Fieldwork/data collection is one of the most important parts in the research process, and it is particularly important for social sciences research. A number of aspects that need to be considered by a researcher before starting data collection include: ethical permission from the concerned ethical body/committee, informed consent, contract with different stakeholders, field settings, time allocation and time management, field leading, data collection, contextual and cultural diversities, community settings, socioeconomic and psychological patterns of the community, political pattern, rapport building between data collectors and respondents, permission to access community, language and mode of data collection, power relations, role of gatekeepers, privacy and confidentiality issues, layers of expectations among researchers/respondents/ funding organization, data recording (written, memorization, voice recording and video recording), and so on. Many aspects are very difficult to understand before going into the field. Sometimes, a researcher’s previous experience about a particular community may help to gain field access, but it may be difficult to assess the field in advance due to rapid changes within people’s livelihoods and other shifts in the community. The change of a political paradigm sometimes seems also to be a challenge at the field level. We believe that although technological innovation has benefited some aspects of the data collection of fieldwork in social research, many other dimensions (mentioned above) of fieldwork endure unchanged.
Browse by title
M. Rezaul Islam, Niaz Ahmed Khan, Siti Hajar Abu Bakar Ah, Haris Abd Wahab and Mashitah Binti Hamidi
Understanding migration patterns and how they change over time has important implications for understanding broader population trends, effectively designing policy and allocating resources. However, data on migration movements are often lacking, and those that do exist are not produced in a timely manner. Social media data offer new opportunities to provide more up-to-date demographic estimates and to complement more-traditional data sources. Facebook, for example, can be thought of as a large digital census that is regularly updated. However, its users are not representative of the underlying population, thus using the data without appropriate adjustments would lead to biased results. This chapter discusses the use of social media advertising data to estimate migration over time. A statistical framework for combining traditional data sources and the social media data is presented, which emphasizes the importance of three main components: adjusting for non-representativeness in the social media data; incorporating historical information from reliable demographic data; and accounting for different errors in each data source. The framework is illustrated through an example that uses data from Facebook’s advertising platform to estimate migrant stocks in North America.
This comprehensive Handbook brings together practical advice from leading international practitioners in sustainable tourism. This guidance is not designed as a guide for long-term academic projects, but instead applies good research design principles within the parameters of modest timeframes and resources, to provide workable and rational step-by-step approaches to researching real-life challenges. The book’s contributors unpack how to undertake environmental, socio-cultural and economic assessments that establish the feasibility for new tourism ventures, or ascertain what impacts they have had over time. The book covers fundamentals for practitioners, such as how to conduct feasibility studies and business plans, and also addresses hot topics such as visitor management and overcrowding. The processes of transferring knowledge from academic research into practical applications are also addressed. This Handbook is critical for researchers at all levels, and particularly to those working within government institutions responsible for tourism and private tourism businesses. It is also an invaluable resource for practitioners, not-for-profit organizations and consultants that provide technical support in the planning, feasibility, development, operation and evaluation of sustainable tourism.
Professor Eve Mitleton-Kelly
Is it possible to effectively address complex problems when there are multiple and often conflicting interests, as well as multiple interacting causalities, within a constantly changing and complex environment? The analysis of such problems often results in an endless list of often contradictory factors and provides a picture with no linear causality and no overall coherent meaning, too random to help explain the complex interactions that led to the problem. Understanding not only the characteristics of organisations with their multiple interacting issues and causalities, but their co-evolutionary dynamics is the key here. This chapter provides detailed advice on how to use the complexity perspective in real life examples showing how the two parts of the EMK methodology were used in a challenging context. The first part was the identification of the multi-dimensional problem space and the co-evolutionary dynamics between the multiple dimensions, which provided a starting point for decision-making. The second part acknowledged that complex problems do not have single solutions, but need a broader enabling environment, capable of addressing the challenge over time as it changes and evolves.
Professor Michael E. Wolf-Branigin, Dr William G. Kennedy, Dr Emily S. Ihara and Dr Catherine J. Tompkins
Human services planners and evaluators require an increasing high level of flexibility and adaptability to remain effective in measuring the effectiveness of social interventions. Understanding the logic and assessing the impact behind the intervention can be difficult because commonly-used evaluative tools are based primarily on linear methods that assume that a set amount of input, throughput, and output will result in a set outcome. This chapter takes a complexity science approach and facilitates the use of agent-based modelling (ABM). It provides the requisite background for evaluators and researchers to frame their efforts as complex adaptive systems. These systems have several components that include agents having options, boundaries, self-organising behaviour, different options from which to choose, feedback to adapt, and an emergent behaviour. Complexity is viewed as a mathematical field where the relations between inputs and are better understood through simulations. Both qualitative and quantitative aspects of complexity are addressed through two applications of ABM that consider related social policy issues.
Associate Professor Benyamin Lichtenstein
Complexity science has been described as an amalgam of ‘models, methods, and metaphors’ for understanding dynamic systems. Methods most commonly associated with complexity are computational simulations. Although these have contributed greatly to organization, they represent just one category of complexity methods. A main goal of this chapter is to introduce what the author considers to be the 15 sciences of complexity, organized into three main paradigms or approaches: computational agent-based modelling; natural sciences and idiographic analogies; and, narrative and multi-method studies. The chapter presents a set of complexity methods and models that may be much broader than the norm. Researchers can use these to help identify the appropriate complexity methods to use to answer a specific research question. The value of this is underlined by many scholars who argue that the choice of a research method should be based on the kind of question being asked, rather than the method most familiar to the researcher.
Julian Burton and Sam Mockett
This chapter looks at the use of visual representations of organisational strategy in combination with facilitated dialogue (’Visual Dialogue’) as a complexity-inspired tool for culture change and organisational development. The process creates spaces for employees and leaders to come together to make sense of what is happening, what needs to change, and what actions are required. At the operational level, the process helps shift the way people talk about change and, as a result, enables the change process to become more meaningful, engaging and effective. We describe some of the cultural challenges of turning strategy into action and show how we have used the Visual Dialogue process as an Organisational Development intervention to address some of the key aspects of these challenges. Finally, we describe the component parts of Visual Dialogue and how each contributes to creating such enabling environments and supporting emergent change.