Search results

A debate on whether new ventures should be supported with public funding is taking place. Adopting a position on this discussion requires rigorous assessments of implemented programs. However, the few existing efforts have mostly focused on regional cases in developed countries. To fill this gap, this paper aims to measure the effects of a regional acceleration program in a developing country (Medellin, Colombia).

The economic notion of capabilities is used to frame the analysis of firm characteristics and productivity, which are hypothesized to be heterogeneous within the program. To test these relationships, propensity score matching is used in a sample of 60 treatment and 16,994 control firms.

This paper finds that treated firms had higher revenue than propensity score-matched controls on average, confirming a positive impact on growth measures. However, such financial growth is mostly observed in service firms rather than other economic sectors.

Further evaluations, with a longer period and using more outcome variables, are suggested in the context of similar publicly funded programs in developing countries.

These findings tip the balance in favor of the literature suggesting supportive programs for high-growth firms as opposed to everyday entrepreneurship. This is an insight, especially under the context of an emerging economy, which has scarce funding to support entrepreneurship.

Designing effective business analytics (BA) platforms that visualise data, provide deep insights and support data-driven decision-making is a challenging task. Understanding the elements shaping BA platform design is crucial for success. The purpose of this study is to explore the impact of visualisation on usability (UI) and user experience (UX) while emphasising the importance of insights understanding in BA platform design.

This paper presents a case study following a startup’s journey as it undergoes two redesign phases for its BA platform. A combination of quantitative and qualitative methods is used to assess UX/UI and insights understanding of the platform. Indicatively this included semi-structured interviews, observations, think-aloud techniques and surveys to monitor runtime per task, number of errors, users’ emotions and users’ understanding.

Our findings suggest that modifications in aesthetics and information visualisation positively influence overall usability, UX, and understanding of platform insights – a critical aspect for the success of the startup.

Our goal is not to make a methodological contribution, but to illustrate how companies, constrained by time and pressure, navigate platform changes without meticulous design and provide learnings on important elements while designing BA platforms.

This paper concludes with suggested methods for assessing BA platforms and recommends practical practices to follow. These practices include recommendations on important elements for BA platform users, such as navigation and interactivity, user control and personalisation, visual consistency and effective visualisation.

This study contributes to practice as it presents a real-life case and offers valuable insights for practitioners.

In additive manufacturing (AM), “complexity for free” is often cited as a major technological benefit. This generalized view has been found inaccurate by several authors dealing with the evaluation of part complexity. However, the term “complexity” is not defined uniformly. The reasons for this are the various AM processes and different evaluation factors used by the respective authors. This is critical because build time heavily depends on the impact of complexity on the additive process through the processing tool (point-to-point-, line- and mask-based) defining competitiveness. This study aims to define appropriate complexity indicators and evaluate the impact on productivity of PBF-LB/P (laser sintering).

An assessment methodology for geometric complexity is developed for point-to-point-based processes using the PBF-LB/P process. First, an overview of part characteristics and their interrelationships with the generation process is provided. In this way, relevant factors, e.g. part volume and perimeter length, are identified. Subsequently, these are used to create a metric to select and manufacture test samples to quantify the impact on build time.

The results indicate a strong impact of geometrical complexity on build time and build-up rate. Consequently, optimizing the geometry in the early design stage and adjusting process parameters during production planning allow to influence the build-up rate.

This paper demonstrates the effects of geometric complexity using manufacturing jobs. As a result, the suitability of existing methods and KPIs is shown to be insufficient. Hence, meaningful indicators for laser sintering, such as contour length vs hatch length, contour length vs part volume and number of hatches vs part volume, are defined and verified.

The use of technological innovations to effectively deliver construction projects is gaining significant coverage. This study aims to assess the inhibiting factors to the utilisation of laser scanners for the delivery of construction projects in developing economies using South Africa as the study area.

Adopting a quantitative technique, this study elicited responses from construction professionals using a questionnaire as the instrument for data collection. A four-pronged data analysis method was used, comprising descriptive statistics, Kruskal−Wallis h-test, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

Findings from the study show that lack of awareness and high cost of acquisition are the barriers rated by the study’s respondents the most. Also, findings from the EFA and CFA conducted showed and affirmed the significance of three constructs inhibiting factors to the utilisation of laser scanners for construction project delivery: technical hindrances, financial impediments and institutional challenges.

This study makes practical contributions to the discourse of using innovative technologies for effective construction project delivery by inhibiting factors to the use of laser scanners.

Evidence from the literature shows that no study has assessed the barriers to the utilisation of laser scanning technology for construction projects in the South African construction industry. This study strives to close this gap in the literature.

Drawing on panarchy theory and adaptive cycles, this study aims to investigate the role of reorganisation capabilities on firms’ supply chain resilience. The conceptual model underpinned by panarchy theory is tested in the agrifood supply chains disrupted by a geopolitical crisis and faced with material shortage. The study considers circularity as a core reorganisational capability and measures its interplay with two other capabilities: new product development and resource reconfiguration capabilities to achieve supply chain resilience.

A quantitative research design is followed to test the relationships between circularity capabilities, resource reconfiguration capabilities, new product development capabilities and supply chain resilience. A cross-sectional survey is applied to a sample drawn from food manufacturers who are dependent on wheat and sunflower oil as raw material and who are faced with material shortages in the aftermath of a geopolitical crisis. Measurement models and hypotheses are tested with the partial least squared structural equation modelling (PLS-SEM) based on 324 responses.

The results show that new product development and resource reconfiguration capabilities fully mediate the relationship between circularity capabilities and supply chain resilience. In other words, the food producers achieved supply chain resilience in response to agrifood supply chain disruption when they mobilised circularity capabilities in combination with new product development and resource reconfiguration capabilities.

The findings suggest that producers in the agrifood industry and even those in other industries need to develop circularity capabilities in combination with new product development and resource reconfiguration capabilities to tackle supply chain disruptions. In a world that is challenged by geopolitical and climate-related crises, this means leveraging 3R practices as well as resource substitution and reconfiguration in new product development processes.

The study explores the release and reorganisation phases of adaptive cycles in a panarchy by analysing the interplay between different capabilities for building supply chain resilience in response to disruptions challenging supply chains from higher levels of the panarchy. The results extend the theoretical debate between circularity and supply chain resilience to an empirical setting and suggest the introduction of new variables to this relationship.

Blockchain and distributed ledger technologies are increasingly prominent, yet their adoption remains complex. This paper addresses the common misalignment between blockchain technology and actual needs, often leading to project failure. It introduces a decision-making framework focused on the technological aspects of blockchain adoption.

We designed the framework by analyzing key decision drivers from existing literature and applied it to a real-world use case in the electric vehicle supply chain. The blockchain solution was tested with live production data.

Blockchain is beneficial for use cases requiring decentralized governance, but it often needs to be supplemented with additional technologies in industrial applications.

The framework provides a set of managerial-level questions that simplify the decision-making process for those without deep technical expertise, helping determine when blockchain is appropriate, valuable and superior to other technologies.

This paper contributes to the existing literature on the gender gap in academic career advancement by focusing on the very early stage of the academic career, i.e. the transition from Ph.D. completion to a tenured position.

Using Italian individual-level data, our econometric analyses estimate the likelihood of holding a tenured position conditional on a set of individual-level covariates.

Our findings support the idea that women have a lower probability of obtaining a tenured position. Results hold even when research productivity and experience are controlled for.

Our conclusions suggest that there is a significant gender gap in progression through an academic career.

In this paper, community identification has been considered as the most critical task of social network analysis. The purpose of this paper is to organize the nodes of a given network graph into distinct clusters or known communities. These clusters will therefore form the different communities available within the social network graph.

To date, numerous methods have been developed to detect communities in social networks through graph clustering techniques. The k-means algorithm stands out as one of the most well-known graph clustering algorithms, celebrated for its straightforward implementation and rapid processing. However, it has a serious drawback because it is insensitive to initial conditions and always settles on local optima rather than finding the global optimum. More recently, clustering algorithms that use a reciprocal KNN (k-nearest neighbors) graph have been used for data clustering. It skillfully overcomes many major shortcomings of k-means algorithms, especially about the selection of the initial centers of clusters. However, it does face its own challenge: sensitivity to the choice of the neighborhood size parameter k, which is crucial for selecting the nearest neighbors during the clustering process. In this design, the Jaya optimization method is used to select the K parameter in the KNN method.

The experiment on real-world network data results show that the proposed approach significantly improves the accuracy of methods in community detection in social networks. On the other hand, it seems to offer some potential for discovering a more refined hierarchy in social networks and thus becomes a useful tool in the analysis of social networks.

This paper introduces an enhancement to the KNN graph-based clustering method by proposing a local average vector method for selecting the optimal neighborhood size parameter k. Furthermore, it presents an improved Jaya algorithm with KNN graph-based clustering for more effective community detection in social network graphs.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Drawing on covariance attribution theory, this study investigates how and when cross-cultural experience develops the entrepreneurial aptitude for rule-breaking. The authors sought to replicate findings in general psychology that morally relativistic thinking mediates these relationships. Further, extant ideas surrounding rebel-like archetypes of successful entrepreneurs were tested: that is, the more entrepreneurial a person considers themselves to be, the more likely they adopt such modes of thinking.

A second-stage moderated mediation model is applied using a novel between-subjects experimental priming design. Participants were recruited to reflect a generalizable sample of prospective entrepreneurs from the United States. Participants engaged in a randomly assigned priming activity to re-active their prior cultural immersion experiences. They then completed a context-adjusted experimental judgment task to assess rule-breaking.

Results show that reflection on prior cross-cultural experience is positively related to proximal scores in morally relativistic cognition. Moderating effects of entrepreneurial intention provide robust evidence that those high in entrepreneurial intention are more likely to rule-break when morally relativistic thinking is high, but that those low in entrepreneurial intention are not.

A growing research stream suggests cross-cultural experience can uniquely instill a range of entrepreneurial aptitudes. While psychology research has found evidence for “dark side” implications of cross-cultural experience, the authors posit that entrepreneurship scholars in this domain have been reluctant to tackle this due to the ethical grey areas between breaking rules constructively and breaking rules in more nefarious ways. This study provides evidence that morally relativistic cognition is more likely to drive people who consider themselves highly entrepreneurial to engage in rule-breaking tendencies.