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In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.

This research aims to analyze the customer satisfaction associated with experiences from 14 ecological hotels in Ecuador by exploring online guest reviews and classifying the most influential factors.

This study applied big data exploration, semantic network analysis, EFA and linear regression. It processed 22,629 online reviews from Google/travel, extracting 100 words with the highest frequency. In addition, CONCOR analysis built a comprehensive structural model gathering essential keywords. Furthermore, exploratory factor analysis and regression were conducted to explore the elements that best express customer satisfaction in ecological hotels.

The words such as green, sustainable, recycle, environment and ecological were not found among the main attributes extracted. Nonetheless, the keywords obtained reflect customer satisfaction, revealing that green practices do not affect comfort and the guests' experience. CONCOR analysis displayed four categories associated with satisfaction: tangibles, experience, location and empathy. Then, EFA restructured and revealed the factors: facilities feature, assurance, reliability, location and experience. Lastly, the regression disclosed location, assurance and facilities features as the most significant factors for customer satisfaction in the 14 ecological hotels. The terms related to the hotel area, staff care and hotel amenities were decisive for guests.

This study demonstrated that employee courtesy and location are the keys to enhancing customer experience and satisfaction. Hotel managers must promote green attributes and practices to increase customer awareness through constant staff training and information disclosure in common areas.

These findings provide insight and empirical evidence for hoteliers to understand how and what guest perceive to be green practices. By identifying the main features or concepts associated with satisfaction in Ecuador's green hotels, hoteliers could address new strategies to respond to expectations, effectively satisfy customers and provide a superior experience.