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Based on a resource-based view, we explore the relationship between ambidextrous innovation human capital and the efficiency of technological innovation and its stage efficiency in big data enterprises. We divide their technological innovation into two stages: technological development and the commercialization of technological achievements. For a more reasonable efficiency measurement, we construct an efficiency evaluation index system based on the entropy value method (EVM) and the analytical hierarchy process (AHP), and we measure and evaluate their technological innovation efficiency from both static and dynamic perspectives. We conduct an empirical analysis with a sample of Chinese big data listed companies from 2014–2017. After regression analysis and its robustness test, we find that ambidextrous innovation human capital has a significant impact on the technological innovation efficiency of big data enterprises, that incremental innovation human capital and radical innovation human capital have opposite impact relationships in the technological development stage and that radical innovation human capital may have a more significant economic significance on the efficiency of commercializing technological achievements of big data enterprises. In the course of our analysis, we also find some other relevant findings. Finally, we formulate some relevant management suggestions. Full article

Successful project management depends on ensuring the project’s objectives. Within these objectives, technical success is associated with achieving the expectations of the project baseline. The baseline of the project is made up of the definition of the scope (WBS), time (schedule) and costs (S curve) of the project. Directly, the project is expected to be technically successful if it manages to deliver its full scope on schedule and without associated cost overruns. Baseline performance management is how project managers track and control the progress of deliverables, timelines and associated costs. In a traditional approach, for waterfall-type projects that use the critical path paradigm, the baseline performance management tool par excellence is earned value management (EVM). Earned value management, in practice, works well when project costs are monitored and controlled; however, applying this approach to measure the status of the schedule presents serious inconsistencies. Over the last several decades, different variations of the original earned value have been developed to overcome some of these inconsistencies when used to measure project schedule status. Within these variations, we have the critical path earned value; the work in progress earned value; the critical path earned value and the work in progress; the earned schedule; and the critical path earned schedule. Each of these proposals tries to address some weakness of the original earned value management applied to time monitoring and control, for example, considering critical tasks as a focus on monitoring the progress of the schedule, solving the problem of task recognition late finishers, reporting schedule variances in time units and measuring adherence to the project’s schedule (P factor). Due to the exposed situation, it is necessary to determine which alternative of the versions of the original earned value is the most appropriate for the management of the project schedule, considering that there are several evaluation criteria that must be considered. In the present research, a systematic review and comparison of EVM and its variations for measuring project baseline schedule performance are performed to determine the most suitable methods for monitoring and controlling the project baseline schedule. For this purpose, the analytic hierarchy process (AHP) is used, and five comparison criteria are considered: schedule variation focused on critical tasks, recognition and measurement of the delay of tasks that finish late, schedule variation in time units, measurement of schedule adherence (P factor) and software support and development. The result of the AHP performed for comparing the methods shows that the best method for monitoring and controlling the project baseline schedule is the critical path earned schedule because it behaves adequately in comparison with the other methods for the evaluated comparison categories. Full article

High-quality economic development is an important approach for achieving sustainable economic development, and it is an essential condition for coordinated development between economic systems and ecosystems. This paper starts from five key points, namely, “innovation, coordination, opening-up, sharing and greenness”, to construct an evaluation system for the index of high-quality economic development, using the AHP and EVM methods to measure the level of high-quality economic development of 30 regions in China from 2004 to 2019. It uses the kernel density estimation model (hereinafter referred to briefly as KDE) and clustering method to analyze time evolution trends and spatial variation characteristics. Moreover, the LSE model is adopted to explore and analyze the factors influencing high-quality economic development in different regions. Additionally, the driving forces of China’s high-quality economic development are analyzed by means of path analysis combined with the average value of each index. The results show the following: (1) The high-quality economic development of 30 regions in China (excluding Hong Kong, Macao, Taiwan and Tibet) is spatially clustered, with obviously different development levels, characterized by the eastern region being better developed than the central and western regions. (2) With the passage of time, the polarization of China’s 30 regions has been alleviated, but they are still facing challenging development situations; (3) The factors affecting the high-quality economic development of these 30 regions in China can be divided into four types: three-factors, four-factors-I, four-factors-II and five-factors. Contributing regional factors show different distribution characteristics. The above conclusion provides a reference and scientific basis for the government to formulate policies of high-quality economic development and to solve problems facing coordinated sustainable development among regional societies, their economies and the environment. Full article