Continuous Innovation (CI) has become one of the hot topics in innovation management field. However, studies focusing on the comprehensive and detailed explanation of CI concept are still limited. This paper aims to elaborate on CI concept using three fundamental questions: WHAT (what is the definition of CI and what are the determining factors?), WHY (why do companies need CI?), and HOW (how can companies develop CI?). The purpose of this paper is also to contribute in giving an understanding that is more exhaustive on CI definition, the importance of CI for companies, necessary elements in determining CI capability, and various strategies for CI development. From this literature study, a new and more comprehensive definition of CI was found, which categorized the reason why the companies need the CI and identified essential elements in determining CI capability. In addition, the mapping process produced a description of the proportion of CI development strategy as follows: technology-based (11%), People based (15%), organizational & system based (32%), strategic-based (11%), knowledge-based (22%) and collaborative & connectivity based (9%). It can be observed that current CI development strategies still focus on organizational, system based approach, and most of them (81%) rely on the internal resources of the company. Future perspectives, in this digital and internet era, which provides connectivity and the shift of the concept of, own economy to sharing economy; companies will have big potentials to work on innovation collaboratively. CI concept development should consider open innovations instead of today's "do-it-yourself" mentality (closed innovation).

<p>Footwear industries get the priority in East Java Province because of their big contribution to the economy and labor absorption. In order to survive and to achieve the competitive advantage they need to do innovation. The innovation capabilities can be measured through Technological Innovation Capabilities (TIC), while the innovation performance can be assessed with Technological Innovation Performance (TIP). This research was conducted to identify SMEs characteristics (scale, age, and product type) and to analyze whether there were different impacts of those characteristics on TIC and TIP. Data collection was completed through questionnaire distribution to 192 footwear SMEs in three footwear center in East Java (Surabaya, Sidoarjo, and Mojokerto). The grand mean of each dimension of TIC and TIP was obtained by calculating the results of questionnaire which used Likert scale. The grand mean can be as a description of TIC and TIP level in those three areas. For TIC, the majority footwear SMEs were on the medium and high level. The highest level of TIC was achieved by footwear SMEs in Mojokerto (4.09), Surabaya got a medium (3.18), and Sidoarjo obtained the lowest (2.81). For TIP, the majority of footwear SMEs had the medium and low level. Footwear SMEs in Sidoarjo held the highest level (3.05), then the footwear SMEs in Mojokerto (2.86), and the lowest is footwear SMEs in Surabaya (2.05). Based on the MANOVA analysis it can be recognized that almost all characteristics of footwear SMEs (scale, age, product type) gave no significant impacts on TIC and TIP. Except among footwear SMEs in Surabaya the age of SMEs had an effect on TIC and TIP.</p><p>Keywords: Footwear SMEs, Innovation Capabilities, Innovation Performance</p>

Purpose The purpose of this paper is to identify and screen continuous innovation capability enablers (CICEs) in Indonesia’s manufacturing sectors, develop a relationship among these enablers and determine their driving power and dependence power in the sector. Design/methodology/approach The initial CICEs identification process is based on a literature review, while a fuzzy Delphi method (FDM) was used for the screening process of CICEs. Total interpretive structural modelling (TISM) was used to develop contextual relationships among various CICEs. The results of the TISM are used as an input for the matrix of cross-impact multiplications applied to classification (MICMAC) to classify the driving power and dependence powers of the CICEs. Findings This paper selected 16 CICEs classified in seven dimensions. TISM results and MICMAC analysis show that leadership, as well as climate and culture, are enablers with the highest driving power and lowest dependence powers; followed by information technology. The results of this study indicate that efforts to continuously develop innovation capabilities in the Indonesian manufacturing industries are strongly influenced by their leadership capability, climate and culture, also information technology-related capability. Practical implications The framework assessed in this study provides business managers and policymakers to obtain a bigger picture in developing policies with evidence-based strategy and priority in regard to continuous innovation capability. Originality/value The results will be useful for business managers and policymakers to understand the relationship between CICEs and identify key CICEs in Indonesia’s manufacturing sectors, which were previously non-existent.

Innovation has become one of the most important sources of a company’s sustainable competitiveness. Therefore, every company strives continuously to improve its innovation capability. A company’s innovation capability is largely determined by various factors originating from its tangible and intangible resources. A lot of research related to increasing innovation capability with assessment factors originating from tangible resources has been carried out, whereas the use of assessment factors originating from intangible capital, such as intellectual capital, is still relatively limited. This study aims to identify and screen the key assessment factors for innovation capability, based on the intellectual capital of Indonesia’s manufacturing sectors. This study used a systematic literature review and focus group discussions to establish 18 initial assessment factors, after which 14 final factors were screened out by industry practitioners and academic experts using the Fuzzy Delphi Method. Four factors had the highest de-fuzzy value (0.89), namely adaptation, innovation behavior, organization culture, climate, and forward linkages. The results also showed that three factors of the aspects of human capital (adaptation, innovation behavior, and high motivation and commitment) are considered important determinants for the assessment of innovation capabilities, based on intellectual capital.