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The research objective was twofold: first, to propose a novel framework for composing an organization’s aggregate risk appetite, and second, to demonstrate the application of this framework in a suitable organization.

A conceptual framework for defining an organization’s aggregate risk appetite was developed based on relevant organizational theory and research through the lens of knowledge management. The organizational appetite for risk framework was subsequently implemented at the São Paulo State Technological Research Institute (IPT) using the design science research approach. Finally, the implementation was carefully examined in order to encourage future applications and to further refine the appetite for risk framework.

The composition and application of the proposed appetite for risk framework optimally identified the aggregated risk appetite of the complete test organization. Moreover, organizational differences between bottom-up tolerance and top-down appetite were revealed.

Our main practical contribution is a comprehensive procedure to conduct a risk assessment and achieve an organization-wide aggregate risk appetite through the lens of knowledge management.

Unlike past theory and research that take a strictly top-down approach to risk appetite, our framework integrates dispersed knowledge on risk-taking at various levels of the organization, thereby contributing to the underexplored role of bottom management in shaping aggregate risk appetite.

The purpose of this paper is to build a classification system which mimics the perceptual ability of human vision, in gathering knowledge about the structure, content and the surrounding environment of a real-world natural scene, at a quick glance accurately. This paper proposes a set of novel features to determine the gist of a given scene based on dominant color, dominant direction, openness and roughness features.

The classification system is designed at two different levels. At the first level, a set of low level features are extracted for each semantic feature. At the second level the extracted features are subjected to the process of feature evaluation, based on inter-class and intra-class distances. The most discriminating features are retained and used for training the support vector machine (SVM) classifier for two different data sets.

Accuracy of the proposed system has been evaluated on two data sets: the well-known Oliva-Torralba data set and the customized image data set comprising of high-resolution images of natural landscapes. The experimentation on these two data sets with the proposed novel feature set and SVM classifier has provided 92.68 percent average classification accuracy, using ten-fold cross validation approach. The set of proposed features efficiently represent visual information and are therefore capable of narrowing the semantic gap between low-level image representation and high-level human perception.

The method presented in this paper represents a new approach for extracting low-level features of reduced dimensionality that is able to model human perception for the task of scene classification. The methods of mapping primitive features to high-level features are intuitive to the user and are capable of reducing the semantic gap. The proposed feature evaluation technique is general and can be applied across any domain.

The purpose of this study is the review of current status of action research (AR) and design science (DS) in logistics and supply chain management (SCM) and to compare AR and DS.

The paper’s approach comprises the literature review of AR and DS articles.

First, not much has changed in terms of number of published AR articles, despite frequent calls for more relevant research. One explanation is the academic system. Second, there is an increased focus on theory, which from a positive perspective is a sign of our field maturing, yet the academic system and current editorial philosophies may also contribute to this development. Third, DS is emerging as a potential replacement of AR.

The study provides suggestion for both authors and editors when it comes to the increased focus on theory. Comparing AR and DS, the two approaches are similar. However, while the increased focus on theory is reflected in DS, it also seems to be an inferior approach for ill-defined change-focused problems, requiring in-depth, collaborative, data-rich, longitudinal studies.

This paper is the first article that reviews and compares AR and DS in LSCM.

To study the strategies of eBay as it moves on from its now “traditional” online market for the masses to extend its expertise into areas such as business to business. The paper also considers online trading in general.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Amanda Aldridge notes that, as well as being an online auction, eBay is increasingly acting as a shop‐front for new goods sold by professional retailers at fixed prices. She recommends that retailers start selling small batches of goods on eBay and to consider how to integrate this with their existing multi‐channel strategies. Glenn Baker warns that, with the fragmentation of traditional marketing media and the rise of the Internet, any company without an e‐marketing strategy may fall by the wayside. Dhruv Grewal et al. suggest that although online retailing started out as a separate retail format, it has now become part of a multi‐channel strategy. They list, and explain, various limiters and enablers to Internet retailing growth. Ralph A. Oliva says that some of the benefits and innovations being brought to individual customers by eBay are now available to small businesses, and that eBay is creating a new marketplace for the sort of things small businesses need. Growth to service bigger industries is a distinct possibility.

Offers advice to businesses which have not yet taken the “online plunge” that they might be wise to test the water, accepting it as just another channel for their goods.

This study, based on stakeholder theory, aims to analyse the factors that can affect the level of visual disclosure in the context of integrated reporting (IR), which represents the last frontier of corporate disclosure.

This study develops an innovative measure to measure the level of visual disclosure of integrated reports that takes into account the use and degree of integration of images and graphs. Furthermore, to test the hypotheses, this study uses a regression model on a sample of 134 international companies that published an integrated report in 2018.

The results show that firm size, firm profitability and industry environmental sensitivity positively affect the level of visual disclosure of the integrated reports.

To our knowledge, this is the first study that examines visual disclosure in the IR context. It also extends the field of application of the stakeholder theory, still little used to explain visual disclosure strategies, and increases knowledge on the determinants of IR.

To cope with the complexity of modern retail stores and personal time constraints, shoppers must be selective in processing information. During a typical shopping trip, they visit only a fraction of a store’s departments and categories, examine a small subset of the available products, and often make selections in just a few seconds. New research techniques can help marketers understand how customers allocate their attention and assess the impact of in-store factors on shopper behavior. This chapter summarizes studies using observational research, virtual reality simulations, and eye tracking to identify the drivers of shopper attention, product engagement, and purchase conversion. These include shopper goals; product assortment, package appearance, price, and merchandising; shelf space allocation, organization, and adjacencies; and salesperson interaction. The research reveals that small changes in a product’s appearance and presentation can have a powerful impact on consideration and choice.

Artifacts are rarely used today to visualize thoughts, insights, and ideas in strategy work. Rather, textual and verbal communication dominates. This is despite artifacts and visual representations holding many advantages as tools to create and make sense of strategy in teamwork. To advance our understanding of the benefits of visual aids in strategy work, I synthesize insights from cognitive psychology, neuroscience, and management research. My analysis exposes distinct neurocognitive advantages concerning attention, emotion, learning, memory, intuition, and creativity from visual sense-building. These advantages increase when sense-building activities are playful and storytelling is used.

Two‐dimensional finite difference calculations are carried out to study laminar flow in longitudinal and transverse convection rolls for three different geometries: a single rectangular cavity with high aspect ratio; a double cavity with a thin separation sheet; and a double cavity with a separation sheet and a honeycomb structure. The equations for the convection‐diffusion in the fluid and conduction in the solid region are solved simultaneously. Good agreement with experimental data is achieved for Rayleigh numbers not too high above the critical value for the onset of secondary convection rolls (Ra < 8500 for vertical and Ra < 2700 for horizontal cavities filled with air). Simulation fails for inclined cavities, where the flow structure is essentially three‐dimensional.

In this paper a numerical simulation, based on finite difference techniques, has been developed in order to analyse turbulent natural and mixed convection of air in internal flows. The study has been restricted to two‐dimensional cavities with the possibility of inlet and outlet ports, and with internal heat sources. Turbulence is modelled by means of two‐equation k‐ε turbulence models, both in the simplest form using wall functions and in the more general form of low‐Reynolds‐number k‐ε models. The couple time average governing equations (continuity, momentum, energy, and turbulence quantities) are solved in a segregated manner using the SIMPLEX method. An implicit control volume formulation of the differential equations has been employed. Some illustrative numerical results are presented to study the influence of geometry and boundary conditions in cavities. A comparison of different k‐ε turbulence models has also been presented.