Pub Date : 2023-02-03DOI: 10.1108/ijieom-10-2022-0052
K. Manoharan, P. Dissanayake, C. Pathirana, D. Deegahawature, Renuka Silva
PurposeLabour efficiency is the key component for the long-term sustainability of construction firms. Recent studies show that modernising organisational/managerial processes is necessary to raise labour efficiency in many emerging nations. Construction supervision is a crucial element in organisational/managerial practices, which provide blood circulation to the project operations by directing labour. Accordingly, this study aims to quantify the impacts of crucial organisational/managerial elements on the efficiency of labour in building construction projects based on the viewpoint of construction supervisors.FindingsA total of 28 factors were determined as critical, where lack of labour motivation, poor labour training facilities, poor performance evaluation practices, no labour rewarding mechanism and poor communication/cooperation between parties were judged to be the top five key issues in the list. The validity and reliability of the study findings were ensured through statistical tests and the experts' discussion outcomes. In view of the evolving challenges facing the industry, the results indicate that the organisational policies of construction enterprises in place addressing financial procedures, communication strategies, resource management and performance management practices must be enhanced.Research limitations/implicationsThe study findings will make a substantial contribution to reducing the disparity between organisation/management policies and labour practices towards changing how the sector operates to increase labour efficiency in construction projects.Originality/valueThis study contributes to addressing the knowledge gap in the industry associated with the organisational protocols, especially to understand/predict how such elements are significant, how much they influence the efficiency of construction practices and what steps can be made to limit their effects on labour efficiency in construction. These could be crucial in modernising organisational policies and procedures for construction management.
{"title":"Organisational elements controlling labour efficiency in building construction operations – a construction supervisors' perspective","authors":"K. Manoharan, P. Dissanayake, C. Pathirana, D. Deegahawature, Renuka Silva","doi":"10.1108/ijieom-10-2022-0052","DOIUrl":"https://doi.org/10.1108/ijieom-10-2022-0052","url":null,"abstract":"PurposeLabour efficiency is the key component for the long-term sustainability of construction firms. Recent studies show that modernising organisational/managerial processes is necessary to raise labour efficiency in many emerging nations. Construction supervision is a crucial element in organisational/managerial practices, which provide blood circulation to the project operations by directing labour. Accordingly, this study aims to quantify the impacts of crucial organisational/managerial elements on the efficiency of labour in building construction projects based on the viewpoint of construction supervisors.FindingsA total of 28 factors were determined as critical, where lack of labour motivation, poor labour training facilities, poor performance evaluation practices, no labour rewarding mechanism and poor communication/cooperation between parties were judged to be the top five key issues in the list. The validity and reliability of the study findings were ensured through statistical tests and the experts' discussion outcomes. In view of the evolving challenges facing the industry, the results indicate that the organisational policies of construction enterprises in place addressing financial procedures, communication strategies, resource management and performance management practices must be enhanced.Research limitations/implicationsThe study findings will make a substantial contribution to reducing the disparity between organisation/management policies and labour practices towards changing how the sector operates to increase labour efficiency in construction projects.Originality/valueThis study contributes to addressing the knowledge gap in the industry associated with the organisational protocols, especially to understand/predict how such elements are significant, how much they influence the efficiency of construction practices and what steps can be made to limit their effects on labour efficiency in construction. These could be crucial in modernising organisational policies and procedures for construction management.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123939634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-23DOI: 10.1108/ijieom-11-2022-0059
M. Ahmed, Hridi Juberi, A. Bari, Muhommad Azizur Rahman, A. Rahman, Md. Ashfaqur Arefin, Ilias Vlachos, Niaz Quader
PurposeThis study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.Design/methodology/approachIn this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).FindingsThe optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.Research limitations/implicationsThe MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.Originality/valueMost studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.
{"title":"Investigation of the effect of vibration in the multi-objective optimization of dry turning of hardened steel","authors":"M. Ahmed, Hridi Juberi, A. Bari, Muhommad Azizur Rahman, A. Rahman, Md. Ashfaqur Arefin, Ilias Vlachos, Niaz Quader","doi":"10.1108/ijieom-11-2022-0059","DOIUrl":"https://doi.org/10.1108/ijieom-11-2022-0059","url":null,"abstract":"PurposeThis study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.Design/methodology/approachIn this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).FindingsThe optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.Research limitations/implicationsThe MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.Originality/valueMost studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133473728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.1108/ijieom-10-2021-0014
Tadele Shimels, Lemma F. Lessa
PurposeInformation systems' security is more critical than ever before since security threats are rapidly growing. Before putting in place information systems' security measures, organizations are required to determine the maturity level of their information security governance. Literature review reveals that there is no recent study on information systems' security maturity level of banks in Ethiopia. This study thus seeks to measure the existing maturity level and examine the security gaps in order to propose possible changes in Ethiopian private banking industry's information system security maturity indicators.Design/methodology/approachFour private banks are selected as a representative sample. The system security engineering capability maturity model (SSE-CMM) is used as the maturity measurement criteria, and the measurement was based on ISO/IEC 27001 information security control areas. The data for the study were gathered using a questionnaire.FindingsA total of 93 valid questionnaires were gathered from 110 participants in the study. Based on the SSE-CMM maturity model assessment criteria the private banking industry's current maturity level is level 2 (repeatable but intuitive). Institutions have a pattern that is repeated when completing information security operations but its existence was not thoroughly proven and institutional inconsistency still exists.Originality/valueThis study seeks to measure the existing maturity level and examine the security gaps in order to propose possible changes in Ethiopian private banking industry's information system security maturity indicators. This topic has not been attempted previously in the context of Ethiopian financial sector.
{"title":"Maturity of information systems' security in Ethiopian banks: case of selected private banks","authors":"Tadele Shimels, Lemma F. Lessa","doi":"10.1108/ijieom-10-2021-0014","DOIUrl":"https://doi.org/10.1108/ijieom-10-2021-0014","url":null,"abstract":"PurposeInformation systems' security is more critical than ever before since security threats are rapidly growing. Before putting in place information systems' security measures, organizations are required to determine the maturity level of their information security governance. Literature review reveals that there is no recent study on information systems' security maturity level of banks in Ethiopia. This study thus seeks to measure the existing maturity level and examine the security gaps in order to propose possible changes in Ethiopian private banking industry's information system security maturity indicators.Design/methodology/approachFour private banks are selected as a representative sample. The system security engineering capability maturity model (SSE-CMM) is used as the maturity measurement criteria, and the measurement was based on ISO/IEC 27001 information security control areas. The data for the study were gathered using a questionnaire.FindingsA total of 93 valid questionnaires were gathered from 110 participants in the study. Based on the SSE-CMM maturity model assessment criteria the private banking industry's current maturity level is level 2 (repeatable but intuitive). Institutions have a pattern that is repeated when completing information security operations but its existence was not thoroughly proven and institutional inconsistency still exists.Originality/valueThis study seeks to measure the existing maturity level and examine the security gaps in order to propose possible changes in Ethiopian private banking industry's information system security maturity indicators. This topic has not been attempted previously in the context of Ethiopian financial sector.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121176404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-04DOI: 10.1108/ijieom-08-2022-0035
Luiz Carlos Roque Júnior, G. Frederico, Maykon L.N. Costa
PurposeA globalized world demands proactive tactics from organizational supply chains. Companies should be capable of mitigating the impacts of natural and manmade disasters, which requires that they understand their stages of maturity and resilience. This study develops a theoretical model of the relationship between maturity and resilience, seeking to guide decision-making about aligning these two concepts.Design/methodology/approachA systematic literature review was conducted to identify the constructs that form the basis for our proposed maturity and resilience model.FindingsThe authors identified the key constructs related to maturity and resilience by analyzing the existing literature and selected 13 constructs and 3 maturity stages to construct our maturity and resilience model.Research limitations/implicationsThis research contributes to the supply chain management literature, especially that involving the themes of maturity and resilience. It can encourage research to develop future empirical research in the field to validate and overcome the limitations of the initial model the authors propose.Practical implicationsThe authors’ proposed model supports supply chain managers in establishing strategies to increase resilience based on the maturity of the chains they manage, enabling them to face crises such as the coronavirus disease 2019 (COVID-19) pandemic.Originality/valueThe model presents a holistic view of maturity and resilience in supply chains contributing to supply chain theory by examining the alignment between the two themes.
{"title":"Maturity and resilience in supply chains: a systematic review of the literature","authors":"Luiz Carlos Roque Júnior, G. Frederico, Maykon L.N. Costa","doi":"10.1108/ijieom-08-2022-0035","DOIUrl":"https://doi.org/10.1108/ijieom-08-2022-0035","url":null,"abstract":"PurposeA globalized world demands proactive tactics from organizational supply chains. Companies should be capable of mitigating the impacts of natural and manmade disasters, which requires that they understand their stages of maturity and resilience. This study develops a theoretical model of the relationship between maturity and resilience, seeking to guide decision-making about aligning these two concepts.Design/methodology/approachA systematic literature review was conducted to identify the constructs that form the basis for our proposed maturity and resilience model.FindingsThe authors identified the key constructs related to maturity and resilience by analyzing the existing literature and selected 13 constructs and 3 maturity stages to construct our maturity and resilience model.Research limitations/implicationsThis research contributes to the supply chain management literature, especially that involving the themes of maturity and resilience. It can encourage research to develop future empirical research in the field to validate and overcome the limitations of the initial model the authors propose.Practical implicationsThe authors’ proposed model supports supply chain managers in establishing strategies to increase resilience based on the maturity of the chains they manage, enabling them to face crises such as the coronavirus disease 2019 (COVID-19) pandemic.Originality/valueThe model presents a holistic view of maturity and resilience in supply chains contributing to supply chain theory by examining the alignment between the two themes.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115902131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-06DOI: 10.1108/ijieom-05-2022-0018
G. K. Badhotiya, Leena Sachdeva, G. Soni
PurposeThe manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.Design/methodology/approachThe barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.FindingsThe impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”Practical implicationsThe ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.Originality/valueThis study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.
{"title":"Investigating and modeling interactions among manufacturing barriers due to Covid-19 pandemic: an interpretive ranking process","authors":"G. K. Badhotiya, Leena Sachdeva, G. Soni","doi":"10.1108/ijieom-05-2022-0018","DOIUrl":"https://doi.org/10.1108/ijieom-05-2022-0018","url":null,"abstract":"PurposeThe manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.Design/methodology/approachThe barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.FindingsThe impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”Practical implicationsThe ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.Originality/valueThis study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129572834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-25DOI: 10.1108/ijieom-08-2022-0033
Anshita Bihari, M. Dash, S. Kar, K. Muduli, Anil Kumar K, S. Luthra
PurposeThis study systematically explores the patterns and connections in the behavioural bias and investment decisions of the existing literature in the Scopus database published between 2007 and 2022. The purpose of this paper is to address this issue.FindingsIn the article it was determined which contributed documents were the most significant in this particular subject area along with the citations, publications and nations that were associated with them. The bibliographic coupling offered more in-depth insights into the papers by organizing them into distinct groups. The pattern of the publications has been brought to light, and the connection between different types of literature has provided insight into the path that future studies should take.Research limitations/implicationsThis study considered only articles from the Scopus database. Future studies can be based on papers that have been published in other databases.Originality/valueThe outcome of this study provides valuable insights into the intellectual structure and biases of investors and adds value to existing knowledge. This review provides a road map for the future trend of research on behavioural bias and investment decisions.
{"title":"Exploring behavioural bias affecting investment decision-making: a network cluster based conceptual analysis for future research","authors":"Anshita Bihari, M. Dash, S. Kar, K. Muduli, Anil Kumar K, S. Luthra","doi":"10.1108/ijieom-08-2022-0033","DOIUrl":"https://doi.org/10.1108/ijieom-08-2022-0033","url":null,"abstract":"PurposeThis study systematically explores the patterns and connections in the behavioural bias and investment decisions of the existing literature in the Scopus database published between 2007 and 2022. The purpose of this paper is to address this issue.FindingsIn the article it was determined which contributed documents were the most significant in this particular subject area along with the citations, publications and nations that were associated with them. The bibliographic coupling offered more in-depth insights into the papers by organizing them into distinct groups. The pattern of the publications has been brought to light, and the connection between different types of literature has provided insight into the path that future studies should take.Research limitations/implicationsThis study considered only articles from the Scopus database. Future studies can be based on papers that have been published in other databases.Originality/valueThe outcome of this study provides valuable insights into the intellectual structure and biases of investors and adds value to existing knowledge. This review provides a road map for the future trend of research on behavioural bias and investment decisions.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117324891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-23DOI: 10.1108/ijieom-10-2022-0046
Aswathy Sreenivasan, M. Suresh
PurposeIt is the responsibility of the national governments to deliver healthcare services that are both effective and affordable to everyone. There are still gaps in this supply, which is extremely demanding. In this sense, companies are attempting to reach neglected markets and disrupt the marketplace with novel solutions. Although there are still anecdotal examples, a thorough literature evaluation is lacking. This study aims to provide a synthesis of the future of healthcare start-ups.Design/methodology/approachPapers that included the term “healthcare start-ups,” “health-tech start-ups,” “start-up,” “Artificial intelligence in healthcare,” and “Health tech start-ups in India” were considered for the analysis. The Biblioshiny package under the R programming tool was considered for a detailed analysis of the papers.FindingsA total of 854 documents were related to healthcare start-ups, from which only 14 papers are related to health-tech start-ups and four papers are related to artificial intelligence in healthcare start-ups. It has been found from the past works of literature that the effectiveness of technology for information and communication in healthcare has significantly increased in recent years. Technology has already begun to permeate the healthcare market from other fields and industries. One way that the internet will help the industry evolve is by integrating digital health into daily life.Research limitations/implicationsThe study is not using other databases but is limited to Google Scholar and Scopus. A significant constraint of this study is the paucity of relevant literature in reputable publications on health and information systems. Another restriction was that gray literature, such as any journal or newspaper written by members of the health community about health-tech start-ups, was not taken into account.Practical implicationsHealthcare players should exhibit a fundamental openness to novel solutions to facilitate the digitalization of the healthcare system. Developing technology is widely used, and from an innovation perspective, a start-up should focus on innovation by employing technology and offering revolutionary healthcare solutions.Originality/valueThe novelty of this research is based on its presentation of an organized and thorough literature evaluation, which defines the current state of the art concerning green start-ups. To create a sustainable start-up, a thorough study of the information gained in respect of its healthcare start-up is presented.
{"title":"Future of healthcare start-ups in the era of digitalization: bibliometric analysis","authors":"Aswathy Sreenivasan, M. Suresh","doi":"10.1108/ijieom-10-2022-0046","DOIUrl":"https://doi.org/10.1108/ijieom-10-2022-0046","url":null,"abstract":"PurposeIt is the responsibility of the national governments to deliver healthcare services that are both effective and affordable to everyone. There are still gaps in this supply, which is extremely demanding. In this sense, companies are attempting to reach neglected markets and disrupt the marketplace with novel solutions. Although there are still anecdotal examples, a thorough literature evaluation is lacking. This study aims to provide a synthesis of the future of healthcare start-ups.Design/methodology/approachPapers that included the term “healthcare start-ups,” “health-tech start-ups,” “start-up,” “Artificial intelligence in healthcare,” and “Health tech start-ups in India” were considered for the analysis. The Biblioshiny package under the R programming tool was considered for a detailed analysis of the papers.FindingsA total of 854 documents were related to healthcare start-ups, from which only 14 papers are related to health-tech start-ups and four papers are related to artificial intelligence in healthcare start-ups. It has been found from the past works of literature that the effectiveness of technology for information and communication in healthcare has significantly increased in recent years. Technology has already begun to permeate the healthcare market from other fields and industries. One way that the internet will help the industry evolve is by integrating digital health into daily life.Research limitations/implicationsThe study is not using other databases but is limited to Google Scholar and Scopus. A significant constraint of this study is the paucity of relevant literature in reputable publications on health and information systems. Another restriction was that gray literature, such as any journal or newspaper written by members of the health community about health-tech start-ups, was not taken into account.Practical implicationsHealthcare players should exhibit a fundamental openness to novel solutions to facilitate the digitalization of the healthcare system. Developing technology is widely used, and from an innovation perspective, a start-up should focus on innovation by employing technology and offering revolutionary healthcare solutions.Originality/valueThe novelty of this research is based on its presentation of an organized and thorough literature evaluation, which defines the current state of the art concerning green start-ups. To create a sustainable start-up, a thorough study of the information gained in respect of its healthcare start-up is presented.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.46254/j.ieom.20210202
Hassan Hijry, Richard Olawoyin, William Edwards, Gary C. McDonald, D. Debnath, Y. Al-Hejri
Due to the rising number of confirmed positive tests, the global impact of COVID-19 continues to grow. This can be attributed to the long wait times patients face to receive COVID-19 test results. During these lengthy waiting periods, people become anxious, especially those who are not experiencing early COVID-19 symptoms. This study aimed to develop models that predict waiting times for COVID-19 test results based on different factors such as testing facility, result interpretation, and date of test. Several machine learning algorithms were used to predict average waiting times for COVID-19 test results and to find the most accurate model. These algorithms include neural network, support vector regression, K-nearest neighbor regression, and more. COVID-19 test result waiting times were predicted for 54,730 patients recorded during the pandemic across 171 hospitals and 14 labs. To examine and evaluate the model’s accuracy, different measurements were applied such as root mean squared and R-Squared. Among the eight proposed models, the results showed that decision tree regression performed the best for predicting COVID-19 test results waiting times. The proposed models could be used to prioritize testing for COVID-19 and provide decision makers with the proper prediction tools to prepare against possible threats and consequences of future COVID-19 waves.
{"title":"Predicting Average Wait-Time of COVID-19 Test Results and Efficacy Using Machine Learning Algorithms","authors":"Hassan Hijry, Richard Olawoyin, William Edwards, Gary C. McDonald, D. Debnath, Y. Al-Hejri","doi":"10.46254/j.ieom.20210202","DOIUrl":"https://doi.org/10.46254/j.ieom.20210202","url":null,"abstract":"Due to the rising number of confirmed positive tests, the global impact of COVID-19 continues to grow. This can be attributed to the long wait times patients face to receive COVID-19 test results. During these lengthy waiting periods, people become anxious, especially those who are not experiencing early COVID-19 symptoms. This study aimed to develop models that predict waiting times for COVID-19 test results based on different factors such as testing facility, result interpretation, and date of test. Several machine learning algorithms were used to predict average waiting times for COVID-19 test results and to find the most accurate model. These algorithms include neural network, support vector regression, K-nearest neighbor regression, and more. COVID-19 test result waiting times were predicted for 54,730 patients recorded during the pandemic across 171 hospitals and 14 labs. To examine and evaluate the model’s accuracy, different measurements were applied such as root mean squared and R-Squared. Among the eight proposed models, the results showed that decision tree regression performed the best for predicting COVID-19 test results waiting times. The proposed models could be used to prioritize testing for COVID-19 and provide decision makers with the proper prediction tools to prepare against possible threats and consequences of future COVID-19 waves.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130508191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.46254/j.ieom.20210203
Y. Samarasinghe, B. S. Kumara, A. Kulatunga
The necessity for food traceability has been increased over the years with the expansion of food supply chains globally over these years due to stringent of food safety regulations. Enhancing the access to quality food safely is one of the essential requirements of food supply chain traceability. Conversely, significant percentages of postharvest losses available especially in developing countries due to poor supply chain and logistics practices thereby threatening food security. Unless there is a possibility to trace the Supply chain, it is difficult to take remedial actions. When it comes to Sri Lanka, currently it is harder to have the traceability in most of the foods supply chains commonly on most of the elementary supply chains such as fruits and vegetables. This has led to postharvest losses since it is harder to identify when and where damages occur, who are accountable, harvested and transient times, supply demand mismatch too. Therefore, this paper aims to investigate the feasibility of tracing of fruit and vegetable supply chain in Sri Lanka and contribute theoretically to facilitate authorities and decision makers for future traceability improvement. Availability of secondary information on fruits and vegetables traceability was examined referring to government agencies. Basic structure of supply chain was identified based on secondary data and a case study was conducted based on supply chains linked to Thambuththegama and Keppetipola Dedicated Economic Centers to gather primary data. To quantify the feasibility of tracing, a feasibility index was developed. Developed index was used to assess the feasibility towards improved traceability of selected chains where it can be applied for other food and non-food supply chains as well. The feasibility index can be used for other fruits and vegetables supply chains too to assess the feasibility prior to implementation of a traceability system. Furthermore, it can be used for non-food supply chains with some modifications. Analysis revealed that poor feasibility of wholesalers compared to farmers and retailers. Product identification technologies, awareness and willingness for traceability improvement were ranged low to fair for all the entity categories. Hence, enhancement of record-keeping and information sharing, adopting product identification and quality measurement technologies, and strengthening of legislation were identified as key improvements for enhanced fruits and vegetable traceability and efficient postharvest management of studied supply chains
{"title":"Traceability of Fruits and Vegetables Supply Chain towards Efficient Management: A Case Study from Sri Lanka","authors":"Y. Samarasinghe, B. S. Kumara, A. Kulatunga","doi":"10.46254/j.ieom.20210203","DOIUrl":"https://doi.org/10.46254/j.ieom.20210203","url":null,"abstract":"The necessity for food traceability has been increased over the years with the expansion of food supply chains globally over these years due to stringent of food safety regulations. Enhancing the access to quality food safely is one of the essential requirements of food supply chain traceability. Conversely, significant percentages of postharvest losses available especially in developing countries due to poor supply chain and logistics practices thereby threatening food security. Unless there is a possibility to trace the Supply chain, it is difficult to take remedial actions. When it comes to Sri Lanka, currently it is harder to have the traceability in most of the foods supply chains commonly on most of the elementary supply chains such as fruits and vegetables. This has led to postharvest losses since it is harder to identify when and where damages occur, who are accountable, harvested and transient times, supply demand mismatch too. Therefore, this paper aims to investigate the feasibility of tracing of fruit and vegetable supply chain in Sri Lanka and contribute theoretically to facilitate authorities and decision makers for future traceability improvement. Availability of secondary information on fruits and vegetables traceability was examined referring to government agencies. Basic structure of supply chain was identified based on secondary data and a case study was conducted based on supply chains linked to Thambuththegama and Keppetipola Dedicated Economic Centers to gather primary data. To quantify the feasibility of tracing, a feasibility index was developed. Developed index was used to assess the feasibility towards improved traceability of selected chains where it can be applied for other food and non-food supply chains as well. The feasibility index can be used for other fruits and vegetables supply chains too to assess the feasibility prior to implementation of a traceability system. Furthermore, it can be used for non-food supply chains with some modifications. Analysis revealed that poor feasibility of wholesalers compared to farmers and retailers. Product identification technologies, awareness and willingness for traceability improvement were ranged low to fair for all the entity categories. Hence, enhancement of record-keeping and information sharing, adopting product identification and quality measurement technologies, and strengthening of legislation were identified as key improvements for enhanced fruits and vegetable traceability and efficient postharvest management of studied supply chains","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128487594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.46254/j.ieom.20210201
A. Alzahrani, Ahmad Al Hanbali
The fire station location is a critical decision to optimize the coverage level as measured in terms of the response time. This paper focuses on optimizing the coverage problem, especially in the fire protection field, with new model features to incorporate realistic business challenges such as location criticality and secondary coverage. We extend the deterministic Maximum Coverage Location Problem to account for Top Corporate Risk locations being covered by different fire stations as primary and secondary coverage. To deal with the response time uncertainty arising in practice, we propose a new binary linear problem based on the Maximum Expected Covering Location Problem. By exploiting the model structural characteristics, we prove that the model complexity can be substantially reduced to yield an efficient solution. In the numerical experiments, we use a real case study with five years of historical data. The optimization results of the models yield a priority ranking of the fire stations to open and show the value of incorporating the coverage uncertainty. Finally, we also compare our model with uncertainty with the standard scenario-based optimization to extend the numerical results.
{"title":"Maximum Coverage Location Model for Fire Stations with Top Corporate Risk Locations","authors":"A. Alzahrani, Ahmad Al Hanbali","doi":"10.46254/j.ieom.20210201","DOIUrl":"https://doi.org/10.46254/j.ieom.20210201","url":null,"abstract":"The fire station location is a critical decision to optimize the coverage level as measured in terms of the response time. This paper focuses on optimizing the coverage problem, especially in the fire protection field, with new model features to incorporate realistic business challenges such as location criticality and secondary coverage. We extend the deterministic Maximum Coverage Location Problem to account for Top Corporate Risk locations being covered by different fire stations as primary and secondary coverage. To deal with the response time uncertainty arising in practice, we propose a new binary linear problem based on the Maximum Expected Covering Location Problem. By exploiting the model structural characteristics, we prove that the model complexity can be substantially reduced to yield an efficient solution. In the numerical experiments, we use a real case study with five years of historical data. The optimization results of the models yield a priority ranking of the fire stations to open and show the value of incorporating the coverage uncertainty. Finally, we also compare our model with uncertainty with the standard scenario-based optimization to extend the numerical results.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116322403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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