Deepika Jhamb, Sukhpreet Kaur, Saurabh Pandey, A. Mittal
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引用次数: 0
摘要
数据科学行业是一个多学科领域,它处理大量数据,并为日常和战略业务决策提供有用的信息。本文的目的是研究定价模型、参与模型和企业绩效(FP)之间的关系。本研究还旨在揭示最有效的定价模式和参与模式,以提高计划生育。设计/方法/方法印度数据科学家是这项研究的受访者。共有213份回答经过精心挑选。采用SPSS-AMOS第25版社会科学统计软件包(Statistical Package for Social Sciences-Analysis of Moment Structures)中的结构方程对数据进行分析。研究结果表明,定价模式和参与模式对计划生育具有显著的正向影响。基于价值的定价策略对FP的影响最大。另一方面,托管服务对FP的影响更大。独创性/价值通过开发一个多方面的框架,本研究对商业战略领域,特别是对数据科学行业,是一个新颖的贡献。
Pricing model, engagement model and firm performance: evidence from Indian data science industry
PurposeData science industry is a multidisciplinary field that deals with a large amount of data and derives useful information for taking routine and strategic business decisions. The purpose of this article is to examine the relationship between pricing models, engagement models, and firm performance (FP). This study also aims at uncovering the most effective pricing model and engagement model for improving FP.Design/methodology/approachIndian data scientists were the respondents of the study. A total of 213 responses were carefully chosen. The data were analyzed using structural equations on Statistical Package for Social Sciences-Analysis of Moment Structures (SPSS-AMOS) version 25 software.FindingsThe findings of the study suggested the positive and significant impact of pricing models and engagement models on FP. Value-based pricing strategies have the maximum impact on FP. On the other hand, managed services have a higher influence on FP.Originality/valueBy developing a multi-faceted framework, this study is a novel contribution to the field of business strategy, especially for the data science industry.
期刊介绍:
Benchmarking is big news for companies committed to total quality programmes. Its enthusiastic reception by many prominent business figures has created high levels of interest in a technique which promises big rewards for co-operating partners. Yet, like total quality itself, it must be understood in its proper context, and implemented single mindedly if it is to be effective - this journal helps companies to decide if benchmarking is right for them, and shows them how to go about it successfully.