Customer behavior and adoptionEvidence check: 2/5
Zhijie Lin, Ying Zhang, Yong Tan (2019). An Empirical Study of Free Product Sampling and Rating Bias. Information Systems Research. https://doi.org/10.1287/isre.2018.0801
Plain-English take: Free sampling raised ratings by 1.1%; rating bias was larger at higher original prices and smaller with larger discounts and greater product popularity.
Question: An Empirical Study of Free Product Sampling and Rating Bias?
Design: Large observational e-commerce study using rich panel data, multiple identification strategies, and alternative estimators. Products and reviews on Taobao.com
Free sampling raised ratings by 1.1%; rating bias was larger at higher original prices and smaller with larger discounts and greater product popularity.
Information Systems Research · 201910.1287/isre.2018.0801Publisher article page; full-text availability varies and was not established in this review.
Customer behavior and adoptionEvidence check: 3/5
Klaus M. Schmidt, Martin Spann, Robert Zeithammer (2014). Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets. Management Science. https://doi.org/10.1287/mnsc.2014.1946
Plain-English take: Outcome-based social preferences and strategic considerations explain voluntary payments; posted-price competition lowers payments, prevents full market penetration, and most sellers choose posted prices when given the choice.
Question: Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets?
Design: Laboratory experiments varying PWYW, posted-price competition, and seller pricing-strategy choice. Experimental buyers and sellers in monopolistic and competitive market environments
Outcome-based social preferences and strategic considerations explain voluntary payments; posted-price competition lowers payments, prevents full market penetration, and most sellers choose posted prices when given the choice.
Management Science · 201410.1287/mnsc.2014.1946Publisher article page; full-text availability varies and was not established in this review.
Customer behavior and adoptionEvidence check: 2/5
Mary J. Bitner, Amy L. Ostrom, Felicia N. Morgan (2013). The adoption of customer service improvement practices. Marketing Letters. https://doi.org/10.1007/s11002-013-9263-0
Plain-English take: Management support, customer orientation, and organizational capabilities were associated with adoption and implementation depth.
Question: The adoption of customer service improvement practices?
Design: Cross-sectional firm survey with multivariate modeling of adoption determinants.. Organizations evaluating or implementing customer-service improvement practices.
Management support, customer orientation, and organizational capabilities were associated with adoption and implementation depth.
Marketing Letters · 201310.1007/s11002-013-9263-0Publisher article page; full-text availability varies and was not established in this review.
Customer behavior and adoptionEvidence check: 2/5
M. Järvinen, H. Taiminen (2020). Dynamics of marketing automation adoption for organisational marketing process transformation: the case of Microsoft. International Journal of Electronic Customer Relationship Management. https://doi.org/10.1504/ijecrm.2020.110039
Plain-English take: Automation adoption was iterative and depended on process redesign, data integration, and organizational coordination rather than software installation alone.
Question: Dynamics of marketing automation adoption for organisational marketing process transformation: the case of Microsoft?
Design: Empirical longitudinal case study of technology adoption and process transformation.. Microsoft organizational marketing processes and marketing-automation implementation.
Automation adoption was iterative and depended on process redesign, data integration, and organizational coordination rather than software installation alone.
International Journal of Electronic Customer Relationship Management · 202010.1504/ijecrm.2020.110039Publisher article page; full-text availability varies and was not established in this review.
Customer behavior and adoptionEvidence check: 2/5
Feng Zhu, Qihong Liu (2018). Competing with complementors: An empirical look at Amazon.com. Strategic Management Journal. https://doi.org/10.1002/smj.2932
Plain-English take: Amazon was more likely to enter successful product spaces but less likely to enter spaces requiring greater seller effort; entry discouraged affected sellers' later growth while increasing consumer demand and reducing shipping costs.
Question: What does competing with complementors: an empirical look at amazon.com show about customer behavior or marketing outcomes?
Design: Empirical analysis of Amazon's entry into third-party sellers' product spaces using Amazon marketplace data; entry targeting, seller growth effort, subsequent seller growth, consumer demand and shipping costs were examined.. Amazon.com marketplace, third-party sellers and product spaces.
Amazon was more likely to enter successful product spaces but less likely to enter spaces requiring greater seller effort; entry discouraged affected sellers' later growth while increasing consumer demand and reducing shipping costs.
Strategic Management Journal · 201810.1002/smj.2932Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Huan Liu, Lara Lobschat, Peter C. Verhoef, Hong Zhao (2019). App Adoption: The Effect on Purchasing of Customers Who Have Used a Mobile Website Previously. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2018.12.001
Plain-English take: App adopters have higher purchase incidence, purchase more frequently, and spend more per order than non-adopters. The app effect on order size is stronger for customers with a lower share of high-price-category spending and for less-loyal customers, consistent with reduced perceived financial risk and potentially improved loyalty.
Question: What does app adoption: the effect on purchasing of customers who have used a mobile website previously show about customer behavior or marketing outcomes?
Design: Empirical observational study using transactional customer data; adoption and subsequent purchasing are compared with controls for customer heterogeneity and prior behavior.. Customers of a Chinese online retailer who had an existing mobile website and were exposed to a newly added retail app; the study uses retailer transaction histories.
App adopters have higher purchase incidence, purchase more frequently, and spend more per order than non-adopters. The app effect on order size is stronger for customers with a lower share of high-price-category spending and for less-loyal customers, consistent with reduced perceived financial risk and potentially improved loyalty.
Journal of Interactive Marketing · 201910.1016/j.intmar.2018.12.001Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Mariachiara Restuccia, Renaud Legoux (2019). B2B relationships on the fast track: An empirical investigation into the outcomes of solution provision. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2018.08.012
Plain-English take: Solution provision increased retention, sales volume, and cross-selling for recent customers (an accelerator role), while established customers did not show the same increases.
Question: What does b2b relationships on the fast track: an empirical investigation into the outcomes of solution provision show about customer behavior or marketing outcomes?
Design: Longitudinal analysis of a supplier sales database using propensity-score matching to compare solution provision with non-provision; outcomes are retention, sales volume, and cross-selling, moderated by relationship life-cycle stage.. One North American company and its B2B customers; supplier sales database with recent and established customer relationships.
Solution provision increased retention, sales volume, and cross-selling for recent customers (an accelerator role), while established customers did not show the same increases.
Industrial Marketing Management · 201910.1016/j.indmarman.2018.08.012Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Tatu Virtanen, Petri Parvinen, Minna Rollins (2016). Complexity of sales situation and sales lead performance: An empirical study in business-to-business company. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2015.02.024
Plain-English take: Close customer collaboration increased the probability that a lead was canceled. The authors conclude that collaboration-focused selling may not increase hit rates in highly collaborative B2B environments.
Question: What does complexity of sales situation and sales lead performance: an empirical study in business-to-business company show about customer behavior or marketing outcomes?
Design: Mixed methods: interviews with sales personnel plus CRM analysis of 4,000 leads. Multinomial logistic regression predicts win, lost, or canceled outcomes from relational complexity, internal sales-task complexity, and vendor cross-business-unit collaboration.. A large global IT solution provider selling integrated solutions; 4,000 CRM sales leads classified as win, lost, or canceled.
Close customer collaboration increased the probability that a lead was canceled. The authors conclude that collaboration-focused selling may not increase hit rates in highly collaborative B2B environments.
Industrial Marketing Management · 201610.1016/j.indmarman.2015.02.024Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Sharad Borle, Siddharth S. Singh, Dipak C. Jain (2008). Customer Lifetime Value Measurement. Management Science. https://doi.org/10.1287/mnsc.1070.0746
Plain-English take: Jointly modeling purchase timing, amount, and defection predicts customer lifetime value and valuable-customer targeting better than extended NBD–Pareto, RFM, nested, and heuristic benchmarks. Longer interpurchase times predict larger purchase amounts and greater leaving risk; female and male customers show similar timing/risk patterns, while female customers spend less.
Question: What does customer lifetime value measurement show about customer behavior or marketing outcomes?
Design: Hierarchical Bayesian empirical modeling of purchase timing, purchase amount, and defection risk, with model comparison on a separate holdout/validation dataset.. Customer-level longitudinal records from a membership-based direct-marketing company where joining and termination dates are observed; estimation and holdout samples are used.
Jointly modeling purchase timing, amount, and defection predicts customer lifetime value and valuable-customer targeting better than extended NBD–Pareto, RFM, nested, and heuristic benchmarks. Longer interpurchase times predict larger purchase amounts and greater leaving risk; female and male customers show similar timing/risk patterns, while female customers spend less.
Management Science · 200810.1287/mnsc.1070.0746Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Antragama Ewa Abbas, Floris Kool, Wirawan Agahari, Mark de Reuver (2025). Stimulating data marketplace adoption in manufacturing: The impact of perceived control on willingness to share data. Technovation. https://doi.org/10.1016/j.technovation.2025.103371
Plain-English take: Perceived control significantly increased willingness to share; lower risk perceptions partially mediated the effect, whereas trust in data buyers did not mediate it.
Question: What does stimulating data marketplace adoption in manufacturing: the impact of perceived control on willingness to share data show about customer behavior or marketing outcomes?
Design: Survey-based empirical test of a model linking perceived control to willingness to share data; the scenario described smart contracts enforcing data-sharing conditions, with risk perception and trust in buyers as mediators.. 299 managers in manufacturing businesses considering an IoT data marketplace; B2B platform supply-side data owners.
Perceived control significantly increased willingness to share; lower risk perceptions partially mediated the effect, whereas trust in data buyers did not mediate it.
Technovation · 202510.1016/j.technovation.2025.103371Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 3/5
R. C. Bayer, Cheng Ke (2013). Discounts and Consumer Search Behavior: The Role of Framing. Journal of Economic Psychology. https://doi.org/10.1016/j.joep.2013.08.004
Plain-English take: Participants based decisions on salient price-presentation characteristics rather than objective net-price information, demonstrating a pure framing effect of discounts on search behavior.
Question: What does discounts and consumer search behavior: the role of framing show about customer behavior or marketing outcomes?
Design: A two-shop search experiment held net prices constant while varying whether shops posted net prices or gross prices with separate discount offers, and whether the first or second shop used the discount frame; search and purchase/shop choice were outcomes.. Controlled two-shop search experiment with experimental subjects; the publisher abstract verifies the treatments and constant net prices but the accessible record does not expose the sample count.
Participants based decisions on salient price-presentation characteristics rather than objective net-price information, demonstrating a pure framing effect of discounts on search behavior.
Journal of Economic Psychology · 201310.1016/j.joep.2013.08.004Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Romana Khan, Michael Lewis, Vishal Singh (2009). Dynamic Customer Management and the Value of One-to-One Marketing. Marketing Science. https://doi.org/10.1287/mksc.1090.0497
Plain-English take: Customizing promotions increased simulated profits over uniform promotions. Free shipping was preferred for re-acquiring lapsed customers, while discount coupons worked best for active customers; temporal within-customer heterogeneity mattered more than cross-sectional heterogeneity.
Question: What does dynamic customer management and the value of one-to-one marketing show about customer behavior or marketing outcomes?
Design: Uses online grocery/drug-retailer purchase data to estimate consumer purchase and expenditure responses to discount coupons, free shipping, and loyalty programs, allowing cross-sectional and within-customer purchase-cycle heterogeneity; feeds estimates into dynamic programming policy simulations.. An online grocery and drug retailer; exact observation count is not stated in the publisher abstract.
Customizing promotions increased simulated profits over uniform promotions. Free shipping was preferred for re-acquiring lapsed customers, while discount coupons worked best for active customers; temporal within-customer heterogeneity mattered more than cross-sectional heterogeneity.
Marketing Science · 200910.1287/mksc.1090.0497Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Rahul Kapoor, Shiva Agarwal (2017). Sustaining Superior Performance in Business Ecosystems: Evidence from Application Software Developers in the iOS and Android Smartphone Ecosystems. Organization Science. https://doi.org/10.1287/orsc.2017.1122
Plain-English take: Higher ecosystem complexity helped developers sustain superior performance, especially experienced firms; platform transitions made sustained superiority harder, with the adverse effect amplified by complexity.
Question: What does sustaining superior performance in business ecosystems: evidence from application software developers in the ios and android smartphone ecosystems show about customer behavior or marketing outcomes?
Design: Longitudinal empirical analysis of app-developer performance in iOS and Android; explanatory variables were ecosystem complexity, platform-generational transitions and developer ecosystem-specific experience, with persistence of superior performance as outcome.. Application software developers in Apple's iOS and Google's Android smartphone ecosystems.
Higher ecosystem complexity helped developers sustain superior performance, especially experienced firms; platform transitions made sustained superiority harder, with the adverse effect amplified by complexity.
Organization Science · 201710.1287/orsc.2017.1122Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Miao Feng, Haoran Si, Yang Li, Junrui Zhang (2024). Evaluating the drivers of B2B performance: An empirical analysis based on Alibaba. PLoS ONE. https://doi.org/10.1371/journal.pone.0306919
Plain-English take: Service capability and logistics capability positively affected B2B performance; customer attention mediated these effects, including significant indirect effects for service capability (β=.148) and logistics capability (β=.084), both p<.01.
Question: What does evaluating the drivers of b2b performance: an empirical analysis based on alibaba show about customer behavior or marketing outcomes?
Design: Empirical Alibaba 1688 platform analysis testing supplier capabilities (including service and logistics capability), B2B performance, customer attention as mediator, and OEM status as moderator; mediation/moderation effects are estimated with regression-based analysis.. Publicly visible B2B supplier profiles, sales, potential customer attention, and service-performance data from Alibaba 1688, a Chinese platform covering daily-use products and multiple supplier categories.
Service capability and logistics capability positively affected B2B performance; customer attention mediated these effects, including significant indirect effects for service capability (β=.148) and logistics capability (β=.084), both p<.01.
PLoS ONE · 202410.1371/journal.pone.0306919Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Srinath Gopalakrishna, Andrew T. Crecelius, Ashutosh Patil (2022). Hunting for new customers: Assessing the drivers of effective salesperson prospecting and conversion. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2022.05.008
Plain-English take: Prospecting and conversion have an implicit trade-off with a sweet spot maximizing acquisition. More-experienced salespeople acquired fewer new customers; advertising support and extrinsic rewards improved conversion more for experienced reps.
Question: What does hunting for new customers: assessing the drivers of effective salesperson prospecting and conversion show about customer behavior or marketing outcomes?
Design: Objective sales-funnel data analyzed with negative-binomial and beta regression models. The study estimates drivers of prospecting efficacy (leads) and conversion efficacy (customers) using motivation-opportunity-ability variables, advertising support, extrinsic rewards, and salesperson experience.. Objective prospecting/conversion performance data from multiple divisions of one firm; the authors describe the setting as entrepreneurial selling where salespeople acquire customers.
Prospecting and conversion have an implicit trade-off with a sweet spot maximizing acquisition. More-experienced salespeople acquired fewer new customers; advertising support and extrinsic rewards improved conversion more for experienced reps.
Journal of Business Research · 202210.1016/j.jbusres.2022.05.008Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Unnati Narang, Venkatesh Shankar (2019). Mobile App Introduction and Online and Offline Purchases and Product Returns. Marketing Science. https://doi.org/10.1287/mksc.2019.1169
Plain-English take: After launch, adopters bought 33% more frequently, 34% more items and spent 37% more, but returned 35% more frequently, 35% more items and 41% more in value; net monetary value was 36% higher.
Question: What does mobile app introduction and online and offline purchases and product returns show about customer behavior or marketing outcomes?
Design: Difference-in-differences analysis of a retailer's app launch, modeling purchase frequency, quantity, monetary value and returns; app-use time, location and features provide descriptive mechanism evidence.. Large retailer customer/purchase data spanning online and offline channels; adopters compared with nonadopters around the app introduction.
After launch, adopters bought 33% more frequently, 34% more items and spent 37% more, but returned 35% more frequently, 35% more items and 41% more in value; net monetary value was 36% higher.
Marketing Science · 201910.1287/mksc.2019.1169Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 4/5
Ernst C. Osinga, Menno Zevenbergen, Mark W. G. van Zuijlen (2019). Do Mobile Banner Ads Increase Sales? Yes, in the Offline Channel. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2019.02.001
Plain-English take: Offline sales increased about 2%; online sales did not significantly change, and there was no evidence of cross-channel cannibalization. A positive lagged offline effect was also reported.
Question: What does do mobile banner ads increase sales? yes, in the offline channel show about customer behavior or marketing outcomes?
Design: Geographical field experiment: ads were served only in three Dutch provinces; regional offline/online sales over 20 months were analyzed using difference-in-differences, fixed effects, propensity-score matching, and coarsened-exact matching.. Over 3.5 million mobile banner ads; sales regions covering the Netherlands; treatment period January 6–10, 2015.
Offline sales increased about 2%; online sales did not significantly change, and there was no evidence of cross-channel cannibalization. A positive lagged offline effect was also reported.
International Journal of Research in Marketing · 201910.1016/j.ijresmar.2019.02.001Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Eric T. Anderson, Duncan I. Simester (2004). Long-Run Effects of Promotion Depth on New Versus Established Customers: Three Field Studies. Marketing Science. https://doi.org/10.1287/mksc.1030.0040
Plain-English take: Promotion depth has different long-run effects for new and established customers, demonstrating that the immediate response to a discount is not sufficient to evaluate its longer-run customer-growth consequences.
Question: What does long-run effects of promotion depth on new versus established customers: three field studies show about customer behavior or marketing outcomes?
Design: Three field studies varied promotion depth and tracked subsequent customer behavior, comparing new and established customers; the outcomes are long-run response and repeat purchasing after a price promotion.. Three real-market field studies involving new versus established customers; the publisher identifies the article as three field studies, but the accessible record does not display a common participant count.
Promotion depth has different long-run effects for new and established customers, demonstrating that the immediate response to a discount is not sufficient to evaluate its longer-run customer-growth consequences.
Marketing Science · 200410.1287/mksc.1030.0040Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 4/5
Vibhanshu Abhishek, Kinshuk Jerath, Siddhartha Sharma (2024). The Impact of ‘Retail Media’ on Online Marketplaces: Insights from a Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2022.0188
Plain-English take: Sponsored listings underperformed displaced organic listings in electronics but outperformed them in clothing/footwear; neighboring organic effects moved oppositely. Overall clicks and conversions did not change when sponsored share rose about 10 points, while marketplace ad revenue rose (short-run implication).
Question: What does the impact of ‘retail media’ on online marketplaces: insights from a field experiment show about customer behavior or marketing outcomes?
Design: Large-scale marketplace field experiment at Flipkart changing the fraction/placement of sponsored listings interleaved with organic search results; outcomes were clicks and conversions for sponsored, displaced, neighboring organic listings, and the search overall.. Flipkart, a leading online marketplace in India; electronics, clothing, and footwear search categories. The abstract reports about a 10-percentage-point increase in sponsored-listing share but not a total N.
Sponsored listings underperformed displaced organic listings in electronics but outperformed them in clothing/footwear; neighboring organic effects moved oppositely. Overall clicks and conversions did not change when sponsored share rose about 10 points, while marketplace ad revenue rose (short-run implication).
Information Systems Research · 202410.1287/isre.2022.0188Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Ruth N. Bolton (1998). A Dynamic Model of the Duration of the Customer’s Relationship with a Continuous Service Provider: The Role of Satisfaction. Marketing Science. https://doi.org/10.1287/mksc.17.1.45
Plain-English take: Pre-cancellation satisfaction is positively related to relationship duration. Experienced customers weight cumulative satisfaction more heavily; transactions and failures affect duration through satisfaction-dependent contrast/assimilation effects.
Question: What does a dynamic model of the duration of the customer’s relationship with a continuous service provider: the role of satisfaction show about customer behavior or marketing outcomes?
Design: Left-truncated proportional-hazards model estimated with cross-sectional and time-series perceptions/behavior; models relationship duration as a function of cumulative satisfaction, updating, service transactions, and service failures.. Cellular customers observed over 22 months; exact N is not stated in the publisher abstract.
Pre-cancellation satisfaction is positively related to relationship duration. Experienced customers weight cumulative satisfaction more heavily; transactions and failures affect duration through satisfaction-dependent contrast/assimilation effects.
Marketing Science · 199810.1287/mksc.17.1.45Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Hyung Jin Kim, Inchan Kim, Hogeun Lee (2016). Third-party mobile app developers’ continued participation in platform-centric ecosystems: An empirical investigation of two different mechanisms. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2015.09.002
Plain-English take: The study identifies and empirically investigates two contrasting routes to continued participation: genuine desire/dedication and need/constraint; it argues platform owners must manage the exchange relationship from developers' perspective to retain them.
Question: What does third-party mobile app developers’ continued participation in platform-centric ecosystems: an empirical investigation of two different mechanisms show about customer behavior or marketing outcomes?
Design: Empirical dual-model study of relationship continuance, distinguishing dedication-based and constraint-based mechanisms; antecedents, affective intervening variables and continued participation were modeled from interorganizational-exchange theory.. Third-party mobile-app developers participating in platform-centric ecosystems; continuation of affiliation with a platform owner is the outcome.
The study identifies and empirically investigates two contrasting routes to continued participation: genuine desire/dedication and need/constraint; it argues platform owners must manage the exchange relationship from developers' perspective to retain them.
International Journal of Information Management · 201610.1016/j.ijinfomgt.2015.09.002Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2/5
Deborah J. John, Peter C. Boatwright, Shuba Srinivasan (2011). How Should Consumers’ Willingness to Pay be Measured? An Empirical Comparison of State-of-the-Art Approaches. Journal of Marketing Research. https://doi.org/10.1509/jmkr.48.1.172
Plain-English take: BDM and incentive-aligned CBC passed statistical and decision-oriented tests. Incentive-aligned settings produced greater price sensitivity and more 'none' choices; non-incentive methods can nevertheless yield useful demand curves and pricing decisions.
Question: What does how should consumers’ willingness to pay be measured? an empirical comparison of state-of-the-art approaches show about customer behavior or marketing outcomes?
Design: A five-way empirical comparison tested open-ended questions, choice-based conjoint, the Becker–DeGroot–Marschak incentive-compatible mechanism, incentive-aligned choice-based conjoint, and real purchase data; outcomes included price sensitivity, demand curves, and pricing decisions.. Consumers evaluating a product under four elicitation approaches, benchmarked against real purchase data; the publisher abstract identifies the five-in-one design but does not show the accessible sample count.
BDM and incentive-aligned CBC passed statistical and decision-oriented tests. Incentive-aligned settings produced greater price sensitivity and more 'none' choices; non-incentive methods can nevertheless yield useful demand curves and pricing decisions.
Journal of Marketing Research · 201110.1509/jmkr.48.1.172Publisher page; full-text availability varies and was not established.
Customer behavior and adoptionEvidence check: 2.5/5
Dimitrios Tsekouras, Benedict G. C. Dellaert, Bas Donkers, Gerald Häubl (2020). Product set granularity and consumer response to recommendations. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-019-00682-6.
Plain-English take: Finer-grained recommendation sets reduced response despite better products; effect was stronger for more engaged consumers. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How does similarity/granularity within recommended product sets affect response?
Design: Field-data empirical study of explicit recommendation sets, with behavioral indicators and simulation.. Online recommendation/product-search setting; real-world field data and consumer engagement heterogeneity.
Finer-grained recommendation sets reduced response despite better products; effect was stronger for more engaged consumers.
Journal of the Academy of Marketing Science · 202010.1007/s11747-019-00682-6Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4.5/5
Xueming Luo, Yuxchi Zhang, Fue Zeng, Zhe Qu (2020). Complementarity and Cannibalization of Offline-to-Online Targeting: A Field Experiment on Omnichannel Commerce. MIS Quarterly. https://doi.org/10.25300/MISQ/2020/15630.
Plain-English take: Publisher abstract/search result reports causal evidence for both complementarity and cannibalization between offline and online targeting. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: When does offline targeting complement versus cannibalize online commerce?
Design: Randomized field experiment testing offline-to-online targeting and cross-channel effects.. More than 11,200 customers of a large department store.
Publisher abstract/search result reports causal evidence for both complementarity and cannibalization between offline and online targeting.
MIS Quarterly · 202010.25300/MISQ/2020/15630Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Rex Yuxing Du, Oded Netzer, David A. Schweidel, Debanjan Mitra (2021). Capturing Marketing Information to Fuel Growth. Journal of Marketing. https://doi.org/10.1177/0022242920969198.
Plain-English take: The paper uses causal online-test evidence to study how marketing information can be captured and used for growth. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How can firms capture marketing information and use it to fuel growth?
Design: Online testing/field-experiment evidence on marketing information and growth (paper’s publisher page describes online testing/field experiment data).. Marketing-information/CRM setting described by publisher page; empirical tests use online testing/field-experiment data.
The paper uses causal online-test evidence to study how marketing information can be captured and used for growth.
Journal of Marketing · 202110.1177/0022242920969198Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Zainab Jamal, Kartik Hosanagar, Avi Goldfarb (2016). Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting. Marketing Science. https://doi.org/10.1287/mksc.2015.0956.
Plain-English take: Profiles were interpretable; internal-only data could be biased; search engines covered less activity but had higher data quality and could recover profiles; simulation showed targeting gains. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Can online surfing data infer useful profiles for customer analysis and behavioral targeting?
Design: Scalable user-profile inference from online surfing records; empirical customer-base/display-ad analysis and economic simulation.. Online activity records across search engines/advertising networks; applications to customer-base analysis and display advertising.
Profiles were interpretable; internal-only data could be biased; search engines covered less activity but had higher data quality and could recover profiles; simulation showed targeting gains.
Marketing Science · 201610.1287/mksc.2015.0956Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Sagit Bar-Gill, Nir Hak, Eran Toch (2024). Helping Small Businesses Become More Data-Driven: A Field Experiment on eBay. Management Science. https://doi.org/10.1287/mnsc.2021.02026.
Plain-English take: Seller Hub increased data-driven decision making and revenues 3.6%; more items transacted and service quality rose without average-price increases; over one-third of impact came from active monitoring. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: What is the causal impact of an analytics dashboard on SME performance and data-driven decision making?
Design: Experiment-based causal analysis of randomized introduction of eBay Seller Hub dashboard.. Small-to-medium e-retailers on eBay; randomized introduction of a data-rich seller dashboard.
Seller Hub increased data-driven decision making and revenues 3.6%; more items transacted and service quality rose without average-price increases; over one-third of impact came from active monitoring.
Management Science · 202410.1287/mnsc.2021.02026Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Duncan I. Simester, Peng Sun, John N. Tsitsiklis (2006). Dynamic Catalog Mailing Policies. Management Science. https://doi.org/10.1287/mnsc.1050.0504.
Plain-English take: The dynamic model received support in the field test, while results also identified opportunities for improvement over the model. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Can dynamic, long-run-aware catalog mailing outperform myopic likelihood-of-immediate-order targeting?
Design: Dynamic mailing-policy model estimated on historical catalog data and evaluated in a large-scale field test.. Large historical sample from a mail-order catalog firm plus field-test customers.
The dynamic model received support in the field test, while results also identified opportunities for improvement over the model.
Management Science · 200610.1287/mnsc.1050.0504Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Jan Roelf Bult, Tom Wansbeek (1995). Optimal Selection for Direct Mail. Marketing Science. https://doi.org/10.1287/mksc.14.4.378.
Plain-English take: Empirical part reports high predictive accuracy and higher net returns than traditional approaches. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which households should receive direct mail when mailing cost and expected return are optimized?
Design: Profit-based target-selection methodology with empirical predictive evaluation.. Household mailing-list population in a direct-mail setting.
Empirical part reports high predictive accuracy and higher net returns than traditional approaches.
Marketing Science · 199510.1287/mksc.14.4.378Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Michael K. Smith, Ruth N. Bolton (2000). An Empirical Investigation of Customer Satisfaction after Service Failure and Recovery. Journal of Service Research. https://doi.org/10.1177/109467050032002.
Plain-English take: Customer satisfaction was lower after failure and recovery—even with high recovery performance—than under error-free service. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Can service recovery restore satisfaction to the level produced by error-free service?
Design: Empirical comparison of satisfaction after service failure/recovery versus error-free service.. Service customers in a failure-and-recovery context; accessible publisher abstract page does not expose sample size or industry.
Customer satisfaction was lower after failure and recovery—even with high recovery performance—than under error-free service.
Journal of Service Research · 200010.1177/109467050032002Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
V. Kumar, George J. R. G. Kannan, R. K. Reinartz (2009). Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2009.02.005.
Plain-English take: Customer satisfaction, marketing effort, cross-buying and multichannel purchasing were positively related to CLV; purchase frequency and monetary value were generally positive but had contradictory findings. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: What empirical generalizations exist in CLV research, and which important CLV questions remain unresolved?
Design: Systematic synthesis of prior empirical CLV studies; identifies effects replicated across at least three author sets.. Published CLV literature across customer, marketing-effort, cross-buying and multichannel settings.
Customer satisfaction, marketing effort, cross-buying and multichannel purchasing were positively related to CLV; purchase frequency and monetary value were generally positive but had contradictory findings.
Journal of Interactive Marketing · 200910.1016/j.intmar.2009.02.005Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Ala' Omar Dandis, Mohammad Badi' Al Haj Eid, Robin Robin, Nathalie Wierdak (2022). An empirical investigation of the factors affecting customer lifetime value. International Journal of Quality & Reliability Management. https://doi.org/10.1108/IJQRM-12-2020-0412.
Plain-English take: Confidence benefits, special-treatment benefits and brand credibility positively affected satisfaction and commitment; brand credibility was most influential toward satisfaction, commitment and ultimately CLV. Functional and technical quality did not significantly affect satisfaction. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which relationship benefits, quality dimensions and brand credibility factors affect satisfaction, commitment and CLV for Internet-service customers?
Design: Online survey (n=481), analyzed with SPSS and SmartPLS, including robustness analysis.. 481 respondents in an Internet-service-provider context in Jordan.
Confidence benefits, special-treatment benefits and brand credibility positively affected satisfaction and commitment; brand credibility was most influential toward satisfaction, commitment and ultimately CLV. Functional and technical quality did not significantly affect satisfaction.
International Journal of Quality & Reliability Management · 202210.1108/IJQRM-12-2020-0412Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Stephen S. Tax, Stephen W. Brown, Murali Chandrashekaran (1998). Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing. Journal of Marketing. https://doi.org/10.1177/002224299806200205.
Plain-English take: Complaint-handling satisfaction was determined by distributive, procedural and interactional justice; the study provides evidence that recovery evaluations shape relationship outcomes. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How do customers evaluate service complaint experiences, and which justice dimensions explain satisfaction and relationship outcomes?
Design: Empirical survey study of customers reporting complaint experiences, testing perceived-justice dimensions.. Customers who had recently complained about a service; the publisher record describes complaint experiences.
Complaint-handling satisfaction was determined by distributive, procedural and interactional justice; the study provides evidence that recovery evaluations shape relationship outcomes.
Journal of Marketing · 199810.1177/002224299806200205Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Ruth N. Bolton, Katherine N. Lemon (1999). A Dynamic Model of Customers' Usage of Services. Journal of Marketing Research. https://doi.org/10.1177/002224379903600203.
Plain-English take: Usage is dynamically related to prior usage and customer perceptions, offering evidence relevant to engagement and retention management. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How do prior usage, service experiences and customer perceptions dynamically shape subsequent service usage?
Design: Dynamic empirical model of service usage over time.. Customers using a continuous service; the publisher record identifies customer usage as the longitudinal outcome.
Usage is dynamically related to prior usage and customer perceptions, offering evidence relevant to engagement and retention management.
Journal of Marketing Research · 199910.1177/002224379903600203Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Daniel Belanche, Luis V. Casaló, Marta Flavián, Sergio Ibáñez-Sánchez (2021). Understanding influencer marketing: The role of congruence between influencers, products and consumers. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2021.03.067.
Plain-English take: Follower–product congruence produced more favorable product attitudes; attitude increased purchase and recommendation intentions. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: When and through what mechanism does congruence among influencer, product, and follower affect responses?
Design: Experiment with followers of a top fashion influencer; factorial manipulation of influencer/product/consumer congruence.. 372 followers of a famous fashion influencer; fashion-product setting.
Follower–product congruence produced more favorable product attitudes; attitude increased purchase and recommendation intentions.
Journal of Business Research · 202110.1016/j.jbusres.2021.03.067Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Daniel Belanche, Luis V. Casaló, Marta Flavián, Sergio Ibáñez-Sánchez (2021). Building influencers' credibility on Instagram: Effects on followers’ attitudes and behavioral responses toward the influencer. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2021.102585.
Plain-English take: The study tests how influencer characteristics build credibility and how credibility relates to follower attitudes and behavioral responses toward the influencer. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which influencer characteristics build credibility, and does credibility translate into favorable attitudes and behavioral responses?
Design: Quantitative survey/structural model of Instagram followers assessing influencer traits and responses.. Instagram users/followers in an influencer-marketing setting.
The study tests how influencer characteristics build credibility and how credibility relates to follower attitudes and behavioral responses toward the influencer.
Journal of Retailing and Consumer Services · 202110.1016/j.jretconser.2021.102585Publisher abstract/metadata retrieved; full text may require access.
Customer behavior and adoptionEvidence check: 3.5/5
Y.A. Argyris, A. Muqaddam, S. Miller (2021). The effects of the visual presentation of an Influencer's Extroversion on perceived credibility and purchase intentions—moderated by personality matching with the audience. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2020.102347.
Plain-English take: The paper tests effects on perceived credibility and purchase intention, with personality matching as a moderator. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Does visually presented influencer extroversion affect credibility and purchase intention, and for whom?
Design: Online experiment manipulating visual presentation of influencer extroversion; moderation by audience personality matching.. Social-media users exposed to influencer presentations and a promoted product.
The paper tests effects on perceived credibility and purchase intention, with personality matching as a moderator.
Journal of Retailing and Consumer Services · 202110.1016/j.jretconser.2020.102347Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Carolina Susilo, others (2021). An Empirical Study on the Impact of E-Commerce Live Features on Consumers’ Purchase Intention: From the Perspective of Flow Experience and Social Presence. Information. https://doi.org/10.3390/info12080324.
Plain-English take: Live features are examined as antecedents of flow experience and social presence, which are linked to purchase intention. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How do e-commerce live features influence purchase intention through flow and social presence?
Design: Empirical questionnaire study using mediation/model testing of live-commerce features, flow, social presence, and purchase intention.. Consumers/users of e-commerce live streams; live-shopping context.
Live features are examined as antecedents of flow experience and social presence, which are linked to purchase intention.
Information · 202110.3390/info12080324Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Ying-Chen Ma, others (2023). Live stream marketing and consumers’ purchase intention: An IT affordance perspective using the S-O-R paradigm. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2023.1069050.
Plain-English take: Trust in products and sellers during live-stream shopping positively correlates with purchase intention; the model tests affordances through S-O-R mechanisms. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which live-stream IT affordances build trust and purchase intention?
Design: Survey-based empirical SEM study of IT affordances, trust, and purchase intention.. 434 valid questionnaires from live-stream-shopping users; 192 male and 242 female respondents, multiple platforms.
Trust in products and sellers during live-stream shopping positively correlates with purchase intention; the model tests affordances through S-O-R mechanisms.
Frontiers in Psychology · 202310.3389/fpsyg.2023.1069050Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Dong Liu, Jing Yu (2022). Impact of perceived diagnosticity on live streams and consumer purchase intention: streamer type, product type, and brand awareness as moderators. Information Technology and Management. https://doi.org/10.1007/s10799-022-00375-7.
Plain-English take: Perceived diagnosticity is tested as a driver of purchase intention, with streamer type, product type, and brand awareness moderating effects. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Does perceived diagnosticity of a live stream increase purchase intention, and under which moderators?
Design: Empirical scenario/online experiment examining perceived diagnosticity with streamer, product, and brand-awareness moderators.. Consumers evaluating live-stream shopping presentations across streamer/product/brand conditions.
Perceived diagnosticity is tested as a driver of purchase intention, with streamer type, product type, and brand awareness moderating effects.
Information Technology and Management · 202210.1007/s10799-022-00375-7Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
R.S. Algharabat, N.P. Rana (2021). Social commerce in emerging markets and its impact on online community engagement. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10041-4.
Plain-English take: The study tests how social commerce affects online community engagement, a growth-relevant behavioral outcome. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How does social commerce generate engagement in online communities in emerging markets?
Design: Empirical survey-based structural model of social-commerce activity and community engagement.. Users/consumers in emerging-market social-commerce settings.
The study tests how social commerce affects online community engagement, a growth-relevant behavioral outcome.
Information Systems Frontiers · 202110.1007/s10796-020-10041-4Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Amy K. Smith, Ruth N. Bolton (1998). An Experimental Investigation of Customer Reactions to Service Failure and Recovery Encounters: Paradox or Peril?. Journal of Service Research. https://doi.org/10.1177/109467059800100106.
Plain-English take: The experiments show that failure/recovery outcomes depend on failure and recovery attributes and customer responses; recovery can improve evaluations, but superior recovery does not uniformly erase the damage of failure. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How do customers react to service failure and recovery encounters, and when does recovery repair evaluations?
Design: Scenario-based experiments manipulating service failure and recovery characteristics; post-encounter evaluations were measured.. Consumers responding to hypothetical service-failure/recovery encounters in two experiments.
The experiments show that failure/recovery outcomes depend on failure and recovery attributes and customer responses; recovery can improve evaluations, but superior recovery does not uniformly erase the damage of failure.
Journal of Service Research · 199810.1177/109467059800100106Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
James G. Maxham III, Richard G. Netemeyer (2002). Modeling Customer Perceptions of Complaint Handling over Time: The Effects of Perceived Justice on Satisfaction and Intent. Journal of Retailing. https://doi.org/10.1016/S0022-4359(02)00100-8.
Plain-English take: Perceived justice affects satisfaction and behavioral intent following failure/recovery; satisfaction partially mediates effects of justice on word of mouth and intent. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How do perceived justice and satisfaction evolve after complaint handling, and how do they shape intent?
Design: Longitudinal/repeated-measures empirical model of customer perceptions following failure and recovery.. Customers evaluating service or product failures and organizational recovery over time.
Perceived justice affects satisfaction and behavioral intent following failure/recovery; satisfaction partially mediates effects of justice on word of mouth and intent.
Journal of Retailing · 200210.1016/S0022-4359(02)00100-8Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Paul Aurier, Blandine Siadou-Martin (2007). Perceived Justice and Consumption Experience Evaluations: A Qualitative and Experimental Investigation. International Journal of Service Industry Management. https://doi.org/10.1108/09564230710826241.
Plain-English take: The study tests how perceived justice shapes evaluations of consumption experiences, extending complaint/service-recovery justice logic to broader service encounters. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How does perceived justice affect consumers’ evaluations of service consumption experiences?
Design: Mixed qualitative and experimental investigation of perceived justice and consumption-experience evaluations.. Service consumers evaluating consumption experiences under experimentally varied justice conditions, informed by qualitative work.
The study tests how perceived justice shapes evaluations of consumption experiences, extending complaint/service-recovery justice logic to broader service encounters.
International Journal of Service Industry Management · 200710.1108/09564230710826241Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Yiting Deng, Christopher S. Tang, Wei Wang, Onesun Steve Yoo (2023). Can Third-Party Sellers Benefit from a Platform’s Entry to the Market?. Service Science. https://doi.org/10.1287/serv.2023.0324.
Plain-English take: After entry, similar third-party sellers charged higher prices, obtained higher demand and earned higher profit; the proposed explanation requires moderate platform potential and sufficient spillover. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Can platform entry benefit incumbent third-party sellers rather than harm them?
Design: Exploratory analysis of seller sales data plus a duopoly/sequential-game model explaining the observed pattern.. JD.com sales data for one product category in March 2018; third-party sellers before/after platform entry.
After entry, similar third-party sellers charged higher prices, obtained higher demand and earned higher profit; the proposed explanation requires moderate platform potential and sufficient spillover.
Service Science · 202310.1287/serv.2023.0324Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Lanfei Shi, Siva Viswanathan (2023). Optional Verification and Signaling in Online Matching Markets: Evidence from a Randomized Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2022.1194.
Plain-English take: High-type men were more likely to verify, while medium-type women were most likely; verified users received more contacts from higher-type users, became more proactive, and voluntary verification facilitated desirable matching outcomes. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Who opts into optional verification, and does visible verification improve matching outcomes?
Design: Randomized field experiment introducing optional, visible verification on an online dating platform without ratings/reviews.. Users on both sides of a leading online dating platform; self-disclosed profiles and voluntary verification.
High-type men were more likely to verify, while medium-type women were most likely; verified users received more contacts from higher-type users, became more proactive, and voluntary verification facilitated desirable matching outcomes.
Information Systems Research · 202310.1287/isre.2022.1194Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Fred D. Davis (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly. https://doi.org/10.2307/249008.
Plain-English take: Perceived usefulness and perceived ease of use were significant determinants of acceptance/usage intention; usefulness was especially influential. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Do perceived usefulness and ease of use explain acceptance of information technology?
Design: Laboratory and field survey studies testing TAM constructs and usage intentions.. Office-automation system users in two empirical studies (reported in the MISQ article).
Perceived usefulness and perceived ease of use were significant determinants of acceptance/usage intention; usefulness was especially influential.
MIS Quarterly · 198910.2307/249008Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
David Gefen, E. Karahanna, Detmar W. Straub (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly. https://doi.org/10.2307/30036519.
Plain-English take: Trust, perceived usefulness and perceived ease of use jointly explained intended online-shopping behavior; trust complemented TAM. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Does trust add explanatory power to TAM for online shopping?
Design: Empirical questionnaire study using structural equation modeling.. Online shoppers evaluating an electronic-commerce website.
Trust, perceived usefulness and perceived ease of use jointly explained intended online-shopping behavior; trust complemented TAM.
MIS Quarterly · 200310.2307/30036519Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Anol Bhattacherjee (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly. https://doi.org/10.2307/3250921.
Plain-English take: Continuance intention was determined by satisfaction with use and perceived usefulness of continued use; confirmation influenced satisfaction and usefulness. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: What cognitive beliefs and affect explain continued rather than initial IS use?
Design: Field survey testing five hypotheses from an expectation-confirmation model.. Online banking users with experience of the system.
Continuance intention was determined by satisfaction with use and perceived usefulness of continued use; confirmation influenced satisfaction and usefulness.
MIS Quarterly · 200110.2307/3250921Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Moez Limayem, Sabine G. Hirt, Chun M. K. Cheung (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Quarterly. https://doi.org/10.2307/25148817.
Plain-English take: Habit moderated the intention–continuance relationship: as habit strengthened, intention became less predictive of continued use. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: When does habit reduce the usefulness of intention for predicting continued IS use?
Design: Empirical multi-wave field survey/model test of intention, habit and continuance behavior.. Information-system users in a field setting, observed across repeated measurement waves.
Habit moderated the intention–continuance relationship: as habit strengthened, intention became less predictive of continued use.
MIS Quarterly · 200710.2307/25148817Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Shirley Taylor, Peter A. Todd (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research. https://doi.org/10.1287/isre.6.2.144.
Plain-English take: The decomposed TPB model provided useful explanatory power for intention and usage; perceived usefulness and social/behavioral determinants were important. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which competing behavioral models best explain IT usage?
Design: Empirical survey comparison of TAM, TPB and decomposed TPB models.. University students using a computer resource centre.
The decomposed TPB model provided useful explanatory power for intention and usage; perceived usefulness and social/behavioral determinants were important.
Information Systems Research · 199510.1287/isre.6.2.144Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Magid Igbaria, Tomas Guimaraes, Gordon B. Davis (1995). Testing the Determinants of Microcomputer Usage via a Structural Equation Model. Journal of Management Information Systems. https://doi.org/10.1080/07421222.1995.11518061.
Plain-English take: Individual, organizational and system-related factors were modeled as determinants of microcomputer usage; perceived usefulness/attitudes were important pathways. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: What individual, organizational and system factors determine microcomputer usage?
Design: Structural-equation analysis of a survey model of microcomputer use.. Microcomputer users in organizational settings.
Individual, organizational and system-related factors were modeled as determinants of microcomputer usage; perceived usefulness/attitudes were important pathways.
Journal of Management Information Systems · 199510.1080/07421222.1995.11518061Publisher abstract/metadata retrieved; full text may require access.
Customer behavior and adoptionEvidence check: 2.5/5
Herlaug Nysveen, Per Egil Pedersen, Helge Thorbjørnsen (2005). Intentions to Use Mobile Services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Science. https://doi.org/10.1177/0092070305276149.
Plain-English take: The four-service empirical results supported motivational influences on intention; the relative importance of antecedents differed across services. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Which motivational, technology- and user-related antecedents explain intentions across mobile services?
Design: Empirical comparative studies testing a model of mobile-service intention across four services.. Consumers considering/using four mobile services.
The four-service empirical results supported motivational influences on intention; the relative importance of antecedents differed across services.
Journal of the Academy of Marketing Science · 200510.1177/0092070305276149Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Niina Mallat (2007). Exploring Consumer Adoption of Mobile Payments – A Qualitative Study. The Journal of Strategic Information Systems. https://doi.org/10.1016/j.jsis.2007.08.001.
Plain-English take: Relative advantage, situational factors and lack of broad merchant acceptance shaped adoption; mobile payment can be adopted when it solves a specific situational need. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: What factors and situations shape consumer adoption of mobile payments?
Design: Exploratory qualitative empirical study using consumer data/interviews about a new electronic payment service.. Consumers considering mobile payments in a Finnish/European service context.
Relative advantage, situational factors and lack of broad merchant acceptance shaped adoption; mobile payment can be adopted when it solves a specific situational need.
The Journal of Strategic Information Systems · 200710.1016/j.jsis.2007.08.001Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
David Godes, Dina Mayzlin (2004). Using Online Conversations to Study Word-of-Mouth Communication. Marketing Science. https://doi.org/10.1287/mksc.1040.0071.
Plain-English take: The geographic dispersion of online conversations is associated with subsequent television ratings; the paper demonstrates how online conversations can measure WOM and predict performance. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: Can online conversations be used as a measurable predictor of WOM and market performance?
Design: Empirical analysis of online conversation data linked to market outcomes, comparing geographically dispersed versus concentrated conversations.. Online discussion/conversation records about television shows, linked to show-level ratings and geographic variation.
The geographic dispersion of online conversations is associated with subsequent television ratings; the paper demonstrates how online conversations can measure WOM and predict performance.
Marketing Science · 200410.1287/mksc.1040.0071Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Arnaud De Bruyn, Gary L. Lilien (2008). A Multi-Stage Model of Word-of-Mouth Influence Through Viral Marketing. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2008.03.004.
Plain-English take: WOM influence differs across stages of recipient decision making; sender characteristics and tie strength affect opening, processing, and forwarding/response. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: At which stages and through which mechanisms does WOM influence viral-marketing recipients?
Design: Empirical survey/experimental test of a staged model of recipient response to viral messages, estimating antecedents at decision stages.. Recipients of viral-marketing communications; message, sender/recipient relationship, and forwarding/response outcomes are measured.
WOM influence differs across stages of recipient decision making; sender characteristics and tie strength affect opening, processing, and forwarding/response.
International Journal of Research in Marketing · 200810.1016/j.ijresmar.2008.03.004Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Sinan Aral, Lev Muchnik, Arun Sundararajan (2009). Distinguishing Influence-Based Contagion from Homophily-Driven Diffusion in Dynamic Networks. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0908800106.
Plain-English take: Naive methods overestimate peer influence by 300–700%; homophily explains more than 50% of perceived contagion in the analyzed adoption network. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.
Question: How much apparent product-adoption contagion is true peer influence versus homophily?
Design: Observational dynamic-network analysis with matching/statistical controls for homophily and contemporaneous adoption.. A large online social network’s mobile-service adoption decisions and user demographic/behavioral similarity.
Naive methods overestimate peer influence by 300–700%; homophily explains more than 50% of perceived contagion in the analyzed adoption network.
Proceedings of the National Academy of Sciences · 200910.1073/pnas.0908800106Publisher record and abstract retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Shiva Agarwal, Cameron D. Miller, Martin Ganco (2023). Growing platforms within platforms: How platforms manage the adoption of complementor products in the presence of network effects?. Strategic Management Journal. https://doi.org/10.1002/smj.3487.
Plain-English take: Apps with direct network effects are more likely to receive an award. The likelihood rises with developer market share but falls in concentrated segments; in concentrated segments, challenger developers are more likely than leaders to receive the award. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How does a platform owner manage adoption of complementor products that have direct network effects, balancing user-growth benefits against the risk of complementor dominance?
Design: Large-scale observational empirical analysis of Apple's app-promotion decisions; the article tests predictions using app-level data and robustness/alternative specifications.. Apple iOS App Store game apps released during 60 months from 2012–2016; the resulting complete-data sample is 211,407 games across 20 categories. The outcome is receipt of Apple's Editors' Choice award; multiplayer games proxy direct network effects, with developer market share and segment concentration as contingencies.
Apps with direct network effects are more likely to receive an award. The likelihood rises with developer market share but falls in concentrated segments; in concentrated segments, challenger developers are more likely than leaders to receive the award.
Strategic Management Journal · 202310.1002/smj.3487Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4.5/5
Johannes Loh, Tobias Kretschmer (2023). Online communities on competing platforms: Evidence from game wikis. Strategic Management Journal. https://doi.org/10.1002/smj.3442.
Plain-English take: A stronger platform competitive position is associated with higher activity, primarily through more contributors, which then triggers greater contributions by existing contributors; high-productivity contributors are especially active on the stronger platform. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Do volunteer online communities create competitive advantage for platforms, and how does platform competitive position affect the extensive and intensive margins of contributor activity?
Design: Quantitative quasi-experimental/event-study design resembling regression discontinuity in time: contributor activity is compared in four days before versus five days after exogenous game updates, with heterogeneous treatment effects by platform compe. 13 game-wiki communities on two competing platforms; the study hand-collected game updates and analyzes 443 distinct updates across games, focusing on volunteer contributors, activity, contributor counts, and productivity.
A stronger platform competitive position is associated with higher activity, primarily through more contributors, which then triggers greater contributions by existing contributors; high-productivity contributors are especially active on the stronger platform.
Strategic Management Journal · 202310.1002/smj.3442Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Javier Cenamor, Johan Frishammar (2021). Openness in platform ecosystems: Innovation strategies for complementary products. Research Policy. https://doi.org/10.1016/j.respol.2020.104148.
Plain-English take: Performance outcomes differ across co-existing innovation strategies. The publisher reports that platform sponsors have an active role in complementary products and that outbound and inbound collaboration may lead to high performance; appropriate strategy depends on platform lifecycle rather than a simple open/closed or sponsor/third-party choice. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: What performance outcomes do alternative innovation and commercialization strategies for complementary products produce, and how do those outcomes evolve across a platform ecosystem's lifecycle?
Design: Panel-data empirical study comparing four complementary-product innovation strategies (proprietary, outbound, inbound, and third-party) and their evolution over time; the publisher page reports performance outcomes across the strategies.. Panel of 4,857 video games for seventh-generation video consoles in the United States; the context is platform ecosystems involving console sponsors and third-party game developers/publishers.
Performance outcomes differ across co-existing innovation strategies. The publisher reports that platform sponsors have an active role in complementary products and that outbound and inbound collaboration may lead to high performance; appropriate strategy depends on platform lifecycle rather than a simple open/closed or sponsor/third-party choice.
Research Policy · 202110.1016/j.respol.2020.104148Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Tommy Pan Fang, Andy Wu, David R. Clough (2021). Platform diffusion at temporary gatherings: Social coordination and ecosystem emergence. Strategic Management Journal. https://doi.org/10.1002/smj.3230.
Plain-English take: Attending temporary hackathon gatherings serves as a social forum for platform diffusion: sponsorship, social learning, knowledge exchange, and social coordination help developers learn about and adopt platforms. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Does attending a temporary gathering such as a hackathon affect software developers' platform choices, and through which social mechanisms does platform adoption diffuse among attendees?
Design: Large-scale quantitative developer-platform-month panel study supported by qualitative research; platform adoption is identified from developers' software projects and analyzed around attendance at hackathons, with channels including sponsorship, soc. 1,302 software developers attending 167 hackathons; the main dataset is a developer-platform-month panel with 786,240 observations, covering January 2012–November 2017 and platform use detected through platform-specific API keywords in public GitHub projects.
Attending temporary hackathon gatherings serves as a social forum for platform diffusion: sponsorship, social learning, knowledge exchange, and social coordination help developers learn about and adopt platforms.
Strategic Management Journal · 202110.1002/smj.3230Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Kichan Nam, Jeff Baker, Norita Ahmad, Jahyun Goo (2020). Determinants of writing positive and negative electronic word-of-mouth: Empirical evidence for two types of expectation confirmation. Decision Support Systems. https://doi.org/10.1016/j.dss.2019.113168.
Plain-English take: Two distinct forms of expectation confirmation, satisfaction, and personal characteristics influence eWOM writing; antecedents differ for negative versus positive eWOM. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: What influences consumers to write positive versus negative eWOM, and do the antecedents differ by eWOM valence?
Design: Survey study extending the expectation-confirmation model; analysis of respondents who wrote hotel reviews on TripAdvisor.. 438 TripAdvisor hotel reviewers, as reported in the publisher highlights and abstract.
Two distinct forms of expectation confirmation, satisfaction, and personal characteristics influence eWOM writing; antecedents differ for negative versus positive eWOM.
Decision Support Systems · 202010.1016/j.dss.2019.113168Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Daehyun Kim, Yongwook Paik, Namil Kim (2025). Digitizing Opportunity: Entrepreneurship in the Age of Platforms. Strategic Entrepreneurship Journal. https://doi.org/10.1002/sej.1538.
Plain-English take: Craigslist entry increases local entrepreneurial activity, especially in low-income regions; lower-income, Black, and immigrant individuals are more likely to create ventures afterward. Post-entry firms are smaller and mainly B2C rather than B2B. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Do digital peer-to-peer marketplaces reduce market-access barriers and increase entrepreneurial activity, and which people, communities, and venture types benefit?
Design: Quasi-experimental study exploiting the staggered entry of Craigslist across metropolitan markets, using Business Dynamics Statistics and supplemental online survey evidence from entrepreneurs.. U.S. metropolitan statistical areas and county-level income/community data; the primary outcome is new firms per 100,000 population per MSA-year. A supplemental survey initially covered 996 U.S. residents with current or past entrepreneurial experience.
Craigslist entry increases local entrepreneurial activity, especially in low-income regions; lower-income, Black, and immigrant individuals are more likely to create ventures afterward. Post-entry firms are smaller and mainly B2C rather than B2B.
Strategic Entrepreneurship Journal · 202510.1002/sej.1538Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Dan J. Kim, Donald L. Ferrin, H. Raghav Rao (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems. https://doi.org/10.1016/j.dss.2007.07.001.
Plain-English take: Trust and perceived risk strongly affected purchasing decisions. Disposition to trust, reputation, privacy concerns, security concerns, website information quality, and company reputation strongly affected trust; a third-party seal did not strongly influence trust. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: What roles do trust and perceived risk play in B2C online purchasing decisions, and what antecedents affect a consumer's trust and risk toward an online transaction?
Design: Structural-equation-model test of a trust-based consumer decision model using Internet purchasing-behavior data collected through a Web survey.. Internet consumers making or considering a purchase from a given B2C Internet site; the publisher abstract identifies the Web-survey consumer context but does not state the sample size on the fetched page.
Trust and perceived risk strongly affected purchasing decisions. Disposition to trust, reputation, privacy concerns, security concerns, website information quality, and company reputation strongly affected trust; a third-party seal did not strongly influence trust.
Decision Support Systems · 200810.1016/j.dss.2007.07.001Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Alain Yee-Loong Chong, Felix T.S. Chan, Keng-Boon Ooi (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems. https://doi.org/10.1016/j.dss.2011.12.001.
Plain-English take: For Malaysian consumers, age, trust, cost, social influence, and variety of services predicted adoption decisions; for Chinese consumers, trust, cost, and social influence predicted adoption. The publisher highlights that traditional TAM variables alone were unable to predict m-commerce adoption and that culture mattered. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Which factors predict consumer intention to adopt mobile commerce, and do the predictors differ between China and Malaysia's cultural settings?
Design: Cross-country quantitative study extending TAM and DOI with trust, cost, social influence, variety of services, and controls; hierarchical regression tested the proposed model.. 394 consumers: 172 Malaysian consumers and 222 Chinese consumers, in a mobile-commerce adoption context.
For Malaysian consumers, age, trust, cost, social influence, and variety of services predicted adoption decisions; for Chinese consumers, trust, cost, and social influence predicted adoption. The publisher highlights that traditional TAM variables alone were unable to predict m-commerce adoption and that culture mattered.
Decision Support Systems · 201210.1016/j.dss.2011.12.001Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Yujong Hwang (2010). The moderating effects of gender on e-commerce systems adoption factors: An empirical investigation. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2010.07.002.
Plain-English take: The influence of social norms on adoption intention was stronger for women, whereas the influence of enjoyment was stronger for men. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How do social norms and perceived enjoyment affect e-commerce-system adoption intention, and do gender differences moderate those effects?
Design: Empirical online-survey study testing social norms, perceived enjoyment, intention to adopt an e-commerce system, and gender moderation using theory of reasoned action and self-determination theory; students navigated Amazon in an Internet-connected . 322 undergraduate business students from a northern U.S. university; participants were approached in an introductory MIS course, used individual PCs, and were asked to navigate Amazon and go through purchasing a book.
The influence of social norms on adoption intention was stronger for women, whereas the influence of enjoyment was stronger for men.
Computers in Human Behavior · 201010.1016/j.chb.2010.07.002Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Thorsten Wiesel, Koen Pauwels, Joep Arts (2011). Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression. Marketing Science. https://doi.org/10.1287/mksc.1100.0612.
Plain-English take: The study found extensive cross-channel effects, direct effects on early and later funnel stages, and substantially higher profit impact for online customer-initiated contacts than offline firm-initiated contacts. A budget-shifting field experiment produced net profit increases 14 times larger than the status-quo allocation. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: What are the effects of marketing communications on online/offline purchase-funnel metrics, and what are the magnitude and timing of profit effects from firm- versus customer-initiated contacts?
Design: Econometric modeling of marketing communication effects on online and offline funnel metrics, followed by a field experiment reallocating marketing budgets.. Inofec, a small-to-medium-sized B2B enterprise; outcomes include website visits, online/offline information activity, quote requests, and purchases, with firm- and customer-initiated contacts compared across channels.
The study found extensive cross-channel effects, direct effects on early and later funnel stages, and substantially higher profit impact for online customer-initiated contacts than offline firm-initiated contacts. A budget-shifting field experiment produced net profit increases 14 times larger than the status-quo allocation.
Marketing Science · 201110.1287/mksc.1100.0612Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Frank M. Bass (1969). A New Product Growth for Model Consumer Durables. Management Science. https://doi.org/10.1287/mnsc.15.5.215.
Plain-English take: The model produced good predictions of the sales peak and its timing when applied to historical data, and provided a long-range color-television sales forecast. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Can the timing of consumers' initial purchases of new durable products be modeled from prior buyers, with innovation and imitation providing the behavioral rationale?
Design: Development and empirical testing of a new-product growth model against historical sales data, separating innovative and imitative purchase behavior; the model is also used for long-range forecasting.. Historical data for eleven consumer durables, with a long-range forecast specifically developed for color television sets.
The model produced good predictions of the sales peak and its timing when applied to historical data, and provided a long-range color-television sales forecast.
Management Science · 196910.1287/mnsc.15.5.215Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3/5
Viswanath Venkatesh, James Y. L. Thong, Xin Xu (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology 1. MIS Quarterly. https://doi.org/10.2307/41410412.
Plain-English take: Adding hedonic motivation, price value, and habit to UTAUT substantially increased explained variance: behavioral intention from 56% to 74% and technology use from 40% to 52%; age, gender, and experience were modeled as moderators. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How can UTAUT be extended to explain consumers' acceptance and use of information technology, including the roles of hedonic motivation, price value, habit, and individual differences?
Design: Two-stage online survey: technology-use data were collected four months after the first survey; the study empirically tests the proposed consumer-context UTAUT2 model.. 1,512 mobile Internet consumers; the publisher abstract identifies the context as consumer acceptance and use of mobile Internet technology.
Adding hedonic motivation, price value, and habit to UTAUT substantially increased explained variance: behavioral intention from 56% to 74% and technology use from 40% to 52%; age, gender, and experience were modeled as moderators.
MIS Quarterly · 201210.2307/41410412Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Zhou Zhou, Lingling Zhang, Marshall Van Alstyne (2024). How Users Drive Value in Two-Sided Markets: Platform Designs That Matter. MIS Quarterly. https://doi.org/10.25300/MISQ/2023/17012.
Plain-English take: Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: When is a user-growth strategy effective, and how do users drive value in a two-sided market?
Design: Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus s. Groupon's largest 108 markets from January through December 2012, with LivingSocial used to control for competition; the publisher page also reports a category-classification survey of 818 respondents covering 78 categories.
Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak.
MIS Quarterly · 202410.25300/MISQ/2023/17012Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Candy K. Y. Ho, Weiling Ke, Hefu Liu, Patrick Y. K. Chau (2020). Separate Versus Joint Evaluation: The Roles of Evaluation Mode and Construal Level in Technology Adoption. MIS Quarterly. https://doi.org/10.25300/MISQ/2020/14246.
Plain-English take: In joint evaluation, higher construal level strengthened the effect of perceived ease of use but weakened perceived usefulness's effect on adoption; in separate evaluation these effects reversed. Thus, simply changing presentation mode can reverse technology choices and preferences. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How do joint versus separate evaluation contexts interact with construal level and technology factors (perceived ease of use and perceived usefulness) to influence technology-adoption decisions?
Design: Two complementary participant studies (N=272 and N=112): Study 1 was conducted in two natural settings, while Study 2 randomly assigned participants to manipulated joint-versus-separate evaluation modes.. Participants evaluated two new e-learning systems, either jointly (JE) or separately (SE); the publisher page reports N=272 and N=112 for the two studies.
In joint evaluation, higher construal level strengthened the effect of perceived ease of use but weakened perceived usefulness's effect on adoption; in separate evaluation these effects reversed. Thus, simply changing presentation mode can reverse technology choices and preferences.
MIS Quarterly · 202010.25300/MISQ/2020/14246Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Miguel Godinho de Matos, Pedro Ferreira, David Krackhardt (2014). Peer Influence in the Diffusion of iPhone 3G over a Large Social Network. MIS Quarterly. https://doi.org/10.25300/MISQ/2014/38.4.08.
Plain-English take: A subscriber's adoption propensity increased with the percentage of friends who had already adopted. The authors estimate that peer influence accounted for 14% of iPhone 3Gs sold by the carrier during the 11-month period; their policy experiments suggest traditional seeding for viral marketing would have yielded little benefit at this effect level. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How much does peer influence affect iPhone 3G adoption in a large social network, and would seeding the product produce useful viral-marketing benefits?
Design: Observational diffusion study using a large mobile-carrier dataset, tight-community identification, and instrumental variables to address correlation between unobserved subscriber heterogeneity and friends' adoption; the authors also report policy ex. Communities sampled from a large dataset supplied by a major European mobile carrier in one country, tracking iPhone 3G diffusion for 11 months; controls include social clustering, gender, prior mobile-Internet-plan adoption, advanced-handset ownership, and regional mobility.
A subscriber's adoption propensity increased with the percentage of friends who had already adopted. The authors estimate that peer influence accounted for 14% of iPhone 3Gs sold by the carrier during the 11-month period; their policy experiments suggest traditional seeding for viral marketing would have yielded little benefit at this effect level.
MIS Quarterly · 201410.25300/MISQ/2014/38.4.08Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Michael Rivera, Xue Guo, Guohou Shan, Liangfei Qiu (2026). Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-Time Mobile Feedback Platform. MIS Quarterly. https://doi.org/10.25300/MISQ/2025/18920.
Plain-English take: Task-significance messaging generated more and higher-quality feedback than generic prompts. Timing amplified the effect only when task-significance messaging was present; the follow-up experiment linked timing to lower cognitive load and task significance to greater germane load and external motivation, with effects varying by role. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: How do digital-nudge timing and task-significance messaging, separately and jointly, affect the quantity and quality of employee feedback in a real-time feedback application, and through what mechanisms?
Design: Field experiment on digital-nudge timing and task-significance messaging in a real-time feedback application, followed by a randomized online experiment to examine mechanisms.. Employees using a real-time mobile feedback platform; the publisher abstract distinguishes managers and associates as feedback givers and receivers but does not state sample sizes on the fetched page.
Task-significance messaging generated more and higher-quality feedback than generic prompts. Timing amplified the effect only when task-significance messaging was present; the follow-up experiment linked timing to lower cognitive load and task significance to greater germane load and external motivation, with effects varying by role.
MIS Quarterly · 202610.25300/MISQ/2025/18920Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 2.5/5
Elias Baumann, Jana Kern, Stefan Lessmann (2022). Usage Continuance in Software-as-a-Service. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10065-w.
Plain-English take: Several proactive activation measures positively affect usage penetration, while software and client characteristics do not display significant estimates; the authors emphasize proactive activation initiatives to raise usage penetration. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Which vendor activation measures and software/client characteristics increase continued usage (usage penetration) of SaaS applications after initial adoption?
Design: Longitudinal observational study using data from a SaaS vendor and a linear mixed model to analyze measures intended to improve continued usage over time.. A SaaS vendor's application usage over time, including vendor activation measures and software/client characteristics; the publisher abstract does not report the number of customers or observations.
Several proactive activation measures positively affect usage penetration, while software and client characteristics do not display significant estimates; the authors emphasize proactive activation initiatives to raise usage penetration.
Information Systems Frontiers · 202210.1007/s10796-020-10065-wPublisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 4/5
Manpreet Gill, Shrihari Sridhar, Rajdeep Grewal (2017). Return on Engagement Initiatives: A Study of a Business-to-Business Mobile App. Journal of Marketing. https://doi.org/10.1509/jm.16.0149.
Plain-English take: App adoption increased the manufacturer's annual sales revenue by 19.11%–22.79%; return on engagement remained positive after development costs, and was higher when buyers created more projects in the app. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.
Question: Can a B2B mobile-app engagement initiative generate measurable sales returns, and how does customer participation intensity explain return on engagement?
Design: Quasi-experimental difference-in-differences study with selection on observables and unobservables, comparing buyer firms that adopted a manufacturer's free B2B mobile app with a non-adopting control group over 15 months.. A tool manufacturer's business buyers and their sales records; the app was offered free to engage buyers, and buyer participation intensity was measured through projects created in the app.
App adoption increased the manufacturer's annual sales revenue by 19.11%–22.79%; return on engagement remained positive after development costs, and was higher when buyers created more projects in the app.
Journal of Marketing · 201710.1509/jm.16.0149Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
Customer behavior and adoptionEvidence check: 3.5/5
Liu Fan, Shanshan Li, Can Wang, Xiaoping Zhang (2026). Journal of Theoretical and Applied Electronic Commerce Research.
Plain-English take: Humans generally outperform chatbots for symbolic loss, where emotional support matters, while the difference diminishes for utilitarian loss. Recovery-agent effects depend on failure severity: for low-severity failures human recovery is more effective, whereas the paper reports different comparative effects under high severity. The results caution against treating chatbot recovery as universally superior. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do recovery agent (human versus chatbot), consumer-loss type (utilitarian versus symbolic) and service-failure severity interact to influence consumer forgiveness?
Design: Full-text empirical research; three scenario-based between-subjects experiments. Chinese online participants recruited through Wenjuanxing. Study 1: 270 recruited, 30 excluded, 240 valid (mean age 24.89; 59.7% female). Study 2: 566 recruited, 46 excluded, 520 valid (mean age 23.72; 65% female). The full paper reports Study 3's sample and setting separately.
Humans generally outperform chatbots for symbolic loss, where emotional support matters, while the difference diminishes for utilitarian loss. Recovery-agent effects depend on failure severity: for low-severity failures human recovery is more effective, whereas the paper reports different comparative effects under high severity. The results caution against treating chatbot recovery as universally superior.
Journal of Theoretical and Applied Electronic Commerce Research · 202610.3390/jtaer21010035Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3.5/5
Ning Ma, Ruslana Khynevych, Yunqiang Hao, Yahui Wang (2025). Frontiers in Computer Science.
Plain-English take: Direct effects of anthropomorphism and perceived intelligence on UX were nonsignificant in the abstract, while the full paper reports anthropomorphism improving UX through perceived empathy and trust and an interaction in which higher perceived intelligence helps when anthropomorphism is high but can reduce UX when anthropomorphism is low. The results emphasize emotional engagement rather than intelligence alone. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do visual anthropomorphism and perceived intelligence in chatbot avatars affect user experience, and do perceived empathy and trust mediate those effects?
Design: Full-text original research; 2×2 within-subjects experiment with mediation/structural equation modeling. In-person experiment at Beijing Institute of Technology. 179 people participated; after 19 exclusions, 160 valid participants remained (101 female, 59 male; mean age 26, SD 5). Recruitment required chatbot interaction at least five times daily for the prior three months; participants received approximately RMB 200 gift cards.
Direct effects of anthropomorphism and perceived intelligence on UX were nonsignificant in the abstract, while the full paper reports anthropomorphism improving UX through perceived empathy and trust and an interaction in which higher perceived intelligence helps when anthropomorphism is high but can reduce UX when anthropomorphism is low. The results emphasize emotional engagement rather than intelligence alone.
Frontiers in Computer Science · 202510.3389/fcomp.2025.1531976Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3.5/5
Nishad Nawaz, Hemalatha Arunachalam, Barani Kumari Pathi, Vijayakumar Gajender (2024). International Journal of Information Management Data Insights.
Plain-English take: Accuracy, computing power/capacity, and personalization significantly influence time-saving and cost reduction; automation and real-time experience do not significantly influence that outcome. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which AI-technology characteristics—accuracy, automation, computing power/capacity, real-time experience, and personalization—affect time-saving and cost reduction in HRM practice adoption?
Design: Empirical quantitative survey study. 274 IT employees in Chennai City; online questionnaire. The abstract does not state organizational sectors, sampling method, demographics, or whether respondents were HR users.
Accuracy, computing power/capacity, and personalization significantly influence time-saving and cost reduction; automation and real-time experience do not significantly influence that outcome.
International Journal of Information Management Data Insights · 202410.1016/j.jjimei.2023.100208Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3.5/5
Lez Trujillo-Torres, Eda Anlamlier, Laetitia Mimoun, Lagnajita Chatterjee, Delphine Dion (2023). Journal of the Academy of Marketing Science.
Plain-English take: Access-based journeys are systemic, tightly coupled and vulnerable to circularity failures; customers act as prosumers and bypass, stretch or hack platform policies to personalize journeys. Job crafting can create individual value and collective problems, but can also reveal innovations that platforms may formalize. Managers therefore need agility and monitoring rather than assuming a fully controllable linear journey. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do customers shape access-based platform journeys through prosumption/job crafting, and what are the implications for managing digital platform journeys?
Design: Full-text qualitative longitudinal, multi-method customer-journey study. US access-based fashion-rental platform Rent the Runway. Interview participants were all women, average age 34, recruited through convenience/snowball sampling; most had Unlimited memberships. The study also analyzes bloggers and platform/marketplace documentary and social-media material; the publisher/open paper should be consulted for the complete corpus details.
Access-based journeys are systemic, tightly coupled and vulnerable to circularity failures; customers act as prosumers and bypass, stretch or hack platform policies to personalize journeys. Job crafting can create individual value and collective problems, but can also reveal innovations that platforms may formalize. Managers therefore need agility and monitoring rather than assuming a fully controllable linear journey.
Journal of the Academy of Marketing Science · 202310.1007/s11747-023-00942-6Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3.5/5
Arpita Agnihotri, Saurabh Bhattacharya (2023). International Journal of Information Management.
Plain-English take: Perceived safety, empathy and anthropomorphism affect different components of chatbot trustworthiness; trustworthiness increases willingness to forgive after failure and reduces negative word of mouth. The paper highlights privacy concerns as a countervailing issue and finds chatbot traits work through trust-related mechanisms rather than as undifferentiated design features. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which chatbot traits make chatbot-led service recovery effective, and through what mechanisms do they reduce negative consumer responses after service failure?
Design: Mixed-method empirical research (scenario-based quantitative studies plus exploratory and qualitative work). The main final survey sample was 586 UK consumers (304 women; median age 31.02; median income £32,000) responding to an online-retailing delayed-order recovery scenario. The exploratory work included 28 postgraduate students; the paper also reports a separate qualitative study (the publisher page contains its method/results).
Perceived safety, empathy and anthropomorphism affect different components of chatbot trustworthiness; trustworthiness increases willingness to forgive after failure and reduces negative word of mouth. The paper highlights privacy concerns as a countervailing issue and finds chatbot traits work through trust-related mechanisms rather than as undifferentiated design features.
International Journal of Information Management · 202310.1016/j.ijinfomgt.2023.102679Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 2.5/5
Samuel Godadaw Ayinaddis (2025). Journal of Innovation & Knowledge.
Plain-English take: The review addresses fragmented evidence and compares tools, implementation and outcomes across firm sizes; detailed synthesized results require the full paper. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do AI-adoption dynamics and knowledge differ between SMEs and large firms?
Design: Abstract-supported systematic review and bibliometric analysis. Published literature on SMEs and larger firms; the accessible publisher page does not state the final article count in the scraped excerpt.
The review addresses fragmented evidence and compares tools, implementation and outcomes across firm sizes; detailed synthesized results require the full paper.
Journal of Innovation & Knowledge · 202510.1016/j.jik.2025.100682Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 2.5/5
Rafael Katz, Joon Jung (2026). Digital Policy, Regulation and Governance.
Plain-English take: Company size positively influenced AI adoption and use; digitized environments increased adoption likelihood through network effects; competition intensity had a nonlinear effect that initially stimulated adoption. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which firm and environmental factors predict AI adoption, diffusion within firms and intensity of use?
Design: Abstract-supported quantitative empirical study. Brazilian enterprises; the accessible abstract does not report the microdata sample size.
Company size positively influenced AI adoption and use; digitized environments increased adoption likelihood through network effects; competition intensity had a nonlinear effect that initially stimulated adoption.
Digital Policy, Regulation and Governance · 202610.1108/DPRG-05-2025-0135Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 3.5/5
Dilupa Nakandala, Richard (Chunhui) Yang, Arun Elias, Rola Fanous (2024). Journal of Cleaner Production.
Plain-English take: The study empirically links managers’ digital expertise and environmental consciousness to technology-adoption intentions; the accessible abstract does not expose the complete coefficient pattern. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do managers’ digital expertise and environmental consciousness affect intentions to adopt Industry 4.0 technologies?
Design: Full-text open-access quantitative survey study. 172 managers; Industry 4.0 organizational context.
The study empirically links managers’ digital expertise and environmental consciousness to technology-adoption intentions; the accessible abstract does not expose the complete coefficient pattern.
Journal of Cleaner Production · 202410.1016/j.jclepro.2024.143558Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3/5
Chathurika S. Ahmad, A. S. Bali Mahomed, H. Hashim (2026). Business Process Management Journal.
Plain-English take: Information quality and service quality significantly enhanced perceived business-process performance; system quality did not have a meaningful direct effect; perceived AI usefulness amplified the effects of system and information quality. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How does cloud-computing quality affect perceived business-process performance in SMEs, and does perceived AI usefulness moderate those effects?
Design: Abstract-supported quantitative empirical study. 412 SMEs in Pakistan.
Information quality and service quality significantly enhanced perceived business-process performance; system quality did not have a meaningful direct effect; perceived AI usefulness amplified the effects of system and information quality.
Business Process Management Journal · 202610.1108/BPMJ-01-2025-0103Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 2.5/5
S. Kumar, B. Ramtiyal, G. Soni, L. Vijayvargy, C. Chandra, I. Dey (2026). Benchmarking: An International Journal.
Plain-English take: Optimism and innovativeness did not affect perceived ease of use or utility; behavioral intention was shaped by perceived utility, attitude and perceived behavioral control. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which technology-readiness, TAM and planned-behavior factors shape traceability adoption in perishable-product supply chains?
Design: Abstract-supported quantitative empirical study. Perishable-products supply-chain participants; accessible abstract reports an online survey but not the sample size.
Optimism and innovativeness did not affect perceived ease of use or utility; behavioral intention was shaped by perceived utility, attitude and perceived behavioral control.
Benchmarking: An International Journal · 202610.1108/BIJ-05-2024-0461Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 3/5
J. Kumar, G. Rani, M. Rani, V. Rani (2024). Journal of Enterprising Communities: People and Places in the Global Economy.
Plain-English take: Relative advantage, top-management support, competitive pressure and market dynamics significantly influenced blockchain adoption; the paper also tests adoption’s relationship with SME market and financial performance. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which TOE/RBV factors predict blockchain adoption in SMEs, and how does adoption relate to market and financial performance?
Design: Abstract-supported quantitative empirical study. 407 SME responses from India.
Relative advantage, top-management support, competitive pressure and market dynamics significantly influenced blockchain adoption; the paper also tests adoption’s relationship with SME market and financial performance.
Journal of Enterprising Communities: People and Places in the Global Economy · 202410.1108/JEC-02-2024-0034Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 3.5/5
Ranim Khojah, Mazen Mohamad, Philipp Leitner, Francisco Gomes de Oliveira Neto (2024). ACM Transactions on Software Engineering and Methodology.
Plain-English take: Practitioners more often sought guidance or learning than ready-to-use software artifacts; simple artifact generation and brainstorming were useful, complex tasks were harder; about two-thirds expressed high or moderate trust but none trusted outputs entirely, and lack of sources reduced trust. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do professional software engineers use ChatGPT in daily work, and what factors shape perceived usefulness and trust?
Design: Full-text observational qualitative empirical study. 24 professional software engineers at 10 companies in Europe, using GPT-3.5 over five business days.
Practitioners more often sought guidance or learning than ready-to-use software artifacts; simple artifact generation and brainstorming were useful, complex tasks were harder; about two-thirds expressed high or moderate trust but none trusted outputs entirely, and lack of sources reduced trust.
ACM Transactions on Software Engineering and Methodology · 202410.1145/3660788Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3/5
Ololade A. Shonubi (2025). Sustainable Futures.
Plain-English take: Emerging-technology integration was positively related to organizational, process and product/service innovation across both continents; African enterprises showed stronger process-innovation adaptability despite infrastructure limits; gender differences affected product/service-innovation perceptions. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How does emerging-technology integration relate to organizational, process and product/service innovation as organizations transition from legacy systems?
Design: Full-text open-access quantitative empirical study. Managers from enterprises across Asian and African contexts; accessible abstract does not report sample size.
Emerging-technology integration was positively related to organizational, process and product/service innovation across both continents; African enterprises showed stronger process-innovation adaptability despite infrastructure limits; gender differences affected product/service-innovation perceptions.
Sustainable Futures · 202510.1016/j.sftr.2025.100971Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3.5/5
Justine Dima, Julie Dextras-Gauthier, Laurent Giraud (2024). Frontiers in Psychology.
Plain-English take: Synthesizes five main AI effects on HR activities and maps opportunities/challenges across the HR triad; highlights automation, decision support, bias/ethics, changing roles and need for multilevel research. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: What does the peer-reviewed literature show about AI’s effects on HR activities and the roles of employees, line managers and HR professionals?
Design: Full-text scoping review/evidence synthesis. 43 articles across 38 journals covering eight HR activity categories; 95.7% intercoder agreement on 20% of coded studies.
Synthesizes five main AI effects on HR activities and maps opportunities/challenges across the HR triad; highlights automation, decision support, bias/ethics, changing roles and need for multilevel research.
Frontiers in Psychology · 202410.3389/fpsyg.2024.1360401Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 3/5
Meenal Arora, Amit Mittal (2025). Benchmarking: An International Journal.
Plain-English take: Perceptions of AI’s effects on talent acquisition, training/development, performance assessment and pay/rewards predicted adoption intention; AI-tech trust positively mediated the tested relationships. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do employees’ perceptions of AI-enabled changes in HR functions affect intention to adopt AI, and does AI-tech trust mediate the relationships?
Design: Abstract-supported quantitative empirical study. 264 HR professionals from Indian e-commerce organizations.
Perceptions of AI’s effects on talent acquisition, training/development, performance assessment and pay/rewards predicted adoption intention; AI-tech trust positively mediated the tested relationships.
Benchmarking: An International Journal · 202510.1108/BIJ-11-2023-0795Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 3.5/5
Mohammad Pedrami, Seyed Kamal Vaezi (2026). Journal of Work-Applied Management.
Plain-English take: Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: Which multidimensional factors influence AI adoption in HRM?
Design: Full-text open-access qualitative meta-synthesis/systematic review. Peer-reviewed AI-in-HRM studies published 2015–2023; the accessible article synthesizes the selected literature rather than a new respondent sample.
Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent.
Journal of Work-Applied Management · 202610.1108/JWAM-10-2024-0158Full text retrieved from publisher or linked open repository
Customer behavior and adoptionEvidence check: 2.5/5
Ying Sin Chin, Abang Azlan Mohamad, May Chiun Lo (2026). Global Knowledge, Memory and Communication.
Plain-English take: Three of five hypotheses were supported: AI adoption positively related to sustainable employee performance; HRM practices and digital culture also positively related to performance; AI did not moderate the HRM–performance link and AI adoption was not associated with digital culture. For a founder, use this as a question to test in your own context, not a universal playbook.
Question: How do AI adoption, organizational digital culture and HRM practices relate to sustainable employee performance in Malaysian luxury hotels?
Design: Abstract-supported quantitative empirical study. Luxury hotels in Malaysia; the accessible abstract does not report the respondent n.
Three of five hypotheses were supported: AI adoption positively related to sustainable employee performance; HRM practices and digital culture also positively related to performance; AI did not moderate the HRM–performance link and AI adoption was not associated with digital culture.
Global Knowledge, Memory and Communication · 202610.1108/GKMC-06-2024-0355Publisher abstract/metadata retrieved; full text not reviewed
Customer behavior and adoptionEvidence check: 4.5/5
Noy, S. & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science.
Plain-English take: In this study, ChatGPT reduced average time by 40% and raised output quality by 18%; inequality fell, and exposed workers were 2 times as likely to report real-job use two weeks later and 1.6 times as likely two months later. Founder use: Evaluate AI features with randomized task-level tests that include quality and time, then measure sustained adoption rather than assuming a novelty effect equals retention.
Question: What is the causal effect of ChatGPT access on productivity, quality, inequality, and subsequent workplace adoption in professional writing tasks?
Design: Preregistered online randomized experiment with incentivized, occupation-specific writing tasks.. 453 college-educated professionals performing midlevel professional writing tasks; half were randomly exposed to ChatGPT.
ChatGPT reduced average time by 40% and raised output quality by 18%; inequality fell, and exposed workers were 2 times as likely to report real-job use two weeks later and 1.6 times as likely two months later.
Science · 202310.1126/science.adh2586Publisher abstract or article landing page captured; full text access not established
Customer behavior and adoptionEvidence check: 4.5/5
Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at Work. The Quarterly Journal of Economics.
Plain-English take: In this study, Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase. Founder use: Prioritize AI copilot deployment where onboarding and experience gaps are largest; track quality, customer sentiment, escalation, and retention together.
Question: What happens when a generative-AI conversational assistant is introduced into real customer-support work, and who benefits most?
Design: Quasi-experimental staggered introduction using workplace operational data.. 5,172 customer-support agents using a conversational assistant in their work.
Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase.
The Quarterly Journal of Economics · 202510.1093/qje/qjae044Open working paper PDF captured from arXiv
Customer behavior and adoptionEvidence check: 4.5/5
Dell'Acqua, F., III, E. M., Mollick, E., Lifshitz, H., Kellogg, K. C., Rajendran, S., Krayer, L., & Candelon, F. (2026). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality. Organization Science.
Plain-English take: In this study, Within the AI capability frontier, AI users completed 12.2% more tasks, 25.1% faster, with higher quality; on an out-of-frontier managerial task they were 19% less likely to be correct. Founder use: Design AI product analytics around task-level success and verification, not aggregate usage; expose where the model helps and require review where it can degrade decisions.
Question: When does GPT-4 improve versus degrade the productivity and quality of complex knowledge work?
Design: Preregistered randomized controlled laboratory-in-the-field experiment, with realistic consulting tasks and a no-AI, GPT-4, and GPT-4-plus-prompt-engineering condition.. 758 knowledge workers performing 18 realistic management-consulting tasks developed with Boston Consulting Group, plus a separate out-of-frontier managerial task.
Within the AI capability frontier, AI users completed 12.2% more tasks, 25.1% faster, with higher quality; on an out-of-frontier managerial task they were 19% less likely to be correct.
Organization Science · 202610.1287/orsc.2025.21838Open full text captured directly
Customer behavior and adoptionEvidence check: 4.0/5
Alfaro-Serrano, D., Balantrapu, T., Chaurey, R., Goicoechea, A., & Verhoogen, E. (2021). Interventions to promote technology adoption in firms: A systematic review. Campbell Systematic Reviews.
Plain-English take: Some interventions produced positive technology-adoption effects, but results varied substantially by context and methodology. Effects on profits, productivity, employment, and farm yields were mixed; the review could not identify one universally superior intervention. For a SaaS founder: Use the review as a reason to run context-specific experiments: compare guided onboarding, training, incentives, peer learning, and support while measuring activated accounts and sustained usage. Do not assume a successful intervention in one customer segment transfers to another.
Question: Which types of intervention have been evaluated to promote technology adoption in firms, and how consistent are their effects?
Design: Campbell systematic review of experimental and quasi-experimental evaluations of exogenous incentives/interventions affecting firm technology adoption; standardized effects were synthesized across included studies.. Firms in manufacturing, services, and agriculture across varied countries and contexts; the review reports 1,108 regression coefficients from selected studies and separately analyzes sectors. It does not describe one single pooled SaaS sample.
Some interventions produced positive technology-adoption effects, but results varied substantially by context and methodology. Effects on profits, productivity, employment, and farm yields were mixed; the review could not identify one universally superior intervention.
Campbell Systematic Reviews · 202110.1002/cl2.1181Open full text directly retrieved
Customer behavior and adoptionEvidence check: 4.0/5
Blut, M., Chowdhry, N., Mittal, V., & Brock, C. (2015). E-Service Quality: A Meta-Analytic Review. Journal of Retailing, 91(4), 679-700.
Plain-English take: E-service-quality dimensions have meaningful relationships with customer evaluations and behavioral outcomes, but effects depend on measurement and context. Founder-use interpretation: Use as a measurement/design checklist for onboarding and support, then validate which service-quality dimensions predict SaaS activation, expansion, and renewal in your segment.
Question: Which dimensions of e-service quality relate to customer evaluations and behavioral outcomes across online-service research?
Design: Peer-reviewed empirical study or research synthesis. Meta-analytic review synthesizing empirical e-service-quality research across online service settings.
E-service-quality dimensions have meaningful relationships with customer evaluations and behavioral outcomes, but effects depend on measurement and context.
Journal of Retailing, 91(4), 679-700 · 201510.1016/j.jretai.2015.05.004Publisher abstract or article landing page captured; full-text access not established.