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

Telepresence in live-stream shopping: An experimental study comparing Instagram and the metaverse

2023 | Electronic Markets | Citations: 0

Authors: Barta, Sergio; Gurrea, Raquel; Flavián, Carlos

Abstract: Advances in digital platforms allow influencers to use live shows to showcase pr ... Expand

Abstract: Advances in digital platforms allow influencers to use live shows to showcase products, which has given rise to live-stream shopping. Moreover, new communication forms have emerged, such as the metaverse. The social interactions that occur in these immersive environments foster influencer-follower interactions. This research compares the impact of live-stream shopping on followers’ experiences and behaviors on two communication channels (live shows on Instagram and in the metaverse) and analyses the moderating role of content involvement in telepresence. Data were collected in a between-subjects quasi-field experiment. Two scenarios that differed in degree of telepresence were created, a live show on Instagram and a live show in the metaverse. The results showed that telepresence is an important part of the user experience and in the success of live shows. Telepresence was seen to have a major influence on experiential value, but not on instrumental value. Both values provided followers with satisfaction with the experience. This satisfaction generated stickiness intention and intention to recommend the influencers’ live shows. The effect of telepresence on experiential value was greater for followers less involved with the influencer’s content. This research is pioneering in comparing an established platform, Instagram, with the metaverse. Despite the greater experiential value provided by the metaverse, to increase its instrumental value metaverse spaces needs to be further developed. Collapse

Topics: video conference virtual reality Instagram social network social media

Methods: survey field experiment statistical power analysis statistical hypothesis test experimental group

Theories: technology acceptance model

How to react to a shock? Effects of Airbnb hosts’ choices and market segmentation at the time of Covid-19

2023 | Information & Management | Citations: 0

Authors: Buzzacchi, Luigi; Milone, Francesco Luigi; Paolucci, Emilio; Raguseo, Elisabetta

Abstract: We investigate the way service providers who operate on an online peer-to-peer ( ... Expand

Abstract: We investigate the way service providers who operate on an online peer-to-peer (P2P) platform readapted their marketing choices to face the Covid-19 pandemic. Through an empirical investigation on a large dataset of Airbnb properties in Rome, observed from January 2018 to December 2020, we provide a threefold contribution by investigating how Airbnb hosts reacted to the Covid-19 pandemic shock, in terms of marketing choices, such as price adjustments and flexible cancellation policies; the direct effects of these choices on their economic returns; and how service providers on Airbnb reacted to address the new needs of their customers during the Covid-19 pandemic. The findings provide useful insights for researchers and practitioners and show that the adoption of combined marketing choices led to more than proportional effects on performances as it allowed Airbnb hosts to exploit profitable market segmentation mechanisms. Collapse

Topics: pandemic Airbnb marketing management price management peer-to-peer model

Methods: econometric modeling descriptive statistic instrumental variables estimation robustness check longitudinal research

Trust and deception with high stakes: Evidence from the friend or foe dataset

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Xunyu; Wang, Xinran; Spitzley, Lee; Nunamaker, Jay

Abstract: Many social interactions rely on the premise of mutual trust, but deception viol ... Expand

Abstract: Many social interactions rely on the premise of mutual trust, but deception violates trust and poses risk. Empirically examining trust and deception, particularly in high-stakes situations, is challenging but essential for improving the research realism and generalizability. To address this difficulty, we study trusting and deceptive behaviors in a high-stakes situation by using a novel dataset created from an American game show, Friend or Foe (FoF). In the show, a contestant's reward was determined through a trust game modified from the prisoner's dilemma. We explore how numerous human behaviors including facial expressions, gaze, head pose, body motion, language, and socio-demographic attributes, were related to a contestant's trusting or deceptive decision. Using a data-driven approach, we find that the deceivers' (contestants who chose Foe) behavior featured a neutralized face, negative facial emotions, enhanced upper body motion, and language with a lower sense of immediacy and agreeableness. The contestants who chose to trust (chose Friend) exhibited opposite behavioral patterns. Socio-demographic factors such as age, height, and facial attractiveness were also associated with a contestant's choice. Combining multimodal information, machine learning classifiers could predict the contes­ tant's choice with an accuracy about 25% greater than earlier reported human accuracy. We contribute to both trust and deception literature by examining the generalizability of trusting and deceptive behaviors to a new high-stakes scenario. We also add to the decision support literature by showing the superior predictive perfor­ mances of combining behavioral and socio-demographic features. Furthermore, we contribute to the academic community by introducing the FoF dataset. Collapse

Topics: decision support website YouTube Python decision making

Methods: meta analysis support vector machine correlation analysis descriptive statistic random forest classification

Continuance Intention of Mobile Payment: TTF Model with Trust in an African Context

2023 | Information Systems Frontiers | Citations: 0

Authors: Franque, Frank Bivar; Oliveira, Tiago; Tam, Carlos

Abstract: The use of mobile payment (m-payment) is growing exponentially in developing cou ... Expand

Abstract: The use of mobile payment (m-payment) is growing exponentially in developing countries. A small number of investigations have been undertaken on what makes people continue to use m-payment in an African context. We combine the task technology fit (TTF) model, expectation-confirmation model (ECM), and trust dimension to explain the influence of continuance use of m-payment. We collected 384 valid questionnaire responses from Mozambique. The results show that the relevant constructs to explain continuance intention are use, individual performance, overall trust, and the moderation role of satisfaction. Collapse

Topics: usage intention user satisfaction perceived usefulness mobile application mobile payment

Methods: survey partial least squares regression partial least squares path modeling Kolmogorov-Smirnov test mediation analysis

Theories: theory of task technology fit expectation confirmation theory theory of planned behavior diffusion of innovations theory technology acceptance model

Positive Demand Spillover of Popular App Adoption: Implications for Platform Owners’ Management of Complements

2023 | Information Systems Research | Citations: 0

Authors: Lee, Mi Hyun; Han, Sang Pil; Park, Sungho; Oh, Wonseok

Abstract: As platform owners interact with end users and complementors, their demand-side ... Expand

Abstract: As platform owners interact with end users and complementors, their demand-side characteristics and performance affect the overall value creation of ecosystems. This research investigated how the emergence of popular complements on a mobile communication platform impacts the usage of other complementary products by the platform’s end users and how platform owners can benefit from such demand spillovers. We identified two different forms of demand spillovers (i.e., backward and forward) and conceptualized how each subsequently affects platform expansion. On the basis of individual user-level app usage data, we empirically demonstrated how the presence of a popular app alters the demand structure of a platform through changes in the usage of other apps operating within it. The findings reveal that popular app adoption by users increases the number of apps used and the duration of app usage, excluding the usage of popular apps, only within the platform offering a popular app. These results support the existence of positive spillovers from popular complement adoption on a platform. Such positive within-platform spillovers are derived from both backward spillovers onto existing apps adopted before popular app adoption and forward spillovers onto new apps to be adopted after the uptake of favored apps. These patterns suggest that positive spillovers of popular app adoption occur through both the increased retrieval of existing apps and reduced uncertainty about newly released apps. Furthermore, forward spillover is considerably stronger than backward spillover, implying that platform owners can reap benefits by coordinating the launch of new complements and the promotion of less-known counterparts to end users with the emergence of a popular app. These results shed light on how platform owners can manage their complements and create value beyond direct contributions from popular complements. History: Yulin Fang, Senior Editor; Yan Huang, Associate Editor. Collapse

Topics: mobile application mobile game Android mobile platform operating system

Methods: experimental group regression analysis method propensity score method longitudinal research propensity score matching

Theories: theory of economic growth

Could Gamification Designs Enhance Online Learning Through Personalization? Lessons from a Field Experiment

2023 | Information Systems Research | Citations: 1

Authors: Leung, Alvin Chung Man; Santhanam, Radhika; Kwok, Ron Chi-Wai; Yue, Wei Thoo

Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As lear ... Expand

Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As learner autonomy is relatively high in online environments, learners must engage in self-regulated learning (SRL) to achieve optimal learning outcomes. Because most learners are unable to consistently engage in SRL, gamification interventions are being implemented to improve SRL engagement; however, mixed results cast doubt on the efficacy of this approach. Massively open online courses (MOOCs), a type of online learning environment, are currently experiencing rapid growth due to widespread adoption by many institutions. In MOOCs, there is no instructor intervention; hence, students have difficulty regulating their own learning and are easily distracted. Therefore, this study investigates whether mixed-research results regarding the efficacy of gamification can be attributed to lack of attention to individual learner traits during design. For this purpose, the study analyzes MOOCs as an instance of online learning by applying SRL theory and gamification principles. We altered a traditional MOOC platform to provide different types of gamified performance feedback to facilitate learners’ SRL engagement. We then examined whether this matched with goal orientation, an individual learner trait to influence SRL and learning outcomes. Using learning-analytics tools, we tracked 760 college students’ SRL engagement on a MOOC platform over five weeks. As theorized, SRL engagement and learning outcomes of participants who had a strong performance-avoidance goal orientation increased with positively framed performance feedback that involved no social comparisons; however, the same feedback had a negative impact on participants with a strong mastery goal orientation. Our findings add to SRL theory by demonstrating that gamification designs can enhance SRL engagement and learning outcomes in online learning, but with a caveat—this occurs only when there is a match with learner traits—confirming the gamification principle stating that task improvements and meaningful engagement can only occur through thoughtful gamification design.History: Raghu Santanam, Senior Editor; J. J. Hsieh, Associate Editor.Funding: Financial supported from the University Grants Committee’s (UGC’s) Special Grant for the Strategic Development of Virtual Teaching and Learning [Project Number 6430900], the UGC Teaching and Learning Funding [Project Numbers 6391211 and 6391001], and the Digital Innovation Laboratory of Department of Information Systems, City University of Hong Kong is gratefully acknowledged.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1123. Collapse

Topics: gamification online learning system electronic mail IT skill business intelligence

Methods: experimental group pilot experiment survey experiment digital trace data

Theories: learning theory

Design Principles for User Interfaces in AI-Based Decision Support Systems: The Case of Explainable Hate Speech Detection

2023 | Information Systems Frontiers | Citations: 0

Authors: Meske, Christian; Bunde, Enrico

Abstract: Hate speech in social media is an increasing problem that can negatively affect ... Expand

Abstract: Hate speech in social media is an increasing problem that can negatively affect individuals and society as a whole. Moderators on social media platforms need to be technologically supported to detect problematic content and react accordingly. In this article, we develop and discuss the design principles that are best suited for creating efficient user interfaces for decision support systems that use artificial intelligence (AI) to assist human moderators. We qualitatively and quantitatively evaluated various design options over three design cycles with a total of 641 participants. Besides measuring perceived ease of use, perceived usefulness, and intention to use, we also conducted an experiment to prove the significant influence of AI explainability on end users’ perceived cognitive efforts, perceived informativeness, mental model, and trustworthiness in AI. Finally, we tested the acquired design knowledge with software developers, who rated the reusability of the proposed design principles as high. Collapse

Topics: artificial intelligence explainable artificial intelligence perceived ease of use usage intention social media

Methods: design science experiment design principle survey qualitative content analysis

Status Regain and Validator Performance: Evidence from Blockchain Platform

2023 | International Conference on Information Systems | Citations: 0

Authors: Park, Sejun; Pinsonneault, Alain; Khern-am-nuai, Warut

Abstract: The paper examines the effects of providing validators with status on transacti ... Expand

Abstract: The paper examines the effects of providing validators with status on transaction verification performance in blockchains (e.g., Collapse

Topics: blockchain user experience corporate network security individual characteristic task productivity

Methods: experimental group longitudinal research difference in differences propensity score matching statistical hypothesis test

Theories: reinforcement theory

When Do Boards of Directors Contribute to Shareholder Value in Firms Targeted for Acquisition? A Group Information-Processing Perspective

2023 | Organization Science | Citations: 0

Authors: Pavićević, Stevo; Haleblian, Jerayr (John); Keil, Thomas

Abstract: We draw on group information-processing theory to investigate how target boards ... Expand

Abstract: We draw on group information-processing theory to investigate how target boards of directors may contribute to target value capture during the private negotiations phase in acquisitions. We view target boards as information-processing groups and private negotiations as information-processing tasks. We argue that target board meeting frequency is associated with increased processing—gathering, sharing, and analyzing—of acquisition-related information, which improves target bargaining and, ultimately, target value capture. We further posit that this value-enhancing effect of target board meeting frequency is more pronounced when target board composition improves the ability of target boards to process acquisition-related information. Finally, we expect that meeting frequency is more consequential for target bargaining and value capture when acquisition complexity imposes high information-processing demands on the target boards during private negotiations. Empirical evidence from a sample of acquisitions of publicly listed firms in the United States offers support for our group information-processing perspective on board contribution to shareholder value in firms targeted for acquisition. Funding: This work was supported by the Strategy Research Foundation [Dissertation Grant SRF-2015DP-0016]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1643. Collapse

Topics: value creation IT career database system task complexity task productivity

Methods: regression analysis method statistical hypothesis test longitudinal research ordinary least square Kolmogorov-Smirnov test

Theories: information processing theory