Changing for good:Transforming existing organizations into sustainable enterprises

Hoe kunnen bestaande organisaties het proces van duurzaam ondernemen stimuleren en in stand houden?Omdat duurzame ontwikkeling niet kan plaatsvinden zonder duurzame organisaties is inzicht in hoe organisaties verduurzaamt kunnen worden essentieel. Dit onderzoek is gebaseerd op de literatuur over duurzaam ondernemerschap en analyseert hoe bestaande organisaties de transitie naar duurzame ondernemingen kunnen maken. De activiteiten van een duurzame onderneming komen overeen met de doelstellingen voor duurzame ontwikkeling. Onderzoek contextHet onderzoek is gebaseerd op empirische observaties die voortvloeien uit een tweejarige etnografische studie bij een woningcorporatie. Deze woningcorporatie implementeerde een nieuwe strategie met het doel de volledige portefeuille energieneutraal te maken. In 2050 moeten alle Nederlandse woningen energieneutraal en aardgasvrij zijn. Deze transitie van ‘normaal’ huis naar een energieneutraal huis dwingt woningcorporaties om veel veranderingen door te voeren. Dat betekent o.a., veranderen van de manier waarop ze zich organiseren, de manier waarop ze omgaan met huurders en de manier waarop ze denken over sociale impact. Achteraf gezien hadden niet alle woningbouwcorporaties bij de eerste verbouwingen genoeg oog voor de impact op de bewoners.Resultaten In dit promotieonderzoek zijn vier belangrijke aspecten geïdentificeerd waarop bestaande organisaties het duurzame ondernemerschapsproces kunnen initiëren: 1. Leiderschap i.e. een veranderaar die de duurzaamheidstransitie kan starten en die een netwerk van externe belanghebbenden kan opbouwen; 2. Het beslissingsproces, waardoor interne organisatie-identiteiten kunnen worden afgestemd op externe organisatie-eisen; 3. Responsieve benadering van duurzaamheid te hanteren in tegenstelling tot een primair proactieve of reactieve houding ten opzichte van milieu- of sociale interventies; 4. Gezamenlijke innovatie-initiatieven, die organisaties helpen bij het herformuleren van het duurzaamheidsprobleem.How can existing organizations induce and maintain the process of sustainable entrepreneurship?Because sustainable development cannot occur without sustainable businesses, understanding how to transform organizations into sustainable ones is essential. The activities of a sustainable entrepreneur are consistent with the United Nations ‘Sustainable development goals. Research context This research is based on empirical observations resulting from an ethnographic study at a housing association implementing a new strategy to transform their entire portfolio into energy neutral houses. By 2050, the housing stock in The Netherlands needs to be transformed to meet the CO2-neutral national targets. This forces housing association to undergo multiple changes. Changes in the way they organize, changes in the way the communicate with the tenants, and in the way they think about social impact. Initial attempts to undertake these changes have failed to properly consider the impact on tenants' well-being. Results This PhD research identified four main aspects in which existing organizations can initiate and maintain the sustainable entrepreneurship process: 1. Leadership, i.e. a change-maker who can initiate the transition and build an external network of supporters; 2. A decision making process in which internal organizational identities are coupled to external societal demands; 3. A responsive approach to sustainability as opposed to a primarily proactive of reactive attitude towards environmental and social interventions; 4. Joint innovation initiatives that help organizations to reformulate the sustainability problem. Simultaneously, this PhD highlights that failing in meeting the users’ needs either leads to unintended consequences or failure of entrepreneurship efforts

Identity reflexivity:A framework of heuristics for strategy change in hybrid organizations

Purpose: The aim of this research is to investigate the relationship between (dual) organizational identity and individual heuristics – simple rules and biases – in the process of strategy change. This paper offers a theory on identity reflexivity as a cognitive mechanism of strategy change in the context of organizational hybridity. Design/methodology/approach: The authors draw on a 2-year ethnographic study at a Dutch social housing association dealing with the process of strategy change. The empirical data comprises of in-depth semi-structured interviews, ethnographic observations as well as secondary sources. Findings: Conflicting identities at the organizational level influence heuristics at the individual level, since members tend to identify with their department's identity. Despite conflicting interpretations, paths of cognitive shortcuts – that the authors define as internal and external identity reflexivity – are shared by the conflicting identities. Research limitations/implications: The findings of this research are subject to limitations typical of a qualitative case-study, such as possibly being context dependent. The authors argue that this research contributes to the understanding of how individual heuristics relate to organizational heuristics, and suggest that the process of identity reflexivity can contribute to the alignment of conflicting identities enabling strategy formation in the context of a dual-identity organization. Practical implications: Understanding how managers with conflicting identities achieve agreements is important to help organizational leaders to pursue sustainability-oriented strategy change. Social implications: Given the pressure experienced by mission-driven organizations to integrate multiple sustainability demands in their mission, understanding managers' decision-making mechanism when adapting to new, often conflicting, sustainability demands is important to accelerate societal sustainability transitions. Originality/value: This paper addresses the process of new strategy design in the context of a socially driven business. This context fundamentally differs from the one addressed by the existing heuristics literature with respect to organizational environment and role, and specific competing demands

Innovating for sustainability through collaborative innovation contests

Innovation contests are increasingly used by businesses as an instrument for open innovation to address sustainability related questions. However, according to the open innovation literature, one of the main pitfalls of this approach can be the mismatch between the solutions proposed by non-experts and the companies’ capabilities to implement such solutions. We introduce the concept of collaborative innovation contests – where companies actively collaborate with non-experts – as a way to address this mismatch. Through participant observations, we analyse the process of a sustainability-oriented collaborative innovation contest guided by design-thinking. Our results indicated that the combination of an open innovation contest and design thinking could, through the creation of constant feedback loops, lead to increased collaboration between the contests participants, the companies proposing a challenge, and other relevant stakeholders. However, our results also highlighted trade-offs between the innovativeness of ideas, the alignment of solutions with firm capabilities and the resources needed for collaborative innovation contests. We conclude that, through the involvement of different stakeholders, their ideas and perspectives, collaborative innovation contests are a useful approach to generate a comprehensive understanding of the sustainability challenges companies face

Wave propagation in pantographic 2D lattices with internal discontinuities

In the present paper we consider a 2D pantographic structure composed by two orthogonal families of Euler beams. Pantographic rectangular 'long' waveguides are considered in which imposed boundary displacements can induce the onset of traveling (possibly non-linear) waves. We performed numerical simulations concerning a set of dynamically interesting cases. The system undergoes large rotations which may involve geometrical non-linearities, possibly opening the path to appealing phenomena such as propagation of solitary waves. Boundary conditions dramatically influence the transmission of the considered waves at discontinuity surfaces. The theoretical study of this kind of objects looks critical, as the concept of pantographic 2D sheets seems to have promising possible applications in a number of fields, e.g. acoustic filters, vascular prostheses and aeronautic/aerospace panels

Network Analysis of Microarray Data

DNA microarrays are widely used to investigate gene expression. Even though the classical analysis of microarray data is based on the study of differentially expressed genes, it is well known that genes do not act individually. Network analysis can be applied to study association patterns of the genes in a biological system. Moreover, it finds wide application in differential coexpression analysis between different systems. Network based coexpression studies have for example been used in (complex) disease gene prioritization, disease subtyping, and patient stratification.Peer reviewe

VOLTA : adVanced mOLecular neTwork Analysis

Motivation: Network analysis is a powerful approach to investigate biological systems. It is often applied to study gene co-expression patterns derived from transcriptomics experiments. Even though co-expression analysis is widely used, there is still a lack of tools that are open and customizable on the basis of different network types and analysis scenarios (e.g. through function accessibility), but are also suitable for novice users by providing complete analysis pipelines. Results: We developed VOLTA, a Python package suited for complex co-expression network analysis. VOLTA is designed to allow users direct access to the individual functions, while they are also provided with complete analysis pipelines. Moreover, VOLTA offers when possible multiple algorithms applicable to each analytical step (e.g. multiple community detection or clustering algorithms are provided), hence providing the user with the possibility to perform analysis tailored to their needs. This makes VOLTA highly suitable for experienced users who wish to build their own analysis pipelines for a wide range of networks as well as for novice users for which a 'plug and play' system is provided.Peer reviewe

Manually curated and harmonised transcriptomics datasets of psoriasis and atopic dermatitis patients

We present manually curated transcriptomics data of psoriasis and atopic dermatitis patients retrieved from the NCBI Gene Expression Omnibus and EBI ArrayExpress repositories. We collected 39 transcriptomics datasets, deriving from DNA microarrays and RNA-Sequencing technologies, for a total of 1677 samples. We provide quality-checked, homogenised and preprocessed gene expression matrices and their corresponding metadata tables along with the estimated surrogate variables. These data represent a ready-made valuable source of knowledge for translational researchers in the dermatology field.Peer reviewe

The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design

Big Data pervades nearly all areas of life sciences, yet the analysis of large integrated data sets remains a major challenge. Moreover, the field of life sciences is highly fragmented and, consequently, so is its data, knowledge, and standards. This, in turn, makes integrated data analysis and knowledge gathering across sub-fields a demanding task. At the same time, the integration of various research angles and data types is crucial for modelling the complexity of organisms and biological processes in a holistic manner. This is especially valid in the context of drug development and chemical safety assessment where computational methods can provide solutions for the urgent need of fast, effective, and sustainable approaches. At the same time, such computational methods require the development of methodologies suitable for an inte-grated and data centred Big Data view. Here we discuss Knowledge Graphs (KG) as a solution to a data centred analysis approach for drug and chemical development and safety assessment. KGs are knowledge bases, data analysis engines, and knowledge discovery systems all in one, allowing them to be used from simple data retrieval, over meta-analysis to complex predictive and knowledge discovery systems. Therefore, KGs have immense potential to advance the data centred approach, the re-usability, and infor-mativity of data. Furthermore, they can improve the power of analysis, and the complexity of modelled processes, all while providing knowledge in a natively human understandable network data model. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Unsupervised Algorithms for Microarray Sample Stratification

The amount of data made available by microarrays gives researchers the opportunity to delve into the complexity of biological systems. However, the noisy and extremely high-dimensional nature of this kind of data poses significant challenges. Microarrays allow for the parallel measurement of thousands of molecular objects spanning different layers of interactions. In order to be able to discover hidden patterns, the most disparate analytical techniques have been proposed. Here, we describe the basic methodologies to approach the analysis of microarray datasets that focus on the task of (sub)group discovery.Peer reviewe

Supervised Methods for Biomarker Detection from Microarray Experiments

Biomarkers are valuable indicators of the state of a biological system. Microarray technology has been extensively used to identify biomarkers and build computational predictive models for disease prognosis, drug sensitivity and toxicity evaluations. Activation biomarkers can be used to understand the underlying signaling cascades, mechanisms of action and biological cross talk. Biomarker detection from microarray data requires several considerations both from the biological and computational points of view. In this chapter, we describe the main methodology used in biomarkers discovery and predictive modeling and we address some of the related challenges. Moreover, we discuss biomarker validation and give some insights into multiomics strategies for biomarker detection.Non peer reviewe