Ankita Singh

Abstract

Movies are often sequentially offered through different distribution channels such as theaters, video sales and rentals, and online streaming. This research answers the question of how the advertising budget should be allocated across the various distribution channels to maximize overall profit. An extant allocation model is limited because of maximizing the logarithms of sales minus costs rather than true untransformed profit. Overcoming this limitation, my research offers a simple, near-optimal rule which takes into account not only the various effectiveness measures of advertising in terms of elasticities and, both, carryover and spillover effects, but also the size of the channels (expected profit) and truly maximizes profit. Due to its cascading property, the rule can be extended to any number of sequential distribution channels. This article also explains how the parameter values for the rule can be obtained and what profit improvement can be gained depending on the data structure.

Abstract

Cognitive demands are increasingly prevalent in today’s complex work environments. With research having established that cognitive demands lead to strain, we introduce and test error management as a strain buffer for cognitive demands. We examined our theoretical model with two field studies. Across both studies, we found that when error management was low, cognitive demands were positively related to strain, while the relationship between cognitive demands and strain vanished when error management was high. This interaction was unique for cognitive demands, as error management did not influence strain in response to workload. Errors in cognitively demanding tasks were seen as more internal, but more controllable and less stable than errors when working with high workloads. Yet, we could not find error management influencing error attributions as we assumed to be the underlying theoretical mechanism. In sum, we suggest error management as a tangible mean by which organizations and employees can mitigate the strain-inducing effect of cognitive demands, which needs further research to be better understood.

Abstract

User-generated content (UGC) is generally understood as an expression of opinion in many forms (e.g., complaints, online customer reviews, posts, testimonials) and data types (e.g., text, image, audio, video, or a combination thereof) that has been created and made available by users of websites, platforms, and apps on the Internet. In the digital age, huge amounts of UGC are available. Since UGC often reflects evaluations of brands, products, services, and technologies, many consumers rely on UGC to support and secure their purchasing and/or usage decisions. But UGC also has significant value for marketing managers. UGC allows them to easily gain insights into consumer attitudes, preferences, and behaviors. In this article, we review the literature on UGC-based decision support from this managerial perspective and look closely at relevant methods. In particular, we discuss how to collect and analyze various types of UGC from websites, platforms, and apps. Traditional data analysis and machine learning based on feature extraction methods as well as discriminative and generative deep learning methods are discussed. Selected use cases across various marketing management decision areas (such as customer/market selection, brand management, product/service quality management, new product/service development) are summarized. We provide researchers and practitioners with a comprehensive understanding of the current state of UGC data collection and analysis and help them to leverage this powerful resource effectively. Moreover, we shed light on potential applications in managerial decision support and identify research questions for further exploration.

Abstract

Sustainability has become a critical concern of many societies worldwide. The need for a more sustainable mode of producing and consuming goods and services while balancing related environmental, social, and economic consequences (i.e., the triple bottom line) is evident. Although research offers insights into many aspects of this necessary transformation, little is known about the extent to which firms and consumers stress environmental, social, and economic sustainability in their communication. This research addresses these questions by conceptualizing the interplay between sustainability-related firm-generated and user-generated content as a signaling phenomenon. In addition, the authors develop a custom dictionary that enables researchers and practitioners to identify and analyze sustainability-related textual data. An illustrative application based on major data sources (corporate websites, Amazon, and YouTube) indicates significant divergence in how firms and consumers communicate about sustainability. Building on this first conceptual and empirical foray into sustainability-related firm-generated and user-generated content, this research outlines open research questions and potential use cases for the provided analytical tool.

Abstract

In this research, we set out to uncover why silver ceilings exist in organizations. Drawing on systematic–heuristic processing theory and recent psychological findings, we propose that “older” workers (aged 45 or more) are less likely to receive promotions because these decisions are based on potential appraisals, which are susceptible to managers’ heuristic (stereotypical) thinking. We test our hypotheses using two-wave field data (Study 1) from a large financial organization and an experiment (Study 2) in which we manipulate age while holding all else equal. Both studies show that employee age has a negative effect on promotion likelihood and that this relationship is mediated by managers’ potential appraisals. Moreover, Study 2 also provides evidence for our theoretical rationale showing that the central effect is driven by managers’ heuristic processing and work-related age stereotypes. Across both studies, our results provide consistent support for our hypothesis that appraisals of potential constitute a potent pathway via which managers’ age stereotypes can affect promotion decisions in organizations. We discuss theoretical contributions to the literature on workplace aging, employee appraisals, and personnel decisions, and formulate practical recommendations to help organizations tackle silver ceilings in the workplace.

Abstract

Global container shipping is integral to international trade, and a nuanced understanding of the role of strategic alliances and market concentration is crucial for the continuous and secure functioning of global logistics across different trades. We investigate the spatio-temporal evolution of alliance deployment and market concentration in the container shipping industry. This study introduces an innovative methodological approach - clustering trade routes using Dynamic Time Warping (DTW) based on alliance deployment and market concentration metrics rather than relying on predefined geographic boundaries. The approach uncovers previously unexplored structural relationships between alliance strategies and market dynamics, providing a more nuanced understanding of the container shipping industry's competitive landscape and potential vulnerabilities. We address important questions on how alliance deployment, market concentration, and inequality correlate or differ across global trade lanes and the implications for a potential threat of market power or collusive behavior for international trade and market accessibility. Our findings reveal that extensive alliance deployment does not inherently lead to a heightened market concentration or inequality. On major East-West trade routes, high levels of alliance deployment correspond with relatively low market concentration and inequality, indicating competitive environments where multiple carriers actively compete for market share. Conversely, niche markets exhibit higher market concentration and inequality, with increased potential for collusive behavior, especially where alliance deployment is minimal or absent. Our results underscore the need for regulatory bodies to foster fair competition, mitigate anti-competitive practices under a differentiated approach, and enhance market accessibility in the context of global trade flows. Finally, our research reveals the risk of power imbalances between regulators of small countries and leading global shipping lines.

Abstract

Diversity, equity, and inclusion (DEI) are at the core of present-day health and humanitarian logistics. Aid organizations advocate inclusive people-centered approaches to ensure that affected communities receive appropriate aid in an effective and equitable way. Tensions and even conflicts can arise if affected communities perceive the distribution of aid as inequitable. These perceptions are driven by people’s so-called distributional preferences. These preferences are shaped by culture, social bonds, and experiences, and they describe how an individual’s well-being and behavior are impacted by potential inequalities. Their importance is increasingly recognized by aid organizations, but research on equity in health and humanitarian logistics remains focused on equal access and prioritizing needs. Using current examples from the Syrian and Rohingya refugee crises, we show the importance of recognizing and managing distributional preferences. Based on these examples and in line with DEI principles, we discuss several ways that we, as the operations community, can help conceptualize inclusive and people-centered approaches that account for distributional preferences.