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The article discusses the use of model-based code generation and its limitations. While there have been successful industrial projects that have used code generation from abstract models, the widespread adoption of code generation from explicitly defined models has not been as successful. The article identifies several challenges, including developers' ability to think in abstract form, the limitations of existing tooling, the need for flexible adaptation of the generator, and weak tool support for defining abstraction levels in a model. The article suggests that a "smart" generator could address these challenges by generating code for various functionalities, such as data transportation, user interfaces, logging, and search functionality. However, the article acknowledges that current code generators are not yet capable of such smartness and that more work is needed in this area. [Extracted from the article]

This research develops a framework for organizational value creation from agile IT applications. Based on the four themes in the business value research—business process perspective, complementarities, application level of analysis, and extent of use—three antecedents (organizational fit, process assimilation, and network adoption) are identified as pre-requisites for realizing the value of agile supply chain applications. Advanced planning and scheduling (APS) systems are used as examples, and two case studies for their implementation in the electronics and consumer goods industry are reported to support the propositions. The theories of diffusion of innovation, complementarities, network externalities, and technology structuration are applied to develop the propositions for fit, assimilation, and network effects. Information sharing and industry clockspeed are identified as the moderating factors in the proposed model. The framework has both managerial and research relevance. The research guides managers regarding ways to more fully realize the value of agile applications and forms a basis for future research on the business value of IT applications. [ABSTRACT FROM AUTHOR]

Since the late 1990s, agile or lightweight software development methodologies have experienced a meteoric rise of interest among systems developers who consider traditional systems development methodologies (such as Structured Systems Development, Information Engineering, and Rational Unified Process) too inflexible for building systems having unpredictable and changing requirements. Agile methodologies try to adapt to rapid requirement changes by having short, iterative development cycles and by encouraging frequent, open communication with customers. However, agile methodologies are still in the process of devising systematic approaches on how to be adaptive to unpredictable and changing requirements and how to incorporate customers into the systems development process. In this study, we show how an ethnographic research process called Strip Resolution can be applied as a systematic complement to projects applying agile development principles. We illustrate, in detail, how the Strip Resolution Process (SRP) enabled us, in the role of systems developers, to adapt to changing and unpredictable user requirements and to incorporate customers into the systems development process. [ABSTRACT FROM AUTHOR]

Computer Supported Collaborative Work (CSCW) can provide an efficient decision-making environment for multi-disciplinary teams faced with the challenge of evaluating agile manufacturing systems. In this paper, the development and evaluation of CSCW prototypes to aid the systematic evaluation of agile manufacturing systems are described. An industrial case study involving the evaluation of alternative design configurations of a cellular manufacturing system (CMS) for agile manufacturing was used for testing with twelve multi-disciplinary teams. The results obtained suggest that engineering design teams can obtain productivity improvements through the use of CSCW tools. The results indicate that CSCW systems can assist decision-makers in reaching consensus especially when advanced decision making tools are incorporated into the problem-solving framework. In this study, we also found that an enhanced CSCW with a neural network module for preference aggregation outperformed a basic CSCW in: (1) decision quality, (2) users' satisfaction and agreement, (3) consensus. These results also have far reaching implications for distributed product development teams that face the problem of reaching consensus on a range of alternative designs with stringent pressures to reduce development time. [ABSTRACT FROM AUTHOR]