932 resultados para Proverbs, Swedish.
Resumo:
Critical organization scholars have focused increasing attention on industrial and organizational restructurings such as shutdown decisions. However, we know little about the rhetorical strategies used to legitimate or resist plant closures in organizational negotiations. In this paper, we draw from New Rhetoric to analyze rhetorical struggles, strategies and dynamics in unfolding organizational negotiations. We focus on the shutdown of the bus body unit of the Swedish company Volvo in Finland. We distinguish five types of rhetorical legitimation strategies and dynamics. These include the three classical dynamics of logos (rational arguments), pathos (emotional moral arguments), and ethos (authority-based arguments), but also autopoiesis (autopoietic narratives), and cosmos (cosmological constructions). Our analysis adds to the previous studies explaining how organizational restructuring as a phenomenon is legitimated, how this legitimation has changed over time, and how contemporary industrial closures are legitimated in the media. This study also increases our theoretical understanding of the role of rhetoric in legitimation more generally.
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We argue in this paper that corporate language policies have significant power implications that are easily overlooked. By drawing on previous work on power in organizations (Clegg, 1989), we examine the complex power implications of language policy decisions by looking at three levels of analysis: episodic social interaction, identity/subjectivity construction, and reconstruction of structures of domination. In our empirical analysis, we focus on the power implications of the choice of Swedish as the corporate language in the case of the recent banking sector merger between the Finnish Merita and the Swedish Nordbanken. Our findings show how language skills become empowering or disempowering resources in organizational communication, how these skills are associated with professional competence, and how this leads to the creation of new social networks. The case also illustrates how language skills are an essential element in the construction of international confrontation, lead to a construction of superiority and inferiority, and also reproduce post-colonial identities in the merging bank. Finally, we also point out how such policies ultimately lead to the reification of post-colonial and neo-colonial structures of domination in multinational corporations.
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This conceptual paper examines bicultural interactions in organizations as they are experienced by the involved individuals. Notions from Bakhtinian dialogism are used in order to conceptualize the sensemaking opportunities provided by the encounter with a cultural otherness. It is argued that in such bicultural situations, because of the lack of intimate understanding of the other culture, the third element in the dialogic relation - ‘thirdness’, i.e. the relation itself, without which there would be no sensemaking potential - may be lacking as a result of the distorting combination of projected similarity and stereotyping, added to certain counterproductive organizational dynamics. Therefore, it is suggested that, to make the bicultural work interaction the rewarding relation it could be, thirdness should be coordinated by management in a way that can transcend the spontaneous negative dynamics of the confrontational situation. If management was to fail to organize (with) thirdness appropriately, bringing in a third party could be a possible alternative in order to initiate the necessary mutual understanding that should eventually lead to a fruitful work interaction.
Resumo:
Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.
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As companies become more efficient with respect to their internal processes, they begin to shift the focus beyond their corporate boundaries. Thus, the recent years have witnessed an increased interest by practitioners and researchers in interorganizational collaboration, which promises better firm performance through more effective supply chain management. It is no coincidence that this interest comes in parallel with the recent advancements in Information and Communication Technologies, which offer many new collaboration possibilities for companies. However, collaboration, or any other type of supply chain integration effort, relies heavily on information sharing. Hence, this study focuses on information sharing, in particular on the factors that determine it and on its value. The empirical evidence from Finnish and Swedish companies suggests that uncertainty (both demand and environmental) and dependency in terms of switching costs and asset specific investments are significant determinants of information sharing. Results also indicate that information sharing improves company performance regarding resource usage, output, and flexibility. However, companies share information more intensely at the operational rather than the strategic level. The use of supply chain practices and technologies is substantial but varies across the two countries. This study sheds light on a common trend in supply chains today. Whereas the results confirm the value of information sharing, the contingent factors help to explain why the intensity of information shared across companies differ. In the future, competitive pressures and uncertainty are likely to intensify. Therefore, companies may want to continue with their integration efforts by focusing on the determinants discussed in this study. However, at the same time, the possibility of opportunistic behavior by the exchange partner cannot be disregarded.
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There is much literature developing theories when and where earnings management occurs. Among the several possible motives driving earnings management behaviour in firms, this thesis focuses on motives that aim to influence the valuation of the firm. Earnings management that makes the firm look better than it really is may result in disappointment for the single investor and potentially leads to a welfare loss in society when the resource allocation is distorted. A more specific knowledge of the occurrence of earnings management supposedly increases the awareness of the investor and thus leads to better investments and increased welfare. This thesis contributes to the literature by increasing the knowledge as to where and when earnings management is likely to occur. More specifically, essay 1 adds to existing research connecting earnings management to IPOs and increases the knowledge in arguing that the tendency to manage earnings differs between the IPOs. Evidence is found that entrepreneur owned IPOs are more likely to be earnings managers than the institutionally owned ones. Essay 2 considers the reliability of quarterly earnings reports that precedes insider selling binges. The essay contributes by suggesting that earnings management is likely to occur before high insider selling. Essay 3 examines the widely studied phenomenon of income smoothing and investigates if income smoothing can be explained with proxies for information asymmetry. The essay argues that smoothing is more pervasive in private and smaller firms.
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ERP system implementations have evolved so rapidly that now they represent a must-have within industries. ERP systems are viewed as the cost of doing business. Yet, the research that adopted the resource-based view on the business value of ERP systems concludes that companies may gain competitive advantage when they successfully manage their ERP projects, when they carefully reengineer the organization and when they use the system in line with the organizational strategies. This thesis contributes to the literature on ERP business value by examining key drivers of ERP business value in organizations. The first research paper investigates how ERP systems with different degrees of system functionality are correlated with the development of the business performance after the completion of the ERP projects. The companies with a better perceived system functionality obtained efficiency benefits in the first two years of post-implementation. However, in the third year there is no significant difference in efficiency benefits between successfully and less successfully managed ERP projects. The second research paper examines what business process changes occur in companies implementing ERP for different motivations and how these changes impact the business performance. The findings show that companies reported process changes mainly in terms of workflow changes. In addition, the companies having a business-led motivation focused more on observing average costs of each increase in the input unit. Companies having a technological-led motivation focused more on the benefits coming from the fit of the system with the organizational processes. The third research paper considers the role of alignment between ERP and business strategies for the realization of business value from ERP use. These findings show that strategic alignment and business process changes are significantly correlated with the perceived benefits of ERP at three levels: internal efficiency, customers and financial. Overall, by combining quantitative and qualitative research methods, this thesis puts forward a model that illustrates how successfully managed ERP projects, aligned with the business strategy, have automate and informate effects on processes that ultimately improve the customer service and reduce the companies’ costs.
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Service researchers and practitioners have repeatedly claimed that customer service experiences are essential to all businesses. Therefore comprehension of how service experience is characterised in research is an essential element for its further development through research. The importance of greater in-depth understanding of the phenomenon of service experience has been acknowledged by several researchers, such as Carú and Cova and Vargo and Lusch. Furthermore, Service-Dominant (S-D) logic has integrated service experience to value by emphasising in its foundational premises that value is phenomenologically (experientially) determined. The present study analyses how the concept of service experience has been characterised in previous research. As such, it puts forward three ways to characterise it in relation to that research: 1) phenomenological service experience relates to the value discussion in S-D logic and interpretative consumer research, 2) process-based service experience relates to understanding service as a process, and 3) outcome-based service experience relates to understanding service experience as one element in models linking a number of variables or attributes to various outcomes. Focusing on the phenomenological service experience, the theoretical purpose of the study is to characterise service experience based on the phenomenological approach. In order to do so, an additional methodological purpose was formulated: to find a suitable methodology for analysing service experience based on the phenomenological approach. The study relates phenomenology to a philosophical Husserlian and social constructionist tradition studying phenomena as they appear in our experience in a social context. The study introduces Event-Based Narrative Inquiry Technique (EBNIT), which combines critical events with narratives and metaphors. EBNIT enabled the analysis of lived and imaginary service experiences as expressed in individual narratives. The study presents findings of eight case studies within service innovation of Web 2.0, mobile service, location aware service and public service in the municipal sector. Customers’ and service managers’ stories about their lived private and working lifeworld were the foundation for their ideal service experiences. In general, the thesis finds that service experiences are (1) subjective, (2) context-specific, (3) cumulative, (4) partially socially constructed, (5) both lived and imaginary, (6) temporally multiple-dimensional, and (7) iteratively related to perceived value. In addition to customer service experience, the thesis brings empirical evidence of managerial service experience of front-line managers experiencing the service they manage and develop in their working lifeworld. The study contributes to S-D logic, service innovation and service marketing and management in general by characterising service experience based on the phenomenological approach and integrating it to the value discussion. Additionally, the study offers a methodological approach for further exploration of service experiences. The study discusses managerial implications in conjunction with the case studies and discusses them in relation to service innovation.
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This thesis analyzes how matching takes place at the Finnish labor market from three different angles. The Finnish labor market has undergone severe structural changes following the economic crisis in the early 1990s. The labor market has had problems adjusting from these changes and hence a high and persistent unemployment has followed. In this thesis I analyze if matching problems, and in particular if changes in matching, can explain some of this persistence. The thesis consists of three essays. In the first essay Finnish Evidence of Changes in the Labor Market Matching Process the matching process at the Finnish labor market is analyzed. The key finding is that the matching process has changed thoroughly between the booming 1980s and the post-crisis period. The importance of the number of unemployed, and in particular long-term unemployed, for the matching process has vanished. More unemployed do not increase matching as theory predicts but rather the opposite. In the second essay, The Aggregate Matching Function and Directed Search -Finnish Evidence, stock-flow matching as a potential micro foundation of the aggregate matching function is studied. In the essay I show that newly unemployed match mainly with the stock of vacancies while longer term unemployed match with the inflow of vacancies. When aggregating I still find evidence of the traditional aggregate matching function. This could explain the huge support the aggregate matching function has received despite its odd randomness assumption. The third essay, How do Registered Job Seekers really match? -Finnish occupational level Evidence, studies matching for nine occupational groups and finds that very different matching problems exist for different occupations. In this essay also misspecification stemming from non-corresponding variables is dealt with through the introduction of a completely new set of variables. The new outflow measure used is vacancies filled with registered job seekers and it is matched by the supply side measure registered job seekers.
Resumo:
Functioning capital markets are a crucial part of a competitive economy since they provide the mechanisms to allocate resources. In order to be well functioning a capital market has to be efficient. Market efficiency is defined as a market where prices at any time fully reflect all available information. Basically, this means that abnormal returns cannot be predicted since they are dependent on future, presently unknown, information. The debate of market efficiency has been going on for several decades. Most academics today would probably agree that financial markets are reasonably efficient since virtually nobody has been able to achieve continuous abnormal positive returns. However, it is clear that a set of return anomalies exists, although they are apparently to small to enable substantial economic profit. Moreover, these anomalies can often be attributed to market design. The motivation for this work is to expand the knowledge of short-term trading patterns and to offer some explanations for these patterns. In the first essay the return pattern during the day is examined. On average stock prices move during two time periods of the day, namely, immediately after the opening and around the formal close of the market. Since stock prices, on average, move upwards these abnormal returns are generally positive and cause the distinct U-shape of intraday returns. In the second essay the results in the first essay are examined further. The return pattern around the former close is shown to partly be the result of manipulative action by market participants. In the third essay the focus is shifted towards trading patterns of the underlying stocks on days when index options and index futures on the stocks expire. Generally no expiration day effect was found. However, some indication of an expiration day effect was found when a large amount of open in- or at-the-money contracts existed. Also, the effects were likelier to be found for shares with high index-weight but fairly low trading volume. Last, in the forth essay the attention is turned to the behaviour of different tax clienteles around the dividend ex-day. Two groups of investors showed abnormal trading behaviour. Domestic non-financial investors, especially domestic companies, showed a dividend capturing behaviour, i.e. buying cum-dividend and selling ex-dividend shares. The opposite behaviour was found for foreign investors and domestic financial institutions. The effect was more notable for high yield, high volume stocks.
Resumo:
Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.
Resumo:
Market microstructure is “the study of the trading mechanisms used for financial securities” (Hasbrouck (2007)). It seeks to understand the sources of value and reasons for trade, in a setting with different types of traders, and different private and public information sets. The actual mechanisms of trade are a continually changing object of study. These include continuous markets, auctions, limit order books, dealer markets, or combinations of these operating as a hybrid market. Microstructure also has to allow for the possibility of multiple prices. At any given time an investor may be faced with a multitude of different prices, depending on whether he or she is buying or selling, the quantity he or she wishes to trade, and the required speed for the trade. The price may also depend on the relationship that the trader has with potential counterparties. In this research, I touch upon all of the above issues. I do this by studying three specific areas, all of which have both practical and policy implications. First, I study the role of information in trading and pricing securities in markets with a heterogeneous population of traders, some of whom are informed and some not, and who trade for different private or public reasons. Second, I study the price discovery of stocks in a setting where they are simultaneously traded in more than one market. Third, I make a contribution to the ongoing discussion about market design, i.e. the question of which trading systems and ways of organizing trading are most efficient. A common characteristic throughout my thesis is the use of high frequency datasets, i.e. tick data. These datasets include all trades and quotes in a given security, rather than just the daily closing prices, as in traditional asset pricing literature. This thesis consists of four separate essays. In the first essay I study price discovery for European companies cross-listed in the United States. I also study explanatory variables for differences in price discovery. In my second essay I contribute to earlier research on two issues of broad interest in market microstructure: market transparency and informed trading. I examine the effects of a change to an anonymous market at the OMX Helsinki Stock Exchange. I broaden my focus slightly in the third essay, to include releases of macroeconomic data in the United States. I analyze the effect of these releases on European cross-listed stocks. The fourth and last essay examines the uses of standard methodologies of price discovery analysis in a novel way. Specifically, I study price discovery within one market, between local and foreign traders.
Resumo:
Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.
Resumo:
The purpose of this thesis is to examine the role of trade durations in price discovery. The motivation to use trade durations in the study of price discovery is that durations are robust to many microstructure effects that introduce a bias in the measurement of returns volatility. Another motivation to use trade durations in the study of price discovery is that it is difficult to think of economic variables, which really are useful in the determination of the source of volatility at arbitrarily high frequencies. The dissertation contains three essays. In the first essay, the role of trade durations in price discovery is examined with respect to the volatility pattern of stock returns. The theory on volatility is associated with the theory on the information content of trade, dear to the market microstructure theory. The first essay documents that the volatility per transaction is related to the intensity of trade, and a strong relationship between the stochastic process of trade durations and trading variables. In the second essay, the role of trade durations in price discovery is examined with respect to the quantification of risk due to a trading volume of a certain size. The theory on volume is intrinsically associated with the stock volatility pattern. The essay documents that volatility increases, in general, when traders choose to trade with large transactions. In the third essay, the role of trade durations in price discovery is examined with respect to the information content of a trade. The theory on the information content of a trade is associated with the theory on the rate of price revisions in the market. The essay documents that short durations are associated with information. Thus, traders are compensated for responding quickly to information