This study assessed the Go-to-Market Strategy of a Student-Led Startup Business as perceived by faculty members and entrepreneur students. It aimed to determine how the respondents evaluated the startup’s strategy in terms of market research and customer segmentation, value proposition and product positioning, marketing and promotion strategy, sales and distribution channel, pricing strategy, and customer engagement and retention. The study was anchored on the Input-Process-Output model, where the inputs included related references, respondents, survey results, and problems encountered; the process involved questionnaire formulation, validation, administration, and assessment of GTM components; and the output was a proposed development plan for improving the student-led startup business. The study employed a descriptive survey method using a cross-sectional survey design. Purposive sampling was used to select 100 respondents from Eulogio “Amang” Rodriguez Institute of Science and Technology in Metro Manila, composed of 90 fourth-year entrepreneur students and 10 faculty members. Data were gathered through a validated survey questionnaire using a five-point Likert scale. The data were analyzed using percentage, weighted mean, ranking, and independent samples t-test at the 0.05 level of significance. The findings showed that the Go-to-Market Strategy of the Student-Led Startup Business was generally assessed positively. Market Research and Customer Segmentation obtained a composite mean of 4.228 and was interpreted as Very High Assessment. Value Proposition and Product Positioning obtained 4.129 and was interpreted as High Assessment. Marketing and Promotion Strategy obtained the highest composite mean of 4.240 and was interpreted as Very High Assessment. Sales and Distribution Channel obtained 4.143, Pricing Strategy obtained 4.179, and Customer Engagement and Retention obtained 4.184, all interpreted as High Assessment. The overall grand mean of 4.184 indicated a High Assessment. The independent samples t-test showed that all computed p-values were greater than 0.05, indicating no significant difference between the assessments of faculty members and entrepreneur students. The proposed business plan was developed to improve market research practices, strengthen value proposition, enhance promotional activities, optimize sales and distribution channels, implement competitive pricing strategies, and develop customer engagement programs. The study aligns with SDG 4 on Quality Education by supporting entrepreneurship learning and applied business instruction, SDG 8 on Decent Work and Economic Growth by strengthening student entrepreneurship, and SDG 9 on Industry, Innovation and Infrastructure by encouraging innovation-driven and digitally supported startup practices. Its sustainability impact lies in improving educational, institutional, technological, and socio-economic sustainability by helping student entrepreneurs develop more competitive, customer-centered, and sustainable startup businesses.

Regulated industries occupy a unique position within modern economies. Organizations operating in sectors such as utilities, energy, telecommunications, transportation, healthcare, financial services, and infrastructure management must simultaneously pursue growth, innovation, operational excellence, and stakeholder value creation while complying with extensive regulatory requirements. This dual responsibility creates a complex leadership challenge: organizations must remain adaptive and competitive in rapidly evolving markets while maintaining compliance, transparency, and accountability within highly structured regulatory environments. This article examines strategic business transformation as a critical mechanism through which regulated enterprises achieve sustainable competitive advantage. Rather than viewing regulation solely as a constraint on organizational flexibility, the study argues that regulatory environments can serve as catalysts for innovation, operational modernization, stakeholder trust, and long-term strategic differentiation. Enterprises that successfully align transformation initiatives with governance requirements often develop stronger organizational capabilities than competitors operating through compliance-focused approaches alone. The article explores the relationships among leadership, governance, digital transformation, organizational culture, risk management, customer-centricity, and stakeholder alignment. Particular attention is given to the role of executive leadership in navigating uncertainty, managing institutional complexity, and fostering organizational adaptability during large-scale transformation efforts. The study further examines how technological innovation, workforce development, operational resilience, and strategic agility contribute to sustainable enterprise performance within regulated environments. Building upon these discussions, the article proposes an Integrated Leadership Framework for Strategic Transformation in Regulated Markets. The framework connects governance, innovation, resilience, customer value creation, stakeholder trust, and organizational learning into a unified model capable of supporting long-term competitiveness. The article concludes that strategic transformation is no longer an optional initiative for regulated enterprises but a leadership imperative that determines organizational relevance, adaptability, and sustained success.

ABSTRACT Traditional restaurants, as Tradition-Based Firms, preserve cultural and historical heritage through time-honored recipes, symbols, and practices. To maintain authenticity, managers must balance innovation implementation with tradition preservation. This study examines how customer value co-creation and customer engagement contribute to sustainable competitive advantage in these businesses. Based on a qualitative exploratory study of long-established restaurants, the findings identify three mechanisms linking these constructs: increased innovation capacity, strengthened organizational image, and the development of customers’ affective memories. We propose guidelines and a design framework for strategy formulation, showing how customer involvement can support innovation while preserving authenticity and heritage.

The rapid advancement of artificial intelligence (AI) is fundamentally transforming human resource management (HRM), creating new opportunities for organizations to enhance workforce effectiveness, improve strategic decision-making, and strengthen long-term competitiveness. Despite growing scholarly attention to AI-enabled HRM practices, existing research remains fragmented and lacks a comprehensive theoretical framework explaining how AI contributes to sustainable organizational performance while balancing the interests of diverse stakeholders. This article addresses this gap by integrating Dynamic Capabilities Theory and Stakeholder Theory to develop a novel conceptual framework for AI-enabled human resource management. Drawing upon Dynamic Capabilities Theory, the study explains how AI technologies enhance organizational capabilities through sensing workforce needs, seizing strategic opportunities, and reconfiguring HR processes to respond to changing business environments. Simultaneously, Stakeholder Theory provides a complementary perspective by emphasizing the importance of creating value for employees, managers, customers, investors, and broader society through responsible and ethical AI implementation. The proposed framework demonstrates how AI-enabled HRM practices, including talent acquisition, employee development, performance management, workforce analytics, and employee engagement, contribute to organizational agility, workforce resilience, stakeholder satisfaction, and sustainable organizational performance. The article further develops a series of research propositions and identifies future research directions for scholars examining the intersection of artificial intelligence, human resource management, organizational sustainability, and strategic management. The framework offers both theoretical and practical insights for organizations seeking to leverage AI technologies while maintaining stakeholder trust and achieving long-term organizational success.

The article analyzes the regulatory framework for the inclusion of dividends in the customs value of goods. Approaches to considering dividends as part of customs value were investigated. The practice of including dividend payments in the customs value of goods was analyzed. The analysis of the practice revealed problems of reliable determination of the customs value of goods when paying dividends to a foreign intermediary. Ways to solve them are proposed.

This study examines the determinants of Customer-Based Brand Equity (CBBE) in Ghana’s hospitality industry, with a particular focus on how sustainability functions as a core component of brand strength. Drawing on a survey of 300 Ghanaian hospitality consumers and using Structural Equation Modeling (SEM), the study investigates how environmental, social, and economic sustainability together with innovation shape perceived quality, brand associations, and loyalty. The findings of this study shed light on how sustainability practices and innovation shape customer-based brand equity (CBBE) in the hospitality industry of Ghana. As the results indicate, the relationships among the three dimensions of sustainability are not uniform in their impact on customers’ perceptions of brand value. Rather, environmental sustainability and innovation emerged as the strongest predictors of CBBE, while economic and social sustainability played more limited or selective roles. These results highlight that in the Ghanaian context, sustainability is not merely an ethical add-on but an integral driver of customer value. The study offers new theoretical insights and practical guidance for hospitality brands seeking long-term competitiveness.

This research examines how agile project management affects economic outcomes, with agile leadership and strategic agility serving as mediators. Data were collected using a time-lagged approach (T1 = 304; T2 = 236) from managers at five major IT and telecommunications companies via a questionnaire, yielding 236 usable responses for analysis. The study uses structural equation modeling (Smart-PLS) to investigate these relationships. The findings suggest that agile leadership and strategic agility serve as mediators between agile project management and economic sustainability. This work contributes to the field by empirically examining the balance between control and flexibility in agile project management. It also expands the definition of strategic agility to include the ability to switch business partners and broadens agile leadership to encompass coordination between partners. The findings suggest that while agile leadership enhances customer value creation, strategic agility is crucial for achieving economic sustainability.

Purpose This study aims to examine how digital sustainability empowerment drives digital green innovation performance among emerging market small and medium-sized enterprises (SMEs), investigating the mediating role of firm customer participation in corporate social responsibility (CSR) value co-creation and the moderating effect of CSR-oriented artificial intelligence (AI) capability. Design/methodology/approach Drawing on stakeholder theory and dynamic capabilities view, the authors used mixed-methods analysis with time-lagged data from 411 emerging market SMEs. Using partial least squares structural equation modeling, PROCESS Macro and fuzzy-set qualitative comparative analysis (fsQCA), they tested the proposed relationships. Findings Results reveal that digital sustainability empowerment significantly enhances digital green innovation performance. Firm customer participation in CSR value co-creation positively mediates this relationship, while CSR-oriented AI capability strengthens the customer co-creation and green innovation link. The fsQCA analysis identifies multiple configurational pathways to achieve superior green innovation performance. Practical implications The findings provide strategic guidance for SME managers on leveraging digital technologies and AI capabilities to enhance CSR value co-creation processes and drive green innovation performance in emerging markets. Originality/value This research demonstrates how digital transformation reshapes CSR practices through B2B customer value co-creation, creating sustainable innovation opportunities for emerging market enterprises. The study advances understanding of mechanisms linking digital sustainability capabilities with green innovation outcomes through customer collaboration.

Effective management and amalgamation of the multi-source financial information so as to provide individualized investment and wealth management services require optimization of ETL (extract, transform, load) pipeline in customer-centric investment solution will be provided as the general methodology in this paper. The project contains data conversion of the former on-premises Oracle systems into the snowflake based data warehouse with the type of data they held was the contributions to the portfolios, product relations, customer relations and information about the participants. There is systematization of the process and includes data modelling, pipeline design and performance optimization. To make sure that the data models are aligned to the business objectives as well as the data governance sets, logical, conceptual and physical data models were developed. Informatica IICS and Powercenter were adopted as effective in extracting, processing and loading of different sources like SQL, Oracle and Azure Databrinks. AWS Lambda control-M and cloud-native services, S3, KMS, SQS and SNS were introduced to automate the processes to reduce the number of processes completed manually and provide scale execution. According to the quantitative statistics, the effectiveness of processing increased significantly: the total ETL processing time was decreased by 42 percent and the data rate increased by 38 percent, which makes the reporting and analysis almost real-time. By applying DAX as KPIs of power BI dashboards, the action could be taken on the customer portfolios based on the specific investment campaigning and tailored financial recommendation. The paper sheds light on the effectiveness, quality of data and customer value of business in customer-centric financial platforms with optimized ETL pipelines.

Global logistics enterprises generate vast transactional records that remain underutilised for strategic profitability management. This paper applies systematic Exploratory Data Analysis (EDA) and multi-dimensional feature engineering to a real-world operational dataset of 180,519 order records from APL Logistics (KWE Group), spanning 20,652 unique customers, 118 products across 50 categories, five global markets, and 23 order regions. The dataset encompasses total portfolio revenue of $36,784,734.31 and net profit of $3,966,902.97, yielding an overall profit margin of 10.78%. Critical findings include: 18.71% of orders (33,784 transactions) are loss-making; total discount expenditure ($3,730,378.40) constitutes 94.0% of net profit; the top 10% of customers (2,066 accounts) account for 49.1% of cumulative profit; a Pearson correlation of r = -0.0027 (p = 0.253) between discount rate and profit ratio — non-significant at the individual order level — coexists with a monotonic 25.2% aggregate-level margin decline from zero-discount to 21–25% discount bands; and a portfolio-wide late delivery rate of 54.83% imposes significant service-quality risk. An interactive six-module Streamlit dashboard is deployed to operationalise analytical outputs for real-time commercial decision support. The study advances the evidence base for profit-centric supply chain analytics and provides actionable recommendations for discount policy reform, customer value tiering, and shipping mode rationalisation

Customer reviews are a vital component of modern e-commerce platforms, offering meaningful insights into customer satisfaction, product quality, and overall user experience. With the rapid growth of online shopping, a massive volume of textual feedback is generated daily. Traditional evaluation methods, such as average ratings and review counts, provide only a general overview and fail to capture the deeper sentiments expressed in textual reviews. As a result, a large portion of valuable customer feedback remains underutilized. Moreover, manual analysis of large-scale review data is time-consuming and inefficient, emphasizing the need for automated analytical solutions. To address these challenges, this research proposes a machine learning-based framework for analysing customer review data and predicting both recommendation outcomes and product ratings. The system incorporates data preprocessing, exploratory data analysis, and text representation using Term Frequency–Inverse Document Frequency (TF-IDF). Multiple machine learning models are implemented, including Restricted Boltzmann Machine (RBM) combined with Logistic Regression (LR) for classification, RBM with Ridge Regressor (RR) for regression, Gradient Boosting (GB), Extreme Gradient Boosting (XGB), and Multi-Task Neural Network with Extra Trees (MTNN-ET) these models are works with Classification and Regression Tree (CART) Model. Experimental results demonstrate that the proposed MTNN-ET-CART model achieves superior performance, with a classification accuracy of 0.9640 and a regression R² score of 1.0000. The framework effectively processes large-scale review datasets and generates reliable predictions, enabling enhanced decisionmaking and improved customer experience in e-commerce platforms

The article explores the theoretical and practical aspects of forming and implementing marketing strategies for enterprises in the food industry under conditions of a dynamic and competitive market environment. Particular attention is given to marketing as a strategic management tool that ensures sustainable competitive advantages and long-term business development. The study defines marketing strategy as a system of coordinated managerial decisions aimed at effective use of resources and adaptation to external changes. Key factors influencing enterprise competitiveness are analyzed, including economic performance, management efficiency, innovation potential, and marketing capabilities. The research highlights the specific features of the food industry, such as short product life cycles, high quality and safety requirements, consumer sensitivity to price and composition, and dependence on logistics and distribution systems. These characteristics necessitate a flexible and adaptive marketing approach. The importance of comprehensive consumer analysis is emphasized, including behavioral and psychological aspects, which form the basis for effective segmentation and positioning. The article also examines the role of product policy, pricing, distribution channels, and marketing communications in creating customer value and strengthening market positions. Special attention is paid to digital technologies, such as CRM systems, data analytics, and e-commerce, which enhance decision-making and improve customer interaction. In addition, the study identifies key marketing tools specific to the food industry, including category management, trade marketing, packaging, and reputation management. Their integrated use contributes to increasing sales efficiency, optimizing costs, and reducing risks. The article concludes that marketing strategy in the food industry is a comprehensive mechanism for managing competitiveness, ensuring business stability, and achieving sustainable development in a changing market environment.

Purpose Hospitality research tends to be concerned with linking the intangible, social and emotional aspects of consumer behaviour predominantly to luxury services, whereas for low-cost services the link is mainly to financial concerns. Building on the Value Attitude Behaviour Model and Consumption Value Theory, this study aims to investigate the effect of personalisation on guests' value perceptions of budget hotels – a growing yet often overlooked accommodation segment – and how consumption values impact upon behavioural intentions through the mediators of attitude and memorability. Design/methodology/approach Four value perceptions were included in the analysis – financial value, functional value, hedonic value and social value – each representing a different aspect of customer value. The analysis employed partial least-squares structural equation modelling, with online questionnaires used to capture the views of 264 guests of budget hotels. Findings Contrary to expectations, the findings emphasise the importance of hedonic value, rather than functional or financial value, in forming guests' attitude and memorability. Social value, meanwhile, was not found to be a significant determinant either of attitudes or memorability, suggesting that individual, rather than social motives, tend to be the generators of value for guests of budget hotels. Practical implications Those who market budget hotels should put more emphasis on personalising the experience for their guests. This will help to ensure that guests receive more than just a reasonably priced, functionally adequate stay. The study also demonstrates the importance of positive attitudes in determining revisit intentions to the hotel. This implies that delivering a memorable experience is not the only, or necessarily the optimal, marketing strategy for budget hotels. Originality/value While previous research had predominantly linked personalisation with luxury and up-scale experience of products and services, the present study examines personalisation in the budget hotel context. Beyond the contextual distinctiveness of the budget hotel setting, this study is among the first to employ a value-based analytical framework to empirically show that, within this industry, personalisation results in hedonic value surpassing functional value.

In the context of rapid digital transformation, tourism enterprises in Vietnam are facing significant changes in the business environment, requiring them to innovate their business models to enhance competitiveness and adapt to market trends. This study aims to analyze the factors influencing business model innovation among tourism enterprises in the digitalization era. Research data were collected through a survey of tourism enterprises in Vietnam and analyzed using quantitative statistical methods. The results indicated that factors such as digital technology capability, managers’ awareness of digital transformation, competitive pressure, government policy support, and firms’ innovation capability had significant impacts on the process of business model innovation. The study also revealed that the adoption of digital technologies not only improves operational efficiency but also created new value for customers through innovative tourism products and services. Based on these findings, the paper proposes several managerial implications to support tourism enterprises in promoting business model innovation in the digital era, thereby enhancing competitiveness and contributing to the sustainable development of Vietnam’s tourism industry.

With the rapid growth of e-commerce and increasing competition in the express logistics industry, effective customer management has become critical for improving operational efficiency and revenue stability. This study proposes a data-driven framework for refined customer management based on real-world waybill data. Customer behavior is characterized using multi-dimensional features derived from aggregated transaction records. A hybrid segmentation approach combining a customer value four-quadrant model and K-means clustering is employed to identify customer value levels and behavioral patterns. Based on the segmentation results, a Random Forest model is developed to classify customers into churn and non-churn groups and identify high-risk customers. Experimental results show that the clustering model achieves a silhouette coefficient of 0.8797, while the Random Forest model outperforms other models with an accuracy of 0.825. The results demonstrate that the proposed framework effectively identifies high-value customers with elevated churn risk and supports more informed customer management decisions.

ABSTRACT International project-based organizations (PBOs) often struggle to sustain performance when positioned at the periphery of global value chains, where difficulties in delivering superior customer value exacerbate their liability of outsidership (LOO). This study investigates how PBOs address LOO by constructing and evolving value innovation (VI) logic that fuses customer orientation and innovation. Drawing on a longitudinal case study of a leading PBO in China with a sensemaking lens, we develop a framework illustrating how VI emerges as an adaptive process shaped by LOO and enacted through social and technical structures. These findings provide process-oriented insights for reframing cognition and sustaining innovation.

Purpose This study explores how lean and digital technologies can be synergistically integrated to enhance prefabricated construction (PC), particularly under dynamic and complex conditions. It aims to address the research gap concerning the lack of configurational pathways that enable lean-digital synergy across different PC developmental stages. Design/methodology/approach This study adopts a stage-based analytical framework to examine the evolution of lean-digital integration through three stages: primary, intermediate and advanced. A combination of Best-Worst Method (BWM) and fuzzy set Qualitative Comparative Analysis (fsQCA) is employed to identify and evaluate the multiple concurrent causal conditions that influence lean-digital transformation in the PC context. The robustness test is also conducted to validate the results. Findings The analysis reveals that no single factor is sufficient to drive lean-digital transformation. Instead, success depends on specific configurations of multiple interrelated factors. At the primary stage, standardized management and digital information systems lay the groundwork. The intermediate stage emphasizes resource coordination and dynamic decision-making through intelligent operations. The advanced stage, however, focuses on delivering customer value and achieving industry–chain collaboration and continuous improvement. Originality/value This study contributes to the theoretical development of lean–digital integration by identifying the dynamic and stage-specific causal pathways critical to transformation in PC. It offers actionable insights for industry stakeholders to strategically implement lean-digital transformation in the real-world, dynamic construction environments, promoting high-performance outcomes aligned with Construction 4.0.

Digital technology encourages retail companies to adapt their marketing strategies to create new value for customers. Digitalization not only facilitates transactions but also creates new experiences that influence how customers perceive value in shopping activities. This study aims to understand how marketing strategies adapt to transform customer value in the digital era through the use of the Alfagift application. This study used a qualitative method with a phenomenological approach. Data were obtained through in-depth interviews with three informants: one Alfamart manager and two customers using the Alfagift application, supported by observation and documentation techniques. Data analysis was conducted using a phenomenological analysis model. Research shows that utilizing the Alfagift app as part of a digital marketing strategy can provide easy access to product and promotional information, increase shopping efficiency, and provide various additional benefits through promotional programs and digital vouchers. Furthermore, the use of the app also influences customer behavior in the purchasing decision-making process. This study concludes that adapting a digital-based marketing strategy not only serves as a promotional tool but also transforms customer value toward a more practical, efficient, and modern shopping experience.

The article addresses the methodological gap in assessing the impact of digital transformation on the competitiveness of retail enterprises, which is particularly acute in the context of systemic shocks affecting the Ukrainian economy. The study develops and validates a three-level diagnostic model that integrates a Digital Maturity Index and a Competitiveness Index through a combined Fuzzy AHP and Fuzzy TOPSIS methodology. The proposed model comprises 25 diagnostic indicators grouped into eight sub-indices covering both technological dimensions (IT infrastructure readiness, business process automation, omnichannel integration, and data analytics) and market performance dimensions (financial efficiency, market position, operational resilience, and customer value). The Fuzzy AHP method is employed to determine the weight coefficients of sub-indices by processing cognitive uncertainty inherent in expert judgments, while the Fuzzy TOPSIS method ranks enterprises according to their proximity to ideal and anti-ideal solutions. The relevance of this research stems from the absence of a unified diagnostic tool that links digital maturity levels with quantitative competitiveness metrics for retail enterprises operating under war conditions and high systemic risks. The article discusses the conceptual architecture of the model, the indicator system and its measurement methodology, the mathematical apparatus based on fuzzy set theory, and the results of a pilot application involving seven leading Ukrainian retailers. The pilot study confirmed the discriminative capacity of the proposed model and revealed a substantial digital divide among the analysed enterprises, with the closeness coefficient ranging from 0.781 for the top-ranked retailer to 0.412 for the lowestranked one. Scenario analysis demonstrated the practical utility of the model for prioritising digital infrastructure investments and formulating targeted transformation strategies. The study contributes to bridging the gap between descriptive digital maturity frameworks and quantitative methods for evaluating competitive performance in the retail sector of transitional economies.

ABSTRACT Grounded in absorptive capacity theory (ACT), this study investigates how small and medium-sized enterprises (SMEs) draw on external knowledge to strengthen innovation outcomes. We focus particular on the role of technology confrontation coping as a moderating mechanism shaping the links among collaboration networks, innovation capability, and customer lifetime value (CLV). Data were gathered through a structured, time-lagged survey conducted in three phases with 348 SMEs, and analyzed using AMOS 24 and SPSS 23. The findings indicate that collaboration networks act as important channels through which firms build innovation capability, which in turn enhances CLV. They also reveal that SMEs with stronger coping capacity are more effective in translating external knowledge into innovation benefits. By integrating coping into the absorptive capacity framework, this research refines theoretical understanding and offers practical insights for industrial SMEs in developing economies.