Venkataramanaiah Saddikuti
@iiml.ac.in
Professor of Operations and Supply Chain Management
Indian Institute of Management Lucknow, India
EDUCATION
Ph.D in Operations Management
RESEARCH INTERESTS
Supply Chain Management
SMEs Competitiveness
Service Operations Management
Lean Healthcare
Healthcare Management
Operations Scheduling
FUTURE PROJECTS
Innovations in delivering high volume high quality pilgrim services at TTD
Applications Invited
Impact Assessment of FASTag and integration of e-way bill
Applications Invited
Healthcare Supply Chain Management
Applications Invited
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Venkataramanaiah Saddikuti, Surya Prakash, Vijaydeep Siddharth, Kanika Jain, and Sidhartha Satpathy
Emerald
PurposeThe primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.Design/methodology/approachThis study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.FindingsIt was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.Research limitations/implicationsThis study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.Practical implicationsThis study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.Originality/valueThis study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.
Rohit Sindhwani, Venkataramanaiah Saddikuti, and Omkarprasad S. Vaidya
Inderscience Publishers
Venkataramanaiah Saddikuti and Pavan Kumar Gudavalleti
Springer International Publishing
Rohit Sindhwani and Venkataramanaiah Saddikuti
Springer International Publishing
Rohit Sindhwani, Jayanth Jayaram, and Venkataramanaiah Saddikuti
Informa UK Limited
In this study, we focus on ripple effect mitigation capability of the Indian pharmaceutical distribution network during disruptions like COVID-19 pandemic. To study the mitigation capabilities, we conduct a multi-layer analysis (network, process, and control levels) using Bayesian network, mathematical optimisation, and discrete event simulation methodologies. This analysis revealed an associative relationship between ripple effect mitigation capabilities and network design characteristics of upstream supply chain entities. Using stochastic optimisation and Lagrangian relaxation, we then find ideal candidates for regional distribution centres at the downstream level. We then integrate these downstream locations with other supply chain entities for building the network optimisation and simulation model to analyse overall performance of the system. We demonstrate utility of our proposed methodology using a case study involving distribution of N95 masks to 'Jan Aushadhi' (peoples' medicines) stores in India during COVID-19 pandemic. We find that supply chain reconfiguration improves service level to 95.7% and reduces order backlogs by 10.7%. We also find that regional distribution centres and backup supply sources provide overall flexibility and improve occupational health and safety. We further investigate alternate mitigation capabilities through fortification of suppliers' workforce by vaccination. We offer recommendations for policymakers and managers and implications for academic research.
Ajay Jha, Rohit Sindhwani, Ashish Dwivedi, and Venkataramanaiah Saddikuti
Emerald
Purpose The purpose of this study is to identify important criteria for sustainable recovery of digital entrepreneurship from distress situation using shared resources. During pandemic disruption, the importance of sharing economy in managing business efficiency is reflected through this research. Design/methodology/approach The present study advances the knowledge on shared resources in business by integrating case study approach with multi criteria decision-making (MCDM) model. A fuzzy analytic hierarchy process approach is adopted to compute criteria weights, and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) technique is used to rank the sharing economy entrepreneurial ventures during COVID-19 pandemic in the context of emerging economy. Findings The present study identified five most important enablers (technological innovation, technology expertise, convergence of virtual and physical spaces, collaboration rather than competition, and benefits to underserved groups through transparency) for sustainable recovery of sharing economy ventures in emerging economy. For example, the study highlights online tutoring through shared intellect as the most sought after sharing economy venture during pandemic disruption, which fulfills the identified enablers. Practical implications The proposed framework provides an accurate decision support tool to rank the various identified potential enablers of sharing economy during disruptions. Further, the approach is practically relevant to sharing economy entrepreneurs in selecting the best approach to recover sustainability during pandemic. Originality/value The study is unique in addressing the need of sustainability for digital ventures via sharing economy approach in emerging economy (India). To develop a conceptual framework, the present study incorporates a case based approach together with the hybrid MCDM model. Further, the extant literature on disruptions is enhanced by prioritizing the enablers for sharing economy during pandemic.
Rohit Sindhwani, G. Pavan Kumar, and Venkataramanaiah Saddikuti
Elsevier
Venkataramanaiah Saddikuti, Mukund Nilakantan Janardhanan, and Vigneshwar Pesaru
Inderscience Publishers
StanislawP Stawicki, ThomasJ Papadimos, SamaraE Soghoian, Prabath Nanayakkara, Sarman Singh, AndrewC Miller, Venkataramanaiah Saddikuti, AchalaUpendra Jayatilleke, SiddharthP Dubhashi, MichaelS Firstenberg,et al.
Medknow
As the COVID-19 pandemic continues, important discoveries and considerations emerge regarding the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pathogen; its biological and epidemiological characteristics; and the corresponding psychological, societal, and public health (PH) impacts. During the past year, the global community underwent a massive transformation, including the implementation of numerous nonpharmacological interventions; critical diversions or modifications across various spheres of our economic and public domains; and a transition from consumption-driven to conservation-based behaviors. Providing essential necessities such as food, water, health care, financial, and other services has become a formidable challenge, with significant threats to the existing supply chains and the shortage or reduction of workforce across many sectors of the global economy. Food and pharmaceutical supply chains constitute uniquely vulnerable and critically important areas that require high levels of safety and compliance. Many regional health-care systems faced at least one wave of overwhelming COVID-19 case surges, and still face the possibility of a new wave of infections on the horizon, potentially in combination with other endemic diseases such as influenza, dengue, tuberculosis, and malaria. In this context, the need for an effective and scientifically informed leadership to sustain and improve global capacity to ensure international health security is starkly apparent. Public health “blind spotting,” promulgation of pseudoscience, and academic dishonesty emerged as significant threats to population health and stability during the pandemic. The goal of this consensus statement is to provide a focused summary of such “blind spots” identified during an expert group intense analysis of “missed opportunities” during the initial wave of the pandemic.
Shailendra Singh, Shantanu Bhattacharya, and Venkataramanaiah Saddikuti
Inderscience Publishers
Venkataramanaiah Saddikuti and Vigneshwar Pesaru
Elsevier BV
Sujeet Kumar Sharma, Avinash Gaur, Venkataramanaiah Saddikuti, and Ashish Rastogi
Informa UK Limited
ABSTRACT The success of e-learning management systems (e-LMSs) such as MOODLE depends on the usage of students as well as instructor acceptance in a virtual learning environment. E-Learning enables instructors to access educational resources to support traditional classroom teaching. This paper attempts to develop a model to understand and predict the effect of individual characteristics (technology experience [TE] and personal innovativeness [PI]) and e-LMS quality determinants (system quality [SYS-Q], information quality, and service quality) on the continuous use of e-LMS by instructors, which is critical to its success. A total of 219 instructors using MOODLE responded to the survey. The structural equation model (SEM) was employed to test the proposed research model. The SEM results showed that SYS-Q, PI, service quality, and TE have a statistically significant influence on continuous usage of e-LMS by instructors. Furthermore, all determinants of the research model were given as input to an NN model to overcome the simplistic nature of the SEM model. The NN model results showed that service quality is the most important predictor of e-learning acceptance followed by SYS-Q, PI, information quality, and TE. This paper attempts to develop a causal and predictive statistical model for predicting instructor e-LMS acceptance.
Venkataramanaiah Saddikuti
Medknow
Shri. A.P.J. Abdul Kalam, former President of India, in his address to Indian Red Cross Society in 2004 strongly suggested for an integrated and institutionalized approach for emergency response. He suggested a scheme using mobile technologies, in which whenever an accident occurs, a message could be sent to the nearest ambulance team and immediate medical help is arranged for. He also recommended for formulating a legal mechanism for providing such emergency support in critical situations.
V. Saddikuti, M. Gopalakrishnan and S. Gopinath
Productivity Press
R Bhatnagar and V Saddikuti
Informa UK Limited
Cellular manufacturing systems comprise categorizing machines used in the firm's production system into cells dedicated to part families that have similar requirements in terms of tooling, setups and operations sequences. Although worker assignment to cells has a significant impact on cell effectiveness, scant attention has been paid to this issue in previous research. We present two models—sequential and concurrent—for cell formation. The sequential model uses a machine–part incidence matrix (MPIM)-based similarity coefficient while the concurrent model uses a similarity coefficient based on both MPIM and machine–operator incidence matrix (MOIM). Our results show that for 50 problem sets widely reported in literature, the concurrent model outperformed the sequential model in most cases. A measure quantifying the difference in MPIM and MOIM was developed and the relative out-performance of the concurrent model was shown to depend on the value of this measure.