The Quality-Signaling Role of Manipulated Consumer Reviews

2023 | Group Decision and Negotiation | Citations: 0

Authors: Zhao, Hui; Wang, Xiaoyuan; Ni, Debing; Li, Kevin W.

Abstract: We develop a quality-signaling game model to characterize a firm that produces a ... Expand

Abstract: We develop a quality-signaling game model to characterize a firm that produces an experience good with private quality information and chooses either a separating or pooling pricing strategy to sell the product to both early-arriving and late-arriving consumers. The firm endogenously determines whether to manipulate early-arriving consumers’ reviews to influence late-arriving review-conscious consumers. We show the existence of multiple perfect Bayesian equilibriums (PBEs) and select the PBEs with the maximum ex ante expected profit. Based on the selected PBEs, we first establish the conditions under which the firm chooses the pooling pricing strategy but succeeds (fails) in manipulating early-arriving consumers to leave positive fake reviews on product quality. We also furnish the conditions under which the firm adopts the separating pricing strategy to truthfully reveal its private quality information, thereby ruling out the possibility of fake reviews. Second, by comparing the cases with and without consumer reviews, we explore how consumer reviews affect the welfare of the firm, consumers, and society. Third, we examine how the firm’s profitability, consumer surplus, and social welfare vary with two key market parameters, the unit reputation cost of positive fake reviews and the probability that late-arriving consumers are review-conscious. Managerial insights are garnered on how the firm should price its product and whether it should manipulate consumer reviews as well as how consumer review manipulation should be regulated under different market conditions. Collapse

Topics: price management IS economics fake review consumer surplus economic surplus

Methods: product review literature study descriptive statistic cross sectional research theorem proofing

Theories: game theory

Discount Schemes for the Preemptible Service of a Cloud Platform with Unutilized Capacity

2021 | Information Systems Research | Citations: 2

Authors: Chen, Shi; Moinzadeh, Kamran; Tan, Yong

Abstract: Rapid growth in the cloud services market provides tremendous opportunities to c ... Expand

Abstract: Rapid growth in the cloud services market provides tremendous opportunities to cloud providers who have invested heavily in computing capacities but also has led, at time, to low utilization of capacities. To alleviate this problem, some providers have launched a low-priority service with preemptible (spot) instances, which allows them to attract more customers while keeping the right to reclaim capacities when necessary. In this study, we consider a provider who faces a heterogeneous pool of customers with fault-tolerant (interruptible) computing jobs. We develop an analytical framework that consists of a customer-choice model and a diffusion model to capture the underlying supply-demand dynamics and the resulting preemption probability. First, we examine a commonly used discount scheme for preemptible instances, namely, the uniform discount scheme, and derive the optimal discounted price, given customers’ expectation of the preemption probability. Then, we propose another practical discount scheme, namely, the interruption-based discount scheme, which provides customers with compensation for interruptions. As long as the provider interrupts the preemptible instances randomly and customers are risk neutral, the two discount schemes are equivalent from the provider’s perspective. That said, the proposed scheme is fairer than the uniform discount scheme from the customers’ perspective, as the former provides more discounts to customers who experience more interruptions. Finally, in the presence of risk-averse customers, through a numerical study, we find that the provider would be better off by adopting the uniform discount scheme in an environment in which the level of surplus capacity stays high and stable. Overall, however, the provider would be better off by adopting the proposed scheme when the level of the surplus capacity is moderate and volatile; the relative advantage of the proposed scheme enlarges as the average surplus capacity decreases and its volatility increases. Collapse

Topics: willingness to pay price management cloud computing provider cloud computing augmented reality

Methods: descriptive statistic optimization model experiment theorem proofing mathematical model

Will Catastrophic Cyber-Risk Aggregation Thrive in the IoT Age? A Cautionary Economics Tale for (Re-)Insurers and Likes

2021 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Pal, Ranjan; Huang, Ziyuan; Lototsky, Sergey; Yin, Xinlong; Liu, Mingyan; Crowcroft, Jon; Sastry, Nishanth; De, Swades; Nag, Bodhibrata

Abstract: Service liability interconnections among networked IT and IoT-driven service org ... Expand

Abstract: Service liability interconnections among networked IT and IoT-driven service organizations create potential channels for cascading service disruptions due to modern cybercrimes such as DDoS, APT, and ransomware attacks. These attacks are known to inflict cascading catastrophic service disruptions worth billions of dollars across organizations and critical infrastructure around the globe. Cyber-insurance is a risk management mechanism that is gaining increasing industry popularity to cover client (organization) risks after a cyber-attack. However, there is a certain likelihood that the nature of a successful attack is of such magnitude that an organizational client’s insurance provider is not able to cover the multi-party aggregate losses incurred upon itself by its clients and their descendants in the supply chain, thereby needing to re-insure itself via other cyber-insurance firms. To this end, one question worth investigating in the first place is whether an ecosystem comprising a set of profit-minded cyber-insurance companies, each capable of providing re-insurance services for a service-networked IT environment, is economically feasible to cover the aggregate cyber-losses arising due to a cyber-attack. Our study focuses on an empirically interesting case of extreme heavy tailed cyber-risk distributions that might be presenting themselves to cyber-insurance firms in the modern Internet age in the form of catastrophic service disruptions, and could be a possible standard risk distribution to deal with in the near IoT age. Surprisingly, as a negative result for society in the event of such catastrophes, we prove via a game-theoretic analysis that it may not be economically incentive compatible, even under i.i.d. statistical conditions on catastrophic cyber-risk distributions, for limited liability-taking risk-averse cyber-insurance companies to offer cyber re-insurance solutions despite the existence of large enough market capacity to achieve full cyber-risk sharing. However, our analysis theoretically endorses the popular opinion that spreading i.i.d. cyber-risks that are not catastrophic is an effective practice for aggregate cyber-risk managers, a result established theoretically and empirically in the past. A failure to achieve a working re-insurance market in critically demanding situations after catastrophic cyber-risk events strongly calls for centralized government regulatory action/intervention to promote risk sharing through re-insurance activities for the benefit of service-networked societies in the IoT age. Collapse

Topics: mobile system internet of things IT security threat supply chain management cloud computing

Methods: case study theory development experiment theorem proofing network analysis

Theories: game theory

Manufacturer driven strategic coordination as a response to “showrooming”

2020 | Decision Support Systems | Citations: 0

Authors: Basak, Shounak; Basu, Preetam; Avittathur, Balram; Sikdar, Soumyen

Abstract: “Showrooming”, a practice where consumers visit a brick-and-mortar store to exam ... Expand

Abstract: “Showrooming”, a practice where consumers visit a brick-and-mortar store to examine and research a product before buying it online, is being increasingly observed in recent times. This not only adversely affects the physical store but also the manufacturer in the long run. Showrooming leads to reduced sales efforts on the part of the brick-and-mortar retailer which leads to a decline in showcasing of the product to consumers. This affects the overall demand for the product in the market. In this paper, we analyze the effect of wholesale prices set by the manufacturer on the retail prices of the products in a multi-channel environment affected by showrooming. To combat the adverse impact of showrooming, we further investigate the feasibility of a manufacturer-driven alliance with the brick-and-mortar retailer so that it expends adequate sales effort that leads to higher demand and a dedicated consumer base. We derive a three-parameter contract that can coordinate the channel and arrive at a win-win situation for the manufacturer and the brick-and-mortar retailer. Our analysis shows that the contract is more beneficial for a brick-and-mortar retailer with lower relative market potential. Additionally, we find that the contract brings down the retail price of the product which benefits the end consumers. Collapse

Topics: electronic commerce decision making decision support price management supply chain management

Methods: theorem proofing mathematical model

Interdependency Analysis in Security Investment against Strategic Attacks

2020 | Information Systems Frontiers | Citations: 2

Authors: Ezhei, Mansooreh; Tork Ladani, Behrouz

Abstract: Information security investment is of high importance in management of IT infras ... Expand

Abstract: Information security investment is of high importance in management of IT infrastructure. There are many researches focused on game theoretical modeling and analysis of security investment of interdependent firms against potential security attacks. However, these studies usually are not concerned with dynamic and strategic nature of attacks which are increasingly important features of today’s cyber systems. Strategic attackers are those who are able to substitute their investments among targets over time by shifting investments towards poorly protected targets in order to obtain more potential financial gains. In this paper we try to analyze the effects of interdependency in security investment of firms against strategic attackers. Note that although there are a limited number of works that consider the strategic nature of attack, they model the defenders as a set of isolated nodes. Hence the positive externality caused by interconnection of the firms is not considered in these models. We consider both the attackers’ actual strategic behaviors (that causes negative externality via the possibility of substituting the target) as well as structural effects of the networked firms (that leads to positive externality via attack propagation). We propose a differential game among the networked firms in which attackers act strategically. In the proposed game, by employing a linear substitution model for characterizing the process of target selection by the attacker, the open-loop Nash solutions are highlighted in an analytical form. The analytical results show how interconnectivity between firms and the strategic behavior of the attacker determines the firms’ incentives for security investment. It is shown that overinvestment or underinvestment could occur depending on the degree of interdependency among the given firms. Accordingly we designed mechanisms to encourage the firms to invest at a socially optimal level. The achieved results in this paper helps security designers to better formulate their policies in tackling strategic attackers. Collapse

Topics: IT security threat data security security policy

Methods: literature study theorem proofing

Theories: game theory

From predictive to prescriptive analytics: A data-driven multi-item newsvendor model

2020 | Decision Support Systems | Citations: 0

Authors: Punia, Sushil; Singh, Surya Prakash; Madaan, Jitendra K.

Abstract: This paper considers a multi-item newsvendor problem with a capacity constraint ... Expand

Abstract: This paper considers a multi-item newsvendor problem with a capacity constraint (Z). The problem has already been addressed in the literature using the classical newsvendor problem. However, provided solutions made assumptions for demand distributions, which are often incorrect and led to errors in the inventory optimization. This research proposes a distribution-free and completely data-driven solution approach to Z. The proposed approach uses sample demand data as input, and machine (and deep) learning methods with empirical risk minimization principle to find order quantities. A heuristic is developed using hierarchies of the retail products to perform multi-item inventory optimization when a capacity constraint is active. The proposed approach is tested on a real-world dataset of retail products. The results from the proposed method are compared with data-driven max-min and empirical inventory optimization methods, and it outperformed all of them. The machine (and deep) learning-based demand forecasting methods (part of the proposed approach) providing better results than neural networks, multiple regression, arima, arimax, etc. Finally, a comparison of total inventory cost from the proposed, max-min, and empirical inventory optimization methods are carried out, and it is observed that the proposed data-driven approach leads to a significant reduction in inventory cost. Collapse

Topics: website

Methods: optimization model longitudinal research time series analysis computational algorithm autoregressive integrated moving average

Hotel selection using a modified TOPSIS-based decision support algorithm

2019 | Decision Support Systems | Citations: 0

Authors: Kwok, P. K.; Lau, Henry Y. K.

Abstract: While many studies pointed out that travellers often consider a basket of factor ... Expand

Abstract: While many studies pointed out that travellers often consider a basket of factors when they are selecting their accommodation, few online travel agency websites allow the travellers to actively express their preference about the selection criteria in order to receive tailor-made recommendations in return. The absence of this feature causes travellers to spend extra effort and time to compare the hotel options themselves. This paper presents a decision support algorithm, namely Vague Set TOPSIS, to help travellers to rank the hotel options. It was found in this research that the structure and assumptions of the conventional TOPSIS methods are not suitable for handling this decision problem. Therefore, this paper is novel in providing a foundational change to the conventional TOPSIS models such that it is more applicable to hotel selection. The validity of the proposed decision support algorithm was proved via three approaches, which are mathematical proofs, computer stochastic simulation experiments and a numerical case study using data obtained from Hotels.com. Collapse

Topics: decision support computer software website recommender system big data

Methods: trade-off analysis method TOPSIS experiment case study computational algorithm

Bidding Decisions with Nonequilibrium Strategic Thinking in Reverse Auctions

2019 | Group Decision and Negotiation | Citations: 0

Authors: Qian, Xiaohu; Fang, Shu-Cherng; Huang, Min; Nie, Tiantian; Wang, Xingwei

Abstract: This paper considers decisions of bidders with bounded rationality in different ... Expand

Abstract: This paper considers decisions of bidders with bounded rationality in different thinking levels for a first-price sealed-bid reverse auction. To characterize the nonequilibrium strategic thinking, we construct a mathematical model that incorporates the “level-k decision rule” to iteratively derive closed-form solutions. Then the effects of bidders’ heterogeneous beliefs of thinking levels on their bid prices and expected payoffs are investigated. We find that under some assumptions, bidders will exhibit oscillating behavior in their bid prices and expected profits in terms of thinking levels. When the thinking level tends to infinity, the bid prices and expected profits converge to those in the conventional analysis with perfectly rational bidders. An interesting finding from theoretical analysis verified by numerical experiments is that any bidder with a thinking level above two should bid according to level-2 bidder’s strategy to achieve the highest expected profit, and in this case the buyer will pay no more than level-2 bidder’s bid price. Collapse

Topics: decision making

Methods: experiment mathematical model descriptive statistic theorem proofing

Theories: theory of bounded rationality

Flexible, Efficient, and Secure Access Delegation in Cloud Computing

2019 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Xiong, Hu; Wang, Yi; Li, Wenchao; Chen, Chien-Ming

Abstract: The convenience of the cloud-assisted Internet of Things has led to the need for ... Expand

Abstract: The convenience of the cloud-assisted Internet of Things has led to the need for improved protections for the large volumes of data collected from devices around the world and stored on cloud-based servers. Proxy re-encryption (PRE) has been presented as a suitable mechanism for secure transmission and sharing of files within the cloud. However, existing PRE schemes do not support unidirectional data transformation, fine-grained controls, multiple hops, and identity-based encryption simultaneously. To solve these problems, we propose a unidirectional multi-hop identity based-conditional PRE scheme that meets all of the above requirements. Our proposal has the additional benefits of a constant ciphertext size, non-interactivity, and collusion resistance. We also prove that our scheme is secure against adaptive identity chosen-ciphertext attacks in the standard model. Collapse

Topics: data encryption cloud storage public key encryption privacy desktop computer

Methods: computational algorithm theorem proofing

Single-Sourcing Versus Multisourcing: The Roles of Output Verifiability on Task Modularity

2018 | Management Information Systems Quarterly | Citations: 0

Authors: Bhattacharya, Shantanu; Gupta, Alok; Hasija, Sameer

Abstract: This paper compares two modes for outsourcing the development of information ser ... Expand

Abstract: This paper compares two modes for outsourcing the development of information services projects: singlesourcing (where one vendor handles all outsourced activities) and multisourcing (where multiple vendors handle those activities). We assess the relative efficacy of these two outsourcing modes by identifying the effects of three factors: task modularity, the extent of alignment between a (verifiable) performance metric and project revenue, and the extent to which project revenue is itself verifiable. We find that if tasks are modular then multisourcing strictly dominates single-sourcing-provided the verifiable performance metric and project revenue are not completely aligned. Yet if tasks are integrated, then the choice of sourcing mode is more nuanced: the best choice depends on trade-offs among the alignment between performance metric and project revenue, the verifiability of project revenue, and moral hazard. If the verifiable performance metric and project revenue are perfectly aligned, or if project revenue is completely verifiable, then firms prefer single-sourcing because it entails less moral hazard than does multisourcing. Comparative statistics for the effects of task interdependence costs and vendors' risk aversion reveal that multisourcing (single-sourcing) should be preferred when there are interdependence costs (/when vendors are strongly risk averse). Collapse

Topics: outsourcing moral hazard task interdependence system quality project management

Methods: case study experiment descriptive statistic simulation theorem proofing

Theories: agency theory