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The textile industry is a labor-intensive industry in which where innovation-oriented studies are conducted intensively. However, identifying potential innovation gaps for a firm operating in the textile industry is not easy and greatly influences the firm's future success. To this end, this study aims to propose a novel integrated approach for the pre-assessment of the firm-level innovation process.

The proposed approach uses two important tools: the technology capability audit tool and innovation audit tool. The proposed approach integrates these tools to discover possible innovation opportunities for firms. The proposed approach is called the innovation gap finder model (IGFM).

A real case study in the textile industry is conducted to show how IGFM works in practice. The results of this study show that decision-makers can easily identify existing innovation gaps using IGFM.

Firms must first identify innovation gaps in order to initiate achievable projects in line with their current situation. Addressing a firm-level pre-assessment of the textile innovation process helps achieve growth and enables the firm to know what it should do in the near future. By identifying innovation gaps by considering the innovation processes at the firm level, it is also easier to prepare an action plan on what and how to do in accordance with the firm's own culture. There is no specific tool developed to discover potential innovation gaps in the literature. To fill this gap, a novel integrated approach is proposed for a pre-assessment of firm level innovation process in this study. The proposed approach can also accelerate the establishment of the “idea-invention-innovation” path within the firm.

The textile sector is one of the sectors where competition is intense and requires the production of high-value-added products. This study aims to conduct patent analysis to find the technology status, recent trends, applications and technological evaluations of protective textile technologies in practice.

More than 36,840 patent documents related to protective textile technologies are available for researchers, patent examiners and patent researchers. Patent analysis is conducted to report the technology status, recent trends and applications of protective textile technologies. This analysis provides insights into the possible future directions of protective textile technologies in practice. Additionally, association rule mining (ARM) is performed to find the hidden patterns among protective textile technologies.

The development of protective textile technologies is revealed by the technology evaluation in this study. In addition, the sub-technology classes affecting protective textile technologies are examined using the cooperative patent classification (CPC) codes of the patent documents. Technology status and recent trends of protective textile technologies are provided in detail. The results of this study show that (1) protective textile technologies are constantly being developed, (2) the working areas of medical protective textiles are increasing, (3) there are frequent studies on fabric structures for saving lives within the framework of human needs and (4) there are four technology classes, namely A41D, Y10T, B32B and A62B impacting the other technology classes related to textile technologies such as D10B, Y10T, F41H, A62D, D04H, Y10S and D10B.

To have a competitive advantage in the marketplace, evaluation of textile technologies is critical in developing “functionalized” and “technologized” textile products. In particular, evaluating technologies in developing protective textile products is extremely important to meet customer demands and present competitive products in the market. Examining these patents for technology developers, decision-makers and policymakers is an urgent and necessary job. However, studies examining the development of protective textile technologies with patent analysis are very limited in the literature. To fill this gap, technology status, recent trends and applications of protective textile technologies are reported based on patent analysis and ARM in this study.

This study aims to propose a novel approach based on utility mining to find the associations among wind energy technologies.

The proposed approach uses patent documents and utility mining. Associations among wind energy technologies have been evaluated to show how the proposed approach works in practice.

Determining the relationships between wind energy technologies provide essential information to investors and decision-makers. Therefore, a real-life case study of wind energy technology is performed to show how the proposed approach works in practice. The proposed approach founds technology classes associated with wind energy technology. Furthermore, the strongest associations among technologies are also obtained by the proposed approach. The results of the case study show that the proposed approach can be easily used in practice. The maximum size of itemsets is 18-level itemsets. Y02E and F03D cooperative patent classification (CPC) codes appear on all itemsets. As the technologies of Y02E and F03D are directly correlated, they will be mutually developed in the future. Additionally, the number of patent corresponding to Y02E and F03D CPC codes are 7,494 and 6,577, respectively.

This is the first study that applies the utility mining-based approach to patent documents. Different levels of importance among technologies based on patent citations and the number of repetitions of each technology class are considered in the proposed approach.

The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social network analysis is used to identify the most influential and connected technologies in the field of wind energy.

In the literature, patent data are often used to evaluate technologies. Patents related to wind energy technologies are obtained from the United States Patent and Trademark Office database and the relationships among sub-technologies based on Corporate Patent Classification (CPC) codes are analyzed in this study. The results of two-phase algorithm for mining high average-utility itemsets algorithm, which is one of the utility mining algorithm in data mining, is used to find associations among wind energy technologies for social network analysis.

The results of this study show that it is very important to focus on wind motors and technologies related to energy conversion or management systems reducing greenhouse gas emissions. The results of this study imply that Y02E, F03D and F05B CPC codes are the most influential CPC codes based on social network analysis.

Analysis of patent documents with social network analysis for technology evaluation is extremely limited in the literature. There is no research related to the analysis of patent documents with social network analysis, in particular CPC codes, for wind energy technology. This paper fills this gap in the literature. This study explores technologies related to wind energy technologies and identifies the most influential wind energy technologies in practice. This study also extracts useful information and knowledge to identify core corporate patent class (es) in the field of wind energy technology.

The aim of this study is to evaluate the relationship between innovative climate, strategic orientation, work motivation, business performance and job performance.

Within the scope of the research, a survey was conducted with 400 engineers working in organizations operating within companies producing spare parts for automobile companies. IBM SPSS 25, IBM SPSS AMOS and LISREL programs were gradually used, and the data obtained were evaluated and analyzed.

The importance of strategic orientation and work motivation for organizations can be seen in the analysis results in terms of their positive effects.

In the production sector, where innovation and competition activities take place, not only strategic decisions but also motivation for employees must be realized within the organizational culture in order for the organizations to be successful. Strategic orientation is effective in achieving innovation and creation to the extent that employees are motivated.

In terms of successful performance, it is very important to manage companies with the right strategic understanding and to involve the employees. In order to realize the innovation climate and to be successful in performance criteria, motivation is considered a key factor, in particular for the automobile sector. Automobile companies are now turning to electric vehicle production using new generation technologies. However, they also attach importance to the use of smart technologies in cars. For this reason, the effects of strategic orientation and work motivation on performance and innovation are investigated in companies producing automobile spare parts.

Coffee is among the primary products that attract the public attention to the social and environmental responsibilities of companies. Coffee shops have a big carbon footprint because of their daily operations. With the rising consciousness about sustainability in developing countries, online disclosure of corporate social responsibility (CSR) is becoming increasingly important for not only multinational but also local coffee chains. The purpose of this study is to analyze the extent to which coffee chains include CSR on their websites.

Turkey, which is a large emerging economy with an expanding coffee chain market, is selected as the research context. The CSR disclosure on the websites of coffee chains is examined by content analysis according to CSR dimensions. A sample of 27 coffee chains with more than ten stores is included in the analysis.

Foreign coffee chains disclose more information on the environment and fair trade than local coffee chains. On the other hand, CSR content in websites of foreign and local coffee chains does not differ significantly in human resources and community dimensions. Foreign coffee chains have comparatively longer brand history, more rooted brands and larger networks than local coffee chains.

To the best of the author’s knowledge, this study is the first that used a content analysis about CSR on the websites of coffee chains in Turkey. Findings contribute to the understanding of CSR disclosure in the coffee chain industry and can be beneficial for researchers and managers in other emerging markets.