Strategies and Effective Decision-Making against Terrorism Affecting Supply Chain Risk Management and Security

Purpose The purpose of this paper is to investigate the knowledge gaps in the published research on terrorism-related risk in supply chains, and to develop a framework of strategies and effective decision-making to enable practitioners to address terrorism-related risks in supply chain risk management (SCRM) and security.Design/methodology/approach The study adopts a novel combination of triangulated methods comprising a systematic literature review (SLR), text mining and network analysis. These methods have not been jointly utilized in past studies, and the approach constitutes a rigorous methodology that cross-validates results and ensures the reliability and validity of qualitative data.Findings The study reveals a number of key themes in the field of SCRM and security linked with terrorism. The authors identify relevant mitigation strategies and practices for effective strategic decision making. This subsequently leads us to develop a strategic framework of strategies and effective decision-making practices to address terrorism-related risk, affecting SCRM and security. The authors also identify key knowledge gaps in the literature and explore the main contributions by disciplines (e.g. business schools, engineering and maritime institutions) and countries.Practical implications The authors provide a strategic framework of strategies and effective decision-making practices that managers can use to minimize terrorism-related risk in the context of SCRM and security.Originality/value This paper introduces a novel methodological combination for improving the quality of SLRs. It uses the approach to systematically review the strategies and effective decision-making practices interlinked with terrorism risk, affecting SCRM and security. It identifies significant knowledge gaps and defines directions for future research

Flexibility Value of Distributed Generation in Transmission Expansion Planning

The efficiency of the classic planning methods for solving realistic problems largely relies on an accurate prediction of the future. Nevertheless, the presence of strategic uncertainties in current electricity markets has made prediction and even forecasting essentially futile. The new paradigm of decision-making involves two major deviations from the conventional planning approach. On one hand, the acceptation the fact the future is almost unpredictable. On the other hand, the application of solid risk management techniques turns to be indispensable. In this chapter, a decision-making framework that properly handles strategic uncertainties is proposed and numerically illustrated for solving a realistic transmission expansion planning problem. The key concept proposed in this chapter lies in systematically incorporating flexible options such as large investments postponement and investing in Distributed Generation, in foresight of possible undesired events that strategic uncertainties might unfold. Until now, the consideration of such flexible options has remained largely unexplored. The understanding of the readers is enhanced by means of applying the proposed framework in a numerical mining firm expansion capacity planning problem. The obtained results show that the proposed framework is able to find solutions with noticeably lower involved risks than those resulting from traditional expansion plans.Fil: Vásquez, Paúl. Consejo Nacional de Electricidad; EcuadorFil: Olsina, Fernando Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin

Implementasi Algoritma Apriori Untuk Aplikasi Data Mining Informasi Manfaat Asuransi Jiwa Studi Kasus : Pada PT Azarel Jelia Sejahtera

— Insurance protection cannot be separated from human life. because there will always be a risk in every human activity. Azarel Jelia Sejahtera Company is one of the office agency of Prudential Life Assurance Company (Prudential Indonesia). As The largest company in Indonesia which is engaged in life insurance, business challenges will be heavier and the amount of competition makes companies must constantly innovate and be forefront of this business. The information system is one of the resources that can be used to improve competitive advantage. Information systems can be used to obtain, process, and disseminate information to support daily operations and at support the strategic decision making. The rapid growth of data accumulation has created a data-rich conditions but minimal information. Data mining is mining or the discovery of new information by looking for certain patterns of large amounts of data that are expected to treat the condition. By leveraging customer data, is expected to yield information about the benefits of insurance through data mining techniques. Categories insurance benefits are measured based on age range, gender, and the amount of premium customers. The algorithm used is Apriori algorithm and the information displayed in the form of support and confidence values of each insurance benefits category. Keywords— Data mining, Apriori algorithm, Insurance Benefit

Sustainable management: a strategic challenge for a global minerals and metals industry

This paper refers to the concept of sustainable management as the management approach which efficiently integrates economic, environmental and social issues into the operations of the minerals and metals industries, with the aim of creating long-term benefits for all stakeholders, and securing the support, cooperation, and trust of the local community. Among many other issues, sustainable management deals with strategy, responsible project feasibility decisions, managing for operational efficiency, improved risk management, enhanced stakeholder relationships, and corporate reputation. Overall, it deals with seeking long-term competitive advantages through responsible management of environmental and social issues. An essential requirement for sustainable management is the corporate commitment to the values of sustainability, but this is not sufficient. Also essential is the development of a business culture where sustainability is a high professional and business value. Furthermore, an organizational structure with specific roles and integration mechanisms and adequate management systems are also required. Regarding business culture, a well-established business code is a necessary but an insufficient condition. Sustainable management relies on individual ethical conduct and trust to foster full participation of stakeholders and to encourage commitment among them. It allows decision making at appropriate levels in the organization and encourages individual risk-taking for continuous improvement. Without trust, social licence is not achievable. In this paper, the concept of sustainable management is introduced as the management approach that integrates a business culture, strong leadership and an organizational structure that strives for long term economics benefits through sustainability. To achieve this goal, sustainability must be vertically integrated at three organizational levels (corporate, divisional and operational) and three functional levels (strategy, planning and implementation)

Prediction of psychosocial risks in teachers using data mining

Integrated management systems aim to improve these everyday situations that are inherent to work and cause for concern. In search for continuous improvement, it is necessary to innovate with techniques in areas that are not yet explored and that contribute to strategic decision-making processes, such as machine learning techniques or machine learning. In occupational safety and health management systems, it is important to carry out the proper follow-ups and process controls in any type of industry and organization whose relationship is direct. This paper presents the application of three methods related to data mining: Support Vector Machine algorithms, Naïve Bayes, and Genetic Algorithms to identify the degree of psychosocial risk in university teachers of the Mumbai University in India. The use of SVM easily recognizes physiological variables and the best prediction performance was achieved with 96.34% accuracy efficiency

Environmental risk assessment of inorganic chemicals in mining environment.

Mining is one of the human‟s earliest industrial activities. Indeed early civilizations such as the Bronze Age and Iron Age are named according to their use of metals; the importance of metals is still central to industrialization and urbanization. The enormous quantities of mine waste and tailings generated by mining every year however, are also of concern. The relocation and removal of large quantities of mineral and waste can also release chemicals into the environment especially surface water, groundwater and soil during the mining lifecycle if good mining engineering and mitigation are not performed. To optimise this risk management based on excellent risk analysis is required. The study analysed the mining life cycle, chemicals in the mining environment, current regulations on chemicals in the environment and the development of environmental risk assessment framework with particular focus on the inorganic substances. Chemicals in the mining environment were then grouped into a) the minor constituents of the ore deposits; b) chemicals used in mining such as explosives, leaching chemicals and froth flotation reagents. c) chemicals generated by mining, milling and smelting including Acid mine drainage (AMD) and emissions from smelting and refining. The natural and anthropogenic sources, potential pathways to environmental and human receptors and the implications on human health of key toxic metals and metalloids in the mining context were then evaluated. A new two-tier risk assessment was developed based on the four-step conventional risk assessment framework by the U.S.National Research Council (NRC). Tier 1 involved analysing and evaluating existing data using two new semi-quantitative risk screening and prioritisation procedures, namely Chemicals of Greatest Concern (CGC) and Media of Greatest Concern (MGC). CGC was developed using specific hazardous properties of the inorganic chemicals and their eco-toxicities in the environment. MGC was a system of decomposition using a combination of various decision-making tools such as Multi-criteria decision making (MCDM) and Hierarchical holographic modelling (HHM) to facilitate hazard identification and assessment. Tier 2 involved quantitative toxicity assessment, exposure assessment and risk characterisation which were used to quantify the total risk to human health using Monte Carlo simulations (MCS). The tiered risk-based approach developed was evaluated using three cases studies, viz, the Rustenburg platinum (Pt) mine, South Africa; the Lisheen lead (Pb) – zinc (Zn) mine, Ireland and the Richmond copper (Cu) smelter. The results from them were evaluated and compared as a basis for Anglo American plc‟s global strategic decision making. Finally, the strengths and weakness of the methodology developed were evaluated in relation to the application at current operational level. Future methodology refinement and incorporation of organic chemicals were also discussed

Development of a Methodology for the Economic Assessment of Managerial Decisions as a Factor of Increased Economic Security

The article notes that the emergence of such a phenomenon as the interdependence of security and development, the so-called security-development nexus, becomes a determinant during the development of strategic documents at all hierarchical levels. It gives relevance to the search for methodological solutions that would on a strategic level take into account any potential threats to economic security, and on a tactical level provide for pragmatic actions that are not in conflict with the strategic development vector of business entities. The authors identify the instability factors that pose a real threat to economic security. They substantiate the expediency of forming a new model of the national economy development with a focal point on new industrialization. The article factors in the most important trends in the development of the global economy that determine the strategic vector of enhancing the economic security in Russia. It is ascertained that in the conditions of new industrialization, the intellectual core of the high-tech economy sector is formed by convergent technologies (NBICS technologies). The authors offer a methodological approach to the economic assessment of managerial decisions in the context of uncertainty. They also identify methodological principles that must be taken into account in developing a modern methodology for the economic assessment of business decisions. The principles include forming a preferred reality, or the so-called “vision of the future,” the priority of network solutions as the basis for the formation of new markets; mass customization and individualization of demands, principal changes in the profile of competences that ensure competitiveness on the labor market, use of the ideology of inclusive development and impact investment that creates common values. The proposed methodology is based on the optimum combination of traditional methods used for the economic assessment of managerial decisions with the method of real options and reflexive assessments with regard to entropy as a measure of uncertainty. The proposed methodological approach has been tested in respect of the Ural mining and metallurgical complex.The article has been prepared with the support of the grant from the Russian Foundation for Basic Research № 16–06–00403 "Modelling the Motivational Potentials of the Multi-subject Industrial Policy in the Context of New Industrialization"

Decision analysis techniques for adult learners: application to leadership

Most decision analysis techniques are not taught at higher education institutions. Leaders, project managers and procurement agents in industry have strong technical knowledge, and it is crucial for them to apply this knowledge at the right time to make critical decisions. There are uncertainties, problems, and risks involved in business processes. Decisions must be made by responsible parties to address these problems in order to sustain and grow the company business. This study investigates some of the most recognized decision analysis techniques applied by global leaders from 2006 to 2016. Several decision analysis tools are introduced such as heuristic decisions, multi-attribute rating, decision trees, Monte-Carlo simulations and influence diagrams. The theoretical development framework is presented. The approach for this research is Analyze, Design, Develop, Implement, and Evaluate (ADDIE), which included cognitive, behavioral, and constructive learning theories. Some of the top decision analysis skills needed for today’s leaders and managers from literature review over the past decade (2006 to 2016), were taught to organization leadership doctorate students. Research scheme, the method chosen for selecting the topic, group of contributors, and the method selected for collecting the data are offered. The learners were in their senior year of a leadership doctorate program and they did not need leadership training along with decision analysis technique training. Older learners had more interest in learning the fishbone and influence diagrams prior to the training. Students with intermediate math were more interested in learning about strategic planning techniques before training. The trainees with more computer skills were interested in learning the Zachman framework technique, which was surprising to the researcher since this tool does not require extensive computer skills. After the training, the researcher observed that learners with higher computer skills showed more interest in learning about group decision-making (consensus versus analytic hierarchy process). That students with intermediate math skills were more interested in top-down induction of decision trees, algorithm decision making (data mining and knowledge discovery), and strategic planning techniques. Spearman correlations with a moderate strength showed that older respondents tended to be more interested in the analytical hierarchy process, fishbone diagram, and risk analysis tool. After the training, students with stronger computer skills showed greater curiosity about learning more about the decision tree analysis, Zachman framework, and risk analysis. It made sense that students with weaker computer skills were less eager to learn about the Monte-Carlo simulation

Models and methods to make decisions while mining production scheduling

Purpose is to develop a new approach to the design of mining operations basing upon models and methods of decision making. Methods. The paper has applied a complex approach involving approaches of decision-making theory. Analysis of the pro-duction development scenarios is proposed for strategic activity planning; criteria to make decisions under the uncertainty conditions as well as decision-making trees for day-to-day management are proposed to determine balanced production level. Findings. It has been identified that mining production design is of the determined character demonstrating changes in “state of the nature” depending upon the made decisions. The idea of mining production is to reduce uncertainty gradually by means of analysis of production scenarios, and elimination of unfavourable alternatives. Operative management is implemented while constructing decision trees, and optimizing operation parameters. Representation of sets of rational equipment types as well as development scenarios, and their comparison in terms of decision-making parameters makes it possible to determine adequate capacity of a working area, and to reduce expenditures connected with the equipment purchase and maintenance. In this context, limiting factors, effecting anticipatory mining out-put, are taken into consideration. Successive comparison of the alternatives helps identify decision-making area for different scenarios of the production development. Originality. To manage mining production, approaches of decision-making theory have been proposed which involve the use of decision trees, decision-making criteria, and analysis of scenarios basing upon representation of operating procedures in the form of a network model within which the shortest route corresponds to optimum decision. Practical implications. Decision-making system has been developed making it possible to optimize operation parameters, to reduce prime cost of mining, and to select a structure of engineering connections with the specified production level. The described approaches may be applied at the stage of a stope design as well as in the process of a field development. Specific attention has been paid to a software development to implement the approaches.Мета. Розробити новий підхід до проектування гірничого виробництва, який базується на моделях та методах теорії прийняття рішень. Методика. В роботі застосовано комплексний метод, який включає підходи теорії прийняття рішень. Для стратегічного планування діяльності запропоновано досліджувати сценарії розвитку виробництва, для визначення раціонального рівня виробництва – критерії прийняття рішень в умовах невизначеності, а також дерева прийняття рішень для поточного управління. Результати. Виявлено, що процес проектування гірничого виробництва має детермінований характер, який демонструє зміну “станів природи” залежно від прийнятих рішень. Суть проектування гірничого виробництва зводиться до послідовного зменшення невизначеності шляхом дослідження сценаріїв виробництва та виключення несприятливих альтернатив. Оперативне управління здійснюється шляхом побудови дерев рішень та оптимізації параметрів експлуатації. Представлення множин раціональних типів обладнання, сценаріїв розвитку подій та порівняння їх за критеріями прийняття рішень дозволяє визначити раціональний рівень видобутку виймальної дільниці і знизити витрати на придбання та обслуговування обладнання, при цьому враховуються обмежувальні фактори, які впливають на величину очікуваного видобутку. Послідовне порівняння альтернатив дозволяє встановити поле прийнятних рішень для різних сценаріїв розвитку виробництва. Наукова новизна. Для управління гірничим виробництвом запропоновано підходи теорії прийняття рішень, які включають застосування дерев рішень, критеріїв прийняття рішень та аналіз сценаріїв, котрі базуються на представленні технологічного процесу у вигляді мережевої моделі, в якій найкоротший маршрут відповідає оптимальному рішенню. Практична значимість. Розроблена система прийняття рішень, дозволяє оптимізувати параметри експлуатації, знизити собівартість видобутку, вибрати структуру технологічних зв’язків з заданим рівнем продуктивності. Описані в роботі підходи можуть бути використані як на стадії проектування очисного забою так і в процесі експлуатації родовища корисних копалин. Особливу увагу приділено розробці програмного забезпечення для впровадження описаних підходів у виробництво.Цель. Разработать новый подход к проектированию горного производства, который базируется на моделях и методах теории принятия решений. Методика. В работе использован комплексный метод, который включает подходы теории принятия решений. Для стратегического планирования деятельности предложено исследовать сценарии развития производства, для определения рационального уровня производства – критерии принятия решений в условиях неопределенности, а также деревья принятия решений для текущего управления. Результаты. Установлено, что процесс проектирования горного производства носит детерминированный характер, который отражает изменение “состояний природы” в зависимости от принятых решений. Суть проектирования сводится к последовательному уменьшению неопределенности путем исследования сценариев производства и исключения неблагоприятных альтернатив. Оперативное управление осуществляется посредством построения деревьев решений и оптимизации параметров эксплуатации. Представление множества рациональных типов оборудования, сценариев развития событий та сравнение их по критериям принятия решений позволяет определить рациональный уровень добычи очистного участка и снизить затраты на приобретение и обслуживание оборудования, при этом учитываются ограничивающие факторы, которые влияют на величину ожидаемой прибыли. Последовательное сравнение альтернатив позволяет установить поле приемлемых решений для разных сценариев развития производства. Научная новизна. Для управления горным производством предложены подходы теории принятия решений, которые включают применения деревьев, критериев принятия решений и анализ сценариев, основанных на представлении технологического процесса в виде сетевой модели, где кратчайший маршрут соответствует оптимальному решению. Практическая значимость. Разработана система поддержки принятия решений, которая позволит оптимизировать параметры эксплуатации, снизить себестоимость добычи, выбрать структуру технологических взаимосвязей с заданным уровнем производительности. Описанные в работе подходы могут быть использованы как на стадии проектирования очистного забоя, так и в процессе эксплуатации месторождения полезных ископаемых. Особое внимание уделено разработке программного обеспечения для внедрения описанных подходов в горное дело.The study has been carried out within the framework of research project of the National Academy Sciences of Ukraine for young scientists “Resource-saving techniques to support mine workings under the complex hydrogeological conditions”; Agreement #29-04/06-2019; official registration #0119U102370

Intelligent student engagement management : applying business intelligence in higher education

Advances in emerging ICT have enabled organisations to develop innovative ways to intelligently collect data that may not be possible before. However, this leads to the explosion of data and unprecedented challenges in making strategic and effective use of available data. This research-in-progress paper presents an action research focusing on applying business intelligence (BI) in a UK higher education institution that has developed a student engagement tracking system (SES) for student engagement management. The current system serves merely as a data collection and processing system, which needs significant enhancement for better decision support. This action research aims to enhance the current SETS with BI solutions and explore its strategic use. The research attempts to follow socio-technical approach in its effort to make the BI application a success. Progress and experience so far has revealed interesting findings on advancing our understanding and research in organisation-wide BI for better decision-making