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The purpose of this paper is to introduce and conceptualize the topic of Cognitive Centres. It emphasizes the importance of complexity management and cognitive technologies in management practice.

It elaborates the relevance of different types of models for management: Stafford Beer's operations room, viable system model, subject‐object and subject‐subject management models, expert‐based mathematical modelling and computational experiment, organizational‐activity games theory and cybernetic (Viplan) methodology.

The paper suggests models and approaches for strategic management. It shows the inadequacy of a subject‐object management model for industrial or regional governance. It integrates a communicative management approach, complexity management methods, the USSR's Gosplan experience of long‐term planning, the Keldysh Institute of Applied Mathematics experience of modelling extremely complex systems and modern cognitive and information technologies into the concept of a Cognitive Centre.

Cognitive Centres can enhance the adaptation and viability of a large network of small organizations: public enterprises, business and not‐for‐profit regional industries. The paper describes two cases of practical implementation.

The paper contributes to research on management models that integrates cybernetics, cognitive technologies and computational experiments.

The purpose of this paper is to present and discuss the methodological approach and the results of the investigation of greenhouse gas emission abatement costs in Upper Austria.

The assessment covers the quantification of marginal abatement costs (MACs) of greenhouse gas (GHG) emissions and the emission reduction potentials of various energy efficiency and fuel switch measures with a special emphasis on the heat, electricity and transport sectors in Upper Austria during the period from 2010 to 2030.

The expert‐based assessment in Upper Austria shows negative abatement costs for 19 of 56 evaluated strategies. While these measures are very efficient from an economic point of view, the remaining 37 measures are associated with higher costs. The evaluation reveals a significant reduction potential of 5.2 million tons CO₂e (which represent 21 per cent) of the current GHG emissions in Upper Austria for the examined period.

MACs are generally limited to a certain time frame. Furthermore, the expert‐based approach is based on several assumptions and neglects behavioural and learning aspects.

This contribution uses a multi‐criteria approach that reveals the economic efficiency and the ecological effectiveness of the considered strategies/technologies with regard to greenhouse gas emission reductions, the improvement of the overall energy efficiency, and the competitiveness of a fuel switch towards renewable energy sources. Drawing upon the findings of this study, policy recommendations can be elaborated and the necessary improvements of the regulative framework can be implemented.

A review of benchmarking literature revealed that there are different types of benchmarking and a plethora of benchmarking process models. In some cases, a model has been uniquely developed for performing a particular type of benchmarking. This poses the following problems: it can create confusion among the users as to whether they should use only the unique benchmarking model that has been developed for particular type or they can use any model for any type of benchmarking; a user may find it difficult when it becomes necessary to choose a best model from the available models, as each model varies in terms of the number of phases involved, number of steps involved, application, etc. Hence, this paper aims to question the fundamental classification scheme of benchmarking and thereby the unique benchmarking models that are developed for each type of benchmarking. Further it aims to propose a universal benchmarking model, which can be applied for all types of benchmarking.

The fundamental benchmarking model developed by Camp has been used to benchmark the existing models, irrespective of the type of benchmarking, to identify the best practices in benchmarking.

Benchmarking the benchmarking models revealed about 71 steps in which around 13 steps have been addressed by many researchers. The remaining unique steps were considered to be the best practices in benchmarking.

The proposed model is highly conceptual and it requires validation by implementing the same in an organization to understand its effectiveness.

Though some of the methodologies used in this paper are already available in the literature, their context of application in the field of benchmarking is new. For example, utilizing the benchmarking process itself to improve the existing benchmarking process is an original concept.

Benchmarking in FM practice although understood and applied globally, little is known about the practice in Nigeria. The purpose of this paper is to develop a framework to guide the use of benchmarking.

The research adopts a cross-sectional survey design. Data were collected using self-administered questionnaires on FM organizations in Lagos metropolis, Abuja and Port Harcourt. The results of the survey were supplemented with interviews with FM unit heads in the study areas. The framework was validated using a focus group discussion with ten FM industry experts.

A framework which serves as a guide for the use of best practice benchmarking was developed. It showed that there is a relationship between best practice benchmarking and location.

The evaluation of the framework was limited by the number of participants involved and being that it has not been put to use.

This study develops a multi-sector framework to guide the use of best practice benchmarking in facilities management (FM). The framework explains the relationship between organizational characteristics and best practice benchmarking. In addition, there are limited empirical benchmarking frameworks in FM literature.

The phenomenon of traffic crash under-reporting has been extensively documented in terms of its extent, but not equally analysed in terms of its reasons. As police distrust has been recently identified as a major reason for crash under-reporting, the purpose of this paper is to look at the police service quality for handling the reporting of traffic crashes.

This study introduces a novel approach to evaluate service quality that combines multi-criteria decision analysis (MCDA) with latent class analysis (LCA). Moreover, this study presents the design of a web-based survey on the basis of the SERVQUAL approach to detecting strengths, opportunities and threats with crash reporting to the police at a strategic level. Transportation stakeholders (e.g. researchers, authorities, consultants, NGO representatives, suppliers) with an interest in traffic safety in Denmark participated in the survey that yielded 86 complete responses.

The novel approach was successfully applied and its implementation demonstrated the usefulness of the tool even in countries with a high police service. Results showed that the participating stakeholders perceived human factors as more important than physical factors in order to increase the crash reporting, with responsiveness as the most important and tangibles as the least important dimensions. Nevertheless, most stakeholders viewed a mixture of human and physical factors as crucial to increase crash reporting rates.

This study advances the knowledge about police service quality with a novel expert-based decision support tool based on SERVQUAL, MCDA and LCA, demonstrates its applicability in countries with a high-police service, and opportunities and barriers for increasing the crash reporting rate.

Researchers have studied processes of improving road traffic-safety culture by explicitly evaluating the socio-psychological phenomenon of traffic-risk. The implicit traffic-system cues play an important role in explaining urban traffic-culture. This paper aims to ascertain an interpretive framework of the alternative processes of road traffic safety culture is antecedent to promote traffic-safety behaviour in Indian urban context. Subsequently, the authors discussed the reasons for those relationships exists.

Four experts of the urban traffic-safety domain participated in total interpretive structural modelling (TISM) study by completing an interpretive consensus-driven questionnaire. The drafted interpretive model was evaluated for road users proactive action orientation about the traffic-safety decision.

The evolved directed graph (digraph) of the culture of urban traffic-safety management was a serial three-mediator model. The model argued: In the presence of traffic-risk cues, people may become apprised to safety goals that initiate traffic-safety action. Consequently, expectancy-value evaluation motivates the continuation of traffic-safety intention that may lead to the implementation of adaptation plan (volitional control), thus habituating road users to traffic-safety management choice.

The modellers of traffic psychology may empirically estimate and test for the quality criteria to ascertain the applicability of the proposed mechanism of urban traffic-safety culture. The decision-makers should note the importance of arousal of emotions regarding traffic-risk, reduce the impact of maladaptive motivations and recursively improve control over safety actions for promoting safety interventions.

The authors attempted to induce an interpretive model of urban traffic-safety culture that might augment extant discussion regarding how and why people behave in an urban traffic system.

The purpose of this paper is to discuss the case-based reasoning (CBR) approach to improve microcredit initiatives by means of providing a borrower risk rating system.

The CBR approach has been used to consider the Kiva microcredit system, which provides a characterization (rating) of the risk associated with the field partner supporting the loan, but not of the specific borrower which would benefit from it. The authors discuss how the combination of available historical data on loans and their outcomes (structured as a case base) and available knowledge on how to evaluate the risk associated with a loan request can be used to provide the end users with an indication of the risk rating associated with a loan request based on similar past situations.

The adopted approach is applied and evaluated employing a selection of cases from individual loans. From this perspective, the case base and the codified knowledge about how to evaluate risks associated with a loan represent two examples of knowledge IT artifacts.

The originality of the work lies in borrower risk rating in online indirect peer-to-peer microcredit lending platforms. The case base and the codified knowledge are the two contributions in knowledge IT artifacts.

The purpose of this paper is to develop a method for the discovery of knowledge in emergency response databases based on police incident reports, generating information that identifies local criminal demands that allow the selection of the appropriate policing strategies portfolio to solve the problem.

The developed model uses a methodology for the discovery of knowledge involving text mining techniques using Latent Dirichlet Allocation (LDA) integrated with the ELECTRE I multicriteria method.

The developed method allowed the identification of the most common criminal demands that occurred from January 1 to December 31, 2016, in the policing areas studied. One of the crimes does not occur homogeneously in a particular locality. In this study, it was initially observed that 40 per cent of the crimes identified in the Integrated Public Safety Area 5, or AISP-5, (historical city center of RJ) had no correlation with AISP-19 (Copacabana - RJ), and 33 per cent of crimes crimes in AISP-19 were not identified in AISP-5. This finding guided the second part of the method that sought to identify which portfolio of policing strategies would be most appropriate for the identified demands. In this sense, using the ELECTRE I method, eight different scenarios were constructed where it can be identified that for each specific criminal demand set there is a set of policing strategies to be applied.

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

The developed methodology contributes in a complementary way to the identification of criminal practices and their characteristics based on reports of police occurrences stored in emergency response databases. The knowledge generated through the identification of criminal demands allows law enforcement decision makers to evaluate and choose among the available policing strategies, which best suit the reality they study, and produce the reduction of criminal indices.

It is possible to infer that by choosing appropriate strategies to combat local crime, the proposed model will increase the population’s sense of safety through an effective reduction in crime.

The originality of the study lies in the integration of text mining techniques, LDA and the ELECTRE I method for detecting crime in a given location based on crime reports stored in emergency response databases, enabling identification and choice, from customized policing strategies to particular criminal demands.

This paper aims to present the “Vulnerability Sourcebook” methodology, a standardised framework for the assessment of climate vulnerability and risk in the context of adaptation planning. The Vulnerability Sourcebook has been developed for the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) and has been applied in more than twenty countries worldwide.

It is based on a participative development of so-called climate impact chains, which are an analytical concept to better understand, systemise and prioritise the climate factors as well as environmental and socio-economic factors that drive climate related threats, vulnerabilities and risks in a specific system. Impact chains serve as the backbone for an operational climate vulnerability assessment with indicators based on quantitative approaches (data, models) combined with expert assessments. In this paper, the authors present the concept and applications of the original Vulnerability Sourcebook, published in 2015, which was based on the IPCC AR4 concept of climate vulnerability. In Section 6 of this paper, the authors report how this concept has been adapted to the current IPCC AR5 concept of climate risks.

The application of the Sourcebook is demonstrated in three case studies in Bolivia, Pakistan and Burundi. The results indicate that particularly the participative development of impact chains helped with generating a common picture on climate vulnerabilities and commitment for adaptation planning within a region. The mixed methods approach (considering quantitative and qualitative information) allows for a flexible application in different contexts. Challenges are mainly the availability of climate (change) and socio-economic data, as well as the transparency of value-based decisions in the process.

The Vulnerability Sourcebook offers a standardised framework for the assessment of climate vulnerability and risk in the context of adaptation planning.

The purpose of this paper is to investigate a benchmarking project carried out by the Dubai Electricity and Water Authority (DEWA) as part of a structured benchmarking initiative. The project was based on the TRADE benchmarking methodology and this paper examines the tools, activities and outcomes that relate to each stage of the adopted methodology.

This study is based on case study methodology. Data were collected from various sources including analysis of project reports written by DEWA’s benchmarking team reporting on their activities during the project. Data were also collected from four project presentations given at different stages of the project. In addition, the research team held three meetings with the DEWA benchmarking team at different stages of the benchmarking project.

The results show the key challenges and successes faced during each stage of the benchmarking project. It indicates the actions taken to overcome the challenges and the role played by internal and external stakeholders in facilitating the success of the benchmarking project.

The study presents information that would guide organisations that wish to carry out a benchmarking project – and particularly those implementing benchmarking for the first time. The study provides a summary of the key lessons learnt by DEWA’s benchmarking team as a guide for other organisations.

Academic research has not adequately examined and analysed the stage-by-stage elements of a benchmarking project from the perspective of the implementing organisation. This study addresses this gap by detailing and analysing the experiences of a benchmarking project by tracking the stage-by-stage activities of the benchmarking team.