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This work investigates a regional hospital, which has an affiliated low-acuity emergency department (ED) facility that currently struggles to meet its service level goal (85% of its patients should be in the room in 60 minutes or less). A capability analysis using data from existing processes at this facility revealed that with the current processes and current level of resources, the facility is not capable of meeting existing service level goal. A simulation was developed to examine multiple alternatives that could improve patient flow at the facility. A set of scenarios were created that modified one or more of the resources such as doctors, nurses, and rooms by changing their schedules or their quantities. The impact of the response variables related to the facility’s service level goal was recorded for each scenario. Based on the results of the simulation, recommendations to the facility for alternative ways to schedule and allocate its resources in order to meet its current service level goal were given.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

A majority of products for manufacturing or consumers have multiple characteristics that must meet the requirements of the customer. For example, a steel beam any have dimensional tolerances on its length, width, or height and functional tolerances on its strength. The characteristics are influenced by different processes that create the product. For an individual characteristic, process capability measures exist that convey the degree to which the characteristic meets the specification requirements. Such measures may indicate the proportion of nonconforming product related to the particular characteristic, under some distributional assumptions of the characteristic. For products with multiple characteristics, the unit costs of rectification may be different, making the satisfaction of some characteristics meeting customer requirements more important than others. In this paper, an aggregate process capability performance measure is developed that considers the relative importance of the characteristic based on unit costs of nonconformance. Based on the aggregate measure, appropriate process capability measures for the individual measures are also derived. Bounds on the aggregate capability measures are also established.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

Strategic management research has shown growing interest in understanding the dynamic resource reconfiguration processes through which firms grow, evolve, and sustain profitability. The goal of our study is to understand how dynamic resource reconfigurations enable firms to pursue growth opportunities. We use the methods of inductive theory building from case studies to elaborate current theoretical understanding about how firms draw on both internal and external resources in the pursuit of growth. We examine the patterns of resource reconfigurations through which Yahoo and Google powered their early growth strategies in their first 10 years of existence. We analyze a total of 192 new product launches in 43 markets by the two firms to capture how they reconfigured resources dynamically. Our analysis reveals that both firms developed highly dynamic strategies exhibiting both surprising similarities and differences. These similarities and differences provided the basis for our theoretical insights about the development of what we term “dynamic resource platforms,” comprising of (a) dynamic resource shifts; (b) targeted resource orchestration; and (c) complementary processes balancing dynamism and capability development. These ideas contribute novel theoretical insights to current strategic management research on dynamic capabilities and on resource reconfiguration and redeployment.

Purpose – The purpose of this paper is to discuss the possible relationship between conditions of national development, as measured by human development indicators (HDIs), and the segmented assimilation of Hispanics in Washington, DC.

Methodology/approach – To discuss the association between these two variables, I identified five indicators of assimilation discussed in the literature and matched them against the United Nations Development Program's (UNDP) ranking of nations according to their HDI composite index. In addition, I selected eight Hispanic groups’ representatives of the three tiers by which nations are ranked in the Human Development Report published by the UNDP.

Findings – My results show that conditions of national development impact immigrant assimilation, at least in the first generation.

Research limitations/implications – Due to the sample size and the peculiar conditions of Washington, DC, the findings presented require further testing.

Originality/value of paper – Despite these limitations, the findings make a significant contribution to the migration literature by taking into account how stock of knowledge contributes to the different rates of assimilation among immigrants with shared ethnicity.