Search Results (44)

Social media influencers strategically design the auditory and visual features of short videos to enhance consumer engagement. Among these, auditory emotional arousal and visual variation play crucial roles, yet their interactive effects remain underexplored. Drawing on multichannel integration theory, this study applies multimodal machine learning to analyze 12,842 short videos from Douyin, integrating text analysis, sound recognition, and image processing. The results reveal an inverted U-shaped relationship between auditory emotional arousal and consumer engagement, where moderate arousal maximizes interaction while excessively high or low arousal reduces engagement. Visual variation, however, exhibits a positive linear effect, with greater variation driving higher engagement. Notably, audiovisual congruence significantly enhances engagement, as high alignment between arousal and visual variation optimizes consumer information processing. These findings advance short video marketing research by uncovering the multisensory interplay in consumer engagement. They also provide practical guidance for influencers in optimizing voice and visual design strategies to enhance content effectiveness. Full article

Optimizing customer journeys is a critical challenge in e-commerce and financial services, attracting attention from marketing, operations research, and business analytics. Traditional customer analytics models, such as rule-based segmentation and regression models, rely heavily on structured transactional data, limiting their ability to capture latent behavioral patterns and adapt to multi-channel dynamics. These models often struggle to integrate unstructured data sources, failing to provide adaptive, personalized insights. To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. Empirical validation using Taiwanese financial institution data shows a 15% improvement in predictive accuracy compared to traditional machine-learning models, significantly enhancing customer lifetime value (CLV) predictions and multi-channel resource allocation. This research highlights the practical value of integrating structured and unstructured data for improving customer analytics. Our framework leverages LDA to extract behavioral patterns from customer interactions, enriching predictive models and enhancing real-time decision-making in financial services. Robustness checks confirm the scalability and adaptability of this approach, offering a data-driven strategy for long-term value optimization in dynamic digital ecosystems. Full article

This study examines the strategic decisions and profit dynamics of suppliers marketing their products through both offline and online channels, alongside online e-commerce platforms providing their own consumer credit services. We develop a model that incorporates consumer disposable income, channel preferences, and credit utility. Four supply chain scenarios are analyzed: wholesale and agency models with either private or open credit strategies. Using Stackelberg game theory, we explore suppliers’ sales model choices and the conditions under which platforms extend credit to offline channels. Our results show that increasing credit utility generally leads to higher equilibrium prices, while higher service fees compel suppliers to adjust their prices, favoring lower-cost channels. Notably, suppliers are more likely to adopt the wholesale model to secure platform credit for offline sales, especially when credit service fees or credit utility are high. Furthermore, platform credit strategies are strongly influenced by suppliers’ sales model choices: In wholesale models, platforms are more inclined to extend credit to offline channels under specific conditions of high disposable income (DPI) and credit utility, whereas in agency models, open credit strategies are only adopted when both DPI proportions and credit utility are low. This research provides new insights into how platforms can tailor credit offerings based on supplier strategies, offering a theoretical foundation for consumer credit policies in multi-channel sales environments and valuable guidance for managers in determining optimal channel strategies and credit service offerings. Full article

This paper presents the first systematic literature review (SLR) that includes the concept of an optichannel strategy, examining the main principles, key characteristics, and implications for retailers when switching from a multichannel to an optichannel approach. The SLR was made using Web of Science, Scopus, and Google Scholar to find literature on the optichannel model in retail. The results show a paradigm shift in retailing from a multichannel, passing through omnichannel and phygital, to an optichannel strategy. This shift means marketers are now adopting a more customer-centric approach to brand management and consumer behaviour. This article has practical and managerial implications for researchers and practitioners. For researchers, the study explains how retailers evolved from multi- to cross-, omni-, phygital, and optichannel strategies. For practitioners, this paper indicates future ways to allow retailers to manage their customers’ needs, ensuring a positive impact on customer experience and the company’s commercial and financial performance. Full article

Customer relationship management (CRM) has become a critical strategy for higher education institutions (HEIs) to enhance student engagement, institutional efficiency, and digital transformation. Despite its growing adoption, the evolution of CRM research in HEIs, including key contributors, dominant themes, and emerging trends, remains underexplored. This study conducts a bibliometric analysis of Scopus-indexed publications (2014–2024) to map the intellectual landscape of CRM research in higher education. Using Biblioshiny with Bibliometrix version 4.0 and VOSviewer version 1.6.20, this study analyzes publication trends, influential authors and institutions, keyword networks, and thematic developments. The findings indicate a transition from early research on service quality and academic reputation to advanced themes such as AI-driven CRM strategies, multi-channel communication, and social media analytics. While the United Kingdom, India, and Indonesia emerge as leading contributors, gaps persist in cross-cultural CRM applications, the integration of emerging technologies, and the development of standardized evaluation frameworks. This study contributes to CRM scholarship by mapping research trajectories, identifying underexplored areas, and offering actionable insights for future studies. It highlights the expanding role of CRM beyond student engagement, encompassing education quality, labor market, employment growth, technological progress and AI-driven decision-making. These findings emphasize the need for interdisciplinary approaches and robust academic performance to maximize CRM’s strategic potential in higher education. Full article

Live e-commerce has proliferated as a new business model in recent years. Live-streaming channel selection strategies and behavioral decisions are critical considerations for retailers to enhance business performance by increasing engagement and profitability. This study introduces the spillover effect between influencer and self-live-streaming channels, offering new theoretical insights into sustainable supply chain management from multichannel retailing, game theory, and spillover effects for channel selection and pricing, optimizing dual-channel tactics for inclusive marketing, and challenging pricing and channel effectiveness beliefs. Hence, inclusive and sustainable business practices in live e-commerce have been examined, focusing on dual-digital-channel strategies involving influencer marketing and self-live-streaming. This paper investigates three digital supply chain structures for sustainability, which are based on influencer characteristics: the single digital channel ($S)$, the dual-digital-channel structure without spillover effect ($D^N$), and the dual-digital-channel structure with spillover effect ($D^S$). This study employs Stackelberg game models to analyze behavioral, pricing, and channel preferences, and it also extends the model to offline channels. This study finds that (a) influencer effort affects influencer live-streaming pricing, which may not always be cheaper than self-streaming digital channels; (b) commission rates significantly impact influencer pricing strategies, leading retailers to use skimming and penetration pricing strategies when commission rates are low and high; and (c) retailers may develop influencer live-streaming channels if the cross-price coefficient is medium and low but prefer it when the coefficient and spillover impact are large. By analyzing how these digital channels contribute to societal sustainability through reduced environmental impact and enhanced social inclusion, this research highlights key marketing decisions that optimize business performance and social responsibility in the digital economy. It offers live e-commerce managers strategic channel selection, pricing, and sustainability advice and recommendations for future empirical validation to enhance practical applicability. Full article

In response to the global imperative of mitigating greenhouse gas emissions (GHGs) and the shifting landscape of business models toward multi-channel structures, this study delves into the intricacies of a green supply chain. Operating through both online and traditional channels with uncertain demands, the producer’s distribution strategy prompts an exploration of supply chain dynamics. Utilizing an integer programming model, this study calculates optimal prices, optimizes total profit, and minimizes transportation costs to curtail carbon dioxide emissions, depending on the transportation mode. Additionally, this study incorporates renewable energy sources into the production and transportation processes to further minimize carbon dioxide emissions. The integration of renewable energy not only supports environmental goals, but also contributes to the overall profitability of the supply chain by reducing energy costs. Employing a theoretical technique for linearization, the model, resolved through the Jimenez and TH methods, demonstrates efficacy in reconciling economic and environmental goals. The Jimenez method enables the transformation of fuzzy parameters into deterministic equivalents, allowing for a more reliable optimization during uncertainty, while the TH method provides an interactive fuzzy multi-objective approach, aligning the model’s dual objectives for both economic and environmental goals. Notably, when transportation costs to both markets are equal, the model prioritizes devices with a lower environmental impact, showcasing adaptability. Furthermore, the proposed solution empowers decision makers to influence pricing and enhance the entire supply chain’s profitability. In conclusion, this research offers nuanced insights, strategically aligning economic viability with environmental sustainability in the discourse on green supply chains. Full article

This study investigates the sustainable operations of a multi-brand restaurant that adopts multiple brands in a store, unlike a typical restaurant that operates only a single brand. We introduce five restaurant operation models, including three traditional single-brand ones (offline, online, and multi-channel) and two recent multi-brand restaurants with a single fixed franchise fee and multiple franchise fees proportional to the number of brands. We then investigate the performance of the models in the changing market and cost environments. Through analytical and numerical analyses, we reveal that adopting a multi-brand restaurant does not always guarantee superior profit performance. Such an adoption is recommended under certain conditions, such as when the potential market base is large, consumers are not very price-sensitive, food and delivery costs are low, an increase in food items does not significantly impact process inefficiency, franchise fees are low, or the relative market power of multiple brands is strong. Otherwise, adopting the traditional single-brand restaurant would guarantee better profit performance. Therefore, for a sustainable multi-brand restaurant adoption, it is important to create a business environment that can lower food prices, and a thorough understanding of the decision dynamics related to the number of brands is required. Full article

This study focuses on the effect of multichannel marketing communication in retail pharmacies to establish customer satisfaction in a world experiencing the digitalization of health sectors. The objective of the study is to understand customer acquisition and retention practices, the role of online and offline integrated communication, and the extent of customer preference for various marketing communication channels. As part of the study, the quantitative analysis of the publications included in the review was made using articles and reports published from 2014 to 2024. The review was conducted on the aspects of marketing using multiple channels in retail pharmacy and the healthcare-associated fields. The studies identified that comprehensive communication channel enhancement policies positively affect the generation of revenues, reduction in costs, and information delivery schedules in pharmaceuticals. Depending on the channel, consumers’ needs and wants differ, and there is success in personalizing and presenting reasonably logical thoughts to people. Synchronicity of online and offline communication effectively increases the customers’ power, trust, and satisfaction. E-marketing has always been significant in enhancing customers’ touch points, which is why digital transformation is vital. This study further supports the fact that multichannel marketing is mandatory for the success of a retail pharmacy in the prevalent, highly competitive environment. The implementation also presupposes knowledge of consumer differences, the synergy of online and offline contacts, the emphasis on personalization, and fast adaptation to the changing technological environment, but often within the framework of severe legislation. Full article

Assessing the olfactory preferences of consumers is an important aspect of fragrance product development and marketing. With the advancement of wearable device technologies, physiological signals hold great potential for evaluating olfactory preferences. However, there is currently a lack of relevant studies and specific explanatory procedures for preference assessment methods that are based on physiological signals. In response to this gap, a synchronous data acquisition system was established using the ErgoLAB multi-channel physiology instrument and olfactory experience tester. Thirty-three participants were recruited for the olfactory preference experiments, and three types of autonomic response data (skin conductance, respiration, and heart rate) were collected. The results of both individual and overall analyses indicated that olfactory preferences can lead to changes in skin conductance (SC), respiration (RESP), and heart rate (HR). The trends of change in both RESP and HR showed significant differences (with the HR being more easily distinguishable), while the SC did not exhibit significant differences across different olfactory perception preferences. Additionally, gender differences did not result in significant variations. Therefore, HR is more suitable for evaluating olfactory perception preferences, followed by RESP, while SC shows the least effect. Moreover, a logistic regression model with a high accuracy (84.1%) in predicting olfactory perception preferences was developed using the changes in the RESP and HR features. This study has significant implications for advancing the assessment of consumer olfactory preferences. Full article

Trace elements such as cobalt (Co), molybdenum (Mo), and zinc (Zn) play necessary roles in different biological functions. Co is a microelement that influences the vascular system. Mo works as an enzymatic cofactor of three enzymes (aldehyde oxidase, sulfite oxidase, and xanthine oxidase dehydrogenase). However, these elements are difficult to detect, since the analytical methods developed have a high cost, which restrict their applicability. In this sense, fluorescent sensors are an alternative for detecting trace elements, such as Mo⁴⁺ ions. Herein, a new multichannel trace elements sensor has been proposed to detect Mo entities. In this sense, two different N-CQDs were synthesized and fully characterized. The N-CQDs presented quantum yield values of 25.93% and 6.02% and excellent solubility in water. Also, a mixture of these two carbon-based nanoparticles was used to identify and to quantify Mo in water between seven different trace elements. The method was found to reach 1.28 and 3.88 ppm for limit of detection (LOD) and quantification (LOQ), respectively. To further verify the potential of the detection platform, the multichannel sensor was applied to identify the different concentrations of metal ions (Fe²⁺, Co²⁺, Mn²⁺, Cu²⁺, Zn²⁺, Mg²⁺, and Mo⁴⁺) in water. The data matrix was treated using different algorithms, such as K-Means and Discriminant Analysis (DA). The detection strategy has successfully identified the molybdenum ions at 5 ppm. This result shows the potential application of a multichannel sensor toward the detection of Mo entities, since it is comparable with the molybdenum test already available on the market. Full article

In the realm of multichannel digital retailing, free shipping has gained popularity as a promotion strategy. However, few studies have investigated how retailers make decisions regarding free shipping. Furthermore, concerns have arisen regarding the sustainability of free shipping promotions for manufacturers. This research employs a simultaneous equation model with fixed effects to explore the determinants of market structure concerning the proportion of retailers offering free shipping and its impact on manufacturers’ product sales. As per our current knowledge, this research is pioneering in establishing a causal relationship between the percentage of free-shipping retailers and manufacturers’ product sales. Specifically, an increase in the percentage of retailers employing free shipping leads to higher product sales, while lower product sales drive increased retailers to adopt free shipping. Our findings indicate that competition among products has a significant positive effect on the percentage of retailers offering free shipping in the interactive relationship. Furthermore, increased competition among retailers results in more retailers adopting free shipping strategies. These results affirm the efficacy of free shipping as a promotional approach to increase manufacturers’ product sales, particularly in highly competitive markets. Full article

Over the past few years, there has been increased interest in photoplethysmography (PPG) technology, which has revealed that, in addition to heart rate and oxygen saturation, the pulse shape of the PPG signal contains much more valuable information. Lately, the wearable market has shifted towards a multi-wavelength and multichannel approach to increase signal robustness and facilitate the extraction of other intrinsic information from the signal. This transition presents several challenges related to complexity, accuracy, and reliability of algorithms. To address these challenges, anomaly detection stages can be employed to increase the accuracy and reliability of estimated parameters. Powerful algorithms, such as lightweight machine learning (ML) algorithms, can be used for anomaly detection in multi-wavelength PPG (MW-PPG). The main contributions of this paper are (a) proposing a set of features with high information gain for anomaly detection in MW-PPG signals in the classification context, (b) assessing the impact of window size and evaluating various lightweight ML models to achieve highly accurate anomaly detection, and (c) examining the effectiveness of MW-PPG signals in detecting artifacts. Full article

The prosperity of e-commerce has made more and more businesses willing to enter the e-commerce market, which has also brought a series of strategic collaboration between firms. This study considers game models with and without collaboration between the platform and the retailer. An e-commerce platform has relative logistics service sharing advantages while the retailer has relative procurement advantages. We formulated a multichannel supply chain consisting of a manufacturer and two retailers to explore the feasibility of the above strategic collaboration model. We utilized the Stackelberg game and Nash game approaches to obtain equilibrium solutions under both cooperative and noncooperative scenarios. Through a further analysis, we determined the impacts of the logistics sensitivity, the cost of the unit logistics service effort, the price of shared logistics service per unit, and the price competition intensity on optimal prices, the logistics service efforts, and the profits. Moreover, the collaborative exchange of advantages between the platform and the retailer needs to consider the interests of participating manufacturers in the game. Our extension suggests all three firms should actively promote deeper collaboration. Full article

The tourism industry has faced several challenges over the years, due to the evolution of technology and behavioral changes of the generations. The research focused on the new generation of tourists, Generation Z. Known as digital natives, the study aimed to identify their current travel behavior in the digital age and their perception of the future of travel in the context of recent technological developments, namely artificial intelligence, and virtual reality, thus highlighting specific elements that could disrupt the travel industry. To achieve this goal, qualitative research was conducted, using two sessions of focus groups among 20 Generation Z tourists. The results show that Generation Z tourists exhibit disruptive behavior primarily due to their heavy reliance on social media platforms, even for travel purposes. Social media has become their primary search engine, and travel influencers hold significant sway over certain individuals in this generation. In addition, they serve as influencers, by sharing visual content from their travels. Another noteworthy trend in the travel industry is Generation Z’s inclination towards multi-channel booking, effortlessly switching between different booking options. Lastly, although the results show little awareness of the potential of advanced technologies, their openness to adopt them to simplify the travel planning process further contributes to the disruption of traditional travel patterns. Generation Z can be considered a bridge between previous and future generations. The study has implications for management and marketing activities in the tourism field. Full article