Research Domain Research Articles

Social media marketing and customer purchase intention: Evidence-based bibliometrics and text analysis

The rapid proliferation of social media platforms has sparked heightened interest among businesses seeking to leverage them to enhance customer purchase intentions. Consequently, there has been a surge in research exploring the intersection of social media marketing and consumer behavior. However, gaps persist regarding the primary themes within this research domain. This study analyzes 282 research papers spanning from 2012 to 2022, sourced from the Web of Science Core Collection, focusing on social media and customer purchase intentions. Leveraging Latent Dirichlet Allocation (LDA) commands in STATA and VOSviewer software, the study investigates emerging trends and prevalent themes, visualizing the dataset. The findings indicate a notable increase in research output, particularly from developed countries, with significant collaboration between developed and developing nations. Moreover, the study identifies five principal research topics: 1) the impact of social media marketing on consumer purchase intention, 2) the consequences of online brand communities on purchase behavior, 3) factors influencing consumer purchase intention, 4) influencer effects on purchase intention, and 5) social media advertising and marketing strategies. Future inquiries should delve into various factors shaping customer purchase intentions, including the role of influencers, word-of-mouth dynamics, and advertising strategies while considering the diverse cultural contexts across different regions. This comprehensive analysis provides valuable insights for researchers and practitioners alike, guiding future endeavors in understanding and harnessing the power of social media in consumer decision-making processes. AcknowledgmentsGiang Hai Ha was funded by the Master, PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), code VINIF.2022.TS030.

Online Illegal Cryptomarkets

Cryptomarkets—online markets for illegal goods—have revolutionized the illegal drug trade, constituting about 10% of all drug trades and attracting users to a greater variety and more addictive substances than available in offline drug markets. This review introduces the burgeoning area of sociology research on illegal cryptomarkets, particularly in the realm of drug trade. We emphasize the expanding role of illicit online trade and its relevance for understanding broader exchange challenges encountered in all illegal trade settings. Examining the effects of online illegal trade on consumption and supply-side policing, we also discuss the harm and potential benefits of moving drug exchange from offline to online markets. We argue for a network perspective's efficacy in this research domain, emphasizing its relevance in assessing trade and discussion networks, technical innovation, and market evolution and vulnerabilities. Concluding, we outline future research areas, including market culture, failure, and the impact of online illegal trade on stratification.

Unraveling noncoding DNA variants and epimutations: a paradigm shift in hereditary cancer research

Exhaustive efforts have been dedicated to uncovering genomic aberrations linked to cancer susceptibility. Noncoding sequence variants and epigenetic alterations significantly influence gene regulation and could contribute to cancer development. However, exploring noncoding regions in hereditary cancer susceptibility demands cutting-edge methodologies for functionally characterizing genomic discoveries. Additionally, comprehending the impact on cancer development of variants in noncoding DNA and the epigenome necessitates integrating diverse data through bioinformatic analyses. As novel technologies and analytical methods continue to advance, this realm of research is rapidly gaining traction. Within this mini-review, we delve into future research domains concerning aberrations in noncoding DNA regions, such as pseudoexons, promoter variants and cis-epimutations.

Saudi millennials’ panic buying behavior during pandemic and post-pandemic: Role of social media addiction and religious values and commitment

The latest version of the pandemic ravaged the world for almost three years. The world is slowly coming back to normal. Behavioral sciences tried to assess its impact on consumer behavior, and panic buying behavior has become a most sought-after domain for current researchers. Millennials were the most affected as they were at the beginning of their career, and COVID-19 disrupted their plans massively. This study assesses the panic buying behavior of millennials during pandemic and post-pandemic scenarios. Scarcity and uncertainty are used as antecedents. Two opposite moderators, social media addiction and religious values and commitment, are taken as moderators. Five hundred-seven Saudi millennials participated in this study. Building upon the theory of reasoned action (TRA) and the theory of planned behavior (TPB) along with the latest literature, the conceptual model was proposed using the S–O–B–C (Stimulus/Situation-Organisms-Behavior-Consequences) framework. Structural equation modeling was used to assess the proposed hypotheses. There was no sense of scarcity, panic buying behavior, or social media addiction. On the other hand, there was a high sense of uncertainty, high religious values and commitment, and a positive post-pandemic buying intention. A low sense of scarcity positively impacts panic buying behavior, which was also low, but a heightened sense of uncertainty has a negative effect. Panic buying behavior had no impact on the post-pandemic intentions, which was positive. Social media addiction (low) and religious values and commitment (high) affected the existing direct relationships. The results were unique and broke many myths. The study has specific implications for all the stakeholders.

Factors influencing correction upon exposure to health misinformation on social media: the moderating role of active social media use

PurposeThe proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.Design/methodology/approachA total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.FindingsResults indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.Originality/valueThis study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

A MeanShift-guided oversampling with self-adaptive sizes for imbalanced data classification

The imbalanced data classification has gained popularity in machine learning research domain due to its prevalence in numerous applications and its difficulty. However, the majority of contemporary work primarily focuses on addressing between-class imbalance issues. Previous researches have shown that combined with other elements, such as within-class imbalance, small sample size and the presence of small disjuncts, the imbalanced data significantly increase the difficulties for the traditional classifiers to learn. Therefore, we propose a novel MeanShift-guided oversampling with self-adaptive sizes for imbalanced data classification. The proposed MeanShift-guided oversampling technique can simultaneously consider the distribution of minority class and majority class within the sphere with the current minority instance as its center, which can favor addressing small sample size and avoiding overlapping issues often caused by the nearest neighbor (NN)-based oversampling techniques. The incorporation of random vector and flexible cut-off mechanism for vector length can enhance the diversity among the generated synthetic minority instances and avoid overlapping, which makes it suitable for small sample size and small disjuncts problems. To address between-class and within-class imbalance issues, we also introduce a self-adaptive sizes assignment strategy for each minority instance to be oversampled, where the assigned size is inversely proportional to its density and its distance from the majority class. In addition to eliminating within-class imbalance, the strategy can ensure that the informative border minority instances have more opportunities to be oversampled, thus improving classification performance. Extensive experimental results on some datasets with different distributions and imbalance ratios show the proposed algorithm outperforms other compared ones with significant difference.

Marketing innovation for sustainability: Review, trends, and way forward

AbstractSustainable development goals are aligning marketing innovations to meet sustainability interventions. Recently, marketing has evolved to incorporate sustainability in outreach objectives. Heightened literature on the interplay between sustainability, innovations, and marketing demands a holistic understanding to guide future research direction. The current review bridges the research gap using quantitative performance analysis and qualitative intellectual structure analysis. The thematic and content analysis points towards permeating sustainability focus across the business verticals and value chain for differentiated brand positioning and sustainability‐based competitive advantage. The emergent conceptual framework underpins the moderated‐mediation role of sustainability and economic enablers with marketing initiatives to promote business innovations beneficial to all stakeholders. The sustainability‐aligned innovations in products and processes reflect in gaining cost advantage, revenue generation, access to newer markets, and differentiation. It can be inferred from the study that sustainability and conducive marketing strategies can co‐create value across the value chain, providing tangible and non‐tangible corporate payoffs. This cross‐section in the research domain calls for environmental and business focus at the micro and macro levels, supported by pro‐business strategies, system efficiencies, productivity, and technological changes in synergy with the societal landscape. The findings discern strategic directions for practitioners to chart out an organizational portfolio centered around marketing innovations to create business value for the shareholders and sustainability value for the stakeholders, ecosystem, and society. The conceptual framework can help academicians comprehend the business model around sustainability, innovations, and marketing. The evolutionary mapping of the research domain can be used to discern corporate or macro‐level policies and transcend reforms aligned to the dynamic market/stakeholder expectations.

Digital financial inclusion, financial stability, and sustainable development: Evidence from a quantile‐on‐quantile regression and wavelet coherence

AbstractThe current research examines the influence of digital financial inclusion (DFI) and financial stability (FS) on sustainable development in Vietnam through a dataset spanning during 2004–2022. Non‐parametric methods, such as quantile regression, Granger tests in different quantiles, and wavelet analysis were employed to elucidate the effect of different quantiles of FS and DFI on various quantiles of sustainable development. Our primary contribution lies in integrating three research domains to examine the relationships among all three factors simultaneously, all within the framework of one of the biggest developing economies. Our findings exhibit the strongly positive influence of FS and DFI on sustainable development in Vietnam across various quantiles and frequencies. This suggests that FS and DFI support the transition of country toward sustainable development.

The digital lab manager: Automating research support

Laboratory management automation is essential for achieving interoperability in the domain of experimental research and accelerating scientific discovery. The integration of resources and the sharing of knowledge across organisations enable scientific discoveries to be accelerated by increasing the productivity of laboratories, optimising funding efficiency, and addressing emerging global challenges. This paper presents a novel framework for digitalising and automating the administration of research laboratories through The World Avatar, an all-encompassing dynamic knowledge graph. This Digital Laboratory Framework serves as a flexible tool, enabling users to efficiently leverage data from diverse systems and formats without being confined to a specific software or protocol. Establishing dedicated ontologies and agents and combining them with technologies such as QR codes, RFID tags, and mobile apps, enabled us to develop modular applications that tackle some key challenges related to lab management. Here, we showcase an automated tracking and intervention system for explosive chemicals as well as an easy-to-use mobile application for asset management and information retrieval. Implementing these, we have achieved semantic linking of BIM and BMS data with laboratory inventory and chemical knowledge. Our approach can capture the crucial data points and reduce inventory processing time. All data provenance is recorded following the FAIR principles, ensuring its accessibility and interoperability.

Childhood maltreatment exposure is differentially associated with transdiagnostic perinatal depression symptoms

History of childhood maltreatment (CM) is common and robustly associated with prenatal and postpartum (perinatal) depression. Given perinatal depression symptom heterogeneity, a transdiagnostic approach to measurement could enhance understanding of patterns between CM and perinatal depression. MethodsIn two independently collected samples of women receiving care at perinatal psychiatry clinics (n = 523 and n = 134), we categorized longitudinal symptoms of perinatal depression, anxiety, stress, and sleep into transdiagnostic factors derived from the Research Domain Criteria and depression literatures. We split the perinatal period into four time points. We conducted a latent profile analysis of transdiagnostic factors in each period. We then used self-reported history of CM (total exposure and subtypes of abuse and neglect) to predict class membership. ResultsA three-class solution best fit our data. In relation to positive adaptive functioning, one class had relatively more positive symptoms (high adaptive), one class had average values (middle adaptive), and one class had fewer adaptive symptoms (low adaptive). More total CM and specific subtypes associated with threat/abuse increased an individual's likelihood of being in the Low Adaptive class in both samples (ORs: 0.90–0.97, p < .05). LimitationsGeneralizability of our results was curtailed by 1) limited racial/ethnic diversity and 2) missing data. ConclusionsOur results support taking a person-centered approach to characterize the relationship between perinatal depression and childhood maltreatment. Given evidence that increased exposure to childhood maltreatment is associated with worse overall symptoms, providers should consider incorporating preventative, transdiagnostic interventions for perinatal distress in individuals with a history of childhood maltreatment.

Evaluating fit indices in a multilevel latent growth model with unbalanced design: a Monte Carlo study

This study informed researchers about the performance of different level-specific and target-specific model fit indices in the Multilevel Latent Growth Model (MLGM) with unbalanced design. As the use of MLGMs is relatively new in applied research domain, this study helped researchers using specific model fit indices to evaluate MLGMs. Our simulation design factors included three levels of number of groups (50, 100, and 200) and three levels of unbalanced group sizes (5/15, 10/20, and 25/75), based on simulated datasets derived from a correctly specified MLGM. We evaluated the descriptive information of the model fit indices under various simulation conditions. We also conducted ANOVA to calculated the extent to which these fit indices could be influenced by different design factors. Based on the results, we made recommendations for practical and theoretical research about the fit indices. CFI- and TFI-related fit indices performed well in the MLGM and could be trustworthy to use to evaluate model fit under similar conditions found in applied settings. However, RMSEA-related fit indices, SRMR-related fit indices, and chi square-related fit indices varied by the factors included in this study and should be used with caution for evaluating model fit in the MLGM.

Fear, defense, and emotion: A neuroethological understanding of the negative valence research domain criteria.

We describe the close correspondence between predatory imminence continuum theory (PICT) and the National Institute of Mental Health's Research Domain Criteria (RDoC) for negative valence. RDoC's negative valence constructs relate aversively motivated behavioral reactions to various levels of threat. PICT divides defensive responses into distinct modes that vary along a continuum of the psychological closeness of predatory threat. While there is a close correspondence between PICT modes and negative valence threat constructs, based on PICT, we describe some potential elaborations of RDoC constructs. Both have consonant views of fear and anxiety and provide explicit distinctions between these emotional states, relating them to specific defensive behaviors and functions. We describe recent data that causally implicate human subjective emotional states with amygdala activity, which is also critical for defensive behavior. We conclude that attention to neuroethological views of defense can advance our understanding of the etiology and treatment of anxiety and stress disorders. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Life in a State of Limbo – Narratives of Place, Health, and Integration Among Later Life Female Migrants in Sweden

International migration is a prioritized domain of European aging research. Using a qualitative approach, the author has gathered accounts among Iranian later-life females in the Swedish city of Malmö, suffering from social isolation. The women in this article found themselves in a situation like that of other later-life migrants in Sweden. Several studies have shown how these groups are at risk of ending up in a social isolation which can be hard to break. The situation of the later-life migrant women discussed in this study is characterized by the loss of numerous deep-seated and natural social bonds connected to ethnicity, family, language, and culture. To cope with their exposed situation, the local Iranian-Swedish association provided some self-arranged activities, offering opportunities to social integration. The aim of the study is to demonstrate how the women described their life situation where a local day center made up the key foundation of their social life in  a Swedish city in 2000–2008. Typical of that period was that solutions of the alarming situation of some foreign-born elderly citizens were discussed by local authorities, as well as volunteer organizations. Thus, the aim is not to describe the present situation among later life migrants. On the contrary, the perspective is retrospective. The theoretical inspirations used in the article derive from a broader backdrop of social-constructive assumptions that define narratives or accounts as explanations of the reality of everyday life and experiences. In the article the women’s stories are defined as small, local, erratic narratives, nevertheless explaining the reality of everyday life and experiences which in their turn reflect the state of illness, locally specific attachment and social isolation. Three salient themes emerge in the material: place bound experiences, illness and unsuccessful integration. The narratives are defined as small irregular accounts, contrasting larger narratives of later-life migration. The article shows how the women depicted their situation as a borderline between an Iranian life in exile and a Swedish society, leaving them in a state of Limbo. The women expressed ambitions of integrate into a Swedish community of senior citizens, providing privileges and civil rights. Thus, the narratives challenge common generalizing images of later-life migrants and their life conditions.

Infants' reorienting efficiency depends on parental autistic traits and predicts future socio-communicative behaviors.

Attentional reorienting is dysfunctional not only in children with autism spectrum disorder (ASD), but also in infants who will develop ASD, thus constituting a potential causal factor of future social interaction and communication abilities. Following the research domain criteria framework, we hypothesized that the presence of subclinical autistic traits in parents should lead to atypical infants' attentional reorienting, which in turn should impact on their future socio-communication behavior in toddlerhood. During an attentional cueing task, we measured the saccadic latencies in a large sample (total enrolled n = 89; final sample n = 71) of 8-month-old infants from the general population as a proxy for their stimulus-driven attention. Infants were grouped in a high parental traits (HPT; n = 23) or in a low parental traits (LPT; n = 48) group, according to the degree of autistic traits self-reported by their parents. Infants (n = 33) were then longitudinally followed to test their socio-communicative behaviors at 21months. Results show a sluggish reorienting system, which was a longitudinal predictor of future socio-communicative skills at 21months. Our combined transgenerational and longitudinal findings suggest that the early functionality of the stimulus-driven attentional network-redirecting attention from one event to another-could be directly connected to future social and communication development.

Toward a sustainable research agenda on food eco-labelling in the business and management research domain

PurposeThis study aims to critically review the research on food eco-labels to identify research gaps and recommend future research directions in business and management.Design/methodology/approachA hybrid integrated review combines bibliometric analysis with an in-depth framework-based study of theory–context–characteristics–methodology (TCCM) and reviews quality research published over 21 years between 2002 and 2022.FindingsWe identify key research themes and the knowledge structure of food eco-label research. Future researchers should explore food eco-label dynamics and phenomena in areas related to consumer behaviour, information, consumer knowledge, environmental concerns, trust, packaging and willingness-to-pay as antecedent factors.Research limitations/implicationsThis review contributes to the business and management literature by quantifying existing research and consolidating its evolution. The articles were sourced from the established Web of Science (WoS) database. Other databases should be included in future reviews. We also focus on research published in business and management. Further studies could include research beyond such specialised domains.Practical implicationsConsumers need more information on the objectives and meaning of food eco-labels. The dissemination of knowledge on eco-labels, as well as effective communication and information on eco-labels, are relevant to future research issues.Social implicationsThe knowledge derived from this research holds significant potential in shaping policies and devising tools aimed at reducing the carbon footprint linked to food production and consumption. Considering the substantial impact of these activities on our planet’s carbon footprint, addressing food security and sustainability emerges as a crucial concern for humanity. Recognising the importance of eco-label communication and information becomes particularly pertinent for future generations, who stand to bear the most substantial impact of climate change and sustainable development. These generations are also more inclined toward embracing and implementing sustainable practices.Originality/valueThere are no comprehensive, integrated reviews exploring the methods, variables and constructs used in studies on food eco-labels based on all articles published in WoS journals in the business and management domains. This is the first comprehensive literature review using a hybrid approach (bibliometric review with TCCM framework) in the field of food eco-label research.

Evaluating visitors’ experience in museum: Comparing artificial intelligence and multi-partitioned analysis

Analysing visitors' behaviour in a museum or in a cultural site is a crucial element to manage spaces and artworks arrangement as well as improving the visit experience. This paper presents the preliminary results of the ARTEMISIA project, exploiting Artificial Intelligence (AI) techniques to study, design and develop a methodology to interpret visitors' behaviour within a museum context, namely the Museum of Rome in Palazzo Braschi (Rome, Italy). The aim is to combine literature on users' experience (UX) analysis with experimental data coming from the visitor anonymous tracking out of motion sensors (users' stand-still positions, viewpoint direction, movements), merging approaches of different research domains. Through the use of agglomerative hierarchical clustering algorithms, four categories of visitors were identified, then associated to user profiles emerged by UX evaluations. Such analysis may lead to new forms of visitors profiling and to the development of a new generation of customised applications in public and private contexts. Identifying and predicting users’ patterns with respect to museum halls arrangement may also be useful to suggest improvement in the museum spaces and exhibitions (new indications, updated storytelling or changes in thematic configuration).© 2023 Elsevier Ltd. All rights reserved.

EEG functional connectivity as a Riemannian mediator: An application to malnutrition and cognition.

Mediation analysis assesses whether an exposure directly produces changes in cognitive behavior or is influenced by intermediate "mediators". Electroencephalographic (EEG) spectral measurements have been previously used as effective mediators representing diverse aspects of brain function. However, it has been necessary to collapse EEG measures onto a single scalar using standard mediation methods. In this article, we overcome this limitation and examine EEG frequency-resolved functional connectivity measures as a mediator using the full EEG cross-spectral tensor (CST). Since CST samples do not exist in Euclidean space but in the Riemannian manifold of positive-definite tensors, we transform the problem, allowing for the use of classic multivariate statistics. Toward this end, we map the data from the original manifold space to the Euclidean tangent space, eliminating redundant information to conform to a "compressed CST." The resulting object is a matrix with rows corresponding to frequencies and columns to cross spectra between channels. We have developed a novel matrix mediation approach that leverages a nuclear norm regularization to determine the matrix-valued regression parameters. Furthermore, we introduced a global test for the overall CST mediation and a test to determine specific channels and frequencies driving the mediation. We validated the method through simulations and applied it to our well-studied 50+-year Barbados Nutrition Study dataset by comparing EEGs collected in school-age children (5-11 years) who were malnourished in the first year of life with those of healthy classmate controls. We hypothesized that the CST mediates the effect of malnutrition on cognitive performance. We can now explicitly pinpoint the frequencies (delta, theta, alpha, and beta bands) and regions (frontal, central, and occipital) in which functional connectivity was altered in previously malnourished children, an improvement to prior studies. Understanding the specific networks impacted by a history of postnatal malnutrition could pave the way for developing more targeted and personalized therapeutic interventions. Our methods offer a versatile framework applicable to mediation studies encompassing matrix and Hermitian 3D tensor mediators alongside scalar exposures and outcomes, facilitating comprehensive analyses across diverse research domains.

The relationship between ethnocentric behaviour and workforce localisation success: The mediating role of knowledge sharing tendency

Ethnocentric conduct among employees is observed in multicultural work environments characterised by the presence of individuals from diverse origins. The existence of ethnocentrism inside the workplace has been observed to have repercussions for colleagues. Nevertheless, despite the significance of the aforementioned factors, there hasn't been a considerable pertinent scholarly study on how these aspects affect the localisation of human resources. This research closes the gap in the literature by integrating ethnocentrism and human resource localisation variables. We used Andrew F. Hayes PROCESS V4.0 to assess the hypothesised relationship between employees' ethnocentric behaviour and human resource localisation success. In addition, employee knowledge-sharing tendency works as a mediator, and employee cultural intelligence (CQ) is a moderated mediator. From the analysis of 361 respondents from multinational Company (MNC) workers, we found that ethnocentric behaviour reduces employee knowledge-sharing tendency among workers and, in return, reduces human resource localisation success. However, CQ moderates the mediated relationship between employee knowledge-sharing direction and localisation success. We also found that when employees have high CQ, the negative effect of ethnocentrism on localisation success weakens. Managers of multicultural organisations should reduce ethnocentrism to ensure the success of human resource localisation. MNCs can consider employing culturally intelligent individuals and giving them sensitivity training. Future research can integrate other variables, such as the firm's cultural characteristics, to continue this research domain. Further research can also consider collecting data from nations with high cultural distances; comparative studies between two countries are also encouraged.

A restrictive design strategy of diffuse metasurfaces based on fibonacci sequences for RCS reduction

The rapid and efficient design strategy represents a highly intriguing research domain within the realm of metasurfaces. It necessitates minimizing the data load in coding metasurface design, facilitating the development of a precise approach to designing metasurfaces with specific characteristics. In this paper, we proposed a restrictive design strategy of metasurface for coding phase distributions based on the Fibonacci sequences, which is efficient to optimize designated radar cross section (RCS) reduction according to application requirements. Through the given restrictive strategy, the encoding range of the metasurfaces is reduced from the entire metasurfaces to the initial phase units in the corners, greatly reducing the total amount of data in the optimization database. In order to verify the availability of the strategy, RCS reduction metasurfaces with variable phase sequences in microwave region are analyzed. For broadband and wide-angle RCS reduction, the optimized Fibonacci discrete phase gradient (FDPG) metasurface is obtained by adjusting the phase sequences. Both the simulation and measured results show that the optimized FDPG metasurfaces by the proposed designing strategy have the RCS reduction of −10 dB in the frequency ranges of 6 GHz to 18 GHz under wide incidence angles from 0° to 30°. The simulated and measured results are good consistent over the whole frequency ranges and angle regions. This method combines mathematical sequences with physics organically, making it an important field in metasurfaces research and it is expected to play an important role in future studies.

Evolution and Dynamics of Technology Based Accounting Information: A Bibliometric Study

This bibliometric study delves into the evolution and dynamics of technology-based accounting information systems (AIS), exploring the intersection of technological advancements and accounting practices. The integration of technology in accounting has catalyzed significant transformations, reshaping how financial data is managed, analyzed, and reported. Through a comprehensive analysis of 780 publications spanning from 1977 to 2024, this research uncovers key trends, influential works, and emerging themes in the field of technology-based AIS. Utilizing bibliometric techniques such as co-citation analysis and network visualization, the study provides insights into the collaborative landscape, thematic clusters, and temporal trends within the domain of technology-based AIS research. The findings shed light on the evolution of AIS research, highlighting the increasing relevance of emerging technologies such as artificial intelligence and blockchain, while also identifying potential areas for future investigation.