Information Systems Journal最新文献

{"title":"Rethinking Artificial Intelligence and Ethics: Uncovering Unexamined Assumptions and Assessing Their Implications","authors":"Chenxi Ma,&nbsp;Alain Yee Loong Chong,&nbsp;Jason Bennett Thatcher,&nbsp;Chee Wei Phang","doi":"10.1111/isj.70042","DOIUrl":"https://doi.org/10.1111/isj.70042","url":null,"abstract":"<div>\u0000 \u0000 <p>Although the rapid advancement of artificial intelligence (AI) has introduced significant ethical challenges, many studies have assumed a consensus on moral actions and outcomes, often overlooking the normative uncertainty inherent in AI development and use. Because the debate over which actions are morally appropriate in AI development and use, and in human–AI interaction, has intensified with AI's increasing autonomy, inscrutability, and learning capacity, this normative uncertainty warrants careful examination. Existing literature reviews have tended to reinforce the assumption of low normative uncertainty by emphasizing the similarity of the studies they examine. In this study, we conduct a problematizing review of empirical research on the ethics of AI published from 2010 to 2025. Drawing on two metaethical debates—the debate over the development of moral judgements (rationalist vs. non-rationalist views) and the debate over their dynamics (absolutist vs. contextualist views)—we analyse how current research constructs moral judgements when studying AI and its interactions with humans. We identify two dominant field-level ethical assumptions: that moral judgements about AI rely primarily on rational deliberation and that such judgements remain static across contexts. These assumptions are shared across three research domains: ethical AI development and governance, ethical evaluation of AI, and joint human–AI agency. Moreover, the assumptions shape the framing of research questions, the selection of research methods, and the conceptualization and measurement of constructs and relationships. By making these assumptions explicit, our study creates opportunities for theoretical inquiry into normative uncertainty. We propose five research approaches for examining rational, nonrational and context-sensitive moral processes, offering scholars in the Information Systems discipline new pathways for theorizing ethical AI.</p>\u0000 </div>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"847-883"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managing Sustainability Data Proactively: Corporate Sustainability Reporting (Directive) as a Driver","authors":"Elizabeth A. Teracino,&nbsp;Christine Legner,&nbsp;Ridwan Bhuiyan","doi":"10.1111/isj.70043","DOIUrl":"https://doi.org/10.1111/isj.70043","url":null,"abstract":"<p>Sustainability has become a key priority for firms, and the increasing number of mandatory regulations only heightens its importance. The Corporate Sustainability Reporting Directive (CSRD) introduces stringent non-financial disclosure requirements, significantly expanding the scope and breadth of reporting, particularly for those operating in industries with global and complex supply chains. A major challenge companies face with sustainability reporting is that it requires collecting, processing, and interpreting thousands of data points, which have not been systematically collected or analysed previously. While many companies tackle the challenges in a reactive, regulation-by-regulation manner, CSRD provides a unique opportunity to rethink and elevate sustainability data management to support forward-looking sustainability initiatives and better decision-making. To guide companies in managing sustainability data proactively, we introduce the Data Excellence Model (DxM) for Sustainability as a comprehensive data management framework that links regulatory demands to concrete business goals, organisational and technical enablers, and measurable results. We illustrate the framework through an exemplary front-runner case of a leading European online fashion retailer and highlight key success factors and practices the firm undertook to holistically and systematically tackle the complex data requirements of CSRD. Building on the DxM for Sustainability, we outline a maturity assessment that companies can use as a diagnostic tool for proactive sustainability data management.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"884-900"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genres of Paradoxical IS Theorising: Of Chaos–Puzzles and Spear–Shields","authors":"Blair Wang,&nbsp;Raffaele F. Ciriello,&nbsp;Lars Mathiassen","doi":"10.1111/isj.70045","DOIUrl":"https://doi.org/10.1111/isj.70045","url":null,"abstract":"<p>Paradox is a powerful lens for theorising information systems (IS) phenomena. However, as scholars apply the term to fundamentally different phenomena, ‘paradox’ risks dilution. Much confusion stems from conflating two concepts under the same English label ‘paradox’: chaos–puzzles (seemingly impossible ideas, aligned with the Chinese term ‘bei lun’); and spear–shields (contradictory pathways of action, aligned with the Chinese ‘mao dun’). Through a hermeneutic analysis of 142 IS papers, we advance a framework of eight genres defined by variations in paradox grounding (chaos–puzzle vs. spear–shield) and paradox articulation (sociocentric vs. technocentric; sensing vs. responding). The framework offers an account of paradoxical IS theorising that is pluralistic by clarifying multiple meanings of paradox; directive by guiding authors, editors, reviewers and readers in articulating and evaluating genre-sensitive contributions; and generative in identifying new avenues for paradoxical IS theorising. By mapping out different ways in which IS scholars can engage with chaos–puzzles and spear–shields, we bring analytical clarity to paradoxical IS theorising and offer a foundation for its further development.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"901-923"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to Demonstrate Trustworthy Use of AI in Public Services: A Case Study","authors":"Natalie Smith,&nbsp;Nicole Gillespie,&nbsp;Tapani Rinta-Kahila,&nbsp;Steven Lockey,&nbsp;Javad Pool,&nbsp;Caitlin Curtis","doi":"10.1111/isj.70025","DOIUrl":"https://doi.org/10.1111/isj.70025","url":null,"abstract":"<p>Government leaders across the globe are grappling with how to harness and integrate artificial intelligence (AI) to enhance public service delivery and efficiency. Yet, a key challenge faced is how to build and maintain the trust of stakeholders. Trust is critical for the acceptance and sustained adoption of AI technologies, as well as to gain the requisite funding, resourcing and authorization to implement AI solutions. However, inherent features of AI—its autonomous capabilities, dynamic learning, and inscrutable operating logic—create challenges for trust, particularly in public services that are subject to high expectations of accountability, transparency, and fairness. We present an in-depth case analysis of how an Australian government department was able to deploy a solution that was widely accepted, and identified as an exemplar of trustworthy AI use. We identify six trust-supporting approaches: benevolent customer-centricity, radical honesty, diverse input, rigorous development and testing, human discretion in decision-making, and aligning the authorising environment. For each approach, we explain how and why it supports trust, and then contrast that approach with a prominent, but widely distrusted application in the Australian government. We conclude with implications for public sector leaders seeking to engender trust in their use of AI.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"823-846"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Trust Formation in AI-Enabled Automation: A Longitudinal Case Study of an Advanced Driver Assistance System","authors":"Kari M. Koskinen,&nbsp;Niina Mallat,&nbsp;Virpi Kristiina Tuunainen,&nbsp;Antti Lyyra","doi":"10.1111/isj.70046","DOIUrl":"https://doi.org/10.1111/isj.70046","url":null,"abstract":"<p>Artificial intelligence (AI)–enabled automation is often utilised in systems that perform human tasks. While useful, these technologies pose a risk of adverse consequences in the case of AI failures as they operate in open environments, learn and are subject to continuous updates. These factors create uncertainty about AI performance that users need to cope with. At the same time, trust in AI-enabled automation has become an elusive target that continuously evolves. In this study, we focused our investigation on the process through which users continuously form trust towards AI-enabled automation. Drawing from coping theory, we conducted a case study of Tesla's advanced driver assistance system and qualitatively analysed longitudinal data on real-life use experiences from a Tesla driver forum. Our findings suggest that users form and evaluate trust continuously as they encounter new experiences and gain new information about AI-enabled automation, which leads to varying levels of compartmentalised trust and diverging adaptation actions over time. Building on these findings, we elaborate on a process model and change mechanisms of users' trust to provide a better understanding of how trust in AI-enabled automation evolves over time.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"924-951"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research Integrity Matters, But It Is Undermined by Generative AI","authors":"Robert M. Davison,&nbsp;Antonio Díaz Andrade,&nbsp;Andreas Eckhardt,&nbsp;Marjolein van Offenbeek,&nbsp;Angsana A. Techatassanasoontorn,&nbsp;Marco Marabelli,&nbsp;Petter Nielsen,&nbsp;Niki Panteli,&nbsp;Gerhard Schwabe,&nbsp;Andrew Hardin,&nbsp;Vanessa Cooper","doi":"10.1111/isj.70055","DOIUrl":"https://doi.org/10.1111/isj.70055","url":null,"abstract":"&lt;p&gt;At the ISJ, we strongly believe that research integrity matters. By this, we refer to the adherence to core ethical, moral and professional standards throughout the research process from conceptualisation through planning, engagement with the literature, data collection, analysis, writing, reviewing and publishing. These standards apply to all of us, as appropriate, whether as authors, reviewers or editors and we assert that these standards are universal across the academic community. Examples of integrity include: ensuring that intellectual work is undertaken by the humans who claim credit as authors; respecting the rights of all stakeholders, including research participants, authors, reviewers and editors; respecting the contributions of the authors whose papers we cite. Situations where integrity has been compromised include instances of plagiarism, data fabrication and misrepresentation. A contemporary cause of integrity violations is misuse of Generative AI (GAI), a technology that is seeing very widespread use among academics, some of which is problematic.&lt;/p&gt;&lt;p&gt;Currently, at the ISJ, we are being flooded with submissions. To receive 20 new submissions a day is becoming normal. Editors at other journals and conferences report similar situations. For instance, the ICIS (&lt;span&gt;2026&lt;/span&gt;) conference received 72.6% more submissions than did the ICIS 2025 conference. We suspect that many of these submissions (at all venues) are created with the assistance of GAI. Many submissions are quite simply out of scope. Indeed, they would be out of scope for any IS journal, or even any journal in any discipline. Here is the title of one such out-of-scope paper submitted to the ISJ: ‘Fractional Bobcat Grey Wolf Optimization: Thin Block Siamese Capsule Parameter Intrusion Detection System for Otolaryngological Cancer Prognosis’. Is that really a human-crafted title? Does it actually mean anything? Or is it perhaps the feral invention of a GAI tool prompted to create a ridiculous title? Papers with titles like this, with bizarre combinations of animals, medical and engineering contexts and optimisation techniques, are submitted every week and are immediately rejected. Our current desk reject rate at ISJ exceeds 60%. Meanwhile, our accept rate has fallen to 4%, which is not something we are proud of; it is far lower than it should be since, like any journal, our mission is to accept and publish good research. As a related point, we have detected that a number of authors (invariably of these same types of out-of-scope paper) are responsible for the submission of enormous numbers of papers: one such person (or perhaps multiple people or bots with the same name and affiliation) has, to the best of Robert's knowledge, submitted several tens of papers to the ISJ over the last few months. When we encounter such huge volumes of submissions, all players in the peer review ecosystem (EinC, SEs, AEs, Reviewers) must work harder to identify those submissions that c","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"817-822"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Information Systems Practitioners Think in Action: Instantiating Donald A. Schön's General Theory of the ‘Reflective Practitioner’","authors":"Allen S. Lee,&nbsp;Yan Li,&nbsp;Manoj A. Thomas","doi":"10.1111/isj.70047","DOIUrl":"https://doi.org/10.1111/isj.70047","url":null,"abstract":"<div>\u0000 \u0000 <p>To examine how information systems (IS) practitioners think in action, we rely on Donald A. Schön's general theory of the ‘reflective practitioner’—a theory that Schön developed to explain how practitioners in architecture, psychotherapy, engineering, planning, and management think in action, and that we apply to IS practitioners. We go over Schön's explanation that a practitioner's thinking-in-action consists of what he calls five moments: knowing-in-action, surprise, reflection, criticism and on-the-spot experiment. Then, based on our interviews with a technical IS practitioner and a managerial IS practitioner, we show how their thinking in action demonstrates each of the five moments. Finally, based on the five moments, we offer recommendations to IS researchers on how to write papers to better support the work of IS practitioners.</p>\u0000 </div>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 6","pages":"952-966"},"PeriodicalIF":8.2,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149163214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Open Banking Regulation to Platform Orchestration: The Evolution of Digital Platform Governance","authors":"Priyadharshini Muthukannan,&nbsp;Daniel Gozman,&nbsp;Barney Tan,&nbsp;Prakash Dhavamani","doi":"10.1111/isj.70030","DOIUrl":"https://doi.org/10.1111/isj.70030","url":null,"abstract":"<p>This study contributes to information systems (IS) scholarship by extending platform governance theory to regulatory contexts, explaining how regulatory forces co-evolve with technological architectures to shape openness and control. This research examines the evolution of platform governance in the context of open banking, where regulatory mandates compel incumbent banks to open their infrastructures to third-party access, by drawing on digital platform governance theory and a seven-year interpretive study. Open banking provides a unique empirical setting in which platform orchestration is co-constructed by banks, regulators, and emerging fintechs. The research identifies three phases of platform governance evolution: regulatory interpretation and codification, marked by technical prescription and restrictive due diligence; strategic platform expansion, characterised by curated innovation co-design and tiered platform access; and platform ecosystem orchestration, with distributed governance and adaptive gateways. The study theorises the antecedents, governance mechanisms, outcomes, and enablers and inhibitors shaping the three phases and the transitions between them. The study offers theoretical and practical insights for managing platform governance evolution, in policy-driven digital platform environments where platformization is not voluntary.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 5","pages":"743-770"},"PeriodicalIF":8.2,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148704282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catch Me If You Can: The Dynamic Nature of Bias in Machine Learning Applications","authors":"Monideepa Tarafdar,&nbsp;Irina Rets,&nbsp;Yang Hu","doi":"10.1111/isj.70034","DOIUrl":"https://doi.org/10.1111/isj.70034","url":null,"abstract":"<p>Bias in machine learning (ML) applications represents systematic differences between expected and actual values of the predicted outputs, such that certain individuals or groups are systematically and disproportionately (dis)advantaged. This paper investigates the dynamic nature of bias in ML applications. We conducted an empirical study of bias in the context of an ML application that assesses applicants' competencies for a given job based on their job interviews. We analysed primary data (27 interviews with 21 members from six departments) and secondary data (e.g., company reports, webinars, and software demonstrations) from the organisation that develops and deploys the application. Drawing on the concept of reflexivity in digitised processes and associated notions of drift and control, we theorise the emergence and evolvement of bias as constituting dynamic relationships among sources of bias and associated effects of drift, and actions of bias mitigation and associated effects of control. We further demonstrate how actions aimed at mitigating bias, while weakening some sources of bias, also create additional sources through unintended side effects. We explain how sources of bias and bias mitigation actions continually (re)shape each other through dynamic and reflexive effects. For HR practitioners and policymakers, we provide actionable insights into bias detection and mitigation in ML-based job competency assessment.</p>","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 5","pages":"710-742"},"PeriodicalIF":8.2,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148704356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scholarly Integrity and Generative AI: Five Boundary Violations for IS Scholarship","authors":"Jonny Holmström,&nbsp;Robert M. Davison","doi":"10.1111/isj.70044","DOIUrl":"https://doi.org/10.1111/isj.70044","url":null,"abstract":"&lt;p&gt;Generative AI (GAI) is no longer a speculative add-on to academic work. By 2026, major institutions had moved beyond tentative warnings toward durable rules and infrastructures: the International Committee of Medical Journal Editors (ICMJE) has added dedicated guidance on GAI use by authors, reviewers, and editors, and Nature has published work demonstrating the end-to-end automation of parts of the research process. For the Information Systems Journal (ISJ), the issue is not whether GAI can simply be ignored. ISJ's current author and reviewer guidelines already stipulate that authors must not use GAI for any intellectual task, including problem formulation, literature review, data analysis, or more general writing (Davison &lt;span&gt;2025&lt;/span&gt;). Implicitly, the actions that authors take as they plan for the revision process, and the writing up of revision notes, are also considered to constitute intellectual tasks and so are similarly restricted. We now specify that authors must explain in a cover letter how, if at all, they have used GAI tools in any respect. The same transparency requirement applies to reviewers and editors, who must not outsource either their critical analysis of a paper under review or their composition of the review itself to a GAI tool. More broadly, most (if not all) academic journals' ethics guidance emphasizes disclosure, human accountability, authorship limits, and confidentiality in peer review (ICMJE &lt;span&gt;2026&lt;/span&gt;; Lu et al. &lt;span&gt;2026&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Nevertheless, even as GAI tools become more popular, and notwithstanding the more or less restrictive policies promulgated by publishers and editors, a broader scholarly consensus as to what constitutes appropriate use remains elusive. Researchers remain divided on what counts as acceptable GAI use in writing, analysis, and review. For instance, as noted above, at the ISJ a strict line is taken such that the use of GAI tools for any intellectual activity is not permitted. However, at some other journals a more relaxed regime appears to be in place, with some editors even encouraging GAI use. Meanwhile, recent controversies, such as the rejection of hundreds of conference papers due to prohibited GAI use, suggest that the central question is no longer whether GAI can accelerate the research production process, but under what conditions that acceleration remains legitimate and accountable (Gibney &lt;span&gt;2026&lt;/span&gt;; Kwon &lt;span&gt;2025&lt;/span&gt;; Naddaf &lt;span&gt;2025&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;This editorial builds on ISJ's own ongoing reflection on what responsible IS scholarship requires. These reflections have appeared over the last decade in editorials.\u0000 &lt;sup&gt;1&lt;/sup&gt;\u0000 For instance, Davison and Tarafdar (&lt;span&gt;2022&lt;/span&gt;) articulate cultural values for ISJ that include transparency, integrity, fairness, accountability, and developmental care. Davison (&lt;span&gt;2021&lt;/span&gt;) stresses the importance of contextual knowledge; Chatterjee and Davison (&lt;span&gt;2021&lt;/span&gt;","PeriodicalId":48049,"journal":{"name":"Information Systems Journal","volume":"36 5","pages":"625-628"},"PeriodicalIF":8.2,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/isj.70044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148704433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}