343,322 research outputs found

    The Role of User Guidance in the Industrial Adoption of MDE Approach

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    Model-Driven Engineering (MDE) has emerged as an actively researched and established approach for next generation control application development. Technology transfer to the industry is a topical research problem. Since most professional factory process control engineers do not have computer science backgrounds, there is an urgent need for studies of the role of user guidance in the professional learning, and thus, of industrial adoption of MDE approaches. In this study professionals were invited to a hands-on assessment of the AUKOTON MDE approach for factory process control engineering. Qualitative empirical material was collected and analyzed to identify the role of user guidance in the context of other factors impacting industrial adoption. Challenges in adoption that could be solved by user guidance were identified with the theory of organizational knowledge creation (SECI) model

    Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

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    The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

    Linking business analytics to decision making effectiveness: a path model analysis

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    While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to manager's knowledge and understanding by demonstrating how business analytics should be implemented to improve DM

    Towards guidelines for building a business case and gathering evidence of software reference architectures in industry

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    Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges. Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain. Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices. Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version

    Relevance, benefits, and problems of software modelling and model driven techniques—A survey in the Italian industry

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    Context Claimed benefits of software modelling and model driven techniques are improvements in productivity, portability, maintainability and interoperability. However, little effort has been devoted at collecting evidence to evaluate their actual relevance, benefits and usage complications. Goal The main goals of this paper are: (1) assess the diffusion and relevance of software modelling and MD techniques in the Italian industry, (2) understand the expected and achieved benefits, and (3) identify which problems limit/prevent their diffusion. Method We conducted an exploratory personal opinion survey with a sample of 155 Italian software professionals by means of a Web-based questionnaire on-line from February to April 2011. Results Software modelling and MD techniques are very relevant in the Italian industry. The adoption of simple modelling brings common benefits (better design support, documentation improvement, better maintenance, and higher software quality), while MD techniques make it easier to achieve: improved standardization, higher productivity, and platform independence. We identified problems, some hindering adoption (too much effort required and limited usefulness) others preventing it (lack of competencies and supporting tools). Conclusions The relevance represents an important objective motivation for researchers in this area. The relationship between techniques and attainable benefits represents an instrument for practitioners planning the adoption of such techniques. In addition the findings may provide hints for companies and universitie

    Enablers and Impediments for Collaborative Research in Software Testing: An Empirical Exploration

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    When it comes to industrial organizations, current collaboration efforts in software engineering research are very often kept in-house, depriving these organizations off the skills necessary to build independent collaborative research. The current trend, towards empirical software engineering research, requires certain standards to be established which would guide these collaborative efforts in creating a strong partnership that promotes independent, evidence-based, software engineering research. This paper examines key enabling factors for an efficient and effective industry-academia collaboration in the software testing domain. A major finding of the research was that while technology is a strong enabler to better collaboration, it must be complemented with industrial openness to disclose research results and the use of a dedicated tooling platform. We use as an example an automated test generation approach that has been developed in the last two years collaboratively with Bombardier Transportation AB in Sweden

    Technology-driven online marketing performance measurement: lessons from affiliate marketing

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    Although the measurement of offline and online marketing is extensively researched, the literature on online performance measurement still has a number of limitations such as slow theory advancement and predominance of technology- and practitioner-driven measurement approaches. By focusing on the widely employed but under-researched affiliate marketing channel, this study addresses these limitations and evaluates the effectiveness of practitioner-led online performance assessment. The paper offers a comprehensive review of extant performance measurement research across traditional, online and affiliate marketing and, employing grounded theory, presents a qualitative in-depth analysis of 72 online forum discussions and 37 semi-structured interviews with the major affiliate marketing stakeholders. As a result, the research identifies a growing need for change in the technology-pushed measurement approaches in affiliate marketing, and proposes actionable improvement recommendations for affiliate and online marketing managers

    On Evidence-based Risk Management in Requirements Engineering

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    Background: The sensitivity of Requirements Engineering (RE) to the context makes it difficult to efficiently control problems therein, thus, hampering an effective risk management devoted to allow for early corrective or even preventive measures. Problem: There is still little empirical knowledge about context-specific RE phenomena which would be necessary for an effective context- sensitive risk management in RE. Goal: We propose and validate an evidence-based approach to assess risks in RE using cross-company data about problems, causes and effects. Research Method: We use survey data from 228 companies and build a probabilistic network that supports the forecast of context-specific RE phenomena. We implement this approach using spreadsheets to support a light-weight risk assessment. Results: Our results from an initial validation in 6 companies strengthen our confidence that the approach increases the awareness for individual risk factors in RE, and the feedback further allows for disseminating our approach into practice.Comment: 20 pages, submitted to 10th Software Quality Days conference, 201
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