Browsing by Subject "responsibility and sustainability e.g. SDGs"

In the domain of education, myths and misconceptions function as invisible barriers, impeding evidence-based teaching and learning practices. Despite robust refutation, these so-called zombie concepts persist, deeply embedded within cultural and institutional frameworks, often making mythbusting seem like a Sisyphean task. This blog post, I examine the dual nature of mythbusting in education: its perceived futility and its undeniable necessity. I argue that while debunking myths is daunting and often feels akin to a battle against windmills, it remains a critical endeavor to foster evidence-informed practices. I outline some challenges involved in changing entrenched misbeliefs but at the same time propose some strategies to mythbusting, such as targeting the undecided middle, fostering mental immunity, and prioritizing the most harmful/impactful myths.

Leaders develop via all domains of their lives. Yet, leaders’ sports involvement has been largely overlooked despite its theoretical and practical relevance, particularly for social development. Moreover, the limited research on the downstream social consequences of leaders’ sports involvement reveals different effects for men and women leaders—even opposing effects for the latter. Thus, we integrate social cognitive theory from developmental psychology to make sense of these contradictory findings. We theorize that sports contexts facilitate women’s networking with higher-status (male) leaders through its playfulness (i.e., leisurely, spontaneous, and socially interactive). An archival study of 644 leaders’ Twitter/X posts shows that sports generate more engagement—especially men interacting with women leaders’ sports posts (Study 1). A qualitative study with 58 leaders suggests sports’ playfulness facilitates these interactions as well as networking, results that we also quantitatively validated using ChatGPT (Study 2). Two recall experiments (Ntotal = 1,076) showed women leaders’ networking in sports (vs. traditional) contexts was more playful, and more playful sports contexts facilitated women (vs. men) leaders’ networking across gender and status differences (Pilot Study, Study 3). Our results show that more playful sports contexts facilitate women leaders’ successful networking across gender and status diversity—an innovation helping to level the playing field of gendered social capital development and future leadership inequalities in organizations. These results advance our understanding of conventional ways of networking as not always strategic and planned while also adding to diversity research by showing that sports—often framed as exclusionary—can also be inclusive.

Teaching-related knowledge management (TKM) extends beyond the storage of lesson plans and materials. It encompasses processes such as knowledge creation, sharing, application, and preservation, empowering educators to transform information into actionable insights for professional growth and improved teaching outcomes. However, TKM is often misunderstood, with prevalent myths reducing it to mere data management, technology reliance, or archival activities. This post critically examines these misconceptions and advocates for a reimagined approach to TKM. By focusing on active engagement, reflection, and adaptation, educators can leverage TKM to enhance their practices, foster continuous learning, and enrich student experiences.

In recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross-disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro- and micro-organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled “Algorithmic Management: Toward a Cross-Disciplinary Research Agenda” delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants highlighted that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions.

Banks typically attempt to quantify climate-related risks, whether physical or transition ones, by adopting a top-down or a bottom-up analytical approach for the risk estimation of their borrowers. The two analytical approaches for risk estimation are regarded as mutually exclusive, when, in reality, they can complement each other in a mutually beneficial way. We discuss the challenges and opportunities of both analytical approaches with a focus on their applicability for commercial banks’ loans, and highlight directions for future research.

Carol Gorelick sets the stage for an interactive and collaborative learning experience. Bill Torbert pitches Collaborative Developmental Action Inquiry (CDAI) as the key modality in action research. Danny van Montfort, Freek Sanders and Tobias Fehr-Bosshard provide spotlights from their ongoing action research PhD journeys and their experimentations with CDAI.

This edited collection explores the past, present, and future of artificiality and sustainability in entrepreneurship, the unforeseen consequences, and how to head forward to a sustainable future. First, we integrate the concepts of entrepreneurship and artificiality. We propose that entrepreneurs produce artefacts of entrepreneurship - new ventures, entrepreneurial firms, etc. - that have functions and goals set to respond to the conditions of the diverse environments in which they operate. Second, we contend that the prevailing technological environment can be perceived as an artefact that significantly impacts entrepreneurs, new ventures, and entrepreneurial firms. Digital technologies effectuated new forms of ventures such as born-digital and transformed incumbents to adopt them. Digital technologies come with virtualising our everyday environments and induce behavioral and cognitive changes, which call for new capabilities, e.g., dynamic capabilities. Finally, we conclude with further research questions to be addressed by the entrepreneurship, technology management and sustainability scholars.

The generally accepted definition of sustainability's has a future orientation where "the needs of the present" are satisfied "without compromising the ability of future generations to meet their own needs” (Brundtland, 1987). That sustainability is at the firm level (as in von Carlowitz, 1712) is an increasingly self-evident proposition. Yet leaders aspiring to make their organizations sustainable face a multitude of challenges, and not exactly because of a lack of choice in the CSR and ESG options available to them. Bafflement can easily turn into frustration when inconsistency, the lack of connection to the firm’s business model or poor-quality data become apparent. On the other hand, progress towards applying sustainability has been considerable over the last decade as exemplified by the ‘big’ global ESG framework and standard-setting organizations. Yet despite the progress made by the copious number of frameworks and measurements, serious issues and blind spots persist. For instance, monopoly positions, subsidies or regulatory privileges are clearly unsustainable and yet rarely captured by existing sustainable frameworks and measurements. This is but one issue—a review of all those identified in the academic and practitioner literature is the paper's first step. In a second step, this paper proposes requirements for sustainability frameworks and measurements. These include: (i) comprehensive capture of sustainable activities; (ii) comprehensive capture of unsustainable activities; (iii) pricing all the value creation and appropriation of the firm; (iv) measuring business model sustainability in relation to the financial statement; (v) measuring the balance of the business model’s sustainable and unsustainable activities. In the third and final step, the paper discusses two sustainable value creation measurements (VCr/VCp) anchored in a multi-disciplinary body theory while developing specific metrics for their calculation. Once empirically validated, the VCp/VCr measurements might inform managers and investors in their choices, inform public policy and could even be employed to adjust equity valuations and credit ratings.

The increasingly prevalent diet-related non-communicable diseases (NCDs) constitute a modern health pandemic. Higher nutrition literacy (NL) correlates with healthier diets, which in turn has favorable effects on NCDs. Assessing and classifying people's NL is helpful in tailoring the level of education required for disease self-management/empowerment and adequate treatment strategy selection. With recently introduced regulation in the European Union and beyond, it has become easier to leverage loyalty card data and enrich it with nutrition information about bought products. We present a novel system that utilizes such data to classify individuals into high- and low- NL classes, using well-known machine learning (ML) models, thereby permitting for instance better targeting of educational measures to support the population-level management of NCDs. An online survey (n = 779) was conducted to assess individual NL levels and divide participants into high- and low- NL groups. Our results show that there are significant differences in NL between male and female, as well as between overweight and non-overweight individuals. No significant differences were found for other demographic parameters that were investigated. Next, the loyalty card data of participants (n = 11) was collected from two leading Swiss retailers with the consent of participants and a ML system was trained to predict high or low NL for these individuals. Our best ML model, which utilizes the XGBoost algorithm and monthly aggregated baskets, achieved a Macro-F1-score of .89 at classifying NL. We hence show the feasibility of identifying individual NL levels based on household loyalty card data leveraging ML models, however due to the small sample size, the results need to be further verified with a larger sample size.

The global food system accounts for 25–30% of anthropogenic greenhouse gas emissions. A large share of these emissions is due to individual food shopping patterns. Despite the rising concern about the environment, many individuals fail to act upon it and change their food consumption. In this study, we attempt to motivate individuals to reduce their food-shopping-induced environmental footprint. To narrow the intention-behavior gap, we propose a novel technical system that gives automated near-term sustainability feedback on individuals’ food shopping recorded on digital receipts and communicates this feedback through the mobile application BetterPlanet, Based on a small sample (n = 8), we find a directional decrease in the overall CO2-Scores. Therefore, our study demonstrates the technical feasibility of automated sustainability feedback from digital receipts. The proposed energy-weighted CO2-Scoring Model contributes to the growing knowledge body of sustainability assessment.