Mid Sweden University

In this paper, we describe a work in progress where a mixed methods approach is used to increase insight into what kind of consequences a temporal disruption or total breakdown of the payment system creates for a large variety of societal actors and to increase insight in how their collaborative behaviour can be guided to be more resilient. This approach includes data from different types of data collections; workshop with high-level decisionmakers from involved sectors, interviews with citizens, representatives from the fuel, foods, and finance sectors, as well as experiences from 15 simulation game exercises with stakeholders. The triangulated and aggregated outcomes of the different data collections resulted in a set of recommendations on how to cope with disruptions in the card payment system.

Large or lengthy disruptions to the card payment system are threats that can cause crisis in society, especially in countries where other payment options are scarce. This paper presents a study that provides suggestions on how to improve a simulation game used to increase societal resilience to payment system disruptions. Questionnaires and interviews have been used to investigate how 16 participant in crisis exercises experience realism, relevance and validity in such exercises. Suggestions on how to improve the simulation game are provided, such as improvements to the 1 https://ec.europa.eu/digital-single-market/en/desi accessed at 2019-09-20 2 Statistics from 2018, analysed by the Swedish Riksbank, see https://www.riksbank.se/globalassets/media/statistik/betalningsstatistik/2018/ payments-patterns-in-sweden-2018.pdf 3 There are several reports of such disruptions in the card payment system, although the duration of the disruptions were shorter than ten days. See for example (all accessed on 2019-10-17): https://www.bbc.co.uk/news/business-44335804 graphical interface and introducing supporting roles from the exercise management.

Maritime transport facilitates trade with bioenergy feedstocks in the Baltic region. The study aims to provide guidance on efficient organisation of logistics at the port of loading for maritime transport of wood chips. The economic effects of using an intermediate terminal as opposed to direct delivery to port were studied, as well as the relationships between production capacity and storage capacity. Discrete-Event Simulation was used to analyse scenarios where a variable part of the volume is handled through the terminal. The total supply cost, including chipping, transportation, storage and handling at inland terminal and port, as well as loading of the ship, varied between €6.73 and 7.85 per MWh in the different scenarios. The volume passing through the terminal had a significant influence on total cost, showing a supply chain cost increase of €0.78 per m3 (approxi-mately €4.67 per dry tonne) for material delivered through the terminal. The difference in storage cost between port and inland terminal determines whether the terminal volumes affect costs, which was shown by a sensitivity analysis. Even so, the terminal offers a possibility to manage uncertainty, both in production rates and inshipping date, and influences the supply network. The main advantage of using a simulation technique for planning production and logistic flows is the visualisation of risks and margins.

The aim of this study is to determine the optimum stock level in the forest. In this research, a goal programming method was used to estimate the optimal stock level of different tree species considering environmental, economic and social issues. We consider multiple objectives in the process of decision-making to maximize carbon sequestration, net present value and labour. We used regression analysis to make a forest growth model and allometric functions for the quantification of carbon budget. Expected mean price is estimated using wood price and variable harvesting costs to determine the net present value of forest harvesting. The fuzzy analytic hierarchy process is applied to determine the weights of goals using questionnaires filled in by experts in order to generate the optimal stock level. According to the results of integrated goal programming approach and fuzzy analytic hierarchy processes, optimal volume for each species was calculated. The findings indicate that environmental, economic and social outcomes can be achieved in a multi-objective forestry program for the future forest management plans.

This paper aims to determine the optimal stock level in Hyrcanian forest of Iran. In this study, a goal programming techniques used to estimate the optimum stock level of different tree species considering economics, environmental and social issues. We consider multiple objectives in the process of decision making to realize the balance of maximizing annual growth, net present value, carbon sequestration and labor. We use regression analysis to develop a forest growth model using allometric functions for the quantification of carbon budget. The expected mean price was estimated to determine the net present value of forest harvesting. We use Expert knowledge to weight the goals in order to generate the optimal stock level. Results show that the total optimum stock is 0.5% lower than based on questioners. The results indicate that goal programming is a suitable methodology in this case. 

In telecommunication research, the assessment of strategic and operational performance has gained a lot of interest. So far, the variability within the operational research of telecommunication derives from the stochastic nature of call arrivals, call duration and abandonments. This study extends the stochastic drivers to capacity by incorporating agent behavior. In this study, we model a Discrete-Event-Simulation model of the Swedish emergency call service provider to assist the strategic issue of skills-based routing. Because of the pull system, we designed skills-based routing using an event-dependent overflow setting with a fixed waiting time threshold, where calls become visible to extended agent classes after a threshold value, providing an advantage to primary idle agents to answer before idle secondary agents. Our model mimics the tail of waiting times better than conventional methods. Because of the accompanied calculation opportunities, the model has assisted both strategic and operational issues in the organization. In addition to practical implications, the study proves that the stochastic nature of agent behavior is crucial. From a queueing theory perspective, the study provides interesting routing effects for an event-dependent overflow setting using a fixed waiting time threshold in a combined “X-N-design”, previously unexplored in research.

Evaluation is often connected to the use of quantitative data. However, in some contexts, quantitative data is not entirely comprehensive. Municipalities offer government services to citizens but have difficulty evaluating the value citizens experience from the services. Therefore, this paper presents the results of a project involving Mid-Sweden University and the Sundsvall municipality in central Sweden by presenting a model for citizen value collection. The value collection targets municipal workers (service providers) and citizens (service receivers). The model is constructed using design science and builds upon the recursive quality management methodology of Plan-Do-Study-Act. The results provide a valuable model for practice (municipalities), allowing citizen and worker values to be collected from municipal services and comparing them to evaluate whether any value gaps must be addressed.

The recent increase in welfare technology implementation calls for the development of evaluation methods. Previous research has identified the need for a coherent evaluation model to create indicators that combine individual, economic and organizational dimensions. The Technology Implementation Evaluation Score (TIES) works in this way. It provides a score by combining statistical and monetary data (quantitative data) with patient and caregiver opinions (qualitative data). This paper aims to investigate the effects of including qualitative data on the outcome of the TIES model, compared to only using quantitative data. Various combinations of inputs are investigated by performing a sensitivity analysis using extreme value scenarios. The result shows that the TIES model is more affected by the number of data types created and the weight attached to each input than the data used as inputs. The assessment shows that the model is appropriately constructed for the current home care case.

Digitalisation in the form of new technologies and solutions is a rapid movement affecting the whole world.Home or assistive care has had a long period of trouble trying keep up, even though it is a promising area of application. As home care tries to catch up, rushing to implement technologies or IT systems can result in misfit solutions that do not satisfy their purpose. The values of healthcare meanthat measuring success of technology implementation is different than in production sectors. The main focus is patient satisfaction and should, therefore, also be included in any evaluation. The present study proposes a conceptual model that aims to facilitate considering both quantitative and qualitative data, including patient and caregiver values, whenmeasuring efficiency in healthcare management. The model combines multi-criteria decision analysis (MCDA) and data envelopment analysis (DEA) to make it possible to handle both crisp and fuzzy values. The model is tested and evaluated using a home care case study, which shows promising results.

By describing companies through their processes it is possible to get a well-established overall understanding of the company. This case study is based on the daily operations of a small logistics company specialized in international transportation. We perform Value Stream Mapping in order to propose improvements leading to reduced processing time. Afterwards a Data Envelopment Analysis based method is used to calculate the leanness score of the current system and estimate how much the leanness can increase by the proposed improvements. Results show that waste produced by bad workplace layout and over-processing can be eliminated. A suggested solution is to introduce standardized processes and to invest in technical instruments in order to automate production. According to this study the business is 45 percent lean at present and could with simple improvements soon become 61 percent lean and finally reach an ideal state at 100 percent leanness if production is automated.

There are usually many sources for the supply of raw material to a pulp or paper mill in Sweden. The decision-maker can procure raw material from the company's own forest(s), buy in from the owners of small forests, swap with other forest operators or purchase on the international market. Wood chips for these mills are brought from sawmills and have their own transportation system, but are included in the model presented here. Optimizing the supply of raw material at a tactical planning level is a challenging task, and can only be managed properly if elements of uncertainty are considered. The solution would otherwise give few options when disturbances occur, for example when weather conditions change. The deterministic equivalent of the scenario model is formulated and solved as a convex mixed integer quadratic model. In this paper, we have focused on model building since this is a challenging task in itself. The model is tested on one small sample problem and one full-scale problem. We show how to simulate and evaluate different strategies in the flow of raw materials, from harvesting operations to delivery at the mills. In our study, the full-scale problem has been solved within reasonable time using commercially available software, and the solution indicates that the hedging effect in the stochastic solution adds flexibility. Future work will involve the development of stochastic programming algorithms to solve large-scale instances of the problem using parallel computing.

There are usually many sources for the supply of raw material to a pulp or paper mill in Sweden. Optimization of this supply is therefore a challenging task, and can only be managed properly if all aspects of risk are considered. In our study, these risks are related to when the weather reduces the load-bearing capacity of the ground or the roads. A stochastic and a deterministic model have been formulated, and they have been solved with mixed-integer quadratic programming and tested with data from a Swedish forest company. The results of this study show that the option value is greater than zero and that both the optimal policy and the option value change whenever the storage cost is altered. This shows that the optimal planning policy obtained from the stochastic model differs from the solution of the deterministic model.

In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.

Intelligent matching of goods and freight transports is a complex task since different transport modes, such as trains, vessels and trucks have different strengths and weaknesses. Today, however, not only transport cost and time are considered but also the low emission is regarded as an important objective in intermodal freight logistics. The paper describes an approach for generating and ordering transports alternatives in the presence of cost, time, and emission conflicts. In order to obtain a reasonable ordering for generated alternatives we propose the use of the normalized Chebyshev distance between an alternative and a reference point, herein defined as a middle point. By doing so, preference information from a decision maker may be taken into account. The approach is tested on a medium sized problem. The results are promising and indicate the possibility of using the developed method in a decision support system. 

This paper presents a multi objective chance constrained programming model for matching of goods and transports in an intermodal transport chain under uncertain delivery time. The objectives in the proposed model are cost, emission, and transport time, where time is considered as an uncertain parameter. An approach to solve the model is proposed, and this approach has been implemented in a web-based system for transport matching in order to provide clients with alternative transport routes in a large system of possible transport solutions. A case study of a Swedish shipping company is analyzed, and the results are presented through comparisons of results from deterministic and stochastic models. The suggested model can help a decision maker to select transport alternative compromising between time, cost, emission, and with respect to uncertainty in transport time parameters.

For traffic safety reasons, Sweden has lowered speed limits on major roads that lack directional separation of traffic. For some of these roads, regional authorities, municipalities, and other local stakeholders have sent appeals to the government opposing the implemented speed limit reductions. The appeals have mainly referred to negative effects on regional development and have suggested that the speed limit reductions be abandoned. This paper identifies the characteristics of roads where appeals against speed limit reductions have been filed and where local stakeholders claim that speed limit reductions are a threat to accessibility and regional development. The results of logistic regression modelling show that appeals are more likely for speed limit reductions on long road sections, on European roads, and in areas with a state university, and less likely in areas with high population density and areas defined as vulnerable by the Swedish Agency for Economic and Regional Growth. We investigated these policy conflicts using frame theory. In this paper, we identify two policy frames: speed limits for traffic safety and speed limits for regional development. These two policy frames are related to different views on how to best strive towards regional accessibility and safety goals in remote areas. The different views are likely not easily aligned by more information or facts since they concern deeper questions, such as what constitutes basic accessibility of good quality and how large risks are acceptable on the road network. This study thus uncovers not only a policy disagreement but a policy controversy in the Swedish context.

We provide an agent based simulation model of the Swedish payment system. The simulation model is to be used to analyze the consequences of loss of functionality, or disruptions of the payment system for the food and fuel supply chains as well as the bank sector. We propose a gaming simulation approach, using a computer based role playing game, to explore the collaborative responses from the key actors, in order to evoke and facilitate collective resilience.

In emergency call centers (for police, firemen, ambulances) a single event can sometimes trigger many incoming calls in a short period of time. Several people may call to report the same fire or the same accident, for example. Such a sudden burst of incoming traffic can have a significant impact on the responsiveness of the call center for other events in the same period of time. We examine data from the SOS Alarm center in Sweden. We also build a stochastic model for the bursts. We show how to estimate the model parameters for each burst by maximum likelihood, how to model the multivariate distribution of those parameters using copulas, and how to simulate the burst process from this model. In our model, certain events trigger an arrival process of calls with a random time-varying rate over a finite period of time of random length.

Forest management in the Iranian Caspian Forest is optimized via harvesting decisions based on individual trees. The theory of optimal control in discrete time, stochastic dynamic programming, is applied. The optimization program utilizes new basal area growth and volume functions for beech, estimated via data from the Iranian Caspian forest.

Recent information about the degree of price variation is used in the optimizations. The optimal control function is defined as a reservation price function, which is determined via backward recursion. The optimal reservation price function and the optimal expected present value function are determined for alternative levels of interest rate and risk. Furthermore, the optimal harvest year and optimal harvest diameter frequency distributions are determined for different degrees of risk and rate of interest. 

This paper discusses the component obsolescence problem and presents a mathematic model for life cycle analysis of long life cycle embedded system maintenance. This model can estimate minimized management costs for different system architecture. Matlab is used to generate a graph and Lingo is used for linear programming. A simple CAN controller system case study is shown to apply this model. A minimized management cost and an optimized management time schedule are given as the result. The responses from the experiments of the model meet our expectation. Although the model has lots of simplifications and limitations, it can give management strategy guidance to the designers who suffer from component obsolescence problems. 

When there is a demand larger than the corresponding number of components in stock, obsolescence problems may occur for those systems with a life cycle longer than that of one or more of their components, such as automotive, avionics, military application, etc. This paper discusses the electronic component obsolescence problem and presents a formal mathematical strategic proactive obsolescence management model for long life cycle systems.

The model presented in this paper utilizes redesign and last-time-buy (LTB) as two management methods. LTB cost is estimated by unit cost, demand quantities, buffer, discount rate and holding cost. Redesign cost is associated with component type and quantities.

This model can estimate the minimum management costs for a system with different architectures. It consists of two parts. The first is to generate a graph, which is in the form of an obsolescence management diagram. A segments table containing the data of this diagram is calculated and prepared for optimization at a second step. This second part is to find the minimum cost for system obsolescence management. Mixed integer linear programming (MILP) is used to calculate the minimum management cost and schedule. The model is open sourced allowing other research groups to freely download and modify it.

A display and control system case study is shown to apply this model practically. A reactive manner is presented as a comparison. The result of the strategic proactive management model shows significant cost avoidance as compared to the reactive manner.

This study concerns some of the relevant topics of the Iranian Caspian forestry planning problem, in particular the first central components in this modelling process, such as forest modelling, forest statistics and growth function estimations. The required data such was collected from Iranian Caspian forests.  To do so, 201 sample plots were determined and the parameters such as number of tree, tree diameter at breast height  and trees height were measured at each sample plot. Three sample plots at different 3 elevations were chosen to measure the tree increment. Data has been used to estimate a modified logistic growth model and a model that describes the growth of basal area of individual trees as a function of basal area. General function analysis has been applied in combination with regression analysis. The results are interpreted from ecological perspectives. Furthermore, a dynamic multi species growth model theory is developed and analyzed with respect to dynamic behavior, equilibria, convergence and stability. Logistic growth models have been found useful in continuous cover forest management optimization. Optimization of management decisions in a changing and not perfectly predictable world should always be based on adaptive optimization.

Forestry in Iran is based on continuous cover forestry (CCF) management principles. CCF often leads to higher expected present values than rotation forestry (RF) with clear cuts. Furthermore, CCF has environmental advantages of several kinds. Many different species of trees grow together in large parts of these forests in Iran. Mixed species forests give advantages compared to monocultures, such as options to adapt harvesting of different species to changes in market prices, climate, species specific damages etc. In order to optimize multi species CCF in Iran, it is necessary to develop mathematical models for operations research studies that represent the relevant parts of the Iranian forestry planning problem. This presentation includes central components in this modelling process: Forest statistics, growth function estimations and the links to forest harvesting, logistics and the forest industry mills.  

The aim of the study is to estimate the aboveground carbon sequestration and to determine the economicvalue of forests in carbon sequestration as a way of mitigating climate change. This research was conductedat Asalem forests in the north of Iran. In order to estimate the amount of annual carbon sequestration, theannual volume growth of stand was determined using the diameter increment data and tariff. The amount ofcarbon sequestration was estimated based on wood density and using the allometric equation. The carbonmodel was obtained for each species. The value of sequestrated carbon in stumpage and the net present valueof carbon sequestration were determined in order to estimate the economic value of carbon sequestration.Results indicated that the annual volume growth per hectare and the carbon stored are 6.023 m3·yr–1 and2.307 t·ha–1, respectively. Finally, the carbon sequestration value of stumpage and the net present value ofcarbon sequestration are 11,023.753 and 790.361 (10,000 IRR·t–1·ha–1), respectively. Our results are very usefulin estimating the total economic value of Asalem forests and other Iranian Caspian forests in the future.

The aim of this study was to estimate a basal area growth model for individual trees in uneven-aged Caspian forests. A survey was conducted in order to find a natural forest without any harvesting activities, a so called ‘untouched forest’ and an area was selected from the Iranian Caspian forest. Three sample plots in the same aspect and of the same forest type were selected. In each plot, total tree height, diameter at breast height, distance of neighbor trees and azimuth were measured. Thirty trees were selected and drilled with increment borer to determine the increment model. Regression analysis was used to estimate the growth model. Results show that, for individual trees, there is a significant nonlinear relationship between the annual basal area increment, as the dependent variable, and the basal area. The results also show that the basal area of competing trees has a positive influence on growth. That the increment is higher with more competing neighboring trees is possibly because plots with higher volume per hectare and more competition, most likely also have higher site index or better soil or better site productivity than the plot with lower volume per hectare.

The aim of this study was to estimate a diameter growth model for individual trees inuneven –aged Caspian forests. Three sample plots in the same aspect and of the same foresttype were selected. In each sample plot, full callipering was conducted and the parameterssuch as total tree height, diameter at breast height, distance of neighbor trees and azimuthwere measured. In each plot, 30 trees were selected and drilled with increment borer, inorder to determine the growth model. Regression analysis was used to estimate the growthmodel. The analysis shows that, for individual trees, there is a strongly significant nonlinearrelation between the annual basal area increment, as the dependent variable, and the basalarea of the individual trees. The results also show, that the basal area of competing trees, inthe sample, has a positive influence on growth. The estimated result that increment is higherwith more competing neighbor trees is probably obtained because of the following reason:The plots with higher volume per hectare, and more “competition”, most likely also havehigher “site index” or “better soil” or “better forest production conditions” than the plotwith lower volume per hectare.

Accessibility is a crucial concept in the study of social inclusion, justice, equity and security as well as the reliability of supply in societies. Research has examined factors that objectively measure accessibility, such as land-use and socioeconomics. However, such approaches often fail to include individual perceptions of accessibility. Thus, this study proposes a multi-linear regression model that focuses on both objective and subjective factors to assess municipal accessibility. In addition, principal component analysis is applied to reduce dimensionality and eliminate the problem of multi-collinearity. The paper contributes a novel model with a higher prediction rate (70.5%) than that of a traditional multi-linear regression model (58%) during an evaluation of accessibility in the Swedish context.

The decisional process involved in IT procurement is complex, largely because it entails a large investment and because it takes time to make the decision. Another layer of complexity arises from the fact that the decision will influence every employee working in the environment supported by the system. This increases the importance of choosing an IT system that improves rather than hinders productivity. The supplier of the IT system can also influence the success of IT procurement, but this aspect is often left out of the equation. This study presents an approach that simplifies the complex decisional process regarding IT procurement. This approach considers not only the IT system to be purchased but also the supplier of the system. The approach combines process mapping of the IT systems (Business Process Modelling and Notation), ranking aggregation of desirable characteristics of the IT systems (Kemeny-Young) and benchmarking through data envelopment analysis. Together, these methods constitute the process-ranking benchmarking model, which is shown to enable a fictional group of decision-makers to reduce the number of prospective IT systems from 10 to just one, thus greatly simplifying their task.

A two-stage stochastic model with binary choice in the first stage has been developed to optimise the upgrading of a real-world forest road network, geographically located in the middle of Sweden. We have compared the model with solutions to the same problem from deterministic scenario analysis. Upgrade policies can be achieved swiftly using both approaches, since the road network is of moderate size. However, a deterministic approach is considerably faster when larger problems are involved. The study here, furthermore, indicates that deterministic scenario analysis provides us with quick, near-optimal solutions to the stochastic model, which are of reasonable good quality. We conclude that the model used here is rather insensitive to uncertainty in critical period length, such as the length of spring thaw, at least when applied to the medium-sized problem presented here. Nevertheless, we strongly recommend the use of the stochastic model whenever possible, since the stochastic and deterministic solutions differ, due to the hedging effect in the stochastic solution.

In a pre-study, concerning roundwood freshness, performed by the Forestry Research Institute of Sweden during the spring of 2000, the quality on the forest road network was identified as a major problem for the Swedish forest sector. These problems mostly occur during spring thaw, but also when rains give muddy gravel roads. The Swedish forest company Holmen Skog decided to support the PhD project presented here with harvest and road data from a forest district, and expert knowledge of road investments.

Upgrading of forest roads has been studied in a major part of this thesis, with two case studies at a forest district of average size located around Sveg in Härjedalen. Deterministic scenario analysis has been used and compared to a two-stage stochastic model. Cost functions, assortment mixtures and scenarios have been analysed, and results have been evaluated together with the staff at Holmen Skog. These case studies indicate that the problem can swiftly be solved, at least at average size forest districts.

In the last paper a model of the roundwood supply chain is developed and tested via a sample problem. The problem is restricted to the supply chain with fixed harvesting and fixed demand at the mills. The considered uncertainty is load-bearing capacity on the road network, which depends on the water content in the road body and the bearing layer quality.

In contrast to the road investment which are long-term decisions, this planning problem is short-term, and in our paper between half a year and one year. One difficult part in this model is the estimation of storage costs. This study, therefore, puts forward the need of measurements of storage costs. Otherwise, it is not possible to optimise the roundwood supply chain in a consistent way. Storage costs should, for that reason, be analysed in the future.

We describe the computational methods to be used in a web based transport matching system in order to providing clients alternative transport routes, and a model for support of combined intermodal transports where time, emissions and costs are jointly handled. We use network optimization and a mixed integer linear model together with subsequent results from a feasibility test carried out within a transport corridor ranging from the west coast of Norway to Finland through Sweden. The test indicates that network optimization is a well suited methodology for this type of problem, providing swift solutions for the selected problem which is of a medium size with respect to the network size. Future development will be focused on the extension and implementation of this model in a web-based multi-criteria decision support system, able to handle conflicts between cost, time, and emissions in the recommendation of admissible transport solutions.

The aim of this study is to assess the relative efficiency of Iranian forest management units using the non-parametric method Data envelopment analyses (DEA). To this end, DEA as a well-known and robust technique for measuring the relative efficiency of organizations is used. The relative efficiency of comparable forest plans was calculated with the most frequently used DEA models – CCR, BCC and SE[LO1] . According to the results of global technical efficiency (CCR) and local pure technical efficiency (BCC), the efficiency averages were 0.83 and 0.93, respectively. The results of scale efficiency (SE) discussed a worrying aspect of these units’ efficiency; namely, there were only 3 efficient forestry plans (Shafaroud, Nav and Fiyab). However, using the Scale Efficiency Index (SEI) or FGL-DEA model brings out some interesting points; there were approximately 58% (7 units out of 12) under Increasing Returns to Scale (IRS). Thus, the managers of forest plans should more focus on forest plans under IRS so that they have the opportunity to become more efficient through growth, otherwise managers will not be able to promote their overall productivity.   

Sweden is experiencing a demographic transition contributing to the rise in care-related costs. This study aims to evaluate whether home care is a better choice than conventional care from an economical and quality standpoint for people over the age of 65. The costs of the two care models were estimated using parametric cost estimation. The fuzzy analytic hierarchy process was used to determine which of the two care models was the most beneficial. The cost estimation implied that conventional care is less expensive than home care. However, the sensitivity analysis indicates that a minimal improvement in efficiency is sufficient enough for home care to become the least expensive option. In addition, the fuzzy analytic hierarchy process revealed that home care should be the prioritized option, even after a sensitivity analysis was conducted. Therefore, from an overall perspective, home care is the preferable care model. This paper evaluated a healthcare management problem using conventional methods, introducing new insight on how to perceive complex problems in today's healthcare environment.

BackgroundThe incidence of myocardial infarction is increasing in South Africa. Prompt treatment is indicated to reduce mortality. One way of expediting treatment is to set up regional referral recommendations that can guide prehospital providers on the best reperfusion strategy for a particular patient. A coronary care network model for patients who present with ST-elevation myocardial infarction is proposed, using the North West province, of South Africa as a case study.

MethodsGeospatial analysis with network optimisation modelling was applied, to determine which strategy (prehospital thrombolysis, in-hospital thrombolysis or percutaneous coronary intervention) was most appropriate for patients presenting within each of the municipal wards of the North West province.

ResultsAn efficient and swift recommendation for the optimal reperfusion strategy is obtained using the current model, even in the instance of a large amount of ward data with additional constraints. For most municipal wards (204, 53%) percutaneous coronary intervention is the preferred reperfusion strategy based on proximity. For the remainder of the wards prehospital (138, 36%) or in-hospital (44, 11%) thrombolysis is recommended.

ConclusionA scalable and efficient method of determining the optimal reperfusion strategy for a patient presenting with ST-elevation myocardial infarction in the North West province, is presented. This approach can serve as a model which can be applied to other settings and can form the basis of regional coronary care network development priorities and resource allocations.

The purpose of this paper is to assess the digital maturity of the manufacturing industry in a Swedish region. Data is collected using a survey conducted among the manufacturing industry in the region. Variables are based on prior research on digital maturity and Industry 4.0, and analyzed using descriptive and inferential statistical analysis. An initial finding was that several of the small organizations within the manufacturing industry does not have a basic digital presence in the form of a website, email or social media accounts, which calls for alternative approaches when assessing and developing digital maturity among these actors. The results from the survey reveal that perceived potential of digitalization and organizational enablers are ranked higher than actual operationalizations in the form of technology implementations and projects. Moreover, the digital maturity varies on variables such as organization size, location of customer base, and level of technological output. Organizations with a high degree of female employees perceive a higher digital maturity concerning some variables, which is an interesting subject for further studies. The overall conclusion is that a large part of the industrial sector in the region has not implemented anything that resemble the concept of Industry 4.0 in the literature.

We present an optimization model for the allocation of shift registers to dual ported FPGA memory blocks. Shift registers are used in real-time video processing for the storage of data flow dependencies. The model is formalized into a mixed integer linear program that can be executed using a general solver. Allocation results from realistic video systems verify the correctness of the model. This model serves as a formal specification and setup for the development of an efficient allocation heuristic.