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The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing applications. For example, consumers compare and review products online, individuals interact with their voice assistants to search, shop, and express their needs, investors seek to extract signals from firms' press releases to improve their investment decisions, and firms analyze sales call transcripts to increase customer satisfaction and conversions. However, extracting meaningful information from unstructured text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering recent embedding-based approaches, pretrained language models, and transfer learning for novel tasks such as automated text generation and multi-modal representation learning. These emerging approaches allow the field to improve its ability to perform certain tasks that we have been using for more than a decade (e.g., text classification). But more importantly, they unlock entirely new types of tasks that bring about novel research opportunities (e.g., text summarization, and generative question answering). We conclude with a roadmap and research agenda for promising NLP applications in marketing and provide supplementary code examples to help interested scholars to explore opportunities related to NLP in marketing.

Across disciplines, researchers and practitioners employ decision tree ensembles such as random forests and XGBoost with great success. What explains their popularity? This chapter showcases how marketing scholars and decision-makers can harness the power of decision tree ensembles for academic and practical applications. The author discusses the origin of decision tree ensembles, explains their theoretical underpinnings, and illustrates them empirically using a real-world telemarketing case, with the objective of predicting customer conversions. Readers unfamiliar with decision tree ensembles will learn to appreciate them for their versatility, competitive accuracy, ease of application, and computational efficiency and will gain a comprehensive understanding why decision tree ensembles contribute to every data scientist's methodological toolbox.

Research on creativity highlights feedback as an important driver of creative ideas. However, it advances a rather mechanistic understanding of communication, which obscures the specific practices in feedback interactions as well as their constitutive role in shaping creative ideas. In this paper, we advance conceptual arguments on how actors interact in communicative feedback processes on creative ideas. By drawing on the theory of communicative action by Jürgen Habermas and Hans Joas’ theory of creative action, we develop a more complex and nuanced understanding of creativity as a phenomenon that is constituted in communication. These authors’ work draws conceptual attention to the practices through which actors negotiate the novelty and usefulness of creative ideas in communicative interactions, the important role of feedback givers as creative actors, and “spaces for play” as a communicative sphere that allows creativity to emerge. We extend the literature on creativity by introducing a theory of communicative and creative action that offers to unpack communicative interactions through which creativity does or does not come into being.

This volume brings together empirical and conceptual papers that investigate the challenges of organizing creativity in the innovation journey in and across different empirical contexts. Seen as the basis for innovating new products, processes or services, organizing creativity is studied as intentional efforts that occur in teams, organizations, and fields. What creativity is, how it is defined, negotiated and recognized is hereby co-constructed with different audiences and in different economic and societal spheres. The papers in this volume extend our understanding of these contextualized social dynamics of organizing creativity in four directions. The first direction sheds light on the temporal dynamics of organizing creativity in artistic fields. The second direction compares creative processes in arts and science, thereby examining tensions and uncertainties in the creative process unfolding in two distinctive contexts of creativity. The third direction examines identity struggles of creative agents in organizations with clashing roles, professional norms, and ambiguities in creativity assessment. The fourth and final direction unravels the communicative journey of ideas from pitching to feedback, revealing how ideas are challenged, enriched, and acquire meaning in communicative interaction. Overall, the papers in this volume contribute to a situated view of creative processes in innovation which goes beyond questions of idea generation to account for dynamics of idea development, judgment, and dissemination which involve identity struggles, evaluation, and communication – processes which are at the heart of organizing for innovation.

This paper aims to investigate the ability of performance measurement systems (PMS) that were implemented by headquarters at foreign subsidiaries to influence decisions made by the subsidiary. This is important because PMS are important control mechanisms in the relationship between headquarters and subsidiaries within multinational firms.

Acknowledging that controlling foreign subsidiaries is particularly challenging when they are geographically distant to headquarters, the authors collect survey‐based data from Chinese subsidiaries of multinational firms. They develop several hypotheses which are tested on a sample of 148 subsidiaries using multiple regression analysis.

The results suggest that the influence of headquarter‐designed PMS on subsidiary decisions is higher when the compensation of subsidiary management is linked to PMS, when additional formal control is enforced, when PMS are affected by external events, when PMS are comprehensive, and when subsidiaries are embedded into the local business environment. Also, the authors find a negative interaction effect between comprehensive PMS and the extent to which PMS are affected by external events on the decision‐influence of PMS.

Limitations arise from the study setting in China. As management accounting research originates from and has mostly focused on Western countries, it remains somewhat unclear whether the constructs and instruments used in this study are fully transferable to China, despite the statistical and conceptual remedies that were applied.

The study offers new insights into the role of PMS in multinational companies. It extends earlier research by offering empirical evidence from one of the most important emerging economies. As such, the results are relevant for almost every global firm using PMS to control foreign subsidiaries.

The purpose of this paper is to propose a conceptual framework of experience co-creation that captures the multi-dimensionality of this construct, as well as a research process for defining of the antecedents of experience co-creation.

The framework of experience co-creation was conceptualized by means of a literature review. Subsequently, this framework was used as the conceptual basis for a qualitative content analysis of 66 empirical papers investigating alternative consumption models (ACMs), such as renting, remanufacturing, and second-hand models.

The qualitative content analysis resulted in 12 categories related to the consumer and 9 related to the ACM offerings that represent the antecedents of experience co-creation. These categories provide evidence that, to a large extent, the developed conceptual framework allows one to capture the multi-dimensionality of the experience co-creation construct.

This study underscores the understanding of experience co-creation as a function of the characteristics of the offering – which are, in turn, a function of the consumers’ motives as determined by their lifeworlds – as well as to service design as an iterative approach to finding, creating and refining service offerings.

The investigation of the antecedents of experience co-creation can enable service providers to determine significant consumer market conditions for forecasting the suitability and viability of their offerings and to adjust their service designs accordingly.

This paper provides a step toward the operationalization of the dimension-related experience co-creation construct and presents an approach to defining the antecedents of experience co-creation by considering different research perspectives that can enhance service design research.

Real-time location sensing (RTLS) systems offer a significant potential to advance the management of construction processes by potentially providing real-time access to the locations of workers and equipment. Many location-sensing technologies tend to perform poorly for indoor work environments and generate large data sets that are somewhat difficult to process in a meaningful way. Unfortunately, little is still known regarding the practical benefits of converting raw worker tracking data into meaningful information about construction project progress, effectively impeding widespread adoption in construction.

The presented framework is designed to automate as many steps as possible, aiming to avoid manual procedures that significantly increase the time between progress estimation updates. The authors apply simple location tracking sensor data that does not require personal handling, to ensure continuous data acquisition. They use a generic and non-site-specific knowledge base (KB) created through domain expert interviews. The sensor data and KB are analyzed in an abductive reasoning framework implemented in Answer Set Programming (extended to support spatial and temporal reasoning), a logic programming paradigm developed within the artificial intelligence domain.

This work demonstrates how abductive reasoning can be applied to automatically generate rich and qualitative information about activities that have been carried out on a construction site. These activities are subsequently used for reasoning about the progress of the construction project. Our framework delivers an upper bound on project progress (“optimistic estimates”) within a practical amount of time, in the order of seconds. The target user group is construction management by providing project planning decision support.

The KB developed for this early-stage research does not encapsulate an exhaustive body of domain expert knowledge. Instead, it consists of excerpts of activities in the analyzed construction site. The KB is developed to be non-site-specific, but it is not validated as the performed experiments were carried out on one single construction site.

The presented work enables automated processing of simple location tracking sensor data, which provides construction management with detailed insight into construction site progress without performing labor-intensive procedures common nowadays.

While automated progress estimation and activity recognition in construction have been studied for some time, the authors approach it differently. Instead of expensive equipment, manually acquired, information-rich sensor data, the authors apply simple data, domain knowledge and a logical reasoning system for which the results are promising.