How innovation can alleviate negative consequences of demanding work contexts:The influence of climate for innovation on organizational outcomes

This study examines climate for innovation as a method by which negative organizational consequences of demanding work may be lessened. It was expected that a climate for innovation would enable employees to develop coping mechanisms or improved work-related processes which counteract negative consequences of work demands. Extending the job demands-resource model (Karasek, 1979), we predicted and found that among the sample of 22,696 respondents from 131 healthcare organizations, organizational climate for innovation alleviated the negative effects of work demands on organizational performance. Thus, this study informs climate theories and guides practitioners' efforts to support the employees. © 2007 The British Psychological Society.

Negative assimilation:how immigrants experience economic mobility in Japan

This paper examines the economic mobility of foreign migrants in Japan. In a country that is largely regarded as homogeneous and closed to outsiders, how and to what extent do immigrants achieve economic success? A survey conducted by the authors revealed that the conventional assimilationist perspective does not fully explain immigrants’ economic success in Japan. Migrants from the West experience what Chiswick and Miller (2011) refer to as “negative assimilation.” That is, their earnings decline over time in Japan. While negative assimilation was not clearly observed among immigrants from neighboring Asian countries, wages among them did not increase with the length of their stay in Japan. For both groups, the skills they brought from abroad were found to be largely accountable for their economic success, while locally specific human capital, such as education acquired in the host society, did not contribute to their earnings.

Negative data in DEA:a directional distance approach applied to bank branches

This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

A DEA model for units with negative data

In this paper we propose an alternative method for measuring efficiency of Decision making Units, which allows the presence of variables with both negative and positive values. The model is applied to data on the notional effluent processing system to compare the results with recent developed methods; Modified Slacks Based Model as suggested by Sharp et al (2007) and Range Directional Measures developed by Silva Portela et al (2004). A further example explores advantages of using the new model.

Nanofabricated media with negative permeability at visible frequencies

A great deal of attention has recently been focused on a new class of smart materials-so-called left-handed media-that exhibit highly unusual electromagnetic properties and promise new device applications. Left-handed materials require negative permeability ν, an extreme condition that has so far been achieved only for frequencies in the microwave to terahertz range. Extension of the approach described in ref. 7 to achieve the necessary high-frequency magnetic response in visible optics presents a formidable challenge, as no material-natural or artificial-is known to exhibit any magnetism at these frequencies. Here we report a nanofabricated medium consisting of electromagnetically coupled pairs of gold dots with geometry carefully designed at a 10-nm level. The medium exhibits a strong magnetic response at visible-light frequencies, including a band with negative ν. The magnetism arises owing to the excitation of an antisymmetric plasmon resonance. The high-frequency permeability qualitatively reveals itself via optical impedance matching. Our results demonstrate the feasibility of engineering magnetism at visible frequencies and pave the way towards magnetic and left-handed components for visible optics. © 2005 Nature Publishing Group.

A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data. In this paper, we propose a semi-oriented radial measure, which permits the presence of variables which can take both negative and positive values. The model is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA: The modified slacks-based model suggested by Sharp et al. [Sharp, J.A., Liu, W.B., Meng, W., 2006. A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs. Journal of Operational Research Society 57 (11) 1–6] and the range directional model developed by Portela et al. [Portela, M.C.A.S., Thanassoulis, E., Simpson, G., 2004. A directional distance approach to deal with negative data in DEA: An application to bank branches. Journal of Operational Research Society 55 (10) 1111–1121]. A further example explores the advantages of using the new model.

Malmquist-type indices in the presence of negative data:an application to bank branches

In this paper we develop an index and an indicator of productivity change that can be used with negative data. For that purpose the range directional model (RDM), a particular case of the directional distance function, is used for computing efficiency in the presence of negative data. We use RDM efficiency measures to arrive at a Malmquist-type index, which can reflect productivity change, and we use RDM inefficiency measures to arrive at a Luenberger productivity indicator, and relate the two. The productivity index and indicator are developed relative to a fixed meta-technology and so they are referred to as a meta-Malmquist index and meta-Luenberger indicator. We also address the fact that VRS technologies are used for computing the productivity index and indicator (a requirement under negative data), which raises issues relating to the interpretability of the index. We illustrate how the meta-Malmquist index can be used, not only for comparing the performance of a unit in two time periods, but also for comparing the performance of two different units at the same or different time periods. The proposed approach is then applied to a sample of bank branches where negative data were involved. The paper shows how the approach yields information from a variety of perspectives on performance which management can use.