Machine Learning Measure-Supported Empirical Studies: A Survey

References

• Adomavicius G, Wang Y (2022) Improving reliability estimation for individual numeric predictions: A machine learning approach. INFORMS J. Comput. 34(1):503–521.Link, Google Scholar
• Allon G, Chen D, Jiang Z, Zhang D (2023) Machine learning and prediction errors in causal inference. Preprint, submitted June 15, https://doi.org/10.2139/ssrn.4480696.Google Scholar
• An B, Bushman R, Kleymenova A, Tomy RE (2024) Bank supervision and organizational capital: The case of minority lending. J. Accounting Res. 62(2):505–549.Crossref, Google Scholar
• Anand P, Kadiyalib V (2024) Smoke and mirrors: Impact of E-cigarette taxes on underage social media posting. Marketing Sci. 43(3):479–487.Link, Google Scholar
• Andrei AG, Benischke MH, Martin GP (2024) Behavioral agency and the efficacy of analysts as external monitors: Examining the moderating role of CEO personality. Strategic Management J. 45(1):113–143.Crossref, Google Scholar
• Arora K, Zheng F, Girotra K (2024) Private vs. pooled transportation: Customer preference and design of green transport policy. Manufacturing Service Oper. Management 26(2):594–611.Link, Google Scholar
• Arts S, Cassiman B, Gomez JC (2018) Text matching to measure patent similarity. Strategic Management J. 39(1):62–84.Crossref, Google Scholar
• Atalay AS, Kihal SE, Ellsaesser F (2023) Creating effective marketing messages through moderately surprising syntax. J. Marketing 87(5):755–775.Crossref, Google Scholar
• Athey S, Imbens G (2016) Recursive partitioning for heterogeneous causal effects. Proc. Natl. Acad. Sci. USA 113(27):7353–7360.Crossref, Google Scholar
• Athey S, Imbens GW (2017) The state of applied econometrics: Causality and policy evaluation. J. Econom. Perspect. 31(2):3–32.Crossref, Google Scholar
• Aubry M, Kräussl R, Manso G, Spaenjers C (2023) Biased auctioneers. J. Finance 78(2):795–833.Crossref, Google Scholar
• Bakeman R, McArthur D, Quera V, Robinson BF (1997) Detecting sequential patterns and determining their reliability with fallible observers. Psych. Methods 2(4):357–370.Crossref, Google Scholar
• Bandalos DL (2018) Measurement Theory and Applications for the Social Sciences (Guilford Press, New York).Google Scholar
• Banerjee M, Cole BM, Ingram P (2023) Distincitive from what? And for whom? Deep learning-based product distinctiveness, social structure, and third-party certifications. Acad. Management J. 66(4):1016–1041.Crossref, Google Scholar
• Banker RD, Ding H, Huang R, Li X (2024) Market reaction to CEOs’ dynamic hemifacial asymmetry of expressions. Management Sci. 70(7):4847–4874.Link, Google Scholar
• Belloni A, Chen D, Chernozhukov V, Hansen C (2012) Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica 80(6):2369–2429.Crossref, Google Scholar
• Bendoly E, Oliva R (2025) Meaningful theoretical pathways for research contributions. J. Oper. Management 71(1):4–10.Google Scholar
• Bengio Y, Courville A, Vincent P (2013) Representation learning: A review and new perspectives. IEEE Trans. Pattern Anal. Machine Intelligence 35(8):1798–1828.Crossref, Google Scholar
• Bergh DD, Boyd BK, Byron K, Gove S, Ketchen DJ (2022) What constitutes a methodological contribution? J. Management 48(7):1835–1848.Google Scholar
• Bertomeu J, Cheynel E, Liao Y, Milone M (2025) Using machine learning to measure conservatism. Management Sci. 71(2):1504–1522.Link, Google Scholar
• Booker A, Curtis A, Richardson VJ (2023) Investor disagreement, disclosure processing costs, and trading volume evidence from social media. Accounting Rev. 98(1):109–137.Crossref, Google Scholar
• Burton-Jones A, Gray P, Majchrzak A (2023) Editor’s comments: Producing significant research. MIS Quart. 47(1):i–xv.Crossref, Google Scholar
• Büschken J, Allenby GM (2020) Improving text analysis using sentence conjunctions and punctuation. Marketing Sci. 39(4):727–742.Link, Google Scholar
• Carlson NA (2023) Differentiation in microenterprises. Strategic Management J. 44(5):1141–1167.Crossref, Google Scholar
• Carlson KD, Herdman AO (2012) Understanding the impact of convergent validity on research results. Organ. Res. Methods 15(1):17–32.Crossref, Google Scholar
• Castro MP, Cire AA, Beck JC (2022) Decision diagrams for discrete optimization: A survey of recent advances. INFORMS J. Comput. 34(4):2271–2295.Link, Google Scholar
• Chakraborty I, Kim M, Sudhir K (2022) Attribute sentiment scoring with online text reviews: Accounting for language structure and missing attributes. J. Marketing Res. 59(3):600–622.Crossref, Google Scholar
• Chawla A (2025) Time complexity of 10 ML algorithms. Accessed May 11, 2026, https://www.dailydoseofds.com/p/time-complexity-of-10-ml-algorithms/.Google Scholar
• Chen MA, Wu Q, Yang B (2019) How valuable is FinTech innovation? Rev. Financial Stud. 32(5):2062–2106.Crossref, Google Scholar
• Chen D, Hu N, Liang P, Swink M (2024) Understanding the impact of trade policy effect uncertainty on firm-level innovation investment. J. Oper. Management 70(2):316–340.Crossref, Google Scholar
• Chen K, Li X, Luo P, Zhao JLL (2021) News-induced dynamic networks for market signaling: Understanding the impact of news on firm equity value. Inform. Systems Res. 32(2):356–377.Link, Google Scholar
• Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W, Robins J (2018) Double/debiased machine learning for treatment and structural parameters. Econom. J. 21(1):C1–C68.Crossref, Google Scholar
• Choi J, Menon A, Tabakovic H (2021) Using machine learning to revisit the diversification–performance relationship. Strategic Management J. 42(9):1632–1661.Crossref, Google Scholar
• Choudhury P, Wang D, Carlson NA, Khanna T (2019) Machine learning approaches to facial and text analysis: Discovering CEO oral communication styles. Strategic Management J. 40(11):1705–1732.Crossref, Google Scholar
• Chung M, Sharma L, Malhotra MK (2023) Impact of modularity design on mobile app launch success. Manufacturing Service Oper. Management 25(2):756–774.Link, Google Scholar
• Clyde A (2022) AI for science and global citizens. Patterns 3(2):100446.Crossref, Google Scholar
• Cookson JA, Niessner M (2020) Why don’t we agree? Evidence from a social network of investors. J. Finance 75(1):173–228.Crossref, Google Scholar
• Corritore M, Goldberg A, Srivastava SB (2020) Duality in diversity: How intrapersonal and interpersonal cultural heterogeneity relate to firm performance. Admin. Sci. Quart. 65(2):359–394.Crossref, Google Scholar
• De Franco G, Vasvari FP, Vyas D, Wittenberg-Moerman R (2014) Debt analysts’ views of debt-equity conflicts of interest. Accounting Rev. 89(2):571–604.Crossref, Google Scholar
• Deng C, Ravichandran T (2024) Managerial response to online positive reviews: Helpful or harmful? Inform. Systems Res. 35(4):1802–1823.Link, Google Scholar
• Dyer TA, Roulstone DT, Van Buskirk A (2024) Disclosure similarity and future stock return comovement. Management Sci. 70(7):4762–4780.Link, Google Scholar
• Ellickson PB, Kar W, Reeder JC III (2023) Estimating marketing component effects: Double machine learning from targeted digital promotions. Marketing Sci. 42(4):704–728.Link, Google Scholar
• Engelberg J, Henriksson M, Manela A, Williams J (2023) The partisanship of financial regulators. Rev. Financial Stud. 36(11):4373–4416.Crossref, Google Scholar
• Esterzon E, Lemmens A, Van den Bergh B (2023) Enhancing donor agency to improve charitable giving: Strategies and heterogeneity. J. Marketing 87(4):636–655.Crossref, Google Scholar
• Fong C, Tyler M (2021) Machine learning predictions as regression covariates. Political Anal. (Oxford) 29(4):467–484.Crossref, Google Scholar
• Furman JL, Teodoridis F (2020) Automation, research technology, and researchers’ trajectories: Evidence from computer science and electrical engineering. Organ. Sci. 31(2):330–354.Link, Google Scholar
• Goldenberg J, Lanz A, Shapira D, Stahl F (2024) Targeting nearby influencers: The acceleration of natural triadic closure by leveraging interconnectors. J. Marketing 88(5):111–130.Crossref, Google Scholar
• Gopal A, Chen P, Oh W, Xu SX, Sarker S (2024) On crafting effective theoretical contributions for empirical papers in economics of information systems: Some editorial reflections. Inform. Systems Res. 35(3):917–935.Link, Google Scholar
• Gordon BR, Lovett MJ, Luo B, Reeder JC (2023) Disentangling the effects of ad tone on voter turnout and candidate choice in presidential elections. Management Sci. 69(1):220–243.Link, Google Scholar
• Guo W, Sengul M, Yu T (2021) The impact of executive verbal communication on the convergence of investors’ opinions. Acad. Management J. 64(6):1763–1792.Crossref, Google Scholar
• Hadsell R, Chopra S, LeCun Y (2006) Dimensionality reduction by learning an invariant mapping. Fitzgibbon A, Taylor CJ, LeCun Y, eds. Proc. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recognition, vol. 2 (IEEE Computer Society, Washington, DC), 1735–1742.Google Scholar
• Hanley KW, Hoberg G (2019) Dynamic interpretation of emerging risks in the financial sector. Rev. Financial Stud. 32(12):4543–4603.Crossref, Google Scholar
• Harrison JS, Josefy MA, Kalm M, Krause R (2023) Using supervised machine learning to scale human-coded data: A method and dataset in the board leadership context. Strategic Management J. 44(7):1780–1802.Crossref, Google Scholar
• Harrison JS, Thurgood GR, Boivie S, Pfarrer MD (2019) Measuring CEO personality: Developing, validating, and testing a linguistic tool. Strategic Management J. 40(8):1316–1330.Crossref, Google Scholar
• Hasan S, Ferguson JP, Koning R (2015) The lives and deaths of jobs: Technical interdependence and survival in a job structure. Organ. Sci. 26(6):1665–1681.Link, Google Scholar
• Hou JR, Zhang J, Zhang K (2023) Pictures that are worth a thousand donations: How emotions in project images drive the success of online charity fundraising campaigns? An image design perspective. MIS Quart. 47(2):535–584.Crossref, Google Scholar
• Hoyle RH, Harris MJ, Judd CM (2002) Research Methods in Social Relations (Cengage Learning, Fort Worth, TX).Google Scholar
• Huang H, Sunar N, Swaminathan JM, Roy R (2023) Do noisy customer reviews discourage platform sellers? Empirical analysis of an online solar marketplace. Manufacturing Service Oper. Management 25(6):2195–2215.Link, Google Scholar
• Huchette J, Muñoz G, Thiago S, Calvin T (2026) When deep learning meets polyhedral theory: A survey. INFORMS J. Comput., ePub ahead of print March 12, https://doi.org/10.1287/ijoc.2024.0902.Google Scholar
• Hwang EH, Singh PV, Argote L (2019) Jack of all, master of some: Information network and innovation in crowdsourcing communities. Inform. Systems Res. 30(2):389–410.Link, Google Scholar
• Hyde SJ, Bachura E, Bundy J, Gretz RT, Sanders WG (2024) The tangled webs we weave: Examining the effects of CEO deception on analyst recommendations. Strategic Management J. 45(1):66–112.Crossref, Google Scholar
• Jarvis CB, MacKenzie SB, Podsakoff PM (2003) A critical review of construct indicators and measurement model misspecification in marketing and consumer research. J. Consumer Res. 30(2):199–218.Crossref, Google Scholar
• Jiang J, Kelly B, Xiu D (2023) (Re-)Imag(in)ing price trends. J. Finance 78(6):3193–3249.Crossref, Google Scholar
• Johnson SL, Safadi H, Faraj S (2015) The emergence of online community leadership. Inform. Systems Res. 26(1):165–187.Link, Google Scholar
• Kalmenovitz J (2023) Regulatory intensity and firm-specific exposure. Rev. Financial Stud. 36(8):3311–3347.Crossref, Google Scholar
• Kang Y, Cai Z, Tan CW, Huang Q, Liu H (2020) Natural language processing (NLP) in management research: A literature review. J. Management Analytics 7(2):139–172.Crossref, Google Scholar
• Kee HW, Knox RE (1970) Conceptual and methodological considerations in the study of trust and suspicion. J. Conflict Resolution 14(3):357–366.Crossref, Google Scholar
• Kim E, Ding MQ, Wang X, Lu S (2023) Does topic consistency matter? A study of critic and user reviews in the movie industry. J. Marketing 87(3):428–450.Crossref, Google Scholar
• Ko DG, Mai F, Shan Z, Zhang D (2019) Operational efficiency and patient-centered health care: A view from online physician reviews. J. Oper. Management 65(4):353–379.Crossref, Google Scholar
• Kwark Y, Lee GM, Pavlou PA, Qiu L (2021) On the spillover effects of online product reviews on purchases: Evidence from clickstream data. Inform. Systems Res. 32(3):895–913.Link, Google Scholar
• Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33(1):159–174.Crossref, Google Scholar
• Lee D, Hosanagar K, Nair HS (2018) Advertising content and consumer engagement on social media: Evidence from Facebook. Management Sci. 64(11):5105–5131.Link, Google Scholar
• Lee JJ, Jung HJ, Park H (2023) Rare is beautiful? Rareness, technology value, and the moderating role of search domain and knowledge maturity. Production Oper. Management 32(4):1019–1040.Crossref, Google Scholar
• Leng Y, Dimmery D (2024) Calibration of heterogeneous treatment effects in randomized experiments. Inform. Systems Res. (4):1721–1742.Link, Google Scholar
• Leung ACM, Agarwal A, Konana P, Kumar A (2017) Network analysis of search dynamics: The case of stock habitats. Management Sci. 63(8):2667–2687.Link, Google Scholar
• Lin Y, Yao D, Chen X (2021) Happiness begets money: Emotion and engagement in live streaming. J. Marketing Res. 58(3):417–438.Crossref, Google Scholar
• Liu L, Dzyabura D, Mizik N (2020) Visual listening in: Extracting brand image portrayed on social media. Marketing Sci. 39(4):669–686.Link, Google Scholar
• Liu X, Lee D, Srinivasan K (2019) Large-scale cross-category analysis of consumer review content on sales conversion leveraging deep learning. J. Marketing Res. 56(6):918–943.Crossref, Google Scholar
• Liu AX, Li Y, Xu SX (2021) Assessing the unacquainted: Inferred reviewer personality and review helpfulness. MIS Quart. 45(3):1113–1148.Crossref, Google Scholar
• Loughran T, Mcdonald B (2016) Textual analysis in accounting and finance: A survey. J. Accounting Res. 54(4):1187–1230.Crossref, Google Scholar
• Lu ZY, Jung S, Peck J (2024) It looks like “theirs”: When and why human presence in the photo lowers viewers’ liking and preference for an experience venue. J. Consumer Res. 51(2):321–341.Crossref, Google Scholar
• Ludwig J, Mullainathan S, Rambachan A (2026) Large language models: An applied econometric framework. Annu. Rev. Econom. 18:283–316.Crossref, Google Scholar
• Luo X, Jia N, Ouyang E, Fang Z (2024) Introducing machine-learning-based data fusion methods for analyzing multimodal data: An application of measuring trustworthiness of microenterprises. Strategic Management J. 45(8):1597–1629.Crossref, Google Scholar
• MacKenzie SB, Podsakoff PM, Podsakoff NP (2011) Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Quart. 35(2):293–334.Crossref, Google Scholar
• Mejia J, Mankad S, Gopal A (2019) A for effort? Using the crowd to identify moral hazard in New York City restaurant hygiene inspections. Inform. Systems Res. 30(4):1363–1386.Link, Google Scholar
• Messick S (1995) Validity of psychological assessment. Amer. Psych. 50(9):741–749.Crossref, Google Scholar
• Momtaz PP (2021) CEO emotions and firm valuation in initial coin offerings: An artificial emotional intelligence approach. Strategic Management J. 42(3):558–578.Crossref, Google Scholar
• Obaid K, Pukthuanthong K (2022) A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news. J. Financial Econom. 144(1):273–297.Crossref, Google Scholar
• Ou AY, Lu Q, Li X, Chi-Nien C, Chen G (2024) CEO humility and corporate social irresponsibility: Evidence based on a new unobtrusive measure. Organ. Sci. 35(6):2016–2039.Link, Google Scholar
• Packard G, Li Y, Berger J (2024) When language matters. J. Consumer Res. 51(3):634–653.Crossref, Google Scholar
• Padmanabhan B, Fang X, Sahoo N, Burton-Jones A (2022) Editor’s comments: Machine learning in information systems research. MIS Quart. 46(1):iii–xix.Crossref, Google Scholar
• Pan Y, Huang P, Gopal A (2019) Storm clouds on the horizon? New entry threats and R&D investments in the U.S. IT industry. Inform. Systems Res. 30(2):540–562.Link, Google Scholar
• Peng J, Hahn J, Huang KW (2023) Handling missing values in information systems research: A review of methods and assumptions. Inform. Systems Res. 34(1):5–26.Link, Google Scholar
• Qiao M, Huang KW (2021) Correcting misclassification bias in regression models with variables generated via data mining. Inform. Systems Res. 32(2):462–480.Link, Google Scholar
• Quan C, Ren F (2010) Sentence emotion analysis and recognition based on emotion words using Ren-CECps. Internat. J. Advanced Intelligence 2(1):105–117.Google Scholar
• Rathje J, Katila R, Reineke P (2024) Making the most of AI and machine learning in organizations and strategy research: Supervised machine learning, causal inference, and matching models. Strategic Management J. 45(10):1926–1953.Crossref, Google Scholar
• Rui H, Liu Y, Whinston A (2013) Whose and what chatter matters? The effect of tweets on movie sales. Decision Support Systems 55(4):863–870.Crossref, Google Scholar
• Ryoo JH, Wang X, Lu S (2021) Do spoilers really spoil? Using topic modeling to measure the effect of spoiler reviews on box office revenue. J. Marketing 85(2):70–88.Crossref, Google Scholar
• Shin D, He S, Lee GM, Whinston AB, Cetintas S, Lee KC (2020) Enhancing social media analysis with visual data analytics: A deep learning approach. MIS Quart. 44(4):1459–1492.Crossref, Google Scholar
• Taeuscher K, Bouncken R, Pesch R (2021) Gaining legitimacy by being different: Optimal distinctiveness in crowdfunding platforms. Acad. Management J. 64(1):149–179.Crossref, Google Scholar
• Templeton GF, Lewis BR (2015) Fairness in the institutional valuation of business journals. MIS Quart. 39(3):523–539.Crossref, Google Scholar
• Van Binsbergen JH, Han X, Lopez-Lira A (2023) Man versus machine learning: The term structure of earnings expectations and conditional biases. Rev. Financial Stud. 36(6):2361–2396.Crossref, Google Scholar
• van de Schoot R, Lugtig P, Hox J (2012) A checklist for testing measurement invariance. Eur. J. Developmental Psych. 9(4):486–492.Crossref, Google Scholar
• van Den Oever K, Shropshire C (2024) More than a feeling: How board member displays of anger and happiness influence strategic decisions. Acad. Management J. 67(6):1525–1552.Crossref, Google Scholar
• Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, et al. (2017) Attention is all you need. von Luxburg U, Guyon I, Bengio S, Wallach H, Fergus R, eds. Adv. Neural Inform. Processing Systems, vol. 30 (Curran Associates Inc., Red Hook, NY), 6000–6010.Google Scholar
• Wang G (2022) The effect of Medicaid expansion on wait time in the emergency department. Management Sci. 68(9):6648–6665.Link, Google Scholar
• Wang X, Lu S, Li X, Khamitov M, Bendle N (2021) Audio mining: The role of vocal tone in persuasion. J. Consumer Res. 48(2):189–211.Crossref, Google Scholar
• Wang K, Mai F, Shan Z, Zhang DD, Peng XD (2025) Analyzing professional ethics of physicians using online patient reviews: A machine learning approach. Production Oper. Management, ePub ahead of print January 31, https://doi.org/10.1177/10591478251318885.Crossref, Google Scholar
• Wei YM, Hong J, Tellis GJ (2022) Machine learning for creativity: Using similarity networks to design better crowdfunding projects. J. Marketing 86(2):87–104.Crossref, Google Scholar
• Wu L, Lou B, Hitt L (2019) Data analytics supports decentralized innovation. Management Sci. 65(10):4863–4877.Link, Google Scholar
• Wu Z, Pan S, Chen F, Long G, Zhang C, Yu PS (2021) A comprehensive survey on graph neural networks. IEEE Trans. Neural Networks Learn. Systems 32(1):4–24.Crossref, Google Scholar
• Xie S, Sharma S, Mehra A, Aziz A (2024) Strategic expectation setting of delivery time on marketplaces. Inform. Systems Res. 35(4):1965–1980.Link, Google Scholar
• Xiong G, Bharadwaj S (2014) Prerelease buzz evolution patterns and new product performance. Marketing Sci. 33(3):401–421.Link, Google Scholar
• Xue W (2023) Correcting strategic misreporting behavior on outcomes in estimating treatment effect. Preprint, submitted September 25, https://doi.org/10.2139/ssrn.4583438.Google Scholar
• Yang J, Zhang J, Zhang Y (2025) Engagement that sells: Influencer video advertising on TikTok. Marketing Sci. 44(2):247–267.Link, Google Scholar
• Yang M, Adomavicius G, Burtch G, Ren Y (2018) Mind the gap: Accounting for measurement error and misclassification in variables generated via data mining. Inform. Systems Res. 29(1):4–24.Link, Google Scholar
• Yang Y, Qin Y, Fan Y, Zhang Z (2023) Unlocking the power of voice for financial risk prediction: A theory-driven deep learning design approach. MIS Quart. 47(1):63–96.Crossref, Google Scholar
• Yin D, Bond SD, Zhang H (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Quart. 38(2):539–560.Crossref, Google Scholar
• Yiu DW, Wan WP, Chen KX, Tian X (2022) Public sentiment is everything: Host-country public sentiment toward home country and acquisition ownership during institutional transition. J. Internat. Bus. Stud. 53(6):1202–1227.Crossref, Google Scholar
• Yoganarasimhan H, Iakovetskaia I (2024) From feeds to inboxes: A comparative study of polarization in Facebook and email news sharing. Management Sci. 70(9):6461–6472.Abstract, Google Scholar
• Zhang M, Briscoe F, DesJardine MR (2023) Corporate boards with street smarts? How diffuse street protests indirectly shape corporate governance. Admin. Sci. Quart. 68(4):1056–1093.Crossref, Google Scholar
• Zhang Q, Wang W, Chen Y (2020) Frontiers: In-consumption social listening with moment-to-moment unstructured data: The case of movie appreciation and live comments. Marketing Sci. 39(2):285–295.Link, Google Scholar
• Zhang S, Lee D, Singh PV, Srinivasan K (2022a) What makes a good image? Airbnb demand analytics leveraging interpretable image features. Management Sci. 68(8):5644–5666.Link, Google Scholar
• Zhang J, Xue W, Yu Y, Tan Y (2026) Debiasing ML- or AI-generated regressors in partially linear models. Inform. Systems Res., ePub ahead of print May 27, https://doi.org/10.1287/isre.2024.1370.Google Scholar
• Zhang Z, Wei X, Zheng X, Li Q, Zeng DD (2022b) Detecting product adoption intentions via multiview deep learning. INFORMS J. Comput. 34(1):541–556.Link, Google Scholar
• Zhou J, Zhang Q, Zhou S, Li X, Zhang XM (2023) Unintended emotional effects of online health communities: A text mining-supported empirical study. MIS Quart. 47(1):195–226.Crossref, Google Scholar