Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
36,824
result(s) for
"MIXED METHODS"
Sort by:
Mixed methods research in poverty and vulnerability : sharing ideas and learning lessons
\"The added value of mixed methods research in poverty and vulnerability is now widely recognized. However, despite the expanding volume of literature on the use of mixed methods, gaps and challenges still remain. This edited volume focuses on issues of credibility, usability and complexity, considering how mixed methods approaches can better respond to these issues so as to make research more credible, usable and responsive to complexity. The contributors share experiences and lessons learned from research in developed and developing country contexts in respect of mixed methods in poverty measurement, evaluation research and the translation from research to policy\"-- Provided by publisher.
Book
How to Construct a Mixed Methods Research Design
This article provides researchers with knowledge of how to design a high quality mixed methods research study. To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered during the design process. We explain ten secondary dimensions of design to be considered for each research study. We also provide two case studies showing how the mixed designs were constructed.
Journal Article
Qualitative and mixed methods data analysis using Dedoose : a practical approach for research across the social sciences
\"Qualitative and Mixed Methods Data Analysis using Dedoose will provide both new and experienced researchers with a guided introduction to dealing with the methodological complexity of mixed methods and qualitative inquiry using Dedoose software. The authors use their depth of experience designing and updating Dedoose as well as their significant research experience to give the reader practical strategies for using Dedoose from a wide range of research studies. Qualitative and Mixed Methods Data Analysis using Dedoose walks researchers, students and evaluators through designing a study, conducting fieldwork and reporting credible findings. In the first section the book gives a quick overview of qualitative and mixed methods research and designing studies to work easily with available software, including Dedoose. The authors pay significant attention to data analysis in the second section, addressing the challenges of working in teams, working with just qualitative data, and analyzing qualitative and quantitative data in a mixed method study. The final section is devoted to reporting results and data visualization within Dedoose. Throughout the book, case studies are presented to illustrate the topics discussed with real research examples. Working through this book will give researchers improved technological skills to use Dedoose effectively in their research\"-- Provided by publisher.
Book
Gameful Experience Questionnaire (GAMEFULQUEST): an instrument for measuring the perceived gamefulness of system use
In this paper, we present the development and validation of an instrument for measuring users’ gameful experience while using a service. Either intentionally or unintentionally, systems and services are becoming increasingly gamified and having a gameful experience is progressively important for the user’s overall experience of a service. Gamification refers to the transformation of technology to become more game-like, with the intention of evoking similar positive experiences and motivations that games do (the gameful experience) and affecting user behavior. In this study, we used a mixed-methods approach to develop an instrument for measuring the gameful experience. In a first qualitative study, we developed a model of the gameful experience using data from a questionnaire consisting of open-ended questions posed to users of Zombies, Run!, Duolingo, and Nike+ Run Club. In a second study, we developed the instrument and evaluated its dimensionality and psychometric properties using data from users of Zombies, Run! (N = 371). Based on the results of this second study, we further developed the instrument in a third study using data from users of Duolingo (N = 507), in which we repeated the assessment of dimensionality and psychometric properties, this time including confirmation of the model. As a result of this work, we devised GAMEFULQUEST, an instrument that can be used to model and measure an individual user’s gameful experience in systems and services, which can be used for user-adapted gamification and for informing user-modeling research within a gamification context.
Journal Article
How to use and assess qualitative research methods
This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.
Journal Article
Guidelines for Conducting Mixed-methods Research: An Extension and Illustration
In this paper, we extend the guidelines of Venkatesh et al. (2013) for mixed-methods research by identifying and integrating variations in mixed-methods research. By considering 14 properties of mixed-methods research (e.g., purposes, research questions, epistemological assumptions), our guidelines demonstrate how researchers can flexibly identify the existing variations in mixed-methods research and proceed accordingly with a study design that suits their needs. To make the guidelines actionable for various situations and issues that researchers could encounter, we develop a decision tree to map the flow and relationship among the design strategies. We also illustrate one possible type of mixed-methods research in information systems in depth and discuss how to develop and validate meta-inferences as the outcomes of such a study.
Journal Article
Innovative Applications and Future Directions in Mixed Methods and Multimethod Social Research
In this editorial, we introduce the FQS special issue \"Mixed Methods and Multimethod Social Research—Current Applications and Future Directions\" by firstly considering changes and continuities in the field since the publication of FQS 2(1) on \"Qualitative and Quantitative Research: Conjunctions and Divergences\" (SCHREIER & FIELDING, 2001). We then provide a brief overview of the historical development of mixed research approaches over the past 20 years so as to arrive at a concise description of the status quo. We highlight some of the advances made by researchers applying integrative designs in multiple research areas, as well as methodologists analyzing the conceptual groundwork of mixed methods and multimethod research (MMMR). However, we also point out some of the critical issues remaining to be resolved, including the increasing internal fragmentation of the MMMR discourse and a seemingly growing gap between MMMR methodology and empirical research practice. We conclude by introducing the 13 contributions assembled in this volume.
Journal Article
Adoption of AI-based chatbots for hospitality and tourism
Purpose
This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.
Design/methodology/approach
To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.
Findings
As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.
Practical implications
This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.
Originality/value
This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.
Journal Article
A DNA Helix Analogy for Interdependent Mixed Methods Research: Enabling Cross-Fertilizations and Interim Meta-Inferences
Mixed methods enable a more integrated and insightful understanding of the phenomena we study, but are complex to plan, execute, and document. This applies to concurrent and fully integrated mixed methods research designs in particular, which remain underrepresented in information systems research. In this paper, we extend the prevailing templates for this type of research and propose a new conceptualization. We argue that different research strands (e.g., qualitative, quantitative, computationally intensive, or other) that unfold at the same time need not be independent. Rather, as they run concurrently, they can interact and inform each other through ongoing cross-fertilization. This offers the opportunity for enhanced validation and deeper research insights. We conceptualize how the interaction between the research strands may unfold and we propose a DNA helix analogy to enable and enhance the conceptualization of such interdependent mixed methods research. We further explain the mechanism through which the different research strands interact in an ongoing cross-fertilization, and how interim meta-inferences may be continuously and incrementally drawn, (re)shaping how each research strand evolves. The research process within this conceptualization is depicted in a flow diagram that can serve as a possible roadmap for this type of research. We also show how this process can be documented, contributing to more transparent accounts of how mixed methods research actually evolves. We refer to our research on cloud adoption as an example and further validate our proposed research design with interviews with junior and experienced researchers engaged in mixed methods research. We conclude with a set of principles to guide interdependent mixed methods research and present their practical implications.
Journal Article
Five common pitfalls in mixed methods systematic reviews: lessons learned
Mixed methods systematic reviews (MMSRs) combine quantitative and qualitative evidence within a single review. Since the revision of the JBI methodology for MMSRs in 2020, there has been an increasing number of reviews published that claim to follow this approach. A preliminary examination of these indicated that authors frequently deviated from the methodology. This article outlines five common ‘pitfalls’ associated with undertaking MMSR and provides direction for future reviewers attempting MMSR.
Forward citation tracking identified 17 reviews published since the revision of the JBI mixed methods methodological guidance. Methods used in these reviews were then examined against the JBI methodology to identify deviations.
The issues identified related to the rationale for choosing the methodological approach, an incorrect synthesis and integration approach chosen to answer the review question/s posed, the exclusion of primary mixed methods studies in the review, the lack of detail regarding the process of data transformation, and a lack of ‘mixing’ of the quantitative and qualitative components.
This exercise was undertaken to assist systematic reviewers considering conducting an MMSR and MMSR users to identify potential areas where authors tend to deviate from the methodological approach. Based on these findings a series of recommendations are provided.
•Common pitfalls in conducting a mixed methods systematic review relate to the justification for undertaking a mixed methods approach to the systematic review, mismatch between the review questions and the synthesis/integration approach used, inadvertent or deliberate exclusion of mixed methods primary research in the review, lack of clarity about data transformation, and the lack of integration of the quantitative and qualitative components of the review.•The review questions inform which mixed methods review approach (i.e., integrated or segregated) should be followed in the conduct of the systematic review.•Regardless of the approach taken, the quantitative and qualitative components of the review should be integrated appropriately.
Journal Article