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  <title>EconStor Community: VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research</title>
  <link rel="alternate" href="https://hdl.handle.net/10419/103659" />
  <subtitle>VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research</subtitle>
  <id>https://hdl.handle.net/10419/103659</id>
  <updated>2026-04-28T16:01:14Z</updated>
  <dc:date>2026-04-28T16:01:14Z</dc:date>
  <entry>
    <title>Demand response through automated air conditioning in commercial buildings – a data-driven approach</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/233188" />
    <author>
      <name>Drasch, Benedict J.</name>
    </author>
    <author>
      <name>Fridgen, Gilbert</name>
    </author>
    <author>
      <name>Häfner, Lukas</name>
    </author>
    <id>https://hdl.handle.net/10419/233188</id>
    <updated>2023-11-10T02:24:53Z</updated>
    <published>2020-01-01T00:00:00Z</published>
    <summary type="text">Title: Demand response through automated air conditioning in commercial buildings – a data-driven approach
Authors: Drasch, Benedict J.; Fridgen, Gilbert; Häfner, Lukas
Abstract: Building operation faces great challenges in electricity cost control as prices on electricity markets become increasingly volatile. Simultaneously, building operators could nowadays be empowered with information and communication technology that dynamically integrates relevant information sources, predicts future electricity prices and demand, and uses smart control to enable electricity cost savings. In particular, data-driven decision support systems would allow the utilization of temporal flexibilities in electricity consumption by shifting load to times of lower electricity prices. To contribute to this development, we propose a simple, general, and forward-looking demand response (DR) approach that can be part of future data-driven decision support systems in the domain of building electricity management. For the special use case of building air conditioning systems, our DR approach decides in periodic increments whether to exercise air conditioning in regard to future electricity prices and demand. The decision is made based on an ex-ante estimation by comparing the total expected electricity costs for all possible activation periods. For the prediction of future electricity prices, we draw on existing work and refine a prediction method for our purpose. To determine future electricity demand, we analyze historical data and derive data-driven dependencies. We embed the DR approach into a four-step framework and demonstrate its validity, utility and quality within an evaluation using real-world data from two public buildings in the US. Thereby, we address a real-world business case and find significant cost savings potential when using our DR approach.</summary>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Editorial: transformation</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/233203" />
    <author>
      <name>Gehrig, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/233203</id>
    <updated>2023-11-03T02:22:27Z</updated>
    <published>2020-01-01T00:00:00Z</published>
    <summary type="text">Title: Editorial: transformation
Authors: Gehrig, Thomas</summary>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Project leaders' control resources and role overload as predictors of project success: developing the job demands–resources model</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/233181" />
    <author>
      <name>Lattrich, Kai-Kristina</name>
    </author>
    <author>
      <name>Büttgen, Marion</name>
    </author>
    <id>https://hdl.handle.net/10419/233181</id>
    <updated>2023-11-02T02:45:48Z</updated>
    <published>2020-01-01T00:00:00Z</published>
    <summary type="text">Title: Project leaders' control resources and role overload as predictors of project success: developing the job demands–resources model
Authors: Lattrich, Kai-Kristina; Büttgen, Marion
Abstract: Drawing on the job demands-resources model (JD-R model), this article introduces information control and team control as project leader-specific job resources, as well as role overload as a demand, and then examines their influences on project experience appraisals and project success. With a sample of 185 project leaders, this study reveals that all three factors drive project success and project leader well-being. The moderating effects of role overload on the relationships between team control and negative experience and between team control and goal attainment are particularly remarkable; goal attainment is highest with high team control and high role overload. Similarly, the most positive experiences occur with high team control and high role overload. This further development of the JD-R model, thus, identifies information and team control as resources specific to project leaders and role overload as a predominant challenge stressor, with an ambivalent nature.</summary>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/233163" />
    <author>
      <name>Bräuer, Sebastian</name>
    </author>
    <author>
      <name>Plenter, Florian</name>
    </author>
    <author>
      <name>Klör, Benjamin</name>
    </author>
    <author>
      <name>Monhof, Markus</name>
    </author>
    <author>
      <name>Beverungen, Daniel</name>
    </author>
    <author>
      <name>Becker, Jörg</name>
    </author>
    <id>https://hdl.handle.net/10419/233163</id>
    <updated>2023-11-03T02:03:00Z</updated>
    <published>2020-01-01T00:00:00Z</published>
    <summary type="text">Title: Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles
Authors: Bräuer, Sebastian; Plenter, Florian; Klör, Benjamin; Monhof, Markus; Beverungen, Daniel; Becker, Jörg
Abstract: Proof-of-concept projects have demonstrated that used electric vehicle batteries (EVBs), after their removal from electric vehicles due to insufficient performance, can be repurposed for less demanding applications. It is expected that numerous batteries will be available for repurposing in the 2020s. However, the information asymmetries and transaction costs of trading used EVBs have remained unexplored, as have principles that guide the design of information systems that support the trade. Based on existing literature and in-depth interviews with battery experts, we conceptualize two key transactions for trading used EVBs. We then identify potential information asymmetries and transaction costs based on new institutional economic theory and propose five design principles that information systems should implement to address these information asymmetries and transaction costs. Subsequent research can build on our results to further frame the economic properties of trading used EVBs and to design information systems in line with new institutional economic theory.</summary>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </entry>
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