Reducing the energy consumption of Internet services requires knowledge about the specific traffic and energy consumption characteristics, as well as the associated end-to-end topology and the energy consumption of each network segment. Here, we propose a shift from segment-specific to service-specific end-to-end energy-efficiency modeling to align engineering with activity-based accounting principles. We use the model to assess a range of the most popular instant messaging and video play applications to emerging augmented reality and virtual reality applications. We demonstrate how measurements can be conducted and used in service-specific end-to-end energy consumption assessments. Since the energy consumption is dependent on user behavior, we then conduct a sensitivity analysis on different usage patterns and identify the root causes of service-specific energy consumption. Our main findings show that smartphones are the main energy consumers for web browsing and instant messaging applications, whereas the LTE wireless network is the main consumer for heavy data applications such as video play, video chat and virtual reality applications. By using small cell offloading and mobile edge caching, our results show that the energy consumption of popular and emerging applications could potentially be reduced by over 80%.Energies 2019, 12, 184 2 of 18 increase since 2014 [2]. Furthermore, the data centers of Akamai consumed 233,090 MWh electricity in 2016, which is an increase of around 50% since 2012 [3].The increasing number of smartphone users together with the emergence of data-heavy mobile applications such as high-definition video play, virtual reality (VR) and augmented reality (AR) are driving the growth in mobile data traffic. These applications typically require very high network bandwidth and smartphone computing resources [4][5][6]. Moreover, the instant messaging (IM) applications, such as WeChat, Twitter, etc., attract a huge number of users because they offer a variety of mobile services including text/picture/voice messages, audio/video chat, moments, etc., and also consume a lot of network resources. Existing research to reduce the overall energy consumption of the Internet, including communication networks, cloud data centers and mobile devices, has focused on segment-specific energy consumption modeling and assessment of the end-to-end delivery of mobile applications, such as power models for smartphones, BSs, and edge and core networks. For example, various power models have been developed for estimating the energy consumption of different smartphone components such as 3G/4G, WiFi, central processing unit (CPU), liquid crystal display (LCD) and global positioning system (GPS). The researches in [7][8][9][10] show that the energy consumption of smartphones is influenced by different traffic characteristics and signaling patterns of mobile applications. Various power models of a long-term evolution (LTE) BS proposed in [11][12][13][14][15] try to assess energy consumption of mobile applications by sep...

We jointly study the impact of audit quality on auditor compensation and initial public offering (IPO) underpricing using a sample of Australian firms going public over the period 1996-2003. We find that quality (Big Four) audit firms earn significantly higher fees than non-Big Four auditors, and audit quality is positively associated with IPO underpricing. The positive relation between audit quality and underpricing is more pronounced for small issues, IPOs underwritten by non-prestigious underwriters, and those that are not backed by venture capitalists. Taken together, our results suggest that quality auditors serve as a signalling device that enhances post-issue market value of equity. Copyright (c) 2008 The Authors. Journal compilation (c) 2008 AFAANZ.

Business succession is one of the primary management challenges for family firms. However, many family firms fail at this task because of financial issues. Although a vast number of studies have investigated the succession process, research thus far has failed to determine how and why family firms select particular forms of financing for succession-related expenditures. Accordingly, this study conceptually and empirically investigates succession financing. We introduce a conceptual framework that investigates the reasons behind an owner-manager's intent to use debt for succession financing. Specifically, our model accounts for general and succession-related personal factors. However, we also include a set of firm-specific financing behavioral controls in our research. The empirical results are derived from a sample of 187 German family firms, and the results highlight financial knowledge, attitudes, succession experience, and succession planning as significant determinants of the owner-managers' debt usage intentions. The implications and avenues for future research are discussed.

Multiaccess edge computing and caching (MEC) is regarded as one of the key technologies of fifth-generation (5G) radio access networks. By bringing computing and storage resources closer to the end users, MEC could help to reduce network congestion and improve user experience. However, deploying many distributed MEC servers at the edge of wireless networks is challenging not only in terms of managing resource allocation and distribution but also in regard to reducing network energy consumption. Here, we focus on the latter by assessing the network energy consumption of different cache updating and replacement algorithms. First, we introduce our proposed proactive caching (PC) algorithm for mobile edge caching with Zipf request patterns, which could potentially improve the cache hit rates compared to other caching algorithms such as least recently used, least frequently used, and popularity-based caching. Then, we present the energy assessment models for mobile edge caching by breaking down the total network energy consumption into transmission and storage energy consumption. Finally, we perform a comprehensive simulation to assess the energy consumption of the PC algorithm under different key factors and compare with that of conventional algorithms. The simulation results show that improving cache hit rates by using the PC algorithm comes at the expense of additional energy consumption for network transmission. INDEX TERMS Wireless edge caching, energy consumption, 5G, multiaccess edge computing, proactive caching.

No abstract