Academic Research
Negative Feedback from Robots Is Received Better than That from Humans: The Effect of Feedback on Human–robot Trust and Collaboration
Intelligent robots continue to transcend their traditional roles as mere tools, evolving to actively engage in collaborative teamwork. Feedback from teammates is a critical component of effective team dynamics. This research investigates how feedback source (robot vs. human teammate) affects behavioral trust and intention for future collaboration through a functional task (Study 1) and a social task (Study 2). It further examines the mediating role of feedback acceptance and the moderating effect of feedback valence (positive vs. negative). The findings reveal that negative feedback from a robot teammate, compare to that from a human teammate, leads to a higher feedback acceptance, which further fosters greater behavioral trust and intention for future collaboration toward the robot. However, the source of positive feedback, whether from a robot or a human teammate, causes no significant differences in recipients’ responses. This research delineates the potential advantages of future robot colleagues in delivering negative feedback.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115333
Authors: Hongzhou Xuan, Guibing He
ABSTRACT
Intelligent robots continue to transcend their traditional roles as mere tools, evolving to actively engage in collaborative teamwork. Feedback from teammates is a critical component of effective team dynamics. This research investigates how feedback source (robot vs. human teammate) affects behavioral trust and intention for future collaboration through a functional task (Study 1) and a social task (Study 2). It further examines the mediating role of feedback acceptance and the moderating effect of feedback valence (positive vs. negative). The findings reveal that negative feedback from a robot teammate, compare to that from a human teammate, leads to a higher feedback acceptance, which further fosters greater behavioral trust and intention for future collaboration toward the robot. However, the source of positive feedback, whether from a robot or a human teammate, causes no significant differences in recipients’ responses. This research delineates the potential advantages of future robot colleagues in delivering negative feedback.
Imitation: Mitigating AI backfire
Previous research suggests that artificial intelligence (AI) influences organizational resources through automation and augmentation. We extend this perspective by identifying backfire effects, driven primarily by technological uncertainty in AI implementation. We propose that imitation strategies can help microenterprises mitigate these challenges. Using a simulation methodology, the findings indicate that imitation is more effective than non-imitation in addressing AI’s backfire effects on microenterprises. Specifically, imitating enterprises within the same size category yields greater advantages than imitating top entities across all categories, with the most effective strategy being to follow the leading entities of the same size. This study contributes to the literature on AI’s dark side and imitation strategies, providing a strategic direction for microenterprises to manage AI-related uncertainties.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115331
Authors: Fan Zhang, Jieyi Pan
ABSTRACT
Previous research suggests that artificial intelligence (AI) influences organizational resources through automation and augmentation. We extend this perspective by identifying backfire effects, driven primarily by technological uncertainty in AI implementation. We propose that imitation strategies can help microenterprises mitigate these challenges. Using a simulation methodology, the findings indicate that imitation is more effective than non-imitation in addressing AI’s backfire effects on microenterprises. Specifically, imitating enterprises within the same size category yields greater advantages than imitating top entities across all categories, with the most effective strategy being to follow the leading entities of the same size. This study contributes to the literature on AI’s dark side and imitation strategies, providing a strategic direction for microenterprises to manage AI-related uncertainties.
Leveraging Machine Learning and Generative AI for Content Engagement: An Exploration of Drivers for the Success of YouTube Videos
Digital content creation has exploded in the last decade offering immense opportunities for brands and content creators. However, more research is needed on textual and aural content for determining video success using video analytics. Yet, data collection and analysis in this research context are labor-intensive. This study leveraged Generative AI (GenAI) models to automatically extract video transcripts and extract relevant metrics. We examined over 1055 YouTube videos released between 2021 and 2023 across three popular smartphones. We extracted semantic metrics from the transcript and comments to build models to explore the drivers of video success. We compared various GenAI-based measures and compared them to traditional methods. The results from this study confirm the superior performance of GPT4 over the benchmarks. The study’s theoretical contributions to the field of video-based content management and the managerial implications for practitioners in the field of video analytics are discussed.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115330
Authors: Arindra Nath Mishra, Pooja Sengupta, Baidyanath Biswas, Ajay Kumar, Kristof Coussement
ABSTRACT
Digital content creation has exploded in the last decade offering immense opportunities for brands and content creators. However, more research is needed on textual and aural content for determining video success using video analytics. Yet, data collection and analysis in this research context are labor-intensive. This study leveraged Generative AI (GenAI) models to automatically extract video transcripts and extract relevant metrics. We examined over 1055 YouTube videos released between 2021 and 2023 across three popular smartphones. We extracted semantic metrics from the transcript and comments to build models to explore the drivers of video success. We compared various GenAI-based measures and compared them to traditional methods. The results from this study confirm the superior performance of GPT4 over the benchmarks. The study’s theoretical contributions to the field of video-based content management and the managerial implications for practitioners in the field of video analytics are discussed.
The Effect of Stress on Compliance With Health-Related Advertising
Given the growing importance of health-related advertising, in our research we examined how the persuasiveness of health-related advertisements is affected by a new antecedent: stress, a universal and draining experience. A series of five studies (including one survey and four experiments) revealed that people are more willing to comply with health-related advertising when they feel stressed. This is because stress increases consumers’ tendency to avoid risk, which consequently prompts their compliance with health-related advertising. Moreover, consumers’ promotion focus was found to be a boundary condition for the effect of stress on compliance with health-related advertising, with the effect being weaker among promotion-focused consumers. Our findings not only reveal a novel variable that could promote health compliance but also suggest what marketers should do to bolster the effectiveness of health-related advertising.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115328
Authors: Sheng Bi, Menglin Li
ABSTRACT
Given the growing importance of health-related advertising, in our research we examined how the persuasiveness of health-related advertisements is affected by a new antecedent: stress, a universal and draining experience. A series of five studies (including one survey and four experiments) revealed that people are more willing to comply with health-related advertising when they feel stressed. This is because stress increases consumers’ tendency to avoid risk, which consequently prompts their compliance with health-related advertising. Moreover, consumers’ promotion focus was found to be a boundary condition for the effect of stress on compliance with health-related advertising, with the effect being weaker among promotion-focused consumers. Our findings not only reveal a novel variable that could promote health compliance but also suggest what marketers should do to bolster the effectiveness of health-related advertising.
Using Generative Artificial Intelligence (Genai) in Marketing: Development and Practices
Generative artificial intelligence (GenAI) is an emerging topic in business research and marketing. This study discusses and classifies the applications of GenAI in the field of marketing. To be specific, this study first conducts a systematic literature search to learn about development on the topic of GenAI in marketing. Then, the collected articles are classified into four major themes, namely (i) applications, adoption and concerns of consumers toward GenAI, (ii) service, (iii) advertising, and (iv) innovation. Next, we discuss the related industrial practices to highlight the current real-world applications of GenAI in various major industries to support marketing activities. Finally, based on the reviewed literature and observed real-world practices, we propose a promising future research agenda that lays the foundation for further studies in the area.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115276
Authors: Hau-Ling Chan, Tsan-Ming Choi
ABSTRACT
Generative artificial intelligence (GenAI) is an emerging topic in business research and marketing. This study discusses and classifies the applications of GenAI in the field of marketing. To be specific, this study first conducts a systematic literature search to learn about development on the topic of GenAI in marketing. Then, the collected articles are classified into four major themes, namely (i) applications, adoption and concerns of consumers toward GenAI, (ii) service, (iii) advertising, and (iv) innovation. Next, we discuss the related industrial practices to highlight the current real-world applications of GenAI in various major industries to support marketing activities. Finally, based on the reviewed literature and observed real-world practices, we propose a promising future research agenda that lays the foundation for further studies in the area.
Consumer Confusion: A Meta-analytic Review
Consumer confusion is a state of mind that occurs when consumers encounter a large number of options or information overload, making it difficult for them to make a confident and informed purchasing decision. This study summarises the consumer confusion literature to analyse the links between the constructs examined in this literature domain. The findings suggest that various information, consumer, and product-related factors prompt consumer confusion which engenders negative consumer responses. Moderation analysis indicates that differences in six methodological factors (research methods, sample type, country, gender dominance, survey administration method, and sample size) and five contextual moderators (price consciousness, industry type, customer involvement, cultural perspectives, and store type) across the studies contribute to inconsistent findings regarding the relationships between the constructs examined in the consumer confusion domain. Theoretically, being the first meta-analytic study on consumer confusion, this study offers a statistical summary of the quantitative results reported in the consumer confusion literature and presents solid relationships between the variables examined in the literature. Practically, we offer useful implications for marketers to minimise the consumer confusion during the purchase decision-making process among specific consumer groups.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115294
Authors: Shadma Shahid, Haroon Iqbal Maseeh, Charles Jebarajakirthy, Bhuvanesh Kumar Sharma, Raiswa Saha, Shubhi Gupta
ABSTRACT
Consumer confusion is a state of mind that occurs when consumers encounter a large number of options or information overload, making it difficult for them to make a confident and informed purchasing decision. This study summarises the consumer confusion literature to analyse the links between the constructs examined in this literature domain. The findings suggest that various information, consumer, and product-related factors prompt consumer confusion which engenders negative consumer responses. Moderation analysis indicates that differences in six methodological factors (research methods, sample type, country, gender dominance, survey administration method, and sample size) and five contextual moderators (price consciousness, industry type, customer involvement, cultural perspectives, and store type) across the studies contribute to inconsistent findings regarding the relationships between the constructs examined in the consumer confusion domain. Theoretically, being the first meta-analytic study on consumer confusion, this study offers a statistical summary of the quantitative results reported in the consumer confusion literature and presents solid relationships between the variables examined in the literature. Practically, we offer useful implications for marketers to minimise the consumer confusion during the purchase decision-making process among specific consumer groups.
How to Use Emerging Service Technologies to Enhance Customer Centricity in Business-to-business Contexts: a Conceptual Framework and Research Agenda
Manufacturers in business-to-business (B2B) industries aim to gain a competitive edge by adopting the concept of customer centricity in their strategy. Acknowledging manufacturers’ challenges in implementing new technologies, we showcase how digital product passports, augmented/virtual reality, smart products, and digital twins foster customer centricity. We classify these technologies based on their use context and introduce the CCTECH-framework, which delineates the impact of (1) experiential, (2) performance-enhancing, and (3) automated technologies on customer-centric processes. This research explores the opportunities for utilizing specific emerging technologies to enhance four customer-centric processes: (1) interactive customer relationship management (discovering implicit needs), (2) customer integration (systematic involvement of customers in decision-making), (3) internal integration (aligning business activities around customer value), and (4) external integration (supply chain-level coordination to respond to customization required by customers). Further, we provide a technology roadmap for manufacturers and suggest a research agenda to guide future research.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115284
Authors: Nancy V. Wünderlich, Markus Blut, Christian Brock, Nima Heirati, Marcus Jensen, Stefanie Paluch, Julia Rötzmeier-Keuper, Zsófia Tóth
ABSTRACT
Manufacturers in business-to-business (B2B) industries aim to gain a competitive edge by adopting the concept of customer centricity in their strategy. Acknowledging manufacturers’ challenges in implementing new technologies, we showcase how digital product passports, augmented/virtual reality, smart products, and digital twins foster customer centricity. We classify these technologies based on their use context and introduce the CCTECH-framework, which delineates the impact of (1) experiential, (2) performance-enhancing, and (3) automated technologies on customer-centric processes. This research explores the opportunities for utilizing specific emerging technologies to enhance four customer-centric processes: (1) interactive customer relationship management (discovering implicit needs), (2) customer integration (systematic involvement of customers in decision-making), (3) internal integration (aligning business activities around customer value), and (4) external integration (supply chain-level coordination to respond to customization required by customers). Further, we provide a technology roadmap for manufacturers and suggest a research agenda to guide future research.
Exploring the Role of Product Attributes in 9-ending Pricing Strategies: a Study on Online Retailing
This study investigates the use of 9-ending pricing strategies in e-commerce by analyzing over 50,000 shoe prices. Using web scraping and a logit model from a German online retailer, the research assesses how product attributes influence the adoption of 9-ending prices. Key findings reveal that 9-ending prices are predominantly used for female and newly introduced products, as well as for items with lower and standard prices. The study also explores the effects of exclusivity and sustainability on pricing strategies, showing that their impact varies with different 9-ending price categories. Overall, this research demonstrates the complex nature of 9-ending pricing strategies, with the 9-zero removal model supporting all hypotheses, whereas the 99c and 95c models show differential effects. This extends our understanding of pricing tactics in online retail and highlights the significance of product attributes for marketing and sales strategies.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115285
Authors: Mariana Gaspar Gonçalves, Belem Barbosa, Jose Ramon Saura, Marcello Mariani
ABSTRACT
This study investigates the use of 9-ending pricing strategies in e-commerce by analyzing over 50,000 shoe prices. Using web scraping and a logit model from a German online retailer, the research assesses how product attributes influence the adoption of 9-ending prices. Key findings reveal that 9-ending prices are predominantly used for female and newly introduced products, as well as for items with lower and standard prices. The study also explores the effects of exclusivity and sustainability on pricing strategies, showing that their impact varies with different 9-ending price categories. Overall, this research demonstrates the complex nature of 9-ending pricing strategies, with the 9-zero removal model supporting all hypotheses, whereas the 99c and 95c models show differential effects. This extends our understanding of pricing tactics in online retail and highlights the significance of product attributes for marketing and sales strategies.
Serve With Voice: the Role of Agents’ Vocal Cues in the Call Center Service
Since pure voice-to-voice communications mainly characterize the call center context, vocal cues provide a novel lens to comprehend consumer-agent dynamics beyond mere words. This study proposes an analytical framework exploiting speech recognition and interpretable machine learning to convert unstructured audio data into quantifiable measures and examines the impact of agents’ voices in a natural setting. The results show that incorporating agents’ vocal cues into consumer dissatisfaction and callback analysis improves out-of-sample forecast accuracy, with an average improvement of 11.65% and 4.30%, respectively. Vocal cues surpass verbal and demographic variables in predictive importance. An affirmative tone and a relatively quick speech rate are identified as key factors that significantly reduce dissatisfaction and callbacks. Our proposed voice feature framework enhances telephone-based service quality assessment, offers practical insights for agent training, and provides novel insights to improve consumer service operations, ultimately leading to the maximization of financial benefits.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115282
Authors: Yuanyuan Zhou, Zhuoying Fei, Jun Yang, Demei Kong
ABSTRACT
Since pure voice-to-voice communications mainly characterize the call center context, vocal cues provide a novel lens to comprehend consumer-agent dynamics beyond mere words. This study proposes an analytical framework exploiting speech recognition and interpretable machine learning to convert unstructured audio data into quantifiable measures and examines the impact of agents’ voices in a natural setting. The results show that incorporating agents’ vocal cues into consumer dissatisfaction and callback analysis improves out-of-sample forecast accuracy, with an average improvement of 11.65% and 4.30%, respectively. Vocal cues surpass verbal and demographic variables in predictive importance. An affirmative tone and a relatively quick speech rate are identified as key factors that significantly reduce dissatisfaction and callbacks. Our proposed voice feature framework enhances telephone-based service quality assessment, offers practical insights for agent training, and provides novel insights to improve consumer service operations, ultimately leading to the maximization of financial benefits.
AI-capable Relationship Marketing: Shaping the Future of Customer Relationships
This study explores the interlinkages between artificial intelligence (AI), dynamic capabilities, and relationship marketing (RM) outcomes. Drawing upon insights from dynamic capabilities and RM theory, this study delineates the strategies and initiatives organizations can adopt using machine learning (ML) and AI to enhance their adaptability to changing market dynamics and customer preferences, in order to develop and maintain stronger relationships with their customers. Based on qualitative data from 67 interviews with managers in different organizations in India, this study contributes to existing theoretical knowledge and managerial practices, as it proposes a comprehensive research framework that demonstrates how AI technologies can enhance customer relationships throughout the entire customer journey. More specifically, it adopts a dynamic capabilities lens to extend our understanding of the marketing applications of AI by conceptualizing the dual role of AI as (a) a distinct organizational capability and (b) an enabler of dynamic capabilities, improving firms’ position to sense, seize, and transform organizational resources and fortify customer relationships. Our findings also highlight several facilitators and barriers to the adoption of AI, both as a dynamic capability and as an enabler for RM.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115309
Authors: Sanjit K. Roy, Ali N. Tehrani, Ameet Pandit, Chrysostomos Apostolidis, Subhasis Ray
ABSTRACT
This study explores the interlinkages between artificial intelligence (AI), dynamic capabilities, and relationship marketing (RM) outcomes. Drawing upon insights from dynamic capabilities and RM theory, this study delineates the strategies and initiatives organizations can adopt using machine learning (ML) and AI to enhance their adaptability to changing market dynamics and customer preferences, in order to develop and maintain stronger relationships with their customers. Based on qualitative data from 67 interviews with managers in different organizations in India, this study contributes to existing theoretical knowledge and managerial practices, as it proposes a comprehensive research framework that demonstrates how AI technologies can enhance customer relationships throughout the entire customer journey. More specifically, it adopts a dynamic capabilities lens to extend our understanding of the marketing applications of AI by conceptualizing the dual role of AI as (a) a distinct organizational capability and (b) an enabler of dynamic capabilities, improving firms’ position to sense, seize, and transform organizational resources and fortify customer relationships. Our findings also highlight several facilitators and barriers to the adoption of AI, both as a dynamic capability and as an enabler for RM.
Digital Brand Equity: the Concept, Antecedents, Measurement, and Future Development
Measuring brand equity is of vital importance to marketing practitioners and scholars. Academics and practitioners have developed a range of tools and metrics for measuring brand equity, but in the fast-paced and transformational digital era, it may be that current metrics are not sufficient. The authors develop a conceptual understanding of the brand equity paradigm using practitioner and scholarly views. A practitioner-focused analysis is given on how companies can best understand and measure brand performance in a digital environment and take actionable insights, using the share of search, digital brand awareness, and digital brand sentiment constructs. The authors argue that digital brand equity metrics cannot be based only on social media and current digital metrics indicators but also must include a human side of the brand and the technology-consumer nuances. The study proposes a research agenda and highlights important research and policy questions in developing digital brand equity.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115273
Authors: Stephen L. France, Nebojsa S. Davcik, Brett J. Kazandjian
ABSTRACT
Measuring brand equity is of vital importance to marketing practitioners and scholars. Academics and practitioners have developed a range of tools and metrics for measuring brand equity, but in the fast-paced and transformational digital era, it may be that current metrics are not sufficient. The authors develop a conceptual understanding of the brand equity paradigm using practitioner and scholarly views. A practitioner-focused analysis is given on how companies can best understand and measure brand performance in a digital environment and take actionable insights, using the share of search, digital brand awareness, and digital brand sentiment constructs. The authors argue that digital brand equity metrics cannot be based only on social media and current digital metrics indicators but also must include a human side of the brand and the technology-consumer nuances. The study proposes a research agenda and highlights important research and policy questions in developing digital brand equity.
Recurring Versus One-time Donation Requests: The Toll on Attracting Donors
Non-profit marketers often design campaigns that ask donors to contribute recurringly. While past research has implied the benefits of giving recurring donations, across six studies using both archival and experimental data, we find convergent evidence that consumers are less attracted to contribute to a non-profit’s recurring (vs. one-time) donation solicitations. Our results suggest that the heightened pain of giving from recurring (vs. one-time) solicitations mediates the effect. Furthermore, we find that the mediating effect of pain of giving attenuates for less frugal consumers, and that the negative effect of recurring (vs. one-time) solicitations on donation willingness mitigates when the solicitations ask for time (vs. monetary) donations. Finally, reconciling our findings with prior research on temporal framing, we find that the effect reverses when a total expected donation amount is salient. This research informs the unintended consequences of recurring donation requests and suggests practical interventions for practitioners.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115317
Authors: Cony Ming-Shen Ho, Shih-Chun (Daniel) Chin, TzuShuo Ryan Wang
ABSTRACT
Non-profit marketers often design campaigns that ask donors to contribute recurringly. While past research has implied the benefits of giving recurring donations, across six studies using both archival and experimental data, we find convergent evidence that consumers are less attracted to contribute to a non-profit’s recurring (vs. one-time) donation solicitations. Our results suggest that the heightened pain of giving from recurring (vs. one-time) solicitations mediates the effect. Furthermore, we find that the mediating effect of pain of giving attenuates for less frugal consumers, and that the negative effect of recurring (vs. one-time) solicitations on donation willingness mitigates when the solicitations ask for time (vs. monetary) donations. Finally, reconciling our findings with prior research on temporal framing, we find that the effect reverses when a total expected donation amount is salient. This research informs the unintended consequences of recurring donation requests and suggests practical interventions for practitioners.
With Great Power Comes Great Responsibility: The Antecedents and Outcomes of Social Media Influencers’ Perceived Social Responsibility Authenticity
This study draws on signaling theory to investigate what signals the authenticity of influencers when communicating social causes and its consequent outcomes from consumers’ perspectives. Two between-subjects experimental studies were conducted. Study 1 found that transparently communicating a social cause positively signals influencers’ authenticity, which is significantly moderated by the level of fit between the social cause and the influencer’s domain of interest. Perceived authenticity positively impacts consumers’ attitudes toward the influencer, subsequently affecting their purchase intention (i.e., pro-influencer behavior) and social cause communication engagement intention (i.e., pro-social behavior). Study 2 aimed to examine the findings of Study 1 in the context of controversial social causes. It was found that congruency between a consumer’s and an influencer’s stance on the cause influences perceived authenticity. From a holistic perspective, this study investigated consumers’ pro-influencer and pro-social behavioral intentions to corroborate influencers’ impacts on both business and societal aspects.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115300
Authors: Angie Lee, Te-Lin Doreen Chung
ABSTRACT
This study draws on signaling theory to investigate what signals the authenticity of influencers when communicating social causes and its consequent outcomes from consumers’ perspectives. Two between-subjects experimental studies were conducted. Study 1 found that transparently communicating a social cause positively signals influencers’ authenticity, which is significantly moderated by the level of fit between the social cause and the influencer’s domain of interest. Perceived authenticity positively impacts consumers’ attitudes toward the influencer, subsequently affecting their purchase intention (i.e., pro-influencer behavior) and social cause communication engagement intention (i.e., pro-social behavior). Study 2 aimed to examine the findings of Study 1 in the context of controversial social causes. It was found that congruency between a consumer’s and an influencer’s stance on the cause influences perceived authenticity. From a holistic perspective, this study investigated consumers’ pro-influencer and pro-social behavioral intentions to corroborate influencers’ impacts on both business and societal aspects.
How Allusion Enhances Consumer Response to Hope Appeals in Health Messaging
While fear appeals often appear in health-oriented Public Service Announcements (PSAs), three experiments demonstrate that a positive appeal, hope, can be effectively used in PSAs to promote healthy eating when combined with an allusion, a type of figurative language. Specifically, Study 1 uses eye-tracking to establish that allusion moderates hope’s encouragement of visual attention and engagement. Study 2′s experiment illustrates how allusion moderates hope’s influence on message outcomes. Study 3 tests whether self-efficacy mediates the relationships between hope and allusion on message outcomes using Hayes PROCESS modeling. Results support self-efficacy’s mediation of the hope-allusion interaction on message response outcomes. One contribution is the investigation of a multimodal allusion incorporating both visual and verbal elements and its ability to enhance message effectiveness. This study also advances the theoretical understanding of the use of positive emotional appeals and the power of self-efficacy to account for their effects in health promotion PSAs.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115237
Authors: Pia A. Albinsson, Bruce A. Huhmann, Bidisha Burman
ABSTRACT
While fear appeals often appear in health-oriented Public Service Announcements (PSAs), three experiments demonstrate that a positive appeal, hope, can be effectively used in PSAs to promote healthy eating when combined with an allusion, a type of figurative language. Specifically, Study 1 uses eye-tracking to establish that allusion moderates hope’s encouragement of visual attention and engagement. Study 2′s experiment illustrates how allusion moderates hope’s influence on message outcomes. Study 3 tests whether self-efficacy mediates the relationships between hope and allusion on message outcomes using Hayes PROCESS modeling. Results support self-efficacy’s mediation of the hope-allusion interaction on message response outcomes. One contribution is the investigation of a multimodal allusion incorporating both visual and verbal elements and its ability to enhance message effectiveness. This study also advances the theoretical understanding of the use of positive emotional appeals and the power of self-efficacy to account for their effects in health promotion PSAs.
The B2B Sharing Economy: Framework, Implications, and Future Research
The sharing economy (SE) has disrupted several sectors. Thus far, this has mainly occurred in consumer markets. Research has therefore focused on these sectors, leaving a research gap regarding the emergence of the SE in business-to-business (B2B) markets. We address this gap by first developing a literature-based framework defining the B2B SE as a service system composed of at least three actors (triadic + ), including an asset-light, intermediating platform that links at least two organizations, with one paying for temporary access to a physical asset from the other organization, for which granting this access is an ancillary service outside of the core business. We also delineate the B2B SE from related concepts, such as cooperatives and co-owning. Second, we provide managerial implications for platforms, incumbents, asset owners, and policymakers. Third, we outline areas for future research, for example, disruption trajectories, incumbent reactions, and the dark side of the B2B SE.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115244
Authors: Sabine Benoit, Katrin Merfeld, Vivian S.C. Tunn, Tobias Schaefers, Tor Wallin Andreassen
ABSTRACT
The sharing economy (SE) has disrupted several sectors. Thus far, this has mainly occurred in consumer markets. Research has therefore focused on these sectors, leaving a research gap regarding the emergence of the SE in business-to-business (B2B) markets. We address this gap by first developing a literature-based framework defining the B2B SE as a service system composed of at least three actors (triadic + ), including an asset-light, intermediating platform that links at least two organizations, with one paying for temporary access to a physical asset from the other organization, for which granting this access is an ancillary service outside of the core business. We also delineate the B2B SE from related concepts, such as cooperatives and co-owning. Second, we provide managerial implications for platforms, incumbents, asset owners, and policymakers. Third, we outline areas for future research, for example, disruption trajectories, incumbent reactions, and the dark side of the B2B SE.
The Role of Social Norms in Retirement Saving: Evidence From Two Natural Field Experiments
Under-saving for retirement is a challenge for society, businesses, and individuals. Therefore, behavioral interventions that promote saving are valuable for economic and social well-being. Previous research demonstrates that retirement saving can be influenced by social-psychological mechanisms such as peer effects and norms. However, few large-scale experiments have investigated the role of different types of social norms in boosting retirement savings. Even fewer studies have examined how the time-framing (e.g., focusing on the present choice of saving vs. the future benefits of current saving) of such norms influences behavior. This paper provides real-life experimental evidence on the effects of (1) descriptive vs. injunctive norms on retirement saving behavior across two stages of the decision-making process (information search and saving behavior), and (2) the time-framing of such norms. Specifically, we conduct two large-scale field experiments on Norway-based bank customers in their online user interface, testing the effects of different norm messages on actual saving behavior. Study 1 (N = 455,509) finds that although injunctive (vs. descriptive) norms lead to higher click-through rates, descriptive norms are more effective than injunctive norms in increasing actual retirement savings. In essence, information about what most other people do (descriptive norms) was more effective in changing behavior than expert opinion on what one should do (injunctive norms). In Study 2 (N = 224,000), we vary descriptive norms across two saving schemes in a 2 (descriptive norm: present-focused vs. future-focused) X 2 (scheme: save-more-tomorrow vs. save-more-today) design. We find stronger effects of present-focused descriptive norms than future-focused descriptive norms in general, driven by differences in the save-more-today scheme. Effect sizes were generally small, but economically meaningful due to the low intervention costs of large-scale implementation. As a whole, our findings broaden the understanding of how social norms and their time-framing influence long-term saving behavior.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115201
Authors: Trond Døskeland, Jareef Bin Martuza, Lars Jacob Tynes Pedersen, Francisco Santos, Hallgeir Sjåstad, Helge Thorbjørnsen
ABSTRACT
Under-saving for retirement is a challenge for society, businesses, and individuals. Therefore, behavioral interventions that promote saving are valuable for economic and social well-being. Previous research demonstrates that retirement saving can be influenced by social-psychological mechanisms such as peer effects and norms. However, few large-scale experiments have investigated the role of different types of social norms in boosting retirement savings. Even fewer studies have examined how the time-framing (e.g., focusing on the present choice of saving vs. the future benefits of current saving) of such norms influences behavior. This paper provides real-life experimental evidence on the effects of (1) descriptive vs. injunctive norms on retirement saving behavior across two stages of the decision-making process (information search and saving behavior), and (2) the time-framing of such norms. Specifically, we conduct two large-scale field experiments on Norway-based bank customers in their online user interface, testing the effects of different norm messages on actual saving behavior. Study 1 (N = 455,509) finds that although injunctive (vs. descriptive) norms lead to higher click-through rates, descriptive norms are more effective than injunctive norms in increasing actual retirement savings. In essence, information about what most other people do (descriptive norms) was more effective in changing behavior than expert opinion on what one should do (injunctive norms). In Study 2 (N = 224,000), we vary descriptive norms across two saving schemes in a 2 (descriptive norm: present-focused vs. future-focused) X 2 (scheme: save-more-tomorrow vs. save-more-today) design. We find stronger effects of present-focused descriptive norms than future-focused descriptive norms in general, driven by differences in the save-more-today scheme. Effect sizes were generally small, but economically meaningful due to the low intervention costs of large-scale implementation. As a whole, our findings broaden the understanding of how social norms and their time-framing influence long-term saving behavior.
How and When AI-Driven HRM Promotes Employee Resilience and Adaptive Performance: A Self-Determination Theory
Despite growing research on AI in HRM, gaps remain, particularly in understanding the mechanisms through which AI-driven HRM influences employee outcomes. This study addresses this gap by developing a conceptual model to examine how AI-driven HRM impacts employee resilience and adaptive performance. Based on self-determination theory, the model proposes that employee exploration mediates the relationships between AI-driven HRM and employee outcomes. Additionally, trust in AI moderates these relationships. Two studies were conducted to test the hypotheses: Study 1 developed and validated a 12-item AI-driven HRM scale across three samples: 50 managers, 150 employees for exploratory factor analysis (EFA), and 150 employees for confirmatory factor analysis (CFA). Study 2, with data from 274 US employees through a three-wave survey, explored the effects of AI-driven HRM on resilience and performance. Results from Study 2 supported all proposed relationships, thereby offering important implications for both theory and practice in the AI-driven HRM field.
Paper Link: https://doi.org/10.1016/j.jbusres.2025.115279
Authors: Hoa Do, Lin Xiao Chu, Helen Shipton
ABSTRACT
Despite growing research on AI in HRM, gaps remain, particularly in understanding the mechanisms through which AI-driven HRM influences employee outcomes. This study addresses this gap by developing a conceptual model to examine how AI-driven HRM impacts employee resilience and adaptive performance. Based on self-determination theory, the model proposes that employee exploration mediates the relationships between AI-driven HRM and employee outcomes. Additionally, trust in AI moderates these relationships. Two studies were conducted to test the hypotheses: Study 1 developed and validated a 12-item AI-driven HRM scale across three samples: 50 managers, 150 employees for exploratory factor analysis (EFA), and 150 employees for confirmatory factor analysis (CFA). Study 2, with data from 274 US employees through a three-wave survey, explored the effects of AI-driven HRM on resilience and performance. Results from Study 2 supported all proposed relationships, thereby offering important implications for both theory and practice in the AI-driven HRM field.
In-Store Technology Personalization: A Typology and Research Agenda Based on Type of Automation and Data Collection
Smart retail leverages novel intelligent technologies that can sense, connect, and interact with customers to apply personalization tactics widely available in online shopping to offline settings. Retailers rely on such technologies to provide customers with personalized messages. The increasing autonomy of the technologies delivering the personalization and the data collection upon which this personalization is based and produce different manifestations of personalization in smart retail. To establish a foundation for research and practice involving these different manifestations, this article proposes a 2 (autonomy of technology: autonomous vs. employee-guiding) × 2 (type of data collection: explicit vs. implicit) in-store personalization-technology typology. Building on this typology, the authors analyze real-world manifestations and thereby establish the state-of-the-art of in-store personalization practices for smart retail. By comparing current knowledge in academic research with the status quo of managerial practice, this article advances an agenda for further research into personalization in smart retail.
Paper Link: https://www.sciencedirect.com/science/article/pii/S0148296325000591?dgcid=rss_sd_all
Authors: Katrin Merfeld, Jan F. Klein, Anouk de Regt, Anne-Sophie Baltin (née Riegger), Sven Henkel
ABSTRACT
Smart retail leverages novel intelligent technologies that can sense, connect, and interact with customers to apply personalization tactics widely available in online shopping to offline settings. Retailers rely on such technologies to provide customers with personalized messages. The increasing autonomy of the technologies delivering the personalization and the data collection upon which this personalization is based and produce different manifestations of personalization in smart retail. To establish a foundation for research and practice involving these different manifestations, this article proposes a 2 (autonomy of technology: autonomous vs. employee-guiding) × 2 (type of data collection: explicit vs. implicit) in-store personalization-technology typology. Building on this typology, the authors analyze real-world manifestations and thereby establish the state-of-the-art of in-store personalization practices for smart retail. By comparing current knowledge in academic research with the status quo of managerial practice, this article advances an agenda for further research into personalization in smart retail.
Inclusive Marketing: A Review and Research Agenda
In today’s globalized, multicultural markets, the diversity of consumer needs highlights the increasing social role of consumption and the demand for marketplace justice. This shift has propelled the importance of inclusive marketing in academic research. Despite its growing relevance, critical aspects of inclusive marketing’s development, including its conceptual framework and consumer responses, remain underexplored. This study systematically reviews 71 articles to elucidate these aspects through four critical research questions. This review utilizes the TCCM framework to scrutinize the predominant theories, contexts, methods, and typologies shaping the domain. It also categorizes scholarly works into a representation of diverse consumers, responses of the marketplace actors, consumer identities in the inclusive marketplace, continuum of inclusive marketing, inclusive marketing under a critical lens, and conceptual boundaries of inclusive marketing. Based on this analysis, the study proposes a refined definition of inclusive marketing. It concludes by suggesting future research directions to advance this emergent field, focusing on unexplored areas with potential for significant academic contribution.
Paper Link: https://www.sciencedirect.com/science/article/abs/pii/S0148296325000979?dgcid=rss_sd_all
Authors: Nikhita Tuli, Vibhava Srivastava, Harish Kumar
ABSTRACT
In today’s globalized, multicultural markets, the diversity of consumer needs highlights the increasing social role of consumption and the demand for marketplace justice. This shift has propelled the importance of inclusive marketing in academic research. Despite its growing relevance, critical aspects of inclusive marketing’s development, including its conceptual framework and consumer responses, remain underexplored. This study systematically reviews 71 articles to elucidate these aspects through four critical research questions. This review utilizes the TCCM framework to scrutinize the predominant theories, contexts, methods, and typologies shaping the domain. It also categorizes scholarly works into a representation of diverse consumers, responses of the marketplace actors, consumer identities in the inclusive marketplace, continuum of inclusive marketing, inclusive marketing under a critical lens, and conceptual boundaries of inclusive marketing. Based on this analysis, the study proposes a refined definition of inclusive marketing. It concludes by suggesting future research directions to advance this emergent field, focusing on unexplored areas with potential for significant academic contribution.
The Impact of New Product Entry on Brand Sales Volatility at the Retailer: A Detailed Look Into Volatility Drivers
Volatile sales patterns with large and uncertain peaks and drops significantly increase operational complexity and complicate inventory activities tremendously. This study examines whether and to what extent the addition of a new product into the assortment of a grocery retailer is responsible for an increase in sales volatility for incumbent offerings and which brand and retailer factors underlie this change. Using time-series models of eight years of sales data from brands in nine categories at six German grocery retailers, a significant and persistent rise in volatility is observed in sales after a new product enters the store for the majority of these brands. National brands are affected the most by the addition of an entirely new brand, whereas sub-brands introduced under an existing national brand name have a more limited impact on sales volatility. Interestingly, the opposite is found for retailers’ private labels, where volatility increases more after the entry of a new sub-brand (rather than a new brand). Several other brand and assortment characteristics can be linked to changes in the sales volatility of incumbent brands at the retailer. Based on this, two prediction tools are developed to anticipate before product entry if—and by how much—brand sales volatility will change. These insights can assist retailers and brand suppliers in managing their inventories and brand operations and provide relevant input for planning marketing support when new products arrive.
Paper Link: https://www.sciencedirect.com/science/article/pii/S0148296325000906?dgcid=rss_sd_all
Authors: Wanxin (Britney) Wang, Barbara Deleersnyder, Gokhan Yildirim
ABSTRACT
Volatile sales patterns with large and uncertain peaks and drops significantly increase operational complexity and complicate inventory activities tremendously. This study examines whether and to what extent the addition of a new product into the assortment of a grocery retailer is responsible for an increase in sales volatility for incumbent offerings and which brand and retailer factors underlie this change. Using time-series models of eight years of sales data from brands in nine categories at six German grocery retailers, a significant and persistent rise in volatility is observed in sales after a new product enters the store for the majority of these brands. National brands are affected the most by the addition of an entirely new brand, whereas sub-brands introduced under an existing national brand name have a more limited impact on sales volatility. Interestingly, the opposite is found for retailers’ private labels, where volatility increases more after the entry of a new sub-brand (rather than a new brand). Several other brand and assortment characteristics can be linked to changes in the sales volatility of incumbent brands at the retailer. Based on this, two prediction tools are developed to anticipate before product entry if—and by how much—brand sales volatility will change. These insights can assist retailers and brand suppliers in managing their inventories and brand operations and provide relevant input for planning marketing support when new products arrive.