Wirtschaftswissenschaftliche Fakultät
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Institute
Fundamental changes in business-to-business (B2B) buying behavior confront B2B supplier firms with unprecedented challenges. On the one hand, a rising share of industrial buyers demands digitalized offerings and processes from suppliers. Consequently, suppliers are urged to implement digital transformations by expanding the range of both digital offerings and processes. On the other hand, B2B buyers increasingly expect suppliers to provide individually tailored solutions to their idiosyncratic needs. Hence, suppliers are also required to implement non-digital transformations by providing offerings and processes that are customized to each customers’ specific requirements.
The rise of these digital and non-digital transformations calls established knowledge into question. Thus, B2B marketing research and practice are urged to create a comprehensive understanding of digital and non-digital transformations by means of novel and empirically grounded insights and derive actionable response strategies. In respond, my dissertation addresses the overall research question of how B2B supplier firms can successfully implement both digital and non-digital transformations in three individual essays.
In Essay 1, I offer a broader perspective on both digital and non-digital transformations by investigating digital service customization (i.e., the tailoring of digital B2B services to customers’ individual needs). Through a systematic literature review and bibliometric analysis, I outline a comprehensive set of factors that favor the application of distinct digital service customization strategies. Essay 2 represents a deep dive into digital transformations of sales processes. By making use of two rich sets of qualitative interview material from supplier and buyer firms, I identify the challenges resulting for B2B salespeople from the introduction of digital sales channels into personal selling. Moreover, I uncover facilitating mechanisms that sales managers can employ to support salespeople in coping with digital sales channels. Finally, Essay 3 constitutes a deep dive into non-digital transformations. Based on qualitative interview material and survey data from matched sales manager–salesperson dyads, the essay explores how configurations of individual salespeople’s personal and procedural competencies facilitate success at selling customer solutions (i.e., highly customized, performance-oriented offerings comprising products and/or services). The essay shows that successfully selling customized offerings like solutions hinges on salespeople’s unique configurations of present and absent competencies.
In a nutshell, these essays provide three major insights on how B2B suppliers can successfully implement digital and non-digital transformations. First, they underscore that a comprehensive understanding of the origins and spillover effects of transformations is a key prerequisite to successfully implementing them. Second, they unveil that digital and non-digital transformations impact on multiple organizational levels. Third, they point out important resources and capabilities that help suppliers to successfully implement transformations, be they digital or non-digital.
With this dissertation, I make substantial contributions to the broader literature on digital and non-digital transformations in B2B contexts. At the same time, my dissertation provides hands-on implications for managers in B2B supplier firms that are facing fundamental transformations in the marketplace—both digital and non-digital in nature.
New arising phenomena in the occupational realm strongly shape contemporary work settings. These developments heavily affect how individuals work within and beyond organizational boundaries. Two phenomena associated with the changing nature of work have been especially prevalent in work settings and intensively discussed in public debates. First, organizations started to introduce mindfulness practices to their workforce. Rooted in spirituality and formerly used in clinical therapy, mindfulness is applied as a human resource development practice to train employees and managers to cope with the increased work intensification. Second, digitization and the importance of individualization opened up the path for work settings beyond organizational boundaries on crowdworking online platforms. On these online platforms, workers process tasks independently and remotely. Research just started to address the implications and meaning of mindfulness practices in organizations and the rise of crowdworking platforms. Several questions remain unanswered. This dissertation addresses unanswered but pressing questions related to these two phenomena shaping contemporary work settings. Structured in four essays the first two essays address the application and meaning of mindfulness practices. The first essay analyzes the meaning and interpretations of these new practices within organizations. The second essay takes contextual factors of the organizational environment into account and investigates their relevance for the successful implementation of mindfulness practices. The second two essays are dedicated to work attitudes and behavior on crowdworking online platform. Essay three captures individuals’ motivation for working on such platforms and their effects for workers’ work performance. The last essay deals with the role of professional crowdworking online communities in the work experience and asses the effects of social support in these communities on occupational identification, work meaningfulness and finally on work engagement. Each essay in this dissertation generates new insights on arising phenomena in contemporary work settings. They address several timely yet unanswered research questions for these rising phenomena and thereby offer a deeper and more nuanced understanding of the role mindfulness practices and crowdworking online platforms play in the context of the future of work.
Job Sequencing and Tool Switching Problems with a Generalisation to Non-Identical Parallel Machines
(2020)
Manufacturing tools have been dominating the manufacturing process since the 1960s. The job sequencing and tool switching problem is an NP-hard combinatorial optimization that has first been introduced in the context of flexible manufacturing systems in the late 1980s. Since then, production systems have undisputedly changed and improved but manufacturing tools still dominate manufacturing processes. Production and system operation processes are continuously adjusted and optimised to changing customer requirements. If the product variety requires an increasing number of tools for processing that exceeds the local tool magazine capacity of the manufacturing system, tool switches become necessary. Although tool changing times within a manufacturing centre or cell may nowadays be very small due to the high degree of automation, tool switching within a dynamic production environment is still a time consuming process that must be avoided. In order to minimize the total tool setup time to enhance productivity, the objectives of the basic job sequencing and tool switching problem are to sequence a set of jobs and simultaneously to determine the best tool loading. Therefore, job sequencing and tool switching problems are gaining considerable attention.
Several solution approaches to the standard problem and related versions of the problem exist. The first part of this dissertation assesses the current state-of-the-art of the job sequencing and tool switching problem and provides a classification scheme for literature on the job sequencing and tool switching problem and its variations. Only few authors consider generalisations of the problem because the level of complexity of extended problems is high. A general approach of the job sequencing and tool switching problem with non-identical parallel machines and sequence-dependent setup times is described in this dissertation. A novel mathematical model based on time periods is presented and analysed which can be adapted to different objective functions. The last part of this dissertation is a quantitative evaluation of fast and effective construction heuristics as well as of an iterated local search algorithm tested on a new set of benchmark instances. As such this dissertation provides a broad basis for future evaluations of solution approaches to the job sequencing and tool switching problem with non-identical parallel machines and sequence-dependent setup times as well as a basis for further generalisations of the problem like for example tool availability constraints or tool-size dependent variations.
Innovate with Crowds. Co-Creation and Idea Evaluation in Internal and External Crowdsourcing.
(2020)
Crowdsourcing seems to be a promising approach for organizations to overcome challenges widely discussed in innovation and organizational research. However, the extent to which an organization can leverage the benefits from crowdsourcing is contingent on which type of crowd is addressed and how crowds are used. Based on unique data from crowdsourcing contests, the dissertation provides insights how to innovate with internal and external crowds in order to utilize their potential for co-creation and idea evaluation.
Investment fraud, cybercrime, inconsistencies in health care or the emission scams at the car manufacturers, economic crime (fraud) manifests itself in many facets. For Germany, the cases of FlowTex, Comroad, HRE-Bad-Bank, Holzmann, Volkswagen and the current fraud suspicions at Porsche AG are prominent examples with mostly appalling consequences (Ballwieser and Dobler 2003; Kögler 2015; Meck, Nienhaus, and von Petersdorff 2011; Peemöller and Hofmann 2005). Nevertheless, newspapers without reports on fraud have become scarce. Headlines such as: "Corruption - the daily business" impress hardly anyone, not least because of their certain regularity. The cases revealed publicly are, however, only the tip of the iceberg, as reported by renowned experts (Bundeskriminalamt 2018; LKA 2018). Currently, the State Criminal Police Office (Landeskriminalamt (LKA)) of Baden-Württemberg and its department for economic and environmental crime and corruption is concerned with 72 major proceedings (LKA 2018). However, fraud could be avoided or at least contained by appropriate preventive measures (Bundeskriminalamt 2018; Bussmann 2004; Hlavica, Klapproth, and Hülsberg 2011). Consequently, the pressure on companies and employees to demonstrate compliant and ethical behavior and to meet the demands of stakeholders at all times within their business activities has grown (Buff 2000). This raises the question about which precautionary measures a company can and must implement (Weick and Sutcliffe 2015). Although corporate awareness of this issue has increased, most in-house detection of fraud is accidental, suggesting that companies are still lacking appropriately functioning and systematic (early) detection mechanism (Hlavica et al. 2011). If a company is accused of fraud, this usually has serious repercussions on its corporate reputation. Prior research found that capital market reputation-based penalties for affected companies are on average 7.5 times higher than penalties imposed by the legal system (Karpoff, Lee, and Martin 2008). Furthermore, the accusation of fraud also affects the external auditor’s reputation, since lacking the detection of manipulations in clients’ (financial) reports not only damages public confidence in the accuracy of firms’ financial statements but also in the reliability of the auditor's report. Therefore, it is not surprising that the demand for greater supervision and control of firms’ (financial) reporting as well as for reliable work of statutory auditors continually increases (Herkendell 2007). Although to a lesser extent, this is also the case for the determination of material (accounting) errors within a firm’s financial statements, which are often difficult to distinguish from accounting fraud. According to the International Accounting Standard (IAS) 8.5, published by the International Accounting Standards Board (IASB), errors are omissions and/or misstatements of items that result from the nonapplication or misapplication of trusted information (IASB 2003). Thus, accounting errors and accounting fraud both result in incorrect information of a firm’s financial reports and consequently affect stakeholders’ decision-making. One resulting attempt in counteracting the broad demand for appropriate protective measures was the implementation of a two-stage enforcement system involving the German Financial Reporting Enforcement Panel (Deutsche Prüfstelle für Rechnungslegung (DPR)) as part of the adopted Financial Reporting Enforcement Act (Bilanzkontrollgesetz (BilKoG)) in 2004. The primary objective of the Federal Government's implementation of this mechanism was to strengthen investors' lost confidence in the German capital market, the information content of financial reporting, and Germany as a financial center in the international competition. In addition, the enforcement system serves as a sanctioning instrument for firms in the event of an error detection and subsequent adverse error disclosure via the German federal registry (elektronischer Bundesanzeiger). This adverse error disclosure not only sanctions denounced firms but also questions the quality of the annual financial statement audit and thus the quality of the responsible audit firm. Hence, the often thin line between firms’ unintentional accounting errors, purposive engagement in earnings management, and intentional fraud in particular presents an increasing challenge for the audit profession.
The objective of my cumulative dissertation is to provide a comprehensive overview of fraud and forensic accounting as well as insights into the distinct dimensions among the concepts of errors, earnings management and fraud from a German accounting perspective. I aim at achieving this objective in three steps: First (1), by providing an overview of discipline-specific education possibilities, existing forensic accounting practices, institutions, and current developments in research. Second (2), by assessing auditors’ obligations and responsibilities for the detection of irregularities within the scope of the annual financial statement audit and whether including forensic services into the service portfolio of audit firms can help increase their audit quality due to spillover effects. Third (3), by examining firms’ reputation (re-)building management in response to financial violations and how this process is associated with managing multiple (stakeholder) reputations. This dissertation is composed of three individual papers whereby each considers one of the above outlined focus areas
Geography, social context, time, and cultural mindset are four (out of many) cornerstones of human interaction. When building statistical models, their consideration is vital: They all cause dependency between individual observations, violating assumptions of independence and exchangeability. While this can be problematic and inhibit the unbiased inference of parameters, it can also be a fruitful source of insights and enhance prediction performance.
One class of models that serves to manage or profit from the presence of dependence is the class of latent variable models. This class of models assumes that the presence of non-explicit, unobserved causes of continuous or discrete nature can explain the observed correlations. Latent variable models explicitly take account of dependency, for example, by modeling an unobserved local source of pollution as a continuous spatial variable. Through their widespread use for information fitering, link prediction, and statistical inference, latent variable models have developed an essential impact on our daily life and the way we consume information.
The four articles in this thesis shed light on assumptions, usage, and potential drawbacks of latent variable models in various contexts that involve geographic and interaction data. We model unobserved sources of pollution in geophysical data, explore individual taste and mindsets in cross-cultural contexts, and predict the evolution of social relationships in software development projects. This combination of various perspectives contributes to the interdisciplinary exchange of methodological knowledge on the modeling of dependent data.