The Effect of Organization Change on Stock Returns and Transmission Channels: A Case Study on Goldwind Sci & Tech

Abstract

Abstract: This paper examines the effect and transmission channels of the organization change in Goldwind Sci & Tech on the stock returns by using the event study method and VAR model. First, the empirical results show that the abnormal returns (AR) and the cumulative abnormal returns (CAR) in the short run are not significant, indicating that the organization change has no significant effect on the returns of Goldwind Sci & Tech. Second, and more interestingly, the CAR in the long run is positive and sometimes becomes significant, implying that the organization change has a positive effect on the development of Goldwind Sci & Tech. Particularly, it is reported that the development of Goldwind Sci & Tech is significantly higher than the industry level, indicating the important role of the organization change. Finally, the operating income has a positive effect on AR, and the operating expenditure has a negative effect, indicating that the operating income and expenditure are two important channels affecting the returns.

Key words: organization change, event study, abnormal returns, M-estimate

Li Fei, Lu Fengbin. The Effect of Organization Change on Stock Returns and Transmission Channels: A Case Study on Goldwind Sci & Tech[J]. Management Review, 2021, 33(4): 339-352.

References

[1] Winter S. G. Understanding Dynamic Capabilities[J]. Strategic Management Journal, 2003,24(10):991-995
[2] Marshak R. J. Morphing:The Leading Edge of Organizational Change in the Twenty-first Century[J]. Organization Development Journal, 2004,22(3):8-21
[3] Ozawa K. Managers' Experiences as Rrecipients:Impact on Organizational Change[J]. Journal of Organizational Change Management, 2019,33(1):143-156
[4] Evans T. R. Improving Evidence Quality for Organisational Change Management through Open Science[J]. Journal of Organizational Change Management, 2020,33(2):367-378
[5] 林鲁生. 谈电子商务企业组织结构设计帆[J]. 商业时代, 2009,12(8):100-102
[6] 刘洋,宋加升,罗晓光. 电子商务环境下企业组织模式的变革[J]. 科技与管理, 2002,4(1):22-24
[7] 林新奇,苏伟琳. 组织管理中的反馈:研究现状及管理启示[J]. 管理现代化, 2018,38(3):123-125
[8] 朱方伟,宋昊阳,王鹏. 项目化变革情境下企业如何克服组织惯性的束缚——基于行动研究法的路径与策略分析[J]. 管理评论, 2018,30(8):208-223
[9] 申静,毕煜,云梦妍. 管理咨询公司的开放式创新组织模式[J]. 技术经济, 2019,38(1):56-62
[10] 郑湛,徐绪松,赵伟,等. 面向互联网时代的组织架构、运行机制、运作模式研究[J]. 管理学报, 2019,16(1):45-52
[11] 戴天婧,汤谷良,彭家钧. 企业动态能力提升、组织结构倒置与新型管理控制系统嵌入——基于海尔集团自主经营体探索型案例研究[J]. 中国工业经济, 2012,(2):128-138
[12] 林海芬,苏敬勤. 路径依赖视角下管理创新机理研究——以浙江移动渠道模式创新为例[J]. 技术经济, 2014,33(1):7-13
[13] 白景坤. 组织惰性视角下组织变革对企业持续成长影响研究——以柯达公司历史上的5次重大组织变革为例[J]. 财经问题研究, 2014,(11):120-126
[14] 陈长彬. 电子商务对传统企业组织结构的影响研究——以海尔集团的组织结构变革为例[J]. 工业经济论坛, 2016,3(5):585-595
[15] 王念新,贾昱,葛世伦,等. 企业多层次信息技术与业务匹配的动态性——基于海尔的案例研究[J]. 管理评论, 2016,28(7):261-272
[16] 陈思如,黄琛,刘文. 对创新组织管理机制在我国商业银行应用、发展的思考[J]. 国际金融, 2018, (3):38-44
[17] Fama E., Fisher L., Jensen M., et al. The Adjustment of Stock Prices to New Information[J]. International Economic Review, 1969,10(1):1-21
[18] MacKinlay C. Event Studies in Economics and Finance[J]. Journal of Economic Literature, 1997,35(1):13-39
[19] Binder J. The Event Study Methodology Since 1969[J]. Review of Quantitative Finance & Accounting, 1998,11(2):111-137
[20] Buigut S., Kapar B. Effect of Qatar Diplomatic and Economic Isolation on GCC Stock Markets:An Event Study Approach[J]. Finance Research Letters, 2020,(37):101352, https://doi.org/10.1016/j.frl.2019.101352
[21] Kim J., Kim J., Lee S. K., et al. Effects of Epidemic Disease Outbreaks on Financial Performance of Restaurants:Event Study Method Approach[J]. Journal of Hospitality and Tourism Management, 2020,(43):32-41
[22] 袁显平,柯大钢. 事件研究方法及其在金融经济研究中的应用[J]. 统计研究, 2006,23(10):31-35
[23] 沈海平. 基于事件研究法的a股市场股权激励效应实证分析[J]. 金融发展研究,2011,(2):73-77
[24] 云昕,辛玲,刘莹,等. 优酷土豆并购案例分析——基于事件分析法和会计指标分析法[J]. 管理评论, 2015,27(9):231-240
[25] 于波,方子睿,周宁. "宝能系"险资举牌的股价效应研究:基于事件研究法[J]. 财务管理研究, 2019, 3(3):20-30
[26] Huber P. J. Robust Regression:Asymptotics, Conjectures and Monte Carlo[J]. Annals of Statistics, 1973,1(5):799-821
[27] Maronna R. A. Robust M-estimators of Multivariate Location and Scatter[J]. Annals of Statistics, 1976,4(1):51-67
[28] 陈希孺. 线性模型m估计大样本理论的进展与问题[J]. 中国科学院院刊, 1999,14(1):21-23
[29] 吴曾,张庆丰. 基于稳健回归的电力负荷预测[J]. 电力科学与工程, 2009,25(4):25-27
[30] 刘晓娟,方建安. 稳健回归方法在电力消费预测中的应用[J]. 电力系统及其自动化学报, 2013,25(5):22-25
[31] 高铁梅. 计量经济分析方法与建模——Eviews应用及实例[M]. 北京:清华大学出版社, 2009
[32] Phillips P. C., Perron P. Testing for a Unit Root in Time Series Regression[J]. Biometrika, 1988,75(2):335-346