Grade-O-Matic: A Tool to Test and Grade Programs

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Doyle, Mart; Shafer, Jeremy

Abstract: To improve learning in higher education, the primary focus should be on engagin ... Expand

Abstract: To improve learning in higher education, the primary focus should be on engaging students in a process that best enhances their learning--a process that includes feedback on the effectiveness of their learning efforts. " [Kolb & Kolb, 2005] If that is true of most subjects of higher education, it is doubly so for teaching programming in the college classroom. Learning programming and related topics requires experience and personal commitment. It requires effort, often prolonged effort, over time. Unfortunately, students (and business students in particular) regularly seek ways to minimize their investment of time and maximize their grade outcome. [Parks-Leduc, et. al., 2022] The only recourse for MIS/IS instructors is, then, to create graded programming assignments with a variety and quantity sufficient to coerce students into investing the time necessary for learning. However, grading student programs is a labor-intensive responsibility for faculty members. It is tedious and error prone. Grading programs consistently and in a timely manner is often a challenge for faculty members. Delays in graded feedback are detrimental to student learning. This paper presents an innovative tool called Grade-O-Matic. It can be used by both students and instructors to grade programs quickly and in large quantities. By using the Grade-O-Matic tool, faculty members can assign more graded programming assignments, and students can get immediate feedback on their work before turning it in to be graded. This paper describes the Grade-O-Matic tool, and its creation, from its inception to its current state using terminology of the Design Science Research Methodology (DSRM) [Peffers, et. al., 2007]. The distinctives of the tool, and how it is different from similar efforts, are noted.The paper concludes with anecdotal evidence to support the claim that the tool, and the immediacy it affords, supports student learning. Also noted are generalized principles that may support future efforts. Collapse

Topics: Python JavaScript

Methods: survey design science

Rising Above vs. Falling Below: When and Why Status Change Affects Interpersonal Helping in Workgroups

2023 | Organization Science | Citations: 0

Authors: Doyle, Sarah P.; Lount, Robert B.

Abstract: The current research sheds new light on how and why status hierarchies impact in ... Expand

Abstract: The current research sheds new light on how and why status hierarchies impact interpersonal helping by examining people’s reactions to recently experienced status change. Specifically, we incorporate findings from research on the self-serving attributional bias to theorize about how the direction of status change (i.e., a gain or a loss) can shape the extent to which people accept or deflect personal responsibility for their change in status, which we argue will then impact other-concern and, thus, their willingness to help. Further, we identify status change legitimacy as a key contingency that will strengthen or weaken the psychological and behavioral effects of status change. Among firefighter teams (Study 1), participants in the laboratory (Studies 2 and 3), and student teams (Study 4), we show that (1) status change impacts interpersonal helping through its impact on changes in other-concern and (2) status change legitimacy moderates the effect of status change on both other-concern and interpersonal helping. Additionally, we document an asymmetry with regards to the effects of status change on both other-concern and helping behavior (i.e., with the negative impact of a status loss being stronger than the positive impact of a status gain). Theoretical and practical implications are discussed. Collapse

Topics: team productivity missing data accounting

Methods: survey polynomial regression parametric test survey design two-way ANOVA

Business Capability Mining - Opportunities and Challenges

2023 | European Conference On Information Systems | Citations: 0

Authors: Drieschner, Clemens; Sensoy, Mert; Weking, Jörg; Krcmar, Helmut

Abstract: Business capability models are widely used in enterprise architecture managemen ... Expand

Abstract: Business capability models are widely used in enterprise architecture management to generate an abstract overview of an organization's business activities for reaching its business objectives. The creation and maintenance of these models are associated with a huge manual workload. Research provides insights into opportunities for automated modeling of enterprise architecture models. However, most papers address the application and technology layer and leave the business layer largely unexplored. Particularly, no research has been conducted on the automated generation of business capability models. This research uses 19 semi-structured interviews to identify possible automated modeling opportunities of business capabilities and related challenges. Based on this a business capability mining approach is developed. This research benefits both, practice and theory, by describing a situation-based business capability mining approach and identifying implementation scenarios. Collapse

Topics: application programming interface

Methods: qualitative interview personal interview business process modeling qualitative coding

Multi-criteria Large-Scale Group Decision-Making in Linguistic Contexts: A Perspective of Conflict Analysis and Resolution

2023 | Group Decision and Negotiation | Citations: 0

Authors: Du, Junliang; Liu, Sifeng; Liu, Yong; Tao, Liangyan

Abstract: As a universal phenomenon, conflicts exist widely in various fields such as poli ... Expand

Abstract: As a universal phenomenon, conflicts exist widely in various fields such as politics, economic life, military, and culture. Group decision-making techniques that effectively identify and resolve conflict during the decision-making process will result in stronger group consensus, while existing studies rarely discuss the multi-criteria large-scale group decision-making (LSGDM) from the perspective of conflict analysis and resolution. This paper systematically studies conflict analysis and resolution approach to obtain consensus decision results. Conflicts among decision makers (DMs) in LSGDM are divided into two kinds: goal conflicts and cognitive conflicts. Based on Pawlak conflict analysis, we introduce three relations among DMs, i.e., conflict, neutrality, alliance into multi-criteria LSGDM in linguistic contexts. Based on linguistic assessment, an improved Pawlak conflict analysis is used to analyze goal conflicts, and the alliance of DMs and the weight of criteria are obtained. According to three cognitive conflict relations, a conflict coordination and feedback mechanism is designed to resolve cognitive conflicts between alliance pairs. Finally, an illustrative example is used to verify the effectiveness and applicability of the proposed model. Collapse

Topics: decision making social network

Methods: computational algorithm business process modeling design science cross sectional research

Unravelling the Business Value of Artificial Intelligence

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Du, Kui; Li, Gaoyong; Li, Liang; Zhang, Wei

Abstract: This study aims to investigate how firms can prepare for artificial intelligenc ... Expand

Abstract: This study aims to investigate how firms can prepare for artificial intelligence (AI) adoption and how AI creates business values for adopting firms. We propose that, first, leveraging AI for value creation depends on the presence of an enabling resource foundation, consisting of a stack of technological and managerial resources. According to the real options theory, the stronger such a resource foundation is, the more valuable the option it creates for a firm to adopt AI, and consequently the firm is more likely to exercise the option to adopt. Second, we propose that, after adoption, the depth of AI use can have negative impacts on employee productivity, while the breadth of AI use can have positive impacts. We empirically validate these hypotheses based on a sample of 6,854 manufacturing firms in a coastal province in China. Collapse

Topics: artificial intelligence individual productivity organizational value value creation productivity

Methods: survey experiment regression analysis method

Theories: real options theory resource based view of the firm options theory

Does IT Enable Collusion or Competition: Examining the Effects of IT on Service Pricing in Multimarket Multihospital Systems

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Du, Kui; Tanriverdi, Hüseyin

Abstract: In the U.S., multihospital systems (MHSs) charge significantly higher prices fo ... Expand

Abstract: In the U.S., multihospital systems (MHSs) charge significantly higher prices for hospital services than stand-alone hospitals. Rivalry restraint theory suggests that MHS with multimarket contact (MMC) can tacitly collude and mutually forebear from price competition to keep their prices above competitive levels. We posit that the success of such MMC-induced rivalry restraints (the truce) is affected by two conflicting roles of IT at the corporate level and market unit levels, respectively. The corporate parent seeks to standardize IT applications enterprise-wide to coordinate market units as a means of jointly implementing the rivalry restraint strategy and keeping prices high enterprise-wide. However, market units, i.e., the member hospitals of MHS clustered in geographic patient markets, face competitive pressures to reduce their service costs. Market units seek to use differentiated IT applications to achieve cost reductions, which then fuel price competition in local markets, jeopardize the sustainability of the truce, and weaken the enterprise-wide price effects of the corporate parent's rivalry restraint strategy. In a longitudinal study of 195 multihospital systems in the U.S. in the 2005-2013 time period, we found support for these ideas. The corporate-wide standardization of the operational IT of MHS complements the rivalry restraint strategy to increase enterprise-wide prices. Market units' use of differentiated analytical IT reduces costs in local markets and weakens the price effects of the rivalry restraint strategy. The study advances IS research and practice by theorizing how the corporate-level and the market unit-level IT of a multi-unit, multimarket (MUMM) organization can have opposing moderating effects on the link between MMC and the average prices charged by the MUMM organization. Collapse

Topics: analytical information system operational information system database system health information system decision making

Methods: theory development robustness check instrumental variables estimation longitudinal research data modeling

Incorporating Multiple Knowledge Sources for Targeted Aspect-based Financial Sentiment Analysis

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

Authors: Du, Kelvin; Xing, Frank; Cambria, Erik

Abstract: Combining symbolic and subsymbolic methods has become a promising strategy as re ... Expand

Abstract: Combining symbolic and subsymbolic methods has become a promising strategy as research tasks in AI grow increasingly complicated and require higher levels of understanding. Targeted Aspect-based Financial Sentiment Analysis (TABFSA) is an example of such complicated tasks, as it involves processes like information extraction, information specification, and domain adaptation. However, little is known about the design principles of such hybrid models leveraging external lexical knowledge. To fill this gap, we define anterior, parallel, and posterior knowledge integration and propose incorporating multiple lexical knowledge sources strategically into the fine-tuning process of pre-trained transformer models for TABFSA. Experiments on the Financial Opinion mining and Question Answering challenge (FiQA) Task 1 and SemEval 2017 Task 5 datasets show that the knowledge-enabled models systematically improve upon their plain deep learning counterparts, and some outperform state-of-the-art results reported in terms of aspect sentiment analysis error. We discover that parallel knowledge integration is the most effective and domain-specific lexical knowledge is more important according to our ablation analysis. Collapse

Topics: microblog domain-specific language Twitter social media knowledge graph

Methods: sentiment analysis RoBERTa transformer model BERT XLNet

Emotional Synchrony and Viewers’ Consumption: Evidence from Live Streaming of Virtual Idols

2023 | International Conference on Information Systems | Citations: 0

Authors: Duan, Menghan; Zhang, Yueyue; Zhang, Qi; Zhang, Cheng

Abstract: Live streaming has become increasingly popular in recent years for users to bro ... Expand

Abstract: Live streaming has become increasingly popular in recent years for users to broadcast live events or experiences to an online audience in real-time. With the prevalence of the metaverse, virtual idols appear on the stage of live streaming. Unlike real human streamers, virtual idols are computer-generated avatars whose appearance does not exist in the physical world. Though existing literature has documented the effect of emotional displays of human streamers on viewers' behavior, whether emotional displays of avatar streamers affect viewers' behavior, especially viewers' consumption behavior has not yet been explored. To fill this gap, we focus on the live streaming of virtual idols and conduct deep learning approaches to investigate the emotional synchrony between avatar streamers and their viewers based on moment-tomoment data. Our analysis of large-scale video data shows that the larger the discrepancy between the streamers' acoustic-and text-emotions, the more likely the viewers will pay. This study sheds light on how avatars can be designed to leverage emotion to engage viewers in more consumption. Collapse

Topics: marketing management human AI collaboration microblog open source Python

Methods: deep learning computational algorithm XGBoost machine learning gradient boosting

An Investigation of Marketing Compensation in Medicine: The Impact of the Information Disclosure Regulations

2023 | HICSS | Citations: 0

Authors: Duan, Wenjing; Cheng, Sherri; Zhou, Wenqi

Abstract: Pharmaceutical scandals frequently occupy national media headlines, and these co ... Expand

Abstract: Pharmaceutical scandals frequently occupy national media headlines, and these controversial practices exacerbate the healthcare expenditure burden and cause ethical concerns. Big Pharma’s marketing strategies involve making various types and sizes of payments to healthcare providers to induce favorable prescribing behaviors for their drugs. Enacted in 2013, the Physician Payments Sunshine Act (PPSA) mandates company disclosures of payments to physicians. Its effectiveness has been explored in various settings, but there have been few rigorous academic studies, and a unified conclusion has not been reached. In this paper, we utilized unique datasets, including pre- and post-PPSA payment data from six major pharmaceutical companies, to examine the impact of state-level disclosure policies and the federal PPSA on pharmaceutical companies’ payments to physicians. Difference-in-difference analysis was adopted to study the dynamics of company payments to physicians before and after the PPSA. We found significant interactions for the state policies and the PPSA on all studied payment types for the six companies. The companies generally decreased their total payments to physicians and the number of paid physicians. However, the policy impacts differed across the payment types and companies. Collapse

Topics: marketing management database system missing data data breach

Methods: difference in differences self reported survey experimental group robustness check post analysis

Exploring perceptions of pro-environmental educational mobile applications based on semantic field analysis

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Duda, Ewa

Abstract: ... Expand

Abstract: Collapse

Topics: mobile application online learning system user behavior IT skill user experience

Methods: qualitative interview focus group