Workplace sexual harassment 30 years on : a review of the literature

Despite its proscription in legal jurisdictions around the world, workplace sexual harassment (SH) continues to be experienced by many women and some men in a variety of organizational settings. The aims of this review article are threefold: first, with a focus on workplace SH as it pertains to management and organizations, to synthesize the accumulated state of knowledge in the field; second, to evaluate this evidence, highlighting competing perspectives; and third, to canvass areas in need of further investigation. Variously ascribed through individual (psychological or legal consciousness) frameworks, sociocultural explanations and organizational perspectives, research consistently demonstrates that, like other forms of sexual violence, individuals who experience workplace SH suffer significant psychological, health- and job-related consequences. Yet they often do not make formal complaints through internal organizational procedures or to outside bodies. Laws, structural reforms and policy initiatives have had some success in raising awareness of the problem and have shaped rules and norms in the employment context. However, there is an imperative to target further workplace actions to effectively prevent and respond to SH.

The effectiveness of literalism-symbolism in business-to-business advertising

A basic element in advertising strategy is the choice of an appeal. In business-to-business (B2B) marketing communication, a long-standing approach relies on literal and factual, benefit-laden messages. Given the highly complex, costly and involved processes of business purchases, such approaches are certainly understandable. This project challenges the traditional B2B approach and asks if an alternative approach—using symbolic messages that operate at a more intrinsic or emotional level—is effective in the B2B arena. As an alternative to literal (factual) messages, there is an emerging body of literature that asserts stronger, more enduring results can be achieved through symbolic messages (imagery or text) in an advertisement. The present study contributes to this stream of research. From a theoretical standpoint, the study explores differences in literal-symbolic message content in B2B advertisements. There has been much discussion—mainly in the consumer literature—on the ability of symbolic messages to motivate a prospect to process advertising information by necessitating more elaborate processing and comprehension. Business buyers are regarded as less receptive to indirect or implicit appeals because their purchase decisions are based on direct evidence of product superiority. It is argued here, that these same buyers may be equally influenced by advertising that stimulates internally-directed motivation, feelings and cognitions about the brand. Thus far, studies on the effect of literalism and symbolism are fragmented, and few focus on the B2B market. While there have been many studies about the effects of symbolism no adequate scale exists to measure the continuum of literalism-symbolism. Therefore, a first task for this study was to develop such a scale. Following scale development, content analysis of 748 B2B print advertisements was undertaken to investigate whether differences in literalism-symbolism led to higher advertising performance. Variations of time and industry were also measured. From a practical perspective, the results challenge the prevailing B2B practice of relying on literal messages. While definitive support was not established for the use of symbolic message content, literal messages also failed to predict advertising performance. If the ‘fact, benefit laden’ assumption within B2B advertising cannot be supported, then other approaches used in the business-to-consumer (B2C) sector, such as symbolic messages may be also appropriate in business markets. Further research will need to test the potential effects of such messages, thereby building a revised foundation that can help drive advances in B2B advertising. Finally, the study offers a contribution to the growing body of knowledge on symbolism in advertising. While the specific focus of the study relates to B2B advertising, the Literalism-Symbolism scale developed here provides a reliable measure to evaluate literal and symbolic message content in all print advertisements. The value of this scale to advance our understanding about message strategy may be significant in future consumer and business advertising research.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Knowledge integration within Japanese firms : the Fujitsu way

The paper analyses knowledge integration processes at Fujitsu from a multi-level and systemic perspective. The focus is on team-building capability, capturing and utilising individual tacit knowledge, and communication networks for integrating dispersed specialist knowledge required in the development of new products and services. The analysis shows how knowledge integration is performed by Fujitsu at different layers of the company.

The politics of technology adoption : Water metering in Progressive Era Chicago

This paper examines the interactions between knowledge and power in the adoption of technologies central to municipal water supply plans, specifically investigating decisions in Progressive Era Chicago regarding water meters. The invention and introduction into use of the reliable water meter early in the Progressive Era allowed planners and engineers to gauge water use, and enabled communities willing to invest in the new infrastructure to allocate costs for provision of supply to consumers relative to use. In an era where efficiency was so prized and the role of technocratic expertise was increasing, Chicago’s continued failure to adopt metering (despite levels of per capita consumption nearly twice that of comparable cities and acknowledged levels of waste nearing half of system production) may indicate that the underlying characteristics of the city’s political system and its elite stymied the implementation of metering technologies as in Smith’s (1977) comparative study of nineteenth century armories. Perhaps, as with Flyvbjerg’s (1998) study of the city of Aalborg, the powerful know what they want and data will not interfere with their conclusions: if the data point to a solution other than what is desired, then it must be that the data are wrong. Alternatively, perhaps the technocrats failed adequately to communicate their findings in a language which the political elite could understand, with the failure lying in assumptions of scientific or technical literacy rather than with dissatisfaction in outcomes (Benveniste 1972). When examined through a historical institutionalist perspective, the case study of metering adoption lends itself to exploration of larger issues of knowledge and power in the planning process: what governs decisions regarding knowledge acquisition, how knowledge and power interact, whether the potential to improve knowledge leads to changes in action, and, whether the decision to overlook available knowledge has an impact on future decisions.

A comparative analysis of business analysis (BA) and business process management (BPM) capabilities

Many initiatives to improve Business processes are emerging. The essential roles and contributions of Business Analyst (BA) and Business Process Management (BPM) professionals to such initiatives have been recognized in literature and practice. The roles and responsibilities of a BA or BPM practitioner typically require different skill-sets; however these differences are often vague. This vagueness creates much confusion in practice and academia. While both the BA and BPM communities have made attempts to describe their domains through capability defining empirical research and developments of Bodies of knowledge, there has not yet been any attempt to identify the commonality of skills required and points of uniqueness between the two professions. This study aims to address this gap and presents the findings of a detailed content mapping exercise (using NVivo as a qualitative data analysis tool) of the International Institution of Business Analysis (IIBA®) Guide to the Business Analysis Body of Knowledge (BABOK® Guide) against core BPM competency and capability frameworks.