We examine the effect of a pre-IPO audit committee on IPO pricing from the perspectives of information asymmetry and agency problems. We propose a bargaining power hypothesis to disentangle the information asymmetry explanation (financial reporting quality) from the agency problems explanation (underwriter bargaining power) on IPO pricing. IPO underpricing can be reduced by increasing the financial reporting quality under information asymmetry and/or by decreasing the underwriter bargaining power under agency problems. An audit committee can raise the quality of financial reporting and reduce the bargaining power of underwriters. With a pre-IPO market, the IPO markets in Taiwan have little information asymmetry, thus leading to the weak importance of reducing information asymmetry. We show that the establishment of a pre-IPO audit committee improves IPO pricing efficiency by reducing underwriter bargaining power rather than by raising the quality of financial reporting in Taiwan.

Introduction

An initial public offering (IPO) is the process of offering shares of a firm that is transitioning from private to public status by selling stocks to a large number of diversified investors. Although information is disclosed in the IPO prospectus, it is still difficult to value an IPO because no price history is available for firms before going public. Because of the value uncertainty of IPO firms, investors cannot fully identify high-value IPOs from low-value IPOs. Leland and Pyle (1977) argue that investors benefit from knowing the true information of the issuers. However, moral hazard hampers the truthful release of information from issuers to investors. Issuers gain substantial rewards by exaggerating positive information. To overcome the existence of substantial information asymmetry between them and investors, issuers must reveal information and credible signals to the market. The best-known anomaly of IPOs is the underpricing of IPO shares that are listed for the first time. Lowry et al. (2017) indicate that most of the fundamental models of IPO underpricing focus on information asymmetry. Because of the heterogeneity of skills among investors, some investors obtain more information on the issuing firms than do other investors (Rock (1986); Amihud et al. (2003)).

This paper examines whether managers’ decisions to engage in income-increasing earnings management are sensitive to discount rates. Rational managers are expected to pursue and favor strategies that maximize their own gains, even at the expense of other stakeholders (Jensen & Meckling, 1976). Financial reporting provides one way to serve self-interests, particularly when information asymmetry exists between users and providers of the reports. Managers can take accounting or real economic actions to manage short-term performance and, consequently, serve self-interests e.g. by triggering earnings-based performance compensation (Gaver, Gaver, & Austin, 1995; Healy, 1985; Holthausen, Larcker, & Sloan, 1995; Watts & Zimmerman, 1986) to meet capital market expectations (Eames, 1998) or prior to IPOs (Teoh, Welch, & Wong, 1998). There is considerable empirical evidence showing that managerial self-interests affect their decision horizon. For example, CEOs respond to personal earnings-based incentives by engaging in short-term performance-enhancing activities, rather than long-term value creation that would benefit shareholders (Bergstresser & Philippon, 2006; Dechow & Sloan, 1991). Similarly, shorter expected CEO tenure has been associated with higher agency costs, lower earnings quality, and greater probability of information-based trading, providing evidence that shorter decision horizons motivate managers to invest in projects with quicker payback (Antia, Pantzalis, & Park, 2010; Gopalan, Milbourn, Song, & Thakor, 2014). The purpose of this paper is to examine whether discount rates affect rational managers’ decisions to manage earnings for a given decision horizon. To increase current earnings managers may exercise their discretion over accruals or real business decisions. The use of income-increasing accruals-based earnings management or real earnings management to inflate earnings is a short-horizon strategy because of two factors: 1) the reversal of discretionary accruals and real consequences of operational decisions, and 2) managers’ reputation risk. First, using accounting discretion related to income-increasing accruals in the current period constrains the ability to manage accruals in the same direction in future periods (Baber, Sok-Hyon, & Ying, 2011; Barton & Simko, 2002; DeFond & Park, 2001). That is, accruals must reverse at some point (Rangan, 1998), unless managers employ even more aggressive earnings management. Similarly, increasing earnings with real business actions is also a short-horizon strategy (Cohen & Zarowin, 2010). Earnings management by real business actions, for example via channel-stuffing increase current cash flow by bringing forward future cash flows. Second, both earnings management strategies are likely to alert analysts, auditors and the press. This increases the risk of reputation loss and labor-market disciplining and pose a threat for managers’ future net benefits (Brickley, Linck, & Coles, 1999; Davidson, Xie, Xu, & Ning, 2007; Kaplan, McElroy, Ravenscroft, & Shrader, 2007).

The world is going through crucial issues like energy scarcity, air pollution, and the emission of greenhouse gas (GHG) (Sang and Bekhet, 2015). Vehicles which use both electrical and internal combustion engines for propulsion purposes, appear to be a very promising prospect (Millo et al., 2014). There are 3 types of road transports powered by electricity such as electric vehicles (EVs), hybrid electric vehicles (HEVs), and plug-in-electric vehicles (PHEVs). These vehicles offset foreign petroleum usage and cost less to refuel per mile than conventional vehicles. EVs are propelled by a battery-powered motor, and the battery is charged by plugging the vehicle into the electric grid either at home or at a public charging station (Ahmadi et al., 2015). EVs do not have an internal combustion engine and therefore do not use petroleum. HEVs are powered by conventional or alternative fuels as well as electric power stored in a battery. The charging of a battery is performed through the internal combustion engine and regenerative braking. Alternatively, the captured battery energy generally lost during braking by the use of electric motor acted as a generator. Contrasting EVs and PHEVs, HEVs are not plugged into charge (Adnan et al., 2017a). However, HEVs use both petroleum and electricity and a good mean for long distance driving. PHEVs are powered by alternative or conventional fuels as well as electric power stored in a battery. The battery can be charged by plugging it into an outside power source, by the internal combustion engine, or by regenerative breaking (Adnan et al., 2017a). Unlike HEVs, which still depend on petroleum, it is possible for PHEVs to run on only electricity when fully charged. Because PHEVs can run off petroleum or electricity, they are a good option for driving long distance if you are uncertain about charging station availability. Moreover, PHEVs are extensively recognised as an answer that will reduce the harmful effect on the climate and lessen the carbon emission (Adnan et al., 2016). Hence, this sort of vehicle offers an advantage in the quest to reduce carbon emissions by as much as 30 percent to 50 percent and be able to attain 40 percent to 60 percent improvement in fuel efficiency. Though, Bonges and Lusk (2016) stated that in actual fact, they are going to be somewhat on the lower side. Several researchers have proved that a great amount of reduction in greenhouse gas emissions and in the increasing dependence on oil could be accomplished by the electrification of the transport sector, which further needs proper understanding and adoption from the consumer’s point of view (Barbarossa et al., 2015; Bateman et al., 2013). Certainly, the emergence of Hybrid Electric Vehicles (HEVs) has received substantial industrial accomplishment starting from the last decade. However, all the vehicles are categorised into 3 major groups, such as Internal Combustion Engine Vehicles (ICEVs), Hybrid Electric Vehicles (HEVs), and All-Electric Vehicles (AEVs) (Adnan et al., 2016a; Boroojeni et al., 2017). Nonetheless et al. (2016) specified that a PHEV has less CO2 emission and it helps towards environmental sustainability. Schuitema et al. (2013) argued that the disadvantage of PHEV batteries is that they cannot offer the same mileage that a pure EV would offer as batteries are easily drained off for PHEVs.

Dynamic pricing, which is defined as the dynamic adjustment of market price, has been widely adopted by marketing researchers and practitioners [1–6]; this is because price is one of the most controllable variables. In the past, dynamic pricing strategies were widely applied to traditional marketing, with a significant cost associated with changing prices [7–9]. With the advent of the Internet marketing, the overhead has greatly diminished [10–13]. Dynamic discount pricing is a common form of dynamic pricing. In contrast to a merely low price, a discounted price typically implies the high quality and unusual bargain of the item and, hence, has strong attraction to rational customers. Consequently, the design and evaluation of dynamic discount pricing strategies have long been a research hotspot in the marketing field [14–20]. As compared to traditional advertizing marketing, the emerging word-of-mouth (WOM) marketing can bring about higher marketing profit at a much lower cost [21–25]; this is especially the case with the popularity of online social networks [26]. To evaluate the performance of different WOM marketing strategies, a number of dynamic models capturing WOM spreading processes have been suggested [27–36]. However, these dynamic models are all population-level, which cannot accommodate the WOM network. As a result, the accuracy of the estimated performance is questionable. To overcome this flaw, individual-level dynamic models, which have been widely applied to areas such as epidemic spreading [37–40], malware spreading [41–47] and cybersecurity [48–50], should be borrowed to more accurately characterize WOM spreading processes. The optimal control theory provides an appropriate mathematical framework for the design of better dynamic strategies [51, 52]. For instance, the optimal control approach has been applied to the dynamic control of malware [53–55], where the virus spreading models accommodate the virus propagation network. To the best of our knowledge, to date the dynamic pricing in WOM marketing has not been dealt with in the framework of optimal control theory. This paper addresses the dynamic discount pricing in WOM marketing by the optimal control approach. First, an individual-level differential dynamic model capturing WOM spreading processes is established. This model accurately characterizes the dynamic discount mechanism and perfectly accommodates the WOM network. On this basis, the expected profit of a WOM marketing champaign is evaluated, and the problem of finding an optimal discount strategy boils down to an optimal control problem.

Today, increased competition between markets, financial pressure, and customer bargaining power have raised issues such as increasing customer value, improving customer relationship management (CRM), and forecasting customer behavior. To increase their profitability, organizations try to maximize the value of their customers using customers’ valuable information and their differences (Chang and Tsai 2011; Farooqi and Raza 2012; Khajvand et al. 2011). Customers have expectations about the price and quality of products and services. Price expectations play an important role in consumer choice processes (PK Kannan 2001). Pricing is an important decision for any business, and especially for emerging online retailers (Shim, Choi, and Suh 2012). Dynamic pricing is a pricing strategy where prices change over time. Economic theories argue that the dynamic pricing is inherently good for corporate profitability, because it allows companies to obtain a greater consumer surplus. Dynamic pricing is determined through up-selling, amount of discount and product packaging (Shim, Choi, and Suh 2012). In the online business where competition and price difference between different suppliers is high; the discount will attract different customers. Discounts encourage customers so that, in some cases, they prefer particular products or brands simply because of gifts and discounts on offer (Liang 2010). Studies indicate that prices and discounts are involved in customer expectations and guide their future behavior. The price varies according to supply and demand conditions. For example, offering lower prices to loyal customers or permanent buyers always meets their expectations. Loyal customers get more discounts, which in turn increases their loyalty (Nikumanesh and Albadvi 2014). The positive impact of discount on customer loyalty is twofold: (1) loyal customers call for rewards for their loyalty and rely on bargaining power, and (2) granting discounts by retailers is necessary for maintaining loyal customers.

The purpose of this note is to study a connection between a model of labor markets with regulation recently defined and analyzed in Fu et al. (2017) and a model of simultaneous single-item auctions which was originally suggested by Bikhchandani (1999) and which has received significant attention in the last few years in the computer science literature on algorithmic game theory. This connection yields new results in both models. In particular, the results of Fu et al. (2017) on labor markets with regulation imply (via the connection we establish here) new bounds on the price of anarchy and the price of stability of simultaneous second price auctions as well as new guarantees on the existence of pure Nash equilibria in this auction game. In the classical labor market model due to Kelso and Crawford (1982) there is a set of firms N, a set of workers M, and a production function v n : 2 M → ℜ+ for every firm n ∈ N, where v n (S) is the production value of firm n if it hires a subset workers S ∈ 2 M . Three main results of this theory are that gross-substitutability of all production functions is a sufficient condition for the existence of a stable matching of workers and firms, that all stable matchings are efficient, and that in fact gross-substitutability is also a necessary condition for the above two properties to hold (this last property is due to Gul and Stacchetti (1999)). Bikhchandani (1999) studies a complete-information auction game where firms compete simultaneously for employees by proposing salaries, and employees pursue the highest offer. This is known in the literature on combinatorial auctions as a First Price Item Bidding (FPIB) auction. Bikhchandani (1999) shows a connection between this auction game and the classic labor market model described above, by showing a correspondence between the set of Nash equilibrium (NE) outcomes of the FPIB game and the set of stable outcomes of a labor market.3 In a recent paper (Fu et al., 2017) we modify the classic labor market model and study labor markets with regulation designed to provide employees with job security. To capture job security we have introduced a weaker solution concept termed JS-stability (where JS stands for job security). That previous paper has three main results: it provides sufficient conditions on the structure of the production functions that ensure the existence of JS-stability, it shows that the welfare in any JS-stable outcome is at least half of the optimal welfare, and it describes necessary and sufficient conditions for the existence of efficient JS-stable outcomes. These results therefore provide a mirror image of the three main results of classic labor markets (without job security) described above. Continuing this thread of thought, our result in this current note parallels the connection between the classic labor market and the FPIB game of Bikhchandani (1999). Specifically, we show a connection between labor markets with job security and the Second Price Item Bidding (SPIB) auction game, introduced in Christodoulou et al. (2008). The difference between FPIB and SPIB is that in the latter an employee’s salary is determined by the second highest offer and not the first. While Bikhchandani (1999) shows a correspondence between the set of pure NE outcomes of the FPIB auction game and the set of stable matchings of the classic labor market (without regulation), we show here a correspondence between the set of pure NE outcomes of the SPIB auction game and the set of JS-stable outcomes in our model of labor markets with regulation. The two theories of labor markets with and without job security are therefore parallel with respect to this property as well. As mentioned above, as an immediate corollary of this connection we obtain several results regarding existence of pure Nash equilibria in the SPIB auction game, and the price of anarchy and price of stability in this game. Section 2 gives more details on the model of a labor market with regulation. Section 3 analyzes the connection between the labor market model and the auction model, and describes some corollaries that this connection yields.

مقاله سال 2016

In the airline industry, price discrimination is known to play a crucial role in setting profitable strategies. Traditional carriers have begun to maximise profits by use of a yield management approach, in which they provide different travel classes (business vs. leisure) to suit passengers’ various willingness to pay (Giaume and Guillou, 2004; Shapiro et al., 1999). However, this type of price discrimination, namely third-degree price discrimination, cannot generally be implemented by low-cost carriers (LCCs), since they tend to provide the same level of service for all passengers1 (MorenoIzquierdo et al., 2015). Instead, LCCs generally rely on intertemporal price discrimination (e.g. Alderighi et al., 2015). They differentiate between highly price-inelastic business passengers, who typically book just a few days before departure, and priceelastic leisure travellers, who often book in advance, and then they maximise revenues by increasing the fares offered as the day of departure approaches (Bergantino and Capozza, 2015). Furthermore, LCCs have been also found to segment the market with regard to some route features, such as length and frequency, and departure day being on a weekend, bank holiday, or other highdemand period (e.g. Malighetti et al., 2010; Piga and Bachis, 2007; Salanti et al., 2012). Interestingly, only a few recent studies have mentioned that airlines appear to vary fares depending on the number of tickets booked on the Internet by a single consumer, thus relying on nonlinear price discrimination (Alves and Barbot, 2009; Lii and Sy, 2009). To the best of our knowledge, no empirical studies on LCCs have thoroughly investigated the presence of quantity discounts2 implemented as a part of nonlinear price discrimination.

In this paper, we make a straightforward contribution to the literature by providing evidence of LCCs’ nonlinear price discrimination exemplified by easyJet’s two-part tariff strategy. Specifically, ticket prices are composed of i) a fixed fee (V17) per booking and ii) a dynamic component that characterizes almost all LCCs’ pricing strategies. Moreover, by use of a multivariate framework, we investigate the joint effect of these two components on unit price at the single-flight level.

We use a unique dataset, which includes fares booked on flights from the Amsterdam Schiphol airport (AMS) towards 20 European different destinations during the period between January and April 2015 (1868 flights). Data on ticket prices and characteristics of the flights (destination airport, date of departure, and hour ofdeparture) are gathered daily from easyJet’s website. Unit prices are collected for reservations composed of 1 seat, 5 seats, and multiples of 5 seats, up to the maximum reservation that can be booked through easyJet’s website, 40 seats.