The socio‐spatial nature of organisational creativity: experiences along the road toward transdisciplinarity

This paper sets out to explore characteristics of transdisciplinary organisational research in practice and in particular how the process of research may be shared and co-produced by both university and business. The case studies presented here outline recent work conducted through ‘Innovation Futures’, a Sheffield Hallam University project which aims to contribute to the development of a region-wide culture of innovation and to create strong links between businesses and the University. The multidisciplinary team, based across Sheffield Business School and the Cultural, Communication and Computing Research Institute, has worked with numerous companies from the manufacturing and service sectors in the last three years. Through a strong process of collaboration throughout the stages of problem structuring,problem investigation, and realisation of findings in practice, the work has sought to help businesses improve processes and, ultimately, performance via a range of analytical measures. By employing a holistic approach to understanding the social-cultural nature of the workspace through the integrated use of Social Network Analysis, Space Syntax and participatory design methods, managers have been able to develop a much greater level of reflexive management practice through their experiences of collaborative research. There is increasing recognition that organisational creativity is not formed through the innate attributes of the individual but is instead a wholly social process involving complex phases of interaction thus making the socio-spatial environment of the organisation, within which such phases are carried out, a key determinant of success. This environment is both shaped, and also shapes, those within it through the requirements of organisation and it is through the experience of transdisciplinary boundary spanning that both academic institution and business can help form research driven management practices

Evolving innovation through office knowledge networks : mapping the ephemeral architecture of organizational creativity

This paper explores positive conditions for the evolution of creative innovation through informal social networks in the office. By drawing on both Social Network Analysis (SNA) and the abstracted evolutionary mechanisms of variation, selection and retention, a multilevel conceptualization of the evolutionary processes underpinning the emergence and development of ideas within an organization is put forward. In this way SNA is used to visualize not just the connectivity of individuals within the company who offer 'expert advice' and 'new ideas' in the development of these products, but also the role of mediators in this process at a digital media company, Dataco

What can secondary data tell us about household food insecurity in a high-income country context?

In the absence of routinely collected household food insecurity data, this study investigated what could be determined about the nature and prevalence of household food insecurity in Scotland from secondary data. Secondary analysis of the Living Costs and Food Survey (2007–2012) was conducted to calculate weekly food expenditure and its ratio to equivalised income for households below average income (HBAI) and above average income (non-HBAI). Diet Quality Index (DQI) scores were calculated for this survey and the Scottish Health Survey (SHeS, 2008 and 2012). Secondary data provided a partial picture of food insecurity prevalence in Scotland, and a limited picture of differences in diet quality. In 2012, HBAI spent significantly less in absolute terms per week on food and non-alcoholic drinks (£53.85) compared to non-HBAI (£86.73), but proportionately more of their income (29% and 15% respectively). Poorer households were less likely to achieve recommended fruit and vegetable intakes than were more affluent households. The mean DQI score (SHeS data) of HBAI fell between 2008 and 2012, and was significantly lower than the mean score for non-HBAI in 2012. Secondary data are insufficient to generate the robust and comprehensive picture needed to monitor the incidence and prevalence of food insecurity in Scotland.</p

Denitrification in the upland soils of a forested land treatment system

The contribution of upland denitrification to nitrate removal in soils, and the factors controlling denitrification, were investigated in the Rotorua Land Treatment System (RLTS), New Zealand. The RLTS is forested with radiata pine and located on free-draining soils formed from pumiceous parent materials. In land treatment systems, a large proportion of the nitrogen added in the wastewater is thought to either be utilised by the cover crop, or by soil microbial processes. An important soil microbial process that is often assumed to occur is denitrification. However, the contribution of upland denitrification to nitrogen renovation, and the effects of wastewater application on the soil denitrifying population, is poorly understood in forested land treatment systems. An initial study was undertaken to establish a suitable method for measuring in situ denitrification rates in the RLTS. Denitrification enzyme activity (DEA) was measured at different soil depths (litter, 0-5, 5-10, 10-20 and 20-40 cm) in three topographic positions of the RLTS (ridge, midslope and toeslope). In addition, in situ denitrification rates were measured, using an acetylene-inhibition technique, at various time intervals before and after irrigation to determine how frequently soil cores needed to be taken to quantify denitrification losses after wastewater irrigation. It was concluded that it was necessary to collect cores from the uppermost 10 cm of the soil profile (including the litter layer), on a daily basis between irrigation events, and repeatedly throughout the year, to accurately estimate annual denitrification rates in the RLTS. Denitrification rates were measured in the RLTS over a period of 12 months. The spatial variability of in situ denitrification rates was investigated by using a nested field design that divided the RLTS into four stages (irrigation block, topographic position, field site and sample point). In situ denitrification rates were measured between irrigation events, to establish how daily denitrification rates varied after wastewater irrigation, and on 21 different occasions during the year, to establish how daily denitrification rates varied seasonally. Annual denitrification rates of 2.4 and 1.7 kg N ha⁻¹ yr⁻¹ were recorded for the wastewater-irrigated and unirrigated soils, respectively. Daily denitrification rates were spatially and temporally variable, with coefficients of variation greater than 100%. Differences in denitrification rates between irrigation blocks contributed significantly more to spatial variability than differences between or within topographic positions. Denitrification rates varied seasonally, with greatest losses occurring in the late summer and autumn. Daily denitrification rates also varied from day-to-day after irrigation. However, the day-to-day pattern of denitrification after irrigation changed throughout the year. Over 12 months, temporal effects contributed more than spatial effects to the overall variation in denitrification rates. Soil moisture content, nitrate concentration, respiration, DEA and temperature were measured during the 12 month field trial to determine their effects on in situ denitrification rates. Using multiple regression analysis, soil and environmental properties could only explain up to 29% of the variation in in situ denitrification rates. Laboratory studies showed that denitrification rates were very small when soil moisture contents were less than 80%. During the field trial, water-filled porosity was low, and in 84% of the samples collected (n = 4527), soil moisture contents were less than the critical threshold value required for denitrification. Therefore, it was proposed that in situ denitrification rates were small in the RLTS because soil moisture contents were low and generally less than the critical moisture content required for denitrification. The size of the denitrifying population was also found to be small in the RLTS. Under optimum laboratory conditions, potential denitrification rates at 25 °C were 13.4 kg N ha⁻¹ yr⁻¹ in the wastewater irrigated soils. However, potential denitrification rates would be expected to be less at average field temperatures (11 °C). Laboratory studies, using disturbed soil samples, suggested that the size of the denitrifying population in the wastewater irrigated soils was limited by soil aeration. When oxygen availability in irrigated soils was limited, the size of the denitrifying population increased to a greater extent than measured in the field. However, adding carbon and nitrate to anaerobic soils did not further increase the denitrifying population in comparison to controls in the irrigated soils. Wastewater-irrigation changed the factors limiting denitrifiers in the RLTS. In the irrigated soils, denitrification is limited by soil aeration, while in the unirrigated soils denitrifiers were limited by both soil aeration and nitrate. Furthermore, wastewater irrigation altered the short-term response of denitrifiers to anaerobiosis. Under low oxygen conditions, in the laboratory, denitrifiers in the wastewater-irrigated soils produced enzymes earlier, and at a greater rate, than soil that had no history of wastewater irrigation. It was concluded that wastewater needs to contain sufficient nitrogen to increase soil nitrate concentrations and should be applied to soils which are less free-draining soils than the soils used in this study, if upland denitrification is to contribute significantly to nitrogen removal in a forested land treatment system. A conceptual model is proposed to assist in establishing the likelihood of upland denitrification significantly contributing to nitrogen removal in a forested land treatment system

The Methodology for Farm-Scale Modelling for Spatio-Temporal Prediction of Soil Carbon Sequestration under Climate Change

A methodology for region-specific adaptation of existing soil carbon (C) models was developed by integrating location-specific automated data with local farm-based knowledge. The aim was to optimise the balance between scientific accuracy and farm-scale practicality of C modelling tools to identify the most influential location-specific variables