Organizational Leadership and Information Analytics at Leeds
Research Themes
- Research Methods
- Future of Work and Workers in the Digital World
- Ethics and Social Responsibility in the New Economy
- Digital Transformation and AI Integration
- Remote Work Dynamics
- Diversity, Equity, and Inclusion
- Employee Well-being and Mental Health
- Leadership Development and Succession Planning
- Data-Driven Decision Making
- Effective Teamwork
- Ethical Implications of Technology
- Globalization and Cross-Cultural Management
- Continuous Learning and Adaptability
No. 24
Management Information Systems Research Journal Rankings
14
Tenure/Tenure-Track Faculty
8
PhD Placements in the past 5 years
Organizational Behavior PhD Placements
Information Systems PhD Placements
Faculty Feature
Christina Lacerenza
Stone Family Faculty Scholar
Assistant Professor
How do leaders receive the kind of thoughtful feedback that truly improves their decisions? Christina Lacerenza explores how “right‑hand partners” help leaders see beyond their blind spots through a process called heedful challenging. Drawing on interviews with more than 70 chiefs of staff and executives, her research reveals how trust, perspective‑taking, and behind‑the‑scenes influence shape stronger organizational outcomes. The findings highlight how intentional partnerships between leaders and trusted advisors can elevate decision quality and strengthen organizations.
Jason Bennett Thatcher
Tandean Rustandy Esteemed Endowed Chair
Professor
Jason Thatcher's research focuses on how individuals and organizations make decisions in high-stakes digital environments. One recent study asked, "How does alignment between a job candidate's social media post and a hiring manager's beliefs affect hiring decisions?" The research found that perceived similarity can significantly influence hiring outcomes, contributing to theories of source credibility for academics and informing best practices and managing digital bias during recruitment for managers with the goal of helping managers understand how to find the right person for the job.
Academy of Management Review
Tony Kong
Jul. 2025, Vol. 50 Issue 3, p641-643.
Abstract: Konig et al. model is theoretically important. It proposes four types of CEO humor can differently influence infomediaries' social evaluations of organizations via (a) induced states of mind ("specific transient emotions, perceptions, and cognitive conditions") and (b) CEO disposition attributions (in conjunction with CEO reole expectations). Specifcally, "social evaluations of a primarily reflexive sociocognitive nature are informed via stats of mind and role-filtered attributions, while social evaluations of a reflective sociocognitive nature are exclusively influenced by role-filltered attributions."
Management Science
Dan Zhang
Additional author: Yan Liu
Oct. 2024, Vol. 70 Issue 10, p6835-6851.
Abstract: Consumers often receive a full or partial refund for product returns or service cancellations. Much of the existing literature studies cash refunds, where consumers get the money back minus a fee upon a product return or service cancellation. However, not all refunds are issued in cash. Sometimes consumers receive credit that can be used for future purchases, oftentimes with an expiration term after which the credit is forfeited. We study the optimal design of credit refund policies. Different from models that consider cash refunds, we explicitly model repeated interactions between the seller and consumers over time. We assume that consumers' valuation for the product/service varies over time and that there is an exogenous probability for product returns. Several interesting results emerge. First, a credit refund policy facilitates intraconsumer price discrimination for a single type of consumers with stochastic valuation. Second, an optimal policy often involves an intermediate credit expiration term, under which a consumer with a high product valuation always makes a purchase, whereas a consumer with a low product valuation may be induced to make a purchase as the credit approaches expiration, leading to a demand induction effect. Finally, a credit refund policy can be more profitable than a cash refund policy and can lead to a win-win outcome for both the firm and consumers under certain conditions. We also consider several extensions to check the robustness of our findings.
Manufacturing & Service Operations Management
Huanan Zhang
Additional authors: Stefanus Jasin, Chengyi Lyu, Sajjad Najafi
Jan/Feb. 2024, Vol. 26 Issue 1, p215-232.
Abstract: Problem definition: Assortment selection is one of the most important decisions faced by retailers. Most existing papers in the literature assume that customers select at most one item out of the offered assortment. Although this is valid in some cases, it contradicts practical observations in many shopping experiences, both in online and brick-and-mortar retail, where customers may buy a basket of products instead of a single item. In this paper, we incorporate customers' multi-item purchase behavior into the assortment optimization problem. We consider both the uncapacitated and capacitated assortment problems under the so-called Multivariate MNL (MVMNL) model, which is one of the most popular multivariate choice models used in the marketing and empirical literature. Methodology/results: We first show that the traditional revenue-ordered assortment may not be optimal. Nonetheless, we show that under some mild conditions, a certain variant of this property holds (in the uncapacitated assortment problem) under the MVMNL model; that is, the optimal assortment consists of revenue-ordered local assortments in each product category. Finding the optimal assortment even when there is no interaction among product categories is still computationally expensive because the revenue thresholds for different categories cannot be computed separately. To tackle the computational complexity, we develop FPTAS for several variants of (capacitated and uncapacitated) assortment problems under MVMNL. Managerial implications: Our analysis reveals that disregarding customers' multi-item purchase behavior in assortment decisions can indeed have a significant negative impact on profitability, demonstrating its practical importance in retail. We numerically show that our proposed algorithm can improve a retailer's expected total revenues (compared with a benchmark policy that does not properly take into account the impact of customers' multi-item choice behavior in assortment decision) by up to 14%.
Academy of Management Journal
Christina Lacerenza, Sabrina Volpone
Additional author: Liza Y. Barnes
Jun. 2024, Vol. 67 Issue 3, p704-736.
Abstract: Powerful leaders need to be challenged and pushed to consider uncontemplated perspectives. Research has indicated that employees in lower-power positions are best poised to challenge leaders, because these individuals better understand others' perspectives and have a different lens on day-to-day organizational issues compared to powerful leaders. While several well-known leaders rely on a lower-power employee (i.e., right-hand partner) to amplify their efforts, it is unclear how one becomes a right-hand partner or what this entails. Relying on qualitative data from 74 individuals (61 chiefs of staff and 13 leaders), we develop a process of heedful challenging: the process of presenting alternative perspectives to someone in an individualized manner. In this process, the lower-power employee utilizes their knowledge of the leader and their understanding of how organizational issues are impacting employees to thoughtfully challenge the leader by presenting differing perspectives and illuminating the implications of their behavior. We articulate how one becomes a right-hand partner through this process, present the defining characteristics and drawbacks of being a right-hand partner, and describe instances when this process goes awry. This work contributes to theory about unequal-power relationships and provides insight into how lower-power employees can broaden leader's perspectives.
MIS Quarterly
Sebastian Schuetz
Additional Authors: Yan Chen, Jens Forderer, Yusi Ma
Sep. 2025, Vol. 49 Issue 3, p1153-1168.
In recent years, ransomware has become one of the most dangerous cyber threats, with successful attacks causing severe operational disruptions and staggering damages. Rationally speaking, investors should react negatively to firms' ransomware disclosures, but this may not always be the case. Based on norm theory, we describe a paradoxical phenomenon wherein investors exhibit negative reactions to ransomware hits (i.e., events that led to operational disruptions) but positive reactions to near misses (i.e., events in which operational disruptions were narrowly avoided). The positive reactions occur due to an outcome bias in which near-miss events—events that are objectively negative but less severe than expected—are viewed positively instead of negatively. We tested these predictions by reporting on an investigation of stock market reactions to disclosures of ransomware hits vs. near misses. To do so, we assembled a comprehensive dataset of ransomware incidents disclosed by U.S. public firms. Using the event study method, we estimated abnormal stock market returns and found evidence in support of our predictions. First, in line with expectations, ransomware hits that led to the expected severe impact resulted in stock price drops of -4.40%. However, near misses, where disruptions were avoided, were rewarded with gains of 2.87%, confirming positive instead of negative reactions. This offers new insights into investors' biased responses to certain cybersecurity incidents. These positive reactions, however, represent a call for caution because, albeit seemingly favorable, they mask underlying risks.
Journal of Operations Management
Jason Thatcher
Additional Authors: Timofey Shalpegin, Tyson R. Browning, Ajay Kumar, Guangzhi Shang, Jan C. Fransoo, Matthias Holweg, Benn. Lawson
Jul. 2025, Vol. 71 Issue 5, p578-587.
The article delves into the integration of Generative Artificial Intelligence (Gen-AI) in academic research, particularly in Operations Management (OM), discussing its potential benefits and challenges. It addresses ethical concerns like privacy, bias, and the importance of human judgment in decision-making processes. Experts highlight the risks of epistemic, methodological, and systemic failures that could impact the reliability of academic knowledge, emphasizing the necessity for transparency and accountability in the responsible use of Gen-AI. The document offers a comprehensive overview of recent AI research, covering applications in research methods, biomedicine, social science, and policy implications, while stressing the importance of research integrity and ethical publishing practices.
MIS Quarterly
Jason Thatcher
Additional Authors: Daniel A. Pienta, Sriram Somanchi, Nishant Vishwamitra, Nicholas Berente
Mar. 2025, Vol. 49 Issue 1, p347-365.
This research note examines how sociocognitive influences can systematically distort crowdsourced ground truth in event-centric data through subgroups. The "wisdom of the crowd" is based on the assumption that consensus drives accuracy. While existing research addresses the tendencies of the overall crowd, this research note shows that identifiable subgroups within the crowd can systematically influence crowdsource validation. We conducted an immersive experiment to investigate whether crowd consensus can be systematically distorted by subgroup-based sociocognitive influences, such as affective polarization. In the experiment, raters from a range of subgroups with varying levels of affective polarization were asked to view and validate crisis data from a violent public riot in the year 2020. Relying in part on double debiased machine learning techniques, we analyzed heterogeneous treatment effects across subgroups. The results show that affective polarization and more extreme raters, via the constructs of loyalty and betrayal, distort consensus-based ground truth in different ways. This research note demonstrates how subgroup-based sociocognitive influences can systematically distort the results of consensus-based crowdsourced validation. Additionally, it provides guidance for research and practice on how to account for identifiable subgroups in the crowd. These findings challenge key assumptions about the wisdom of crowds and the accuracy of crowdsourced ground truth in event-centric situations.
MIS Quarterly
Jason Thatcher
Additional Authors: Martin Enger, Andreas Hein, Likoebe M. Maruping, Helmut Krcmar
Mar. 2025, Vol. 49 Issue 1, p91-122.
This research investigates the interplay of top-down control and bottom-up self-organization within digital platform ecosystems (DPEs), focusing on the formation and management of complementor coalitions. Although these coalitions can increase a DPE's generativity, they can also threaten its integrity. We investigate this tension by employing information ecology (IE) theory, which allows us to examine complementor coalitions as holons that navigate between self-assertiveness and integration within the structural hierarchies of DPEs. Utilizing an inductive, embedded case-study approach, we analyze the interplay between top-down control exerted by platform owners and the bottom-up selforganization of complementors in two enterprise software platform ecosystems. Our findings identify three distinct interaction modes—mandated, supported, and autonomous self-organization—each presenting hierarchical trade-offs between platform owner control and complementor autonomy. Our findings extend the prevalent owner-centric theory of platform governance by highlighting the significant impact of bottom-up self-organization on the governance and evolution of DPEs. We propose an integrated theory that accommodates these new dynamics, suggesting soft power as an effective governance mechanism. This study contributes to a deeper understanding of the complexities in governing DPEs and offers practical insights for managing top-down control and bottom-up self-organization in the evolving landscape of enterprise software DPEs.
Information Systems Research
Jason Thatcher
Additional Authors: Shih-Lun "Allen" Tseng, Heshan Sun, Radhika Santhanam, Shuya Lu
Dec. 2024, Vol. 35 Issue 4, p1743-1765.
Abstract: Current studies show gamification, the integrating of game design elements into target systems, enhances user engagement and instrumental task outcomes. Despite its potential for improving behavioral outcomes, gamification can also lead to maladaptive behaviors, behaviors directed at misappropriating gamified systems. We conceptualized gamified system maladaptive behaviors (GSMB), which involve technology and gamified task maladaptations. We developed a model that depicts three drivers of GSMB from design elements, how they fulfill or frustrate psychological innate needs, which in turn drive GSMB, and how GSMB affect task performance. We tested how the three drivers of design elements affect GSMB in Study 1 by empirically examining users of a gamified system, Pocket Points. The results support our conceptualization of GSMB, and design issues as its antecedents. To further unpack this relationship, we then employed a within-subject experiment and a follow-up survey in Study 2. By manipulating the design issues, we found that GSMB adversely affect task performance, because these users may focus too intently on winning the game, at the expense of task performance. By assessing the fulfillment of psychological needs, our findings suggest that design in gamified systems may not uniformly fulfill the satisfaction of psychological needs and consequently triggers GSMB. Despite the increasing interest in gamified systems and excitement about their potential positive impact on user engagement, a few studies have started to note gamification failures, which can result from user maladaptive behaviors, or behaviors directed at misappropriating gamified systems. In this research, we examine how such maladaptive behaviors can result from design issues of gamified systems and how such behaviors impact task performance. To date, little is known about design issues which may drive users to maladapt, and why they maladapt gamified systems. We systematically conceptualize gamified system maladaptive behaviors (GSMB) as having two dimensions: technology maladaptation and gamified task maladaptation. Based on goal-setting theory and self-determination theory, we develop a research model of GSMB. The model depicts three drivers of GSMB: game-task goals misalignment, game-task complexity, and gamification structure injustice, and how they fulfill or frustrate psychological innate needs (i.e., needs for autonomy, competence, and relatedness), which in turn drive GSMB. We conducted two studies using different contexts. We tested the model with Study 1 empirically examining users of a gamified system, Pocket Points. With Study 2, we employed a within-subject experiment. By manipulating the design issues, we assessed the fulfillment of psychological needs induced by the gamified system. The results largely support our conceptualization of GSMB and the research model, highlighting the design issues as the main drivers of GSMB, and that the greater the GSMB, the greater the negative impact on task performance. Findings from this research have implications for both information systems research and gamification practices.
Information Systems Research
Jason Thatcher
Additional Authors: Malte Greulich, Sebastian Lins, Daniel Pienta, Ali Sunyaev
Dec. 2024, Vol. 35 Issue 4, p1586-1608.
Abstract: Encouraging employees to take security precautions is a vital strategy that organizations can use to reduce their vulnerability to information security (ISec) threats. This study investigates how the bright- and dark-side effects of trust in organizational information security impact employees' intention to take security precautions. Employees who trust organizational security practices are more committed to protecting the organization and are more willing to take security precautions. To foster trust in organizational security practices and security commitment, ISec managers should establish a trusting security climate to ensure that employees can speak freely about the security problems they face in their work and receive support to resolve those problems if needed. This study also alerts managers to the potential adverse consequences of employees' trust in the organization's protective structures. We find that employees' trust in the organization's protective structures can backfire, making employees complacent regarding security. Further analyses indicate that security mindfulness mediates the influence of security complacency and security commitment on precaution taking. This study contributes by exploring and verifying the bright- and dark-side effects of trust in organizational ISec. Employees' precautionary security behaviors are vital to the effective protection of organizations from cybersecurity threats. Despite substantial security training efforts, employees frequently do not take security precautions. This study draws from trust theory and mindfulness theory to investigate how the bright- and dark-side effects of two conceptualizations of trust in organizational information security impact employees' precaution taking. Insights drawn from a survey of 380 organizational employees suggest that employees who trust their organization's security practices are more committed and less complacent in protecting their organization and more likely to take security precautions. In contrast, we find evidence of the dark-side effect of employees' trust in organizational protective structures by showing that such trust can lead to complacency regarding security. Analyses indicate that security mindfulness mediates the influence of security complacency and security commitment on precaution taking. These results highlight the crucial roles of security commitment, security complacency, and security mindfulness in shaping employees' precaution taking. This study contributes to information security research by providing empirical evidence concerning the simultaneous bright- and dark-side effects of employees' trust in organizational information security, thereby creating valuable opportunities for researchers to theorize about the ways in which trusting beliefs shape employees' security behaviors.
MIS Quarterly
Jason Thatcher
Additional Authors: Katharina Pflügner, Christian Maier, Jens Mattke, Tim Weitzel
Jun. 2024, Vol. 48 Issue 2, p679-698.
Abstract: Understanding how technostressors lead to technostrain, such as high job burnout or low job performance, has become a core question in information systems (IS) research and practice. To unpack this relationship, we build on general systems theory to argue that the next step for technostress research is to go beyond examining the independent influences of technostressors and discuss how their interdependencies lead to technostrain. To illustrate our argument empirically, we use fuzzy-set qualitative comparative analysis (fsQCA) and identify four configurations of high- and low-intensity technostressors that lead to high job burnout and one that leads to low job performance. We show that three types of interdependencies among technostressors, i.e., complementarity, contingency, and substitution, form configurations that lead to technostrain. Within these configurations, high-intensity technostressors can mutually enhance their effects and low-intensity technostressors can buffer the impact of other high-intensity technostressors on technostrain. The results help to explain why organizational interventions that address independent technostressors may fail if they do not account for the interdependencies among technostressors. Our work provides evidence of the need to further develop theories that explain how and why interdependencies among technostressors lead to technostrain.