Dynamic Performance Evaluation of the EcoGreen Structure in Blockchain Technology

Abstract

This study explores the behavior of the EcoGreen building structure under dynamic loading, using SAP2000 for finite element analysis. By implementing Response Spectrum and Time History methods in accordance with IS 1893 (Part 1): 2016, the research assesses the structural response, including base shear, displacements, and story drifts. Results indicate significant variation in dynamic response depending on the analysis technique, with Time History analysis offering detailed time-dependent behavior essential for precise seismic evaluation. The findings contribute valuable insight into improving structural design strategies for sustainability and resilience.

Introduction

I. Structural Integrity and Seismic Performance of EcoGreen

• EcoGreen is a multi-story, sustainable commercial building with unique design elements, requiring dynamic seismic analysis due to its height and irregular geometry.

• The study uses SAP2000 software for structural modeling and applies dynamic analysis techniques such as:

  • Response Spectrum Analysis (per IS 1893:2016, Zone IV)

  • Time History Analysis (using the El Centro earthquake record)

• The model adheres to Indian standards IS 456:2000 and IS 875, incorporating real material and structural parameters.

• Results provide insights into displacement, acceleration, and structural behavior during seismic events.

II. Literature Review

A. Online Food Delivery (OFD) and Digital Transformation

• OFD platforms are reshaping food consumption, especially in countries like India, due to their convenience, speed, and user-centric features.

• Growth is driven by urbanization, digital penetration, and changing consumer behavior.

B. Technology Adoption Theories

• Technology Acceptance Model (TAM): Focuses on Perceived Usefulness (PU) and Perceived Ease of Use (PEOU).

• Extended TAM: Incorporates trust and risk, especially important for platforms handling user data and digital payments.

• Unified Theory of Acceptance and Use of Technology (UTAUT): Adds dimensions like performance expectancy, effort expectancy, social influence, and facilitating conditions, which are highly relevant in collectivist societies like India.

• Post-Adoption Theories (Bhattacherjee): Focus on user satisfaction and continued usage.

C. Consumer Behavior in OFD

• Key adoption factors: Convenience, discounts, loyalty programs, and mobile usability.

• Trust and security in payments and service delivery are vital, especially with India’s fast-evolving digital payment infrastructure.

• User interface quality, personalization, and real-time tracking also enhance user satisfaction.

D. Demographic & Psychographic Factors

• Younger users (18–35) are the primary adopters due to tech-savviness and time constraints.

• Income, education, and urban residency influence usage patterns and order preferences.

• Psychographic traits (e.g., health-consciousness) affect platform and food choices (e.g., demand for organic or vegan options).

III. Blockchain Technology Overview

1. Concept

• Blockchain is a decentralized, cryptographically secure ledger system first introduced through Bitcoin.

• Transactions are verified and added to blocks, which are linked to form a tamper-resistant chain.

2. Key Characteristics

• Decentralization: No single authority controls the data.

• Traceability: Complete audit trail through cryptographic linking.

• Transparency: Data is visible (public) or selectively shared (private/consortium).

• Anonymity: Users interact through pseudonymous addresses.

• Immutability: Data, once added, cannot be altered without system-wide recalculations.

3. Blockchain Categories

• Public Blockchains: Open to all (e.g., Bitcoin, Ethereum).

• Private Blockchains: Restricted access, controlled by one entity.

• Consortium Blockchains: Shared control among multiple authorized entities.

IV. Research Methodology: Structural Analysis

A. Modeling

• EcoGreen’s structure was modeled using SAP2000, considering actual construction parameters and design codes.

• The building includes shear walls and moment-resisting frames to enhance seismic resistance.

B. Dynamic Analysis

• Response Spectrum Analysis was conducted using IS 1893:2016 data for Zone IV.

• Time History Analysis used the El Centro earthquake record to simulate real seismic effects, measuring displacement and acceleration responses.

Conclusion

The structural integrity of buildings, particularly under seismic loads, is paramount in earthquake-prone regions. EcoGreen is a multi-story commercial building with a unique architectural and functional design that prioritizes sustainability. Given its height and geometry, dynamic analysis is crucial for understanding how it will perform during seismic events. This research leverages modern computational tools to evaluate the dynamic behavior of EcoGreen and offers recommendations based on simulation outcomes. II. LITERATURE REVIEW The digital transformation of the food and beverage industry has been markedly evident in recent years, particularly through the expansion of Online Food Delivery (OFD) platforms. These services have disrupted traditional food consumption patterns by offering increased convenience, time efficiency, and user-centric experiences. In rapidly urbanizing nations like India, where consumer behavior is being increasingly shaped by digital ecosystems, OFD platforms have seen exponential growth. Understanding the drivers of this adoption and the behavioral intentions of consumers is therefore critical from both academic and practical perspectives. A. Technology Adoption Models A significant body of research has investigated technology adoption behaviors through established theoretical frameworks. One of the most influential models is the Technology Acceptance Model (TAM) proposed by Davis (1989), which posits that Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) are primary determinants influencing users\' attitudes toward adopting a new technology. PU refers to the degree to which a user believes that using a particular system enhances their performance, while PEOU refers to the extent to which the system is free from effort. These constructs have been validated across various technology adoption contexts, including mobile applications and e-commerce services. Extensions to TAM have sought to increase its explanatory power. For instance, Pavlou (2003) introduced the notion of perceived trust and perceived risk, particularly relevant in online transaction environments. In OFD platforms, where users share personal information and make digital payments, trust becomes a central concern. Similarly, Bhattacherjee (2001) explored post-adoption behaviors, arguing that satisfaction and confirmation of expectations play critical roles in the continued use of technology, an aspect particularly relevant for subscription-based or recurrent services like OFD. The Unified Theory of Acceptance and Use of Technology (UTAUT), developed by Venkatesh et al. (2003), integrated eight existing models, including TAM, to produce a more comprehensive framework. UTAUT includes constructs such as performance expectancy, effort expectancy, social influence, and facilitating conditions. These constructs allow for a more nuanced analysis of consumer adoption behavior in various socio-cultural contexts, including collectivist societies like India where social norms can heavily influence individual decision-making. B. Consumer Behavior in Online Food Delivery In the context of OFD services, empirical studies have identified several factors influencing consumer adoption. Ray et al. (2019) emphasize convenience, timeliness, and discounts as primary motivators. The ability to order food anytime, from a wide array of restaurants, directly from a mobile device caters to modern urban lifestyles characterized by fast-paced routines and limited time for cooking or dining out. Promotional offers, loyalty points, and subscription models further enhance the perceived value of these platforms. Perceived trust and security are also pivotal in determining consumer acceptance. Gefen et al. (2003) argue that in e-service environments, trust plays a role comparable to that of quality in traditional services. Consumers are particularly concerned with the integrity of payment systems, data privacy, and the reliability of service delivery. In India, where digital payment infrastructure has rapidly evolved with the advent of Unified Payments Interface (UPI) and digital wallets, trust issues remain due to occasional reports of data breaches or service inconsistencies. Another important factor is user interface design. A seamless, user-friendly app interface with personalized recommendations, real-time tracking, and easy payment options can significantly enhance the user experience and encourage repeated usage. Studies have shown that mobile app usability can serve as a differentiator among competing OFD platforms, making technological sophistication a critical area for service providers. C. Demographic and Psychographic Influences Demographic factors play a significant role in shaping consumer behavior in OFD services. Jayaraman et al. (2021) note that younger consumers, particularly those aged 18–35, are the most frequent users of OFD platforms. This demographic is more digitally literate, time-constrained, and open to adopting new technologies. Income levels and employment status also influence the frequency and type of food ordered. Higher income groups may opt for premium restaurants or gourmet options, while budget-conscious users may be drawn to value meals and discounts. Educational background and urban residency are also relevant. Educated consumers tend to be more aware of the risks and benefits associated with online transactions and are more likely to evaluate app quality, customer reviews, and hygiene ratings before placing an order. Urban centers, where internet penetration and smartphone usage are higher, naturally exhibit greater OFD adoption compared to rural areas. Psychographic variables such as lifestyle, health consciousness, and food preferences have gained attention in recent studies. For instance, health-conscious consumers may avoid ordering from fast-food chains and instead seek OFD platforms offering healthier alternatives. The availability of vegetarian, vegan, and organic food options has influenced consumer choices, particularly in metropolitan areas where dietary preferences are diverse. The diagram illustrates a consumer segmentation model based on a utility threshold over the interval [0,1], with three distinct decision regions (I, II, III) determined by specific threshold values involving prices and green premiums. D. Blockchain Blockchain technology has garnered significant attention in recent years due to its potential to enable secure, transparent, and decentralized data management. This section discusses the conceptual foundations, inherent characteristics, and classification of blockchain systems. 1) Concept of Blockchain The concept of blockchain was initially popularized by the advent of Bitcoin, which introduced a decentralized form of digital currency. The core innovation of Bitcoin lies in its underlying blockchain architecture, which facilitates secure and verifiable transactions across a distributed network without relying on a centralized authority or trusted intermediary. A blockchain is essentially a continuously growing ledger comprising a series of chronologically linked blocks, each containing a verified set of transactions. Transactions originate when a participating node generates a cryptographic key pair (public and private keys) and constructs a transaction using a wallet or a scripting tool. This transaction is then signed using the sender’s private key and broadcast to the network via a peer-to-peer (P2P) protocol. Upon receiving the transaction, neighboring nodes validate its authenticity. Miners subsequently collect valid transactions and attempt to add them to the blockchain by creating a new block, following a predefined consensus mechanism. Once a block is successfully mined, it is propagated across the network. Other nodes then verify the block and determine its validity. A transaction is deemed complete when the block containing it is accepted and added to the local chains of the majority of nodes, thereby achieving consensus. 2) Characteristics of Blockchain Blockchain exhibits several salient features that render it suitable for a wide range of applications requiring trust, transparency, and resilience: • Decentralization: Blockchain operates without a central authority, leveraging a distributed database architecture where each node maintains a copy of the entire ledger. The departure or failure of individual nodes does not compromise system integrity, ensuring robustness and fault tolerance. • Traceability: All transactions are publicly recorded and timestamped, enabling complete auditability. Data within the blockchain is organized using a chain of blocks, each cryptographically linked to its predecessor, allowing any transaction to be traced to its origin. • Transparency: In public blockchain systems, all transaction records are visible to every participant, fostering trust through openness. In contrast, access to data in private and consortium blockchains is restricted to authorized participants, maintaining selective transparency. • Anonymity: Blockchain ensures user privacy by allowing nodes to interact without disclosing personal identities. Participants use pseudonymous addresses to conduct transactions, and trust is established through asymmetric cryptographic protocols, enabling secure interactions in trustless environments. • Immutability: Blockchain’s integrity is maintained through cryptographic hashing, where each block references the hash of the previous block. This structural linkage renders historical data immutable. Any attempt to alter recorded data would necessitate recalculating the hashes of the altered block and all subsequent blocks, which is computationally infeasible, thereby ensuring data permanence and resistance to tampering. 3) Categories of Blockchain Blockchain networks can be broadly categorized based on their access control mechanisms: • Public (Permissionless) Blockchains: These systems are fully decentralized and open to all users. Anyone can read, write, and participate in the network without prior authorization. Bitcoin and Ethereum exemplify this category. • Private Blockchains: Access to private blockchains is restricted to a predefined set of participants. Only authorized entities can read or write data, and end users of blockchain-based services typically do not have direct access to the blockchain itself. • Consortium Blockchains: A hybrid model in which multiple organizations jointly maintain the blockchain. These systems aim to balance openness and control, often employing consensus protocols resistant to censorship. While participation may be open, data integrity is enforced through economic incentives and governance agreements. III. METHODOLOGY A. Structural Modeling The EcoGreen building was modeled using SAP2000. The model incorporated real-world parameters including material properties, member dimensions, and boundary conditions, adhering to IS 456: 2000 for reinforced concrete design and IS 875 for load combinations. The building features an irregular geometry with a combination of shear walls and moment-resisting frames. B. Dynamic Analysis Techniques Two key dynamic analysis methods were applied. This approach uses pre-defined spectra to evaluate maximum expected structural responses. The response spectrum from IS 1893:2016 for Zone IV was employed. A real ground motion record (El Centro earthquake) was used to assess the building\'s response over time, capturing variations in displacement and acceleration across the structure. Consumer Segmentation Thresholds We define two critical threshold values that segment consumers based on their green preference level ??[0,1] in [0, 1]: 1) Threshold for Abandoning Purchase (Lower bound between Region III and II): Consumers with ??2 opt for non-blockchain green products. 3) The profit ?i,t for agent i at time t is calculated as the revenue minus a cost term. The revenue is given by the product of the price pi,t and the demand di,t . The cost is proportional to the square of a quantity gi,t scaled by a constant m, and halved. C. Research Gaps and Future Directions While the existing literature provides a comprehensive overview of the factors influencing OFD adoption, certain gaps remain. Most studies focus on urban or metropolitan users, neglecting semi-urban and rural demographics where digital adoption is rising but under-researched. Furthermore, the post-pandemic environment has introduced new behavioral patterns such as increased hygiene awareness and preference for contactless delivery, which merit further investigation. Additionally, there is a lack of longitudinal studies that assess consumer behavior over time, especially in the face of changing economic conditions, technological advancements, and policy regulations. Integrating psychological models like the Theory of Planned Behavior (TPB) or the Health Belief Model (HBM) could offer richer insights into specific consumer segments, such as health-conscious or elderly users. IV. RESULTS AND DISCUSSION Comparative results show that displacements are higher when evaluated using Time History analysis than Response Spectrum analysis. Maximum top-story displacement reached approximately 40 mm in Time History analysis versus 32 mm in the spectrum method, indicating a more realistic simulation of seismic behavior with the former. The inter-story drift observed remained within the permissible limit of 0.004*h (where h is story height) as defined by IS 1893. However, Time History analysis highlighted greater fluctuations in drift across stories, suggesting the need for drift control mechanisms. Time History analysis predicted higher base shear forces, indicating a more conservative assessment of foundation and lateral load-resisting systems. Base shear values were approximately 2500 kN for Time History and 2100 kN for the Response Spectrum method.

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Copyright

Copyright © 2025 Dr. S Thilagavathi, Dr. S Rajeswari, Mr. S Vignesh, Mrs. C. Kavitha , Mr. P. Dhamotharan, Mr. K. Rajesh Rao, Dr. R. Revathi, Mr. C. Balaji. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.