Energy waste significantly contributes to increased costs in the automotive manufacturing industry, which is subject to energy usage restrictions and taxation from national and international policy makers and restrictions and charges from national energy providers. For example, the UK Climate Change Levy, charged to businesses at 0.554p/kWh equates to 7.28% of a manufacturing business's energy bill based on an average total usage rate of 7.61p/kWh. Internet of Things (IoT) energy monitoring systems are being developed, however, there has been limited consideration of services for efficient energy-use and minimisation of production costs in industry. This paper presents the design, development and validation of a novel, adaptive Cyber-Physical Toolset to optimise cumulative plant energy consumption through characterisation and prediction of the active and reactive power of three-phase industrial machine processes. Extensive validation has been conducted in automotive manufacture production lines with industrial three-phase Hurco VM1 computer numerical control (CNC) machines.
Marketers need evidence to help them select music to promote their products. Ethnicity, social class and/or personality type can distinguish individual music tastes, but age and nostalgia may be the largest determinant of all (North, American Journal of Psychology,123, 199–208, 2010). Research into listener preference for music from different eras has found conflicting results. Papers generally agree that it takes an inverse U shape, but disagree on the era for which people are most nostalgic. The seminal paper found a peak for music released when listeners were 23 years of age (Holbrook & Schindler, Journal of Consumer Research,16, 119–124, 1989), a follow-up 9 years of age (Hemming, Musicae Scientiae,17, 293–304, 2013), and 19 years of age (Holbrook & Schindler, Musicae Scientiae,17, 305–308, 2013). This paper attempts to correct the issues raised by Holbrook & Schindler (Musicae Scientiae,17, 305–308, 2013) by improving the representativeness of the sample and introducing a new analysis technique, the two-lines test. This paper finds support for Holbrook & Schindler, but with a slightly younger age peak of roughly 17 years. Additionally, the larger sample allows investigation of differences by generation, which reveals differences that may be caused by their different current age, and so the relationship with, and interplay of nostalgia and music. The central conclusion of the paper is that people do exhibit a preference for music released during their late adolescence/early adulthood. When targeting consumers of a narrow age demographic, music released during this time is more likely to be preferred than any other.
The advice to musicians and marketers is to focus on what they love: a truism for practitioners is to find 1000 'true fans' and make $100 from each of them (Kelly, 2008. 1000 True fans. The Technium). If this advice is correct, we should see musicians with loyal user bases engaging more with their favourite artists and less with other music, suggesting a narrow targeting strategy would suffice. On the other hand, the established marketing laws indicate that the listeners of very different genres should overlap more than conventional wisdom would suggest, supporting the need for a much broader approach to targeting potential audiences. Given these conflicting views, musicians need to know if they should market to their existing listeners, the listeners of music similar to theirs (i.e., the same genre), or if they should try to reach a much wider audience. We turn to established choice patterns from the marketing literature to address these questions in the music context. This study examines 84,000,000 observations of music listening from 27,000 unique global users between 2013 and 2014 and survey data from 2019 containing music listening from over 1000 representative respondents in the United States. The results show that listening follows the Duplication of Purchase law for genres, artists, albums, and songs, at an annual, 6-months, 3-months, 1-month, and 1-week period, with no indication of partitioned music listening. The implication is that musicians should try to reach all potential listeners, regardless of what they already listen to. These findings contribute to the theoretical knowledge about duplication analyses of various durations, extend the contexts of choice behaviour that exhibit this pattern, and managerially, to knowledge about the extent of potential audiences and 'share of ear' competition. | INTRODUCTIONMusic listening is a popular and prevalent human choice activity. Americans spend about 32 h a week, or four-and-a-half hours a day, listening to music (Nielsen, 2017). There are over 250 million paid music streaming service subscribers, accounting for 37% of the US$19B industry (International Federation of the Phonographic Industry, 2019). Streaming technologies provide unprecedented access to millions of songs (Krause et al., 2015), making finding music a potentially overwhelming choice. Record companies invest at least US$5.8B annually on new artist scouting and marketing activities (International Federation of the Phonographic Industry, 2019).
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