The field of organizational psychology is currently in what some scholars have referred to as an affective era (Judge, Weiss, Kammeyer-Mueller, & Hulin, 2017) and have called for examinations of discrete emotions at work. In response to these calls, the subject of gratitude has recently received attention in management research, but there is still little knowledge of the functions of gratitude in the workplace. Therefore, the purpose of this symposium is to provide understanding of gratitude in organizations by exploring its antecedents and outcomes. Specifically, this symposium demonstrates the many ways gratitude can enhance the employment experience for individuals and can foster inclusive organizations. This symposium consists of four papers that explore the significance of gratitude as it is felt and expressed between employees and their coworkers, supervisors, and organizations. Specifically, the first paper investigates the relative contribution of feelings of gratitude toward the organization in the employee-organization relationship as compared to alternative theoretical explanations. The second paper examines the influence of attributions on employee expressions of gratitude toward their supervisors. The third study examines which characteristics of work events lead employees to feel and express gratitude toward coworkers. Finally, the last paper explores the manifestation and functions of gratitude culture at multiple levels of analysis. Together, these papers advance understanding of the positive impact that gratitude can have on employees and their organizations. We believe that this symposium showcases the importance of gratitude in organizations and will motivate future research in this area.
peer-reviewed Purpose - This paper aims to report on the design and development of a new approach for automatic classification and subject indexing of research documents in scientific digital libraries and repositories (DLR) according to library controlled vocabularies such as DDC and FAST.Design/methodology/approach - The proposed concept matching-based approach (CMA) detects key Wikipedia concepts occurring in a document and searches the OPACs of conventional libraries via querying the WorldCat database to retrieve a set of MARC records which share one or more of the detected key concepts. Then the semantic similarity of each retrieved MARC record to the document is measured and, using an inference algorithm, the DDC classes and FAST subjects of those MARC records which have the highest similarity to the document are assigned to it.Findings - The performance of the proposed method in terms of the accuracy of the DDC classes and FAST subjects automatically assigned to a set of research documents is evaluated using standard information retrieval measures of precision, recall, and F1. The authors demonstrate the superiority of the proposed approach in terms of accuracy performance in comparison to a similar system currently deployed in a large scale scientific search engine.Originality/value - The proposed approach enables the development of a new type of subject classification system for DLR, and addresses some of the problems similar systems suffer from, such as the problem of imbalanced training data encountered by machine learning-based systems, and the problem of word-sense ambiguity encountered by string matching-based systems. Submitted
Paper presented at the 4th International Conference on Software and Data Technologies (ICSOFT 2009), 26-29 July 2009, Sofia, Bulgaria Supporting people in the pursuit of their everyday activities is a laudable objective and one which researchers in various disciplines including computing, actively seek to accomplish. The dynamic nature of the end-user community, the environments in which they operate, and the multiplicity of tasks in which they engage in, all seem to conspire against the desired objective of providing services to the end-user community in a transparent, intuitive and context -aware fashion. Indeed, this inherent complexity raises fundamental problems for software engineers as they frequently lack the tools to effectively model the various scenarios that dynamic user behaviour give rise to. This difficulty is not limited to exotic applications or services; rather, it is characteristic of situations where a number of factors must be identified, interpreted, and reconciled such that an accurate model of the prevailing situation at a given moment in time can be constructed. Only in this way, can services be delivered that take into account the prevailing human, social, environmental and technological conditions. Constructing such services calls for a software solution that exhibits, amongst others, diffusion, autonomy, cooperation and intelligence. In this paper, the potential of embedded agents for realising such solutions is explored. Science Foundation Ireland Conference details http://www.icsoft.org/ICSOFT2009/
We consider the problem of a searcher that looks, for example, for a lost flashlight in a dusty environment. The searcher finds the flashlight as soon as it crosses the ray emanating from the flashlight. In order to pick it up, the searcher moves to the origin of the light beam. We compare the length of the path of the searcher to the shortest path to the goal. First, we give a search strategy for a special case of the ray search---the window shopper problem---, where the ray we are looking for is perpendicular to a known ray. Our strategy achieves a competitive factor of $1.059ldots$, which is optimal. Then, we consider rays in arbitrary position in the plane. We present an online strategy that achieves a factor of $22.513ldots$, and give a lower bound of $2pi,e=17.079ldots$.