企业数据向善、数字创新能力与价值创造
王天东1，林晓玥2，刘天森1
（1.哈尔滨工程大学 经济管理学院，黑龙江 哈尔滨150001；
2.吉林大学 商学与管理学院，吉林 长春130012)
摘要：企业数据向善和数字创新能力对价值创造的影响在实践中已逐步显现，但理论研究对数据向善的动因、数据向善与数字创新能力相互的影响机制以及对价值创造的影响等关键问题尚未予以清晰的回答。本研究以丁香园和百度地图为案例，运用扎根理论研究方法尝试回答上述问题，构建数据向善与数字创新能力协同创造价值的“动因-行为/能力-产出”机理模型。研究发现：（1）数据向善的动因包括来自市场、法律、多主体的外部压力性和激励性因素，以及战略、精神、互补资产方面的内部主客观性因素。（2）数据向善和数字创新能力协同影响价值创造的机制是二者相互影响、相互促进的动态提升过程。（3）数据向善创造价值有两条主要路径，一是基于外部压力性和激励性因素，企业负责任的使用数据，并在与数字敏捷能力的互动提升过程中实现企业价值；二是基于内部主客观性因素，企业进行数据慈善，并在与重构创新能力的互动提升过程中实现社会价值。研究结论清晰地揭示了数据向善创造价值的规律和本质，为实务界和学术界提供了可借鉴的理论框架，并且有助于拓展数据向善与数字创新能力在互动机制、前因结果、研究方法方面的理论研究。
：企业数据向善；数字创新能力；价值创造
主要研究结论：通过对丁香园和百度地图的探索性案例研究，本研究挖掘了企业数据向善的动因、数据向善和数字创新能力协同影响价值创造的机制和实现路径等相关议题，并建立数据向善与数字创新能力协同创造价值的机理模型。研究发现：
（1）数据向善的动因包括外部压力性和激励性因素以及内部主客观性因素，说明了企业实施数据向善的前提准备和关键步骤，是一个重要而复杂的问题，有助于解释为什么有的企业能够实施数据向善造福社会，而有的企业却利用数据作恶的原因。案例分析表明，来自市场、法律、多主体的外部压力性因素和外部激励性因素是企业进行数据向善的条件，能够解释数据向善的必要性，是负责任的使用数据的主要驱动力，也影响着数字创新能力。这是因为负责任的使用数据已经成为企业必须遵守的行为准则，并受到外界的监督和管理。战略、精神、互补资产方面的内部主观性因素和内部客观性因素是企业进行数据向善的根据，能够解释数据向善的可能性，是数据慈善的主要驱动力，也影响着数字创新能力。这是因为数据慈善不具有强制性，而是鼓励企业积极承担责任的主动性行为。林晓玥等学者认为对数据向善动因展开讨论是必要的，企业对于如何实施数据向善的现实指引需求也十分迫切。然而，数据向善研究仍处于萌芽阶段，研究成果局限于定义、维度和量表等基础性问题，目前尚未对动因进行深入讨论。本研究尝试回答这一问题，这将是一次有意义的探索，具有较强的前沿性和启发性。
（2）数据向善和数字创新能力协同影响价值创造的机制是二者相互影响、相互促进的动态提升过程。一方面，数据向善有助于数字创新能力的构建和升级，只有将数据向善内化为创新能力，才能够持续创造积极价值。数据向善基于内外部数据资源的实时连接和运算不断转化为新的洞察力，补充知识体系，快速反馈到对资源组合的调整，帮助企业减少商业风险和促进产品、服务、算法、商业模式、多主体关系创新，这一过程也是创新能力不断强化和提升的过程。另一方面，数字创新能力支持数据向善的实施，影响着数据向善的水平和效果。数字创新能力将数据向善快速落地为具体的新产品或新服务，同时帮助企业发现数据向善的新方法和新途径，为数据向善提供新的可能性。从数据向善研究来看，数据向善的影响和结果是必须解决又尚未得到充分讨论的问题。从数字创新能力研究来看，数字创新能力的已有研究成果集中于内涵和结构基础等问题，具有一定的启发性，并已意识到数字创新能力对于激发数据资源价值的重要意义，但其前因和结果未能得到严谨科学方法的检验和证实，特别是企业如何理解和发现数字资源的潜力并影响组织行为等诸多问题都需要更进一步的挖掘。从数据向善和数字创新能力的关系来看，数据向善与数字创新能力的研究相对独立，尚未意识到两者存在的协同作用，导致已有文献对现实中数据向善创造价值现象的解释力不足。本研究创新性地剖析数据向善与数字创新能力如何形成协同效应影响企业价值和社会价值创造，拓展了数字创新能力与数据向善在互动机制、前因结果、研究方法方面理论研究的知识边界，推动数据伦理研究与数字能力研究之间建立深度联系。
（3）本研究构建“动因-行为/能力-产出”研究框架，提出数据向善创造价值的机理模型，发现数据向善创造价值有两条主要路径：一是基于外部压力性和激励性因素，企业负责任的使用数据，并在与数字敏捷能力的互动提升过程中实现企业价值。案例企业面对外界关于企业合理使用数据而不得侵害消费者权益等愈发强烈的要求，以及在政策和公众的鼓励下，坚持负责任的使用数据，保证数据使用的公平性、准确性、保密性和透明性，并通过对数据的迅速收集和分析，快速优化和整合内外部必要的资产、知识和关系来发现创新机会，促进现有产品和服务根据用户需求快速迭代升级，形成数字敏捷能力，建立良性反馈，创造企业价值，带来更好的绩效、声誉和多主体关系。二是基于内部主客观性因素，企业进行数据慈善，并在与重构创新能力的互动提升过程中实现社会价值。案例企业凭借数字技术和数据方面的天生优势，在自身积极的价值观、战略和精神的驱动下，愿意为了社会公益而捐赠或共享数据、人才服务和技术，尤其在疫情期间将汇集的数据与公众、政府、企业、研究机构共享，建立起新的联结方式和交流机制，促进多主体进行思想、资源、能力的深度互动。价值空间中多主体通过从数字资源使用端出发的使用重组路径和从使用端出发的设计重组路径，实现模式、产品、服务等重新组合或创造，形成重组创新能力，并开启能力和行为相互促进的新循环，从而推动社会向更好的方向发展，创造社会价值。由此，本研究构建了数据向善与数字创新能力协同创造价值的机理模型，首次描绘出数据向善“从哪来”“到哪去”“如何去”的全貌，对于数据向善价值创造理论的构建和发展具有重要意义。
Enterprise data for good, digital innovation capability and value creation
Wang Tiandong1, Lin Xiaoyue2, Liu Tiansen1
(1. School of Economics and Management, Harbin Engineering University, Harbin 150001, Heilongjiang, China;
2. School of Business and Management, Jilin University, Changchun 130012, Jilin, China)
Abstract:As the new round of technological revolution and industrial change evolves, data has become a valuable strategic resource and a new factor of production. The focus of the discussion on data science has shifted from "whether data can be used" to "how to leverage the positive value of data". At home and abroad, some typical enterprises have emerged with data for good, such as DXY and Baidu Maps, which have created great business and social values. However, more enterprises are at a loss of what to do in the face of data for good, and some of them have even made data wrongdoings such as data killing, illegal data collection and sensitive data leakage. The reason for this is the lagging awareness of data for good in the practical world. However, data for good research is in its infancy, and only basic issues such as definitions, dimensions, and scales have been initially explored. The lack of influential research results on the key issue of how data for good creates business and social value has led to the limited guidance of existing research on the practice of data usage. Therefore, it is of great theoretical and practical significance to explore the mechanism of data for good affects value creation.
In fact, there is a natural link between data for good and digital innovation capability. As data is the core of digital resources, enterprises need to build and cultivate their innovation capability to creatively utilize, coordinate and develop digital resources at different levels and areas of their business and operations, which is an important prerequisite for value creation. It can be inferred that synergy between data for good and digital innovation capability is the key to value creation. Specifically, this paper focused on the following three questions: what are the antecedents of data for good? How can the synergy between data for good and digital innovation capability create value? And how is the path of value creation realized?
This paper took DXY and Baidu Maps as examples, and used the grounded theory research method to answer the above questions. A "motivation-behavior/capability-output" mechanism model was constructed for the synergy between data for good and digital innovation capability to create value. The research found that the motivations for data for good include external pressure and incentive factors from the market, law, and multi-actors, as well as internal subjective and objective factors in terms of strategy, spirit, and complementary assets; the synergy between data for good and digital innovation capability affects value creation, and the mechanism is a dynamic enhancement process in which the two influence each other and promote each other; there are two main paths for data for good to create value. Firstly, based on external pressure and incentive factors, enterprise should make a responsible use of data and realize business value in the process of interacting with digital agility capability. Secondly, based on internal subjective and objective factors, enterprise should conduct data charity, and realize social value in the process of interacting with recombinative capability.
This paper further clarified the motivation of data for good, the mechanism path of value creation through the synergy of data for good and digital innovation capability. Therefore, the theoretical contributions of this paper are as follows: First, this paper discussed the motivation of data for good, and responded to the call of scholars to discuss the antecedents of it, which is of great significance to enrich the theoretical study of data for good. Second, this paper clarified the synergistic effect between data for good and digital innovation capability, expanded the theoretical research on the interaction mechanism, antecedent, and results, as well as research methods of the two, and promoted the establishment of a deep connection between data ethics research and digital capability research. Finally, this paper proposed a mechanism model for the synergy between data for good and digital innovation capability to create value, which will not only provide a clear research framework for following studies, but also help to reveal the laws and essence of data for good more clearly.
More importantly, there is still a long way to go in the development of data for good research and practice, and this paper is only a small step to further enrich the data for good research in China and is hoped to provide wisdom for the construction of theory on data for good.
Key words:enterprise data for good; digital innovation capability; value creation
引用本文：王天东,林晓玥,刘天森.企业数据向善、数字创新能力与价值创造[J].科研管理,2023,44(9):20-28.
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