China Small And Medium Company's Dynamic Capability Investigation Through Big Data Technology

Small and medium enterprises (SME) are managed mostly by founders. They lack resources and rely on the innovative spirit of entrepreneurs so as to generate business growth. SMEs play a very important role in China economy. Therefore, it is necessary to facilitate SMEs to identify and exploit opportunities through innovation, objectives and long-term policies of the organization. At the same time,external environment plays a role in achieving strategic competitiveness and obtains above-average returns. The spirit of innovation strategy allows SME management identifies sustainable competitive advantage, captures new business opportunity and coordinates resources. Small and medium enterprises in China account for 99.5% of registered entities, which is a crucial foundation in China's economic and social development. The rapid proliferation of SMEs in China promotes the development of social productive forces. More and more small and medium enterprises make use of "bottleneck assets" to create competitive advantage through creating, combining, transferring, accumulating and protecting intangible assets. Resource-based theory was evolved from the core competitiveness,which proposed the competitive advantage of valuable tangible and intangible resources.Resources are heterogeneous. Short-term competitive advantages are converted into a sustainable competitive advantage. Most SME entrepreneurs can identify and distinguish good information for their decision-making, high-speed response and analysis in order to maintain SMEs sustainable competitive advantage. This core capability is called dynamic capability or dynamic competitiveness.Dynamic capability is difficult to be determined in a business. It does not show itself explicitly until reveal and use. It was originally defined as "the ability to integrate enterprise, build and reconfigure internal and external resources, forming competitiveness and respond rapidly against changing environment". SMEs face dynamic market environment. Dynamic capability emphasizes on learning ability."Information" matches internal resources against environment,adjusting the allocation of resources catering for internal strengths and shortcomings, and identifying external opportunities and challenges. "Change" is the next logical step in the process of Dynamic capability, including the creation of stimulus response. "Assessment" and"Select" are alternative steps from the information generated. Finally, "Reserved"allocation of resources is achieved. Dynamic capability is complemented with absorptive capacity leading to enhance combat capability, revamping competitive advantage,and build "dynamic capabilities based on knowledge." Enterprises capture new knowledge from market and internal feedback. The results are to reconfiguring organizational learning. Dynamic knowledge and learning contribute to a better understanding of knowledge. The role of dynamic capability is to develop various concepts or summary. Absorptive capacity studies, collects, identifies and accesses to external knowledge. This assimilates knowledge integration and transforms new external knowledge internally to achieve organizational resilience. Four dimensions are necessary to explore the process of assimilation, conversion and learning, which improve business performance, competitive advantage, innovation, strategic flexibility,adapt to change and enhance competitiveness. Successful absorption capacity is the ability to dynamic change. Real-time analysis is an important tool which can solve the weak signal theory in information asymmetry. Real-time (or low latency) big data analysis changes the rules of the game. Customer and market appear and disappear in weak signals. SMEs have the opportunity to identify and take action through weak signals. Big Data's location-based services show a huge potential through real-time access to critical data sources to achieve business metrics. Real-time data matching'determines the performance in predictive analytics, and achieve prediction and optimization of enterprise stakeholders. Corporate executives play a critical role in evolving competing strategy and specific decisions.Big data drastically changes SME business model through new insights, customer interaction,and analysis of competitor information,improving profitability,and real-time delivery. Data is explored from different sources to reflect value. New information technology accesses and analyzes massive amounts of data in seconds, and extracts high-value information to drive business change. Ultra-high-efficiency data does change the rules of the game between SMEs and large enterprises. Big data serves the key functions of data mining, detection and assessment model, describing the variable"relevance." The definition of big data has four priorities: the first is the size of the data set and volume related; second is the complexity, and structure, behavior and related arrangement; third is technology, and related tools and technology; fourth great deal and complex data collection. Big Data is perceived in size, diversity, speed and density value.The lynchpin between dynamic competitiveness and large data systems theory is weak signal theory. It describes market behavior, including individuals or organizations,in accessing different information. Under a normal circumstance, the sender party must know how to communicate. Receiving party must choose how to interpret the signal.Signal theory moves forward in organization for learning. Signaling theory facilitates scholars to develop new ways to solve complex formula and understand nuanced changes. Dynamic capability can integrate corporate resources, build and reconfigure internal and external resources in order to cope with rapid changes in business environment. It is the ability to guide and help SMEs redeploying and allocating resources so as to meet customer needs and respond to the changing strategies in competitors. Dynamic capability is a collective experience, which generate and modify its operating system through the organization. it pursues high efficiency, coordination and integration,learning reconfiguration and transformation. In turn, dynamic capability allows the company to create new products, processes and core competitiveness.This empirical research shows that dynamic capability has different influence on strategic change and firm performance. Big Data is a key component of information management for small and medium enterprises. According to the Big Data dimension(capacity,variety,speed,authenticity and value),the dynamic capability dimension is proposed to fulfill the objective in competitiveness. Research objective of this study is the synergies across Big Data technology, small and medium enterprises,competitiveness and dynamic capabilities between the synergies.Through Literature review and Big Data survey in China small and medium enterprises, there are five core research variables in dynamic capabilities: 1) weak signal;2) business environment sensing; 3) business adjustment; 4) resource capacity conversion and; 5) resource scheduling (marketing and technical capabilities,coordination and integration capabilities, and strategic responses to environmental competition).Mixed method is adopted in this research. The first part is to find twenty small and medium companies and study their Big Data requirements. The 20 SMEs are located in five China cities, Tokyo, Europe, Brazil, Hong Kong and Singapore. Deep unstructured interviews are used. The second part is qualitative content analysis and theme identification. Then,questionnaire is prepared to survey electronically. 2000 samples were issued, and eventually 600 electronic copies are collected. Finally, empirical results solicited from questionnaires establish Big Data driven dynamic capabilities model in small and medium-sized enterprises.Three innovation perspectives are inducted from qualitative interviews. First one is"high-speed transformation and resource reconfiguration of small and medium-sized enterprises through dynamic capability"; second one is "refining weak signals through large data means to strengthen dynamic competitiveness"; and the last one is "through large-scale real-time data to enhance the dynamic decision-making capacity of SMEs.".Information Technology (Big Data) overwhelmingly resolves data management issues, grasps the transformation of the industry to improve the efficiency and performance of large enterprise data. Through analyzing secondary data from industries,absorptive capacity in SMEs is established. It is not a simply polymerization in company structure and industry resources, but contains dynamic capabilities as well.Absorptive capacity of the internal and external information aggregated into knowledge to improve the ability to adapt.Through this empirical research, four resolution strategies are identified. First strategy is "to establish a small and medium-sized enterprise-led large data sharing platform"; second strategy is "to establish a large data privacy center for small and medium enterprises"; third strategy is "Data system": and the last strategy is" to enhance the ability of small and medium enterprises large data real-time analysis."...