An Adversarial Dance: Toward an Understanding of Insiders’ Responses to Organizational Information Security Measures

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Balozian, Puzant; Burns, A.; Leidner, Dorothy

Abstract: Despite the increased focus on organizational security policies and programs, s ... Expand

Abstract: Despite the increased focus on organizational security policies and programs, some employees continue to engage in maladaptive responses to security measures (i.e., behaviors other than those recommended, intended, or prescribed). To help shed light on insiders' adaptive and maladaptive responses to IS security measures, we conducted a case study of an organization at the forefront of security policy initiatives. Drawing on the beliefs-actions-outcomes (BAO) model to analyze our case data, we uncover a potentially nonvirtuous cycle consisting of security-related beliefs, actions, and outcomes, which we refer to as an "adversarial dance." Explaining our results, we describe a novel belief framework that identifies four security belief profiles and uncovers an underexplored outcome of IS security: insiders' lived security experiences. We find that individuals' unfavorable lived security experiences produce counterproductive security-related beliefs that, in turn, lead to maladaptive behaviors. Maladaptive behaviors create new potential for security risk, leading to increased organizational security measures to counter them. Thus, the adversarial dance continues, as the new security measures have the potential to reinforce counterproductive security-related beliefs about the importance and risk of IS security and lead to new maladaptive behaviors. To help situate our findings within the current security literature, we integrate the results with prior research based on extant theories. While this paper is not the first to suggest that security measures can elicit maladaptive behaviors, the emergent belief framework and expanded BAO model of IS security constitute an important contribution to the behavioral IS security literature.Puzant Balozian is an assistant professor of computer information systems at James Madison University. His research focus is primarily on the impacts of organizational factors on individual user behaviors in the context of information security and privacy and addressing security policy compliance and violation. Collapse

Topics: IT security IT security defense productivity IT security threat anonymity

Methods: case study qualitative interview personal interview theory development survey

Theories: information systems theory neutralization theory behavioral theory

Let Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Deng, Yipu; Zheng, Jinyang; Huang, Liqiang; Kannan, Karthik

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer t ... Expand

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer to investigate how intelligent image processing (IIP)-based shelf monitoring aids manufacturers' shelf management by using data from a quasi-experiment and a field experiment. We discovered that such artificial intelligence (AI) assistance significantly and consistently improves product sales. Several underlying mechanisms were revealed by our quantitative and qualitative analysis. First, retailers are more likely to comply due to the greater monitoring effectiveness enabled by AI assistance. Second, the positive effect of IIP-based shelf monitoring partially persists after it is terminated, implying that human learning takes place. Third, the value of IIP-based shelf monitoring can be attributed to independent retailers rather than chain retailers. Since the degree of contract heterogeneity is the major difference between these retailers in terms of monitoring, this finding further suggests that AI is relatively more scalable when coping with more heterogeneous instances. Apart from these great benefits, we demonstrate the low marginal costs of implementing IIP-powered shelf monitoring, which indicates its long-term applicability and potential to generate incremental value. Our research contributes to several literature streams and provides managerial insights for practitioners who consider AI-assisted operational models. Collapse

Topics: artificial intelligence organizational value cost benefit analysis mobile application human AI collaboration

Methods: experimental group field experiment qualitative interview experiment quasi experiment

How to attract low prosocial funders in crowdfunding? Matching among funders, project descriptions, and platform types

2023 | Information & Management | Citations: 0

Authors: Li, Yuanqing; Cabano, Frank; Li, Pingshu

Abstract: The amount of crowdfunding research that investigates funding success factors ha ... Expand

Abstract: The amount of crowdfunding research that investigates funding success factors has been increasing. The existing research shows inconsistent evidence regarding how a prosocial project description affects funding success and largely ignores the issue of alignment/misalignment among different factors in affecting funding success. We suggest that funders’ prosocial motivation can be an important factor for this inconsistent evidence. We integrate the elaboration likelihood model and language expectancy theory and demonstrate distinct decision-making patterns from high and low prosocial motivation funders. Through three experiments, we provide evidence for alignment/misalignment effects among funders’ prosocial motivation, prosocial project descriptions, and platform types (donation-based vs. reward-based). While there are no differences for participants with high prosocial motivation across conditions, we find that participants with low prosocial motivation are more willing to contribute to a project that has alignment between the different factors, namely to a project that has a high prosocial description on a donation-based platform, or to a project that has a low prosocial description on a reward-based platform. This research sheds light on the crowdfunding and prosocial motivation literature. Collapse

Topics: crowdfunding crowdsourcing decision making cost benefit analysis cross cultural research

Methods: experiment parametric test descriptive statistic ANOVA one-way ANOVA

Theories: expectancy theory of motivation elaboration likelihood model organizational behavior theory

LOOKING FOR QUALITY IN TRASH: DATA QUALITY IN IOT LITTER-BINS

2023 | European Conference On Information Systems | Citations: 0

Authors: Saarikko, Ted; Lundström, Anders

Abstract: Internet of Things (IoT) holds significant potential for municipal efficiency a ... Expand

Abstract: Internet of Things (IoT) holds significant potential for municipal efficiency and effectiveness. It enables subsystems to seamlessly communicate and permits their integration into a connected whole, affording new opportunities for value creation. In this paper, we present a study of municipal litter-bins that have been retrofitted with sensors to convey data on trash volume in each receptacle. Based on interviews, strategy documents, and notes from project meetings, we analyse their implementation from a data quality perspective and reflect on social-and technical issues. The case illustrates the propensity and consequences of overestimating benefits and oversimplifying technical interventions. This paper contributes to our practical understanding of socio-technical implications of technology use in the public sector in general and the deployment of IoT for smart cities in particular. Collapse

Topics: data quality internet of things mobile system smart city information system use

Methods: qualitative interview case study qualitativ observational study design artifact

Cost-based analysis of the impact of data completeness and representational consistency

2023 | Decision Support Systems | Citations: 0

Authors: Timmerman, Yoram; Nasfi, Rihem; De Tré, Guy; Pattyn, Filip; Bronselaer, Antoon

Abstract: Data quality is an important topic for businesses and therefore requires appropr ... Expand

Abstract: Data quality is an important topic for businesses and therefore requires appropriate analysis tools. Although several rule-based systems exist today for quality measurement, their results do not always reflect the real impact of quality issues on practical data usability and are therefore not well-suited to base economic decisions on. This work practically implements and evaluates an alternative, cost-based approach for data quality analysis starting from a ‘fitness for use’-perspective. The practical impact of completeness and representational consistency of data stored in an integrated relational database is investigated in an experiment with 218 volunteers. Two alternative versions of this database are then prepared by manually improving their data quality. Participants are randomly assigned to one of three databases and are given a set of questions to resolve by means of SQL. As questions are resolved, we measure several cost-based indicators such as ability to solve, time to solve and number of attempts. Results indicate that the impact of data quality issues can differ significantly from what would be expected when using rule-based measurement. Effects range from almost no impact to a 65% reduction in time needed to solve tasks. Effect sizes up to 0.43 using one-way ANCOVA tests are observed. Collapse

Topics: database system data quality structured query language usability missing data

Methods: experiment analysis of covariance binomial logistic regression path analysis moderation analysis

CARING ABOUT EMPLOYEES’ HEALTH@WORK – UNDERSTANDING HEALTH BELIEFS AND THE USE OF DIGITAL HEALTH INTERVENTIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Weißenfels, Silke; Kappler, Karolin; Smolnik, Stefan

Abstract: Employees find contemporary ways of working very demanding. Blurred boundaries ... Expand

Abstract: Employees find contemporary ways of working very demanding. Blurred boundaries between life and work cause technostress and considerable mental strain. To overcome these shortcomings, digital health interventions (DHIs) possess the power to prevent employees from suffering health-related issues at and due to their work. We developed a theoretically sound instrument employing a unified conceptualization of health beliefs, technology acceptance, privacy concerns, and autonomy to predict preventive health and technology use behavior at work. Accordingly, we conducted a survey-based study to investigate the factors influencing DHIs use for preventive health behavior at work. Our empirical results emphasize that employees undertake a cost-benefit analysis, valuing the benefits of reducing health threats and the perceived usefulness of DHIs for taking preventive actions at work. We confirm that privacy concerns and autonomy play a vital role. Our research outlines new avenues in DHIs use by contributing a valid theoretical framework for healthier work environments. through behavior change approaches (Pagoto and Bennett, 2013). For instance, wearables for selftracking (Giddens et al., 2017) that enable self-care and autonomy at work, enhance employees' health and well-being (Lupton, 2016). Against this background, we ask which beliefs and perceptions are important in evaluating the outcome of a particular behavior (Agarwal and Karahanna, 2000) as, for example, using DHIs for preventive health behavior at work. Surprisingly, despite the radical challenges of work practices with severe implications for employees, and the grown work around health interventions, the discourse on research referring to DHIs as facilitators of preventive health behavior in organizations is still in its infancy (Melzner et al., 2014;Yassaee and Mettler, 2019;Oesterle et al., 2019;Howarth et al., 2018). We shift our attention from technology use only and move toward an understanding of preventive health and technology use behavior, supported by DHIs in occupational settings. To address our research objectives, we refer to and extend previous research on preventive health behavior and technology use with multiple technological options beyond a narrow focus on which technology to use. Our work is rooted in research on health beliefs, based on the health belief model (HBM) (Rosenstock, 1974) considering the potential to initiate and change health behavior patterns (Abraham and Sheeran, 2005), and assuming that individuals attempt to avoid perceived health threats (Abraham and Sheeran, 2005;Rosenstock, 1974;Champion and Skinner, 2008). Additionally, we investigate employees' behavior in DHIs use at work. Interestingly, the decision-making process regarding technology use for health-related reasons differs from similar processes in other contexts (Sun et al., 2013). Hence, to understand employees' preventive health behavior supported by technology use, we expect that they intend to use DHIs, which, according to the technology acceptance model (TAM) (Davis, 1989;Venkatesh et al., 2003), is a result of systemrelated characteristics that we combine with health-related variables. Further, in offering voluntary DHIs use at work to encourage employees' empowerment, we have to consider their privacy concerns and autonomy, to engage them in healthy behavior at work (Roossien et al., 2021). As it is not clear whether or how health beliefs influence preventive health and technology use behavior at work, nor whether there is a link in-between, this paper seeks to answer the following research question: What impact do health beliefs, privacy concerns, and autonomy have on employees' DHIs use for preventive health behavior at work? More specifically, our research objectives are (1) to explore whether health beliefs influence employees' preventive health behavior at work, (2) to predict employees' technology use behavior of DHIs, (3) to empirically validate the link between health beliefs, DHIs use, and preventive health behavior, and (4) to theorize the influence of privacy concerns and autonomy on DHIs use at work. Our study follows the call to unfold and predict preventive health behavior through complex causal models (Champion and Skinner, 2008) and to demonstrate the interventions' effectiveness (Abraham and Sheeran, 2005). While DHIs have the potential to intervene in unhealthy (working) behavior, we suggest an analysis of the health-related beliefs and factors related to technology use. Therefore, our theoretical framework is to develop a deeper understanding of HBM and TAM as theoretical lenses and their interplay and to offer new perspectives that could ensure healthier work environments. In a quantitative research setting, we use an online-based survey to evaluate our hypothesized relations empirically. Our findings provide compelling evidence that technology use and preventive health behavior do not emerge in isolation. More precisely, our study demonstrates the relationship between health beliefs and system-related characteristics in DHIs use at work. These results help organizations to understand the conditions under which DHIs are likely to have an impact on employees' preventive health behavior and well-being in occupational settings, which can in turn develop into a meaningful quality of work (Rongen et al., 2013). The paper is structured as follows: Section 2 introduces the theoretical background for research on preventive health and technology use behavior and the development of our theoretical conceptualization for the quantitative analysis. Section 3 introduces our survey-based approach to address the research question. We present our analysis in Section 4. Our results and implications are summarized in Section 5 together with a discussion of related literature. Section 6 concludes the paper. Collapse

Topics: information system use information privacy concern perceived usefulness decision making technology adoption

Methods: survey partial least squares regression card sorting theory development factor analysis

Theories: technology acceptance model measurement theory health belief model

Ethical framework for Artificial Intelligence and Digital technologies

2022 | International Journal of Information Management | Citations: 9

Authors: Ashok, Mona; Madan, Rohit; Joha, Anton; Sivarajah, Uthayasankar

Abstract: The use of Artificial Intelligence (AI) in Digital technologies (DT) is prolifer ... Expand

Abstract: The use of Artificial Intelligence (AI) in Digital technologies (DT) is proliferating a profound socio-technical transformation. Governments and AI scholarship have endorsed key AI principles but lack direction at the implementation level. Through a systematic literature review of 59 papers, this paper contributes to the critical debate on the ethical use of AI in DTs beyond high-level AI principles. To our knowledge, this is the first paper that identifies 14 digital ethics implications for the use of AI in seven DT archetypes using a novel ontological framework (physical, cognitive, information, and governance). The paper presents key findings of the review and a conceptual model with twelve propositions highlighting the impact of digital ethics implications on societal impact, as moderated by DT archetypes and mediated by organisational impact. The implications of intelligi­ bility, accountability, fairness, and autonomy (under the cognitive domain), and privacy (under the information domain) are the most widely discussed in our sample. Furthermore, ethical implications related to the gover­ nance domain are shown to be generally applicable for most DT archetypes. Implications under the physical domain are less prominent when it comes to AI diffusion with one exception (safety). The key findings and resulting conceptual model have academic and professional implications. Collapse

Topics: artificial intelligence societal evaluation criteria privacy organizational impact business model

Methods: structured literature research synthesis conceptual modelling literature study literature sample

Theories: semiotic theory

Assessing the Impact of Virtual Health Communities and Environmental Characteristics of Chronic Pain Mobile Health Apps on Users’ Privacy Decisions: A Multilevel Perspective

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Bantan, May; Alrefaei, Doaa; Alharbi, Raed

Abstract: Chronic pain has been identified as one of the most widespread health-related p ... Expand

Abstract: Chronic pain has been identified as one of the most widespread health-related problems. Potential chronic pain apps users seek health communities for current and previous reviews to assess the quality of the apps and make a decision regarding disclosing their information to these apps. In this study, we present a multilevel perspective on how virtual health communities and environmental characteristics of chronic pain mobile health apps impact users' privacy decisions. We used Exploratory Data Analysis and Machine Learning (ML) to operationalize the Theory of Multilevel Information Privacy. The results revealed that the most influential factors affecting users' cost-benefit analysis are Chronic Pain MHA's characteristics related to user's information privacy. The ML results indicate that the existence of information privacy policy can be predicted through the ways the apps use to Collect Data, App's Category, Country, and Store Type, which in turn affect users' decisions. Collapse

Topics: privacy mobile application mobile application market digital distribution shapley additive explanation

Methods: machine learning support vector machine exploratory data analysis natural language processing sentiment analysis

Theories: theory of multilevel information privacy privacy calculus theory

Online prejudice and barriers to digital innovation: Empirical investigations of Chinese consumers

2022 | Information Systems Journal | Citations: 3

Authors: Che, Tong; Peng, Zeyu; Lai, Fujun; Luo, Xin (Robert)

Abstract: China is widely considered a world leader in e-commerce. In recent years, e-comm ... Expand

Abstract: China is widely considered a world leader in e-commerce. In recent years, e-commerce in China has made significant progress and gone through rounds after rounds of innovations. Technological advancements have enabled the integration of online and offline channels, allowing consumers to choose their preferred shopping channel. Thus, competition and cooperation between online and offline channels have become important issues. Drawing on confirmation bias theory and the unique cultural lens (low uncertainty avoidance and a high level of cynicism) that exists in China, we conceptualize online prejudice and propose a model to analyse how it affects channel selection. A scenario-based survey, along with an explorative pre-study, was conducted to test our hypotheses. The results showed that prejudice toward the online channel does exist in China. Further, this online prejudice mediates the relationship between perceived uncertainty and channel selection. That is, uncertainty can induce consumers' online prejudice, which in turn predicts their channel selection behaviour. Furthermore, the mediating effect of online prejudice is contingent upon product type (i.e., experience products vs. search products). Collapse

Topics: electronic commerce electronic business experience good website decision making

Methods: survey Student's t-test SEM tool theory development statistical hypothesis test

Social Influence, Competition, and Free Riding: Examining Seller Interactions Within an Online Social Networ

2022 | Management Information Systems Quarterly | Citations: 0

Authors: Huang, He; Huang, Yan; Yan, Zhijun; Zhang, Han

Abstract: Online social networks are increasingly being used to conduct commercial activit ... Expand

Abstract: Online social networks are increasingly being used to conduct commercial activities, and many online social networking platforms allow users to sell products to their online connections. Although extensive research has been conducted on the interactions among buyers within a social network, interactions among sellers have rarely been explored. Using seller data from a company that sells on a major online social networking platform in China, we empirically examine how sellers’ efforts and sales performance are affected by the efforts and sales performance of other sellers they are connected to (i.e., their inviters and invitees) and the commissions they themselves have received. We find evidence for social influence and competition effects in the “inviter-to-invitee” direction and sellers’ free-riding behavior driven by the commissions they receive from their invitees’ sales. These results extend the social network literature that has largely focused on connected buyers (or users) to connected sellers and offer implications for social networking platforms to promote seller participation. Collapse

Topics: social influence social network WeChat mobile phone social media

Methods: robustness check instrumental variables estimation cross sectional research descriptive statistic