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From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop a decision-oriented approach for the valuation of football players that could theoretically help clubs determine the subjective value of investing in a player to assess its potential economic advantage.

We build on a semi-investment-theoretical risk-value model and elaborate an approach that can be applied in imperfect markets under uncertainty. Furthermore, we illustrate the valuation process with a numerical example based on fictitious data. Due to this explicitly intended decision support, our approach differs fundamentally from a large part of the literature, which is empirically based and attempts to explain observable figures through various influencing factors.

We propose a semi-investment-theoretical valuation approach that is based on a two-step model, namely, a first valuation at the club level and a final calculation to determine the decision value for an individual player. In contrast to the previous literature, we do not rely on an econometric framework that attempts to explain observable past variables but rather present a general, forward-looking decision model that can support managers in their investment decisions.

This approach is the first to show managers how to make an economically rational investment decision by determining the maximum payable price. Nevertheless, there is no normative requirement for the decision-maker. The club will obviously have to supplement the calculus with nonfinancial objectives. Overall, our paper can constitute a first step toward decision-oriented player valuation and for theoretical comparison with practical investment decisions in football clubs, which obviously take into account other specific sports team decisions.

The purpose of this paper is to explain the effects of innovation, specialisation, qualifications and sectoral structure on the resilience of German regions (municipal level) facing the Great Recession in 2008/2009.

To calculate the effects of various variables on the resilience of German regions against the Great Recession, the authors use quantile regressions. To measure resilience, the authors create a number of indexes representing different parts of the economy: resistance performance index, recovery performance index, shift-share resistance index, shift-share recovery index, manufacturing resistance index, manufacturing recovery index, service resistance index and service recovery index.

The results of this study confirm that locations with employment growth before the crisis and with a good industry structure show better employment dynamics during and after the crisis. The authors find evidence for positive relationship between innovativeness, qualification, the share of the service sector, specialisation and resistance. The authors obtain positive results for related variety and both resistance and recovery. The share of the manufacturing sector only shows a positive relationship with recovery.

The authors expand the existing literature in three aspects: First, instead of using regions as observation units, the authors conduct the analyses on the basis of municipalities and their surroundings. By doing so, the authors reduce the modifiable area unit problem because the authors do not rely on regions defined for administrative reasons. Second, the authors apply quantile regressions to detect nonlinear effects. Third, in addition to the resilience of the whole economy, the authors also study the resilience of the manufacturing and service sectors separately and examine the resilience of the local shift effect.

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

Extant literature in supply chain management tends to address a portion of the product flow to make food accessible to clients in need. The authors present a broader view of food insecurity and present nuances relevant to appreciate the complexities of dealing with this social problem.

The authors conducted an inductive study to reveal the deep meaning of the context as managers of nonprofit organizations (NPO) define and address food insecurity. The focus was on a delimited geographic area for capturing interactions among NPOs which have not been described previously.

This study describes the role of supply chains collaborating in unexpected ways in the not-for-profit context, leading to interesting insights for the conceptual development of service ecosystems. This is relevant because the solution for the food insecure stems from the orchestration of assistance provided by the many supply chains for social assistance.

The authors introduce two concepts: customer sharing and customer release. Customer sharing enables these supply chains behave like an ecosystem with no focal organization. Customer release is the opposite to customer retention, when the food insecure stops needing assistance.

The authors describe the use of customer-centric measures of success such improved health measured. The solution to food insecurity for an individual is likely to be the result of the orchestration of assistance provided by several supply chains.

The authors started asking who the client is and how the NPOs define food insecurity, leading to discussing contrasts between food access and utilization, between hunger relief and nourishment, between assistance and solution of the problem, and between supply chains and ecosystems.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.

This study aims to ascertain the personal characteristics of a group of successful academic entrepreneurs in a South African university enterprise and the prevalent barriers and enablers to their entrepreneurial endeavour.

The authors used a Delphi process to identify and rank the characteristics, enablers, barriers and behaviours of entrepreneurial academics, with a Nominal Group Technique applied to establish challenges they encounter managing their enterprise and to propose solutions.

Perseverance, resilience and innovation are critical personal characteristics, while collaborative networks, efficient research infrastructure and established research competence are essential for success. The university’s support for entrepreneurship is a significant enabler, with unnecessary bureaucracy and poor access to project and general enterprise funding an impediment. Successful academic entrepreneurs have strong leadership, and effective management and communication skills.

The main limitation is the small study participant group drawn from a single university enterprise, which complicates generalisability. The study supported the use of Krueger’s (2009) entrepreneurial intentions model for low- and middle-income country (LMIC) academic entrepreneur investigation but proposed the inclusion of mitigators to entrepreneurial activation to recognise contextual deficiencies and challenges.

Skills-deficient LMIC universities should extensively and directly support their entrepreneurial academics to overcome their contextual deficiencies and challenging environment.

This study contributes to addressing the paucity of academic entrepreneur research in LMIC contexts by identifying LMIC-specific factors that inhibit the entrepreneur’s movement from entrepreneurial intention to entrepreneurial action.

This study aims to investigate the interaction effect between offering supply chain finance (SCF) programmes and sustainability ratings on the liquidity performance of buyers and suppliers.

The study uses a unique sample of buyers that each have an SCF programme. The sample is complemented with financial information and sustainability scores. The data is analysed through a random effects model.

Aligning with recent advances in SCF literature, the results confirm a tendency for SCF programmes to favour buyers over suppliers. However, the relationship between SCF programme adoption and liquidity performance for buyers and suppliers is positively moderated by the strong sustainability performance of both parties.

Buyers and suppliers are advised to implement and adopt effective SCF programmes that are beneficial for both parties. For buyers, the authors suggest leveraging on SCF programmes as incentives to foster sustainable behaviour among suppliers. For suppliers, the authors recommend caution before joining programmes offered by buyers that do not perform well on sustainability.

Enhancing sustainability within global supply chains and fostering favourable payment practices towards suppliers are crucial for policy development and regulation. The findings clarify the connection between both components, offering valuable insights for policymakers in this domain.

The study is built on a manually picked, unique database of buyers offering SCF programmes to their suppliers. This allows, across a large sample, an evaluation of the differences between buyers that offer SCF programmes and those that do not.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

The purpose of this paper is to provide answers regarding the factors that motivate or discourage the quadruple helix (QH) stakeholders and the wider public in citizen science (CS) activities. The research reveals a current overview of the perceptions, attitudes, concerns and motivation with regard to development of CS ecosystem in four countries: Greece, Lithuania, the Netherlands and Spain.

The researchers deploy a mixed methodology, entailing an in-depth literature review and a large-scale quantitative survey (approximately 2,000 citizens) targeting QH stakeholders and general public from the local national ecosystems. The results contain both descriptive statistics and statistical analysis per country. After the comprehensive overview of drivers and barriers regarding the participation in CS activities in general, the focus is narrowed down on the engagement motivation of different QH stakeholders and the differences in enabling/hindering factors at the local ecosystems.

Depending on the country and the pre-existing level of CS maturity, the results provide a complicated network of factors that unlock or block participation in CS activities. These factors include, to name a few, political maturity, civic engagement, technological infrastructures, economic growth, culture of stakeholder collaboration, psychological stimulus and surplus of resources. The implications of the findings necessitate the alignment of the envisioned CS ecosystem with the local dynamics in each country.

The quantitative nature of the survey method, limited sample size and only four countries context are noted as limitations of the study and offer future research potential for longitudinal settings and mixed-methods studies.

The results contribute to the wider literature on CS that focuses on perspectives, possibilities and differences in local contexts with respect to the public engagement by developing CS ecosystem. At the same time, its added value lies in the overall practical proposition, and how the latter can effectively and efficiently attract and retain different stakeholder groups and citizens, under a collaborative approach.

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.

A review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.

This study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.

The results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.

This is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.