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The police often respond to persons who are not in direct violation of the law, but are rather undergoing behavioral crises due to mental illness or substance abuse disorders. The purpose of this study is to examine how police behavior influences civilian bystanders' emotional responses and perceptions of procedural justice (PPJ) when officers interact with these populations, which traditionally have been stigmatized in American culture.

Using a factorial vignette approach, the authors investigate whether perceived public stigma moderates the relationship between police behaviors (i.e. CIT tactics, use of force) and PPJ. The authors also investigate whether emotional reactions mediate the relationship between police behaviors and PPJ.

Regardless of suspect population (mental illness, substance use), use of force decreased participants' PPJ, and use of CIT tactics increased PPJ. These effects were consistently mediated by anger, but not by fear. Interactive effects of police behavior and perceived public stigma on PPJ were mixed.

Fear and anger may operate differently as antecedents to PPJ. Officers should note using force on persons in behavioral crisis, even if legally justifiable, seems to decrease PPJ. They should weigh this cost pragmatically, alongside other circumstances, when making discretionary decisions about physically engaging with a person in crisis.

This present study aims to investigate the mediating effect of halal label perceived importance (HPI) on buying intention (BI) of small and medium enterprises (SME) food products in a Muslim-majority environment by involving attitude (ATT), subjective norms (SN) and perceived behavioral control (PBC) as the antecedents.

A self-administered survey was conducted with 437 Muslim respondents who shop at an SME shopping center. Subsequently, the structural equation modeling technique was used to test the hypotheses.

The findings showed that ATT and PBC significantly influence the BI of halal-labeled food products. On the other hand, HPI partially mediates the relationship between ATT, PBC and BI.

The results provided insights that SME actors will be benefited from selling halal-labeled products as the label amplifies Muslim consumers’ BI. Moreover, the government must intensify the halal campaign to strengthen public awareness and social pressure on purchasing halal-labeled brands.

As SMEs are the major contributor to the national economy, this sector’s business growth will benefit the Indonesian people. Moreover, as the most Muslim-populated country, halal product development will contribute significantly to the whole national economy.

This study provides empirical evidence on the halal labeling mediation role in the relationship between consumer motivation and halal buying intention in a major Muslim setting.

The problem of environmental pollution is becoming increasingly severe, and international consensus confirms the need for eco-friendly consumption. Worldwide, the eco-friendly food market is booming, so understanding consumers’ motivations to purchase these foods is crucial. This paper aimed to construct a model explaining consumers’ intentions to purchase eco-friendly food by combining stimuli-organism-response (SOR) and signalling theories and exploring the mechanisms by which macro- and micro-signals impact perceptions of value and consumers’ subsequent willingness to purchase eco-friendly food.

An online questionnaire was distributed through the Qualtrics platform, and the completed questionnaires were collected in March and April 2023. The study used partial least squares structural equation modelling (PLS-SEM) to analyse the 331 valid responses received.

The results indicated that trustworthy eco-labels for high-quality and health-promoting products, as conveyed in macro signals, significantly enhanced consumers’ perceptions of functional value. The peer effect and a moderate level of food anthropomorphism conveyed in micro-signals substantially improved their perceptions of social value, whilst the perceived value of products significantly and positively influenced their purchase intentions.

This study explains consumers’ motivations to purchase eco-friendly products. This provides an explanation for the effect of macro- and micro-signals on value perceptions. By integrating the different dimensions of these signals to create a unified research perspective, the paper provides an integrated model, thereby filling a research gap concerning the influence of two-dimensional signals on purchase intention. By supporting eco-friendly food use, the paper contributes to environmental protection and sustainable development.

The primary objective of this study is to explore the nuanced interplay of conspicuous consumption, ethical label purchasing and the ensuing dynamics of civic virtue and cynicism within the luxury foodservice context.

Grounded in a theoretical understanding of solidarity within the context of product consumption, this research employs a two-pronged approach involving secondary data analysis and scenario-based experimental studies. The initial phase involves analyzing firm-level data from the Euromonitor database in 2019 and 2021. The main study employs a between-subjects experimental design with a cohort of 316 participants sourced from an online panel.

The results reveal a consistent pattern in the consumption of luxury foodservice and underscore a distinct upward trajectory in consumer demand for ethically labeled food. Notably, these findings underscore the moderating role of ethical label purchasing in the relationship between conspicuous consumption and consumers civic virtue. Additionally, ethical label purchasing moderates the impact of conspicuous consumption on consumer cynicism, both directly and indirectly through emotional solidarity related to both communal and equitable principles.

This study holds significance for both luxury food service researchers and market design practitioners. It provides valuable insights into how ethical labeling interacts with consumers conspicuous consumption, all facilitated by emotional solidarity.

The purpose of this study is to review the role of knowledge-sharing and its association with the Theory of Planned Behavior (TPB). TPB is the most used theory in understanding knowledge-sharing behavior in many contexts.

Based on the bibliometric approach, this study extracted and analyzed 229 journal articles on the Web of Science. In addition, two analyses (bibliographic coupling and co-word) were performed to provide science mapping in presenting the knowledge structure on the present and future research direction on knowledge-sharing and TPB.

The findings of this study suggest that two stand-out clusters are determinants and antecedents of knowledge-sharing behavior based on TPB and the role of the virtual platform and social media in facilitating knowledge-sharing among users.

This study will benefit researchers and scholars in studying individual behavioral traits underpinning TPB in achieving organizational excellence.

This study extends the findings of the previous review because of their limitations on methods. This study confirms the determinants of knowledge-sharing intention and behavior. However, this study suggests integrating TPB with other theories to provide more insights into knowledge-sharing behavior and use online and technology-based platforms to facilitate knowledge-sharing behavior.

Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.

This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.

Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.

MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.

On the one hand, this paper is to further understand the residents' differentiated power consumption behaviors and tap the residential family characteristics labels from the perspective of electricity stability. On the other hand, this paper is to address the problem of lack of causal relationship in the existing research on the association analysis of residential electricity consumption behavior and basic information data.

First, the density-based spatial clustering of applications with noise method is used to extract the typical daily load curve of residents. Second, the degree of electricity consumption stability is described from three perspectives: daily minimum load rate, daily load rate and daily load fluctuation rate, and is evaluated comprehensively using the entropy weight method. Finally, residential customer labels are constructed from sociological characteristics, residential characteristics and energy use attitudes, and the enhanced FP-growth algorithm is employed to investigate any potential links between each factor and the stability of electricity consumption.

Compared with the original FP-growth algorithm, the improved algorithm can realize the excavation of rules containing specific attribute labels, which improves the excavation efficiency. In terms of factors influencing electricity stability, characteristics such as a large number of family members, being well employed, having children in the household and newer dwelling labels may all lead to poorer electricity stability, but residents' attitudes toward energy use and dwelling type are not significantly associated with electricity stability.

This paper aims to uncover household socioeconomic traits that influence the stability of home electricity use and to shed light on the intricate connections between them. Firstly, in this article, from the perspective of electricity stability, the characteristics of the power consumption of residents' users are refined. And the authors use the entropy weight method to comprehensively evaluate the stability of electricity usage. Secondly, the labels of residential users' household characteristics are screened and organized. Finally, the improved FP-growth algorithm is used to mine the residential household characteristic labels that are strongly associated with electricity consumption stability.

1. The stability of electricity consumption is important to the stable operation of the grid.

2. An improved FP-growth algorithm is employed to explore the influencing factors.

3. The improved algorithm enables the mining of rules containing specific attribute labels.

4. Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

The stability of electricity consumption is important to the stable operation of the grid.

An improved FP-growth algorithm is employed to explore the influencing factors.

The improved algorithm enables the mining of rules containing specific attribute labels.

Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

This research paper explores customer experience (CX) among low-literate customers in organized retail environments. It integrates theories from customer literacy, CX and patronage literature to understand CX comprehensively.

The study gathered data from 470 respondents using mall intercept and snowball sampling. Data analysis employed partial least squares (PLS) modeling.

The results indicate that all the dimensions do not have the same effect on CX. Answering calls for future research, the results establish CX's nomological validity by showing its positive influence on retail reputation, retail quality and satisfaction. However, it does not directly affect patronage but has an indirect influence through retail quality and satisfaction. Also, the authors conclude that retail quality and satisfaction are consequences of CX and not previously conceptualized proxies for it.

Conducting primary research with low-literate customers (LLCs) has its own set of limitations that give rise to further research directions. While acknowledging limitations, the study suggests avenues for future research by surveying LLCs with an objective questionnaire, contributing to limited empirical research in this segment.

The findings highlight the multidimensional nature of CX. In summary, this research paper provides insights into CX dimensions and outcomes for LLCs in organized retail. It contributes to marketing literature, assisting retailers in improving CX and driving patronage across customer segments.

The paper contributes to marketing literature by studying LLCs, testing a comprehensive CX model, confirming antecedents in retail patronage and exploring reciprocal relationships in retailing.

The present study surveyed consumers in Taiwan and Japan to analyse the influence of marketing mix on purchase intention and the willingness to pay for Taiwanese pork and to establish a marketing-oriented model of consumer behaviour.

A total of 1,134 valid Internet surveys were collected, which included 526 Taiwanese respondents and 608 Japanese respondents.

An analysis of the results indicated that product quality constitutes the foundation of marketing strategies and significantly affects purchase intention and willingness to pay through physical evidence, promotional activities, place and price. Both physical evidence and product strongly affect the purchase intention of Taiwanese consumers, followed by price, whereas price and physical evidence significantly affect willingness to pay. For Japanese consumers, price, product and promotion strongly affect purchase intention, but place and physical evidence exert negative effects; by contrast, price and promotion significantly affect willingness to pay.

The results determined that a modified marketing mix should be applied for agricultural products. In the domestic market, marketing should promote the modernisation and scale of pork farms and possibly the brand value or market rarity. In international markets, particularly those of neighbouring countries, marketing should focus on the promotion of Taiwanese pork as a high-quality, reasonably-priced product with transparent product information and convenient purchase channels. This study contributes to the application of marketing theory to the market for staple foods by incorporating considerations for domestic and international markets.