Academic literature on the topic 'Degree Discipline: Statistics and Operations Research'

This paper explores the relevance to industry's needs of operations management (OM) teaching in higher education, by researching the content of OM modules delivered by UK academics and comparing the results of this research with the views of business practitioners having had first-hand experience of OM teaching on MBA programmes. To determine whether a gap exists in terms of the importance placed on key content areas, the views of OM academics and practitioners were empirically tested using an online survey instrument. The findings indicate that although there is a broad degree of cohesion among academics relating to module content there are gaps between academics and practitioners in terms of the relative importance of key content areas. Such differences are most evident with regard to supply chain management, capacity management, inventory control and lean production tools and techniques. In this regard, the results provide a backdrop for the development of this important subject discipline to ensure that what is taught in the lecture theatre is valued in the business environment.

Analysis of incident investigation findings as a means of identifying common precursors or causal factors is a common topic of safety research. Historically this type of research has been conducted through a single lens, depending on the researcher’s discipline, with incidents analysed in accordance with a favoured theory, or grouped according to industry or region. This has led to the development of numerous frameworks and taxonomies that attempt to predict or analyse events at various levels of granularity. Such theories and disciplines include safety culture and climate, human factors, human error, management systems, systems theory, engineering and design, chemistry and maintenance. The intent of such research is ostensibly to assist organisations in understanding the degree to which their operations are vulnerable to known precursors or causal factors to major accident events and to take proactive measures to improve the safety of their operations. However, the discipline-specific nature of much of this research may limit its application in practice. Specific frameworks and taxonomies may be of assistance when organisations have identified a relevant area of vulnerability within their operations, but are unlikely to assist organisations in identifying those vulnerabilities in the first place. This paper seeks to fill that gap. A multidisciplinary approach was taken to identify common causal factors. Investigation reports published by independent investigation agencies across various industries were analysed to determine common causal factors regardless of discipline or industry.

Purpose The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index. Design/methodology/approach Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities. Findings Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research. Originality/value This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas.

The article contains a study of the methodological problem of developing the components of an effective computer-oriented methodological system for teaching the discipline «Theory of Probability with Elements of Mathematical Statistics», which is provided for in the training plan for future teachers of mathematics. The methodical and procedural issues of implementing the method of least squares to determine the functional dependence between the characteristics of the sample of the general population in the mathematical software environment Mathcad are considered. Examples of solving problems of equalizing the values of the characteristics of the sample of the general population along a polynomial of the first degree (linear dependence), a polynomial of the second degree (parabola) and a polynomial of the third degree (cubic parabola) are given. A brief review of the scientific, educational and methodical literature, which is used during the teaching of the course of probability theory with elements of mathematical statistics, was carried out, the expediency of using mathematical software during the development of the content of the specified discipline was substantiated. The provision on the need to develop a complex of test tasks of various levels of complexity from probability theory with elements of mathematical statistics for the purpose of objective assessment of students' educational achievements has been formulated. The article formulates conclusions and outlines the directions of further scientific and pedagogical research in the field of implementation of mathematical statistics methods when finding statistical estimates of a sample of values of a random variable of the general totality. The methodological developments given in the article can be useful to students for the organization and activation of independent scientific and pedagogical activities, teachers of secondary educational institutions, leaders of optional and group work of students, teachers of the course of probability theory with elements of mathematical statistics of pedagogical higher educational institutions. Key words: least squares method, probability theory, elements of mathematical statistics, statistical sample, general totality.

Abstract-Educational operations in educational units have several objectives that must be achieved, especially at the level of basic education which will become the foundation for continuing education. The main objective is student achievement. High student learning achievement is one indicator of the quality of education. Many things are thought to have a relationship with student achievement. Among others, discipline and teacher work motivation. Therefore, the focus of this study is to determine the degree of relationship between teacher discipline and work motivation with student achievement, both individually and simultaneously. The research method used is descriptive and verification methods, with data collection techniques using a Likert scale questionnaire, to 60 teachers. Processing of research results using regression analysis techniques. The significance test used the F-test. The results showed that: (1) There is a positive and significant relationship between teacher work discipline and student achievement. (2) There is a positive and significant relationship between teacher work motivation and student achievement. (3) There is a positive and significant relationship between work discipline and teacher work motivation (together) simultaneously with student achievement. Starting from these conditions the authors suggest: (1) The results of the study have shown that operationally there is a significant relationship between teacher work discipline and student achievement. This means that improving the conditions of teacher work discipline can encourage increased student achievement. The condition of teacher work discipline based on the respondent's assessment is in a good category, except that discipline towards the rules is very good. The author suggests that to encourage the improvement of student achievement, so that time discipline and responsibility are increased through exemplary and tightened supervision from the principal. (2) According to the results of the study, the teacher work motivation factor also has a relationship with student achievement. According to the respondent's assessment, the work motivation of teachers is in the very good category, except for the aspects of the motivation and understanding of the teacher's school goals. Therefore, to maximize student learning achievement, it is recommended to increase the motivation for the teacher through clear job descriptions and involve the teacher in setting school goals so that the teacher becomes more aware of the goals that the school must achieve.

The asymptotic decay rate of the sojourn time of a customer in the stationary M/G/1 queue under the foreground–background (FB) service discipline is studied. The FB discipline gives service to those customers that have received the least service so far. We prove that for light-tailed service times, the decay rate of the sojourn time is equal to the decay rate of the busy period. It is shown that FB minimizes the decay rate in the class of work-conserving disciplines.

Purpose – The purpose of this paper is to examine the leadership role of authors, institutions, and countries based on research co-authorship networks in the field of operations management (OM) and ranks European authors, institutions, and countries using network centrality measures. It also identifies the primary research areas of each of the leading European authors and maps the areas that European research in general has focussed most on. Design/methodology/approach – Based on co-authorships in publications appearing in a representative set of three leading OM journals over the 15-year period of 1998-2012, network measures of total degree centrality and betweenness centrality are used to identify influential European agents serving as leaders and bridge builders in OM research. Keyword analysis is used to identify the dominant areas of OM research in Europe as well as the primary areas of research of the leading authors. Findings – With UK, Spain, The Netherlands, and Italy accounting for the dominant share of authorship of papers in the journal set, many authors and institutions from these countries are also found to rank high on network centrality measures. While certain authors, institutions, and countries are found ranking high on total degree centrality based on number of direct connections in the network, others are found to play uniquely important roles as gatekeepers and bridge builders in network relationships. The body of research is found to be focussed most on the area of supply chain management. It is also found to be focussed more on manufacturing than service. Research limitations/implications – The examination of networks in this study based on co-authorships in publications in the set of three leading journals: Journal of Operations Management, International Journal of Operations & Production Management, and Production and Operations Management, is not all encompassing as there are likely other co-authorship relationships of OM researchers that go beyond publications in this set of journals. Practical implications – Co-authorship of papers in the leading academic journals in a discipline provides a window on patterns of collaboration among key researchers within that academic community. The findings of this study inform the community of stakeholders on who the leading European agents in OM research are, what the primary areas of research of the leading European authors are, and areas that European research has focussed most on. Originality/value – This is the first study of its kind that identifies and maps key European authors, institutions, and countries based on the analysis of co-authorship networks of researchers who have published in a set of leading OM journals that are considered to be among the most relevant outlets in the field of OM. It also maps the primary areas of research.

One of the main reasons for acquiring a Bachelor's Degree is the perception of higher education as a means of improving graduates' financial status. In light of the increased accessibility of higher education, a growing number of students hope to use their studies as a financial springboard. In the current study we sought to examine this perception and to check whether and to what degree baccalaureate degrees indeed improve graduates' financial situation. In cooperation with Israel's Central Bureau of Statistics we gathered data on 6,091 graduates who completed their studies at the Ariel University Center during 2000-2008. Data analysis included exploring graduates' rate of employment and monthly salary from the day they began their academic studies until eight years later. We divided and distinguished between graduates by discipline and gender. The findings show that graduates earn almost three times the national average salary (and five times the median salary) and indicate employment rates of nearly 100%. Analysis of findings by discipline indicates that the most profitable fields are computer sciences and mathematics, engineering, and architecture. Salaries in the natural and social sciences and in the humanities are significantly lower both compared to the former fields and to the national average salary, at least for this eight year span. Analysis of the data by sex showed that the rate of employment among men is 12% higher than among women and that there is a disparity in employment within each discipline as well. Research conclusions show that academic degrees per se are not a guarantee of financial or occupational security. Employees with degrees in the social sciences and the humanities may find that their pay is no higher than those with no degree. One of the implications of this issue, already evident at this stage is that students are attempting to attain higher degrees in the hope of improving their financial status. The equation of a higher education with a higher income seems to involve other components as well, such as graduates' field of study, seniority on the job, and field of occupation.

We consider a closed queueing network with a fixed number of customers, where a single server moves cyclically between N stations, rending service in each station according to some given discipline (Gated, Exhaustive, or the Globally Gated regime). When service of a customer (message) ends in station j, it is routed to station k with probability Pjk. We derive explicit expressions for the probability generating function and the moments of the number of customers at the various queues at polling instants and calculate the mean cycle duration and throughput for each service discipline. We then obtain the first moments of the queues' length at an arbitrary point in time. A few examples are given to illustrate the analysis. Finally, we address the problem of optimal dynamic control of the order of stations to be served.

The role of GIS within the discipline of geography, not to mention its role within the daily operation of a very large range of human enterprises in the developed world, has undergone major changes in the decade-plus since the first edition of Geography in America (Gaile and Willmott 1989) was published. Not the least of these major changes is an important redefinition of the acronym. In 1989, GIS meant only “geographic information systems” and referred to an immature but rapidly developing technology. Today, many geographers make an emphatic distinction between the technology (GISystems or GIS) and the science behind the technology (GIScience or GISci). This important transition from a focus on the technology to a focus on the farranging theoretical underpinnings of the technology and its use are clearly reflected in the research progress made in this field in the past decade. This chapter highlights some of the significant aspects of this diverse research and its related impacts on education and institutions. The chapter focuses on the work of North American geographers, though reference to the work of others is unavoidable. We recognize the many and increasing contributions of our colleagues in other disciplines and overseas to the development of GISci, but focus our attention to the scope defined by the present volume. The chapter closes with speculations on the future of GIS in geography in America in the coming decade. In the late 1980s, geographic information systems (GIS) were large stand-alone software and information systems being applied to a growing range of application areas. Today GIS are well integrated into the normal operations of a large range of industries as diverse as forestry, health care delivery, retail marketing, and city planning. Developments in the capabilities of and access to GIS technology during the past decade have paralleled developments in the computer industry as a whole. Similarly, academic research into the fundamental concepts and theories that underlie GIS has matured and become better connected across multiple disciplines. Drawing on fields as diverse as computer science, cognitive science, statistics, decision science, surveying, remote sensing, and social theory, “geographic information science” (Goodchild 1992b) has emerged as an important synthesizing influence during the 1990s.