This paper studies the home-country determinants of outward FDI with a focus on nine empirically recognized host-country determinants of inward FDI, namely market size, labor cost, exchange rate, inflation, interest rate, political risks, corruption, openness, and technology. Based on a panel with 183 observations from BRICS and five developed countries (Australia, Germany, Japan, UK, US), evidence is found that market size, inflation, interest rate, political risks, and openness have significant influence on FDI outflows. Moreover, the results of this study show that there are striking differences between developing and developed countries regarding to the drivers for outward FDI.

I dagens föränderliga värld står SME ofta inför en mängd varierande utmaningar, där det krävs en rad olika strategier och lösningar för att lyckas navigera igenom de utmaningarna som företagen ställs inför. En av de händelser som ofta förknippas med stora och komplexa utmaningar är tiden av hög tillväxt. Tillväxt skiljer sig mellan företag men även på individnivå och behöver mer teoretiskt stöd för att minska riskerna som är associerade med tillväxt. Det är av stor vikt att växa som företag, då det minskar riskerna och/eller är ett sätt att skydda sig mot exempelvis ökade kostnader för råvaror, konkurrens, konjunkturförändringar eller brister på kompetens. Tillväxt ska inte enbart förknippas med framgång utan medför även risker då dålig hantering annars kan leda till minskat förtroende, personalomsättning eller i värsta fall konkurs för företag. En stor del av att lyckas med hög tillväxt är kopplat till kompetenshantering och finansiellt kapital och beroende på hur bra företagen är på att effektivt arbeta med dessa faktorer kan vara skillnaden mellan en lyckad och en misslyckad tillväxt. Hur hanterar företagsledningen i SME balansen mellan att attrahera och behålla kompetens på ett finansiellt hållbart sätt under perioder av hög organisk tillväxt? Syftet med denna studie är att utvärdera hanteringen av kompetens inom företag som genomgått hög tillväxt, med särskilt fokus på att attrahera och behålla kompetens och personalkostnader. Där målet med studien är att bidra med praktiska rekommendationer på effektiva strategier till företagsledare som står inför eller är i en period av hög tillväxt. För att ta reda på dessa strategier kommer studien genom ett deduktivt angreppssätt identifiera huvudteman utifrån redan befintlig forskning och teori. Teorigenerade teman kommer sedan att undersökas genom en kvalitativ undersökning med semistrukturerade intervjuer. Respondenterna i studien är företagsledare inom den kunskapsintensiva branscherna som är verksamma i företag som har haft en eller flera perioder av hög tillväxt. Slutsatsen av undersökningen var att det skiljer sig en del från vad tidigare teorier säger och hur företagslandskapet är idag där attraktionsvärdet hos företaget tidigare har fokuserat på lönenivåer som nu har bytts ut mot vikten av företagskultur och utvecklingsmöjligheter i samband med att kompetenskraven ökar i takt med teknikens framgång.

當投資環境發生變化時, 某些企業便會出現移動現象, 尤其受到全球整體經濟不景氣的影響下, 企業營運的快速因應更是重要。 中國自1979年鄧小平推動改革開放，歷經將近40年的發展，中國藉由低廉的勞動人力帶動經濟高度成長，吸引了全球各國目光，紛紛到中國投資。隨著中國勞動力成本的優勢不再，整體營運成本上升，政府要求企業產業轉型升級等，對台商在經營上產生很大的影響。而許多資料也指出，在面臨中國整體運營成本上升時，不少台商選擇到具備低廉勞動力成本和人口紅利優勢的東南亞國家進行投資設廠。 本研究結合企業成長理論、資源基礎理論，並配合區位選擇理論和生產力工資理論，探討台商在大陸經營成長過程中，面對中國投資環境改變，對於區位選擇的策略影響。期望藉由本研究提供未來台商在區位選擇上的參考。透過個案公司的深入訪談，本研究發現台灣中小企業受限於企業規模及營運資金規模，加上大環境是連動、相互影響的複雜動態系統，許多決策是多面向且多變的，因此台商在思考區位選擇時，除了首重關注勞動成本，也需考量目標市場及產業特性和其他因素的影響。 / When the investment environment changes, some enterprises will experience a transformational phenomenon, especially in recent years, with the global financial crisis, and the global economic downturn. It is more important than ever that business operations rapidly change in response to such influences. After nearly 40 years of development in China, since Deng Xiaoping promoted an economic revolution in order to help the economy in 1979, now China becomes the second largest economy in the world. During this period, the high economic growth in China was driven by low labor force and attracted the attention from all of the world and started to invest. After the advantage of labor cost gradually disappear, the overall operation cost increase, and the government asked the transformation and upgrading for enterprises, these factors brought a large burden on business operation. And many information also pointed out that many Taiwanese Small and Medium Enterprises choose to invest and relocate the factory in Southeast Asian countries which have cheaper labor force and demographic dividend advantage when they face the constrains in China. This study uses business growth, resource-based, location select and productivity wage as theoretical approach to discuss Taiwanese Small and Medium Enterprises growth process in China, the impact of location select strategy when their face the investment environment changes in China. It is expected that this study will provide a reference for further Taiwanese enterprises in terms of location selection. Through in-depth interview with case companies, this study found that Taiwanese Small and Medium enterprises are limited by the size of enterprise itself and the scale of operation capital, in addition, the environment is the complex dynamic system with linkage, complex and interaction. Many decisions ought to be made by cogitating in the short term and long term, in addition, the labor cost is the priority when Taiwanese enterprises select the location, but also consider the target market, industrial characteristics and other factors.

The main point of my thesis is a complete analysis of the performance of human capital, which can be found in the practical part of the thesis. Synthesis of results and recommendations are summarized in the penultimate chapter. The company innovated the measurement of the performance of its employees in 2010 through the introduction of a new monitoring system Citect SCADA which gives the employee evaluation new dimension, which enabled to increase productivity and reduce labor expenses.

This thesis is organized into two parts, one for my main area of research in the field of stochastic games, and the other for my contributions in the area of service systems. We first provide an abstract for my work in stochastic games. The field of stochastic games has been actively pursued over the last seven decades because of several of its important applications in oligopolistic economics. In the past, zero-sum stochastic games have been modelled and solved for Nash equilibria using the standard techniques of Markov decision processes. General-sum stochastic games on the contrary have posed difficulty as they cannot be reduced to Markov decision processes. Over the past few decades the quest for algorithms to compute Nash equilibria in general-sum stochastic games has intensified and several important algorithms such as stochastic tracing procedure [Herings and Peeters, 2004], NashQ [Hu and Wellman, 2003], FFQ [Littman, 2001], etc., and their generalised representations such as the optimization problem formulations for various reward structures [Filar and Vrieze, 1997] have been proposed. However, they suffer from either lack of generality or are intractable for even medium sized problems or both. In our venture towards algorithms for stochastic games, we start with a non-linear optimization problem and then design a simple gradient descent procedure for the same. Though this procedure gives the Nash equilibrium for a sample problem of terrain exploration, we observe that, in general, it need not be true. We characterize the necessary conditions and define KKT-N point. KKT-N points are those Karush-Kuhn-Tucker (KKT) points which corresponding to Nash equilibria. Thus, for a simple gradient based algorithm to guarantee convergence to Nash equilibrium, all KKT points of the optimization problem need to be KKT-N points, which restricts the applicability of such algorithms. We then take a step back and start looking at better characterization of those points of the optimization problem which correspond to Nash equilibria of the underlying game. As a result of this exploration, we derive two sets of necessary and sufficient conditions. The first set, KKT-SP conditions, is inspired from KKT conditions itself and is obtained by breaking down the main optimization problem into several sub-problems and then applying KKT conditions to each one of those sub-problems. The second set, SG-SP conditions, is a simplified set of conditions which characterize those Nash points more compactly. Using both KKT-SP and SG-SP conditions, we propose three algorithms, OFF-SGSP, ON-SGSP and DON-SGSP, respectively, which we show provide Nash equilibrium strategies for general-sum discounted stochastic games. Here OFF-SGSP is an off-line algorithm while ONSGSP and DON-SGSP are on-line algorithms. In particular, we believe that DON-SGSP is the first decentralized on-line algorithm for general-sum discounted stochastic games. We show that both our on-line algorithms are computationally efficient. In fact, we show that DON-SGSP is not only applicable for multi-agent scenarios but is also directly applicable for the single-agent case, i.e., MDPs (Markov Decision Processes). The second part of the thesis focuses on formulating and solving the problem of minimizing the labour-cost in service systems. We define the setting of service systems and then model the labour-cost problem as a constrained discrete parameter Markov-cost process. This Markov process is parametrized by the number of workers in various shifts and with various skill levels. With the number of workers as optimization variables, we provide a detailed formulation of a constrained optimization problem where the objective is the expected long-run averages of the single-stage labour-costs, and the main set of constraints are the expected long-run average of aggregate SLAs (Service Level Agreements). For this constrained optimization problem, we provide two stochastic optimization algorithms, SASOC-SF-N and SASOC-SF-C, which use smoothed functional approaches to estimate gradient and perform gradient descent in the aforementioned constrained optimization problem. SASOC-SF-N uses Gaussian distribution for smoothing while SASOC-SF-C uses Cauchy distribution for the same. SASOC-SF-C is the first Cauchy based smoothing algorithm which requires a fixed number (two) of simulations independent of the number of optimization variables. We show that these algorithms provide an order of magnitude better performance than existing industrial standard tool, OptQuest. We also show that SASOC-SF-C gives overall better performance.