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This conceptual paper aims to explore the current state of sustainability communication research, focusing on the challenges of communicating inconvenient truths in an era of scientific mistrust. Therefore, this study aims to (1) examine the existing research landscape in sustainability communication, (2) identify unresolved problems and challenges, and (3) propose strategies for counteract misinformation through targeted communication.

For this, the authors conducted a critical literature review and analyzed the resulting sample (n = 473 journal articles) by means of qualitative content analysis to (1) evaluate existing communication approaches dealing with the communication of sustainability's inconvenient truth, (2) identify stakeholder groups involved in sustainability communication, (3) discuss limitations of current communication approaches and (4) present recommendations on (more) effective communication strategies to address the unresolved issues in sustainability communication.

The analysis reveals that when it comes to sustainability communication and its unresolved problems, literature refers to four key stakeholder groups: (1) science deniers; (2) adaptation skeptics; (3) whitewashers and (4) world saviors. Furthermore, the analysis provides valuable insights into the complex dynamics involved in communicating sustainability, emphasizes the need for tailored approaches to engage and address the concerns of each stakeholder group, and exposes limitations in current communication methods and approaches. Accordingly, the analysis highlights the necessity of developing new theories, models and methods specific to sustainability communication to tackle its unique challenges effectively.

Like our society, communication sciences need a fundamental transformation to meet sustainability communication's new challenges induced by the necessary shift toward sustainable development.

This paper provides a comprehensive overview of the current state of sustainability communication in research, specifically addressing the challenges of effectively communicating unpleasant news in the context of scientific mistrust. It fills a gap in existing literature by examining the progress made in addressing these issues and identifying the emerging challenges that need to be addressed.

The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and interpretive plane. This allows for the automatic and reliable interpretation of results from the multiple correspondence analysis (MCA) as previously proposed and published. Consequently, the users can seamlessly apply these concepts to their data, both via R commands and a corresponding graphical interface.

Within the context of this study, and through extensive literature review, the advantages of developing software using the Shiny library were examined. This library allows for the development of full-stack applications for R users without the need for knowledge of the corresponding technologies required for the development of complex applications. Additionally, the structural components of a Shiny application were presented, leading ultimately to the proposed software application.

Software utilizing the Shiny library enables nonexpert developers to rapidly develop specialized applications, either to present or to assist in the understanding of objects or concepts that are scientifically intriguing and complex. Specifically, with this proposed application, the users can promptly and effectively apply the scientific concepts addressed in this study to their data. Additionally, they can dynamically generate charts and reports that are readily available for download and sharing.

The proposed package is an implementation of the fundamental concepts of the exploratory MCA method. In the next step, discoveries from the geometric data analysis will be added as features to provide more comprehensive information to the users.

The practical implications of this work include the dissemination of the method’s use to a broader audience. Additionally, the decision to implement it with open-source code will result in the integration of the package’s functions by other third-party user packages.

The proposed software introduces the initial implementation of concepts such as interpretive coordination, the interpretive axis and the interpretive plane. This package aims to broaden and simplify the application of these concepts to benefit stakeholders in scientific research. The software can be accessed for free in a code repository, the link to which is provided in the full text of the study.

This article aims to explain the role of philosophical anchors and research paradigms in business research, and how they can be extrapolated in the transformative era of automation, digitalization, hyperconnectivity, obligations, globalization and sustainability (ADHOGS) in the midst of disruption, volatility, uncertainty, complexity and ambiguity (DVUCA).

This article entails a general review based on the 3Es of exposure, expertise and experience, delving into the ontological, epistemological, methodological, axiological and rhetorical aspects of the major research paradigms—i.e. positivism, post-positivism, constructivism, interpretivism and pragmatism—and their interplay with the emergent trends shaping business research.

This article underscores the multifaceted nature of business research in the modern day, with an increasing need for blending, or shifting between, research paradigms to address the complex issues arising from automation, digitalization, hyperconnectivity, obligations, globalization and sustainability (ADHOGS). This article also highlights the nuanced interplay between research paradigms and theoretical perspectives, demonstrating the rich, diverse potential of business research inquiries.

While this article provides a broad overview of the interplay between research paradigms and emerging trends, future research could explore each of these interplays in greater detail, conducting empirical studies or utilizing specific case studies.

Researchers and practitioners should be open to adopting, combining or switching between different paradigms according to the demands of their research questions, context and trends shaping the business landscape, thereby underscoring the need for methodological flexibility and reflexivity in business research.

The shift toward embracing digital transformations and integrating sustainability in business research holds significant implications, driving socially responsible and sustainable business practices at the micro-level, and by extension, industrial revolution and sustainable development at the macro-level.

This article offers a holistic and contextualized view of the philosophy of science and research paradigms for business research, bridging the gap between philosophical foundations and contemporary research trends.

In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations for researchers using structural equation models.

This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.

There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.

Researchers should be more conscious, open and respectful regarding different research paradigms.

Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.

This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.

Being acquainted with both lean and action learning in theory and in practice, this study finds that the theoretical complementarity of these two research streams has traditionally been underexploited. In this conceptual paper, this study aims to advance the theoretical understanding of lean by exploring the complementarity of lean thinking and action learning leading to a proposed integrated theory of these two research streams. Target audience is the operations management research community.

By deliberately adopting a process of theorising, this paper explores, reflects upon and combines individual experiences of researching, teaching and engaging in lean and action learning as operations management scholars.

Having taken a gemba walk through the literature and practices of lean and action learning, this study views and notices a systematic and complementary relationship between the two domains. The overlapping theoretical and practical complementarities of lean and action learning suggest that these two research streams are ripe for synthesis into an integrated theory. This finding provides an opportunity to (1) progress towards an integrative design of interventions leading to more sustainable lean system adoptions and (2) add new depth to our theoretical explanation of the success and failures of lean system adoptions.

This paper contributes an original integrated theory perspective on lean and action learning.

This study aims to construct an evaluation system for farmers’ livelihood capital in minority areas and evaluate the impact of relocation in response to climate change on farmers’ livelihood capital.

According to the characteristics of Yunnan minority areas, the livelihood capital of farmers in minority areas is divided into natural, physical, financial, social, human and cultural capital. The improved livelihood capital evaluation system measures farmers’ livelihood capital from 2015 to 2021. The net impact of relocation on farmers’ livelihood capital was separated using propensity score matching and the difference-in-difference (PSM-DID) method.

The shortage of livelihood capital makes it difficult for farmers to resist climate change, and the negative impacts of climate change further aggravate their livelihood vulnerability and reduce their livelihood capital. Relocation has dramatically increased the livelihood capital of farmers living in areas with poor natural conditions by 15.67% and has enhanced their ability to cope with climate change and realise sustainable livelihoods.

An improved livelihood capital evaluation system is constructed to realise the future localisation and development of livelihood capital research. The PSM-DID method was used to overcome endogeneity problems and sample selection bias of the policy evaluation methods. This study provides new ideas for academic research and policy formulation by integrating climate change, poverty governance and sustainable livelihoods.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

The purpose of the current study is to assess Omani teachers’ performance on tasks related to the stages of engineering design. To achieve this, data from an engineering design test was used, and demographic variables that are correlated with this performance were identified.

This descriptive study employed a cross-sectional design and the collection of quantitative data. A sample of preservice science teachers from Sultan Qaboos University (SQU) (n = 70) participated in this study.

Findings showed low and moderate levels of proficiency related to the stages of engineering design. Differences between males and females in terms of performance on engineering design tasks were found, with females scoring higher overall on the assessment. Biology preservice teachers scored higher than teachers from the other two majors (physics and chemistry) in two subscales. There were also differences between teachers studying in the Bachelor of Science (BSc) program and the teacher qualification diploma (TQD) program.

This study provides an overview, in an Arab setting, of preservice science teachers’ proficiency with engineering design process (EDP) tasks. It is hoped that the results may lead to improved instruction in science teacher training programs in similar contexts. Additionally, this research demonstrates how EDP competency relates to preservice teacher gender, major and preparation program. Findings from this study will contribute to the growing body of research investigating the strengths and shortcomings of teacher education programs in relation to science, technology, engineering and mathematics (STEM) education.

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

Relations in university settings are becoming more heterogeneous in terms of race, ethnicity, religion, nationality, class, and gender. In South Africa, transformation imperatives have radically changed the complexion of the country’s university campuses but have also entrenched political imperatives in its universities. As a consequence, the university is a highly politicised space. This is not new. What is new is a communication environment characterised by real-time, global networked digital communication and the uptake of digital media platforms (including social media platforms). We explore the effects of politicisation and new modes of communication using the case of a controversial article published in a South Africa journal and the ensuing polemic. Drawing on both institutional theory and Castells’ description of the network society, we conceptualise collegiality along two dimensions: horizontal collegial relations which exist for the purpose of knowledge creation and transfer which, in turn, depends on self-governance according to a taken-for-granted code of conduct; and vertical collegiality which describes collegial relations between academic staff and university management, and which is necessary for the governance of the university as a complex organisation. We conclude that the highly personal nature of communication that is propelled by digital communication has a direct impact on collegial relations within the university. The motivations of both university academic staff and management, as well as the public, extend beyond stimulating collective debate in the service of knowledge production to serving individual and/or ideological agendas as the communication of science becomes politicised. While issues pertaining to collegiality in South Africa may at first glance appear to be unique to the country, we believe that in a globally transforming academy, the South African case may offer novel insights and useful lessons for other highly politicised university systems.