Does the new entrant eat my pie or enlarge my pie? Market entry investigation in the online-to-offline on-demand context

2023 | Decision Support Systems | Citations: 0

Authors: Dai, Hongyan; Ta, La; Xu, Xun

Abstract: The facilitation of information technology has led to the rapid development of o ... Expand

Abstract: The facilitation of information technology has led to the rapid development of online-to-offline commerce, and this mode is attracting increasing businesses to enter the market. Its unique on-demand features affect con­ sumers’ shopping behaviors. This study uses a difference-in-difference approach with propensity score matching and machine learning approaches to examine the impact of a new giant online-to-offline entrant on consumers’ ordering and spending behavior. We find that overall, the new entrant has a negative impact on consumers’ ordering and spending from the perspective of existing providers. This negative impact is amplified if the con­ sumers are highly engaged on the platform. However, the new entrant effect is reduced if the providers use inhouse rather than outsourced deliverymen or consumers have a relatively long distance from the new entrant. Furthermore, the new entrant effect is altered if the platform implements technological innovation. On a provider level, the new entrant has a direct negative impact on consumers’ ordering and spending from homogenous providers; however, a positive spillover effect is observed in terms of increasing consumers’ spending on het­ erogeneous providers. The direct effect occurs immediately, while the spillover effect appears in a time-lagged pattern. On a product level, we find that the new entrant negatively affects consumers’ ordering and spending on substitute products also sold by the new entrant, but that their spending on non-substitute products is boosted. Our findings provide decision support for the new entrant and existing providers to expand the market to stimulate consumers’ purchase from both, to enhance their financial performance. Collapse

Topics: decision support digital innovation innovation management electronic commerce financial performance

Methods: experimental group k-means clustering machine learning computational algorithm Student's t-test

Does IT Enable Collusion or Competition: Examining the Effects of IT on Service Pricing in Multimarket Multihospital Systems

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Du, Kui; Tanriverdi, Hüseyin

Abstract: In the U.S., multihospital systems (MHSs) charge significantly higher prices fo ... Expand

Abstract: In the U.S., multihospital systems (MHSs) charge significantly higher prices for hospital services than stand-alone hospitals. Rivalry restraint theory suggests that MHS with multimarket contact (MMC) can tacitly collude and mutually forebear from price competition to keep their prices above competitive levels. We posit that the success of such MMC-induced rivalry restraints (the truce) is affected by two conflicting roles of IT at the corporate level and market unit levels, respectively. The corporate parent seeks to standardize IT applications enterprise-wide to coordinate market units as a means of jointly implementing the rivalry restraint strategy and keeping prices high enterprise-wide. However, market units, i.e., the member hospitals of MHS clustered in geographic patient markets, face competitive pressures to reduce their service costs. Market units seek to use differentiated IT applications to achieve cost reductions, which then fuel price competition in local markets, jeopardize the sustainability of the truce, and weaken the enterprise-wide price effects of the corporate parent's rivalry restraint strategy. In a longitudinal study of 195 multihospital systems in the U.S. in the 2005-2013 time period, we found support for these ideas. The corporate-wide standardization of the operational IT of MHS complements the rivalry restraint strategy to increase enterprise-wide prices. Market units' use of differentiated analytical IT reduces costs in local markets and weakens the price effects of the rivalry restraint strategy. The study advances IS research and practice by theorizing how the corporate-level and the market unit-level IT of a multi-unit, multimarket (MUMM) organization can have opposing moderating effects on the link between MMC and the average prices charged by the MUMM organization. Collapse

Topics: analytical information system operational information system database system health information system decision making

Methods: theory development robustness check instrumental variables estimation longitudinal research data modeling

Content Creators Between Platform Control and User Autonomy

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Hödl, Tatjana; Myrach, Thomas

Abstract: Content creators generate and upload content on social media platforms. If these ... Expand

Abstract: Content creators generate and upload content on social media platforms. If these platforms have a revenue-sharing policy, content creators earn income from advertising revenue. This income is heavily dependent on the distribution of the content and the resulting view counts. Platform owners may exert algorithmic control that impacts content distribution, advertising income, and, consequently, the behaviour of content creators. The objectives of the platform owners combined with the interests of the content creators may lead to paradoxical tensions between the aims of control and autonomy. The opaque nature of algorithms coupled with the need to be recognised by the algorithm further reinforces this phenomenon. This study follows an interpretive qualitative research approach applying grounded theory methodology. This research uses semi-structured interviews with content creators to develop a theory explaining the tension between control and autonomy on revenue-sharing social media platforms. The study shows that algorithmic control and incentivisation create paradoxical tensions that affect the autonomy of content creators. Content creators attempt to minimise tensions of algorithm versus audience, regularity versus scheduling autonomy, and analytics versus decision-making autonomy in two ways: through self-centred measures such as improving metrics, pre-production, and being a pioneer and extraneous measures involving their own businesses, products, and sponsorships. This study sheds some light on the phenomenon of paradoxical tensions and provides guidance and strategies for content creators and platform owners about proceeding with their relationship. This study’s findings provide platform owners and decision-makers with a deeper understanding of the behaviour of content creators and the hurdles they face in platform work. The findings help them identify challenges, draw conclusions, and implement changes. Collapse

Topics: social media YouTube Twitch advertising management price management

Methods: qualitative interview computational algorithm grounded theory theory development personal interview

MaCuDE IS Task Force Phase II Report: Views of Industry Leaders on Big Data Analytics and AI

2023 | Communications of the Association for Information Systems | Citations: 2

Authors: Lyytinen, Kalle; Topi, Heikki; Tang, Jing

Abstract: This paper represents the Phase II report of the Management Curriculum for the ... Expand

Abstract: This paper represents the Phase II report of the Management Curriculum for the Digital Era (MaCuDE) disciplinary task force on information systems (IS). Aligned with the current work of the AIS (Association for Information Systems) and ACM (Association for Computing Machinery), we focus on the current and future industry driven educational needs and requirements posed by big data analytics (BDA), artificial intelligence (AI), machine learning (ML), and related innovations. In this report, we probe and report on the views of industry leaders regarding BDA/AI education needs. We conducted 18 rich semi-structured interviews with a representative sample of industry leaders situated around key changes and issues related to workforce demands in digital transformation and associated educational needs. We performed a grounded theory based analysis of key themes in reported education needs. We note the shifting meaning of AI and BDA phenomena and identify three main organizational level needs for the digital eracapability improvement and transformation, decision-making strategies and tactics, and changes in operations or products -and connect them to three individual professional competencies necessary to deliver them: fundamental environmental competencies, data information and content, and system design competencies. Based on the analysis we outline several novel competency-based IS curriculum recommendations for the master's and undergraduate level IS education.Architecting for cloud: "And so the thing I noticed, a lot of these companies, when their data is growing so big and their database costs are running so high, they think about going towards Open Source Software, Open Source databases to store all the data and, hence, that creates a demand on the workforce to actually know how to use those. "Understanding data structures, architectures, and governance: "So that's his role, and the key requirement for that role again is Data Architecture, data Engineering and Data Management" Building and managing machine learning models: "Second, of course, is strong competency in the use of Machine Learning packages or models. This field is evolving aggressively." "For developing or programming our own AI solutions, our employees have no deep knowledge of mathematical models and how to build mature and value-creating AI applications." IS management and operations: "The talent sort of wars out there are really, really tough, and finding people who understand that, (how to) generate the data, use the data, think about the data, manipulate it are really, really important. I agree. It used to be you had to have people with Project Management. That was critical and that was everyone competed for that, and now it's that plus the data, the Machine Learning."Based on the data collected in this study, we cannot offer a clear answer to the questions of how BDA and AI affect areas that do not belong to the two main areas of the study. Given, however, how quickly BDA and AI have grown and how substantial related resource requirements are in organizations, it is clear that they already have an impact on several competency needs such as programming language selection, selection of BDA and AI tools based on cloud-based solutions, data architecture, data governance, service repertoires available on platform environments, and special characteristic of BDA and AI projects and how they affect education for project management needs and competencies. Summary of Findings Related to Individual CompetenciesGenerally, we observe a strong alignment and continuity between the recent information systems curriculum recommendations and the findings of this study. The data highlights the continued importance of IS core topics covered in all past curricula, such as data management, systems development, IT infrastructure and architecture (including security), and IS (project) management.The results also highlight also multiple areas that need more emphasis and careful design decisions when schools plan and implement their BDA and AI based programs: Integration of business and technology competencies in ways that allow seamless communication with both business and technology experts  A stronger emphasis on multiple life cycle models and concepts related to data management and data science than in the recent model curricula focused on system life cycles  Heightened focus on new dimensions of data analytics competencies (including communication-related elements such a storytelling and visualization)  The growing importance of ethics as a foundation for ensuring privacy and security of BDA and AI models  Need for more skills in statistics  Understanding the novel requirements that AI solutions set up for IT infrastructure  The importance of competencies in AI systems development and deployment. Collapse

Topics: artificial intelligence big data analytical information system data management decision making

Methods: qualitative interview machine learning meta learning field study personal interview

Dynamic Pricing on Two-Sided Platforms: Consequences on Customers’ Fairness Perceptions and Purchase Intentions

2023 | International Conference on Information Systems | Citations: 0

Authors: Röder, Andreas; Bohnen, Eva; Züllig, Kilian; Kupfer, Alexander; Zimmermann, Steffen

Abstract: ... Expand

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Topics: price management dynamic pricing ride sharing platform logistics management Airbnb

Methods: experiment statistical hypothesis test chi squared test survey parametric test

Theories: equity theory

Business model archetypes for data marketplaces in the automotive industry

2022 | Electronic Markets | Citations: 6

Authors: Bergman, Rômy; Abbas, Antragama Ewa; Jung, Sven; Werker, Claudia; de Reuver, Mark

Abstract: Policymakers and analysts are heavily promoting data marketplaces to foster data ... Expand

Abstract: Policymakers and analysts are heavily promoting data marketplaces to foster data trading between companies. Existing business model literature covers individually owned, multilateral data marketplaces. However, these particular types of data marketplaces hardly reach commercial exploitation. This paper develops business model archetypes for the full array of data marketplace types, ranging from private to independent ownership and from a hierarchical to a market orientation. Through exploratory interviews and case analyses, we create a business model taxonomy. Patterns in our taxonomy reveal four business model archetypes. We find that privately-owned data marketplaces with hierarchical orientation apply the aggregating data marketplace archetype. Consortium-owned data marketplaces apply the archetypes of aggregating data marketplace with additional brokering service and consulting data marketplace. Independently owned data marketplaces with market orientation apply the facilitating data marketplace archetype. Our results provide a basis for configurational theory that explains the performance of data marketplace business models. Our results also provide a basis for specifying boundary conditions for theory on data marketplace business models, as, for instance, the importance of network effects differs strongly between the archetypes. Collapse

Topics: business model value creation business-to-business network effect data quality

Methods: qualitative interview literature study archival research grounded theory personal interview

Theories: economic theory

The Diffusion, Impacts, Adoption and Usage of ICTs upon Society Mini-track Introduction

2022 | HICSS | Citations: 0

Authors: Choudrie, Jyoti; Kurnia, Sherah; Sundaram, David

Abstract: ... Expand

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Topics: technostress innovation management electronic commerce enterprise social network dynamic pricing

Methods: qualitative coding qualitative content analysis grounded theory case study

Greening the Cloud: A Load Balancing Mechanism to Optimize Cloud Computing Networks

2022 | Journal of Management Information Systems | Citations: 0

Authors: Kumar, Chetan; Marston, Sean; Sen, Ravi; Narisetty, Amar

Abstract: Approximately 55 percent of the world's 7.3 billion people access the Internet, ... Expand

Abstract: Approximately 55 percent of the world's 7.3 billion people access the Internet, creating a significant demand in information technology (IT) services for both organizations and consumers. The number of data centers continue to increase to meet this demand, consuming 2 percent of the energy produced worldwide. Many organizations moving towards cloud computing due to its ability to meet users' needs on demand. Greening cloud computing technology has become an important aspect of an organization's design and use of cloud computing. One aspect of greening the cloud is through efficiently using cloud-based resources. In this study, we focus on the resource allocation applications of cloud computing technologies to green an organizations cloud. We design a pricing and allocation mechanism for a private cloud computing service that allows the firm to effectively load balance their cloud computing resources. Our optimal pricing mechanism is a dynamic pricing model, which maximizes the net value of users in a private cloud computing service. Additionally, we create a job allocation algorithm based on our dynamic pricing model to load balance the cloud. We show that balancing the job allocation such that the number of jobs at individual resource servers as close to equal as possible is optimal. Furthermore, simulations were run on the allocation mechanism to examine the effects on the cloud resources while gaining insight to effectively distribution resources to public clouds. Our model can help organizations to efficiently distribute their cloud-based resources, which allows for a greener cloud computing system. Collapse

Topics: cloud computing price management resource allocation dynamic pricing peer-to-peer model

Methods: simulation computational algorithm mathematical model survey

Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness

2022 | European Journal of Information Systems | Citations: 0

Authors: Rana, Nripendra P.; Chatterjee, Sheshadri; Dwivedi, Yogesh K.; Akter, Shahriar

Abstract: The data-centric revolution generally celebrates the proliferation of business a ... Expand

Abstract: The data-centric revolution generally celebrates the proliferation of business analytics and AI in exploiting firm’s potential and success. However, there is a lack of research on how the unintended consequences of AI integrated business analytics (AI-BA) influence a firm’s overall competitive advantage. In this backdrop, this study aims to identify how factors, such as AI-BA opacity, suboptimal business decisions and perceived risk are responsible for a firm’s operational inefficiency and competitive disadvantage. Drawing on the resource-based view, dynamic capability view, and contingency theory, the proposed research model captures the components and effects of an AI-BA opacity on a firm’s risk environment and negative performance. The data were gathered from 355 operational, mid-level and senior managers from various service sectors across all different size organisations in India. The results indicated that lack of governance, poor data quality, and inefficient training of key employees led to an AI-BA opacity. It then triggers suboptimal business decisions and higher perceived risk resulting in operational inefficiency. The findings show that operational inefficiency significantly contributes to negative sales growth and employees’ dissatisfaction, which result in a competitive disadvantage for a firm. The findings also highlight the significant moderating effect of contingency plan in the nomological chain. Collapse

Topics: artificial intelligence data quality analytical information system competitive advantage explainable artificial intelligence

Methods: partial least squares path modeling survey partial least squares regression conceptual modelling theoretical contribution

Theories: contingency theory dynamic capabilities theory resource based view of the firm

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