Abstract Firms are known to commonly imitate peers' foreign investment location choices. We shed further light on this phenomenon by exploring the role of foreign locations' cultural tightness, which refers to the prevalence of social norms in a location and the tolerance for deviance from them. Combining institutional theory with insights from research on cultural tightness, we hypothesize that firms are more strongly inclined to imitate peers' choice for a subnational foreign investment location when the location is culturally tighter. Our hypothesis receives consistent support in conditional logit analyses based on 2900 foreign investments in new manufacturing plants in US metropolitan areas over the period 2008–2019. Furthermore, the amplifying effect of a subnational location's cultural tightness on firms' propensity to imitate their peers' choice for the location seems to depend on firms' experience with cultural tightness and their home country's cultural distance from the USA. Our findings enrich international management research on location choice imitation, legitimacy risks, and cultural tightness.
Abstract The symbol is one of the key concepts in organization and management scholarship. Yet as indicated by the authors in this debate, it has not been adequately conceptualized and as such it remains rather blunt and opaque. In what is the first systematic conceptual debate on this topic, the authors of this Point‐Counterpoint debate seek to address this issue. The respective essays, despite marked differences in their approaches, offer novel and thought‐provoking accounts of what the symbol is and how it works. Taken together, these contributions offer a series of exciting new avenues to guide and redirect future research in this area.
Imagine this scenario: You have just published a multi-year, data-rich paper. It was hard, time-consuming, and consequential work. You pushed the boundaries in a real add-on contribution to knowledge. Two days after the paper is published, you Tweet and LinkedIn post your substantive findings, because that is what we do today. You then receive a spontaneous email: ‘I loved your paper. In fact, I am working on something similar. Can you share your data with me or point me to where your data are stored, and maybe show me some of your study processes and analysis plan or coding?’ What would you do? That's the dilemma we faced when receiving this query. When we asked our colleagues about their reaction to this request, most said they know sharing data is helpful, but were just not confident enough in the act of sharing itself. And this got us wondering; does our outlook on data ownership undermine fundamental principles of high-quality and open science? The journey of scientific discovery is built on the bedrock of data sharing, a principle that has propelled fields from astronomy to medicine towards ground-breaking advancements (Anagnostou et al., 2015). Yet, within the corridors of management research, the notion of sharing our data fills many of us with a sense of dread. This fear isn't unfounded; it stems from a combination of concerns over data misuse, ethical breaches, and the potential for our work to be scooped before we've had the chance to stake a claim in the academic community. Our own journey through the academic landscape has been punctuated by moments that underscore this fear. One of the authors recalls the tension that followed a brown bag session where, for transparency, data were shared, only to face immediate backlash from a co-author worried about the research being captured by those in attendance. This incident reflects a broader sentiment that pervades our field: a guarded approach to research, where the desire for collaboration is often overshadowed by a fear of losing control over valuable data and our contributions. Despite the clear benefits of data sharing, exemplified by the development and dissemination of COVID-19 vaccines through open data practices (Duan et al., 2022), the management research community remains trapped in a paradox: We acknowledge the importance of making our data findable, meaning accessible and transparent (Kowalczyk and Shankar, 2011), yet we hesitate, disincentivized and limited by fear and uncertainty. This reluctance hinders not just the reproducibility and integrity of our work but also its potential impact. This essay is a personal reflection on the barriers that keep us all from sharing our data more freely.[1] It is a call to confront the fears that hold us back, to recognize the value of data openness, not just for the sake of compliance, but for the advancement of knowledge itself. As we navigate these complex issues, we must challenge ourselves and our institutions to foster a culture where sharing is not seen as a risk but as a responsibility – a fundamental shift that could redefine the future of management research. In our opening case, we highlighted how our journey into data sharing began after a major project that required years of data collection and analysis, involving significant time, effort, and ownership rights. Although we took pride in our published work, the idea of sharing our data initially seemed to diminish its value, triggering apprehension linked to four fears deeply embedded in academic life. Recognizing and confronting these fears is essential to fostering better data sharing practices. The email request for our data and methodologies raised concerns about the exposure and vulnerability of our research. These concerns stem from need for self-verification, which is deeply connected to professional identities, status, and the validation of our academic work. This fear, grounded in attribution theory, acts as a protective mechanism for our self-image, with researchers often blaming external factors, like insufficient resources or lack of support, for not sharing (Houtkoop et al., 2018). Data sharing risks increased scrutiny and potential criticism, threatening our expertise and self-worth. Despite journals advocating for data accessibility, researchers’ willingness to share, especially qualitative data, remains low due to associated concerns of exposure risks. This fear highlights the reluctance of researchers to share their ‘investment’ in painstakingly collected data without guaranteed protections. When the researcher (unknown to us) approached us to share our data, another immediate concern was the competitive landscape of academia. Why should we share data that took years to gather, given the risk to ongoing data ownership and use, potentially allowing someone else to benefit from our work? Given data use potential, this mindset is deeply ingrained in many of us from early in our academic training. Reflecting on our formative years as junior faculty, the narrative was clear: ‘hold your data close and trust sparingly’. In the scheme of a publish or perish culture, this fear of being ‘scooped’ by competitor peers – of having research ideas or results published by someone else – is a common anxiety, especially given the high stakes of academic progression. A single instance of someone else publishing your data could jeopardize career aspirations, as we have seen with a junior faculty colleague whose publicly accessible doctoral dissertation data were scooped. Scooping prompts a concern of losing control over intellectual property, or a reluctance to expose work to scrutiny, reflecting a judgmental stance by others, further diminishing the overall motivation to engage in open science practices. This fear has profound implications on identity and self-worth in the academic sphere. When approached, our hesitance to share our published data wasn't merely rooted in self-preservation but also in the altruistic aspect of protecting the confidentiality and security of our participants. Given the legal landscape surrounding data privacy, sharing data without robust safeguards can have far-reaching implications (Nahai, 2019). Our responsibility as researchers extends to ensuring the safety and privacy of our participants. We had to grapple with the dilemma of how much risk is acceptable when weighing scientific progress against the confidentiality of non-sensitive data. As the experience of a colleague with qualitative data further highlighted for us, even when data is shared in aggregate form, challenges from readers on finding accuracy and potential legal implications from industry respondents creates a tumultuous sharing environment. The academic landscape isn't just shaped by peer interactions but is also heavily influenced by those higher up in the system: journal editors, publishers, university administrators, funding bodies, media, and senior academics. Given the concentration of power, with their impact on academic progression and reputation, these gatekeepers introduce the element of vertical risk. Sharing data doesn't only open potential scrutiny from peers but also from these authoritative figures. A minor oversight in shared data, if spotlighted by an influential academic or editor, could lead to public retractions or criticisms, jeopardizing our standing. Moreover, when reinterpreted by gatekeepers, data could yield conclusions that overshadow or even challenge original findings. Additionally, there's an institutional layer of concern with universities prioritizing research impact and reputation. Without formal agreement, openly sharing data might be seen as relinquishing control over valuable (technically university-owned) research assets. If data are used in ways misaligned with our institution's goals, could we face repercussions or reduced opportunities? Reflecting status differences in academia, these vertical power structures compound the hesitations around data sharing, adding another dimension to fear. Through our data sharing journey, we have identified two key insights. First, overcoming the fear of sharing begins with self-awareness. Recognizing our initial reluctance as a defence mechanism was crucial, leading us to reconsider our stance on data sharing. We understood that, though legitimate, our fears could be mitigated with a proper mindset and tools. Second, we acknowledged the necessity of transitioning from individual ownership to collective stewardship. This shift entails not only changing practices but also adopting a mindset of collaboration over apprehension. Failure to confront these fears risks reinforcing the notion that sharing is too hard, ignoring the potential for collective management of these concerns. Our experience illustrates the importance of these insights. Initially focused on problems, we shared data in a way that alleviated our fears. Upon reflection, we identified six actionable steps to address data sharing apprehensions, highlighting the value of a comprehensive strategy to tackle these fears. Our initial venture into data sharing resulted in a mentorship program within one of our departments. After our project, we initiated a scheme pairing experienced researchers with junior faculty to guide them on ethical data sharing, anonymization of sensitive information, and intellectual property management. This mentorship, transcending technical advice, was pivotal in fostering confidence and trust in sharing all types of data, alleviating fears of exposure and criticism. The emotional support and practical guidance from mentors proved crucial in helping researchers (and us) navigate the apprehensions of open sharing. Reflecting on this, we recognized the benefits of a comfortable, phased approach to sharing. Starting with sharing data among a small, trusted group allowed us to fine-tune our approach in a safe setting, gradually extending our reach to a broader academic audience and then the public. Implementing structured feedback mechanisms also helped address concerns of data misinterpretation and facilitated constructive peer review sessions. These sessions, emphasizing respect and constructive criticism, promoted a culture of open dialogue and collaboration, essential for shared learning and research advancement. This experience underscores the importance of systemic and collective efforts (Bouckenooghe et al., 2023) to foster an environment of openness and collaboration. The lack of standardized data sharing protocols often pushes researchers towards makeshift solutions, making sharing daunting. This issue is particularly evident in journal policies, where data sharing norms vary significantly. Our experience with submitting supplementary data from a multi-year study to journals underscores this challenge. We encountered resistance from journals that deemed our paper ‘too long’ due to the additional data (especially its qualitative data), despite our intention to promote transparency. The optional nature of data sharing in several management journals inadvertently reinforces the prevailing culture of data hoarding, stifling potential progress. Without mandatory data sharing policies, the implicit message is that data sharing is a secondary concern, failing to address common fears of criticism or being scooped. Transitioning to mandatory data sharing and management plans by journals and funding bodies could cultivate a more open research culture. Adopting editorial policies like those of Science (https://www.science.org/content/page/science-journals-editorial-policies#data-and-code-deposition), serve as a model for boosting research visibility and impact, necessitating a strong commitment from all involved parties. Furthermore, the academic community often struggles with the specifics of responsible data sharing, a challenge exacerbated in the realm of qualitative data, due to a lack of guidance on suitable software, licensing, and storage. Bridging this gap with comprehensive data management training could normalize data sharing, transforming it from a punitive measure to a standard practice. Such training would provide researchers with the skills needed for secure data sharing, including sensitive qualitative data, thereby reducing risks and promoting openness. While training individual researchers on responsible data sharing is crucial, it is important to acknowledge that broader, collective solutions are necessary to address systemic data sharing challenges. Institutional reform is crucial for enhancing data sharing among researchers by mitigating perceived barriers. This open science action includes providing data management resources, establishing supportive policies, and incentivizing sharing. Such reform can increase a sense of agency among researchers. They need not be radical but should integrate into existing frameworks through collaborative efforts, promoting a culture where data sharing is normalized and valued without prejudice. Initiatives could involve embedding data sharing importance in university recruitment, paralleling mandatory training in ergonomics or safety, and fostering inter-institutional collaboration to streamline processes like metadata storage. Leveraging models from other fields, academic bodies can adopt standardized, accessible data sharing systems, akin to two-factor authentication, to notify researchers about the use and impact of their data, thereby encouraging a culture of mutual benefit. Furthermore, funding agencies and institutions could mandate data sharing for grant or tenure considerations, prioritizing its role in research impact. The key challenge lies in initiating this shift, determining who will lead the way in institutionalizing data sharing as a fundamental research practice. Recently, while preparing a manuscript, we faced a common dilemma: a journal required data availability for submission. Intended to enhance research quality, this requirement sparked concerns about moving beyond our comfort zone. However, the journal's precise instruction and guidelines led to a positive encounter, as an exercise in providing rigour and transparency to sharing. This transparency can help bolster the credibility of our findings. The experience taught us that data sharing need not be an all-or-nothing approach but can be more nuanced and tailored to recognize the breadth of sharing challenges. Institutions and funding bodies play a vital role in this landscape, offering training and resources on data sharing benefits and incentivizing researchers for their past sharing efforts. The adoption of open science methods for all types of data, like the transparency and openness promotion (TOP) guidelines (Miguel et al., 2014), provides options such as pre-registration of data collection and open access publishing. Additionally, negotiating fee waivers with publishers for data sharing can cultivate a culture of transparency. Public data repositories with open access plans, supported by platforms like Figshare, Zenodo, Dataverse, and Data Dryad, are crucial for this shift. Journals can encourage conditional data sharing and citation, ensuring security and longevity through such stable repositories and controlled access via DOIs. Sharing data without explicit consent, however, requires a balance of ethical concerns and potential IRB processes. Ethics committees must navigate these complexities, possibly redrawing conduct codes or creating broader data access types. In searching for data sharing solutions, we also considered the potential of blockchain technology for managing sensitive data. By leveraging encryption within a decentralized network, blockchain ensures participant anonymity and addresses privacy concerns, thereby fostering trust in the research ecosystem. This technology offers incentives for data sharing such as tokens or compensation for open access publication fees, while aligning with initiatives like the Center for Open Science's open data badges (https://www.cos.io/initiatives/badges), nurturing a sharing culture. Blockchain reframes errors in data reporting as part of the scientific process, diminishing the fear of judgement and criticism, while innovations like smart contracts guarantee data access solely to authorized researchers, mitigating worries about data misuse (Macrinici et al., 2018). Simultaneously, blockchain helps bolster sharing sensitive qualitative data, by prioritizing the implementation of sophisticated deidentification techniques. Utilizing advanced methods like natural language processing (NLP) and AI-based tools, including named-entity recognition and pattern matching, enables researchers to effectively anonymize sensitive information, safeguarding participant privacy without compromising data integrity. Institutions championing these advanced deidentification methods take a proactive stance in privacy protection, enhancing the willingness among researchers and participants to share data, and thereby enriching the collective research landscape. The integration of blockchain technology and advanced deidentification techniques, can enable more knowledge transparency. To effectively mitigate the vertical risks in academia associated with data sharing, gatekeepers need to spearhead initiatives that foster a supportive and collaborative research environment. Creating a protective framework for data sharing is a critical first step, where policies safeguard researchers by ensuring that critiques or reanalyses of shared data involve the original contributors, maintaining context and integrity. This approach should be complemented by promoting a culture of constructive engagement, where the academic community prioritizes collaborative improvement and knowledge advancement over punitive scrutiny. Such a culture relies on open dialogue and constructive feedback on data, helping to alleviate fears of reputational damage or data misinterpretation. By hosting forums, workshops, and discussions that bring together researchers, policymakers, and the public, gatekeepers can cultivate a more nuanced understanding of the complexities and benefits of data sharing. This collective effort not only demystifies the process but also highlights the communal benefits of open science, ensuring that the pursuit of knowledge is a shared endeavour, marked by transparency, respect, and mutual support. In drafting this essay, one of us faced a common hurdle in academia: seeking specific data (correlation coefficients) from authors and encountering non-responsiveness or refusal. This experience underscores a wider reluctance in management research to share data, fuelled by valid concerns and perpetuating a cycle of withholding information. But this reluctance stalls the development of data sharing guidelines and policies, limiting the field's growth potential. Open science holds universal benefits, yet fears about data sharing persist, necessitating innovative approaches and a shift in mindset. Drawing from successful models in fields like science or medicine, we can overcome these barriers for both qualitative and quantitative data. Advancing management research requires a collective effort to promote data availability, engage in dialogue on research practices, and sharing training. By confronting fears around data sharing, we can foster a more collaborative future in management research, embracing open science to unlock our data's full potential. Open access publishing facilitated by University of New South Wales, as part of the Wiley - University of New South Wales agreement via the Council of Australian University Librarians.
Abstract Performance gap recognition derives from social comparison with rivals. We propose that the attribution of these gaps to foreign direct investment (FDI) inadequacy – and thus the likelihood of responding with FDI – is also guided by such social comparisons. Specifically, the performance gap becomes a stronger trigger for foreign market investment when underperforming peers are less engaged in FDI than outperforming counterparts, as this highlights the role of FDI scarcity in explaining the gap. Similarly, a firm's lower FDI involvement increases the performance gap's capacity to trigger FDI by making FDI inadequacy a more plausible explanation, whereas extensive existing FDIs shift the blame away from FDI insufficiency. By examining the locus of investment activity under the performance gap, we show that the associated FDI‐triggering capacity is limited to institutionally proximate environments where the upside potential for addressing the performance gap can be recognized upfront through current models, methods, and resources. Institutionally distant investments, whose potential evolves through experimentation with the local context, become increasingly unlikely as a firm falls behind its rivals. These findings suggest that a firm's response to the performance gap is shaped by inferences about the causes of underperformance and the clarity of an alternative's capacity to address the gap.
Abstract We draw on the historical case of the UK pharmacy industry from 1880–1905 to examine how, in the face of a competitive threat to their survival, lower status professionals seek to reinvigorate the memory of their role in providing community service in the public interest. Derived from this, our study reveals how mnemonic work has a nuanced nature in professionalized settings. First, lower status actors enact certain types of mnemonic work because they need to maintain professional purity. Second, to maintain professional purity, lower status professionals also need to carefully sequence their mnemonic work and pay particular attention to the social context within which they are seeking to manipulate collective memory. Our study also shows how, within such a sequencing, for lower status professionals to successfully enact mnemonic work, they need to collectively mobilize their ranks and may engage in entryism to professional bodies dominated by their higher status peers.
Abstract This study investigates dynamics of subnational regions in determining firm performance over time and by ownership type. We explain theoretically how subnational regions affect firm performance over time in the context of path dependence and the institution‐based view and test these predictions using annual data of manufacturing firms in China from 2000 to 2014 – before and after a major negative institutional shock (2008 financial crisis). Consistent with path dependence, regional institutional quality diverges across regions before 2008, a pattern that is disrupted post‐2008. Firm performance is increasing in institutional quality so that location effects are increasingly important before the financial crisis but less so post‐crisis. These effects are greater for private‐ than state‐owned enterprises consistent with differences in organizational objectives under the institution‐based view.
Abstract The work relationships between CEOs and Chairpersons are key to the functioning of the firm. This study uses survey and interview data to explore how these work relationships serve as a micro‐foundation for an organization's communication climate. Survey data suggested that CEO‐Chairperson relationships can be characterized by emotional carrying capacity (ECC; constructively expressing more positive and negative emotions). The survey‐based model further demonstrated that CEOs and Chairpersons perceive their ECC to positively predict organizational communication climate and, in turn, knowledge creation capabilities. The latter, in turn, are positively associated with firm performance. CEO‐Chairperson dyadic interview data supplemented the associations identified in our survey model. Interviewees identified specific mechanisms behind the associations in the survey model, such as the strategic sharing of positive and negative emotions. Our mixed‐methods approach provides initial evidence for the importance of emotional expression and management as micro‐relational foundations that underpin firm‐level capabilities and performance.
Abstract Firms often make attributions regarding their actions in managing relationships with shareholders and investors. While research utilizing attribution theory has found that firms tend to attribute negative outcomes to external factors and positive outcomes to internal ones, this behaviour can have both positive and negative consequences. Addressing these contrasting results, our paper adopts a multidimensional framework of attribution to study how firms offer explanations for their actions. Leveraging insights from attribution theory and expectancy violation theory, we investigate whether investors respond diversely to firms' heterogeneous attributions for terminating acquisitions. Our findings indicate that an initial positive market reaction to an acquisition announcement is negatively correlated with the market reaction to the acquisition's termination. This negative relationship diminishes when the acquirer attributes the termination to external, uncontrollable and unstable factors. This paper contributes to the acquisition literature by highlighting multiple categories of attributions for firms to strategically manage market reactions.
Abstract Addressing societal challenges requires engaging diverse actors, but clashes between social and commercial interests often hinder coordination. In established fields, conflicting social interests can be integrated by challenging dominant commercial positions and rallying powerful actors. However, creating new fields without established actors and coordination mechanisms is more complex, especially when interests conflict. We explore this challenge through the development of reusable containers for takeaway food and beverages, where incompatible perspectives initially led to a field impasse. A pioneering social enterprise blending commercial and social interests emerged as a referent, facilitating collaboration and breaking the impasse. After initial field organizing succeeded, regulatory changes and increased demand exposed the shortcomings of early solutions, leading to setbacks. New social enterprises developed solutions to fill supply–demand gaps, anchoring new models in a market and driving both standardization and innovation. We introduce the concept of ‘social enterprise referents’ to highlight their essential role in organizing nascent fields to address complex societal issues. Without these referents, models for building new fields struggle to take hold. Successfully transitioning from an underorganized to an organized field requires sustained efforts from multiple social enterprise referents to anchor solutions in a market and uphold collaboration with field actors.
Abstract Although prior research on the dark side of corporate political activity (CPA) has examined the negative impact of CPA on firms from the perspective of the macro cost of CPA (i.e., organizational loss) and the self‐interested motives of executives (i.e., personal gain), it has largely overlooked the negative repercussions of CPA for individuals intimately engaged in that process (i.e., personal loss). Drawing on the conservation of resources (COR) theory and focusing on Chief Executives Officers (CEOs) who engage in political networking (PN), we investigate how PN affects CEO burnout. We conceptualize PN as a form of relational exchanges between firms and political entities, positing that PN entails substantial resource depletion for those deeply involved, primarily due to significant ethical and moral challenges (i.e., identity threat). As PN intensifies, CEOs are compelled to allocate more time, effort and energy to navigate these escalating challenges, consequently exacerbating CEO burnout. Through the analysis of a 2‐year matched survey of CEOs and comprehensive archive data, we find robust support for our hypothesis. Furthermore, our findings suggest that CEO altruism and institutional knowledge weaken the relationship between PN and CEO burnout, indicating that individual intentions to benefit the collective and the ability to navigate such networking practices alter CEOs’ perceived identity challenges. Our study contributes an individual‐level resource‐depletion perspective of CPA and cautions against the propensity of CEOs to engage in CPA driven by Machiavellian logic.