Advancing environmental productivity: Organizational mindfulness and strategies

This study investigates the importance of mindfulness‐based organization systems and policies on the organization's continuous efforts to become a greener company. The study is devised as a pooled cross‐sectional time series analysis of productivity in energy consumption, water utilization, and waste generation and recycling of U.S. companies. The data set taken from U.S. Newsweek 500 recorded 600 companies dispersed into 63 industries during the period of 2012–2014 and provided 1,498 company–industry–year observations. The study found that systems and policies (e.g., deployment of third‐party auditors for its environmental metrics report; linkage of the remuneration of company's senior executive team with the achievement of environmental performance targets; and establishment of a committee at the Board of Directors' level whose mandate includes sustainability of the company in environment‐ and resource‐related matters) connect the company's mindfulness to its effort in improving the environmental quality through the company's productivity in energy consumption, water utilization, and waste generation and recycling. The relationships are positive and significant. Also, systems and policies serve as a motivator for the firm to continue to improve upon the current achievements. The study emphasizes the importance of translating organizational and individual mindfulness into organization policies and systems in order to motivate the organization to continuously improve its productivity in energy consumption, water utilization, and waste generation and recycling leading to improvements in environmental quality.     

Revisiting the expatriate failure concept: A qualitative study of Scandinavian expatriates in Hong Kong

This article advances the understanding of expatriate failure, which remains a contested social phenomenon in international work life as well as scholarly research. The study challenges the definition of expatriate failure and its inherent biases, i.e., the epistemological primacy of the firm level and the failure/success binary. We argue that this qualitative study of 51 Scandinavian expatriates in Hong Kong can contribute to advancing theory on the expatriate failure concept by asking individual expatriates what constitutes failure to them. By applying social constructionist and social anthropological ideas to the expatriate failure concept debate, we develop the internationality thesis which demonstrates a discrepancy between the expatriates’ perceptions of successful international assignments and the actual nature of their lived lives; many expatriates desire to enrich their lives through experiencing an international/intercultural and adventurous lifestyle, but, in fact, living lives with limited intercultural exposure and interaction. We conclude by proposing a reconceptualisation of expatriate failure in terms of offering both a new definition and approach to researching expatriate failure in which time/duration, context, and geographical location need to be taken into account. We believe the new approach can overcome some of the empirical unsoundness of mainstream definitions.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Predicting Household Poverty: A Methodological Note with a Kenyan Example

Household surveys provide data that is used for identifying and measuring the poverty status of households and individuals. However, carrying out such surveys is expensive, especially in poor developing countries. Thus it is important to make maximum use of the available survey data in developing countries, especially in sub‐Saharan Africa, where such data are expensive to collect and analyse. This paper develops a simple method for using poverty indices derived from survey data for a given year, to predict poverty rates for subsequent periods without having to conduct a new household survey. We illustrate the workings of the method with data from Kenyan household surveys for 1994 and 1997.     

Gender and Piece Rates, Commissions, and Bonuses

Previous work shows that establishments with higher proportions of women are more likely to use piece rates but that individual women are less likely to receive performance pay. We present a model in which lower expected tenure and labor force attachment are positively associated with piece rates but are negatively associated with other forms of performance pay. Analysis of the National Longitudinal Survey of Youth (NLSY) confirms that women are more likely to be paid piece rates and simultaneously less likely to be paid commissions and bonuses.     

The Local Whittle Estimator of Long-Memory Stochastic Volatility

We propose a new semiparametric estimator of the degree of persistencein volatility for long memory stochastic volatility (LMSV) models.The estimator uses the periodogram of the log squared returnsin a local Whittle criterion which explicitly accounts for thenoise term in the LMSV model. Finite-sample and asymptotic standarderrors for the estimator are provided. An extensive simulationstudy reveals that the local Whittle estimator is much lessbiased and that the finite-sample standard errors yield moreaccurate confidence intervals than the widely-used GPH estimator.The estimator is also found to be robust against possible leverageeffects. In an empirical analysis of the daily Deutsche Mark/USDollar exchange rate, the new estimator indicates stronger persistencein volatility than the GPH estimator, provided that a largenumber of frequencies is used.     

Information styles of marketing and R&D personnel during technological product innovation projects

Abstract The research question in the present article can be phrased in the following way: what are the elements which influence the perception of the utility of information received from another function? A field study research has been conducted in 40 Belgian companies. In each company, we have studied two on-going innovation projects (one planning project, one development project). Crossfunctional communication behaviours at the R&D/marketing interface have been measured by means of mailed structured questionnaires. Three-hundred and eighty-six questionnaires have been returned. The data analyses show that there are four underlying information dimensions, i.e. the perceived relevance, the perceived comprehensibility, the perceived novelty and the perceived credibility of information. We also discuss some contingency variables (function of the message receiver, stage in the innovation process) that might moderate the impact of these dimensions. It will be shown that the interaction between source and receiver has a significant impact on the perceived credibility, the perceived comprehensibility and the perceived novelty of the received information.     

Optimal immigration, education and growth in the long run

The paper extends Manning's model on education and balanced growth to include labour immigration. Each immigration unit is assumed to consist of one skilled worker and some unskilled members. The optimal immigration policy which maximizes the per capita steady-state consumption of the host country is derived. We show that optimal immigration policy can reduce the steady-state skilled labour ratio. More interesting still, contrary to the widespread belief that immigration of skilled workers hurts local skilled workers, it is the unskilled local workers whose interests are threatened by optimal immigration policy.     

Rural traffic management: The Burrator Reservoir experiment

The introduction of traffic management schemes has been one response of the National Parks to the problem of ever-increasing car-borne visitors and the consequent damage caused to the rural environment. By reviewing these schemes and by determining and explaining attitudes towards one particular traffic management experiment, the paper aims to deduce lessons for future policy. The analysis, based on two visitor surveys, suggests that the likelihood of success is improved when schemes are integrated, containing both ‘carrot’ and ‘stick’ elements. Since public perceptions are also found to be pivotal to its success, appropriate marketing of a scheme is vital. The paper concludes, however, that to achieve the fundamental objective of greater accessibility with less mobility, a more wide-ranging marketing effort is required intended to engender a sea change in attitude towards both the car and public transport.