Agent‐based supply chain disintermediation versus re‐intermediation: economic and technological perspectives

One important stream of information systems research addresses the role and future of supply chain and market intermediaries. But whereas many researchers hypothesize a trend toward disintermediation—principally enabled by information technology (IT)—others proffer theoretical arguments for IT‐enabled re‐intermediation. With regard to IT, it is particularly unclear whether the emerging technology associated with software agents is better suited to enable supply chain disintermediation or re‐intermediation. And if agent technology is better suited to either disintermediate or re‐intermediate supply chain activities, can we say this is always the case? Or will certain contingency factors intervene in various circumstances to suggest agent‐based disintermediation over re‐intermediation in some cases and vice versa in others? The research described in this paper takes some first steps toward addressing these questions. We first draw from the intermediation economics literature to summarize some of the key works and arguments for and against IT‐based dis/re‐intermediation, and we use this discussion to outline a preliminary set of conditions favoring agent application in such roles along the supply chain. We then draw from the agent technology literature to summarize key capabilities associated with extant agent technologies, and we compare such emerging IT with more conventional information systems and applications. Guided by this background of intermediation theory and extant agent capability, we describe a proof‐of‐concept multi‐agent system called ‘the Intelligent Mall’ in the context of supply chain dis/re‐intermediation. We use this implemented multi‐agent system to show how it reflects current agent technology, and we identify the contingent economic conditions that can be satisfied through this implemented system. The paper then closes, as we identify a several new lines of research stemming from this investigation. © 2000 John Wiley & Sons, Ltd.     

Dynamic optimal hedge ratio design when price and production are stochastic with jump

Annals of Finance - In this paper, we focus on the farmer’s risk income when using commodity futures, when price and output processes are randomly correlated and represented by jump-diffusion...     

Equity‐based incentives and shareholder say‐on‐pay

We study the relationship between CEO pay‐performance sensitivity, pay‐risk sensitivity, and shareholder voting outcomes as part of the “say‐on‐pay” provision of the 2010 US Dodd‐Frank Act. Consistent with our hypothesis, we provide evidence that shareholders tend to approve of compensation packages that are more sensitive to changes in stock price (pay‐performance sensitivity). Our findings are consistent with theoretical predictions that outside owners approve of equity incentives as a means of aligning managers' interests with those of shareholders. We also document that future changes to equity‐based incentives are related to voting outcomes and that shareholders incorporate CFO incentives into their votes. Collectively, these results provide evidence of the importance of equity‐based incentives from the perspective of those most concerned with firm value and of the effectiveness of say‐on‐pay as a governance mechanism.     

Toward an ontology‐driven blockchain design for supply‐chain provenance

An interesting research problem in our age of Big Data is that of determining provenance. Granular evaluation of provenance of physical goods (e.g., tracking ingredients of a pharmaceutical or demonstrating authenticity of luxury goods) has often not been possible with today's items that are produced and transported in complex, interorganizational, often internationally spanning supply chains. Recent adoptions of the Internet of Things and blockchain technologies give promise at better supply‐chain provenance. We are particularly interested in the blockchain, as many favored use cases of blockchain are for provenance tracking. We are also interested in applying ontologies, as there has been some work done on knowledge provenance, traceability, and food provenance using ontologies. In this paper, we make a case for why ontologies can contribute to blockchain design. To support this case, we analyze a traceability ontology and translate some of its representations to smart contracts that execute a provenance trace and enforce traceability constraints on the Ethereum blockchain platform.     

Risk‐based explanation for the book‐to‐market effect

This paper proposes a risk‐based explanation for the book‐to‐market (B/M) effect. I decompose B/M into net operating asset‐to‐market (NOA/M) and net financing asset‐to‐market (NFA/M) components. Portfolio analysis shows that (i) positive B/M, NOA/M and NFA/M are positively related to future returns and (ii) negative B/M, NOA/M and NFA/M are negatively related to future returns. To the extent that positive B/M, NOA/M and NFA/M act as measures of asset risk and negative B/M, NOA/M and NFA/M act as inverse measures of borrowing risk, the nonlinear relations between B/M, NOA/M and NFA/M and future returns provide some evidence to support the risk‐based explanation for the book‐to‐market effect in stock returns.     

Religious‐based portfolio selection

We examine religious attendance and portfolio selection decisions for an individual with religious beliefs within a continuous-time framework. Our findings are three-fold. First, religious contributions increase with wealth capital, the degree of religious devotion, and an increase in the wage level. Second, religious attendance positively relates to wealth capital and the performance of stock investments, but negatively correlates with wage return rates. Third, participation in religious activities can result in declining demand for risky asset investments. Theoretically, this study explains how individuals’ portfolio choices correlate with their religious activities.     

The flight‐to‐quality effect: a copula‐based analysis

We derive and estimate a copula combining the features of the Frank and Gumbel copulas to analyse the relationship between equity and long‐term bond returns. Our analysis of quarterly returns from 1952 to 2003 finds that, in general, there is a positive relationship between equity returns and bond returns. In extreme situations, however, there is approximately a one‐in‐seven chance of a flight‐to‐quality effect where large negative equity returns are associated with large positive bond returns.     

Fundamental‐based Market Strategies

A significant body of literature has raised the possibility that portfolio outperformance based on a simple accounting‐based investment strategy can persist through time because markets may ignore and potentially misinterpret financial market signals. Employing a fundamental‐based strategy, we show that superior performance can be earned consistently through time by identifying and investing in firms with more favourable performance and credit signals. The strength of these portfolios are additionally characterised by the ability of the strategies to avoid firms with poor future prospects. These findings are robust across varying time periods after both transaction costs and related market constraints are considered.     

A neural‐network‐based decision‐making model in the peer‐to‐peer lending market

This study proposes an investment recommendation model for peer‐to‐peer (P2P) lending. P2P lenders usually are inexpert, so helping them to make the best decision for their investments is vital. In this study, while we aim to compare the performance of different artificial neural network (ANN) models, we evaluate loans from two perspectives: risk and return. The net present value (NPV) is considered as the return variable. To the best of our knowledge, NPV has been used in few studies in the P2P lending context. Considering the advantages of using NPV, we aim to improve decision‐making models in this market by the use of NPV and the integration of supervised learning and optimization algorithms that can be considered as one of our contributions. In order to predict NPV, three ANN models are compared concerning mean square error, mean absolute error, and root‐mean‐square error to find the optimal ANN model. Furthermore, for the risk evaluation, the probability of default of loans is computed using logistic regression. Investors in the P2P lending market can share their assets between different loans, so the procedure of P2P investment is similar to portfolio optimization. In this context, we minimize the risk of a portfolio for a minimum acceptable level of return. To analyse the effectiveness of our proposed model, we compare our decision‐making algorithm with the output of a traditional model. The experimental results on a real‐world data set show that our model leads to a better investment concerning both risk and return.     

Optimal auction design in two‐sided markets

A key feature of online markets for advertising (e.g., sponsored links) is that clicking rates depend on the searchers' expectations that the platform selects relevant advertisers. This article studies auction design by a platform that maximizes profits in the long run, where clicking rates are mechanism dependent. In line with the practice of the major search engines, the revenue‐maximizing mechanism is a scoring auction that combines the willingness to pay and the relevance to searchers of advertisers. By trading off rent extraction and clicking volume, this mechanism works as a cross‐subsidization device between searchers and advertisers.     

Evaluating risk‐based capital regulation

This paper evaluates the effectiveness of risk‐based capital (RBC) regulation and challenges some evidence from the well‐known study by Haldane and Madouros (2012). We reconsider the evidence on the relationship between RBC ratios and failures of US banks from Haldane and Madouros (2012) and find their results are not robust to changes in the sample period or regression model. Using data on US commercial banks from 2000 through 2015 and an improved regression model, we compare banks’ RBC ratios and simple capital ratios as predictors of bank risk. We find simple capital ratios to be significantly better than complex RBC ratios as predictors of bank risk.     

Chief Financial Officers’ Short‐ and Long‐term Incentive‐based Compensation and Earnings Management

This study examines the association between chief financial officers’ (CFOs) short‐ and long‐term compensation and discretionary current and non‐current accruals. The CFO's cash bonus is used as a measure of short‐term incentives and shares plus options is used as a measure of long‐term incentives. The results show a significant and positive association between CFOs’ short‐term compensation and the absolute value of discretionary current accruals. The results also show a significant and positive association between CFOs’ long‐term compensation and the absolute value of discretionary non‐current accruals. STUDY provides evidence that the earnings management behaviour of CFOs is associated with type of CFO compensation.     

A knowledge‐based framework for incorporating investor's preference into portfolio decision‐making

This paper describes a framework for the integration of a rule‐based system capable of identifying an investor's risk preference into a quantitative portfolio model based on risk and expected return. By inferring rules consisting of an investor's objective and subjective risk preferences, the integrated methodology provides the assets suitable for the preferences. Through investment in the portfolio composed of the assets, the investor is able to obtain the following bene?ts: reduction of costs and time spent to determine target assets, and alleviation of anxiety from ‘out‐of‐favor’ assets. The framework is applied to the development of a knowledge‐based portfolio system for constructing an investor's preference‐oriented portfolio. In the procedure of the system for ?nding an optimal portfolio, the system uses an arti?cial intelligence method of a case‐based reasoning to obtain preference thresholds for an investor when the investor's past investment records are available. Experimental results show that the framework contributes signi?cantly to the construction of a better portfolio from the perspective of an investor's bene?t/cost ratio than that produced by the existing portfolio models. Copyright © 2004 John Wiley & Sons, Ltd.     

The Use of Performance‐based Remuneration: High versus Low‐growth Firms

This study analyses the CEO remuneration structure and level for 100 Australian‐listed entities. Consistent with expectations, it finds that high‐growth firms pay their CEOs a greater proportion of performance‐based pay, when equity‐based rewards only are considered. High‐growth firms also place greater reliance on market and/or non‐financial performance standards for the award of performance‐based pay. The extent to which performance‐based remuneration is used as a component of CEO pay is positively associated with firm size and growth options. Other potential determinants of performance‐based pay, such as financial performance, are not significantly associated with the use of performance‐based remuneration.     

A multi‐agent‐based hybrid framework for international marketing planning under uncertainty

The increased complexity and competition in the global marketing environment present new challenges to decision‐makers. The characteristics of the international marketing planning problem are clarified in this paper. The advantages and disadvantages of relevant techniques and technologies that may be applied to deal with the planning problem are analysed. A multi‐agent‐based hybrid intelligent framework for international marketing planning and associated Internet strategy formulation is then established, with underlying techniques, technologies, software architecture and integration method outlined. In addition, a software prototype of the hybrid framework, called AgentsInternational, is created and presented, with initial evaluation results reported. Further work on this topic is also planned. Copyright © 2009 John Wiley & Sons, Ltd.     

The Performance of Characteristics‐based Indices1

This paper analyses a set of characteristics‐based indices that, it has been argued, outperform market cap‐weighted indices. We analyse the performance of an exhaustive list of these indices and show that i) the outperformance over value‐weighted indices may be negative over long time periods, and ii) there is no significant outperformance over equal‐weighted indices. An analysis of the style and sector exposures of characteristics‐based indices reveals a significant value tilt. When this tilt is properly adjusted for, the abnormal returns of these indices decrease considerably. Moreover, it is straightforward to construct portfolios with higher Sharpe ratios than characteristics‐based indices through factor or sector tilts.     

Earnings‐based Delisting Regulations and Government Subsidies

This paper examines who receives government subsidies when a firm faces delisting risk and how subsidies affect such a firm's performance in China. It focuses on the accounting‐based delisting rule issued in 1998 that relies heavily on the profitability of firms. Using the probit model, this study finds that subsidies are less likely to be granted to a firm that has a higher risk of being delisted than a healthy firm, but are more likely to be granted to such a firm if it is state‐owned. It is also found that having a political connection increases a firm's chance of receiving subsidies, but such an effect disappears when a firm faces a delisting risk. In assessing the impact of a subsidy on firm performance, this study shows that a subsidy increases a firm's valuation and profitability for firms at delisting risk.