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The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

As climate change shocks and stresses increasingly affect urban areas in developing countries, resilience is imperative for the purposes of preparation, recovery and adaptation. This study aims to investigate demographic characteristics and social networks that influence the household capacity to prepare, recover and adapt when faced with prolonged droughts or erratic rainfall events in Mbale municipality in Eastern Uganda.

A cross-sectional research design was used to elicit subjective opinions. Previous studies indicate the importance of subjective approaches for measuring social resilience but their use has not been well explored in the context of quantifying urban resilience to climate change shocks and stresses. This study uses 389 structured household interviews to capture demographic characteristics, social networks and resilience capacities. Descriptive and inferential statistics were used for analysis.

The ability of low-income households to meet their daily expenditure needs, household size, and networks with relatives and non government organizations (NGOs) were significant determinants of preparedness, recovery and adaptation to prolonged droughts or erratic rainfall events.

The results imply that policymakers and practitioners have an important role vis-à-vis encouraging activities that boost the ability of households to meet their daily expenditure needs, promoting small household size and reinforcing social networks that enhance household resilience.

Even the low-income households are substantially more likely to prepare for and recover from prolonged droughts or erratic rainfall events if they can meet their daily expenditure needs. This finding is noteworthy because the poorest in society are generally the most vulnerable to hazards.

The purpose of this paper is to investigate how specialised capabilities including absorptive capacity and marketing capabilities influence innovation commercialisation in manufacturing and service firms in Nigeria. The authors hypothesise that absorptive capacity measures including openness and formal training for innovation, and marketing capabilities encompassing new product marketing and marketing innovation are positively associated with innovation performance.

The authors examine commercialisation of innovation within the profiting from innovation (PFI) and dynamic capabilities (DC) framework and use data from the 2012 Nigeria Innovation Survey to test the hypothesis by means of a Heckman sample selection model.

The authors find that absorptive capacity measures comprising openness and formal training are positively associated with innovation performance. The authors also find that marketing capabilities as indicated by new product marketing and marketing innovation are positively associated with innovation performance.

The authors acknowledge that firms undergo continuous changes and that there may be the presence of unobserved or unmeasured heterogeneity. Taking into cognisance that Nigeria is a federal state, cultural diversity and economic factors are likely to differ widely between geographical regions. Also, while the proposed conceptual framework offers a deeper understanding of innovation performance, examining how integrating activities of the R&D department, human resource department and marketing department affect innovation commercialisation is likely to provide more meaningful insights.

The role that inter-organisational learning and intra-organisational learning play in driving innovation performance provide managers with a basis for incorporating absorptive capacity building programs that boost employees’ ability to recognise and apply valuable external knowledge to commercial ends. Similarly, firms may benefit from offering marketing capabilities development programs. Furthermore, innovation policies in Nigeria are generally designed to focus on fostering innovation activities aimed at developing innovative output. Accordingly, government support explicitly targeting new product marketing and marketing innovation is likely to play a vital role in the successful commercialisation of innovation in Nigeria.

This study fuses the PFI and DC framework to examine why innovating firms may not necessarily succeed. This area of study has received scant attention in sub-Saharan Africa given that extant literature focusses on value creation as opposed to value capture.

Entrepreneurial ecosystems provide the context for start-ups to access resources. The authors investigate the reliance of start-ups on their entrepreneurial ecosystem and the driving factors behind the proportion of local actors (belonging to their entrepreneurial ecosystem) within their overall set of relationships (their business ecosystem). Recognizing the limited relational capacity of firms, the authors focus on three differentiating firm characteristics: size, age and innovation of firms.

The authors developed a sample of 163 start-ups located in the entrepreneurial ecosystem of Toulouse, France. The authors investigated the characteristics of their relationship sets using regression analysis.

The results confirm that age is inversely related to the proportion of a start-up's relationships located in its entrepreneurial ecosystem. More surprisingly, for older start-ups, the authors also highlight the presence of a moderating effect of the start-up's size on the relationship between its degree of innovation and the proportion of its relationships in its entrepreneurial ecosystem: Larger and more innovative start-ups appear to rely more on their local entrepreneurial ecosystem.

This research increases the understanding of the characteristics driving the interactions of start-ups with their entrepreneurial ecosystems by adopting a relational capacity approach. The authors introduce digital methods as an innovative approach for uncovering firms' ecosystems. Finally, from a practical point of view, the research should provide public authorities seeking to promote the link between local resources and the development of innovative start-ups in their regions with interesting insights.

Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance.

This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA.

The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness.

The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times.

This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance.

Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.

The COVID-19 pandemic has exposed the fragility of government institutions and prompted a broad range of policy measures from governments around the world. Policy responses to the pandemic have varied considerably, both in nature and in success. This paper highlights the policy capacities of the UAE in different areas that have contributed to managing the COVID-19 crisis. Specifically, the paper examines the functional capacity, analytical capacity, fiscal capacity, well-timed information-sharing capacity and political capacity of the UAE in addressing the pandemic.

The study on which this paper was based adopted a mixed-method approach to analyze policy capacities. The trajectory and timeframe of COVID-19 from February 2020 to February 2021 were observed intensively and included in the policy capacity analysis. The secondary dataset was collected from several sources and assessed using rapid content analysis to highlight the formal and institutional policy measures implemented during the crisis. To complement the policy analysis and understand the key role of policymakers, semi-structured interviews were conducted with local officials working in various line departments that formulate and implement policy strategies for the UAE government.

The findings of the study showed that although COVID-19 has severely impacted the UAE, the nation has effectively controlled the spread of the virus and reduced its mortality rate. The UAE government has taken swift policy actions concerning coercive control and mitigation based on a centralized decision-making style, the strengthening of administrative capacity by collaboration, coordination with different departments, successful communication with residents, the allocation of adequate financial resources and a high level of trust in the government by citizens.

This work contributes to the existing literature by highlighting the policy capacity approach to managing the crisis. The UAE case can be used by policymakers as comparative studies of policy designs, tools and capabilities that can be implemented to manage future pandemics and other crises.

This study aimed to examine the similarities and differences between the ability to analyze the environment and exploit new knowledge (absorptive capacity) and the skills to generate value from innovation (appropriation). These fields have similar origins and are sometimes confused by practitioners and academics.

A review was conducted based on a full-text analysis of 681 and 431 papers on appropriation and absorptive capacity, respectively, from Scopus, Science Direct and Lens, using methodologies such as text mining, backward citation analysis, modularity clustering and latent Dirichlet allocation analysis.

In business disciplines, the fields are considered different; however, in other disciplines, it was found that some authors defined them quite similarly. The citation analysis results showed that appropriation was more relevant to absorptive capacity, or vice versa. From the dimension perspective, it was found that although appropriation was considered a relevant element for absorptive capacity, the last models did not include it. Finally, it was found that studies on both topics identified the importance of appropriation and absorptive capacity for innovation performance, knowledge management and technology transfer.

This is one of the first studies to examine in-depth the relationship between appropriation and absorptive capacity, bridging a gap in both fields.

This study aims to identify context-specific antecedents to schools’ absorptive capacity (AC) and to show how those can enact “a virtuous learning circle.”

The study uses a mixed method: an exploration based on semi-structured interviews with educational experts; the development of a measurement scale and a partial least squares structural equation modelling to test the impact of the antecedents.

The results yielded four empirically-grounded antecedents and their measurement scales, namely, prior knowledge, employees’ skills, educational projects and interactions with the environment (Studies one and two). All antecedents are significantly and positively related to AC processes (study three). Using the organizational learning theory perspective, the results have been interpreted as an AC “virtuous learning circle.”

With increasing pressures to adapt, a case of which was the COVID-19 pandemic, schools can greatly benefit from absorbing knowledge flows. This suggests the construction a favourable environment for AC. To this end, the individual (employees’ prior knowledge and skills), organizational (educational projects) and institutional level of managerial action (interactions with the environment) can be effective when create a recursive organizational learning circle. In addition, this study offers an expert-validated measurement scale for self-assessment of a school’s specific contingencies, and thus, for planning of punctual interventions to develop AC.

This study advances the existing body of knowledge management in the educational context by rigorously identifying and validating a scale for measuring the antecedents of AC and developing an interpretive approach to the AC “virtuous circle.”

The purpose of this study is to develop an appropriate new product development (NPD) process of Company “T”, a medium-sized firm, by analyzing the existing NPD process and failure cases of the Company.

The proposed research framework is as follows: first, prospective studies of the NPD process are performed using the existing literature and preliminary references; second, comparative analysis between the current processes and a NPD process is performed; third, phase-based evaluations upon failed product cases are conducted with a NPD process so as to identify the abridged steps and root-causes of failures; finally, renewed priorities are set forth by utilizing the analytic hierarchy process analysis and questionnaire analysis upon the above identified causes of failures.

The resulting accomplishments include the establishment of NPD processes that resonates with the current states of Company “T”, which, in turn, ensures the increase of efficiency, the decrease in development duration and the strategy of capacity-concentration and priority-selection.

As Company “T”’s development process is outdated and products are developed without adequate market information research and feasibility analysis, the percentage of failed development project is as high as 87 per cent. Thus, this study aims to develop an appropriate NPD process of Company “T” by analyzing the existing NPD process and failure cases of the Company.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.