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This study examines the implications of real asset liquidity for accounting conservatism. We investigate whether the liquidity of a firm’s physical assets mitigates lenders’ demand for conservatism by increasing the amount lenders can recover if the firm is liquidated, a theoretical prediction in Göx and Wagenhofer (2009).

We use an asset redeployability index as a proxy for firm-level real (physical) asset liquidity and adopt ordinary least squares (OLS) regressions in the test. We also investigate the differential impact of real asset liquidity on conservatism in two unique settings where lenders’ demand for accounting conservatism varies (loan initiation and bank deregulation).

We find that accounting conservatism decreases as real asset liquidity increases. The negative effect of real asset liquidity on conservatism increases as the quantity of the firm’s real assets increases, and the negative association is strengthened when firms face high financing constraints and have access to public debt markets. The moderating effect of real asset liquidity on lenders’ demand for conservatism increases (decreases) when real asset liquidity is more (less) important to lenders.

This study provides direct empirical evidence for the theoretical prediction in Göx and Wagenhofer (2009). Prior research shows that real asset liquidity impacts a firm’s capital structure and investment decisions (Campello and Giambona, 2013; Kim and Kung, 2017; Ortiz-Molina and Phillips, 2014; Williamson, 1988). We complement this literature by providing evidence that real asset liquidity also plays a role in financial reporting by reducing accounting conservatism.

Following calls at different times in the United States for the definition of the body of knowledge (BOK) of real estate discipline, this briefing sets out to define the intellectual boundaries of real estate and applies the definitional concept to map out the scopes of real estate professions and real estate valuation vocation

The study essentially uses a literature review to draw out definitional issues that have been tackled before. It reviews calls that have been made in the past for a definition of the BOK of the real estate discipline. Further, it reviews past attempts at definition to reveal why they failed at the definition project.

The study found three key suggestions made in the past: that there is a need to define real estate’s BOK, that there is a need to use a “central structure” to define the BOK of real estate, and that definition of the BOK of real estate should rely on the activity nodes that constitute real estate. The study has relied on these three key ideas to define real estate as the science of value creation, distribution and sustenance in built space.

The definition of the BOK will help in curriculum development for real estate education. It will help faculties and departments to single out what fits into the real estate curriculum and what does not fit in.

A definition of the BOK for real estate: reconceptualizing the discipline and delineating jurisdictional boundaries of its practice.

To evaluate the temperature-dependency of the Young’s and shear moduli of concrete after exposure to moderately elevated temperatures using the non-destructive impulse excitation technique (IET).

The study involved heating the concrete up to 225 °C and measuring the dynamic Young’s and shear moduli using the non-destructive technique of impulse excitation, which measures the natural vibration frequency from a mechanical impulse received by an acoustic sensor. The effects of temperature on the dynamic Young’s and shear moduli were analysed and the importance of the spatial variability of the measured values was also verified.

The study found that even moderately elevated temperatures (below 225 °C) resulted in a significant permanent reduction in the Young’s modulus of concrete (reduction in the range of 23%–36% for the maximum temperature considered in this research) as well as a modest and permanent reduction in the shear modulus of around 6%. It was also observed that spatial variability of the mechanical properties of concrete plays an important role in the measured values; higher dispersion of the results was found for the values of the Young’s and shear moduli of concrete measured along the height of the beam. The non-destructive test method used in this study was found to be extremely useful in the investigation of heat-related damage in concrete structures for its ease of use, low time consumption and accuracy. The results were consistent with the published literature.

This study provides important insights into the temperature-dependent behaviour of the dynamic Young’s and shear moduli of concrete and highlights the significance of proper consideration of the spatial variability of the measured values. The use of a non-destructive test method for continuous acoustic testing during heating and cooling proved to be effective, and the findings contribute to the fields of materials science and civil engineering in understanding the effects of elevated temperatures on concrete properties. The findings confirm that IET can be easily used to gather important information in the condition assessment and rehabilitation of concrete structures after a fire event. Further studies to foster the application of this technique to real structures are suggested.

This paper presents an original approach for learning models, partially known, of particular interest when performing source identification or structural health monitoring. The proposed procedures employ some amount of knowledge on the system under scrutiny as well as a limited amount of data efficiently assimilated.

Two different formulations are explored. The first, based on the use of informed neural networks, leverages data collected at specific locations and times to determine the unknown source term of a parabolic partial differential equation. The second procedure, more challenging, involves learning the unknown model from a single measured field history, enabling the localization of a region where material properties differ.

Both procedures assume some kind of sparsity, either in the source distribution or in the region where physical properties differ. This paper proposed two different neural approaches able to learn models in order to perform efficient inverse analyses.

Two original methodologies are explored to identify hidden property that can be recovered with the right usage of data. Both methodologies are based on neural network architecture.

This article presents a fuzzy cognitive map for the evaluation of innovation in organizations.

The purpose of this paper is to develop a model to evaluate the innovative capacity of organizations based on fuzzy cognitive maps (FCM), particularly for micro, small and medium-sized enterprises (MSMEs). The specification of the innovation evaluation model based on FCM was carried out with the “Intelligent Decision Support System” methodology. It is a six-step methodology: selection of experts, definition of concepts and relationships, model design, inference, interpretation and decision.

Our approach yielded good results in three case studies, effectively determining the level of innovation in an organization. The fuzzy cognitive maps demonstrated a high level of accuracy, with an accuracy of 82% in the Colombian case studies and 92% in the global case studies. These results highlight the effectiveness of the model for quantitatively assessing levels of innovation within organizations. Furthermore, the study revealed the most influential and essential innovative activities/variables within organizations, contributing significantly to the improvement of their operations and competitiveness.

It is important to automate the definition of the relationships between the concepts of the context and of our FCM. It is also possible to improve the behavior of the FCM by analyzing the variables with a greater impact on the level of innovation and very dynamic in the context since they are the variables to be observed in real-time to follow the evolution of the innovative behavior of an organization.

The study found that innovative activities emerged as an influential factor in organizations, essential to improving their operations and competitiveness. Our model can help in identifying areas that require improvement to impact positively organizations. By improving innovation assessment through the FCM model, organizations can anticipate higher profitability because innovations are often closely tied to revenue generation and cost savings. The tool can determine the necessity of new products or services, improve operational processes or enter new markets.

The previous results in the literature show that although there are relevant advances on this topic, there is not enough knowledge to provide clear guidelines for evaluating innovation and improving performance in an organization using intelligent systems. Also, previous works have not defined a framework for evaluating innovation in MSMEs based on FCMs. They also do not use the data of an organization to assess the key characteristics related to innovation. This work applies FCM to automate the evaluation of the process and the capacity for innovation in an organization. These are the main differences between our approach and previous studies.

Higher education institutions are the contemporary embodiment of knowledge-intensive organizations. The role of knowledge sharing among academics in enhancing teaching, research and innovation performance cannot be overlooked. However, a paucity of studies were devoted to uncovering the influencing factors of knowledge sharing among academics in China. This study aims to dig into the factors that influence academics’ knowledge sharing behaviors in the context of Chinese higher education.

Semi-structured interviews were conducted with 13 academics from universities across various regions in China by using a combination of convenience, snowball and purposive sampling methods. Thematic analysis was employed where data sets were examined according to the initial categorization of factors based on a review of the literature while new factors were searched based on frequency of re-occurrence.

Perceived loss of power and time and effort significantly hinder knowledge sharing, whereas expected self-development and association are major catalysts of knowledge sharing. The organizational climate in higher education is featured by competition and individualism, which are not conducive to knowledge sharing, while affiliation and trust are essential for cultivating a pro-sharing environment. Technological tools are perceived as user-friendly and useful in facilitating knowledge sharing, but doubts were raised about the effectiveness of online knowledge sharing compared to face-to-face communication.

Deviating from the conventional quantitative approach, this study provides novelty insights on this topic by revealing some less-investigated factors of knowledge sharing among Chinese academics by taking the qualitative approach.

Extant studies propose music sentiment as a novel measure of individuals’ sentiment. These studies argue that individuals’ choice of music reflects their emotional condition in real time and influences their cognitive ability, making it a powerful tool for assessing their mood. This study aims to use music sentiment as a proxy for auditors’ mood and explore its impact on audit quality.

A sample of the US firms from 2017 to 2020 is used in the study. The authors apply the ordinary least squares regressions and the logit regressions to the audit quality models. The authors use absolute discretionary accruals and the propensity to meet or beat earnings forecasts as proxies for audit quality and calculate a stream-weighted average sentiment measure for Spotify’s Top-200 songs of each day during the audit period of a client firm to capture the sentiment of auditors.

The authors find that music sentiment is positively associated with audit quality. The result is consistent with the mood maintenance hypothesis, which suggests that a positive mood can induce auditors to be more careful in risky situations. Furthermore, the result is robust to various sensitivity analyses.

The study contributes to the scarce literature that focuses on auditors’ emotional state and highlights the importance of monitoring auditor mindset during the audit period.

The objective of this article is to analyze the integration between the internal functions related to demand and supply processes. The studied object was an agribusiness company that uses digital technologies to operate its inbound logistics.

A case study was conducted in a global agribusiness company that went through a restructuring process with the implementation of a shared service center. In-depth interviews were conducted with employees from the demand and supply areas. The analysis involved description of cross-functional integration processes from the areas of demand and supply, the identification of technologies from Industry 4.0 present in the activities of those areas and their role in the integration process.

The analysis revealed the mediating role of technology in cross-functional integration, the presence of new integration factors and their impact on process performance. A framework was developed that describes the relationship between technology and integration factors, their impacts, and the implications for theory and practice.

Regarding this study, the focal company migrated its activities, which were previously isolated and dispersed across branches, to a centralized shared services unit. This research contributes by providing managers with elements to support their investment decisions in technologies that facilitate the integration process, mainly in the areas of planning and execution. It also contributes to the planning of processes, helping managers who are implementing or migrating activities and areas to new management structures.

This paper brings two new assumptions that may guide future investigations about cross-functional integration and its effects on demand and supply integration (DSI): (1) Digital technologies are able to support cross-functional integration in order to provide information integrity, team alignment, agile and assertive decision making within supply and demand processes; (2) Cross-functional integration, mediated by digital technologies, can generate agility and accuracy of information in the demand and supply processes. This accuracy and agility provide improvements in demand and supply process performance metrics, such as predictability, assertiveness, standardization, productivity and response time.

Introduction: Globalization and customer expectations have made managing the supply chain challenging. Blockchain technology has enhanced visibility, accountability, and safety in supply Chain management (SCM), which helps overcome various issues. The research aims to provide insight into Blockchain technology for improving supply chains toward sustainability in the retail sector. This study describes how clients and merchants in various retail business activities may significantly utilize Blockchain technology. From manufacturer to consumer, blockchain can track materials. It ensures product authenticity, transparency, and retail supply chain trust. Retail items are tracked before they reach customers to assess quality and discard expired items, building client confidence. Retail personnel’ SC (Supply Chain) blockchain adoption aspirations are examined in this study.

Methodology: This study validates SCM blockchain adoption using an adjusted UTUAT (Unified Theory of Acceptance and Use of Technology) model. This study examines how blockchain adoption improves employee performance using the UTUAT Model. Data was evaluated using exploratory factor and structural equation modeling.

Result: Behavioural intention was significantly associated with BCT (Block Chain Technology) in retail SCM.

Practical Implications: The following factors influence the behavioral intent to utilize the technology: performance expectations, affect expectations, subjective standards, and favorable conditions, which have a significant impact on adoption.

Conclusion: Performance and effort assumptions affect SCM blockchain adoption behavior.

The case was written using information and data from secondary sources. It describes real people and the situations experienced by them. It does not use any fictitious names, scenarios or organizations.

The case study “Melanie Perkins: Poised to Redesign Canva from Tech Unicorn to Tech Giant?” describes the entrepreneurship journey of Melanie Perkins (she) (Perkins), the CEO of Australia-based tech unicorn and graphic design company, Canva Pty Ltd. (Canva). The case starts with a brief look into Perkins’ background and documents her entrepreneurial spirit, which, at the age of 19, led her to identify a hitherto unserved market (yearbooks) in the graphic design industry and offer an online design system through her venture, Fusion Books (Fusion). Fusion was completely bootstrapped and became a runaway success within five years. That encouraged her to envision setting up a one-stop-shop design site that would make design accessible to everyone.

However, when she tried to raise funds, Perkins encountered multiple rejections from venture capitalists. She persevered and continually refined her strategy. Eventually, she managed to raise venture capital funding and establish her design startup, Canva, in 2013. Canva then went on to disrupt the graphic design industry. The case describes in detail the reasons for Canva’s success, which went on to be one of the few profitable unicorn start-ups. The case also throws light on how Perkins used Canva as a tool to change society with her two-step plan. Despite its market success, Canva faced heavy competition in the design and publishing space from well-established players. Can Perkins challenge the competition and ultimately make Canva a software giant in the future?

The case is intended for use in teaching the subjects “Entrepreneurship Development,” “Business Strategy,” “Leadership Skills and Change Management” and “Positive Psychology for Managers” in both graduate and post-graduate programs.