THE DARK SIDE OF DIGITAL PLATFORMS: UNDERSTANDING SMALL AND MEDIUM ENTERPRISES' DEPENDENCE ON THIRD-PARTY PLATFORMS

2023 | European Conference On Information Systems | Citations: 0

Authors: Asadullah, Ahmad; Faik, Isam; Lim, Shi Ying

Abstract: The digital platform business model has evolved and become a dominant form of e ... Expand

Abstract: The digital platform business model has evolved and become a dominant form of economic interaction worldwide. Small and medium enterprises (SMEs) had to shift their business to platforms to survive in this new market. While existing studies show the positive side of SMEs' use of platforms, there has been little research on the dark side of their participation in the platform economy, particularly their high dependence on platforms. We conducted a qualitative study to examine the mechanisms of dependence and its repercussions on SMEs' performance. Our findings suggest that SMEs' dependence on platforms arises from high importance, low discretion, and limited substitutability. We also find that, beyond their dependence on single platforms, SMEs generally become dependent on an oligopolistic system of dominant platforms. This dependence heightens the power asymmetry between platforms and SMEs. We highlight major manifestations of this power asymmetry, including the platform's ability to restrict access to resources and to prioritize different stakeholders' interests in their ecosystem. Collapse

Topics: electronic commerce digital platform business-to-consumer website electronic business

Methods: qualitative interview field study computational algorithm personal interview theory development

Theories: resource dependency theory

Information systems for sustainable remote workplaces

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Asatiani, Aleksandre; Norström, Livia

Abstract: This review discusses the challenges associated with the sustainability of remot ... Expand

Abstract: This review discusses the challenges associated with the sustainability of remote workplaces, which have become more prevalent due to the growing trend of work digitalization and the pandemic-induced push to remote work. These challenges are highlighted in literature across various disciplines, including information systems, but these discourses have remained isolated from each other. In this review, we consolidated and synthesized research on remote work from the perspective of individual workers by reviewing 187 articles published between 1999 and 2020 in recognized academic journals from fields including information systems, organizational studies, economics, human resources, sociology, and psychology. We identified five key themes that concern opportunities and challenges to sustainable remote workplaces: (1) key character­ istics, (2) work-life boundaries; (3) health and well-being; (4) social interaction, and (5) lead­ ership. Building on our findings we created a framework that recognizes two interrelated categories of factors influencing remote workplace sustainability – rigid base characteristics and contextual remote workplace variables – that together shape the trajectory of remote workplace sustainability in the long term. The framework also identifies the potential role of information systems in modulating the impact of the base characteristics to build continuities that encourage more sustainable remote workplaces. The paper concludes by offering a research agenda for in­ formation systems for sustainable remote workplaces based on the three IS theoretical frames: inclusion, dignity, and boundary objects. Collapse

Topics: remote work IT supported collaboration green IS pandemic task characteristic

Methods: literature sample literature study laboratory experiment journal ranking mixed method

Theories: boundary objects theory leader–member exchange theory

Seizing the Potential of Algorithms: The Power of Personalized Persuasive Messages on the Use of Algorithmic Advice

2023 | International Conference on Business Informatics | Citations: 0

Authors: Asbach, Simon; Graf-Vlachy, Lorenz; Fügener, Andreas

Abstract: Recommendations of algorithms are frequently superior to human judgment, but hu ... Expand

Abstract: Recommendations of algorithms are frequently superior to human judgment, but humans often fail to seize the full potential of algorithms. Research has made initial advances to increase the use of algorithmic advice, but achieved levels remain far from optimal. However, research has not yet considered user personality traits to develop interventions to increase the use of algorithms. We propose to communicate the algorithmic advice via a persuasive message that fits the user's regulatory focus, i.e., the tendency towards promotion-versus prevention focus, to create regulatory fit. To test our hypotheses, we conduct an experiment with a forecasting task and 605 participants. Results support a positive effect of a persuasive message on the use of algorithmic advice. Further, results do not support a regulatory fit effect. Our article adds to theory and practice by developing and empirically testing novel interventions to increase the use of algorithms. Next research steps are discussed. Collapse

Topics: personality

Methods: computational algorithm experiment survey statistical hypothesis test statistical power analysis

At What Price? Exploring the Potential and Challenges of Differentially Private Machine Learning for Healthcare

2023 | HICSS | Citations: 1

Authors: Aslan, Aycan; Matschak, Tizian; Greve, Maike; Trang, Simon; Kolbe, Lutz

Abstract: The increased generation of data has become one of the main drivers of technolog ... Expand

Abstract: The increased generation of data has become one of the main drivers of technological innovation in healthcare. This applies in particular to the adoption of Machine Learning models that are used to generate value from the growing available healthcare data. However, the increased processing of sensitive healthcare data comes with challenges in terms of data privacy. Differential privacy, the method of adding randomness to the data to increase privacy, has gained popularity in the last few years as a possible solution. However, while the addition of randomness increases privacy, it also reduces overall model performance, generating a privacy-utility trade-off. Examining this trade-off, we contribute to the literature by providing an empirical paper that experimentally evaluates two prominent and innovative methods of differentially private Machine Learning on medical image and text data to deepen the understanding of the existing potential and challenges of such methods for the healthcare domain. Collapse

Topics: privacy differential privacy healthcare data knowledge base data protection

Methods: experiment computational algorithm machine learning blood pressure PyTorch

Building Digital Trust to Protect Whistleblowers - A blockchain-based Reporting Channel

2023 | HICSS | Citations: 0

Authors: Asprion, Petra; Grieder, Hermann; Grimmberg, Frank; Moriggl, Pascal

Abstract: Organizations today need internal reporting channels to report illegal/unethical ... Expand

Abstract: Organizations today need internal reporting channels to report illegal/unethical misconduct. For this purpose, organizations set up one or more - often digital - internal reporting channels. Persons/Employees who want to report misconduct, so-called whistleblowers, expose themselves to reprisals and therefore need trustworthy reporting channels which ensure ´Digital Trust´. Blockchain, a technology that overcomes the need for trust due to its properties of immutability and integrity of data, could be promising as underlying technology for a digital reporting channel which is recognized as trustworthy. In our research, we explored multiple perspectives relevant to a trustworthy digital reporting system. Applying design science research, we evaluated the current state of the art of (digital) reporting channels and developed a prototypical blockchain-based reporting solution called “Integrity@Inside”. The prototype is being iteratively demonstrated and pre-evaluated. Collapse

Topics: blockchain electronic health privacy IT security usability

Methods: design artifact qualitative interview design process design science expert panel

Counterfactual Explanations for Incorrect Predictions Made by AI Models

2023 | International Conference on Information Systems | Citations: 0

Authors: Asrzad, Amir; Li, Xiaobai

Abstract: Advanced AI models are powerful in making accurate predictions for complex prob ... Expand

Abstract: Advanced AI models are powerful in making accurate predictions for complex problems. However, these models often operate as black boxes. This lack of interpretability poses significant challenges, especially in high-stakes applications such as finance, healthcare, and criminal justice. Explainable AI seeks to address the challenges by developing methods that can provide meaningful explanations for humans to understand. When black box models are used for prediction, they inevitably produce errors. It is important to appropriately explain incorrect predictions. This problem, however, has not been addressed in the literature. In this study, we propose a novel method to provide explanations for misclassified cases made by black box models. The proposed method takes a counterfactual explanation approach. It builds a decision tree to find the best counterfactual examples for explanations. Incorrect predictions are rectified using a trust score measure. We validate the proposed method in an evaluation study using real-world data. Collapse

Topics: artificial intelligence explainable artificial intelligence local interpretable model agnostic explanation decision making enterprise information system

Methods: machine learning decision tree classification literature study random forest classification experiment

The Role of Followers and Followees in the Adoption of Innovations

2023 | HICSS | Citations: 0

Authors: Atlas, M.; Gavious, A.; Ravid, G.

Abstract: An online social network is a key platform through which innovation diffuses. T ... Expand

Abstract: An online social network is a key platform through which innovation diffuses. To learn about innovativeness, we simultaneously investigate two Twitter networks, the relationships network, following-follower relationships, and the activity network, the flow of tweets. Specifically, the innovativeness relations to the networks' indegree and outdegree, the volume of platform use, and the profile's age. The more active and central the user, the earlier the adoption. Innovativeness increases with the number of followers only when at least several of them adopt the innovation. Surprisingly, having more followees is linked to later engagement with the innovation. This association is mediated by the number of adopters' followees. Those who created a Twitter profile later are also more likely to adopt innovations later. This study is novel in distinguishing between the two networks and analyzing their interactions. Its contribution lies in identifying the innovativeness of users in an online social network platform diffusion. Collapse

Topics: Twitter mindfulness social network innovation management user acceptance

Methods: descriptive statistic regression analysis method

Consumers’ Online Brand Attacking and Defending Under Ideological Polarisation: A Case of Cantopop Group “Mirror”

2023 | International Conference on Information Systems | Citations: 0

Authors: Au, Cheuk Hang; Chou, Chih-Yuan; Ho, Kevin

Abstract: This paper reports the preliminary findings of a netnographic case study that i ... Expand

Abstract: This paper reports the preliminary findings of a netnographic case study that investigates how online brand defending and attacking behaviours are influenced by ideological polarisation. Mirror, a Cantopop group from Hong Kong that pro-Beijing Internet users have targeted, has been selected as the subject of this study. Our preliminary findings show that online brand defending and attacking behaviours for or against a brand may be explained by a modified, looped Belief-Action-Outcome (BAO) framework under ideological polarisation, which complements existing research on Internet users' impact on brand management and sheds light on politically-driven online brand-attacking behaviours. Results also show that brand-attacking behaviours would further polarise, and thus de-stabilise society. We plan to collect and incorporate further data for more in-depth analyses for building a holistic model to explain the relationships of ideological polarisation on brand defending and attacking behaviours, and their impacts on business and organisation strategies. Collapse

Topics: internet technology online community filter bubble individual impact social media

Methods: qualitative coding case study triangulation theoretical contribution netnography

Women Mentoring Programs to Reduce the Gender Gap in IT Professions A Literature Review and Critical Reflection

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aufschläger, Lisa Theresia; Kusanke, Kristina; Witte, Anne-Katrin; Kendziorra, Jennifer; Winkler, Till

Abstract: Technical professions and industries remain heavily male-dominated. To countera ... Expand

Abstract: Technical professions and industries remain heavily male-dominated. To counteract this imbalance, measures are being taken, including mentoring programs for women. In this study, a literature review is conducted to answer the research question of how women's mentoring programs need to be designed in order to contribute to the reduction of the gender gap. The results of 13 empirical studies from 2013 to 2022 are analyzed and 21 factors influencing the design of women's mentoring programs are identified and grouped under three headings (relationship aspects, content-related aspects, and organizational aspects). On this basis, an exemplary women's mentoring program is discussed, the core of which consists of a hybrid e-mentoring program. While mentoring programs are considered helpful at the individual level, closing the gender gap at the structural level definitely needs more focus from both research and practice. Collapse

Topics: IT workforce database system

Methods: literature study meta analysis

The Interplay of InfoSec Mindfulness and Sanctions on Extra Role Security Behaviors: A Trait Activation Perspective

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Austin, Rebekah

Abstract: Organizational information security performance is inextricably tied to the sec ... Expand

Abstract: Organizational information security performance is inextricably tied to the security behavior of employees. While employee behavior has long been considered a challenge to information security, recent shifts to a more remote work force have amplified organizational focus on employees to protect information assets. Under these conditions, InfoSec Extra Role Behaviors (ERBs) have become increasingly important to mitigating security threats. The literature suggests that mindfulness is an important human factor that may lead to InfoSec ERBs. We examine mindfulness through the lens of trait activation theory. Trait activation theory (TAT) explicitly ties individual traits to situational features of the environment to predict trait related behavior. In TAT, a relevant feature of the organizational environment is situation strength which constrains behavioral variance through trait expression. Thus, we operationalize sanctions as a measure for situation strength in the InfoSec context and propose a model that examines the interplay between a relevant human factor, mindfulness, and a common organizational intervention, sanctions, and the impact that interplay has on InfoSec ERB enactment. Collapse

Topics: mindfulness ergonomics data security

Methods: survey