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This study aims to determine how much company participation in a type of cluster affects its economic performance.

This study includes companies operating in seven industries (automotive, engineering, textiles, information technology (IT) services, furniture, packaging and nanotechnology) in the Czech Republic. The companies are divided into three groups: members of institutionalized cluster, operating in the same region (natural clusters) and operating in other regions. Data envelopment window analysis is used to measure their performance for 2009–2019.

Results show that the effect of clustering differs among industries. Companies in three industries (automotive, engineering, nanotechnology) reveal a positive impact of the cluster initiative on performance growth. Two industries (textile, packaging) with companies operating in a natural cluster show better performance than those in an institutionalized cluster. Moreover, the IT services and the furniture industries show no positive effect of clustering on corporate performance.

This research includes 686 companies from seven industries and monitored for 11 years. On the one hand, the sample includes a relatively high number of companies overall; but on the other hand, the sample is relatively small, especially for nonclustered companies. The reason is the lack of available financial statements for small companies.

From the perspective of practical cluster policy, the authors can recommend that monitoring the performance of member companies in clusters must be one of the criteria for evaluating the success of a cluster, such as cluster initiatives.

This study distinguishes between long-standing natural clusters in a given industry and institutionalized ones that have emerged because of a top-down initiative. An original database is created for clustered and nonclustered companies in seven industries, covering the entire Czech Republic.

The paper aims to carry out a comprehensive literature mapping to synthesise and descriptively analyse the research trends of biodiversity accounting, providing implications for managers and policymakers, whilst also outlining a future agenda for scholars.

A bibliometric analysis is carried out by adopting the Preferred Reporting Items for Systematic Review and Meta-Analyses protocol for searching and selecting the scientific contributions to be analysed. Citation analysis is used to map a current research front and a bibliographic coupling is conducted to detect the connection networks in current literature.

Biodiversity accounting is articulated in five thematic clusters (sub-areas), such as “Natural resource management”, “Biodiversity economic evaluation”, “Natural capital accounting”, “Biodiversity accountability” and “Biodiversity disclosure and reporting”. Critical insights emerge from the content analysis of these sub-areas.

The analysis of the thematic evolution of the biodiversity accounting literature provides useful insights to inform both practice and research and infer implications for managers, policymakers and scholars by outlining three main areas of intervention, i.e. adjusting evaluation tools, integrating ecological knowledge and establishing corporate social legitimacy.

Currently, the level of biodiversity reporting is pitifully low. Therefore, organisations should properly manage biodiversity by integrating diverse and sometimes competing forms of knowledge for the stable and resilient flow of ecosystem services for future generations.

This paper not only updates and enriches the current state of the art but also identifies five thematic areas of the biodiversity accounting literature for theoretical and practical considerations.

It is crucial for information retrieval systems to learn more about what users search for in order to fulfil the intent of searches. This paper introduces query taxonomy generation, which attempts to organise users’ queries into a hierarchical structure of topic classes. Such a query taxonomy provides a basis for the in‐depth analysis of users’ queries on a larger scale and can benefit many information retrieval systems. The proposed approach to this problem consists of two computational processes: hierarchical query clustering to generate a query taxonomy from scratch, and query categorisation to place newly‐arrived queries into the taxonomy. The results of the preliminary experiment have shown the potential of the proposed approach in generating taxonomies for queries, which may be useful in various Web information retrieval applications.

The purpose of this paper is to propose an approach regarding the management measures for solving environmental problems in protected areas. Two neighboring protected areas with different features were chosen in order to investigate the similarity of the environmental problems with regard to these two areas and if it is possible for these problems to be solved through a network of protected areas.

The research was carried out through the use of a questionnaire which was distributed to the inhabitants and visitors of both areas, as well as through interviews with the representatives of organizations responsible for the management and administration of those areas and representatives of the municipalities and the regional authorities these two national parks belong to. Simple random sampling was applied to the inhabitants and cluster sampling to the visitors.

The results show that with regard to the visitors the most important problem is illegal hunting while for the inhabitants equally important is the problem of pollution and cleanliness. However, those responsible with the management of the two National Parks think that the greatest threat to the wider area is the problem of floods.

The views of the stakeholders in a given time, provides us with the best possible information for solving the problems faced and can be used as a tool for increasing the effectiveness of the measures which have been taken to deal with the particular problems.

This paper aims to focus on the perceived role of clusters in inter‐firm cooperation and social networks.

The study was carried out in a region of Latin America where limited research has been conducted in terms of inter‐firm relationships. Managers from three key natural resources‐based industries in Chile participated in the survey; one of these industries constituted a well‐defined cluster whereas the other two did not. The survey assessed managers' perceptions of the benefits and opportunities of inter‐firm cooperation in strategic marketing activities.

Results support the advantages of clusters. Managers of firms which are part of clustered industries tend to perceive more benefits and opportunities for inter‐firm co‐operation in marketing activities. Additionally, significant differences between clustered and non‐clustered industries in terms of their co‐operation behavior and objectives were found.

The findings shed light on strategies for the enhancement of inter‐firm cooperation in marketing, of particular value for marketers in small‐and‐medium sized enterprises. The paper suggests establishing new clusters and promoting more regional clusters policies since clustering seems to provide better and positive inter‐firm interaction leading to cooperation.

There are lessons to be learned at national and regional levels for Latin American and emerging economies fostering new industry cluster policies.

Clustered firms and industries may result in more innovative marketing strategies at both local and international levels than non‐clustered firms. The authors encourage regional development bodies to foster more cooperation among firms and trade associations.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

This research aims to investigate cooperative strategies within the Chilean wine cluster, in particular the factors that influence the development of inter‐firm marketing cooperation.

A 2011 census of the Chilean wine cluster was undertaken. A 30 per cent response rate was obtained and the results are presented.

The results highlight that location benefits of collaboration and access to information and technologies are important to success. Previous research has tended to focus on the issue of terroir. Results also provide evidence of cooperation between firms located close to the focal firm, in particular those directly involved in its value chain. There is also evidence of firms cooperating in marketing activities designed to attract new customers and to strengthen the resulting B2B relationship.

The findings shed light on strategies for the enhancement of formal and informal business networks as a facilitator of effective inter‐firm cooperation in marketing, particularly within SMEs. This study will also be of interest to local authorities and industry bodies seeking to enhance cooperation between local clustered firms.

This study contributes to the understanding and definition of traditional and marketing externalities that cluster “members” accrue as a result of co‐location.

Small and medium enterprises (SMEs), which main objective is to satisfy the basic needs of the entrepreneur, when geographically concentrated make up subsistence clusters. The purpose of this paper is to analyze collective efficiency in subsistence clusters as growth strategy and how is the process through which the relational capital and territorial proximity altogether improve performance of firms.

The research uses partial least squares techniques applied to a sample of 113 SMEs of wood industry in Oberá, Argentina.

SMEs in subsistence clusters can use relational capital and territory as resources to generate competitive advantages. These competitive advantages foster performance. In consequence, collective efficiency appears as growth strategy in subsistence SMEs.

Data are cross-sectional and in a conjuncture of economy expansion, future research should monitor the sample of firms using panel data to assess the development of relations. Sample is in a particular region and sector and generalizations should be done carefully.

SMEs probably should integrate and share industrial and business structures to develop systemic competitive advantages with a collective character. SMEs should leverage their spatial interaction to build trust and establish networks of cooperation that will be the source of their collective efficiency. These collaboration networks should base in the local knowledge.

Subsistence SMEs have strong impact on the most disadvantaged areas in developing countries. Growth strategies to professionalize these SMEs will have a major impact on the endogenous development of those territories.

The research provides a mechanism through which collective efficiency leads to better performance for subsistence SMEs.

The purpose of this paper is to investigate the lender-borrower relationship as it relates to Sannong loans for agricultural and rural financial markets by Rural Credit Cooperatives (RCCs) and other rural lenders. This paper is motivated by recent reforms to the rural credit market designed to encourage increased lending, particularly to farmers. Little is understood about the lender-borrower relationship in rural China. This paper fills that gap.

The paper investigates relational attitudes between 120 loan officers at RCCs in China's costal Shandong province, paired with a field survey using matched questions to 394 farm households in the same region. Pairing lenders’ perception toward borrowers regarding RCC microcredit lending mechanism, against borrowers’ perception toward lenders and how themselves were perceived by lenders in the same regards, the paper investigates the degree of disconnect between lenders and with distinct cluster groupings based on their perceptions, the paper analyzes the influence of demographics on the borrower and lender cluster memberships.

The paper identifies four borrower clusters and two lender clusters. Borrower clusters are segmented on credit access and satisfaction with their rural lender. The paper also identifies two lender clusters, segmented principally on financial incentives and lending activities. While all lenders view farming with higher regard than farmers believe they do, one cluster is clearly pro-farmer while the second is somewhat indifferent. Indifference is more related to current portfolio activities. The paper draws conclusions that policy initiatives should be put in place at RCCs that close the gap between lender and borrower in their credit relationship. Rural lenders should concentrate on advocating RCCs’ care and trust toward agriculture and farm households. At the institutional level, effort should be extended to train a dedicated team of loan officers that specialize in servicing farm households with standardized lending practices. This research provides financial institutions with outreach mechanisms to borrowers, while also training lenders to borrowers’ sensitivities.

Management studies of RCCs are few. This is the first paper that the authors are aware of that studies farmer and lender attitudes on the same scale.

The purpose of this study is the empirical measurement and analysis of economic size and performance of dispersed and clustered small‐scale enterprises (SSEs) in India.

Methodology is descriptive and comparative, using a combination of different official databases. Economic size is measured by distribution of SSEs by employment, output, fixed capital investment, and export variables. Measurement of economic performance is focused on output/capital ratio, output/labour ratio, and labour/capital ratio.

The results offer evidence for economic diversity in the size compositions and performance variations of dispersed and clustered SSEs; and bigger economic size and higher economic performance of clustered than dispersed SSEs.

Subject to the comparability of economic structure, the results and implications for India are of relevance for promotion and development of clustered SSEs in other developing countries.

From the viewpoint of policy formulation, the results offer a strong empirical basis for a cluster approach rather than a dispersed approach for promotion and development of SSEs in India. The cluster approach has implications for establishing linkages between formal and informal SSEs and for elimination of smallness of dispersed SSEs.

The paper provides a comparative analysis of economic size and performance of the dispersed and clustered SSEs by consolidating the diverse databases in India.