|
|
|
| The Impact of Big Data Analytics Capabilities on Enterprise Digital Transformation: The Moderating Effect of Local Policy Perception |
| Yu Feifei,Jiang Qing |
| (School of Business, Hohai University, Nanjing 210000, China) |
|
|
|
|
Abstract Digital transformation is now necessary for enterprise growth with the fusion of digital technology and the real economy. The local governments have been paying particular attention to ways to assist enterprises in implementing digital transformation at the central government's request. Provincial governments and relevant departments have taken the initiative to formulate detailed rules and measures to promote the digital transformation of local enterprises.#br#Existing research mainly focuses on the measurement of digital transformation at the national, regional and industry levels and lacks measurement of enterprise digital transformation at the micro level, mainly by the case study method to describe the transformation process. Only a few studies have measured the enterprise digital transformation on word frequency analysis. In general, the current research on enterprise digital transformation is still in its infancy. It still lacks the division of the stages of the digital transformation process and the comparison of the differences between different phases. In particular, there is a lack of quantitative measurement of different stages of enterprise digital transformation. Moreover, existing research generally agrees that big data analytic capabilities include organizational, technical and human capabilities, without which big data analytics capabilities cannot be effectively implemented. In addition, big data analytics capabilities are found to play a critical role in improving performance, driving innovation and digital transformation. But it has rarely been mentioned of how to quantitatively characterize the impact of big data analysis capabilities on the degree of enterprise digital transformation and the differentiated effect of each digital transformation stage. Finally, from the perspective of external factors, there is a shortage of research from the standpoint of local policies perception to examine the impact of local digitalization policies on the enterprises' digital transformation and compare their differentiated effects on the various stages of digital transformation.#br#Addressing the above issues of the existing research, this study conducts empirical research through questionnaires to explore the impact of big data analytics capabilities on the differentiation at each stage of enterprises' digital transformation and the moderating role of local policy perceptions. In view of the fact that the collected questionnaire data are all from the self-report of middle and senior managers in the enterprise, in order to prevent the interference of common method bias in the results, this paper employs the commonly used Harman single factor test method. With 356 valid questionnaires, the hypotheses are tested accordingly. The findings suggest that big data analytics capabilities can significantly increase enterprises' digital transformation in the initial preparation, practice implementation and deep exploration stages. Local policy perception positively moderates the impact of big data analytics capabilities on the initial preparation stage and practice implementation stage of enterprise digital transformation. In contrast, the relationship between big data analytics capabilities and the deep exploration stage of enterprise digital transformation is not significant.#br#This study has three theoretical contributions. First, the stages of digital transformation are rarely divided because the current characterization of its dimensions and indicators is still in its infancy with focus on case studies and word frequency analysis. This study divides the enterprise digital transformation process into three stages, i.e. initial preparation, practice implementation and deep exploration, and describes each stage at the micro-enterprise level using a questionnaire survey. This division further advances the existing research on the measurement of enterprise digital transformation. Second, from the perspective of big data empowerment, this study introduces big data analytics capabilities based on the theory of dynamic capabilities and investigates their impact on the digital transformation of enterprises in various stages. These findings significantly extend the discussion of enterprise digital transformation from the internal organization view by contrasting the effects of big data analytics capabilities on the differentiation of different transformation stages. Therefore, this study advances the relevant research on the internal factors of enterprise digital transformation. Third, from the perspective of institutional environment perception, it investigates the moderating role of local policy perception between big data analytics capabilities and different transformation stages of enterprises. These moderating results are conducive to enriching the current research on the external driving factors of enterprise digital transformation and expanding the evaluation of the implementation effect of relevant local policies.#br#
|
|
Received: 12 July 2022
|
|
|
|
|
|
[1] JAFARI-SADEGHI V,GARCIA-PEREZ A,CANDELO E,et al. Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: the role of technology readiness,exploration and exploitation[J]. Journal of Business Research,2021,124: 100-111.
[2] 陈堂,陈光. 数字化转型对产业结构升级的空间效应研究——基于静态和动态空间面板模型的实证分析[J]. 经济与管理研究,2021,42(8): 30-51.
[3] 杨雅程,雷家骕,陈浩,等.加工制造企业数字化转型的机理——基于资源编排视角的案例研究[J].管理案例研究与评论,2022,15(2):198-220.
[4] 张黎娜,苏雪莎,袁磊.供应链金融与企业数字化转型——异质性特征、渠道机制与非信任环境下的效应差异[J].金融经济学研究,2021,36(6):51-67.
[5] 史宇鹏,王阳.营商环境与企业数字化转型:影响表现与作用机制[J/OL].北京交通大学学报(社会科学版):1-15[2022-04-30].https://doi.org/10.16797/j.cnki.11-5224/c.20220420.008.
[6] PAPPAS I O,MIKALEF P,GIANNAKOS M N,et al. Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies[J]. Information Systems and e-Business Management,2018,16(3): 479-491.
[7] AKTER S,WAMBA S F,GUNASEKARAN A,et al. How to improve firm performance using big data analytics capability and business strategy alignment[J]. International Journal of Production Economics,2016,182:113-131.
[8] ASHAARI M A,SINGH K S D,ABBASI G A,et al. Big data analytics capability for improved performance of higher education institutions in the era of IR 4.0: a multi-analytical SEM & ANN perspective[J]. Technological Forecasting and Social Change,2021,173: 121119.
[9] MIKALEF P ,BOURA M,LEKAKOS G,et al. Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment[J]. British Journal of Management,2019,30(2):272-298.
[10] 李树文,罗瑾琏,葛元骎.大数据分析能力对产品突破性创新的影响[J].管理科学,2021,34(2):3-15.
[11] DREMEL C,HERTERICH M,WULF J,et al. How AUDI AG established big data analytics in its digital transformation[J]. MIS Quarterly Executive,2017,16(2): 81-100.
[12] NWANKPA J K,ROUMANI Y. IT capability and digital transformation: a firm performance perspective[EB/OL].https://aisel.aisnet.org/icis2016/ISStrategy/Presentations/4/,2016.
[13] MOI L,CABIDDU F. Leading digital transformation through an agile marketing capability: the case of Spotahome[J]. Journal of Management and Governance,2021,25(4): 1145-1177.
[14] 杨贤宏,宁致远,向海凌,等.地方经济增长目标与企业数字化转型——基于上市企业年报文本识别的实证研究[J].中国软科学,2021(11):172-184.
[15] RACHINGER M,RAUTER R,MUELLER C,et al. Digitalization and its influence on business model innovation[J]. Journal of Manufacturing Technology Management,2019,30(8): 1143-1160.
[16] GURBAXANI V,DUNKLE D. Gearing up for successful digital transformation[J]. MIS Quarterly Executive,2019,18(3): 209-220.
[17] VERHOEF P C,BROEKHUIZEN T,BART Y,et al. Digital transformation: a multidisciplinary reflection and research agenda[J]. Journal of Business Research,2021,122: 889-901.
[18] 吴建南,陈子韬,李哲,等.基于“创新—理念”框架的城市治理数字化转型——以上海市为例[J].治理研究,2021,37(6):99-111.
[19] 林艳,张欣婧.制造企业数字化转型不同阶段的影响因素——基于扎根理论的多案例研究[J].中国科技论坛,2022,38(6):123-132,142.
[20] WARNER K S R,WGER M. Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal[J]. Long Range Planning,2019,52(3): 326-349.
[21] WANG Y ,KUNG L A ,BYRD T A . Big data analytics: understanding its capabilities and potential benefits for healthcare organizations[J]. Technological Forecasting & Social Change,2018,126:3-13.
[22] LIN C,KUNNATHUR A. Strategic orientations,developmental culture,and big data capability[J]. Journal of Business Research,2019,105: 49-60.
[23] LAI Y,SUN H,REN J. Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management[J]. The International Journal of Logistics Management,2018,29(2): 676-703.
[24] 卢章平,王晓晶.国家和地方科技成果转化政策对比分析[J].图书情报工作,2012,56(24):83-88.
[25] 许成磊,张超,郭凯,等.政策支持、创业激情与技术创业成功:政策感知的调节作用[J/OL].科技进步与对策:1-10[2022-05-08].http://kns.cnki.net/kcms/detail/42.1224.g3.20210826.1110.006.html.
[26] 王雪冬,聂彤杰,孟佳佳.政治关联对中小企业数字化转型的影响——政策感知能力和市场感知能力的中介作用[J].科研管理,2022,43(1):134-142.
[27] SINGH S,SHARMA M,DHIR S. Modeling the effects of digital transformation in Indian manufacturing industry[J]. Technology in Society,2021,67: 101763.
[28] MACKENZIE S B,PODSAKOFF P M,PODSAKOFF N P. Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques[J]. MIS Quarterly,2011: 293-334.
[29] STICH V,ZELLER V,HICKING J,et al. Measures for a successful digital transformation of SMEs[J]. Procedia CIRP,2020,93: 286-291.
[30] LI H,WU Y,CAO D,et al. Organizational mindfulness towards digital transformation as a prerequisite of information processing capability to achieve market agility[J]. Journal of Business Research,2021,122: 700-712.
[31] 王核成,王思惟,刘人怀. 企业数字化成熟度模型研究[J]. 管理评论,2021,33(12): 152-162.
[32] 傅颖,徐琪,林嵩. 在位企业流程数字化对创新绩效的影响——组织惰性的调节作用[J]. 研究与发展管理,2021,33(1): 78-89.
[33] 卢艳秋,赵彬,宋昶. 决策逻辑、失败学习与企业数字化转型绩效[J]. 外国经济与管理,2021,43(9): 68-82.
[34] HSU P-F,RAY S,LI-HSIEH Y-Y. Examining cloud computing adoption intention,pricing mechanism,and deployment model[J]. International Journal of Information Management,2014,34(4): 474-488.
[35] LOEBBECKE C,PICOT A. Reflections on societal and business model transformation arising from digitization and big data analytics: a research agenda[J]. The Journal of Strategic Information Systems,2015,24(3): 149-157.
[36] 史宇鹏,王阳,张文韬.我国企业数字化转型:现状、问题与展望[J].经济学家,2021(12):90-97.
|
|
|
|
