نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکترای مدیریت صنعتی، دانشکده اقتصاد، مدیریت و حسابداری دانشگاه یزد، یزد، ایران
2 دانشیار گروه مدیریت، دانشکده اقتصاد، مدیریت و حسابداری دانشگاه یزد، یزد، ایران
3 استاد گروه مدیریت، دانشکده اقتصاد، مدیریت و حسابداری دانشگاه یزد، یزد، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
EXTENDED ABSTRACT
Introduction: Governments around the world have always looked for ways to deal with tax evasion. It’s a serious issue, when people or companies don’t pay the taxes they owe, it affects everyone. Public services like schools, hospitals, and roads rely on tax money. So when that money doesn’t come in, the whole system suffers.But tackling tax evasion isn’t easy. It’s not just about catching a few rule-breakers. It’s about understanding why people evade taxes in the first place, and how the system might be unintentionally encouraging it. Many different groups are involved, taxpayers, tax officials, politicians, business owners, and more. Each group sees the problem differently, and their interests don’t always align. On top of that, every decision has political, social, and economic consequences. A change that helps reduce evasion might also upset a powerful group or create other unexpected problems.Because of this complexity, the usual one-size-fits-all solutions often don’t work. Policymakers are constantly searching for better ways to look at the problem and design more effective, realistic solutions.
Methodology: Most of the time, when researchers or governments try to deal with tax evasion, they rely on hard, technical models. These models use numbers, formulas, and fixed rules to predict behavior or design policy. While they can be helpful in some cases, they don’t always match the messy reality of human behavior and real-world systems.Think about it: people don’t always act logically. Their choices are shaped by habits, emotions, social pressures, and how fair they think the system is. So a cold, mathematical model might miss important parts of the picture.That’s why, in this study, we used a different approach called Soft Systems Methodology (SSM). It’s not about finding one “correct” answer. Instead, it helps people understand complex problems by looking at them from different angles. SSM is especially useful when the problem involves many actors, with different views and goals, exactly the case with tax evasion.We started by identifying the key players: individuals, institutions, and organizations involved in or affected by tax evasion. Then we looked at the conditions they operate under, what motivates them, what pressures they face, what tools or rules are already in place, and what gaps might exist in the system.Next, we brought together experts and stakeholders to talk openly about how they see the problem. By doing this, we created a shared picture of what’s going on. That shared understanding helped us build a practical model that included not just laws and tools, but also things like human motivation, systemic barriers, and real-world enforcement.
Discussion and Results: One of the most powerful outcomes of this approach was the ability to bring many different perspectives together into a single, clear picture. Instead of arguing over whose view is “right,” we focused on building a deeper understanding of the full system.We discovered that many existing actions to prevent tax evasion are applied unevenly. Some are used often but poorly executed. Others are barely used, even though they might be very effective. And how these actions are carried out, whether formally and consistently or informally and randomly, makes a big difference in how well they work.For example, a public awareness campaign about tax honesty might be a great idea. But if it’s done half-heartedly, or once every few years, it won’t change much. On the other hand, a well-planned, frequent, and relatable campaign can slowly shift how people think and act.We also saw that some actions are stronger when combined. A new detection tool might not work well by itself, but when paired with expert analysis and smart communication, it becomes much more powerful.
Conclusion: What we learned is simple but important: solving tax evasion isn’t just about rules and punishment. It’s about creating a smarter, fairer, and more human system, one that understands the people inside it.Some of our key recommendations include:Creating clear, structured processes that are followed regularly. Bringing together experts to evaluate what’s working and what’s not. Encouraging cooperation between different organizations and government bodies.Using simulation tools that let us “test” ideas before implementing them in the real world. Running regular, creative awareness campaigns that talk to people, not just at them.Promoting a culture where paying taxes is seen as part of being a responsible citizen, not just an obligation. We also suggest simplifying the system by removing weak or repetitive policies and focusing on a smaller number of well-designed, well-executed actions. The goal isn’t to make the system more complicated, it’s to make it smarter and more trusted.Finally, we believe future work should explore combining soft approaches like SSM with simulation tools. This mix can help policymakers see both the human side and the technical side of a problem, giving them better insight and more confidence in their decisions.
کلیدواژهها [English]
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