Investing in conflict zones:a firm-level analysis

The purpose of this paper is to examine, using panel data econometric techniques, the determinants of a firm’s strategy to invest in a conflict location. To the best of our knowledge this has not been done before. We use a large database of firm-level data that includes 2858 multinational firms that have a subsidiary in a developing country (during 1999-2006). Out of these firms 290 are classified as having a subsidiary in a conflict location. The choice of a conflict location is based on data from the Inter Country Risk Guide (ICRG). We start with the population of multinationals who have chosen to invest in low income countries with weak institutions. Our analysis then proceeds to explain the decision of those firms to invest in conflict locations. We have four hypotheses: (1) Firms with concentrated ownership are more likely to invest in a conflict region; (2) Firms from countries with weaker institutions are more likely to invest in conflict regions; (3) Firms and Countries with less concern over corporate social responsibility are more likely to invest in conflict countries; and (4) that there is large sector level differences in the propensity to invest in a conflict region. The results suggest that all of these hypotheses can be confirmed.

A multi-level investigation of psychological contract breach and organizational identification through the lens of perceived organizational membership:testing a moderated-mediated model

Drawing on the perceived organizational membership theoretical framework and the social identity view of dissonance theory, I examined in this study the dynamics of the relationship between psychological contract breach and organizational identification. I included group-level transformational and transactional leadership as well as procedural justice in the hypothesized model as key antecedents for organizational membership processes. I further explored the mediating role of psychological contract breach in the relationship between leadership, procedural justice climate, and organizational identification and proposed separateness–connectedness self-schema as an important moderator of the above mediated relationship. Hierarchical linear modeling results from a sample of 864 employees from 162 work units in 10 Greek organizations indicated that employees' perception of psychological contract breach negatively affected their organizational identification. I also found psychological contract breach to mediate the impact of transformational and transactional leadership on organizational identification. Results further provided support for moderated mediation and showed that the indirect effects of transformational and transactional leadership on identification through psychological contract breach were stronger for employees with a low connectedness self-schema.

Teams, HRM and innovation:an organisation-level analysis

For organizations to survive and prosper they have to develop new and improved products, services and ways of working. Innovation is vital for organizational survival. Much research and managerial attention is therefore devoted to understanding the factors that predict innovation in organizations. This paper describes a research study of product innovation in manufacturing organizations and explores the extent to which team based working and team working effectiveness in these organizations predict product innovation. It also considers whether combinations of good HRM systems and practices, extensive team based working and effective team working are associated with product innovation.

Multi-level visualisation using Gaussian process latent variable models

Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.

Optimization method for PSA-based multi-level regenerators

We develop an analytical methodology for optimizing phase regeneration based on phase sensitive amplification. The results demonstrate the scalability of the scheme and show the significance of simultaneous optimization of transfer function and the signal alphabet.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Multi-level optimization of a fiber transmission system via nonlinearity management

Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.

Between global ambitions and local change:how multi-level cooperation advances norm implementation in weak states

The purpose of this article is to investigate in which ways multi-level actor cooperation advances national and local implementation processes of human rights norms in weak-state contexts. Examining the cases of women’s rights in Bosnia and Herzegovina and children’s rights in Bangladesh, we comparatively point to some advantages and disadvantages cooperative relations between international organisations, national governments and local NGOs can entail. Whereas these multi-level actor constellations (MACs) usually initiate norm implementation processes reliably and compensate governmental deficits, they are not always sustainable in the long run. If international organisations withdraw support from temporary missions or policy projects, local NGOs are not able to perpetuate implementation activities if state capacities have not been strengthened by MACs. Our aim is to highlight functions of local agency within multi-level cooperation and to critically raise sustainability issues in human rights implementation to supplement norm research in International Relations.

The employee satisfaction -performance link: A unit -level analysis

In this dissertation, I present an integrated model of organizational performance. Most prior research has relied extensively on testing individual linkages, often with cross-sectional data. In this dissertation, longitudinal unit-level data from 559 restaurants, collected over a one-year period, were used to test the proposed model. The model was hypothesized to begin with employee satisfaction as a key antecedent that would ultimately lead to improved financial performance. Several variables including turnover, efficiency, and guest satisfaction are proposed as mediators of the satisfaction-performance relationship. The current findings replicate and extend past research using individual-level data. The overall model adequately explained the data, but was significantly improved with an additional link from employee satisfaction to efficiency, which was not originally hypothesized. Management turnover was a strong predictor of hourly level team turnover, and both were significant predictors of efficiency. Full findings for each hypothesis are presented and practical organizational implications are given. Limitations and recommendations for future research are provided. ^

HRM and Innovation: A Multi-level Organizational Learning Perspective

Drawing on the 4I organizational learning framework (Crossan et al., 1999), this article develops a model to explain the multi-level and cross-level relationships between HRM practices and innovation. Individual, team, and organizational level learning stocks are theorized to explain how HRM practices affect innovation at a given level. Feed-forward and feedback learning flows explain how cross-level effects of HRM practices on innovation take place. In addition, we propose that HRM practices fostering individual, team, and organizational level learning should form a coherent system to facilitate the emergence of innovation. The article is concluded with discussions on its contributions and potential future research directions.

Multi-residue analysis of 39 pesticides in surface waters of Ria de Aveiro

A multi-residue gas chromatography-mass spectrometry method was developed in order to evaluate the presence of 39 pesticides of different chemical families (organophosphorus, triazines, imidazole, organochlorine), as well as some of their transformation products, in surface water samples from Ria de Aveiro. Ria de Aveiro is an estuarine coastal lagoon, located in the northern west region of Portugal, which receives inputs from agriculture, urban and industrial activities. The analytical method was developed and validated according international guidelines and showed good linearity, with correlation coefficients higher than 0.9949 for all compounds, adequate precision and accuracy, and high sensitivity. Pesticides were chosen from the priority pollutants list of the Directive 2008/105/EC of the European Parliament and of the Council (on environmental quality standards in the field of water policy), or were selected due their common use in agricultural practices. Some of these 39 pesticides are, or are suspected to be, endocrine disruptor compounds (EDCs), being capable of altering the endocrine system of wildlife and humans, causing form malfunction and ultimately health problems. Even those pesticides which are not EDCs, are known to be awfully toxic and have a recognised impact in human health. The aquatic environment is particularly susceptible to pollution due to intentional and accidental release of chemicals to water [3]. Pesticide contamination of surface water is a national issue as it is often used as drinking water. This concern is especially important in rural agricultural areas where population uses small private water supplies, regularly without any laboratory surveillance. The study was performed in seven sampling points and the results showed a considerable concern pesticide contamination of all samples.