Investigating Information Systems with Action Research

Action research is an established research method in use in the social and medical sciences since the mid-twentieth century, and has increased in importance for information systems toward the end of the 1990s. Its particular philosophic context is couched in strongly post-positivist assumptions such as idiographic and interpretive research ideals. Action research has developed a history within information systems that can be explicitly linked to early work by Lewin and the Tavistock Institute. Action research varies in form, and responds to particular problem domains. The most typical form is a participatory method based on a five-step model, which is exemplified by published IS research

Cognitive Control of Escape Behaviour

When faced with potential predators, animals instinctively decide whether there is a threat they should escape from, and also when, how, and where to take evasive action. While escape is often viewed in classical ethology as an action that is released upon presentation of specific stimuli, successful and adaptive escape behaviour relies on integrating information from sensory systems, stored knowledge, and internal states. From a neuroscience perspective, escape is an incredibly rich model that provides opportunities for investigating processes such as perceptual and value-based decision-making, or action selection, in an ethological setting. We review recent research from laboratory and field studies that explore, at the behavioural and mechanistic levels, how elements from multiple information streams are integrated to generate flexible escape behaviour

Selecting a Suitable Methodology for Designing Innovative Solutions to Support Capability Improvement in a Complex Organisational Context as part of an Industry- Academic Collaboration

This paper describes the process of investigating a number of different research methodologies in order to select a suitable approach for an effective Industry-Academic collaborative research project. The research project in question is a 15-month research partnership between a global financial organisation and a research team from a university institute. The aim is to collaboratively design innovative solutions to support the company’s programme to improve their Information Technology (IT) capabilities using the IT Capability Maturity Framework (IT-CMF). A number of potential approaches were investigated, including Action Research (AR), Canonical Action Research (AR), Design Science Research (DSR), Design Thinking/User Experience (UX) and Action Design Research (ADR). Having discussed these approaches, this paper then explains why ADR was chosen as the approach for this project and examines its validity in practice throughout the first half of the project. The key contribution of this paper is a critical discussion of a decision-making process around methodology selection in a current Industry-Academic research project that aims to produce innovative solutions based on an organisational intervention. This problem is relevant to any discipline that engages in Industry-Academic collaboration, particularly with regard to socio-technical problems, including, for example, Information Systems (IS), Management and Organisation Studies

Improving the triple bottom line returns from smallholder tree farms in the Philippines: A systems approach

This paper outlines the application of Systems Thinking in investigating ways to improve the returns to smallholder tree farmers in the Philippines. The paper illustrates how a systems approach was used in the conceptualisation of the project and how systems thinking facilitated a shared understanding of the how each individual’s research contributed to the broader project activities. Systems Thinking has also been used in the design and implementation of various project activities. Three examples are provided. The first example illustrates how a systems diagram was developed which outlined the direct and indirect linkages between biophysical data on tree farms and various activities designed to increase returns. The second example illustrates how the suggested approach for improving the flow of information concerning tree registration, harvest and transportation regulations and approval mechanisms link with various project activities and have been informed by a series of action research workshops. The third example illustrates how systems thinking has also been applied to understand the factors affecting the production of high quality tree seedlings and to investigate the effect of policy interventions on improving the quality of seedlings available to smallholders

Improving the triple bottom line returns from smallholder tree farms in the Philippines: A systems approach

This paper outlines the application of systems thinking in investigating ways to improve the returns to smallholder tree farmers in the Philippines. The paper illustrates how a systems approach was used in the conceptualisation of the project and how systems thinking facilitated a shared understanding of the how each individual’s research contributed to the broader project activities. Systems thinking has also been used in the design and implementation of various project activities. Three examples are provided. The first example illustrates how a systems diagram was developed which outlined the direct and indirect linkages between biophysical data on tree farms and various activities designed to increase returns. The second example illustrates how the suggested approach for improving the flow of information concerning tree registration, harvest and transportation regulations and approval mechanisms link with various project activities and have been informed by a series of action research workshops. The third example illustrates how systems thinking has been applied to understand the factors affecting the production of high quality tree seedlings and to investigate the effect of policy interventions on improving the quality of seedlings available to smallholders

Engaged Problem Formulation in IS Research

“Is this the problem?”: the question that haunts many information systems (IS) researchers when they pursue work relevant to both practice and research. Nevertheless, a deliberate answer to this question requires more than simply asking the involved IS practitioners. Deliberately formulating problems requires a more substantial engagement with the different stakeholders, especially when their problems are ill structured and situated in complex organizational settings. On this basis, we present an engaged approach to formulating IS problems with, not for, IS practitioners. We have come to understand engaged problem formulation as joint researching and as the defining of contemporary and complex problems by researchers and those practitioners who experience and know these problems. We used this approach in investigating IS management in Danish municipalities. In this paper, we present the approach to formulating problems in an engaged way. We discuss it in relation to ideas and assumptions that underpin engaged scholarship, and we discuss the implications for IS action research, design science research, and mixed approaches

A review of UK research and development for organic food and farming

The objective of the project is to draw together information on current levels of funding for organic research throughout all UK public sector, private and charitable sources. A list of 268 potential organic food and farming research funders and contractors throughout the UK was drawn together and questionnaires were mailed to them in the week of 24th February 2003. With regular follow up of all recipients to achieve the best return rate possible a response rate of 41% was achieved. We asked for details on all projects that were ongoing in the period between Jan 2000 and March 2003. The survey identified 168 individual projects. The total cost of this research was £23,578,902 of which nearly £20M was solely from the public purse with 72 per cent of this funding provided by DEFRA. However, nearly £3M was funded by sources other than the public purse including a range of charities and companies. There was also £0.75M of joint funding by public and non-public sources. Of the 168 projects 151 were purely organic with a further 17 of relevance to organic systems. The majority of the research undertaken was field or bench research followed by desk studies. The overwhelming majority of the research undertaken had been covering aspects of production. Whole farm systems, soils & nutrient cycling, cropping and livestock systems accounted for nearly 70 per cent of the total funding. There were also a surprisingly small number of projects investigating the environment (8 projects) and funding only accounted for about 8 per cent of the total spend, although environmental considerations would be investigated in other topic areas such as soils & nutrient cycling. The amount of research undertaken on off-farm activities in the organic food production chain was limited. Only a small amount of research had been directed at processing, marketing or food quality. These three areas accounted for only 12 projects and 7 per cent of the total funding. Understanding the other (non-environmental) benefits or disbenefits of organic farming have also been studied to a lesser extent. Only six Economics and rural development projects have been undertaken and account for only 4 per cent of the total funding. It is recommended that DEFRA and the Organic Action Plan Group: • Establish an Organic Research Priorities Board (ORPD) to work with all stakeholders including funders to ensure identification and a co-ordinated implementation of the research and technology transfer necessary to help achieve the objectives of the Action Plan. It would then be appropriate for DEFRA , the Organic Action Plan Group and/or the ORPD to intiate; • A consultation on organic R&D priorities, particularly focussing on the needs of the businesses that may be willing to participate in LINK or other joint funded projects. • Further assessment of the benefit arising from the projects identified. • Analysis of the intensity of research and the value to the end user (government, farmers, processors etc.) from the point of view of the priority research areas (crops, livestock etc) and the different types of research and development (desk, field, extension etc.). This should aim to define the most beneficial approach to organic research and development. • Analysis of the quality and extent of the dissemination of the research results from the projects. • An investigation into the possible conflict between organic research funding and the objectives and approaches of LINK programmes need to be addressed and if a real barrier is identified a solution must be found. However, it is believed that it is important that research continues directed towards improving production methods and efficiency (financially, socially and environmentally) in those enterprises where the technical challenges are greatest or where the proportion of UK sourced farm products is relatively low

The Generation of Qualitative Data in Information Systems Research: The Diversity of Empirical Research Methods

This paper investigates the concept of data collection in information systems qualitative research. In this text, I replace the term “data collection” with “data generation” to emphasize that the researcher arranges situations that produce rich and meaningful data for further analysis. Data generation comprises activities such as searching for, focusing on, noting, selecting, extracting, and capturing data. This paper analyzes and compares a repertoire of empirical research methods for generating qualitative data. It describes and visualizes (through a common data-generation template) 12 research methods: interviewing, questionnaire study, document study, artifact study, observation study, participant observation, intervention study, practice-based design study, lab-based design study, focus group study, test study, and self-reporting. I compare these data-generation methods according to 1) the researcher’s role in data generation, 2) data generation’s influence on everyday life reality, 3) each data-generation method’s relationship to everyday life reality, 4) what parts/mediators of everyday life reality each data-generation method addresses, 5) the expected value of generated data and 6) possible shortcomings in generated data. As a basis for investigating data generation, I ontologically clarify (based on a practice-theoretical perspective) the empirical landscape of information systems (the kinds of phenomena and sources of data that exist). A concluding discussion contains 1) analyses concerning relationships between data-generation methods and compound research methods/strategies such as case study research, action research, and design science research and 2) the role of interpretation in data generation versus data analysis

Using Travel Simulation to Investigate Driver Response to In-Vehicle Route Guidance Systems,

A major application for developed satellite navigation systems is the in-vehicle route guidance market. As systems become cheaper to purchase and easier to install and indeed car manufacturers begin to fit the equipment as standard in new vehicles, the potential market for such systems in the developed world is massive. But what are the consequences of giving navigational assistance to car drivers? How will drivers respond to this information? Such information is liable to have a big impact upon driver route choice behaviour and is also subject to their interpretation of the guidance and action upon receiving it. This response may change under different travel circumstances. The impact of collective response to driver guidance is also of importance to traffic engineers and city planners, since routing through environmentally sensitive areas or heavily congested corridors should be avoided. The overall network effects are therefore of key importance to ensure efficient routing and minimal disruption to the road network. It is quite difficult to observe real-life behaviour on a consistent basis, since there are so many confounding variables in the real-world, traffic is never the same two days running, let alone hour by hour and a rigorous experimental environment is required, since control of experimental conditions is paramount to being able to confidently predict driver behaviour in response to navigational aids. Also the take up of guidance systems is still in its infancy, so far available only to a niche market of specialist professionals and those with disposable income. A need to test the common publics’ response to route guidance systems is therefore required. The development of travel simulation techniques, using portable computers and specialist software, gives robust experimental advantages. Although not totally realistic of the driving task, these techniques are sufficient in their realism of the decision element of route selection, enough to conduct experimental studies into drivers’ route choice behaviour under conditions of receiving simulated guidance advice. In this manner driver response to in-vehicle route guidance systems can be tested under a range of hypothetical journey making travel scenarios. This paper will outline the development of travel simulation techniques as a tool for in-vehicle route guidance research, including different methods and key simulation design requirements. The second half of the paper will report in detail on the findings from a recently conducted experiment investigating drivers’ response to route guidance when in familiar and unfamiliar road networks. The results will indicate the importance of providing meaningful information to drivers under these two real-life circumstances and report on how demands for route guidance information may vary by type of journey. Findings indicate that the guidance acceptance need not only depend on the optimum route choice criteria, it is also affected by network familiarity, quality and credibility of guidance advice and personal attributes of the drivers

Cognitive Control of Escape Behaviour

When faced with potential predators, animals instinctively decide whether there is a threat they should escape from, and also when, how, and where to take evasive action. While escape is often viewed in classical ethology as an action that is released upon presentation of specific stimuli, successful and adaptive escape behaviour relies on integrating information from sensory systems, stored knowledge, and internal states. From a neuroscience perspective, escape is an incredibly rich model that provides opportunities for investigating processes such as perceptual and value-based decision-making, or action selection, in an ethological setting. We review recent research from laboratory and field studies that explore, at the behavioural and mechanistic levels, how elements from multiple information streams are integrated to generate flexible escape behaviour