Authors: Arsalan Najmi, Mirza A. Haq, Sohail Majeed, Naveed R. Khan
Title: EFFECTS OF PRODUCT\'S WARRANTY ON CUSTOMERS\' PREFERENCES: EMPIRICAL FINDINGS ON REVERSE LOGISTICS MODELS
Keywords: product warranty, customers\' preferences, brand, price, reverse logistics models.
Background: IT products are now becoming the part of every one's life. Since Pakistan didn't manufacture IT products, so the customers had to purchase the products that are available in the markets. During such purchase, customers not only gave preference to brand or price or both but they also consider its warranty so that they are secured with the post purchase risks.
Methods: This study was aimed to identify the impact of the warranty on customers' preferences towards brand and price. A conceptual framework was made on the basis of available literature and then data was collected. It was collected from 298 respondents through survey questionnaire and after applying Factor Analysis, One Way MANOVA was applied on the factors.
Results and conclusions: The study found that the product's warranty has a significant impact on preferences towards brand, concern for price and price intentions whereas the impact on willingness to pay was found insignificant. The results conclude that Pakistani customers need a branded IT product on competitive prices, which give more in less along with the warranty so that they can enjoy the same quality of the product for a period of time whereas, they are not willing to pay any additional amount for the product just because of Warranty.
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|MLA||Najmi, Arsalan, et al. "Effects of product\'s warranty on customers\' preferences: empirical findings on reverse logistics models." Logforum 10.3 (2014): 7.|
|APA||Arsalan Najmi, Mirza A. Haq, Sohail Majeed, Naveed R. Khan (2014). Effects of product\'s warranty on customers\' preferences: empirical findings on reverse logistics models. Logforum 10 (3), 7.|
|ISO 690||NAJMI, Arsalan, et al. Effects of product\'s warranty on customers\' preferences: empirical findings on reverse logistics models. Logforum, 2014, 10.3: 7.|