Modelling innovation support systems for regional development – analysis of cluster structures in innovation in Portugal

The present article offers a concise theoretical conceptualization and operational analysis of the contribution of innovation to regional development. The latter concepts are closely related to geographical proximity, knowledge diffusion and filters and clustering. Institutional innovation profiles and regional patterns of innovation are two mutually linked, novel conceptual elements in this article. Next to a theoretical framing, the article employs the regional innovation systems concept as a vehicle to analyse institutional innovation profiles. Our case study addresses three Portuguese regions and their institutions, included in a web-based inventory of innovation agencies which offered the foundation for an extensive database. This data-set was analysed by means of a recently developed principal coordinates analysis followed by a Logistic Biplot approach (leading to a Voronoi mapping) to design a systemic typology of innovation structures where each institution is individually represented. There appears to be a significant difference in the regional innovation patterns resulting from the diverse institutional innovation profiles concerned. These profiles appear to be region specific. Our conclusion highlights the main advantages in the use of the method used for policy-makers and business companies.     

Market drivers of sustainability and sustainability learning capabilities: The moderating role of sustainability control systems

This study examines (i) the impact of market drivers of sustainability on the adoption of sustainability learning capabilities and (ii) the moderating role of sustainability control systems (SCS) on the relationship between market drivers of sustainability and sustainability learning capabilities. Drawing on the levers of control framework, stakeholder theory and organisational learning literature, survey data were collected from 175 large scale local and multinational companies operating in Sri Lanka. Findings reveal that market drivers of sustainability have a significant positive impact on sustainability learning capabilities. Whereas the interactive use of SCS shows a positive moderating impact, the diagnostic use of SCS shows a negative impact. The study enhances our understanding of (i) the influence of market drivers of sustainability on the adoption of sustainability learning capabilities and (ii) the use of SCS in enabling sustainability learning capabilities. The study reveals novel insights for managers responding to changing market drivers of sustainability, on how to (re)align different uses of SCS to enable sustainability learning capabilities.     

Tax-benefit systems and differences in aggregate labour force participation: Comparative evidence from the Czech Republic and Hungary

This paper investigates the extent to which cross-country differences in aggregate participation rates can be explained by differences in tax-benefit systems. We take the example of two countries, the Czech Republic and Hungary, which – despite a lot of similarities – differ markedly in labour force participation rates. Using comparable individual-level labour supply estimates, we simulate how the aggregate participation rate would change in one country if the other country’s tax and social welfare system were adopted. The estimation results for the two countries are quite similar, suggesting that individual preferences are essentially identical in the two countries. The simulation results show that about one-third of the difference in the participation rates of the 15–74 year-old population and more than two-thirds of the participation of the prime-age population can be explained by differences in the tax-benefit systems.     

Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts).     

A new hub and spoke system proposal: A case study for Turkey's aviation industry

In this paper, we are proposing a multi-objective mathematical model for the selection of a newly constructed hub and spoke system. The objectives of this model are maximizing aircraft utilization and revenue whilst reducing the commercially infeasible network detour factor. The sensitivity analysis of the model is tackled using weights related to the objectives as well as the network detour factor. The number of available aircraft and the range that an aircraft can reach are also considered in this model. Since Istanbul has already got a hub and spoke system with busy airports on both sides of the city, the model is applied to three other major cities of Turkey, Ankara, Antalya, and Izmir. The test data consists of over 90 cities in Europe and in the Middle East. The data includes unit passenger revenues and operating costs for the segments, distances between cities and hubs, expected load factors and flying times of segments. The scenarios are tested under specific expectations of airline network experts and the results are visualized by using Pareto front graphs. Compared to other candidates, Antalya stands out as a good choice for a new hub and spoke system in Turkey. The results of this model could be helpful for airlines and other airports in Turkey in order to identify their potential and competitive position in relation to their counterparts.     

基于多维频谱地图的干扰规避

针对复杂电磁环境下卫星移动通信系统可靠通信需求，利用频谱地图多维数据呈现优势，提出了基于多维频谱地图的干扰规避方法。通过建立卫星移动通信系统波束、时隙、子频带、干扰强度等多维信息关联的频谱地图，利用数据挖掘方法对频谱可用情况进行预测，基于预测结果及用户QoS(Quality of Service)需求生成干扰规避策略，通过星地联合频谱资源调配实现系统干扰规避。该方法为卫星移动通信系统干扰规避提供了一种全新的思路，可提升卫星移动通信系统干扰防护能力。     

Does the spatial representation affect criteria weights in environmental decision-making? Insights from a behavioral experiment

The need and interest to consider cognitive and motivational biases has been recognized in different disciplines (e.g. economics, decision theory, risk analysis) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes spatial Multi Criteria Decision Analysis (MCDA) a particularly interesting domain to explore new dimensions of cognitive biases. This study proposes a behavioral experiment aimed at discovering to what extent the spatial visualization (i.e. maps) of criteria versus the non-spatial one (i.e. tables) can bias the weight elicitation phase of a spatial MCDA process. The experiment simulates a very common analysis in environmental and land use planning: land suitability analysis. Our findings show that there are significant consequences on how important we perceive a certain criterion to be, depending on whether it is represented as a map or as a table among a mix of maps and tables. Indeed, the map representation of the same criterion leads to higher weights attributed to that criterion compared to the table representation. Visualizing the same information as a map or as a table, although technically equivalent, is thus not psychologically equivalent for Decision Makers. The results of this experiment are expected to have implications for spatial decision-making processes, by generating better awareness on the impacts of map-mediated land suitability analysis.     

The performance of performance appraisal systems: understanding the linkage between appraisal structure and appraisal discrimination complaints

Abstract

Employee perceptions of the fairness of performance evaluations are critical to the success of any appraisal system. Research on performance management includes extensive studies on how bias emerges in the appraisal process. Despite this, there is no empirical evidence linking formal discrimination complaint filings – a key measure of bias - and performance appraisals. To close this gap, we conduct an empirical analysis using information on appraisal systems and discrimination complaints from the US federal government. Our findings suggest that agencies with better-designed appraisal systems will experience higher appraisal-related discrimination complaints, contrary to expectations. In particular, an expansion of training and voice opportunities are associated with an increase in appraisal discrimination complaints, while increased differentiation between performers is not consistently associated with complaints. For managers struggling with performance management, it may be better to spend time on improving performance-focused interpersonal communication rather than redesigning appraisal systems.     

Inference for large financial systems

We treat the parameter estimation problem for mean‐field models of large interacting financial systems such as the banking system and a pool of assets held by an institution or backing a security. We develop an asymptotic inference approach that addresses the scale and complexity of such systems. Harnessing the weak convergence results developed for mean‐field financial systems in the literature, we construct an approximate likelihood for large systems. The approximate likelihood has a conditionally Gaussian structure, enabling us to design an efficient numerical method for its evaluation. We provide a representation of the corresponding approximate estimator in terms of a weighted least‐squares estimator, and use it to analyze the large‐system and large‐sample behavior of the estimator. Numerical results for a mean‐field model of systemic financial risk highlight the efficiency and accuracy of our estimator.     

基于离散选择模型的推荐系统改进算法

准确地预估用户的点击率,并根据该概率对商品排序以供用户选择在推荐系统领域有着重要的意义。推荐系统中常用的因子分解机等机器学习模型一般只考虑用户选择单个商品的概率,忽略了候选商品之间的相互影响,离散选择模型则考虑将商品候选集作为整体进行考虑。提出了使用深度学习模型来改进离散选择模型,模型使用相对特征层、注意力机制等网络结构帮助深度学习模型进行不同商品间的特征比较,研究结果表明引入离散选择模型的深度学习模型表现优于梯度提升决策树、因子分解机等模型。