Information & Management最新文献

{"title":"Does the industrial big data environment matter? An evaluation of its effect on the production performance","authors":"Liwen Hou","doi":"10.1016/j.im.2025.104159","DOIUrl":"10.1016/j.im.2025.104159","url":null,"abstract":"<div><div>The widespread deployment of the Internet of Things has created a brand-new digital environment—an industrial big data environment (IBDE) characterized by a multitude of data resources. This study posits that IBDE, which has been commonly neglected in previous research, not only incubates affordance awareness capability, but also incurs data debt (DD), a new type of technical debt. This study uses affordances of manufacturing, manufacturing agility, and manufacturing excellence, together with DD, to parse the mechanism about how IBDE influences the enterprise production performance. We hypothesize that these three mediators are in charge of transmitting the influence of the munificent IBDE on the production performance. Empirical results confirm that IBDE significantly influences the three mediators, which in turn exert significant effects on the production performance. As such, we validate the existence of the mediating effect, and the significance of IBDE on the actions of affordance actualization. Further, despite the overall positive effect of the mediators on performance, the adverse influence of DD nevertheless cannot be neglected. These findings remind enterprises that a balanced development strategy of digital environment is imperative in terms of actualization of the affordances.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 6","pages":"Article 104159"},"PeriodicalIF":8.2,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895382","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":"Stylometric characteristics of code-switched offensive language in social media","authors":"Lina Zhou ,&nbsp;Zhe Fu","doi":"10.1016/j.im.2025.104153","DOIUrl":"10.1016/j.im.2025.104153","url":null,"abstract":"<div><div>Offensive language is a significant detriment to social media environments. Existing research predominantly assumes monolingual expression, overlooking the prevalent behavior of code-switching (CS). To address this critical knowledge gap, this study identifies and empirically validates the distinct stylometric characteristics of code-switched (CSed) offensive language. Additionally, we developed methods to construct the first social media dataset specifically for CSed offensive content. Our analysis of this dataset reveals that CSed offensive language exhibits unique stylometric characteristics; moreover, these characteristics vary between the language segments involved in the CS. Furthermore, incorporating these features significantly enhances the performance of offensive language detection models. These findings offer significant research and practical implications for social media researchers, platforms, moderators, and users.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 6","pages":"Article 104153"},"PeriodicalIF":8.2,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869813","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":"A new exploration of signaling theory in social commerce facilitated cross-border retailing: A four-stage approach","authors":"Xiao-Yu Xu ,&nbsp;Qing-Dan Jia","doi":"10.1016/j.im.2025.104154","DOIUrl":"10.1016/j.im.2025.104154","url":null,"abstract":"<div><div>This study offers a holistic interpretation of signaling theory by demonstrating a four-stage research rationale innovatively to unveil the mechanism of five signaling elements in resolving the information asymmetry in social commerce-facilitated cross-border e-commerce. Using different data sources and methods, stages 1 and 2 cross-validate the significance of the signaling elements that are deconstructed as second-order constructs and mirror the dual routes in the elaborated likelihood model. The artificial neural networking analysis in stage 4 reveals the importance ranks of the information factors in three consumer segments that are identified via unobserved heterogeneity analysis regarding the receiver's moderating role in stage 3.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 5","pages":"Article 104154"},"PeriodicalIF":8.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833563","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":"Examining the evolving influence of early-stage team context on individuals’ IS usage over time during implementation","authors":"Kyootai Lee ,&nbsp;Kailash Joshi ,&nbsp;Jin-Gyu Kim ,&nbsp;Jongweon Kim","doi":"10.1016/j.im.2025.104155","DOIUrl":"10.1016/j.im.2025.104155","url":null,"abstract":"<div><div>Drawing from the literature on collective information system (IS) usage and social learning theory, we identified how early-stage team IS usage characteristics shape the evolution of individuals’ IS usage. We obtained actual IS usage data from a news organization, covering 504 employees across 43 teams over 14 weeks. The results showed that early-stage team IS usage characteristics created assimilation gaps among individuals after the early stage. However, the impact of these team characteristics declines over time. This study contributes to the literature by investigating the time-dependent roles of collective IS usage characteristics for individuals’ usage and providing an integrated view of switching and post-adoption behaviors.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 6","pages":"Article 104155"},"PeriodicalIF":8.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869814","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":"Cracking the AI recruitment code: Striving for transparency in finding the right person–job fit","authors":"Aihui Chen ,&nbsp;Feifei Han ,&nbsp;Xinyi Zhang ,&nbsp;Yaobin Lu","doi":"10.1016/j.im.2025.104156","DOIUrl":"10.1016/j.im.2025.104156","url":null,"abstract":"<div><div>The use of artificial intelligence (AI) has significantly enhanced the efficiency of resume screening; however, discrepancies in person–job fit assessments between AI and human evaluators can adversely affect the recruitment process. This study introduces the concept of \"person–job fit perception difference\" to describe these discrepancies and proposes a theoretical model outlining the relationships among person–job fit perception difference, AI transparency, and algorithmic literacy. Based on data from a 2 × 3 factorial-design experiment (<em>N</em> = 286), the findings reveal that both external transparency and functional transparency of AI recruitment systems negatively influence the person–job fit perception difference. Additionally, two distinct aspects of algorithmic literacy moderate different pathways in this process.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 5","pages":"Article 104156"},"PeriodicalIF":8.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854910","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":"Resilience through an online platform: Evidence from airbnb and hotels","authors":"Jooho Kim ,&nbsp;Joohun (Justin) Lee ,&nbsp;Hyun Jong (Henry) Na","doi":"10.1016/j.im.2025.104157","DOIUrl":"10.1016/j.im.2025.104157","url":null,"abstract":"<div><div>This paper examines how online platforms enhance the resilience of affiliated properties during crises, using the COVID-19 pandemic as a natural experiment. Employing difference-in-differences approach, we compare the performance of platform-listed hotels and their non-listed counterparts in New York City before and after the pandemic's onset. Our findings reveal that platform-affiliated hotels achieved significantly higher booking rates during the pandemic by leveraging operational adaptability and building trust at a greater scale. These results are robust to various specifications, including propensity score matching, synthetic difference-in-differences, and several sensitivity analyses. By identifying the unique role of platforms in fostering resilience, this study extends the literature on digital resilience and offers actionable insights for traditional businesses navigating external shocks.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 5","pages":"Article 104157"},"PeriodicalIF":8.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833446","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":"To shine or not to shine: Startup success prediction by exploiting technological and venture-capital-related features","authors":"Chih-Ping Wei ,&nbsp;Evana Szu-Han Fang ,&nbsp;Chin-Sheng Yang ,&nbsp;Pin-Jun Liu","doi":"10.1016/j.im.2025.104152","DOIUrl":"10.1016/j.im.2025.104152","url":null,"abstract":"<div><div>Startups play a crucial role in driving economic growth, job creation, regional development, and technological innovation. However, they often encounter risks stemming from uncertainties in technology, unfamiliar markets, and limited resources. Given these challenges, effectively predicting startup success, defined as achieving a successful exit within a specific observation window, is vital for shaping investment decisions and facilitating the strategy formulation of stakeholders such as venture capitalists and startups themselves. In this study, we are interested in startups in high-tech industries. Existing startup success prediction research primarily focuses on exploiting features related to company profile, funding, founder, and top management team, and pays less attention to technological and venture-capital-related (VC-related) features that are prominent to high-tech startups. Furthermore, prior studies do not assess the effectiveness of startup success prediction over different prediction time points. To address these gaps, we design a startup success prediction method that incorporates three categories of features: basic, technological, and VC-related. For empirical evaluation purposes, we collected a dataset comprising 4415 startup cases and their corresponding feature values from the Securities Data Company's VentureXpert database and the USPTO database. Our evaluation results indicate the superiority of our method over the literature model, suggesting the predictive value of our proposed technological and VC-related features. Our results also show that the VC-related features are more salient in predicting high-tech startup success than the technological and basic features. Finally, our exploratory study of the deep learning approach reveals that using deep learning (e.g., graph convolutional network) to extract VC features automatically may not enhance prediction effectiveness at the very early stage of startups but shows a potential advantage over statistical and machine learning methods at a later prediction time point due to the increased number of VCs investing in the startups.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 6","pages":"Article 104152"},"PeriodicalIF":8.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873945","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":"Why pill becomes poison? Examining the damaging effect of increased information technology use on internal control process failures","authors":"Chaitanya Sambhara ,&nbsp;Arun Rai ,&nbsp;Sean Xin Xu","doi":"10.1016/j.im.2025.104144","DOIUrl":"10.1016/j.im.2025.104144","url":null,"abstract":"<div><div>We examine how the impact of accounting and finance enterprise systems (AFES) use on internal control process failures is influenced by the competence (or lack thereof) of internal controls. We draw on resource- and knowledge-based theories to motivate our hypotheses. We test our model using a six-year multisource panel dataset for 143 firms. We find that when firms lack requisite competence for internal controls, AFES use has a damaging effect on internal control processes, widening the scope of process failures. Our findings show that inopportune pursuit of information technology use initiatives can have far-reaching adverse impacts on firms.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 5","pages":"Article 104144"},"PeriodicalIF":8.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769275","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":"Corrigendum to ‘Disentangling the impact of vendor in-role and extra-role performance on client citizenship behavior in enterprise system projects: A response surface analysis’ [Information & Management 62/2 (2025) 104104]","authors":"Yuting Wang ,&nbsp;Jie Fang ,&nbsp;Bojue Xu ,&nbsp;Shuning Zheng ,&nbsp;Zhao Cai","doi":"10.1016/j.im.2025.104140","DOIUrl":"10.1016/j.im.2025.104140","url":null,"abstract":"","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 4","pages":"Article 104140"},"PeriodicalIF":8.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807115","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":"Speciesism toward AI: The mechanism of AI affection expression on user satisfaction","authors":"Aihui Chen ,&nbsp;Yunshuang Yu ,&nbsp;Yaobin Lu","doi":"10.1016/j.im.2025.104145","DOIUrl":"10.1016/j.im.2025.104145","url":null,"abstract":"<div><div>Evaluations of AI services may be adversely influenced by speciesism due to AI's distinctiveness from humans. We conducted four studies to investigate the impact of speciesism on AI evaluations. Our findings suggest that AI's capacity for affection expression (AE) increases people's satisfaction with AI services by reducing their speciesism toward AI. Additionally, we found that the influence of speciesism on AI satisfaction is moderated by the type of task. This study offers novel recommendations for AI service providers and designers.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"62 5","pages":"Article 104145"},"PeriodicalIF":8.2,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830298","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}