KLU faculty members, post-docs, and PhD candidates regularly publish the results of their research in scientific journals. You will find a complete overview of all KLU publications below (e.g. articles in peer-reviewed journals, professional journals, books, working papers, conference proceedings and cases). Search for relevant terms and keywords, or filter the list by name, year or type of publication. The references include DOIs and abstracts where available, and you can download them to your own reference database or platform. We regularly update the database with new publications. Please send your enquires about KLU publications to library@klu.org
Journal Articles (Peer-Reviewed)
(In press): EXPRESS: Equity in Health and Humanitarian Logistics: a People-Centered Perspective, Production & Operations Management: .
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.
(In Press): Diversity and inclusion under pressure: Building relational resilience into humanitarian operations, Production and Operations Management: .
Abstract: In this essay, our analysis takes important insights on diversity and inclusion from the behavioral literature but critically contextualizes them against the reality of humanitarian operations. Humanitarian operations are characterized by system immanent diversity, particularly between local and expatriate aid workers, who not only bring valuable different perspectives to the table but also differ along multiple dimensions of diversity into a so-called diversity faultline. Such a faultline, however, provides fertile ground for continued conflict resulting in relational fractures and, ultimately, inefficient collaboration. While, in theory, inclusion could help overcome the negative effects of faultlines, in practice, the time pressure for humanitarian organizations to quickly respond to disasters makes it effectively impossible to engage in it. Against this background, we argue, humanitarian organizations should take preemptive action before disaster strikes. Specifically, we posit that the pre-disaster phase presents an opportunity to engage in inclusion in order to cultivate relational resilience between local and expatriate aid workers. Such resilience would enable them to not only better weather the inevitable relational fractures during a disaster response (and thus stay more functional throughout), but also quickly realign with each other in the post-disaster phase. We conclude with a set of concrete recommendations for practicing inclusion in the pre-disaster phase.
(In press): Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries: “Coordination and Competition”, Production & Operations Management: .
Abstract: Several low- and middle-income countries’ emergency transportation systems (ETSs) do not have a centralized emergency number. Instead, they have many independent ambulance providers, each with a small number of ambulances. As a result, ETSs in these contexts lack coordination and ambulances. Using a free-entry equilibrium model, we show that in such decentralized systems, the probability that any given call can be served by at least one ambulance, that is, its coverage, is at most 71.54%, regardless of the ETS’s profitability. We examine three business models that can address the ETS’s lack of coordination and ambulances: (i) a competitor-only business model, where an entrepreneur enters the ETS and acquires ambulances to compete with existing providers; (ii) a platform business model, where an entrepreneur coordinates existing providers; and (iii) an innovative platform-plus business model, where an entrepreneur combines (i) and (ii): setting-up a platform and acquiring platform-owned ambulances. We also examine a government-run platform that takes no commissions from providers. Using a game-theoretic approach, we find that it is optimal for all platform models to incentivize all providers to join. However, only the government-run platform may incentivize providers to acquire additional ambulances. Furthermore, a government-run platform offers higher coverage than a platform-plus only when the platform’s power to coordinate ambulance providers is moderate. Our results can help entrepreneurs and policymakers in LMICs navigate various tradeoffs in improving their countries’ ETS.
(In Press): How Identity Impacts Bystander Responses to Workplace Mistreatment, Journal of Management: .
Abstract: Integrating a social identity approach with Cortina's (2008) theorizing about selective incivility as modern discrimination, we examine how identification—with an organization, with one's gender, and as a feminist—shapes bystanders’ interpretations and responses to witnessed incivility (i.e., interpersonal acts of disrespect) and selective incivility (i.e., incivility motivated by targets’ social group membership) toward women at work. We propose that bystanders with stronger organizational identification are less likely to perceive incivility toward female colleagues as discrimination and intervene, but female bystanders with stronger gender identification are more likely to do so. Results from two-wave field data in a cross-lagged panel design (Study 1, N = 336) showed that organizational identification negatively predicted observed selective incivility 1 year later but revealed no evidence of an effect of female bystanders’ gender identification. We replicated and extended these results with a vignette experiment (Study 2, N = 410) and an experimental recall study (Study 3, N = 504). Findings revealed a “dark side” of organizational identification: strongly identified bystanders were less likely to perceive incivility as discrimination, but there were again no effects of women's gender identification. Study 3 also showed that bystander feminist identification increased intervention via perceived discrimination. These results raise doubts that female bystanders are more sensitive to recognizing other women's mistreatment as discrimination, but more strongly identified feminists (male or female) were more likely to intervene. Although strongly organizationally identified bystanders were more likely to overlook women's mistreatment, they were also more likely to intervene once discrimination was apparent.
(In Press): Does CEO extraversion pay off when in need? Evidence from the global financial crisis, The British Accounting Review: .
Abstract: We examine the effect of CEO extraversion on corporate performance during the Global Financial Crisis (GFC). Contrary to the expectation that extraverted CEOs should shield firms better from GFC adversities, we document that the extraversion characteristic of CEOs places a significant, though negative, effect on corporate performance during the financial crisis. Our findings are robust to controlling for other CEO personality traits. We also perform a battery of robustness tests and validate the underperformance of firms with extraverted CEOs during the GFC using stock returns and measures of operating performance. We argue that because extraverted CEOs are associated with heightened firm risk profile, this can hurt firms when the market disciplines excessive risk-taking during the crisis.
(In Press): Comparative Configurational Process Analysis: A New Set-Theoretic Technique for Longitudinal Case Analysis, Organizational Research Methods: .
Abstract: In the past 20 years, researchers have significantly advanced various management fields by examining organizational phenomena through a configurational lens, including competitive strategies, corporate governance mechanisms, and innovation systems. Qualitative comparative analysis (QCA) has emerged as a primary method for empirically investigating organizational configurations. However, QCA has traditionally struggled to capture the temporal aspects of configurational phenomena. In this paper, we present configurational comparative process analysis (C2PA), which merges QCA with sequence analysis. We introduce the concept of configurational themes—recognizable temporal patterns of recurring combinations of explanatory conditions—to identify and track the temporal dynamics among these phenomena. We also outline configurational matching—a method for empirically identifying these themes by distinguishing theme-defining from theme-supporting conditions. C2PA allows researchers to explore the temporal dynamics of configurational phenomena, such as their stability, emergence, and decline at critical junctures. We illustrate the application of C2PA through a study of shareholder value orientation and discuss its potential for addressing key questions in management research.
(In press): “I Just Don’t Fit There!” Anticipated Cultural Mismatch and Social Disparities in Students’ Intention to Enter Higher Education, Social Psychological and Personality Science: .
Abstract: Despite political and societal efforts to reduce social inequality in education, students from nonacademic households (no parent holds a university degree) are less likely to enter higher education than their peers from academic households. Drawing on Cultural Mismatch Theory, we tested whether social disparities in enrollment intentions are related to students’ anticipated mismatch between their self-construal and expected higher education culture. Experimental data (N = 264) revealed a corresponding mismatch effect between students’ self-construal and expected culture on their anticipated fit in a higher education program. In addition, field data (N = 574) from upper secondary school students revealed that students from nonacademic households more strongly anticipate a mismatch and, in turn, have a lower intention to enter higher education. Corroborating our theorizing, these social disparities are contingent on the expected culture in higher education. These findings highlight the role of students’ self-construal and anticipated fit for higher education enrollment.
(In Press): Tax privacy concerns hamper digitization of the Nanostore Channel, Decision Sciences: .
Abstract: Various entities, such as startups, suppliers and governments, face substantial difficulties in convincing nanostore shopkeepers to adopt digital technologies. Given the informal status of nanostores, we posit that shopkeepers experience Tax Privacy Concerns from their operational records potentially becoming transparent to the tax authorities, which hampers their inclination to digitize. Through the application of a survey and vignette experiments in the field with hundreds of shopkeepers across three cities in Latin America, we find consistent evidence for the negative role of Tax Privacy Concerns, above and beyond shopkeepers' willingness to share data with various entities, trust in the government and other entities, and general privacy concerns. Further, we show that having entities that shopkeepers trust and are willing to share data with offer technological solutions does not mitigate shopkeepers' Tax Privacy Concerns and boosts digitization. In contrast, positive word of mouth that data are unlikely to be shared with the tax authorities does mitigate Tax Privacy Concerns. Overall, our findings provide novel evidence for the existence and influence of privacy concerns for operational data among microentrepreneurs, which answers calls in the extant literature to explore privacy concerns.beyond the consumer context.
(In press): Anti-trafficking and Humanitarian Operations: Transferring Learnings for a Better World, Journal of Humanitarian Logistics and Supply Chain Management: .
(In press): Demand and supply side effects of COVID-19 on music streaming, Journal of Media Economics: 1-27.
Abstract: Restrictions imposed to fight the Covid-19 pandemic dramatically changed life. This affected the entertainment industry with consequences on the demand (consumer behavior in terms of quantity and preferences) and supply side (quantity of published products). Suffering from revenue losses because of canceled live events due to Covid-19, the music industry heavily relied on streaming revenues so we investigate how the lockdowns and other restrictions affected demand and supply within the music streaming industry. Using daily Spotify streaming data, as well as the MusicBrainz encyclopedia, we empirically investigate changes in the number of streams per day, listening preferences (demand side), and the number of releases (supply side) for the United States, Germany, Brazil, and Indonesia. For the demand side, the results imply that lockdown measures led to a decrease in the total number of streams per day. This coincided with country-specific changes in music preferences such as a short-term increase in the consumption of happy music. On the supply side, a global increase in songs released with increasing lockdown measures was found. Although most effects mitigate over time, they lead to serious ongoing financial consequences for artists, record labels, and streaming services.
(In press): Opening the floodgates:How big companies can reap the benefits of internal crowdfunding, Business Horizons: .
Abstract: Digital technologies enable employees at all levels to participate in distributed decision-making. We examine the design principles, benefits, and challenges of a new type of distributed decision-making: internal crowdfunding. We build on a five-year case study of internal crowdfunding contests at Siemens AG to deepen our understanding of the design principles of internal crowdfunding and its potential for corporate innovation. Based on this data, we discuss the three design choices in internal crowdfunding (contributors, configuration, and control), find four key benefits (decentralization, cross-collaboration, institutionalization, and intrapreneurship), and identify three key challenges (dealing with rejected ideas, evaluation biases, and implementation and follow-on funding) and potential actions by managers to overcome them. The paper contributes to both the emerging literature on internal crowdfunding and the literature on distributed decision-making.
(In press): How Mixed Performance Feedback Shapes Exploration: The Moderating Role of Self-Enhancement, Organization Science: 1-43.
Abstract: We conduct an experiment to examine how providing decision makers with high vs. low peer performance information influences choices between exploration and exploitation. Previous work on organization-level learning suggests a high-performing peer would fuel exploration, while a low-performing peer would dampen it. In line with this, we find that individuals who receive information about a high-performing peer explore more than those who receive information about a low-performing peer. However, we also find that, compared to individuals with a low tendency to self-enhance, individuals with a high tendency to self-enhance are less likely to explore when receiving information about a high-performing peer. In fact, these individuals explore at levels comparable to those who receive information about a low-performing peer. We explain this behavioral pattern by demonstrating that, as individuals learn and improves, information about a high-performing peer increasingly results in mixed performance feedback; under these conditions of relative interpretive flexibility, exploration is moderated by decision makers’ tendency to self-enhance. When these individual dynamics are aggregated, our data suggest that an organization that provides peer performance information may experience either the same or less exploration than an organization that does not, with the exact difference depending on its proportion of high self-enhancers. These insights into the contingencies and aggregate effects of how individuals interpret and respond to peer performance information are particularly relevant given recent interest in designing organizations that shape employee behavior through the provision of feedback, rather than through traditional instruments of coordination and control such as incentives or hierarchy.
(In press): Marketing inputs and outcome heterogeneity – Using a quantile regression framework in the entertainment industry, Journal of the Academy of Marketing Science: .
(In press): The role of inventory in firm resilience to the Covid‐19 pandemic, European Financial Management: 1-33.
Abstract: We study the role of inventory in corporate resilience to Covid-19 in 2020, which triggered exogenous shocks to consumer demand, commodity prices and supply chains. Unexpected drops in consumer demand and commodity prices increase the costs of inventory. Conversely, inventory holdings can buffer against supply disruptions. Empirically, US firms with higher inventory experienced more negative stock market responses early in the crisis due to falling consumer demand. However, since May 2020, inventory has become valuable as a hedge against supply disruptions, improving firm performance. During Covid-19, unlike other crises, inventory played a unique role as a hedge against supply disruptions.
(2024): Studying complex causal processes in technological innovation and entrepreneurship with set-theoretic mediation models, Technovation, 134 (6): 103015.
Abstract: Researchers often turn to linear mediation models to understand the complex causal processes inherent within innovation and entrepreneurship phenomena. However, these models are not always the most appropriate methods for increasing our understanding of these phenomena. This is because linear models depend on the principle of reductionism – which separates causal processes into their independent components – and overlooks systemwide attributes. To advance research findings that do not adequately address complex causal processes, we advocate using set-theoretic mediation models that offer analytical features better suited for holistically uncovering interdependent and intervening pathways. This method enables investigating complex causal processes associated with the conjunction, equifinality, and asymmetry that can occur with multiple interdependent variables. We provide researchers with practical guidance on constructing and testing set-theoretic mediation models using widely available software while demonstrating these procedures with an illustrative analysis. In doing so, we seek to guide researchers interested in integrating these models into their studies and recommend best practices for implementation. We argue that set-theoretic meditation models can be utilized in various contexts, as they offer new research opportunities for exploring unified necessity and sufficiency relational systems in ways existing methods have yet to address.
(2024): Automatically identifying customer needs in user-generated content using token classification, Decision Support Systems, 178: 1-11.
Abstract: Users generate tremendous amounts of data on the Internet every day. This so-called user-generated content (UGC) is valuable input for organizations since it may include individual experiences, opinions, and desires with respect to the products and services they offer. To automatically process UGC, automated techniques, typically referred to as Needmining, have been developed. Existing Needmining approaches extract customer needs from UGC by binarily classifying unstructured textual data into need-content and no-need content. However, they are not able to extract the specific needs. We address this research gap by developing a decision support artifact that re-conceptualizes Needmining from a binary classification problem to a token-classification problem to extract specific needs from informative content. To achieve this, we break down customer needs into components, i.e. attributes and characteristics and develop a token classification artifact. The artifact accurately identifies the need-components and, therefore, can identify specific customer needs in user-generated content. We organize and discuss the value of the artifact's output and further enrich the model with sentiment data to distinguish relevant needs. If applied, the artifact can realize efficiency gains for decisionmakers in the field of product development as it automatically and quickly identifies relevant consumer needs.
(2024): Understanding customers’ choice for digital D2C versus multi-brand operations, Journal of Retailing, 100 (2): 256-273.
Abstract: In recent years, the emergence of highly successful digital multi-brand retailers has facilitated an omnichannel distribution strategy to become the norm for brands. Rather than relying solely on these multi-brand retailers, it is necessary for companies’ omnichannel strategy to establish strong brand-owned direct-to-consumer (D2C) webstores. To help D2C brands make decisions regarding distribution channel choices, this paper investigates the circumstances under which customers prefer brands’ D2C webstores over digital multi-brand retailers and how these circumstances vary across phases of the customer journey. The results from an extensive experimental study demonstrate that, depending on the customer journey, brands’ D2C webstores can compete with digital multi-brand retailers, particularly in product categories characterized by deep assortments, the need for extensive product information, exclusive products, or a high degree of personalization.
(2024): When necessity is the mother of disruption: Users versus producers as sources of disruptive innovation, Journal of Product Innovation Management, 41 (1): 62-85.
Abstract: This study investigates the sources of disruptive innovation. The disruptive innovation literature suggests that these do not originate from existing customers, in contrast to what is predicted by the user innovation literature. We compile a unique content-analytical dataset based on 60 innovations identified as disruptive by the disruptive innovation literature. Using multinomial and binomial regression, we find that 43% of the sample disruptive innovations were originally developed by users. Disruptive innovations are more likely to originate from users (producers) if the environment has high turbulence in customer preferences (technology). Disruptive innovations that involve high functional (technological) novelty tend to be developed by users (producers). Users are also more likely to be the source of disruptive process innovations and to innovate in environments with weaker appropriability. Our article forges new links between the disruptive and the user innovation literatures, and offers guidance to managers on the likely source of disruptive threats.
(2024): A network design problem for upgrading decentrally produced biogas into biomethane, Journal of Cleaner Production, 452 (5): 1-15.
Abstract: In this paper, we explore the possibility of connecting decentralized biogas plants via a pipeline network to terminals that upgrade biogas into biomethane. We present a mixed-integer linear program that forms subnetworks of such plants, decides on suitable terminal locations, and establishes pipeline connections to maximize profit. We apply this model to a real-world scenario in Northern Germany. The results show a much higher total profit for the optimized network compared to the benchmark solutions where each plant upgrades biogas into biomethane on its own. Therefore, plants can increase their profitability by collaborating with other (neighboring) plants. However, the collaboration requires a fair profit-sharing model as network participation is not individually profitable for all plants, especially small ones.
(2024): Does bigger still mean better? How digital transformation affects the market share–profitability relationship, International Journal of Research in Marketing: .
Abstract: Extensive research has examined the effect of market share on profitability and, in general, has found a significantly positive relationship between the two metrics. However, this article demonstrates that the digital transformation of companies has substantially altered this relationship and its underlying mechanisms. The authors first theoretically develop the different influences of digital transformation on the traditional market share–profitability framework. Subsequently, they estimate a firm–profitability model based on a sample of 6,389 observations from 824 U.S. firms over 25 years that accounts for companies’ degree of digital transformation by text mining their financial statements using a self-developed and validated dictionary. The authors find a significantly negative interaction between the degree of digital transformation of a company and the impact of market share on profitability. However, they also show that this effect is moderated by i) a firm’s digital transformation emphasis (i.e., digital transformation of internal vs. external processes; digital transformation through platformization), ii) a firm’s general strategic emphasis (value appropriation relative to value creation), and iii) a firm’s general market environment (B2C versus B2B). The findings suggest that managers and investors of digital companies should exercise caution when relying on market share as a metric for performance.
(2024): Availability of essential, generic medicines before and during COVID-19 at selected public pharmaceutical supply agencies in Ethiopia: a comparative cross-sectional study, BMJ open, 14 (3): .
Abstract: OBJECTIVES Lockdowns and border closures impacted medicine availability during the COVID-19 pandemic. This study aimed to assess the availability of essential, generic medicines for chronic diseases at public pharmaceutical supply agencies in Ethiopia. DESIGN Comparative cross-sectional study. SETTING The availability of essential, generic medicines for chronic diseases was assessed at two public pharmaceutical supply agency hubs. PARTICIPANTS The current study included public supply agency hub managers, warehouse managers and forecasting officers at the study setting. OUTCOMES The assessment encompassed the availability of chronic medicines on the day of data collection, as well as records spanning 8 months before the outbreak and 1 year during the pandemic. A total of 22 medicines were selected based on their inclusion in the national essential drug list for public health facilities, including 17 medicines for cardiovascular disease and 5 for diabetes mellitus. RESULTS The results of the study indicate that the mean availability of the selected basket medicines was 43.3% (95% CI: 37.1 to 49.5) during COVID-19, which was significantly lower than the availability of 67.4% (95% CI: 62.2 to 72.6) before the outbreak (p<0.001). Prior to COVID-19, the overall average line-item fill rate for the selected products was 78%, but it dropped to 49% during the pandemic. Furthermore, the mean number of days out of stock per month was 11.7 (95% CI: 9.9 to 13.5) before the outbreak of COVID-19, which significantly increased to 15.7 (95% CI: 13.2 to 18.2) during the pandemic, indicating a statistically significant difference (p<0.001). Although the prices for some drugs remained relatively stable, there were significant price hikes for some products. For example, the unit price of insulin increased by more than 130%. CONCLUSION The COVID-19 pandemic worsened the availability of essential chronic medicines, including higher rates of stockouts and unit price hikes for some products in the study setting. The study's findings imply that the COVID-19 pandemic has aggravated already-existing medicine availability issues. Efforts should be made to develop contingency plans and establish mechanisms to monitor medicine availability and pricing during such crises.
(2024): Resilience analysis of large-scale dynamic food flow networks using an optimization-based N-1 contingency approach, AIP Conference Proceedings, 3034 (1): .
Abstract: Food supply systems are national critical infrastructures embedded in changing and uncertain environments. Hence, testing and evaluating them in their ability to meet food supply is key to reduce vulnerability to shortages. This paper presents an optimization approach to assess the resilience of nationwide food supply systems using the N-1 contingency criteria, which investigates whether the isolation of one region from the transport network destabilizes the food supply. To this end, we build a multi-regional multi-commodity large-scale model for food flow networks. Then, we implement a constraint optimization problem to find the management of food flows along the supply chain stages that minimize shortage, costs and penalties induced by the disruption for both the isolated and connected system. Lastly, resilience is quantified with established metrics. A numerical case study illustrates the proposed method, revealing which regions are critical to maintain the stability of the national food supply.
(2024): A conceptual framework for supply chain digital twins – development and evaluation, International Journal of Logistics: Research and Applications: 1-23.
Abstract: Digital twins, due to digitalisation, are increasingly adopted across industries. The supply chain industry, with its process-driven nature, collaboration of multiple stakeholders and dependability on real-time events, demands unique characteristics for the implementation of digital twins. While these twins can enhance supply chain transparency and responsiveness, there is a lack of an application framework. The aim of this paper is to address this absence of a specialised application framework. The framework outlines multiple layers, dimensions, and stakeholder-technology dependencies for early-phase adoption. It is designed to guide planners and operators of supply chains in planning, implementing, and introducing new supply chain digital twins. Using the design science approach as a research methodology, the framework is informed by literature and expert interviews. Its validity is confirmed through further expert evaluations, and the study concludes with key insights and guidelines derived from the framework.
(2024): Does Market Share Still Matter?, Harvard Business Review: .
Abstract: Market share has traditionally correlated strongly with profitability because of efficiency, market efficiency, and customer perception effects. But, as the authors demonstrate, the relationship has been changed by the digital transformation in firms. The authors’ research finds that the market-share profitability relationship has become weaker for firms that favor investment in value creation over value appropriation and for firms operating in B2B markets. In both cases, digital helps smaller firms catch up with larger rivals. But digital can also amplify market share effects for large firms focusing digital investments on customer-facing processes and for large firms that create digital platforms.
(2023): Supply chain risk management strategies in normal and abnormal times: policymakers' role in reducing generic medicine shortages, International Journal of Physical Distribution & Logistics Management, 53 (2): 206-230.
Abstract: Purpose This paper links supply chain risk management to medicine supply chains to explore the role of policymakers in employing supply chain risk management strategies (SCRMS) to reduce generic medicine shortages. Design/methodology/approach Using secondary data supplemented with primary data, the authors map and compare seven countries' SCRMS for handling shortage risks in their paracetamol supply chains before and during the first two waves of the COVID-19 pandemic. Findings Consistent with recent research, the study finds that policymakers had implemented few SCRMS specifically for responding to disruptions caused by COVID-19. However, shortages were largely avoided since multiple strategies for coping with business-as-usual disruptions had been implemented prior to the pandemic. The authors did find that SCRMS implemented during COVID-19 were not always aligned with those implemented pre-pandemic. The authors also found that policymakers played both direct and indirect roles. Research limitations/implications Combining longitudinal secondary data with interviews sheds light on how, regardless of the level of preparedness during normal times, SCRMS can be leveraged to avert shortages in abnormal times. However, the problem is highly complex, which warrants further research. Practical implications Supply chain professionals and policymakers in the healthcare sector can use the findings when developing preparedness and response plans. Social implications The insights developed can help policymakers improve the availability of high-volume generic medicines in (ab)normal times. Originality/value The authors contribute to prior SCRM research in two ways. First, the authors operationalize SCRMS in the medicine supply chain context in (ab)normal times, thereby opening avenues for future research on SCRM in this context. Second, the authors develop insights on the role policymakers play and how they directly implement and indirectly influence the adoption of SCRMS. Based on the study findings, the authors develop a framework that captures the diverse roles of policymakers in SCRM.