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The proportion of real estate in a non‐property company’s asset portfolio has increased to an extent where it has become an asset capable of enhancing corporate wealth. This initial study hopes to establish the foundation and provide background information on corporate real estate holding profiles of listed Singapore business firms. Using financial statement data and firm market values from 1987 to 1996, this paper provides an analysis of real estate holdings in both absolute and relative terms. Real estate holdings by business segment and asset subtype, growth in corporate real estate holdings over time; and key financial characteristics of corporate real estate (eg real estate as a percentage of shareholders’ equity and real estate relative to market value of the firm) are included in the paper.

The purpose of this paper is to review and provide recommendations to extend the current open standard data models for describing monitoring systems and circular economy precepts for built assets. Open standard data models enable robust and efficient data exchange which underpins the successful implementation of a circular economy. One of the largest opportunities to reduce the total life cycle cost of a built asset is to use the building information modelling (BIM) approach during the operational phase because it represents the largest share of the entire cost. BIM models that represent the actual conditions and performance of the constructed assets can boost the benefits of the installed monitoring systems and reduce maintenance and operational costs.

This paper presents a horizontal investigation of current BIM data models and their use for describing circular economy principles and performance monitoring of built assets. Based on the investigation, an extension to the industry foundation classes (IFC) specification, recommendations and guidelines are presented which enable to describe circular economy principles and asset monitoring using IFC.

Current open BIM data models are not sufficiently mature yet. This limits the interoperability of the BIM approach and the implementation of circular economy principles. An overarching approach to extend the current standards is necessary, which considers aspects related to not only modelling the monitoring system but also data management and analysis.

To the authors’ best knowledge, this is the first study that identifies requirements for data model standards in the context current linear economic model of making, using and disposing is growing unsustainably far beyond the finite limits of planet of a circular economy. The results of this study set the basis for the extension of current standards required to apply the circular economy precepts.

This study examines the influence of corporate real estate (CRE) on shareholder value using two value‐based measures: economic value added (EVA) and market value added (MVA). We find that CRE has impacted negatively on non‐real estate firms' EVA and MVA in the period 1997‐2001. This happens for the non‐real estate corporations from different industries. Further, the higher the real estate asset intensity, the greater the negative impact on the firms' EVA and MVA. Our results have important implications for the traditional notion that there is a competitive advantage in owning CRE by diversified conglomerates. Specifically, more studies are needed to explore and compare the main reasons and motivations as to why Asian non‐real estate firms are still more involved with real estate activities than their counterparts in Europe and USA even though ownership of CRE appears to destroy shareholders' wealth.

This study seeks to enhance productivity, motivation and well-being of workers by improving decision-making processes. Using inner knowledge management (IKM), this study aims to identify, manage and transform unconscious beliefs and negative emotions that limit decision-making processes.

The methodology used is empirical research, analyzing multiple cases qualitatively and using the T-test statistical model to analyze the hypotheses. The study tests the relation between different limiting beliefs and negative emotions that influence decision-making processes.

This study shows that IKM is positively related to the productivity, motivation and well-being of workers.

The study is limited to workers who are mentally healthy, who work in teams and who seek professional help to achieve their goals.

The results indicate that there is a lot of potential to be explored applying IKM in companies and organizations. Specifically, this study proves that there are several inner knowledge assets that constrain the workers’ potential and therefore affect the efficiency of businesses.

The results have strong implications for how companies and organizations can create great value for themselves and their workers.

To the best of the authors’ knowledge, this is the first data-based study using an IKM model. The importance of this study opens the door to further exploration of the effects on IKM on productivity, motivation and the general well-being of workers.

This paper aims to examine whether financially distressed firms manipulate core or operating income through the misclassification of operating expenses as income-decreasing special items.

This sample comprises firms in the USA with data from 1989 to 2010. The authors used the methodology given in McVay (2006) and multiple regressions.

Managers of financially distressed firms are more likely to inflate core or operating income as compared to the healthy firms to meet or beat earnings benchmarks. They do so by misclassifying core or operating expenses as income-decreasing special items. Specifically, core expenses are shifted to income-decreasing special items like goodwill impairments, settlement costs, restructuring costs and write downs.

The paper sheds light on an important firm characteristic, financial distress that intensifies classification shifting – an earnings management tool which auditors, investors and regulators find tough to detect. The findings have implications for investors, as they fail to comprehend such shifting (McVay, 2006); analysts, who issue forecasts based on street earnings; lenders, as distressed firms may be concealing their true performance; and regulators, as the misclassification of income statement items is a violation of accounting principles.

The authors extend the literature on accruals and real earnings management by the financially troubled firms and present first evidence that the managers of such firms also manipulate core or operating income through classification shifting.

During the last decade, a firm's ability to innovate has gained substantial attention in the literature devoted to innovation and strategic management. This study aims at discussing on what is the relationship of a firm's commitment to learn and its open-mindedness with its activity in introducing organizational innovations. The data collection was carried out in Russia. In order to make the research more specific, the organizational innovation is broken down into two subtypes, namely innovation in management practices and innovation in workplace organization.

The study is grounded on the data obtained by the surveying of 123 Russian top managers working in manufacturing firms. The structural equation modeling was approached in order to investigate the impact of a firm's commitment to learn and open-mindedness on its organizational innovation.

The results indicate that the commitment to learn and the open-mindedness have considerable impact on organizational innovation activity in a firm. The findings also provide evidence that both the investigated subtypes of organizational innovation are positively influenced by commitment to learn and open-mindedness, though the degree of that influence differs.

The literature traditionally focuses mostly on the technological type of innovation leaving the organizational innovation covered by scarce research. In this respect the study contributes to the theory of organizational innovation by elaborating its relations with organizational learning dimensions. Apart from the investigation on the research question at a general level, the study explores the specific context related to the manifestation of phenomenon in a transition economy of Russia.

Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

The objective of this paper is to critically examine the Canadian Accounting Standards Board's (AcSB) legitimacy management strategies directed toward financial statement users.

Suchman's legitimacy typology is used as a lens through which the AcSB's legitimacy management strategies directed toward users are analyzed. The data sources consist of documentary public information available for the overall Canadian standard‐setting process and for a sample of standard‐setting projects.

The results indicate that the AcSB devotes much more efforts to symbolic features and cultural accounts than to pragmatic concerns to ensure its legitimacy toward financial statement users. The legitimacy management strategies used mimic those in the USA and at the international level. Such an isomorphism contributes to the AcSB's cognitive legitimacy and overall cultural legitimacy.

Future research could assess a standard‐setting institution legitimacy management strategies directed to other audiences such as preparers, auditors, or other groups that fall under a broader public interest umbrella.

The results provide Canadian users with a general picture of the AcSB's efforts in their regard and invite them to be sceptical and critical about the so‐called user perspective in standard setting. It also provides standard setters with a legitimacy framework that they can use to identify areas for improvement to enhance users' view of their legitimacy and to help them better fulfil their mission statement.

This paper innovates by studying a standard‐setting institution legitimacy management strategies directed toward a specific audience, financial statement users.

Tree pattern is at the core of XML queries. The tree patterns in XML queries typically contain redundancies, especially when broad integrity constraints (ICs) are present and considered. Apparently, tree pattern minimization has great significance for efficient XML query processing. Although various minimization schemes/algorithms have been proposed, none of them can exploit broad ICs for thoroughly minimizing the tree patterns in XML queries. The purpose of this research is to develop an innovative minimization scheme and provide a novel implementation algorithm.

Query augmentation/expansion was taken as a necessary first‐step by most prior approaches to acquire XML query pattern minimization under the presence of certain ICs. The adopted augmentation/expansion is also the course for the typical O(n⁴) time‐complexity of the proposed algorithms. This paper presents an innovative approach called allying to effectively circumvent the otherwise necessary augmentation step and to retain the time complexity of the implementation algorithm within the optimal, i.e. O(n²). Meanwhile, the graph simulation concept is adapted and generalized to a three‐tier definition scheme so that broader ICs are incorporated.

The innovative allying minimization approach is identified and an effective implementation algorithm named AlliedMinimize is developed. This algorithm is both runtime optimal – taking O(n²) time – and most powerful in terms of the broadness of constraints it can exploit for XML query pattern minimization. Experimental study confirms the validity of the proposed approach and algorithm.

Though the algorithm AlliedMinimize is so far the most powerful XML query pattern minimization algorithm, it does not incorporate all potential ICs existing in the context of XML. Effectively integrating this innovative minimization scheme into a fully‐fledged XML query optimizer remains to be investigated in the future.

In practice, Allying and AlliedMinimize can be used to achieve a kind of quick optimization for XML queries via fast minimization of the tree patterns involved in XML queries under broad ICs.

This paper presents a novel scheme and an efficient algorithm for XML query pattern minimization under broad ICs.

As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).

The paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.

The digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.

This research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.