Measuring self‐regulated learning in the workplace

In knowledge‐intensive industries, the workplace has become a key locus of learning. To perform effectively, knowledge workers must be able to take responsibility for their own developmental needs, and in particular, to regulate their own learning. This paper describes the construction and validation of an instrument (the Self‐Regulated Learning at Work Questionnaire) designed to provide a measure of self‐regulated learning (SRL) behaviour in the workplace. The instrument has been validated through a pilot study with a cohort of 170 knowledge workers from the finance industry. Results indicate that the five scales of the instrument are reliable and valid, testing a broad range of sub‐processes of SRL. The instrument can be used to identify knowledge workers who demonstrate different levels of SRL in workplace contexts for further exploration through qualitative studies and could also provide the basis of professional development tools designed to explore opportunities for self‐regulation of learning in the workplace.     

Green Product Innovation in Manufacturing Firms: A Sustainability‐Oriented Dynamic Capability Perspective

Despite environmental sustainability being identified as one of the key drivers of innovation, extant literature lacks a theoretically sound and empirically testable framework that can provide specific insights into green product innovation from a capability perspective. This study develops a theoretical framework from a sustainability‐oriented dynamic capability (SODC) perspective. We conceive SODCs as consisting of three underlying processes (external resource integration, internal resource integration, and resource building and reconfiguration) that influence the change/renewal of sustainability‐oriented ordinary capabilities (SOOCs) (green innovation capability and eco‐design capability). This study answers two key questions: which SODCs are needed to develop green innovation and eco‐design capabilities? Which of these capabilities lead to better market performance of green products? We test a structural model linking SODCs to market performance in 189 Italian manufacturing firms. First, we find that the nature of the SODC–performance link (direct or indirect) depends on the SODC type. Specifically, resource building and reconfiguration is the only SODC with a direct effect on market performance. Second, all three types of SODC affect the eco‐design capability, which mediates the link between SODCs and market performance. Third, we find that external resource integration is the only SODC affecting the green innovation capability, which mediates the link between external resource integration and market performance. Resource building and reconfiguration is the SODC with the overall (direct and indirect) highest impact on market performance. This study, among the first to consider capabilities for green product innovation under a dynamic capability perspective, provides implications for scholars, managers and policy makers. Copyright © 2016 John Wiley & Sons, Ltd and ERP Environment     

THE INFORMATION CONTENT AND USEFULNESS OF THE TERM STRUCTURE OF THE NEW ZEALAND BANK BILL MARKET

This paper applies the rationality concept and expectations hypothesis to test the information efficiency of the term structure of the New Zealand bank bill market. Weekly data is collected from June 1986 to November 1988. The sample period is partitioned into two subperiods by the sharemarket crash in October 1987. The empirical results suggest the presence of a time varying risk premium. This is reflected by the significantly positive volatility measure in the first subperiod and the significant interest rate level variable in both subperiods. The forecast errors correlate significantly with the growth in money supply and overseas interest rate variables. Factors other than market information inefficiency could be responsible for the significant correlation; namely the impact of the sharemarket crash on market perceptions about inflation expectations and the non-simultaneous data problem in calculating the differential costs of borrowing. Despite the rejection of the joint hypothesis, forward rates are found to have information about future spot rates beyond that contained in past spot rates, and are able to predict interest rates at least 30 days ahead.     

The Ex-Dividend Day Stock Price Behavior: The Case of Portugal

This paper examines the ex-dividend day behavior of stock prices in the Lisbon Stock Market over the period 1990–1998, extending on international evidence and discussing the adequacy of competing theories, considering the Portuguese institutional environment. We find that on the ex-day stock prices fall by less than the dividend, which is in line with the findings of several studies based on US and non-US data. The main contributions of this paper are: (1) the rejection of a tax explanation for the stock price drop, because it is inconsistent with the Portuguese tax regime; (2) considering the very small stock price tick and the fact that dividends are always integer multiples of tick size, the discreteness hypothesis of Bali and Hite (Journal of Financial Economics 47(2):127–159, 1998) is also ruled out as a possible explanation for ex-day price movements. We find no evidence of tax related clientele effects. We propose that ex-day price behavior may be an anomaly, reflecting a less than efficient market with low liquidity levels, price stickiness, and insipid arbitrage trading.

Participation and Consumption of Illegal Drugs among Adolescents

This paper identifies the determinants affecting the adolescent populations' decision regarding whether or not to consume illegal drugs. The authors estimate a simultaneous Type II Tobit model for each sample substance, including marijuana, LSD, amphetamines, cocaine, volatile substances, and heroine. The data are drawn from three Spanish Surveys on Drug Use in the School Population conducted in 1994, 1996, and 1998. The results indicate that illegal drug use among Spanish adolescents is clearly determined by economic variables. It is similarly determined by other sociodemographic variables, such as personal habits, family environment, and the receipt of information regarding the negative consequences of drug use. This paper was partially written while José Alberto Molina was Visiting Researcher at the Fundación de Estudios de Economía Aplicada-FEDEA (Madrid, Spain), to which he would like to express his thanks for the hospitality and facilities provided. The authors are grateful to two anonymous referees for their helpful observations on an earlier version of this paper. Similarly, Namkee Ahn, as well as various participants at the XIX Spanish Health Economics Meeting (Zaragoza, Spain) and at the 2001 Annual Meeting of the Population Association of America (Washington DC), have all offered valuable comments and suggestions. Finally, the authors would like to express their gratitude for the financial support provided by the Spanish Ministry of Education-CICYT and the European Commission (Project FEDER 2FD97-2057). The usual disclaimer applies.     

Asymptotic and Bootstrap techniques for testing the expected value of a fuzzy random variable

In this paper we will consider hypothesis-tests for the (fuzzy-valued) mean value of a fuzzy random variable in a population. For this purpose, we will make use of a generalized metric for fuzzy numbers, and we will develop an approach for normal fuzzy random variables, and two different approaches for the case of fuzzy random variables taking on a finite number of different values. A real-life example illustrates the use of the last two approaches. Finally, a comparison between the introduced techniques is developed by means of simulation studies leading to close inferential conclusions.Acknowledgements.The research in this paper has been partially supported by MCYT Grants BFM2002-01057 and BFM2001-3494. Their financial support is gratefully acknowledged. The authors are sincerely grateful to their colleague Gil González-Rodríguez for all his comments and suggestions in connection with this paper; his scientific support has been very valuable. The authors want also thank the referees of the first version of the paper because of their useful hints to improve it.     

Does corruption affect income inequality and poverty?

This paper provides evidence that high and rising corruption increases income inequality and poverty. An increase of one standard deviation in corruption increases the Gini coefficient of income inequality by about 11 points and income growth of the poor by about 5 percentage points per year. These findings are robust to use of different instruments for corruption and other sensitivity analyses. The paper discusses several channels through which corruption may affect income inequality and poverty. An important implication of these findings is that policies that reduce corruption will most likely reduce income inequality and poverty as well. Received: March 2, 2000 / Accepted: September 20, 2001     

Neural network forecasting of quarterly accounting earnings

This study uses an artificial neural network model to forecast quarterly accounting earnings for a sample of 296 corporations trading on the New York stock exchange. The resulting forecast errors are shown to be significantly larger (smaller) than those generated by the parsimonious Brown-Rozeff and Griffin-Watts (Foster) linear time series models, bringing into question the potential usefulness of neural network models in forecasting quarterly accounting earnings. This study confirms the conjecture by Chatfield and Hill et al. that neural network models are context sensitive. In particular, this study shows that neural network models are not necessarily superior to linear time series models even when the data are financial, seasonal and non-linear.