Dheeraj Sharma

Bio: Dheeraj Sharma is an academic researcher from Indian Institute of Management Rohtak. The author has contributed to research in topics: Supply chain & Empirical research. The author has an hindex of 3, co-authored 13 publications receiving 184 citations.

Unethical Pro-organizational Behavior: A Systematic Review and Future Research Agenda

Abstract: Since the conceptualization of unethical pro-organizational behavior ten years ago, scholarly interest in exploring this phenomenon has multiplied. Given a burgeoning body of empirical research, a review of unethical pro-organizational behavior literature is warranted. This study, therefore, systematically reviews the extant literature on unethical pro-organizational behavior and presents a comprehensive theory-based review of the past developments in this field. We classify previous studies based on their underlying theoretical perspectives and discuss the antecedents and consequences of unethical pro-organizational behavior in work context. We also explicate the boundary conditions under which the influence of these antecedents gets accentuated or alleviated. Overall, this study synthesizes past knowledge to elucidate why, how, and when unethical pro-organizational behavior unfolds in the workplace. Finally, the gaps in the extant theorization are identified and an agenda for future research is proposed.

Big data analytics and machine learning: A retrospective overview and bibliometric analysis

Abstract: The research and practice of information systems have progressed by leaps and bounds due to the emergence of big data analytics and machine learning. The paper undertakes a bibliometric study to analyze the contributions of major authors, universities/organizations, and countries in terms of productivity, citations, and bibliographic coupling. A sample of 2160 articles from the Scopus for the period 2006–2020 is the basis of the study. The publications are grouped into five clusters, of which Cluster 1 is consistently dominant in the information systems publication landscape. Cluster 2 includes published studies on the Internet of Things, security, and cloud computing, which have also been widely researched. Cluster 3, the third-largest cluster, has attempted to investigate social media analytics. Cluster 4 aims to look into the impact of classification and predictive, which is found to have sustained research interest. Topics with scant coverage in terms of papers are primarily in Cluster 5, indicating saturation in the area and the need for conducting inter-disciplinary studies. The results of our study provide valuable insights for potential contributors and global audiences in terms of emerging topics for research.

Family incivility and instigated workplace incivility: How and when does rudeness spill over from family to work?

Abstract: Extant research has documented the role of workplace-related factors in eliciting uncivil employee behaviors in the workplace, while the role of family-related variables has been largely overlooked Drawing on the work-home resources model and the conservation of resources theory, the present study attempts to bridge this gap in the literature by exploring the relationship between family incivility and instigation of incivility towards subordinates in the workplace In addition, this study examines the intervening role of family emotional exhaustion and the buffering role of mindfulness and LMX within the proposed relationship Results based on time-lagged survey data collected from 282 supervisor-subordinate dyads indicate that family emotional exhaustion mediates the relationship between family incivility and instigated workplace incivility Results also indicate that mindfulness weakens the impact of family incivility on family emotional exhaustion, while LMX dampens the impact of family emotional exhaustion on instigated workplace incivility Further, results suggest that mindfulness and LMX together mitigate the overall impact of family incivility on instigated workplace incivility through family emotional exhaustion This study is an attempt to explore the spillover effects of family-related variables on uncivil employee behaviors in the workplace Additionally, this study offers new insights with respect to the boundary conditions that may help to alleviate the ramifications of family incivility in the workplace The results of this study may be utilized by managers in developing appropriate measures to prevent the incidence of uncivil behavior in the workplace

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.