How to Compensate After a Data Breach? Investigating Compensation Types and Role of Fairness in Customer Repatronage Intentions

2023 | ACM SIGMIS Database | Citations: 0

Authors: Mohammed, Zareef A.; Tejay, Gurvirender P.

Abstract: Data breach recovery is often likened to service failure recovery. Like service ... Expand

Abstract: Data breach recovery is often likened to service failure recovery. Like service failure recovery, compensation is a major factor toward data breach recovery. However, compensation involves different types, which may have varying effects on data breach recovery. This study investigates the effect of compensation types on customer's repatronage intentions to organizations that have suffered a data breach. Three compensation types were identified in this study: monetary, service, and psychological compensation. The findings of this study indicate that only service and psychological compensation have a significant effect on customers' perceptions of being treated fairly by the organization following a data breach. Furthermore, service compensation impacts the trust a customer regains in the company. Monetary compensation did not play a statistically significant role in the data breach recovery process. In turn, both perceived fairness and regained trust influences customer repatronage intentions. This study contributes to the information privacy field by identifying the types of compensation that are impactful to re-engage individuals who suffered PII related data breach. Collapse

Topics: data breach privacy service quality electronic commerce word of mouth

Methods: survey statistical power analysis partial least squares path modeling factor analysis data transformation

Theories: social exchange theory organizational justice theory justice theory

Cooperation with Strangers: Spillover of Community Norms

2023 | Organization Science | Citations: 1

Authors: Molina, Mario; Nee, Victor; Holm, Hakan

Abstract: Why do leaders of organizations cooperate with players with whom they may never ... Expand

Abstract: Why do leaders of organizations cooperate with players with whom they may never transact again? Such transactions can involve the incentives to exploit the other party because these interactions are not recurrent or embedded in networks. Yet, in a market economy, organizational actors learn to cooperate with strangers; otherwise, they risk closure from new ideas and business opportunities outside of their local community. With a large random sample of CEOs of manufacturing firms in the Yangzi River Delta region of China, we measured social norms using vignettes that describe hypothetical situations illustrating the social mechanisms of norm enforcement in respondents’ local communities. Several years later, in a laboratory-in-the-field experiment, we asked the same participants to play a one-shot Prisoner’s Dilemma (PD) game with a complete stranger. Our findings suggest that belief in the reliability of robust norm enforcement is positively associated with a higher probability of cooperation with strangers. To our knowledge, this mixed-method study is the first to explore the relationship between social norms and cooperation with strangers using a large sample of leaders of organizations outside the environment of the laboratory. Finally, to explore the generalizability of our behavioral findings, we experimentally manipulated norm vignettes and study the PD game in online experiments with managers in the Yangzi River Delta region.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: V. Nee gratefully acknowledges funding for research from the John Templeton Foundation (2005-2009 and 2015-2018), and from the College of Arts and Sciences at Cornell University. H. Holm thanks the Jan Wallander’s and Tom Hedelius’ Foundation for funding lab-in-the-field behavioral game.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1521. Collapse

Topics: social norm crowdsourcing website organization structure organizational success

Methods: experiment survey logistic regression statistical power analysis simulation

Theories: prisoner's dilemma organizational behavior theory

Digitizing local search: An empirical analysis of mobile search behavior in offline shopping

2023 | Decision Support Systems | Citations: 0

Authors: Molitor, Dominik; Daurer, Stephan; Spann, Martin; Manchanda, Puneet

Abstract: Mobile devices have become increasingly prevalent in the context of consumers’ o ... Expand

Abstract: Mobile devices have become increasingly prevalent in the context of consumers’ offline search and shopping behavior by acting as personal decision support tools. This paper investigates the relationship between con­ sumers’ real-time location and their search behavior when shopping offline. We develop two location-specific measures based on mobile device usage to analyze the association between a consumer’s real-time location and their search behavior: Present store distance and present store density. We apply these measures to a unique dataset from a leading mobile product information app that includes >13 million search sessions from 2.5 million consumers searching for 1.8 million different products. Our findings show that store distance and store density significantly influence consumers’ mobile search behavior: detailed searches for product-specific attributes (search depth) increase as store distance decreases and store density increases, while the number of jointly searched products within the same category (search breadth) increases as store distance and density increase. We also find that durable products weaken the main effects of store distance and density on search depth but strengthen it for search breadth. These results provide insights for offline retailers to better understand locationspecific consumer demands and improve their mobile in-app targeting and product assortment decisions. Collapse

Topics: mobile application mobile system geographic information system global navigation satellite system location based service

Methods: descriptive statistic statistical hypothesis test theory development likelihood-ratio test robustness check

Theories: construal level theory

Trusting the Moral Judgments of a Robot: Perceived Moral Competence and Humanlikeness of a GPT-3 Enabled AI

2023 | HICSS | Citations: 0

Authors: Momen, A.; De Visser, E.; Wolsten, K.; Cooley, K.; Walliser, J.; Tossell, C.

Abstract: Advancements in computing power and foundational modeling have enabled artifici ... Expand

Abstract: Advancements in computing power and foundational modeling have enabled artificial intelligence (AI) to respond to moral queries with surprising accuracy. This raises the question of whether we trust AI to influence human moral decision-making, so far, a uniquely human activity. We explored how a machine agent trained to respond to moral queries (Delphi, Jiang et al., 2021) is perceived by human questioners. Participants were tasked with querying the agent with the goal of figuring out whether the agent, presented as a humanlike robot or a web client, was morally competent and could be trusted. Participants rated the moral competence and perceived morality of both agents as high yet found it lacking because it could not provide justifications for its moral judgments. While both agents were also rated highly on trustworthiness, participants had little intention to rely on such an agent in the future. This work presents an important first evaluation of a morally competent algorithm integrated with a human-like platform that could advance the development of moral robot advisors. Collapse

Topics: robotic artificial intelligence decision making healthcare data web application

Methods: experiment survey computational algorithm Student's t-test survey design

Socially responsible design science in information systems for sustainable development: a critical research methodology

2023 | European Journal of Information Systems | Citations: 0

Authors: Monson, Mike

Abstract: This study presents an Information Systems (IS) research methodology for the con ... Expand

Abstract: This study presents an Information Systems (IS) research methodology for the conduct of critical research into sustainable development that encompasses the objectives of socially inclusive and environmentally sustainable economic growth. The specific context is the application of critical research in the problem definition phase of IS Design Science Research for sustainable development. The paper guides IS research through problem scenarios of unsustainable development where power can distort truth and corrupt the public discourse in the furtherance of their ambitions. The methodology provides a structured approach to engage in inquiry of topics which are by their nature, deceptive and opaque. The methodology enables research inquiry encompassing societal topics, macro-social issues related to sustainable development and the application of nomothetic inquiry to address systemic problems. The paper concludes with illustrative examples of outcomes from the application of the prescribed methodology. The study provides an IS response to systemic social and environmental challenges by identifying the routes to transformation which in turn inform the design of IS solutions. Consequently, the study lays a foundation for IS engagement in socially responsible design science research. Collapse

Topics: legal context IS discipline innovation management digital media organizational context

Methods: design science design theory survey cross sectional research archival research

Theories: social sciences theory information systems theory theory of economic growth

SUSTAINABILITY IN PRIVATE HOUSEHOLDS - INVESTIGATING ACCEPTANCE OF SMART ENERGY APPS

2023 | European Conference On Information Systems | Citations: 0

Authors: Moors, Marietta; Schäfer, Ricarda

Abstract: As the use phase of buildings produces a substantial negative environmental imp ... Expand

Abstract: As the use phase of buildings produces a substantial negative environmental impact, mechanisms to guide individuals towards more sustainable energy consumption are of interest. Smart energy apps which constantly monitor energy consumption and provide energy reduction recommendations to private households are a promising tool to tackle this issue. However, as little is known about factors driving their adoption, it remains unclear whether their potential can be leveraged. Against this backdrop, this study derives a technology acceptance model for smart energy apps which builds on a quantitative survey with 300 participants and the partial least squares approach. The results highlight personal innovativeness and environmental norms as additional acceptance factors. Our study points at the importance integrating both individual and technological aspects in technology adoption research, unveils potential levers for IS to drive adoption, and provides guidance to smart energy app designers. Collapse

Topics: mobile application behavioral intention usage intention personality digital literacy

Methods: survey partial least squares regression structural equation modeling computational algorithm factor analysis

Theories: extended unified theory of acceptance and use of technology technology acceptance model technology acceptance theory socio technical theory

Smartphone addiction and cultural dimensions

2023 | HICSS | Citations: 0

Authors: Moqbel, M.; Bartelt, V.; Alam, M.; Shaik, A.; Montoya, S.; Larson, M.

Abstract: Smartphone addiction is causing severe damage to individuals and societies alik ... Expand

Abstract: Smartphone addiction is causing severe damage to individuals and societies alike. Previous studies have mainly focused on the effects of smartphone addiction, but they hardly focused on the cultural aspects leading to addiction. This study attempts to fill this void by shedding light on how Hofstede's four cultural dimensions, including 1) individualism-collectivism, 2) masculinity-femininity, 3) power distance, and 4) uncertainty avoidance, affect individuals' smartphone addictive behavior through the lens of attachment and coping theories. We offer suggestions for future research and practical implications based on these findings. Collapse

Topics: smartphone addiction mobile system smartphone information technology addiction

Methods: survey theory development

Theories: cultural dimensions theory attachment theory

A new perspective of BDA and information quality from final users of information: A multiple study approach

2023 | International Journal of Information Management | Citations: 0

Authors: Morales-Serazzi, Manuel; González-Benito, Óscar; Martos-Partal, Mercedes

Abstract: Although organizational factors related to big data analytics (BDA) and its perf ... Expand

Abstract: Although organizational factors related to big data analytics (BDA) and its performance have been studied extensively, the number of failed BDA projects continues to rise. The quality of BDA information is a commonly cited factor in explanations for such failures and could prove key to improving project performance. Using the resource-based view (RBV) lens, data analytics literature, business strategy control, and an empirical setup of two studies based on marketing and information technology managerial data, we draw on the dimensions of the balanced scorecard (BSC) as an integrating framework of BDA organizational factors. Specifically, we tested a model –from two different perspectives– that would explain information quality through analytical talent and organizations’ data plan alignment. Results showed that both managers have a different understanding of what information quality is. The characteristics that make marketing a better informer of information quality are identified. In addition, hybrid (embedded) type analyst placements are seen to achieve better performance. Moreover, we add greater theoretical rigour by incorporating the moderating effect of the use of big data ana­ lytics in companies. Finally, the BSC provided a greater causal understanding of the resources and capabilities within a data strategy. Collapse

Topics: data quality marketing management organizational productivity analytical information system big data

Methods: SEM tool conceptual modelling survey theoretical contribution data transformation

Theories: resource based view of the firm

How Additive Manufacturing Platforms are Digitizing the Manufacturing Value Proposition

2023 | European Conference On Information Systems | Citations: 0

Authors: Morar, Dominik; Hiller, Simon; Petrik, Dimitri

Abstract: Digital platforms are established in business ecosystems with primarily non-tan ... Expand

Abstract: Digital platforms are established in business ecosystems with primarily non-tangible value creation (e.g., social networks, entertainment, software). All partners of a platform usually benefit from network effects. The digitization of physical products and processes drives industrial platformization, so manufacturing companies increasingly establish digital manufacturing platforms. The impact of digital manufacturing platforms on value creation in the manufacturing industry is of great interest. A highly promising technology for emerging production platforms seems to be Additive Manufacturing (AM), which enables economical manufacturing of small batches, individualization, and high flexibility in production. This study examinates the relation between platform providers and related platforms in the AM field. A literature review and a subsequent cluster analysis of AM platforms are the two pillars of our research design to identify five patterns of platform-based value creation in digital manufacturing. The discussion of the resulting value creation patterns highlights implications for platform business model design by manufacturing companies and knowledge on digital platforms. Collapse

Topics: value creation business model production management 3D printing innovation management

Methods: cluster analysis literature study qualitative content analysis structured literature research machine learning

Theories: lemon market theory

Time Series Prediction Using Deep Learning Methods in Healthcare

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Morid, Mohammad Amin; Sheng, Olivia R. Liu; Dunbar, Joseph

Abstract: Traditional machine learning methods face unique challenges when applied to heal ... Expand

Abstract: Traditional machine learning methods face unique challenges when applied to healthcare predictive analytics. The high-dimensional nature of healthcare data necessitates labor-intensive and time-consuming processes when selecting an appropriate set of features for each new task. Furthermore, machine learning methods depend heavily on feature engineering to capture the sequential nature of patient data, oftentimes failing to adequately leverage the temporal patterns of medical events and their dependencies. In contrast, recent deep learning (DL) methods have shown promising performance for various healthcare prediction tasks by specifically addressing the high-dimensional and temporal challenges of medical data. DL techniques excel at learning useful representations of medical concepts and patient clinical data as well as their nonlinear interactions from high-dimensional raw or minimally processed healthcare data. In this article, we systematically reviewed research works that focused on advancing deep neural networks to leverage patient structured time series data for healthcare prediction tasks. To identify relevant studies, we searched MEDLINE, IEEE, Scopus, and ACM Digital Library for relevant publications through November 4, 2021. Overall, we found that researchers have contributed to deep time series prediction literature in 10 identifiable research streams: DL models, missing value handling, addressing temporal irregularity, patient representation, static data inclusion, attention mechanisms, interpretation, incorporation of medical ontologies, learning strategies, and scalability. This study summarizes research insights from these literature streams, identifies several critical research gaps, and suggests future research opportunities for DL applications using patient time series data. Collapse

Topics: missing data health information system database system healthcare data

Methods: longitudinal research time series analysis structured literature research ontological modelling literature study