Introduction to systematic literature review
Systematic literature review is a fundamental step in scientific work where researchers identify and evaluate relevant literature and studies to answer their own research questions and support their work[1]. The definition and purpose of literature review is to gain a comprehensive understanding of the current state of research on a particular topic or question and to uncover possible knowledge gaps or research needs[2]. The process of literature review involves finding, compiling, and analyzing published information and studies in order to track research progress in a particular area and critically evaluate the quality and relevance of the identified literature[3].
Identifying relevant literature requires a thorough and systematic search of various sources such as scientific databases, books, journals, and online platforms[1]. Several factors must be taken into account to ensure that the selected sources are actually relevant and valid for one’s own research work. These include, but are not limited to: – The use of appropriate search terms and strategies to make the search effective and targeted – Assessing the quality and credibility of the sources, for example by checking the author’s qualifications, year of publication and citation frequency – Taking into account different perspectives and opinions in order to obtain a balanced and comprehensive picture of the state of research[3].
The critical evaluation of the literature is another important step in the process of literature review, in which researchers assess the quality, relevance, and reliability of the identified sources[2]. The aim is not only to check the methodological quality of the studies, but also to evaluate their contribution to the understanding of the research topic. Some aspects that should be considered when critically evaluating literature include: – The clarity and validity of the research question or hypothesis – The adequacy of the methods and analytical procedures – The quality and representativeness of the data – The coherence and comprehensibility of the reasoning and results – The limitations and possible bias of the studies[4]. By applying these criteria to the critical evaluation of literature, they can ensure that their own work is based on solid and reliable evidence and makes a valuable contribution to scientific research[3].
Conducting expert interviews according to Mayring
Expert interviews are a valuable method for gathering detailed, qualitative data from knowledgeable sources within a specific subject area or subject area [2]. The main purpose of these interviews is to obtain specific information, opinions, and insights that can help answer specific research questions or address complex problems [4]. Conducting expert interviews using Mayring’s qualitative content analysis method ensures a systematic and structured approach to the evaluation and interpretation of the collected data, which can ultimately increase the quality and validity of a research project [3].
To conduct expert interviews effectively, researchers need to follow several important steps. This includes the planning and preparation, the conduct of the interview, the transcription of the interview and finally the analysis of the data using the method of qualitative content analysis according to Mayring [2]. Proper planning and preparation includes identifying suitable experts, developing clear research questions, and deciding on the appropriate interview format (e.g., face-to-face, phone, or online) [3]. During the interview, researchers should focus on building a relationship with the expert, asking open-ended questions, and actively listening to the expert’s answers [5]. After the interview, the researcher must transcribe the recorded conversation, which means that the audio or video recording is converted into a written document that can be analyzed more easily [6].
The analysis of expert interviews according to Mayring’s qualitative content analysis requires a systematic and structured process of coding and categorizing the textual data [7]. This method can be divided into four main steps: implementation, coding, inductive categorization, and summary of results [2]. Implementation requires splitting the textual data into manageable units, while encoding requires assigning codes to those units based on specific themes or themes [1]. Inductive category formation is about developing categories from the coded data, which can be achieved through a step-by-step process, as described in Mayring’s much-cited book [8]. Finally, the purpose of summarizing the results is to draw conclusions from the categorized data that will help answer the research question and feed into the overall results of the scientific work [1]. By following this structured approach, researchers can ensure a thorough and rigorous analysis of expert interview data and ultimately contribute to the credibility and reliability of their research findings [9].
Statistical analysis of online interviews
Online interviews, also known as web-based interviews or internet interviews, are an increasingly popular method of data collection in qualitative and quantitative research. This includes conducting interviews with research participants via online platforms such as video conferencing software, chat rooms or email[10]. The main purpose of online interviews is to gather in-depth information and insights from respondents that can be used to explore complex topics, understand individual experiences, or evaluate expert opinions[3]. Online interviews allow researchers to access a wide range of participants, overcome geographical barriers, and reduce the costs associated with traditional in-person interview methods[11].
There are several advantages and disadvantages associated with online interviews. Key benefits include: – Flexibility in scheduling and conducting interviews, allowing researchers to cater to participants‘ availability and time zones[11]. – Reduced costs as online interviews eliminate travel expenses and venue bookings[11]. – The ability to reach a wider range of participants, including those who may be geographically dispersed or have limited access to traditional research environments[11]. – Increased anonymity, which can lead to more honest and open responses from participants[3]. However, online interviews also have some drawbacks: – Potential problems with the technology, such as poor internet connections, software bugs, or difficulty navigating online platforms[11]. – Challenges in building rapport and trust with participants, as non-verbal cues and body language are often limited in online settings[5]. – Greater difficulties in ensuring the privacy and confidentiality of participants, especially when discussing sensitive issues[4].
When analyzing data from online interviews, researchers can use various statistical methods to identify patterns, trends, and correlations within the information collected. These methods may include descriptive statistics such as calculating measures of central tendency (e.g., mean, median, mode) and dispersion (e.g., range, variance, standard deviation), as well as inference statistics, which draw conclusions about a population based on a sample[5]. In addition, researchers can use qualitative content analysis techniques, such as Mayring’s approach, to systematically process and categorize interview data, allowing them to answer specific research questions and draw meaningful conclusions from their findings[7]. By integrating these statistical methods and content analysis strategies, researchers can effectively analyze online interview data and gain valuable insights for their scientific work[3].
Advantages of combining different research methods
Triangulation of research methods allows researchers to combine different perspectives and approaches to gain a more comprehensive understanding of a phenomenon. Through the use of qualitative and quantitative methods, such as the scientific work of systematic literature review, the evaluation of expert interviews according to Mayring and the statistical evaluation of online interviews, researchers can look at their results from different angles and thus analyze possible weaknesses or gaps in their analysis [3]. Some benefits of using triangulated research methods include: – Increased validity and reliability of research results – Complementary insights from different data sources – Versatility and flexibility in data collection and analysis
The increased validity and reliability of research results, which are achieved by combining different research methods, are of great importance for scientific work. For example, Mayring’s qualitative content analysis offers a transparent and systematic approach to the evaluation of expert interviews [11]. This method is not dependent on the cooperation of the participants and can be applied to different materials [7]. The combination of this qualitative method with quantitative approaches, such as the statistical analysis of online interviews, enables researchers to collect and evaluate both objectifiable and numerical data [5]. This allows them to validate their research results from different perspectives and increase the reliability of their conclusions.
Finally, complementary insights from different data sources provide an added advantage when combining research methods. In the context of Mayring’s in-depth model, the main purpose of expert interviews in the research process is to present and explain the results from the quantitative part of the study [12]. By integrating expert interviews into scientific work, researchers can gain additional information and insights that may not be available through the use of quantitative methods alone. These complementary findings allow researchers to strengthen their conclusions and recommendations, providing a more comprehensive analysis of the phenomenon studied.
Challenges in combining different research methods
The integration of different data sources is a crucial aspect of conducting scientific research, as it allows researchers to gain a comprehensive understanding of the topic. A popular approach for this is qualitative content analysis, as developed by Mayring [13]. This method allows researchers to systematically evaluate expert interviews and other qualitative data sources such as document analysis and guided interviews [14]. However, combining qualitative data from interviews with quantitative data, such as online surveys, can be a complex process, as a careful balance between the two types of data is required to ensure a coherent and accurate analysis [15].
Time and resource constraints are common challenges that researchers face when combining different research methods, especially when it comes to evaluating expert interviews according to Mayring’s qualitative content analysis [3]. This process involves coding and analyzing interview data, which can be time-consuming and labor-intensive [4]. In addition, researchers also need to consider the amount of time required to plan and conduct the interviews themselves, as well as the potential need for multiple interview sessions to collect sufficient data [3]. To overcome these challenges, researchers must carefully plan and allocate resources to ensure the efficient and effective integration of different research methods.
The potential for conflicting results is another challenge for researchers when combining different research methods, such as expert interviews and statistical evaluations of online interviews [5]. This is because qualitative data from expert interviews may provide more nuanced, context-specific insights, while quantitative data from online surveys may provide more generalizable, statistically significant insights [5]. Therefore, researchers need to be careful when interpreting and integrating the results from these different data sources, as they may not always agree or complement each other [12]. To mitigate this risk, researchers should strive to maintain a clear and consistent research focus, as well as a robust methodological approach that allows for adequate synthesis of both qualitative and quantitative data.
Conclusion and future directions
The implications for future research in the field of scientific work are immense, as the combination of different research methods can lead to more accurate and comprehensive insights. A systematic literature review, the evaluation of expert interviews according to Mayring and the statistical evaluation of online interviews can contribute to a more well-founded understanding of a topic [4]. By incorporating these different approaches, researchers can gain insights from multiple perspectives, reducing potential bias and ensuring that the conclusions drawn are rounded and supported by different sources of evidence.
The importance of combining different research methods becomes clear in expert interviews, which are often evaluated on the basis of Mayring’s structuring content analysis [3]. This technique of qualitative content analysis allows researchers to carefully examine the data collected from interviews and identify key themes, patterns, and insights that emerge from the expert’s answers [16]. In addition, the integration of statistical evaluation methods, such as those used in online interviews, adds a quantitative dimension to the research and allows the study of numerical data and objectifiable information [5]. The combination of both qualitative and quantitative methods can lead to a more comprehensive understanding of the research topic and provide a more solid basis for future studies.
Especially with regard to the evaluation of expert interviews, there is considerable potential for further development of research techniques. Mayring’s in-depth model, for example, suggests that the primary purpose of expert interviews is to present the results from the quantitative part of the research process [12]. As research techniques evolve, researchers can explore new ways to integrate the insights gained from expert interviews with other research methods such as systematic literature review and statistical analysis [17]. By continuously refining and improving the methods used in scientific research, scientists can ensure that their work remains at the forefront of their respective fields and makes a meaningful contribution to the continuous pursuit of knowledge.
In conclusion, the process of scientific research includes various methods, including systematic literature review, expert interviews according to Mayring, and statistical analysis of online interviews. The combination of these methods can lead to a more comprehensive understanding of the research topic, increase the validity and reliability of the results, and provide complementary insights from different data sources. However, integrating disparate data sources can also present challenges, such as time and resource constraints, as well as the possibility of conflicting results. Despite these challenges, the combination of different research methods holds great potential for further advances in research techniques and the development of more accurate and reliable results. Future research should continue to explore the benefits and challenges of combining different research methods and aim to develop more effective strategies for integrating different data sources.
Quellen:
1.Qualitative Analyse über das Kaufverhalten und …. (n.d.) Retrieved November 30, 2023, from fhburgenland.contentdm.oclc.org
2. Experteninterview Auswertung – Leitfaden zum Erfolg. (n.d.) Retrieved November 30, 2023, from www.bachelorprint.de/methodik/experteninterview-auswertung/
3. qualitative Inhaltsanalyse nach Mayring. (n.d.) Retrieved November 30, 2023, from www.acad-write.com
4. Die Auswertung des Experteninterviews in 4 Schritten – Scribbr. (n.d.) Retrieved November 30, 2023, from www.scribbr.de/methodik/auswertung-experteninterview/
5. Interviews auswerten, Inhaltsanalyse nach Mayring. (n.d.) Retrieved November 30, 2023, from www.ghostwriter-arbeiten.de/interviews-auswerten/
6. MASTERARBEIT. (n.d.) Retrieved November 30, 2023, from diglib.tugraz.at
7. Qualitative Inhaltsanalyse nach Mayring in 5 Schritten – Scribbr. (n.d.) Retrieved November 30, 2023, from www.scribbr.de/methodik/qualitative-inhaltsanalyse/
8. Induktive Kategorienbildung nach Mayring (Beispiel …. (n.d.) Retrieved November 30, 2023, from shribe.de/induktive-kategorienbildung/
9. Qualitative Inhaltsanalyse nach Mayring / Methodenzentrum. (n.d.) Retrieved November 30, 2023, from methodenzentrum.ruhr-uni-bochum.de
10. Induktives und deduktives Codieren. (n.d.) Retrieved November 30, 2023, from sozmethode.hypotheses.org/842
11. Warum sollte ich eine qualitative Inhaltsanalyse nach Mayring …. (n.d.) Retrieved November 30, 2023, from www.scribbr.de
12. MASTERARBEIT. (n.d.) Retrieved November 30, 2023, from diglib.tugraz.at
13. Moderne Forschungsmethoden im Wirtschaftsingenieurwesen …. (n.d.) Retrieved November 30, 2023, from industrielogistik.unileoben.ac.at
14. Bannwart, Rebe. (n.d.) Retrieved November 30, 2023, from irf.fhnw.ch
15. Methodik. (n.d.) Retrieved November 30, 2023, from link.springer.com/chapter/10.1007/978-3-658-40024-8_3
16. Prof. Dr. Edeltraud Günther. (n.d.) Retrieved November 30, 2023, from tud.qucosa.de/api/qucosa%3A25322/attachment/ATT-1/
17. Soziale Deutungsmuster der Gerechtigkeit W-besoldeter …. (n.d.) Retrieved November 30, 2023, from d-nb.info/1138999741/34