- P-ISSN1738-3110
- E-ISSN2093-7717
- SCOPUS, ESCI
ISSN : 1738-3110
Vol.23 No.9
Abstract
Purpose: Charitable and humanitarian supply chains have long suffered from inadequate funding and resource management, misappropriation, corruption, and distribution imbalances, severely undermining organizational credibility, donor motivation, and impediments to achieving philanthropic goals. This study examines how blockchain technology enhances supply chain transparency and integration in Chinese charitable organizations while assessing the moderating effects of external challenges through an integrated Technology-Organization-Environment and institutional theory lens. Research design, data, and methodology: Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the authors analyzed survey data from 298 blockchain-exposed China Charity Federation (CCF) members. Results: Blockchain adoption significantly improves transparency and integration. External challenges asymmetrically moderate these relationships: regulatory pressures weaken transparency gains while technical standards strengthen integration A self-reinforcing cycle emerges between transparency and integration, driven by standardized protocols like blockchain-audited financial reports. Conclusions: Blockchain serves as both a technological solution and a governance paradigm for charitable supply chains. Drawing empirical insights from China's charitable ecosystem, this study proposes a framework with broader applicability to other models of charitable coordination. The research elucidates blockchain's potential to enable charitable organizations and their supply chains globally to reconcile ethical accountability with operational efficiency amid increasing digitization of humanitarian service delivery.
Abstract
Purpose: This study aims to extract strategic insights into startup success by applying interpretable machine learning techniques within the context of Management Technology and entrepreneurial strategy. It addresses the challenge of balancing predictive accuracy with transparency by incorporating explainable artificial intelligence (XAI) into the model development process. Research design, data and methodology: Utilizing data from 923 startups listed on Crunchbase, the study focuses on key features such as total funding, team size, investor relationships, investment stages, industry sector, and geographic distribution. Three machine learning models—Logistic Regression, Random Forest, and XGBoost—were employed to classify startup success. To ensure interpretability, SHAP (Shapley Additive Explanations) was used for both global and local explanations of model predictions. Results: Among the models, XGBoost demonstrated superior predictive performance with an accuracy of 84% and an AUC-ROC score of 0.90. SHAP analysis revealed that total funding, professional relationships, and number of funding rounds were the most significant predictors of success, while industry type and location had a marginal influence. Conclusions: This research presents a replicable, data-driven framework that integrates predictive analytics with interpretability. The results offer actionable implications for founders, investors, and policymakers involved in startup incubation, venture capital, and entrepreneurial ecosystem development.
Abstract
Purpose: This study aims to analyze how six logistics service quality components impact customer satisfaction and loyalty in the context of e-commerce distribution in Vietnam. It focuses on exploring how these elements, including customer service, delivery service, reverse logistics, product quality, product availability, and information quality influence customer satisfaction and loyalty. Research Design and Methodology: A mixed-methods approach was adopted, combining qualitative interviews with a quantitative survey conducted between January and May 2025. Using non-probability sampling, 327 valid responses were collected from online customers. Structural Equation Modeling (SEM) was used to analyze the relationships between the six aforementioned elements, customer satisfaction, and loyalty. Results: The findings show that five components - customer service, delivery service, reverse logistics, product quality, and product availability - positively influence customer satisfaction. Among them, product availability shows the strongest effect, whereas information quality has no significant impact. The results also confirm that higher customer satisfaction leads to greater customer loyalty. Conclusions: This study contributes to the understanding of logistics service impacts in digital marketplaces. It offers practical implications for e-commerce firms and policymakers aiming to enhance service performance, improve customer satisfaction, and foster long-term customer loyalty in competitive online environments.
Abstract
Purpose: This study examines the pivotal roles of configuration, collaboration, and coordination in enhancing supply chain performance within the tourism industry, which remains underexplored. These elements are crucial for optimizing operational efficiency; however, their combined impact, particularly under the moderating influence of governmental policies, requires further investigation. Grounded in supply chain management theory, this research elucidates how strategic configuration of supply chain networks, robust stakeholder collaboration, and effective operations coordination contribute to performance improvements. It also highlights the moderating role of governmental policies in amplifying these effects through a supportive regulatory framework.. Research design, data and methodology: Empirical data were gathered from 350 tourism industry managers and analyzed using SmartPLS 4.0 to assess the relationships among variables. Results: The results confirm that configuration, collaboration, and coordination significantly enhance supply chain performance. Governmental policies moderate these relationships, strengthening the effects of configuration and coordination on performance, while their influence on collaboration is minimal, thereby enhancing overall efficacy. Conclusions: These findings enrich the theoretical understanding of supply chain dynamics in tourism and offer practical guidance for tourism managers to optimize performance through strategic configurations, enhanced collaboration, and efficient coordination. Policymakers can support these efforts by implementing regulations that promote sustainable industry growth.
Abstract
Purpose: This study investigates the influence of Electronic Word-of-Mouth (eWOM) on consumers’ online purchase intentions, focusing on its mediating mechanisms via argument quality, source credibility, and customer involvement. It further examines the implications for distribution channels, e-commerce logistics, and supply chain management in Vietnam’s rapidly evolving digital trade environment. Research Design, Methodology, and Approach: Drawing on the Elaboration Likelihood Model (ELM) and Purchase Behavior Theory (PBT), an online survey was conducted with 240 valid responses from Vietnamese consumers. The measurement model was assessed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and hypotheses were tested via Structural Equation Modeling (SEM) with SPSS and AMOS. Results: Argument quality and source credibility significantly affect eWOM effectiveness, whereas customer involvement demonstrates no significant impact. EWOM strongly predicts online purchase intentions, accounting for 59.2% of its variance. Conclusions: eWOM is pivotal for building consumer trust and shaping purchasing behaviors in digital marketplaces. These findings enrich ELM and PBT, and provide practical insights for enterprises to enhance distribution efficiency, logistics responsiveness, and customer engagement through credible eWOM strategies. This research underscores how eWOM analytics can support logistics planning and supply chain agility, ensuring improved product availability and delivery performance in competitive e-commerce environments.
Abstract
Purpose: In the era of digital transformation, mobile commerce plays an important role in promoting the operational efficiency of retail businesses. This study aims to consolidate the theoretical understanding of Vietnamese consumers’ usage intention of m-commerce, thereby helping retail enterprises make decisions regarding mobile retail channels. Research design, data and methodology: The research framework was developed from integrating the FFM model and the UTAUT model. The survey data from 343 Vietnamese mobile phone users were analyzed using the PLS-SEM model. Results: The results confirmed the impact of extraversion, neuroticism, conscientiousness, and openness on effort expectation, performance expectation, and then on the intention to use m-commerce. Unlike other personality traits, agreeableness only had a positive effect on effort expectation but had an insignificant impact on performance expectation. Conclusions: These findings significantly enhance understanding of the influence of personality traits on mobile commerce usage intention, mediated by effort and performance expectation. The results enable mobile retail businesses to formulate targeted strategies by leveraging insights into how these personality dimensions shape consumer perceptions in using mobile commerce. This understanding can effectively stimulate consumer purchases on their platforms and subsequently aid in optimizing mobile retail distribution by streamlining the entire product flow from supplier to consumer.
Abstract
Purpose: This study examines the role of perpetual convertible bonds (CBs) as restructuring instruments in Korea’s logistics and shipping industry. It specifically focuses on the dilution of shareholder value upon CB conversion into equity and the resulting conflicts between creditors and existing shareholders. Despite these risks, perpetual CBs are frequently used to stabilize distressed firms, especially through state-owned financial institutions. Research Design, Data, and Methodology: A qualitative case study method analyzes the case of HMM. The analysis draws upon academic literature, analyst reports, public disclosures, and financial news. The study investigates how the issuance and conversion of perpetual CBs affected HMM’s corporate governance, market valuation, and investor sentiment. Results: The findings reveal that while CBs offer short-term liquidity and balance sheet improvement, their conversion leads to substantial equity dilution and loss of value for minority shareholders. HMM’s case highlights how ambiguous dividend policies, excessive cash reserves, and concentrated public ownership contribute to continued undervaluation. Unresolved CB obligations further hinder attempts at privatization. Conclusion: The study recommends policy reforms to strengthen disclosure standards, enhance governance transparency, and protect shareholder rights. These measures are critical for improving the effectiveness and sustainability of mezzanine financing in corporate restructuring practices.
Abstract
Purpose: This study empirically examines the determinants of business performance among Korean export firms in the distribution sector during the COVID-19 pandemic. The study compares two types of internationalized firms—Traditional Internationalizers (TIs) and Born Globals (BGs)—based on different paths of internationalization. Research design, data and methodology: Drawing on the Resource-Based View, Dynamic Capabilities Theory, and Network Theory, this study uses Export Capability, Human Capital, and International Customer Quality as independent variables. Control variables include firm size, firm age, and export intensity. The analysis is based on 664 firms from KOTRA’s Global Competency Level Test data, using factor analysis, correlation, and multiple regression. Results: The findings show that Export Capability and International Customer Quality positively affect business performance in both TIs and BGs. Human Capital significantly influences BGs’ performance but not that of TIs. Firm size and export intensity were also found to be positively related to business performance. Conclusions: The results suggest that export-oriented capabilities and global buyer quality are key performance drivers regardless of internationalization type. For Born Globals in particular, securing globally competent human resources plays a critical role in overcoming structural limitations and enhancing early-stage international success.
Abstract
Purpose: This study investigates the supply chain of recovery among middle-aged women who transformed burnout into mindful teaching. By conceptualizing recovery and teaching as distributional flows, it traces the logistical “paths” through which mindfulness-based stress reduction (MBSR) practices move from personal healing to pedagogical delivery, sustaining both resilience and professional presence. Research design, data and methodology: Seven women who experienced burnout and later completed MBSR instructor training were interviewed in-depth. Colaizzi’s descriptive phenomenological method was applied to capture key distribution nodes in their recovery process. Data analysis mapped the experiential supply chain, identifying critical transfer points from individual healing practices to instructional embodiment. Results: Five thematic distribution hubs emerged: burnout as demand shock, entry into mindfulness as supply input, transformation as process realignment, practice as restorative logistics, and integration as final delivery. Participants reported improved emotion regulation and nonjudgmental awareness, which circulated into their teaching, reinforcing both personal recovery and mindful instruction. Conclusions: Mindfulness operated not merely as a stress-relief product but as a supply framework enabling identity reconstruction and ethical teaching. Through sustained engagement, participants achieved resilience and compassion, which were redistributed into educational contexts. These findings suggest that MBSR functions as a self-sustaining supply chain of healing and mindful pedagogy.
Abstract
Purpose: This study reviews recent trends and future directions in performance distribution and path management of soccer players using GPS and wearable technologies. The purpose is to synthesize advances in monitoring movement, workload, and spatial patterns, and to explore implications for training optimization, tactical strategies, and sports science innovation. Research design, data and methodology: A literature review was conducted using academic databases and industry reports, focusing on GPS tracking, wearable sensors, and performance analytics in soccer. Studies were categorized into themes: workload distribution, positional path analysis, and injury prevention. This systematic synthesis highlights both technological capabilities and practical applications in elite soccer contexts. Results: Findings show that GPS and wearable technologies provide valuable insights into player movement, intensity, and workload distribution. Performance data enhances tactical decision-making, supports individualized training, and reduces injury risk. Emerging studies suggest integration with AI-based models, enabling predictive performance management and real-time adjustments in both professional matches and training. Conclusions: The review concludes that GPS and wearable technologies are transforming performance distribution and path management in soccer. However, challenges remain regarding data standardization, privacy, and implementation costs. Future research should focus on integrating advanced analytics, machine learning, and longitudinal monitoring to ensure sustainable adoption and evidence-based decision-making in sports performance.
Abstract
Purpose: This study aims to explore how artificial intelligence can optimize marketing strategies in the fresh food e-commerce sector. With a focus on perishability, transparency, and consumer trust, the research investigates AI applications that strengthen distribution and logistics, ultimately enhancing competitiveness and sustainability in a rapidly expanding digital marketplace. Research design, data and methodology: The study employs the Delphi method to gather structured expert insights across multiple survey rounds. A panel of industry and academic experts evaluated potential AI-driven strategies, while agreement indices and the Content Validity Ratio (CVR) were applied to ensure consensus and validity. This iterative process identified strategies with strong expert support. Results: Findings indicate that AI-driven approaches such as real-time demand forecasting, automated inventory management, and last-mile delivery optimization were rated highly essential by experts. High consensus and CVR values confirmed their validity. These strategies provide actionable solutions for improving marketing effectiveness, reducing waste, and strengthening operational efficiency in fresh food e-commerce. Conclusions: The study concludes that integrating AI into fresh food e-commerce requires strategies validated through both consensus and CVR, ensuring relevance and reliability. While expert-based methods present limitations, the research provides a robust foundation. Future studies should test these strategies empirically, expanding practical applications across global contexts in distribution and logistics.
Abstract
Purpose: This study examines how scarcity, trustworthiness, aesthetic appeal, and experiential quality of airline-issued non-fungible token (NFT) art influence consumers’ perceived value and purchase intention, with NFT purchase purpose (investment vs. non-investment) as a moderating variable. Research design, data, and methodology: A survey was conducted with 247 consumers familiar with NFTs, and structural equation modeling (SEM) was used to test the hypothesized relationships. Multi-group SEM was applied to evaluate moderating effects. Results: All four NFT attributes significantly enhanced perceived value, which in turn positively affected purchase intention. Scarcity influenced perceived value only among investment-oriented consumers, whereas trustworthiness, aesthetics, and experiential quality were significant in both investment and non-investment groups. Conclusions: The findings advance theoretical understanding of value-creation mechanisms in Web3-based distribution and provide practical insights for airlines developing NFT strategies. Specifically, tailoring NFT offerings to consumer motives—investment versus non-investment—can improve adoption and engagement.
Abstract
Purpose: The current research aims to explain the significance of power in the supply chain, with a particular emphasis on the buyer's perspective. In doing so, this research investigates the influence of network centrality on trust and collaborative decision-making in supply chain. Power, in this research, is measured with two structural dimension of network centrality: degree centrality and betweenness centrality. Research design, data and methodology: The empirical analysis is performed with the survey answered by supply chain managers from various industries in Korean corporations. The survey encompasses constructs, including trust, power, and collaborative decision-making. This study performs several statistical tests to analyze the direct effect model, the mediation effect model, the moderation effect model, and the moderated moderation effect model. Results: The indirect effect of trust on collaborative decision-making through degree centrality is significant whereas the mediation effect of betweenness centrality is not. The moderation test results indicate that the relationship between trust and collaborative decision-making is not influenced by the levels of degree centrality and betweenness centrality. Conclusions: This study discloses managerial implications such that even in the presence of coercive or opportunistic behaviors stemming from high level of network centrality, trust-based collaboration may not be significantly influenced.