Single-Sourcing vs. Multisourcing: An Empirical Analysis of Large Information Technology Outsourcing Arrangements

2023 | Information Systems Research | Citations: 0

Authors: Bapna, Ravi; Gupta, Alok; Ray, Gautam; Singh, Shweta

Abstract: As the information technology (IT) services landscape matures, clients are incre ... Expand

Abstract: As the information technology (IT) services landscape matures, clients are increasingly adopting multisourcing arrangements that involve multiple vendors. Although a large body of information systems (IS) literature addresses issues of whether to outsource (to a single vendor), what types of contracts to use, and how to achieve optimal relational governance, little is known about the antecedents and consequents of the single versus multisourcing decision. Moreover, while conceptual and analytical models of single-sourcing versus multisourcing have been developed, there is no empirical IS research using a large-scale data set with rigorous econometric analysis that examines the antecedents and consequents of multisourcing in the IT context. This paper fills this void, using the transaction cost economic lens and a data set of 49,057 large IT outsourcing arrangements that spans multiple industries and dates back 25 years. We find that there is a curvilinear relationship between number of IT services in an IT outsourcing arrangement and the likelihood of multisourcing. This relationship increases as the number of IT services increases to up to five services and then decreases. For managers who plan to multisource IT outsourcing arrangements, this research provides guidance to minimize exchange hazards through a better understanding of the relationship between sourcing choice, client IT outsourcing capabilities, the competitiveness of the vendor landscape, and the number of IT services in an IT outsourcing arrangement. We provide empirical evidence that the choice between single-sourcing and multisourcing is material to the performance of outsourcing contracts as an incorrect sourcing choice is likely to result in negative contract outcomes. History: Paul A. Pavlou, Senior Editor; Ning Su, Associate Editor. Collapse

Topics: outsourcing system integration IS management service desk data center

Methods: XGBoost robustness check machine learning k-nearest neighbor statistical hypothesis test

Theories: transaction cost economics game theory

Someone Else to Blame: The Effectiveness of Egocentric and Alter-Centric Impression Management Tactics in the U.S. Food Retail Industry

2023 | Organization Science | Citations: 0

Authors: Diestre, Luis; Montauti, Martina; Pinto de Sousa, Helena

Abstract: We investigate the effectiveness of two types of impression management tactics i ... Expand

Abstract: We investigate the effectiveness of two types of impression management tactics implemented around negative attributes: egocentric (claiming the absence or low presence of a negative attribute in a focal organization) and alter-centric tactics (claiming the greater presence of a negative attribute in an organization’s competitor). We claim that the effectiveness of each tactic depends on the risk of audiences’ skepticism, which stems from the incongruence between the information conveyed in the tactic and audiences’ default expectations about the presence of the attribute among members of a given market segment. Audiences expect a conspicuous presence of the attribute, we propose, the more stakeholders contest a market segment for that very attribute. Thus, we advance that egocentric (alter-centric) tactics are less likely to be effective for contested (uncontested) attributes because the information conveyed in such tactics clashes with audiences’ default expectations, triggering skepticism. We find support for our predictions looking at the impact of nutrient content claims on product sales in the U.S. food retail industry between 2006 and 2015. Funding: H. Pinto de Sousa acknowledges the support, in the form of a research scholarship, granted by the Portuguese Foundation for Science and Technology (Fundação para a Ciência e Tecnologia), under the European Social Fund and the Human Capital Operational Program (Programa Operacional Capital Humano) funding program [Grant SFRH/BD/128536/2017]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1612. Collapse

Topics: database system marketing management Twitter social influence sensemaking

Methods: experimental group survey descriptive statistic statistical hypothesis test probit regression

Green Data Analytics of Supercomputing from Massive Sensor Networks: Does Workload Distribution Matter?

2023 | Information Systems Research | Citations: 0

Authors: Guo, Zhiling; Li, Jin; Ramesh, Ram

Abstract: Energy costs represent a significant share of the total cost of ownership in hig ... Expand

Abstract: Energy costs represent a significant share of the total cost of ownership in high-performance computing (HPC) systems. Using a unique data set collected by massive sensor networks in a petascale national supercomputing center, we first present an explanatory model to identify key factors that affect energy consumption in supercomputing. Our analytic results show that, not only does computing node utilization significantly affect energy consumption, workload distribution among the nodes also has significant effects and could effectively be leveraged to improve energy efficiency. Next, we establish the high model performance using in-sample and out-of-sample analyses. We then develop prescriptive models for energy-optimal runtime workload management and extend the models to consider energy consumption and job performance tradeoffs. Specifically, we present four dynamic resource management methodologies (packing, load balancing, threshold-based switching, and energy optimization), model their application at two levels (purely within-rack and jointly cross-rack resource allocation), and explore runtime resource redistribution policies for jobs under the emergent principle of computational steering and comparatively evaluate strategies that use computational steering with those that do not. Our experimental studies show that packing is preferred when the total workload of a rack is higher than a threshold and load balancing is preferred when it is lower. These results lead to a threshold strategy that yields near-optimal energy efficiency under all workload conditions. We further calibrate the energy-optimal resource allocations over the full range of workloads and present a bicriteria evaluation to consider energy consumption and job performance tradeoffs. We demonstrate significant energy savings of our proposed strategies under various workload conditions. We conclude with implementation guidelines and policy insights into energy-efficient computing resource management in large supercomputing data centers. History: Olivia Liu Sheng, Senior Editor; Xiaobai Li, Associate Editor. Funding: The authors thank the National Supercomputing Center of Singapore for enabling and supporting this research. J. Li received support from the National Natural Science Foundation of China [Grants 71901169, 72032006, and T2293774]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2023.1208. Collapse

Topics: data center high-performance computing task productivity resource allocation analytical information system

Methods: optimization model experiment simulation descriptive statistic longitudinal research

Model-Based Cybersecurity Analysis

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Jiang, Yuning; Jeusfeld, Manfred A.; Ding, Jianguo; Sandahl, Elin

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical co ... Expand

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid. Collapse

Topics: IT security virtualization technology database system knowledge representation data center

Methods: reference modelling case study qualitative interview design artifact simulation

Pollution-reducing and pollution-generating effects of the metaverse

2023 | International Journal of Information Management | Citations: 0

Authors: Kshetri, Nir; Dwivedi, Yogesh K.

Abstract: Different metaverse applications vary widely in terms of their carbon footprints ... Expand

Abstract: Different metaverse applications vary widely in terms of their carbon footprints and environmental impacts. In general, leisure and enjoyment activities of the consumer metaverse has adverse energy and environmental consequences. Many industrial metaverse applications, on the other hand, are likely to have a positive envi­ ronmental impact. This editorial analyzes the current stage of development patterns and use of different meta­ verse applications and critically evaluates the pollution-generating and pollution-reducing effects of the metaverse. Collapse

Topics: virtual reality data center

Improving Information Systems Sustainability by Applying Machine Learning to Detect and Reduce Data Waste

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Savarimuthu, Bastin Tony Roy; Corbett, Jacqueline; Yasir, Muhammad; Lakshmi, Vijaya

Abstract: Big data are key building blocks for creating information value. However, infor ... Expand

Abstract: Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem. Collapse

Topics: mobile application online review Python data management Google+

Methods: deep learning product review computational algorithm design artifact RoBERTa

Availability-Aware Virtual Resource Provisioning for Infrastructure Service Agreements in the Cloud

2023 | Information Systems Frontiers | Citations: 0

Authors: Yuan, Shuai; Das, Sanjukta; Ramesh, Ram; Qiao, Chunming

Abstract: Service availability is a key construct in Service Level Agreements (SLA) betwee ... Expand

Abstract: Service availability is a key construct in Service Level Agreements (SLA) between a cloud service provider and a client. The provider typically allocates backup resources to mitigate the risk of violating the SLA-specified uptime guarantee. However, initial backups may need to be adjusted in response to real-time failure and recovery events. In this study, we first develop a recurrent intervention at fixed intervals (RIFI) strategy that allows the provider to adjust the allocation of backup resources such that the expected total cost is minimized. Next, we focus on the limit to number of interventions, starting from single intervention strategy, as frequent reallocations may be operationally disruptive. Particularly, we provide a cost minimization approach to guide the service providers in their virtual resources management, and a specific downtime minimization approach for more mission-critical applications as a more aggressive alternative. We present computational results exploring the impact of intervention on the likelihood of SLA violation for the rest of the contract period, and evaluate parameters such as time and quantum of resource level adjustment, penalty levels desired by clients, and their influences on the backup resource provisioning strategies. We also validate our models through the analysis of use cases from Amazon Elastic Compute Cloud. Finally, we summarize this study by providing key practical managerial implications for resource deployment in the availability-aware cloud. Collapse

Topics: backup cloud computing resource allocation price management high-performance computing

Methods: computational algorithm experiment literature study simulation

The Impact of the COVID-19 on Online Food Delivery Service: Evidence from China

2023 | International Conference on Information Systems | Citations: 0

Authors: Zhao, Hongying; Liu, Luning

Abstract: The COVID-19 has had a profound effect on society as a whole. To examine the ef ... Expand

Abstract: The COVID-19 has had a profound effect on society as a whole. To examine the effect of the COVID-19 on online food delivery services, we collected sales data from a large online food delivery platform in 195 Chinese cities from November 2019 to July 2020. Interrupted time series analysis and time-varying difference-in-difference methods were used to estimate the impact of the COVID-19 and city lockdown policies on online food delivery services. The COVID-19 had a considerable negative effect on the online food delivery services. Lockdown policies caused further disruptions. As the pandemic and lockdown policies ended, the negative impacts dissipated. This finding reflected digital channels' resilience to the catering industry during the pandemic and helped it withstand its impact. There were significant differences among urban characteristics. The government can formulate relevant policies to deal with potential public health risks in the future based on these findings. Collapse

Topics: pandemic website missing data consumer behavior data center

Methods: longitudinal research regression analysis method time series analysis meta analysis experimental group

Theories: theory of economic development

Information Technology Investment and Carbon Intensity in the Era of Cloud Computing: A Cross-National Study

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Dedrick, Jason; Kim, Jooho; Park, Jiyong

Abstract: To tackle climate change in the digital economy, there has been increasing atte ... Expand

Abstract: To tackle climate change in the digital economy, there has been increasing attention to the role of information technology (IT) investment in decoupling economic growth from greenhouse gas emissions, or reducing carbon intensity. This research examines the impact of cloud computing on carbon intensity and further scrutinizes how the advent of cloud computing has altered the relationship between IT capital and carbon intensity. We combine data on IT capital stock for 51 countries during 1995-2014 with a natural experiment involving the staggered launches of cloud data centers across countries. Our preliminary findings suggest that cloud on-ramps availability is positively associated with carbon intensity, whereas it negatively moderates the impact of IT capital on carbon intensity. Taken together, our preliminary evidence implies that the environmental impact of cloud computing may not be as adverse as conjectured if we factor in its indirect effect on making overall IT capital greener. Collapse

Topics: cloud computing data center IT investment cloud computing provider environmental sustainability

Methods: natural experiment longitudinal research experimental design experimental group

Theories: theory of economic growth

Take Your Time? How Activity Timing Affects Organizational Learning and Performance Outcomes

2022 | Organization Science | Citations: 0

Authors: Desai, Vinit; Madsen, Peter

Abstract: Organizational learning theory has long examined how organizations learn to perf ... Expand

Abstract: Organizational learning theory has long examined how organizations learn to perform better as they accumulate experience. Although experience accumulation is inherently related to the timing of the repeated activities carried out by an organization, the direct relationship between activity timing and organizational learning has not been examined explicitly in the literature and remains an open question. Organizational learning theory contains two competing perspectives on how timing should impact learning—one suggesting that iterating faster is better for learning and one suggesting that taking more time between iterations is more helpful. Here, we reconcile these perspectives and develop a theory about the boundary conditions between them, arguing that, in general, iterating more rapidly enhances learning but that iterations of novel or complex activities, or ones following recent failure, benefit from a slower pace. We conduct tests of this theoretical perspective using data from the entire history of the orbital satellite launch industry from 1957–2017, and we find broad support for our theory and hypotheses. Collapse

Topics: organization learning accounting data center logistics management business process management

Methods: instrumental variables estimation regression analysis method descriptive statistic theory development robustness check

Theories: learning theory organizational knowledge creation organizational learning theory