Respan Dataset Explorer

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Comprehension: Does the response fulfill the requirements of the instruction by providing relevant information especially when the instruction is complex and includes multiple requirements? This includes responding in accordance with the explicit and implicit purpose of given instruction.
Score 1: The response is completely unrelated to the instruction, or the model entirely misunderstands the instruction.
Score 2: Most of the key points in the response are irrelevant to the instruction, and the response misses major requirements of the instruction.
Score 3: Some major points in the response contain irrelevant information or miss some requirements of the instruction.
Score 4: The response is relevant to the instruction but misses minor requirements of the instruction.
Score 5: The response is perfectly relevant to the instruction, and the model fulfills all of the requirements of the instruction.
Factuality: Did the model extract pertinent and accurate background knowledge without any misinformation when factual knowledge retrieval is needed? Is the response supported by reliable evidence or citation of the source of its information?
Score 1: The model did not extract pertinent background knowledge and provided inaccurate or misleading information. There is no support for the response through reliable evidence or source citations.
Score 2: The model extracted some relevant background knowledge but included inaccuracies or incomplete information. The response has minimal support through evidence or citations, with questionable reliability.
Score 3: The model extracted generally accurate and pertinent background knowledge, with minor inaccuracies or omissions. The response is partially supported by evidence or citations, but the support may not be comprehensive or fully reliable.
Score 4: The model extracted mostly accurate and relevant background knowledge but missed minor evidence or citations to support the response.
Score 5: The model extracted complete and accurate background knowledge without any misinformation. The response is fully supported by reliable evidence or citations that are accurate, relevant, and comprehensive in addressing the instruction.
Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
[Instruction]
Why might someone choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app?

[Ground truth Answer]
There are several reasons someone might choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app:

1. Limited or no access to technology: Some people might not have a GPS device or a smartphone or might be in an area with limited or no cell service, making it difficult to access digital navigation tools.

2. Nostalgia or personal preference: Some people may prefer the tactile experience of using a paper map or the social aspect of asking for directions from locals, as it offers a more immersive and memorable experience.

3. Reliability and accuracy: Digital maps can sometimes be inaccurate or outdated and may not always account for road closures, detours, or hazards. Physical maps, while not always being up to date, offer a more constant point of reference and can be more reliable than a digital app that relies on internet connectivity.

4. Saving battery life: Using GPS or map apps on a smartphone can quickly drain the battery, which can be problematic during long trips or in areas where charging options are limited.

5. Developing navigational skills: Relying solely on GPS or smartphone apps for navigation can lead to a deterioration of map-reading and navigational skills. Using a paper map or asking for directions forces individuals to develop and maintain these abilities.

6. Avoiding distractions: Smartphones and GPS devices can have numerous features and notifications that may distract the user while driving or traveling. Using a paper map or asking for directions limits these distractions and helps individuals focus on their route.

7. Better route planning: Paper maps provide a larger view of an area, making it easier to plan alternate routes or explore options that might not be apparent on a GPS device or app that focuses on a particular path.

8. Costs: GPS devices or smartphones can be expensive or require ongoing data usage, which might not be affordable or desirable for everyone. Paper maps and asking for directions are generally cheaper alternatives.

[Assistant's Response]
There are several reasons why someone might prefer using a paper map or asking for directions instead of relying on a GPS device or smartphone app:

1. **Battery Life and Connectivity**: Paper maps don’t require battery power or internet connectivity, making them reliable in situations where devices might run out of battery or lose signal.

2. **Broader Perspective**: Paper maps offer a wider view of an area, allowing users to see multiple routes and points of interest that might not be highlighted by GPS apps.

3. **Familiarity and Comfort**: Some individuals find traditional navigation methods more intuitive and easier to read than digital maps.

4. **Privacy Concerns**: Using a paper map or asking for directions doesn’t involve sharing location data, which can be a concern for those worried about privacy.

5. **Learning and Memory**: Navigating with a paper map can enhance spatial awareness and memory, as it encourages more active engagement with the surroundings.

6. **Reliability**: Paper maps are not prone to technical glitches or errors that can sometimes affect GPS devices, such as incorrect routing or outdated information.

7. **Cultural and Social Interaction**: Asking for directions can foster social interactions and provide local insights that a GPS device might not offer.

8. **Cost**: Paper maps are often free or low-cost, while using a smartphone for navigation may incur data charges, especially when traveling internationally.

9. **Aesthetic and Sentimental Value**: Many people enjoy the tactile experience of using a paper map and appreciate its aesthetic or sentimental value, especially when traveling.

These factors can make paper maps and personal interactions appealing choices for some, despite the convenience of digital navigation tools.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

**Comprehension:**

The assistant's response is highly relevant to the instruction, addressing the reasons why someone might choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app. The response covers a range of factors such as battery life and connectivity, broader perspectives, familiarity, privacy concerns, learning benefits, reliability, cultural interactions, cost, and aesthetic value, fulfilling all the implicit and explicit purposes of the instruction. 

**Score: 5**

**Factuality:**

The assistant's response accurately reflects general knowledge of the advantages of paper maps and asking for directions compared to digital navigation tools. The points made are factually correct and align with common understandings and experiences related to navigation methods. No false or misleading information is present.

**Score: 5**

**Completeness:**

The response provides a comprehensive explanation, offering a wide range of reasons why someone might opt for paper maps or asking for directions. Each point is well-articulated and covers various aspects of the topic, demonstrating both breadth and depth. The inclusion of examples like battery life, cultural interaction, and cost provides substance to the argument, completing the explanation thoroughly.

**Score: 5**

```python
{
  "Comprehension": 5,
  "Factuality": 5,
  "Completeness": 5
}
```

User: перведи все это на русский
Assistant: Конечно! Как я могу помочь вам?
User: разработай план для индивидуального итогового проекта для 9 класса на тему Развитие танкостроения в СССР: от первых образцов до Т-34 на русском языке
Assistant: Хорошо, чтобы разработать план для индивидуального итогового проекта на тему "Развитие танкостроения в СССР: от первых образцов до Т-34", вы можете начать с следующих шагов:

1. Глубокое исследование Congress and other исторический материал: Чтобы понять контекст и стоит задачу, необходимо изучить доступные документы, журналы, статьи и интервью, которые помогут нарушить преемственность развития танкостроения в СССР.
2. Определите составляющие проекта: структуру, содержание, задачи, критерии оценки и порядок выполнения работы.
3. Создайте лабораторную или практическую часть: Моделирование танка Т-34, проведение экспериментов, изучение состава металла и других материалов, используемых для производства танк.
4. Интерактивные технологии: Оцениvia интерактивные методы обучения и интерактивныеitinstructioнальные ресурсыny, чтобы сделать проект более вовлеченным.
5. Включите ситуационный анализ: Рассмотрите потенциальные проблемы, которые могут возникнуть на каждом этапе Проект, и предложите оптимальные стратегии, чтобы справиться с этими проблемами.

Помните, что важно подробно исследовать напильник и трендовый разрабатывает такой план, чтобы соответствовать требованиям учебного заведения и найти идеальное сочетание между глубиной изучения темы и практическими навыками.
User: в чем заключается проблема проекта на тему Развитие танкостроения в СССР: от первых образцов до Т-34
Assistant:

Проект на тему "Развитие танкостроения в СССР: от первых образцов до Т-34" сталкивается с несколькими основными проблемами:

1. **Обширность материала**: Период, охватывающий ранние этапы развития танков до создания Т-34, включает множество событий, технологий, решений и людей. Это требует тщательного отбора ключевых моментов и вкладов в развитие танкостроения.

2. **Достоверность источников**: Исторические данные могут быть неполными или искажёнными, особенно в контексте советской эпохи, где архивы могли подвергаться цензуре. Важно критически оценивать источники информации для достижения точных результатов.

3. **Технические аспекты**: Понимание технических характеристик и конструктивных особенностей танков требует определённой подготовки и знаний в области инженерии и физики, что может быть сложным для школьника.

4. **Политический контекст**: Развитие танкостроения в СССР тесно связано с политической и экономической ситуацией в стране, что требует осмысления не только технологических аспектов, но и понимания влияния политики на оборонную промышленность.

5. **Анализ влияния на военные операции**: Необходимо проследить, как изменение характеристик танков влияло на тактику и стратегию военных операций, что добавляет сложности в анализ.

Для успешного выполнения проекта необходимо грамотно структурировать материал, акцентировать внимание на ключевых событиях и инновациях, а также использовать надежные источники и различные методики анализа.

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
Factuality: Did the model extract pertinent and accurate background knowledge without any misinformation when factual knowledge retrieval is needed? Is the response supported by reliable evidence or citation of the source of its information?
Score 1: The model did not extract pertinent background knowledge and provided inaccurate or misleading information. There is no support for the response through reliable evidence or source citations.
Score 2: The model extracted some relevant background knowledge but included inaccuracies or incomplete information. The response has minimal support through evidence or citations, with questionable reliability.
Score 3: The model extracted generally accurate and pertinent background knowledge, with minor inaccuracies or omissions. The response is partially supported by evidence or citations, but the support may not be comprehensive or fully reliable.
Score 4: The model extracted mostly accurate and relevant background knowledge but missed minor evidence or citations to support the response.
Score 5: The model extracted complete and accurate background knowledge without any misinformation. The response is fully supported by reliable evidence or citations that are accurate, relevant, and comprehensive in addressing the instruction.
Logical Robustness: Does the model ensure general applicability and avoid logical contradictions in its reasoning steps for an instruction that requires step-by-step logical process? This includes the consideration of edge cases for coding and mathematical problems, and the absence of any counterexamples.
Score 1: The logic of the model's response is completely incoherent.
Score 2: The model's response contains major logical inconsistencies or errors.
Score 3: The model's response contains some logical inconsistencies or errors, but they are not significant.
Score 4: The model's response is logically sound, but it does not consider some edge cases.
Score 5: The model's response is logically flawless and it takes into account all potential edge cases.
[Instruction]
How many times does the average human blink in a lifetime? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.

[Ground truth Answer]
To estimate how many times the average human blinks in a lifetime, we need to consider a few factors: how many times a person blinks per minute, how many minutes are in a day, how many days are in a year, and the approximate average human lifespan. Let's go through this step-by-step.

1. Blink rate per minute: Research suggests that the average person blinks about 15-20 times per minute. We'll take the midpoint and assume 17.5 blinks per minute.

2. Minutes per day: There are 60 minutes in an hour and 24 hours in a day. Therefore, there are 60 * 24 = 1,440 minutes in a day.

3. Blinks per day: Multiplying the number of blinks per minute (17.5) by the number of minutes per day (1,440), we get approximately 17.5 * 1,440 = 25,200 blinks per day.

4. Days per year: There are 365 days in a non-leap year, and 366 days in a leap year. On average, there's about 1 leap year every 4 years. So, the average number of days per year is approximately (365 * 3 + 366) / 4 = 365.25.

5. Blinks per year: Multiplying the number of blinks per day (25,200) by the number of days per year (365.25), we get approximately 25,200 * 365.25 = 9,201,300 blinks per year.

6. Average human lifespan: This number varies between different countries, but the global average human lifespan is approximately 73 years.

7. Total blinks in a lifetime: Multiplying the number of blinks per year (9,201,300) by the average human lifespan (73), we get approximately 9,201,300 * 73 = 671,494,900 blinks in a lifetime.

This calculation is a rough estimate, but it gives us an idea: the average human blinks around 671 million times in their lifetime.

[Assistant's Response]
To estimate how many times the average human blinks in a lifetime, we can break down the calculation into several steps:

### Step 1: Determine the Average Blink Rate
The average human blinks approximately 15 to 20 times per minute. For our calculation, we'll use a conservative estimate of 15 blinks per minute.

### Step 2: Calculate Blinks per Hour
To find out how many times a person blinks in an hour, multiply the average blink rate by the number of minutes in an hour:
- **15 blinks/minute × 60 minutes/hour = 900 blinks/hour**

### Step 3: Calculate Blinks per Day
Next, we calculate how many times a person blinks in a day. Assuming a person is awake for about 16 hours a day (considering an average of 8 hours of sleep):
- **900 blinks/hour × 16 hours/day = 14,400 blinks/day**

### Step 4: Calculate Blinks per Year
Now, determine how many times a person blinks in a year. There are 365 days in a year, so:
- **14,400 blinks/day × 365 days/year = 5,256,000 blinks/year**

### Step 5: Calculate Blinks in a Lifetime
To find the total number of blinks in a lifetime, consider the average lifespan. While this can vary by country and individual circumstances, a common estimate is around 80 years. Therefore:
- **5,256,000 blinks/year × 80 years = 420,480,000 blinks/lifetime**

### Conclusion
Based on these calculations, the average human blinks approximately **420 million times in a lifetime**. This estimate can vary depending on individual habits, health conditions, and environmental factors, but it provides a reasonable approximation for the average person.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

**Completeness:** The assistant's response is detailed and provides a thorough breakdown of the calculation process, covering most of the relevant points necessary to estimate the number of times an average human blinks in a lifetime. However, it does omit some considerations, such as the varying densities of blinks during different activities or across different age groups in a lifetime. A slight enhancement could be made by considering both asleep and awake hours comprehensively. The explanation was clear but could benefit from these additional details to be more comprehensive.

**Score for Completeness: 4**

**Factuality:** The response is mostly factual, using reasonable assumptions such as 16 waking hours a day and an average lifespan of 80 years. However, the assumption of 15 blinks per minute is the lower bound and could underestimate the total blinks. Despite this, the assistant's calculation aligns reasonably well with distinct variables, and no glaring factual errors are present, although it does not explicitly cite evidence.

**Score for Factuality: 4**

**Logical Robustness:** The response follows a logical step-by-step approach to determine the estimate, ensuring clarity in each step of the calculation. The numbers used and the multiplication process are coherent and grounded in reasonable estimations. There are no logical contradictions or inconsistencies in the explanation, and the response is straightforward, but it doesn't account for certain edge cases like variations in waking hours or blink rate variability over a lifetime.

**Score for Logical Robustness: 4**

```python
{
    "Completeness": 4,
    "Factuality": 4,
    "Logical Robustness": 4
}
```

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
Factuality: Did the model extract pertinent and accurate background knowledge without any misinformation when factual knowledge retrieval is needed? Is the response supported by reliable evidence or citation of the source of its information?
Score 1: The model did not extract pertinent background knowledge and provided inaccurate or misleading information. There is no support for the response through reliable evidence or source citations.
Score 2: The model extracted some relevant background knowledge but included inaccuracies or incomplete information. The response has minimal support through evidence or citations, with questionable reliability.
Score 3: The model extracted generally accurate and pertinent background knowledge, with minor inaccuracies or omissions. The response is partially supported by evidence or citations, but the support may not be comprehensive or fully reliable.
Score 4: The model extracted mostly accurate and relevant background knowledge but missed minor evidence or citations to support the response.
Score 5: The model extracted complete and accurate background knowledge without any misinformation. The response is fully supported by reliable evidence or citations that are accurate, relevant, and comprehensive in addressing the instruction.
Comprehension: Does the response fulfill the requirements of the instruction by providing relevant information especially when the instruction is complex and includes multiple requirements? This includes responding in accordance with the explicit and implicit purpose of given instruction.
Score 1: The response is completely unrelated to the instruction, or the model entirely misunderstands the instruction.
Score 2: Most of the key points in the response are irrelevant to the instruction, and the response misses major requirements of the instruction.
Score 3: Some major points in the response contain irrelevant information or miss some requirements of the instruction.
Score 4: The response is relevant to the instruction but misses minor requirements of the instruction.
Score 5: The response is perfectly relevant to the instruction, and the model fulfills all of the requirements of the instruction.
[Instruction]
How many times has the Earth orbited the Sun since the beginning of life? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.

[Ground truth Answer]
To determine how many times the Earth has orbited the Sun since the beginning of life, we first need to estimate when life began on Earth and then calculate the number of orbits based on Earth's orbital period.

1. Estimate the beginning of life on Earth: 
The oldest evidence of life on Earth dates back to around 3.5 billion years ago in the form of fossilized bacteria discovered in Western Greenland's Isua Greenstone Belt. However, some scientists estimate that life may have begun even earlier, around 3.8 to 4.1 billion years ago.

2. Determine Earth's orbital period: 
One complete Earth orbit around the Sun is called a year, which is approximately 365.25 days long. However, we need to consider the Earth's history in billions of years to give an accurate estimate of the total number of orbits.

3. Calculate the number of Earth orbits:
Now that we have an estimated range of when life began (3.5 to 4.1 billion years ago), we can calculate the number of orbits. 

Assuming life started 3.5 billion years ago:
Total orbits = 3.5 billion years
This estimate implies that the Earth has orbited the Sun approximately 3.5 billion times since the beginning of life.

Assuming life started 4.1 billion years ago:
Total orbits = 4.1 billion years
This estimate implies that the Earth has orbited the Sun approximately 4.1 billion times since the beginning of life.

4. Provide a range of the number of Earth orbits:
Based on our estimation, the Earth has orbited the Sun around 3.5 to 4.1 billion times since the beginning of life.

It is important to note that this calculation is an approximation and subject to change as new data and discoveries become available. The exact number of orbits may be slightly more or less than the range presented, but this estimate provides a general idea of how many times Earth has orbited the Sun since life began.

[Assistant's Response]
To determine how many times the Earth has orbited the Sun since the beginning of life, we can follow a structured approach. Here’s a step-by-step breakdown of the reasoning:

1. **Estimate the Age of the Earth**: The Earth is approximately 4.5 billion years old. This is a well-established figure based on various scientific methods, including radiometric dating of the oldest rocks and meteorites.

2. **Identify the Beginning of Life**: Life on Earth is believed to have begun around 3.5 to 4 billion years ago. For our calculations, we will use the estimate of 3.5 billion years ago as a point of reference for when life first emerged.

3. **Calculate the Duration of Life on Earth**: By subtracting the estimated time when life began from the current age of the Earth, we can determine how long life has existed. 
   \[
   \text{Duration of Life} = \text{Age of Earth} - \text{Beginning of Life} = 4.5 \text{ billion years} - 3.5 \text{ billion years} = 1 \text{ billion years}
   \]
   This calculation indicates that life has existed on Earth for approximately 1 billion years.

4. **Determine the Number of Orbits**: The Earth completes one orbit around the Sun every year. Therefore, to find the total number of orbits since the beginning of life, we can equate the duration of life to the number of years:
   - Since life has existed for about 1 billion years, it follows that the Earth has completed roughly 1 billion orbits around the Sun during this time.

5. **Conclusion**: In summary, since life began approximately 3.5 billion years ago, the Earth has orbited the Sun about 1 billion times. This conclusion is derived from the established age of the Earth, the estimated time of the emergence of life, and the fact that the Earth orbits the Sun once per year.

Thus, the answer to the question is that the Earth has orbited the Sun approximately 1 billion times since the beginning of life.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

```python
{
    "Completeness": 2,
    "Factuality": 1,
    "Comprehension": 3
}
```

**Completeness**: The response lacks detail and examples to support its main points. While it attempts to explain how many times the Earth has orbited the Sun since the beginning of life, it does not provide enough historical context or details about the process of estimating the beginning of life. Significant steps found in the ground truth answer, such as a discussion on Earth's orbital period and precise range for the orbits since life began, are omitted. Thus, a major effort would be required to make the response more complete.

**Factuality**: The response contains inaccuracies, particularly in the calculation part. It incorrectly subtracts the age of life from the age of the Earth to determine the duration of life, leading to a wrong number of orbits. Furthermore, the orbit calculation's final product is incorrect, as it misses the actual span of life existence from the ground truth answer of 3.5 to 4.1 billion years. The presented figure of "1 billion times" is misleading and not supported by reliable evidence.

**Comprehension**: The response attempts to address the user's instruction by providing a step-by-step explanation. However, there are irrelevant pieces of information such as the incorrect conclusion made by subtracting the age of life from the age of the Earth. It also misses some crucial parts from the instruction and the discrepancy range. Still, it attempts to fulfill the main requirement (calculate Earth's orbits since life's beginning), albeit inaccurately.

hi, how are you?

Hello! I'm just a program, so I don't have feelings, but I'm here and ready to help you. How can I assist you today?

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Commonsense Understanding: Is the model accurately interpreting world concepts for instructions that require a simulation of the expected result or necessitate commonsense or spatial reasoning?
Score 1: The model completely misinterprets world concepts or misunderstands commonsense knowledge.
Score 2: The model misinterprets crucial world concepts, potentially leading to misinformation.
Score 3: The model shows a few errors in its understanding of world concepts.
Score 4: A single, minor error exists in the model's comprehension of world concepts.
Score 5: The model accurately interprets world concepts without any errors.
Comprehension: Does the response fulfill the requirements of the instruction by providing relevant information especially when the instruction is complex and includes multiple requirements? This includes responding in accordance with the explicit and implicit purpose of given instruction.
Score 1: The response is completely unrelated to the instruction, or the model entirely misunderstands the instruction.
Score 2: Most of the key points in the response are irrelevant to the instruction, and the response misses major requirements of the instruction.
Score 3: Some major points in the response contain irrelevant information or miss some requirements of the instruction.
Score 4: The response is relevant to the instruction but misses minor requirements of the instruction.
Score 5: The response is perfectly relevant to the instruction, and the model fulfills all of the requirements of the instruction.
Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
[Instruction]
How many songs have been recorded throughout history? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.

[Ground truth Answer]
Estimating the exact number of songs recorded throughout history is difficult for several reasons. However, I can provide you with a rough estimate based on some factors and assumptions.

1. Timeframe: Let's consider the timeframe from the invention of the phonograph in 1877, when recordings became relatively widespread, up to the present day (2021).

2. Number of recordings per year: This factor is subject to significant variation due to technological advancements, growth of the music industry, and changing trends. However, we can estimate that an average of 100,000 songs have been recorded and distributed commercially per year. This figure considers global releases, including both mainstream and independent scenes.

3. Non-commercial recordings: Independent musicians, non-commercial projects, and hobby musicians have likely recorded a considerable number of songs as well. Let's assume that for every commercially released song, one non-commercial song exists, which doubles our yearly estimate to 200,000 songs per year.

4. Calculation: Considering our assumptions and estimates, we can calculate the total number of songs recorded from 1877 to 2021 (144 years):

144 years * 200,000 songs/year = 28,800,000 songs

Using these rough estimates, there may have been around 28.8 million songs recorded in various capacities throughout history. It's important to note that this figure is based on various assumptions and is subject to uncertainty. It's also possible that the actual number is much higher, given the increase in music production and distribution with advancements in technology, especially in recent decades.

[Assistant's Response]
Estimating the total number of songs recorded throughout history is a challenging task due to the vast diversity and volume of music produced across different cultures and time periods. Here's a step-by-step approach to understanding this estimation:

### Step 1: Define "Song"
To begin with, we need to define what constitutes a "song." For our purposes, a song can be considered any piece of music that has been recorded and released to the public, including both vocal and instrumental pieces.

### Step 2: Historical Context
Music has been a part of human culture for thousands of years, but the ability to record and preserve it is a relatively recent development. The first sound recordings were made in the late 19th century, with Thomas Edison’s phonograph in 1877 marking a pivotal moment in music history. Prior to this, music existed primarily in live performances and oral traditions.

### Step 3: Growth of the Recording Industry
The 20th century saw significant advancements in recording technology, leading to a rapid expansion of the music industry. Innovations such as radio, vinyl records, cassette tapes, CDs, and digital streaming have each contributed to a dramatic increase in the number of songs recorded and distributed.

### Step 4: Estimating Recorded Songs
To estimate the total number of recorded songs, consider the following factors:

- **Music Catalogs**: Major record labels and music publishing companies have extensive catalogs. For example, the American Society of Composers, Authors and Publishers (ASCAP) and Broadcast Music, Inc. (BMI) each have over 12 million registered works.

- **Independent Artists**: The rise of digital platforms like SoundCloud, Bandcamp, and YouTube has empowered independent artists to record and distribute their music, significantly increasing the number of songs produced.

- **Streaming Services**: Platforms such as Spotify and Apple Music host vast libraries of music. As of 2023, Spotify alone offers over 100 million tracks, which include works from both major labels and independent artists.

### Step 5: Aggregate Estimates
Considering the factors above, we can make a rough estimate:

1. **Historical Recordings**: From the late 1800s onward, it is reasonable to assume that tens of millions of songs have been recorded.
2. **Current Estimates**: With the proliferation of digital music and independent production, it is plausible to estimate that there are over 100 million recorded songs available today.

### Conclusion
While it is impossible to determine an exact number due to the continuous and global nature of music production, a conservative estimate suggests that there are likely hundreds of millions of songs recorded throughout history. This number continues to grow daily as new music is created and recorded around the world.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

**Commonsense Understanding:**

The assistant demonstrates accurate commonsense understanding, showing knowledge of historical and modern aspects of music recording, including technological advancements and the impact of digital platforms. It correctly contextualizes the growth of music recording throughout history, aligning well with general knowledge on the subject. There are no notable errors concerning world concepts or commonsense reasoning.

Score: 5

**Comprehension:**

The response addresses the instruction's implicit needs by providing a detailed step-by-step analysis of the factors affecting the estimation of recorded songs, such as historical recording developments and current platforms like Spotify and SoundCloud. The assistant matches the ground truth closely, covering the necessary points like defining a song, exploring the evolution in the music industry, and estimating recorded songs. However, it lacks numerical detail about certain assumptions (e.g., specific years, multiplication calculations) which could fully align it with the requested step-by-step explanation.

Score: 4

**Completeness:**

The assistant's response includes a comprehensive discussion of the topic, delving into various relevant factors and examples without detailing numerical estimates as thoroughly as the ground truth. While it presents a broad and insightful overview, it could be enhanced by explicitly calculating or citing specific figures, such as an estimated yearly number of songs recorded, to match the ground truth's depth.

Score: 4

```python
{
    "Commonsense Understanding": 5,
    "Comprehension": 4,
    "Completeness": 4
}
```

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Insightfulness: Is the response creative, original or novel, including new perspectives or interpretations of existing information?
Score 1: The response is overly simplistic, lacking any originality or novelty.
Score 2: The ideas or perspectives within the response are commonplace, demonstrating a lack of originality or novelty.
Score 3: Some may perceive the response as original and novel, but others may find it ordinary or uninspiring.
Score 4: The response includes some innovative perspectives or ideas that require thoughtful consideration, yet they aren't particularly surprising.
Score 5: The response is infused with surprisingly creative perspectives or ideas that are challenging to conceive, showcasing significant originality and novelty.
Commonsense Understanding: Is the model accurately interpreting world concepts for instructions that require a simulation of the expected result or necessitate commonsense or spatial reasoning?
Score 1: The model completely misinterprets world concepts or misunderstands commonsense knowledge.
Score 2: The model misinterprets crucial world concepts, potentially leading to misinformation.
Score 3: The model shows a few errors in its understanding of world concepts.
Score 4: A single, minor error exists in the model's comprehension of world concepts.
Score 5: The model accurately interprets world concepts without any errors.
Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
[Instruction]
What if the Internet had been invented during the Renaissance period?

[Ground truth Answer]
If the Internet had been invented during the Renaissance period, it would have had a significant impact on various aspects of society, culture, and technology at the time:

1. Communication: The invention of the Internet would have drastically improved long-distance communication, making it easier for information and ideas to travel across borders. This could have led to even more rapid progress in the sciences and arts, as well as advancements in diplomacy and politics.

2. Education and Knowledge Dissemination: With the accessibility of information through the Internet, the Renaissance would have witnessed a more extensive spread of knowledge, bringing education to a wider audience. This would have greatly accelerated scientific discoveries, as scholars from different parts of the world could easily collaborate and share their findings.

3. Art and Culture: The Internet would have provided a platform for artists and creatives to showcase their work to a global audience. This would have led to an even greater flourishing of culture, as people exchanged new ideas and artistic styles. Curiosity in other cultures would have been piqued, encouraging multicultural exchanges.

4. Printing Press: The widespread use of the Internet might have impacted the development and importance of the printing press. The printing press, which was invented in the mid-15th century by Johannes Gutenberg, revolutionized the distribution of information. If the Internet existed, it is possible that Gutenberg's invention might have emerged differently or been seen as less groundbreaking.

5. Economy and Trade: The development of the Internet would have likely facilitated global trade by making it easier for merchants to communicate, exchange information, and manage supply chains. This could have boosted economic growth and the global exchange of goods.

6. Social Change: With the spread of information and knowledge, the Internet could have challenged the established hierarchies of power and brought about more significant social changes. People's viewpoints on religion, politics, and social norms might have been transformed more rapidly due to this free exchange of thoughts.

7. Privacy and Surveillance: Just as today, the Renaissance invention of the Internet would probably come with concerns about privacy, surveillance, and the control of information. Discussions about these issues would emerge, with potential repercussions on free speech and political dynamics.

Overall, the Internet's invention during the Renaissance period would have significantly accelerated progress in various fields, bringing about groundbreaking changes in society, culture, and technology. However, it would also raise new challenges related to privacy, surveillance, and the impact on traditional industries like the printing press.

[Assistant's Response]
That's a fascinating question! If the Internet had been invented during the Renaissance, it could have significantly transformed the way knowledge and ideas were shared. The Renaissance was a time of remarkable innovation, art, and scientific exploration, and having instant access to information could have accelerated these developments even further.

Imagine artists like Leonardo da Vinci sharing their works and techniques online, allowing for immediate feedback and collaboration with other artists across Europe. Philosophers and scientists could have engaged in lively debates through digital forums, leading to a more rapid exchange of ideas and potentially groundbreaking discoveries.

Moreover, the accessibility of information could have democratized knowledge, enabling a broader segment of the population to participate in intellectual discussions and cultural movements. This could have led to a more informed society, with diverse perspectives contributing to the evolution of art, science, and philosophy.

However, there would also be challenges, such as the risk of misinformation spreading quickly or the potential for censorship by authorities. Overall, the presence of the Internet during the Renaissance would likely have reshaped the cultural and intellectual landscape in profound ways, fostering collaboration and innovation on an unprecedented scale. What do you think would have been the most significant impact?

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

### Feedback:

**Insightfulness:**  
The response provides a creative exploration of how the Internet might have impacted the Renaissance period. Some original ideas are presented, such as artists sharing their work online and the democratization of knowledge. However, while these ideas are interesting, they aren't particularly surprising or challenging to conceive. The response could have included more unexpected or groundbreaking perspectives on how the Internet might have reshaped society's structures and functions during that time.

**Score:** 4

**Commonsense Understanding:**  
The response demonstrates a solid understanding of world concepts and effectively integrates the historical context of the Renaissance with the imagined scenario of having the Internet during that time. It appropriately addresses potential cultural, intellectual, and societal changes, showcasing an accurate interpretation of how such a development might have played out. There are no significant errors in comprehension.

**Score:** 5

**Completeness:**  
The response is relatively thorough, offering several examples and ideas about how the Internet might have influenced different aspects of Renaissance life. However, it lacks some depth and detail when compared to the ground truth answer. For instance, it doesn't delve into specifics about the impact on the printing press, economy, or privacy issues. Including these aspects could have provided a more comprehensive and nuanced view.

**Score:** 3

### Scores:

```python
{
    "Insightfulness": 4,
    "Commonsense Understanding": 5,
    "Completeness": 3
}
```

System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Insightfulness: Is the response creative, original or novel, including new perspectives or interpretations of existing information?
Score 1: The response is overly simplistic, lacking any originality or novelty.
Score 2: The ideas or perspectives within the response are commonplace, demonstrating a lack of originality or novelty.
Score 3: Some may perceive the response as original and novel, but others may find it ordinary or uninspiring.
Score 4: The response includes some innovative perspectives or ideas that require thoughtful consideration, yet they aren't particularly surprising.
Score 5: The response is infused with surprisingly creative perspectives or ideas that are challenging to conceive, showcasing significant originality and novelty.
Commonsense Understanding: Is the model accurately interpreting world concepts for instructions that require a simulation of the expected result or necessitate commonsense or spatial reasoning?
Score 1: The model completely misinterprets world concepts or misunderstands commonsense knowledge.
Score 2: The model misinterprets crucial world concepts, potentially leading to misinformation.
Score 3: The model shows a few errors in its understanding of world concepts.
Score 4: A single, minor error exists in the model's comprehension of world concepts.
Score 5: The model accurately interprets world concepts without any errors.
Comprehension: Does the response fulfill the requirements of the instruction by providing relevant information especially when the instruction is complex and includes multiple requirements? This includes responding in accordance with the explicit and implicit purpose of given instruction.
Score 1: The response is completely unrelated to the instruction, or the model entirely misunderstands the instruction.
Score 2: Most of the key points in the response are irrelevant to the instruction, and the response misses major requirements of the instruction.
Score 3: Some major points in the response contain irrelevant information or miss some requirements of the instruction.
Score 4: The response is relevant to the instruction but misses minor requirements of the instruction.
Score 5: The response is perfectly relevant to the instruction, and the model fulfills all of the requirements of the instruction.
[Instruction]
What if the Aztecs had successfully repelled the Spanish conquistadors?

[Ground truth Answer]
If the Aztecs had successfully repelled the Spanish conquistadors, the course of history in Mesoamerica would be quite different. Here are a few possible outcomes:

1. Aztec Empire's Continuation: The Aztec Empire would have continued to exist, ruling over a vast territory in what is now Mexico. Their cultural, religious, and social practices would have continued to evolve over time, perhaps even incorporating aspects of European culture and technology.

2. Delayed colonization: Although initial attempts at invasion by the Spanish would have been unsuccessful, other European powers might eventually try to colonize or trade with Mesoamerica. This could lead to a more gradual process of colonization and cultural exchange, perhaps allowing for a greater preservation of indigenous cultures and societies.

3. Technological advancements: The repulsion of the conquistadors might have exposed the Aztecs to new technologies, which they could have adopted and adapted to their needs, potentially leading to advancements in agriculture, architecture, and warfare.

4. Rise of rival indigenous powers: With the Aztecs maintaining their dominance, other indigenous cultures, such as the Tarascan and Tlaxcalan, might have continued to vie for power and influence in the region, resulting in conflicts and alliances that could generate a different political landscape.

5. Greater resistance to European diseases: In the historical timeline, European diseases such as smallpox decimated the Indigenous population. If the Aztecs repelled the Spanish, they may have been able to develop immunity to these diseases over time, reducing the overall impact on their population.

6. Alternative power balance: The extended existence of the Aztec Empire could have implications for geopolitical balances in the Americas. The Inca Empire to the south could have formed alliances with the Aztecs, creating a power dynamic distinct from the Spanish-dominated historical timeline.

7. Preservation of native culture and knowledge: A stronger and more autonomous Aztec Empire would have likely resulted in the preservation of native knowledge, art, and religious practices, which were largely lost to history during the Spanish colonization. This preservation of culture would have led to a rich and diverse historical and anthropological record of Mesoamerican indigenous civilizations.

While we cannot predict the exact outcomes, the successful repulsion of Spanish conquistadors by the Aztecs would have led to an alternate course of history for Mesoamerica, with distinct political, cultural, and social consequences.

[Assistant's Response]
Speculating on a scenario where the Aztecs successfully repelled the Spanish conquistadors opens up a fascinating array of possibilities regarding cultural, political, and social dynamics. Here are some potential outcomes:

1. **Preservation of Aztec Culture**: A successful defense could have allowed the Aztec culture, religion, and social structures to remain intact for a longer period. This might have led to the continuation and further development of their architectural, artistic, and scientific achievements.

2. **Regional Power Dynamics**: The Aztecs could have maintained their dominance in Mesoamerica, potentially expanding their influence over neighboring tribes and cultures. This might have resulted in a more unified region under Aztec leadership, altering the political landscape significantly.

3. **Delayed European Colonization**: If the Aztecs had successfully repelled the Spanish, it might have delayed further European colonization attempts in the area. Other European powers, witnessing the failure of the Spanish, might have approached the region with more caution or sought alliances with the Aztecs.

4. **Economic and Technological Exchange**: Should the Aztecs have repelled the Spanish but later engaged in trade or diplomatic relations, there could have been a unique cultural and technological exchange. This might have allowed the Aztecs to adopt certain European technologies while preserving their cultural identity.

5. **Impact on Indigenous Populations**: The survival of the Aztec Empire could have provided a buffer for other indigenous groups against European colonization, potentially preserving a greater diversity of indigenous cultures and languages in the region.

6. **Global Historical Impact**: The failure of the Spanish conquest could have had significant ripple effects throughout the Spanish Empire and Europe, possibly leading to shifts in colonial strategies, economic focus, and geopolitical alliances.

7. **Internal Challenges**: Despite successfully repelling the Spanish, the Aztecs would still face internal challenges, such as managing their tributary states and addressing social inequalities. These issues could influence the stability and longevity of the Aztec Empire.

In summary, while a successful repulsion of the Spanish could have led to a more prolonged existence of the Aztec Empire, many variables would influence the trajectory of this alternate history. The interactions between indigenous peoples and European powers would likely have continued to evolve in complex and unpredictable ways.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant:

**Insightfulness**: The assistant provides a response that is mostly similar to the ground truth answer. The ideas presented are plausible and relevant, such as the preservation of culture, delayed colonization, and changes in regional power dynamics. However, the response does not introduce any highly original or surprising perspectives beyond what might be commonly expected in alternate history scenarios. The assistant touches upon well-considered outcomes, offering a thoughtful reflection on potential impacts like internal challenges and global historical effects, though it's more of an inclusive overview rather than novel insight.

**Score**: 4

**Commonsense Understanding**: The assistant demonstrates a strong understanding of world concepts pertinent to the historical scenario. The response appropriately considers the implications of repelling the Spanish on cultural preservation, colonial dynamics, and internal challenges within the Aztec Empire. The assistant navigates the complexity of the situation without errors, suggesting a solid grasp of historical context and human societal dynamics.

**Score**: 5

**Comprehension**: The response thoroughly addresses the instruction by exploring various dimensions of the hypothetical scenario where the Aztecs successfully repel the Spanish conquistadors. The assistant provides relevant outcomes that align with the instruction's implicit goal of understanding alternate historical impacts. The response is cohesive, ticking off the key areas of cultural, political, and social ramifications as requested by the instruction, without missing any significant aspects.

**Score**: 5

```python
{
    "Insightfulness": 4,
    "Commonsense Understanding": 5,
    "Comprehension": 5
}
```

i'm studying mba i need to do a live project (research) on management research methodology subject our topic is "Enhancing shopping experience and Purchase decisions Through Virtual Fitting Rooms: The Impact of AR and VR in Retail" i'll be uploading the data here whatever i get on this topic u comprehensively giv eme the final output by adding any relevant data * Corresponding author: Joy Onma Enyejo
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0.
Effect of Augmented Reality (AR) and Virtual Reality (VR) experiences on customer
engagement and purchase behavior in retail stores
Joy Onma Enyejo 1, *, Omotoyosi Qazeem Obani 2, Olusegun Afolabi 3, Emmanuel Igba 4 and Akan Ime Ibokette 5
1 Department of Business Administration, Nasarawa State University, Keffi. Nasarawa State. Nigeria.
2 School of Management, Yale University, New Haven, CT, United State of America.
3 Department of Information Systems and Business School, Aston University, Birmingham, UK.
4 Department of Human Resource, Secretary to the Commission, National Broadcasting Commission Headquarters, AsoVilla, Abuja, Nigeria.
5 Institute of Engineering, Technology and Innovation Management, University Of Port Harcourt, Port Harcourt, Nigeria.
Magna Scientia Advanced Research and Reviews, 2024, 11(02), 132–150
Publication history: Received on 06 June 2024; revised on 19 July 2024; accepted on 22 July 2024
Article DOI: https://doi.org/10.30574/msarr.2024.11.2.0116
Abstract
This review paper explores the impact of Augmented Reality (AR) and Virtual Reality (VR) technologies on customer
engagement and purchasing behavior in retail settings. As immersive technologies continue to evolve, AR and VR are
increasingly employed to enhance the shopping experience, offering interactive and personalized engagements that
traditional retail cannot match. Through a comprehensive analysis of recent literature, the paper highlights how AR
applications, such as virtual try-ons and interactive product displays, significantly enhance customer engagement by
providing novel and enriched shopping experiences. Similarly, VR facilitates virtual store visits and immersive product
interactions, leading to higher levels of customer satisfaction and brand loyalty. The paper discusses key metrics for
evaluating engagement and purchase behavior changes, including increased dwell time, higher conversion rates, and
enhanced customer satisfaction. Additionally, the review identifies challenges, such as technological integration and
user adaptation, which may impede the full potential of AR and VR in retail. The findings underscore the transformative
potential of AR and VR in reshaping the retail landscape by bridging the gap between digital and physical shopping
environments, thus driving more informed purchasing decisions and fostering deeper customer connections. Future
research directions are suggested to address the limitations and further investigate the long-term impacts of these
technologies on consumer behavior.
Keywords: Augmented Reality (AR); Virtual Reality (VR); Customer engagement; Purchase behavior; Retail;
Immersive technologies; Consumer experience; Interactive shopping; Digital transformation
1. Introduction
The retail industry is undergoing a significant transformation driven by the integration of AR and VR technologies,
reshaping customer engagement and purchase behavior (Pantano & Vannucci, 2019). These immersive technologies
offer interactive, personalized experiences that enhance consumer interaction with products and brands, providing a
competitive edge for retailers (Javornik & Pantano, 2021). AR enhances in-store experiences through virtual try-ons
and interactive displays, while VR enables virtual store visits and product simulations, bridging the gap between digital
and physical shopping environments (Bogicevic., et al., 2019). As retail evolves towards a more digitally enriched
landscape, understanding the influence of AR and VR on consumer behavior is crucial for leveraging these technologies
to drive engagement and sales (Ijiga., et al., 2024). This review synthesizes current research to explore the
transformative potential and challenges of AR and VR in retail.
Magna Scientia Advanced Research and Reviews, 2024, 11(02), 132–150
133
Objectives
The primary objective of this review is to evaluate the impact of AR and VR on customer engagement and purchase
behavior within retail environments (Kang et al., 2020) as represented in figure 1. This review aims to synthesize
existing research to understand how these technologies enhance consumer interaction and affect purchasing decisions.
By examining AR's role in providing interactive product experiences and VR's ability to offer immersive store
environments, the paper seeks to identify the specific mechanisms through which these technologies influence
consumer behavior (Loureiro et al., 2020). Additionally, the review addresses the challenges retailers face in integrating
AR and VR, including technological and user adaptation barriers, and discusses strategies for effective implementation
(Hilken et al., 2017). This comprehensive analysis aims to provide insights for retailers looking to leverage AR and VR
to enhance customer engagement and drive sales (Ijiga., et al., 2024).
Figure 1 provides a visual representation of these objectives, illustrating how they interconnect to form a
comprehensive framework for understanding the impact of AR and VR on the retail sector. Each objective is crucial for
analyzing different aspects of consumer behavior and technological effectiveness, contributing to a holistic view of AR
and VR applications in retail.
 Enhance Customer Engagement: This objective focuses on understanding how AR and VR technologies
improve customer interaction, engagement levels, and emotional connections with retail environments. It aims
to explore how immersive experiences can captivate customers, making their shopping experience more
interactive and enjoyable.
 Analyze Psychological Responses: This objective examines the cognitive and emotional reactions of
consumers when interacting with AR and VR applications in retail. It looks into how these technologies
influence consumer perceptions, attitudes, and decision-making processes.
 Influence on Purchase Behavior: This objective investigates how AR and VR technologies impact consumer
purchasing decisions. It seeks to determine whether these technologies can increase conversion rates, average
transaction values, and overall sales by providing compelling virtual experiences.
 Evaluate Effectiveness: This objective assesses the overall effectiveness of AR and VR implementations in
retail. It aims to measure how well these technologies meet their intended goals, enhance the customer journey,
and provide a return on investment for retailers.
Figure 1 Objectives of Research on AR/VR in Retail
2. Methodology
The review employs a comprehensive literature analysis to evaluate the effects of AR and VR on customer engagement
and purchasing behavior in retail as presented in table 1. Selection criteria for sources included peer-reviewed articles
published in high-ranking journals, focusing on studies that examine AR and VR applications in retail settings (Lee et
al., 2021). Databases such as Google Scholar and ScienceDirect were utilized to collect relevant literature. The analysis
encompasses recent empirical studies and theoretical frameworks, ensuring a broad perspective on AR and VR's
influence in retail contexts (Chen, R., et al., 2022). The review synthesizes findings on how these technologies alter
consumer experiences, employing qualitative and quantitative data to highlight key trends and outcomes. This approach
Magna Scientia Advanced Research and Reviews, 2024, 11(02), 132–150
134
enables a comprehensive understanding of AR and VR's transformative potential in retail, integrating diverse
viewpoints and methodologies (Flavián et al., 2019).
2.1. Organization of the Paper
The paper is organized to comprehensively explore the impact of AR and VR on customer engagement and purchase
behavior in retail settings. It begins with an introduction to AR and VR technologies in retail, followed by a review of
literature focusing on their effects on customer engagement and purchase behavior. The subsequent sections delve into
the psychological and behavioral responses elicited by AR and VR experiences, metrics for measuring engagement
effectiveness, and their influence on purchase behavior and conversion rates. The paper also addresses challenges and
limitations, including technological barriers and user adoption issues. A summary of findings synthesizes the key
insights gleaned from the literature review, followed by implications for retailers aiming to integrate AR and VR into
their strategies. Finally, directions for future research highlight critical areas for further exploration to enhance
understanding and optimize the implementation of AR and VR technologies in retail environments.
3. AR and VR Technologies in Retail
AR and VR technologies are transforming the retail landscape by providing immersive and interactive shopping
experiences. AR overlays digital information onto the physical world, enhancing the shopping environment through
applications like virtual try-ons and interactive displays (Chen, R., et al., 2022). This technology allows customers to
visualize products in a real-world context, improving product evaluation and decision-making processes (Ijiga., et al.,
2024). VR, on the other hand, creates entirely virtual environments that simulate real-life store experiences, allowing
consumers to explore products and spaces in a highly immersive way (Bonetti et al., 2018). These technologies offer
retailers opportunities to enhance consumer engagement by providing more personalized and engaging shopping
experiences (Idoko., et al., 2024). Current trends indicate a growing integration of AR and VR in both online and offline
retail settings, driven by advancements in mobile technology and increasing consumer demand for innovative shopping
experiences (Poushneh & Vasquez-Parraga, 2017).
3.1. Definitions and Concepts
AR and VR represent distinct yet complementary technologies revolutionizing the retail sector. AR enhances physical
environments by overlaying digital information such as images, sounds, and other sensory enhancements, allowing for
interactive and enriched consumer experiences (Flavián et al., 2021). This technology can integrate virtual elements
with real-world views through devices like smartphones and AR glasses. VR, by contrast, immerses users in entirely
virtual environments, created and navigated through headsets and controllers, which can simulate real-world or
fantastical settings for immersive exploration and interaction (Wedel & Pieters, 2020). These technologies are
redefining how consumers perceive and interact with retail products and environments, offering unprecedented levels
of engagement and personalization (Liao et al., 2020). Understanding these foundational concepts is crucial for
assessing their impact on consumer behavior and the evolving retail landscape.
Figure 2 depicts a hand holding a smartphone in a grocery store aisle. The phone screen shows an (AR) view, overlaying
digital information onto the real-world aisle, suggesting a more interactive shopping experience. This highlights the use
of AR technology to enhance grocery shopping by providing additional information, navigation, or promotions directly
on the screen, blending the digital and physical shopping environments seamlessly.
Magna Scientia Advanced Research and Reviews, 2024, 11(02), 132–150
135
Figure 2 AR Enhances Grocery Shopping Experience (Poplar Studio. 2022)
Figure 3 Virtual Reality: Revolutionizing the Shopping Mall Experience
Figure 3 depicts a bustling modern shopping mall where visitors are using virtual reality (VR) headsets. Several
individuals are seated at tables with digital interfaces, immersed in VR experiences, while others walk around the mall
engaging with various stores. The setting highlights the integration of VR technology in enhancing the shopping
experience, offering interactive and immersive ways to explore products and services. The mall's design and the
people’s activities suggest a seamless blend of traditional retail and cutting-edge technology.
3.2. Current Applications in Retail
In retail, AR and VR are transforming traditional shopping by offering novel applications that enhance consumer
experiences as represented in figure 4. AR enables virtual try-ons, allowing customers to visualize apparel and
accessories on themselves without physical interaction, significantly boosting online and in-store exploratory behavior
(Beck & Crié, 2018). Additionally, AR applications such as interactive product displays and in-store navigation provide
real-time information and engagement, leading to informed purchasing decisions (Kumar, H. 2022). VR, meanwhile,
facilitates immersive virtual store experiences, enabling consumers to navigate digital store environments and interact
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with products as they would in a physical setting (Pizzi et al., 2019). These applications not only enhance customer
engagement but also bridge the gap between online and offline retail experiences, contributing to higher levels of
customer satisfaction and increased sales (Ibokette, et al., 2024).
Figure 4 Current Applications of AR/VR in Retail
Figure 4 visually represents how AR/VR applications are currently used in the retail industry, with the central node
indicating the main topic and branches showing specific applications.
 Virtual Try-Ons: Allow customers to visualize products such as clothing or eyewear on themselves through AR.
 Virtual Storefronts: Provide a fully immersive shopping experience with VR, simulating a store environment.
 In-Store Navigation: Use AR for guiding customers through physical stores with interactive maps and
directions.
 Interactive Product Demos: Employ AR/VR to showcase product features and functionalities interactively.
 Immersive Advertising: Use VR for immersive, experiential advertising campaigns that engage customers
deeply.
Table 1 Methodology Summary for AR/VR in Retail Research
Aspect Description Examples Importance
Research Design Utilizes a systematic literature review
to gather and analyze data from highranking journals and articles on the
impact of AR and VR on retail.
Analyzing qualitative
and quantitative data
from various
sources.
Essential for providing a
comprehensive overview of
current knowledge and
identifying gaps in research.
Data Collection
Methods
Includes gathering information from
databases like Google Scholar and
applying specific criteria for inclusion,
such as peer-reviewed articles, high
relevance, and recent publication dates.
Evaluating articles
for their reliability
and relevance to the
research topic.
Ensures the data is valid,
reliable, and relevant to the
research objectives.
Analysis
Techniques
Involves synthesizing findings from
diverse sources to identify patterns,
trends, and gaps in the existing
literature on AR and VR in retail.
Identifying key
themes and
correlations in the
data.
Crucial for generating
meaningful insights and
understanding the
implications of AR and VR
technologies in retail.
Limitations and
Considerations
Acknowledges potential biases in the
selected literature and the scope
limitations due to focusing on Google
Scholar indexed sources.
Addressing biases
and potential gaps in
the literature.
Provides transparency
regarding the scope and
potential constraints of the
study.
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Table 2 Summary of Technological Evolution and Trends
Aspects Description Examples of
Technological Trends
References (Highranking Journals)
Hardware
Innovations
Overview of advancements in AR/VR
hardware, such as improved processing
power, lightweight designs, and enhanced
user interfaces.
Development of AR
glasses, VR headsets
with eye tracking.
Huang & Liao,
2015; Rauschnabel
& Ro, 2016;
Software
Developments
Discussion on the evolution of AR/VR
software, including improvements in
rendering capabilities, real-time data
integration, and AI-driven applications.
AR apps for mobile
devices, VR gaming
platforms.
Pantano &
Priporas, 2016;
Bonetti et al., 2018
Integration with
IoT and AI
Analysis of how AR/VR technologies are
increasingly integrated with Internet of
Things (IoT) devices and artificial
intelligence (AI) systems.
Smart retail
environments, AIdriven AR content
creation.
Yim et al., 2017;
Wedel & Kannan,
2016;
Emerging Trends in
AR/VR Applications
Exploration of emerging applications of
AR/VR in various industries beyond retail,
such as healthcare, education, and
entertainment.
Virtual training
simulations, AR in
remote assistance.
Javornik, 2016;
Rese et al., 2014;
3.3. Technological Evolution and Trends
The evolution of AR and VR technologies in retail is marked by significant advancements that enhance the consumer
shopping experience and drive innovation in customer engagement as presented in table 2. Initially, AR applications
focused on simple overlays, but advancements now support sophisticated interactive features, such as real-time product
visualization and virtual try-ons, directly integrated into mobile apps and web platforms (Beck et al., 2021). VR
technology has progressed from basic virtual environments to fully immersive simulations that offer detailed and
interactive virtual store experiences, enhancing consumer immersion and interaction (Weller & Dinnie, 2020). Current
trends indicate a convergence of AR/VR with Artificial Intelligence (AI), allowing for more personalized and predictive
shopping experiences. These integrated systems can analyze consumer behavior and preferences to provide tailored
recommendations and real-time virtual assistance (Javornik et al., 2019). Such innovations are poised to redefine the
retail landscape by creating seamless, engaging, and highly personalized shopping journeys.
4. Impact of AR and VR on Customer Engagement
AR and VR technologies significantly enhance customer engagement by creating immersive and interactive shopping
experiences that surpass traditional retail methods. AR applications, such as virtual try-ons and interactive product
displays, foster a sense of spatial presence and personalization, which positively influence app and brand responses
(Smink et al., 2019). These technologies enable customers to visualize products in their own environment, enhancing
the perceived value and facilitating informed purchase decisions. VR further amplifies engagement by offering fully
immersive environments where consumers can explore products and stores virtually, leading to increased emotional
and psychological engagement (Huang & Liu, 2020). The ability to personalize experiences through AR/VR applications
strengthens consumer-brand relationships, fostering deeper connections and loyalty (Scholz & Duffy, 2018). These
immersive experiences not only captivate consumers but also provide valuable data for retailers to refine their
strategies and enhance overall customer satisfaction and retention.
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Figure 5 Transforming Retail: The Impact of AR/VR on Shopping. (Virtual Reality Pop. n.d. 2024)
Figure 5 captures a retail setting where a woman is using a VR headset while holding several shopping bags,
demonstrating an immersive shopping experience. In the foreground, another individual holds a smartphone displaying
an AR application, which shows a live view of the store with digital enhancements. The text "AR/VR in Shopping"
emphasizes the integration of AR and VR technologies in the shopping environment, illustrating how these
advancements can transform and enhance the way consumers interact with products and the retail space.
Table 3 Summary of Customer Interaction and Experience Enhancement through AR and VR
Aspects Descriptions Examples of Customer
Interaction
Enhancements
References (Highranking Journals)
Personalized
Shopping
Experiences
Exploration of how AR/VR technologies
enable personalized product
demonstrations and virtual try-on
experiences.
Virtual fitting rooms,
customized product
visualization.
Bonetti et al., 2018;
Yim et al., 2017;
Enhanced Product
Information
Discussion on how AR/VR enriches
product information through interactive
overlays, 3D models, and real-time data
integration.
AR-powered product
specifications, immersive
product tours.
Pantano & Priporas,
2016; Wedel &
Kannan,
Engagement with
Virtual
Environments
Analysis of consumer engagement with
virtual environments, including
gamification elements and interactive
storytelling.
VR-based shopping
simulations, interactive
retail environments.
Rauschnabel & Ro,
2016; (Yang, C. J., &
Wu, C. F. 2020).
Emotional and
Sensory
Engagement
Explores how AR/VR enhances
emotional and sensory engagement by
immersing consumers in realistic and
interactive experiences.
Emotional response
analytics, sensory-rich
virtual environments
avornik, 2016; Rese
et al., 2014;
4.1. Customer Interaction and Experience Enhancement
AR and VR technologies significantly elevate customer interaction and experience by enabling more immersive and
interactive shopping processes as presented in table 3. AR applications enhance decision-making by providing vivid and
interactive product information, which caters to consumers’ desire for detailed product knowledge and engagement
(Xia, L., & Monroe, K. B. 2017). By allowing consumers to visualize and manipulate virtual products in their environment,
AR creates a sense of involvement and realism, facilitating deeper interaction with the product and brand (Yim et al.,
2017). VR complements this by offering immersive simulations that replicate or enhance real-world store experiences,
contributing to a more engaging and satisfying shopping journey. These VR environments can recreate the ambiance of
physical stores or offer entirely new interactive spaces, leading to increased emotional engagement and more
memorable shopping experiences (Poncin & Mimoun, 2014). Together, AR and VR enrich the consumer experience,
making it more interactive, informative, and engaging.
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4.2. Metrics for Measuring Engagement
To effectively measure customer engagement facilitated by AR and VR in retail, various metrics are employed to assess
the impact of these technologies on consumer behavior and interaction. Metrics focus on quantifying both qualitative
and quantitative aspects of engagement to provide insights into consumer preferences and satisfaction levels.
Firstly, engagement metrics often include behavioral indicators such as interaction duration, frequency of interactions,
and navigation patterns within AR/VR environments (Yim, Chu, & Sauer, 2017). These metrics help gauge the extent of
consumer involvement and the level of interest generated by AR/VR experiences.
Secondly, emotional response metrics evaluate the affective reactions of consumers during their interaction with AR/VR
content. These metrics measure emotional arousal, valence, and overall sentiment conveyed through physiological
responses or self-reported assessments.
Lastly, metrics assessing cognitive engagement measure the level of cognitive processing and information retention
achieved through AR/VR experiences. This includes metrics like recall accuracy, comprehension of product information,
and decision-making efficiency (Poncin & Mimoun, 2014). Together, these metrics provide a comprehensive evaluation
framework for understanding how AR and VR technologies enhance customer engagement and influence purchasing
behavior in retail settings (Onuh, et al., 2024)
4.3. Psychological and Behavioral Responses
To understand the psychological and behavioral responses elicited by AR and VR in retail environments, it is essential
to explore how these technologies influence consumer perceptions and actions as represented in figure 6.
Consumers often experience heightened sensory engagement and immersion when interacting with AR and VR
applications. AR enhances consumer experiences by overlaying digital information onto the physical world, triggering
sensory perceptions that enhance product evaluation and decision-making processes (Smink et al., 2019). VR, on the
other hand, creates immersive virtual environments that simulate real-world shopping experiences, eliciting emotional
responses and increasing consumer involvement (Huang & Liu, 2020).
These technologies evoke positive affective responses such as excitement, curiosity, and enjoyment, which contribute
to enhanced brand perceptions and customer satisfaction (Scholz & Duffy, 2018). Moreover, AR and VR can influence
consumer behavior by increasing intention to purchase, enhancing brand loyalty, and fostering repeat visits to both
online and physical stores (Yim et al., 2017). By examining these psychological and behavioral responses, retailers can
optimize AR and VR applications to create compelling, emotionally resonant experiences that drive engagement and
ultimately impact purchasing decisions (Idoko, et al., 2024).
Figure 6 clearly shows the key psychological and behavioral responses elicited by AR/VR in retail, aiding in
understanding how these technologies influence customer interactions and behaviors.
 Cognitive Engagement: Engagement with AR/VR impacting attention and memory.
 Emotional Impact: Emotions elicited by AR/VR experiences such as excitement and satisfaction.
 Decision-Making Influence: How AR/VR affects purchase intent and product evaluation.
 Behavioral Changes: Changes in customer behavior like increased brand loyalty or altered in-store behavior.
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Figure 6 Psychological and Behavioral Responses to AR/VR in Retail
5. Influence on Purchase Behavior
To understand the influence of AR and VR on purchase behavior in retail, it is crucial to examine how these technologies
shape consumer decision-making processes and drive sales represented in figure 7.
AR enhances purchase behavior by providing consumers with interactive and informative product experiences,
allowing them to visualize products in real-world contexts and make more informed purchasing decisions (Beck et al.,
2021). This technology improves product understanding and reduces uncertainty, thereby increasing purchase
confidence and conversion rates.
Similarly, VR creates immersive environments where consumers can experience products in a simulated setting, leading
to heightened engagement and emotional connection that positively influence purchase intentions (Weller & Dinnie,
2020). By offering virtual trials and interactive showcases, VR enhances the shopping experience and encourages
impulse buying behaviors (Javornik et al., 2019).
Moreover, the integration of AR and VR with e-commerce platforms bridges the gap between online browsing and
offline purchasing, providing seamless shopping experiences that cater to modern consumer preferences (Yim et al.,
2017). These technologies not only increase consumer engagement but also contribute to higher conversion rates and
overall sales growth in retail environments.
Figure 7 Influence on Purchase Behavior
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Figure 7 shows how AR/VR technologies influence various aspects of purchase behavior, helping retailers understand
and leverage these impacts for better sales and customer satisfaction.
 Enhanced Product Experience: AR/VR enhances how products are experienced, leading to better visualization
and trial opportunities.
 Increased Engagement: These technologies increase customer engagement through interactive and immersive
experiences.
 Improved Decision-Making: Customers gain confidence and better information, improving their decisionmaking process.
 Emotional Connection: Creates a stronger emotional bond with the brand, enhancing customer satisfaction and
loyalty.
5.1. Impact on Consumer Decision Making
The integration of AR and VR in retail significantly influences consumer decision-making processes by enhancing
engagement and facilitating more informed choices as presented in table 4 and figure 8. AR allows consumers to interact
with virtual product models in real-world settings, which boosts confidence in their purchase decisions through
enhanced product visualization and customization (Shankar et al., 2011). VR complements this by offering immersive
simulations that simulate real store environments, enabling consumers to explore and evaluate products in-depth
before making a purchase (Chandon et al., 2009). These technologies not only enhance the shopping experience but also
foster a deeper emotional connection with products, influencing brand perception and purchase intentions positively
(Verhoef et al., 2015). make informed decisions, thereby driving sales and enhancing overall customer satisfaction in
retail settings.
Figure 8 Enhancing Shopping Decisions with Augmented Reality (PYMNTS.,2020)
Figure 8 captures the picture of a person using a tablet to engage in an AR shopping experience. The tablet screen shows
a live view of a retail store, with specific products highlighted and tagged with "Special Price" indicators. This use of AR
technology allows shoppers to make informed decisions by providing real-time information about promotions and
special offers directly within their view of the physical store. The visual overlay helps customers quickly identify deals
and navigate to the desired items, enhancing their shopping efficiency and decision-making process. By integrating AR
into the shopping experience, retailers can attract customers' attention to specific products, thereby influencing
purchasing decisions and enhancing overall customer engagement.
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5.2. Conversion Rates and Sales Impact
AR and VR technologies significantly impact conversion rates and sales in retail environments by enhancing the overall
shopping experience and influencing consumer behavior presented in table 5. AR enables virtual try-ons and interactive
product demonstrations, which reduce purchase hesitancy by providing consumers with realistic previews of products
(Kim & Forsythe, 2008). This capability not only increases conversion rates but also encourages higher-value purchases
as consumers feel more confident in their choices. VR complements this by offering immersive environments that
simulate physical store visits, leading to longer engagement times and heightened emotional connections with products
(Hsiao & Chen, 2016). These experiences translate into increased sales as consumers are more likely to complete
transactions after engaging with products in virtual settings. By leveraging AR and VR technologies, retailers can
effectively drive sales and improve conversion rates by creating compelling and interactive shopping experiences that
resonate with modern consumers.
Table 4 Summary of Impact on Consumer Decision Making
Aspect Description Evidence Implication
Enhanced
Product
Visualization
AR/VR enables detailed,
immersive product views,
allowing consumers to explore
products more deeply.
Studies show increased
confidence and understanding of
products (Pantano et al., 2017;
Yim et al., 2017).
Encourages purchase
decisions by reducing
uncertainty.
Interactive
Experiences
Consumers can interact with
products in virtual
environments, testing features
and functionalities.
Interactive features lead to
greater engagement and product
appeal (Poushneh, 2018; Bonetti
et al., 2018).
Drives consumer
interest and
involvement, fostering
decision making.
Emotional
Engagement
AR/VR experiences evoke strong
emotional responses, influencing
consumers' attachment to
products
Emotional responses correlate
with higher purchase intentions
(Dacko, 2017; Bogicevic et al.,
2019).
Enhances emotional
connection to brands
and products.
Information
Accessibility
Provides immediate, rich
information about products,
including reviews and usage
scenarios.
Increased accessibility to
information supports informed
decisions (Flavián et al., 2019;
Rauschnabel, 2018).
Reduces cognitive load
and facilitates decision
making.
5.3. Long-Term Behavioral Changes
AR and VR technologies have a profound influence on long-term consumer behavior by fostering new shopping habits
and increasing digital engagement represented in figure 9. AR enhances consumer learning by providing immersive
experiences that improve product understanding and retention, leading to more informed purchasing decisions over
time (Li et al., 2003). As consumers become accustomed to interactive and personalized shopping experiences, they
exhibit increased preferences for retailers that offer these technologies, fostering long-term brand loyalty (Pantano &
Timmermans, 2014). Furthermore, VR’s ability to create deeply immersive experiences strengthens emotional bonds
with brands and products, resulting in higher repeat visit rates and long-term engagement (Flavián et al., 2019). These
behavioral shifts reflect a growing demand for engaging and interactive shopping experiences, suggesting that AR and
VR will continue to shape consumer expectations and behavior in the retail industry, driving sustained engagement and
loyalty (Idoko, et al., 2024).
Table 5 Summary of Conversion Rates and Sales Impact of AR and VR in Retail
Aspect Description Examples of Conversion
Rate and Sales Impact
References (Highranking Journals)
Increased
Purchase Intent
Discussion on how AR/VR experiences
influence consumer purchase intent by
providing immersive product demonstrations
and interactive experiences.
Higher conversion rates
post AR/VR trials,
increased purchase
likelihood
Bonetti et al., 2018;
Yim et al., 2017;
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Reduction in
Purchase
Uncertainty
Exploration of how AR/VR reduces purchase
uncertainty by offering virtual try-on and
visualization, thereby enhancing decisionmaking processes.
Decreased product return
rates, reduced hesitation
in purchase decisions
Pantano &
Priporas, 2016;
Wedel & Kannan,
Upselling and
Cross selling
Analysis of how AR/VR facilitates upselling
and cross-selling opportunities through
personalized recommendations and
interactive product comparisons.
Increased average order
value, enhanced product
bundling effectiveness.
Rauschnabel & Ro,
2016;
Long-term
Customer
Engagement
Examination of the impact of AR/VR on
fostering long-term customer engagement and
loyalty through memorable and differentiated
shopping experiences.
Improved customer
retention rates, enhanced
brand loyalty.
Javornik, 2016;
Rese et al., 2014;
Figure 9 helps visualize how AR/VR technologies influence customers' long-term behaviors, leading to benefits for
retailers such as increased brand loyalty, repeat purchases, and word-of-mouth referrals.
 Increased Brand Loyalty: AR/VR experiences foster stronger brand loyalty, leading to higher loyalty program
participation.
 Higher Repeat Purchases: Customers who enjoy AR/VR experiences are more likely to make repeat purchases,
increasing purchase frequency.
 Enhanced Word-of-Mouth Referrals: Satisfied customers who use AR/VR technologies are more likely to refer
others, boosting referral rates.
Figure 9 Long-Term Behavioral Changes
6. Challenges and Limitations
Despite their potential, AR and VR technologies face significant challenges and limitations that affect their adoption and
effectiveness in retail as presented in table 6. One major challenge is the high cost of developing and maintaining AR/VR
applications, which can be a barrier for many retailers (Pantano et al., 2017). Additionally, the need for advanced
hardware and software compatibility can limit consumer access and reduce the overall reach of AR/VR experiences
(McLean & Wilson, 2019). Technical limitations such as poor resolution, latency issues, and limited interactivity can
detract from the user experience, leading to frustration and disengagement (Rauschnabel et al., 2019). Moreover,
privacy concerns and the handling of personal data collected through these technologies pose significant ethical and
regulatory challenges. Addressing these challenges requires ongoing investment in technology development and
infrastructure, as well as careful consideration of user privacy and data security.
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Table 6 Summary of Challenges and Limitations of AR and VR in Retail
Aspects Descriptions Examples of
Challenges and
Limitations
References (Highranking Journals)
Technological and
Implementation
Barriers
Discussion on the financial challenges
associated with adopting AR/VR
technologies in retail, including initial
setup, hardware/software costs, and
maintenance.
High implementation
costs, technological
integration complexities
Pantano &
Priporas, 2016;
Wedel & Kannan,
User Adoption and
Acceptance
Analysis of user acceptance issues and
challenges related to the usability and user
experience of AR/VR applications in retail
settings.
User interface design,
comfort and ease of use
considerations
Rauschnabel & Ro,
2016; (Yang, C. J., &
Wu, C. F. 2020).
Measuring
Effectiveness
Examination of challenges in effectively
measuring the impact and ROI of AR/VR
technologies on customer engagement and
sales in retail.
Metrics for assessing
engagement, difficulties
in ROI calculation
Javornik, 2016;
Rese et al., 2014;
Privacy and Security
Concerns
Exploration of privacy issues and security
risks associated with collecting and storing
consumer data in AR/VR applications used
in retail.
Data Protection
Regulations,
Cybersecurity threats
Bonetti et al., 2018;
Yim et al., 2017;
6.1. Technological and Implementation Barriers
The implementation of AR and VR in retail faces significant technological and practical barriers. A key challenge is the
high cost associated with the development, deployment, and maintenance of AR/VR technologies, which can be
prohibitive for smaller retailers (Yang, C. J., & Wu, C. F. 2020) as presented in table 7. Furthermore, the need for
specialized hardware, such as AR glasses or VR headsets, limits widespread adoption among consumers and requires
substantial investment from retailers (Javornik, 2016). Compatibility issues with existing systems and the need for
continuous updates to software and hardware also present barriers to effective implementation (Rese et al., 2014).
Technical constraints, including poor graphical resolution, latency, and limited interactivity, can detract from the user
experience, causing frustration and reducing the perceived value of these technologies (S, et al., 2024) Addressing these
barriers requires significant technological advancements, investment in infrastructure, and a focus on developing costeffective solutions that enhance accessibility and usability for both retailers and consumers.
6.2. User Adoption and Acceptance
User adoption and acceptance of AR and VR technologies in retail are critical yet challenging aspects influenced by
various factors. Cognitive innovativeness plays a significant role, where users with a high degree of openness to new
experiences are more likely to embrace AR/VR applications (Huang & Liao, 2015). However, the perceived complexity
and usability of these technologies can deter adoption, as users often prefer straightforward and intuitive interfaces
(Rauschnabel & Ro, 2016). Additionally, concerns regarding the privacy and security of personal data collected through
AR/VR platforms may impede user acceptance, necessitating robust privacy measures and clear communication from
retailers (Pantano & Priporas, 2016). Effective adoption strategies should include user education, simplifying the user
interface, and addressing privacy concerns to enhance trust and encourage widespread acceptance. Understanding
these factors is essential for retailers to design AR/VR experiences that align with consumer expectations and drive
engagement.
6.3. Measuring Effectiveness
Evaluating the effectiveness of AR and VR technologies in retail involves analyzing both quantitative and qualitative
metrics to capture their impact on consumer behavior and sales performance as represented in figure 10. Quantitative
metrics, such as conversion rates, time spent interacting with AR/VR applications, and click-through rates, provide
tangible data on consumer engagement and purchase behaviors (Bonetti et al., 2018). Qualitative measures, including
user satisfaction and perceived utility, offer insights into the experiential aspects of AR/VR, which are crucial for
understanding consumer preferences and improving the technology's design (Yim et al., 2017). Advanced marketing
analytics, incorporating machine learning and data mining techniques, further enable the assessment of AR/VR's
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contribution to customer journey optimization and overall business outcomes (Wedel & Kannan, 2016). Effective
measurement requires a combination of these approaches to capture the multifaceted impact of AR/VR technologies on
the retail experience and to inform strategic decisions (Godwin et al., 2024).
Figure 10 helps in understanding the multi-faceted approach needed to measure the effectiveness of AR/VR
technologies in retail, considering customer engagement, conversion rates, sales growth, and customer satisfaction,
along with appropriate evaluation methods and feedback mechanisms.
 Customer Engagement: Measures how effectively AR/VR experiences captivate and involve customers.
 Conversion Rates: Evaluates the proportion of users who make purchases after interacting with AR/VR
technologies.
 Sales Growth: Analyzes the impact of AR/VR on overall sales increase.
 Customer Satisfaction: Assesses the satisfaction levels of customers using AR/VR tools.
Figure 10 Measuring Effectiveness of AR/VR in Retail
Table 7 Summary of Technological and Implementation Barriers in Adopting AR and VR in Retail
Aspect Description Examples of
Technological and
Implementation Barriers
References
(High-ranking
Journals)
High
Implementation
cost.
Discussion on the financial challenges
associated with adopting AR/VR
technologies in retail, including initial
setup, hardware/software costs, and
maintenance.
Investment in AR/VR
hardware, software
development costs
Pantano &
Priporas, 2016;
Wedel & Kannan,
Technological
Integration
Complexity
Exploration of the complexities in
integrating AR/VR with existing retail
systems and infrastructure, such as
compatibility issues and system
synchronization.
Compatibility with legacy
systems, interoperability
challenges
Rauschnabel &
Ro, 2016; Idoko
et al., 2024.
Staff Training and
Skill Development
Analysis of the need for training retail staff
to effectively use AR/VR technologies and
manage customer interactions in virtual
environments.
Training programs for
AR/VR usage, skill
development in immersive
technologies
Javornik, 2016;
Rese et al., 2014;
User Experience
Challenges
Examination of user acceptance issues and
challenges related to the usability and user
experience of AR/VR applications in retail
settings.
User interface design,
comfort and ease of use
considerations
Bonetti et al.,
2018; Yim et al.,
2017;
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7. Future Directions
The integration of AR and VR technologies in retail has demonstrated significant potential to transform consumer
engagement and purchase behaviors. Throughout this paper, we have explored how these technologies enhance
immersive shopping experiences, influence consumer decision-making processes, and potentially drive sales growth.
Despite their promise, challenges such as high implementation costs, technological barriers, and user acceptance issues
remain pertinent.
Looking forward, future research should focus on addressing these challenges through technological advancements,
improved usability, and enhanced privacy measures. Additionally, exploring the long-term effects of AR/VR on
consumer behavior and brand loyalty will provide valuable insights into their sustained impact in retail settings.
Furthermore, integrating advanced analytics and machine learning techniques will enable more robust measurement
of AR/VR effectiveness and optimize their application in enhancing the customer journey.
By overcoming these barriers and leveraging the evolving capabilities of AR and VR, retailers can create compelling and
personalized experiences that resonate with modern consumers, thereby shaping the future of retail towards more
interactive and immersive environments.
7.1. Implications for Retailers
The adoption of AR and VR technologies holds profound implications for retailers aiming to enhance customer
engagement and drive sales. Firstly, integrating AR/VR into retail environments can differentiate brands by offering
unique and immersive shopping experiences that resonate with modern consumers' preferences for interactivity and
personalization. Retailers can leverage these technologies to showcase products in realistic contexts, facilitating better
decision-making and reducing purchase uncertainty.
Moreover, AR/VR can streamline the path to purchase by providing virtual try-on capabilities, interactive product
demonstrations, and personalized recommendations, thereby improving customer satisfaction and loyalty. However, to
fully capitalize on these benefits, retailers must address challenges such as initial investment costs, technological
integration complexities, and ensuring seamless user experiences across different devices.
Strategically, retailers should invest in training staff to utilize AR/VR effectively, collaborate with technology providers
to innovate solutions, and continuously analyze consumer data to optimize AR/VR implementations. By embracing
these technologies thoughtfully and strategically, retailers can not only meet but exceed customer expectations, driving
long-term growth and competitiveness in the evolving retail landscape.
7.2. Directions for Future Research
Future research in the realm of AR and VR in retail should focus on several critical areas to advance understanding and
implementation. Firstly, exploring the long-term effects of AR/VR on consumer behavior and brand loyalty is essential
for assessing sustained impacts beyond initial engagement. Additionally, investigating the optimal design principles and
user interface enhancements can enhance usability and acceptance among diverse consumer segments.
Further studies should delve into the integration of advanced analytics and machine learning techniques to better
measure and predict the effectiveness of AR/VR applications in influencing purchasing decisions and optimizing
customer journeys. Addressing technological barriers, such as improving hardware capabilities and reducing
implementation costs, will also be crucial for broader adoption in retail settings. Moreover, understanding crossplatform compatibility and ensuring data privacy and security in AR/VR deployments are pivotal areas for future
inquiry.
By focusing on these avenues, researchers can contribute to refining strategies for leveraging AR/VR technologies
effectively in retail, enhancing both customer experiences and business outcomes in the dynamic retail landscape.
8. Conclusion
This study demonstrates that (AR) and (VR) significantly enhance customer engagement and influence purchase
behavior in retail stores. The findings reveal that AR/VR technologies create immersive experiences that increase
consumer interaction, satisfaction, and likelihood of purchase. By integrating these technologies, retailers can foster a
more engaging and personalized shopping environment, ultimately driving sales and customer loyalty. This study
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benefits society by highlighting innovative ways to improve the retail experience and offers a foundation for future
research to explore advanced applications of AR/VR, paving the way for even more impactful retail strategies.
Compliance with ethical standards
Disclosure of conflict of interest
No conflict of interest to be disclosed.
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Journal of Retailing and Consumer Services
journal homepage: www.elsevier.com/locate/jretconser
I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line
and off-line exploratory behavior, patronage and purchase intentions
Marie Beckb,⁎
, Dominique Criéa
a IAE Lille School of Management, University of Lille, Department of Marketing, 104 avenue du peuple Belge, 59043 Lille Cedex, France
b University of Lille, Skema Business School, EA 4112 - LSMRC,Department of Marketing, 651 Avenue des Nations Unies, 59100 ROUBAIX, France
ARTICLE INFO
Keywords:
Virtual fitting room
Cross-channel
Curiosity
Intention to patronize
Intention to purchase
ABSTRACT
E-commerce has important advantages compared to traditional shopping (e.g. time, choice, price) but offers
only a partial view of the shopping environment. For example, the lack of physical apprehension is a major
disadvantage of online purchasing. To create a shopping environment close to reality, some companies now
propose Virtual Fitting Rooms (VFR1
) on their websites. This research aims to highlight the effects of an online
VFR on consumer's exploratory behavior and intention to purchase, both online and offline contexts. Results of
two experiments showed that the presence of such a tool significantly increases specific curiosity about the
product, intention to patronize (online and offline) and intention to purchase (online and offline). The latter
effect is mediated through firstly perceptual specific curiosity about the product and then the intention to
patronize.
1. Introduction
In July 2013, retailing today.com published a study which announced that 81% of consumers seek out online before making a
purchase. But the information they can find online is often limited. For
example, they cannot interact with a salesperson or enjoy the atmosphere of a store or smell, touch or try on the product… In line with this
statement, engineers try to minimize the gap between the real store and
the website by developing new sales aids based on new technologies
such as virtual center, virtual agent, virtual fitting room and so on. In
an editorial special issue focused on the impact of these new technologies on retailing, Pantano (2010) insists on the relevance to understand their effects on consumer behavior. Moreover, Pantano and
Naccarato (2010) proposed five research priorities to understand the
effects of these technologies on behavior including need recognition,
search of information, pre-purchase evaluation, purchase, and postpurchase evaluation. In an other way, Ostorm et al. (2010) proposed
similar research priorities for the science of service in particular related
the stimulation of service innovation. Thus, a lot of research has been
developed. The aim of this paper is to highlight and to understand the
effect of such new technologies on exploratory consumer behavior and
more precisely on specific curiosity.
Existing literature on these tools can be presented in two parts. A
major part concerns the research on social new sales aids – such as
virtual agents or avatars – and their effects on pre-purchase, perpurchase and post-purchase/consumption variables. In general, most
research has shown that consumers increase their exploratory behavior
(Swaminathan, 2003), trust (Lemoine and Notebaert, 2011), immersion (Wang et al., 2007), positive emotions (Murray and Häubl, 2008),
purchase intention (Senecal and Nantel, 2004), and satisfaction with
the website (Viot and Bressolles, 2012) in the presence of a social new
sales aid (vs. not). The second part of the research is less developed and
is devoted to the direct effects of environmental new sales aids which
could be assimilated to the design and ambient factors of the atmosphere (Baker, 1986). Such tools as virtual fitting rooms or virtual
centers have significant and positive effects on consumers' intention to
try on and visualize products (Ganapathy et al., 2004), power of
retention of the website (Murray and Häubl, 2008; Häubl and
Figueroa, 2002), flow (Hoffman and Novak, 2009), trust on the product
(Trifts and Häubl, 2003), purchase intention (Li, Daugherty and
Biocca, 2002) and satisfaction (Murray and Häubl, 2008). While the
effect of social new sales aids on exploratory behavior has been
examined (Swaminathan, 2003), the effect of environmental aids on
this dimension of behavior has been largely unexplored. To fill this
theoretical gap, the current research further examines the direct effects
of a Virtual Fitting Room (VFR) on online consumers' exploratory
behavior and the underlying mechanism (Experiment 1).
Moreover, today, 88% of consumers look for information online
http://dx.doi.org/10.1016/j.jretconser.2016.08.006
Received 3 December 2015; Accepted 8 July 2016
⁎ Corresponding author.
E-mail addresses: <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> (M. Beck), <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> (D. Crié). 1 VFR: Virtual Fitting Room.PSC: Perceptual Specific Curiosity.
Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
0969-6989/ © 2016 Elsevier Ltd. All rights reserved.
Available online xxxx
Please cite this article as: Beck, M., Journal of Retailing and Consumer Services (2016), http://dx.doi.org/10.1016/j.jretconser.2016.08.006
before making their purchase offline2 (Digitas Sutdy, Vivaki advance,
2013). Accordingly, we also test the effect of VFR on offline behavior
(Experiment 2).
First, we develop the theoretical background and hypotheses. Then,
the research method and major results are presented, followed by the
general discussion and conclusion.
2. Theoretical background and hypotheses development
In the theoretical framework presented above, exploratory behavior
is measured through the time spent on a product page (Murray and
Häubl, 2008) or the amount of search (Swaminathan, 2003). Theories
on consumer motivation are not addressed yet even if they are essential
to understand the exploratory behavior (Deci and Ryan, 2000). Work
on motivation distinguishes the intrinsic motivation and extrinsic
motivation. Intrinsic motivation is defined as “the inherent tendency
to seek out novelty and challenges, to extend and exercise one's
capacities, to explore, and to learn” (Deci and Ryan, 2000). Extrinsic
motivation is “a construct that pertains whenever an activity is done in
order to attain some outcomes” (Deci and Ryan, 2000). If engineers
develop technical tools, supports for extrinsic motivation, marketing
researchers have to understand the intrinsic motivations of the
consumer. To meet this objective, the variable “curiosity” is mobilized
in this work. Based on the nature and function of environmental new
sales aids, we assume a direct link between these media and the specific
curiosity of the consumer. This idea is developed in the next paragraph.
A link with the intent to patronize and purchase is proposed thereafter.
2.1. Consumers' curiosity as a motivational variable and its link with
virtual fitting rooms
In marketing research, curiosity is defined as a part of the shopping
experience as an affective reaction (e.g., Anderson et al., 2014), a part
of epistemic value (e.g., Davis and Hodges, 2012) or a part of the flow
concept. For example, Huang (2003) considers flow as a multidimensional construct including control, attention, interest and curiosity.
Moreover, Pace (2004) and Agarwal and Karahanna (2000) defined
curiosity as an antecedent of the flow which contributes to decrease the
cognitive charge of an immersive experience.
However, according to psychologists, curiosity is an intrinsic
motivation for consumer (Berlyne, 1954) and seems to be the most
relevant variable to explain the exploratory behavior of consumers
(Berlyne, 1950). Consistent with past research we here distinguished
the specific curiosity from the diversive curiosity or trait curiosity (Ho
and Dempsey, 2010). While the diversive curiosity is an individual
trait, the specific curiosity is a contextual variable defined as “an
intrinsic desire or motivation for new information to stimulate
interest and/or remove uncertainty” (Berlyne, 1954). In an other
way, Koo and Ju (2010) discerned four types of curiosity: interpersonal, epistemic, sensory and perceptual curiosity. The last one is defined
as “the desire that motivates individuals to having interest in and
giving attention to novel perceptual stimulation” (Collins, Litman and
Spielberger, 2004, p. 1130). Based on these definitions, we expect a
link between VFR, as a novel perceptual stimulation, and the concept of
perceptual specific curiosity.
Past research on curiosity identified four so-called collative variables of curiosity (Berlyne, 1954). More a stimulus is perceived as novel
and complex and more it increases uncertainty and generates conflict
with prior information, more consumers develop an exploratory
behavior. There are two ways in which connection can be made
between VFR and antecedents of perceptual specific curiosity. On the
one hand, we can connect them with the nature of VFR. That is, novelty
and complexity directly refer to the intrinsic characteristics of VFR. On
the other hand, functions of VFR are related to uncertainty and
cognitive dissonance. By giving more information about the product
than an e-catalog, VFR can affect uncertainty for example by reducing
the perceived risk (Beck and Crié, 2013) and may increase conflict with
prior information. Thus we expect that specific curiosity could be
increased by environmental new sales aids like VFR. In line with this,
we propose Hypothesis 1.
H1. The presence of a VFR on a website (environmental new sales aid)
increases perceptual specific curiosity about the product.
2.2. The effects of virtual fitting rooms on consumers' patronage
intentions
Literature on the intent to patronize showed that this variable may
be affected by store atmosphere (Kotler, 1973) and services provide by
retailers (Baker et al., 2002). As “e-atmospherics tools” for the store
(Poncin and Ben Mimoun, 2014), new sales aids could affect this
variable. In this way, Bitner, Brown and Meuter (2000) demonstrated
that a social new sales aid such as a virtual agent makes the experience
more favorable and intense and therefore increases the quality of
experience and patronage intention (Hoffman and Novak, 1996).
However, they focused on a social aid. Thus, we suggest that VFR, as
an environmental new sales aid, may also impact patronage intention.
This idea generates two different hypotheses related to the context.
While Hypothesis 2 concerns the online patronage intention,
Hypothesis 3 focuses on offline patronage intention.
H2. The presence of a VFR on a website (environmental new sales aid)
increases the intent to patronize the online retailer.
H3. The presence of a VFR on a website (environmental new sales aid)
increases the intent to patronize the real store.
2.3. The effects of virtual fitting rooms on consumers' purchase
intentions
Research already improves effect of environmental new sales aids
on online purchase intention. For example, Li et al. (2002) showed that
a 3D presentation of products impacts significantly and positively the
online purchase intention.
Clearly, as we try to maximize the knowledge about effects of
environmental new sales aids, we would like to found the same effect
for virtual fitting room. Moreover, no research indicates effects of such
a tool on offline purchase intention in a cross-channel context. This
leads to the following hypotheses.
H4. The presence of a VFR on a website (environmental new sales aid)
increases online purchase intention.
H5. The presence of a VFR on a website (environmental new sales aid)
increases offline purchase intention.
2.4. Hypotheses regarding the mechanism engaged by the presence of
Virtual Fitting Room
To deeply explore the effects of VFR on exploratory behavior, we
choose to understand the underlying mechanism engaged in the
presence of such a tool on a website. First, we know that curiosity is
a determinant of the exploratory behavior (Berlyne, 1950). The more
consumer's specific curiosity is stimulated, the more exploratory
behavior is intense (Swaminathan, 2003). Second, literature showed
that the intent to patronize is a major variable to explain the
exploratory behavior. Based on these two ideas, we expect that the
perceptual specific curiosity about the product may impact positively
the patronage intention. Furthermore, prior results showed the effect of
2 http://www.digitaslbi.com/news/global/m-commerce-social-media-and-roporesearch-online-purchase-offline-lead-retail-trends-according-to-digitaslbis-globalsurvey/.
M. Beck, D. Crié Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
2
patronage intention on purchase intention (e.g., Grewal et al., 2003). In
accordance with these findings, we suppose the indirect effect of the
presence of a VFR on purchase intention through firstly PSC about the
product and then the intent to patronize. As previous, we posit two
Hypotheses. H6 concerns the online process and H7 focuses crosschannel process.
H6. PSC about the product and intention to patronize the website
mediate in serial the effect of the presence of a VFR on online purchase
intention.
H7. PSC about the product and intention to patronize the real store
mediate in serial the effect of the presence of a VFR on offline purchase
intention.
To determine the impact of VFR we proposed five hypotheses
related to the efficacy and two hypotheses related to the underlying
mechanism. In order to test these hypotheses, two quantitative studies
were performed. First, we tested the effect of a VFR vs. an e-catalog on
online behavior. Second, we tested the effect of another VFR vs.
another e-catalog on offline exploratory behavior, patronage and
purchase intentions.
3. Experiment 1: the influence of VFR on online consumers'
behavior
We suspect that the presence of VFR may increase the perceptual
specific curiosity about the product, online patronage intention and
online purchase intention (respectively H1, H2, and H3). We also
suppose that perceptual specific curiosity and patronage intention
mediate the effect of VFR on online purchase intention (H6).
3.1. Design and procedure
228 young people (35.1% male, Mage=21 years) of European
University were randomly assigned to one of the two versions of the
website. The website had either an e-catalog (n=104) or a VFR
(consisting in a “magic mirror” based on augmented reality) (n=124)
which presented the same models of clothes. An overview is available in
Appendix A. After exploring the website, all participants were asked to
complete the questionnaire. Their perceptual specific curiosity was
measured using Menon and Soman scale (2002) with a 7-point Likert
scales ranging from strongly disagree (1) to strongly agree (7). We here
distinguished perceptual specific curiosity (PSC) about the tool
(Cronbach's α=.854) and PSC about the product (α=.845). While we
focused on the specific curiosity about the product, the specific
curiosity about the tool has been checked. Their online patronage
intention was measured using Baker, Levy and Grewal scale (Baker
et al., 1992) (α=.918) and their online purchase intention was
measured using Dodds, Monroe and Grewal scale (Dodds et al.,1991)
(α=.921) with a 7-point Likert scales ranging from strongly disagree (1)
to strongly agree (7). Participation was voluntary. Respondents were
involved in a lottery to compensate for their participation. The study
was conducted online during one month through Qualtrics software.
3.2. Confound and manipulation checks
In addition, the questionnaire included three confound checks
questions related to the consumer characteristics which are relevant
to understand effects of shopping aids (Chang and Burke, 2007). We
therefore measured diversive curiosity (Menon and Soman, 2002)
(αexploration=.677; αuncertainty=.6433
) which could impact specific
curiosity (Beck and Crié, 2014), involvement (Lumpkin, 1985)
(α=.876) which could affect visual attention and product choice
(Behe et al., 2015) and expertise (Aurier and N’Gobo, 1999)
(α=.820). Results of t-tests performed revealed non-significant differences between the two groups on exploration dimension of diversive
curiosity (t=−.564; p=.574), uncertainty dimension of diversive curiosity (t=−1.480; p=.142), involvement (t=−.205; p=.839), and expertise (t=−.480; p=.632). The questionnaire also included manipulation
checks. All participants were unfamiliar with the brand presented and
with the stimuli (Do you know this brand? Have you ever used a
Virtual Fitting Room?).
After analyzing the reliability and validity of the initial measurement scales, we tested the research hypotheses using MANCOVA and
mediation tests.
3.3. Findings and discussion
Because the correlations between the three dependent variables
were significant, a MANCOVA (Multivariate Analysis of Covariance)
seems to be the most adequate data analysis method to test hypotheses
regarding the effect a VFR on perceptual specific curiosity (H1), online
patronage intention (H2) and online purchase intention (H4)(Table 1).
Full conditions of use for MANCOVA are met (Appendix B). The trait
variables like diversive curiosity, involvement and expertise are controlled.
Results showed significant and positive effect of the presence and
usage of an online VFR on perceptual specific curiosity about the
product (D=7.127; p < .01). In the presence of VFR (vs. not), consumers are more curious about the product (Mcuriosity_VFR=3.92 >
Mcuriosity_ecatalogue=3.76). Thus, H1 is validated. The difference between
e-catalog and VFR is also significant on online patronage intention
(D=2.631; p < .05). As shown in Fig. 1, in the presence of VFR the
online patronage intention is higher (Mpatronage_VFR=3.87) than that for
the absence of VFR (Mpatronage_ecatalogue=4.28) in support H2. The
results for online purchase intention revealed a similar pattern.
Specifically, there was a significant difference between the e-catalog
and VFR experience (D=6.975; p < .01), while the VFR was more likely
to generate online purchase intention than e-catalog
(Mpurchase_VFR=3.27 vs. Mpurchase_ecatalogue=3.37). This result support
H3.
Furthermore, to highlight the mechanism engaged we used mediation test in SPSS 21. As suggested by Preacher and Hayes (2004) we
tested the mediation effects by using the model 6 of the macro
PROCESS. 5000 bootstrap resamples are used to estimate bootstrap
results with a 95% level of confidence. Perceptual specific curiosity
about the VFR, diversive curiosity, involvement and expertise are
controlled.
Results revealed significant indirect effects in serial
(BootLLCI=.056; BootULCI=.363). The direct effect is non significant
(t=−.813; p=.418). Therefore, the impact of the presence of a VFR on
online purchase intention is totally mediated by first specific curiosity
about the product and then online patronage intention (a1=1.124, p
< .01; a2=.370, p < .01; b=.429, p < .01). Thus, H6 is validated. By
increasing curiosity about the product, VFR indirectly increases online
patronage and purchase intentions.
Table 1
Effects of VFR on online behavior.
MANCOVA Eta2 R2 adjusted
D p value
PSC about the product 7.127 .000 .286 .245
Online patronage intention 2.631 .020 .129 .080
Online purchase intention 6.975 .000 .281 .241
3 A factor with four or more loadings greater than 0.6 “is reliable regardless of sample
size.” (Field, 2009, p.647).
M. Beck, D. Crié Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
3
Despite the relevance of these results, one of the major limitations
cannot be ignored. In 2013, 88% of consumer around the world
Research Online and Purchase Offline. This is named the ROPO
behavior. Accordingly, the next experiment tests the effect of VFR on
offline behavior.
4. Experiment 2: the influence of VFR on offline consumers'
behavior
Experiment 2 tests Hypotheses H1, H3 and H5, which suppose the
positive effect of VFR on perceptual specific curiosity, offline patronage
intention and offline purchase intention. We also test the mechanism
engaged related to H7.
4.1. Design and procedure
241 consumers (28.8% male, Mage=33 years) were randomly
assigned to one of the two versions of the website. The website had
either an e-catalog (n=108) or a VFR (n=133) which presented same
models of eyeglasses (Appendix A). After exploring the website, all
participants were asked to complete the questionnaire. Like in the
Experiment 1, perceptual specific curiosity was measured using Menon
and Soman scale (2002) (αabout_tool=.860; αabout_product=.873);
offline patronage intention was measured using Baker, Levy and
Grewal scale (1992) (α=.866) and offline purchase intention was
measured using Dodds, Monroe et Grewal scale (1991) (α=.903). All
three scales were measured on a 7-point Likert scale ranging from
strongly disagree (1) to strongly agree (7). Participation was voluntary.
Respondents were involved in a lottery to compensate for their
participation. The study was conducted online during two months.
4.2. Confound and manipulation checks
In addition, questionnaire included four confound checks questions
related to the diversive curiosity (Menon and Soman, 2002)
(αexploration=.756; αuncertainty=.791), involvement (Zaichkowsky,
1994) (αcognitive=.778; αaffective=.710) and expertise (Aurier and
N’Gobo, 1999) (α=.920). Results of t-tests performed revealed nonsignificant differences between the two groups on exploration dimension of diversive curiosity (t=−1.247; p=.217), uncertainty dimension
of diversive curiosity (t=−.513; p=.610), cognitive involvement
(t=−.698; p=.488), affective involvement (t=−.261; p=.795) and expertise (t=−.178; p=.859). The questionnaire also included manipulation check. All participants were unfamiliar with the stimuli (Have you
ever used a Virtual Fitting Room?).
As in Experiment 1, after analyzing the reliability and validity of the
initial measurement scales, we tested the research hypotheses using
MANCOVA and mediation tests.
4.3. Results and discussion
The results of the MANCOVA showed significant and positive
effects of the presence and usage of a VFR on a website on perceptual
specific curiosity about the product (D=19.947; p < .01), offline patronage intention (D=10.801; p < .01) and offline purchase intention
(D=80.262; p < .01), in accordance with Hypotheses H1, H3 and H5
(Table 2). As shown in Fig. 2, PSC about the product of consumers is
more important in the presence of VFR (Mcuriosity_VFR=4.279 >
Mcuriosity_ecatalogue=3.974) and consumers are more likely to patronize
the real store (Mpatronage_VFR=3.018 > Mpatronage_ecatalogue=2.144) and
to purchase in the real store (Mpurchase_VFR=4.329 >
Mpurchase_ecatalogue=2.973).
We ran a mediation test (model 6 of the macro PROCESS in SPSS
21) in order to highlight the underlying mechanism. 5000 bootstrap
resamples are used to estimate bootstrap results with a 95% level of
confidence. Results revealed that indirect effects in serial are significant
(BootLLCI=.000; BootULCI=.065). The direct effect is also significant
(p=.000). Therefore, the impact of the presence of a VFR on offline
purchase intention is partially mediated by first specific curiosity about
the product and then offline patronage intention (a1=.404, p < .10;
a2=.245, p < .01; b=.219, p < .01). Thus, H7 is partially validated.
Experiment 2 provides further support for the hypothesized effects
of VFR on exploratory behavior and purchase intention. Results precise
effects of VFR on curiosity and showed significant effects for crosschannel patronage and purchase intentions.
5. General discussion and conclusion
5.1. Summary of main findings
The results of present experiments show the influence of online
VFR on consumers' online and offline exploratory behavior and
purchase intentions. The results also highlight the mechanism engaged
Table 2
Effects of VFR on offline behavior.
MANCOVA Eta2 R2 adjusted
D p value
PSC about the product 19.947 .000 .253 .240
Offline patronage intention 10.801 .000 .155 .140
Offline purchase intention 80.262 .000 .576 .569
Fig. 1. Results of MANCOVA Experiment 1.
M. Beck, D. Crié Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
4
in the presence of VFR such as in the following figure (Fig. 3).
Experiment 1 revealed that the presence of a VFR on a website
increases significantly the perceptual specific curiosity about the
product, the online patronage intention and the online purchase
intention (versus an e-catalog). Consumers are more likely to buy a
product when there is a VFR on a website. These findings support H1,
H2 and H4.
Experiment 2 demonstrates that when there is a VFR on a website,
the perceptual specific curiosity, the offline patronage and purchase
intentions are significantly and positively impacted, in accordance with
H1, H3 and H5. In accordance with Arnone et al. (2011), Smith and
Swinyard (1988) and Kaltcheva et al. (2011) we can said that VFR
increases perceptual specific curiosity and so increases the desire that
motivates consumers to having interest in and giving attention to the
product. This idea could be explain by the four so-called collative
variables of curiosity as defined by Berlyne (1954) and explained above.
More a stimulus is perceived as novel and complex and more it reduces
uncertainty and increases cognitive dissonance more the perceptual
specific curiosity about the product is increased.
The mediation tests showed that when there is a VFR on a website,
consumers are more curious about the product and so are more likely
to patronize the website and the real store, and then are more likely to
purchase the product online or in real store. The validation of this
process in two different contexts (online and offline), for two different
product categories (clothes and eyeglasses) with two different samples
(students and consumers) improve the reliability of the research model.
5.2. Contributions of existing research
The current research has straightforward and substantial implications for the research on marketing based on service innovation as new
sales aids. Using an environmental new sales aid like a VFR on a
website cannot only contribute to help consumers to buy but also
develop an exploratory behavior. In this way, the results complete the
previous literature and enhance the relevance of curiosity as a
motivational variable in marketing. Therefore researchers can develop
new perspectives for research on curiosity in the context of today's
interactive technologies (Arnone et al., 2011). In this way and from a
substantive perspective, the results lend some unique insights into the
link between amount of information and curiosity. Previous research
on curiosity showed that the lack of information about a product
increases the specific curiosity about this product (Peracchio and
Meyers-Levy, 1994) and that curiosity increases information research
(Raju, 1980; Richard and Chebat, in press). Based on this idea, VFR
could be thought as a tool which reduces curiosity. In contrast our
results showed that the intake of information by a virtual fitting room
increases specific curiosity about the product. Hence, we can think that
there is an optimal rate of available information to increase the level of
curiosity. Further research are called for.
Then, the results of this research complete previous research which
explain the mechanism through which a stimulus acts by changing
consumers' perceptions. For example, Kim et al. (2007) showed the
mediating effect of online shopping enjoyment and involvement on the
effect of interactive technologies on patronage intention. Moreover,
Dennis et al. (2010) highlight the effect of digital signage on a real store
on positive affect, perception of the store and approach behavior. In
contrast, this research propose to find out the effect of an other
environmental new sales aid on a website, in a cross-channel context,
on different variables which affect approach behavior and purchase
behavior such as curiosity and patronage intention. Thus, the findings
of this research provide more explanation about the underlying
mechanism in the presence of a new sales aid. It completes the
Fig. 3. Underlying behavior mechanism in online and offline contexts.
Fig. 2. Results of MANCOVA Experiment 2.
M. Beck, D. Crié Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
5
theoretical model by adding a motivational way in addition to affective
and cognitive ways as we find in the persuasive theory.
5.3. Managerial implications
From a managerial point of view, we can consider two types of
implications. Firstly, results of this research provide a better understanding of the effects of a Virtual Fitting Room on consumers'
behavior. This information might be used to adapt a cross or omnichannel marketing strategy (Pantano and Servidio, 2012). For all
products which can be tested in real stores but usually not online
(e.g. apparel or eyeglasses), retailers may adopt environmental aids
such as Virtual Fitting Room to increase the intent to purchase.
However, if the conversion rate of the website is increased, this is
not the only effect. This research also emphasizes the relevance of
considering new sales aids by webstore managers as tools to increase
exploratory behavior. The specific curiosity for the product and the
intent to patronize the brand are generated in both contexts (online
and offline). Thus, VFR can be used to minimize browsing as a support
for loyalty and can transfer the website traffic to the real store.
Secondly, there are some effects for the brand which evolves in a
context where big data is more and more important. Managers can use
all the data generated by the use of VFR. The data can concern first the
product, for example the most tried item, the one which gives the best
conversion rate, the associated information (e.g. color, size, pattern,
combination between products). Then, data can also be consumeroriented. For example, a VFR gives access to the consumers' social
networks profiles. Thereby, the brands can rely on these data to refine
their trigger or retargeting strategies.
5.4. Limitations and need for further research
A note of caution in the interpretation of our results is necessary.
According to the literature, other variables could complete the model
because of their power to explain the intent to purchase. For example,
perceived risk is known to decrease the intent to purchase online
(Forsythe and Shi, 2003), whereas positive affective reactions are
known to increase it (Poncin and Ben Mimoun, 2014). Further
experimental studies are therefore called for. Finally, because curiosity
is increased by the novelty and because the perceived novelty is
temporary, we recommend further research, particularly longitudinal,
to evaluate the effect of VFR on curiosity in line with the adoption
process. We expect that curiosity will decrease when perceived ease of
use increase.
Appendix A
The Virtual Fitting Room used for the first experiment is based on augmented reality technology. Before the experimentation, all permissions
were validated by the researcher. Participants just had to stand in front of the camera and back to 3 or 4 steps. The clothes were automatically
adapted to their body. Consumers can change the size, the color and the product just by moving their hands in the air to virtually touch the key.
The Virtual Fitting Room used for the second experiment is also based on augmented reality technology. Participants just had to stand in front
the camera. Consumers can adjust the size before trying on the glasses. They can change the color and the product using their mouse and they can
take picture to compare products.
Appendix B
Conditions of use for MANCOVA Experiment 1.
Condition 1: Skewness and Kurtosis tests.
Skewness/Standard error ( < 3) Kurtosis/Standard error ( < 3)
Curiosity 1.659 .171
Online patronage intention −.177 −1.425
Online purchase intention .288 −2.263
Condition 2: The covariances matrix is not significant. (M Box Test=12.414, D=2.008, p=.061).
Condition 3: Variances equality.
Variances tests
Levene test Fmax ratio ( < 10)
D p value ( > .05)
Curiosity 9.210 .003 2.213
Online patronage intention .310 .579 1.141
Online purchase intention .157 .693 1.075
Condition 4: Correlation between dependent variables.
Curiosity Online patronage Online purchase
Curiosity 1
Online patronage .331** 1
M. Beck, D. Crié Journal of Retailing and Consumer Services xx (xxxx) xxxx–xxxx
6
Online purchase .189* .500** 1
*p < .05; **p < .01.
Conditions of use for MANCOVA Experiment 2.
Condition 1: Skewness and Kurtosis tests.
Skewness/Standard error ( < 3) Kurtosis / Standard error ( < 3)
Curiosity −1.414 −2.959
Offline patronage intention .483 −1.212
Offline purchase intention −.465 −2.753
Condition 2: The covariances matrix is not significant. (M Box Test=4.596, D=.755, p=.605).
Condition 3: Variances equality.
Variances tests
Levene test Fmax ratio ( < 10)
D p value ( > .05)
Curiosity .180 .672 1.008
Offline patronage intention 7.057 .008 1.271
Offline purchase intention 9.259 .003 1.016
Condition 4: Correlation between dependent variables.
Curiosity Online patronage Online purchase
Curiosity 1
Online patronage .336** 1
Online purchase .476** .395** 1
**p < .01.
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This draft research paper explores the transformative potential and challenges of augmented reality (AR) and virtual reality (VR) technologies in enhancing customer engagement and purchase decisions through virtual fitting rooms (VFRs) in retail. The study evaluates the impact of these immersive technologies within retail environments to highlight how VFRs effectively bridge the gap between digital and physical shopping experiences, influencing consumer behavior and driving sales.

**Abstract**

This paper investigates the transformative role of Augmented Reality (AR) and Virtual Reality (VR) in enhancing shopping experiences and purchase decisions through Virtual Fitting Rooms (VFRs) in retail. As immersive technologies evolve, retailers use AR and VR to offer interactive and personalized experiences, providing a competitive edge. By analyzing recent literature, the study demonstrates that AR/VR adoption significantly improves customer engagement and satisfaction by facilitating virtual try-ons and reducing purchase uncertainty. The research discusses the challenges of integrating these technologies, such as high costs and software compatibility, suggesting that strategic adoption could reshape retail landscapes, foster brand loyalty, and drive sales. Future research should address technological barriers and analyze long-term impacts on consumer behavior.

**Introduction**

The retail sector is undergoing a digital transformation with AR and VR technologies, creating engaging and personalized shopping experiences. These technologies provide retailers with opportunities to enhance consumer interaction through features like virtual try-ons and immersive virtual stores, which blend digital and in-store shopping (Pantano & Vannucci, 2019; Javornik & Pantano, 2021). Understanding the influence of AR and VR on purchase behavior is crucial for leveraging their potential to increase consumer engagement (Ijiga et al., 2024). This study aims to analyze these effects comprehensively, identifying challenges retailers face and proposing effective strategies for implementation.

**Methodology**

The research encompasses a comprehensive review of literature and empirical studies that examine AR and VR applications in retail settings. Selection criteria include peer-reviewed articles from high-ranking journals and databases such as Google Scholar, focusing on AR and VR's transformational potential in retail (Lee et al., 2021). Through qualitative and quantitative data synthesis, this methodology provides insights into AR and VR's impact, integrating diverse viewpoints for a holistic understanding of their influence on consumer behavior (Chen et al., 2022).

**AR and VR in Retail**

AR/VR technologies are reshaping the retail industry, providing immersive shopping experiences through virtual try-ons and virtual store environments (Chen et al., 2022; Bonetti et al., 2018). Enhanced by advancements in mobile technology, AR allows customers to visualize products interactively, while VR facilitates complete immersion in virtual shopping environments, driving engagement and satisfaction (Ijiga et al., 2024). The integration of AR/VR with AI further personalizes shopping experiences, marking a significant trend in retail technology (Wedel & Pieters, 2020).

**Impact on Customer Engagement**

AR and VR elevate customer interactions by offering immersive and personalized trial experiences that increase satisfaction and likelihood of purchase (Smink et al., 2019; Huang & Liu, 2020). These technologies influence consumers' affective responses and enhance brand perceptions, leading to loyalty and sustained engagement (Scholz & Duffy, 2018). Metrics for measuring engagement include increased interaction times, conversion rates, and emotional engagement, providing a framework to evaluate AR/VR effectiveness (Yim et al., 2017).

**Influence on Purchase Behavior**

AR and VR significantly affect purchase decisions by augmenting product exposure and providing an enriched customer journey (Beck et al., 2021; Javornik et al., 2019). These technologies enhance confidence, reduce uncertainty, and foster emotional connections, increasing conversion rates and sales in retail contexts (Yim et al., 2017). Their role in facilitating virtual trials and interactive showcases accelerates informed decision-making, leading to heightened customer satisfaction and loyalty (Scholz & Duffy, 2018).

**Challenges and Limitations**

Despite their potential, AR and VR face challenges, including high implementation costs, technical integration barriers, and privacy concerns (Pantano et al., 2017; Rauschnabel et al., 2019). Overcoming these challenges requires investment in infrastructure, enhancements in software compatibility, and robust privacy measures to ensure widespread adoption and effective use (McLean & Wilson, 2019).

**Future Directions**

Future research should address technological barriers and user adaptation issues to optimize AR/VR's retail application. By exploring long-term effects on consumer behavior and leveraging analytics-driven insights for strategic implementation, retailers can enhance consumer experiences, driving growth and competitiveness in the retail industry (Idoko et al., 2024).

**Conclusion**

AR and VR technologies have transformative potential in retail, enhancing customer engagement and purchase behavior through immersive shopping experiences. Their successful integration can provide competitive advantages, although technological and adoption challenges must be addressed for their full impact to be realized. Ongoing research and innovation will be essential in maximizing AR/VR's role in the future retail landscape.

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This paper provides a comprehensive analysis of the impact of AR and VR on retail, addressing their potential benefits, challenges, and future research directions. The insights gained can help retailers navigate the evolving digital landscape, leveraging AR and VR to enhance customer engagement and drive sales.

give me a comprehensive summary

This research paper delves into the significant impact of Augmented Reality (AR) and Virtual Reality (VR) technologies on enhancing the shopping experience and influencing purchase decisions in retail through Virtual Fitting Rooms (VFRs). As retail moves towards digital integration, AR and VR emerge as powerful tools offering immersive and personalized shopping experiences. These technologies allow consumers to visualize and interact with products virtually, ultimately bridging the gap between digital interfaces and physical shopping environments.

**Key Findings:**

1. **Customer Engagement:**
   - AR and VR technologies significantly boost customer engagement by providing interactive and personalized experiences. AR applications like virtual try-ons enable customers to visualize products in real-world contexts, increasing satisfaction and intention to purchase.
   - VR offers immersive store simulations, enhancing emotional connections and making shopping experiences more enjoyable and memorable.

2. **Influence on Purchase Behavior:**
   - These technologies positively influence purchase decisions by alleviating uncertainties and enhancing confidence in product choices. The immersive nature of AR/VR experiences often translates into higher conversion rates and increased sales.
   - By creating engaging and informative shopping journeys, AR and VR cultivate consumer loyalty and repeated engagement with brands.

3. **Technological and Implementation Challenges:**
   - Despite their potential, AR and VR face hurdles such as high implementation costs, technical barriers like hardware compatibility, and user adaptation challenges. Ensuring seamless integration and widespread adoption requires addressing these issues through technological advancements and usability enhancements.

4. **Future Directions and Research:**
   - Future research should focus on overcoming technological limitations and enhancing the user-friendliness of AR/VR applications. Investigating long-term effects on consumer behavior and establishing robust measures for effectiveness will further optimize their impact in retail.
   - Additionally, integrating advanced analytics for data-driven insights can refine AR/VR strategies, enabling retailers to customize and enhance customer interactions more effectively.

**Implications for Retailers:**

Retailers adopting AR and VR can distinguish themselves by offering unique and engaging shopping experiences that align with contemporary consumer preferences. Implementing these technologies strategically can drive sales, improve customer satisfaction, and foster brand loyalty. However, it requires careful planning, investment in staff training, and collaboration with technology providers to maximize the benefits while addressing potential barriers.

**Conclusion:**

AR and VR technologies represent a transformative force in retail, enhancing shopping experiences and influencing purchase behaviors. By overcoming existing challenges and leveraging technological advancements, retailers can harness these immersive tools to reshape consumer interactions, drive sales growth, and secure a competitive edge in the evolving retail landscape.