955 resultados para Employee stock options


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Since the 1960s, the value relevance of accounting information has been an important topic in accounting research. The value relevance research provides evidence as to whether accounting numbers relate to corporate value in a predicted manner (Beaver, 2002). Such research is not only important for investors but also provides useful insights into accounting reporting effectiveness for standard setters and other users. Both the quality of accounting standards used and the effectiveness associated with implementing these standards are fundamental prerequisites for high value relevance (Hellstrom, 2006). However, while the literature comprehensively documents the value relevance of accounting information in developed markets, little attention has been given to emerging markets where the quality of accounting standards and their enforcement are questionable. Moreover, there is currently no known research that explores the association between level of compliance with International Financial Reporting Standards (IFRS) and the value relevance of accounting information. Motivated by the lack of research on the value relevance of accounting information in emerging markets and the unique institutional setting in Kuwait, this study has three objectives. First, it investigates the extent of compliance with IFRS with respect to firms listed on the Kuwait Stock Exchange (KSE). Second, it examines the value relevance of accounting information produced by KSE-listed firms over the 1995 to 2006 period. The third objective links the first two and explores the association between the level of compliance with IFRS and the value relevance of accounting information to market participants. Since it is among the first countries to adopt IFRS, Kuwait provides an ideal setting in which to explore these objectives. In addition, the Kuwaiti accounting environment provides an interesting regulatory context in which each KSE-listed firm is required to appoint at least two external auditors from separate auditing firms. Based on the research objectives, five research questions (RQs) are addressed. RQ1 and RQ2 aim to determine the extent to which KSE-listed firms comply with IFRS and factors contributing to variations in compliance levels. These factors include firm attributes (firm age, leverage, size, profitability, liquidity), the number of brand name (Big-4) auditing firms auditing a firm’s financial statements, and industry categorization. RQ3 and RQ4 address the value relevance of IFRS-based financial statements to investors. RQ5 addresses whether the level of compliance with IFRS contributes to the value relevance of accounting information provided to investors. Based on the potential improvement in value relevance from adopting and complying with IFRS, it is predicted that the higher the level of compliance with IFRS, the greater the value relevance of book values and earnings. The research design of the study consists of two parts. First, in accordance with prior disclosure research, the level of compliance with mandatory IFRS is examined using a disclosure index. Second, the value relevance of financial statement information, specifically, earnings and book value, is examined empirically using two valuation models: price and returns models. The combined empirical evidence that results from the application of both models provides comprehensive insights into value relevance of accounting information in an emerging market setting. Consistent with expectations, the results show the average level of compliance with IFRS mandatory disclosures for all KSE-listed firms in 2006 was 72.6 percent; thus, indicating KSE-listed firms generally did not fully comply with all requirements. Significant variations in the extent of compliance are observed among firms and across accounting standards. As predicted, older, highly leveraged, larger, and profitable KSE-listed firms are more likely to comply with IFRS required disclosures. Interestingly, significant differences in the level of compliance are observed across the three possible auditor combinations of two Big-4, two non-Big 4, and mixed audit firm types. The results for the price and returns models provide evidence that earnings and book values are significant factors in the valuation of KSE-listed firms during the 1995 to 2006 period. However, the results show that the value relevance of earnings and book values decreased significantly during that period, suggesting that investors rely less on financial statements, possibly due to the increase in the available non-financial statement sources. Notwithstanding this decline, a significant association is observed between the level of compliance with IFRS and the value relevance of earnings and book value to KSE investors. The findings make several important contributions. First, they raise concerns about the effectiveness of the regulatory body that oversees compliance with IFRS in Kuwait. Second, they challenge the effectiveness of the two-auditor requirement in promoting compliance with regulations as well as the associated cost-benefit of this requirement for firms. Third, they provide the first known empirical evidence linking the level of IFRS compliance with the value relevance of financial statement information. Finally, the findings are relevant for standard setters and for their current review of KSE regulations. In particular, they highlight the importance of establishing and maintaining adequate monitoring and enforcement mechanisms to ensure compliance with accounting standards. In addition, the finding that stricter compliance with IFRS improves the value relevance of accounting information highlights the importance of full compliance with IFRS and not just mere adoption.

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A recent decision by the Australian High Court means that, unless faculty are bound by an assignment or intellectual property (IP) policy, they may own inventions resulting from their research. Thirty years after its introduction, the US Bayh-Dole Act, which vests ownership of employee inventions in the employer university or research organization, has become a model for commercialization around the world. In Australia, despite recommendations that a Bayh-Dole style regime be adopted, the recent decision in University of Western Australia (UWA) v Gray1 has moved the default legal position in a diametrically opposite direction. A key focus of the debate was whether faculty’s duty to carry out research also encompasses a duty to invent. Late last year, the Full Federal Court confirmed a lower court ruling that it does not, and this year the High Court refused leave to appeal (denied certiorari). Thus, Gray stands as Australia’s most faculty-friendly authority to date.

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In this paper, we follow Jegadeesh and Titman's (1993, Journal of Finance) approach to examine 25 momentum/contrarian trading strategies using monthly stock returns in China for the period from 1994 to 2007. Our results suggest that there is no momentum profitability in any of the 25 strategies. In contrast, there is some evidence of reversal effects where the past winners become losers and past losers become winners afterward. The contrarian profit is statistically significant for the strategies using short formation and holding periods, especially for the formation periods of 1 to 3 months and the holding periods of 1 to 3 months. The contrarian strategies can generate about 12% per annum on average. Moreover, we follow Heston and Sadka (2008, Journal of Financial Economics) to investigate where there is any seasonal pattern in the cross-sectional variation of average stock returns in our momentum/contrarian strategies. There is no evidence of any seasonal pattern, and the results are robust to different formation and holding periods.

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Todoy's monogers-drowing on the expertise of their IT professiono/s-employee output and achieving unprecedented degrees of control of their workers. On the other hand, Australian workers reportedly spend 3.6 hours per week using the Intemet for personal reasons. Top Fortune 500 US companies have reported losing billions of dollars because of 'cyber-Ioofing'. Yet workploce surveiffonce-token to extremesmay impact negatively on perceived levels of trust within the organisation, cantribute to employees' increased stress and decreased job dissatisfaction, and affect productivity. Highlighted are current trends in workplace privacy, key communication and control issues, the current legal climate, and ethical issues that communication professionals need to address to forestall future problems. lA questionnaire is included as a starting point for communication professionals to assess their own attitudes and values to workplace surveillance.

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Pragmatic construction professionals, accustomed to intense price competition and focused on the bottom line, have difficulty justifying investments in advanced technology. Researchers and industry professionals need improved tools to analyze how technology affects the performance of the firm. This paper reports the results of research to begin answering the question, “does technology matter?” The researchers developed a set of five dimensions for technology strategy, collected information regarding these dimensions along with four measures of competitive performance in five bridge construction firms, and analyzed the information to identify relationships between technology strategy and competitive performance. Three technology strategy dimensions—competitive positioning, depth of technology strategy, and organizational fit—showed particularly strong correlations with the competitive performance indicators of absolute growth in contract awards and contract award value per technical employee. These findings indicate that technology does matter. The research also provides ways to analyze options for approaching technology and ways to relate technology to competitive performance for use by managers. It also provides a valuable set of research measures for technology strategy.

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Nonprofit organizations are not exempt from the imperatives of employee attraction, retention, and motivation. As competition for staff, donors, and funding increases, the need to manage employee performance will continue to be a critical human resource management issue. This article outlines a study of the introduction of a performance management system in an Australian nonprofit organization and analyzes its design and implementation. It explores how performance management can be introduced and used effectively within a nonprofit environment to benefit staff and the organization. However, the use of performance management is not without its challenges, and the research also identified initial employee resistance and a resulting initial spike in labor turnover. However, findings indicate that if nonprofit organizations are willing to undertake consultation with staff and ensure that the organization's specific context, values, and mission are reflected in the performance management system, it can be a useful tool for managers and a direct benefit to employees.

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Genetic variation is the resource animal breeders exploit in stock improvement programs. Both the process of selection and husbandry practices employed in aquaculture will erode genetic variation levels overtime, hence the critical resource can be lost and this may compromise future genetic gains in breeding programs. The amount of genetic variation in five lines of Sydney Rock Oyster (SRO) that had been selected for QX (Queensland unknown) disease resistance were examined and compared with that in a wild reference population using seven specific SRO microsatellite loci. The five selected lines had significantly lower levels of genetic diversity than did the wild reference population with allelic diversity declining approximately 80%, but impacts on heterozygosity per locus were less severe. Significant deficiencies in heterozygotes were detected at six of the seven loci in both mass selected lines and the wild reference population. Against this trend however, a significant excess of heterozygotes was recorded at three loci Sgo9, Sgo14 and Sgo21 in three QX disease resistant lines (#2, #5 and #13). All populations were significantly genetic differentiated from each other based on pairwise FST values. A neighbour joining tree based on DA genetic distances showed a clear separation between all culture and wild populations. Results of this study show clearly, that the impacts of the stock improvement program for SRO has significantly eroded natural levels of genetic variation in the culture lines. This could compromise long-term genetic gains and affect sustainability of the SRO breeding program over the long-term.

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Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.