The marketing intelligence contributions made by industrial sales forces as part of the corporate planning process

This thesis has been concerned with analysing the involvement of industrial sales forces in providing adequate and realistic intelligence to be used as a basis for the forward planning undertaken by the Marketing function. An empirical study of the activities, of the sales force in 60 companies has been undertaken. The type of intelligence being acquired by salesmen has been examined and divided into five categories (ie. Product, Customer/Market, Competition, Long Term Volume Forecasts, and Other Topics). The different reporting techniques for conveying the intelligence to the Marketing department have been evaluated, and an analysis made of the use to which the information has been placed by staff of the department. The research shows the necessity for companies to create intermediary agencies to scrutinise intelligence passing between salesmen and Marketing staff. Several hypotheses have been, tested against the information collected in the investigation. The results obtained from examining such hypotheses illustrate the need for companies to think of the following matters when considering how a sales force reporting system can be made effective: 1) the provision of key production and financial data to salesmen to improve their knowledge of company policies; 2) the organisation structure within which salesmen operate; 3) the implementation of training programmes to develop the interactive skills of salesmen; 4.) the means of motivating salesmen to gather facts; 5) the categorisation of the different types of customer call made by salesmen. The investigations reveal that companies selling high cost products and systems to markets characterised by rapid technological change have been most prominent in requesting sales force intelligence. Salesmen have been most active in the collection of intelligence about products and competitors, and have been less concerned with analysing customer operations and developing business volume forecasts.. The salesman is a costly corporate asset, and the research highlights that in his information-gathering role he helps to- devise marketing strategies that can materially affect corporate performance

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

A Comparison of Information Systems Coverage in the CPA, CIA and CMA Examinations for the Period 1987-1991

In recent years, three major accounting professional organizations, the American Institute of Certified Public Accountants (AICPA), Institute of Management Accountants (IMA) and Internal Auditors Institute (IIA) have considered and issued statements on the body of knowledge deemed necessary for practice as a Certified Public Accountant, Certified Management Accountant and Certified Internal Auditor. In each instance, knowledge and skills in information systems technology were included. This is not surprising, in view of the fact that changes in technology have dramatically altered the way in which accounting data is gathered, processed, stored, accessed and reported. Each of these professional organizations also requires or recommends the passing of an organization-sponsored certification examination for entry into or recognition within the various practice areas. While the examinations are not the only means of assessing the knowledge and skills necessary for certification, they are an important tool in evaluating the extent of the qualifications presented by a candidate. In view of the above, one may postulate that the certification examination, in each instance, would include coverage of the areas of knowledge included in the prerequisite body of knowledge. In particular, since each of the professional groups cite information systems (IS) knowledge as an important knowledge component, one would expect to observe test items addressing current IS in each exam

A knowledge based system for valuing variations in civil engineering works: a user centred approach

There has been much evidence that valuing variations in construction projects can lead to conflicts and disputes leading to loss of time, efficiency, and productivity. One of the reasons for these conflicts and disputes concerns the subjectivity of the project stakeholders involved in the process. One way to minimise this is to capture and collate the knowledge and perceptions of the different parties involved in order to develop a robust mechanism for valuing variations. Focusing on the development of such a mechanism, the development of a Knowledge Based System (KBS) for valuing variations in civil engineering work is described. Evaluation of the KBS involved demonstration to practitioners in the construction industry to support the contents of the knowledge base and perceived usability and acceptance of the system. Results support the novelty, contents, usability, and acceptance of the system, and also identify further potential developments of the KBS

Review of research in feature-based design

Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems do. The evolution of feature definitions is briefly discussed. Features and their role in the design process and as representatives of design-objects and design-object knowledge are discussed. The main research issues related to feature-based design are outlined. These are: feature representation, features and tolerances, feature validation, multiple viewpoints towards features, features and standardization, and features and languages. An overview of some academic feature-based design systems is provided. Future research issues in feature-based design are outlined. The conclusion is that feature-based design is still in its infancy, and that more research is needed for a better support of the design process and better integration with manufacturing, although major advances have already been made

Knowledge Base Population using Semantic Label Propagation

A crucial aspect of a knowledge base population system that extracts new facts from text corpora, is the generation of training data for its relation extractors. In this paper, we present a method that maximizes the effectiveness of newly trained relation extractors at a minimal annotation cost. Manual labeling can be significantly reduced by Distant Supervision, which is a method to construct training data automatically by aligning a large text corpus with an existing knowledge base of known facts. For example, all sentences mentioning both 'Barack Obama' and 'US' may serve as positive training instances for the relation born_in(subject,object). However, distant supervision typically results in a highly noisy training set: many training sentences do not really express the intended relation. We propose to combine distant supervision with minimal manual supervision in a technique called feature labeling, to eliminate noise from the large and noisy initial training set, resulting in a significant increase of precision. We further improve on this approach by introducing the Semantic Label Propagation method, which uses the similarity between low-dimensional representations of candidate training instances, to extend the training set in order to increase recall while maintaining high precision. Our proposed strategy for generating training data is studied and evaluated on an established test collection designed for knowledge base population tasks. The experimental results show that the Semantic Label Propagation strategy leads to substantial performance gains when compared to existing approaches, while requiring an almost negligible manual annotation effort.Comment: Submitted to Knowledge Based Systems, special issue on Knowledge Bases for Natural Language Processin