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Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

In human action recognition based on wearable sensors, most previous studies have focused on a single type of sensor and single classifier. This study aims to use a wearable sensor based on flexible sensors and a tri-axial accelerometer to collect action data of elderly people. It uses a statistical modeling approach based on the ensemble algorithm to classify actions and verify its validity.

Nine types of daily actions were collected by the wearable sensor device from a group of elderly volunteers, and the time-domain features of the action sequences were extracted. The dimensionality of the feature vectors was reduced by linear discriminant analysis. An ensemble learning method based on XGBoost was used to build a model of elderly action recognition. Its performance was compared with the action recognition rate of other algorithms based on the Boosting algorithm, and with the accuracy of single classifier models.

The effectiveness of the method was validated by three experiments. The results show that XGBoost is able to classify nine daily actions of the elderly and achieve an average recognition rate of 94.8 per cent, which is superior to single classifiers and to other ensemble algorithms.

The research could have important implications for health care, including the treatment and rehabilitation of the elderly, and the prevention of falls.

Instead of using a single type of sensor, this research used a wearable sensor to obtain daily action data of the elderly. The results show that, by using the appropriate method, the device can obtain detailed data of joint action at a low cost. Comparing differences in performance, it was concluded that XGBoost is the most suitable algorithm for building a model of elderly action recognition. This method, together with a wearable sensor, can provide key data and accurate feedback information to monitor the elderly in their rehabilitation activities.

Building on the three-factor theory, this study aims to unravel how the role of hotel attributes such as basic, excitement and performance factors could differ in accordance with different hotel star ratings and distinct customer segments.

This study explores the asymmetric effects of hotel attributes on customer satisfaction by extracting 412,784 consumer-generated reviews from TripAdvisor across different cities in China.

By taking into account the origins of customers and hotel star ratings, the study uncovers that guests’ expectations of hotel performance differ with respect to their origins (domestic and international guests) and the star ratings of the hotels being reviewed, thereby moderating the asymmetric impact of hotel attributes on customer satisfaction.

The study compares and contrasts the determinants of customer satisfaction for domestic and international guests in the context of Chinese hotels. Care should still be exercised when generalizing the insights gleaned from this study to other contexts.

The findings from this study translate into actionable guidelines for hotel operators to make informed decisions regarding service improvement.

The study extends previous work by offering a deeper understanding of the asymmetric impact of hotel attributes on customer satisfaction. Specifically, this study provides a deep understanding of the different hotel attributes such as basic, performance and excitement factors in explaining customer satisfaction among different hotel customer segments. Findings from this study can not only inform hotel operators on the significance of various hotel attributes in determining customer satisfaction but also guide the formulation of business strategies to retain customers by inducing delight and not frustration.

The purpose of this paper is to provide an overview of the organisational and procedural arrangements for healthcare reform in China, and describe the role of social values in the relevant decision‐making process.

An analysis of recent developments aimed at achieving universal coverage in China was undertaken in the context of describing the influence of underlying social values.

The key underlying social value was found to be social solidarity. Other values were implicit rather than explicitly stated, and were subservient to the overall aim of comprehensive coverage.

The paper shows that China is embarking on the largest‐scale health reforms in the world. There is an eagerness to share experiences with other countries in an attempt to ensure the success of the reforms. There is an increasing understanding of the need to make the values underpinning the reforms more explicit and, in particular, those concerned with efficiency and appropriateness.

This study aims to explore how marketers can use text mining to analyze actors, actions and performance effects of service encounters by building on the role theory. This enables hotel managers to use introduced methodology to measure and monitor frontline employees’ role behavior and optimize their service.

The authors’ approach links text mining and importance-performance analysis with role theory’s conceptual foundations taking into account the hotel industry’s specifics to assess the effect of frontline hotel employees’ actions on consumer satisfaction and to derive specific management implications for the hospitality sector.

This study identifies different actors involved in hotel frontline interactions revealing distinct role behaviors that characterize consumers’ perspectives of service encounters with different role types associated with front-office employees. This research also identifies role performance related to role behavior to improve service encounters.

Customer–employee interactions can be assessed by user-generated contents (UGC). Performance evaluations relate to frontline employee roles associated with distinct role scripts, whereby different hotel segments require tailored role designs. Insights of this study can be used for service optimization, market positioning as well as for improving human resource management practices in the hotel industry.

This study contributes to the service encounter literature by applying role theory in the text mining of UGC to assess frontline employees as actors and the effects of their actions on service quality delivery.

The paper aims to analyze some properties of GM(1,1,β) model based on the principle that the grey GM(1,1) model parameters are grey and adjustable.

At first, according to the principle that grey GM(1,1) model parameters are grey and adjustable, and the GM(1,1,β) model with parameter packet is put forward. Second, some properties of the GM(1,1,β) model are discussed, and the applicable region of the GM(1,1,β) model is given based on the grey differential equation of the GM(1,1,β) model. At last, the background value coefficient's calculation formula and optimization algorithm of the GM(1,1,β) model are also given. A numeric example is also computed in the last part of the paper.

The result of the study shows that the application scope of the GM(1,1,β) model is (−8,+8).

The GM(1,1,β) model provides the theoretical basis for the GM(1,1) model's optimization and can hence forecast its precision.

The paper succeeds in realizing the GM(1,1) model's application scope (−2,+2) is broadened to (−8,+8).

The paper summarizes data from 12 countries, chosen to exhibit wide variation, on the role and place of public participation in the setting of priorities. The purpose of this paper is to exhibit cross-national patterns in respect of public participation, linking those differences to institutional features of the countries concerned.

The approach is an example of case-orientated qualitative assessment of participation practices. It derives its data from the presentation of country case studies by experts on each system. The country cases are located within the historical development of democracy in each country.

Patterns of participation are widely variable. Participation that is effective through routinized institutional processes appears to be inversely related to contestatory participation that uses political mobilization to challenge the legitimacy of the priority setting process. No system has resolved the conceptual ambiguities that are implicit in the idea of public participation.

The paper draws on a unique collection of country case studies in participatory practice in prioritization, supplementing existing published sources. In showing that contestatory participation plays an important role in a sub-set of these countries it makes an important contribution to the field because it broadens the debate about public participation in priority setting beyond the use of minipublics and the observation of public representatives on decision-making bodies.

In order to create sustainable health systems, many countries are introducing ways to prioritise health services underpinned by a process of health technology assessment. While this approach requires technical judgements of clinical effectiveness and cost effectiveness, these are embedded in a wider set of social (societal) value judgements, including fairness, responsiveness to need, non-discrimination and obligations of accountability and transparency. Implementing controversial decisions faces legal, political and public challenge. To help generate acceptance for the need for health prioritisation and the resulting decisions, the purpose of this paper is to develop a novel way of encouraging key stakeholders, especially patients and the public, to become involved in the prioritisation process.

Through a multidisciplinary collaboration involving a series of international workshops, ethical and political theory (including accountability for reasonableness) have been applied to develop a practical way forward through the creation of a values framework. The authors have tested this framework in England and in New Zealand using a mixed-methods approach.

A social values framework that consists of content and process values has been developed and converted into an online decision-making audit tool.

The authors have developed an easy to use method to help stakeholders (including the public) to understand the need for prioritisation of health services and to encourage their involvement. It provides a pragmatic way of harmonising different perspectives aimed at maximising health experience.

All health care systems are facing increasing demands within finite resources. Although many countries are introducing ways to prioritise health services, the decisions often face legal, political, commercial and ethical challenge. The research will help health systems to respond to these challenges.

This study helps in increasing public involvement in complex health challenges.

No other groups have used this combination of approaches to address this issue.