Abstract:The rapid development of digital technologies has significantly transformed marketing practices and consumer behavior. In recent years, digital marketing, particularly through social media platforms, has become an essential…
ial strategy for firms to enhance consumer engagement and influence purchase decisions. Despite the growing body of literature, the relationships among social media marketing, brand trust, customer preference, and purchase decision remain fragmented across previous studies. Therefore, this study aims to provide a comprehensive overview of the research landscape and identify emerging trends in this field. This study employs a Systematic Literature Review (SLR) combined with bibliometric analysis to examine publications related to social media marketing, brand trust, customer preference, and purchase decision. Data were collected from the Scopus database covering the period from 2021 to 2026. Bibliometric mapping and keyword co-occurrence analysis were conducted using VOSviewer to identify research clusters, thematic structures, and the evolution of research topics. The findings reveal a significant increase in publications on social media marketing and consumer behavior, indicating growing academic interest in this domain. The bibliometric analysis shows that social media marketing acts as a central theme connecting key variables such as brand trust, customer preference, and purchase intention/decision. Furthermore, overlay visualization indicates that emerging research topics include consumer engagement, influencer marketing, electronic word-of-mouth (e-WOM), and perceived value, reflecting a shift toward a more integrated and experiential understanding of consumer behavior in digital environments. This study contributes to the literature by mapping the intellectual structure and research evolution in the social media marketing domain and highlighting potential directions for future research. The findings also provide insights for researchers and practitioners in developing more effective and trust-oriented digital marketing strategies to influence consumer purchase decisions
Abstract:The rapid development of digital technology and social media platforms has significantly transformed consumer purchasing behavior, particularly in relation to digital products. Social media has evolved beyond its traditional…
onal role as a communication platform and now functions as an important environment where consumers discover, evaluate, and purchase products. This study aims to explore the psychological factors that influence consumer decision-making in purchasing digital products through social media platforms. A qualitative research approach was employed to gain an in-depth understanding of consumers' experiences and perspectives. Data were collected through semi-structured in-depth interviews with social media users who had purchased digital products based on information encountered on social media platforms. The collected data were analyzed using thematic analysis to identify patterns and themes related to consumer psychology in digital purchasing behavior. The findings reveal that consumer decision-making in purchasing digital products is influenced by several interconnected psychological and social factors. Five major themes emerged from the analysis: social media as a discovery environment, cognitive evaluation of digital products, trust formation and credibility cues, psychological motivations for purchasing digital products, and social influence from peers, influencers, and online communities. The results indicate that social media plays a significant role not only in introducing digital products but also in shaping consumer perceptions, trust, and purchase intentions. Consumers actively interpret information obtained from social media, evaluate product credibility through reviews and recommendations, and rely on social interactions to reduce uncertainty before making purchase decisions. This study contributes to the understanding of consumer psychology in digital environments by highlighting how psychological motivations and social influences interact within social media platforms to shape digital purchasing decisions. The findings also provide practical insights for digital marketers and product creators to design more effective strategies that emphasize authenticity, trust-building, and community engagement in promoting digital products.
Abstract:The persistent gap between theoretical instruction and real-world practice remains a critical challenge in business education, particularly in contexts involving Micro, Small, and Medium Enterprises (MSMEs). Experiential…
learning has been promoted as a pedagogical response to this challenge; however, many initiatives lack structured frameworks that integrate student learning with meaningful community engagement. This study examines the implementation of the BRIDGE model (Build, Reach, Discover, Grow, and Elevate) as a structured business mentoring approach grounded in experiential learning principles. Using a qualitative participatory action research design, the study involved 15 undergraduate business students and five MSMEs in Semarang City, Indonesia. Data were collected through participant observation, in-depth interviews, focus group discussions, reflective journals, and program documentation, and analyzed using thematic analysis. The findings indicate that the BRIDGE model facilitates deep experiential learning by enabling students to connect theoretical concepts with contextual business realities, while simultaneously generating instrumental and symbolic benefits for MSME partners. Despite limitations related to program duration, the model demonstrates strong potential as a feasible and transferable framework for experiential business education in emerging economy contexts.
Abstract:This research aims to examine and analyze the influence of brand image on the purchasing decisions of students at the Faculty of Economics, Nias University, in the context of online shopping. The background of this study…
stems from the rapid growth of e-commerce in Indonesia, which has significantly changed consumer shopping behavior, particularly among students who are highly adaptive to digital technology. In online shopping situations, where consumers cannot physically assess the product, brand image becomes one of the main factors influencing consumer trust, perceived quality, and confidence in making purchasing decisions. The type of research employed is quantitative research with a survey approach. The study population consisted of 1,959 active students of the Faculty of Economics, Nias University, with a sample of 95 respondents determined using the Slovin formula. Data were collected using a Likert-scale questionnaire covering brand image indicators (strength, favorability, and uniqueness of brand association) as well as purchasing decision indicators (problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior). The data were analyzed using validity and reliability tests, simple linear regression analysis, t-test, and determination test with the aid of SPSS software. The results of the study indicate that brand image has a positive and significant effect on students' purchasing decisions in online shopping. This finding implies that the stronger the brand image, the higher the tendency of students to make online purchases. Therefore, companies or online businesses need to develop and strengthen their brand image through consistent marketing communication strategies, clear product information, and credible brand reputation to increase consumer loyalty and purchase intention.
Abstract:The focus of research shifts from the dominance of positivism to a non-positivistic approach that places meaning, interpretation, and social construction at the center of analysis. One of the main approaches within this…
paradigm is Grounded Theory Research (GTR), a qualitative method developed by Glaser and Strauss (1967) to build empirically data-based theory through a rigorous inductive process. In the accounting context, GTR becomes increasingly relevant because reporting practices, accountability, and financial decision-making cannot be understood solely through objective measurements, but rather through social interactions, organizational values, and the interpretations of the actors involved (Ahrens & Chapman, 2006). This article aims to examine the role and relevance of GTR in modern accounting research by highlighting its philosophical foundations, methodological procedures, and contributions to the development of practice-based accounting theory. Through a systematic literature review, it is found that GTR has the ability to uncover the social dynamics that shape accounting practices such as accountability, ethics, managerial control, and institutional legitimacy that have previously been overlooked by positivistic approaches (Charmaz, 2006; Bryant & Charmaz, 2007). GTR has also proven relevant in the context of changing reporting systems, accounting digitalization, and the integration of sustainability principles such as ESG, where meaning, professional identity, and interpretive processes are dominant elements (Adams & Larrinaga, 2019). The study's findings confirm that GTR not only offers a systematic method for data collection and analysis, but also provides a more reflective, context-sensitive epistemological framework capable of generating substantive theory that is truly rooted in organizational reality. Thus, GTR is a powerful methodological alternative in enriching accounting knowledge, while providing a deeper understanding of how accounting practices are executed, negotiated, and interpreted in everyday organizational life.
Abstract:This study aims to determine the Effect of Raw Material Inventory Management on Work Productivity of PT. KSS (Karunia Sejahtera Sejati) Nias Branch. The research method used is a quantitative approach. The sample in this…
study amounted to 31 respondents. Data collection techniques were carried out through the distribution of questionnaires and documentation. Data analysis techniques used simple linear regression analysis, classical assumption tests, coefficient of determination tests and t-tests with the help of the SPSS version 25 statistical application. The R2 Determination Test that has been carried out obtained the result that the R2 value is 0.620. This shows that the Raw Material Inventory Management variable (X) can explain Work Productivity (Y) by 62%, while the remaining 38% is explained by other factors not covered in this study. Based on the data analysis, it shows that simultaneously the Raw Material Inventory Management variable has a positive and significant effect on Work Productivity with a significance of 0.000 <0.05 and the T-value obtained is 6.877> 1.696 so that it can be concluded that Ha is accepted and has an effect on the dependent variable of Work Productivity (Y). The conclusion of this study is that the Raw Material Inventory Management variable partially or simultaneously has an effect on Work Productivity and it is recommended that PT. KSS (Karunia Sejahtera Sejati) provide increased competency and understanding of employees regarding inventory management that is very necessary so that they are able to carry out their tasks more efficiently and effectively, so that work productivity increases. Periodic training and socialization regarding inventory management and its relationship to work productivity must continue to be carried out.
Abstract:In recent years, the housing market has faced significant challenges, including fluctuating prices and declining sales. To solve this issue, there was an increasing need for more sophisticated methods to predict housing…
prices accurately. This study aimed to provide real estate marketers with a tool to enhance their pricing tactics and mitigate the decline in home sales by predicting house prices using machine learning techniques. Several parameters were considered in this study, such as location, number of bedrooms, number of bathrooms, land area, building area, and number of carports. Linear regression and neural network methods were used to develop predictive models. The findings showed that the neural network method was more accurate than linear regression, which made it a better tool for real estate pricing strategies, with land area and number of carports being the most influential aspects in house price prediction.
Abstract:The increased integration of operational technology (OT), Internet of Things (IoT), and business IT systems has allowed sophisticated attackers to circumvent isolated security features and launch cross-platform assaults.…
Current fragmented techniques, with discrete detectors monitoring Modbus, Kubernetes, MQTT, or other domain-specific protocols, cannot handle cross-system risks. These methodologies overlook 68% of multi-vector marketing that uses both physical and digital channels. This study introduces a transfer learning architecture to integrate detection capabilities by correlating threats across protocols, devices, and settings. The architecture generates a unified feature space that extracts behavioral semantics from industrial control system logs, cloud telemetry, network traffic, and device-level signals to produce protocol-agnostic threat representations. Adversarial domain adaptation and semantic graph embeddings enable cross-domain knowledge transfer with minimum retraining. Security teams may now discover kill chains like infected cloud containers preceding illegal PLC command execution every 23 minutes. Validated against real-world attack datasets from water treatment facilities (OT) and cloud infrastructure (IT), the system achieved 93.4% cross-platform attack recall, a 41.3 percentage point improvement over prior methodologies. It reduced OT data labeling by 89% and false positives by 93.5%. This paradigm shift transforms threat correlation from a reactive, domain-specific process to adaptive intelligence, boosting resilience for critical infrastructure, industrial ecosystems, and smart environments facing cyber-physical hazards. The framework's practical validation in energy, industry, and vital infrastructure shows its importance in protecting an increasingly linked world.
Abstract:Islamic views on property ownership depart from the notion that individuals have an innate desire to possess property (fithrah), as Islamic societies depend on other people to function. The riches or money that Allah SWT…
has bestowed upon this universe is a gift to humanity and should be used as efficiently as possible to ensure everyone's financial security. One topic covered in economics classes, including socialism, capitalist, and Islamic economics, is ownership rights. Ownership rights are determined by certain characteristics of each economic system. The number of assets (goods and services) that can be owned is limited under a socialist economy, but the method of acquisition (quality) remains unconstrained. This suggests that you can distribute it in whatever way you want. Meanwhile, the capitalist economic system views property ownership as unlimited, both in terms of quantity and quality; that is, any kind of property ownership is acceptable as long as it does not restrict the freedom of others. Islam acknowledges, but does not fully give, the right of humans to own the materials they use for production and consumption, in contrast to socialism and capitalist economic systems.
Abstract:Artificial intelligence is likely to have a significant impact on marketing strategies and customer behaviors in the years ahead. Research in this field has grown considerably, demonstrating AI's ability to simulate human…
n behavior and perform tasks intelligently. With growing interest among marketing researchers and practitioners, this research aims to provide an overview of the evolution of both marketing and AI research fields. This paper explores the emerging role of artificial intelligence in personalized engagement marketing, which focuses on creating, communicating, and delivering customized offerings to customers. Utilizing the Systematic Literature Review technique, we examined over 300 academic articles to uncover prevalent themes and gain a deeper understanding of current AI utilization in marketing. We then propose a plan for future research that examines potential changes in marketing strategies and customer behaviors while emphasizing critical policy considerations related to privacy, bias, and ethics. The implications for marketing managers are discussed along with predictions about how AI will impact branding and customer management practices going forward. Our research highlighted several benefits of integrating AI into marketing such as improved customer interactions, increased revenue, reduced expenses, and enhanced overall efficiency. However, this research also pointed out areas requiring further investigation including challenges posed by AI integration like shortage of skilled personnel and data privacy concerns.