Search results

This research paper aims to contribute to the field of innovation performance benchmarking by identifying appropriate benchmarking groups and exploring learning opportunities and integration directions.

The study employs a multi-dimensional innovation-driven clustering methodology to analyze data from the 2019 edition of the Global Innovation Index (GII). Hierarchical and K-means Cluster Analysis techniques are applied using various sets of distance matrices to uncover and analyze distinct innovation patterns.

This study classifies 129 countries into four clusters: Specials, Advanced, Intermediates and Primitives. Each cluster exhibits strengths and weaknesses in terms of innovation performance. Specials excel in the areas of institutions and knowledge commercialization, while the Advanced cluster demonstrates strengths in education and ICT-related services but shows weakness in patent commercialization. Intermediates show strengths in venture-capital and labour productivity but display weaknesses in R&D expenditure and the higher education quality. Primitives exhibit strength in creative activities but suffer from weaknesses in digital skills, education and training. Additionally, the study has identified 35 indicators that have negligible variance contributions across countries.

The study contributes to finding the relevant countries’ grouping for the enhancement of communication, integration and learning. To this end, this study highlights the innovation structural differences among countries and provides tailored innovation policies.

The main aim of this study is to investigate the role of fathers and mothers in the intergenerational educational persistence for sons and daughters under two dimensions that characterize the clusters of countries: redistributive policy and governance.

Data from the Global Database of Intergenerational Mobility (GDIM), hierarchical cluster analysis on principal components and panel regression are used in this study to estimate intergenerational educational correlation and to investigate its determinants related to the parents’ and descendants’ education variables in 93 countries grouped in four clusters. The empirical analysis is differentiated by gender combinations of parents and descendants.

In the clusters of countries characterized by high inequalities and poor governance, our findings show that the role of the fathers is stronger than that of the mothers in educational transmission; fathers and mothers are more influential for the daughters rather than for the sons; parental educational privilege is the main driver of intergenerational educational persistence; there is an inverse U-curve in the association between educational inequality of the parents and educational correlation for the sons. Differently, in the countries characterized by high income, low redistributive conflict and better governance, the role of the mothers is stronger and education mobility for the daughters is higher than that for the sons.

The authors’ results remark on the importance of social welfare policies aimed to expand a meritocratic public education system including schooling transfers for lower social class students and narrowing the gender gap in educational mobility between daughters and sons. Social welfare policies should also be oriented to spread high quality child care systems that help to foster greater women equality in the labor market, because the strength of educational persistence depends on the position of the mother in the economic hierarchy.

The distinctiveness of the paper can be found in the fact that this study investigates the parental role differentiating by gender and coupling hierarchical cluster analysis on principal components with panel regression models. This allows us to have a sample of 93 countries aggregated in four groups defined in two dimensions: redistributive policy and governance. Amongst the determinants of educational transmission, we consider not only education’s years of the parents but also other determinants, such as educational inequality and privilege of the parents. We also identify the effects of investment in human capital and educational inequalities for the descendants on education mobility.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

This study aims to answer the following research question: What are the opportunities for future research concerning the Frugal Innovation (FI) phenomenon? To address this, the authors propose a novel approach to literature review on the topic. They do so in view of synthesising scholars’ recommendations for subsequent studies. They also advocate that it is time to contribute to the establishment of the FI field by mapping the future of this approach.

The authors conducted a systematic literature review (SLR) to connect past and future research on FI. After the screening process of the documents extracted from multiple databases, they performed a bibliometric analysis to provide an overview of the field. Furthermore, the lexical analysis and descending hierarchical analysis were generated through the IRAMUTEQ software to identify the clusters for future research on FI.

This research not only demonstrates the current state of the art of FI literature but also identifies a research agenda with six categories of opportunities for further studies on the topic: frugal consumer behaviour; establishment of the field; sustainable impact; approaches to different contexts; implementation processes; and challenges for value creation.

The FI phenomenon is receiving increasing attention from scholars in the management field due to its socioeconomic and managerial implications, especially after the Covid-19 outbreak. Therefore, the findings benefit scholars striving to expand the scope of FI research, as well as entrepreneurs, managers and organisations aiming to enhance their social responsibility to reduce their environmental impact.

The aim of this paper is to offer a comprehensive overview of the field of international human resource management (IHRM) research by tracing its evolutionary development over a 24-year period. The study seeks to understand how the field has progressed by considering historical research themes and their subsequent integration into more recent scholarly work, thereby identifying current and emerging research trends.

This paper employs bibliometric analysis to examine the evolutionary path of IHRM research from 1995 to 2019. A dataset of 1,507 articles from journals specializing in IHRM, international business and general management was created. Analysis at the keyword, thematic and network levels was conducted to identify trends, historical context and the interrelatedness of research themes.

The analysis reveals that IHRM research has gone through several phases of thematic focus, from initial emphasis on cultural differences and expatriate management to more recent topics like global talent management and digital transformation. Earlier research themes continue to be incorporated and re-contextualized in modern scholarship, highlighting the field’s dynamic nature.

This paper is one of the first to use a bibliometric approach to systematically examine the evolution of IHRM research. It not only provides a historical perspective but also outlines future research trends, incorporating the institutional logic perspective. The findings offer deep insights that are valuable for researchers, practitioners and policymakers interested in the development of IHRM research and its practical implications.

This study aimed to identify and profile segments of seaweed consumers in the United Kingdom.

Hierarchical k-means cluster analysis was used to identify consumer segments based on consumers' self-identity and environmental values. In addition, the study used subjective knowledge, intentions and consumption to profile different consumer segments. The data were collected in 2022 through a consumer survey with a representative sample from the United Kingdom (n = 1,110).

Cluster analysis segmented consumers into three groups: progressive (39%), conservative (33%) and egoistic (28%). The progressive segment was most likely to consume seaweed food products. Consumers in the progressive segment identify themselves as food innovative and healthy; they also highly value the environment and their pleasure. Conservative and egoistic consumers were significantly less likely to consume seaweed food products.

The results suggest that public policy officers and marketers promote seaweed food products by emphasizing biospheric values for innovative (younger) consumers, as well as seaweed’s good taste and nutritional/health qualities.

This study identifies and examines the profiles and characteristics of seaweed consumers based on their values and self-identity. Through this research, the authors have discovered how environmental values and self-identity can effectively group consumers into homogeneous segments. Moreover, the authors have identified a specific consumer group in the UK that is more likely to consume seaweed food products.

Public sector institutional entrepreneurship efforts may contribute to addressing social challenges by creating an enabling regulatory environment that promotes social enterprise formation and fosters complementarity between the public sector and social enterprises. The outcomes of such public sector institutional entrepreneurship are explored in this study. To assess the outcomes of such public sector initiatives in South Korea, the perspectives of executives (n = 40) of government-certified social enterprises are assessed.

Several research methodologies were combined, including purposive sampling with an 11-point Likert scale, hierarchical clustering and principal component analysis. The literature on government–nonprofit relations as well as public sector institutional entrepreneurship was leveraged.

This research results indicate that the enabling regulatory environment with entrenched funding and incubation mechanisms produces mixed-to-positive outcomes if framed with reference to public sector–social enterprise complementarity. The authors identified three perspective-based ideal types that have differential views of isomorphic regulatory pressures, the efficacy of incubation and scaling programs, participation in policymaking and other aspects of public sector patronage.

This study contributes to relating the literature on public sector institutional entrepreneurship and government–third sector relations by empirically assessing how social enterprises attracted by government demand-side signaling to become certified as social enterprises encounter and perceive an ostensibly enabling regulatory ecosystem, with its derivative policies and mechanisms, crafted by the public sector.

This study aims to understand the importance of participatory governance in the identity of social enterprises (SEs). To this end, this paper provides a framework by means of the value co-creation process and by drawing from the service-dominant logic perspective and the stakeholder theory. An explanation is also provided regarding the opportunity to include fundamental issues in defining SE collective identity, such as those related to an organisation’s participatory nature of involving the stakeholders affected by its activities, the exercise of democratic decision-making and its autonomy from the state and market.

On the statistical exploitation of a large international data set, the authors approach the conceptualisation of SEs by providing an index to measure their social, economic and governance characteristics, thereby enabling these enterprises to be categorised into different groups.

This study found that the inclusion of the governance dimension in the research incorporates the greatest variability between the various models of SE, thereby justifying participatory governance as the raison d’être of the two fundamental schools in SE, namely, Anglo-Saxon and European.

This research offers a tool to policymakers to be used as a criterion of classification and hierarchical organisation for public procurement. It enables the various organisations to be ordered and takes social and cultural influence into consideration. This tool would be highly useful as a support of social entrepreneurship from the public environment, especially at the local level.

This study justifies the value of incorporating participatory governance as a distinctive dimension for the definition of categories of SEs. Furthermore, an index to craft taxonomies of SEs is developed based on social, economic and governance indicators, which provides a framework that facilitates the empirical research of the SE.

While consumer preferences for sporting goods have been widely researched within sport management, literature is lacking on aspects of social and environmental sustainability. Accordingly, this study aims to investigate the role of social and environmental sustainability for purchase decisions of sportswear and compares them to the role of price and functionality.

Based on a conjoint analysis among 1,012 Europeans, the authors conducted a two-step cluster analysis. First, the authors investigated the number of segments via Ward’s method. Second, the authors ran a k-means analysis based on part-worth utilities from the conjoint analysis.

The authors identified four segments which differ in terms of preferred product attributes, willingness to pay, and sociodemographic, behavioral, and psychographic characteristics: undecided, sustainable, price-focused and function-oriented consumers. Based on this segmentation, the authors found that the importance of social and environmental sustainability is growing, but not among all consumers.

The generalizability of the study is limited since it is not built on a sample representative for the included European countries, it focuses on a single product, and participants are potentially subject to a social desirability bias.

The consumer analysis comprises the uptake of attributes related to social and environmental sustainability. The authors thereby address a literature gap as previous research (thematizing sporting goods) in the sport management field has often neglected sustainability elements despite their rapidly growing importance within the sport sector.

The study’s objective is to measure the importance consumers attach to AI-based attributes, namely, chatbots, face recognition, virtual fitting room, smart parking and cashier-free station in retail stores. The study also examines the specific purpose of using these attributes for shopping.

A conjoint experiment was conducted using fractional factorial design. Consumers were given 14 profiles (AI attributes and its levels) to rank according to their visiting preferences.

The results revealed that the retail chatbot was considered the most important attribute, followed by face recognition, virtual fitting room, smart parking system and cashier-free station. Moreover, consumers prefer to use chatbots for in-store shopping assistance over alerts and updates, customer support and feedback. Similarly, consumers wish a face recognition facility for greetings while entering the store over other services. In addition, cluster analyses revealed that customer groups significantly differ in their preferences for AI-based attributes.

The study guides retail managers to invest in AI technologies to provide consumers with a technology-oriented shopping experience.

Our results provide an insight into the receptivity of AI technologies that consumers would like to experience in their favorite retail stores. The present study contributes to the literature by investigating consumer preferences for various AI technologies and their specific uses for shopping.