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This research introduces a hypothesis for establishing typologies and patterns for architectural plans based on their climate, culture and orientation. The repetition and reproduction of spaces in architectural plans are rooted in mathematical equations. Factorial and permutation formulae are the type of equations used as scientific tools to define typology. In addition, a new perspective on culture and privacy in line with the Arabic house is included to illustrate the practicality of restricted plans according to cultural needs.

To make the approach accessible, the theory is integrated into a software using C++ as the programming tool. Accordingly, all patterns and typologies are reproduced by inserting digits or numbers to simulate the process of using permutations and factorials for the creation of diagrammatic patterns and, subsequently, architectural plans.

The authors recommend that this method be integrated in future housing studies at earlier stages to obtain a high number of alternatives for architectural plans. The results of mathematical permutation of this study will help architects and designers to evolve their methods and processes through creating alternative patterns and culture (and climate)-specific typologies to provide more design possibilities.

This study is set to improve the adjacency diagram theory into the adjacency diagram with orientation theory, which accounts for the geographical orientation to obtain more comprehensive and climate-responsive patterns.

In large organizations, space planning relies on workgroup leaders to indicate spatial adjacency preferences. However, many factors affect workgroups’ adjacency preferences, and it is not clear how the choices are made. This paper aims to explore whether the adjacency preferences are influenced by the collaboration relationship or constrained by the organizational structure.

The authors studied a large company’s spatial adjacency planning with an in-depth analysis of its formal organizational structure and collaboration network. A sample of 183 managers was surveyed regarding groups with whom they want to be spatially adjacent and groups with whom they mostly interact. The data enabled us to test three structural factors related to adjacency preference: department affiliation, workgroup’s prestige and collaboration relation. The authors used the quadratic assignment procedure analysis to examine the correlations between network matrices.

The results suggest that department affiliation and collaboration relations are significantly correlated to adjacency preferences. The authors did not find evidence supporting the notion that a workgroup’s prestige affects the preference. Among the three factors, collaboration relation best predicts the preference, which echoes Pena et al.’s (1977) argument that space planners should look into how groups function, rather than merely following the organizational chart.

To the best of the authors’ knowledge, this research was the first to explore the choice of spatially adjacent workgroup through a detailed network analysis of the formal structure, work collaboration relations and other group-level characteristics. The findings have noteworthy cross-disciplinary implications, given that spatial proximity can be taken as a human resource management strategy to facilitate the overall interactions between workgroups.

This paper aims to propose an innovative building information modelling (BIM)-based framework for multi-objective and dynamic temporary construction site layout design (SLD), which uses a hybrid approach of systematic layout planning (SLP) and mathematical modelling.

The hybrid approach, which follows a step-by-step process for site layout planning, is designed to facilitate both qualitative and quantitative data collection and processing. BIM platform is usedto facilitate the determination of the required quantitative data, while the qualitative data are generated through knowledge-based rules.

The multi-objective layout model represents two important aspects: layout cost and adjacency score. The result shows that the model meets construction managers’ requirements in not only saving cost but also assuring the preferences of temporary facility relationships. This implies that the integration of SLP and mathematical layout modelling is an appropriate approach to deliver practical multi-objective SLD solutions.

The proposed framework is expected to serve as a solution, for practical application, which takes the advantage of technologies in data collection and processing. Besides, this paper demonstrates, by using numerical experimentation and applying Microsoft Excel Solver for site layout optimisation, how to reduce the complexity in mathematical programming for construction managers.

The original contribution of this paper is the attempt of developing a framework in which all data used for the site layout modelling are collected and processed using a systematic approach, instead of being predetermined, as in many previous studies.

This paper aims to examine how client requirements undergo representational and transformational shifts and changes in the design process and explore the consequence of such changes.

A series of design resources relating to hospital departmental configurations are examined and analysed using a social semiotic framework. The findings are supplemented by practitioner opinion.

Construction project requirements are represented and transformed through semiotic resource use; such representations deliver specific meanings, make new meanings and affect project relationships. Requirement representations may be understood as socially motivated meaning-making resources.

The paper focuses on one set of project requirements: hospital departmental configurations from a National Health Service hospital construction project in the UK.

The use of semiotic resources in briefing work fundamentally affects the briefing and design discourse between client and design teams; their significance should be noted and acknowledged as important.

The findings of the paper indicate that briefing and design work may be understood as a social semiotic practice.

This original paper builds upon scholarly work in the area of construction project communications. Its fine-grained analysis of briefing communications around representations of specific requirements is novel and valuable.

The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.

The user interface, in broad terms, is the medium through which the user and the information come together. The types of searches a public access catalog (PAC) can perform are defined by the indexing strategy and retrieval software. The way the user's interest is communicated to the retrieval software and the way the results are communicated to the user is, by a more narrow definition, the interface software. Both the kinds of searches that can be performed by a variety of CD‐ROM PACs and how their workstations are used to accomplish the searches are considered.

This paper introduces a schema for the product assembly feature data in an object-oriented and module-based format using Unified Modeling Language (UML). To link production with product design, it is essential to determine at an early stage which entities of product design and development are involved and used at the automated assembly planning and operations. To this end, it is absolutely reasonable to assign meaningful attributes to the parts’ design entities (assembly features) in a systematic and structured way. As such, this approach empowers processes such as motion planning and sequence planning in assembly design.

The assembly feature data requirements are studied and definitions are analyzed and redefined. Using object-oriented techniques, the assembly feature data structure and relationships are modeled based on the identified requirements as five UML packages (Part, three-dimensional (3D) models, Mating, Joint and Handling). All geometric and non-geometric design data entities endorsed with assembly design perspective are extracted or assigned from 3D models and realized through the featured entity interface class. The featured entities are then associated (used) with the mating, handling and joints features. The AssemblyFeature interface is realized through mating, handling and joint packages related to the assembly and part classes. Each package contains all relevant classes which further classify the important attributes of the main class.

This paper sets out to provide an explanatory approach using object-oriented techniques to model the schema of assembly features association and artifacts at the product design level, all of which are essential in several subsequent and parallel steps of the assembly planning process, as well as assembly feature entity assignments in design improvement cycle.

The practical implication based on the identified advantages can be classified in three main features: module-based design, comprehensive classification, integration. These features help the automation and solution development processes based on the proposed models much easier and systematic.

The proposed schema’s comprehensiveness and reliability are verified through comparisons with other works and the advantages are discussed in detail.

Continually evolving market structures characterized by high competition and simultaneous coopetition raise the need for the awareness of strategic actions of industry stakeholders and therefore the field of competitive intelligence (CI). Hence, this paper aims to provide a case-based method to enrich and automate the entire CI cycle using open-source data to analyze the industry environment.

The research method is based on design science research and accompanied by a three-year continuous in-depth case study in the automotive supply industry using unstructured, qualitative data to examine the activities of 25 industry stakeholders.

This paper provides a new holistic method for gaining valuable insights for decision-makers presented through a multiple-layer perspective of the industry development including structural transformation and strategic alignments in functional and cross-sectional areas of the stakeholders.

The development of a holistic approach using open-source data combines the knowledge-based view and industry economics and allows easy transferability to any other industry.

The proposed method shows an increase in knowledge for managers to support daily work as well as strategic decision-making. Furthermore, it is proven that even unexperienced CI analysts are empowered to deliver high-quality results.

The paper contributes to the literature and practice of CI by using an approach, which uses unstructured, qualitative data to enrich the entire CI cycle in a business-to-business environment. The case description confirms performance and time improvements of the method and shows the potential of the created insights.