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Close interaction between universities, industries, and governments has given rise to hybrid organizations incorporating economic development alongside scientific research and higher education. We will approach this phenomenon and the related organization-theoretical problems by looking at two cases of discipline making to discuss the potential of the concept of organizational field introduced by the neoinstitutionalist school of organization theory. As this concept presumes the Bourdieusian theory of social fields, we will consider possibilities of reflective contesting of the states of doxa in discipline making in regard to organizational aspects of disciplinary boundaries in the university-centered system of higher education, its demarcation to business and schooling, as well as to the related ideology of professionalism and science policy. We will also comment on the Bourdieusian conceptuality inscribed in the neoinstitutionalist metaphor of organizational field from the perspective of systems theory inspired by Luhmann. This is because we believe that further development of the semantic focus in the problem of disciplinary boundaries would benefit from Luhmannian tools designed to grasp organizations as social systems that facilitate interrelations of differentiated function systems relevant for discipline making in current technoscience.

Many recent studies have voiced the growing concern that the body of knowledge that springs from organization science is hardly taken notice of in management practice. This has given rise to urgent calls for making organization research more relevant to practitioners and an intensive debate on how to realize this aim has set in (e.g., Hodgkinson, Herriot, & Anderson, 2001; Rynes, Bartunek, & Daft, 2001; MacLean & MacIntosh, 2002; Baldridge, Floyd, & Markoczy, 2004; Van de Ven & Johnson, 2006). In most of the existing literature one can identify three main reasons for the observable lack of connection between organization research and practice: research is not sufficiently focused on the “real” problems of practitioners (e.g., Rynes, McNatt, & Breetz, 1999), research results are not properly disseminated to practitioners (e.g., Spencer, 2001), and the language of science is not properly translated into the language practitioners' use (e.g., Starkey & Madan, 2001; Van de Ven & Johnson, 2006). The underlying assumption is that if scientists redressed these shortcomings, their findings would be utilized by practitioners and thus the gap between theory and practice would be bridged.

The purpose of this paper is to present retrospective, current and prospective aspects of social marketing and systems science integration.

The paper uses a periodization methodology, based on turning points of conceptual integration between social marketing and systems science.

The paper identifies three periods of integration between social marketing and systems science: initialization of marketing and systems science integration; further conceptualization of the link between marketing and systems science, coupled by permeation of systems thinking into social marketing; and deep integration of social marketing with systems science. The latter period is ongoing and focuses on the origination of strategic systems-based theories and practices for sustainable social change.

The use of a periodization methodology might be biased by subjectivity, as chronological sequences of conceptualization-related events can be hard to decipher and can be reluctant to structural analysis. The necessity to examine the link between marketing and systems science, in so far as social marketing draws upon marketing theory regarding integration with systems science, has social marketing overshadowed by marketing at some points in time.

Historical research of social marketing and systems science integration provides a robust platform for large-scale practical manifestation of system-based strategic projects in social marketing.

This paper demonstrates that the permeation of systems thinking into the social marketing paradigm is gaining momentum and describes the trends, prospects and complexities associated with the accelerating integration.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Three problematic issues followed by paradigm changes over the recent history of human intellectual endeavour are identified as 1. mysticism/superstition to – conventional science (of physics), 2. predominant use of qualitative/quantitative properties for analysis and design to – structural or systemic properties, and 3. current speculative/fragmented, multiple approaches to the “systemic view” to – a firmer knowledge-based approach reflecting the empirical and universal nature of this view. This paper aims to consider the problematic issues, to conclude that conventional science is inadequate to cope with the 2nd paradigm change and to introduce a “new science of systems” which can integrate conventional science and alleviate the 3rd problematic issue by suggesting three principles implemented by linguistic modelling as operational model.

The highly successful methodology of conventional science is followed with systemic content by suggesting three general principles of systems, namely, principle of existence (pervasiveness of structural description), principle of complexity (aggregates for emergence of outcomes) and principle of change (change by purpose or chance), and linguistic modelling of static and dynamic scenarios based on natural language as operational model. This language is processed to “elementary constituents”, of which complex structures can be constructed. These constituents are converted into reasoning schemes consisting of “ordered pairs” and “predicate logic statements” in static and dynamic states.

Stories of problematic scenarios are converted into the universal scheme of “management/producers” – “products” – “users/consumers” by constructing linguistic networks of products and semantic diagrams of organizations/user/consumers for investigating the emergence of outcomes in analysis and for designing prototypes. Problematic issues of individual objects in a scenario are resolved by methods of conventional science, which is thus integrated with systems science to form the “scientific enterprise”.

Once the new approach is debated, further developments in the mathematics of ordered pairs, predicate logic and uncertainties are needed. The linguistic basis is to be further investigated. Connection with AI and “logical atomism of Bertrand Russell” is to be explored.

Further applications to large-scale scenarios by practitioners using the “universal scheme” and development of software are needed.

The approach is rooted in accepted branches of knowledge, is highly teachable and should lead to be used by professionals and others once debated and accepted.

The current field of systems thinking consists of a variety of views, methods and a number of organisations involved with these views which suggests a state of confusion and fragmentation of the field which fundamentally is supposed to be a uniform view of structures or systems. This can be interpreted as a “crisis situation”. A resolution of the crisis in the form of a “new science of systems” is proposed. Assuming this new science becomes part of the field of systems thinking, a debate of the elements of the field is suggested with a view to consider its current state and future developments. “Crisis - resolution - debate” is the central theme of the paper.

The field of current systems thinking is described in terms of views, methods and organisations and is seen as the “problematic issue”. A “new science of systems” strongly rooted in natural language as its primary symbolism and consisting of three general principles of systems and linguistic modelling is outlined to be considered as the resolution of the crisis. A set of criteria is discussed for use of judging the quality of models and element of the field of systems thinking including the “new science of systems”. To demonstrate a preliminary use of these criteria, the same example is worked out using both, the “soft systems methodology” and “linguistic modelling” for comparison.

The universal view of parts of the world as structures or systems is inconsistent with the multiple methods basically pursuing the same purpose: modelling aspects of systems which prevail in current systems thinking. To try to resolve this anomaly an equally universally applicable approach, the “new science of systems” is proposed which can also serve as an aid to problem solving, in particular to an integrated systems and product design. This approach is to be part of the suggested debate of the field of systems thinking. In general, there is no alternative to the structural view.

The “new science of systems”, if found acceptable, can offer research opportunities in new applications of accepted branches of knowledge like logic, linguistics, mathematics of ordered pairs, uncertainties and in the philosophy of science. New teaching schemes can be developed at classroom level combined with engineering as creator of novelties with linguistics as the symbolism to supplement mathematics. Further considerations can be given to current methodologies of systems thinking as part of a debate with a view of future developments in exploring pioneering ideas. New software is needed for working out the dynamics of scenarios.

The debate, if it takes place, should result in new developments in the field of systems thinking such as concepts accepted as fundamental in the discipline of systems. Applications of the “new science of systems” to larger scale scenarios and organisations guided by the universal scheme in Figure 1 and linguistic modelling with software are needed for development of schemes for problem solving schemes “utilising” or “producing” products.

The “new science of systems” is rooted in accepted branches of knowledge; it is highly teachable at school and university levels and should lead to use by professionals and in everyday life activities once found acceptable. The use of the scheme in Figure 1 should help in clarifying confusing scenarios and to aid problem solving.

The suggestion of a debate is an original idea. The “new science of systems” consists of three general principles of systems implemented by linguistic modelling of static and dynamic states. Mathematics of uncertainty and topics from conventional science at the object level supplement the “new science” which together form the “scientific enterprise”. The notions of cognitive value and informative content of models are introduced for evaluating their cognitive worth.

The purpose is to forward systems theory one more step towards social theory and integrate problem-solving and theory-building, and search for the integration and unity of science by revealing the nature and role of critical systems thinking (CST).

This article describes relations between systems theory and social theory in three parts. First, it examines the links of systems methodologies with three social science approaches as well as the role of CST. Second, the focus of theory and the form of explanation are discussed from critical social science (CSS) perspective. Third, the direction of theorizing of a CST-based systems theory is investigated.

First, CST is a hidden assumption of system dynamics (SD)/systems thinking (ST). Second, systems theory is positioned in CSS. Third, CST integrates traditional and soft systems methodologies (SSM), and connects systems science and social science. Fourth, this article reveals hidden links between systems approaches and three corresponding social science approaches. Fifth, the theoretical focus of a CST-based systems theory could be formal/structure theory and/or substantive/content theory. Sixth, the form of explanation could be structural/mechanismic explanation combining causal and interpretive explanations. Seventh, a CST-based systems theory may adopt abduction, which complements a defect in deduction and induction in a difficulty of nonlinearity.

It illustrates a graph of the competing approaches in systems science corresponding to paradigms in social science.

Taiwan serves as a case study to investigate the association between the expansion and reform of higher education and the growth of science production. More specifically, what driving forces facilitated the growth of science production in different types of Taiwanese universities and other sectors, from 1980 to 2011.

The contribution charts differential contributions to overall production. Taiwanese data from Thomson Reuters’ Science Citation Index Expanded (SCIE) is analyzed to show the expansion of the higher education system and its relationship to the production of science. The author uses sociological organization theories to facilitate our understanding of how and why the landscape of science production changed.

Results show that the growth of science production is associated with processes of isomorphism and competition within the higher education system. Findings also suggest that universities quickly seized upon external opportunities and turned themselves into what is known as the “knowledge conglomerate.” Unique organizational features bolster universities’ position as the driving force behind advancing national innovation.

This study extends previous research by examining multiple sectors of higher education, using longitudinal and recent data, and highlighting themes that have been ignored or overlooked, such as competition and collaboration among universities and industry partners.

An emerging synthesis between natural and social sciences is discussed and the new science of “chaos” which originates in chemical researches is introduced. Educational systems are seen to be dissipative structures allowing analysis of them in “chaotic” terms. Such structures have a self‐organising dynamic which produces “second order” changes to a new regime. This has long been associated with analysis of leadership. The creative input of a single individual, though small, may lead to far‐reaching effects if guided by vision.

The paper attempts to provide an outline account of the development and context of scientific and technical communication during the twentieth century. The main channels and forms of communication are reviewed, and their changing contributions to the overall pattern of information flow. The ever‐increasing volume and diversity of scientific and technical information are emphasised. The paper concludes with some reflections on what may be learnt from this history.