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4 Essays on Sustainable Development and Organizations’ Response to Stakeholder’s Expectations
(2024)
As integral part of the society, environment, and economy, the organization’s survival and growth depend on legitimacy which reflects the social support and acceptance of its stakeholders, the institutions and individuals it interacts with. Organizations interact with internal and external stakeholder groups which not necessarily have the same legitimacy expectations. Due to several reasons, such as the adoption of new laws or the invention of new technologies, stakeholders’ expectations of legitimate actions can change in the course of time. Thus, to respond to changing stakeholder’s expectations, as integral part of a changing environment, is complex.
The main objective of this dissertation is to answer the research question: “How do organizations respond to changing stakeholder’s expectations in context of sustainable development?”. Building on two empirical settings with four essays, this dissertation provides insights into organizations’ responses as reaction to changing stakeholder expectations with regard to sustainable development. In particular, it takes a closer look on the interplay between internal stakeholders, such as employees, and external stakeholders, such as politics or customers. The first essay summarizes the organizational factors for the implementation of a research data management (RDM) system within higher education institutes (HEI) and how they interact with each other. Based on Leavitt’s (1965) classical model of organizational change, the essay provides an overview about the interrelation between the individual components that make up an RDM system. The second essay investigates how early career researchers within HEI make use of different respond strategies to the state, market, professional, and community logic in context of RDM. It provides insights how employees deal with changing environmental conditions and the organization’s response to them. The third essay analyses the shift from voluntary to mandatory sustainability reporting and demonstrates different strategies organizations adopt to respond to it. The fourth essay incorporates the findings of the third essay and investigates which factors influence the organization’s strategy
to respond. It focuses on the interface between the top management team and the chief executive officer.
This dissertation makes at least two overall contributions to management and organization studies research. First, it emphasizes the role of different stakeholder groups and their impact on the organizations’ activities. Second, this dissertation shows the value of connecting different theoretical approaches such as institutional logics, upper echelon theory, and organizational transparency research in context of organizational legitimacy and demonstrates that a nuanced view is necessary to understand the concept of organizational legitimacy. This cumulative dissertation is structured as follows. Part A is an introduction to the study organizational legitimacy. Part B contains the four essays.
With the increasing use of digital technologies in the automotive sector, the traditional automobile is undergoing a structural transformation, requiring new technologies and enabling innovative mobility concepts.
In particular, the ability to drive automatically or even fully autonomously, update control software, and remain connected to the environment allows attackers to infiltrate highly critical vehicle systems and take control without adequate protection.
Once not only individual vehicles but entire fleets are dominated by software, cyberattacks could disrupt a significant portion of the infrastructure and expose passengers to substantial risks.
This work follows a holistic approach to protecting highly automated software-defined vehicles from cyberattacks by designing and implementing security concepts in the main phases of a vehicle's lifecycle.
We use SAE level 4 prototype vehicles to evaluate our proposed techniques.
We start with a systematic security requirement analysis using the ISA-62443 standard series, demonstrating how threats can be identified in a collaborative, hierarchical process and how the resulting security risks impact the software and hardware architecture of a self-driving vehicle.
We show how this analysis process results in concrete requirements whose consideration reduces the overall security risk to a tolerable level.
Subsequently, we develop technical solutions for selected requirements. We begin by securing the CAN and FlexRay legacy protocols, which we foresee being used in specific areas of SDV in a transitional period despite technological changes.
To enable vehicle-wide security management, we address the management and distribution of cryptographic keys within such networks, mainly focusing on resource-constrained devices.
We propose using lightweight implicit certificates for deriving cryptographic group keys that can be used in CAN networks.
Additionally, we demonstrate how the slot-based frame structure of the FlexRay protocol allows for efficient "multi-slot" authentication, for which we calculate cryptographic keys using hash-based key chains.
SDV use Ethernet-based communication protocols and custom middleware stacks to transmit large amounts of data in real-time.
We develop a three-stage security process for the novel ASOA, which enables the development and central orchestration of system-agnostic functional software components on embedded systems and HPC platforms.
After the central specification of the security architecture at the data flow level, security tokens are automatically calculated and distributed for runtime protection of the service-oriented, DDS-based data transmission.
Our process ensures the strict separation of function and system knowledge, allowing for cost-effective and adaptable security architecture management.
The evaluation in four self-driving, software-defined vehicles demonstrates an average runtime overhead of approximately 5.71%.
As the initial risk analysis and actual cyberattacks have shown, protective measures against the compromise of control units must be taken alongside communication security.
To address this, we develop a method for verifying and validating the software integrity of control units.
A governmental third party confirms a measurement through a digital certificate, proving the examined vehicle's trustworthiness and suitability for participation in automated traffic.
In the final step of this work, we present an assessment scheme that allows software-defined vehicles to evaluate security incidents during operation in terms of their maximum expected damage and initiate appropriate countermeasures.
We follow the ISO/SAE 21434 standard and model attack paths using a graph representing dependencies among internal vehicle assets to account for the propagation effects of cyberattacks.
The assessment of a security incident considers not only the probability of individual attack paths but also the vehicle context.
Our practical evaluation demonstrates that we can detect, report, and assess security incidents below the human reaction time in the earlier mentioned prototype vehicles.
The collection of personal information by organizations has become increasingly essential for social interactions. Nevertheless, according to the GDPR (General Data Protection Regulation), the organizations have to protect collected data. Access Control (AC) mechanisms are traditionally used to secure information systems against unauthorized access to sensitive data. The increased availability of personal sensor data, thanks to IoT-oriented applications, motivates new services to offer insights about individuals. Consequently, data mining algorithms have been proposed to infer personal insights from collected sensor data. Although they can be used for genuine purposes, attackers can leverage those outcomes, combining them with other type of data, and further breaching individuals’ privacy. Thus, bypassing AC mechanisms thanks to such insights is a concrete problem.
We propose an inference detection system based on the analysis of queries issued on a sensor database. The knowledge obtained through these queries, and the inference channels corresponding to the use of data mining algorithms on sensor data to infer individual information, are described using Raw sensor data based Inference ChannEl Model (RICE-M). The detection is carried out by RICE-M based inference detection System (RICE-Sy). RICE-Sy considers at the time of the query, the knowledge that a user obtains via a new query and has obtained via his query history, and determines whether this is sufficient to allow that user to operate a channel. Thus, privacy protection systems can take advantage of the inferences detected by RICE-Sy, taking into account individuals’ information obtained by the attackers via a database of sensors, to further protect these individuals.
The impact of urban development on local residents in the urban periphery oscillates between processes of empowerment and processes of marginalization as well as between state-controlled order and decentralized self-organization. Consequently local authorities, including urban planners and local residents need to negotiate their respective roles in the production and usage of urban space defined by transition, transformation and ambiguity. Therefore, this work examines the underlying patterns, interactions and structures which define the negotiation of state-society relations in the framework of a porous peri-urban landscape in Vietnam’s secondary cities.
In Chapter 1, peri-urban areas are defined as space of transformation where pattern of rural land use are intertwined with pattern of urban land use to create an urban-rural interface with blurred boundaries. The main characteristic of the spatial pattern in Tam Kỳ and Buôn Ma Thuột is rooted urban porosity leading to the spatial intertwining of rural, peri-urban and urban spaces. The emerging urban landscape can be defined as peri-urban city. Three main themes define this peri-urban city beyond porosity: (1) processes of transformation creating the peri-urban city, (2) networks of power and control as means to adapt to these transformations and (3) mobility as prerequisite for ability to benefit from the changing landscape in peri-urban cities.
Chapter 2 describes how state authorities, urban planners and private investors at the local level in Tam Kỳ and Buôn Ma Thuột use porous space to reproduce the city based on their aspirations. This leads to a cargo cult urbanism, where urban planning is rooted in future aspirations for the city. Plans and construction efforts reference the image of a modern urban future and produce the image of a city, which does not exists in the real urban space of Tam Kỳ and Buôn Ma Thuột. In the meantime, practices based in peri-urban space are often contradictory to the official aspirations of local state authorities
Chapter 3 explores this emerging divergence between the aspired urban space by the state and the reality of urban space rooted in material and social porosity. Traditional, newly accessible and environmental porosity provide an array of accessible space which transforms the peri-urban city into a social arena of encounters and interaction. Consequently, porosity enables local residents to maintain urban space as commons. This counters the push towards the privatization of urban space by state and private actors and creates multiple aspirations for the urban future.
Rooted in urban space as commons, porosity enables the usage of peri-urban space as spaces of resistance as discussed in Chapter 4. Mobility and interaction are means of reproduction in the porous ambiguity of urban materiality but also become means of everyday resistance. The emerging spatialities of emancipation provide opportunities for an emerging urban citizenship. Urban materiality and urban citizenship have a mutually constitutive relationship.
In summary, this cumulative dissertation investigates the application of the conjugate gradient method CG for the optimization of artificial neural networks (NNs) and compares this method with common first-order optimization methods, especially the stochastic gradient descent (SGD).
The presented research results show that CG can effectively optimize both small and very large networks. However, the default machine precision of 32 bits can lead to problems. The best results are only achieved in 64-bits computations. The research also emphasizes the importance of the initialization of the NNs’ trainable parameters and shows that an initialization using singular value decomposition (SVD) leads to drastically lower error values. Surprisingly, shallow but wide NNs, both in Transformer and CNN architectures, often perform better than their deeper counterparts. Overall, the research results recommend a re-evaluation of the previous preference for extremely deep NNs and emphasize the potential of CG as an optimization method.
People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place.
The growing demand for electric vehicles (EV) in the last decade and the most recent European Commission regulation to only allow EV on the road from 2035 involved the necessity to design a cost-effective and sustainable EV charging station (CS). A crucial challenge for charging stations arises from matching fluctuating power supplies and meeting peak load demand. The overall objective of this paper is to optimize the charging scheduling of a hybrid energy storage system (HESS) for EV charging stations while maximizing PV power usage and reducing grid energy costs.
This goal is achieved by forecasting the PV power and the load demand using different deep learning (DL) algorithms such as the recurrent neural network (RNN) and long short-term memory (LSTM). Then, the predicted data are adopted to design a scheduling algorithm that determines the optimal charging time slots for the HESS. The findings demonstrate the efficiency of the proposed approach, showcasing a root-mean-square error (RMSE) of 5.78% for real-time PV power forecasting and 9.70%
for real-time load demand forecasting. Moreover, the proposed scheduling algorithm reduces the total grid energy cost by 12.13%.
From transportation to urbanization, energy and digitalization, China-backed projects of infrastructural development are increasingly common throughout Southeast Asia and the global South as both a means and outcome of development. This trend has accelerated since China’s Belt and Road Initiative (BRI) in 2013. Against this backdrop, the present ASEAS issue invites to rethink the roles infrastructure plays in forms of development that place connectivity at the center.
Contents:
Simon Rowedder, Phill Wilcox & Susanne Brandtstädter
Negotiating Chinese Infrastructures of Modern Mobilities: Insights from Southeast Asia
Current Research on Southeast Asia
Panitda Saiyarod
The Deviated Route: Navigating the Logistical Power Landscape of the Mekong Border Trade
Franziska S. Nicolaisen
The Politicization of Mobility Infrastructures in Vietnam — The Hanoi Metro Project at the Nexus of Urban Development, Fragmented Mobilities, and National Security
Arratee Ayuttacorn
Chinese Investor Networks and the Politics of Infrastructure Projects in the Eastern Economic Corridor in Thailand
Karin Dean
Belt and Road Initiative in Northern Myanmar: The Local World of China’s Global Investments
Mira Käkönen
Entangled Enclaves: Dams, Volatile Rivers, and Chinese Infrastructural Engagement in Cambodia
Research Workshop
Tim Oakes
Infrastructure Power, Circulation and Suspension
Susanne Brandtstädter
Infrastructural Fragility, Infra-Politics and Jianghu
Book Reviews
Michael Kleinod-Freudenberg
Book Review: Tappe, O., & Rowedder, S. (Eds.). (2022). Extracting Development: Contested Resource Frontiers in Mainland Southeast Asia
This book collects ten of Sandra Huebenthal’s most important contributions to the application of Social Memory Theory in Biblical studies. The volume consists of four parts, each devoted to a particular field of research. Part one addresses the general impact of Social Memory Theory for the New Testament. The second part analyzes how Social Memory Theory adds to exploring the phenomenon of (biblical) intertextuality as a strategy for negotiating Early Christian identity and the third part investigates how New Testament pseudepigraphy provides a different approach for understanding the negotiation and formation of Christian identities. Finally, part four provides an outlook how the hermeneutical approach can enhance Patristic research. The ten essays originate from discussions about Social Memory Theory and the New Testament at international conferences, three of them are translations of German contributions, while two are published for the first time in this volume.
(Verlagsbeschreibung)
Technological advancements and new legal requirements are continuously changing the online data disclosure landscape in terms of both, the quantity and quality of data that firms can acquire. Nowadays, consumers are required to disclose personal data online multiple times a day and in a variety of different contexts, such as creating user profiles, online payment or using location-based services. Despite consumers’ increasing online privacy concerns, firms rely ever more strongly on consumer data that they convert into a competitive advantage through personalized product recommendations and targeted advertising. In an effort to encourage consumer data disclosure, many firms have focused on building trust as a way to counterbalance privacy concerns and mitigate risk perceptions. Correspondingly, marketing literature has continued to examine the interplay of trust and consumer privacy concerns. While the extant research has considerably advanced our understanding of the role of trust in privacy-related decision-making, the majority of studies has mainly focused on single-stage, dyadic disclosure settings and cognitive decision-making processes.
Against this background, the overarching goal of this thesis is to shed light on under-researched data disclosure contexts involving trust and to explore additional facets of the underlying decision-making processes. For example, considering pre- and post-disclosure stages when evaluating consumers’ data disclosure decisions allows for a more holistic picture of the decision-making process. Similarly, social media and sharing economy settings challenge the traditional assumption of purely dyadic consumer-firm data disclosure, thus extending traditional conceptualizations of trust. Across three independent essays, this thesis addresses the overarching research question of how the peculiarities of multi-stage and multi-actor settings shape consumers’ trust-based decision-making strategies.