The BSCBAS: a Balanced Scorecard‐based appraisal system for improving the performance of software organizations

Hamouda, Alaa

doi:10.1002/smr.1566

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Fuzzy Logic was initiated in 1965 [9] by Lotfi A. Zadeh , professor for computer science at the University of California in Berkeley. Basically, Fuzzy Logic is a multivalued logic that allows intermediate values to be defined between conventional evaluations like true/false, yes/no, high/low, etc.…”

Section: Fuzzy Logicmentioning

confidence: 99%

Design of Prediction System for Key Performance Indicators in Balanced Scorecard

MohamedAbdEL-Mongy¹,

Hamouda²,

Nounou³

et al. 2013

IJCA

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The balanced scorecard (BSC) is a performance management system that supplements traditional financial measures with the criteria that measure the performance from different perspectives. For strategists, they need to predict the KPIs future values to make good decisions during the design of BSC and the determination of the suitable target for each objective and KPI. From historical data, the dependency between KPIs can be discovered through developing traditional prediction model. Hence, the KPI future values can be predicted. However, such prediction does not consider the nature of KPIs in the BSC. The historical values of KPIs depend on the previously settled targets for objectives and KPIs. This raises the challenge of finding a solution to make more accurate prediction that considers the real values of KPIs beside the previous settled targets. For achieving that, we propose a solution that uses fuzzy logic to categorize the KPI values and then predict the future KPI values. Then, we develop a third predictor model as a data fusion module to predict the KPI values depending on both previous values and category predictors. We find that the prediction accuracy of our proposed solution significantly overcomes the normal values prediction of KPIs.

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Section: Fuzzy Logicmentioning

confidence: 99%

Design of Prediction System for Key Performance Indicators in Balanced Scorecard

MohamedAbdEL-Mongy¹,

Hamouda²,

Nounou³

et al. 2013

IJCA

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A Systematic Literature Review on the Influence of Enhanced Developer Experience on Developers' Productivity: Factors, Practices, and Recommendations

Razzaq,

Buckley,

Lai

et al. 2024

ACM Comput. Surv.

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Context and Motivation – Developer eXperience (Dev-X) is a recent research area that focuses on developers perceptions, feelings, and values with respect to software development and software quality. Research suggests that factors and practices related to Dev-X can have a substantial impact on developer productivity (Dev-P). However, despite a large and diverse body of literature on factors that can impact Dev-P in general, there is no coherent and comprehensive characterization of how Dev-X-specific insights can influence developer productivity. Aims – In the presented research, we aim to provide a coherent, comprehensive characterization of factors and practices related to Dev-X, with a particular focus on those factors and practices that potentially affect Dev-P. Method – To this end, we performed a systematic literature review and identified 218 relevant papers in this area. We characterize the papers based on the related frameworks, and concepts common to Dev-X and Dev-P as presented in the existing literature. Dev-X factors such as ’work fragmentation’ and practices such as ’collaboration with owner-developer’ are identified using a grounded-in-the-literature, content-analysis method, guided by the theory. For each Dev-X factor, we identify attributes that might be used to assess/measure the current status (of an organisation or project) regarding that factor and how that factor and its effects on productivity have been evidenced in the literature (mentioned vs. considered in questionnaires vs. substantiated with a more positivist evaluation). Results – We identify 33 Dev-X-related factors and 41 Dev-X-related practices which are organized into ten themes to summarize their influence. The results suggest that the availability of required resources, relevant expertise re the allocated tasks, and fewer interruptions are among the top positively impacting factors. Conversely, factors like code complexity, heterogeneous contexts of tasks, and non-adherence to standardization harm Dev-X and Dev-P. Top industrial practices employed to mitigate the negative influence of factors include characterization-based task assignments, mental model support, and the timely evolution of technologies. Conclusions – Overall, this research suggests that organizations can influence Dev-P through improved Dev-X, incorporating suitable practices to mediate relevant factors in their context. Important in this regard are practices like fragmenting large tasks, highlighting the utility of proposed tasks/changes to the developers, and promoting (developer) ownership of artefacts. Finally, our results point to areas where further research seems appropriate, i.e., where Dev-X factors/practices have been proposed as being impactful on Dev-P but not yet fully substantiated or explored as such (factors like ‘Nature of Activity’ and practices like choosing practices/protocols appropriately).

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The BSCBAS: a Balanced Scorecard‐based appraisal system for improving the performance of software organizations

Cited by 2 publications

References 12 publications

Design of Prediction System for Key Performance Indicators in Balanced Scorecard

Design of Prediction System for Key Performance Indicators in Balanced Scorecard

A Systematic Literature Review on the Influence of Enhanced Developer Experience on Developers' Productivity: Factors, Practices, and Recommendations

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