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A recommendation system for an extended process of information retrieval in distributed information systems is proposed. This system is both a model of dynamic cognitive categorization processes and powerful real application useful for knowledge management. It utilizes an extension of fuzzy sets named evidence sets as the mathematical mechanisms to implement the categorization processes. It is a development of some aspects of Pask’s conversation theory. It is also an instance of the notion of linguistic‐based selected self‐organization here described, and as such it instantiates an open‐ended semiosis between distributed information systems and the communities of users they interact with. This means that the knowledge stored in distributed information resources adapts to the evolving semantic expectations of their users as these select the information they desire in conversation with the information resources. This way, this recommendation system establishes a mechanism for user‐driven knowledge self‐organization.

This paper aims to present an object detection methodology to categorize 3D object models in an efficient manner. The authors propose a dynamically generated hierarchical architecture to compute very fast objects’ 3D pose for mobile service robots to grasp them.

The methodology used in this study is based on a dynamic pyramid search and fast template representation, metadata and context-free grammars. In the experiments, the authors use an omnidirectional KUKA mobile manipulator equipped with an RGBD camera, to localize objects requested by humans. The proposed architecture is based on efficient object detection and visual servoing. In the experiments, the robot successfully finds 3D poses. The present proposal is not restricted to specific robots or objects and can grow as much as needed.

The authors present the dynamic categorization using context-free grammars and 3D object detection, and through several experiments, the authors perform a proof of concept. The authors obtained promising results, showing that their methods can scale to more complex scenes and they can be used in future applications in real-world scenarios where mobile robot are needed in areas such as service robots or industry in general.

The experiments were carried out using a mobile KUKA youBot. Scalability and more robust algorithms will improve the present proposal. In the first stage, the authors carried out an experimental validation.

The current proposal describes a scalable architecture, where more agents can be added or reprogrammed to handle more complicated tasks.

The main contribution of this study resides in the dynamic categorization scheme for fast detection of 3D objects, and the issues and experiments carried out to test the viability of the methods. Usually, state-of-the-art treats categories as rigid and make static queries to datasets. In the present approach, there are no fixed categories and they are created and combined on the fly to speed up detection.

This paper aims to develop frameworks to support implementation and competitive leveraging of distinct sustainable supply chain operations. This derives from conceptual definition of the dynamic capabilities required to support Hart’s (1995) natural-resource-based view resources in the supply chain.

This conceptual study uses qualitative content analysis to extract capabilities from review and analysis of literature related to natural-resource-based view (NRBV) and sustainable supply chain management. Intercoder reliability assessments support conceptual development of such capabilities into dynamic capability frameworks.

Specific interrelations between each NRBV resource and corresponding supply chain strategies are conceptualised. From this, capabilities are categorised to corresponding resources, dynamic capabilities activities and internal–external focus. This results in definition of 107 dynamic NRBV capabilities.

Contributions are threefold: distinct frameworks for competitive sustainable supply chain management is offered; the NRBV benefits from enhanced practical guidance via the definition of its dynamic capabilities, addressing the theory-practice gap; and understandings of dynamic capabilities and their role in both the NRBV sustainable supply chain management is advanced.

This paper offers four frameworks to allow firms to tailor sustainability strategies to suit their needs and guide competitive leveraging. Definition of capabilities offers practical guidance to operationalise NRBV resources.

This is the first holistic interpretation of NRBV capabilities and explicit application of dynamic capabilities. This forms the basis of a broader research agenda for the NRBV in sustainable supply chain management.

Conflict is one of the important aspects of the expatriate-host country nationals (HCNs) dyad. The purpose of this study is to understand how the level of conflict between assigned expatriates and HCNs emerges and evolves during acculturation over time.

Building on expatriate literature, diversity literature, and acculturation literature, the authors adopted a longitudinal lens and developed a conceptual model to describe the dynamic process of conflict emergence and evolvement between assigned expatriates and HCNs.

This study offers a dynamic multi-stage conceptual model with the authors' novel propositions to explain how conflicts between assigned expatriates and HCNs emerge and evolve through the acculturation process.

This study provided a theoretical framework demonstrating when and how conflicts between HCNs and expatriates emerge and evolve during acculturation. In doing so, the authors integrate the conflict and diversity literature with the expatriate literature and offer a theoretical foundation to enrich the authors' understanding of the conflict between expatriates and HCNs.

The purpose of this paper is to introduce the concept of work group diversity dynamics as a novel approach for studying diverse work groups. The authors profile the dynamic processes within diverse work-groups and provide an overview of main objectives.

The paper draws on years of accumulated diversity research to cast a temporal and dynamic lens on the processes taking place within diverse work groups. After outlining the state of the art in work group diversity research, the definition, overall framework and profile of work group diversity dynamics is offered.

The paper argues that by adopting a temporal and dynamic perspective for studying diverse work groups, one can shift focus from the traditional perspective of “what is diversity” to “what happens within diverse work groups”. The paper disentangles the activities taking place within diverse work groups, defines the actual team processes and finally highlights how these processes might be affected by time and dynamism.

After almost 30 years of diversity research the mechanisms and processes through which diversity is translated into individual and organizational outcomes are not yet sufficiently understood and studied. This paper highlights a temporal and dynamic perspective for studying work group diversity, a view that is yet uncharted in diversity literature.

The purpose of this paper is to enhance the predictive power of bankruptcy prediction models by taking the past values of firms’ financial ratios as benchmark. For this purpose, the paper proposes an indicator variable expressing the time trends of financial ratios.

The proposed measure uses the minimum and the maximum of financial ratios from the previous period as benchmarks in order to give a more complete picture about the present financial performance of firms. The most popular classification methods of bankruptcy prediction were employed: discriminant analysis, logistic regression, decision trees. Sample specific results and conclusions were avoided by applying tenfold stratified cross-validation.

The empirical results suggest that the proposed measure can increase the predictive performance of bankruptcy prediction models compared to models based solely on static financial ratios. The results gave evidence for the fact that the firms’ past financial performance is a useful benchmark for evaluating the risk of future insolvency.

The proposed concept is completely new to the literature and practice of bankruptcy prediction. Similar concept has not been published to date. The suggested dynamization approach has three important advantages. It is easy to compute from time series of financial ratios. It is applicable within any classifier irrespective of its mathematical background. The performance of models can be enhanced without the necessity of giving up the interpretability of bankruptcy models, so the proposed measure may play very important role in the practice of credit scoring modeling as well.

Purpose – To develop a new model of restorative reparation that attempts to capture the dynamic role of shared identity perceptions.

Design/methodology/approach – Drawing on recent advances in restorative justice theory (Wenzel, Okimoto, Feather, & Platow, 2008), we explore the theoretical proposition that a greater understanding of the identity relations between victims, offenders, and the groups in which they are embedded is key to understanding a victim's underlying motives toward justice, and thus, predicting when victims will react favorably to restorative justice processes and prefer them over traditional retributive justice interventions.

Findings – We argue that a perceived shared identity between the victim and the offender determines the extent to which the victim understands the transgression as requiring a revalidation of the rules, values, or morals undermined by the offense. Moreover, we propose that these identity relations are dynamic in that they both affect and are affected by the experience of injustice. Thus, identity is also shaped by the transgression itself through, inter alia, processes associated with positive social identity maintenance. Importantly, these shifts in identity determine how injustice victims are likely to respond to constructive approaches to conflict resolution such as restorative justice.

Originality/value – We offer a series of testable hypotheses aimed at engendering future research in the domain of constructive justice restoration in groups. Moreover, this work suggests that to develop effective resolution strategies, we must consider how an injustice event shapes the relations between the affected parties over time rather than simply assuming identity relations are static.

The purpose of this study is to identify factors affecting an organization’s dynamic capability and, consequently, its ability to manage organizational change.

A single case study was conducted to provide a deeper understanding of the situation that the case company experienced during a specific phase of reconfiguration. Data were collected through nine in-depth, semi-structured interviews and analyzed using the Gioia methodology.

Challenges, barriers and enablers affecting the organization's dynamic capability in the reconfiguration phase were identified.

This study contributes to the theory of dynamic capabilities and to the current investigatory stream regarding microfoundations by presenting practical examples of challenges, barriers and enablers that affect an organization’s ability to succeed during an organizational reconfiguration. These examples are intended to aid in discussions on microfoundations of dynamic capabilities and their impact in practice.

Categorizing projects allows for better alignment of a portfolio with the organizational strategy and goals. An appropriate project categorization helps understand portfolio’s structure and enables proper project portfolio selection (PPS). In practice, project categorization is, however, conducted in intuitive approaches. Furthermore, little attention has been given to project categorization methods in the project management literature. The purpose of this paper is to provide researchers and practitioners with a data-driven project categorization process designed for PPS.

The suggested process was modeled considering the main characteristics of project categorization systems revealed from the literature. The clustering analysis is used as the core-computing technology, allowing for an empirically based categorization. This study also presents a real-world case study in the automotive industry to illustrate the proposed approach.

This study confirmed the potential of clustering analysis for a consistent project categorization. The most important attributes that influenced the project grouping have been identified including strategic and intrinsic features. The proposed approach helps increase the visibility of the portfolio’s structure and the comparability of its components.

There is a lack of research regarding project categorization methods, particularly for the purpose of PPS. A novel data-driven process is proposed to help mitigate the issues raised by prior researchers including the inconsistencies, ambiguities and multiple interpretations related to the taken-for-granted categories. The suggested approach is also expected to facilitate projects evaluation and prioritization within appropriate categories and contribute in PPS effectiveness.