A framework for big data integration within the strategic management process based on a balanced scorecard methodology

Alnoukari, Mouhib

doi:10.37380/jisib.v1i1.693

Cited by 7 publications

(8 citation statements)

References 35 publications

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“…e balanced scorecard includes the goal balance of learning and growth, internal operation, customers, and finance and is mostly used in the evaluation of performance management system, including internal and external multilevel and multidimensional indicators. According to the characteristics and operation mode of public stadiums and gymnasiums, and according to the aspects involved in their performance management, the research subdivides the contents of the four dimensions into internal management; internal personnel and service audience; promotion and development; and social and economic benefits [20]. When constructing the hierarchical matrix, it is necessary to judge the consistency of the matrix with the help of scale consistency.…”

Section: Construction Of Public Stadium Performance Management Evalua...mentioning

confidence: 99%

“…e grey evaluation coefficient indicates the severity of the performance management risk faced by each index. In Figure 6(b), the risk evaluation coefficient values of public stadiums and gymnasiums in management system (B1) and human resource management (B2) are more than 15 points, and the grey evaluation coefficients of performance appraisal system (C5-19.162), management flexibility (C7-18.282), operating income (C16-18.857), and social support conditions (C19-17.242) are in the [17][18][19][20] score range, It shows that the risk of its performance management is large, and timely management countermeasures should be taken. e statistical results of the membership degree and final score of the primary evaluation index into a graph are drawn (Figure 8).…”

Section: Application Effect Analysis Of Performance Managementmentioning

confidence: 99%

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Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

et al. 2022

Mathematical Problems in Engineering

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The importance of public stadiums has become increasingly prominent, but the efficiency of its performance management operation mechanism is low, which affects the overall operation efficiency of the whole stadium. However, due to the diversity and incompleteness of its data types, the traditional analytic hierarchy process is difficult to construct its index system. This article introduces the grey fuzzy analytic hierarchy process. Based on the analysis of its performance management problems, this article constructs the index system and makes an application case analysis. The results show that the GFAHP method (group fuzzy analytic hierarchy process) can ensure the integrity of information data. In data classification, the highest accuracy of sample classification is 40.13%, and the relative error rate is basically less than 6%. The performance effect is much higher than other classification algorithms. At the same time, the total score of the evaluation index system constructed by GFAHP is more than 3, the overall operation is good, and the risk evaluation effect of each influencing index factor is also good. Using the grey analytic hierarchy process to evaluate the operation and performance management of public stadiums and gymnasiums will help managers do a good job in risk control and quality dynamic adjustment, so as to improve the operation efficiency and benefit of stadiums and gymnasiums.

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Section: Construction Of Public Stadium Performance Management Evalua...mentioning

confidence: 99%

Section: Application Effect Analysis Of Performance Managementmentioning

confidence: 99%

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

et al. 2022

Mathematical Problems in Engineering

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“…In another study, the researcher shows that adopting BSC in the integration of big data and strategic management, not only will help to overcome complexities in the organizations, but also will help to improve the effectiveness of the strategic plan performance, and new insight will be available for managers decisions. 7 …”

Section: Introductionmentioning

confidence: 99%

How to improve information technology strategic planning effectiveness using balanced scorecard, risk and maturity analysis, case study health information technology? A qualitative study

Moinzad

Akbarzadeh

2022

Health Science Reports

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Background and Aims Although many health strategic plans have been developed by scholars and organizations, they still suffer from a limited view. Since most health‐related strategies in the future will depend on information technology (IT), as the main driver of today's industry, technology, and society, IT merits attention in health strategic plans. While the majority of the health strategic plan developed based on the interviews and questioner and these plans didn't consider the role of IT in their actions, this research will develop a framework to integrate risk and maturity analysis with the strategic planning process in health information technology strategic plan. Methods The present research introduces an integrated framework based on a balanced scorecard (BSC) and control objectives for information and related technologies (COBIT). Also, The American Productivity & Quality Centre framework and COBIT were employed in this model to define the processes and activities of health IT (HIT) organizations. The organization's maturity and risk are analyzed in terms of information and management criteria using BSC, COBIT, and the analytical hierarchy process. Results Later this model was implemented in a Remote Health care System to improve the strategic management process for this technology. Using this framework, 17 business goals have been developed and presented for the case. Also, the total related risk was 48% and the maturity level was at 1/18. The results are presented as decision‐making parameters and strategies for successful IT implementation. Conclusion The presented framework provides deeper insight for the decision‐maker through integrating risk and maturity analysis in the HIT strategic planning process. The results are presented as decision‐making parameters and strategies for successful IT implementation. These strategies help investors decide about resource allocation based on the risk‐taking capability, certainty, and uncertainty results of the plan.

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“…Big data technology is a field that has developed rapidly in recent years, which also promotes the development of intelligent life and production [7,8]. e core advantage of big data technology is the processing of cumbersome data.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Influence Analysis of the Development Scale of Market Economy on the Level of Music Innovation

Zhang

Gong

2022

Discrete Dynamics in Nature and Society

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Music art is a form of conveying cultural information and humanistic emotions. From ancient times to the present, the form of music has undergone great changes. The change of music form is closely related to the change in dynasties, the development of the market economy, and the change in humanistic spirit. Today, the development of music has reached a relatively prosperous stage, which is closely related to the rapid development of the market economy. At the heart of the quantitative analysis is the study of associations between data. However, it will be a difficult task to analyze the relationship between the development scale of the market economy and the form of music innovation only by artificial means. This research mainly uses a convolutional neural network and long and short-term memory neural network technology to quantitatively analyze the relationship between the development scale of the market economy and the form of music innovation, which is mainly a quantitative analysis of classical music, pop music, and rap music. The research results show that convolutional neural networks and long short-term memory neural networks have sufficient capabilities to quantitatively analyze the relationship between the market development scale and the form of music innovation. Neural networks with LSTM layers have lower errors in predicting market economic correlates than neural network methods without LSTM layers. The error is reduced by 0.27%. For the prediction of innovative forms of music, the largest prediction error is only 2.93%, which is closely related to the variability of popular music. The linear correlation indices for the predictions of the three forms of musical innovation also all exceed 0.955.

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A framework for big data integration within the strategic management process based on a balanced scorecard methodology

Cited by 7 publications

References 35 publications

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

How to improve information technology strategic planning effectiveness using balanced scorecard, risk and maturity analysis, case study health information technology? A qualitative study

Quantitative Influence Analysis of the Development Scale of Market Economy on the Level of Music Innovation

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