Unforeseen Costs Research Articles

RISK MANAGEMENT OF TIME CONTROL ON THE CONSTRUCTION OF SAUMLAKI PORT

In the development of the port, there are potentially risk factors that are not identified during its implementation, which can affect work delays and add to unforeseen costs, thus requiring handling in accordance with the classification of risks that occur. The risk is in accordance with the type of activity and the environment of the construction project implemented. The study aims to analyze the influential risk factors during the work carried out, based on the perspective of service providers (consultants and contractors) and owners as well as how to handle risks (mitigation) and the effect of the implementation of the Saumlaki Port Facility Construction work on controlling the timing of work. Identifying risks - risks encountered in the study using the interview method against potential risksthat are likely to occur. The survey results show that there are three risks that have a high risk classification from the perspective of service providers that have the greatest impact on project delays. Theconclusion in the research is the need to apply risk management to the implementation of development to minimize delays and reduce unforeseen costs.

MULTIAGENT APPROACH TO COMPUTER MANAGEMENT IN A HETEROGENEOUS DISTRIBUTED COMPUTER ENVIRONMENT

The reliability of modern computing control systems in a heterogeneous distributed computing environment, along with efficiency, survivability, security, control efficiency, is an important component of their quality. Increasingly, these systems fall into the category of "critical", have an absolute impact on the activities of organizations and enterprises within which they operate. The loss of such systems, even for a short time, leads to serious problems related to loss of income, unforeseen costs, downtime of production and personnel, loss of time, and sometimes man-made disasters. As you know, the greatest impact on the reliability of control systems has the reliability and fault tolerance of a set of software and hardware. Therefore, solving problems related to improving the reliability of the software part of the systems is the most urgent task. Currently, significant results have been obtained in the field of evaluation and forecasting of reliability indicators of elements and typical software packages at the stage of their design; a large number of methods known to algorithms and programs are known; a number of normative documents on project reliability assessment have been developed. However, the task of real-time reliability assessment, when accurate and operational accounting of a number of factors is required, has not been sufficiently solved. To solve the problem of multi-agent approach to computing control in a heterogeneous distributed computing environment used methods of systems analysis, set theory - to develop models of task distribution, models of tasks and computing resources, general systems theory - to study and develop methods of task distribution, logic-theory theory. for modeling computational processes. The article considers a multi-agent approach to computing control in a heterogeneous distributed computing environment. The algorithm is based on the use of economic mechanisms to regulate the supply and demand of resources in the computing environment. The architecture of the multi-agent approach and the functions of the agents are described. Particular attention is paid to calculating the reliability of the task plan based on the logical-probabilistic method.

Optimization of schedules for early garbage collection and disposal in the megapolis

It is shown that due to the growth of waste generated by the metropolis, the processes of their removal and disposal must be more accurately accounted and controlled. If it is impossible to introduce “smart” control systems, it is proposed to search for reserves to increase the efficiency of the processes in their structure. A structural model of operations has been developed that can reduce time costs. The use of incomplete information on the accumulation and removal of garbage leads to unplanned mileage of trucks. In order to avoid unforeseen costs, it is proposed to use early garbage collection, which reduces the frequency of emptying containers. This leads to an increase in the number of truck arrivals to load, but eliminates unforeseen mileage due to inconsistencies in the loading forecast. It is shown that to effectively organize the work of garbage trucks on the transport network of the city, an active, shortest schedule of operations is required, which must be made for several periods. To develop an optimal cyclic schedule of garbage trucks, a method based on the ordering of mixed graphs is proposed. The mixed graph shows the set of garbage collection operations and the time relationships between their execution times. In order to develop an optimal schedule from such a graph, cycles must be removed from the graph. To do this, the “divide and conquer” method was used. The proposed algorithm for graph ordering is used to study the current garbage collection system. As a result of research, higher productivity of garbage trucks and timely removal of organic waste were achieved. The reduction of the weekly working time of 6 garbage trucks with the use of the 70 % container filling level reached 42 hours.

Clash Cost Analysis in Electrical Installations Based on BIM Technologies

One of the core features of delivering a Building Information Modelling (BIM) project is design coordination and clash detection. In the traditional way of conducting investments, the design process consists in the separate work of individual industry specialists on an individual part of the project and checking its compliance with coordination checkpoints. Building information modelling/management is emerging as an innovative way to virtually design and manage projects. Clashes are one of the most problematic elements in construction. They can interfere in the decision-making process by generating unexpected costs of additional materials, work and actions. The purpose of the following paper is to analyze the impact of BIM on limiting cost of clashes and also to check how clashes affect the unforeseen costs of a construction investment and how the BIM methodology can help to reduce them, especially in electrical installations. Basic construction collisions with algorithms of their solutions were presented. The possible financial benefits associated with the use of the BIM approach have been described using mathematical relationships.

Entrepreneurial Risks: Nature, Types, Assessment Methods and Ways to Reduce Them

The article studies the essential, substantive properties and features of the concept (category) “entrepreneurial risk”, defines the types and methods of assessing entrepreneurial risks and ways to reduce them. It is established that entrepreneurial risk characterizes the specifics of the business entity in the direction of overcoming the uncertainty of the situation of inevitable choice, in which it is possible to assess the probability of achieving the desired result, failure and deviation, contained in selected alternatives. It has been found out that the analysis of entrepreneurial risk should be carried out at the expense of: qualitative analysis of entrepreneurial risks, which identifies, describes and classifies risks, as well as a breakdown of what may be caused by them; quantitative analysis of entrepreneurial risks, as a result of which possible entrepreneurial risks are formalized, modelled, calculated and evaluated; the choice of methods of influencing business risks, as a result of which it is expected to reduce business risks or completely neutralize them; making management decisions regarding the protection of business results from the consequences of situations caused by risks; control of results from the occurrence of business risks, their revaluation and adjustment through the adoption of operational management decisions. For the assessment of business risk, it is advisable to use expert methods, calculation and analytical methods, statistical methods, methods of analogies, and methods of cost-effectiveness analysis. It is determined that the ways to reduce the impact of business risks on business activities are: to directly reduce the amount of damage that occurs due to business risk; creation of appropriate conditions under which it is possible to react quickly to the consequences of the realization of business risks; transfer of responsibility for potential risk to third parties; distribution of risk between participants who jointly carry out business activities; business risk insurance; setting aside funds that are necessary to cover unforeseen costs by eliminating partial risks; reducing risks through their financing. In the prospect of further research, it is proposed to investigate the components and features of the accounting system and analytical support of business risk management.

Micro-study on Telework Activity

This paper is a micro-study on telework activity, the author wanting to highlight certain aspects of this form by which today's employees can perform their own tasks that they perform in order to obtain salaries. Starting from the economic meaning of the concept of “work”, we come to the presentation of some advantages and disadvantages that appear, the institutional framework applicable to telework in Romania is adequately treated, resorting to some quantitative or qualitative approaches. The investigations also reveal, in addition to benefits for employees and employers, some risks regarding data protection and surveillance systems, difficulties arising from living in apartments with large family members, high and unforeseen costs, etc.

Factors Influencing the Purchase of Individual Health Insurance Policy in Urban India with Special Reference to Visakhapatnam City

Post insurance reforms of India witnessed new insurance products in the health sector which were not available before the reforms. The share of health care expenditure to GDP is very low in India compared to other developing nations. Due to the exponential increase in the health care segment, the demand for health insurance product increased. As the demand for health care services is increasing in India it becomes important to study the factors which induce the demand for health insurance. Due to the absence of proper health care system in India, private health care system emerges very strongly and cost per head in health care is increasing very fast. It has become very difficult for lower-middle and middle-class people to afford the cost of health care. This has improved the awareness level of having health insurance to protect them from any unforeseen health cost in near future. I assume and propose that rising cost of health insurance would help people to understand the importance of unforeseen risk in case of health cost and induce to purchase health insurance products. As the cost of health seems to be rising so far In India people are becoming more conscious of health insurance purchase. The change in lifestyle encourages people to take treatment at high-end hospitals. This factor and the rising inflation are making individuals purchase health insurance. The outcome of this study would help the insurers and financial policy makers formulate proper strategies to increase the penetration of health insurance.

Too much of a good thing? The unforeseen cost of tags in online retailing

The advent of internet shopping brings countless options for consumers. In response, online retailers aim to facilitate search by attaching descriptive terms to their inventory (e.g., product genres or categories). Called “tagging,” such a practice has been shown to increase product visibility/exposure in an otherwise limitless sea of options. Across five distinct platforms covering a gamut of consumer domains (i.e., food recipes, mobile games, books, videos, and journal publications), we find that the benefits of tagging for product visibility/exposure come with unexpected costs. Indeed, though assigning more tags to a product does indeed boost its visibility/exposure online, doing so also hurts said product’s perceived quality. This effect emerges regardless of proxies used to quantify (i) visibility/exposure or (ii) product liking. We draw on categorization and learning research to explain these results. While multi-tagging increases the likelihood of a product to appear in consumers’ search, it also increases the likelihood of a mismatch between what consumers really sought and what said product can actually deliver.

Limitations and Hypothesis Underlying the Application of CIDA Price Fluctuation Formula in Sri Lanka

The CIDA price fluctuation formula has been recommended in construction projects of more than three months’ duration. The aim is to recover unforeseen costs due to open market escalation, at least to some extent. The industrial perception has not however been researched in detail for further improvements. This research is to gauge the industrial enthusiasm towards the CIDA price fluctuation formula as a means of recovery of loss. The objectives are to disclose the limitations and hypothesis underlying its application, reveal the context in which it operates, measure the perception and key concerns of the users with regard to its reliability. At the outset, a desk review was carried out to identify the logic behind the formula. Existing pre-published information was tracked down in this review. A literature survey was carried to understand the context in which it operates. A series of interview was conducted to gauge the individual perception of practitioners who have been dealing with the formula application. A Maximum Variation Sampling method was adopted to ensure collecting a wide range of participants with different viewpoints and, a narrative analysis method was used to identify shared comprehension among the practitioners. It was found that many of the criticisms entail a valid basis. Hence, it is recommended to publish the indices regularly and calculate the input proportions jointly. It is also recommended to calculate cost adjustment factors for individual contracts and publish the price indices in district basis or introduce price adjustment procedure specific to each administrative district.
 Keywords: CIDA formula; Compensation; Open market vacillations; Price escalation

The interactive model for automatic calculation of the well cluster construction complex cost

Currently, companies are consuming transitions to the development of the difficult oil and gas fields. The difficulty implies factors: features of geological conditions, remote geographic location, features of the relief. The development of new oil and gas fields requires design approaches that ensure maximum profitability on complex assets. One of the promising development options is the digitalization and automation of design processes. The paper proposes a new approach to assessing capital costs when designing well pads in the field. A new method is proposed for calculating costs and restrictions at the stage of resources for optimizing a well pad, taking into account detailed topography and resource availability through digitalization and automation. The problem was solved using an interactive ontological model with built-in knowledge bases and calculation algorithms. The model was tested at the field, the possible risks of using the model were assessed, and sufficient accuracy of the obtained values was obtained. The results of the work make it possible to improve the stage of optimization of the well pad, taking into account the costs of resources: drilling, engineering preparation, backfilling of the road, supply of communications, availability of resources and unforeseen costs. The work supports the trends of digitalization and technological processes and business processes. The developed model made it possible to digitize the stage of optimizing the location of the well pad, to automate the multifactor calculation of costs and restrictions. The results make the possible full automation for definition well pad placement, later on, taking into account detailed topography and resource availability.

How Followers Navigate Leader Self-Disclosure: Examining Leader Self-Disclosure Depth

Self-disclosure, the act of sharing information about the self to others which can at times entail intimate information, provides disclosers with many advantages such as increased intrinsic reward and feeling closer to recipients. However, previous research on self-disclosure has not taken into account the perspective of recipients who are obligated to reciprocate to the discloser regardless of whether they find the disclosure favorable or not. This unforeseen cost from the recipient perspective is even more accentuated within the workplace where relationships are formed involuntarily based on assignments and hierarchy, and where the pursuit of instrumental goals takes precedence before that of socioemotional goals. Thus, high depth self-disclosure, or self-disclosure with intimate information, may not be an effective relationship behavior within the workplace as currently theorized. In this paper, I theorize on the consequences of leader self-disclosure depth within the workplace, a context where instrumental motives outrank the socio-emotional motives. Drawing from social exchange theory, I posit that a leader disclosing high depth information to a follower influences the follower recipient to experience LMX or role overload as a function of the degree to which the information shared is scarce. Furthermore, I explain how these perceptions motivate interpersonal citizenship behavior and interaction avoidance, respectively. Overall, I establish a distinct recipient-based model of self-disclosure.

Determinants of Financial Well-Being Among Young Workers in Jakarta During the Covid-19 Pandemic

This study aims to analyze the effect of financial attitudes, financial behavior, and financial literacy on financial welfare. This research model uses convenience sampling technique through distributing questionnaires and collected as many as 163 respondents. The data was processed using the Structural Equation Modeling (SEM) method with smartPLS 3 software. The results indicate that financial attitudes have a positive influence on financial welfare. A good financial attitude can increase awareness to manage finances so as to improve financial well-being. Financial behavior has a positive influence on financial well-being. Good financial behavior encourages people to make long-term plans to cover unforeseen costs which can ultimately improve financial well-being. Financial literacy has a positive influence on financial well-being. Financial literacy not only affects the way individuals manage finances and solve financial problems, but also has implications for the individual's ability to make financial decisions related to investments, savings, and other financial risks. Thus financial prosperity can be achieved.

Closed-Loop Supply Chain Design and Pricing in Competitive Conditions by Considering the Variable Value of Return Products Using the Whale Optimization Algorithm

In today’s competitive environment, organizations, in addition to trying to improve their production conditions, have a special focus on their supply chain components. Cooperation between supply chain members always reduces unforeseen costs and speeds up the response to customer demand. In the new situation, according to the category of return products and their reprocessing, supply chains have found a closed-loop structure. In this research, the aim was to design a closed-loop supply chain in competitive conditions. For this purpose, the key decisions of this chain included locating retail centers, adjusting the inventory of chain members, and selling prices of final products, optimally determined. For this purpose, a nonlinear integer mathematical model is presented. One of the most important innovations of this research was considering the variable value for return products. Then, in order to solve the proposed model, a whale optimization algorithm was developed. Numerical results from the sample examples showed that the whale algorithm had a very good performance in terms of response quality and speed-of-action in finding the optimal solution to this problem.

Multi-objective vendor managed inventory system with interval type-2 fuzzy demand and order quantities

PurposeThe proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer, multi-item and a consolidated vendor store. Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers, we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI (T1FMOVMI) model. The suggested solution technique can solve both crisp MOVMI and T1FMOVMI problems. By finding the optimal ordered quantities and backorder levels, the Pareto-fronts are constructed to form the solution sets for the three models.Design/methodology/approachA multi-objective vendor managed inventory (MOVMI) is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0. Due to the evolving market conditions, the characteristics of the individual product, the delivery period and the manufacturing costs, the demand rate and order quantity of the MOVMI device are highly unpredictable. In such a scenario, a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem. This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory (IT2FMOVMI) system, which uses interval type-2 fuzzy numbers (IT2FNs) to represent demand rate and order quantities. As the model is an NP-hard, the well-known meta-heuristic algorithm named NSGA-II (Non-dominated sorted genetic algorithm-II) with EKM (Enhanced Karnink-Mendel) algorithm based solution method has been established.FindingsThe experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company. Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model, offering more accurate Pareto-Fronts and efficiency measurement values.Originality/valueUsing fuzzy sets theory, a significant amount of work has been already done in past decades from various points of views to model the MOVMI. However, this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.

Translating the invisible: Governing underground utilities in the Amsterdam airport Schiphol terminal project

Governing material conditions—including physical, material subjects such as machines, build constructions, construction materials, and subsoils—is a crucial challenge within projects and is underrepresented in project governance theory. To clarify the relationship between project governance and materiality, we draw on translation theory, which is essentially about the reinterpretation, appropriation, and representation of interests related to materials. This paper studies the challenges of governing the underground during the construction of the new terminal at Amsterdam Schiphol Airport. The findings show that, during the project life cycle, the translation of the underground by project actors hampered the necessary relocation of utilities in this project. This eventually resulted in delays and unforeseen costs. This translation is explained by a combination of the governance of the project, strategic interactions of project actors, and the characteristics and context of the material conditions. We contribute to project governance studies by demonstrating the usefulness of translation theory to better understand the mechanisms at play in governing underrepresented material conditions in infrastructure projects.

Machine Learning in Hazardous Building Material Management: Research Status and Applications

Assessment of the presence of hazardous materials in buildings is essential for improving material recyclability, increasing working safety, and lowering the risk of unforeseen cost and delay in demolition. In light of these aspects, machine learning has been viewed as a promising approach to complement environmental investigations and quantify the risk of finding hazardous materials in buildings. In view of the increasing number of related studies, this article aims to review the research status of hazardous material management and identify the potential applications of machine learning. Our exploratory study consists of a two-fold approach: science mapping and critical literature review. By evaluating the references acquired from a literature search and complementary materials, we have been able to pinpoint and discuss the research gaps and opportunities. While pilot research has been conducted in the identification of hazardous materials, source separation and collection, extensive adoption of the available machine learning methods was not found in this field. Our findings show that (1) quantification of asbestos-cement roofing is possible from the combination of remote sensing and machine learning algorithms, (2) characterization of buildings with asbestos-containing materials is progressive by using statistical methods, and (3) separation and collection of asbestos-containing wastes can be addressed with a hybrid of image processing and machine learning algorithms. Analysis from this study demonstrates the method applicability and provides an orientation to the future implementation of the European Union Construction and Demolition Waste Management Protocol. Furthermore, establishing a comprehensive environmental inventory database is a key to facilitating a transition toward hazard-free circular construction.

Dynamic multistep uncertainty prediction in spatial geometry

Maintenance procedures for complex engineering systems are increasingly determined by predictive algorithms based on historic data, experience and knowledge. Such data and knowledge is accompanied by varying degrees of uncertainty which impact equipment availability, turnaround time and unforeseen costs throughout the system life cycle. Once quantified, these uncertainties call for robust forecasting to facilitate dependable maintenance costing and ensure equipment availability.This paper builds on the theory of spatial geometry as a methodology to forecast uncertainty where available data is insufficient for the application of traditional statistical analysis. To ensure continuous forecast accuracy, a conceptual dynamic multistep prediction model is presented applying spatial geometry with long-short term memory (LSTM) neural networks. Based in MATLAB, this deep learning model predicts uncertainty for the in-service life of a given system. The further into the future the model predicts, the lower the confidence in the uncertainty prediction. Forecasts are therefore also made for a single time step ahead. When this single step is reached in real time, the next step is forecast and used to update the long range prediction. The uncertainty here is contributed by an aggregation of quantitative data and qualitative, subjective expert opinions and additional traits such as environmental conditions. It is therefore beneficial to indicate which of these factors prompts the greatest impact on the aggregated uncertainty for each forecast point. Future work will include the option to simulate and interpolate input data to enhance the accuracy of the LSTM and explore suitable approaches to mitigate, tolerate or exploit uncertainty through deep learning.

Комерційні ризики морських перевезень в умовах льодової навігації

The commercial risks of sea transportation in ice navigation conditions differ from the usual shipping conditions due to additional factors that affect the fulfillment of the terms of the sea transportation contract. During ice navigation, disputes and litigation often arise between shipowners, charterers, cargo owners and consignees due to the commercial interests of the parties.Purpose.The purpose of this article is to analyze the commercial risks of maritime transport in ice navigation and identify possible ways to reduce them by making additional amendments to the contract of carriage in the global maritime market.Methods. To solve the problem, the following methods were used: the method of theoretical generalization, the method of analysis and synthesis, the method of systema-tization, the method of deduction.Results. The analysis of the international regulatory documents regulating commercial conditions and risks of navigation in the conditions of ice navigation is carried out. The main commercial risks arising from the organization of shipping and icebreaking of ships are identified and characterized, and measures to reduce them are proposed.Originality. The need to improve the commercial conditions for sea transport during the ice navigation period is due to an increase in commercial risks and, as a consequence, a decrease in cargo flows in ports in the winter. It is proposed to create new rational approaches to the conclusion of contracts of carriage by sea, taking into account international experience in order to reduce risks and attract cargo.Output. In conditions of ice navigation, the commercial risks of international maritime transport increase significantly due to. This has a significant impact on the business costs of the transport participants due to delays, unforeseen costs and additional risks. All of these factors reduce the commercial efficiency of maritime transport for all participants. It is necessary to constantly refine and improve the charter conditions in ice navigation conditions.Keywords: ice navigation, sea transportation, commercial operation of a vessel, commercial risks.

Economic-mathematical model for complex risk assessment of the enterprise investment project using fuzzy logic

The article proposes an economic-mathematical model for determining a comprehensive risk assessment of the investment project of the enterprise which are based on the approaches of A. Nedosekin. The model is built using fuzzy logic and takes into account the probability of occurrence of each of the identified risks and the level of impact of each of them on the project. The probability of risk is set by experts in the form of points and converted into linguistic terms, and the level of influence of each of them on the project – the ratio of benefits and is determined using Fishburne scales. The proposed Project Risk Model consists of the following stages: formation of initial data using expert opinions; construction of a hierarchical project risk tree; determination of weight coefficients (Fishburne weights) of project risks; selection and description of membership function and linguistic variables; conversion of input data provided by experts from a score scale into linguistic terms; recognition of qualitative input data on a linguistic scale; determination of a complex indicator of investment project risks; interpretation of a complex indicator. The developed model allows managing the risks of the project to maximize the probability of its successful implementation, to compare alternative projects and choose less risky, to minimize the level of unforeseen costs of the project.

Artificial intelligence as a tool for evaluating the efficiency of innovative technologies for hard-to-recover reserves development

The possibility of artificial intelligence use for improvement of efficiency of development of hard-to-recover reserves in Russian oil and gas complex are considered in research article. The share of hard-to-recover reserves increases annually in cumulative oil production in the territory of the Russian Federation, therewith ups and downs of prices for oil well-known brands increase the risks of unforeseen costs and material losses when developing new reserves, that is why the authors establish a goal to analyze the efficiency of geological exploration and development of oil hard-to-recover reserves using artificial intelligence technologies and also based on the calculation of a comparative model for assessing the use of artificial intelligence on groups of fields of the Bazhenov formation. Artificial intelligence can have a beneficial effect on decrease of human error risk when selecting potential cased holes and facilitate in choosing the best methods of development and feed production stimulation. As a result of the comparative assessment of the return on investment in the development of wells using artificial intelligence and traditional technologies, the advantages and disadvantages of AI technologies were identified in the context of increasing the economic efficiency of hard-to-recover oil production.