Competency-Based Theory For Achieving Innovation: The Case Of Post-Disaster Reconstruction

For those working in the humanitarian sector, achieving positive outcomes for postdisaster communities through reconstruction projects is a pressing concern. In the wake of recent natural disasters, NGOs have become increasingly involved in the permanent reconstruction of affected communities. They have encountered significant barriers as they implement reconstruction programmes and this paper argues that it is important to address the visible lack of innovation that is partially to blame. The theoretical bedrock of a current research project will be used as the starting point for this argument, the overall goal of which is to design a competency-based framework model that can be used by NGOs in post-disaster reconstruction projects. Drawing on established theories of management, a unique perspective has been developed from which a competency-based reconstruction theory emerges. This theoretical framework brings together 3 distinct fields; Disaster Management, Strategic Management and Project Management, each vital
to the success of the model. The objectives of this paper are a) to investigate the role of NGOs in post-disaster reconstruction and establish the current standard of practice b) to determine the extent to which NGOs have the opportunity to contribute to sustainable community development through reconstruction c) to outline the main factors of a theoretical framework first proposed by Von Meding et al. 2009 and d) to identify the innovative measures that can be taken by NGOs to achieve more positive outcomes in their interventions. It is important that NGOs involved in post-disaster reconstruction become familiar with concepts and strategies such as those contained in this paper. Competency-based organizational change on the basis of this theory has the potential to help define the standard of best practice to which future NGO projects might align themselves.

Values based supply chain management and emergent organizational structure

Purpose – The purpose of this paper is to describe an emergent supply chain management system that supports a sustainable values based organization (VBO) using a structuration theory-based framework.

Design/methodology/approach – A case study of a sustainable beef cooperative employing a structuration theory framework provides insights into sustainable supply chain management models.

Findings – The supply chain design and management afford the key to the VBO’s success. In order to attain the necessary price premium, the unique product attributes acquired through the natural beef production process must be sustained along the entire supply chain and communicated to the end customer. Structuration theory is useful in understanding supply chain management in VBOs.
Research limitations/implications – The paper has implications for studying VBOs, particularly those prioritizing sustainability values. The descriptive model presented is useful in settings where organizational structure and the supply chain are needed to support sustainable products and processes and whose success is facilitated by establishing strategic partners, especially those that make possible economies of scale. The study is limited to one, privately owned firm, operating in a specialty industry sector.

Practical implications – The paper has implications for those entities with an identified values set that endows the product with unique characteristics that must be conveyed to their end consumer in order to command a price premium and/or differentiate the product from a commodity. The case study provides an example of how a unique product as well as a facilitating organizational structure and supply chain emerge out of the application of a set of core values.

Originality/value – Little previous research focuses on implications of supply chain management in VBOs. In addition, the paper contributes to both the supply chain management and sustainability literature by relating supply chain management to a more comprehensive sustainability agenda including social, environmental, and long-term economic sustainability and by a theoretically based structuring.

Keywords Sustainable development, Supply chain management, Food industry, Organizational culture, Animal husbandry

Transaction Costs and Organizational Learning in Strategic Oursourcing Relationships

The present paper examines the role of organisational learning and transaction costs economics in strategic outsourcing decisions. Interorganisational learning is critical to competitive success, and organisations often learn more effectively by collaborating with other organisations. However, learning processes may also complicate the process of forming interorganisational partnerships which may increase transaction costs. Based on the literature, the authors develop refutable implications for outsourcing supply chain logistics and a sample of 121 firms in the supply chain logistics industry is used to test the hypotheses. The results show that trust and transaction costs are significant and substantial drivers of strategic outsourcing of supply chain logistics (a strategic flexibility action). Learning intent and knowledge acquisition have no significant influence on the decision to outsource supply chain logistics. The paper concludes with a discussion of the different and often conflicting implications for managing interorganisational learning processes.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

A comparative study on the thermophysical properties for two bis[(trifluoromethyl)sulfonyl]imide-based ionic liquids containing the trimethyl-sulfonium or the trimethyl-ammonium cation in molecular solvents

Herein, we present a comparative study of the thermophysical properties of two homologous ionic liquids, namely, trimethyl-sulfonium bis[(trifluoromethyl) sulfonyl]imide, [S₁₁₁][TFSI], and trimethyl-ammonium bis[(trifluoromethyl)sulfonyl]imide, [HN₁₁₁][TFSI], and their mixtures with propylene carbonate, acetonitrile, or gamma butyrolactone as a function of temperature and composition. The influence of solvent addition on the viscosity, conductivity, and thermal properties of IL solutions was studied as a function of the solvent mole fraction from the maximum solubility of IL, x_s, in each solvent to the pure solvent. In this case, x_s is the composition corresponding to the maximum salt solubility in each liquid solvent at a given temperature from 258.15 to 353.15 K. The effect of temperature on the transport properties of each binary mixture was then investigated by fitting the experimental data using Arrhenius' law and the Vogel-Tamman-Fulcher (VTF) equation. The experimental data shows that the residual conductivity at low temperature, e.g., 263.15 K, of each binary mixture is exceptionally high. For example, conductivity values up to 35 and 42 mS·cm^-1 were observed in the case of the [S ₁₁₁][TFSI] + ACN and [HN₁₁₁][TFSI] + ACN binary mixtures, respectively. Subsequently, a theoretical approach based on the conductivity and on the viscosity of electrolytes was formulated by treating the migration of ions as a dynamical process governed by ion-ion and solvent-ion interactions. Within this model, viscosity data sets were first analyzed using the Jones-Dole equation. Using this theoretical approach, excellent agreement was obtained between the experimental and calculated conductivities for the binary mixtures investigated at 298.15 K as a function of the composition up to the maximum solubility of the IL. Finally, the thermal characterization of the IL solutions, using DSC measurements, showed a number of features corresponding to different solid-solid phase transitions, T_S-S, with extremely low melting entropies, indicating a strong organizational structure by easy rotation of methyl group. These ILs can be classified as plastic crystal materials and are promising as ambient-temperature solid electrolytes. © 2013 American Chemical Society.

Can the scaling behavior of electric conductivity be used to probe the self-organizational changes in solution with respect to the ionic liquid structure? The case of [C8MIM][NTf2]

Electrical conductivity of the supercooled ionic liquid [C8MIM][NTf2], determined as a function of temperature and pressure, highlights strong differences in its ionic transport behavior between low and high temperature regions. To date, the crossover effect which is very well known for low molecular van der Waals liquids has been rarely described for classical ionic liquids. This finding highlights that the thermal fluctuations could be dominant mechanisms driving the dramatic slowing down of ion motions near Tg. An alternative way to analyze separately low and high temperature dc-conductivity data using a density scaling approach was then proposed. Based on which a common value of the scaling exponent [gamma] = 2.4 was obtained, indicating that the applied density scaling is insensitive to the crossover effect. By comparing the scaling exponent [gamma] reported herein along with literature data for other ionic liquids, it appears that [gamma] decreases by increasing the alkyl chain length on the 1-alkyl-3-methylimidazolium-based ionic liquids. This observation may be related to changes in the interaction between ions in solution driven by an increase in the van der Waals type interaction by increasing the alkyl chain length on the cation. This effect may be related to changes in the ionic liquid nanostructural organization with the alkyl chain length on the cation as previously reported in the literature based on molecular dynamic simulations. In other words, the calculated scaling exponent [gamma] may be then used as a key parameter to probe the interaction and/or self-organizational changes in solution with respect to the ionic liquid structure.