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Purpose The purpose of this paper is to illustrate the systematic role played by Six Sigma methodology in improving the quality of healthcare. The literature review identifies the relevant opportunities for successful introduction and development of Six Sigma approach in healthcare sector. Design/methodology/approach A systematic methodology to identifying literature on Six Sigma in healthcare is presented. Web of Science, Medline, Emerald Insight, ASQ and ProQuest databases (1998-2016) were searched, and 68 papers of fair methodological quality were identified. Findings The findings of the systematic review reveal a growing interest in research on Six Sigma adoption in healthcare. The findings indicate that Six Sigma applications in healthcare have been focused on the entire hospital with no real focus on a particular department or function. The key findings on benefits, success factors, challenges and common tools of Six Sigma from the existing literature are also presented in the paper. Research limitations/implications The papers included in the systematic review were peer-reviewed papers available in English. Due to these limitations, relevant papers may have been excluded. Moreover, the authors have excluded all conference and white papers for their inclusion in this study. Originality/value This paper can serve as a guide on how Six Sigma approach can be applied to improve the quality of healthcare. The authors also believe that this is possibly the most comprehensive systematic literature review on the topic and will set the foundation for various research avenues based on the key findings of this study.

PurposeThe pandemic has severely affected sharing economy businesses specially ride-hailing services due to high levels of human-touch points. This research investigates the impact of COVID-19 infodemic, identification, and emotional support on intention to use ride-hailing. The authors further examine the moderating effects of internalization, compliance, social currency and informational support in the proposed conceptual model.Design/methodology/approachThe data were collected from 412 respondents from Delhi in India, and hypothesized relationships were tested using hierarchical regression.FindingsThe results indicate that COVID-19 infodemic has a negative association with intention to use ride-hailing. Identification and emotional support show a positive association with intention to use ride-hailing. The results also support internalization and compliance as moderators between infodemic, identification and intention to use ride-hailing. Further, social currency and information support moderate the relationship between emotional support and intention to use.Originality/valueThis is the first research, which adds to the expanding literature on ride-hailing, especially during the post-pandemic period of “new normal”.

Alfred Korzybski argued that human potential, much like electricity, must be intentionally directed; otherwise, it manifests as social upheaval--revolutions, wars, and instability. History demonstrates that societies failing to harness human energy through innovation and progress often descend into chaos. In Manhood of Humanity, he advocated for strategic governance and social engineering to channel this dynamic force toward constructive development rather than destruction.

As Big Data has undergone a transition from being an emerging topic to a growing research area, it has become necessary to classify the different types of research and examine the general trends of this research area. This should allow the potential research areas that for future investigation to be identified. This paper reviews the literature on ‘Big Data and supply chain management (SCM)’, dating back to 2006 and provides a thorough insight into the field by using the techniques of bibliometric and network analyses. We evaluate 286 articles published in the past 10 years and identify the top contributing authors, countries and key research topics. Furthermore, we obtain and compare the most influential works based on citations and PageRank. Finally, we identify and propose six research clusters in which scholars could be encouraged to expand Big Data research in SCM. We contribute to the literature on Big Data by discussing the challenges of current research, but more importantly, by identifying and proposing these six research clusters and future research directions. Finally, we offer to managers different schools of thought to enable them to harness the benefits from using Big Data and analytics for SCM in their everyday work.

Disaster management (DM), within a broad field of operations management, is becoming an emergent area of interest for academics and practitioners. This study examines the literature evolving on disaster management linked to application of simulation modelling. Many literature review studies on disaster management are offered by numerous authors. However, broad analysis of various applications of simulation based modelling within a DM context are not adequate. As a result, the proposed research carries out a review of 100 papers published in numerous peer-reviewed academic journals during the period 2000 and January 2016. In particular, the paper presents a classification of publications based on the simulation technique(s) used; examines the disaster issues addressed by the technique (s) used; analyzes trends and identifies the impact of published research on simulation modeling pertaining to DM. This study would enable researchers to understand the significance of various simulation modelling techniques in resolving a variety of disaster related challenges.

Purpose The purpose of this paper is to review the existing literature on supply chain performance measures and metrics (PMMs). It provides a critical evaluation of 234 articles published in past 24 years. Design/methodology/approach The paper examines the studies published from 1991 to 2014 by adopting the bibliometric technique of citation and co-citation analysis. Findings The analysis of the results indicate that the number of articles on supply chain PMMs is increasing at its fastest pace in the past few years. Furthermore, the study identifies some of the most influential articles on performance measurement and metrics. Finally, it concludes that there has been a transition from traditional to more sophisticated performance measurement system. Research limitations/implications This study focuses only on supply chain performance measurement and metrics and excludes research on performance management and control. Thus, researchers may explore and extend this area of research. Originality/value To the knowledge of the authors, this is the first study to review the literature on supply chain PMMs by using citation and co-citation analysis. The study includes 234 articles over the time of 24 years (1991-2014).

Purpose - The emergent field of Internet of Things (IoT) has been evolving rapidly with a geometric growth in the number of academic publications in this field. The purpose of this paper is to review the literature of IoT in past 16 years using rigorous bibliometric and network analysis tools, offering at the same time future directions for the IoT research community and implications for managers and decision makers. Design/methodology/approach - The authors adopted the techniques of bibliometric and network analysis. The paper reviewed the articles published on IoT from 2000 to 2015. Findings - This study identifies top contributing authors; key research topics related to the field; the most influential works based on citations and PageRank; and established and emerging research clusters. Scholars are encouraged to further explore this topic. Research limitations/implications - This study focusses only on vision and applications of IoT. Scholars may explore various other aspects of this area of research. Originality/value - To the best of authors' knowledge, this is the first study to review the literature on IoT by using bibliometric and network analysis techniques. The study is unique as it spans a long time period of 16 years (2000-2015). The study proposes a five-cluster classification of research themes that may inform current and future research in IoT.

Humanitarian organizations are increasingly facing challenges in terms of improving the efficiency and the effectiveness of their disaster relief efforts. These challenges often arise due to a lack of trust, poor collaboration and an inability to respond to disaster affected areas in a timely manner. Our study attempts to understand how these challenges are overcome by seeking answers to questions related to the topics of swift-trust, collaboration and agility in humanitarian supply chains. For instance, in our study we have attempted to examine how information sharing and supply chain visibility in humanitarian supply chains improve the swift-trust among the humanitarian actors engaged in disaster relief operations. Further, we attempt to understand how-swift trust, commitment and collaboration among the humanitarian actors improve the agility in humanitarian supply chains. In our study we provide both theoretical and data-driven answers to our stated research gaps. Our theoretical model is firmly grounded in organizational information process theory and relational view. We tested our research hypotheses using variance based structural equation modelling with survey data collected using a web based pre-tested instrument from 147 NGOs respondents drawn from the National Disaster Management Authority database. Our results help to advance the theoretical debates surrounding “swift-trust”, “collaboration” and “agility” in humanitarian settings. We further provide direction to managers engaged in disaster relief operations. The humanitarian actors engaged in disaster relief often fail to understand how to build swift-trust. Moreover, how swift-trust further affects commitment and collaboration which in turn further affect agility in humanitarian supply chains. Thus humanitarian organizations must understand how information sharing and supply chain visibility is key to swift-trust among humanitarian actors and agility in humanitarian supply chains. Finally, we outline the limitations of our study and offer some future research directions for investigation.

PurposeBig data and predictive analytics (BDPA) has received great attention in terms of its role in making business decisions. However, current knowledge on BDPA regarding how it might link organizational capabilities and organizational performance (OP) remains unclear. Drawing from the resource-based view, the purpose of this paper is to propose a model to examine how information technology (IT) deployment (i.e. strategic IT flexibility, business–BDPA partnership and business–BDPA alignment) and HR capabilities affect OP through BDPA.Design/methodology/approachTo test the proposed hypotheses, structural equation modeling is applied on survey data collected from 159 Indian firms.FindingsThe results show that BDPA diffusion mediates the influence of IT deployment and HR capabilities on OP. In addition, there is a direct effect of IT deployment and HR capabilities on BDPA diffusion, which also has a direct relationship with OP.Originality/valueThrough this study, authors demonstrate that IT deployment and HR capabilities have an indirect impact on OP through BDPA diffusion.

Purpose The purpose of this paper is to improve the understanding of the integration of business process management (BPM), business process re-engineering (BPR) and business process innovation (BPI) with big data. It focusses on synthesizing research published in the period 2006-2016 to establish both what the authors know and do not know about this topic, identifying areas for future research. Design/methodology/approach The research is based on a review of 49 published papers on big data, BPM, BPR and BPI in the top journals in the field 2006-2016. Findings In this paper, the authors have identified the most influential works based on citations and PageRank methods. Through network analysis the authors identify four major clusters that provide potential opportunities for future investigation. Practical implications It is important for practitioners to be aware of the benefits of big data, BPM, BPR and BPI integration. This paper provides valuable insights for practitioners. Originality/value This paper is based on a comprehensive literature review, which gives big data researchers the opportunity to understand business processes in depth. In addition, highlighting many gaps in the current literature and developing an agenda for future research, will save time and effort for readers looking to research topics within big data and business processes.