Extended Generativity Theory on Digital Platforms

2023 | Information Systems Research | Citations: 2

Authors: Fürstenau, Daniel; Baiyere, Abayomi; Schewina, Kai; Schulte-Althoff, Matthias; Rothe, Hannes

Abstract: The assumption that generativity engenders unbounded growth has acquired an almo ... Expand

Abstract: The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth. History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor. Collapse

Topics: digital platform innovation management open source electronic commerce accounting

Methods: longitudinal research Granger causality time series analysis Student's t-test parametric test

The Impact of Strategic Core-Component Reuse on Product Life Cycles

2022 | Business & Information Systems Engineering | Citations: 0

Authors: Mihale-Wilson, Cristina; Felka, Patrick; Hinz, Oliver; Spann, Martin

Abstract: The mobile games business is an ever-increasing sub-sector of the entertainment ... Expand

Abstract: The mobile games business is an ever-increasing sub-sector of the entertainment industry. Due to its high profitability but also high risk and competitive atmosphere, game publishers need to develop strategies that allow them to release new products at a high rate, but without compromising the already short lifespan of the firms' existing games. Successful game publishers must enlarge their user base by continually releasing new and entertaining games, while simultaneously motivating the current user base of existing games to remain active for more extended periods. Since the core-component reuse strategy has proven successful in other software products, this study investigates the advantages and drawbacks of this strategy in mobile games. Drawing on the widely accepted Product Life Cycle concept, the study investigates whether the introduction of a new mobile game built with core-components of an existing mobile game curtails the incumbent's product life cycle. Based on real and granular data on the gaming activity of a popular mobile game, the authors find that by promoting multi-homing (i.e., by smartly interlinking the incumbent and new product with each other so that users start consuming both games in parallel), the core-component reuse strategy can prolong the lifespan of the incumbent game. Collapse

Topics: mobile game mobile system online game video game website

Methods: longitudinal research Dickey-Fuller-test quantitative observational study Mann Whitney U test nonparametric test

Professional Peer Support in Online Health Communities

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Sabzehzar, Amin; Mousavi, Reza; Raghu, T. S.

Abstract: This paper investigates whether and what kind of social support exchange in Pro ... Expand

Abstract: This paper investigates whether and what kind of social support exchange in Professional-only OnlineHealth Communities (POHC). Focusing on the recent fast-growing outbreak-Coronavirus Disease 2019 (COVID-19)-we find that healthcare professionals benefit from peer social support in POHCs, particularly by exchanging emotional support and learning from collective experience-based knowledge. Using the Reddit/r/medicine data, we show that posts' popularity varies depending on the authors' emotions and informativeness. In particular, a post's negative emotion and narrative tone have a significant and positive association with the post's popularity. These findings speak to the important role of POHC associated with healthcare professionals' integrity during the pandemic. Collapse

Topics: pandemic Reddit covid 19 social media application programming interface

Methods: longitudinal research robustness check natural language processing vector autoregression Dickey-Fuller-test

Moderating effects of business-systems corruption on corruption in basic national institutions and electronic government maturity: Insights from a dynamic panel data analysis

2021 | International Journal of Information Management | Citations: 0

Authors: Khan, Anupriya; Krishnan, Satish

Abstract: Corruption has emerged as a well-debated subject against the backdrop of electro ... Expand

Abstract: Corruption has emerged as a well-debated subject against the backdrop of electronic government (e-govern­ ment). While e-government has attained a level of sophistication in leading countries, there are countries for which going digital remains comparatively new on their national schedules. Their struggle and lag in reaching maturity in e-government can be attributed to corruption, which is an infamous issue prevalent across the globe and argued to impede technological innovation. Despite such a possibility, there is a paucity of research examining the “corruption–e-government” linkage. This study, hence, adopts the institutional perspective for conceptualizing corruption and seeks to understand the relationship of corruption in basic national institutions and national stakeholder service systems with e-government maturity. Specifically, by grounding the discussion on the agency theory, the rent-seeking theory, and the perspective of institutions as structures of cooperation and power, this study analyses the moderating influence of corruption in a national stakeholder service system (i.e., business systems) on the relationship of corruption in three basic national institutions (i.e., political, legal, and media) with e-government maturity in a country. The hypothesized relationships are empirically validated using a panel data of 94 countries, and the findings confirm that political corruption, legal corruption, and businesssystems corruption in a country play vital roles in influencing its e-government maturity. Implications of our results to research and practice are discussed. Collapse

Topics: government system enterprise information system innovation management knowledge base legal information system

Methods: longitudinal research autocorrelation analysis survey post-hoc analysis theory development

Theories: agency theory theory of economic growth game theory transaction cost economics public choice theory

The value of firm engagement: How do ratings benefit from managerial responses?

2021 | Decision Support Systems | Citations: 0

Authors: Sheng, Jie; Wang, Xiaojun; Amankwah-Amoah, Joseph

Abstract: This research explores firms’ digital presence in an online interactive network. ... Expand

Abstract: This research explores firms’ digital presence in an online interactive network. Anchored in the literature on firm engagement and firm-generated content, this study discusses and empirically examines the impact of managerial response to online reviews on future ratings. A big data approach coupled with text analytics is employed on a large field dataset to analyse both structured review/response metrics and unstructured response text. Results show that an increase in future review valence is positively associated with the intensity, promptness, and sentiment of managerial responses, and the magnitude of effects is contingent upon firms’ rating status and market position. Mixed evidence is obtained for comprehensiveness and standardisation of response content. These findings reveal that the influence of firm engagement in the online review network is likely to be shaped by the goodwill signalled by managerial responses. Collapse

Topics: online review website online word of mouth word of mouth user-generated content

Methods: machine learning support vector machine longitudinal research hierarchical linear modeling chi squared test

The Influence of Design Updates on Users: the Case of Snapchat

2019 | HICSS | Citations: 0

Authors: Franzmann, Daniel; Fischer, Lukas; Holten, Roland

Abstract: Today’s smartphone apps are regularly updated and enhanced through software upda ... Expand

Abstract: Today’s smartphone apps are regularly updated and enhanced through software updates. The case at hand is the popular social multimedia messaging app Snapchat that released a design overhaul in February 2018. While the update neither changed any features nor caused any relevant bugs or crashes, it led to an uproar of Snapchat’s users and significantly decreased its app store ratings and consequently revenue. As a result, Snap Inc., the company behind Snapchat, was forced to reverse design changes to appease their users. The initial adverse effects of the update were surprising; however, after using difference-in-difference tests in combination with sentiment analysis, our results indicate that design updates can be perceived negatively by users. We contribute to IS literature by evaluating the effect of design changes and the role of perceived ease of use in the post-adoption stage. Collapse

Topics: Snapchat mobile application market mobile application digital distribution perceived ease of use

Methods: natural language processing sentiment analysis parametric test longitudinal research Student's t-test

Arousal, valence, and volume: how the influence of online review characteristics differs with respect to utilitarian and hedonic products

2019 | European Journal of Information Systems | Citations: 13

Authors: Ren, Jie; Nickerson, Jeffrey V.

Abstract: Online reviews influence consumers’ purchase decisions. Product type – specifica ... Expand

Abstract: Online reviews influence consumers’ purchase decisions. Product type – specifically, whether a product is utilitarian or hedonic – can help explain how consumers react to reviews. Characteristics of reviews – in particular, valence, measured by ratings, the arousal level of the language used in the text and the volume of the reviews – provide heuristics that consumers may use in making purchase decisions. Product type moderates the effect of these characteristics. Empirical evidence for this claim comes from multiple sources: a panel data analysis of 26,357 Amazon products and an online experiment with 541 participants. The findings of studies based on this evidence show that product type (hedonic or utilitarian) moderates the effect of the three heuristic attributes of online reviews (valence, volume, and arousal) on sales. The analysis uses OLS-fixed effects models and Granger causality tests. These findings explain why past studies have found that sometimes online review valence is more influential than volume and arousal with respect to sales and why sometimes this is reversed. Our findings have significant theoretical and practical implications for the design of choice architectures in online review systems. Collapse

Topics: online review user-generated content decision making consumer behavior

Methods: experiment Granger causality longitudinal research robustness check time series analysis

An empirical study on predicting cloud incidents

2019 | International Journal of Information Management | Citations: 1

Authors: Roumani, Yaman; Nwankpa, Joseph K.

Abstract: With the increasing rate of adoption and growth of cloud computing services, bus ... Expand

Abstract: With the increasing rate of adoption and growth of cloud computing services, businesses have been shifting their information technology (IT) infrastructure to the cloud. Although cloud vendors promise high availability and reliability of their cloud services, cloud-related incidents involving outages and service disruptions remain a challenge. Understanding cloud incidents and the ability to predict them would be helpful in deciding how to manage and circumvent future incidents. In this study, we propose a hybrid model that employs machine learning and time series methods to forecast cloud incidents. We evaluate the proposed model using a sample of 2261 incidents collected from two cloud providers namely, Netflix and Hulu. Unique to this study is that our model relies solely on historical data that is independent of the underlying cloud infrastructure. Results suggest that the proposed hybrid model outperforms individual forecasting models: neural network, time series and random forest. Results also reveal important temporal insights from the proposed model and highlights the practical relevance of historical data to forecast and manage cloud incidents. Collapse

Topics: cloud computing digital service Hulu Netflix IT manager

Methods: autoregressive integrated moving average longitudinal research time series analysis artificial neural network machine learning

Prognostic Model Development with Missing Labels: A Condition-Based Maintenance Approach Using Machine Learning

2019 | Business & Information Systems Engineering | Citations: 0

Authors: Zschech, Patrick; Heinrich, Kai; Bink, Raphael; Neufeld, Janis S.

Abstract: Condition-based maintenance (CBM) has emerged as a proactive strategy for deter ... Expand

Abstract: Condition-based maintenance (CBM) has emerged as a proactive strategy for determining the best time for maintenance activities. In this paper, a case of a milling process with imperfect maintenance at a German automotive manufacturer is considered. Its major challenge is that only data with missing labels are available, which does not provide a sufficient basis for classical prognostic maintenance models. To overcome this shortcoming, a data science study is carried out that combines several analytical methods, especially from the field of machine learning (ML). These include time-domain and time-frequency domain techniques for feature extraction, agglomerative hierarchical clustering and time series clustering for unsupervised pattern detection, as well as a recurrent neural network for prognostic model training. With the approach developed, it is possible to replace decisions that were made based on subjective criteria with data-driven decisions to increase the tool life of the milling machines. The solution can be employed beyond the presented case to similar maintenance scenarios as the basis for decision support and prognostic model development. Moreover, it helps to further close the gap between ML research and the practical implementation of CBM. Collapse

Topics: decision support decision making

Methods: cluster analysis hierarchical clustering computational algorithm descriptive statistic longitudinal research

Free Versus for-a-Fee: The Impact of a Paywall on the Pattern and Effectiveness of Word-of-Mouth Via Social Media

2016 | Management Information Systems Quarterly | Citations: 0

Authors: Oh, Hyelim; Animesh, Animesh; Pinsonneault, Alain

Abstract: Information goods providers such as print newspapers are experimenting with diff ... Expand

Abstract: Information goods providers such as print newspapers are experimenting with different pricing models for their online content. Despite research on the topic, it is still not clear how information pricing strategy influences word-of-mouth (WOM) via social media, which has become a dominant channel for raising awareness about a newspaper's articles and attracting new visitors to its website. Using The New York Times' paywall rollout as a natural experiment, our study examines how the implementation of paywall by a firm (i.e., a shift from free to for-a-fee) influences the pattern and effectiveness of online WOM in social media. Our results indicate that implementing a paywall (i.e., charging for content that was earlier available for free) has a disproportionate impact on WOM for popular and niche articles, creating a longer tail in the WOM (i.e., content sharing) distribution. Further, we find that the impact of WOM on the NYT's website traffic weakens significantly after the introduction of a paywall. These results show that a paywall has implications for product and promotion strategies. The study offers novel and important implications for the theory and practice of strategic use of social media and paywall. Collapse

Topics: paywall website Twitter online word of mouth price management

Methods: experimental group natural experiment longitudinal research literature sample descriptive statistic

Theories: economic search theory