Smriti Mathur

Purpose : The purpose of this study was to identify, structure, and examine the causal dominance of critical success factors underlying marketing intelligence using a multi-method analytical framework. Methodology : With reference to the growing importance of marketing intelligence for intelligent marketing, this study conducted an extensive literature review (N = 152) and identified 29 critical success factors of marketing intelligence. Further data was collected (n = 256) for principal component analysis and (n = 13) for employing fuzzy DEMATEL. Findings : The results of principal component analysis segmented the 29 dimensions into 7 corresponding factors. Further, fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) was employed to establish Strategic Marketing Planning (SMP), Strategic Business Intelligence (SBI), Customer Brand Co-Creation (CBC), Tactical Marketing (TM), and Strategic Customer Intelligence (SCI) as cause factors, and Competitive Intelligence Analysis (CIA), Digital Dynamism (DD) as effect factors. Originality : This study offered a novel multi-method investigation by integrating the PRISMA framework, PCA, and Fuzzy DEMATEL to identify cause and effect dimensions and enhance system-level understanding of marketing intelligence implementation.

Purpose: This study seeks to explore how customers’ perceptions of the benefits, risks and continuation intention toward Marketing Technologies (MarTech) influence their actual usage. This research study utilizes the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework for assessing the usage and continuation intention (intention – behavior) of customers toward adopting marketing technologies. Design/methodology/approach: Data was collected from 266 respondents and analyzed using partial least squares structural equation modeling (PLS-SEM). A post-hoc analysis was undertaken using importance-performance matrix analysis (IPMA) to assess the importance and performance of determinants in the PLS-SEM model. Findings: The results of the study indicate that perceived usefulness, perceived enjoyment and social influence have positive effects on Marketing Technologies (MarTech) usage intention. Additionally, usage intention has no effect on continuation intention. The performance of Perceived Usefulness is 74.879, which is higher than other constructs and ascertains that perceived usefulness contributes largely to predicting MarTech continuation intention. Originality/value: This study enriches the technology adoption literature by investigating the predictors of marketing technologies (MarTech) adoption and usage from the perspective of customers. Notably, the novelty of this research lies in investigating the impact of perceived trust and perceived risk on MarTech usage and continuation intention of customers.

Purpose: This study aims to formalize a comprehensive, contemporary and holistic definition of marketing intelligence (MI) by mapping the relevant literature of the last 60 years from 1962–2022. Design/methodology/approach: This study centralizes around the qualitative assessment of explored definitions by using thematic analysis. By identifying patterns and themes within the qualitative dataset, thematic analysis provides accessible and systematic procedures for generating codes and themes by discovering commonalities and contradictions in keywords. Findings: The result of study 1 identified 127 papers indexed in databases distributed across 56 different journals. The manual screening of 127 research papers resulted in the selection of 15 definitions of MI. In study 2, thematic analysis was applied to these definitions through author-attribute mapping and assessment of weights, resulting in the identification of 25 key attributes representing five emerging themes. Study 3 identifies the gaps in definitions and proposes a comprehensive and complete definition of MI. Originality/value: This research’s novelty corresponds to author-attribute mapping, exploring gaps in existing definitions and proposing a holistic and contemporary definition of MI.

Purpose: ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model (ISSM) to examine the role of ChatGPTs in strengthening information quality (IQ), system quality (SQ) and service quality (SEQ) for improving customer usage intention (UI) and satisfaction (SAT). The study also investigates the moderating impact of perceived innovativeness between these relationships.Design/methodology/approach: The research collected data from a sample of 400 customers through an online survey and validated the hypothesized relationships using structural equation modelling (SEM). Process Macros 4.1 in SPSS 22.0 is used to test the moderating role of perceived innovation between IQ, SQ and SEQ and UI and SAT.Findings: The results of SEM analysis indicate that IQ, SQ and SEQ all positively support UI to use ChatGPT for professional communication with SAT. The result also establishes that perceived innovativeness positively moderates the relationship between IQ, SQ and SEQ and UI and SAT.Originality/value: This research study offers novel contributions to the literature and body of knowledge by establishing the moderating role of perceived innovativeness in strengthening the relationship between IQ, SQ and SEQ and UI and SAT. Further, this study also proposes a 2*2 matrix to segment the UI and SAT of ChatGPT users in professional communication with varying degrees of perceived innovativeness.

With the change in the communication pattern, end-users are engaging in creating content and referring to the content created by other users while making purchase decisions. This research aims at modelling factors affecting consumers’ usage intention (UI) towards user-generated content (UGC) using Need for Cognition (NfC) as a moderator of the proposed relationships. The factors affecting consumers’ UI involve perceived usefulness (PU), source credibility (SC), information quality (IQ) and NfC. Further, a novel attempt has been made by using the neural network approach to assess the predictive accuracy of the model. A structured questionnaire was used to collect data from 298 consumers through a survey. Data were analysed using two-stage structural equation modelling (SEM) and artificial neural network (ANN). All the independent variables viz., PU, SC, IQ and NfC significantly affect attitude towards UGC, which in turn affects UI. Results of multi-group analysis and a series of chi-square difference tests reveal that a NfC significantly moderates the relationship between PU and attitude, as well as that between SC and attitude. The root mean square error values from the neural network analysis suggest that the models show good predictive accuracy. This study provides a novel assessment of the usage of a hybrid SEM-ANN approach for understanding of UGC by incorporating NfC as a moderator in shaping consumers’ attitudes and intentions to use UGC.

Purpose: The current study employs a modified framework of the unified theory of acceptance and use of technology (UTAUT) to predict students' intention to adopt online learning in India. The moderating role of openness to change in influencing the proposed relationships is also assessed.Design/methodology/approach: A structured questionnaire was emailed to 650 students enrolled in various courses in public and private universities in India. In total 424 responses were considered for analysis using structural equation modeling (SEM). Moderation analysis was carried out with multi-group SEM and chi-square difference tests.Findings: The results reveal that there is a significant impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FS) and perceived security (PS) on students' intention to adopt online learning. Further, openness to change moderates the impact of PE, FS and PS on intention of students to opt for online learning.Originality/value: This study is one of the initial efforts to examine the factors affecting students' intention to adopt online learning at the onset of third wave of coronavirus disease 2019 (COVID-19) pandemic in India. Besides the factors of the UTAUT model, this study highlights the importance of PS and openness to change in influencing students' intention to opt for online learning.

User-Generated Content (UGC) has overshadowed other marketing trends and is a version of social proof. Current customer showcases their real-life experience and motivates potential customers to try these products and services. Building trust, creating community, customer engagement, loyalty, and social amplification are the denouements of UGC. This research investigates the impact of Brand Engagement (BE), Perceived Credibility (PC), Perceived Benefit (PB), and Information Quality (IQ) on attitude towards User-Generated Content (UGC). Also, how a consumer’s purchase intention is impacted by a consumer’s attitude towards UGC. The mediating effect of consumer’s attitudes towards UGC was also examined by this study. A sample of 260 consumers was collected in a structured survey for the analysis of data. To examine the hypothesized linkages between the mentioned variables, structural equation modeling was used. It was found that BE, PC, PB, and IQ have a positive effect on consumers’ attitudes towards UGC. Also, it was found that the consumer’s attitude towards UGC positively affected online purchase intentions. The Bootstrapping procedure shows that consumers’ attitude towards UGC possesses significant influence as a mediator between BE, PC, PB, IQ, and PI. The findings of this study can be useful for managers and marketers to enhance their understanding of the new marketing communication strategies.