Frontline Service Employee Compliance With Customer Special Requests
| Autor: | Jessica Ogilvie, Sijun Wang, Betsy Bugg Holloway, Sharon E. Beatty, William Magnus Northington, Mary P. Harrison |
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| Rok vydání: | 2015 |
| Předmět: |
Service (business)
Organizational Behavior and Human Resource Management Customer retention Sociology and Political Science 05 social sciences Plan (drawing) Compliance (psychology) Customer advocacy 0502 economics and business Customer reference program 050211 marketing Business Marketing Customer to customer 050203 business & management Information Systems |
| Zdroj: | Journal of Service Research. 19:158-173 |
| ISSN: | 1552-7379 1094-6705 |
| DOI: | 10.1177/1094670515624978 |
| Popis: | As companies struggle to deliver excellent service, many find they need to understand and plan for a diverse array of customer requests. Some requests are unexpected and require employees to go beyond their usual job duties. These requests may be classified as special requests. Knowing how and when to comply with these requests is critical to the firm and the employee, given that failing to comply could negatively affect customer satisfaction, while complying may produce unwanted consequences for the firm. We use grounded theory and content analysis of critical incident special requests from frontline employees to develop a framework and classification scheme that categorizes customer special requests and employee assessments of these requests. Customer special requests were classified into four types of customer deficiencies—physical resources, knowledge, financial, and time. Employee assessments were categorized as positive compliance factors (motivations and ability) or deterrents to compliance, including policy or legal, potential risk, and lack of resources. These findings contribute to theory, as they represent the first effort to categorize customer special requests and employee responses to them. Companies need to be better informed about the types of requests employees receive so that employees can make the most appropriate decisions. |
| Databáze: | OpenAIRE |
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