Consumer on-line behaviors are more important than ever due to highly growth of on-line shopping. The purposes of this study were to design placement methods of background music for shopping website and examine the effect on browsers’ emotional and cognitive response. Three placement points of background music during the browsing, i.e. 2 min., 4 min., and 6 min. from the start of browsing were considered for entry points. Both browsing without music (no music) and browsing with constant music volume (full music) were treated as control groups. Participants’ emotional state, approach-avoidance behavior intention, and action to adjust music volume were collected. Results showed that participants had a higher level of pleasure, arousal and approach behavior intention for the three placement points than for no music and full music. Most of the participants for full music (5/6) adjusted the background music. Only 16.7% (3/18) participants for other levels turn off the background music. The results indicate that playing background music after the start of browsing is benefit for on-line shopping atmosphere. It is inappropriate to place background music at the start of browsing shopping website. The marketer must manipulated placement methods of background music for a web store carefully.

With the vigorous development of emerging technology and the advent of the Internet generation, high-speed Internet and fast transmission 5G wireless networks contribute to interpersonal communication. Now, the Internet has become popular and widely available, and human life is inseparable from various experiences on the Internet. Many base stations and data centers have been established to convert and switch from electrical transmission to optical transmission; thus, it is entering the new era of optical fiber networks and optical communication technologies. For optical communication, the manufacturing of components for the purpose of high-speed networks is a key process, and the requirement for the stability of its production conditions is very strict. In particular, product yields are always low due to the restriction of high-precision specifications associated with the limitations of too many factors. Given these reasons, this study proposes a hybrid fuzzy control-based model for industry data applications to organize advanced techniques of box-and-whisker plot method, association rule, and decision trees to find out the determinants that affect the yield rate of products and then use the fuzzy control Proportional-Integral-Derivative (PID) method to manage the determinants. Since it is unrealistic to test the real machine online operation at the manufacturing stage, the simulation software supersedes this for improved results, and a mathematical neural network is used to verify the given data to confirm whether its result is similar to that of the simulation. The study suggests that excessive temperature differentials between substrate and cavity can lead to low yields. It suggests using fuzzy control technology for temperature management, which could increase yield, reduce labor costs, and accelerate the transition to high-speed networks by mass-producing high-precision optical filters.

Facing the global competitive market and ever-changing customer demands, manufacturers must navigate intense competition and uncertain demand while striving to enhance customer satisfaction. As a result, the demand for customized products has become a crucial design consideration. To respond accurately and swiftly in a competitive market, manufacturers must focus on customer needs, analyze market trends and competitor information, and leverage data analysis as a reference for new product development and design. This study presents a new product development model by integrating quality function deployment (QFD), decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and fuzzy set theory. It first uses a 2-tuple fuzzy DEMATEL to identify significant interrelationships among factors. A revised house of quality (HOQ) is then constructed to map relationships among customer requirements (CRs), engineering requirements (ERs), and the influences of CRs on ERs. To address uncertainty in human judgment, fuzzy set theory is incorporated into the ANP. The integrated model can determine the relative importance of the ERs. The proposed model is applied to touch panel development, and the results are recommended to the R&D team for new product development.