Cultural differences and postmerger problems: Misconceptions and cognitive simplifications.

Researchers and practitioners have increasingly explained post-merger organizational problems with cultural differences, especially in the context of cross-border mergers and acquisitions. It is suggested here that cultural differences have great explanatory power in the context of post-merger change processes. There are, however, problems with a number of superficial cultural conceptions that are common in research in this area and in managerial rhetoric. This critical article provocatively delineates misconceptions widely held by researchers and practitioners in this field, which not only disregard cultural differentiation, fragmentation, inconsistencies and ambiguities, but further, illustrate a lack of understanding of cultural permeability and embeddedness in the environment, an overemphasis on abstract values and lack of attention to organizational practices, an overemphasis on initial structural differences and lack of attention to the new cultural layer, a lack of recognition of the political dimensions and a failure to recognize cultural differences as sources of value and learning. In this article, the theoretical problems associated with these misconceptions are examined and new conceptual perspectives suggested. The risks at stake for decision makers are also discussed.

On the Benefits and Problems of the Object-Oriented Paradigm including a Finnish Study

Several researchers are of the opinion that there are many benefits in using the object-oriented paradigm in information systems development. If the object-oriented paradigm is used, the development of information systems may, for example, be faster and more efficient. On the other hand, there are also several problems with the paradigm. For example, it is often considered complex, it is often difficult to make use of the reuse concept and it is still immature in some areas. Although there are several interesting features in the object-oriented paradigm, there is still little comprehensive knowledge of the benefits and problems associated with it. The objective of the following study was to investigate and to gain more understanding of the benefits and problems of the object-oriented paradigm. A review of previous studies was made and twelve benefits and twelve problems were established. These benefits and problems were then analysed, studied and discussed. Further a survey and some case studies were made in order to get some knowledge on what benefits and problems with the object-oriented paradigm Finnish software companies had experienced. One hundred and four companies answered the survey that was sent to all Finnish software companies with five or more employees. The case studies were made with six large Finnish software companies. The major finding was that Finnish software companies were exceptionally positive towards the object-oriented information systems development and had experienced very few of the proposed problems. Finally two models for further research were developed. The first model presents connections between benefits and the second between problems.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

Technology-related peso problems in stock returns

Although empirical evidence suggests the contrary, many asset pricing models assume stock returns to be symmetrically distributed. In this paper it is argued that the occurrence of negative jumps in a firm's future earnings and, consequently, in its stock price, is positively related to the level of network externalities in the firm's product market. If the ex post frequency of these negative jumps in a sample does not equal the ex ante assessed probability of occurrence, the sample is subject to a peso problem. The hypothesis is tested for by regressing the skewness coefficient of a firm’s realised stock return distribution on the firm’s R&D intensity, i.e. the ratio of the firm’s research and development expenditure to its net sales. The empirical results support the technology-related peso problem hypothesis. In samples subject to such a peso problem, the returns are biased up and the variance is biased down.

Nonlinear mixture autoregressive model: economic applications

The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.

Substance misuse problems during pregnancy with special emphasis on buprenorphine

Maternal drug abuse during pregnancy endangers the future health and wellbeing of the infant and growing child. On the other hand, via maternal abstinence, these problems would never occur; so the problems would be totally preventable. Buprenorphine is widely used in opioid maintenance treatment as a substitute medication. In Finland, during 2000 s buprenorphine misuse has steadily increased. In 2009 almost one third of clientele of substance treatment units were in treatment because of buprenorphine dependence. At Helsinki Women s Clinic the first child with prenatal buprenorphine exposure was born in 2001. During 1992-2001 in the three capital area maternity hospitals (Women s clinic, Maternity hospital, Jorvi hospital) 524 women were followed at special antenatal clinics due to substance abuse problems. Three control women were drawn from birth register to each case woman and matched for parity and same place and date of the index birth. According to register data mortality rate was 38-fold higher among cases than controls within 6-15 years after index birth. Especially, the risk for violent or accidental death was increased. The women with substance misuse problems had also elevated risk for viral hepatitis and psychiatric morbidity. They were more often reimbursed for psychopharmaceuticals. Disability pensions and rehabilitation allowances were more often granted to cases than controls. In total 626 children were born from these pregnancies. According to register data 38% of these children were placed in out-of-home care as part of child protection services by the age of two years, and half of them by the age of 12 years, the median follow-up time was 5.8 years. The risk for out-of-home care was associated with factors identifiable during the pre- and perinatal period. In 2002-2005 67 pregnant women with buprenorphine dependence were followed up at the Helsinki University Hospital, Department of Obstetrics and Gynecology. Their pregnancies were uneventful. The prematurity rate was similar and there were no more major anomalies compared to the national statistics. The neonates were lighter compared to the national statistics. They were also born in good condition, with no perinatal hypoxia as defined by standard clinical parameters or certain biochemical markers in the cord blood: erythropoietin, S100 and cardiac troponin-t. Almost 80% of newborns developed neonatal abstinence syndrome (NAS) and two third of them needed morphine medication for it. Maternal smoking over ten cigarettes per day aggravated and benzodiazepine use attenuated NAS. An infant s highest urinary norbuprenorphine concentration during their first 3 days of life correlated with the duration of morphine treatment. The average length of infant s hospital stay was 25 days.

Quantification problems in the design of forest policy programs.

XVIII IUFRO World Congress, Ljubljana 1986.

Private and municipal forests and the forestry planning system in Japan - trends and problems after World War II.

XVIII IUFRO World Congress, Ljubljana 1986.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.