Conversation Analytics: Can Machines Read between the Lines in Real-Time Strategic Conversations?

2023 | HICSS | Citations: 0

Authors: Chen, Y.; Rui, H.; Whinston, A.

Abstract: Strategic conversations involve one party with an informational advantage and t ... Expand

Abstract: Strategic conversations involve one party with an informational advantage and the other with an interest in the information. This paper proposes machinelearning based measures to quantify the degrees of evasiveness and incoherence of the informed party during real-time strategic conversations. The specific empirical context is the questions and answers (Q&A) part of earnings conference calls during which managers endure high pressure as they face analysts' scrutinizing questions. Being reluctant to disclose adverse information, managers may resort to evasive answers and sometimes respond less coherently due to increased cognitive load. Using data from the earnings calls of the S&P 500 companies from 2006 to 2018, we show that the proposed measures predict worse nextquarter earnings. Moreover, the stock market perceives incoherence as a negative signal. This paper contributes methodologically by developing two novel machinepowered measures to automatically evaluate behavioral cues during real-time strategic conversations. The proposed analytical tools are particularly beneficial to resource-constrained and informationally disadvantaged parties such as retail investors who may not be able to effectively trade on signals buried deep in unstructured conversational data. Collapse

Topics: database system artificial intelligence electronic finance missing data accounting

Methods: computational algorithm BERT deep learning machine learning next sentence prediction

Theories: theory of economic growth

The Impact of High-Frequency Trading on Modern Securities Markets

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Clapham, Benjamin; Haferkorn, Martin; Zimmermann, Kai

Abstract: High-frequency traders account for a significant part of overall price formation ... Expand

Abstract: High-frequency traders account for a significant part of overall price formation and liquidity provision in modern securities markets. In order to react within microseconds, high-frequency traders depend on specialized low latency infrastructure and fast connections to exchanges, which require significant IT investments. The paper investigates a technical failure of this infrastructure at a major exchange that prevents high-frequency traders from trading at low latency. This event provides a unique opportunity to analyze the impact of high-frequency trading on securities markets. The analysis clearly shows that although the impact on trading volume and the number of trades is marginal, the effects on liquidity and to a lesser extent on price volatility are substantial when high-frequency trading is interrupted. Thus, investments in high-frequency trading technology provide positive economic spillovers to the overall market since they reduce transaction costs not only for those who invest in this technology but for all market participants by enhancing the quality of securities markets. Collapse

Topics: electronic trading IS impact

Methods: experimental group regression analysis method descriptive statistic robustness check cross sectional research

Theories: transaction cost economics

Machine economies

2023 | Electronic Markets | Citations: 0

Authors: Hartwich, Eduard; Rieger, Alexander; Sedlmeir, Johannes; Jurek, Dominik; Fridgen, Gilbert

Abstract: This fundamentals article discusses efficient machine economies in which non-hum ... Expand

Abstract: This fundamentals article discusses efficient machine economies in which non-human agents can autonomously exchange information and value. We first identify criteria for achieving Pareto efficiency in such economies by drawing on the Coase Theorem. We then translate these economic criteria to technical requirements before developing a framework that characterizes four types of machine economies. We discuss real-life examples for each type to highlight key challenges in achieving Pareto efficiency. In particular, we highlight that machine economies with human involvement in economic interactions and governance face significant challenges regarding perfect information, rationality, and transaction costs. Machine economies without human involvement, in turn, promise a high degree of Pareto efficiency, but there are still many open questions, particularly regarding machine-enforced governance. We conclude with opportunities for future research on the interactions and governance in machine economies. Collapse

Topics: anonymity smart contract public good

Theories: transaction cost economics theory of bounded rationality lemon market theory economic theory

Effect of Market Information on Bidder Attrition in Online Auction Markets

2022 | Management Information Systems Quarterly | Citations: 0

Authors: Ghasemkhani, Hossein; Goes, Paulo; Tripathi, Arvind

Abstract: Information generated in online markets can affect both buyers’ and sellers’ exp ... Expand

Abstract: Information generated in online markets can affect both buyers’ and sellers’ expectations and therefore their choices. In this research, we investigate the effect of market information, generated in online auction markets, on buyers’ expectations and choices. To clear large inventories, sellers often conduct many auctions selling identical items over time, which creates an online auction market where competition dynamics spill over from one to auction to another. In these markets, bidders can participate in many auctions over a period of time, observe market information (supply, demand, and competition), and gain experience to increase their payoffs. We observe that despite having an opportunity to compete and win in future auctions, many bidders stop participating in these auction markets. We argue that observed market information affects their choices. We explore how bidders form expectations about market supply, demand, and competition based on information from two sources—market design parameters and behavior of market participants. By employing a hierarchical Bayesian latent attrition model, we empirically detect and investigate the effect of bidders’ expected market supply, demand, and competition on their attrition in these markets. Our study shows that the effect of market information on attrition is nuanced by bidders’ value heterogeneity. Through the lenses of behavioral economics theories, we show that the attrition behavior of high-value bidders is completely opposite that of low-value bidders. We discuss the practical implications of our findings. Collapse

Topics: online auction decision making electronic market willingness to pay consumer behavior

Methods: descriptive statistic hidden Markov model Markov chain Monte Carlo conceptual modelling theoretical contribution

Theories: economic theory endowment effect behavioral economics lemon market theory social learning theory

Designing Hybrid Mechanisms to Overcome Congestion in Sequential Dutch Auctions

2022 | Management Information Systems Quarterly | Citations: 1

Authors: Lu, Yixin; Gupta, Alok; Ketter, Wolfgang; Heck, Eric van

Abstract: A common problem in many mature markets is how to deal with congestion—a situati ... Expand

Abstract: A common problem in many mature markets is how to deal with congestion—a situation in which transaction requests from market participants cannot be accommodated in an expedited manner. This paper examines the congestion problem in sequential Dutch auction markets. Transactions in these markets typically involve perishable goods, making market clearing speed crucial. Traditionally, sequential Dutch auctions have been implemented with fast-paced auction clocks that process equally attractive bids in the order they arrive and only award the first bidder as the winner of each round, which can lead to serious congestion in case of a demand surge. We propose a hybrid mechanism that capitalizes on the discrete nature of the auction clock and batches together the highest bids, allowing multiple transactions at the same price in each round. To evaluate the performance of the hybrid mechanism, we first develop a game-theoretic model comparing the hybrid mechanism to the traditional sequential Dutch auction mechanism. Our model predicts that the hybrid mechanism will achieve higher operational efficiency without compromising allocative efficiency. We then complement the theoretical analysis by evaluating the hybrid mechanism through a quasi-natural field experiment. The empirical analysis of the field data shows that the hybrid mechanism can significantly speed up the market clearing process and increase price stability without affecting the expected revenue. Our findings shed new light on the design and operation of multi-unit auctions. Collapse

Topics: price dispersion price management willingness to pay data breach business-to-business

Methods: experiment pilot experiment field experiment descriptive statistic mathematical model

Theories: game theory

Development and Evaluation of a Collaborative Stock Trading Environment in Virtual Reality

2022 | International Conference on Business Informatics | Citations: 0

Authors: Yigitbas, Enes; Gottschalk, Sebastian; Nowosad, Alexander; Engels, Gregor

Abstract: Due to the proliferation of Virtual Reality (VR) technology, VR is finding new ap ... Expand

Abstract: Due to the proliferation of Virtual Reality (VR) technology, VR is finding new applications in various domains, such as stock trading. Here, traders invest in stocks intending to increase their profit. For this purpose, in conventional stock trading, traders usually make use of 2D applications on desktop or laptop devices. This leads to many drawbacks such as poor visibility due to limited 2D representation, complex interaction due to indirect interaction via mouse and keyboard, or restricted support for collaboration between traders. To overcome these issues, we have developed a novel collaborative, virtual environment for stock trading, which enables stock traders to view financial information and trade stocks with other collaborators. The main results of a usability study indicate that the VR environment, compared to conventional stock trading, shows no significant advantages concerning efficiency and effectiveness, however, we could observe an increased user satisfaction and better collaboration. Collapse

Topics: virtual reality user satisfaction usability computer hardware extended reality

Methods: parametric test usability testing design science Student's t-test survey

Welfare Implications in Intermediary Networks

2021 | Information Systems Research | Citations: 0

Authors: Nguyen, Thành; Kannan, Karthik

Abstract: We study the welfare implications of competing middlemen in a two-sided market, ... Expand

Abstract: We study the welfare implications of competing middlemen in a two-sided market, where goods are intermediated between providers and purchasers. In our model, each intermediary sets the quantities it intermediates, and the prices are a consequence of a Cournot competition. Our analysis shows that, unlike traditional markets, increasing competition is not always beneficial for market efficiency and that mergers can have an ambiguous effect on efficiency. We also analyze how the underlying network influences social welfare. We define a parameter called the intermediary capacity of the network and show how the price of anarchy depends on this parameter. These results suggest an intuitive and simple measure for the level of competitiveness in a networked market involving intermediaries. Collapse

Topics: IS economics economic surplus consumer surplus ride sharing platform network effect

Methods: survey literature study cross sectional research chi squared test

A permissioned blockchain-based implementation of LMSR prediction markets

2020 | Decision Support Systems | Citations: 0

Authors: Carvalho, Arthur

Abstract: Since the seminal work by Hanson (2003), the Logarithmic Market Scoring Rule (LM ... Expand

Abstract: Since the seminal work by Hanson (2003), the Logarithmic Market Scoring Rule (LMSR) has become the de facto market-maker mechanism for prediction markets. We suggest in this paper three potential issues with centralized implementations of LMSR, which we refer to as the availability, security, and privacy problems. We also explain how a permissioned blockchain-based implementation of LMSR effectively solves all the above problems. Following the design science research framework (Peffers et al., 2007), our main contribution is a fully functional permissioned blockchain-based implementation of LMSR that is ready to be deployed. We believe our results are of great value not only to prediction market researchers and practitioners looking for LMSR implementations, but also to blockchain professionals looking for fully developed solutions as well as applications of suitable research frameworks to guide blockchain research and development. Collapse

Topics: blockchain privacy Hyperledger Ethereum research and development

Methods: design science simulation design artifact modeling language

Simultaneous service selection for multiple composite service requests: A combinatorial auction approach

2019 | Decision Support Systems | Citations: 0

Authors: Moghaddam, Mahboobeh; Davis, Joseph G.

Abstract: Emerging developments in service-based systems have contributed to a range of pr ... Expand

Abstract: Emerging developments in service-based systems have contributed to a range of proposals for the rapid development of complex applications by composing existing web services through standards-based interfaces. With the availability of a large number of such services offering identical functionality at varying levels of price and other Quality-of-Service (QoS) parameters, selecting the best web services for composition is critical– the problem referred to as composite service selection (CSS). Extant CSS approaches have tended to offer solutions to the problem for a single composite service. We extend CSS to address the setting involving multiple, simultaneous composite service requests. We propose a service selection mechanism based on combinatorial auctions to solve this problem by simultaneously matching the web service offers and requests and performing extensive evaluations in four market sectors with varying economic sizes and complexity of requests. The results indicate that the proposed simultaneous mechanism achieves a higher success rate in allocating services to requesters compared to sequential matching mechanisms. While the average cost difference in procuring composite services under the two mechanisms is not statistically significant, the simultaneous mechanism achieves more stable and homogenous costs over time. Collapse

Topics: web service price management dynamic pricing procurement management business process management

Methods: nonparametric test Kruskal Wallis test experiment simulation optimization model

Information or noise: How Twitter facilitates stock market information aggregation

2019 | International Conference on Information Systems | Citations: 0

Authors: Pöppe, Thomas; Kiesel, Florian; Kolaric, Sascha; Schiereck, Dirk

Abstract: We assess the relevance of Twitter for stock-relevant information dissemination ... Expand

Abstract: We assess the relevance of Twitter for stock-relevant information dissemination in financial markets on the single stock level. We use a unique dataset including more than 12 million Twitter feeds linked to specific firms. Using intraday data for the computation of advanced trading metrics, such as effective spreads, intraday volatility, and a daily version of the microstructure variable probability of informed trading (PIN), we measure the impact of Twitter activity on trading and information dissemination. The PIN model indicates that more uninformed than informed traders rush to the market along with rising Twitter activity. These results indicate that Twitter serves as an excellent indicator of news that is relevant for the stock market. However, we show that Twitter does not lead traditional news channels. In contrast, Twitter activity follows the market and has no predictive power with regard to future stock trading volume or volatility on the single stock level. Collapse

Topics: Twitter web forum microblog

Methods: longitudinal research descriptive statistic event study nonparametric test Kruskal Wallis test