Live streaming commerce has rapidly emerged as a key platform in e-commerce, yet the socio-technical mechanisms underlying consumer-platform interactions remain underexplored. This study addresses this gap by examining both task-oriented purchasing behaviors and pleasure-driven engagement through the lens of social exchange theory. A web-based survey was conducted with 300 respondents in South Korea, all of whom had prior experience with live streaming commerce. The data were analyzed using PLS-SEM to evaluate the proposed model. The results reveal that procedural and interactional justice positively affect trust, while co-experience enhances perceived playfulness. Both trust and playfulness, in turn, significantly impact purchase and repeated viewing intentions. These findings provide valuable insights into the dynamics of live commerce, offering a comprehensive model for understanding consumer behavior in the context of live commerce.

Smart speakers become a versatile and convenient device to provide digital contents in our daily life. However, given the challenges of privacy management in smart speakers, it is required to examine how users cope with privacy threats of the devices. In this study, we examine how the privacy-enhancing attributes of smart speakers influence users’ preferences when choosing devices. The preference structure was generated from a conjoint approach, dealing with four privacy-enhancing features (parasite function, data storage method, security notice, and speaker recognition function) and two typical factors affecting consumer decision making (brand and price). Data collected from a survey of 516 consumers identified that, aside from the attribute of price, parasite function was ranked as the most preferred attribute. We also compared the findings across three user clusters. By examining concrete and explicit attributes regarding privacy-enhancing features, the present study provides novel insights into users’ understanding of privacy.

Smart speakers, which provide continuous real-time information and convenient services, increasingly permeate into users’ homes. On the other hand, the environments of the smart speaker also cause privacy issues for the users by always listening to users’ voices in their private homes. The privacy-prone environments of the smart speakers lead to the users’ coping behaviors against privacy threats not only by increasing the users’ privacy concerns but also by creating negative emotions. However, prior studies have predominantly focussed on cognitive frameworks and overlooked the impact of effect on users’ coping behaviors in the context of privacy threats. Drawing on the stimuli-organisms-responses(S-O-R) framework, this study examines the mediating role of three representative negative emotions (anger, anxiety, disappointment) between users’ privacy concerns and behaviors. The results indicate that the relationships between privacy concerns, negative emotions, and various privacy behaviors in the context of the smart speaker, emphasizing the mediating role of negative emotions. Findings of the study can enhance our knowledge of privacy research by adding the influence of effect in the cognitive-dominant framework.

Kimchi is one of the most important dishes in Korean cuisine. One of the main ingredients of Kimchi is Chinese cabbage. The production of Chinese cabbage has a great influence on the consumer price of South Korea. Therefore, it is very important to accurately grasp the harvest of Chinese cabbage. Unmanned aerial vehicles (UAVs) and sensors have the advantage of accurately and quickly acquiring information on agricultural sites where crops are grown. Therefore, various methods have been examined to find a way to precisely apply UAV and field sensor to agricultural field. First, we tried to find a way to improve the accuracy of the UAV by applying the GPS-RTK method and to minimize the error between the images taken in time series. Secondly, a comparative method to analyze errors and differences between UAV, portable field survey equipment and stationary observation equipment was adopted and examined. In this study, the vegetation index was examined by adopting the most commonly used Normalized Difference Vegetation Index (NDVI). The purpose of this study was to investigate the correlation between the UAV system and the portable spectro-radiometer (ASD) which can periodically observe the cabbage cultivation testbed.

Though, solar radiation data is not available in maximum weather stations, it is an important parameters for biogeochemical models hence there is an increasing demands of available energy data. The seasonal model described here can be used for a rough estimation of maximum available solar energy in nearby areas of the measuring station in clear sky condition with minimum calculation and efforts. Other than that it is found that sunshine duration is the best for estimating solar radiation. Prevalent cloud condition over Korean peninsula makes sunshine fraction most important factor determining available solar energy than other. The variation of residuals in the seasonal model (Fig. 5) also indicates the strong dependency of radiation data on sunshine fraction. Still, many weather stations does not have sunshine duration data whereas temperature is one of the mostly and easily available parameters that can be used for estimating solar radiation. Cloudiness data is also measured in many weather stations and found to be a good estimator for solar radiation, better than temperature. Therefore, low validation error and high regression coefficient indicate that all these parameters can be used for successful solar radiation modelling.

The aim of this study was to perform a precise spatial distribution of solar radiation estimation using UAV as a way to use solar energy efficiently. Fixed wing UAV was used to acquire image for a precisely topographical map. The whole work can be divided into two step. In first step, images acquired by UAV are used to build a digital surface model based on point cloud method. In the next step, calculated slope and angle data is used to model clear sky solar radiation. The solar radiation data for 2015 was taken from Korean Meteorological Administration (KMA). The highest daily solar radiation appears in May of 22.7 MJ/m2, and the lowest daily solar radiation in May appears 15.7MJ/m2. And the range of daily solar radiation appears in December is 2.9 MJ/m2to 7.1 MJ/m2. These results may be useful providing input to agricultural and ecosystem that are dependent on solar radiation, such as engineers, designers, developers, and so forth, during the selection location process for solar installation.

Available solar radiation is an important crop growth monitoring and water balance that determines South Korea's crop productivity but has been poorly characterized. This paper studied the method of estimates for the available solar energy and crop growth monitoring based on data of Satellite imagery and meteorological observed data between 1982 and 2005 in South Korea. The objectives of this study are: a) assess of daily and monthly global radiation which most closely associated with rice growth; b) estimates for the available solar energy of the South Korea. Results from the study not only monitor the solar radiation in investigation area, but also illustrate the powerful potential to provide information about solar radiation based geostationary satellite imagery data.

The objective of this study was to evaluate surface heat fluxes based on satellite remote sensing data and field measurement data. Surface heat fluxes were estimated around the city of Cheongju, South Korea using Landsat 5 TM data and modeler of ERDAS Imagine. Landsat data was acquired on 6 August, 2006 (path 115, row 35). Field measurement was conducted in the paddy field and upland. And it was collected the same day with acquisition of Landsat imagery using net radiometer (Q-7.1, Campbell Scientific Inc.) and geothermometer (MF-180M, EKO Instruments Trading Co.). The result of this study was that net radiation at the surface was 350 ~ 670 W/m2. The percentage of surface heat fluxes were approximately 30% from sensible heat flux to the air, approximately 10% from soil heat flux, and 60% from latent heat flux. The surface heat flux in paddy field data was similar to Landsat data. The upland data was much alike, but they do have dissimilarities because the upland was too small area, considering Landsat image resolution. The results suggest that the methodology was feasible to estimate surface heat fluxes with reasonable accuracy over study areas.