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A computer environment to support the strategic decision‐making process in construction firms is presented. The system implements modelling concepts originally developed to evaluate project execution strategies, extending and generalizing the modelling methodology to a broader range of strategic decisions. An application to a construction firm's strategic planning is used in this paper to illustrate the modelling process. The computer system is designed to help the users in building a conceptual model for the decision problem, this model is a simplified structure of the variables and interactions that influence the decisions being analysed, including internal as well as external factors. An analytical model is then designed to predict the impact of these strategies, integrating expert knowledge and assessments of the strategic planning team into a mathematical model. The mathematical component uses concepts of cross‐impact analysis and probabilistic inference to capture uncertainties and interactions among project variables. The system provides multiple analysis capabilities, including sensitivity analysis, selected outcome prediction, isolated or combined effect of strategies and changes in performance due to changes in the external environment. The system allows management to test different combinations of long‐term strategies and predict expected sales, market share or other measures of performance.

The purpose of this paper is to understand the underlying logics applied by different project evaluation approaches and to propose an alternative research agenda.

This paper explores the project evaluation literature via conducting a qualitative research applying systematic literature review and thematic analysis.

The project evaluation literature has mainly concentrated on the objective aspects of project evaluation and overlooked the subjective aspects that reflect the temporal, dynamic, complex and subjective nature of today’s projects. The authors propose a meta-framework that helps project practitioners to select an appropriate project evaluation criterion for their projects by considering the strengths and limitations of their preferred project evaluation model as well as making project evaluators aware of the underlying logics associated to diverse project evaluation approaches.

This study suggests that new conceptual approaches to deal with some of the major challenges in the project evaluation field. Practice-based views, narrative analysis and actor-network theory are likely to be useful tools to better understand and cope with the projects’ uncertainty and complexity.

The findings of this research assist project management practitioners and particularly project evaluators to enhance their understanding of the subjectivity, complexity and dynamics of current projects. To increase the reflexivity and resilience of project evaluation practice, this study also proposes new directions to apply different criteria, sub-criteria and indicators to the evaluation practice.

The originality of this study relies on transcending the conventional objective and rational approaches prevailing in current project evaluation practices. It proposes a research agenda that pave the way to address the shortcomings of conventional project evaluation practice.

The aim of the autopoietic model of knowledge is to act as a common foundation for KM to overcome the numerous knowledge management failures highlighted by the literature attributed to inaccurate or constantly debated definitions of knowledge. This paper seeks to evaluate such a model.

Participants for this interpretivist evaluation study were selected by convenience sampling. Experts known to the authors were asked to participate, and 12 took part. Face‐to‐face interviews were conducted and lasted between 45 to 60 minutes. Member checking was used during the interviews. The data was analysed using the recursive abstraction method.

The study highlighted the complexities of conducting an expert evaluation of a model that was deemed both too high level and too low level by the experts. The study highlighted the challenge of evaluating a model that is theoretically correct, but required acceptance in the knowledge management discipline. The study also showed that the application of autopoiesis to knowledge management has potential, but is still in its infancy.

The main limitation of this study came from the initial autopoietic model of knowledge: most experts found it too difficult to engage with in the time available. The knowledge management foundation aspired to by applying autopoiesis to the domain is hard to achieve as little value was placed on models by some experts.

The evaluation of the autopoietic model of knowledge presented in this paper represents the first expert evaluation of an autopoietic epistemology. The study is an incremental step towards providing a sound conceptual foundation for knowledge management.

The purpose of this article is to provide an introduction to the LEONARDO diagnostic tool which assists organizations in determining their current level of achievement towards a learning culture.

Using a combination of the analytical hierarchy process and the Delphi technique, the research obtained the critical questions for evaluating an organization's investment and progress towards achieving a learning culture. The questions are categorized based on five areas of a learning culture and three levels of learning within an organization. These questions are translated into a web‐based diagnostic that is validated and released for use by engineering and construction organizations.

The paper provides an overview of the LEONARDO diagnostic tool including the mathematical weighting system employed for scoring organization progress and investment, the web‐based availability, and the evaluation report card provided to users. The paper also provides a summary of the validation process including how organizations used the tool to determine internal learning progress.

The study obtained input primarily from large organizations and may not fully represent the entire engineering and construction industry perspective.

The study provides a tool that assists any organization in advancing towards a learning culture that is a requirement for remaining competitive in a changing engineering marketplace.

The paper provides an introduction to how to achieve a learning organization as an advance over collecting and managing knowledge. This is the beginning of a movement toward the next stage in achieving success within the knowledge era.

To evaluate the use of neural networks in healthcare facilities risk management.

The data used to develop the input to the national health service facilities risk exposure system (NHSFRES) was solicited from 60 healthcare managers. Risk exposure system has been developed using the risk knowledge that was articulated from experienced healthcare operators through postal questionnaires and repertory grid interviews. This knowledge was then transformed and represented in Trajan 4.0, an expert system shell that uses artificial neural networks as its modelling technique.

It provides healthcare facilities operators an avenue to evaluate their own risk management method (point score system) based on their own healthcare business knowledge/judgment and corporate objectives for various FM service operations.

The key issue that should always be noted by NHSFRES users is that, the concept of measuring or evaluating business risks will always be uncertain. Professional judgment, based on sound information, is an essential element in interpreting and using the system.

The model provides healthcare facilities managers a vehicle for predicting pre‐ and post‐facilities risk‐factors in healthcare operations before they occur. A clear understanding of the risk signals would mean that appropriate management course of action should to be considered that will improve FM operators' business performance.

The NHSFRES is developed using the risk knowledge that was articulated from experienced healthcare operators through postal questionnaires and repertory grid interviews. It provides a reasonable early warning signal to the healthcare managers, and can be used by decision makers to evalute the severity of risks on healthcare facilities business operations.

Studies have so far focused on learning in organizations, factors affecting learning, learning effectiveness and so on but the concept of learning in a hybrid work arrangement is yet unexplored. The purpose of this study is to measure the perception of faculty members in higher education institutions towards learning in a hybrid work arrangement and also to measure the differences of perception towards hybrid work arrangement based on employees’ gender and organization type.

The data was collected from a sample of 390 faculty members composing of Assistant Professors, Associate Professors and Professors, purposely chosen from two of the premier higher education institutions (one private and one public) located in Punjab, India. A self-structured questionnaire was administered to the faculty members who are working on a regular basis and have minimum of two years of work experience with the chosen university. For analysing the collected data exploratory factor analysis and other descriptive statistics have been applied.

The findings of the survey show that in terms of gender differences, it is the female employees who are more satisfied with different aspects of hybrid/remote work arrangement as compared to male employees. In regard to organizational differences in the perception towards learning in a hybrid work arrangement it is found that public university employees have a more positive attitude so far as individual factors are concerned, but in terms of organizational factors, it is the private university that is scoring better than the public university.

The study is limited to only two higher education institutions, and its findings to be applicable in all higher education institutions, further studies may be required on a larger canvas. Future studies may be undertaken using advanced statistical tools like structural equation modelling to explore various variables associated with learning in a hybrid work arrangement.

Applicability of hybrid work arrangement is very high in higher education institutions and to the best of the authors’ knowledge, this is the first study which adds to the literature on perception of employees towards organizational learning in a hybrid work arrangement.

The purpose of this paper is to provide an overview of recent developments in employment relations in Chile, focusing on recent episodes of contract labour mobilisation in the forestry and copper mining sectors.

This paper is based on a consolidation of existing evidence from a range of primary, secondary and tertiary sources.

The paper demonstrates the inadequacy of Chile's employment relations institutions to protect vulnerable workers and shows the capacity of contract workers to overcome such limitations by recurring to mobilisation. It argues that contract labour mobilisation rather than a shift left in government seems to offer a more plausible explanation of current developments in Chilean employment relations.

The paper identifies salient issues but further research is necessary to understand the actual social processes of collective action involved in recent episodes of contract labour mobilisation.

This information could contribute to better policy making, better management of the employment relationship, and informing the revitalisation of labour movements.

There are few studies on contract workers' collective action particularly in developing countries, and a contribution is made to critical debates on the sustainability of Chile's neoliberal socio‐economic and employment relations system.

The purpose of this paper is to provide a new type of entry mode decision‐making model for construction enterprises involved in international business.

A hybrid method combining analytic hierarchy process (AHP) with preference ranking organization method for enrichment evaluations (PROMETHEE) is used to aid entry mode decisions. The AHP is used to decompose the entry mode problem into several dimensions and determine the weight of each criterion. In addition, PROMETHEE method is used to rank candidate entry modes and carry out sensitivity analyses.

The proposed decision‐making method is demonstrated to be a suitable approach to resolve the entry mode selection decision problem.

The research provides practitioners with a more systematic decision framework and a more precise decision method.

The paper sheds light on the further development of entry strategies for international construction markets. It not only introduces a new decision‐making model for entry mode decision making, but also provides a conceptual framework with five determinants for a construction company entry mode selection based on the unique properties of the construction industry.