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With technological innovation elements and the competitive market environment becoming increasingly complex, numerous firms utilize network embeddedness to achieve and sustain innovation. However, empirical research has not conclusively established which form of network embeddedness more effectively facilitates corporate innovation. Drawing on the heterogeneous network resources perspective, this study explores the impact of market network embeddedness, technology network embeddedness and their synergy on the green innovation performance of manufacturing small and medium-sized enterprises (SMEs). Furthermore, it investigates the moderating role of resource orchestration capability in these relationships.

Through an online questionnaire survey of Chinese manufacturing SMEs, 293 sample data were collected, and the hierarchical regression analysis was conducted to test the hypothesis.

The results indicate that market and technology network embeddedness significantly enhance green innovation performance, with the former exerting a more significant impact. Furthermore, the synergy between market and technology network embeddedness positively influences green innovation performance. Additionally, resource orchestration capability strengthens the positive effects of both market and technology network embeddedness on green innovation performance, while the moderating effect of resource orchestration capability on the relationship between the synergy of the two and green innovation performance was insignificant.

The study faced many limitations, such as collecting primary data, which relied on a questionnaire only, using cross-sectional data and examining only manufacturing SMEs.

Based on the heterogeneous network resources perspective and integrating social network theory and resource orchestration theory, this study explores the impact of network embeddedness on the green innovation performance of manufacturing SMEs, which sheds new light on the network embeddedness research framework and also enriches the antecedents of green innovation. In addition, this study provides implications on how manufacturing SMEs effectively utilize network embeddedness and resource orchestration capability to enhance green innovation performance.

This paper examines the relationship between heterogeneous political connections and corporate overinvestment.

Based on a comprehensive Malaysian dataset of 834 publicly listed companies from 2000 to 2022, the authors employed multivariate ordinary least squares regression to test the relationship.

Despite different types of political connections, the findings demonstrate a positive relationship between political connections and corporate overinvestment. In particular, the association is more profound in government-linked companies (GLCs) but weaker in firms that developed political ties through family members of ruling elites. Further analysis reveals that the “helping hand” effect is only observed in GLCs and firms with politically connected directors and businessmen, whereas the “grabbing hand” effect is observed among firms connected through board, businessmen, and family ties. Moreover, the relationship is more persistent among firms with politically connected directors and businessmen around the regime change.

Regardless of the types of political connections, the findings show that politically connected firms tend to engage in rent-seeking through political patronage networks and high levels of government interference in resource allocation. Therefore, a more sophisticated monitoring system should be developed within the political patronage networks to reduce the likelihood of different types of political-business collusion. In terms of research limitations, the research design does not consider the influence of financial constraints and management efficiency. Future research could explore these facets to comprehensively understand the dynamics between political connections and corporate investment decisions.

The evidence informs market participants about the relationship between heterogeneous political connections and corporate overinvestment, reinforcing previous findings that crony capitalism, political patronage, agency problems, and weak governance are well-entrenched in Malaysia’s emerging economy. The government should acknowledge these concerns by enacting anti-corruption campaigns and promoting a fair business environment. In the meantime, policymakers might redesign regulations and revise corporate governance frameworks to substantially reduce the value of political connections, thereby diminishing the bargaining power of politicians.

As corporate investment efficiency has a considerable impact on firm value, investment decisions that enhance firm value will increase share price and maximise shareholder value. Conversely, firms may damage shareholder value if they overinvest or undertake projects that do not yield sufficient. Hence, the findings of this study may assist investors in making more informed judgements, particularly by understanding different types of business-government relations, as political connections are one of the determinants of corporate overinvestment.

This study reveals that the degree to which overinvestment issues manifest within firms is influenced by the nature of the political connections those firms possess. This indicates that politically connected firms should not be regarded as a homogenous group of firms.

Recently, the tourism and hospitality industry has been increasingly hit by serious crises. In particular, the implications of the COVID-19 pandemic and phenomena such as a shortage of skilled workers and overtourism are presenting numerous destinations and their key stakeholders with new, increasingly complex challenges. In addition, the continued development of meta-processes such as demographic change and digitalisation in many respects implies an ‘end of tourism as we know it’ (Destinationthink.com, 2017). In order to successfully face these complex challenges, it is necessary – as with most wicked problems – to think and act ‘outside the box’. An increasing individualisation and pluralisation of lifestyles is taking place in most societies and represents another challenge that should not be underestimated. This implies that diversity and diversity management are becoming ever more important strategic success factors, both for human resource management and for the development of new markets and target groups. Unfortunately, however, far too few players in the tourism and hospitality sector value diversity management as part of their corporate strategy. This chapter therefore aims to raise awareness of diversity and diversity management as a concept that has become increasingly important in recent years but still only occupies a niche in tourism-specific contexts. The intensified strategic valorisation of diversity can actually sustainably increase the competitiveness of destinations and their key actors. Against this backdrop, this contribution explores conceptual understandings of diversity and diversity management from a theoretical perspective and uses specific case studies to illustrate how the corresponding management approach can be successfully valorised in tourist destinations.

The relationship between cooperative R&D network embeddedness and firm innovation resilience is understudied. This paper seeks to answer the questions of whether and how embedding in cooperative R&D networks improve digital firms’ innovation resilience.

Based upon social capital theory, this paper proposes a conceptual model with several hypotheses. The empirical analysis is based on a sample of 2,908 observations from 2005 to 2022. We measure firm innovation resilience by drawing on economic resilience and use LSM tests to assess the effect of cooperative R&D network position on innovation resilience.

The results indicate that cooperative R&D network centrality has a positive impact on firm innovation resilience and that the structural holes of the cooperative R&D network have an inverted U-shaped relationship with firm innovation resilience. Moreover, technological turbulence negatively moderates the relationship between centrality and firm innovation resilience while also steepening the inverted U-shaped relationship between structural holes and firm innovation resilience. Market turbulence positively moderates the relationship between centrality and firm innovation resilience. However, the moderating effect of market turbulence on the inverted U-shaped relationship between structural holes and firm innovation resilience is not significant.

Innovators' knowledge needs, bounded rationality, interests, and even organizational environments change over time, thus prompting them to constantly seek new opportunities to exchange and integrate knowledge, meet new beneficial partners, maintain beneficial cooperation, or terminate unhelpful cooperation. The utility of the network structure has dynamic characteristics. Only by considering the dynamics of the network can research on the mechanism of network structure be more complete, accurate and convincing. Therefore, future research can pay more attention to the relationship between dynamic networks and firm innovation resilience.

Firms should actively embed themselves in the cooperative R&D network and occupy a beneficial network position. By joining the cooperative R&D network, firms can gain resource advantages and enhance their ability to resist external shocks and improve innovation resilience.

This research advances our understanding of the antecedents of firm innovation resilience through the lens of organizational cooperation and uncovers the boundary conditions under which network embeddedness influences innovation resilience, thereby further enriching the theoretical framework of innovation resilience.

This study aims to explore the effects of expertise diversity on project efficiency and creativity in health-care project teams.

This study analyzes hierarchical linear models using multi-source data from 50 project teams in a large health-care organization in the USA. This data set includes self-reported survey responses from 274 team members and human resource information for all 515 members across the 50 teams. Expertise diversity is operationalized by professional diversity and positional diversity reflecting two dimensions, domain and level, of the concept of expertise.

This study reveals that professional diversity is negatively related to project efficiency and project creativity, whereas positional diversity is positively related to project efficiency.

Successfully managing a project team of experts within a limited time frame is a challenge for organizations. This study advances the understanding of the double-edged sword effect of expertise diversity on project teams, focusing on professional and positional diversity. It provides important insights for human resource development in terms of the composition of project teams regarding members’ expertise.

There is a growing body of literature discussing the green logistics practices (GLPs) that companies could introduce to reduce the logistics environmental impact. Current approaches also identify several influencing factors within firms that could serve as barriers to, or enablers of, GLPs. However, less is known about the role of extra-firm stakeholders, even though these are crucial to operationalizing green logistics effectively. This study merges current theoretical understanding with empirical evidence to provide a detailed stakeholder analysis of GLPs.

Using stakeholder theory as a theoretical lens, the authors aimed at offering a mid-range contribution by conducting multiple embedded case studies examining Italian logistics service providers and shippers. GLPs and the related influencing factors were examined as sub-units of analysis within broader companies' environmental sustainability strategies.

The authors identified cascading effects among factors influencing the adoption of GLPs (e.g. key economic factors are affected by external factors which also influence organizational and collaboration factors). These effects are moderated by interdependencies between primary and secondary stakeholders, and the study highlights the prominent involvement of secondary stakeholders, such as final consumers.

This paper contributes to better understanding how and why companies adopt GLPs, emphasizing the wide set of stakeholders involved and illustrating how different stakeholders impact on GLPs adoption by affecting a set of influencing factors. By combining insights from the available literature with contemporary empirical data, the authors emphasize how Logistics Service Providers (LSPs) and shippers can no longer address the adoption of GLPs as “focal companies”, but only as part of a “focal network of interconnected stakeholders”, all of them influencing GLPs adoption.

Although the literature provides insights into the role of experiential learning based on prototypes in identification of latent customer need, it offers different views on the role of product prototypes in improving the efficacy of learning customer need, and also neglects the role of vicarious learning in prototype-based experiential learning. In a data-rich environment, market big data create new opportunities to learn from vicarious, digitalized experiences that are not observable with prototype-based learning. Therefore, the purpose of this study is to compare the effects of product prototype strategies – basic prototype strategy and enhanced prototype strategy – on identification of latent customer needs, and determine how each prototype strategy interacts with vicarious learning based on market big data to identify latent customer needs.

We collected data from 299 Chinese manufacturing firms via on-site surveys to explore our research question. All of our hypotheses were supported by the regression results.

This study finds that both the enhanced and basic prototype strategies (experiential learning from direct market experience based on prototyping) have positive effects on latent need identification, but the effect of enhanced prototypes is stronger. Furthermore, the enhanced and basic prototype strategies have different interaction effects with market big data (vicarious learning from indirect market experiences) on latent need identification.

This research extends the literature on prototype-based learning for latent need identification. It also contributes to the experiential prototype-based learning literature by exploring the role of vicarious learning based on market big data.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

Entrepreneurial activity is a phenomenon that increases the economic growth of countries and improves their social welfare. The economic development levels of countries have significant effects on these entrepreneurial activities. This research examines which institutional and macroeconomic variables explain early-stage entrepreneurship activities in developed and developing economies.

The authors conducted panel data analysis on the data from the Global Entrepreneurship Monitor (GEM) and International Monetary Fund (IMF) surveys covering the years 2009–2018.

First, the authors' results reveal that cognitive, normative and regulatory institutions and macroeconomic factors affect early-stage entrepreneurial activity in developed and developing countries differently. Second, the authors' findings indicate that cognitive, normative and regulatory institutions affect early-stage entrepreneurship more positively in developed than developing countries. Finally, the authors' results report that macroeconomic factors are more effective in early-stage entrepreneurial activity in developing countries than in developed countries.

This study provides a better understanding of the components that help explain the differences in entrepreneurship between developed and developing countries regarding institutions and macroeconomic factors. In this way, it contributes to developing entrepreneurship literature with the theoretical achievements of combining institutional theory and macroeconomic indicators with entrepreneurship literature.