Formulation and estimation of dynamic models using panel data

This paper presents a statistical analysis of time series regression models for longitudinal data with and without lagged dependent variables under a variety of assumptions about the initial conditions of the processes being analyzed. The analysis demonstrates how the asymptotic properties of estimators of longitudinal models are critically dependent on the manner in which samples become large: by expanding the number of observations per person, holding the number of people fixed, or by expanding the number of persons, holding the number of observations per person fixed. The paper demonstrates which parameters can and cannot be identified from data produced by different sampling plans.     

Trading Behavior and Asset Returns: Evidence from the Interday Serial Correlations of Intraday‐to‐Intraday Daily Returns of Taiwan

This paper sheds light on the importance of trading behavior in the determination of asset prices by examining the interday serial correlations of intraday‐to‐intraday daily returns of the Taiwan Stock Exchange (TSEC). The TSEC exhibits positive serial correlation in the beginning and the end of the week and negative serial correlation in the middle of the week. The interday serial correlation is not a result of non‐synchronous trading, bid‐ask bounce in transaction price, or price limits. The serial correlation is positively related to trading volume and similar to the pattern in the US. We suggest that trading behavior seems to be an important determinant of asset prices.     

Maternal full-time employment and overweight children: Parametric, semi-parametric, and non-parametric assessment

We use the matched mother-child data from the 2000 wave of the US National Longitudinal Survey of Youth 79 (NLSY79) to assess the impact of full-time working mothers on children’s body mass index (BMI) and the likelihood of becoming overweight. Parametric, semi-parametric and non-parametric methods are employed to correct the bias of selection on observables and unobservables. Pros and cons of various methods are discussed and specification tests are conducted. In general, we find that a mother’s full-time employment does have some impact on her children’s BMI and likelihood of becoming overweight across models and inference procedures.     

Antecedents of flow in retail store shopping

“Flow” has been established as a critical determinant of an online shopping experience. Online consumers with flow experience tend to be less price-sensitive and to have favorable attitudes and high re-patronage intention. As retail stores account for 90% of retail sales, it is important to advance our knowledge of flow theory in physical retail stores. However, the antecedents (navigational challenge, web skill) derived from the extant online flow literature are not applicable to in-store shopping. To fill the void, the two objectives here are (1) to provide a theoretical foundation to develop the antecedents (challenges and skills) associated with in-store shopping, and (2) to examine their impacts on consumer flow experience (concentration, control, and enjoyment) and subsequent future shopping intentions. The results will advance the literature of flow and offer helpful suggestions to retail marketing.     

Integrated reporting: background,measurement issues,approaches and an agenda for future research

We discuss the background to integrated reporting, a new reporting framework focused on firms’ future value creation narrative. We consider why integrated reporting is an area of interest for the accounting profession, accountants, investors, regulators and managers. We provide an overview of the integrated reporting literature, discuss measurement and research design issues to take into account when designing studies on integrated reporting and identify approaches and set an agenda for future research.     

A service innovation framework for start-up firms by integrating service experience engineering approach and capability maturity model

The service sector contributes more than 70 % to the GDP of many countries in which their services should continually be innovated to improve customer satisfaction. This study reviews the literature from 1995 to 2014 in the field of service innovation, service experience and engineering, and maturity model. Results show that the existing service innovation frameworks lack a focus on business process improvement, particularly for start-up firms. It causes the startups not ready enough to deal with inevitable challenges that may be encountered in the future. Accordingly, this study proposes a novel framework that combines the service experience engineering method and capability maturity model of integration for service to develop a new innovative service and improve service quality process for start-up firms. A practical case is implemented by applying the proposed framework. A service innovation prototype system is developed on the basis of the case study to deliver a mobile campus merchandise purchasing service.     

A novel framework for customer complaint management

Complaining is one option available to customers to express their dissatisfaction with inadequate services. Their complaints contain valuable information for service providers to improve customer relationships and operational quality, which can ultimately enhance business profitability. Customer complaints are frequently handled at the individual level, however, which addresses the symptoms rather than the causes of customer dissatisfaction. This paper presents a framework integrating a decision tree approach, a common data mining tool, into Six Sigma methodology to analyze customer complaints in aggregate and improve service quality by identifying and addressing the underlying causes of failed service. A case study of a restaurant chain was used to demonstrate the effectiveness of the proposed framework. The results indicated a significant (60%) decrease in the number of customer complaints received. Subsequent long-term benefits can be expected.     

Panel parametric,semiparametric, and nonparametric construction of counterfactuals

We consider panel parametric, semiparametric and nonparametric methods of constructing counterfactuals. We show through extensive simulations that no method is able to dominate other methods in all circumstances, since the true data‐generating process is typically unknown. We therefore also suggest a model‐averaging method as a robust method to generate counterfactuals. As an illustration of the sensitivity of counterfactual construction, we reexamine the impact of California's Tobacco Control Program on per capita cigarette consumption and election day registration (EDR) laws on voters' turnout by different methods.