@article{53611,
  author       = {{Hoffmann, Christin and Thommes, Kirsten}},
  issn         = {{0095-0696}},
  journal      = {{Journal of Environmental Economics and Management}},
  keywords     = {{Management, Monitoring, Policy and Law, Economics and Econometrics}},
  publisher    = {{Elsevier BV}},
  title        = {{{Can leaders motivate employees’ energy-efficient behavior with thoughtful communication?}}},
  doi          = {{10.1016/j.jeem.2024.102990}},
  year         = {{2024}},
}

@article{50719,
  abstract     = {{We propose an indicator for detecting anomalous stock market valuation in real time such that market participants receive timely signals so as to be able to take stabilizing action. Unlike existing approaches, our anomaly indicator introduces three methodological novelties. First, we use an endogenous, purely data-driven, nonparametric trend identification method to separate long-term market movements from more short-term ones. Second, we apply SETAR models that allow for asymmetric expansions and contractions around the long-term trend and find systematic stock price cycles. Third, we implement these findings in our indicator and conduct real-time market forecasts, which have so far been neglected in the literature. Applications of our indicator using monthly S&P 500 stock data from 1970 to the end of 2022 show that short-term anomalous market movements can be identified in real time up to one year ahead. We predict all major anomalies, including the 1987 Bubble and the initial phase of the Financial Crisis that began in 2007. In total, our anomaly indicator identifies more than 80% of all – even minor – anomalous episodes. Thus, smoothing market exaggerations through early signaling seems possible.}},
  author       = {{Fritz, Marlon and Gries, Thomas and Wiechers, Lukas}},
  issn         = {{1469-7688}},
  journal      = {{Quantitative Finance}},
  keywords     = {{General Economics, Econometrics and Finance, Finance}},
  pages        = {{1--14}},
  publisher    = {{Informa UK Limited}},
  title        = {{{An early indicator for anomalous stock market performance}}},
  doi          = {{10.1080/14697688.2023.2281529}},
  year         = {{2024}},
}

@article{48086,
  abstract     = {{Individuals strive to make decisions that are consistent with not only their consumer preferences but also their psychological needs. However, they are confronted with complex, ambiguous or even false information. Ideologies and belief systems provide guidance when processing and evaluating information and give a coherent and comprehensible interpretation of reality. The first question is: why is an individual attracted to a particular ideology? Individuals choose ideologies that resonate with their subjective psychological needs and preferences. Second, how do individuals search for ideologies and find out which suit them best? We model an individual’s sequential information search for the best matching ideologies by applying Bayesian learning and utility optimization. Additional information enhances utility by reducing uncertainty. As a search is costly, the process may stop once an individual adopts an ideology even if the information set remains incomplete. Third, once they have chosen a particular ideology, individuals adhere to its rules and norms when making everyday decisions. Consumers not only physically consume, but they also act in accordance with their psychological needs.}},
  author       = {{Burs, Carina and Gries, Thomas and Müller, Veronika}},
  issn         = {{2158-3609}},
  journal      = {{Journal of Organizational Psychology}},
  keywords     = {{Economics, Ideology, Decision-making}},
  number       = {{1}},
  publisher    = {{North American Business Press}},
  title        = {{{The Choice of Ideology and Everyday Decisions}}},
  doi          = {{10.33423/jop.v23i1.6033}},
  volume       = {{23}},
  year         = {{2023}},
}

@article{53329,
  author       = {{Tao, Youshan and Winkler, Michael}},
  issn         = {{1468-1218}},
  journal      = {{Nonlinear Analysis: Real World Applications}},
  keywords     = {{Applied Mathematics, Computational Mathematics, General Economics, Econometrics and Finance, General Engineering, General Medicine, Analysis}},
  publisher    = {{Elsevier BV}},
  title        = {{{Analysis of a chemotaxis-SIS epidemic model with unbounded infection force}}},
  doi          = {{10.1016/j.nonrwa.2022.103820}},
  volume       = {{71}},
  year         = {{2023}},
}

@article{53226,
  author       = {{Marín, Raquel and Santos-Arteaga, Francisco J. and Tavana, Madjid and Di Caprio, Debora}},
  issn         = {{2444-569X}},
  journal      = {{Journal of Innovation & Knowledge}},
  keywords     = {{Management of Technology and Innovation, Marketing, Economics and Econometrics, Business and International Management}},
  number       = {{4}},
  publisher    = {{Elsevier BV}},
  title        = {{{Value Chain digitalization and technological development as innovation catalysts in small and medium-sized enterprises}}},
  doi          = {{10.1016/j.jik.2023.100454}},
  volume       = {{8}},
  year         = {{2023}},
}

@article{44591,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The ability of various policy activities to reduce the reproduction rate of the COVID-19 disease is widely discussed. Using a stringency index that comprises a variety of lockdown levels, such as school and workplace closures, we analyze the effectiveness of government restrictions. At the same time, we investigate the capacity of a range of lockdown measures to lower the reproduction rate by considering vaccination rates and testing strategies. By including all three components in an SIR (Susceptible, Infected, Recovery) model, we show that a general and comprehensive test strategy is instrumental in reducing the spread of COVID-19. The empirical study demonstrates that testing and isolation represent a highly effective and preferable approach towards overcoming the pandemic, in particular until vaccination rates have risen to the point of herd immunity.</jats:p>}},
  author       = {{Fritz, Marlon and Gries, Thomas and Redlin, Margarete}},
  issn         = {{2199-9023}},
  journal      = {{International Journal of Health Economics and Management}},
  keywords     = {{Health Policy, Economics, Econometrics and Finance (miscellaneous)}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{The effectiveness of vaccination, testing, and lockdown strategies against COVID-19}}},
  doi          = {{10.1007/s10754-023-09352-1}},
  year         = {{2023}},
}

@article{41192,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>We examine distortions caused by tax base allocation systems–separate accounting (SA) or formula apportionment (FA)–with respect to the allocation of assets and workforce within multinational entities (MNEs). The effects of both systems are intensively debated by EU Member States as they are striving to implement a European tax system. Its introduction would lead to a switch from SA to FA. Moreover, Pillar One of the recent global tax reform includes a mix of both tax base allocation systems. We find that, against the claims of the EU, FA does not necessarily create lower distortions of the factor allocation. Decisive for that assessment is the level of profit shifting under SA. Our results indicate that, in tendency, the factor allocation is more severely distorted by FA when the profit shifting possibilities were rather low under SA. In contrast to former studies, we highlight the importance of analyzing the status quo under the recently applied system (SA) in order to be able to assess the consequences of a switch from SA to FA. Our results are interesting for policy-makers as they help anticipating reactions of MNEs to a change in the applied tax base allocation system and for companies as a basis for future tax planning.</jats:p>}},
  author       = {{Ortmann, Regina and Pummerer, Erich}},
  issn         = {{0044-2372}},
  journal      = {{Journal of Business Economics}},
  keywords     = {{Economics and Econometrics, Business and International Management}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Distortional effects of separate accounting and formula apportionment on factor allocation}}},
  doi          = {{10.1007/s11573-022-01133-5}},
  year         = {{2023}},
}

@article{41929,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The advent of social media and its commodification have created a never-ending feedback loop between businesses and their customers. In this context, constant negative Word-of-Mouth (NWOM) may jeopardize a corporate image and cause defensiveness in corporate communication. This paper presents a case study of several customer service accounts of the railway company Deutsche Bahn on Twitter to investigate the management and control of constant NWOM and the impact of accountability strategies on customers’ perception of the firm. To this end, a sample of 36,757 Twitter postings was drawn and analyzed by means of sentiment and content analysis techniques. The findings suggest that the perceived accountability towards the firm declined in case of an attitude shift towards the user. In contrast, the firm was being held accountable more insistently after expressed defensiveness, regardless of the firm’s actual accountableness. With this paper, we introduce the notion of accountability management and an accompanying theoretical framework to the literature. This provides a novel perspective on constant NWOM countermeasures for organizations that are part of ‘toxic’ industries or face unrightfully claimed accusations, i.e., when being held accountable for outer circumstances beyond their control.</jats:p>}},
  author       = {{Mirbabaie, Milad and Stieglitz, Stefan and Marx, Julian}},
  issn         = {{2366-6153}},
  journal      = {{Schmalenbach Journal of Business Research}},
  keywords     = {{Management of Technology and Innovation, General Economics, Econometrics and Finance, General Business, Management and Accounting}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Negative Word of Mouth On Social Media: A Case Study of Deutsche Bahn’s Accountability Management}}},
  doi          = {{10.1007/s41471-022-00152-w}},
  year         = {{2023}},
}

@article{43105,
  author       = {{Black, Tobias and Fuest, Mario and Lankeit, Johannes and Mizukami, Masaaki}},
  issn         = {{1468-1218}},
  journal      = {{Nonlinear Analysis: Real World Applications}},
  keywords     = {{Applied Mathematics, Computational Mathematics, General Economics, Econometrics and Finance, General Engineering, General Medicine, Analysis}},
  publisher    = {{Elsevier BV}},
  title        = {{{Possible points of blow-up in chemotaxis systems with spatially heterogeneous logistic source}}},
  doi          = {{10.1016/j.nonrwa.2023.103868}},
  volume       = {{73}},
  year         = {{2023}},
}

@article{45401,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>This paper investigates the price impact of the fuel discount in Germany, which was introduced between June and August 2022 to partially compensate increased energy costs. Using the augmented synthetic control method (ASCM) to construct the counterfactual, we provide quantitative evidence to the heated debate concerning the impact of this policy tool and find the fuel discount to have decreased consumer prices of petrol (diesel) by at least 0.30 euro per litre (0.10 euro per litre) on average. The results are robust to various sensitivity checks. Thus, oil companies and petrol stations decreased prices for consumers and passed on about 85 % (65 %) of the discount in case of petrol (diesel). Moreover, we do not find signs of excessive price increases in anticipation of the fuel discount.</jats:p>}},
  author       = {{Seiler, Volker and Stöckmann, Nico}},
  issn         = {{1465-6485}},
  journal      = {{German Economic Review}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{The Impact of the German Fuel Discount on Prices at the Petrol Pump}}},
  doi          = {{10.1515/ger-2022-0108}},
  year         = {{2023}},
}

@article{30341,
  author       = {{Hoyer, Britta and van Straaten, Dirk}},
  issn         = {{2214-8043}},
  journal      = {{Journal of Behavioral and Experimental Economics}},
  keywords     = {{General Social Sciences, Economics and Econometrics, Applied Psychology}},
  pages        = {{101869}},
  publisher    = {{Elsevier BV}},
  title        = {{{Anonymity and Self-Expression in Online Rating Systems - An Experimental Analysis}}},
  doi          = {{10.1016/j.socec.2022.101869}},
  volume       = {{98}},
  year         = {{2022}},
}

@article{34197,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Comprehensive data understanding is a key success driver for data analytics projects. Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis techniques. Especially in data-driven product planning, knowledge about the data is a necessary prerequisite because data of the use phase is very heterogeneous. However, companies often do not have the necessary know-how or time to build up solid data understanding in connection with data analysis. In this paper, we develop a methodology to organize and categorize and thus understand use phase data in a way that makes it accessible to general data analytics workflows, following a design science research approach. We first present a knowledge base that lists typical use phase data from a product planning view. Second, we develop a taxonomy based on standard literature and real data objects, which covers the diversity of the data considered. The taxonomy provides 8 dimensions that support classification of use phase data and allows to capture data characteristics from a data analytics view. Finally, we combine both views by clustering the objects of the knowledge base according to the taxonomy. Each of the resulting clusters covers a typical combination of analytics relevant characteristics occurring in practice. By abstracting from the diversity of use phase data into artifacts with manageable complexity, our approach provides guidance to choose appropriate data analysis and AI techniques.</jats:p>}},
  author       = {{Panzner, Melina and von Enzberg, Sebastian and Meyer, Maurice and Dumitrescu, Roman}},
  issn         = {{1868-7865}},
  journal      = {{Journal of the Knowledge Economy}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Characterization of Usage Data with the Help of Data Classifications}}},
  doi          = {{10.1007/s13132-022-01081-z}},
  year         = {{2022}},
}

@article{33221,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Non-pharmaceutical interventions are an effective strategy to prevent and control COVID-19 transmission in the community. However, the timing and stringency to which these measures have been implemented varied between countries and regions. The differences in stringency can only to a limited extent be explained by the number of infections and the prevailing vaccination strategies. Our study aims to shed more light on the lockdown strategies and to identify the determinants underlying the differences between countries on regional, economic, institutional, and political level. Based on daily panel data for 173 countries and the period from January 2020 to October 2021 we find significant regional differences in lockdown strategies. Further, more prosperous countries implemented milder restrictions but responded more quickly, while poorer countries introduced more stringent measures but had a longer response time. Finally, democratic regimes and stronger manifested institutions alleviated and slowed down the introduction of lockdown measures.</jats:p>}},
  author       = {{Redlin, Margarete}},
  issn         = {{0922-680X}},
  journal      = {{Journal of Regulatory Economics}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Differences in NPI strategies against COVID-19}}},
  doi          = {{10.1007/s11149-022-09452-9}},
  year         = {{2022}},
}

@article{33665,
  author       = {{Fritz, Marlon}},
  issn         = {{2110-7017}},
  journal      = {{International Economics}},
  keywords     = {{General Economics, Econometrics and Finance, General Business, Management and Accounting}},
  pages        = {{157--167}},
  publisher    = {{Elsevier BV}},
  title        = {{{Improved output gap estimates and forecasts using a local linear regression}}},
  doi          = {{10.1016/j.inteco.2022.09.007}},
  volume       = {{172}},
  year         = {{2022}},
}

@article{33714,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Industry 4.0 promises many potentials in production. Examples are a data-driven optimization of production processes of individual machines, driverless transport systems, and assistance systems. Nevertheless, companies are still hesitant to invest in Industry 4.0 applications. Studies show that one of the main reasons for that is the unclear economic benefit. In this work, we present a systematic approach for the evaluation of Industry 4.0 applications in production. The main goal of the systematic is to create transparency over the evaluation process of an investment in an Industry 4.0 application in production. The evaluation of a concrete technical solution in an existing production system is supported. As a theoretical foundation, a characterization of investments in Industry 4.0 applications is given. From that, a procedure model is derived. It puts the activities to be carried out, the tools to be used and results in a temporal context. The application of the systematic is shown on the basis of an application example.</jats:p>}},
  author       = {{Joppen, Robert and Kühn, Arno and Förster, Magdalena and Dumitrescu, Roman}},
  issn         = {{1868-7865}},
  journal      = {{Journal of the Knowledge Economy}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Evaluation of Industry 4.0 Applications in Production}}},
  doi          = {{10.1007/s13132-022-00959-2}},
  year         = {{2022}},
}

@article{33953,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Comprehensive data understanding is a key success driver for data analytics projects. Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis techniques. Especially in data-driven product planning, knowledge about the data is a necessary prerequisite because data of the use phase is very heterogeneous. However, companies often do not have the necessary know-how or time to build up solid data understanding in connection with data analysis. In this paper, we develop a methodology to organize and categorize and thus understand use phase data in a way that makes it accessible to general data analytics workflows, following a design science research approach. We first present a knowledge base that lists typical use phase data from a product planning view. Second, we develop a taxonomy based on standard literature and real data objects, which covers the diversity of the data considered. The taxonomy provides 8 dimensions that support classification of use phase data and allows to capture data characteristics from a data analytics view. Finally, we combine both views by clustering the objects of the knowledge base according to the taxonomy. Each of the resulting clusters covers a typical combination of analytics relevant characteristics occurring in practice. By abstracting from the diversity of use phase data into artifacts with manageable complexity, our approach provides guidance to choose appropriate data analysis and AI techniques.</jats:p>}},
  author       = {{Panzner, Melina and von Enzberg, Sebastian and Meyer, Maurice and Dumitrescu, Roman}},
  issn         = {{1868-7865}},
  journal      = {{Journal of the Knowledge Economy}},
  keywords     = {{Economics and Econometrics}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Characterization of Usage Data with the Help of Data Classifications}}},
  doi          = {{10.1007/s13132-022-01081-z}},
  year         = {{2022}},
}

@article{35740,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.</jats:p>}},
  author       = {{Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}},
  issn         = {{1019-6781}},
  journal      = {{Electronic Markets}},
  keywords     = {{Management of Technology and Innovation, Marketing, Computer Science Applications, Economics and Econometrics, Business and International Management}},
  number       = {{1}},
  pages        = {{375--396}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Systematizing the lexicon of platforms in information systems: a data-driven study}}},
  doi          = {{10.1007/s12525-022-00530-6}},
  volume       = {{32}},
  year         = {{2022}},
}

@article{34473,
  abstract     = {{Psychologists claim that being treated kindly puts individuals in a positive emotional state: they then treat an unrelated third party more kindly. Numerous experiments
document that subjects indeed ‘pay forward’ specific behavior. For example, they are less generous after having experienced stinginess. This, however, is not necessarily
driven by emotions. Subjects may also imitate what they regard as socially adequate behavior. Here, I present an experiment in which imitation is not possible at the next
opportunity to act with a stranger: after being given either a fun or an annoying job, subjects have to decide whether to be generous or not. I find that although subjects who are given the annoying job report more negative emotions than those with the fun job, they do not treat an unrelated third person more unkindly in terms of passing on less money.
}},
  author       = {{Schnedler, Wendelin}},
  issn         = {{0899-8256}},
  journal      = {{Games and Economic Behavior}},
  keywords     = {{Economics and Econometrics, Finance}},
  pages        = {{542--558}},
  publisher    = {{Elsevier BV}},
  title        = {{{The broken chain: Evidence against emotionally driven upstream indirect reciprocity}}},
  doi          = {{10.1016/j.geb.2022.10.008}},
  volume       = {{136}},
  year         = {{2022}},
}

@article{53238,
  author       = {{Tavana, Madjid and Khalili Nasr, Arash and Mina, Hassan and Michnik, Jerzy}},
  issn         = {{0038-0121}},
  journal      = {{Socio-Economic Planning Sciences}},
  keywords     = {{Management Science and Operations Research, Statistics, Probability and Uncertainty, Strategy and Management, Economics and Econometrics, Geography, Planning and Development}},
  publisher    = {{Elsevier BV}},
  title        = {{{A private sustainable partner selection model for green public-private partnerships and regional economic development}}},
  doi          = {{10.1016/j.seps.2021.101189}},
  volume       = {{83}},
  year         = {{2022}},
}

@article{36815,
  abstract     = {{<jats:p>Iso-octane is frequently used as a surrogate fuel or as a component in primary reference fuel blends when low-temperature combustion strategies in engines are investigated. To develop control strategies for these engines, the reaction kinetics of iso-octane must be known starting from the low temperatures and intermediate pressures before ignition to the high temperatures and pressures of combustion. This work adds new experimental data sets to the validation data for reaction mechanism development by investigating the oxidation of iso-octane in stoichiometric mixtures in a flow reactor at pressures of <jats:italic>p</jats:italic> = 1, 10, and 20 bar and 473K ≤ T ≤ 973 K. The experimental data are compared to simulations with recent reaction mechanisms [Atef et al., Combustion and Flame 178, (2017), Bagheri et al., Combustion and Flame 212, (2020), Cai et al., Proceedings of the Combustion Institute 37, (2018), Fang et al., Combustion and Flame 214, (2020)]. The comparison between experimental and simulated mole fractions as function of temperature show reasonable agreement for all investigated pressures. In particular, the experimentally observed onset of low-temperature reactivity above a certain pressure, the shift of the negative temperature coefficient (NTC) regime with increasing pressure to higher temperatures, and the acceleration of the high-temperature chemistry are captured well in the simulations. Deviations between experimental and simulated results are discussed in detail for the reactivity of iso-octane and some key intermediates such as 2,2,4,4-tetramethyl-tetrahydrofuran, iso-butene and acetone at low temperatures.</jats:p>}},
  author       = {{Shaqiri, S. and Kaczmarek, D. and vom Lehn, F. and Beeckmann, J. and Pitsch, H. and Kasper, Tina}},
  issn         = {{2296-598X}},
  journal      = {{Frontiers in Energy Research}},
  keywords     = {{Economics and Econometrics, Energy Engineering and Power Technology, Fuel Technology, Renewable Energy, Sustainability and the Environment}},
  publisher    = {{Frontiers Media SA}},
  title        = {{{Experimental Investigation of the Pressure Dependence of Iso-Octane Combustion}}},
  doi          = {{10.3389/fenrg.2022.859112}},
  volume       = {{10}},
  year         = {{2022}},
}