While there is a general recognition that breakthrough innovation is non-linear and requires an alignment between producers (supply) and users (demand), there is still a need for strategic intelligence about the emerging supply chains of new technological innovations. This technology delivery system (TDS) is an updated form of the TDS model and provides a promising chain-link approach to the supply side of innovation. Building on early research into supply-side TDS studies, we present a systematic approach to building a TDS model that includes four phases: (1) identifying the macroeconomic and policy environment, including market competition, financial investment, and industrial policy; (2) specifying the key public and private institutions; (3) addressing the core technical complements and their owners, then tracing their interactions through information linkages and technology transfers; and (4) depicting the market prospects and evaluating the potential profound influences on technological change and social developments. Our TDS methodology is illustrated using the field of Big Data & Analytics ("BDA").

To tackle serious environmental problems and overcome the negative impact of an almost exclusively Gross Domestic Product (GDP) oriented performance management, a number of local governments in China have started to establish and promote Environmental Protection Performance Evaluation (EPPE) systems for their cadres since the early 2000s. How these systems work in practice within their wider administrative context has not been examined so far. This paper makes a first attempt to assess the efficacy of this EPPE system by looking at its indicator system, the policy process around it, its political implications, and its actual environmental consequences. It does so for the case of Shenzhen, one of China's most forward-looking cities in terms of socio-economic development and political reform. We find that the system can be flexibly used and does push environmental interests higher up the agenda of the local government, but is negatively affected by high levels of uncertainty in its actual use and the strict hierarchy of its application. The main impact of EPPE is on the impression municipal leaders have of the evaluated cadres and on their reputation among their peers, both indirect factors for their political career and thus incentives for the local environmental management. Empirical data show that Shenzhen's environmental quality has not changed significantly in the past five years, although an overall improvement should have been visible if the EPPE systems worked as intended. From this perspective, the efficacy of the EPPE system remains low. At the end a number of policy recommendations are given to enhance the system's effectiveness and fairness.

Innovations around "Big Data" can be characterized in terms of rapid technology development and deployment dynamics. For this purpose, combining "tech mining" (extraction of usable intelligence) from publication and patent databases with tech mining of business-related databases can elucidate activities and interests of business communities regarding Big Data innovation pathways. In this paper, we focus on commercially oriented databases - ABI/INFORM as a source from which to extract business intents. We select the database to help gauge "hot topics" in industry with regard to Big Data. Our results show that certain types of firms can be clustered into thematic groups relating to Big Data discussions and activities. In the paper we demonstrate that such analyses can illuminate themes being pursued by businesses. Like social media analyses, this text mining can provide useful intelligence to inform more in-depth investigation mobilizing other data sources and techniques.