Customer expectations for automotive design are increasingly rising, which plays an important role in purchasing behavior. Among them, automobile interior materials are one of the factors that have a ...significant influence on the overall luxuriousness and satisfaction of automobiles. One of the main affective responses to automotive interior materials is a tactile sensation, and since it is complexly constructed, systematic modeling is required. The current research proposed and tested a structural equation model (SEM) that describes hypothesized relationships among affective variables affecting tactile satisfaction such as luxury, soft, slippery, smooth, bumpy, and thick. A total of 26 samples including natural and synthetic leather using interior material in an automobile was selected as a stimulus to recruit 53 participants. All affective variables were found to affect luxuriousness that subsequently affected tactile satisfaction (path coefficient = 0.652). In particular, perceived softness was a dominant factor affecting tactile luxuriousness in leather (path coefficient = 0.305). The findings of the present study have significant implications for both theory and practice on affective responses and levels that affect tactile satisfaction in leather using automobile interior.
•Establishing SEMs of tactile satisfaction using affective variables.•Investigation on correlations between satisfaction and tactile properties.•Perceived softness and slipperiness were key factors on the tactile satisfaction.
Across the globe, public acceptance of nuclear power is a crucial factor for governmental establishment of a nuclear energy program. Therefore, it is important to understand the determinants of ...public acceptance of nuclear power. This study examines the effects of knowledge, trust, risk, and benefit related factors on public acceptance of nuclear power across 19 countries. We consider three levels of public acceptance – strongly accept, reluctantly accept, and oppose – and classify countries into four groups according to the ratio of those three levels of public acceptance. Our results indicate that knowledge of nuclear inspection is more effective than trust in inspection authorities in creating stronger public acceptance among people in the countries with a high level of reluctant acceptance and a low level of strong acceptance, while trust in inspection authorities is more important than knowledge of nuclear inspection for the selection between opposition and reluctant acceptance in countries with a low level of reluctant acceptance and a high level of strong acceptance. Without grouping the countries, we found that trust in inspection authorities is crucial for the decision between opposition and reluctant acceptance. Additionally, the generation of electricity has the most positive effect on public acceptance of nuclear power.
•We examine public acceptance (PA) of nuclear power across 19 countries.•Three levels of PA – strongly accept, reluctantly accept, and oppose – are considered.•Knowledge is most effective in creating stronger PA.•Trust is effective in shifting PA from opposition to reluctant acceptance.•Low risk and benefit of electricity generation enhance PA the most.
Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through ...deep learning based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), Very Deep Convolutional Networks for Large-Scale Image Recognition developed by Visual Geometry Group (VGG), and convolutional neural network architecture that expanded with few changes. The HAM10000 dataset is used and the proposed method has outperformed other methods with more than 85% accuracy. Its robustness in recognizing the affected region much faster with almost 2× lesser computations than the conventional MobileNet model results in minimal computational efforts. Furthermore, a mobile application is designed for instant and proper action. It helps the patient and dermatologists identify the type of disease from the affected region's image at the initial stage of the skin disease. These findings suggest that the proposed system can help general practitioners efficiently and effectively diagnose skin conditions, thereby reducing further complications and morbidity.
The Fukushima nuclear disaster has significantly changed public attitudes toward nuclear energy. It is important to understand how this change has occurred in different countries before the global ...community revises existing nuclear policies. This study examines the effect of the Fukushima disaster on public acceptance of nuclear energy in 42 countries. We find that the operational experience of nuclear power generation which has significantly affected positive public opinion about nuclear energy became considerably negative after the disaster, suggesting fundamental changes in public acceptance regardless of the level of acceptance before the disaster. In addition, contrary to our expectation, the proportion of nuclear power generation is positively and significantly related to public acceptance of nuclear energy after the Fukushima accident and government pressure on media content led to a greater decrease in the level of public acceptance after the accident. Nuclear energy policymakers should consider the varied factors affecting public acceptance of nuclear energy in each country depending on its historical, environmental, and geographical circumstances before they revise nuclear policy in response to the Fukushima accident.
•Fukushima accident has negatively changed public attitudes toward nuclear energy.•Effect of operational experience became considerably negative after the accident.•Effect of proportion of nuclear power generation is positive after the accident.•Effect of government pressure on media content became negative after the accident.•Country specific policy responses on nuclear public acceptance are required.
The present study aims to compare and analyze the performance of two tokenizers, Mecab-Ko and SentencePiece, in the context of natural language processing for sentiment analysis. The study adopts a ...comparative approach, employing five algorithms - Naive Bayes (NB), k-Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Networks (ANN), and Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN) - to evaluate the performance of each tokenizer. The performance was assessed based on four widely used metrics in the field, accuracy, precision, recall, and F1-score. The results indicated that SentencePiece performed better than Mecab-Ko. To ensure the validity of the results, paired t-tests were conducted on the evaluation outcomes. The study concludes that SentencePiece demonstrated superior classification performance, especially in the context of ANN and LSTM-RNN, when used to interpret customer sentiment based on Korean online reviews. Furthermore, SentencePiece can assign specific meanings to short words or jargon commonly used in product evaluations but not defined beforehand.
•We analyze industry convergence in entire U.S. industries, its trends and patterns.•We conduct a text mining analysis for a large volume of unstructured data.•We find that overall industry ...convergence is increasing over time.•The phenomenon has been greater within industry than between industries.•However, the dynamic patterns of industry convergence are mixed by industry pairs.
Because of the accelerated life cycle in technology and correspondingly rapid technological saturation in markets, firms are not only accelerating the rate of technological innovation but also expanding the scope of their products or services by combining product or service features of other markets, which eventually leads to industry convergence. However, despite the significant impact of industry convergence on the economy, our understanding of the phenomenon is still limited because previous studies explored only a few cases and come largely from the technological perspective. Therefore, it is still questionable whether industry convergence is a general phenomenon that is prevalent across entire industries. In this paper, we analyze the phenomenon in entire U.S. industries, focusing on its trends and patterns. To do so, we conduct a co-occurrence-based analysis of text mining for a large volume of unstructured data – 2 million newspaper articles from 1989 to 2012 – and suggest using an industry convergence (IC) index based on normalized pointwise mutual information (PMI). We find that overall industry convergence is increasing over time. Moreover, the rate of the increase has been greater within industry than between industries at a given industry level. However, when we cluster the dynamic patterns of industry convergence among industry pairs, the patterns are mixed, and, while some industry groups are converging over time, others are stationary. These findings suggest that significant transformation is under way in the economy, but this phenomenon is not yet prevalent across entire industries. In addition, this study provides a method for anticipating the future direction of industry convergence.
The importance of the convergent approach to technology development has increased recently. Therefore, understanding the characteristics of technology convergence, which refers to the combination of ...two or more technological elements in order to create a new system with new functions, is an important issue not only for researchers in technology development, but also for company directors for their successful management of product competitiveness. Therefore, in order to investigate the patterns and the mechanism of technological convergence, we examine the printed electronics technology which has typical characteristics of technology convergence. Based on the printed electronics-related patents registered between 1976 and 2012, we perform network analysis of the technology components in order to identify key technologies which played a central role among the groups of convergence technologies and to examine their dynamic role corresponding to the development of technology convergence. The results show that control technologies which control the role of other technologies over the technology convergence process play significant role. The centrality value is highest in the case of control technology, and devices related technologies have the largest number of patents quantitatively, thereby confirming the results. In addition, the trajectory analysis of the centrality value reveals a co-evolution pattern in technology convergence.
It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the ...process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.
► The interrelationship of triple helix contributes to the regional entrepreneurship. ► University R&D plays a role as an ‘entrepreneurial mediator’. ► University and government R&D generate a ...positive synergistic effect on firm birth. ► The synergy of university and industrial R&D enhances the sustainability of firms. ► Industrial R&D and habitat factors play important roles in regional firm birth.
The ‘triple helix’ of the university–industry–government relationship and habitat are accepted as important determinants of innovation and entrepreneurship. However, empirical explorations of the effects of these variables and their interrelationships on regional entrepreneurial activities are highly limited. To fill this gap, we investigate the effect of the triple helix system and habitat on birth and death rates of U.S. firms at the state level. As expected, we find that industrial R&D expenditure plays an important role in promoting regional firm birth. However, university and government R&D also generate a synergistic effect that indirectly influences regional firm birth rates. In addition, we find that the synergy between university and industrial R&D enhances the sustainability of firms, while the interactions between (1) university and government R&D and (2) government and industrial R&D are associated with an increase in firm death. Other factors linked to more favorable conditions for firm formation include higher educational attainment in a region, lower tax rate, and habitat factors affecting quality of life, such as lower housing prices and higher rates of health insurance coverage. In regions with high entrepreneurial activity, we find positive synergistic effects of the interactions between (1) university and government R&D and (2) university and industrial R&D on firm birth rate, suggesting that university R&D plays an important role as an ‘entrepreneurial mediator’ among the three spheres in the triple helix system. In low entrepreneurial regions, the only triple helix system factors significantly influencing firm birth rate were tax rate. This finding suggests that the independent and interdependent components of the triple helix system and habitat are less powerful in low entrepreneurial regions.
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