Browsing by Author "Hsu, Wei-Yen"

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An empirical study on the effects of an enterprise fan page
(2018-01-01)
Shang, Shari S. C.
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Hsu, Wei-Yen
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Tseng, Hsiao-Ting
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Jiang, Jen Jen
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Chiang, Chieh-Jen
Most major enterprises have invested in social networking to provide services, promote products, or communicate with customers. However, to date, no clear understanding on the effects of social networks on business performance has emerged. This study examines the relationship between the capability of the enterprise to manage social networks and the resultant benefits of their investing in the social network. A fan page on Facebook is the selected target of study. By analyzing the effort required to manage a fan page, we measured the fan-page managing capability by its number of fans. Then, we proposed six hypotheses for empirical examination of the causal relationship between enterprises' social network managing capability and business benefits. The study applied two-stage data collection and testing. The first stage is to build a general understanding of the relationship between the number of fans and business revenue. Based on findings of the first stage, the study tested the hypotheses on selected global firms and sought patterns of benefits generated from the fan page. This study builds deep understanding from various aspects about fan-page effects on enterprises, and proposes that firms that provide products and services with characteristics of low-product price, short-product durability, and low-customer involvement are empirically influenced by the management of their fan pages.
IoT-Based Image Recognition System for Smart Home-Delivered Meal Services
(2017-07-01)
Tseng, Hsiao-Ting
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Hwang, Hsin-Ginn
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Hsu, Wei-Yen
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Chou, Pei-Chin
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Chang, I-Chiu
Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the 10-year long-term care program 2.0. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.