Steven E. Wallis

Existing and Emerging Methods for Integrating Theories within and between Disciplines

Abstract Our conceptual systems (including theories, models, policies, and schema) all help us to understand our world. For highly complex situations such as those found in natural systems and service systems, it is important to understand them from an interdisciplinary perspective because these real-world systems do not respect the boundaries of any single discipline. While many conceptual systems exist, they have not proven to be highly effective for understanding issues that are the focus of their disciplines. Still fewer conceptual systems have been developed that cut across disciplinary boundaries — and they have not been shown to be any more effective than their mono-disciplinary companions. This article investigates emerging and existing methods for creating and integrating theories within and between disciplines. This includes ‘soft’ methods (ad-hoc, cherry-picking, and intuitive) as well as ‘rigorous’ (formal grounded theory (FGT), reflexive dimensional analysis (RDA), and integrative propositional analysis (IPA)). The article demonstrates that soft methods are relatively easy to use, but they do not produce conceptual systems of great or lasting value. In contrast, it is proposed that rigorous methods are more likely to yield conceptual systems which are measurably more systemic, more useful, and more effective for understanding and engaging the highly complex systems of our world.

Developing effective ethics for effective behavior

Purpose - The purpose of this paper is to investigate the internal structure of Gandhis ethics as a way to determine opportunities for improving that systems ability to influence behavior. In this paper, the author aims to work under the idea that a system of ethics is a guide for social responsibility. Design/methodology/approach - The data source is Gandhis set of ethics as described by Naess. These simple (primarily quantitative) studies compare the concepts within the code of ethics, and their relationships to one another. Findings - Gandhis ethics are robust at the 0.25 level (the scale is zero to one – zero is lowest). This is consistent with theories of the social sciences (that do not work well in practice). Gandhis success might be ascribed to his leadership ability. Research limitations/implications - Some suggest this approach is reductionist because of its superficial similarity to approaches of physical science. The implications for research are profound. First, this approach provides an objective method for comparing (and so, advancing) systems of ethics. Second, this paper suggests the opportunity to compare the internal structure of ethics with “external” aspects – the implementation of ethical systems. Practical implications - By itself, Gandhis system of ethics cannot be reliably applied in practice - it cannot be expected to change behavior more than any other system of ethics. This raises concerns about other ethical codes as well. The practical implications of the form of analysis presented in this paper are immense because it provides a way for practitioners to objectively compare two codes of ethics and determine which one will be more effective. Originality/value - The approach documented in the paper has never been applied to the field of ethics. It is unique in that it addresses the “internal” structure of a system of ethics (compared to the “external”, or application, of ethical systems).

Seeking the robust core of organisational learning theory

Organisational learning theory (OLT) has become a hot topic of conversation in academic journals. However, the variety of descriptions seem to suggest no unified understanding of what OLT is. In this paper, I draw on a sample of 12 recent papers as samples of normal science and exemplars of our present level of scholarship to conduct a propositional analysis of the structure of OLT. This analysis identifies the core of OLT and finds that OLT has a robustness of 0.16 on a scale of zero to one. This low level of robustness suggests that OLT may be of limited efficacy in application. This paper creates a benchmark for the progress of OLT and suggests opportunities for advancing our understanding of OLT.

The imperviance of conceptual systems: cognitive and moral aspects

Purpose The complexity of the modern world calls for the increasingly complex (i.e. containing more concepts) and systemic (i.e. containing more causal connections between the concepts) conceptual systems, such as theories and mental models which may exist at varying levels of complexity and systemicity. Yet, these systems are often found to be impervious to data and counter-arguments. Examples of such disputes are found in arguments over global warming and in the many debates between political groups. The purpose of this paper is to review the reasons behind this imperviance and identify ways to move forward. Design/methodology/approach The paper brings together the insights from the burgeoning science of conceptual systems as well as selected ideas from the moral philosophies of Niklas Luhmann and Jurgen Habermas. The science of conceptual systems is utilized to unearth the cognitive reasons for the imperviance of conceptual systems, while the work of Luhmann and Habermas is brought to bear on the moral reasons. Findings The most salient cognitive reasons for this imperviance are shown to be related to the questionable validity of data, the situational inappropriateness of conceptual systems, as well as their low complexity and systemicity. The effect of the moral content of conceptual systems on their imperviance is ambivalent. For Luhmann, moral communication may enhance imperviance and induce conflicts. In contrast, the Habermasian discourse ethics may counteract imperviance by stimulating the rational moral argumentation. Originality/value The science of conceptual systems is uniquely positioned to analyze the pervasive problem of their imperviance, especially if this problem is aggravated by moral reasons.

Using Integrative Propositional Analysis for Evaluating Entrepreneurship Theories

Previous studies have noted a proliferation of disparate theories of entrepreneurship. This makes it difficult to find the best theory for application in teaching, practice, and research. Choosing the right entrepreneurship theories to teach and encourage is critical to providing entrepreneurs with the knowledge they need to succeed. Scholars have recommended integrating entrepreneurship theories across disciplines and across practice; however, rigorous methods to assess and integrate the best theories are lacking. Integrative propositional analysis is an emerging method to assess and improve theories using the theory structure as data, rather than relying on empirical data and opinion alone. This exploratory study pilot tested this approach with a sample of nine entrepreneurship theories. Several insights emerged that entrepreneurship researchers, educators, and practitioners can use to synthesize and improve theories for their specific needs and to collaboratively integrate the best theories from research and experience to create better theories.

Evaluating Explanations through Their Conceptual Structures

Many scholars discuss concepts and even conceptual systems along with the importance of understanding them. As Umpleby (1994) claims, “Explicit attention to conceptual systems, or to beliefs and values, is not a new development within the social sciences.” Past investigations have been useful in helping us understand (to some extent) the place of concepts within a larger process of communication and action (the science of cognitive systems). However, we have not become adept at understanding our conceptual structures from a systemic perspective (the science of conceptual systems). Indeed, because our minds are full of conflicting mental models (Lane, 1992), our conceptual lenses are not very clear. Thus, many investigations may have been made using one fuzzy lens to evaluate the fuzziness of another lens; we do not understand conceptual structures as systems unto themselves. This, for systems thinkers, is highly problematic.

What drives technology transitions? An integration of different approaches within transition studies

ABSTRACT This paper aims to provide a deeper understanding of transition drivers by reviewing four major strands of inquiry in transition studies: Multi Level Perspective (MLP); Strategic Niche Management (SNM); Transition Management (TM); Technological Innovation Systems (TIS). To the best of our knowledge, none of these contributions have so far provided a clear-cut classification of main drivers of transitions, as evidenced by the difficulty of practitioners in reaching goals as entrepreneurs, or policy makers in supporting economic growth. We believe that these theoretical streams share views relating the origin and drivers of transitions and that the analysis of the multi-level developments and systemic sub-processes by using the Integrative Propositional Analysis (IPA) allows for a more comprehensive identification of transition drivers. By mapping causal relationships within each perspective and by developing an integrative framework that takes in due account of overlaps between theories, we derived a new conceptual structure for the identification of transitions’ drivers.