From Consumer-Centric Innovation to Sustainable Restaurant Performance: A Study of Strategic Capability Integration in an Emerging Market Context

Abstract

Increasing pressure for innovation-driven competitiveness requires hospitality firms to integrate technological capability, market intelligence, and customer-focused innovation into coherent strategic configurations. However, prior research has largely examined these capabilities separately, limiting understanding of how their integration influences restaurant marketing performance in emerging markets. This study develops and empirically tests an integrated capability framework linking techno-resonance innovation capability, competitor orientation, consumer-centric innovation strategy, and new service development to restaurant marketing performance using survey data from 300 restaurant managers in Java and Bali, Indonesia. The results of PLS-SEM analysis indicate that techno-resonance innovation capability significantly strengthens consumer-centric innovation strategy and new service development, which subsequently improves marketing performance outcomes. The findings extend dynamic capabilities theory by demonstrating that capability integration—rather than isolated strategic actions—supports innovation-driven competitiveness in emerging hospitality markets and provides practical guidance for restaurant managers seeking to enhance performance under resource-constrained conditions.

1. Introduction

The increasing volatility and complexity of the modern business landscape challenge organizations to rethink their approaches to marketing performance. While firms have traditionally focused on financial outcomes and market share as primary indicators of marketing success, the digital revolution, shifting consumer behaviors, and intensifying competition necessitate a more adaptive and holistic approach (Kabir et al., 2025; Sharma, 2024; Theodorakopoulos & Theodoropoulou, 2024). Recent developments in the hospitality sector indicate growing pressure for digital adaptation, customer responsiveness, and strategic capability renewal in restaurant businesses operating in competitive and evolving service markets. These trends reflect intensifying pressures toward capability-based innovation and sustainability integration.

Companies need to pursue a customer-centric strategy in rapidly evolving markets to achieve sustainable growth, with consideration of customer needs and providing personalized value having been highlighted as essential strategies to succeed in a competitive environment (Tuominen et al., 2022). Research has shown that companies that adopt a customer-centric approach tend to achieve higher customer loyalty and profitability (Akbar, 2024; Gupta & Ramachandran, 2021). Given that emerging markets such as Indonesia exhibit accelerated digital adoption, shifting consumer values, and sustainability pressures, understanding strategic determinants of marketing performance in this context is crucial. Positioning the study within an emerging-market setting enhances its theoretical relevance, as empirical evidence in developing economies remains limited and fragmented (Djakasaputra et al., 2026; Guan, 2023; Sharabati et al., 2024). Unlike experience-based tourism, which emphasizes episodic encounters, or conscious consumerism, which focuses on ethical purchasing behaviors, lifestyle-driven business logic aims to create recurring behavioral patterns that guide service co-creation and influence sustainability outcomes over time (Brozović et al., 2020; Palakshappa et al., 2023; Peng & Gu, 2024; Vidickienė & Lankauskienė, 2025).

Emerging markets such as Indonesia are characterized by rapid digital adoption, high market turbulence, and resource constraints, making capability-based strategies increasingly important for sustaining firm performance. This context provides a valuable setting for examining how firms integrate technological capability and market intelligence into service innovation to strengthen their competitive advantage in dynamic hospitality environments (Dana et al., 2022; Hughes & Chandy, 2021; Jemmy, 2025; Kasamani et al., 2024; Van Hoang et al., 2025).

Service development is key to meeting customer needs through innovative solutions (Hollebeek & Rather, 2019; Nebaba et al., 2023). Prioritizing excellent service delivery allows companies to stand out in a competitive market, thereby increasing customer satisfaction and loyalty (Koay et al., 2022; Shrestha, 2021; Uzir et al., 2021). This shift towards service innovation reflects a shift from product-centric strategies to experience-oriented products that are more aligned with consumer expectations (de Kwant et al., 2021; Gupta & Ramachandran, 2021).

Competitive orientation, involving the systematic analysis of competitors, enables companies to predict market trends and adapt their strategies accordingly. This approach helps companies to remain competitive, respond effectively to industry changes, and capitalize on opportunities to strengthen their market position (Chaudhary et al., 2022; Gotteland et al., 2020; Indriyani et al., 2025).

Despite recognizing strategies such as consumer-centricity, service development, and competitive orientation individually, their combined impact on marketing performance remains unexplored (Dash, 2022; Schulze et al., 2022). Addressing this gap is critical to understanding how these strategies collectively improve business outcomes (Farida & Setiawan, 2022). Previous studies have often investigated consumer-centric strategy, service development, and competitive orientation in isolation, and their interactions have not been thoroughly examined. This lack of integration limits a comprehensive understanding of strategic marketing approaches (Al-Surmi et al., 2020; Blake et al., 2019; Schulze et al., 2022). Although competitive orientation and service innovation are linked to marketing outcomes, the synergy between these elements is still unclear. The existing literature cannot explain how these elements collectively contribute to strategic marketing goals (Bilgin & Adiguzel, 2021; Maclean et al., 2023; Sondhi et al., 2024).

Most studies have focused on static market environments, overlooking changing consumer preferences and the dynamic nature of the competitive environment. This highlights the need to overhaul traditional marketing models to become more flexible and adaptable (Cake et al., 2020). Few studies have provided solid evidence of the relationship between consumer focus, service development, and competitive awareness (Chirieleison et al., 2021; Guha et al., 2021; Halkiopoulos & Papadopoulos, 2022). Recent studies have emphasized the importance of consumer-centric strategies for loyalty and retention (Alayli, 2023; Zha et al., 2023), and the need for organizational agility in response to market turbulence and competitor intelligence for proactive strategy has been highlighted (Aguinis et al., 2020; Y. Liu et al., 2021). However, the literature remains fragmented, with limited integration across these domains. State-of-the-art marketing practice calls for interconnected capabilities that enable firms to swiftly interpret and act on market signals, but empirical evidence for such integration is scarce—especially in dynamic, emerging markets (S. W. Khan et al., 2022; Shehata, 2020). Existing studies have examined consumer-centric strategies, competitor orientation, and innovation capabilities as isolated predictors of market outcomes, resulting in a fragmented body of knowledge that lacks theoretical integration (Alshaketheep et al., 2025; Alzyadat, 2025). This fragmentation is particularly problematic in emerging markets, where firms operate in turbulent environments that require synchronized deployment of adaptive capabilities rather than isolated strategies (Adenuga et al., 2025; Martin et al., 2020). Therefore, an integrated theoretical model is required to explain how firms jointly leverage consumer insights, technological capability, and competitive intelligence to enhance their marketing performance (Hutabarat & Budianto, 2026; Oduro & Mensah-Williams, 2023). This study fills a research gap by empirically testing the integration of consumer-centric innovation, techno-resonance capability, and competitor orientation within the context of Indonesia’s hospitality and tourism industry, an emerging market where empirical evidence remains limited.

This study presents a novel, integrative framework that unifies consumer-centricity, service agility, and competitor intelligence as interdependent drivers of marketing performance. Unlike previous studies that examine these constructs separately, this research explores their combined impacts and interaction effects, providing new theoretical and practical insights. Moreover, it extends the application of this integrative model to an emerging market context, addressing a gap in the existing research where developed economies are the predominant focus.

Although consumer-centricity, service agility, and competitor intelligence have been independently linked to organizational performance, few empirical studies have synthesized these dimensions into a unified model (Hughes & Chandy, 2021; Jemmy, 2025; H. Khan & Khan, 2021). The lack of holistic perspectives limits understanding of how these elements interact to enhance marketing outcomes, particularly in fast-changing, resource-constrained environments. Prior research has largely overlooked the mediating mechanisms, such as the role of service agility, that may explain how consumer orientation and competitor awareness translate into tangible performance gains (Agag et al., 2025; D’souza et al., 2021). Despite extensive research on consumer-centricity, service innovation, and competitor orientation, empirical studies that integrate these strategic capabilities into a unified framework remain scarce, particularly in emerging markets where firms face resource constraints and sustainability pressures (Z. Liu et al., 2025; S. Park & Cho, 2022; J. Wang et al., 2022).

To strengthen the identification of the research gap, a keyword co-occurrence mapping analysis using VOSviewer 1.6.20 was conducted to examine dominant thematic structures in the sustainable tourism and hospitality innovation literature. The mapping results indicate that existing research clusters are primarily centered on themes such as sustainable tourism governance, SDGs, authenticity, employment impacts, crisis management, and destination-level sustainability indicators (Figure 1). While these themes reflect the strong macro-level orientation of the existing tourism sustainability literature, capability-based innovation constructs at the firm level—particularly techno-resonance innovation capability, consumer-centric innovative strategy, competitor orientation, and new service development—are largely absent from the mapped thematic structure. This pattern suggests that prior studies have rarely examined how integrated organizational capabilities translate into measurable restaurant marketing performance outcomes. Accordingly, this study addresses an important research gap by developing and empirically testing a capability integration framework that explains how technological readiness, market intelligence, and customer-focused innovation jointly influence restaurant marketing performance in emerging hospitality markets.

The network illustrates dominant thematic clusters in the tourism sustainability literature, including governance, sustainable development goals, authenticity, employment impacts, crisis management, smart tourism, and sustainability indicators. Node size represents keyword frequency, while link strength reflects co-occurrence relationships among research themes. The visualization indicates that the firm-level capability integration constructs examined in this study—specifically techno-resonance innovation capability, consumer-centric innovative strategy, competitor orientation, and new service development—are largely absent from the dominant thematic clusters. This mapping supports the identification of a research gap related to capability-based explanations of restaurant marketing performance in emerging hospitality markets and provides bibliometric justification for the proposed conceptual framework.

The mapping identifies dominant research clusters centered on governance, SDGs, authenticity, employment, crisis management, and sustainability indicators, reflecting the prevailing macro-level orientation of tourism sustainability scholarship. In contrast, the capability integration constructs examined in this study—techno-resonance innovation capability, consumer-centric innovative strategy, competitor orientation, and new service development—are largely absent from the mapped structure. This evidence supports the identification of a firm-level capability integration gap and justifies the development of the proposed structural model explaining restaurant marketing performance in emerging hospitality markets.

Building on dynamic capabilities theory and the resource-based view, this study proposes that restaurant firms improve marketing performance not through isolated strategic actions but, rather, through the coordinated interaction of technological capability, competitor orientation, customer-centered innovation strategy, and new service development processes. By positioning these constructs within a unified structural framework, this study contributes to capability-based marketing strategy research and provides empirical insight into how innovation-oriented capability configurations operate in resource-constrained emerging-market restaurant environments.

This study introduces a framework that integrates consumer focus, service development, and competitive awareness and evaluates their collective impact to provide a holistic view beyond standard marketing performance metrics. The strategies adopted in dynamic and competitive markets highlight the importance of approaches that are adaptable to a rapidly changing industry (Hunt & Madhavaram, 2020; Koguashvili & Otinashvili, 2022; Prdić & Kuzman, 2023; Urefe et al., 2024). Unlike previous studies that isolated these elements, this study highlights their combined impact and provides valuable insights for the adjustment of internal and external strategies to improve the results (Hussain et al., 2023; Mahadik et al., 2023). It advances marketing theory by presenting an integrated model that connects consumer behavior, service innovation, and competitive strategy, broadening our understanding of how these factors interact and affect marketing outcomes while redefining traditional frameworks through a comprehensive approach that aligns consumer focus, service innovation, and competitive awareness to achieve better results (Alkandi & Helmi, 2024; Ed-Dafali et al., 2023; Rincón et al., 2022). This study not only integrates consumer-centricity, service agility, and competitor intelligence into a unified framework, but also positions the model as a portable template for global consumer marketing management. Based on the theoretical framework and identified research gap, this study addresses the following research questions:

• How do techno-resonance innovation capability and competitor orientation influence consumer-centric innovative strategy and new service development in restaurant firms?
• To what extent do consumer-centric innovative strategy and new service development mediate the relationship between capability-based strategic orientations and restaurant marketing performance?
• How does capability integration among technological readiness, competitive intelligence, and customer-centered innovation strategy explain restaurant marketing performance in emerging hospitality markets?

This research aims to develop and empirically test an integrative model that examines how consumer-centricity, techno-resonance innovation capability, and competitor orientation influence marketing performance both individually and in combination, with particular focus on the mediating role of new service development. Although existing studies examine consumer-centricity, service innovation, or competitor orientation individually, empirical integration of these capabilities remains scarce, particularly in emerging markets with resource constraints and sustainability pressures (Chithambo et al., 2020; Lemy et al., 2026). This study addresses this gap by testing an integrated capability model using hospitality data from Indonesia. Although previous studies have examined consumer-centric strategy, innovation capability, and competitor orientation independently, limited research has focused on explaining how these capabilities function as an integrated capability system influencing restaurant marketing performance in emerging markets (Chou et al., 2020). This study addresses that gap by proposing and testing a capability integration framework grounded in dynamic capabilities theory and the resource-based view. By positioning techno-resonance innovation capability as an enabling mechanism and consumer-centric innovation strategy as a mediating pathway, this study advances the understanding of how restaurants convert technological and competitive intelligence into sustainability-aligned marketing outcomes. In this study, the strategic capability framework is operationalized through five constructs that are directly measured and tested; namely, techno-resonance innovation capability, competitor orientation, consumer-centric innovative strategy, new service development, and restaurant marketing performance. Grounded in dynamic capabilities theory and the resource-based view, these constructs represent organizational capabilities through which restaurant firms sense market change, mobilize technological and competitive knowledge, and translate these inputs into innovation-related performance outcomes (Fatoki, 2021; Kero & Bogale, 2023; Pundziene et al., 2021; Robertson et al., 2021; Tawfig & Aggad, 2025).

Although sustainability and the sustainable development goals provide an important contextual backdrop for innovation in the hospitality sector, the present study does not directly measure environmental or SDG performance indicators (Elshaer et al., 2025; Hussein et al., 2024; Olazo, 2022). Accordingly, the SDG perspective is treated as a contextual motivation for capability development, rather than as an empirical outcome variable in the tested model (Calderón et al., 2023; Elkhwesky et al., 2022; Elsharnouby & Elbanna, 2021). The focus of the study is specifically on restaurant marketing performance and the capability mechanisms that may contribute to it.

2. Literature Review

Drawing on dynamic capabilities theory (Pereira-Moliner et al., 2021; Rotjanakorn et al., 2020) and the resource-based view (Barney, 1991; Barney et al., 2001), this study conceptualizes consumer-centric innovation, technology capability, and competitor orientation as adaptive resources that enable performance outcomes in volatile environments. Building on the role of techno-resonance innovation capability in enabling sustainability-oriented innovation, how these technological capabilities support the development of customer-centric services in hospitality are examined in the following section (Hiong et al., 2020). This definition clarifies the boundaries between overlapping concepts and strengthens the replicability of the theoretical model for future research. The reviewed literature reveals fragmented treatment of individual capabilities, highlighting a gap in integrated empirical models which are capable of explaining how capability bundles influence sustainable development goal-oriented performance in hospitality.

Techno-resonance innovation capability refers to how well an organization balances technological advances with customer expectations and its own goals. This alignment ensures that innovations resonate with stakeholders and achieve sustainable success (Chin et al., 2022; Saunila, 2020). Techno-resonance innovation capability is based on dynamic capabilities theory, which emphasizes an organization’s ability to adapt and respond to technological change effectively (Daronco et al., 2022; Koo & Le, 2024; Mendoza-Silva, 2020; Paipa et al., 2024). This capability enhances sustainable competitive advantage. Advances in artificial intelligence and big data analytics have significantly improved techno-resonance innovation capability, enabling product customization and increasing user satisfaction (Hiong et al., 2020; Novillo-Villegas et al., 2022). Organizations using techno-resonance innovation capability often achieve higher customer retention, loyalty, and brand equity by closely aligning innovation with consumer needs (Alayli, 2023; Evanschitzky et al., 2021). Participation in innovation ecosystems where companies collaborate strengthens techno-resonance innovation capability through resource sharing, expertise sharing, and technology partnerships (Lemy et al., 2025). Digital platforms, the Internet of Things, and cloud technologies enhance techno-resonance innovation capability, especially in service-oriented industries (Jiang et al., 2022b). Furthermore, techno-resonance innovation capability is increasingly linked to sustainable innovation to meet the growing demand for environmentally friendly and socially responsible solutions (Juliana et al., 2025a, 2025b; Lemy et al., 2022). Despite its transformative potential, techno-resonance innovation capability adoption may face constraints, including initial investment cost, readiness of personnel, technology-learning fatigue, and a mismatch between digital tools and customer comfort levels. This suggests that technological capability does not automatically convert into performance, unless supported by complementary organizational resources and adoption maturity (Das, 2025).

The hospitality and tourism industry has significantly benefited from techno-resonance innovation capability, which is leveraged to provide personalized services that improve customer experience and gain a competitive advantage (Benitez et al., 2023; Surucu-Balci et al., 2024). Key performance indicators of techno-resonance innovation capability include the technology adoption rate, time-to-market innovations, and customer satisfaction scores (Kripalani, 2024). Despite its benefits, companies often face challenges such as traditional practices, limited technical know-how, and resistance to change (Jiang et al., 2022b; Patrício et al., 2024). Effective leadership is essential to drive techno-resonance innovation capability by fostering a culture of experimentation, continuous learning, and strategic risk-taking (Gren & Ralph, 2022). Cross-functional collaboration combines different technical, market, and creative perspectives, leading to holistic innovation (Buhalis et al., 2022; Kumar et al., 2022). Incorporating consumer feedback and co-creation ensures that innovations remain relevant and user-centric (Gemser et al., 2024). New technologies such as blockchain, augmented reality, and virtual reality are transforming techno-resonance innovation capability applications and expanding innovation opportunities (Silitonga et al., 2025). Techno-resonance innovation capability varies by region, with emerging markets adopting mobile-based innovations and demonstrating adaptability (Hiong et al., 2020). Further research into the role of techno-resonance innovation capability in sustainability, inclusion, and diversity may reveal additional benefits and applications (Ma et al., 2024; Xu et al., 2024). Managers should prioritize aligning technical capabilities with market needs to maximize the effectiveness of TRICs (Faraj & Leonardi, 2022; Ramesh et al., 2024). Techno-resonance innovation capability enhances sustainability performance by enabling firms to design resource-efficient solutions aligned with sustainable development goal principles, while simultaneously strengthening competitive advantage in turbulent markets.

Market orientation explains how competitor orientation and consumer-centric strategies enhance business adaptability, according to several studies (Pehrsson, 2020; C. H. Wang, 2020). The new service development process systematically creates and introduces new services that meet evolving consumer preferences (Istanti et al., 2024; Koval et al., 2021). NSD is crucial for brand differentiation, especially in competitive markets where unique services provide a competitive advantage (E. Kim et al., 2021; Shi et al., 2024). The process typically involves ideation, concept validation, prototype development, service evaluation, and market launch (Blindheim et al., 2020; Durães et al., 2020). Incorporating customer input throughout the NSD process ensures alignment with market needs, reduces the risk of failure, and improves service acceptance (Blindheim et al., 2020; Durães et al., 2020). Advanced technologies such as AI and machine learning enable predictive analytics and customized solutions, facilitating the development of innovative and personalized services (Kedi et al., 2024; Vandanapu, 2024). As consumers increasingly demand personalized experiences, customization within NSD becomes more critical (Kamali et al., 2024; Kanaparthi, 2024; Vandanapu, 2024). Collaborative partnerships and ecosystems foster resource sharing and co-creation, improving NSD outcomes (Alam, 2021; Blindheim et al., 2020; Okeke et al., 2024). Key performance indicators for NSD include faster time to market, improved service quality, and increased customer satisfaction (Licup & Materum, 2023). However, challenges such as resource limitations, high failure rates, and scalability issues remain significant (Castro et al., 2024).

Global NSD strategies must consider cultural differences to ensure relevance and effectiveness in different markets (Balashova & Urupa, 2024; Valtakoski et al., 2019). Integrating sustainability into NSD meets the growing consumer demand for environmentally friendly solutions and enhances corporate social responsibility (Bukhari et al., 2020; F. Liu et al., 2024). Service blueprints can help to visualize the NSD process, identify potential issues, and ensure smooth service delivery (Jang & Ryu, 2025; Ryu et al., 2020). Employee training and preparation are critical to the success of NSD, enabling teams to adapt to new ways of doing things (Herjuna et al., 2024; Santos & Stuart, 2003). NSD requires agility to respond quickly to competitive innovations, especially in dynamic industries such as technology and hospitality (Atkinson et al., 2020; López-Gamero et al., 2022).

Industries such as healthcare and hospitality are leading the way in NSD adoption, focusing on innovations that improve the patient and guest experience (Goel et al., 2022; Gounaris et al., 2020). Competitive orientation is the systematic gathering of information about competitors’ strategies to anticipate challenges and identify opportunities for differentiation (Alghamdi & Agag, 2024; Kitsios & Grigoroudis, 2020; Satar et al., 2024). This promotes innovation and adaptability, enabling companies to remain competitive and proactive in dynamic environments (AlTaweel & Al-Hawary, 2021; López-Gamero et al., 2022). Consumer-centric innovation focuses on understanding consumer behavior and addressing evolving needs and preferences. The service-dominant logic model (Onofrei et al., 2022; Woo, 2019) emphasizes creating value through collaboration, making consumer insights critical for innovation. Combining competitive focus with consumer-centric strategies creates a balanced approach that balances market intelligence and customer-centric innovation.

Competitor orientation drives firms to continuously monitor and respond to competitor strategies (Cheung et al., 2021; Gounaris et al., 2020). This orientation fuels service innovation as companies strive to differentiate themselves (Mandal, 2022). Simultaneously, consumer engagement mediates this relationship by facilitating two-way communication and enhancing customer involvement (Casidy et al., 2020; Tajeddini et al., 2023). This orientation also indirectly shapes consumer engagement, as organizations aligned with market trends can more effectively attract and involve customers (Mandal, 2021). Moreover, consumer engagement acts as both a mediator and an outcome in this triadic relationship. Engaged consumers provide feedback, co-create value, and fuel the innovation process, thereby completing a dynamic loop that reinforces competitive advantage (Yen et al., 2020). This aligns with the resource-based view and dynamic capability theory, highlighting how internal (Audretsch & Belitski, 2022; Hameed et al., 2021) and external knowledge interplay in service innovation (Agostino et al., 2020).

2.1. Hypothesis Development

Based on the dynamic capabilities theory (Pereira-Moliner et al., 2021; Rotjanakorn et al., 2020) and the resource-based view (Barney, 1991; Barney et al., 2001), strategic capability integration enables firms to align technological readiness, customer insight, and competitive intelligence into coherent innovation strategies that improve marketing performance outcomes. Based on this theoretical framing, the proposed hypotheses examine how technology-based capability, competitive intelligence, and customer-oriented innovation interact to influence restaurant marketing performance through direct and mediated relationships. Accordingly, the following hypotheses are proposed to examine both direct and mediating relationships among these constructs.

2.2. Techno-Resonance Innovation Capability and New Service Development

Organizations with strong techno-resonant innovation capabilities can effectively respond to dynamic market demands by developing innovative services (H. Park et al., 2023; Raddats et al., 2022). This involves strategically integrating advanced technologies into business processes, promoting creativity, and improving operational efficiency (Navaratnaseel & Periyathampy, 2016; H. Park et al., 2023). Leveraging technological advances allows organizations to optimize service development, quickly adapt to changing consumer preferences, and adapt to new market trends (Schiefer et al., 2024; Serov & Korol, 2024). The effective use of technology in service innovation accelerates the creation of value-based solutions tailored to specific consumer needs (Opazo-Basáez et al., 2021).

In the restaurant industry, techno-resonant innovation is key to improving service development (Daim et al., 2021; Laudien et al., 2024). Restaurants in competitive markets face the challenge of maintaining differentiation while meeting different customer expectations (Schiff et al., 2023; Yakubiv & Boryshkevych, 2020). Companies can use advanced technologies to innovate in areas such as personalized dining experiences, optimized ordering systems, and creative menu options. These advancements improve service delivery and create unique value propositions that differentiate them from competitors (Dmitrishin, 2023; Valencia-Arias et al., 2024).

Furthermore, organizations with robust techno-resonance capabilities can predict and meet consumers’ potential desires through innovative service offerings. For example, using artificial intelligence to analyze customer preferences and integrating intelligent technologies into service interactions provides opportunities to improve customer satisfaction. Research suggests that companies that properly leverage technology in their innovation process gain a competitive advantage by introducing new services that meet or exceed consumer expectations (Blöcher & Alt, 2020; Schalow, 2025).

H1. 

Techno-resonance innovation capability positively and significantly affects new service development.

2.3. Techno-Resonance Innovation Capability with Consumer-Centric Innovative Strategy

Integrating technology with a higher degree of consumer-centricity positively influences market adaptability through enhanced customer engagement and value co-creation, aligning with market orientation Techno-resonance innovation capabilities enable companies to develop strategies that prioritize personalization and customer satisfaction (Andreassen, 2024; Jyoti et al., 2024), better leveraging technological advances to understand consumer behavior, preferences, and expectations. Incorporating innovative technologies into organizational processes enables companies to develop value-based strategies that are closely aligned with consumer needs. Techno-resonance innovation helps companies to adapt their approach in order to provide highly personalized, customer-oriented services, thereby driving increased satisfaction and loyalty (De Miguel et al., 2022; Valencia-Arias et al., 2024). Incorporating techno-resonant innovation into strategic planning can help companies to maintain their presence in competitive markets by prioritizing consumer needs. This capability improves the alignment of organizational operations with consumer preferences, allowing for the development of strategies that resonate with target markets. Using data-driven insights and predictive analytics, companies can anticipate consumer needs and provide personalized solutions that enhance customer-centric practices (Gafarov, 2024; Kotha, 2020). Such a proactive approach is essential to building sustainable competitive advantage and maintaining long-term customer relationships (Priya et al., 2025; Kripalani, 2024).

Furthermore, techno-resonant innovation drives the use of advanced tools such as artificial intelligence, machine learning, and big data analytics to refine customer-centric strategies (Adeniran et al., 2024; Grandhi et al., 2020). These technologies allow companies to process large amounts of consumer data, generate actionable insights, and develop innovative approaches tailored to individual preferences (Prisca et al., 2024; Segun-Falade et al., 2024). Refs. Jiang et al. (2022a) and Kripalani (2024) point out that this capability drives external customer engagement and satisfaction, enabling companies to maintain a competitive advantage in a dynamic marketplace while improving internal operational efficiency.

Introducing techno-resonant innovations reshapes business strategies by shifting the focus from generic market solutions to personalized, consumer-centric practices (Bari et al., 2022; Berawi et al., 2020). This alignment meets customer expectations and strengthens brand loyalty and differentiation. By leveraging technology to improve customer-centric practices, companies can ensure a sustainable competitive advantage and achieve long-term success in an increasingly competitive industry (Eldor, 2020; Kotha, 2020). As a firm’s dynamic resource, service development capabilities positively contribute to long-term competitive advantage beyond traditional marketing performance, supported by the resource-based view (Franco et al., 2021; Zheng et al., 2024b).

H2. 

Techno-resonance innovation capability positively and significantly affects consumer-centric innovative strategy.

2.4. Competitor Orientation and Consumer-Centric Innovative Strategy

Competitor actions teach companies to combine customer care with unique services that stand out from those of competitors. Companies that adopt a rival posture diligently gather market insights, including knowledge about competitors’ capabilities and limitations, and develop tactics to meet customer needs while maintaining their market niche (Huang et al., 2020). Refs. Prentice et al. (2020) and Thakur (2019) argue that rival companies are good at identifying market potential and risks, allowing them to develop new products that meet customers’ changing needs. Such a proactive strategy enables companies to meet ignored customer demands while setting themselves apart from competitors.

Moreover, observing competitors’ actions can help companies to better gauge people’s preferences, allowing them to create suitable products for customers. By meticulously examining rival products, enterprises can spot market voids and exploit this intel to cultivate and enhance their goods or services (Mousavi et al., 2022; Zheng et al., 2024a). This synchronization guarantees that enterprises fulfill client expectations and deliver distinctive remedies that distinguish them, nurturing enduring client allegiance and sector dominance. In thriving sectors such as tourism and care services, mingling knowledge about competitors with customer-focused methods is quite significant (Fainshtein et al., 2023).

H3. 

Competitor orientation positively and significantly affects the consumer-centric innovative strategy.

2.5. Consumer-Centric Innovative Strategy with Restaurant Marketing Performance

A company that focuses on what customers want makes their products, services, and interactions better for them. We promote more substantial customer involvement and commitment, which are crucial for boosting our marketing results, and show that businesses that prioritize their customers’ needs succeed in building a strong brand and market presence (Yu, 2022).

Implementing these strategies can enhance marketing success through achieving better customer engagement and increased loyalty. Ref. Juliana et al. (2025c) proposes that loyalty rebates and tailored offers improve continuous purchasing and foster constructive digital recommendations. This increased visibility and goodwill ultimately boosts marketing outcomes. Competitor orientation fosters proactive market strategies, strengthening a firm’s ability to innovate and sustain differentiation in competitive markets, which aligns with dynamic capabilities theory (Alonso & Kok, 2018; Bari et al., 2022).

Moreover, tailor-made tactics guarantee that eateries maintain flexibility and quick reactions to fluctuating customer demand. By using up-to-date information, restaurants make their offerings unique to what people want. Studies have shown that user-led innovation boosts operational efficiency and marketing success indicators like improved conversion metrics and enhanced customer loyalty (Smith et al., 2022). This dynamic alignment of innovation and marketing ensures long-term performance improvement. Restaurant performance is uniquely shaped by service quality variance, staff attentiveness, menu adaptation, and sensory experience, making innovation effects context-dependent rather than uniform. Accordingly, consumer-centric strategies may amplify competitor orientation outcomes when aligned with service delivery quality and local dining expectations.

H4. 

Consumer-centric innovative strategy positively and significantly affects restaurant marketing performance.

2.6. Competitor Orientation Influence on Restaurant Marketing Performance

Rival scrutiny propels businesses to vigilantly observe and scrutinize adversaries’ maneuvers, plans, and commerce undertakings, enabling them to stay nimble in adapting to changing market conditions. This training helps companies to figure out where their competitors are weak and create better plans for their customers, which makes them stand out. Refs. Abosag et al. (2020) and An and Han (2020) note that entities with a keen rivalry mindset actively collect market data to synchronize their inventive activities with consumer demands, providing distinction in crowded industries. Competitors’ insights and what buyers like match up well, giving a strong base to make new and appealing ideas for customers. Through rival analysis, companies react to market dynamics and foresee client needs by utilizing knowledge gained from comparative evaluation.

Furthermore, paying attention to competitors helps companies to find ways to improve, enabling them to stay on top of their game in places where many businesses are trying to be leaders. Refs. Ahmad et al. (2021) and Varadarajan (2020) contend that enterprises cognizant of competitor interests are more inclined to adopt progressive tactics that satisfy unaddressed and changing customer demands. By tailoring propositions through marketplace analysis, businesses can guarantee that their customer-focused tactics align with niche demographics and tackle the distinct adversities that competitors may disregard.

Empirical research has shown that such strategies help to improve brand loyalty, market share, and overall performance (Zhou et al., 2023). Hence, a peer-focused strategy serves as an accelerant for nurturing demand-driven innovations that are both distinctive and tailored to consumer expectations, yielding a persistent market edge.

H5. 

Competitor orientation positively and significantly affects restaurant marketing performance.

2.7. New Service Development on Restaurant Marketing Performance

New service development is essential to achieve superior marketing performance by responding to changing consumer demands and differentiating companies in a competitive market. Introducing innovative services allows companies to create unique value propositions that appeal to target customers. Refs. Japutra et al. (2019) and Kiatkawsin and Sutherland (2020) emphasize that new service developments improve brand reputation, increase customer engagement, and foster loyalty, thereby contributing to improved marketing performance. In the catering industry, innovations such as technology-driven ordering systems and unique catering concepts provide opportunities for differentiation and market expansion (Mousavi et al., 2022; Pascual-Fernández et al., 2020). Restaurants that invest in new service development often achieve higher customer satisfaction and retention by offering solutions that meet or exceed consumer expectations. The authors of (Lee et al., 2021; H. Park et al., 2023) found that service innovations such as personalized dining experiences and eco-friendly initiatives strongly appeal to modern consumers, resulting in positive word of mouth and repeat patronage. This alignment of service innovations and consumer preferences ensures that marketing strategies deliver tangible performance benefits, such as increased customer loyalty and market share (Utari et al., 2024; Ushkarenko & Sorokin, 2024).

New service development enables restaurants to respond effectively to dynamic market trends and consumer behaviors, ensuring long-term sustainability. Introducing innovative services such as contactless payment systems and curated dining experiences can improve operational efficiency and enhance a restaurant’s value proposition (Cantele & Cassia, 2020; Da Costa Maynard et al., 2020). The authors of (Dai et al., 2020; Rahman et al., 2021) point out that service innovation helps to build emotional connections with customers, leading to improved marketing outcomes such as increased brand equity and higher customer lifetime value.

NSD’s impact on marketing performance lies in its ability to create differentiated, value-driven products tailored to specific customer segments. Research has consistently shown that innovative services increase customer satisfaction, brand attachment, and loyalty (Do & Pereira, 2023; Kaakeh et al., 2020). In the competitive restaurant industry, such innovations can bring essential advantages and improve marketing performance by aligning services with customer needs and market demands.

H6. 

New service development positively and significantly affects restaurant marketing performance.

2.8. New Service Development Mediates the Relationship Between Techno-Resonance Innovation Capability and Restaurant Marketing Performance

Engaging in techno-resonant innovation is essential for developing new services in the restaurant sector, as introducing new technologies significantly improves service efficiency, personalization, and overall customer experience (Yun et al., 2020). Research has shown that companies integrating technological innovation into their service offerings can gain a competitive advantage by meeting customer needs more effectively (Cho et al., 2019; Da Costa Maynard et al., 2020). For example, digital ordering systems and AI-powered customer analytics can improve service processes and increase customer satisfaction.

The relationship between techno-resonant innovation capabilities and restaurant marketing performance is mediated by new service developments that transform technological capabilities into marketable innovations. These innovations solve operational challenges and create unique value propositions for customers (Burtseva et al., 2024; Najib et al., 2020). This process aligns technological advances with strategic marketing goals, enhancing a company’s competitive position.

The effectiveness of new service development depends on whether it resonates with target customers while responding to evolving market needs (Kitsios & Kamariotou, 2020). By leveraging technology for service innovation, restaurants can provide experiences that attract and retain customers, ultimately improving marketing performance.

The interplay between technological performance and service innovation is key to achieving superior marketing results (Esposito et al., 2022; Nijssen & Ordanini, 2020). New service development acts as a bridge, ensuring that investments in technology translate into tangible business outcomes. This move highlights the importance of integrating innovation strategies into service development frameworks to optimize marketing effectiveness (Kitsios & Kamariotou, 2020; Wu et al., 2021).

H7. 

New service development mediates the relationship between techno-resonance innovation capability and restaurant marketing performance.

2.9. Consumer-Centric Innovative Strategy Mediates the Relationship Between Techno-Resonance Innovation Capability and Restaurant Marketing Performance

Consumer-centric innovative strategy mediates the relationship between techno-resonance innovation capability and restaurant marketing performance by translating technological readiness into customer-aligned service adaptation (Tsaur et al., 2024). While technological capability enhances firms’ ability to process market signals, performance improvements occur only when those signals are embedded into customer-focused service innovation processes. This mechanism reflects the dynamic capability transformation logic through which sensing and seizing activities support performance outcomes (J. Kim et al., 2020).

Techno-resonance innovation capability reflects a firm’s ability to align technological readiness with market-responsive service innovation processes that support adaptive strategic action. Within the framework of dynamic capabilities theory, technological capability alone does not automatically translate into improved performance outcomes unless it is effectively integrated into customer-oriented strategic initiatives (Fainshtein et al., 2024; Quang-Huy, 2023). In restaurant contexts, technological adoption must be interpreted and operationalized through innovation strategies that respond directly to changing customer expectations and service experiences (Jose & Joseph, 2025). Therefore, consumer-centric innovative strategy functions as a transformation mechanism that converts technological inputs into market-relevant service solutions. As a result, the influence of techno-resonance innovation capability on marketing performance is expected to occur indirectly through customer-focused innovation alignment, rather than through direct technological deployment alone (Aydin, 2020).

Furthermore, consumer-centric innovative strategies strengthen a firm’s ability to translate technological insights into differentiated service offerings, improved customer engagement, and enhanced perceived value creation (Munir et al., 2025). This strategic alignment enables restaurants to design innovation initiatives that reflect customer preferences more accurately, thereby improving marketing effectiveness and strengthening performance indicators such as sales growth and return on investment. In emerging-market hospitality environments, where technological investments often face resource constraints, customer-centered innovation strategies become particularly important in ensuring that technological capability produces measurable performance benefits (Huddin et al., 2025). Accordingly, a consumer-centric innovative strategy is expected to mediate the relationship between techno-resonance innovation capability and restaurant marketing performance by linking internal capability readiness with externally oriented innovation execution (Yu, 2022). Based on this reasoning, the following hypothesis is proposed:

H8. 

Consumer-centric innovative strategy mediates the relationship between techno-resonance innovation capability and restaurant marketing performance.

2.10. New Service Development Mediates the Relationship Between Competitor Orientation and Restaurant Marketing Performance

New service development mediates the relationship between competitor orientation and restaurant marketing performance because competitive intelligence alone does not directly generate performance advantages unless it is converted into differentiated service offerings (Ratang, 2025; Sanchez, 2025; Schulze et al., 2022). By translating competitor insights into innovative service features and delivery processes, firms improve responsiveness to market expectations and strengthen their competitive positioning. Competitor orientation reflects a firm’s ability to systematically monitor competitor strategies, anticipate market positioning shifts, and respond proactively to emerging competitive pressures (Crick et al., 2020; Crick, 2020). Within the dynamic capabilities framework, competitor-related intelligence becomes strategically valuable when it supports organizational learning processes that enable firms to reconfigure service offerings in response to changing market conditions. In restaurant environments characterized by rapid menu innovation cycles and evolving customer expectations, competitor orientation helps managers to identify both gaps in existing service portfolios and opportunities for differentiation (Crick & Crick, 2020; Tafesse & Wood, 2023). However, competitor awareness alone does not automatically translate into improved performance outcomes unless it is operationalized through structured innovation activities. Therefore, new service development functions as a key mechanism through which competitor-oriented knowledge is transformed into actionable service innovations that strengthen marketing performance (Baratta & Simeoni, 2021; Kitsios & Kamariotou, 2020).

Furthermore, new service development enables restaurant firms to convert competitive intelligence into tangible service improvements such as menu innovation, experience enhancement, and delivery format adaptation that respond to evolving customer preferences (Kamali et al., 2024). These innovation processes improve perceived service value and strengthen customer attraction and retention, thereby supporting performance indicators such as sales growth and return on investment. In emerging-market restaurant contexts where competition is increasingly intensified by digital platforms and experiential differentiation strategies, the ability to translate competitor insights into structured service innovation becomes particularly important for sustaining performance advantages (Cowan & Kostyk, 2020). Accordingly, competitor orientation is expected to influence restaurant marketing performance indirectly through its effect on new service development activities that enable firms to respond strategically to market competition (Giertz et al., 2022). Based on this reasoning, the following hypothesis is proposed:

H9. 

New service development mediates the relationship between competitor orientation and restaurant marketing performance.

2.11. Consumer-Centric Innovative Strategy Mediates the Relationship Between Competitor Orientation and Restaurant Marketing Performance

Competitive orientation provides key insights that allow companies to predict market trends and effectively adjust their strategies (Van et al., 2023). By closely studying competitors’ actions, restaurants can discover opportunities to differentiate their offerings and develop customer-centric strategies. This methodology allows companies to remain relevant and competitive in a rapidly changing market environment (Sanchez, 2025).

Developing customer-centric, innovative strategies is a mediating factor to leverage competitor insights to achieve superior marketing performance (Ali et al., 2020; Talafubieke et al., 2021). These strategies focus on effectively meeting customer needs and expectations beyond what competitors offer, thereby increasing customer value (Andre & Raharjo, 2020). Companies can achieve higher customer retention rates by focusing on customer satisfaction and promoting increased brand loyalty (Erwin et al., 2021; Kanaan, 2023).

Customer-centric strategies resulting from competitive orientation allow restaurants to proactively respond to market trends and create a unique position within the industry (Al-Surmi et al., 2020; Alqahtani & Uslay, 2020). Offering personalized dining experiences and incorporating innovative delivery services can help restaurants to outperform their competitors while effectively responding to changing customer preferences. These efforts improve marketing outcomes, such as customer acquisition and retention (Pranata et al., 2024).

The following hypothesis highlights the mediating role of customer-centric strategies in linking competitive orientation and marketing success (Mulyana et al., 2020); in particular, focusing on customer-centric innovation based on competitor analysis allows restaurants to achieve strategic marketing goals and maintain a competitive advantage (Han, 2024). This move highlights the importance of integrating a customer-centric approach into the innovation process for sustainable business growth.

H10. 

Consumer-centric innovative strategy mediates the relationship between competitor orientation and restaurant marketing performance.

3. Research Methodology

3.1. Research Design

This study adopts a quantitative explanatory research design to examine the relationships among techno-resonance innovation capability, competitor orientation, consumer-centric innovative strategy, new service development, and restaurant marketing performance in emerging hospitality markets. The research objective focuses on testing capability integration mechanisms through which organizational strategic resources influence performance outcomes rather than evaluating environmental sustainability indicators directly. Accordingly, the analytical framework is grounded in capability-based strategic management perspectives derived from dynamic capabilities theory and the resource-based view (Barney, 1991; Barney et al., 2001).

Data were collected using a structured questionnaire distributed to restaurant managers and decision-makers operating in Indonesia. Therefore, the unit of analysis represents organizational decision-level responses rather than consumer perceptions. This design enables evaluation of strategic capability deployment within operational restaurant environments characterized by dynamic competition and service innovation pressures. Data were analyzed using SEM-PLS to examine mediating and direct relationships across constructs. A systematic literature review informed indicator development by screening peer-reviewed sources from 2020 to 2025. All participants provided informed consent voluntarily, with anonymity protected and no identifying data recorded. The research protocol followed institutional ethical approval guidelines.

3.2. Population and Sampling

The population of this study consists of restaurant managers operating in Java and Bali, Indonesia’s two primary hospitality market clusters. These regions represent the largest concentration of restaurant businesses in Indonesia and are characterized by strong tourism intensity, advanced digital service adoption, and highly competitive dynamics. Consequently, they provide an analytically appropriate setting for examining capability integration strategies within emerging-market hospitality contexts.

Purposive sampling was employed to select respondents with managerial responsibility and decision-making authority related to innovation strategy and marketing performance. This sampling strategy ensured that participants possessed the relevant operational knowledge required to evaluate capability-based constructs. A total of 300 valid responses were collected between January and June 2024. Although purposive sampling introduces limitations regarding statistical generalization, it strengthens construct validity by targeting respondents directly involved in strategic decision processes. The target group for this study is restaurateurs aged 25 years and above.

3.3. Sample Size Adequacy and Statistical G Power Analysis

To ensure that the sample size was sufficient for structural model estimation, an a priori statistical power analysis was conducted using G*Power version 3.1.9.4. Following recommended procedures for Partial Least Squares Structural Equation Modeling (PLS-SEM), the analysis applied a linear multiple regression framework (fixed model, R² deviation from zero) to approximate the minimum sample size required for estimating structural relationships involving multiple predictors (Kang, 2021; Kock & Hadaya, 2018).

The calculation assumed a medium effect size (f² = 0.15), a significance level (α) of 0.05, a statistical power level (1 − β) of 0.95, and five predictors, corresponding to the maximum number of structural paths directed toward an endogenous construct in the proposed research model. The G*Power results indicated that the minimum required sample size was 138 observations.

As the final dataset consisted of 300 restaurant managers operating in Java and Bali, the achieved sample size substantially exceeded the recommended threshold. This confirms that the dataset possesses sufficient statistical sensitivity to detect both direct and indirect structural relationships among techno-resonance innovation capability, competitor orientation, consumer-centric innovative strategy, new service development, and restaurant marketing performance.

The achieved statistical power value (actual power = 0.9508) further supports the adequacy of the sample for prediction-oriented structural modeling. Accordingly, the sample size satisfies recommended methodological requirements for PLS-SEM estimation and strengthens confidence in the robustness and reliability of the hypothesis testing results.

3.4. Measurement Instrument

Data were collected using a structured questionnaire measured on a six-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree) (Hu & Yuan, 2020). The use of an even-numbered response scale was intended to reduce central-tendency bias and encourage respondents to provide directional managerial judgments rather than selecting a neutral midpoint. This format is considered particularly appropriate when measuring organizational innovation capability and performance-related perceptions among managerial respondents. The questionnaire was pre-tested with 30 restaurant managers to ensure the clarity, content validity, and reliability of the measurement items before full data collection. Participation was voluntary and anonymous, and no identifying information was recorded. The research protocol followed institutional ethical approval procedures consistent with accepted academic research standards.

3.5. Construct Operationalization

The constructs investigated in this study were adapted from previously validated instruments to ensure measurement reliability and conceptual consistency. The constructs investigated were refined into actionable variables, also called indicators. When examining the “techno-resonant innovativeness” variable, indicators such as technology-based design skills and configuration skills are used, as proposed by (Daim et al., 2021; Laudien et al., 2024). The competitive orientation construct is assessed using companies focusing on competition and proactive responses to competitive actions (Kabadayi et al., 2020; Trunfio et al., 2022). Indicators of consumer-oriented innovation strategies are based on (Adeniran et al., 2024; Grandhi et al., 2020) and were evaluated based on creative solutions and the visualization of service design. Indicators of new service development constructs include the integration of customer feedback and quality of service execution (Juliana et al., 2022; Luo & Ye, 2020). Finally, restaurant marketing performance is analyzed based on sales volume and return on investment (Cantele & Cassia, 2020; Da Costa Maynard et al., 2020). In this study, restaurant marketing performance is operationalized using managerial indicators such as sales volume growth and return on investment, which represent observable outcomes of strategic capability deployment (Chaturvedi et al., 2022; Robinson et al., 2023). Accordingly, the theoretical framework focuses on capability integration mechanisms through which technological readiness, competitive intelligence, and customer-oriented innovation strategies influence performance outcomes, rather than environmental sustainability metrics.

3.6. Data Analysis Technique

Before structural model estimation, the distributional properties of the dataset were examined and indicated moderate deviations from multivariate normality, which are common in managerial survey research. Therefore, Partial Least Squares Structural Equation Modeling (PLS-SEM) was selected as the appropriate analytical technique. PLS-SEM is recommended for prediction-oriented research involving complex mediation relationships, multiple latent constructs, and non-normally distributed data (Hair et al., 2017, 2019; Sarstedt et al., 2022). As this study aims to examine capability integration mechanisms influencing restaurant marketing performance rather than to confirm a covariance-based model structure, the use of PLS-SEM is methodologically appropriate and consistent with current best-practice recommendations in hospitality and strategic management research.

3.7. Measurement Model Evaluation

The measurement model was evaluated prior to structural model estimation to ensure construct reliability and validity following recommended PLS-SEM procedures. Indicator reliability was confirmed through outer loadings exceeding the threshold of 0.70, while internal consistency reliability was supported by Cronbach’s alpha and composite reliability values above 0.70. Convergent validity was established using average variance extracted (AVE) values greater than 0.50 for all constructs. Discriminant validity was assessed using the Heterotrait–Monotrait ratio (HTMT), with all values below the recommended threshold of 0.90. In addition, variance inflation factor (VIF) values were below 3.3, indicating no critical multicollinearity issues. These results confirm that the measurement model satisfies established reliability and validity requirements and is appropriate for subsequent structural model analysis (Hair et al., 2024).

3.8. Structural Model Evaluation

After confirming the adequacy of the measurement model, the structural model was evaluated to examine the hypothesized relationships among techno-resonance innovation capability, competitor orientation, consumer-centric innovative strategy, new service development, and restaurant marketing performance using recommended PLS-SEM procedures (Ringle et al., 2023). Collinearity diagnostics indicated that all VIF values were below the threshold of 3.3, confirming the absence of multicollinearity concerns. The explanatory power of the model, assessed using R² values, indicates modest but acceptable variance explanation consistent with exploratory capability-based modeling contexts. Predictive relevance was supported by Stone–Geisser Q² values greater than zero, confirming the model’s predictive capability. The significance of structural relationships was evaluated using bootstrapping procedures, which confirmed several statistically significant direct and indirect relationships, including mediation effects through consumer-centric innovative strategy and new service development. Overall, the structural model provides meaningful empirical insight into how capability integration influences restaurant marketing performance in emerging hospitality markets.

3.9. Post Hoc Heterogeneity Assessment (PLS-POS)

To examine potential unobserved heterogeneity, a post hoc prediction-oriented segmentation (PLS-POS) analysis was conducted (Sarstedt & Ringle, 2010). The results indicated subgroup-level differences in structural relationships; however, one segment contained a very small number of observations, which may lead to unstable parameter estimation and potential overfitting. Therefore, the segmentation results were not retained for substantive interpretation, and only the aggregate structural model estimates are reported. This decision is consistent with recommended methodological practice when subgroup sample sizes are insufficient for reliable inference. Accordingly, the findings should be interpreted as representing overall capability integration patterns across the sampled restaurant managers, rather than segment-specific differences.

4. Findings and Discussion

4.1. Respondent Profile

Data were collected from restaurant managers and decision-makers responsible for innovation and marketing strategy implementation, rather than restaurant customers. Therefore, the demographic profile presented in

Table 1. Demographic profile of respondents.

Demographic Variables		Samples (n)	Percentage (%)
Gender	Man	140	46.7
	Woman	160	53.3
Age	17–24 years	27	9.0
	25–30 years	90	30.0
	31–35 years	163	54.3
	36–40 years	14	4.7
	Over 40 years	6	2.0
Education	High school/equivalent	6	2.0
	Diploma/equivalent	74	24.7
	S1	215	71.7
	Postgraduate	5	1.7
Length of Time with Open Restaurant	<1 year	100	33.3
	1–2 years	100	33.3
	>1–5 years	2	0.7
	>5–11 years	36	12.0
	>11 years	62	20.7

reflects managerial characteristics rather than consumer attributes.

As shown in Table 1, the respondent profile reflects the managerial characteristics of restaurant decision-makers, with the largest proportion aged 31–35 years and holding a bachelor’s degree. The corrected percentages now provide a consistent descriptive overview of the sample structure.

4.2. Evaluation of Measurement Models

The reliability and convergent validity of the measurement model in

Table 2. Reliability and validity test.

	Cronbach’s Alpha	Composite Reliability (rho_a)	Composite Reliability (rho_c)	Average Variance Extracted (AVE)
Competitor orientation	0.727	0.734	0.827	0.545
Consumer-centric innovative strategy	0.766	0.801	0.848	0.5834
New service development	0.774	0.795	0.8521	0.589
Restaurant marketing performance	0.744	0.784	0.835	0.559
Techno-resonance innovation capability	0.751	0.781	0.839	0.566

were assessed using Cronbach’s alpha, rho_A, composite reliability, and average variance extracted (AVE). The results indicate that all constructs achieved acceptable reliability levels, with Cronbach’s alpha values ranging from 0.727 to 0.774 and composite reliability values between 0.827 and 0.852, exceeding the recommended threshold of 0.70. Additionally, the AVE values ranged from 0.545 to 0.589, surpassing the minimum requirement of 0.50, confirming adequate convergent validity. These findings suggest that all indicators reliably represent their respective latent constructs and are appropriate for further structural model analysis.

The measurement model is depicted in Figure 2, which illustrates the outer model with observed indicators and latent constructs, confirming the factor structure and validity of the measurement model.

Validity testing was carried out using the Heterotrait–Monotrait Ratio (HTMT), as stated by (Henseler et al., 2015). The test results are presented in

Table 3. HTMT values.

	Competitor Orientation	Consumer-Centric Innovative Strategy	New Service Development	Restaurant Marketing Performance	Techno-Resonance Innovation Capability
Competitor orientation
Consumer-centric innovative strategy	0.230
New service development	0.055	0.240
Restaurant marketing performance	0.088	0.238	0.220
Techno-resonance innovation capability	0.120	0.199	0.263	1.146

, with the HTMT value below 0.90. It can be concluded that all indicators are able to be discriminated to measure their respective constructs.

4.3. Structural Models

The structural (inner) model can be tested if the existing model is declared valid (outer model). Based on the explanations from several past studies (Hair et al., 2017, 2019; Sarstedt et al., 2022), the inner model test was carried out to observe the quality of the relationship between variables and to test the existing hypotheses. The results are displayed in

Table 4. VIF values.

Path Analysis	VIF
Competitor orientation → Consumer-centric innovative strategy	1.000
Competitor orientation → New service development	1.034
Consumer-centric innovative strategy → New service development	1.066
Consumer-centric innovative strategy → Restaurant marketing performance	1.038
New service development → Restaurant marketing performance	1.038
Techno-resonance innovation capability → Consumer-centric innovative strategy	1.000
Techno-resonance innovation capability → New service development	1.031

below.

The R-square values shown in

Table 5. R-square.

	R-Square	R-Square Adjusted
Consumer-centric, innovative strategy	0.062	0.056
New service development	0.075	0.068
Restaurant marketing performance	0.057	0.051

for the three dependent variables of consumer-centric innovative strategy (6.2%), new service development (7.5%), and restaurant marketing performance (5.7%) are relatively low, reflecting the limited explanatory capacity of the independent variables included in the model. The adjusted R-square values exhibit a slight decrease across all constructs, indicating a modest reduction in explanatory strength after factoring in the number of predictors. These findings suggest that considerable variance in these constructs remains unexplained, indicating the influence of additional elements not captured by the current model.

These results underscore potential deficiencies in the model and highlight the need for further refinement. External influences such as shifting market trends or organizational dynamics may affect consumer-centric innovative strategies. In contrast, competitive pressures or digital strategies may shape new service development and marketing performance. Future research should aim to incorporate additional predictors, mediating variables, or moderating effects. This approach would fortify the theoretical framework and yield more actionable insights for practitioners within the service and marketing sectors. The R² values for consumer-centric innovative strategy (0.062), new service development (0.075), and restaurant marketing performance (0.057) indicate weak explanatory power. These results suggest that the constructs included in the model account for only a small proportion of the variance in the endogenous variables and, therefore, should not be interpreted as strong predictors of restaurant performance. Rather, the findings provide exploratory evidence that these capabilities are associated with performance outcomes, while implying that other unmeasured organizational, market, and contextual factors likely play a more substantial role.

The R² value for restaurant marketing performance (0.057) indicates weak explanatory power, suggesting that the constructs included in the model account for only a limited proportion of the variance in performance outcomes. These results imply that additional organizational, environmental, and market-related variables likely play a more substantial role in explaining restaurant marketing performance beyond the capability constructs examined in this study.

The f² values shown in

Table 6. F-square.

Hypothesis	f-Square	Result
Competitor orientation → Consumer-centric innovative strategy	0.034	Small effect size
Consumer-centric innovative strategy → New service development	0.026	Small effect size
Consumer-centric, innovative strategy → Restaurant marketing performance	0.031	Small effect size
New service development → Restaurant marketing performance	0.018	No effect size
Techno-resonance innovation capability → Consumer-centric, innovative strategy	0.031	Small effect size
Techno-resonance innovation capability → New service development	0.041	Small effect size

indicate that all relationships in the model exhibit a small effect size, meaning that while the independent variables have statistically significant effects on their respective dependent variables, their practical impact remains limited. Competitor orientation shows a slight but notable influence on consumer-centric innovative strategy (f² = 0.034), indicating that while competition awareness drives innovation, other factors likely play a more significant role. Similarly, consumer-centric innovative strategy has a minor impact on new service development (f² = 0.026) and restaurant marketing performance (f² = 0.031), suggesting that additional variables such as technological adoption, market positioning, or customer engagement may substantially influence these outcomes. New service development has the weakest effect on restaurant marketing performance (f² = 0.018), implying that service innovation alone cannot drive performance improvements without proper strategic support.

On the other hand, techno-resonance innovation capability, which refers to the integration of technology in business innovation, demonstrates a small yet slightly higher effect on new service development (f² = 0.041) compared to its influence on consumer-centric innovative strategy (f² = 0.031). This suggests that leveraging technology is more impactful in driving new service creation than in shaping consumer-driven innovation strategies. However, since all effect sizes remain within the small range, no single variable dominates the model. These findings highlight the need for a more comprehensive approach that integrates additional mediating or moderating variables to enhance the impact of innovation strategies on restaurant marketing performance.

The Q² predict values in

Table 7. Q-square.

Variable	Q2 Predict	Result
Consumer-centric innovative strategy	0.029	Small predictive relevance
New service development	0.037	Small predictive relevance
Restaurant marketing performance	0.028	Small predictive relevance

indicate the predictive relevance of the model’s endogenous constructs using the PLS-SEM methodology. Based on the results, consumer-centric innovative strategy (Q² = 0.029), new service development (Q² = 0.037), and restaurant marketing performance (Q² = 0.028) all exhibit small predictive relevance. This suggests that while the model provides some level of predictive accuracy, it remains relatively weak in explaining the variance in these constructs. The low R² values, including the final dependent variable’s R² of 0.057, further reinforce this limitation.

Although the Q² values indicate modest predictive relevance, they do not invalidate the structural model but suggest opportunities for further theoretical refinement and model extension. Future research may strengthen explanatory power by integrating additional theoretical perspectives such as the resource-based view and dynamic capabilities theory, as well as incorporating constructs such as customer experience, service quality, market turbulence, and technological readiness as mediating or moderating variables. In addition, the relatively low explanatory power may reflect the influence of omitted variables, contextual differences across firms, or potential unobserved heterogeneity within the sample. Therefore, the findings should be interpreted cautiously and viewed as exploratory evidence of capability integration mechanisms influencing restaurant marketing performance in emerging hospitality markets. The PLS-POS results reveal substantial heterogeneity across segments, with one subgroup showing very high explanatory power and another showing weak explanatory power. This pattern suggests that the aggregated model may mask important subgroup differences and that the structural relationships are unlikely to be uniform across all restaurant contexts. Therefore, the aggregate findings should be interpreted with caution, and the results are better understood as exploratory evidence of heterogeneous capability–performance relationships rather than as universally stable effects. Future research might consider employing multi-group analysis or latent class modeling to better account for heterogeneity and improve model fit across different segments.

4.4. Hypothesis Test

Hypothesis testing is carried out to determine whether the variables’ influence is supported (Hair et al., 2017, 2019; Sarstedt et al., 2022). This test was carried out by bootstrapping using a one-tailed test approach with an alpha value of 0.05, and the results can be seen in

Table 8. Hypothesis testing.

Hypothesis	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	p Values
Competitor orientation → Consumer-centric innovative strategy	0.179	0.050	3.540	0.000
Consumer-centric innovative strategy → New service development	0.158	0.064	2.449	0.014
Consumer-centric innovative strategy → Restaurant marketing performance	0.175	0.062	2.827	0.005
New service development → Restaurant marketing performance	0.132	0.067	1.980	0.048
Techno-resonance innovation capability → Consumer-centric innovative strategy	0.171	0.057	3.021	0.003
Techno-resonance innovation capability → New service development	0.197	0.063	3.109	0.002

.

Based on Table 8, it can be concluded that the variables competitor orientation, consumer-centric innovative strategy, new service development, techno-resonance innovation capability, and consumer-centric innovative strategy have the most substantial significant effect on restaurant marketing performance because each variable has a p-value < 0.05. Although all of the hypothesized relationships are statistically significant, the standardized path coefficients indicate modest effect sizes, suggesting that the examined capability variables represent only part of a broader performance formation mechanism in restaurant contexts. Hypothesis H1 proposes that techno-resonance innovation capability positively influences consumer-centric innovative strategy. The results confirm that H1 is supported (β = 0.171, t = 3.021, p = 0.003), indicating that technological readiness contributes to strengthening customer-centered innovation alignment, supporting the role of techno-resonance capability in facilitating strategic responsiveness to customer expectations in restaurant contexts.

Hypothesis H2 proposes that techno-resonance innovation capability positively influences new service development. The results confirm that H2 is supported (β = 0.197, t = 3.109, p = 0.002), suggesting that technological capability enables restaurant firms to develop new service offerings more effectively, reinforcing the importance of innovation-oriented capability deployment in supporting service differentiation.

Hypothesis H3 proposes that competitor orientation positively influences consumer-centric innovative strategy. The results confirm that H3 is supported (β = 0.179, t = 3.540, p < 0.001), indicating that monitoring competitor behavior supports firms in adjusting innovation strategies to remain aligned with market expectations and competitive positioning.

Hypothesis H4 proposes that consumer-centric innovative strategy positively influences new service development. The results confirm that H4 is supported (β = 0.158, t = 2.449, p = 0.014), suggesting that customer-centered innovation strategies contribute to the development of new service initiatives that respond to evolving consumer preferences in restaurant environments.

Hypothesis H5 proposes that consumer-centric innovative strategy positively influences restaurant marketing performance. The results confirm that H5 is supported (β = 0.175, t = 2.827, p = 0.005), indicating that aligning innovation activities with customer needs contributes to improved marketing outcomes such as sales growth and return on investment.

Hypothesis H6 proposes that new service development positively influences restaurant marketing performance. The results confirm that H6 is supported (β = 0.132, t = 1.980, p = 0.048), suggesting that the introduction of new service offerings contributes modestly to marketing performance improvements, supporting the role of structured service innovation in strengthening restaurant competitiveness. The results support the capability integration perspective proposed in this study, demonstrating that techno-resonance innovation capability and competitor orientation influence restaurant marketing performance primarily through customer-centered innovation strategy and new service development mechanisms rather than through isolated direct capability effects.

Table 9. Total effect.

	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	p Values
Competitor orientation → Consumer-centric innovative strategy	0.178	0.053	3.357	0.000
Competitor orientation → New service development	0.005	0.067	0.074	0.470
Competitor orientation → Restaurant marketing performance	0.032	0.020	1.619	0.053
Consumer-centric innovative strategy → New service development	0.162	0.066	2.445	0.007
Consumer-centric innovative strategy → Restaurant marketing performance	0.201	0.058	3.479	0.000
New service development → Restaurant marketing performance	0.155	0.067	2.308	0.011
Techno-resonance innovation capability → Consumer-centric innovative strategy	0.170	0.057	3.003	0.001
Techno-resonance innovation capability → New service development	0.225	0.060	3.761	0.000
Techno-resonance innovation capability → Restaurant marketing performance	0.065	0.027	2.411	0.008

presents the total effects among the study variables, combining both direct and indirect structural relationships within the proposed capability integration framework. Although several total effects are statistically significant, their relatively modest magnitude indicates that additional organizational and environmental variables beyond those included in the present model are likely to play an important role in explaining restaurant marketing performance. The results for Hypothesis 7 indicate that competitor orientation has a significant total effect on consumer-centric innovative strategy (β = 0.178, t = 3.357, p < 0.001), suggesting that competitor-related intelligence contributes to strengthening customer-aligned innovation initiatives in restaurant firms. However, the results for Hypothesis 8 regarding competitor orientation do not show a significant total effect on new service development (β = 0.005, t = 0.074, p = 0.470), nor do those for Hypothesis 9 regarding restaurant marketing performance (β = 0.032, t = 1.619, p = 0.053), indicating that its contribution to performance outcomes operates primarily through intermediate strategic mechanisms rather than through direct influence.

The results for Hypotheses 10 and 11 further demonstrate that a consumer-centric innovative strategy has a significant total effect on both new service development (β = 0.162, t = 2.445, p = 0.007) and restaurant marketing performance (β = 0.201, t = 3.479, p < 0.001). These findings suggest that customer-oriented innovation alignment plays an important role in translating strategic capability into service innovation initiatives and marketing performance improvements. Similarly, the results for Hypothesis 12 regarding new service development show a significant total effect on restaurant marketing performance (β = 0.155, t = 2.308, p = 0.011), supporting the argument that structured service innovation contributes to measurable performance outcomes such as sales growth and return on investment in restaurant contexts.

Hypotheses 13–15, regarding techno-resonance innovation capability, demonstrate significant total effects on consumer-centric innovative strategy (β = 0.170, t = 3.003, p = 0.001), new service development (β = 0.225, t = 3.761, p < 0.001), and restaurant marketing performance (β = 0.065, t = 2.411, p = 0.008). These results indicate that technological readiness contributes both directly and indirectly to marketing performance through customer-centered innovation strategy and service development mechanisms. However, the relatively modest magnitude of the total effects suggests that techno-resonance innovation capability operates as one component within a broader capability configuration influencing restaurant performance rather than as a dominant explanatory factor.

The total-effects analysis supports the capability integration perspective proposed in this study by demonstrating that technological capability, competitor orientation, and customer-centered innovation strategy contribute to restaurant marketing performance primarily through interconnected strategic pathways rather than through isolated capability effects.

To further examine whether the relationships among capability variables operate through indirect strategic mechanisms, mediation effects were evaluated using bootstrapping procedures in PLS-SEM (

Table 10. Mediation analysis.

Hypothesis	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	p Values
Competitor orientation → Consumer-centric innovative strategy → New service development	0.029	0.031	0.015	1.914	0.028
Competitor orientation → New service development → Restaurant marketing performance	−0.004	−0.004	0.012	0.298	0.383
Techno-resonance innovation capability → Consumer-centric innovative strategy → New service development → Restaurant marketing performance	0.004	0.005	0.003	1.423	0.077
Competitor orientation → Consumer-centric innovative strategy → Restaurant marketing performance	0.031	0.035	0.015	2.159	0.015
Consumer-centric innovative strategy → New service development → Restaurant marketing performance	0.025	0.027	0.016	1.617	0.053
Techno-resonance innovation capability → Consumer-centric innovative strategy → New service development	0.027	0.030	0.016	1.773	0.038
Techno-resonance innovation capability → New service development → Restaurant marketing performance	0.031	0.038	0.023	1.353	0.088
Techno-resonance innovation capability → Consumer-centric innovative strategy → Restaurant marketing performance	0.030	0.036	0.021	1.445	0.074
Competitor orientation → Consumer-centric innovative strategy → New service development → Restaurant marketing performance	0.004	0.005	0.003	1.301	0.097

). The mediation analysis assessed whether consumer-centric innovative strategy and new service development function as intermediate capability integration pathways linking techno-resonance innovation capability and competitor orientation to restaurant marketing performance.

The results for testing Hypothesis 16 indicate that consumer-centric innovative strategy significantly mediates the relationship between competitor orientation and new service development (β = 0.029, t = 1.914, p = 0.028), suggesting that competitor intelligence contributes to service development primarily through customer-aligned innovation strategy rather than through direct strategic adaptation alone. Similarly, regarding Hypothesis 19, consumer-centric innovative strategy significantly mediates the relationship between competitor orientation and restaurant marketing performance (β = 0.031, t = 2.159, p = 0.015), indicating that competitor orientation supports performance improvement indirectly through customer-focused innovation alignment.

The results for testing Hypothesis 20 show that consumer-centric innovative strategy mediates the relationship between techno-resonance innovation capability and new service development (β = 0.027, t = 1.773, p = 0.038), suggesting that technological readiness contributes to service innovation through customer-centered strategic alignment rather than through direct technological deployment alone. However, regarding Hypothesis 21, the indirect effect of consumer-centric innovative strategy on restaurant marketing performance through new service development is only marginally significant (β = 0.025, t = 1.617, p = 0.053), indicating that this sequential mediation pathway should be interpreted cautiously.

Furthermore, the results of testing Hypotheses 22–24 show that several sequential mediation paths involving multiple intermediate constructs are not statistically significant, including the indirect effect of competitor orientation through new service development on restaurant marketing performance (β = −0.004, t = 0.298, p = 0.383), the sequential mediation path linking techno-resonance innovation capability through consumer-centric innovative strategy and new service development to restaurant marketing performance (β = 0.004, t = 1.423, p = 0.077), and the indirect effect of techno-resonance innovation capability through new service development on restaurant marketing performance (β = 0.031, t = 1.353, p = 0.088). These findings indicate that not all capability integration pathways operate through extended sequential mediation mechanisms within the proposed structural model.

The mediation results suggest that a consumer-centric innovative strategy plays a more consistent mediating role than new service development in linking strategic capability variables to restaurant marketing performance. Therefore, the findings support the argument that customer-aligned innovation strategy represents an important transformation mechanism through which technological readiness and competitor orientation influence marketing outcomes in restaurant firms, although the strength of these mediation effects remains modest within the overall explanatory structure of the model. Although several mediation pathways are statistically significant, the relatively small magnitude of the indirect effects indicates that additional organizational and environmental factors beyond those included in the present model are likely to contribute to restaurant marketing performance outcomes.

The inner model evaluation was conducted to assess structural relationships among latent constructs and test the proposed hypotheses, while the outer model evaluation ensured measurement validity and the reliability of indicators representing each construct.

The structural relationships among variables are presented in Figure 3, which highlights the inner model and shows the hypothesized pathways between competitor orientation, techno-resonance innovation capability, consumer-centric innovative strategy, new service development, and restaurant marketing performance.

The IPMA results shown in Figure 4 indicate that indicators associated with consumer-centric innovative strategy and new service development demonstrate the highest importance values for improving restaurant marketing performance, suggesting that customer-focused innovation mechanisms represent the most effective managerial leverage points. In contrast, competitor orientation and techno-resonance innovation capability indicators show comparatively lower importance levels, confirming their supporting role within the capability integration framework. These findings highlight that performance improvements are primarily driven by the translation of technological readiness and competitive intelligence into customer-relevant service innovation activities.

4.5. Discussion

The relatively modest explanatory power observed in the structural model reflects the complexity of emerging hospitality markets, where marketing performance is influenced not only by innovation capability integration but also by contextual variables such as service quality variance, digital readiness heterogeneity, and market turbulence.

This study examined how techno-resonance innovation capability and competitor orientation influence restaurant marketing performance through consumer-centric innovative strategy and new service development within an emerging-market hospitality context. The findings support the capability integration perspective derived from dynamic capabilities theory, which emphasizes that organizational performance improvements arise from the coordinated interaction of sensing, integrating, and reconfiguring strategic resources rather than from isolated capability deployment. Prior hospitality research has confirmed that dynamic capabilities enhance operational and innovation performance through intermediate mechanisms such as resilience, integration processes, and adaptive strategic alignment rather than through direct capability effects alone (Abou Kamar et al., 2023). This suggests that restaurant firms improve marketing performance primarily when technological readiness and competitive intelligence are translated into customer-aligned innovation strategies.

The results demonstrate that techno-resonance innovation capability significantly strengthens both consumer-centric innovative strategy and new service development. This finding aligns with prior hospitality innovation research showing that technological capability enables service organizations to adapt innovation inputs into value-creating service outputs that improve competitive positioning and responsiveness to customer expectations (Huddin et al., 2025). In restaurant environments, where service differentiation depends heavily on rapid adaptation to changing customer behavior and digital interaction platforms, technological readiness plays a critical role in supporting innovation responsiveness. Importantly, this study extends the existing literature by demonstrating that technological capability contributes most effectively to performance when integrated with a customer-centered innovation strategy, rather than functioning as a stand-alone technological resource.

Similarly, competitor orientation was found to significantly influence consumer-centric innovative strategy but did not directly affect restaurant marketing performance. This result suggests that competitor intelligence operates primarily as an enabling capability that supports innovation alignment, rather than as a direct performance driver. Prior research has confirmed that organizational strategy often mediates the relationship between innovation-related inputs and competitive advantage outcomes, reinforcing the importance of strategic translation mechanisms in capability–performance relationships (Musiello-Neto et al., 2021). In restaurant contexts characterized by rapid imitation cycles and intensified competition through digital platforms, competitor orientation therefore contributes indirectly to performance by shaping innovation responses that reflect evolving market positioning conditions.

The findings further show that a consumer-centric innovative strategy significantly influences both new service development and restaurant marketing performance. This result confirms that customer-aligned innovation represents a critical transformation mechanism linking capability readiness with measurable marketing outcomes such as sales growth and return on investment. Prior hospitality research has similarly demonstrated that innovation performance improves when service organizations integrate customer knowledge into strategic decision-making and service development processes (Al-Sabi et al., 2023). In emerging-market restaurant environments, where customer expectations evolve rapidly due to digital engagement and experiential differentiation trends, a customer-centered innovation strategy becomes particularly important for translating capability readiness into performance improvements.

The results also indicate that new service development contributes positively to restaurant marketing performance, although the magnitude of this effect remains modest. This finding is consistent with the hospitality innovation literature, suggesting that service innovation improves competitiveness primarily through differentiation and customer engagement mechanisms rather than through dominant direct performance effects. Previous research has further confirmed that innovation behavior in hospitality firms often produces incremental performance improvements, rather than large direct gains, because innovation operates within broader organizational capability ecosystems (Baratta & Simeoni, 2021; Kitsios & Kamariotou, 2020). Accordingly, the present findings reinforce the argument that service innovation should be interpreted as part of a coordinated capability configuration, rather than as an isolated determinant of marketing performance.

The mediation analysis provides additional insight into how capability integration mechanisms operate within restaurant firms. Consumer-centric innovative strategy was found to mediate the relationship between techno-resonance innovation capability and restaurant marketing performance, indicating that technological readiness contributes to performance primarily through customer-aligned innovation execution rather than through direct technological deployment alone. This result is consistent with prior dynamic capability research demonstrating that intermediate strategic alignment mechanisms frequently explain how technological capability influences organizational performance in service industries (Rodriguez et al., 2020). Similarly, consumer-centric innovative strategy mediates the relationship between competitor orientation and restaurant marketing performance, reinforcing the argument that competitive intelligence strengthens performance outcomes only when translated into customer-relevant innovation initiatives.

However, several extended sequential mediation pathways involving multiple intermediate constructs were not statistically significant. These results indicate that capability integration mechanisms operate primarily through shorter transformation pathways, rather than through complex multi-stage innovation chains. Similar findings have been reported in hospitality innovation research, demonstrating that innovation inputs and outputs often operate through selective strategic pathways rather than through fully sequential capability chains (Huddin et al., 2025).Therefore, the present results support the interpretation that a customer-centered innovation strategy represents the most consistent transformation mechanism linking capability readiness with restaurant marketing performance outcomes.

Importantly, although the structural relationships tested in this study are statistically significant, the explanatory power of the model remains modest. The relatively low R² values indicate that technological readiness, competitor orientation, and innovation strategy explain only part of the variance in restaurant marketing performance. Prior MDPI research has similarly emphasized that hospitality innovation performance depends on broader capability ecosystems involving quality management practices, employee empowerment, and organizational learning processes, rather than on isolated strategic variables (Al-Sabi et al., 2023). Accordingly, the present findings should be interpreted as exploratory evidence supporting capability integration mechanisms, rather than as confirmation of dominant causal drivers of restaurant performance.

This study contributes to the hospitality marketing and innovation strategy literature by demonstrating that restaurant marketing performance in emerging markets is shaped primarily through the coordinated interaction of technological readiness, competitor intelligence, and customer-centered innovation strategy rather than through isolated capability deployment. By integrating these capability dimensions into a unified structural framework, the study extends dynamic capabilities theory within the restaurant sector and provides empirical evidence supporting the role of innovation alignment mechanisms in explaining performance outcomes under resource-constrained service conditions. Although several structural paths are statistically significant, the low R² and small effect size values indicate that the practical contribution of the tested predictors is limited. Accordingly, the findings should be interpreted as exploratory evidence of association rather than as strong confirmation that capability integration is a dominant driver of restaurant marketing performance. Additionally, capability integration is statistically associated with restaurant marketing performance, although the explanatory strength of this relationship remains limited. Although sustainability-related outcomes were not directly operationalized as dependent variables in this study, the capability integration framework identified here provides a managerial pathway for restaurant firms to strengthen their long-term competitiveness, consistent with SDG-oriented transformation agendas.

To complement the structural model results and enhance the managerial relevance of the study, an Importance–Performance Map Analysis (IPMA) was conducted to identify priority areas for improving restaurant marketing performance. The results indicate that indicators associated with consumer-centric innovative strategy demonstrate the highest importance values, suggesting that strengthening customer-oriented innovation mechanisms represents the most effective pathway for improving marketing performance outcomes. Indicators related to new service development also show relatively high importance levels, confirming the role of continuous service innovation in translating organizational capabilities into measurable performance improvements. In contrast, competitor orientation and techno-resonance innovation capability exhibit comparatively lower importance values, indicating that these capabilities function primarily as supporting strategic mechanisms that enhance the effectiveness of customer-centered innovation rather than acting as direct performance drivers. Importantly, the IPMA results provide actionable guidance for restaurant managers by identifying capability areas that should be prioritized to achieve more effective innovation-driven performance improvements in competitive hospitality environments. The IPMA findings reinforce the importance of capability integration in supporting marketing performance enhancement in emerging hospitality markets.

5. Conclusions

This study demonstrates that restaurant marketing performance in emerging markets is shaped by the integration of techno-resonance innovation capability, competitor orientation, consumer-centric innovation strategy, and new service development into a coordinated strategic capability configuration. The study contributes to the capability-based hospitality strategy literature by identifying capability integration mechanisms that may support innovation-driven competitiveness in emerging markets and provides a foundation for future research examining direct sustainability performance indicators aligned with SDG frameworks.

The results confirm that technological readiness alone does not directly generate performance advantages, unless translated into customer-aligned innovation strategies. Consumer-centric innovation strategy plays a critical mediating role, linking technological capability to marketing outcomes. These findings extend dynamic capabilities theory by highlighting capability integration as a key mechanism explaining performance variations in resource-constrained hospitality environments. From a managerial perspective, restaurant operators should prioritize aligning their digital innovation investments with customer insight generation and service development processes, in order to strengthen their competitiveness under sustainability-driven market conditions. Future research should incorporate moderating variables such as market turbulence, digital readiness, and service quality differentiation to improve explanatory power across diverse hospitality contexts.

This study provides exploratory evidence that techno-resonance innovation capability, competitor orientation, consumer-centric innovative strategy, and new service development are related to restaurant marketing performance in statistically significant but practically limited ways. As the model explains only a small proportion of variance in the endogenous constructs, the findings should not be interpreted as indicating that these capabilities are the primary drivers of performance. Moreover, the heterogeneity identified through the PLS-POS analysis suggests that these relationships may differ substantially across restaurant subgroups. Therefore, the contribution of the study lies in theory development and identifying potential capability–performance pathways that merit further testing with stronger designs, richer predictor sets, and subgroup-sensitive modeling approaches.

6. Implications

This study contributes to the capability-based strategic management literature by extending dynamic capabilities theory through the integration of technological capability, competitor orientation, consumer-centric innovative strategy, and new service development within a unified capability configuration framework. While prior studies have often examined these strategic capabilities independently, the present study demonstrates that marketing performance improvements in emerging hospitality markets are better explained through their interaction and mediation mechanisms rather than through isolated capability effects. In particular, the findings highlight the mediating role of consumer-centric innovative strategy and new service development as key transformation mechanisms that translate technological readiness and competitive intelligence into measurable performance outcomes. These results contribute to the growing literature on capability integration by providing empirical evidence from the restaurant sector in emerging-market contexts, where resource constraints require firms to coordinate multiple strategic capabilities simultaneously. Furthermore, the study refines the application of dynamic capabilities theory in hospitality research by showing that capability orchestration—rather than capability possession alone—represents a critical pathway supporting innovation-driven competitiveness.

From a practical perspective, restaurant operators should develop structured mechanisms for integrating customer feedback into service innovation and menu development processes, in order to respond more effectively to changing market expectations. Strengthening coordination between technological capability deployment and frontline service innovation can further enhance marketing performance outcomes. Although sustainability indicators were not directly measured in this study, the capability integration framework identified here provides a useful foundation for supporting innovation-driven competitiveness consistent with longer-term sustainability-oriented transformation in the hospitality sector.

The findings suggest that restaurant managers should prioritize strengthening techno-resonance innovation capability as a foundation for enhancing consumer-centric innovative strategy and new service development activities. The results also indicate that competitor orientation contributes indirectly to marketing performance, through its role in supporting customer-focused innovation processes. Therefore, restaurant managers are encouraged to integrate technological readiness, competitive intelligence, and customer-centered service innovation into coordinated strategic initiatives, rather than implementing these capabilities separately to improve marketing performance outcomes.

This study offers some avenues for future research on capability-based innovation strategies in emerging hospitality markets. Future research could draw from sustainability performance indicators—including those related to energy efficiency, waste management practices, and circular service innovation—thus strengthening the relevance to sustainable development goal-oriented hospitality transformation. Furthermore, studies can expand on the model by incorporating more strategic variables such as digital marketing capability, service experience innovation, and organizational learning capability to enhance its explanatory ability. Additionally, longitudinal research designs and multi-country comparative studies may better capture the dynamics of capability development and heterogeneity across different hospitality environments.