{"title":"Language maintenance and loss: evidence from language perception and production","authors":"A. E. Aissati, A. Schaufeli","doi":"10.1515/9783110807820.363","DOIUrl":"https://doi.org/10.1515/9783110807820.363","url":null,"abstract":"","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80737590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Journeys up the mountain: Different paths to learning object-oriented programming","authors":"H.James Nelson, Gretchen Irwin, David E. Monarchi","doi":"10.1016/S0959-8022(96)00024-0","DOIUrl":"https://doi.org/10.1016/S0959-8022(96)00024-0","url":null,"abstract":"<div><p>Among the challenges facing companies transitioning from structured to object-oriented (OO) programming is how (and whether) to retrain existing procedural programmers. Common wisdom has it that old-time programmers can be retrained in object technology only with great difficulty, but new programmers lack experience building large systems and the knowledge of the business. This paper describes a study of students learning OO programming where the participants ranged in experience from a single semester of programming to over 10 years of professional programming. The purpose of this study was to explore how students learn OO programming by observing them between their first exposure to OO programming and the time they finally “get it.” We identified five categories of learners who each took a different path to learning OO programming, encountered different obstacles, and adopted different learning strategies. We describe some factors that may play a part in helping and/or hindering a student's progress and that may be used to predict a student's learning category. We conclude with suggestions for alternative training program strategies that may be appropriate for each category and with directions for future research.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"7 2","pages":"Pages 53-85"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0959-8022(96)00024-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89993694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Workflow meets work practice","authors":"Kari Thoresen","doi":"10.1016/S0959-8022(97)00002-7","DOIUrl":"10.1016/S0959-8022(97)00002-7","url":null,"abstract":"<div><p>This paper explores computer-supported cooperative work in a workflow oriented material administration system in a large company. The community of users belong to different job categories with different opinions of the system. The company's regulative framework for material administration forms the basis for the workflow embedded in the system. However, the assumptions regarding organizational context underlying the regulations and the workflow, are based on conditions only partly fulfilled in everyday work practice. This creates a disparity between intended and actual use of the system, requiring articulation work. The paper identifies elements of the disparity, and analyzes the conditions that necessitates the articulation work. It is argued that the disparity is due to complex interactions between system design and organizational context. The paper intends to contribute to the development and grounding of concepts that enable us to grapple with the complexity of this interaction.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"7 1","pages":"Pages 21-36"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0959-8022(97)00002-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77353697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Accounting information systems and organization learning: A simulation","authors":"Aris M. Ouksel, Ken Mihavics, Peter Chalos","doi":"10.1016/S0959-8022(97)00001-5","DOIUrl":"10.1016/S0959-8022(97)00001-5","url":null,"abstract":"<div><p>Accounting Information Systems may facilitate or impede organizational learning. Critical attributes of accounting systems that have the potential to affect organizational learning include: (1) characteristics of the information environment, whether uniform, dispersed or clustered importance weights; (2) information distribution, whether overlapping or segregated information; and (3) information coordination mechanisms, whether expert teams, majority voting teams or hierarchies. Organizational learning and performance was simulated in the following manner: (i) the organization was faced with a continuous sequence of repetitive but not identical problems; (ii) the organizational task was subdivided between analysts; and (iii) analysts learned by basing their decisions on the relationship found between information available to them and organizational outcomes. Simulation results indicated that learning in flatter (team) organizations is generally more accurate than in hierarchical organizations. Learning is also faster with majority teams than hierarchies, but slower with expert teams. Overlapping accounting information transmission between agents was found to offer only limited benefits. These findings have implications for the design of accounting information systems in organizations.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"7 1","pages":"Pages 1-19"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0959-8022(97)00001-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81760423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Applications of uncertainty-based mental models in organizational learning: A case study in the Indian automobile industry","authors":"V Srinivas, B. Shekar","doi":"10.1016/S0959-8022(97)80164-6","DOIUrl":"10.1016/S0959-8022(97)80164-6","url":null,"abstract":"<div><p>In this paper, we discuss the applicability of qualitative and quantitative reasoning techniques to study the process of Organizational Learning. We have used cognitive maps of a company (for the past five years) taken from the Indian automobile industry to understand the Organizational Learning process. We have conducted stochastic simulation experiment on an uncertainty-based cognitive map (the latest year). We generated scenarios for the future and analysed each scenario with respect to data obtained from the past five-years cognitive maps, in light of the theory on Organizational Learning.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"7 2","pages":"Pages 87-112"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0959-8022(97)80164-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91544761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Managing Complexity in Large Data Bases Using Self-Organizing Maps","authors":"B. Back, M. Irjala, K. Sere, H. Vanharanta","doi":"10.1016/S0959-8022(98)00009-5","DOIUrl":"https://doi.org/10.1016/S0959-8022(98)00009-5","url":null,"abstract":"","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"40 1","pages":"191-210"},"PeriodicalIF":0.0,"publicationDate":"1996-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78099570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A comment on the intellectual structures of information systems development","authors":"Soon Ang","doi":"10.1016/0959-8022(96)00014-8","DOIUrl":"10.1016/0959-8022(96)00014-8","url":null,"abstract":"","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"6 1","pages":"Pages 65-69"},"PeriodicalIF":0.0,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0959-8022(96)00014-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81885394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The enactments and consequences of token, shared, and compliant participation in information systems development","authors":"Laurie J. Kirsch, Cynthia M. Beath","doi":"10.1016/S0959-8022(96)90015-6","DOIUrl":"10.1016/S0959-8022(96)90015-6","url":null,"abstract":"<div><p>System development methodologies assert that user participation is crucial for successful information systems development efforts. User participation is advocated for product and process reasons: to select system features and to coordinate the work between client and developer. However, a closer examination of the methodologies reveal that the prescriptions for user participation are often contradictory. The IS research literature acknowledges these contradictions, but presents empirical results that are largely inconclusive. The purpose of this paper is to examine how user participation is actually enacted in practice, and to explain why those enactments' result in particular project outcomes, such as task-system fit, psychological involvement, and client ownership of the system. An in-depth qualitative analysis of eight information systems development projects reveals three patterns of user participation enactment: token, shared, and compliant. These patterns vary in terms of who brings technical and domain knowledge to the project, who controls feature selection, what coordination mechanisms are used, and how conflict is handled. Further, the analysis shows that: (1) the form of the enactment is as much the choice of the client as it is the choice of systems developers; (2) client ownership of systems is not a result of sign-offs, but a result of how clients view their overall responsibilities and organizational accountability; (3) intense user participation is not required for high task-system fit; and (4) client attitudes can be influenced by the actions of developers. Implications for research and practice are drawn.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"6 4","pages":"Pages 221-254"},"PeriodicalIF":0.0,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0959-8022(96)90015-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84145007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An empirical investigation of judgment feedback and computerized decision support in a prediction task","authors":"Vairam Arunachalam, Bonita A. Daly","doi":"10.1016/0959-8022(96)00020-3","DOIUrl":"10.1016/0959-8022(96)00020-3","url":null,"abstract":"<div><p>This study examines the effects on judgment accuracy of cognitive and outcome feedback provided using a computerized decision support tool. Five feedback conditions were examined in a two-stage experiment utilizing 294 participants: an outcome feedback condition, two cognitive feedback conditions (judgment policy feedback and model predictions feedback), and two joint feedback conditions (judgment policy plus outcome feedback, and model predictions plus outcome feedback). In the first stage, decision makers specified the judgment policies (i.e. cue weights and function forms) that they believed they would use in making their earnings predictions. They were then asked to forecast earnings per share for several companies based on average earnings for the last three years, current year gross margin percentage, quick ratio and eamings yield. Using appropriately modified end-user software, feedback was then provided to all participants, except those receiving outcome feedback only. Judgment policy feedback consisted of informing decision makers of the cue weights and function forms underlying their actual predictions, while model predictions feedback consisted of earnings predictions generated from the decision makers' stated judgment policies. In the second stage, decision makers revised or retained their original judgment policies and then made another set of earnings predictions. Outcome feedback, consisting of information about the actual earnings attained by the companies, was then provided to participants in the outcome feedback and joint feedback conditions. This process was then repeated for a new set of companies to determine how the various forms of feedback influenced judgment accuracy. Results indicated that providing decision makers with either type of cognitive feedback, relative to providing outcome feedback, contributed to improvements in judgment accuracy. There were no significant differences between the judgment accuracy of the cognitive feedback conditions and of the respective joint feedback conditions, indicating that adding outcome feedback did not enhance judgment accuracy. Results also suggested that model predictions feedback may be more effective than judgment policy feedback, which in turn is superior to outcome feedback. All cognitive feedback conditions, relative to outcome feedback only, also demonstrated convergence between stated model predictions and actual predictions. These results are discussed in terms of implications for the design of decision support systems for individual judgment tasks.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"6 3","pages":"Pages 139-156"},"PeriodicalIF":0.0,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0959-8022(96)00020-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81448581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring the intellectual structures of information systems development: A social action theoretic analysis","authors":"Rudy Hirschheim, Heinz K. Klein, Kalle Lyytinen","doi":"10.1016/0959-8022(96)00004-5","DOIUrl":"10.1016/0959-8022(96)00004-5","url":null,"abstract":"<div><p>In this paper we explore the intellectual structures upon which the field of information systems development (ISD) is cultivated. The conceptual base of our work comes from the social action theories of Habermas and Etzioni. We propose a framework which reconceptualizes the field in terms of domains, orientations, object systems, and development strategies. Our analysis not only justifies the reflection of the field as a so-called “fragmented adhocracy”, but also shows why this is so: because IS researchers' mind sets fundamentally differ in terms of how problems are formulated and consequently solved. The intellectual structures of our framework suggest nine conceptual frames which mold these mind sets. Each frame acts as a lens and embraces a different development strategy which distinguishes itself in its dominant orientation of control, sense-making and argumentation, respectively. The framework organizes the field into interrelated sets of intellectual communities, and in so doing, acts as a vehicle for conceptualizing core research issues and identifying future research directions. The paper suggests an intellectual base for penetrating the ambiguities which envelope underresearched islands of ISD.</p></div>","PeriodicalId":100011,"journal":{"name":"Accounting, Management and Information Technologies","volume":"6 1","pages":"Pages 1-64"},"PeriodicalIF":0.0,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0959-8022(96)00004-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74646206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}