BOHR International Journal of Operations Management Research and Practices最新文献

{"title":"Reconfiguring a multi-period facility model—An empirical test in a dynamic setting","authors":"E. Samunderu, Otto Hahn Hahn","doi":"10.54646/bijomrp.2022.03","DOIUrl":"https://doi.org/10.54646/bijomrp.2022.03","url":null,"abstract":"Facility location is an important problem faced by companies in many industries. Finding an optimal location for facilities and determining their size involves the consideration of many factors, including proximity to customers and suppliers, availability of skilled employees and support services, and cost-related factors, for example, construction or leasing costs, utility costs, taxes, availability of support services, and others. The demand of the surrounding region plays an important role in location decisions. A high population density may not necessarily cause a proportional demand for products or services. The demography of a region could dictate the demand for products, and this, in turn, affects a facility’s size and location. The location of a company’s competitors also affects the location of that company’s facilities. Another important aspect in facility location modeling is that many models focus on current demand and do not adequately consider future demand. However, while making location decisions in an industry in decline, carefully and accurately considering future demand is especially important, and the question in focus is whether to shrink or close down certain facilities with the objective of keeping a certain market share or maximizing profit, especially in a competitive environment. This paper develops a model which enables companies to select sites for their businesses according to their strategy. The model analyzes the strategic position of the company and forms a guideline for the decision. It investigates which facilities should be closed, (re)opened, shrunk, or expanded. If facilities are to shrink or expand, the model also determines their new capacities. It depicts the impact on market share and accounts for the costs of closure and reopening. A number of papers deal with location theory and its applications, but few have been written for modeling a competitive environment in the case of declining demand. Existing papers in this area of research are mostly static in nature, do not offer multi-period approaches, nor do they incorporate the behavior of competitors in the market. To demonstrate the validity of the model, it is first solved using a small problem set–three facilities, three demand locations, and three periods–in LINGO solver. To get a better understanding of the model’s behavior, several additional scenarios were constructed. First, the number of demand locations was extended to 10. Our findings show that the model presented provides an extension of existing facility location models that can be applied to a variety of location problems in commercial and industry sectors that need to make their decisions considering future periods and competitors. The developed heuristic shows multiple options for solving the problem, including their advantages and disadvantages, respectively. The Java code and LINGO fragments thus developed can be used to provide easy access to related problems.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122482769","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}

{"title":"Entrepreneurship Education Development Strategies to Increase Students’ Entrepreneurship Intentions in Bali","authors":"N. Yasa, I. P. Sukaatmadja, Anak Agung Vedanta, Putu Laksmita, Dewi Rahmayanti","doi":"10.54646/bijomrp.006","DOIUrl":"https://doi.org/10.54646/bijomrp.006","url":null,"abstract":"This study aimed to identify strengths, weaknesses, opportunities, and threats (SWOT) of entrepreneurship education programs at universities in Bali. The identified results are used as the basis for formulating strategies for developing entrepreneurship education in order to be able to create more and more young entrepreneurs. The approach used in this research is SWOT analysis and internal–external matrix. The results of the study indicate that entrepreneurship education at universities in Bali has been going well; however, there are still obstacles or threats faced and weaknesses from the entrepreneurship education programs that have been running, such as lack of high public appreciation, especially parent’s respect toward the entrepreneurial profession, and the lack of awards obtained from universities. Based on the existing environmental conditions, in the future, the obstacles and weaknesses of existing entrepreneurship education need to be improved by frequently conducting literacy on entrepreneurship education to the community and giving higher awards to students who succeed in becoming entrepreneurs.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122687572","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}

{"title":"Case report: Curriculum management practices by headof schools: empirical evidence from secondary schoolsin the Nnewi Education Zone","authors":"Chukwuka Judith Nkolika","doi":"10.54646/bijomrp.2022.02","DOIUrl":"https://doi.org/10.54646/bijomrp.2022.02","url":null,"abstract":"The curriculum management strategies of highly experienced and less experienced secondary school principalswere compared in this study. The study was guided by a single research topic, and a null hypothesis was testedat the 0.05 level of significance. The study was conducted using a descriptive survey research approach. Theparticipants in this study were 106 secondary school principals and vice principals from 44 public secondaryschools in the Nnewi Education Zone. Because the research population was manageable, no sampling was done.As a result, the study’s population size was made up of 106 secondary school principals and vice principals. Datawas collected using a questionnaire produced by a researcher called the Curriculum Management Practice Scale.Two professionals independently verified the tool. Cronbach alpha was employed to examine the instrument’sinternal consistency, and reliability values of 0.75 were obtained. The researcher and five research assistants useddirect administration to collect data for the study. There was a 100% return rate. The study question was answeredusing arithmetic mean and standard deviation scores, and the null hypothesis was tested using at-test at the0.05 level of significance. The study’s findings indicated that there is no discernible difference in the curriculummanagement techniques of highly experienced and less experienced secondary school principals. Most schoolheads do a review of all course curricula and hold meetings to establish what type of extra-curricular activities arerequired. The study’s implications and findings were drawn.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124134996","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}

{"title":"Enjoyment in academic pursuit and performance improvement","authors":"Narendra K. Sharma","doi":"10.54646/bijomrp.2022.01","DOIUrl":"https://doi.org/10.54646/bijomrp.2022.01","url":null,"abstract":"Academic pursuit is a long-term commitment, which can lead to negative consequences, such as lack of motivation, dissatisfaction, and disappointment if performance in an examination is low. Enjoyment in academic pursuits can sustain the interest and focus necessary to learn and perform. The flow theory, optimal level of arousal, positive academic self-perception, and positive emotional environment provide the necessary intrinsic motivation and important directions to develop strategies to enjoy academic pursuit. A framework has been developed to indicate that simultaneous activation of positive academic self-perception and positive emotional environment routes leads to effective learning with consequent improvement in performance. Students can use these devices through continuous academic self-assessment. Research directions and applications are indicated.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"339 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122995326","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}

{"title":"Unpacking the impact of CRA’s watch announcement on EUsovereign bond yields: empirical examination ofEx Anteand post ante effects of the CRAII regulation","authors":"Samunderu Eyden, Layher Nicolleta","doi":"10.54646/bijomrp.2022.08","DOIUrl":"https://doi.org/10.54646/bijomrp.2022.08","url":null,"abstract":"The study aims to analyze whether there is a correlation between credit rating agencies’ (CRAs) watchannouncements on EU sovereign bond yields and EU sovereign bond yields after the implementation of the CRAII Regulation. In theory, the role of rating agencies is to provide key information to investors regarding the riskassociated with investing in sovereign bonds. However, it remains unclear whether CRAs influence EU sovereignbond yields. Sovereign bond yields are collected for Austria, Germany, Belgium, Finland, France, the Netherlands,Ireland, Italy, Spain, and Portugal. These countries’ samples represent the empirical analysis of our study. Dataused for this analysis include information on European sovereign bond yields, credit watch announcements fromStandard & Poor’s Financial Services, Moody’s Investors Service, and Fitch Ratings, and interest rate volatilityare all extrapolated from the Bloomberg database. European sovereign bond yields are collected from 1940to 2015. Our study conducted multiple linear regression tests to determine whether there is evidence that achange in yield is determined by a watch announcement made by the big three credit rating agencies beforeand after the introduction of the CRA II Regulation and hence, whether CRAs do influence yields with their watchannouncements. According to theF-test andp-value results, the study of sovereign bonds with 10 and 5-yearmaturities shows statistical significance in both situations at 95 and 99% confidence levels. With 0 for all regressionanalyses, interest rate volatility is also statistically significant","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125234075","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}

{"title":"Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic Setting","authors":"Samunderu Eyden, Brose Sven","doi":"10.54646/bijomrp.003","DOIUrl":"https://doi.org/10.54646/bijomrp.003","url":null,"abstract":"Facility location is an important problem faced by companies in many industries. Finding an optimal location for facilities and determining their size involves the consideration of many factors, including proximity to customers and suppliers, availability of skilled employees and support services, and cost-related factors, for example, construction or leasing costs, utility costs, taxes, availability of support services, and others. The demand of the surrounding region plays an important role in location decisions. A high population density may not necessarily cause a proportional demand for products or services. The demography of a region could dictate the demand for products, and this, in turn, affects a facility’s size and location. The location of a company’s competitors also affects the location of that company’s facilities. Another important aspect in facility location modeling is that many models focus on current demand and do not adequately consider future demand. However, while making location decisions in an industry in decline, carefully and accurately considering future demand is especially important, and the question in focus is whether to shrink or close down certain facilities with the objective of keeping a certain market share or maximizing profit, especially in a competitive environment. This paper develops a model which enables companies to select sites for their businesses according to their strategy. The model analyzes the strategic position of the company and forms a guideline for the decision. It investigates which facilities should be closed, (re)opened, shrunk, or expanded. If facilities are to shrink or expand, the model also determines their new capacities. It depicts the impact on market share and accounts for the costs of closure and reopening. A number of papers deal with location theory and its applications, but few have been written for modeling a competitive environment in the case of declining demand. Existing papers in this area of research are mostly static in nature, do not offer multi-period approaches, nor do they incorporate the behavior of competitors in the market. To demonstrate the validity of the model, it is first solved using a small problem set – three facilities, three demand locations, and three periods – in LINGO solver. To get a better understanding of the model’s behavior, several additional scenarios were constructed. First, the number of demand locations was extended to 10. Our findings show that the model presented provides an extension of existing facility location models that can be applied to a variety of location problems in commercial and industry sectors that need to make their decisions considering future periods and competitors. The developed heuristic shows multiple options for solving the problem, including their advantages and disadvantages, respectively. The Java code and LINGO fragments thus developed can be used to provide easy access to related problems.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123375639","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}

{"title":"Application of GATS, a hybrid mega-heuristic model,and DOE, to solve flexible flow shop scheduling problems:a case study","authors":"Phong Nguyen Nhu, Thu Trang Nguyen Le","doi":"10.54646/bijomrp.2023.14","DOIUrl":"https://doi.org/10.54646/bijomrp.2023.14","url":null,"abstract":"Flexible flow shop scheduling (FFSS) is an NP-hard combinatorial optimization problem. Solving this problem using mathematical modeling approaches is very difficult. Mega-heuristic algorithms, such as the genetic algorithm (GA) and tabu search (TS), are powerful tools for finding near-optimal solutions to problems of this type. This paper develops a GATS model by combining GA and TS for solving FFSS problems. In the model, GA is used as the platform for global search, and TS is used to support GA in local search. This paper also uses the design of experiments (DOE) to optimize the parameters of the GATS model. The performance of the models, GATS and GATS with DOE, is compared with traditional heuristics being used. The result indicates that the models are good approaches for FFSS problems.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125724537","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}

{"title":"Application of genetic algorithm, a mega-heuristic approach, to solve a real-size vehicle routing problem: a case study","authors":"Phong Nguyen Nhu, Thao Do Thi","doi":"10.54646/bijomrp.2023.12","DOIUrl":"https://doi.org/10.54646/bijomrp.2023.12","url":null,"abstract":"Most of the 3PL companies that provide transportation services are handling thousands of orders per day. Vehicle routing problems (VRPs) help plan the distribution of goods with the optimum fleet of vehicles and delivery routes and play an important role in helping businesses reduce transportation costs while ensuring service level. VRPs are NP-hard combinatorial optimization problems. It is quite difficult to achieve an optimal solution for real-size problems with a mathematical modelling approach because of its NP-hard structure. Genetic algorithm (GA) plays a major role in searching for near-optimal solutions for NP-hard optimization problems. This article develops the GA model for VRPs. The result shows that the delivery cost is reduced by 17.88%, while the service level increase from 88.7 to 100%. It indicates that the model can be a good technique for VRPs.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131531926","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}

{"title":"Unpacking the Impact of CRAsWatch Announcement on EU Sovereign Bond Yields: Empirical Examination of Ex Ante and Post Ante Effects of the CRAII Regulation","authors":"E. Samunderu, Nicoletta Layher","doi":"10.54646/bijomrp.008","DOIUrl":"https://doi.org/10.54646/bijomrp.008","url":null,"abstract":"The paper aims to analyze whether if, there is a correlation relationship between Credit Rating Agencies’ (CRAs) watch announcements on EU sovereign bond yields and EU sovereign bond yields after the implementation of CRA II regulation. In theory, the role of rating agencies is to provide key information to investors regarding the risk associated with in investing in sovereign bonds. . . However, it remains unclear whether CRAs influence EU sovereign bond yields. Sovereign bond yields are collected for Austria, Germany, Belgium, Finland, France, the Netherlands, Ireland, Italy, Spain and Portugal. This country sample represents the empirical analysis of our study. Data used for this analysis includes information on European sovereign bond yields, credit watch announcements from Standard & Poor’s Financial Services, Moody’s Investors Service and Fitch Ratings and interest rate volatility are all extrapolated from Bloomberg Database. European sovereign bond yields are collected from 1940 until 2015. Our study conducted multiple linear regressions tests in order to determine if evidence exists whether there a change in yield is determined by a watch announcement made by the big three credit rating agencies before and after the introduction of the CRA II Regulation and hence, whether CRAs do influence yields with their watch announcements. According to the F-test and p-value results, the study of sovereign bonds with ten and five-year maturities shows statistical significance in both situations at a 95% and 99% confidence level.With 0 for all regression analyses, interest rate volatility is also statistically significant.","PeriodicalId":433289,"journal":{"name":"BOHR International Journal of Operations Management Research and Practices","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125901961","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}