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The global rise in obesity can be closely linked to excessive calorie consumption and misperceptions regarding food intake. Thus, the purpose of this paper is to review the existing literature to have a better understanding how heuristic cues – mental shortcuts used for decision-making – impact calorie underestimation and consequently lead to unhealthy eating habits.

A search was conducted across multiple databases with priority given to studies in developed countries that provided insights into the cognitive processes behind food choices, the application of specific heuristics, and the association with eating behaviours. Articles were also selected based on their methodological quality.

The main findings are that the dichotomous categorization of foods as healthy or unhealthy can result in underestimating the calorie content in those foods perceived as healthy. Although nutrition claims, health claims and campaigns help in the fight against obesity, there is also the risk that consumers’ reliance on heuristic-based decision-making could aggravate the problem because a misinterpretation or misrepresentation could lead to calorie underestimation and overeating.

To establish effective behavioural interventions for obesity prevalence -, it is critical for interventions and policies to understand how consumers perceive calorie content and how they interpret claims on food marketing or packaging. Recognizing and addressing these heuristic-driven biases and understanding the factors influencing food choices are crucial for encouraging healthier eating habits.

To the best of the authors’ knowledge, this paper is the only review to date that consolidates research on the topic, drawing from multiple disciplines.

It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word.

First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model.

The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment.

This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

This study aims to examine the relation between error management culture and restaurant employee promotive and prohibitive voices. Drawing on socially desirable responding theory, the authors also propose a dual-mediation mechanism underlying the impact of error management culture on employee voice: psychological empowerment, as the agentic motive, and psychological safety, as the communal motive.

The authors recruited 223 participants working in 37 restaurants in China for the two-wave surveys with a one-week interval. The authors use a multilevel modeling paradigm to test the study hypotheses.

This research examines a multilevel model suggesting that error management culture can boost employee promotive voice and prohibitive voice via the mechanisms of psychological safety and empowerment. In addition, the results suggest that psychological empowerment (vs psychological safety) has a strong mediation effect between error management culture and promotive voice, but the authors find no difference in mediating effects between error management culture and prohibitive voice.

Restaurants can encourage employee voice by developing and maintaining an error management culture. Organizations can also consider motivating employees from both agentic and communal perspectives. Moreover, managers should focus more on empowering employees in areas characterized by Confucianism or collectivism.

The current research adds to the voice literature by identifying an organizational cultural antecedent of employee voice–error management culture. Agentic and communal motives are two motivational paths of employee voice. It also extends the social desirability theory by highlighting the role of the agentic motive in the Chinese restaurant context.

The purpose of this paper is to design an online-data driven adaptive control scheme based on fuzzy rules emulated network (FREN) for a class of unknown nonlinear discrete-time systems.

By using the input-output characteristic curve of controlled plant and the set of IF-THEN rules based on human knowledge inspiration, the adaptive controller is established by an adaptive FREN. The learning algorithm is established with convergence proof of the closed-loop system and controller’s parameters are directly designed by experimental data.

The convergence of tracking error is verified by the theoretical results and the experimental systems. The experimental systems and comparison results show that the proposed controller and its design procedure based on input-output data can achieve superior performance.

The theoretical aspect and experimental systems with the light-emitting diode (LED) current control and the robotic system prove that the proposed controller can be designed by using only input-output data of the controlled plants when the tracking error can be affirmed the convergence.

The proposed controller has been theoretically developed and used through experimental systems by using only input-output data of the controlled plant. The novel design procedure has been proposed by using the input-output characteristic curve for both positive and negative control directions.

With the end of the Cultural Revolution and the rise of Deng Xiaoping, China began a new era of economic and political reform. In 1978 the open door policy was initiated. In October of 1984, Deng Xiaoping set in motion an ambitious program of financial and industrial reform aimed at eventually restructuring China's economy into a vaguely defined market system. This “second revolution” has run into difficulties because the Chinese officials lacked experience controlling a supply and demand economy and because of the opposition from conservative factions within the Chinese bureaucracy.