Market Adoption Research Articles

Integrated One-Step Fabrication of Protonic Sensing Devices for Respiratory Monitoring.

The development of direct fabrication routes with seamless integration of both the macro/micropatterning process and nanostructure synthesis is crucial for the commercial realization of cost-effective nanoscale sensor devices. This, if realized, can liberate us from the conventional limitations inherent in nanoscale device manufacturing. Specifically, such fabrication routes can, in principle, address the challenges such as the complexity, multistep nature, and substantial costs associated with existing technologies, which are not suitable for widespread market adoption in everyday-use devices. Herein, we propose a novel yet facile one-step fabrication approach that simultaneously accomplishes both patterning and nanostructure synthesis by employing low-power, cost-effective laser technology with a minimal environmental footprint. Versatile in nature, this approach can enable the incorporation of diverse functionalities spanning a broad spectrum of technologies, encompassing fields such as sensors, catalysts, photonics, energy storage, and biomedical monitoring devices. As a proof of concept, using our approach, we fabricated an ultra responsive, high-speed protonic sensing device for real-time respiratory monitoring. The enhanced temporal characteristics of our as-fabricated device, particularly in the relative humidity levels of interest in breath monitoring (typically over 55%), exhibited a superior response/recovery time in rapid humidity fluctuations. We envisage that the advantages brought by the presented fabrication approach can pave the way to establish a new method for inexpensive large-scale functional-material-based device fabrication.

High performance Calcium Copper Titanate/Polyimide dielectrics composites enabled through colloidal stabilization

AbstractTransition to electrified transportation demands advanced power electronic components with the capability to improve range, reliability, and cost of ownership to accelerate mass market adoption. Thus, improvement in the current designs, manufacturing processes, materials, and components capable of providing reliable and efficient operation at higher temperatures play important roles in meeting future needs. To address these challenges, this article focuses on novel dielectric materials designed to reduce the volume of the most important and bulky component of a power electronic system, a capacitor. A new composite dielectric material was developed by integrating the positive attributes of both polymer and ceramic capacitors to overcome the challenges of state‐of‐the‐art dielectric materials. The developed composite properties have been evaluated and showed promising results, achieving a dielectric constant of 250 at 100 Hz, 25°C, unseen in current literature. Additionally, these materials can function at high temperatures (>150°C) with good breakdown strength, providing promising working conditions for capacitors, especially in electric vehicle applications.Highlights Dielectric composites were synthesized from calcium copper titanate and polyimide. A dispersive agent showed promise in achieving a homogenous, stable mixture. Composites were prepared using tape casting. A dielectric constant of 250 was achieved at 100 Hz, 25°C. At elevated temperature, the dielectric constant increased to over 700%.

Lightweighting cost impacts on market adoption and GHG emissions in U.S. light-duty vehicle fleet

Abstract Vehicle lightweighting is a promising strategy that can reduce energy consumption and GHG emissions without compromising vehicle’s performance or size. The cost of lightweighting plays a critical role in determining the adoption of lightweighting technologies by consumers and manufacturers among advanced vehicle technologies. This analysis estimates the cost of lightweighting needed to achieve significant light-duty vehicle adoption to provide reductions in GHG emissions. Three different costs of lightweighting scenarios in the U.S. market including a baseline scenario, advanced technology scenario, and widespread scenario are evaluated employing Automotive Deployment Options Projection Tool (ADOPT). ADOPT leverages a database of over 700 existing vehicle models and options, enabling it to provide a high degree of realism and capture the unique characteristics of popular vehicles and the endogenously evolvement of the vehicle options. For baseline scenario, the lightweighting fraction reached by about 15% and GHG emissions are reduced by more than 50% in 2046 compared to 2015. The widespread scenario further reduces the GHG emissions by about 4% from the additional 10% glider mass reduction compared to the baseline scenario. The benefit came largely from lightweighting being implemented in the large market segment of lower-price vehicles, due to the relatively low lightweighting cost ($5/kg).

E-commerce market entry strategy, adoption and market performance: Basis for e-commerce industry synergy framework

E-commerce market entry strategy, adoption and market performance: Basis for e-commerce industry synergy framework

Portfolio Evolution Analysis for SPL Scoping: Unveiling the dynamics with dedicated time-series dashboards

Software Product Line Engineering (SPLE) is a recognized methodology for systematically developing reusable software components and tailored software products for specific market segments. A critical activity within domain engineering is SPL Scoping, aimed at profiling the SPL boundaries and fitting this market segment. Yet, this market is a moving target, which requires SPLs to be proactive in anticipating and addressing future challenges and opportunities. In this setting, rather than all the possible products potentially derived from the SPL’s Feature Model (i.e., the potential portfolio), the subset of products actually deployed is a better indicator of market adoption and customer preferences, and ultimately, of the SPL’s fitness to the market. This study characterizes the phenomenon of ‘deployed portfolio evolution’ in terms of the size and frequency of portfolio changes. We then elaborate on the advantages of utilizing this data source and the necessity for dedicated tools for Portfolio Evolution Analysis integrated within variability managers. To achieve this, we introduce the functional requirements, implementation, and architecture of PortfolioScan, a dashboard for Portfolio Evolution Analysis built on top of pure::variants. The dashboard enables the evaluation of feature usage through time-series charts such as temporal heat maps, line charts, and also a scoping-criteria comparison matrix. Evaluation results (n=13) indicate a positive perception. Practitioners also recognize the benefits of Portfolio Evolution Analysis for Testing Resource Optimization and Configuration Assistance. The ultimate goal of the study is to establish a basis for more responsive and market-oriented decision-making in SPL tasks.

Towards Hydraulic Design Optimization of Shaft Hydropower Plants: A 3D-CFD Application Based on Physical Models

The shaft hydropower plant (SHPP) is a novel hydraulic concept for low-head hydropower sites with several environmental and operational advantages over conventional layouts. However, the first two projects implementing this concept have shown comparatively high construction costs and project risks. Therefore, further optimization is required to increase economic attractiveness and enable broader market adoption. Initial model tests recommend a square-shaped shaft inlet with a three-sided approach flow for low-loss and fish-friendly inflow conditions. Yet, this design requires significant space for structural implementation and may be unsuitable for use with multiple shafts or as an extension of non-powered dams and weirs. This research paper presents the application of a computational fluid dynamics simulation setup to evaluate the hydraulic performance of various design configurations, especially alternative design layouts with a one-sided approach flow without further physical model tests. The simulation setup is calibrated against observations including head loss and velocity measurements from the physical model tests, and its satisfactory performance enables the analysis of alternative design layouts. This study aims to derive the most significant design parameters for achieving the desired hydraulic conditions at the intake. Increasing the flow depth before the intake and enlarging the inlet area have the most significant impact, while increasing the overflow of the front gate has the least significant effect. The chosen CFD application is deemed suitable for hydraulic design optimization and provides guidance on the key parameters to focus on for tailored site-specific design development.

Comparative Assessment of Expected Safety Performance of Freeway Automated Vehicle Managed Lanes

The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts.

Identifying mass market adoption in the transition to electric vehicles

Abstract When plug-in electric vehicles (PEVs)—plug-in hybrids and battery electric vehicles—reach mass market adoption, their growth may be self-sustaining and their replacement of fossil-fuel vehicles nearly certain. Understanding this milestone is important, because afterward research and policy interventions that support PEVs will be less necessary. In this paper we outline how to identify mass market adoption and show that the PEV market has not reached this point based on two essential criteria: achieving adoption (not sales) of about 16% and the resolution of early market issues (any deficiencies affecting vehicles, infrastructure, and the surrounding ecosystem). The fact that neither of these criteria have been met highlights the early stage of the PEV market and means PEVs will require policy support throughout this decade.

Nudging towards sustainability: Exploring the role of behavioral interventions in circular bio‐economy development for the fashion industry

AbstractThe fashion and food industries are major contributors to waste generation, making sustainability management a priority for both practitioners and scholars. This study examines how nudging can promote the development of a circular bioeconomy within the fashion industry, specifically investigating whether nudging techniques can facilitate the market adoption of fashion products made from sustainable textiles derived from food waste. Using a dataset of 2112 participants from four European countries, we employ regression and clustering analyses to identify consumer profiles based on psychological and behavioral characteristics. Our econometric analysis reveals that gender, education, and psychological factors such as environmental responsibility and awareness significantly impact sustainable behaviors. Additionally, a left‐leaning political orientation is positively associated with engagement in sustainable practices and willingness to pay for eco‐friendly products. Clustering analysis identifies distinct consumer profiles: “enthusiastic” individuals demonstrate high commitment to sustainability, while “skeptics” shows low engagement and responsiveness to environmental issues. The study offers key policy implications on the effectiveness of nudging interventions in enhancing the sustainability of the fashion industry.

The Influence of Artificial Intelligence on Modern Marketing

This paper explores how Artificial Intelligence (AI) is reshaping the marketing landscape, using data primarily sourced from Statista. By analysing global trends up to March and July 2023, we aim to provide a clear understanding of AI's impact on marketing strategies and outcomes. We begin by examining the rapid growth of AI in marketing, including its market size, revenue, and the preferences of users worldwide. We also highlight the popularity of leading AI text tools among users, giving insights into their market dominance and adoption rates. In addition, we investigate the funding landscape for AI marketing-related startups, showcasing the industry's investment trends and innovation potential. Furthermore, we identify the most effective ways marketers are using AI and marketing automation, offering practical insights for professionals seeking to leverage these technologies. Our study also looks at where AI is being used in marketing, revealing the diverse applications that are shaping strategies globally. We delve into the tools and platforms driving AI integration in marketing and advertising, as well as the main tasks undertaken by professionals using generative AI. A key focus is on AI-assisted writing, where we outline how marketers are employing AI for content creation and its impact on efficacy. We also explore the perceived benefits of AI tools according to marketing professionals, providing actionable insights for decision-making. Lastly, we assess the effectiveness of chat-based search advertising, particularly among paid search marketers in the United States. Through a concise summary of our findings, this paper aims to offer a comprehensive view of AI's transformative role in marketing, providing practical insights for industry stakeholders navigating this evolving landscape. In conclusion, this research serves as a roadmap for marketers, entrepreneurs, and industry professionals, guiding them through the integration of AI technologies into marketing strategies and operations. By understanding the current trends and potential benefits of AI, stakeholders can adapt and thrive in an increasingly AI-driven marketing environment.

Multidimensional Taxonomies for Research, Development, and Implementation of Electric Aircraft Ecosystem

The electrification of aviation represents a significant technological frontier, promising substantial advancements in sustainable transportation. This paper presents a comprehensive set of taxonomies that systematically categorize and analyze the multifaceted aspects of electric aviation, with a particular focus on machine-related components and systems. It provides detailed classifications of electric aircraft propulsion systems, power management architectures, and energy storage technologies, offering insight into their design, functionality, and integration challenges. The paper explores the ecosystem of electric aviation, including key stakeholders, use cases, and enabling technologies, which are vital for coordinating machine development strategies and fostering sustainable growth. The creation of business models that cater to the dynamic nature of the industry, emphasizing the role of innovative machine designs in shaping market adoption are discussed in the paper. The study highlights the importance of electric aviation for regional development, outlining predictive models for regional market development that consider machine capabilities and infrastructure requirements.

Defect-driven ion storage on hexagonal boron nitride for fire-safe and high-performance lithium-ion batteries

The mass market adoption of electric vehicles has increased the risk of safety concerns, such as overheating and flammability. Rational design of fire-safe and high-capacity anodes with thermal tolerance, capable of fast-charging and long cycle-life, is crucial for the development of next generation Li-ion batteries operating under extreme conditions. Here we report a defect engineered hexagonal boron nitride (hBN) anode to mediate the safety dilemma. We demonstrate that the defects generated via cryomilling catalyze the reversible LiF formation and enable the pseudocapacitive type Li-ion storage on hBN. The non-flammability and excellent thermal tolerance of hBN allows high specific capacity (880 mAh/g @ 25 mA/g), rate performance (480 mAh/g @ 5 A/g) and stable cycling (5000 cycles) at 60 °C. The Li-ion full-cell with the defective hBN anode and the conventional cathode (LiNiMnCoO2) delivers significantly higher energy (400 Wh kg−1) and power density (1 kW kg−1) when compared to graphite/LiNiMnCoO2 full-cells (121 Wh kg−1 and 250 W kg−1). First-principles calculations confirm that nitrogen antisite (NBVN) defects are responsible for the electrochemical activation of otherwise inactive hBN. The strategy of defect-induced electrochemical activation opens up new avenues in the design of high-performance electrode materials for numerous secondary batteries.

Metal additive manufacturing adoption in SMEs: Technical attributes, challenges, and opportunities

Recent advancements in Metal Additive Manufacturing (MAM) are transforming manufacturing. Most research and market adoption of MAM have focused on Powder Bed Fusion (PBF), with less attention given to Directed Energy Deposition (DED), Binder Jetting (BJ), and Metal Material Extrusion (MEX), which are only now reaching industrial readiness. This increased availability of MAM processes provides SMEs with a wider range of options, opening up new opportunities that were previously inaccessible. However, despite recent technological improvements that broaden potential applications, the suitability of these processes for industrial use by SMEs is not yet well understood. SMEs currently face difficulties in adopting MAM due to complexities and costs. Moreover, existing literature often overlooks the distinct characteristics and needs of SMEs, making it challenging for them to identify the most suitable MAM processes. This study addresses this gap by using a fuzzy logic approach to evaluate the technical characteristics of PBF, DED, BJ, and MEX, focusing on their compatibility with SME requirements. Each process is ranked based on criteria including costs, complexity, energy consumption, mechanical quality, geometrical quality, speed, and market demand. This evaluation is refined through logarithmic normalization and scaling, resulting in a comprehensive scoring system from 1 to 5. Based on these findings, an SME-focused evaluation matrix is proposed to guide SMEs in selecting the most appropriate MAM process for their specific contexts. This matrix promotes informed and effective adoption strategies, supported by practical examples illustrating the application of each MAM process in SME environments.

Factors Influencing Activity and Electrochemical Stability of Ru-Based Oxygen Evolution Electrocatalysts

A hydrogen-based energy economy is a viable candidate to provide clean power and alleviate carbon emissions produced by hydrocarbon-based fuels. Hydrogen produced by proton exchange membrane water electrolysis (PEMWE) provides a path to clean affordable energy; however, PEMWE costs are still too high for wide-scale market adoption. Electrochemical splitting of water is energetically hindered by the oxygen evolution reaction (OER) which has sluggish kinetics, and the benchmark OER catalyst iridium oxide (IrO2) has high costs and very limited global supply. Ruthenium oxide (RuO2) provides a higher activity and lower cost compared to IrO2; however, under the high potential and highly acidic environment required for OER, RuO2 shows lower stability compared to IrO2. Our prior study demonstrated that Ti-substitution within RuO2 improved electrochemical stability, but also resulted in lower activity.1 Here, we expand our study by exploring the effects of phase, composition, surface structure, electrolyte, and operating voltage on the activity and electrochemical stability of Ru-based OER catalysts to identify key contributing factors towards improving the electrochemical stability. Catalysts materials were synthesized using wet-chemistry or high energy ball milling, and commercial materials were used for comparison and baselining. Structure was determined using X-ray diffraction, scanning electron microscopy, porosimetry measurements, and x-ray photoelectron spectroscopy. We evaluate electrochemical OER activity and stability using rotating disk electrode electrochemistry, coupled with inductive coupled plasma mass spectrometry for analysis of dissolved metals within the electrolyte. We develop structure-activity-electrochemical stability correlations to determine driving factors influencing degradation and provide a pathway to the development of materials with improved catalyst performance and lower cost. References Godínez-Salomón, J. F.; Ospina-Acevedo, F.; Albiter, L.; Bailey, K.O.; Naymik, Z.G.; Mendoza-Cruz, R.; Balbuena, P.B.; Rhodes, C.P., ACS Appl. Nano Mater. 2022, 5, 11752-11775.

The Impact of Carbon Corrosion Towards Oxygen Reduction Reaction Activity on Atomically Dispersed M-N-C Catalysts

Atomically dispersed Pt group metal free (PGM free) M-N-C catalysts offer a promising pathway towards a clean energy future.1 This class of materials has proven to be a viable substitute for commercial Pt/C to catalyze oxygen reduction reaction (ORR) with similar activity at only a fraction of the raw material cost.2 To gain a wider market adoption, however, M-N-C catalysts need to significantly improve its durability compared to Pt and its alloys in a real-world operating condition. Towards this end, substantial efforts have focused on making more durable M-N-C catalysts while simultaneously maintaining and improving its ORR activity.3,4 As part of the effort to understand the fundamental aspects that control M-N-C catalysts’ durability during ORR condition, we employ a combined approach using first principles density functional theory (DFT) and density functional tight binding theory (DFTB) to identify the impact of carbon corrosion occurring on M-N-C catalyst towards ORR activity. Our starting atomic representation of the ORR active site is the “C10” type local structure composed of FeN4C10 local defect5 embedded in a monolayer graphene support of varying cell size. As carbon corrosion occurs and consequently creating local carbon vacancies surrounding the active site, we then obtain a family of FeN4C11 and FeN4C12 type of local structures. Our DFT calculations of OH binding energy on these corrosion derived structures suggest that the presence of C vacancies and the subsequent H passivation on dangling C introduces elastic structural deformation to various degree that decreases the theoretical ORR limiting potential. This decrease in DFT calculated ORR limiting potential across a family of FeN4C10, FeN4C11, and FeN4C12 local structures can be attributed to a mechanical energy arising from the surface reconstructions. Reference D. A. Cullen et al., Nat Energy, 6, 462–474 (2021).G. Wu, K. L. More, C. M. Johnston, and P. Zelenay, Science, 332, 443–447 (2011).E. F. Holby, G. Wang, and P. Zelenay, ACS Catal., 10, 14527–14539 (2020).T. Patniboon and H. A. Hansen, ACS Catal., 11, 13102–13118 (2021).H. T. Chung et al., Science, 357, 479–484 (2017).

The Technology Innovation of Hybrid Electric Vehicles: A Patent-Based Study

A hybrid electric vehicle (HEV) is a relatively practical technology that has emerged as electric vehicle technology has gradually matured. The analysis of the HEV patent lifecycle is crucial for understanding its impact on the development of this technology. This lifecycle tracks the progress of HEV technologies from their inception and patenting, through their market adoption, and to the expiration of their patent protection. In this study, we aimed to evaluate the technology lifecycle of the HEV industry using the growth S-curve method. The purpose of this study is to describe the technological lifecycle trajectory and current stage of the HEV industry, as well as the technical stages of each sub-technology, to facilitate better decision making. As part of this study, we used patent family data collected from the Derwent Innovation Index database from 1975 to 2022 and established an S-curve model for HEVs and their sub-technologies using logistic regression. In 2022, the technological maturity of HEVs reached 44%. The sub-technologies with the most substantial diffusion capabilities are energy management, propulsion systems, and cooling circuits. According to predictions, the saturation period for the patent family quantity related to HEVs is estimated to be around 53 years.

The OPEVA Manifest: OPtimisation of Electrical Vehicle Autonomy, a Research and Innovation project

Electromobility is a critical component of Europe’s strategy to create a more sustainable society and support the European Green Transition while enhancing quality of life. Electrification also plays an important role in securing Europe’s position in the growing market of electric and autonomous vehicles (EAV). The EU-funded OPEVA project aims to take a big step towards deployment of sustainable electric vehicles by means of optimising their support in an ecosystem. Specifically, the project focuses on analysing and designing optimisation architecture, reducing battery charging time, and developing infrastructure, as well as reporting on the driver-oriented human factors. Overall, OPEVA’s goal is to enhance EAV market penetration and adoption, making them more accessible and convenient. The aim of this paper is to inform the European automotive, transportation, energy and mobility community be presenting the OPEVA manifestation, and the overall solution strategy solidified through the progress throughout the first year of the project.

Consumer preference and willingness to pay for 3D-printed chocolates: A discrete choice experiment

This study explores the emerging field of 3D food printing, specifically examining consumer preferences for 3D-printed chocolate bars. While 3D printing has revolutionized various industries, the consumer acceptance of 3D-printed food remains a relatively underexplored topic. A discrete choice experiment was conducted to investigate consumer preferences and willingness to pay for 3D-printed chocolate bars in the UK. Key attributes included in the study were price, chocolate type, and the use of 3D printing technology. Using a mixed logit model, preference heterogeneity was assessed, revealing a general inclination towards 3D-printed chocolates, with an estimated increase in willingness to pay of £0.21 per 100 g. Furthermore, the influence of individual (participants’) characteristics, such as age, gender, prior knowledge of 3D food printing, and food technology neophobia, on perceived benefits associated with this technology and willingness to pay was also explored, using a structural equation modeling analysis. The results indicated that only perceived hedonic benefits, such as improved texture, positively impacted the willingness to pay, while food technology neophobia acted as a significant barrier. The results of this study therefore contribute valuable insights into the consumer acceptance of 3D-printed foods, specifically chocolates, highlighting potential avenues for market adoption and emphasizing the importance of effective communication in shaping consumer attitudes toward novel food processing technologies.

Green hydrogen prospects in Peninsular Malaysia: a techno-economic analysis via Monte Carlo simulations

According to Malaysia's National Energy Transition Roadmap, hydrogen is a critical component of the country's energy transition. However, there is a scarcity of hydrogen studies for Peninsular Malaysian states, which limits discussions on green hydrogen production. This study employs a Monte Carlo model to assess the economic and technical factors influencing the success of green hydrogen in Peninsular Malaysia. The study focuses on three target years: 2023, 2030, and 2050, representing various stages of technological development and market adoption. The levelized cost of hydrogen (LCOH) of a 1-MW Proton Exchange Membrane (PEM) electrolyzer system ranges from $5.39 to $10.97 per kg in 2023, highlighting early-stage challenges and uncertainties. A 6-MW PEM electrolyzer system could achieve an LCOH of $3.50 to $4.72 per kg by 2030, indicating better prospects. Because of technological advancements and cost reductions, a 20-MW PEM electrolyzer system could achieve an LCOH of $3.12 to $3.64 per kg in 2050. The findings indicate that the northern regions of Peninsular Malaysia have consistently low LCOH values due to favorable geographical conditions. Due to minor variations in solar capacity factors, uncertainty distributions in LCOH remain stable across different regions. Some states may face increased uncertainty, emphasizing the need for additional policy support mechanisms to mitigate risks associated with green hydrogen investments. The sensitivity analysis shows that key cost drivers are shifting, with early-stage electrolyzer investments dominating in 2023 and electricity prices becoming more important in 2030 and 2050. Future research could focus on optimizing green hydrogen systems for areas with underdeveloped green hydrogen industries. This study contributes to informed discussions about green hydrogen production by emphasizing the importance of tailored strategies that consider local conditions and highlighting the role of Peninsular Malaysia in the energy transition.

Commentary: Perceiving Innovation: Unveiling the Impact on Market Performance

The new challenge confronting leaders is investing in improving customer satisfaction or perceived innovativeness. The challenge also reflects the focus of leadership: to make operations more efficient and effective or invest in tomorrow's solutions? Intuitively, both are linked to the financial impact of the firm. In this article, the author explores the mechanisms “behind the scenes” driving perceived quality, and customer satisfaction on one side, and perceived innovativeness and relative attractiveness on the other side. Both routes are linked to customer loyalty, customer lifetime value, customer equity, and firm value. The findings underscore the importance of customer-centric innovation for market performance, suggesting that innovations must resonate with customer needs and expectations to foster market adoption and growth. The article advocates for the extension of this research into global contexts and digital transformation, highlighting the potential for these insights to inform strategi decision-making in an increasingly digitalized business environment. Bridging academic theory with practical application, the article offers a nuanced understanding of how innovation perceptions influence market outcomes. It suggests future research directions, including exploring strategies to enhance customer perception of innovation and leveraging these perceptions for competitive advantage.