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This study examines the impact of FASB Interpretation No. 48 (FIN48), Accounting for Uncertainty in Income Taxes, on earnings management (EM) activity, by focusing on changes in the deferred tax asset valuation allowance (DTVA). FIN48 was adopted, in part, over concerns that firms were using the reserve for uncertain tax positions (cushion) to manage earnings. However, there are reasons to believe that the adoption of FIN48 may have impacted the extent to which firms utilize DTVA changes as a strategic accounting choice. As the provision for income taxes is one of the final accounts closed prior to an earnings announcement, income tax accounting is generally regarded as a final opportunity to strategically meet earnings goals. To the extent that FIN48 reduced cushion-based EM, firms may have increasingly used DTVA changes as a substitute. Alternatively, the attention that FIN48 brought to firms’ income tax footnotes may have curbed the strategic use of income tax accounting, in general. This study employs a sample of publicly traded US firms over the period of 2003–2010. A regression model and an analysis of the frequency of DTVA-based EM reveal no evidence of a systematic change in behavior attributable to FIN48. However, further analysis reveals that firms identified as managing earnings to meet analyst forecasts increasingly used discretionary DTVA changes relative to changes in tax cushion in the post-FIN48 period. The results have implications for existing research on income tax-based EM.

Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved.

The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency.

A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled.

Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.

Social media has fundamentally changed the leisure travel behavior of Singapore residents. The purpose of this paper is to focus on Facebook and its impact on travel behavior. The study focuses on Singapore residents.

A total of 16 input and five output variables were tested, with a sample of 203 Facebook users residing in Singapore. Primary data modeling was done using ADANCO, a structural equation modeling tool that uses composite modeling approach for hypothesis testing. The analysis performed an estimated structural model and then determined the best model fit by measuring reliability, validity and path analysis and estimating model parameters.

Research findings indicate that Facebook has had a strong behavioral influence on the frequency of travel, itinerary planning and social sharing, while it had no impact during the destination-selection stage of travel planning.

Facebook’s influence on leisure travel behavior confirms the theory of planned behavior proposed by Icek Ajzen. From Facebook’s perspective, the outcome of this study is helpful in recommending the best use of the platform for destination providers.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

This paper aims to analyze and model consumer behavior on hotel online search interest in the USA.

Discrete Fourier transform was used to analyze the periodicity of hotel search behavior in the USA by using Google Trends data. Based on the obtained frequency components, a model structure was proposed to describe the search interest. A separable nonlinear least squares algorithm was developed to fit the data.

It was found that the major dynamics of the search interest was composed of nine frequency components. The developed separable nonlinear least squares algorithm significantly reduced the number of model parameters that needed to be estimated. The fitting results indicated that the model structure could fit the data well (average error 0.575 per cent).

Knowledge of consumer behavior on online search is critical to marketing decision because search engine has become an important tool for customers to find hotels. This work is thus very useful to marketing strategy.

This research is the first work on analyzing and modeling consumer behavior on hotel online search interest.

The purpose of this paper is to study the impact of government supervision and market environment on farmers' pesticide application behavior, as well as the intermediary effect of farmers' literacy, and investigate the substitution effect between government supervision and market environment.

In this paper, logit and Poisson regression models were used to investigate the comprehensive impact of government supervision and market environment on farmers' pesticide application behavior, and the intermediary effect model is used to examine the intermediary effect of farmers' literacy.

Government supervision is an important constraint for the formation of individual behavior paradigm, but it has both positive and negative effects, depending on different instruments. The market subject constraint and market incentive are two important ways that the market environment affects Chinese farmers' pesticide application behavior. Farmers' literacy plays a partial mediating role in the influencing mechanism of government and market factors. The government supervision and market environment, two different constraint forces, have substitution effects in the process of regulating farmers' pesticide application behavior.

In the influence mechanism, farmers' literacy, such as values, responsibilities and skill requirement related to scientific pesticide use, was included into the analysis framework as intermediary variables. The authors found that government supervision and market environment not only directly affect farmers' pesticide application behavior but also indirectly affect farmers' pesticide application behavior through farmers' literacy.

Challenging behaviours are defined in part by the risks of harm they present and the support of individuals who challenge would be improved with effective assessments of the risks posed by challenging behaviours. The purpose of this paper is to outline a model of risk assessment and review literature that provides relevant information.

Literature review.

Forensic risk assessment has a well worked-out and validated approach but tools used to assess challenging behaviours are not effective risk predictors. Applied Behaviour Assessment provides methods that can be more effectively used for risk assessment.

There is a need to develop valid risk assessment procedures for assessing the risks presented by challenging behaviours.

This is a fresh perspective on risk assessment in relation to challenging behaviours.

The purpose of this paper is to present a methodology for estimating scheduled and manual override heating events and heating settings from indoor air temperature and gas use measurements in UK homes.

Living room air temperature and gas use data were measured in ten UK homes built to low energy standards. The temperature measurements are used to establish whether the central heating system is turned on or off and to estimate the heating setpoint used. The estimated heating periods are verified using the homes' average daily gas consumption profiles.

Using this method, the average number of heating periods per day was 2.2 (SD = 0.8) on weekdays and 2.7 (SD = 0.5) on weekends. The weekday mean heating duration was 8.8 h and for weekends, it was 9.8 h. Manual overrides of the settings occurred in all the dwellings and added an average of 2.4 h and 1.5 h to the heating duration on weekdays and weekends respectively. The mean estimated setpoint temperatures were 21.2 and 21.4°C on weekdays and weekends respectively.

Manual overrides of heating behaviours have only previously been assessed by questionnaire survey. This paper demonstrates an alternative method to identifying these manual override events and responds to a key gap in the current body of research that little is currently reported on the frequency and duration of manual heating overrides in UK homes.

The results could be used to better inform the assumptions of space heating behaviour used in energy models in order to more accurately predict the space heating energy demands of dwellings.

Manual overrides of heating behaviours have only previously been assessed by questionnaire survey. This paper demonstrates an alternative method to identifying these manual override events and responds to a key gap in the current body of research that little is currently reported on the frequency and duration of manual heating overrides in UK homes.

The purpose of this paper is to initially use a stochastic model to fit data of customer behavior stickiness and customer value, then estimate the corresponding parameters and use Bayesian rule to calculate its mathematical expectation.

The authors use expectations of customer behavior stickiness as an independent variable, expectations of customer value as a dependent variable, motivations of consumption as moderator and conduct regression analysis to research the relationship among the three. First, we will use the data of behavior for customer network shopping in the questionnaire to establish the random probability model and forecast. Second, we calculate the expected customer behavior stickiness and customer value. Finally, we use resurvey data of 100 subjects after three months (selected randomly from 373 objects) to test the model prediction.

The findings show that customer behavior stickiness has a significant effect on customer value, and the moderating effect of the hedonic motivation of consumption on the relationship above is proved. The value of customers who hold high hedonic motivation of consumption is mainly driven from website’s single visit time, whereas the value of customers who hold low or middle hedonic motivation of consumption is mainly driven from a website’s visit frequency.

The paper proves and quantifies the effects of the customer behavior stickiness for customer value in times of behavior. The results prove the moderation role of consumer motivation of the customer for the path of customer behavior stickiness→customer value, and make clear that the hedonic motivation is a necessary condition of average site visit time that has a significant impact on customer value.

Cluster analysis is applied to the union and employer tactics used in a sample of Ontario organising campaigns to identify the combinations of tactics or strategies that are used most often. Seven union organising strategies and five employer resistance strategies are revealed. Contingency table analysis shows that the union and employer strategies are not independent of one another. More active campaigns by one side (in terms of more tactics used) are met by more active campaigns by the other side. Regression analysis is used to estimate the effects of the strategies on the outcome of the organising campaign. The most active strategies, including intensive communication with workers and worker committees, work best for the employers. For unions, strategies emphasising personal communication through house calls are the most effective.