Making visible the coding process : Using qualitative data software in a post-structural study

Qualitative research methods require transparency to ensure the ‘trustworthiness’ of the data analysis. The intricate processes of organizing, coding and analyzing the data are often rendered invisible in the presentation of the research findings, which requires a ‘leap of faith’ for the reader. Computer assisted data analysis software can be used to make the research process more transparent, without sacrificing rich, interpretive analysis by the researcher. This article describes in detail how one software package was used in a poststructural study to link and code multiple forms of data to four research questions for fine-grained analysis. This description will be useful for researchers seeking to use qualitative data analysis software as an analytic tool.

Trust and strong ties in the selection and evaluation of business advisors by small firms

Principal Topic A small firm is unlikely to possess internally the full range of knowledge and skills that it requires or could benefit from for the development of its business. The ability to acquire suitable external expertise - defined as knowledge or competence that is rare in the firm and acquired from the outside - when needed thus becomes a competitive factor in itself. Access to external expertise enables the firm to focus on its core competencies and removes the necessity to internalize every skill and competence. However, research on how small firms access external expertise is still scarce. The present study contributes to this under-developed discussion by analysing the role of trust and strong ties in the small firm's selection and evaluation of sources of external expertise (henceforth referred to as the 'business advisor' or 'advisor'). Granovetter (1973, 1361) defines the strength of a network tie as 'a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding) and the reciprocal services which characterize the tie'. Strong ties in the context of the present investigation refer to sources of external expertise who are well known to the owner-manager, and who may be either informal (e.g., family, friends) or professional advisors (e.g., consultants, enterprise support officers, accountants or solicitors). Previous research has suggested that strong and weak ties have different fortes and the choice of business advisors could thus be critical to business performance) While previous research results suggest that small businesses favour previously well known business advisors, prior studies have also pointed out that an excessive reliance on a network of well known actors might hamper business development, as the range of expertise available through strong ties is limited. But are owner-managers of small businesses aware of this limitation and does it matter to them? Or does working with a well-known advisor compensate for it? Hence, our research model first examines the impact of the strength of tie on the business advisor's perceived performance. Next, we ask what encourages a small business owner-manager to seek advice from a strong tie. A recent exploratory study by Welter and Kautonen (2005) drew attention to the central role of trust in this context. However, while their study found support for the general proposition that trust plays an important role in the choice of advisors, how trust and its different dimensions actually affect this choice remained ambiguous. The present paper develops this discussion by considering the impact of the different dimensions of perceived trustworthiness, defined as benevolence, integrity and ability, on the strength of tie. Further, we suggest that the dimensions of perceived trustworthiness relevant in the choice of a strong tie vary between professional and informal advisors. Methodology/Key Propositions Our propositions are examined empirically based on survey data comprising 153 Finnish small businesses. The data are analysed utilizing the partial least squares (PLS) approach to structural equation modelling with SmartPLS 2.0. Being non-parametric, the PLS algorithm is particularly well-suited to analysing small datasets with non-normally distributed variables. Results and Implications The path model shows that the stronger the tie, the more positively the advisor's performance is perceived. Hypothesis 1, that strong ties will be associated with higher perceptions of performance is clearly supported. Benevolence is clearly the most significant predictor of the choice of a strong tie for external expertise. While ability also reaches a moderate level of statistical significance, integrity does not have a statistically significant impact on the choice of a strong tie. Hence, we found support for two out of three independent variables included in Hypothesis 2. Path coefficients differed between the professional and informal advisor subsamples. The results of the exploratory group comparison show that Hypothesis 3a regarding ability being associated with strong ties more pronouncedly when choosing a professional advisor was not supported. Hypothesis 3b arguing that benevolence is more strongly associated with strong ties in the context of choosing an informal advisor received some support because the path coefficient in the informal advisor subsample was much larger than in the professional advisor subsample. Hypothesis 3c postulating that integrity would be more strongly associated with strong ties in the choice of a professional advisor was supported. Integrity is the most important dimension of trustworthiness in this context. However, integrity is of no concern, or even negative, when using strong ties to choose an informal advisor. The findings of this study have practical relevance to the enterprise support community. First of all, given that the strength of tie has a significant positive impact on the advisor's perceived performance, this implies that small business owners appreciate working with advisors in long-term relationships. Therefore, advisors are well advised to invest into relationship building and maintenance in their work with small firms. Secondly, the results show that, especially in the context of professional advisors, the advisor's perceived integrity and benevolence weigh more than ability. This again emphasizes the need to invest time and effort into building a personal relationship with the owner-manager, rather than merely maintaining a professional image and credentials. Finally, this study demonstrates that the dimensions of perceived trustworthiness are orthogonal with different effects on the strength of tie and ultimately perceived performance. This means that entrepreneurs and advisors should consider the specific dimensions of ability, benevolence and integrity, rather than rely on general perceptions of trustworthiness in their advice relationships.

Sustainable subdivisions – ventilation data analysis

This project, as part of a broader Sustainable Sub-divisions research agenda, addresses the role of natural ventilation in reducing the use of energy required to cool dwellings

Looking through the haze of discontent : smokers as a data source

In the case of industrial relations research, particularly that which sets out to examine practices within workplaces, the best way to study this real-life context is to work for the organisation. Studies conducted by researchers working within the organisation comprise some of the (broad) field’s classic research (cf. Roy, 1954; Burawoy, 1979). Participant and non-participant ethnographic research provides an opportunity to investigate workplace behaviour beyond the scope of questionnaires and interviews. However, we suggest that the data collected outside a workplace can be just as important as the data collected inside the organisation’s walls. In recent years the introduction of anti-smoking legislation in Australia has meant that people who smoke cigarettes are no longer allowed to do so inside buildings. Not only are smokers forced outside to engage in their habit, but they have to smoke prescribed distances from doorways, or in some workplaces outside the property line. This chapter considers the importance of cigarette-smoking employees in ethnographic research. Through data collected across three separate research projects, the chapter argues that smokers, as social outcasts in the workplace, can provide a wealth of important research data. We suggest that smokers also appear more likely to provide stories that contradict the ‘management’ or ‘organisational’ position. Thus, within the haze of smoke, researchers can uncover a level of discontent with the ‘corporate line’ presented inside the workplace. There are several aspects to the increased propensity of smokers to provide a contradictory or discontented story. It may be that the researcher is better able to establish a rapport with smokers, as there is a removal of the artificial wall a researcher presents as an outsider. It may also be that a research location physically outside the boundaries of the organisation provides workers with the freedom to express their discontent. The authors offer no definitive answers; rather, this chapter is intended to extend our knowledge of workplace research through highlighting the methodological value in using smokers as research subjects. We present the experience of three separate case studies where interactions with cigarette smokers have provided either important organisational data or alternatively a means of entering what Cunnison (1966) referred to as the ‘gossip circle’. The final section of the chapter draws on the evidence to demonstrate how the community of smokers, as social outcasts, are valuable in investigating workplace issues. For researchers and practitioners, these social outcasts may very well prove to be an important barometer of employee attitudes; attitudes that perhaps cannot be measured through traditional staff surveys.

Preliminary report on data mining techniques for life prediction

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source. In the initial software, no attempt was made to choose between the results offered or construct a case for retention in the casebase. In this phase of the project, alternative data mining techniques will be explored and evaluated. A process for selecting a unique service life prediction for each query will also be investigated. This report summarises the initial evaluation of several data mining techniques.

Report : school survey to collect data on material performance

A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.

Final Report : learning system for life prediction of infrastructure

The project has further developed two programs for the industry partners related to service life prediction and salt deposition. The program for Queensland Department of Main Roads which predicts salt deposition on different bridge structures at any point in Queensland has been further refined by looking at more variables. It was found that the height of the bridge significantly affects the salt deposition levels only when very close to the coast. However the effect of natural cleaning of salt by rainfall was incorporated into the program. The user interface allows selection of a location in Queensland, followed by a bridge component. The program then predicts the annual salt deposition rate and rates the likely severity of the environment. The service life prediction program for the Queensland Department of Public Works has been expanded to include 10 common building components, in a variety of environments. Data mining procedures have been used to develop the program and increase the usefulness of the application. A Query Based Learning System (QBLS) has been developed which is based on a data-centric model with extensions to provide support for user interaction. The program is based on number of sources of information about the service life of building components. These include the Delphi survey, the CSIRO Holistic model and a school survey. During the project, the Holistic model was modified for each building component and databases generated for the locations of all Queensland schools. Experiments were carried out to verify and provide parameters for the modelling. These included instrumentation of a downpipe, measurements on pH and chloride levels in leaf litter, EIS measurements and chromate leaching from Colorbond materials and dose tests to measure corrosion rates of new materials. A further database was also generated for inclusion in the program through a large school survey. Over 30 schools in a range of environments from tropical coastal to temperate inland were visited and the condition of the building components rated on a scale of 0-5. The data was analysed and used to calculate an average service life for each component/material combination in the environments, where sufficient examples were available.

Report : wireless data throughput testing on a mobile device using WiFi and GPRS

This project report presents the results of a study on wireless communication data transfer rates for a mobile device running a custombuilt construction defect reporting application. The study measured the time taken to transmit data about a construction defect, which included digital imagery and text, in order to assess the feasibility of transferring various types and sizes of data and the ICT-supported construction management applications that could be developed as a consequence. Data transfer rates over GPRS through the Telstra network and WiFi over a private network were compared. Based on the data size and data transfer time, the rate of transfer was calculated to determine the actual data transmission speeds at which the information was being sent using the wireless mobile communication protocols. The report finds that the transmission speeds vary considerably when using GPRS and can be significantly slower than what is advertised by mobile network providers. While WiFi is much faster than GPRS, the limited range of WiFi limits the protocol to residential-scale construction sites.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Nonfatal heroin overdoses in Queensland, Australia : an analysis of ambulance data

In the past decade, the utilization of ambulance data to inform the prevalence of nonfatal heroin overdose has increased. These data can assist public health policymakers, law enforcement agencies, and health providers in planning and allocating resources. This study examined the 672 ambulance attendances at nonfatal heroin overdoses in Queensland, Australia, in 2000. Gender distribution showed a typical 70/30 male-to-female ratio. An equal number of persons with nonfatal heroin overdose were between 15 and 24 years of age and 25 and 34 years of age. Police were present in only 1 of 6 cases, and 28.1% of patients reported using drugs alone. Ambulance data are proving to be a valuable population-based resource for describing the incidence and characteristics of nonfatal heroin overdose episodes. Future studies could focus on the differences between nonfatal heroin overdose and fatal heroin overdose samples.

Benchmarks for recycling practices in commercial office building refurbishment : data collection challenges

In recent years considerable effort has gone into quantifying the reuse and recycling potential of waste generated by residential construction. Unfortunately less information is available for the commercial refurbishment sector. It is hypothesised that significant economic and environmental benefit can be derived from closer monitoring of the commercial construction waste stream. With the aim of assessing these benefits, the authors are involved in ongoing case studies to record both current standard practice and the most effective means of improving the eco-efficiency of materials use in office building refurbishments. This paper focuses on the issues involved in developing methods for obtaining the necessary information on better waste management practices and establishing benchmark indicators. The need to create databases to establish benchmarks of waste minimisation best practice in commercial construction is stressed. Further research will monitor the delivery of case study projects and the levels of reuse and recycling achieved in directly quantifiable ways

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

What value do users derive from social network applications?

Research on social networking sites like Facebook is emerging but sparse. This exploratory study investigates the value users derive from self-described ‘cool’ Facebook applications, and explores the features that either encourage or discourage users to recommend applications to their friends. The concepts of value and cool are explored in a social networking context. Our qualitative data reveals consumers derive a combination of functional value along with either social or emotional value from the applications. Female Facebook users indicate self-expression as important motivators, while males tend to use Facebook applications to socially compete. Three broad categories emerged for application features; symmetrical features can both encourage or discourage recommendation, polar features where different levels of the same feature encourage or discourage, and uni-directional features only encourage or discourage but not both. Recommending or not recommending an application tends to be the result of a combination of features and context, rather than one feature in isolation.

Strongly Secure Certificateless Key Agreement

We introduce a formal model for certificateless authenticated key exchange (CL-AKE) protocols. Contrary to what might be expected, we show that the natural combination of an ID-based AKE protocol with a public key based AKE protocol cannot provide strong security. We provide the first one-round CL-AKE scheme proven secure in the random oracle model. We introduce two variants of the Diffie-Hellman trapdoor the introduced by \cite{DBLP:conf/eurocrypt/CashKS08}. The proposed key agreement scheme is secure as long as each party has at least one uncompromised secret. Thus, our scheme is secure even if the key generation centre learns the ephemeral secrets of both parties.