Purpose Service fairness has been conceptualized as a major part of the foodservice industry due to the intangibility of foodservice, which is difficult to be evaluated by customers. Considering this challenge, this study investigates the impacts of perceived service fairness dimensions in encouraging brand citizenship behaviors (i.e. brand enthusiasm and brand endorsement) along with the mediating roles of brand trust and brand experience in the foodservice industry. Design/methodology/approach Based on an established framework of perceived service fairness, brand trust, brand experience and brand citizenship behavior, an exploratory conceptual model was formulated and empirically assessed. Survey data were collected from customers of casual dining franchise restaurants in Korea. Data analysis consisted of frequency analysis, reliability analysis, confirmatory factor analysis, correlation analysis and structural equation modeling. Findings The empirical results indicated that brand trust was significantly influenced by price, procedural, outcome and interactional fairness, while brand experience was significantly affected by price, outcome and interactional fairness. Additionally, brand trust and brand experience had positive influences on brand enthusiasm and brand endorsement, respectively. Practical implications A foodservice enterprise’s violation of customers’ fundamental need for fairness leads to negative outcomes, such as customers voicing the undesirable situation and/or leaving the restaurant. Thus, this study provides a strategy for maintaining service fairness to better develop brand relationships with customers in the restaurant industry. Originality/value There is a paucity of research on the effect of perceived service fairness on brand development in the restaurant industry. The findings provide greater insights into the impacts of perceived service fairness, brand trust and brand experience on customers’ brand citizenship behaviors.

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The goal of the current study is to investigate how the sound change is reflected in production or in perception, and what the effect of lexical frequency is on the loss of sound contrasts. Specifically, the current study examined whether the vowel length contrasts are retained in Korean speakers' productions, and whether Korean listeners can distinguish vowel length minimal pairs in their perception. Two production experiments and two perception experiments investigated this. For production tests, twelve Korean native speakers in their 20s and 40s completed a read-aloud task as well as a map-task. The results showed that, regardless of their age group, all Korean speakers produced vowel length contrasts with a small but significant differences in the read-aloud test. Interestingly, the difference between long and short vowels has disappeared in the map task, indicating that the speech mode affects producing vowel length contrasts. For perception tests, thirty-three Korean listeners completed a discrimination and a forced-choice identification test. The results showed that Korean listeners still have a perceptual sensitivity to distinguish lexical meaning of the vowel length minimal pair. We also found that the identification accuracy was affected by the word frequency, showing a higher identification accuracy in high-and mid-frequency words than low frequency words. Taken together, the current study demonstrated that the speech mode (read-aloud vs. spontaneous) affects the production of the sound undergoing a language change; and word frequency affects the sound change in speech perception.

Medical tourism organizations have increasingly recognized that loyalty makes a medical clinic a marketing success. To increase understanding of the importance of medical clinics, this study examined the roles of servicescapes, emotions, and satisfaction in the development of customer loyalty toward medical clinics and destination. Data were collected among international medical tourists visiting Korea. Results identified that dimensions of medical clinics’ servicescape (ie, medical clinic environment, medical treatment, staff, and doctor) influenced emotions and satisfaction among international medical tourists. Also, positive emotions and the 2 dimensions of satisfaction with a medical clinic and doctor mediate the influence of medical clinics’ servicescapes on 2 types of loyalty (the medical clinic and Korea for medical care). Overall, these findings indicate that the interrelationship of servicescapes, positive emotion, and satisfaction is essential in influencing international medical tourists’ loyalty to a medical clinic.

Deep learning-based object detection technology can efficiently infer results by utilizing graphics processing units (GPU). However, when using general deep learning frameworks in embedded systems and mobile devices, processing functionality is limited. This allows deep learning frameworks such as TensorFlow-Lite (TF-Lite) and TensorRT (TRT) to be optimized for different hardware. Therefore, this paper introduces a performance inference method that fuses the Jetson monitoring tool with TensorFlow and TRT source code on the Nvidia Jetson AGX Xavier platform. In addition, central processing unit (CPU) utilization, GPU utilization, object accuracy, latency, and power consumption of the deep learning framework were compared and analyzed. The model is You Look Only Once Version4 (YOLOv4), and the dataset uses Common Objects in Context (COCO) and PASCAL Visual Object Classes (VOC). We confirmed that using TensorFlow results in high latency. We also confirmed that TensorFlow-TensorRT (TF-TRT) and TRT using Tensor Cores provide the most efficiency. However, it was confirmed that TF-Lite showed the lowest performance because it utilizes a GPU limited to mobile devices. Through this paper, we think that when developing deep learning-related object detection technology on the Nvidia Jetson platform or desktop environment, services and research can be efficiently conducted through measurement results.