addressing small-series production within EU's apparel industry, as key context to address managerial awareness, and responses to tensions regarding location and supply network configuration decisions. Seven cases were selected for variation in customization and implementation (early/established), ownership, location and company size, to identity commonalities.

The study highlights performing tensions related to sustainability, and risk, in addition to confirming traditional goal-related tensions predominantly impacting small volume production. With on-demand/custom production, tensions include costs in conflict with process scale, and several process-related tensions (flexibility, expansion/development, risk management). Identified multidimensional responses do not include location or structural decisions, instead focusing on synthesis, through product-operations efficiency, knowledge development and process innovation and supply chain collaboration. Temporal separation is found with customization, including reducing product/process complexity short-term with enhancing process development, which suggests latent learning tensions and limited awareness.

Future research should address the extent to which tensions can be resolved or remain paradoxical, as well as dynamic decision-making and latent tensions.

The paper shows how paradox theory facilitates a deeper understanding of complex network configuration decisions, including reshoring/localization. The findings identify organizing tensions/elements and elaborate upon performing/performing-organizing tensions suggested with small-series production, location decisions and supply chain management.

Organisational strategy becomes reality by connecting organisation’s resources and capabilities in daily operations, and physical workspace is one of the environments in which this takes place. This study aims to explore to what extent factors required for successful strategy implementation are considered when designing, using and managing workspaces of knowledge-intensive organisations.

For the study, managers in 25 large and medium-sized knowledge-intensive organisations were interviewed. The semi-structured interviews focused on organisation’s strategy, strategy implementation practices and workspace design and management. To form a comprehensive framework of strategy implementation success factors for the study, the factors of 11 frameworks were analysed, grouped and renamed.

Current workspace design, usage and management mainly support human-related strategy implementation factors. However, both organisation- and human-related factors are needed for the strategy implementation to be successful. Therefore, the organisations studied may have unused potential in their workspaces to ensure strategy-aligned operations and behaviour.

Due to the potential imbalance between organisation- and human-related strategy implementation factors, a more holistic, organisational-level approach to workspace design, usage and management is recommended to ensure the success of strategy implementation.

Workspaces have extensively been studied from individual strategy implementation factors’ as well as employees’ perspectives. Prior to this work, there are only few studies exploring workspace in the holistic, strategy implementation context.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.