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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.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

Although green entrepreneurial orientation (GEO) has received much attention, it is unclear whether it affects technological green innovation (GI). Therefore, this study aims to understand how GEO affects technological GI, with its dimensions green product innovation (GPRODI) and green process innovation (GPROCI), as well as to explore whether resource orchestration capability (ROC) moderates the relationships between them.

Based on a cross-sectional survey design, data were gathered from 177 managers of large manufacturing firms in Yemen and analysed using partial least squares structural equation modelling via SmartPLS software.

The results revealed that GEO positively affects both GPRODI and GPROCI, with a higher effect on GPROCI. Importantly, ROC does, in fact, positively moderate the link between GEO and GPRODI.

This research adds to knowledge by combining GEO, ROC and technological GI into a unified framework, considering the perspectives of the resource-based view and the resource orchestration theory. However, the study’s use of cross-sectional survey data makes it impossible to infer causes. This is because GEO, ROC and technological GI all have effects on time that this empirical framework cannot account for.

The findings from this research provide valuable insights for executives and decision makers of large manufacturing companies, who are expected to show increasing interest in adopting ROC into their organisations. This suggests that environmentally-conscious entrepreneurial firms can enhance their GI efforts by embracing ROC.

By adopting the proposed framework, firms can carry out their activities in ways that do not harm environmental and societal well-being, as simply achieving high economic performance is no longer sufficient.

Theoretically, the results offer an in-depth understanding of the role of GEO in the technological GI domain by indicating that GEO can promote GPRODI and GPROCI. In addition, the results shed new light on the boundaries of GEO from the perspective of resource orchestration theory. Furthermore, the findings present important insights for managers aiming to enhance their comprehension of leveraging GEO and ROC to foster technological GI.

The study aims to test the framework that proposes the role of resources (intellectual capital) in mobilizing entrepreneurial orientation that influences the competitiveness improvement of micro-small-medium enterprises (MSMEs) under the lens of resource orchestration theory.

In this study, 347 respondents from the MSMEs participated through a structured questionnaire. For the data analysis purpose, the structural equation modeling technique was employed using SmartPLS software.

The results suggest human, structural, and relational capital are significant antecedents of entrepreneurial orientation, which leads to competitiveness improvement. The findings also indicate the mediation role of entrepreneurial orientation between intellectual capital and competitiveness improvement.

The current study presumably will supplement the promising research effort to progress the research orchestration theory and also could be a strategic guideline for the managers/owners of the MSMEs.

This study is possibly a novel attempt to divulge the association between intellectual capital (tripartite model) and competitiveness improvement of firms under the lens of resource orchestration theory.

This article aims to examine the impact of multiple suppliers on competitive advantage by exploiting digital capabilities.

The author propose a structural equation model with the adopted measure from the literature. Hence, the study conducted an online survey in Indonesia with 450 qualified respondents involving managers and owner-managers.

The results indicate multiple suppliers help the firms to exploit digital capabilities, which foster them to achieve competitive advantage. Hence, different level of market turbulences determines the impact of numerous suppliers on competitive advantage. Specifically, the multiple-suppliers approach is more effective in supporting buyer firms to gain a competitive advantage during high market turbulence than low market turbulence.

This study offers empirical evidence with unit analysis of buyer firms that seek competitive advantage by exploiting digital capability. However, this approach focusses on a single unit analysis, which is buyer firms. Hence, there is an opportunity to adopt qualitative approach to explore the suppliers and end-users from different perspectives from other supply chain players.

This article contributes to the growing literature on the resource-based theory by examining the relationship between the multiple-sourcing model and competitive advantage. The authors also discuss the intersection between resource-based, dynamic capability and stakeholder theory.

Managing resources is crucial for firms to gain competitive advantages and succeed, particularly for startups with limited resources. It is important to understand how digital startups in general and digital academic spin-offs (ASOs) in particular may orchestrate their resources to optimize value. This paper integrates the resource-based perspective with digital entrepreneurship to analyze the resource configurations leading to success of digital ASOs.

The paper adopts an inductive approach and applies qualitative comparative analysis (QCA) on a longitudinal dataset of digital ASOs to identify the resource configurations for a successful outcome.

The authors' paper identifies two main paths to success among digital ASOs, consisting of five distinct resource configurations. The first path is termed “market exploiters” that operate in favorable market conditions where specific technological resources and research collaboration resources are lacking. The second path involves “technology explorers” that combines both technological and commercial resources to achieve success.

By outlining distinct pathways to the success of digital ASOs, this paper contributes to the digital academic entrepreneurship literature and the resource-based view of entrepreneurial firms. The paper also suggests implications for policymakers and managers in managing resources for the success of digital ventures.

By exploring the resource configurations leading to the success of ASOs commercializing digital technologies, the paper shows that favorable market conditions and complementary resource configurations can be alternative pathways to success.

The COVID-19 pandemic was an eye-opening experience that put to the test our crisis management competencies across many institutions, including those offered by institutions of higher education. This study aims to review the literature on international business (IB) risks and IB education (IBE) to question whether business graduates are equipped to make decisions in today’s volatile, uncertain, complex and ambiguous (VUCA) marketplace.

While the IB literature has discussed the importance of various sources of risks on global business operations, IBE did not effectively adopt an integrative approach to building the needed risk management competencies related to those risks into our education. The authors argue that this integrative approach to teaching IB is critically needed to prepare future global managers for addressing crises, like that of the pandemic and others. Specifically, this study proposes that this integrated risk management competency can be developed through the building of “synergistic mindsets”.

This study presents a conceptual framework for the components of the synergistic mindset, with intelligence that directly links to present IB risks. These components are cultural intelligence (CQ), emotional intelligence (EQ), public policy intelligence (PPQ), digital intelligence (DQ) and orchestration intelligence (OQ).

Insights related to IBE effectiveness in addressing today’s VUCA market demands and IB risks are discussed.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.