330 Wirtschaft
Refine
Year of publication
Document Type
- Doctoral thesis (24)
Institute
Language
- English (24) (remove)
Keywords
- Corporate Social Responsibility (3)
- Kundenmanagement (3)
- Prognoseverfahren (3)
- Big Data (2)
- Data Science (2)
- Electronic Commerce (2)
- Logistik (2)
- Management (2)
- Organisationsstruktur (2)
- Service recovery (2)
This cumulative dissertation examines the phenomenon of employee silence in professional service firms (PSFs). Although both research streams are independently well-established areas of organizational research, there has been a lack of research investigating the withholding of information, problems, or concerns in the knowledge-intensive context of PSFs. This thesis starts the academic and practitioner discourse about it and opens a multitude of further research opportunities.
The first manuscript draws on a literature-based and conceptual approach to examine the intersections of PSF and silence research. It identifies characteristics of PSFs that lead to employee silence and derives research propositions about the links between PSFs and silence. By applying a multi-method research approach, the second manuscript empirically investigates the extent to which employee silence is prevalent in PSFs. It determines PSF-specific antecedents fostering the unfavorable phenomenon and professionals' motives to remain silent. The third manuscript takes a grounded-theory approach to examine how employee silence in PSFs can be prevented or reduced. It develops overarching fields of action and concrete measures that help practitioners overcome employee silence.
The objective of this cumulative dissertation is to mitigate cognitive bias in human expert judgments intending to increase accuracy of judgments. The latter is important as it is known to be essential for business success. The approach for this purpose is to combine the strengths of humans and machines by giving the expert feedback generated by a statistical model (the machine) based on previous errors of the expert. Based on this concept of collaborative intelligence, a Decision Support System (DSS) is developed and tested in several experiments. The cumulative dissertation consists of three articles. Article 1 and Article 2 investigate different aspects of the DSS and Article 3 merges and supports the statements thereof. Article 1 considers the impact of personal error pattern feedback on further point estimates. The error feedback is based on personal prior judgments originating from different categories, assuming that experts selectively apply the feedback and are able to reduce bias and error. Thereby it is examined, how the feedback is used to change the direction of error and to reduce bias and error. This is investigated in general disregarding categories as well as selectively regarding difference between categories. Article 1 also covers the comparison between human corrected bias and machine auto-corrected bias. Article 2 deals with experiments with the same DSS, but focusing on certainty (confidence) interval estimation and decreasing overprecision (overconfidence) and over- and underestimation biases. Here, the DSS requires users to indicate a 90% certainty interval as an answer to estimation questions. It is investigated how feedback based on own error patterns can help to reduce overprecision by broadening certainty intervals. Moreover, aiming to mitigate over- and underestimation biases, shifts of the intervals are examined. Article 3 supports the statements of Article 1 and 2 by taking into account additional experiments with a larger sample size with the same categories as well as new categories to make the results more robust and generally valid. Article 3 also includes a further analysis regarding the comparison between human corrected bias and machine auto-corrected bias.
This cumulative dissertation investigates the newly emerged phenomenon of customer success management (CSM). CSM has received a significant amount of attention from academics and practitioners alike. However, the body of academic literature is still in its infancy, especially when comparing CSM’s relevance to the field of relationship marketing.
Manuscript 1: Zakrzewski, K., Krause, V., Pfaff, C. & Seidenstricker, S. (2023). Is customer success management a new relationship marketing practice? A review, definition, and future research agenda based on practice theory.
Manuscript 2: Zakrzewski, K., Krause, V., Eberl, D. & Rangarajan, D. (2023). Dynamic & proactive segmentation of post-sale customer relationships in B2B subscription settings: The customer health score.
Manuscript 3: Zakrzewski, K. (2023). Customer success management - closing a capability gap in the customer-focused structure toward customer centricity in B2B service contexts.
The first manuscript adopts a new approach to the investigation of CSM, providing a practice-based definition that distinguishes CSM from other relationship marketing constructs. By utilizing the 3 Ps framework of practice theory (praxis, practices, and practitioners), the definition of CSM as a strategic function was refined. In addition, the second manuscript utilized praxis to develop the customer health score, which can be used as an indicator for the dynamic and proactive segmentation of customers. The third manuscript builds on this functional definition to show how CSM’s organizational embeddedness can help overcome barriers to customer centricity by enabling adaptive organizational capability.
In forecast combination, multiple predictions are linearly combined through the assignment of weights to individual forecast models or forecasters. Various approaches exist for defining the weights, which typically involve determining the number of models to be used for combination (selection), choosing an appropriate weighting function for the forecast scenario (weighting), and using regularization techniques to adjust the calculated weights (shrinkage). The papers listed address the integration of the three approaches into holistic data analytical models.
The first paper develops a two-stage model in which weights are first calculated based on the in-sample error covariances to minimize the error on the available data by combining the individual models. Based on the selection status of a model, the weight of an individual model is then linearly shrunk either toward the mean or toward zero. The selection status is thereby derived apriori from information criteria, where Contribution 1 introduces the selection based on the model’s in-sample accuracy and performance robustness under uncertainty.
Contribution 2 modifies the two-stage model to shrink the forecasters’ weights non-proportionally to the mean or zero. Further, a new information criterion based on forward feature selection is proposed that iteratively selects the forecaster that is expected to achieve the largest increase in accuracy when combined.
Contribution 3 extends the iteration-based information criterion presented in the second contribution to consider diversity gains in addition to accuracy gains when selecting and combining forecasters.
A one-stage model for simultaneous weighting, shrinking, and selection is finally built and evaluated on simulated data in Contribution 4. Instead of requiring a prior selection criterion, the model itself learns which forecasters to shrink to the mean or to zero, while relying on a new sampling procedure to tune the model.
"Present Bias in Choices over Food and Money: Evidence from a Framed Field Experiment" - this paper presents results from a field experiment investigating dynamically inconsistent time preferences over real food choices and commitment take-up in a natural environment. We implement a longitudinal consumption experiment with a continuous convex budget: College students repeatedly choose and consume lunch menus at their college canteen. We not only allow for a full continuum of healthy or unhealthy foods; we also explicitly design the consumption stage to comply with the consume-on-receipt assumption: utility is created right after handing out the food. The paper also focuses on the implications for effective policy design: It sheds light on consumers' tendency to utilize different types of self-control devices to commit to personal consumption plans. We further compare inconsistent behavior between convex food and money choices to investigate the applicability of monetary reward studies to natural behavior. We find no correlation between time parameters in food vs. money tasks. Utility estimates from food choices suggest that dynamically consistent individuals substitute internal self-control with commitment take-up. Non-committing individuals tend to be present-biased and naive about their inconsistency.
"Dynamic Inconsistencies and Food Waste: Assessing Food Waste from a Behavioral Economics Perspective" - this paper investigates the link between dynamically inconsistent time preferences and individual food consumption and waste behavior. Food waste is conceptualized as unintended consequence of consumption choices along the food consumption chain: Because inconsistent individuals postpone the consumption of healthier food at home, storage time is prolonged and food more likely to be wasted. Capitalizing on a rich data set from a nationally representative survey, the paper constructs targeted measures of time-related food consumption and waste behaviors. In line with the theory, the paper finds that more present-biased individuals waste more food. The mechanism can be empirically supported: Although dynamically inconsistent individuals plan their food consumption, they deviate from their consumption plans more compared to consistent individuals. Deviation behavior is significantly associated with food waste. The paper points to the importance of considering dynamic inconsistencies at different stages of the food consumption process to foster the intended effects of food policies (increase in healthy nutrition) and diminish unintended consequences (increase in food waste).
"Economic Behavior under Containment: How do People Respond to Covid-19 Restrictions?" - this paper investigates the effects of policy interventions on individual decision-making and preferences by looking at a period of unprecedentedly strict regulation: the Covid-19 pandemic. Focusing on Germany, we measure regulatory strictness by calculating a policy stringency index at the federal state level. Capitalizing on exogenous variation in predetermined election cycles across states, we instrument policy stringency with the distance to the next election. Results support a positive relation between weeks to next election and state policy stringency. Leveraging a nationally representative short panel, the paper exploits this exogenous variation in policy stringency across states and over time to assess behavioral changes in different economic domains. The paper finds that government restrictions increase working from home and the provision of childcare at home, while it reduces the number of grocery shopping trips. Containment policies also affect risk preferences and fear of Covid-19: individuals become more risk-averse and afraid of Covid-19 as a consequence of stricter policies. The results are robust against various different model specifications.
The overall aim of this cumulative dissertation is to contribute to a better understanding of both antecedents of the usage of automated mobility offerings and outcomes that individual consumers experience from such usage. The dissertation contains three distinct papers:
Paper 1: Janotta, F. (2022), “Making emergent technologies more tangible - Effects of presentation form on user perceptions in the context of automated mobility”
Paper 2: Janotta, F. & Hogreve, J. (2022), “Ready for take-off? The dual role of affective and cognitive evaluations in the adoption of Urban Air Mobility services”
Paper 3: Janotta, F.; Hogreve, J.; Gustafsson, A. & Lervik-Olsen, L. (2022), “Will automated mobility contribute to consumer well-being? The role of mindfulness interventions in the context of automated driving”
Each paper addresses a specific prevailing research gap in the literature related to automated mobility offerings, focusing on different use cases of automated mobility. Paper 1 investigates the effects of different presentation forms of automated driving on consumers’ perceptions, thereby addressing the challenge of effectively visualizing emergent automated technologies and making them more tangible to respondents in the context of empirical research, thus providing a methodological basis for the further investigation. Paper 2 investigates antecedents of consumers’ adoption intentions of autonomous passenger drones, specifically focusing on the dual role of affective and cognitive considerations in the formation of usage intentions. Paper 3 investigates outcomes of consumers’ usage of automated mobility offerings, focusing on the use case of automated driving and its effects on individual well-being of consumers.
This thesis develops methodological approaches to extend the service spectrum of price comparison websites for electronic consumer goods with respect to the determination of the optimal purchase time point. The central decision criterion of price comparison sites’ customers is the (expected) minimum price.
This paper therefore focuses on the prediction of minimum prices and therefrom derived events and answers three questions that set the stage for extending services of price comparison sites:
1. How long do is the expected waiting time to buy our desired product for a set budget or desired price?
2. When should a customer buy so that s/he pays the lowest price within a short, predefined decision horizon?
3. How can a price comparison site make price predictions for a large, heterogeneous set of products over different horizons, and what are the best methods for doing so?
The database used for the analysis results from the specific requirements of the study context. While the first two papers focus on a subset of electronic consumer goods - smartphones - to demonstrate the application of the developed methodology, the third paper addresses the challenges of price prediction for the heterogeneous product landscape on price comparison sites and therefore includes multiple product categories in the analysis.
The cumulative dissertation consists of three articles.
The first article analyses the use of vertical manager interlocks for tax avoidance purposes.
The second article studies the effect of tax department organization on tax avoidance and tax risk.
The third article contains an analysis of the effects of tax evasion penalties levied on corporations or managers on aggressive tax avoidance.
Abstract paper 1:
This paper examines how service firms (i.e., car dealers) should manage the remedy for a recalled vehicle, specifically the timing of the repair and the message on its outcome. Drawing on the Protective Action Decision Model (PADM), we consider the repair for a recalled product as a protective action and propose a central role of customers' risk concerns for managing this process. Across multiple studies (including interviews with car dealers, archival data, and experiments with car owners), we show that firms' service processes are not well-aligned with these concerns. Regarding the timing, firms often delay the repair service until the next regular inspection for convenience, while customers prefer an immediate repair if they perceive a high risk and if risk exposure time (time until next inspection) is long. Regarding the outcome message, firms often communicate a benefit such as a value increase (a camouflage signal), which is ineffective. Instead, customers' satisfaction and loyalty with the service firm are increased by communicating a risk reduction (a need signal), mediated by perceived credibility. We recommend that service firms should let customers choose the timing for the repair and frame its outcome as a risk reduction, rather than concealing it as a benefit.
Abstract paper 2:
This paper examines the remedial effect of complaint process recovery (CPR) on customer outcomes (trust and repatronage intentions) after double deviations. CPR refers to improvements in complaint-handling processes aimed at avoiding another recovery failure. Drawing on the stereotype content model, we propose that CPR communication (i.e., informing customers about the improved complaint-handling processes after a double deviation) and CPR verification (i.e., providing evidence of these improvements when customers experience another service failure) foster repatronage intentions, serially mediated by perceived competence and trust. Further, it is proposed that CPR communication reinforces the latter mediation effect. Findings from one scenario-based experiment and two longitudinal field experiments support these hypotheses. Further, the effects of CPR communication and verification are robust across different levels of perceived failure severity and across strong- vs. weak-relationship customers. As a major managerial takeaway, firms learn how to signal their competence and remedy a double deviation, even when accepting and admitting that service failures can reoccur.
Abstract paper 3:
Purpose:
This paper examines how customer expectations of service quality change if a service provider is forced to adapt its service provision due to the social distancing rules applied during pandemic times.
Design/methodology/approach: This research draws on the concept of zone of tolerance for service quality, using field data to determine the zones of tolerance for different service quality dimensions in traditional and adapted service settings for mass events. Customers’ zones of tolerance are compared through repeated measures analyses of variance. Further, the effect of perceived service quality on customer outcomes (i.e., satisfaction with the adapted service and repatronage intention after the pandemic) is examined through a mediation analysis, with usage frequency as the mediating variable.
Findings: This paper shows that customers’ zones of tolerance narrow following service adaptations, which can be explained by rising expectations of minimum tolerable service levels. If the perceived service exceeds this lower threshold of the zone of tolerance, customers show higher satisfaction with the adapted service. Additionally, satisfaction with the adapted service has a positive effect on repatronage intention for the traditional service (i.e., after the pandemic), mediated by usage frequency of the adapted service.
Originality: The topic of service adaption is examined from a customer point of view.
Practical implications: The findings of this study provide important implications for service providers about how to handle service adaption during times of social distancing.
Die kumulative Dissertation „The Effectiveness of Segment Disclosures under the Management Approach: Empirical Evidence from Europe” untersucht die Determinanten und ökonomischen Auswirkungen von Segmentberichtsangaben, welche nach International Financial Reporting Standard (IFRS) 8 aufgestellt wurden. Die Dissertation erweitert die bestehende Literatur zur Wirksamkeit des IFRS 8 in Europa und besteht dabei aus drei Beiträgen.
Der erste Beitrag untersucht den Einfluss von Kultur als Determinante für die Quantität und Qualität der Segmentberichtsangaben europäischer Unternehmen. Im Rahmen der empirischen Analyse werden darüber hinaus die ökonomischen Auswirkungen der kulturinduzierten Veröffentlichungsmuster nachgewiesen.
Der zweite Beitrag beantwortet die Forschungsfrage welche Auswirkungen Non-IFRS Segmentdaten auf die Prognosegenauigkeit von Finanzanalysten haben. In der empirischen Analyse wird dieser Wirkungszusammenhang zudem für spezielle Abweichungen von IFRS Rechnungslegungsgrundsätzen untersucht.
Der dritte Beitrag stellt Änderungsvorschläge an IFRS 8 seitens des internationalen Standardsetters vor und untersucht deren potenzielle Auswirkungen aus Perspektive der Jahresabschlussersteller.