Organizing Entrepreneurial Teams: A Field Experiment on Autonomy over Choosing Teams and Ideas

2023 | Organization Science | Citations: 1

Authors: Boss, Viktoria; Dahlander, Linus; Ihl, Christoph; Jayaraman, Rajshri

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team pe ... Expand

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team performance. Yet, there are different types of autonomy, and they come at a cost. We shed light on whether two fundamental organizational design choices—granting teams autonomy to (1) choose project ideas to work on and (2) choose team members to work with—affect performance. We run a field experiment involving 939 students in a lean startup entrepreneurship course over 11 weeks. The aim is to disentangle the separate and joint effects of granting autonomy over choosing teams and choosing ideas compared with a baseline treatment with preassigned ideas and team members. We find that teams with autonomy over choosing either ideas or team members outperform teams in the baseline treatment as measured by pitch deck performance. The effect of choosing ideas is significantly stronger than the effect of choosing teams. However, the performance gains vanish for teams that are granted full autonomy over choosing both ideas and teams. This suggests the two forms of autonomy are substitutes. Causal mediation analysis reveals that the main effects of choosing ideas or teams can be partly explained by a better match of ideas with team members’ interests and prior network contacts among team members, respectively. Although homophily and lack of team diversity cannot explain the performance drop among teams with full autonomy, our results suggest that self-selected teams fall prey to overconfidence and complacency too early to fully exploit the potential of their chosen idea. We discuss the implications of these findings for research on organizational design, autonomy, and innovation.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The authors are grateful for funding from the Innovation Growth Laboratory, the Peter Curtius Foundation, and the Deutsche Forschungsgemeinschaft [Grant CRC TRR 190].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1520. Collapse

Topics: team productivity entrepreneurship missing data intrinsic motivation evaluation criteria

Methods: experiment experimental group survey causal mediation analysis field experiment

Does the sharing economy change conventional consumption modes?

2022 | International Journal of Information Management | Citations: 1

Authors: Fang, Yu-Hui; Li, Chia-Ying

Abstract: The development of peer-to-peer platforms has reduced the profitability of exist ... Expand

Abstract: The development of peer-to-peer platforms has reduced the profitability of existing business operations. How­ ever, relatively few studies have explored consumer switching between sharing economy platforms and existing business operations. By using the push–pull–mooring framework, this study explores the predictors that affect consumer switching between a third-party online travel agent (OTA) platform and Airbnb to understand spe­ cifically how push, pull, and mooring factors shape consumers’ switching behaviors. Data are collected from 347 users of third-party OTA platforms and Airbnb through an online questionnaire survey. Confirmatory factor analysis and structural equation modeling are performed using AMOS 24.0. The findings reveal that push factors (low structural assurance and low standardization), pull factors (monetary saving, sustainability, interactivity, and authenticity), and mooring factors (substitutability) positively influence switching behavior. Substitutability moderates the positive effects of push factors on switching behavior. This study contributes to the PPM frame­ work by identifying factors that influence consumers’ behavior of switching between a third-party OTA platform and Airbnb. In addition, this study is the first to consider substitutability and network externalities as mooring variables that facilitate switching by consumers. Airbnb and traditional hotels compete across various market segments, which results in substitutability as well as complementary relationships between them in some cities. Traditional business sections may also consider leveraging their strengths to distinguish themselves from new sharing economy services, thus delivering distinct value propositions to their consumers. This study provides reference that managers of third-party OTA platforms can use to differentiate their services from Airbnb and to maintain or increase profit by encouraging or discouraging switching among consumers. Collapse

Topics: Airbnb network effect sharing platform anonymity online community

Methods: survey structural equation modeling SEM tool chi squared test confirmatory factor analysis

Theories: push-pull-mooring theory

Can Platform Competition Drive Ratings Inflation? The Impact of Vertical Spillover Effects

2022 | International Conference on Information Systems | Citations: 0

Authors: Vorotyntseva, Yulia; Aaltonen, Aleksi; Kumar, Subodha; Pavlou, Paul

Abstract: The familiar 5-star ratings system is an important information source for consu ... Expand

Abstract: The familiar 5-star ratings system is an important information source for consumers deciding where to eat or what products to buy. Ideally, a retail platform owner should safeguard ratings against various biases, yet platform owners sometimes let average ratings become inflated. We study a situation in which a platform faces competition from another platform that offers the same items and, consequently, consumers may see different ratings for items across the platforms. Using a series of experiments in an online food ordering setting, we show that consumers are more likely to buy the item from a platform where it is rated higher. Therefore, a platform that offers lower but perhaps more accurate ratings risks hurting itself by not letting its ratings become inflated. We explain this by a vertical spillover effect by which diverging average ratings across platforms influence platform choice and discuss implications to platform owners, regulators, and consumers. Collapse

Topics: user interface usability pandemic digital platform consumer behavior

Methods: experiment Monte Carlo simulation Pearson's chi-squared test experimental design within subject experiment

Does Platform Competition Drive Ratings Inflation? The Impact of Vertical Spillover Effects

2022 | European Conference On Information Systems | Citations: 0

Authors: Vorotyntseva, Yulia; Aaltonen, Aleksi; Kumar, Subodha; Pavlou, Paul

Abstract: The familiar 5-star ratings system is an important information source for consu ... Expand

Abstract: The familiar 5-star ratings system is an important information source for consumers deciding where to eat or what products to buy. Ideally, a retail platform owner should safeguard ratings against various biases, yet platform owners sometimes let average ratings become inflated. We study a situation in which a platform faces competition from another platform that offer the same items and, consequently, consumers may see different ratings for items across the platforms. Using a series of experiments in an online food ordering setting, we show that consumers are more likely to buy the item from a platform where it is rated higher. Therefore, a platform that offers lower but perhaps more accurate ratings risks hurting itself by not letting its ratings become inflated. We explain this by a vertical spillover effect by which diverging ratings across platforms influence platform choice and discuss implications to platform owners, regulators, and consumers. Collapse

Topics: digital platform consumer behavior advertising management competitive advantage fake review

Methods: experiment experimental design survey Monte Carlo simulation Pearson's chi-squared test

In the same boat: social support in online peer groups for career counseling

2021 | Electronic Markets | Citations: 1

Authors: Felgenhauer, Annette; Kaufmann, Katharina; Klier, Julia; Klier, Mathias

Abstract: The success and growth of online peer groups has evoked interest in their potent ... Expand

Abstract: The success and growth of online peer groups has evoked interest in their potential to provide support for their members who share similar challenges. While there is a growing body of knowledge in this field, there is still a lack of understanding social support in online peer groups for career counseling, a prevention for youth unemployment. The unique dataset underlying our explorative study contains messages written by pupils in online peer groups for career counseling at the German Federal Employment Agency. Applying content analysis and logistic regression analysis we analyze which types of social support arise in the online peer groups depending on peers’ characteristics. We show that the online peer groups provide types of social support traditional one-on-one counseling cannot offer. Our analysis indicates that depending on peers’ gender and average school grade, the prevalence of the different types of social support changes. To a smaller extent this is also the case for differences in migration background. Our results contribute to a better understanding of social support in online peer groups for career counseling to address youth unemployment. Collapse

Topics: IT career logistics management individual characteristic social network social media

Methods: qualitative content analysis regression analysis method logistic regression descriptive statistic qualitative coding

Individual Rank and Response: Survey-Based Evidence on the Effects of Rank-Based Performance Feedback

2021 | HICSS | Citations: 0

Authors: Huschens, Martin; Ernst, Claus-Peter; Rothlauf, Franz

Abstract: Evidence suggests that rank-based performance feedback (RBPF) can influence work ... Expand

Abstract: Evidence suggests that rank-based performance feedback (RBPF) can influence workplace performance. Still, knowledge about the differential effects of RBPF on two central antecedents of employees’ performance — perceived pressure and individual goal-setting — is still sparse. We address these gaps by using a survey-based study and found that the effects of RBPF on individual goal-setting are positive for high, intermediate, and low performing individuals. However, these positive effects come with a price: Low performers who find themselves at the bottom of the ranking perceive their situation as more pressuring compared to a situation without ranking. Although these results point to a potential benefit, they also cast doubt on the implementation of rankings within the workplace. Collapse

Topics: Tencent QQ intrinsic motivation

Methods: survey experimental group parametric test Pearson's chi-squared test experiment

Developing a Taxonomy for Sustainable Digital Finance

2021 | International Conference on Information Systems | Citations: 3

Authors: Puschmann, Thomas; Shiba, Sayaka

Abstract: The financial system is currently being transformed by digitization and sustain ... Expand

Abstract: The financial system is currently being transformed by digitization and sustainability. However, existing research on the topic of sustainable digital finance, which bridges both areas, is still rare and a more comprehensive understanding of the domain is a missing component in existing research. Therefore, this paper develops a taxonomy based on a comprehensive literature analysis to structure this emerging field more precisely. The taxonomy includes a strategic, an organizational, a systems and a sustainability benefits perspective. The application of the taxonomy to 126 startups reveals that their solutions primarily focus on applications in the energy, financial services and government sector and their major focus is only on five of the seventeen SDGs, which shows a clear preference for climate, energy, infrastructure, cities, and partnerships as the primary goals. Surprisingly, the startups focus merely on operational efficiency optimization like improved processes rather than disruptive innovations in product or customer-related areas. Collapse

Topics: electronic finance business model green IS blockchain business process management

Methods: literature study test of association between categorical variables Pearson's chi-squared test design methodology literature sample

Factors Influencing Approval of Wikipedia Bots

2020 | HICSS | Citations: 0

Authors: Dalgali, Ayse; Crowston, Kevin

Abstract: Before a Wikipedia bot is allowed to edit, the operator of the bot must get appr ... Expand

Abstract: Before a Wikipedia bot is allowed to edit, the operator of the bot must get approval. The Bot Approvals Group (BAG), a committee of Wikipedia bot developers, users and editors, discusses each bot request to reach consensus regarding approval or denial. We examine factors related to approval of a bot by analyzing 100 bots’ project pages. The results suggest that usefulness, value-based decision making and the bot’s status (e.g., automatic or manual) are related to approval. This study may contribute to understanding decision making regarding the humanautomation boundary and may lead to developing more efficient bots. Collapse

Topics: decision making Wikipedia requirements analysis wiki website

Methods: topic model logistic regression Student's t-test statistical hypothesis test parametric test

Determinants and Success Factors of IT Outsourcing in the Public Sector

2020 | Communications of the Association for Information Systems | Citations: 1

Authors: Gantman, Sonia; Fedorowicz, Jane

Abstract: Public organizations often turn to the private sector for guidance and best prac ... Expand

Abstract: Public organizations often turn to the private sector for guidance and best practice examples when faced with technological or organizational change. However, private-sector business practices do not always translate neatly into the government domain. In this study, we analyze data from 82 collaborative projects in the public safety domain to establish whether public-sector IT outsourcing (ITO) practices match practices that researchers have documented in the private sector. In particular, we focus on the ITO decision process components and outcomes that they have identified as challenging for public-sector ITO. Results show that: 1) public organizations adopt ITO due to expertise gaps and cost considerations more than any other factor, 2) capital funding’s availability affects ITO decisions, 3) public-sector organizations outsource complex systems more often, 4) multiple successful ITO configurations exist, and 5) like the private sector, knowledge sharing and the vendor’s involvement in defining requirements represent important factors for whether ITO projects in public organizations succeed. Our descriptive, exploratory study extends previous ITO research by providing a framing for the fragmented literature on ITO in the public sector and laying a foundation for more systematic and theory-based scholarship. Our observations also guide governmental practitioners in their sourcing decisions. Collapse

Topics: outsourcing decision making knowledge sharing IS sourcing project management

Methods: qualitative interview survey Student's t-test qualitative comparative analysis computational algorithm

Mining Semantic Soft Factors for Credit Risk Evaluation in Peer-to-Peer Lending

2020 | Journal of Management Information Systems | Citations: 0

Authors: Wang, Zhao; Jiang, Cuiqing; Zhao, Huimin; Ding, Yong

Abstract: While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by h ... Expand

Abstract: While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by high credit risk due to information asymmetry. Besides conventional hard information, soft information also enters into the lending decision process. The descriptive loan texts submitted by borrowers have great potential for exploiting useful soft factors, but also pose great challenges due to the semantic sensitivity to context and the complexity of content representation. We propose a novel text mining method for automatically extracting semantic soft factors from descriptive loan texts. The method maps terms to an embedding space, assembles semantically related terms together into semantic cliques, and then defines semantic soft factors corresponding to the semantic cliques. Empirical evaluation shows that the extracted semantic soft factors contributed to significant improvement on credit risk evaluation in terms of both discrimination performance and granting performance. This work advances our knowledge of soft information indicative of a borrower's credit risk. Collapse

Topics: crowdsourcing peer-to-peer lending information retrieval peer-to-peer model missing data

Methods: machine learning computational algorithm classification method lasso regression natural language processing