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International Journal of Operations & Production Management

ISSN : 0144-3577

Article publication date: 1 February 2002

This paper reviews the use of case study research in operations management for theory development and testing. It draws on the literature on case research in a number of disciplines and uses examples drawn from operations management research. It provides guidelines and a roadmap for operations management researchers wishing to design, develop and conduct case‐based research.

• Operations management
• Methodology
• Case studies

Voss, C. , Tsikriktsis, N. and Frohlich, M. (2002), "Case research in operations management", International Journal of Operations & Production Management , Vol. 22 No. 2, pp. 195-219. https://doi.org/10.1108/01443570210414329

Copyright © 2002, MCB UP Limited

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Operational Research in Health-care Settings

Rajesh kunwar.

Department of Community Medicine, TS Misra Medical College, Department of Community Medicine, Prasad Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

V. K. Srivastava

Origin of the term operational research (OR), also known as operations research, can be traced back to World War II when a number of researches carried out during military operations helped British Forces produce better results with lesser expenditure of ammunition. The world soon realised the potential of this kind of research and many disciplines especially management sciences, started applying its principles to achieve better returns on their investments.

Following World War II in 1948, the World Health Organization (WHO) came into existence with research as one of its core functions. It emphasized the need of identifying health-related issues needing research and thereby generation, dissemination, and utilization of the newly acquired knowledge for health promotion.[ 1 ] In 1978, Alma Ata Declaration acknowledged that primary health care was well known globally but, at the same time, also noted that modalities of its implementation were likely be different in different countries depending on their socioeconomic conditions, availability of resources, development of technology, and motivation of the community. A number of issues were yet to be resolved and researched before primary health care was operationalized under local conditions.[ 2 ]

T HE D EFINITION

The kind of research that Alma Ata Declaration recommended for improvement of health-care delivery is essentially OR. Described as “the science of better,” it helps in identifying the alternative service delivery strategy which not only overcomes the problems that limit the program quality, efficiency, and effectiveness but also yields the best outcome.[ 3 ] In its report on “The Third Ten Years of the WHO,” WHO has highlighted the usefulness of OR in improvement of health-care delivery in terms of its efficiency, effectiveness, and wider coverage by testing alternative approaches even in countries with limited national resources.[ 4 ]

OR has been variously defined. Dictionary of Epidemiology defined it as a systematic study of the working of a system with the aim of improvement.[ 5 ] From a health program perspective, OR is defined as the search for strategies and interventions that enhance the quality and effectiveness of the program.[ 6 ] A global meeting held in Geneva in April 2008 to develop the framework of OR, defined the scope of OR in context to public health as “ Any research producing practically usable knowledge (evidence, finding, information, etc.) which can improve program implementation (e.g., effectiveness, efficiency, quality, access, scale up, sustainability) regardless of the type of research (design, methodology, approach), falls within the boundaries of OR .”[ 7 ]

OR, however, is different from clinical or epidemiological research. It addresses a specific problem within a specific program. It examines a system, for example, health-care delivery system, and experiments in the environment specific to the program with alternative strategies to find the most suitable one and has an objective of improvement in the system. On the other hand, clinical or epidemiological research studies individuals and groups of individuals in search of new knowledge. In addition, ethical issues, which form an integral part of all clinical and epidemiological research, have their role poorly defined in OR, more so if it is based on secondary data.

The keyword in all the definitions is improvement, which is to be brought about by means of research in the operation of an ongoing program. Its characteristics include:

• It focuses on a specific problem in an ongoing programme
• It involves research into the problem using principles of epidemiology
• It tests more than one possible solution and provides rational basis, in the absence of complete information, for the best alternative to improve program efficiency
• It requires close interaction between program managers and researchers
• It succeeds only if the research is conducted in the existing environment and study results are implemented in true letter and spirit.

T HE P ROCESS

In health-care settings, an ongoing health program often fails to achieve its expected objective and the program managers are faced with problems factors responsible for which are not apparent. This is the stage where process of OR is initiated. In a standard OR process, planning begins with organization of a research team, which should have a mix of people with different backgrounds such as epidemiology, biostatistics, health managements, etc., The program managers may not be able to carry out the research themselves because of their work responsibility and in all probability, their biased views. However, they need to have a working relationship with the research team to ensure smooth conduct of the research and ownership of the result by all parties.

According to Fisher et al ., OR is a continuous process of problem identification, selection of a suitable strategy/intervention, experimentation of the selected strategy/intervention, dissemination of the findings, and utilization of the information so derived.[ 8 ] However, it may not always be possible to follow a step by step approach in OR since it is carried out in the existing environment, and many of the activities may be taking place simultaneously. The process involves the following steps [ Figure 1 ].

Process of operational research

Identifying problems

Like any other research, it is essential to have a research question as to the first and foremost step for beginning the process of OR. Discussion with program managers and staff, review of project reports and local documentation, discussion with experts in the field and literature search gives an insight into why the problem is occurring and what are possible solutions; and help in the identification of the research question. OR methods are useful for the systematic identification of problems and the search for potential solutions. Structured approaches to identifying options, such as the strategic choice approach or systematic creativity approaches have great potential for use in low-resource settings.[ 9 ]

Choosing interventions

Choosing appropriate interventions is clearly a crucial step. Effectiveness, safety, cost, and equity should all be considered, and researchers should be familiar with standard textbook methods for assessing these. Finding the best combinations and delivery methods is a major research exercise in its own right. Modeling different intervention strategies before rollout is now ubiquitous in many industries but is less common in healthcare.[ 10 ] Modeling work has been done on ways to reduce maternal mortality and in cervical cancer screening in low-resource settings.[ 11 ]

An appropriate intervention design, depending on available time and resources, should have a written protocol spelling out details of steps to be taken during implementation. Only valid and reliable instruments – be it quantitative or qualitative study-should be used; and wherever possible, a pilot study be carried out to further refine the conduct of the intervention. The contribution that OR and management science can make to design and delivery is not restricted to high technology. Oral rehydration therapy is a “low-tech–low-cost–high-impact” innovation, in which OR was used to explore ways it could be administered using readily available ingredients by laypeople, with an escalation pathway to treatment by health-care professionals when necessary.[ 12 ]

Small-scale projects generally need considerable modifications to work on a larger scale. Classic OR techniques such as simulation modeling can be used in locating services, managing the supply chain, and developing the health-care workforce.

Integrating into health systems

After analysis of the result, the information gathered should be disseminated to stakeholders and decision-makers. The modalities of information utilization should have been predecided and included in the research proposal. Successes in global health programs often result from synergistic interactions between individual, community and national actors rather than from any single “magic bullet.” A greater focus is needed on how interventions should be used in a complex behavioral environment, to better capture the dynamics of social networks, and to understand how complex systems can adapt positively to change. This is a task where OR and management science tools can be useful, as demonstrated by systems analysis of programs for cervical cancer prevention[ 13 ] or agent simulation modeling of spread of HIV in villages.[ 14 ]

E VALUATION

One of the greatest challenges for global health is the measurement and evaluation of performance of projects and programs. The WHO defines evaluation as “ the systematic and objective assessment of an ongoing or completed initiative, its design, implementation, and results. The aim is to determine the relevance and fulfillment of objectives, efficiency, effectiveness, impact, and sustainability .”[ 15 ] It may or may not lead to improvement.

Accelerated Child Survival and Development (ACSD) program, an initiative of UNICEF, was implemented in eleven West African countries from 2001 to 2005 with an objective of reducing mortality among under-fives by at least 25% by the end of 2006. Retrospective evaluation of the program was carried out in Benin, Ghana, and Mali by comparing data of ACSD focus districts with those of remainder districts. It showed that the difference in coverage of preventive interventions in ACSD focus areas before and after program implementation was not significant in Benin and Mali. This probably resulted in failure of ACSD program to accelerate survival of under-fives in-focus areas of Benin and Mali as compared to comparison areas. The inputs obtained from the evaluation of the program if translated into policy or national program would have delivered the desired result of ACSD program implementation.[ 16 ] Evaluation, thus, is fundamental to good management and is an essential part of the process of developing effective public policy. It is a complex enterprise, requiring researchers to balance the rigors of their research strategies with the relevance of their work for managers and policymakers.[ 17 ]

Standard control trial approaches to evaluation are sometimes feasible and appropriate but often a more flexible systems-oriented approach is required, together with modeling to help assess the effectiveness of preventive interventions.[ 18 ] Decision tree modeling can give rapid insights into the operational effectiveness and cost-effectiveness of procedures[ 19 ] and programs.[ 20 ]

O PERATIONAL R ESEARCH IN H EALTH-CARE S ETTINGS : E XAMPLES

The relevance of OR in health-care settings cannot be overemphasized. It has been successfully used all over the world in various health programs such as family planning, HIV, tuberculosis (TB), and malaria control programs to name a few. Its role in causing improvement in various health programs and the development of policies has been acknowledged globally. Sustained OR efforts of several decades helped in developing the Global strategy for control of TB. India and Malawi provide the most successful example of OR in this field.[ 21 ] In India, it was demonstrated by OR that successful implementation of DOTS strategy throughout the country led to reduction in the prevalence of TB, reduction in fatality due to TB and release of hospital beds occupied by TB patients; and thereby a potential gain to the Indian economy.[ 22 ]

For the treatment of TB, about half of TB patients in India rely on the private sector. In spite of it being a notifiable disease, TB notification from private sector has been a challenge. In 2014, Delhi state, by adopting direct “one to one” sensitization of private practitioners by TB notification committee, was able to accelerate notification of TB cases from the private sector.[ 23 ]

In view of the growing burden of multidrug-resistance TB (MDR-TB), an OR was conducted in the setting of Revised National Tuberculosis Programme on patients with presumptive MDR-TB in North and Central Chennai, in 2014 to determine prediagnosis attrition and pre-treatment attrition, and factors associated with it. Prediagnosis and pretreatment attrition were found 11% and 38%, respectively. The study showed that patients with smear-negative TB were less likely to undergo drug susceptibility testing (DST) and more attention was required to be paid to this group for improving DST.[ 24 ]

One of the most successful examples of OR in India is the experimental study carried out in Gadchiroli district of Maharashtra from 1993 to 1998. In their path-breaking field trial, Bang et al . trained village level workers in neonatal care who subsequently made home visits at scheduled intervals and managed premature birth/low birthweight, birth asphyxia, hypothermia, neonatal sepsis, and breastfeeding problems. This led to a significant reduction in neonatal mortality rates in intervention villages.[ 25 ] Encouraged by the success of this field trial, Home-Based Newborn Care has been adopted by many districts in India to combat neonatal mortality.

In leprosy case detection campaign (LCDC), introduced under National Leprosy Eradication Programme of India in 2016, false-positive diagnosis is a major issue. A study carried out in four districts of Bihar found 30% false-positive cases during LCDC. Using “appreciative inquiry” as a tool, Wagh et al . were able to achieve a decline in false-positive diagnosis.[ 26 ]

OR has been successfully used in hospital settings too. In Latin America, unsafe abortions used to be one of the most common causes of high maternal mortality. Billings and Bensons reviewed ten completed OR projects conducted in public sector hospitals of seven Latin American countries. Their findings indicated that sharp curettage replaced by manual vacuum aspiration for conducting abortion reduced the requirement of resources for postabortion care, reduced cost, and length of hospital stay and reduced maternal mortality.[ 27 ]

C ONCLUSION

Following Alma Ata declaration and Millennium Development Goals, all countries of the world have instituted their own National Health Programmes in a bid to improve health of their countrymen. Although health programs are in place, Governments are committed, guidance from the WHO is available, support from NGOs have been garnered, still many countries have not been able to achieve their desired goals. Operational Research is now being used as a key instrument, especially in resource-poor countries, to tap the untapped information. Administrators are using it as a searchlight for discovering what is still in the dark. It is there to stay. It is high time that the scientific community working in health-care settings gets acquainted with the nuances of OR and uses it more often for improving the outcome of health programs and for making them more efficient and effective.

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• © 2022

Africa Case Studies in Operations Research

A Closer Look into Applications and Algorithms

• Hatem Masri 0

College of Business Administration, University of Bahrain, Sakhir, Bahrain

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• Provides an overview of operations research practices and development in Africa
• Includes case studies of best and effective practices to solve real life problems
• Demonstrates the application of models and algorithms to promote economic development in Africa

Part of the book series: Contributions to Management Science (MANAGEMENT SC.)

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Table of contents (10 chapters)

Front matter, traveling advisor problem in occupational health and safety field with a case study from egypt.

• Said Ali Hassan, Prachi Agrawal, Talari Ganesh, Ali Wagdy Mohamed

Data Envelopment Analysis for Healthcare Systems Assessment: Review and Applications from Tunisia

• Marwa Hasni, Safa Bhar Layeb, Najla Omrane Aissaoui, Aymen Mannai

Artificial Intelligence and Operations Research in a Middle Ground to Support Decision-Making in Healthcare Systems in Africa

• Safa Elkefi, Safa Bhar Layeb

A CODAS Disaggregation Approach for Urban Rainwater Management

• Mouna Regaieg Cherif, Hela Moalla Frikha

Evaluating How the Regulatory Ecosystem Promotes Entrepreneurial Activities in Africa

• Pawoumodom Matthias Takouda, Mohamed Dia, Alassane Ouattara, Konan Vincent De Paul Kouadio

Exact Resolution for Healthcare Facility Location Problem: A Case Study of the Specific Pharmacy of Tunisia

• Fatma Ben Amor, Manel Kammoun, Taicir Loukil

Applications of Transportation Models in Africa

• Houda Alaya

Operations Research Case Study Papers for Africa: A Bibliometric Review

• Majdi Argoubi, Hatem Masri

Economic Resilience and Foreign Development Aid: Lessons from Sub-Saharan Africa

• Somar Al-Mohammad, Ammar Jreisat, Mourad Messaadia, Audil Rashid Khaki

Fintech Adoption for Poverty Alleviation in African Countries: Application of Supervised Machine Learning Approach

• Audil Rashid Khaki, Mourad Messaadia, Ammar Jreisat, Somar Al-Mohammad

This book presents contributions to the 50 th Annual Conference of the Operations Research Society of South Africa (ORSSA), which was jointly hosted with the African Federation of Operations Research Societies (AFROS) at North-West University in Potchefstroom, South Africa from 12 to 15 September, 2021. Focusing on innovative case studies and recent applications of Operations Research models and algorithms in African countries, each chapter highlights findings emerging from the countries in question and explains the lessons learned. As such, the book offers an up-to-date overview of Operations Research practices and developments in Africa.

AFROS is a “not for profit” organization that aims to promote Operations Research in Africa. Its affairs are regulated by an Executive Committee consisting of representatives/alternates of all its member societies. The members of the Federation undertake to co-operate in the advancement of knowledge, interestand education in Operations Research by appropriate means, particularly the exchange of information, the holding of meetings and conferences, and the awarding of prizes.

• Decision Analysis
• Research and Development
• Optimization
• Information Sciences
• Engineering
• Business and Economics

Hatem Masri

Hatem Masri is a Professor of Business Analytics and Dean of the College of Business Administration at the University of Bahrain, Kingdom of Bahrain. He received a Master in operations research (1999) and PhD in management science (2004) from the University of Tunis, Tunisia. His research interests include business analytics, supply chain management, financial engineering, and Islamic finance. He has published more than 33 articles and eight books, including a textbook on Islamic business administration. Hatem is Past President of the African Federation of Operational Research Societies, Founder of the INFORMS Bahrain International Group, General Secretary of the Tunisian Decision Aid Society, a member of INFORMS and IEEE, and a volunteer/mentor with the AACSB. He is leading a research group in Business Analytics and Responsible Management in Bahrain and member of several steering boards and advisory committees among them the SKEMA Artificial Intelligence Institute.

Book Title : Africa Case Studies in Operations Research

Book Subtitle : A Closer Look into Applications and Algorithms

Editors : Hatem Masri

Series Title : Contributions to Management Science

DOI : https://doi.org/10.1007/978-3-031-17008-9

Publisher : Springer Cham

eBook Packages : Mathematics and Statistics , Mathematics and Statistics (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

Hardcover ISBN : 978-3-031-17007-2 Published: 10 November 2022

Softcover ISBN : 978-3-031-17010-2 Published: 11 November 2023

eBook ISBN : 978-3-031-17008-9 Published: 09 November 2022

Series ISSN : 1431-1941

Series E-ISSN : 2197-716X

Edition Number : 1

Number of Pages : VI, 210

Number of Illustrations : 1 b/w illustrations

Topics : Operations Research/Decision Theory , Operations Research, Management Science

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Case Study.Operation Management. Operation Research. Linear Programming.Method of Transportation

Operation Management. Operation Research. Linear Programming. Method of Transportation Transportation method is a method used to set the distribution of sources that provide the same product or kind of to the destination optimally. This distribution is done in such a wayso that requests from multiple destinations can be met from several place of origin of each can have different requests or capacities . Using the method transport, can be obtained a distribution allocation usage of items that can minimize total transportation cost. In addition to set on distribution of goods, methods transportation can also be used for other problems, such as scheduling in the process production in order to obtain the total processing time lowest, placement inventory to get total inventory cost smallest, or capital expenditure in order to get the greatest investment return. In the related to planning facilities, transportation methods can be used for choose a location that can minimizing total operating costs.Here we give examples of working methods of transportation with linear programming. Some Methods are NCR, LCM, STS, VAM.

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In the field of operations research, modelling of transportation problem is fundamental in solving most real life problems as far optimization is concerned. It is clear that a lot more effort has been put in by many researchers in seek of appropriate solution methods to such problem. Vogel’s Approximation Method (VAM), among the class of algorithms provided to solve the Initial Basic Feasible Solution (IBFS) proved to be best. Likewise is the Modified Distribution Method in testing the optimality of the IBFS. However, for some time now, manual calculations and LINDO are the tools used by most researchers in the application of these efficient proposed techniques. In this work, an equivalent MATLAB program was written that would aid in the computation of such problems with ease especially when the problem at hand has a larger cost matrix.

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Transportation Algorithm uses for solving Transportation Problem to find feasible solution which may optimal or not. This is now a challenge that developed such an algorithm which gives optimal solution without using Optimality Methods like as MODI, Stepping-Stone. For this reason there are several transportation algorithm exists for solving TP like as North West Corner Rule (NWC), Least Cost Method (LCM), Vogel’s Approximation Method (VAM) etc. where VAM provides the feasible solution which is lower than NWC and LCM and for some case of TP it coincides with optimal solution. In this paper we proposed a new approach named “Implied Cost Method (ICM)” where feasible solutions are lower than VAM and very close to optimal solution or sometimes coincides with optimal solution.

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