Process Of Theory Development Research Articles

Guiding computationally intensive theory development with explainable artificial intelligence: The case of shapley additive explanations

This study advances the field of Computationally Intensive Theory Development (CTD) by examining the capabilities of Explainable Artificial Intelligence (XAI), in particular SHapley Additive exPlanations (SHAP), for theory development, while providing guidelines for this process. We evaluate SHAP’s methodological abilities and develop a structured approach for using SHAP to harness insights from black-box predictive models. For this purpose, we leverage a dual-methodological approach. First, to assess SHAP’s capabilities in uncovering patterns that shape a phenomenon, we conduct a Monte-Carlo simulation study. Second, to illustrate and guide the theory development process with SHAP for CTD, we apply SHAP in a use-case using real-world data. Based on these analyses, we propose a stepwise uniform and replicable approach giving guidance that can benefit rigorous theory development and increase the traceability of the theorizing process. With our structured approach, we contribute to the use of XAI approaches in research and, by uncovering patterns in black-box prediction models, add to the ongoing search for next-generation theorizing methods in the field of Information Systems (IS).

Developing an initial explanatory theory for Partnering for Change using realist evaluation.

Partnering for Change (P4C) is an innovative practice model for school-based occupational therapy developed in Canada and informed by a program of research spanning nearly two decades. National and international interest in P4C necessitated development of an explanatory theory to guide implementation in varied contexts. The purpose of this study is to document the process of theory development and to provide an overview of the initial P4C explanatory theory. Realist evaluation was used to construct an initial explanatory theory of P4C drawing on P4C developers' conceptualisations of the model, document analysis, and analysis of transcripts from interviews and focus groups. No consumers were involved in the study design or analysis. Four sets of premises expressed as context-mechanism-outcome configurations (CMOCs) comprise the initial explanatory theory of P4C. An abstracted summary of these four sets along with contexts, mechanisms, and outcomes central to the P4C initial explanatory theory is presented. An exemplar CMOC is shared to illustrate how theoretical premises are developed and expressed using realist evaluation. This study advances knowledge regarding the hypothesised core elements of P4C and provides an example of using realist evaluation to advance knowledge in occupational therapy. Preliminary implications for clinical practice are discussed. Partnering for Change (P4C) is a way of providing occupational therapy services in schools that helps all children to learn and participate successfully. P4C was created in Ontario, Canada, and has been researched for almost 20 years. People in different parts of Canada and other countries are interested in trying P4C. As the researchers who created P4C, we think there is a need to explain how it works so it can be used in different places. This study explains how we created a theory to describe P4C. To develop this theory, we used a method called realist evaluation that would help us explain how, why, and in what situations P4C works best. To do this, we analysed documents and transcripts of interviews and focus groups. Our findings are organised into four main ideas, each explained in terms of contexts (the situations), mechanisms (how and why P4C works), and outcomes (the impacts of P4C). One detailed example is given to show how these ideas were formed and work together. In conclusion, our study helps us understand the key parts of P4C and shows how realist evaluation can be used to improve knowledge in occupational therapy. The study also suggests some early ideas on how P4C can be used in practice.

Compassionate Care for Parents Experiencing Miscarriage in the Emergency Department: A Situation-Specific Theory.

In many countries, parents experiencing miscarriage seek treatment in the emergency department (ED). Parents frequently report dissatisfaction with ED care, while nurses report not knowing how to provide optimal care. This article describes the development of a situation-specific theory, Compassionate care for parents experiencing miscarriage in the ED , based on 4 concepts (change trigger, transition properties, conditions of change, and interventions). This theory evolved from a comprehensive review of the literature, 2 empirical studies, Transitions Theory, and collaborative efforts of an experienced team. The detailed theory development process facilitates its integration in practice and supports new theory development.

Research on Critical Factors Influencing Organizational Resilience of Major Transportation Infrastructure Projects: A Hybrid Fuzzy DEMATEL-ISM-MICMAC Approach

To strengthen major transportation infrastructure projects’ (MTIPs’) organizational resilience and fortify their capacity for crisis management and project risk prevention. In this paper, based on the resilience theory development process, the connotation of organizational resilience of MTIPs is defined, and 20 influencing factors of organizational resilience of MTIPs are extracted from four categories of stability, redundancy, adaptability, and rapidity according to the literature analysis and case study method. The significance, causality, and multilevel recursive order structure of the influencing factors were investigated by the fuzzy DEMATEL-ISM approach, and their driving and dependent characteristics were analyzed through MICMAC. The results indicate that risk warning and prediction, human resources management, inter-organizational synergies, resource reserve situations, organizational leadership, and organizational learning are the crucial factors of organizational resilience in MTIPs. There are three levels and five ranks in the multilevel recursive rank structure of the factors affecting MTIPs’ organizational resilience. Among them, risk warning and prediction, equipment condition and performance, human resources management, and organizational leadership have the deepest impact on organizational resilience in MTIPs. The findings can clarify ideas for subsequent research on organizational resilience in this area and inform project decision-makers in developing strategies for optimizing organizational resilience.

How do you know that you don’t know?

Whenever someone in a team tries to help others, it is crucial that they have some understanding of other team members’ goals. In modern teams, this applies equally to human and artificial (“bot”) assistants. Understanding when one does not know something is crucial for stopping the execution of inappropriate behavior and, ideally, attempting to learn more appropriate actions. From a statistical point of view, this can be translated to assessing whether none of the hypotheses in a considered set is correct. Here we investigate a novel approach for making this assessment based on monitoring the maximum a posteriori probability (MAP) of a set of candidate hypotheses as new observations arrive. Simulation studies suggest that this is a promising approach, however, we also caution that there may be cases where this is more challenging. The problem we study and the solution we propose are general, with applications well beyond human–bot teaming, including for example the scientific process of theory development.

Centring participant experience: a realist evaluation of a menstruator-friendly facility design project in a refugee settlement, Lebanon

IntroductionMenstrual health in humanitarian contexts is a neglected topic. Its taboo nature presents difficulties for participants in menstrual health projects in these particularly challenging settings. Namely, their experiences may be concealed or overlooked in projects that are typically outcome focused. Realist Evaluation is a useful method to unearth and explore the hidden mechanisms and their causes, which lead to positive or negative participant experiences. The authors have applied this approach to a robust humanitarian menstrual health project to explore how to centre the emotional wellbeing of participants at all stages: prior to, during, and post-participation.Study settingThe project studied was led by the International Federation of Red Cross and Red Crescent Societies who piloted their adaptable manual for menstruator–friendly water, sanitation and hygiene (WaSH) facility design in humanitarian contexts. It was conducted by the Lebanese Red Cross in an informal tented settlement hosting Syrian refugees in Qaa, Lebanon.MethodsThe authors collected interview and focus group data on the contextual factors and processes within the project from nine project staff and 16 settlement inhabitants. They used a realist process of theory development, testing, and consolidation to understand how and under what circumstances the project inputs affected participants’ wellbeing.ResultsThe contextual factors and causal mechanisms promoting participant experience comprised individual (choices influencing and experience during participation), interpersonal (group dynamics and the role of non-menstruators), and organisational (expertise and knowledge, relationship to participants and cultural differences) factors.ImplicationsThe research uses a case study from a renowned humanitarian organisation who provided a well-delivered project in a conducive environment to explore the mechanisms and contexts that can promote wider learning and refine understanding and programming in this under-researched and -theorised space. Specifically, it informs which contextual factors and project inputs must be present within a menstrual health project to ensure participant satisfaction whilst efficiently delivering well-designed menstruator-friendly WaSH facilities.

The Use of Artificial Intelligence (AI) in Qualitative Research for Theory Development

Theory development is an important component of academic research since it can lead to the acquisition of new knowledge, the development of a field of study, and the formation of theoretical foundations to explain various phenomena. The contribution of qualitative researchers to theory development and advancement remains significant and highly valued, especially in an era of various epochal shifts and technological innovation in the form of Artificial Intelligence (AI). Even so, the academic community has not yet fully explored the dynamics of AI in research and there are significant gaps in our understanding of how AI can be used most effectively in the context of theory building. The aim of this paper, which is driven by critical and conceptualization methodological dynamics, is to investigate the role of AI in the theory development process. As such, it critically evaluates the opportunities and limitations of AI in theory building, delivers a conceptual map of the nexus between AI and theory development, and presents key considerations for the use of AI in the creation of new theories or the advancement of existing ones. Though the necessity of AI tools in theory creation is contested given that the researchers' cognitive and evaluative skills are regarded as critical in this process, the value of AI in advancing theory is not to be underestimated.

The significance of educational biography for the professional self-image of GDR psychotherapists

Since the reunification of Germany, a debate on the professional activities of GDR psychotherapists has rised up. This debate is partly conducted by the spirit of coming to terms with the past and partly by legitimizing therapeutic activities in the GDR. The aim of this work is to show in individual patterns the professional self-image of selected GDR psychotherapists. The study focused from a sociological perspective with the intention of differentiating this topic. In course of this, the range of political positioning of GDR psychotherapists will also be determined on a case-by-case basis and it will be shown how this was shaped in the often named "niche of psychotherapy". Based on-biographical interviews, educational biographical trajectories of GDR psychotherapists were reconstructed. The interviews were analyzed using grounded theory in a circular process of material selection and theory development. According to the principle of maximum contrast (theoretical sampling), four women were selected for reconstruction from a sample of 39 interviews from the joint project Seelenarbeit im Sozialismus (Soul Work in Socialism) and analyzed using Teifel's (2005) coding guide based on educational theory. Within the four cases, extremely individual educational biographies emerge on the levels of the coding strategy (meaning/structure perspective and mode of action), each showing different characteristics with regard to their ability to adopt a reflexive stance and the adoption of professional agency. The cases also show different characteristics with regard to their different positions on the system of GDR. The results of the case reconstructions can be summarized in an overarching scheme. This shows that the role of each individual's educational access, their educational paths and their individual practice of action must be seen in relation to the influence of the political system and the ability to adopt a professional attitude. The psychotherapists of the GDR cannot be understood per se as a group acting subversively against the state.

The theory of technological response and progress in chaos

PurposeThis study aims to develop the first Theory of Technological Response and Progress in Chaos (TRPC) and examine the case of technological development during the COVID-19 pandemic. The research objectives of this study were to: identify the key technologies that act as a response mechanism during the chaos event, specifically in the case of COVID-19; examine how technologies evolve, develop and diffuse in an immediate crisis and a chaotic environment; theorise various types and periods of technological response and progress during the emergence of chaos and the stages that unfold; and develop policy-oriented recommendations and establish technological foundations to address subsequent chaos events.Design/methodology/approachThis study used the grounded theory as a methodology with a mixed-method approach that included quantitative and qualitative methods. The authors used the quantitative method to assist with the qualitative step to build the TRPC theory. Accordingly, this study integrated machine learning and text mining approaches to the qualitative data analysis following the steps of the grounded theory approach.FindingsAs a result of the TRPC theory development process, the authors identified three types of technologies (survival, essential and enhancement technologies) and five types of periods (stable, initial, survival-dominant, essential-dominant and enhancement-dominant periods) that are specific to chaos-technology interactions. The policy implications of this study demonstrate that a required technological base and know-how must be established before a chaotic event emerges.Research limitations/implicationsConcerning the limitations of this study, social media data has advantages over other data sources, such as the examination of dynamic areas and analyses of immediate responses to chaos. However, other researchers can examine publications and patent sources to augment the findings concerning scientific approaches and new inventions in relation to COVID-19 and other chaos-specific developments. The authors developed the TRPC theory by studying the COVID-19 pandemic, however, other researchers can utilise it to study other chaos-related conditions, such as chaotic events that are caused by natural disasters. Other scholars can investigate the technological response and progress pattern in other rapidly emerging chaotic events of an uncertain and complex nature to augment these findings.Practical implicationsFollowing the indications of the OECD (2021a) and considering the study conducted by the European Parliamentary Research Service (Kritikos, 2020), the authors identified the key technologies that are significant for chaos and COVID-19 response using machine learning and text intelligence approach. Accordingly, the authors mapped all technological developments using clustering approaches, and examined the technological progress within the immediate chaos period using social media data.Social implicationsThe key policy implication of this study concerns the need for policymakers to develop policies that will help to establish the required technological base and know-how before chaos emerges. As a result, a rapid response can be implemented to mitigate the chaos and transform it into a competitive advantage. The authors also revealed that this recommendation overlaps with the model of dynamic capabilities in the literature (Teece and Pisano, 2003). Furthermore, this study recommends that nations and organisations establish a technological base that specifically includes technologies that bear 3A characteristics. These are the most crucial technologies for the survival- and essential-dominant stages. Moreover, the results of this study demonstrate that chaos accelerates technological progress through the rapid adoption and diffusion of technologies into different fields. Hence, nations and organisations should regard this rapid progress as an opportunity and establish the prior knowledge base and technologies before chaos emerges.Originality/valueThe authors have contributed to the chaos studies and the relationship between chaos and technological development by establishing the first theoretical foundation using the grounded theory approach, hereafter referred to as the TRPC theory. As part of the TRPC theory, the authors present three periods of technological response in the following sequence: survival technology, essential technology and enhancement technology. Moreover, this study illustrates the evolving technological importance and priorities as the periods of technological progress proceed under rapidly developing chaos.

Understanding individual psychological and behavioral responses during COVID-19: Application of stimulus-organism-response model.

To comprehend the nature, implications, risks and consequences of the events of the COVID-19 crisis, individuals largely relied on various online information sources. The features of online information exchange (e.g., conducted on a massive scale, with an abundance of information and unverified sources) led to various behavioral and psychological responses that are not fully understood. This study therefore investigated the relationship between exposure to online information sources and how individuals sought, forwarded, and provided COVID-19 related information. Anchored in the stimulus-organism-response model, cognitive load theory, and the theory of fear appeal, this study examined the link between the online consumption of COVID-19-related information and psychological and behavioral responses. In the theory development process, we hypothesized the moderating role of levels of fear. The research model included six hypotheses and was empirically verified on self-reported data (N=425), which was collected in early 2021. The results indicate that continuous exposure to online information sources led to perceived information overload, which further heightened the psychological state of cyberchondria. Moreover, the act of seeking and providing COVID-19 information was significantly predicted by perceived cyberchondria. The results also suggest that higher levels of fear led to increased levels of seeking and providing COVID-19-related information. The theoretical and practical implications of these findings are presented, along with promising areas for future research.

Articulating Grounded Theory Methodology for Public and Nonprofit Administration Scholars and Practitioners

Abstract Grounded theory as a term and as a methodology has received increasing attention from public administration scholars since the mid-2000s. Unfortunately, the application of grounded theory methodology across social science research—including public and nonprofit administration—is often shrouded in vagueness; however, rigorously conducted grounded theory research, particularly classic ground theory, holds great potential to develop theory that is relevant to practice. This article seeks to provide clarity on grounded theory methodology by detailing it through the lens of classic grounded theory methodology (i.e., the foundational methodology). Additionally, the authors examine the interpretation and application of grounded theory methodology through a conceptual content analysis of top public administration journals. The analysis reveals scholars either do not have a clear understanding of grounded theory methodology or needs to improve their reporting of such, as the theory development process is not clearly reported. Insight on directions forward to improve the rigor of grounded theory research in the field is offered, including adhering to established methodology.

Connecting Practice Research With the Process of Theorizing

In this analysis, we contend that theorizing strengthens the connections between practice and research by requiring researchers to check their working assumptions, premises, conclusions, and implications for research, theory, and practice. Our exploration of the process of theorizing in practice research is rooted in the concept of “sensemaking” ( Weick, 1995 ) whereby practice researchers engage in disciplined imagination by reflecting on diverse forms of evidence, being attentive to specific practices and problems, and moving between intuition and reasoned explanation. The analysis includes the following components: 1) tools for theorizing from research findings (abductive analysis and problematization), 2) processes for theorizing about practice research findings (focusing on practice, researcher repertoire, and theory development processes), 3) an example of theorizing from key findings, and 4) the construction of interventive theory. It concludes with implications for social work practice research.

European tech startups' responses to the COVID-19 pandemic: integrating McKinsey's 5R's paradigm and the Newtonian gravitational field

PurposeGiven the nature of corona chaos, tech startups confront strategic disorientation; therefore, this study aims to constructively engage with the theory development process in the area of management decision, adopt causal complexity with a configurational approach of McKinsey's 5R paradigm and the Newtonian gravitational field.Design/methodology/approachThis study provides a novel conceptualization of systematic research of explanatory mechanisms for navigating the turbulence and consequences of the COVID-19 crisis. This configurational study shows how European tech startups adopt strategies in addressing COVID-19 challenges successfully.FindingsThe analysis reveals configurations that lead to the outcome of the conceptual model, namely, reimagining the equifinal paths to the next normal. The findings suggest that, in navigating the crisis, tech startups are able to seize market opportunities, capture technological opportunities and consolidate their future positions.Research limitations/implicationsThe principal limitation consists of limited empirical evidence regarding tech startups’ ability to navigate Covid-19 crisis and choose the appropriate path to the next normal.Practical implicationsThis study enhances European tech startups’ capability to adopt reflexivity and openness while navigating the Covid-19 chaotic context. Furthermore, the study provides a managerial toolkit to guide strategic decisions via deepening their understanding of the new created realities.Originality/valueThis study provides a novel conceptualization of systematic research on explanatory mechanisms for navigating the turbulence and consequences of the COVID-19 crisis context. This configurational study shows how European tech startups adopt strategies that address COVID-19 challenges successfully.

Novel Use of Experiential Learning in an Online Doctor of Philosophy Theory Course.

Due to their abstract nature and lack of real-world application, theory development and testing are often difficult concepts for PhD students to embrace, especially within a virtual learning environment. Although experiential learning is a preferred method, there is a lack of evidence regarding its use in online PhD programs. Four PhD nursing students enrolled in a Foundations of Theory course participated in an innovative experiential learning project designed to introduce the process of theory development and testing. Participants, led by a faculty-researcher, tested the applicability of a conceptual model using the Framework Method with the diary of a Holocaust survivor. This experience increased the learners' understanding and appreciation of theory development and testing processes as they relate to the nurse scientist's role. Experiential learning in an online theory course is a viable option to promote learning, student engagement, and professional socialization. [J Nurs Educ. 2021;60(7):391-393.].

Destination management amid COVID-19: a case study in La Cerdanya, Spain

ABSTRACT This study, following the initial stage of the grounded theory development process, investigates how the COVID-19 influences the tourism practice and management in La Cerdanya, Spain. Empirical data were obtained from a field trip in October 2020 and were inductively analysed to provide pertinent insights. The results show that the current destination planning and management should focus on the local tourism market and destination image rather than seeking for one-size-fits-all solutions, and the existing challenges should be addressed by meeting future tourism trends and strengthening collaborations. Based on the high volume of the political and social-cultural complexities revealed in this study, the implications for ensuing research and practices are presented.

Perceived barriers and enablers to physical activity participation in people with Alopecia Areata: a constructivist grounded theory study

BackgroundAlopecia Areata (AA) is an autoimmune disease that is characterised by hair loss. Individuals diagnosed with it often describe feelings of trauma and social rejection due to cosmetic repercussions and are at high risk of experiencing psychological distress. Physical activity (PA) participation has been associated with better mental health outcomes in diverse populations. A preliminary study of individuals with AA indicated that severe hair loss is associated with symptomatic depression, anxiety and stress, which negatively impacted PA participation. While strategies to increase PA participation in the general population have been established, little is known about PA participation in people with AA. This study aimed to understand barriers and enablers to PA participation in people with AA to inform the development of evidence-based interventions.MethodsThe study used a grounded theory (GT) methodology, relying on an iterative and simultaneous process of data collection, coding, theory development, and data comparisons to explore the perceived barriers and enablers to PA. Data were collected through a focus group (8 participants [33.38 ± 10.81 years]) and individual telephone interviews (8 participants [33.89 ± 11.87 years]). The study was conducted in Melbourne, Australia. Interview data were recorded digitally, transcribed verbatim and analysed. Recruitment continued until theoretical saturation was achieved.ResultsThe constructivist grounded theory method used has assisted to develop an explanatory model which is used to explain the themes for barriers and enablers to PA participation. The four phases in the explanatory model are as follows (1) onset of AA; (2) reaction towards the condition; (3) adjustment; and (4) acceptance.ConclusionThe findings highlighted perceived barriers and enablers to PA participation in people with AA. Future interventions could consider addressing these barriers specifically to maximise effectiveness and to improve mental health status based on the phases of the explanatory model.

Exploring the Future of Universities Through Experimental Foresight

Throughout 2018/2019, The Futures Lab, Inc. (TFL) was commissioned to undertake a comprehensive foresight study on the potential futures for universities in Norway. For the most part, the project followed the full, TFL comprehensive six-stage foresight process and a number of customized approaches that leveraged the specificities of the Norwegian Education System. The foresight project covered two future time horizons, namely 2025 to 2030 and 2031 to 2040. Rather than focus here on the Future of the University project itself, this paper considers five experimental foresight methods that produced an extra edge to the creative inputs to this project and delivered some unexpected and critical insights that became decisive platforms and framing cues for the ultimate seven futures scenarios that were delivered, and for which strategies and action plans were created. The term experimental foresight is interpreted as freeform thinking, testing the boundaries, incorporating unorthodox, disparate approaches, tools, artifacts and environment, and real-time improvization, it is about testing new techniques and repurposing and updating older ones. Experimental foresight is closely allied with and some would claim often indistinguishable from experiential futures, which has become prominent within foresight. We distinguish the two insomuch that experiential refers to the way the foresight is conducted, whereas experimental is what is conducted. The paper describes the five experimental foresight methods and techniques based upon theory, practice and proprietary development processes, reflecting various approaches to creative thinking. The paper outlines the design and architecture of each method as well as how it was applied to the Future of the University project, the outcomes, values and benefits. Where appropriate examples of the outcomes have been used to explain or underpin the purpose and benefits of the method under discussion. The methods selected are always harmonized with the more linear, mathematical and modeling applied in the practice of foresight.

Context sensitivity and economic-geographic (re)theorising

AbstractDrawing upon critical realism and the literature on theorising in social sciences, this article contributes to the understanding of theorising in economic geography by highlighting the role of context throughout the theory development process. By critically reviewing two key concepts in economic geography—related variety and knowledge bases—from a critical realist theory development perspective, scholars’ sensitivity to local context through the whole theorising process is examined. We argue that the particular strength of economic geography with regard to advancing theory lies in the continuous application of concepts and theories (that is, generalities) within new contexts (that is, confrontation with new particularities).

Using computer assisted qualitative data analysis software (CAQDAS; NVivo) to assist in the complex process of realist theory generation, refinement and testing

ABSTRACT There have been several calls for more transparency in realist methods, particularly in the complex process of programme theory development and refinement. This paper will describe the way in which Computer Assisted Qualitative Data Analysis Software, specifically, NUD*IST Vivo (NVivo), was used to build and refine programme theories (using literature and interview data) in a realist evaluation. This article presents the evolving and complex process of coding several data sources to nodes and child nodes, whilst writing ‘attached memos’ to highlight the process of theory generation. In this project, NVivo helped create an explicitly documented and evidenced audit trail of the process of programme theory refinement, answering to calls for further transparency in realist analysis. RAMESES I and II have provided a platform to improve transparency in reporting realist research, by developing consensus and evidence-based reporting guidelines. We propose that the use of NVivo in realist approaches can help structure the iterative and by nature ‘messy’ process of generating, refining and testing complex programme theories when drawing on multiple data sources simultaneously. This effectively creates a structured track record of the analytical process, which increases its rigour and transparency.

Which mechanisms explain the motivation of primary health workers? Insights from the realist evaluation of a maternal and child health programme in Nigeria

IntroductionWell-trained, adequately skilled and motivated primary healthcare (PHC) workers are essential for attaining universal health coverage (UHC). While there is abundant literature on the drivers of workforce motivation, published knowledge...