A Column Generation Approach for the Product Grouping Problem

We study the product grouping problem (PGP) which seeks to optimize its production process to minimize total materials and equipment changeover cost in a manufacturing plant.  A simplified version of the problem that ignores materials cost is equivalent to the clique partition problem (CPP).  This paper presents a column generation-based algorithm to solve CPP and PGP.  The algorithm is particularly attractive as it requires less fine-tuning of its parameters, produces lower bounds that can be used to assess the quality of the solutions to the problem, and generates improved solutions for a benchmark dataset.

Sponsor: Oklahoma State University
PI/PD: Ali Amiri

 

Optimization of Product Category Allocation to Minimize Order Splitting

We study the problem of allocating product categories to multiple warehouses to reduce online order splitting and ultimately reduce shipping costs.  We propose a column generation-based algorithm to solve the problem.

Sponsor: Oklahoma State University
PI/PD: Ali Amiri

 

Identifying Injury Severity Risk Factors in Automobile Crashes: A Hybrid Explainable AI ApproachWe designed and developed a hybrid methodology involving predictive analytics, explainable AI, and heuristic optimization techniques to investigate the injury severity risk factors in automobile crashes. We proposed an explanation method based on a variable neighborhood search procedure and compared it with the existing methods. By applying an information fusion technique, we identified a ranking list of the most influential injury severity characteristics related to the driver, vehicle, and accident. The findings can be used by practitioners and policymakers to improve traffic safety by mitigating injury-related risk factors.

Sponsor: Oklahoma State University

PI/PDs: Ali Bagheri, Dursun Delen, Mostafa Amini

 

Measuring the Relative Performance of Accountable Care Organizations: The Role of Electronic Health Records

Accountable Care Organizations (ACOs) were established to address the issues related to the soaring costs of healthcare delivery. We propose an evaluation framework to measure ACO efficiency, based on their ability to use health care resources to maximize patient health outcomes. Drawing on a nationwide sample of ACOs, we find that larger ACOs are more likely to exhibit lower efficiency relative to smaller ACOs. We also find that usage of electronic health records mitigates the negative impact of size on ACO performance.

Sponsors: Oklahoma State University, University of Texas

PI/PDs: Chenzhang Bao

University of Texas: Indranil Bardhan

 

Antecedents and Impact of Health Information Sharing on Hospital Performance: EMR Sourcing Strategies and HIE Participation

Despite significant investments in health information technologies (IT), there is still a dearth of information sharing among healthcare providers and hospitals, which constrain adopters from reaping the full benefits of health IT. In this study, we examine the impact of electronic medical records (EMR) sourcing strategies of healthcare providers, as well as their participation in health information exchanges (HIE), on the extent of health information sharing. We attempt to identify the underlying mechanisms through which the benefits of health IT on hospital outcomes are realized.

Sponsors: Oklahoma State University, University of Texas

PI/PDs: Chenzhang Bao

University of Texas: Indranil Bardhan

 

IT Spillover Effects in Levels of Healthcare Delivery

Recent literature has examined positive IT spillover effects in regional healthcare. We extend this idea and argue that patient and information exchange occur mainly between care-delivery levels (e.g. from primary care clinics to tertiary care hospitals and vice versa) rather than within a care level (e.g. from one tertiary care hospital to another). Using the Medicare Cost Report and HIMSS database, we assess how IT adoption by primary care clinics affect the operating cost of tertiary care hospitals.

Sponsor: Oklahoma State University

PI/PDs: Chenzhang Bao, Ankita Srivastava, Dursun Delen

 

Investigating Uneven Distribution of Health IT Vendor Products

While there is an increasing trend of adopting systems from several dominating vendors, health IT markets remain competitive and fragmented. This study investigates the distribution of different vendor products and how hospitals adopt health ITs compared to other neighboring peers in the local healthcare market. We focus on the longitudinal trajectories of different applications across years.

Sponsor: Oklahoma State University

PI/PD: Chenzhang Bao

 

Evolution of EMRs and the Impact on Performance

Health IT applications have been criticized for the lack of interoperability across vendor products. We investigate the difference in vendor selection of EMR applications within a hospital referral region. We cluster the longitudinal patterns of this evolution in vendor difference/similarity and examine its impact on hospital performance.

Sponsors: Oklahoma State University, Temple University

PI/PDs: Chenzhang Bao

Temple University: Sezgin Ayabakan

 

Health Information Exchange: Hype or Hope?

In recent years, healthcare providers increasingly adopt health IT systems primarily from a single supplier in order to maximize their capability to share patient health data. However, little is known about how much variation this merit in health information exchange explains the variations in hospital performance. In this study, we observe that while single-sourcing improves hospital performance, the level of information sharing has negligible explanation on relationship. Compared to information sharing, the benefit of adopting a single-sourced IT system is more likely rooted in its capability to facilitate clinical workflow.

Sponsor: Oklahoma State University

PI/PD: Chenzhang Bao

 

Technostress Among Physicians and Nurses: A Longitudinal Investigation of Health IT Strategies and User Satisfaction

In this research, we propose a strategic technostress model to study how EHR strategies impact clinicians’ satisfaction with IT. We perform text mining on data collected from the Glassdoor website to reveal clinicians’ techno-satisfaction and combine it with organizational EHR strategies. Our analysis indicates that EHR adoption is positively associated with techno-satisfaction. We also observe that EHR sourced from multiple vendors is associated with higher satisfaction. However, these relationships are negatively moderated by EHR experience. Our study provides significant theoretical insights about clinicians’ perception of IT and managerial insights for system design.

Sponsors: Oklahoma State University, Temple University

PI/PDs: Chenzhang Bao, Ankita Srivastava, Surya Ayyalasomayajula, Dursun Delen

Temple University: Sezgin Ayabakan

 

Quantum Information Systems: Harnessing Individual and Group Energies

In this working paper, we propose that an organization is a living organism that generates energy to achieve certain outcomes. We propose that the relationship between the inputs (individual and group use of information systems) and the outputs (strategic alignment and competitive advantage) of a system depends on the basic principles of quantum mechanics. Specifically, we connect the neuroscience research that addresses qualia (individual) and quale (group) to the Management Information Systems (MIS) research. In this paper, we proffer our research objective, discuss our constructs, and present our interview process and survey items that we plan to conduct and administer.

Sponsors: Oklahoma State University, Virginia Military Institute, Indiana University of Pennsylvania

PI/PDs: Corey Baham

Virginia Military Institute: Jennifer Gerow

Indiana University of Pennsylvania: James Rodgers

 

Using Multi-Factor Authentication for Online Account Security: Examining the Influence of Anticipated Regret

Authentication plays an important role in securing our systems but is threatened by increasingly sophisticated account hacking and account take over. Several security services have been developed, including multifactor authentication designed to cope with online account authentication. It remains unknown how users perceive and evaluate secure authentication for online accounts and consequently use it to avoid online account threats. This study investigates the factors that affect the use of secure authentication to avoid online account threats. This work extends PMT by showing how the emotion of anticipated regret heightens appraisals of threat and coping.

Sponsors: Oklahoma State University, University of North Texas

PI/PDs: Corey Baham

University of North Texas: Obi Ogbanufe

 

Issues, Challenges, and Discussion of a Theoretical Core of Agile Software Development Research

Information systems researchers need to balance their pursuit of theoretical contribution by applying the level of nuance needed to make an impact in both research and practice. We argue that the most expedient way to overcome challenges in conducting ASD research and evaluating knowledge claims is first to develop a theoretical core and second, address issues of rigor in ASD research. This paper aims to highlight major issues facing ASD research in IS, discuss how these issues can be overcome, and propose a theoretical core that can be debated, refined, and used in future research.

Sponsors: Oklahoma State University, Louisiana State University

PI/PDs: Corey Baham

Louisiana State University: Rudy Hirschheim

 

Is Technostress Forcing Physicians to Leave Their Careers? An Exploration of EHR-Related Physician Burnout?

The growing evidence on physician burnout is gaining paramount attention among practitioners, researchers and policy-makers. IS literature has theorized this phenomenon as technostress and there is considerable causal evidence explaining the effect of use of ICT’s on manifestations of strain and reduced productivity. We argue that the existing literature on technostress fails to generalize in healthcare and thus needs to be extended. We propose that an understanding of how EHR’s contribute to physician burnout is needed. A qualitative study using interviews will be deployed at all three levels of care delivery- primary, secondary and tertiary for a holistic exploration.

Sponsor: Oklahoma State University

PI/PDs: Corey Baham, Ankita Srivastava, Dursun Delen

 

Generational Differences in Handling Technology Interruptions: A Qualitative Study

Digital native and digital immigrant user types characterize the differences between those who grew up in a world of ubiquitous information systems and those who pre-date it. The rise in computer-mediated communication (CMC) technologies is creating more opportunities for interruption. Researchers have explored the impact of growing up in a world of technology, but little research has been conducted to understand potential differences concerning how different user types handle technology interruptions. This paper examines how individuals handle CMC interruptions differently based on the role of technology and its level of pervasiveness in the environment in which they grew up.

Sponsors: Oklahoma State University, Auburn University

PI/PDs: Corey Baham, Ramesh Sharda

Auburn University: Pankush Kalgotra

 

Signals and Mechanisms for Unintended Consequences in AI: A Grounded Theory Approach

Artificial Intelligence (AI) technologies such as including machine learning, deep learning, computer vision, and natural language processing, are becoming general-purpose technologies that significantly impact the economic and social structure of organizations and society. However, that impact has not been entirely positive. There have already been many cases where undesirable or negative consequences of AI tools have harmed their respective organizations in social, financial, and legal spheres. This research seeks to uncover common signals and mechanisms that lead to unintended consequences in AI. Using a grounded theory approach, we propose a unifying theoretical framework for unintended consequences in AI projects.

Sponsors: Oklahoma State University, Churadata Inc.

PI/PDs: Corey Baham, David Biros, Madhav Sharma

Churadata Inc.: Jacob Biros

 

Entrepreneurial Organizational Culture, IT-business Alignment, and Firm Agility: A Moderated Mediation

IT-business strategic alignment is one of the most long-standing managerial challenges. Research differs concerning its impact on firm agility. To better understand this relationship, we study the impact of both intellectual and social alignment on firm agility in the context of entrepreneurial organizational culture (EOC) to account for a firm's level of entrepreneurial intensity.  In a field study of 100 CIOs, we find that EOC positively impacts firm agility through mediated and moderated effects of both social and intellectual alignment, respectively. This paper provides a theory-driven explanation of the dynamics of social and intellectual alignment's impact on firm agility. 

Sponsors: Oklahoma State University, University of Tennessee, Virginia Military Institute

PI/PDs: Corey Baham, Andy Luse, Ramesh Sharda

University of Tennessee: Randy Bradley

Virginia Military Institute: Jennifer Gerow

 

Bridging the Acceptance-Routinization Gap in Agile Software Development Assimilation: An Exploratory Cross Case Analysis

Agile software development methods represent a departure from the strong document-driven procedures of plan-driven approaches. As organizations continue to adopt agile methods, understanding how to sustain agile methods is a growing concern. In recent years, researchers have focused their attention on the issues of sustained agile use in order to extend our knowledge on agile assimilation. However, little research has been conducted to expose the assimilation gaps that occur as organizations seek to increase the extent and intensity of their agile use. Following prior literature, we investigate the role of organizational factors in the continuance of agile methods.

Sponsors: Oklahoma State University, Louisiana State University, Georgia State University

PI/PDs: Corey Baham

Louisiana State University: Rudy Hirschheim

Georgia State University: Likeobe Maruping

 

The Moderating Effect of Ambiguity on Fake News and Sensemaking

Fakes news on the Internet has emerged as an issue with far-reaching consequences. Given fake news’ breadth of influence, depth of consequences, and perpetuity, we extend this line of inquiry to a less studied area - uncertainty-reducing behaviors in fake news online. In this study, we examine ambiguity in fake news and its relationship to information seeking and sensemaking. Our results yield strong theoretical and practical implications for public policy and future research.

Sponsors: Oklahoma State University, Louisiana State University

PI/PDs: Corey Baham

Louisiana State University: Reginald Tucker

 

Data is the Disaster: Data Issues in Disaster Management Scenarios

The 21st Century has been termed “the century of disasters” (Achenbach, 2011) due to several notorious forms of disasters (e.g., geophysical, hydrological, climatological). Among these, the recent biological disaster of the COVID-19 disease epidemic has seen global impacts. The disastrous effects of COVID-19 have exacted a devastating toll on civil and technological infrastructure and society as a whole (e.g., loss of human life, social and economic disturbances, and industry interruptions and shutdowns).

Sponsor: Oklahoma State University

PI/PDs: Corey Baham, Andy Luse, Ramesh Sharda, Jared Taylor

 

A text-mining based cyber-risk assessment and mitigation framework for critical analysis of online hacker forums

Online hacker communities are meeting spots for aspiring and seasoned cybercriminals where they can engage in technical discussions, and share exploits and relevant hacking tools to be used in launching cyber-attacks on business organizations. Sometimes, the affected organizations can detect these attacks in advance, with the help of cyber-threat intelligence derived from the explicit and implicit features of hacker communication in these forums. In this research, we develop a novel text-mining based cyber-risk assessment and mitigation framework, which performs the cyber-risk assessment using explicit and implicit features applying various machine learning algorithms, sentiment analysis, and topic detection methods.

Sponsor: Oklahoma State University

PI/PD: Dursun Delen

 

A critical analysis of COVID-19 research literature: Text mining approach

Among the stakeholders of COVID-19 research, clinicians particularly experience difficulty keeping up with the deluge of SARS-CoV-2 literature while performing their much-needed clinical duties. To discover the major topics and trends, this study proposes a text-mining approach to navigating large volumes of COVID-19 literature (i.e., a corpus of 65,262 articles). We utilized natural language processing to curate and generate the term list. We applied topic modeling analyses and multiple correspondence analyses to reveal the trends and major topics, and the associations among topics, journal countries, and publication sources.

Sponsors: Oklahoma State University, University of Alabama – Birmingham

PI/PDs: Dursun Delen

University of Alabama – Birmingham: Ferhat D Zengul, Ayse G Zengul, Michael Mugavero, Nurettin Oner, Bunyamin Ozaydin, James H Willig, Kierstin C. Kennedy, James Cimino

 

Clustering Temporal Disease Networks to Assist Clinical Decision Support Systems in Visual Analytics of Comorbidity Progression

Detection and characterization of comorbidity, the presence of more than one distinct disorder or illness concurrently occurring among a specific cohort of patients, is an invaluable decision aid and a prominent challenge in healthcare research and practice. The aim of this study is to design a novel visual analytics system that can support efficient pattern detection and intuitive visualization of comorbidity progression modeled via temporal disease networks (TDNs). Through two case studies on Clostridioides Difficile and stroke, we demonstrate that the proposed system is able to provide evidence-based and visual insights regarding comorbidity progression effectively for clinical decision support.

Sponsors: Oklahoma State University, Center for Health Systems Innovation

PI/PDs: Dursun Delen

Center for Health Systems Innovation: Yajun Lu, Suhao Chen, Zhuqi Miao, Andrew Gin

 

An Investigation of the COVID-19 Characteristics Using HER Data from Cerner DW

Discovery of new novel patterns related to age, race and gender disparities on hospitalization, length-of-stay and mortality in COVID-19 patients through the use of machine learning and data mining techniques and specifically created database on COVID-19 patients within Cerner HealthFacts data warehouse.

Sponsors: Oklahoma State University, Center for Health Systems Innovation

PI/PDs: Dursun Delen

Center for Health Systems Innovation: Zhuqi Miao

 

Predicting and Explaining Pig Iron Production on Charcoal Blast Furnaces: A Machine Learning Approach

Pig iron, the source for a variety of iron-based products, is traded in commodity markets. Therefore, enhanced productivity has significant economic implications for the producers. In this study, we design, develop, and deploy novel machine learning models on a rich data sample covering more than 20 production variables spanning nine years of an actual operational period, collected at one of the largest pig iron production plants in Brazil. We show that, given the blast furnace parameters, machine learning models are capable of unveiling novel insights by illuminating the black box and successfully predicting production levels at different configurations.

Sponsors: Oklahoma State University, Metalsider - Brazil, Sabanci University – Istanbul, Turkey

PI/PDs: Dursun Delen

Metalsider - Brazil: Marcio Salles Melo Lima

Sabanci University - Istanbul, Turkey: Enes Eryarsoy

 

A Probabilistic Bayesian Inference Model to Investigate Injury Severity in Automobile Crashes

One area that has great potential to leverage the value of big data and analytics is the critical analysis of traffic accidents, where results can provide an in-depth understanding of the risks and provide measures to enhance the well-being of individuals involved in such accidents. This study proposes a data science methodology in a field where probabilistic modeling makes much sense for faster, better decision-making. The main objective of this data analytics study is to identify the high-risk factors with their apparent significance to influence the probability of injury severity on automobile crashes using a geographically representative car crash dataset.

Sponsors: Oklahoma State University, University of Tulsa

PI/PDs: Dursun Delen

University of Tulsa: Kazim Topuz

 

Crafting Performance-based Cryptocurrency Mining Strategies Using a Hybrid Analytics Approach

Crafting and executing the best cryptocurrency mining strategy is vital for success. This study aims to identify the best cryptocurrency mining strategy based on service providers' performance for cryptocurrency mining using a hybrid analytics approach, which integrates the Analytic Hierarchy Process (AHP) and Fuzzy-TOPSIS techniques, along with sensitivity analysis. The results show that hosted mining is the overall best cryptocurrency mining strategy, followed by home mining and cloud mining, based on both total cost of operations and cryptocurrency payout criteria.

Sponsors: Oklahoma State University, Ibn Haldun University - Turkey

PI/PDs: Dursun Delen

Ibn Haldun University - Turkey: Umit Hacioglu, Dounia Chlyeh, Mustafa K Yilmaz, Ekrem Tatoglu

 

To Imprison or Not to Imprison: An Analytics Model for Drug Courts

Analytics can have a significant social impact on decisioning in drug courts. An alternative to traditional criminal courts, drug courts attempt to identify and transform the traditional punitive jurisprudence to a therapeutic one, where the eligible offenders are considered as individuals in need of rehabilitative treatments and are persuaded to undergo a regimen that seeks to return them back to the community, rather than sending them to prison. This initiative, if performed properly, has proven to be effective in lowering the costs and improving the social outcomes. The current study attempts to develop decision support systems for drug courts.

Sponsors: Oklahoma State University, University of Dayton, State of Oklahoma

PI/PDs: Dursun Delen

University of Dayton: Hamed M. Zolbanin,

State of Oklahoma: Durand Crosby, David Wright

 

Derivation and Validation of Essential Predictors and Risk Index for Early Detection of Diabetic Retinopathy Using Electronic Health Records

Diabetic retinopathy (DR) is a leading cause for blindness among working-aged adults. The growing prevalence of diabetes urges for cost-effective tools to improve the compliance of eye examinations for early detection of DR. The objective of this research is to identify essential predictors and develop predictive technologies for DR using electronic health records. These predictive technologies can provide an early warning sign that motivates patients to comply with eye examinations for early screening and potential treatments.

Sponsors: Oklahoma State University, Center for Health Systems Innovation

PI/PDs: Dursun Delen

Center for Health Systems Innovation: Ru Wang, Zhuqi Miao, Tieming Liu, Mei Liu, Kristine Grdinovac, Xing Song, Ye Liang, William Paiva

 

Discovering New Patters in COVID-19 Literature Using Text Mining and Topic Modeling

Although the topic is rather fresh, there seem to be very large and rich literatures already accumulating on COVID-19-related research studies. In this text mining and topic modeling study, we accumulated several thousands of published articles and used data mining, Latent Semantic Indexing, and Latent Dirichlet Analysis (LDA) techniques to characterize the research landscape on COVID-19. The outcome of this research is expected to paint a picture on what has been done, what patterns are found to be significantly consistent, and what else needs to be explored (future research directions) relevant to the characterization and management of this epidemic.

Sponsors: Oklahoma State University, University of Wisconsin – Whitewater, University of Dayton

PI/PDs: Dursun Delen

University of Wisconsin – Whitewater: Behrooz Davazdahemami

University of Dayton: Hamed Majidi Zolbanin

 

Identifying Adverse Drug Events with Big Data Analytics

In pharmacovigilance terminology, Adverse Drug Event (ADE) is a general term that refers to any injury caused by a medication. Although, pharmaceutical companies conduct rather extensive, time-demanding clinical studies to identify such adversities beforehand, it is not possible to do so for unexpected and slow-moving adverse outcomes. This research aims to discover such ADRs, using Big Data and advanced AI (machine learning techniques). The ultimate goal is to use HER, social media/network, medical literature, and biological/chemical databases to develop inelegant systems that detect ADR, thereby saving human lives.

Sponsors: Oklahoma State University, University of Wisconsin - Whitewater

PI/PDs: Dursun Delen

University of Wisconsin – Whitewater: Behrooz Davazdahemami

 

Improving Student Retention with Predictive Analytics

Accurately predicting and ranking students that are at risk of attrition is the key component of any retention management system. The goal of this research project is to use historical data to develop machine learning based prediction models to accurately identify the freshmen students that are at a greater risk of dropping out after their first year of college. The system not only predicts those students that are at risk but also prioritizes them based on their likelihood of dropping out so that the limited resources for the intervention and retention programs can optimally be utilized. 

Sponsor: Oklahoma State University

PI/PD: Dursun Delen

 

Developing a Decision Support Systems for Predicting the Financial Success of Hollywood Movies

Motion picture business is one of the riskiest endeavors for investors, especially in today’s ever-changing needs and wants, and likes and dislikes of the potential audience. In this study, we aim at developing a Web-based DSS (which we refer to as Movie Forecast Guru, or MFG in short) for investors, movie producers, distributors, and exhibitors to make better decisions in their selection of movie projects. In addition to predicting the box-office success of potential movie projects, this DSS is also capable of assessing the importance and contribution of movie parameters such as genre, super stars, technical effects, release time, etc.

Sponsor: Oklahoma State University

PI/PD: Dursun Delen

 

Balanced Scorecard-based Analysis of Customer Expectations for Cosmetology Services: A Hybrid Decision Modeling Approach

The goal of this study is to analyze and characterize customer expectations in the cosmetics sector. By employing a multi-criteria decision analysis methodology, the weighted importance of the underlying criteria is identified, and leading cosmetic service providers are ranked. The findings of the study indicate that consumer-focused criteria (i.e., diversification of services, feedback on the product and services, and customer loyalty) have the most significant impact on the success of the cosmetology firms in Ukraine.

Sponsors: Oklahoma State University, Kharkiv National University of Economics - Ukraine, Medipol University - Turkey

PI/PDs: Dursun Delen

Kharkiv National University of Economics - Ukraine: Oleksandr Dorokhov, Liudmyla Dorokhova,

Medipol University - Turkey: Hasan Dinçer, Serhat Yüksel

 

ICT4D and the Capability Approach: Understanding How Conversion Factors Affect Opportunity and Process Freedoms at the Country-Level

Prior macro-level research on ICT4Ds has measured country-level development using resource- or utilitarian-based approaches. We argue for a people-centered lens using the capability approach, using opportunity and process freedoms. Four conversion factors of ICTs are identified as enablers/restrictors of opportunity or freedoms. Using archival data and a 2SLS model, we test ICT-cost and ICT-infrastructure, and the interaction of e-participation and freedoms on ICTs to predict a country’s human development (HD). Results suggest that cost and infrastructure significantly affect HD, e-participation interacts with freedoms on ICTs such that freedom is only effective when accompanied by high levels of e-participation within a country.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Gabriel Bahr, Andy Luse

 

International Technology Diffusion, Development, and Trading Partner Spillovers

The purpose of this paper is to expand ICT4D literature by investigating the associations between international trade of technology merchandise and development across countries. Using a spatial autoregression model and data on 45 upper-middle and high-income countries from 2009 to 2018, we examine the effects of imports and exports of technology driven trade on two measures of development (GDP and Human Development Index). Additionally, we define spatial borders through a trade partner network and discover spillover effects of trade on development through the associated trading partner countries.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Gabriel Bahr, Andy Luse

 

The Role of Technological Progress in Vertical Specialization and Economic Growth

Previous research has studied how ICT adoption impacts trade on economic and human growth. Countries contribute to the global supply chain (GSC) with various levels of intermediate to final production. This research investigates to what extent countries with a higher intermediate to final product trade ratio and a higher IT skills/capabilities see faster levels of growth (GDP & HDI) than countries with lower IT skills/capabilities over time. Using 2SLS and data on 82 countries spanning 2005 to 2015, we examine the moderating impact of IT Skills/Capabilities with vertical specialization on economic growth and human development.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Gabriel Bahr, Andy Luse

 

The Neuro-Correlates of Information Privacy Concerns and Trust: A Longitudinal Study of Approach-Avoidance Behavior Using EEG

Privacy research has mainly focused on cognitive, conscious conceptualizations for privacy concerns and trust. Not much is known in how privacy operates in the subconscious mind. We posit, in a privacy-salient context, that trust operates as an approach-mechanism for information sharing; privacy concerns operates as an avoidance-mechanism. Using a longitudinal experimental design, we determine the extent to which levels of privacy influence approach/avoidance behavior. Additionally, whether the order of privacy level influences sharing behavior.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Andy Luse

 

The Role of Psychological Contract Violations in Social Media Platforms

Online business entities rely on privacy seals and user agreements to facilitate user information sharing. Interactions among users of social media platforms (SMP) do not rely on user agreements. As a form of social exchange, information sharing on SMPs uses a psychological contract (PC; implicit and assumed reciprocal obligations). This study investigates how PC violations (PCVs) affect sharing intentions on SMPs. We find that sharing intention is negatively influenced by interpersonal and institutional PCVs through privacy concern and trust. PCV by another user positively influences the perceived violation by the SMP, suggesting a collateral damage of interpersonal-PCV towards the SMP.

Sponsors: Oklahoma State University, Oregon State University

PI/PDs: Bryan Hammer

Oregon State University: Forough Nasirpouri Shadbad

 

Privacy as a Multidirectional Problem: A Social Relations Model of The Reciprocation of Privacy and Trust Using Network Analysis

Previous research on privacy (IS, Marketing, Management, Psychology, etc.) models information exchange in privacy salient situations as unidirectional, often from the perspective of a single user. As a social construct, privacy operates in social exchanges in which information moves between and among groups of individuals. Using network analysis, we model privacy and trust within a social relation model. Data come from an organization that uses a social media platform as its primary communication tool. We determine that trust is a reciprocating mechanism within relationships; however, privacy information concerns are not reciprocated, especially between management and subordinate relationships.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Andy Luse

 

Information Sharing as a Multidimensional Phenomenon: A Multilevel Study of Multiplex Relationships, Privacy, and Trust in Social Media Platforms

Research on privacy and trust often model relationships (interpersonal, business-consumer, etc.) as unidimensional, lacking depth. Prior research indicates multidimensional relationships enhance trust, resource sharing, and satisfaction. This research proposes that multidimensional (i.e. multiplex) relationships increase trust, decrease privacy concerns, and increase information sharing in social media platforms (SMP). Data was gathered from an organization utilizing Facebook as their primary communication platform. Results suggest that more multiplex relationships lead to information exchange, especially when information sensitivity increases.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Andy Luse

 

The Fear of Social Exclusion and Our Need to Belong: A Study of Interpersonal Privacy and Trust in Social Media Platforms

All individuals have an innate desire to belong to society in order to reduce costs of living as well as experience a reciprocation of welfare. Social media platforms (SMP) provide a vehicle that delivers a means to experience this. This research proposes that individuals’ fear of social exclusion and goal-directed enjoyment leads to information sharing in SMP While enjoyment influences all types of information (low, medium, high), social exclusion only influences sharing of low-sensitive information. Interpersonal trust leads to high-sensitive information sharing, but not medium- or low-sensitive; interpersonal privacy concern decreases medium- and low-sensitive information sharing, but not high.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Andy Luse

 

The Antecedents of Habit on IS Continuance

This study theorizes the antecedents of the habit construct in hedonic IS usage. Studies of habit in IS investigated habit as a construct in both utilitarian and hedonic contexts, but the link between habit and hedonic IS usage isn't fully understood. Investigating the antecedents of habit should help establish a clearer picture. We investigate social network site and online gaming users through MTurk anonymous surveys to better understand the link between habit and antecedents from the literature.

Sponsor: Oklahoma State University

PI/PDs: Bryan Hammer, Jerome Kirtley, Andy Luse

 

Interruptions and Information Recall: Differences Between Virtual and Face-to-Face Learning

This study investigates the link between sensory interruptions and information recall in computer-mediated learning. There is a dearth of literature concerning sensory interruptions in IS literature and with the rising prevalence of virtual learning in the current environment, investigation of this phenomenon is critical. We will conduct an experiment combined with a survey to assess the effect of visual and audio interruptions on information recall.

Sponsors: Oklahoma State University

PI/PDs: Bryan Hammer, Jerome Kirtley, Andy Luse

 

Are You Game? A Meta-Analysis of Gamified Elements and Behavioral Outcomes

Commercial systems contribute increasing business value by playing a pivotal role in enhancing performance of firms (Melville et al. 2004). Despite the proliferation of technology in our lives, creating systems that maintain user engagement is a struggle for vendors. Previous research has investigated the interplay between gamified elements and user interaction. Using a meta-analysis approach, this research investigates hundreds of published research to investigate the saliency of gamified elements with different types of users and systems.

Sponsors: Oklahoma State University, Oregon State University

PI/PDs: Bryan Hammer, Andy Luse, Gabriel Bahr, Jerome Kirtley

Oregon State University: Forough Nasirpouri Shadbad

 

Hacking the Value Gap: Cybersecurity Investments, Cybersecurity Talent, and Vulnerability Relative to Peers

Cybersecurity investments, when publicly emphasized, create economic rents through gained legitimacy from stakeholders and a reduction in the cost of capital. The results suggest: 1) Publicly Emphasizing Cybersecurity Investments (PECI) are associated with a generally positive value as measured by Tobin’s q, return on assets, and return on sales, 2) PECIs accompanied by security talent generate significantly higher gains, and 3) PECIs are more profitable for under-performing firms as well as over-performing firms. While PECIs without sufficient talent support does not significantly reduce subsequent cyber breaches, it generates market rewards for under- and over-performing firms.

Sponsors: Oklahoma State University, City University of Hong Kong, Temple University, Purdue University

PI/PDs: Bryan Hammer

City University of Hong Kong: TJ Zhang

Temple University: Taha Havakhor

Purdue University: Mohammad Rahman

 

Do I need to be liked to do my job? Perception on Information Security staff and Success of Cooperative Security Operations

This research examines the effect of employees’ perception on their information security staff on the success of security operations. The extent research has identified various mechanisms, such as sanctions, incentives, and employee training programs, that can improve the performance of information security. We propose that how employees perceive their security team (e.g., controller, projector, enabler, etc.) also plays critical roles, directly and indirectly, in security operations by encouraging or discouraging security-enhancing behaviors. The study will extend the model of security enhancing behaviors and suggest additional methods to improve information security controls.

Sponsor: Oklahoma State University

PI/PD: JinKyu Lee

 

The Role of Individual Differences in Acceptance of Information Security Policies

Previous studies on corporate information security pointed out that employee incompliance is a major causes of information security incidents. While extant literature suggests that organizations can adopt various incentives and training programs to encourage employees’ compliance with information security policies, most studies considered employees as an invariant group of people regardless their paygrade, job type, industry, etc. In this study, we explore personal factors that can moderate employees’ conformity level in presence of compliance incentives and training programs. This study will identify major personal dispositions that can cause the disparity in policy compliance behaviors and propose a solution. 

Sponsor: Oklahoma State University

PI/PD: JinKyu Lee

 

Technical Control or Managerial Control? – A Decision Making Framework for Infosec Control Selection

Employee training has been widely recognized as one of the most important means to strengthen the information security posture of an organization. However, its complementary and supplementary roles with technical measures in a corporate security architecture has not been clearly understood. This study examines the effectiveness of employee trainings on organizational security posture in relation to technical security countermeasures for various types of information security threats. This study will focus on identifying underlying characteristics that determine the control effectiveness and develop a decision-making framework for managers who need to select an optimal mix of technical and managerial security controls.

Sponsor: Oklahoma State University

PI/PD: JinKyu Lee

 

Strong vs. Weak Theory:  An Evaluative Mechanism for Theoretical Development

The goal of many theoreticians is to develop sound theory that will be utilized within their field both by researchers and practitioners.  Yet, scholars have not arrived at a consensus concerning what constitutes appropriate theoretical structure. In this paper, we offer an approach to theory design and analysis based on a categorization of strong and weak theory structure.  We first offer a concrete definition of the meaning of strong and weak theory that is based on a variety of literature. Second, we apply this evaluative framework to a prominent stream of theory development and discuss the nature of theory evolution.

Sponsors: Oklahoma State University, Iowa State University

PI/PDs: Andy Luse, Bryan Edwards

Iowa State University: Anthony Townsend

 

Does Technology Thwart Gender Stereotypes: An Impression Formation-based Examination of the Differential Influence of Technology across Gender and Message

This research examines the relationship between gender, message bias, and technology use on the way that observers form impressions of others. Building on impression formation and gender stereotype research and theory, we develop a two-study research methodology for examining how impressions are formed of technology users. The results of our two studies indicate that technology use is an important component in impression formation, significantly inhibiting the effects of gender stereotyping, such that women and men are not evaluated differently based upon their apparent competency in using technology nor on the content of their messaging.

Sponsors: Oklahoma State University, Iowa State University

PI/PDs: Andy Luse

Iowa State University: Anthony Townsend

 

Company-Sponsored Online Co-Creation and Financial Incentives: The Impact of Intrinsic Motivation on Participation Intention

In this study, we use LEGO Ideas, a prominent COCB, as an exemplar and employ a between-subjects randomized experimental design to examine the effect of different types of financial incentives on IM’s impact on participation intention in a COCB context, either directly or indirectly through personal innovativeness in the domain of information technology.  Our findings suggest that focused financial incentives, representing situations where financial rewards are administered exclusively on the basis of excellent performance, offer the best outcome for predicting PI.  Findings provide support for cognitive evaluation theory and insight into the role of financial incentives in a COCB context.

Sponsors: Oklahoma State University, Iowa State University

PI/PDs: Andy Luse

Iowa State University: Anthony Townsend, Sidharth Baswani

 

Using a Virtual Lab Network Testbed to Facilitate Real-world Hands-on Learning in a Networking Course

The use of an Internet testbed technology named ISEAGE allows students to design and implement fully functional networks using public IP space that is contained in the testbed. To the students, it appears as if they were directly connected to the Internet while still being protected. This paper shows that ‘real world’ projects using virtual lab technology can have a positive effect both on objective networking knowledge, as well as subjective self-assessments of self-efficacy with regard to implementing the technology. It also demonstrates that ‘real world’ final projects encourage student thinking at upper levels of Bloom's taxonomy.

Sponsors: Oklahoma State University, Iowa State University

PI/PDs: Andy Luse

Iowa State University: Julie Rursch

 

Gophish: Implementing a Real-World Phishing Exercise to Teach Social Engineering

Social engineering is a large problem in our modern technological world, but while conceptually understood, it is harder to teach compared to traditional pen testing techniques. This research details a class project where students implemented a phishing exercise against real-world targets. Through cooperation with an external corporate partner, students learned the legal, technical, behavioral, analysis, and reporting aspects of social engineering. The outcome provided both usable data for a real-world corporation as well as valuable educational experience for the students.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Jim Burkman

 

This Isn’t Your Parent’s TV Show…Oh Wait, It Is

Whether it be old games, books, technology, movies, or TV shows, the prevailing thought is that the younger generation prefers newer things. While this view may be perpetuated online and in popular press, it may also be less than accurate as data actually shows younger generations preferring older content. Utilizing Uses and Gratifications Theory, this research tests this assumption by tracking favorite TV shows of Millennials and Gen Z’ers over a seven-year period. Results show that these individuals actually prefer non-current TV shows and that the level of “non-currentness” of their preference is growing over time.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Jim Burkman

 

Wearables in the Workplace: Examination Using a Privacy Boundary Model

Wearable types can take many forms but this study focuses on RFID wearables due to their low cost, proven durability and reusability (Zhu & Hou, 2020). This research investigates the use of RFID wearables in the context of a corporate environment. Utilizing privacy boundary research, findings show that while being monitored negatively impacts employee satisfaction, this satisfaction further varies based on the voluntary nature of the implementation and the gender of the employee. Findings suggest that greater transparency in implementation may alleviate some of the negative aspects of implanting such technologies in the workplace.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Jim Burkman

 

Hot or Not: The Impact of Self-Perceived Facial Attractiveness on Webcam Use During Virtual Meetings

This research investigates the impact of facial attractiveness in the decision of an individual to display their webcam during a videoconference. Results show that while men are driven by self-views of their own facial attractiveness, women are instead driven by their beliefs about what others think of their facial attractiveness. This provides important information for those who wish to create a richer interaction for the widespread use of videoconferencing tools.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Jim Burkman, Erin Stewart

 

Hackalytics: Using Computer Hacking to Engage Students in Analytics

This teaching brief describes a novel approach to teaching analytics through computer hacking. Students are exposed to the entire data lifecycle by first collecting intrusion detection data through the hacking of other student machines and then utilizing simple analytics procedures to analyze this data. Quantitative and qualitative results show that the students enjoy the activity both in terms of the fun of hacking their fellow classmates as well as analyzing this data in an area less utilized in analytics instruction – security analytics. Three levels of the exercise are provided as well as how-to materials for students to run the exercise.

Sponsors: Oklahoma State University, Oregon State University

PI/PDs: Andy Luse

Oregon State University: Forough Shadbad

 

Best of Both Worlds: The Inclusion of Gamified Elements in Virtual Lab Environments to Increase Educational Value

This research explores the idea of investigating both contexts within one unified platform. We examine whether using gamified elements within virtual labs is effective in enhancing learners’ educational performance. Particularly, we employ leaderboards as a motivational gamification mechanism for more engagement and participation that can result in higher learning outcomes. Using a sample of students, our results show that utilization of gamification within a virtual lab environment causes students to exhibit higher performance in terms of more task accomplishments (specifically those tasks that are more complex in nature) and higher self-efficacy.

Sponsors: Oklahoma State University, Oregon State University

PI/PDs: Andy Luse, Gabe Bahr, Bryan Hammer

Oregon State University: Forough Shadbad

 

Positive Spillover Effects of Mask Mandate Policy and COVID-19 Spread

The mean daily case growth dropped 1.5 to 2.9 percent more following mask mandates for cities subject to the policy relative to non-mandate cities. We also examined whether mask mandate effects spilled over to neighboring municipalities without mandates and found evidence that spillover effects do occur. The spillover framework extends work in relational mobility to demonstrate that a relationally mobile society can have not only negative effects with regard to the spread of the virus, but also positive effects with regard to mask wearing spillover. This argues that mask mandates by major metro areas can be beneficial to neighboring communities.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Greg Eaton, Jared Taylor, Ramesh Sharda

 

Learned Helplessness Attributional Scale (LHAS): Development and Validation of an Attributional Style Measure

In answer to the call to increase the use of attribution theory, we look to both the theory of learned helplessness and Weiner’s attribution theory to create a new set of scales to provide a stable, parsimonious instrument for measuring attributions.  Twelve sections of four courses across ten semesters were used to develop the scales and test them across groups and time.  The final result is a new measurement tool, the Learned Helplessness Attribution Scale (LHAS), that demonstrates solid psychometric properties.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Jim Burkman

 

Blocking Effects of Information Sensitivity and Approach-avoidance Disposition on Online Information Disclosure: A Longitudinal Experiment Using EEG

We theorize that an overarching approach-avoidance mechanism drives information disclosure in which privacy- and trust-related concepts are driven by avoidance tendencies and approach tendencies, respectively. We posit blocking effects and approach-avoidance dispositions explain the inconsistencies. Using a longitudinal experimental design with EEG, we found that while sharing behavior of low sensitive information is not affected by either the approach-avoidance tendencies of the individual or initial information exposure, the sharing of highly sensitive information is significantly affected by both, such that disclosure is negatively impacted by initial exposure to highly sensitive information for those who display avoidance tendencies.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Bryan Hammer

 

Information Sharing as a Multidimensional, Dyadic Problem: A Multilevel Study of Multiplex Relationships, Privacy, and Trust

Using network theory, we theorize that privacy concerns, trust, and information sharing occur at two levels: relational (i.e., dyadic) and individual. Relationships characterized as multiplex, or more multidimensional, are richer and experience greater trust while reducing privacy concerns. Utilizing data collected from an organization using Facebook as their communication and organization platform, we analyze our data using a Bayesian multilevel model approach. Our results indicate that privacy concerns operate mainly through the individual level while trust operates at the relational level. Our findings suggest that privacy mechanisms are more complex than previously modeled and that they depend on interpersonal relationships.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Bryan Hammer

 

Are Some Countries Wasting Their Time and Money with ICT4D Initiatives? A Process Freedom Approach to Understanding ICT4D Barriers

Using publicly available archival data and a 2SLS model with instrumental variables, we test ICT cost, ICT infrastructure, and the interaction effect between e-participation and freedom of expression on ICTs to predict a country’s human development. Results suggest that both ICT cost and infrastructure significantly affect human development and that e-participation interacts with freedom of expression on ICTs in a way that freedom of expression is only effective when accompanied by high levels of e-participation within a country.

Sponsor: Oklahoma State University

PI/PDs: Andy Luse, Bryan Hammer, Gabe Bahr

 

Journal Rankings and Impact Factors: A Comparative Analysis

Publishing in journals of high quality and reputation has become increasingly important for faculty performance reviews, promotion and tenure.  The jury is still out regarding the best way to assess publications and varies widely among universities.  Traditionally, international universities have depended more on impact factors while nationally, results of journal ranking studies have taken precedence over impact factors which are based on cite scores.  This study investigates journal rankings and impact factors for business related publications looking at the correlation between the two.

Sponsor: Oklahoma State University

PI/PD: Jeretta Horn Nord

 

Critical Components in Organizational Performance

Organizational performance is one of the most important factors leading to a company’s success.  Recognizing the vital role of competencies, knowledge-oriented leadership, and innovation in organizations, there is a need to study how these variables affect organizational performance. This research builds a model with four constructs, i.e., competencies, knowledge-oriented leadership, innovation, and performance within manufacturing companies to find out, through path modeling, 1) the effect of competencies on innovation, 2) the effect of knowledge-oriented leadership on innovation, and 3) the effect of innovation on performance. The survey instrument included four constructs – Competencies, Knowledge-oriented Leadership, Innovation, and Performance. 

Sponsor: Oklahoma State University

PI/PDs: Jeretta Horn Nord, Alex Koohang, Joanna Paliszkiewicz, Marcin Soniewicki

 

Data Analytics in Organizations: Leadership, Management, Talent, and Performance

The success of today’s organizations depends on data analytics—obtaining data, analyzing it, and using the results to make informed decisions. Although the significance of analytics is recognized more than ever by those in businesses, many lack the leadership and talent to optimize the transition from data analytics to data-driven decision making. This research investigates the state of data analytics in organizations through an investigation of leadership, management, talent, and performance.

Sponsor: Oklahoma State University

PI/PD: Jeretta Horn Nord

 

The Internet of Things (IoTs)

Those in the emerging digital world have recently witnessed the proliferation and impact of IoT-enabled devices. The Internet of Things (IoTs) has provided new opportunities in the technology arena while bringing security, privacy, and trust challenges to an increased level of concern. This research investigates the usage, benefits, and challenges of IoTs in organizations. The research has both practical and theoretical impetus since IoT is still in its infancy, yet is considered by many as the most important technology initiative of today.

Sponsor: Oklahoma State University

PI/PD: Jeretta Horn Nord

 

Using the Gaussian Copula to Generate the Predictive Distribution in Monotonic Nonlinear Models: An Efficient Resampling Approach

We present a resampling approach for generating the predictive distribution of a dependent variable that has monotonic nonlinear relationships with its predictors. The procedure provides an empirical estimate of the predictive (conditional) distribution in terms of the original variables without requiring analyst intervention to identify appropriate transformations (and back-transformations) of variables. This allows predictions based on the estimated conditional expectation, and prediction intervals based on the estimate of conditional variance. It employs the well-known Gaussian copula, is easily implementable and is computationally efficient.

Sponsors: Oklahoma State University, University of Oklahoma

PI/PDs: Rathindra Sarathy

University of Oklahoma: Krish Muralidhar

 

When will I get out of the hospital? Modeling Length of Stay using Comorbidity Networks

Using the EMR hosted by CHSI, we build models for predicting hospital length of stay by incorporating historical and probable comorbidities that a patient is likely to face during their hospital stay. The results show significant improvement in predictive performance.

Sponsors: Oklahoma State University, Auburn University

PI/PDs: Ramesh Sharda

Auburn University: Pankush Kalgotra

 

Pandemic Information Support Lifecycle: Evidence from the Evolution of Mobile Apps during COVID-19

We propose a pandemic information support lifecycle (PISL) consisting of five phases: awareness, preventive care, active information, confidence building and evaluation. We validated this PISL using analysis of the mobile apps developed worldwide.

Sponsors: Oklahoma State University, Auburn University

PI/PDs: Ramesh Sharda

Auburn University: Pankush Kalgotra, Ashish Gupta

 

Examining multimorbidity differences across racial groups: a network analysis of electronic medical records

Using the EMR hosted through CHSI, we study health differences by analyzing multi-morbidities among seven population groups based on race. Our multimorbidity network analysis identifies specific differences in diagnoses among different population groups, and presents questions for biological, behavioral, clinical, social science, and policy research.

Sponsors: Oklahoma State University, Auburn University

PI/PDs: Ramesh Sharda, Julie Croff

Auburn University: Pankush Kalgotra

 

What should I believe? Exploring information validity on social network platforms

We develop a theoretical framework to explore the accuracy and objectivity of oscial networks content by employing social capital theory. The proposed and validated measures can help assign an accuracy and objectivity score to a conversation taking place in social media.

Sponsors: Oklahoma State University, Wright State University

PI/PDs: Ramesh Sharda

Wright State University: Daniel Asamoah

 

How Can Our Tweets Go Viral? Point-Process Modelling of Brand Content

We develop and test stochastic models based on Hawke’s process to be able to predict which tweets are likely to go viral.

Sponsors: Oklahoma State University, Wright State University

PI/PDs: Ramesh Sharda

Wright State University: Amir Hasan Zadeh

 

Analytics/Data Science Decision Support for Management of Oklahoma COVID pandemic

We assist the State of Oklahoma with data accuracy analyses and positivity rate changes to better understand and mitigate the Covid-19 pandemic.

Sponsors: Oklahoma State Department of Health

PI/PDs: Ramesh Sharda, Andy Luse

 

COVID Increase Drives Decrease in Travel Risk Perception

This is a comparative analysis of perceived international travel risk immediately prior to COVID outbreak and in the months following most airlines returning to near full capacity.

Sponsor: Oklahoma State University

PI/PD: Mark Weiser

 

Task-based Self-efficacy and Perception Changes from Short-term Study Abroad Experiences

This study evaluates the practical value of short-term faculty-led study abroad experiences to increase an individual's efficacy in tasks specifically related to traveling and interacting abroad, and in comfort and security perceptions about the country of travel and other countries.

Sponsor: Oklahoma State University

PI/PD: Mark Weiser

 

Close to Home: A Survey of Municipal Policies for Short-term Home Rentals

This study surveys municipal legislation from small cities in which a Division 1 FBS school is located to categorize approaches in developing home-sharing markets.

Sponsor: Oklahoma State University

PI/PD: Mark Weiser

 

Impacts of Smart Technology on Short-term Rentals Operations

This study analyzes the financial and operational impacts of deploying smart technologies in short-term rentals. Landlords are usually not co-located with lodging units rented through short-term agents, such as Airbnb and VRBO. Application of smart thermostats, plugs, and energy monitors can have a significant impact on costs without a comparable increase in operational burden. Using a case study of five properties, we assess the impact of these devices and explore additional benefits derived from behavioral changes by tenants due to the presence of these devices.

Sponsor: Oklahoma State University

PI/PD: Mark Weiser