Social Entrepreneurship & Innovation

For-profit social enterprises are facing the dual challenges of fulfilling social purpose on the one hand and surviving business competition on the other. Being a sustainable for-profit social enterprise, the company must balance between economic, social and environmental aspects throughout their business operations. In order to achieve the desired end of sustainability, organization need to keep learning about the social needs and the business environment in order to develop sustainable business processes, and better fulfill their purpose as organizations formed to create social value. The study aims to fill the gaps in sustainability research literature about organizational learning in for-profit social enterprises by exploring how effective learning processes occur at individual, group and organizational level and how to facilitate these learning processes to improve sustainability. The study develops an analytical framework by combining the 4I framework for organizational learning process (Crossan et al., 1999) and an AKO (activities, knowledge source, outcomes) framework for understanding learning activities, knowledge sources and learning outcomes. Four for-profit social enterprises in both Denmark and Sweden are chosen as cases. Based on findings, three organizational learning mechanisms are identified on selected cases. Practical implications and insights are also generated for for-profit social enterprises to facilitate organizational learning for sustainability.

Academics, practitioners, and policymakers are devoting heightened attention to social entrepreneurship: the creation and pursuit of innovative opportunities to produce positive externalities that improve conditions harmful to society. Scholars from across the behavioural, managerial, and organizational sciences are increasingly studying social entrepreneurs and their activities. However, one discipline -economics- is underrepresented in social entrepreneurship research. To address the lack of integration between economics and social entrepreneurship, we identify the unique economic characteristics of social entrepreneurship and explain how adopting an economic lens stands to generate important insights about the phenomenon. We then isolate three potential connection points between work in social entrepreneurship and economics: institutional economics and multi-logic hybrid organizations, narrative economics and social entrepreneurship discourse, and the economics of emotion and social entrepreneurs' emotions. Our integration of social entrepreneurship and economics contributes to scholarship in both domains and identifies avenues for research at the intersections of the two disciplines.

Despite the ubiquity of small towns, the forces shaping entrepreneurship in cities of limited size, reach, and scope are unexamined. To address the lack of attention to small town entrepreneurship, a comparative-case study of two small towns (Newton Falls, Ohio and Geneva, Ohio) was conducted. The study examines how and to what extent entrepreneurial activity manifests in small towns and identifies the strategies and contextual forces that promote and hinder small town entrepreneurship. Findings reveal (a) a variety of entrepreneurial activities occur in small towns, (b) community members engage in market and community-based strategies to encourage entrepreneurship, and (c) there is an ecosystem of economic and community dynamics that spur and discourage entrepreneurial activity. The findings contribute to research on entrepreneurship and economic development in small towns and generate practical implications for policymakers and entrepreneurs.

Social innovations and their diffusion are critical in bridging the multiplicity of deprivations experienced by those in subsistence contexts. Yet they often do not diffuse as expected. To better understand this prevalent problem, this article develops a theory of diffusion that explains the reproduction (duplication) of social innovations in subsistence contexts. The theory utilizes a bottom‐up perspective that considers what attributes of innovations and capacities of actors matter to reproduction, particularly for subsistence user‐producers. Adopting an inductive, case‐based approach, the authors draw on examples of social innovations in sub‐Saharan Africa. Based on the authors' research and extant literature, this article builds a typology that captures different modes of reproduction. The typology delineates three archetypes of reproduced social innovations: mimetic, facilitated, and complex, and notes how frugal innovations can emerge from these archetypes. These archetypes are based on the interactions of: (1) a product's resource and knowledge complexities, and (2) the knowledge capabilities or resources of various actors, including subsistence user‐producers and bridging agents. The typology thus illuminates the conditions under which subsistence user‐producers might independently reproduce a social innovation (mimetic innovations), when they need assistance from bridging agents (facilitated innovations), and when the mix of resources and knowledge are beyond their capacity (complex innovations). Moreover, by exploring reproduction experiences of subsistence users, this article recognizes the implications of low literary, close social networks, and physical limitations. By examining who controls the knowledge and resources imperative to reproduction, the authors go beyond a focus on the social benefits of innovations to consider how intellectual property and profits matter to different actors. This article pulls together these various insights and identifies key implications that social innovators and intermediaries should consider when working to reproduce social innovations in subsistence contexts and with subsistence user‐producers.

Practitioner Points
The article develops a theory of the reproduction of social innovations (SI) from the perspective of subsistence producer‐users, noting how literacy, closely linked relationships, physicalities, and access to resources and knowledge can affect the reproduction process.
A typology is created to help practitioners understand why SI do or do not “go viral” through reproduction and when bridging agents are needed. (Un)Successful reproductions hinge on whether subsistence user‐producers can feasibly acquire/manage two intersecting dimensions of SI—complexities of resources and complexities of knowledge.
Three archetypes of SI are proposed. Complex: subsistence users may consume but will likely not produce (e.g., MPesa). Mimetic: subsistence users can readily produce on their own (e.g., simple solar cookers). Facilitated: subsistence users require bridging agents to enable reproduction (e.g., water ponds).
Practitioners need to consider the heterogeneity in subsistence users' resources, knowledge, and physical capabilities, train for the “know‐hows” and the “know‐whys” in reproduction, address subsistence user‐producers' potential risks/costs, support bricolage behavior, and recognize trade‐offs in the competitive accrual of social and economic benefits.

This paper reviews the literature on green marketing intervention strategies and sustainable development with an emphasis on green marketing intervention strategies to environmental problems facing the world today. The review indicates that individuals and organizations can benefit from green marketing strategies and at the same time protect the environment to achieve sustainable development. The weaknesses and the future of green marketing as a discipline and future directions for researchers are also reviewed.

Social entrepreneurship is an emerging entrepreneurial concept accompanied by an increase in the social driven enterprises, in addition to the lack of commercial enterprises, which meet the social needs for individuals and community. Social enterprise legal formats can be "for-profit" enterprises or "not-for-profit" enterprises, where the essential part of social enterprise is having social value proposition that provides a social value and meet the social aims of an entrepreneur. Additionally, business modeling is an emerging entrepreneurial concept that has received limited attention from scholars. Consequently, there is no clear agreement between scholars on a unified definition, structure, features, characteristics and evolution of the business model. Some scholars argue that many startups fail, even if they have unique idea, have passion, have sufficient resources and have attractive market opportunity; their failure may come from a poor and immature business model behind the startup. Hence the importance of a business model for the success of startups and entrepreneurs, whether a traditional startup or a sustainable-social startup.. Accordingly, this paper focuses in social enterprises and help social entrepreneurs in taking the decision related to choosing a suitable business model that translates all their social and financial values and aims. This is accomplished through discussing business models types, definitions and analyzing their pros and cons, especially the traditional and sustainable business models. The main output of the paper proposes a hybrid social business model (HSBM) that combines traditional and sustainable-social models. This business model can be used as a tool by social enterprises, creating a balance for the social impact and financial values of their social enterprise. Also, it helps in translating their social and financial aims in a structured and tailored way that suits the nature of their enterprises.

Literaturessay zu Mariana Mazzucato: The Value of Everything. Making and Taking in the Global Economy, London 2018 (dt. Wie kommt der Wert in die Welt? Von Schöpfern und Abschöpfung. Aus dem Englischen von Bernhard Schmid, Frankfurt am Main/New York 2019)).

Entrepreneurship Education (EE) is a study relating to the Practice(s) of Entrepreneurship. It consists of the theoretical/academic skills, competencies, technicalities and psychological awareness required of an individual in the birth, growth and development of a Business idea into a Profitable venture. Entrepreneurship Training (ET) is the practical aspect of Entrepreneurship. It is meant to equip individuals, entrepreneurs and small business owners on the technicalities required in the running, survival and development of a business venture. Entrepreneurship Education and Training is being regarded as the path way to the Practice(s) of Entrepreneurship. Entrepreneurship/vocational training has been one of the most sort after activities by Entrepreneurship trainers/facilitators in recent years, but too little has been said on its impact on Student owned business/enterprise in Nigeria. This study is aimed at knowing the impact of Entrepreneurship Education and Training (EET) on the development of Student Owned Enterprise in Nigeria. Using the Secondary Method of data collection, the study made use of existing literatures on Entrepreneurship Education by authors in the Entrepreneurship and Business management field in the world.  The study found out that the inclusion of Entrepreneurship Education in Nigerian Institution’s syllabus has led to the rapid rise of student owned enterprise on the University campus. The study also found out that Entrepreneurship Training (ET) has majorly impacted students with the skills and technicalities needed for the development and sustenance of their business. It was concluded from the study that Entrepreneurship Education and Training are needed for the survival and development of Student Owned Business Enterprise in Nigeria. The study made recommendations to the Government of the Nation, young individuals, entrepreneurship educators, vocational trainers, existing university based business incubators.
Keywords: Entrepreneurship, Entrepreneurs, Training, Education, Impact, Survival, Development, Student, Enterprise

If we look at Bauhaus as business excellence model, we have to look at the power of business' men like Walter Gropius and Mies van der Rohe, and their influence in industrial design and architecture in practice AND in design education in history. Focussing Bauhaus presence and education system for creative industries, these personalities used their income and their market awareness to organise the design school. Their buildings demonstrated that Bauhaus teacher occupied constructing architecture for eternity-matching to the spirit of modernity, but always with support by rich entrepreneurs and an intellectual playground. Teacher at Bauhaus were used to create market suitable products, but very often profit was based on "partnerships" with women at Bauhaus. They gave great impulse for "new" design and architecture: beneficial partnerships, based on mixed teams, but not in time to announce women as official project-partner. Beside this, beneficial economic, practise based projects mirrored back the drive of interdisciplinary combined courses of Bauhaus for a changing market. Following design education strategies, today we use concepts like thinking design in interdisciplinary AND hierarchy less AND cross cultural creative playground in succession of Bauhaus education heritage, to come to advanced business models in design /-education. Further aspects of the long paper:-Bauhaus: influence in industrial design history-Relationship in economic interests and the genius of male creative minds at Bauhaus and their ideal partnership: case studies: Lilly Reich, Lotte Stam-Beese, Anni Albers-Who is interested in practice based / applied solutions for industrial products-what a kind of market / demands-Thinking Design in relation to design education history in Germany-Retroactive effect for industrial design education BRANDS in history and tomorrow References:

Sappiamo che la tecnologia ha il potenziale per trasformare i nostri sistemi d’istruzione. Governi, ONG e fondazioni stanno investendo cospicue risorse nel tentativo di migliorare le scuole attraverso la tecnologia.

Ma cosa rende questi ambiziosi investimenti in tecnologia efficaci e incisivi nel cambiamento?

Per rispondere a questa domanda il progetto di ricerca “Making the most of technology in education systems” ha analizzato nove casi di studio (tre in Italia, sei dal resto del mondo) che suggeriscono modelli sperimentali per la valorizzazione degli investimenti tecnologici nelle scuole, con nuovi ruoli e approcci assunti da policy-maker, dirigenti scolastici, insegnanti e studenti.

Este artigo aborda uma realidade que, não sendo completamente nova, mereceu nos últimos anos particular atenção no que concerne à sua teorização e delimitação: o fenômeno (conceito e prática) da “inovação social”. Na primeira parte, a análise focaliza a diversidade de concepções que se tem produzido em torno da definição da inovação social, conforme se olha o fenômeno como resposta a problemas sociais e a condições sociais, ou é primordialmente concebido no
contexto da governança democrática e da vontade de transformação social. Por julgarmos possível, e desejável, entabular pontes entre modelos que, portadores de pressupostos importantes, se revelam incompletos na sua formulação própria, avançamos, na segunda parte do texto, com a proposta de um novo modelo estratégico para a inovação social local, que é distinto das duas concepções anteriores.
Essa proposta é a de que se interprete o conceito de “inovação social”,
quando associado a uma estratégia de desenvolvimento local, como composto por dois eixos fundamentais: um eixo instrumental (inovações setoriais + governança e externalidades) e um eixo político (learning communities + missão social e visão transformadora). No âmbito de tal proposta, estimam-se ainda as implicações práticas decorrentes da adoção deste modelo.

Abstract – EN

What opportunities and risks will artificial intelligence (AI) bring along? How will work change in the coming decade? How and to what extent will these changes affect South Tyrol in particular? The aim of my bachelor thesis is to attempt answering these questions, analysing the general impact of artificial intelligence on work through a review of the main literature on the topic and empirically researching the specific effects that AI will have on the South Tyrolean labour market.
To analyse how technology affects production and labour demand this thesis will use the model proposed by Acemoglu and Restrepo (2019a). According to this model, the AI does not only increase labour productivity, it also shifts the distribution of tasks towards one of the two factors of production, namely labour and capital. The resulting perspective shows that technology always displaces labour in favour of capital, but it also has the potential to create brand new tasks that require human labour. The literature suggests that the most impacted jobs will be routine ones, both manual and cognitive. However, AI is increasingly taking over almost every kind of job from the low-skill to the high-skill ones, the most affected sectors being transport, finance, manufacturing and construction. Nonetheless the studies show that it has the potential to transform and enhance already existing jobs through the integration of human work and technology as well as to create brand new tasks and occupations.
The final part of the thesis presents the outcomes of an empirical research conducted on 214 firms operating in South Tyrol. The results of the on-line survey are generally in consonance with the findings presented in the literature review. Although the majority of the firms in South Tyrol are not using AI technologies yet, they are planning to introduce them within the next 10 years. Firms which are already using them witness an increase in productivity and the creation of new tasks. The overall perception is that AI will provide both new challenges and chances for workers and increase the quality and safety of work.

Keywords: artificial intelligence, AI, labour market, South Tyrol, industry 4.0
 
Abstract – IT

Quali possibilità e quali rischi porta con sé l’avvento dell’intelligenza artificiale (IA)? Come cambierà il mondo del lavoro nei prossimi dieci anni? In che modo questi cambiamenti interesseranno l’Alto Adige in particolare? La mia tesi di laurea cercherà di dare risposta a queste domande, analizzando l’impatto generale dell’intelligenza artificiale sull’occupazione grazie a un’attenta revisione della letteratura sul tema e ricercando nello specifico gli effetti dell’intelligenza artificiale sul mercato del lavoro altoatesino.
Per analizzare come la tecnologia influisca sulla produzione e la domanda di lavoro verrà usato il modello proposto da Acemoglu e Restrepo (2019a). Secondo questo modello la tecnologia non aumenta solo la produttività del lavoro, ma ha principalmente l’effetto di spostare l'allocazione dei compiti verso uno dei due fattori di produzione, lavoro e capitale. Ne risulta che la tecnologia di per sé riduce sempre il lavoro a favore del capitale, ma può anche creare compiti completamente nuovi per i quali torna ad essere necessario il lavoro umano. La letteratura suggerisce che gli impieghi più toccati saranno quelli di routine, sia manuali che cognitivi. Tuttavia, l'IA sta progressivamente subentrando a un numero di lavori sempre maggiore, dai meno ai più altamente qualificati, ed i settori più colpiti sono i trasporti, la finanza, la produzione e l'edilizia. Ciò nonostante, gli studi dimostrano che l’IA ha il potenziale per trasformare e migliorare i mestieri già esistenti attraverso l'integrazione del lavoro umano con la tecnologia, nonché per creare compiti e occupazioni completamente nuovi.
L’ultima parte della tesi presenta i risultati di una ricerca empirica condotta su 214 aziende attive in Alto Adige. I risultati del sondaggio on-line sono generalmente in accordo con quanto emerso dall’analisi della letteratura. Sebbene la maggior parte delle aziende in Alto Adige non utilizzi ancora le tecnologie di IA, esse prevedono di introdurle entro i prossimi dieci anni. Le aziende che già utilizzano l’IA stanno riscontrando un aumento della produttività e la creazione di nuove mansioni all’interno dell’azienda. Nel complesso, la percezione è che l'IA presenterà sia nuove sfide che opportunità per i lavoratori e aumenterà la qualità e la sicurezza del lavoro.

Parole chiave: intelligenza artificiale, IA, mercato del lavoro, Alto Adige, industria 4.0 

Abstract – DE

Welche Chancen und Risiken birgt das Aufkommen der künstlichen Intelligenz (KI) in sich? Wie wird sich der Arbeitsmarkt im kommenden Jahrzehnt verändern? Wie und inwieweit werden sich diese Veränderungen auf Südtirol auswirken? Das Ziel meiner Bachelorarbeit besteht in der Beantwortung dieser Fragen, was zum einen durch die Analyse der allgemeinen Auswirkungen der KI auf den Arbeitsmarkt unter Bezugnahme auf relevante Fachliteratur und zum anderen durch die Beleuchtung der Ergebnisse der durchgeführten Untersuchung zu den spezifischen Auswirkungen der KI auf den Südtiroler Arbeitsmarkt erreicht werden soll.
Zur Analyse des Einflusses der KI auf Produktion und Arbeitsnachfrage wird das von Acemoglu und Restrepo (2019a) vorgeschlagene Modell angewendet. Nach diesem Modell bewirkt die KI nicht nur eine Steigerung der Arbeitsproduktivität, sondern auch eine Verlagerung der Aufgabenverteilung auf einen der beiden Produktionsfaktoren, nämlich Arbeit und Kapital. Demzufolge verdrängt die Technologie immer Arbeit zugunsten des Kapitals. Obwohl dem so ist, birgt sie auch das Potential in sich, völlig neue Aufgaben zu schaffen, die den Einsatz menschlicher Arbeit erforderlich machen. Die Fachliteratur weist darauf hin, dass Routinearbeiten, sowohl manueller als auch kognitiver Art, am stärksten betroffen sind. Allerdings übernimmt die KI in zunehmendem Maße gering bis hoch qualifizierte Aufgaben, wovon im Besonderen die Sektoren Verkehr, Finanzen, Manufaktur und Bauwesen betroffen sind. Dennoch zeigen Studien, dass die KI es vermag, bestehende Erwerbstätigkeiten durch die Integration von menschlicher Arbeit und Technologie zu verändern und zu verbessern sowie völlig neue Berufsbilder zu schaffen.
Der letzte Teil der Arbeit legt die Ergebnisse einer empirischen Untersuchung dar, die an 214 Südtiroler Unternehmen durchgeführt wurde. Die Resultate der Online-Umfrage stimmen zumeist mit jenen der Literaturrecherche überein. Obwohl die meisten Südtiroler Firmen noch keine KI einsetzen, rechnen sie damit, diese in den nächsten 10 Jahren einzuführen. Unternehmen, die die KI bereits nutzen, stellen jetzt schon eine Steigerung der Produktivität und die Schaffung neuer Tätigkeitsfelder fest. Insgesamt gehen die Betriebe davon aus, dass die KI sowohl neue Herausforderungen als auch neue Chancen für Arbeitnehmer sowie eine Erhöhung der Arbeitsqualität und -sicherheit mit sich bringen wird.

Schlagwörter: künstliche Intelligenz, KI, Arbeitsmarkt, Südtirol, Industrie 4.0