A typology of the interaction between research nature and analytical techniques: reflections on methodologies in social science research

The Special Feature led by Sutherland, Dicks, Everard, and Geneletti (Methods Ecology and Evolution, 9, 7–9, 2018) sought to highlight the importance of “qualitative methods” for conservation. The intention is welcome, and the collection makes many important contributions. Yet, the articles presented a limited perspective on the field, with a focus on objectivist and instrumental methods, omitting discussion of some broader philosophical and methodological considerations crucial to social science research. Consequently, the Special Feature risks narrowing the scope of social science research and, potentially, reducing its quality and usefulness. In this article, we seek to build on the strengths of the articles of the Special Feature by drawing in a discussion on social science research philosophy, methodology, and methods. We start with a brief discussion on the value of thinking about data as being qualitative (i.e., text, image, or numeric) or quantitative (i.e., numeric), not methods or research. Thinking about methods as qualitative can obscure many important aspects of research design by implying that “qualitative methods” somehow embody a particular set of assumptions or principles. Researchers can bring similar, or very different, sets of assumptions to their research design, irrespective of whether they collect qualitative or quantitative data. We clarify broad concepts, including philosophy, methodology, and methods, explaining their role in social science research design. Doing so provides us with an opportunity to examine some of the terms used across the articles of the Special Feature (e.g., bias), revealing that they are used in ways that could be interpreted as being inconsistent with their use in a number of applications of social science. We provide worked examples of how social science research can be designed to collect qualitative data that not only understands decision‐making processes, but also the unique social–ecological contexts in which it takes place. These examples demonstrate the importance of coherence between philosophy, methodology, and methods in research design, and the importance of reflexivity throughout the research process. We conclude with encouragement for conservation social scientists to explore a wider range of qualitative research approaches, providing guidance for the selection and application of social science methods for ecology and conservation.

The computer software known as SPSS has gained significant importance in the realm of social science research since its beginnings. The primary goal of SPSS Inc. is to enhance the functionality and usability of the SPSS software. SPSS offers researchers a proficient software platform for programming that enables successful execution of statistical analysis. However, some researchers inconsistently using the right methodology in social sciences research, especially a newcomer from pure sciences. The reason why newcomer researchers, especially those from pure sciences, may not use the right methodology of social science can be attributed to several factors. This study aimed to refine the recent utilisation of IBM SPSS Statistics in social science research. IBM SPSS Statistics is important in social science research for several reasons: (a) data analysis; (b) data management; (c) descriptive and inferential statistics; (d) visualization and reporting; and (e) accessibility and user-friendliness. This study suggests that, IBM SPSS Statistics is widely recognised as a prevalent computer software utilised for statistical analysis inside the realm of social sciences. The software's high level of comprehensiveness and its user-friendly interface contribute to its popularity among users. It is recommended that future research in the realm of social sciences consider including this software, particularly in studies employing survey methodologies.

From mobile phones and laptop computers to in vitro fertilization and social networks on the Internet, technological devices, products and services are increasingly shaping the lives of people around the world. The pervasiveness of technology and the underlying science that makes it possible has led to a certain ambivalence: most people trust that ‘science’ will eventually help them to live longer, healthier and happier lives. However, they also feel increasingly uncomfortable about certain new technologies, often those that challenge or improve on ‘nature’. Genetically modified crops, gene therapy, stem cell research, cloning, renewed interest in nuclear power: the list of controversial topics involving science and technology is growing steadily and debates on these topics regularly occupy centre stage in public and political arenas. > …the research process itself constitutes a largely overlooked opportunity for addressing social concerns Policy‐makers have responded by calling for increased attention to be paid to the ethical, legal and social aspects of scientific research and technological developments. In particular, new and emerging areas of research—such as genomics, synthetic biology and nanotechnology—have been accompanied by studies of their broader societal implications as well as public‐engagement efforts, in order to guide research and development in ways that respect societal concerns. Such attempts to shape technological trajectories have traditionally occurred both before scientific research, for example, through research policy, technology assessment or public participation, and afterwards, through regulations or market mechanisms. Although these stages are crucial points at which to intervene, the research process itself constitutes a largely overlooked opportunity for addressing social concerns. Indeed, if one acknowledges the central role that scientific research has in the innovation process, this is an area well worth examining. Shaping technological trajectories will, at some point, include shaping the very research processes that help to characterize them (Fisher et al , 2006). Social and …

Use of dimensional analysis in social science research

Methodological debates in the comparative studies field have become polarized. On the one hand, philosophers such as Winch, Quine and Louch have argued for different reasons that scientific method is inappropriate for social science research. Winch (1958) rules out the possibility of cross-cultural comparison, claiming that outside observers are unable to understand the meaning of rule-governed behaviour, which is dependent on the motives, reasons and decisions of participants in a particular society or culture. Quine's 'translational indeterminacy' thesis implies that equivalence of meaning across cultures is impossible. Louch (1969) argues that observer values will inevitably preclude objective scientific investigation, since social science concepts are moral, not scientific, and that generalization is precluded in any case because activity occurs in such varied contexts. On the other hand, it has been maintained that scientific method in comparative research is conditionally possible, given improved accuracy of measurement (Deutsch 1966), testing of the equivalence of meaning (Levison 1974), or moving to an appropriate and lower level of generalization than scientific laws (MacIntyre 1971). Macintyre argues that the research questions should ask what functions institutions serve in the culture, rather than, as Winch suggests, what institutions mean for participants. With such a move from a subjective towards an objective frame of reference, theory-building becomes possible. The views which support scientific method in social science research are persuasive on both philosophical and practical grounds. Those philosophers who argue that comparative research is impossible, have not only produced incomplete evidence and flawed argument, they have failed to notice that the gap between natural and social science is in practice far narrower than in theory: natural science is subject to uncertainty, based on the difficulty of disentangling causal chains and on the variability of observer perceptions, which is quantitatively, but not qualitatively, different from the uncertainty of social science research. Polarization seems endemic in social science methodology: fact vs meaning; structuralism vs phenomenology; quantitative vs qualitative method. Such debates are likely to continue. Therefore,

The study is an attempt to explain why Public Relations strategy is an effective avenue to tackle electoral malfeasance in Nigeria. The Nigerian Presidential Campaign of 2015 election with specific reference to the People’s Democratic Party (PDP) candidate presented a ready case study for an analysis. The paper is a public relations analysis aimed at identifying public relations strategy adopted by the PDP’s presidential campaign team and evaluate success and failure including factors responsible for it in the 2015 election. The conceptual framework adopted is SWOT analysis which forms the background for the public relations strategy and method adopted is Analysis, i.e. in-depth study of the Public Relations Strategy. The paper identified that PDP relied on SWOT analysis model instead of detailed social scientific empirical research. The PDP presidential campaign failure arose from over-reliance on strengths and opportunities which resulted to a bunker mentality and dependence on electoral malfeasance. The paper recommends that politicians and political parties rely on experts in social scientific empirical research to direct campaign public relations strategy to avoid reliance on electoral malfeasance among others. The paper demonstrates the weakness and problems arising from sole dependence on SWOT analysis. It is a subjective and depends on individual interpretation. It highlights the need for Nigerian politicians and political parties to rely more on social scientific empirical research to direct public relations strategy in electoral campaign. This paper demonstrates the need for a social scientific research, electoral campaign driven to combat electoral malfeasance in Nigeria.

The presented paper is methodical in character. Marketing methodology is an important matter looking from the prism of identifying its scientific status. There are differing views on the scientific status of marketing, nevertheless marketing, from the perspective of scientific cognition, has developed dynamically throughout its entire history. The main objective of this article is to present the methodological dilemmas of marketing in the context of social and economic sciences.The foundations of the methodology of research on marketing cannot be separated from the methodology of social sciences. Marketing belongs to social sciences, so it is based on similar assumptions with regard to the character of reality and scientific cognition. Marketing is engaged in exploring human behaviour and, similarly to other social sciences, makes use of such research methods and techniques. It is difficult to conduct research in the area of marketing without referring to the methodology of social sciences.The article presents the foundations of marketing research methodology, assumptions of the analysis of methodology of research on marketing in comparison to methodology of social and economic research and final remarks.

Since its inception in February 2005, Methodology, the official journal of the European Association of Methodology, has been an online journal with a strong European vocation and dedication ‘‘to promote research and the development of empirical research methods in the fields of behavioral, social, educational, health and economic sciences, as well as in the field of evaluation research’’ (Ato & Eid, 2005; Ato & Hox, 2009). In 2009, the then editors of Methodology, Manuel Ato and Joop Hox, wrote an editorial in which they looked back at the first 4 years of Methodology (Ato & Hox, 2009). Now, 6 years later, two different editors, Peter Lugtig of Utrecht University and Nekane Balluerka of the University of the Basque Country, have taken over the editorship of Methodology. As Methodology celebrates its 10th birthday, it is time to look back and forward. Just like the editors before us, we firmly believe that the methodology underpinning the social sciences has many similarities across disciplines. Any differences between the sciences mostly reflect differences in the type of research questions asked, in research designs and data analysis practices, and in historical developments. Many of the articles published in Methodology have taken a cross-disciplinary perspective and many of the developments in social science methodology are similar across disciplines. A large number of articles in Methodology have explored the methodology of the Generalized Linear Model (Schweizer, 2010; Voelkle & McKnight, 2012). Simulation studies have, for example, focused on the properties of multilevel models (Bell, Morgan, Schoeneberger, Kromrey, & Ferron, 2014; Pacagnella, 2011). Latent variables in general, and how to model the measurements, is probably the topic that has been written about most, whether in the context of psychometrics (Balluerka, Plewis, Gorostiaga, & Padilla, 2014; Botella & Suero, 2012; Gonzalez-Betanzos & Abad, 2012), or of factor analysis to estimate equivalence across groups (Kankaras & Moors, 2011; Lugtig, Boeije, & Lensvelt-Mulders, 2012; Steinmetz, 2013). Other articles dealing with data collection methods have often focused on comparing different approaches to deal with violations of model assumptions (Blanca, Arnau, Lopez-Montiel, Bono, & Bendayan, 2013; Haupt, Losel, & Stemmler, 2014; Schmider, Ziegler, Danay, Beyer, & Buhner, 2010; Wolff Smith, & Beretvas, 2014). Apart from methodological advances in the field of data analysis, another development in social science research methodology is the availability of software tools. Here, a number of articles have discussed methods to implement new statistical modeling methodologies in software packages (e.g., Flora, 2011; Grilli & Variale, 2014). We envisage that in the coming years developments in this field of research will continue. The growing possibilities in terms of statistical modeling will increase demand for articles explaining which model should be used when, and how. For this reason, future issues of Methodology will feature a section with tutorial articles which show how to implement statistical modeling techniques in widely used software packages. To ensure such articles can be used by applied social science researchers, we will publish the data and code accompanying these articles. It is our continuing goal to feature special thematic issues edited by prominent researchers in their field. Since 2009, four special issues have been published. In 2009, Michael Eid and Fridtjof Nussbeck edited an issue to celebrate the 50th anniversary of the multitrait-multimethod matrix (Eid & Nussbeck, 2009). In 2010, Elmar Schlueter and Peter Schmidt provided an issue on ‘‘survey experiments’’ (Schlueter & Schmidt, 2010), while in the same year Andries Van der Ark and Jeroen Vermunt edited an issue on ‘‘new developments in missing data analysis’’ (Van der Ark & Vermunt, 2010). In 2013, Gordon Willis and Hennie Boeije contributed a special issue on the ‘‘systematic reporting of questionnaire development and pretesting’’ (Willis & Boeije, 2013). Readers of Methodology

BackgroundThe level of funding provides a good proxy for the level of commitment or prioritisation given to a particular issue. While the need for research relevant to social, economic, cultural and behavioural aspects of neglected tropical diseases (NTD) control has been acknowledged, there is limited data on the level of funding that supports NTD social science research.MethodA case study was carried out in which the spending of a major independent funder, the Bill and Melinda Gates Foundation (BMGF) - was analysed. A total of 67 projects funded between October 1998 and November 2008 were identified from the BMGF database. With the help of keywords within the titles of 67 grantees, they were categorised as social science or non-social science research based on available definition of social science. A descriptive analysis was conducted.ResultsOf 67 projects analysed, 26 projects (39%) were social science related while 41 projects (61%) were basic science or other translational research including drug development. A total of US$ 697 million was spent to fund the projects, of which 35% ((US$ 241 million) went to social science research. Although the level of funding for social science research has generally been lower than that for non-social science research over 10 year period, social science research attracted more funding in 2004 and 2008.ConclusionThe evidence presented in this case study indicates that funding on NTD social science research compared to basic and translational research is not as low as it is perceived to be. However, as there is the acute need for improved delivery and utilisation of current NTD drugs/technologies, informed by research from social science approaches, funding priorities need to reflect the need to invest significantly more in NTD social science research.

Peter Piot (Executive Director of UNAIDS) challenged Bangkok International AIDS Conference attendees to think ahead 10 years or more so we will be prepared to meet the challenges that will face us [1]. Over this next decade, many formidable challenges are likely to stem from the interactions of social, ecological, political, and economic change; existing social structures; the changing HIV epidemic, and changes produced by emerging biomedicine and viral evolution. Although some challenges will be unpredictable, we should plan ahead for those we are able to anticipate. This paper identifies important social research issues regarding the changing global epidemic so funding agencies, journal editors, social science communities, individual researchers and students, non-governmental organizations, communitybased organizations, and the general public can debate them and, hopefully, act on them.

This comment is approached with some trepidation. My eclectic background does not allow me the peace of mind I might have if I had arrived at this point in my life with a more connected or cohesive history. I therefore approach this review from at least three perspectives: (i) as a sociologist with training in traditional social science research methods and methodology, (ii) as a lawyer with some experience prosecuting in provincial court, and (iii) as an academic who has recently dabbled in feminist legal methods and methodology, in law and the social sciences. The first two perspectives require assumptions about social science research and law; the third perspective challenges, questions, and debunks many of these assumptions. Whether there can be an integration of the third with the first or the second is the subject of much debate among feminist academics in, and between, the social sciences and law. At times it is unclear which perspective is influencing my comments, and so I slide from one to another and back again.

Research is key in the quest to enhance Africa’s development and to try to achieve the Sustainable Development Goals. Most research practice constructs in social sciences are predominantly well defined and constructed, but the research problem that is focused on with this study is that many authors hold different interpretations of certain key terms and concepts, causing a degree of confusion, overlap and uncertainty. The term ‘qualitative research’ is such a case in point. Not only does this concept show different interpretations by many authors, but there is also uncertainty about how this concept relates to exploratory research or other contemporary social research practice concepts. It is also unclear whether a longitudinal time horizon can be applied to qualitative research or related concepts. In order to provide a clear perspective on the above-mentioned dilemma, the authors recommend the application of the so-called social sciences research methodology framework, which follows Saunders, Lewis and Thornhill’s research ‘onion’ approach. In addition, the current coronavirus disease 2019 (COVID-19) necessitates thoughtful selection of data collection techniques and research methods. Therefore, and with the proposed framework as guide, the appropriate data collection techniques and research methods to be used during the pandemic are highlighted. The research employed was fundamental in nature. Inductive rational philosophical reasoning was used, and a theoretical analysis was applied through a systematic literature review of published text. In the end, the social sciences research methodology framework provides a unified understanding of most social sciences research constructs. This proposed framework provides an uncluttered and unambiguous guide to social sciences research methodology with relevant social sciences methodologies and constructs clearly positioned in a structured and simplistic way. The social sciences research methodology framework could be used as a tool in the evaluation of all academic work, thereby enabling various examiners to provide clear and unambiguous guidance to contributors and students alike. Also, the framework can be used as a guide to select appropriate data collection techniques and research methods to conduct research during COVID-19.

Research is inevitable for the professionals for their career growth and for the cause of the society. Research must be done in systemic and righteous manner so that it augments the understanding of the real problem and facilitates the solution of the problems under consideration. It is important to have a deep understanding of research methodology for pursuing research in Social Sciences. A field survey on awareness about research methodology involve conducting research directly by interviewing researchers/teachers/professionals/ students from different academic backgrounds and sectors to assess their understanding and knowledge of key research methodologies. Nowadays, research has become popular in all the fields because it supports in decision-making. The present research paper is based on a field survey conducted in some areas of district Yamuna Nagar, Haryana. The research aims to measure the overall level of awareness about research methodology and its various steps and components and to identify specific areas where knowledge gaps exist regarding different research methods. Targeted Sampling: Participants from diverse academic disciplines, such as social sciences, humanities, Commerce have been selected using random sampling. The students of postgraduate classes from different streams and different colleges were included in the sample. The field survey report finds that there is general awareness about research methodology and plagiarism. There is lack of detailed and technical k knowledge about research techniques. The survey recommends that more and more research methodology workshops must be organised to develop research skills of the students. They should be taught about act of plagiarism and the types of plagiarism. The curriculum can be designed in a way which encourages students to undertake research.

The knowledge economy requires that social science researchers start questioning the type of knowledge they are producing and the type of methods they are using to produce this knowledge. This chapter explains how the knowledge economy is linked to creativity, innovation, and qualitative research. This chapter aims specifically to highlight the need and importance of innovative research methodologies in a knowledge economy. Emerging innovative qualitative research methodologies in social sciences are briefly identified, and arguments for and against methodological innovation are explored. The stages of creativity and phases of innovation are highlighted in a research environment to show social science researchers that innovative research methodologies can be generated and that barriers to creativity and innovation can be overcome using various techniques. After reading this chapter, the reader will be able to apply creativity and innovation to identify new and novel ways of undertaking qualitative research, as well as being able to integrate innovate methodologies with existing methodologies.

For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research and social issues, which may outperform standard regression methods in some cases. Under the circumstances, this article proposes a methodological workflow for data analysis by machine learning techniques that have the possibility to be widely applied in social issues. Specifically, the workflow tries to uncover the natural mechanisms behind the social issues through a data-driven perspective from feature selection to model building. The advantage of data-driven techniques in feature selection is that the workflow can be built without so much restriction of related knowledge and theory in social science. The advantage of using machine learning techniques in modelling is to uncover non-linear and complex relationships behind social issues. The main purpose of our methodological workflow is to find important fields relevant to the target and provide appropriate predictions. However, to explain the result still needs theory and knowledge from social science. In this paper, we trained a methodological workflow with left-behind children as the social issue case, and all steps and full results are included.