This research explores the characteristics of green influencer messages on follower engagement by examining the interplay between message framing (gain vs. loss), construal level (high vs. low), and post timing (weekdays vs. weekends). Green influencers (also: greenfluencers or sustainable influencers) are considered a key agent for a change to more sustainable consumption. A pilot field study of 1000 green influencers, however, indicates that the current communication practices of green influencers (which strongly focus on gain frames, low construal, and posts during the week) are not ideal for maximizing engagement and sustainable behavioral intentions. Two experiments replicate this finding and establish the process through which green influencer posts affect engagement: gain frames increase fluency, which increases engagement; low construal levels decrease psychological distance, which increases engagement. Timing moderates these processes in that weekend posts increase the engagement with gain frames and week posts increase the engagement with low-construal frames. These findings highlight that there is no silver bullet in green influencer messages, but that green influencers need to adapt the framing and construal of their messages to the posts' timing to increase their contribution to more sustainable lifestyles and the greater good.

In today's data-driven era, ubiquitous concern about environmental issues pushes more startups to engage in business model innovation that promotes environmentally friendly technologies. The goal of these startups is to create technology-based products and services that enhance environmental sustainability. In this context, artificial intelligence promises to be a key instrument to create, capture, and deliver value. However, the existing literature lacks a deep understanding of how startups using AI innovate their business models to achieve a positive environmental impact. Therefore, this paper investigates how green technology startups utilize AI from a business model innovation perspective for environmental sustainability. We conduct a qualitative, exploratory multiple-case study using the Eisenhardt methodology, based on interview data analyzed using qualitative content analysis. We derive five predominant manifestations for AI-driven business model innovation and identify archetypical connections between business model dimensions. Further, we establish three overarching archetypical associations among the cases. In doing so, we contribute to theory and practice by providing a deeper account of how green technology startups attempt to maximize their positive environmental impact through AI. The results of this study also highlight how business model innovation driven by AI can support society in securing a more environmentally sustainable future.

Purpose When CEOs are publicly weighing in on sociopolitical debates, this is known as CEO activism. The steadily growing number of such statements made in recent years has been subject to a flourishing academic debate. This field offers first profound findings from observational studies. However, the discussion of CEO activism lacks a thorough theoretical grounding, such as a shared concept accounting for the heterogeneity of sociopolitical incidents. Thus, the aim of this paper is to provide an archetypal framework for CEO activism. Design/methodology/approach The authors used a multiple case study approach on 145 activism cases stated by CEOs and found seven distinct statement archetypes. Findings The study identifies four main structural design elements accounting for the heterogeneity of activism, i.e. the addressed meta-category of the statement, the targeted outcome, the used tonality and the orientation of the CEOs’ positions. Further, the authors found seven distinguishable archetypes of CEO activism statements: “Climate Alerts”, “Economy Visions”, “Political Comments”, “Self-reflections and Social Concerns”, “Tech Designs”, “Unclouded Evaluations” and “Descriptive Explanations”. Research limitations/implications This typology classifies the heterogeneity of CEO activism. It will enable the analysis of interrelationships, mechanisms and motivations on a differentiated level and raise the comprehensibility of research-results. Practical implications The framework supports executives in understanding the heterogeneity of CEO activism and to analyse personality-fits. Originality/value To the authors’ knowledge, this marks the first conceptualisation of activism developed cross-thematically. The work supports further theory-building on CEO activism.

The complexity of the public value discussion has hindered the development of consensual measurement guidelines for use in public administration practice. This article explores the use of the cost-benefit analysis (CBA) framework in the transportation sector and considers its relevance in assessing public value. A case study is presented on the reconfiguration of a public transport network in the municipality of Arganil, Portugal. The CBA did not fully capture the effects of the network reconfiguration, demonstrating its limitations in assessing public value.

When organizations leverage artificial intelligence (AI) to automate processes previously performed by people, it frequently causes uncertainty and fear among those affected. An often suggested way for organizations to navigate such challenges is to seek guidance from AI ethics principles. Leaders, however, find it difficult to make practical use of these abstract, high-level principles. Based on a case study of the large-scale implementation of robotic process automation at an energy service provider in Germany, we provide recommendations for translating AI ethics principles into practice.

Industrie 4.0 bringt neben vielen Potenzialen auch eine erhebliche Komplexitätssteigerung mit sich. Um dieser effektiv zu begegnen, bieten Demonstratoren einen wertstiftenden Beitrag. Ihr Einsatz erlaubt eine nutzerzentrierte Systementwicklung mit einhergehender Komplexitätsreduktion durch Modellierung und Simulation. Dieser Beitrag untersucht ihre Potenziale am Beispiel des Projektes „ConSensE“ mit Fokus auf Sensortechnologien und deren Nachrüstung.

Über die Analyse des Finfluencer-Marktes und die Erhebung von Anforderungen an die Kooperation zwischen Finfluencern und börsennotierten Unternehmen hinaus umfasst das hier vorgestellte Kooperationsprojekt einen dritten Schritt, der auf eine Qualitätsbewertung von Finfluencern abzielt. Ein Team der HHL Leipzig hat zu diesem Zweck ein Scoring-Modell entwickelt, das im Folgenden kurz vorgestellt wird.

The opacity of the impact investment decision-making process is one of the main constraints hampering further growth in the impact investing ecosystem. This paper takes a differentiated view on why (investment motivation) and how (investment decision criteria) the major private impact investor types allocate funding to investees. We incorporate insights from 34 interviews with the five major impact investor types: social business angels, foundations, social banks, impact investment funds, and crowdvesting platforms. We find that motivation and decision-making significantly differ between the impact investor types, especially concerning strict vs. ambiguous impact definitions, active vs. passive investment approaches, and return requirements reaching from capital preservation to market-driven returns. By providing a differentiated overview of the investor type-specific motivations and most important investment criteria, our study offers social entrepreneurs a roadmap to identify the most appropriate impact investors for their business model.

Purpose In public management research, the focus in the public value debate has been on public administration organizations’ broader societal outcomes. Public value describes how public administrations form a vital part of the social context in which people develop and grow. However, there has not yet been an analysis of how public administration contributes to happiness in society. Design/methodology/approach In this study, we empirically analyze the relationship between people’s happiness and the public value of public administration. Our approach is based on a unique Swiss survey dataset comprising 870 individuals. Findings We find a positive relationship between public administration’s public value and happiness. We also find preliminary evidence with a moderation analysis that the relationship between a value-creating public administration sector and self-reported happiness is stronger for public administration employees. Research limitations/implications While correlation studies cannot claim causal explanations and common method bias may additionally limit any research in social science, we took a number of measures to mitigate related problem. We tested our model in two samples and took both several procedural techniques and a survey design minimizing common method bias. Practical implications The paper discusses implications for public sector performance measurement for public management and practitioners. Social implications This study calls for a more positive view on the multiple functions public administration performs for society. After an era of critical voices, our study helps reclaim public administration as a positive force for society at large in times of grand challenges, such as climate crisis, demographics and digitization. Originality/value This study has highlighted the importance between public administration’s public value and happiness in Swiss public service organizations. The study also showed that an employment in the public administration contributes to the happiness of individuals and beyond to society.

Over the last decade, the green bond market experienced strong growth rates fueled by the need to combat climate change. However, the discourse on enhancing the effectiveness of green bonds primarily revolves around regulatory measures, often overlooking the possibility of designing inherent incentives. We show that a green bond with a coupon structure positively related to the carbon price development stimulates (early) investment in an emission-reducing project and creates higher net present values (NPVs) when applied in project financing. In our simulation-based framework, we model carbon prices using a geometric Brownian motion, and create a general optimal stopping time problem regarding the start of the project. The green bond in our setting carries the risk of default, also mitigated by its carbon price-linked coupon structure.