Publications
Dr. Tali Režun published articles, business concepts and academic dissertations based on his work and experience in the past 20-years.
Dr. Tali Režun (2026)
Chasing Jarvis: Can Technically Sophisticated Non-Programmers Deploy SaaS Applications Using AI Coding Agents?
This empirical study investigates whether technically sophisticated non-programmers—domain experts with substantial technology experience but without traditional programming backgrounds—can successfully build and deploy production-grade Software-as-a Service (SaaS) applications using AI coding agents, addressing a central question in the ongoing debate about AI’s impact on software development accessibility. Through a two-year participatory action research approach (2023–2025), combining systematic tool experimentation with the development and deployment of Lumina AI—a production RAG chatbot widget platform built entirely through AI-assisted development—this study provides empirical evidence on the capabilities and limitations of contemporary coding agents. The research synthesizes findings from 80+ peer-reviewed sources, industry reports, and technical documentation alongside first-hand development experience across multiple AI coding platforms (Cline, Claude Code, Augment Code, Google AI Studio, Cursor). Results demonstrate that technically sophisticated non-programmers can indeed achieve production deployment, though success depends critically on mastering ‘context engineering’—the systematic structuring of information environments for AI systems—rather than traditional programming skills.
The Research Question
Can technically sophisticated non-programmers — domain experts without traditional programming backgrounds — deploy production SaaS applications using AI coding agents? This paper examines that question through a two-year empirical case study, challenging the assumption that software development remains the exclusive domain of trained engineers.
Context Engineering as the Core Bottleneck
The central finding reframes the challenge entirely: the primary barrier is not coding skill — it is context engineering. The ability to structure, maintain, and communicate the right information to an AI agent at the right moment determines success more than any technical background. This shifts what expertise is actually required.
Five Propositions, One Conclusion
From production deployment feasibility and the "70% problem" to security verification risks and orchestration as the new expertise, the paper's five propositions converge on a single insight: a new class of technically sophisticated non-programmers can build and deploy production software — but only if they master context, not code.
Dr. Tali Režun & Anton Dobrina (2026)
Law = Code: Can AI Democratise the World's Most Exclusive Algorithm?
he rapid convergence of advanced AI reasoning models and legal practice is producing what may be the most consequential democratisation story of our era. According to the World Justice Project, 5.1 billion people — roughly two-thirds of humanity — currently have at least one unmet justice need. In the United States alone, 92% of civil legal problems faced by low-income individuals receive no or inadequate help (Legal Services Corporation, 2022). The average US lawyer now bills $341 per hour, up 34% since 2018, pricing ordinary people out of the system that governs every aspect of their lives. This article, co-authored by Dr. Tali Režun and legal expert Anton Dobrina, examines why legal reasoning is structurally identical to code — operating through formal rules, conditional logic, and precedent-based interpretation — and why this identity makes law uniquely well-suited to AI analysis. Drawing on the Vals AI LegalBench leaderboard, Box AI’s enterprise evaluations of Gemini 3.1 Pro Preview, and industry data from Harvey AI, Thomson Reuters CoCounsel, and LexisNexis, the authors present a technical and practical case for AI as the infrastructure for legal democratisation. The article covers six applied use cases, addresses the hallucination risk honestly, and provides a step-by-step practical framework for non-specialists. The conclusion is direct: the monopoly on legal understanding is ending. The law has always belonged to everyone. Now, finally, so does the ability to read it.
Keywords: legal AI, access to justice, Gemini 3.1 Pro, LegalBench, law as code, rules as code, justice gap, AI democratisation, contract analysis, hallucination risk
The Justice Gap and Why Law = Code
Two-thirds of the global population have unmet legal needs, not because the law is against them, but because they could not afford someone to explain it. This article establishes that law and code share a structural identity: statutes function as axioms, contract clauses as methods, definition sections as variable declarations, loopholes as bugs, and case law as version history. This is not a metaphor -- it is the foundation of computational law, formalised by Stanford CodeX, MIT's Computational Law programme, and national governments from New Zealand to Germany. It is also precisely why advanced AI reasoning models, trained simultaneously on programming logic and legal text, are exceptionally well-suited to legal analysis.
Gemini 3.1 Pro and the Technical Breakthrough
Three advances define the current generation. First, the 2-million token context window -- processing up to 3,000 pages simultaneously -- eliminates the fundamental flaw of earlier RAG-based approaches, which systematically missed the long-range dependencies that legal reasoning depends on. Second, Box AI's enterprise evaluation (February 2026) found legal accuracy jumping from 57% to 74% -- a 17 percentage point improvement -- with the model correctly applying a directionality test in a due diligence scenario where earlier models failed. Third, the adjustable thinking-level parameter enables genuinely multi-step legal reasoning on demand. On the formal LegalBench benchmark, Gemini 3 Pro leads at 87.04% accuracy (Vals AI, February 2026).
Six Use Cases, One Honest Warning, and the Road Ahead
The article presents six applied use cases -- contract analysis, regulatory navigation, due diligence at scale, family law support, commercial dispute assessment, and property conveyancing -- each available to non-specialists today for the cost of a monthly subscription. It also confronts the hallucination risk directly: Stanford HAI found leading legal AI tools hallucinating 17% to 43% of the time. The critical distinction is that document-grounded queries in large context windows are substantially more reliable than memory-based queries -- and human verification before any consequential action remains non-negotiable. The industry is already moving: $5.99 billion in legal tech funding in 2025, Harvey AI at an $8 billion valuation, and CoCounsel serving 1 million professionals across 107 countries.
Dražen Kapusta, DBA & Dr. Tali Režun (2026)
The Great Reckoning: Vanguard Leadership in the Age of Intelligent Machines
This article examines the accelerating displacement of white-collar labor by artificial intelligence (AI) and autonomous systems, analyzing the phenomenon through the Vanguard Leadership Framework (VLF) and the NEO Cotruglian philosophical tradition.
Drawing on verified labor data, European AI adoption research, emerging economies analysis, and 26 years of institutional leadership at COTRUGLI Business School, the
author argues that the current disruption is not a cyclical adjustment but a structural
reorganization of the global labor economy. The article presents a three-horizon model: the immediate US displacement wave; Europe’s compressed and coming reckoning (estimated 2028–2029); and Africa’s strategic window for leapfrog development. Embedded throughout is the VLF operating system—Sense, Seize, Transform—and the NEO Cotruglian Triple Entry (NCTE) framework as trust infrastructure for the emerging machine economy. The article concludes with a Vanguard Leadership imperative: lead
with intelligence at the core, or become the institution that history passes by.
The Great Reckoning: Vanguard Leadership in the Age of Intelligent Machines
The Signal Everyone Is Reading Wrong
Last week, a CEO publicly announced the elimination of 4,000 positions—nearly half his company's workforce. The following day, his stock surged 25%. Markets did not punish him. They rewarded him for telling the truth. In his message to employees, he stated: We're already seeing that the intelligence tools we're creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. And that's accelerating rapidly.
The Democratization Paradox: When Displacement Meets Opportunity
The white-collar displacement documented above creates a profound paradox that demands attention from Vanguard Leaders: the same AI systems eliminating millions of jobs are simultaneously democratizing the capacity to create software, lowering barriers to entrepreneurship, and fundamentally restructuring who can participate in digital innovation. This is not a footnote to the displacement narrative. It is a critical dimension of the structural reorganization itself, and one that illuminates both the severity of the challenge and the pathways through it.
The Vanguard Leadership Imperative
The CEO who cut 4,000 positions said something that every leader reading this should write on their wall: "I'd rather take a hard, clear action now and build from a position we believe in than manage a slow reduction of people toward the same outcome." That is the definition of Vanguard Leadership. Not the glamorized version—the one that appears on conference keynote slides and LinkedIn carousels—but the actual doctrine: make the hard call before the market makes it for you, take accountability for the decision, and build forward from clarity rather than from crisis.
Dr. Tali Režun & Dražen Kapusta (2025)
The Energy and Water Footprint of Generative AI
The rapid proliferation of generative artificial intelligence (AI) and large language models (LLMs) has ushered in a transformative era for industries. However, it imposes substantial environmental costs through energy and water consumption. This article, grounded in the vanguard leadership framework (VLF), examines the resource demands of generative AI, focusing on energy and water usage, efficiency comparisons among LLMs, and regional implications in Europe, the United States, and Asia. It contrasts AI’s environmental footprint with Bitcoin mining and proposes strategic solutions to mitigate additional energy demands, aligning with the VLF’s adaptive principles. By integrating real-time data, academic insights, and industry trends, the article underscores the urgent need for leaders to harness AI as a force multiplier while navigating its ecological and economic challenges within a three-year window to maintain competitive advantage in Industry 5.0.
Keywords: artificial intelligence, Bitcoin, consumption, disruptive technology, energy,
Industry 5.0, LLM (large language models), technology, vanguard leadership framework
Massive Energy and Water Consumption Scale
Generative AI's resource demands are escalating rapidly, with the International Energy Agency projecting that AI-driven data center electricity demand will more than double by 2030, reaching nearly 1,000 TWh—equivalent to Japan's entire annual electricity consumption. Water usage is equally concerning, with Google reporting a 20% increase in water consumption from 2021 to 2022, using 5 billion gallons of fresh water in 2022 alone. A single ChatGPT query consumes about 0.3 Wh of energy (10 times that of a Google search) and approximately 0.01 liters of water for cooling.
Significant Efficiency Variations Among AI Models
Different large language models show substantial variations in energy efficiency, creating strategic opportunities for organizations. Mixtral 8x22B achieves the highest efficiency at about 0.15 Wh per 1,000-token query, while Claude 3.5 consumes about 0.4 Wh per query. Open-source models like Llama 3.1, when locally hosted, can reduce energy costs by 40% compared to cloud-based solutions. Algorithmic optimizations like quantization can reduce computational load by up to 50%, and domain-specific smaller models can consume up to 10 times less energy than general-purpose LLMs.
AI's Environmental Impact Compared to Bitcoin Mining
While Bitcoin mining currently consumes significantly more energy (130 TWh in 2023 vs. AI's 7.3 TWh), AI's growth trajectory is more concerning due to its scalability with user demand. Bitcoin is projected to reach 160 TWh by 2026, while AI could reach 73 TWh by the same year. However, AI offers productive societal benefits like climate modeling, whereas Bitcoin's proof-of-work mechanism generates about 81 million tons of CO2 annually with limited productive output. The key difference is that AI's inference phase scales directly with user adoption, potentially surpassing Bitcoin's consumption if left unchecked.
Dr. Tali Režun (2025)
Exploring Early Indicators of AGI in Coding Agents: A Case Study on MCP-Powered Systems
This study, conducted under the COTRUGLI Business School Co-lab initiative in Q1 and Q2 2025, investigates whether Model Context Protocols (MCPs) can enhance large language models (LLMs) to exhibit early indicators of Artificial General Intelligence (AGI) in coding agents. We developed a Retrieval-Augmented Generation (RAG) Software-as-a-Service (SaaS) application using Streamlit, integrating n8n workflows and Supabase for authentication and coupon management. The Cline Coding Agent, powered by Grok 3 Mini and augmented by five MCPs (Context7, Sequential Thinking, Knowledge Graph Memory, GitHub, and Supabase), completed 90% of the application in nine days for approximately $30 in API costs, compared to a non-MCP baseline that failed within 48 hours. These findings demonstrate that MCPs significantly enhance LLMs’ planning, reasoning, and contextual awareness, approximating early AGI-like behaviours. However, challenges in complex debugging highlight the gap to true AGI. This paper, the first in a series on Context Engineering, underscores the transformative potential of MCPs in AI-driven software development and sets the stage for future experiments with flagship models and local LLMs.
Intelligence and reasoning in coding
Coding is a cognitively demanding process that requires both intelligence and reasoning to integrate various frameworks into a cohesive application architecture. As originally conceptualized by the author, modern software development, in most cases, involves assembling pre-existing building blocks—open-source frameworks like Python, LightRAG, and Supabase—to create functional applications.
Context Ingineering
Context Engineering, or prompt engineering, is the process of designing precise, context-rich instructions to guide LLMs in complex tasks. It is crucial for overcoming LLMs’ limitations in context retention, planning, and reasoning (Brown et al., 2020). In coding, Context Engineering ensures clarity in task specifications, enabling agents to produce relevant outputs and avoid errors like hallucination loops (Bender et al., 2021).
Role of MCPs
The Model Context Protocol (MCP), introduced by Anthropic in November 2024, standardizes interactions between AI agents and external systems using a JSON-RPC 2.0 protocol (Anthropic, 2024). MCP servers enable AI agents to access real-time data, tools, and services, enhancing scalability and interoperability (Vaughan-Nichols, 2025). Early adopters like Replit and Sourcegraph have demonstrated MCP’s utility in AI-driven workflows (Anthropic, 2024).
Key Findings Overview; Interactive Dashboard
This dashboard visualizes key insights from a 2025 study examining whether Model Context Protocol (MCP) servers enhance the intelligence and reasoning of large language models (LLMs) in coding tasks, potentially revealing early indicators of Artificial General Intelligence (AGI).
Dr. Tali Režun (2025)
AI as a Force Multiplier: Leaders for Industry 5.0 Research Article
The rapid ascent of artificial intelligence (i.e. AI) technologies—spanning large language models (i.e. LLMs), no-code platforms, AI agents, automation tools, and Web3 integration—presents both opportunities and challenges for business leaders navigating a volatile, uncertain, complex, and ambiguous (i.e. VUCA) landscape. This article, grounded in the Vanguard Leadership framework (i.e. VLF), evaluates the strategic potential of AI tools to augment organizational performance. It provides a comparative analysis of LLMs, focusing on open-source versus closed-source models, privacy implications, and local hosting for data security. We explore no-code tools, Retrieval-Augmented Generation (i.e. RAG), AI agents, automation platforms, Web3 synergies, and cybersecurity threats, illustrating their applications through practical use cases like document interaction, coding, and back-office optimization. By synthesizing vendor data, industry trends, and academic insights, we propose a model for leaders to deploy AI as a force multiplier, aligning with VLF’s adaptive principles. The article concludes with a call to action for leaders to master frontier technologies, ensuring competitiveness in an AI-driven future.
Keywords: AI, artificial intelligence, LLM, large language models, agent, Vanguard Leadership, open-source, Web3, technology, disruptive technology, leaders, industry 5.0, VUCA
No-Code Tools: Empowering Non-Technical Teams
No-code AI platforms, such as ChatGPT, DALL·E 3, and GitHub Copilot, democratize advanced capabilities, enabling non-technical roles like secretaries, CMOs, and CEOs to boost productivity by 20-50%. These tools streamline tasks like scheduling, content creation, and coding, but require human oversight to ensure strategic alignment and avoid shallow outputs.
AI Agents: Autonomous Performance Boosters
AI agents, such as Cline for SaaS development, act as autonomous digital operatives, enhancing efficiency by 300% in tasks like coding and testing. These agents integrate reasoning and external tools, enabling a single developer to rival entire teams, supporting VLF’s force-multiplier ethos through scalable, precise automation.
Web3 and Cybersecurity: Securing the AI Future
Web3’s blockchain technology complements AI agents by enabling secure, trustless transactions and communications, critical for scalable deployments. Meanwhile, leaders must counter AI-driven cyber threats like phishing and deepfakes through training, local LLM hosting, and audits, ensuring resilience in an AI-driven Industrial Revolution.
Dr. Tali Režun & 4thTech team (2017 - 2024)
4thTech Project Whitepaper
The internet changed the way we live, it opened the highway to unlimited communication and revolutionized access to information, but it failed greatly regarding our digital freedom. Instead of providing a safe environment for online communication (i.e. emailing, messaging, data exchange) that we depend on every day, the internet evolved into a system of centralized intermediaries which trade the ease of access for mass surveillance and user data mining. While the majority of users have no problems accessing legacy email, messaging, or data file-sharing platforms, the “permissioned access” issue remains. Enforced usually based on censorship misbehaviour, de-platforming cases are well known leading to various cases of access restrictions. The fact remains, that the current legacy communication platforms are designed to grant permission for every email or message that we send based on pre-approval mechanics. There is also the matter of data ownership. Did you know that the moment you attach any data file to an email attachment or share it via any “free” messaging service or data file-sharing app there is a big data ownership loss possibility? Blockchain always offered the promise of enabling permissionless, secure, non-custodial, immutable communication with uninterrupted up-time, while retaining data and identity ownership, it is by design the right tool for the job. 4thTech addressed this issue already in 2017 when the “on-chain” communication R&D started. The solution presented itself in the form of an OCC (i.e. on-chain communication) framework accompanied by a dedicated SDK (i.e. software development kit).
Context
In the past decade, digital communication has become most relevant as digital data has become extremely valuable. Communication in the form of emailing, messaging and data file sharing forms personal and business relations. Humankind has grown a dependency on digital communication as it relies on and depends on it to be confidential, private, secure, or even intimate.
One Email/Message = One L1/L2 Transaction
The dChat W2W message exchange happens on-chain, as one short message represents one L1 transaction. As dMail is data heavier, lite encrypted JSON files are created to hold dMail metadata (i.e. subject, content & attachment location) while the link to this JSON metadata & checksum (i.e. dMail content structure SHA-256 hash) are recorded on-chain in the form of an L1 transaction. So again the core primitive “one email/message = one L1 transaction” applies.
Not Your Keys = Not Your Email/Message
Every wallet becomes an on-chain identity & message data vault, accessible/decrypted only with users' private keys!;
L1 security + Encryption + Decentralized storage = Web3 Secured W2W dMail & dChat Communication
True dMail & dChat security is achieved by utilising L1s security, encryption cocktail (i.e. AES, RSA, SHA-256, ECDH) and decentralized storage.
Dr. Tali Režun, Denis Jazbec (2021)
Solana L1 Secured W2W dChat Communication Framework, FOURim Protocol Light Paper
Whenever we speak about online security we consider it a topic important to us. Securing your digital communications should be your highest priority when going online. Blockchain has always offered the promise of enabling secure, immutable W2W communication while retaining data and identity ownership, it is by design the perfect security tool. However, it could never really take off due to early-generation blockchains’ scalability and cost constraints. To address this issue the 4thTech developed a Solana-based dChat, which leverages L1s trust to provide end-to-end encrypted immutable on-chain messaging.
Keywords: web3, 4thTech, dChat, internet, digital transformation, blockchain technology, decentralization, peer-to-peer, online trust, online security, online privacy, DLT, Solana blockchain
Background Key Points:
(1) the right to online safety should be above all and provided for all online communications; (2) blockchain protocols offered great promise but scalability, throughput and cost were always an issue; (3) Web3 projects & DAOs all use Web2 communication tools, which goes against the decentralization ethos, and; (4) immutable on-chain W2W messaging is prime to become the future of secure communication - Not Your Keys, Not Your Message!
Solutions Key Points:
(1) establishing an on-chain communication framework that is web, desktop & mobile interoperable (one message = one L1 Transaction); (2) bringing social communication to the Web3 Ecosystem; (3) E2EE secure, immutable, censorship-resistant, scalable & accessible »on-chain« messaging; (4) Web3 wallet login, no signup or personal information; (5) resistant to data mining, data tracking & identity theft; (6) W2W private, group & community on-chain messaging with an option of NFT curated chat groups; (7) data file & media sharing via decentralized storage; (8) stand-alone app or White labelled (SDK); (9) interoperable with all significant wallets, and; (1) due to heavy on-chain activity (i.e. 1 message = 1 TX), 4thTech dApps can bring significant growth in daily L1 transactions volume.
Research Article, Dr. Tali Režun, (2020)
Initial steps toward blockchain enterprise adoption
Blockchain has been acknowledged and recognised also in the mainstream enterprise sector. With its ability to improve online trust, transparency, efficiency and cut the middle man, blockchain solutions are developing at a light speed with the potential to revolutionise enterprise digital communication and collaboration. With major benefits to create, store and exchange sensitive information like electronic data and documents, blockchain can substantially change the technological landscape as we know it. This article clarifies the basic steps towards blockchain enterprise adoption and acts as a guideline using two suitable project use-cases as examples; (1) HashNet as an advanced scalable blockchain network, and; (2) 4thtech as a blockchain application suite, that leverages trust provided by the blockchain to provide secure, immutable, instant cross-border electronic data and document exchange and eDelivery.
Keywords; blockchain, enterprise, adoption, private chain, public chain, DLT, hashnet, 4thtech, digital identity, electronic data exchange, document notarisation
The landscape & Opportunity
According to PwC Time to trust Report 2020, blockchain has the potential to boost global domestic product (i.e. GDP) by 1.76 trillion dollars over the next decade and hit the mainstream by 2030.
Blockchain Technology
With major benefits to create, store and exchange sensitive information like electronic data and documents, blockchain can substantially change the technological landscape as we know it.
Blockchain Networks
Every blockchain transaction is executed by a blockchain network such as Bitcoin, Ethereum, Tolar HashNet, Polkadot and others. Every network has its own characteristics, so it all comes down with the project requirements.
Blockchain Enterprise Ecosystem
Establishing a viable ecosystem is another key requirement prior to blockchain implementation.
Private versus Public
Public blockchains allow anyone to read or write to the public charged ledger, while private Enterprise blockchains can restrict access to their network partners.
GDPR Compliance
While the data protection EU authorities have not yet concluded which blockchain approaches deliver GDPR compliance, possible solutions are already emerging.
Interoperability
According to the EU blockchain forum report, blockchain platforms will need to be able to communicate and share data, which is a property usually referred to as interoperability.
Blockchain Digital Identity
Trusted identities of blockchain participants are crucial to the operation success and can enable complex transactions and reduce risk.
Blockchain Electronic Data Exchange
The need for immutable, unmodifiable digital data and documents exchange is imminent. E-mail is not appropriate, non-secure and does not fulfil the task in question.
Blockchain Document Notarisation
Notarisation can be described as a fraud prevention process that enables document authenticity and guarantees that the document has not been changed in the course of a transaction between parties.
Research Article, Dr. Tali Režun, (2019)
Is Blockchain the missing internet link? Reality, Integration, Adoption and Mainstream
The internet changed the way we live, it opened the ways of unlimited communication and revolutionised access to information, but it failed greatly in regards to our personal digital freedom. Instead of providing trust, granted privacy, security, auditability, peer-to-peer communication, simplification and digital money, it evolved into a system of global intermediaries, that manipulate our private data and charge a percentage for every interaction. There is a new technology at the horizon called blockchain, that in its core excludes any intermediary’s, it brings peer-to-peer communication, online trust, security, privacy, authenticity, identity, synchronize ledger and much more. Could this be the long-awaited solution that could upgrade the internet and how it’s evolving?
Keywords: internet, digital transformation, cryptocurrency, blockchain technology, decentralisation, peer-to-peer, online trust, online security, online privacy, libra
Introduction
As an answer to 2008 global financial crisis Bitcoin was created, as a decentralised, independent digital cash network, that operated above the internet, out of banks and institutional reach. Soon the innovation of its backing technology (i.e. blockchain) was discovered as it could offer permissiveness solution to online privacy, security, digital identity, authenticity, peer-to-peer transactions and much more.
Blockchain Recognition and Adoption by Constitutional Organizations
To achieve fastest worldwide adoption several challenges should be overtaken; (1) establishment of legal regulatory and governance framework that could be adopted worldwide; (2) synchronise the competing interests, and; (3) achieving infrastructure replacement or upgrade.
Adoption by Big Banks and Big Tech
It took a few years for the Big Banks and Big Tech to officially acknowledge cryptocurrencies, blockchain technology and discard the offence position. The benefits of technology are just too hard to dismiss.
The Mainstream Adoption
To achieve blockchain global scale adoption, there are still open network issues to address like transaction cost, scalability and energy consumption.
Conclusion
The possibility to enable access to financial instruments to over 1.7bn underbanked people is truly revolutionary. Blockchain could solve open questions in the fields of finance, insurance, notary functions, supply chain management, identity, privacy and digital rights management, IoT (i.e. internet of things), state administration, online security, seaborne cargo tracking, 4D printing, quantum computing, augmented data discovery, machine learning, autonomous driving, virtual reality and much more.
Research Article, Dr. Tali Režun, (2019)
Online Brand Awareness, Brand Equity and the importance of Professional Value-Added Content
This research article deals with online brand awareness, brand presence, brand trust and brand equity. The research article was constructed to explore alternatives to paid online brand promotion and to offer a different perspective to online branding. Part of the research, literary review and implementation is directly sourced from Dr Rezun doctorate dissertation “Company Generated Problem-Solving Content on Social Media (SM) and Online Brand Equity: Designing and Testing a Model for Its Effectiveness”. This research article, also emphasises the importance of professional value-added brand content in the context of brand reference and reveals the components behind the online brand awareness building process.
Keywords: online brand awareness, brand equity, corporate identity, online brand presence, online brand exposure, brand trust, business performance
Introduction
The importance of online brand awareness and professional value-added content with its positive effect on brand equity and business performance has become an exceedingly important marketing issue.
OBA
OBA (Online Brand Awareness) is a process, that combines professional value-added content, use of advanced web technologies, use of advanced SEO techniques and the use of Social Media. OBA results in brand positioning, brand exposure and online brand equity.
Brand Equity
Brand equity has been defined as a set of brand assets and liabilities that are linked to the brand's name and symbol (Verbeeten & Vijn, 2010).
Brand Concept
Brand development is a complex process involving the creation of a unique brand image which represents the product and attracts consumers’ attention. A brand needs to associated with a deeper meaning and value, that consumers can later identify with.
Professional Value-Added Content
The importance of professional content and its positive effect on brand awareness and business performance has become an exceedingly important marketing issue (Botha, Farshid, & Pitt, 2011).
Research Article, Dr. Tali Režun, (2019)
Artificial Intelligence is here! Reality, Integration, Research, and Adoption
Artificial Intelligence (i.e. AI) is already a part of our lives. It impacted the way we interact, shop, travel, work, do business and challenge our society and culture, while becoming a vital part of self-driving cars, trucks, healthcare diagnostics, IoT, stock market, surveillance, military, agriculture, advanced manufacturing, robotics, etc. Artificial Intelligence has the potential to be the next step towards a new industrial revolution and can change human evolution altogether, but with all that disruptive change, big questions and topics are emerging, that will sooner or later need to be addressed; (1) human versus machine dilemma; (2) What is intelligence?; (3) Will Artificial Intelligence enhance our life or threaten our survival?; (4) How will AI change the nature of our jobs?
Keywords: artificial intelligence, ai, internet, digital transformation, big data, singularity, machine learning, neural networks
Introduction
Artificial Intelligence history goes to 1930s when the Turing machine was invented, that could, in theory, do all the calculations that humans were able to do. According to Max Little (2017), the practice started to take off later when AT&T labs invented a transistor and the microchip, and with that started an era of microcomputers.
Intelligence Defined
The definition of intelligence is controversial, some groups of psychologists have defined it as; A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience.
The Technology Behind AI
WIPO (2019), devised a framework of AI understanding, dividing AI-related technologies to three groups; (1) machine learning; (2) functional application, such as speech recognition and computer vision, and; (3) telecommunication and transportation.
Future Jobs, Adoption, and Integration
In the 1980s, Owen (1988) envisioned AI possibilities in; (1) farming, using computer-controlled robots, that could control pest, prune trees and harvest mixed crops: (2) manufacturing, where computer-controlled robots could execute dangerous and boring assembly, inspections and maintenance jobs; (3) medical care, where computers could help with diagnosis, monitor patients, manage treatment and make beds, and; (4) household work, where machines could mow the lawn, do the laundry and perform maintenance chores.
Conclusion
Artificial Intelligence is here! Reality, Integration, Research, and Adoption research article and overview tries to shed some light on the AI open questions. The article tried to establish, the relation between nature and machine and provided the reader's facts to draw their own conclusions. For now, one thing is clear, nature and machines cannot be equal.
DBA Manual, Dr. Tali Režun (2018)
The DBA dissertation Guidebook
A DBA (i.e. doctor of business administration) is one of the most advanced and prestigious degrees in business education. Usually, a DBA is an upgrade to an MBA (i.e. master of business administration) for individuals that need to continue their education. DBA programs provide professionals and executives, with advanced research skills and wider perspective needed to manage, lead, plan or research.
The DBA Guidebook has been created to provide potential and current DBA students overview to DBA writing process. Guidebook opens explanations to dissertations main chapters, provides writing tips and deeper understanding into methodology choices.
Keywords: DBA, dissertation, guidebook, writing a thesis, doctor of business administration
DBA Proposal
The beginning phase of the DBA study begins with a dissertation proposal. The dissertation proposal consists of the first three chapters and APA-style references list.
DBA Chapters & Structure
DBA dissertation consists of four, sometimes five chapters, depending on the study. Chapter one presents the study foundations, chapter two covers the literature review, chapter three explores the research method and chapter four covers findings and discussion.
Chapter One
Chapter one covers the introduction and background of the problem the study is addressing. More importantly, the chapter addresses applied research, identify and solve an applied business problem and presents empirical arguments.
Chapter Two
Chapter two stands for review of the professional and academic literature where the theoretical/conceptual framework must be reported.
Chapter Three
Chapter three or research method and design provide extensive examination and justification of the study nature, research design and data collection.
Chapter Four
Chapter four is a chapter of findings presentation. In chapter four, tests, tables, variables, statistics, answers to research questions and results are presented.
Technology
The biggest challenge lies in literature organisation needed to complete literature review (e.g. citations, quotes, written existing materials for the specific topic). Literature content organisation can be done manually (i.e. photocopying the chosen segments and arranging them like a puzzle to complete the big picture), or it can be done digitally.
Doctorate of Business Administration (DBA), Tali Režun (2012 - 2018)
Company Generated Problem-Solving Content on Social Media (SM) and Online Brand Equity: Designing and Testing a Model for Its Effectiveness
Based on 15 years of online experience and research dealing with online brand positioning and advanced technologies the doctorate dissertation emerged. Doctorate dissertation (i.e. DBA) titled: “Company Generated Problem-Solving Content on Social Media (SM) and Online Brand Equity: Designing and Testing a Model for Its Effectiveness” deals with online model development using professional value-added content with a purpose to aid small and mid-sized enterprises promote their brands online. The four year research period from 2012 to 2016, followed company “Naton HR” as the main research subject using dissertation model to position its brand online. Data was collected and the model confirmed. The importance of professional content and its positive effect on brand visibility and business performance has become an exceedingly important marketing issue. To date, there has been limited empirical literature on professional “content-type” in social media (SM). However, there is consensus among researchers that content has a positive effect on brand exposure, and, in fact, results in improved company sales.
Keywords: online marketing, online brand positioning, social media, digital content, online technologies
Introduction
The importance of professional content and its positive effect on brand visibility and business performance has become an exceedingly important marketing issue (e.g., Botha, Farshid & Pitt, 2011; Cheng, 2012; Kumar, et al., 2016; Schweidel & Moe, 2014)
Purpose Statement
The aim of this dissertation is to test a model developed by the researcher to aid small and mid-sized enterprises (i.e. SMEs) to promote their brands online.
Research Objectives
The research objective of this dissertation is to provide effective support for online marketing strategies for those companies that currently have an online presence or desire one.
Research Questions
Three research questions have been posed to test the model presented in this dissertation.
Research Methods
This study employs qualitative and quantitative or mixed methods.
Data Collection
Qualitative data were collected in several ways.
Significance of the Study
This study seeks to test a model that could possibly assist companies in developing a successful online marketing presence on their websites. By applying the model to their companies, marketers and marketing campaigns can better position company brands in highly competitive new social media (SM) environments.
Assumptions and Limitations
There are six assumption and limitations of this study.
Research Business Model, Dr. Tali Režun
Conceptual business effect model on the positive effect of firm generated problem solving content on social media and online brand equity
This model is a general online business model, derived from observation and extant theories which may be adopted by small and medium-sized companies, (b) the model and its underlying theory provided general guidance for online support building brand equity and online business exposure, and (c) the model offers detailed support, general guidance, and an explanation of proposed processes to SMEs companies, though other industries may take alternate approaches when applying the model.
There are few available and proven business models available about online marketing in the fast-paced, quickly changing global online business environment. Many companies lack the knowledge to adapt and to support online business development (Ha, 2005). To address the problem, a business model was developed as part of doctorate dissertation (i.e. Company Generated Problem-Solving Content on Social Media (SM) and Online Brand Equity: Designing and Testing a Model for Its Effectiveness A dissertation submitted in partial fulfilment for the degree of Doctor of Business Administration) to help companies develop successful online marketing campaigns and to position their brands in existing new social media environment.
The results from testing the model showed positive results on higher brand equity and exposure and resulted in better business performance and overall recognition in the targeted region. This confirmation of the model is one of the major contributions of related study because it maps a possible path and process for other companies to follow and modify accordingly. The model is effective, is easy to use, and is suitable for use by other companies.
Keywords: content model, business online model, social media content, online brand positioning model
Description
There are few available and proven business models available about online marketing in the fast-paced, quickly changing global online business environment.
Model Legend
Describing model shapes and what they represent.
Business Model
Graphic representation of the conceptual business effect model on the positive effect of firm generated problem-solving content on social media and online brand equity.
Research Article, Dr. Tali Režun (2018 - 2019)
Identifying key quality factors of a small hotel: Article researching Business Success Model of a High-quality Small Hotel in Ljubljana
The purpose of this research article was to construct a guidebook, identifying the key quality factors that forge a successful small high-quality hotel business model. The research reveals and identifies the key success components needed for a successful high-quality small hotel to operate.
Keywords: small hotel, small hotel quality, small hotel success factors, city hotel, boutique hotel
Introduction
Hotel is often referred to as a “Home away from home” (LE, N. 2010). According to Maria, I., Madalina, T., Catalina, B., & Diana, I. (2008), tourism is a sector in which the structure of supply is extremely volatile and the solid and consistent part is the demand.
Research Subject
To gather most valuable, up to date information, the real hotel business is a part of this research article. The research subject is a new four-star hotel in the Slovenian capital Ljubljana.
Hotel Quality Definition
According to the AA Quality Standards for Hotels, there are five levels of quality ranging from One to Five Stars. To obtain a higher star rating a progressively higher quality and range of services and physical facilities should be provided across all areas with particular emphasis in six key areas.
Findings and Discussion
Upon review of the available literature and the research done at the chosen small Ljubljana hotel, key success factors were determined; (1) location; (2) room quality; (3) bed quality; (4) breakfast, and; (5) hospitality.
Conclusion and Implications
The main goal of this research article was to Identify key quality factors needed for a small city hotel to succeed. The literary review clearly established that Small hotel has specific advantages over big ones.
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