Browsing by Subject "Norm"

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Development of a spatial data infrastructure for precision agriculture applications
(2021) Jackenkroll, Markus; Gerhards, Roland
Precision agriculture (PA) is the technical answer to tackling heterogeneous conditions in a field. It works through site specific operations on a small scale and is driven by data. The objective is an optimized agricultural field application that is adaptable to local needs. The needs differ within a task by spatial conditions. A field, as a homogenous-planted unit, exceeds by its size the scale units of different landscape ecological properties, like soil type, slope, moisture content, solar radiation etc. Various PA-sensors sample data of the heterogeneous conditions in a field. PA-software and Farm Management Information Systems (FMIS) transfer the data into status information or application instructions, which are optimized for the local conditions. The starting point of the research was the determination that the process of PA was only being used in individual environments without exchange between different users and to other domains. Data have been sampled regarding specific operations, but the model of PA suffers from these closed data streams and software products. Initial sensors, data processing and controlled implementations were constructed and sold as monolithic application. An exchange of hard- or software as well as of data was not planned. The design was focused on functionality in a fixed surrounding and conceived as being a unit. This has been identified as a disadvantage for ongoing developments and the creation of added value. Influences from the outside that may be innovative or even inspired cannot be considered. To make this possible, the underlying infrastructure must be flexible and optimized for the exchange of data. This thesis explores the necessary data handling, in terms of integrating knowledge of other domains with a focus on the geo-spatial data processing. As PA is largely dependent on geographical data, this work develops spatial data infrastructure (SDI) components and is based on the methods and tools of geo-informatics. An SDI provides concepts for the organization of geospatial components. It consists of spatial- and metadata in geospatial workflows. The SDI in the center of these workflows is implemented by technologies, policies, arrangements, and interfaces to make the data accessible for various users. Data exchange is the major aim of the concept. As previously stated, data exchange is necessary for PA operations, and it can benefit from defined components of an SDI. Furthermore, PA-processes gain access to interchange with other domains. The import of additional, external data is a benefit. Simultaneously, an export interface for agricultural data offers new possibilities. Coordinated communication ensures understanding for each participant. From the technological point of view, standardized interfaces are best practice. This work demonstrates the benefit of a standardized data exchange for PA, by using the standards of the Open Geospatial Consortium (OGC). The OGC develops and publishes a wide range of relevant standards, which are widely adopted in geospatially enabled software. They are practically proven in other domains and were implemented partially in FMIS in the recent years. Depending on their focus, they could support software solutions by incorporating additional information for humans or machines into additional logics and algorithms. This work demonstrates the benefits of standardized data exchange for PA, especially by the standards of the OGC. The process of research follows five objectives: (i) to increase the usability of PA-tools in order to open the technology for a wider group of users, (ii) to include external data and services seamlessly through standardized interfaces to PA-applications, (iii) to support exchange with other domains concerning data and technology, (iv) to create a modern PA-software architecture, which allows new players and known brands to support processes in PA and to develop new business segments, (v) to use IT-technologies as a driver for agriculture and to contribute to the digitalization of agriculture.
Understanding social-psychological determinants and effects of collaborative consumption
(2017) Roos, Daniel; Hahn, Rüdiger
This doctoral thesis aims to define collaborative consumption and advance the understanding of its social-psychological determinants and effects. In order to achieve these aims, the thesis presents three studies, each of which has been accepted at scientific conferences and developed further based on feedback from experts and reviewers. Two of the studies have been published in peer-reviewed journals. The introduction provides an overview of collaborative consumption as a comparably sustainable consumption practice. Moreover, three research deficits are identified that are the motivation for the subsequent studies. First, it is shown that the basic idea and the scope of collaborative consumption remain unclear. Second, it is found that understanding of determinants is limited to isolated variables leaving relative strengths of and interdependencies between variables untapped Finally, it is assessed that actual effects of collaborative consumption on consumers’ mindsets are not well understood. The first study titled “Prototypical collaborative consumption behaviors and their relations: A conceptual review and empirical study” examines consumer behaviors that are comprised by the term “collaborative consumption” and the relations between these behaviors. In order to identify prototypical collaborative consumption behaviors, original definitions of collaborative consumption in the literature are reviewed. To derive hypotheses on the relationships between the prototypical behaviors, the study draws on theoretical foundations from the field of consumer lifestyles and behavioral spillover. The second study titled “Understanding collaborative consumption: An extension of the theory of planned behavior with value-based personal norms” aims to understand which social-psychological variables and underlying values and beliefs determine actual collaborative consumption. The theory of planned behavior is used as the primary theoretical framework, as it is a well-established model that has been shown to explain a wide range of consumer behaviors. However, reviews and meta-analyses have found the theory’s ability to account for normative motives to perform a behavior is weak and have called for further theory development. As normative motives are expected to be particularly important in the context of collaborative consumption, the theory is extended with a value-based personal norm variable. The third study titled “Does collaborative consumption affect consumers’ values, attitudes, and norms? A panel study” examines the nature of causality between collaborative consumption and behavioral factors in order to determine whether collaborative consumption affects consumers’ values, attitudes, and norms over time. The study primarily builds on the theory of planned behavior, value theory, and the value-belief-norm theory to determine the theoretical framework linking collaborative consumption, values, attitudes, and norms over time. The theoretical framework is tested based on a two-wave panel over a time period of nine months using survey data from 168 consumers. In conclusion, the thesis contributes to the literature in six ways. First, the thesis conceptually defines collaborative consumption, a term that was used ambiguously so far. Second, it empirically advances the understanding of social-psychological determinants of collaborative consumption. Third, it explains social-psychological effects of collaborative consumption on consumers over time, something that has not been done in the literature before. Fourth, the thesis identifies and examines the relationships between five prototypical collaborative consumption behaviors. Fifth, it argues for the extension of the theory of planned behavior by a value-based personal norm variable and provides supporting empirical evidence. Finally, it advances knowledge on the causal relationship between values, attitudes, norms, and behavior.