Classification of micro,small and medium enterprises (M-SME) based on their available levels of knowledge

This paper proposes a novel and practical method of classifying micro, small and medium enterprises (M-SME) based on their available levels of knowledge. This classification considers that the specific problems that dominate a company’s operations are related to the level of knowledge available. Therefore, identifying the dominant problem groups facing the company can enable an estimate of the level of knowledge available in the enterprise.Data from 2698 Mexican M-SMEs are used to identify operational problems. The main problem groups are obtained through a cluster analysis. The proposed classification consists of three levels of knowledge based on the interpretation of the dominant problem groups in each enterprise. Each of the 2698 Mexican M-SME are classified by a discriminant analysis.Nearly half of the M-SME are classified as having a lower level of available knowledge, and only 10% are classified with the highest level. No difference is observed between the size of the company and the level of available knowledge. This means that growth in the number of employees and sales of M-SMEs is not necessarily accompanied by an accumulation of knowledge that companies can use to improve their operations.     

Service quality of airports' food and beverage retailers. A fuzzy approach

Nowadays the profitability of airports is largely based on non-aeronautical or commercial activities, and particularly on retail and food and beverage services. Further, researchers concur that shopping, eating and drinking in airports have to be considered an important part of tourists' experience and activities that can significantly enhance or damage the tourist destination image. Despite this, there is still little research that analyses how service quality (SQ) is perceived by passengers consuming food and beverages (F&B) in airport areas. This study aims to deepen the scientific debate on this topic. Specifically, this study applies fuzzy numbers with a sample of 551 passengers flying from Olbia-Costa Smeralda Airport (Sardinia Region, Italy) with the aim of determining how they perceive the SQ delivered by F&B retailers and whether age plays a determinant role in segmentation. Findings reveal which F&B features outperform others; furthermore, they show that age is a moderating factor in consumer satisfaction, with older passengers being less satisfied than their counterparts. This study adds knowledge to the literature devoted to SQ, applying a fuzzy number approach to the under-investigated research area related to F&B consumption in airport areas. Further, it provides information useful to airport managers on the features of F&B services that are most important in shaping consumer satisfaction, based also on their age. Limitations of the study are also discussed and suggestions for future research are given.     

Comparing efficiency of holding business model and individual management model of airports

This research compares the efficiency of holding business model to individual management model of airports, employing some robust non-parametric partial frontier-based methods to compare the statistical distributions of efficiency, under different scenarios, to find out which group of airports yields better global performance. The comparison between groups will follow a Malmquist index decomposition, which seems to be the most appropriate tool for within- and inter-group performance comparison. For this purpose, a sample of 145 airports from three continents is utilized. The results provide evidence that European airports are the most productive ones, and within this cluster, the individual management model presented a significant frontier shift with respect the holding cluster frontier, meaning that the former is much more productive than the latter.     

Dynamic DEA models with network structure: An application for Iranian airlines

Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Framing the usefulness of eHRM in talent management: A case study of talent identification in a professional services firm

As talent management evolves from intuitive to evidence‐based decision‐making, the role of electronic Human Resource Management (eHRM) to gather, distribute, and analyze data becomes more critical. However, surprisingly few academic studies investigate the role of technology in talent management. Drawing on a qualitative case study of talent management in a large professional services firm, this paper critically examines how eHRM information technologies are framed as useful within talent identification discourses. The findings reveal two distinct but interrelated sets of processes employed to identify talent and suggest that the perceived usefulness and centrality of eHRM are influenced by how stakeholders shape their understanding of effective talent management. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.     

中国政府科技投入变化态势及与经济增长的关系

全面剖析了1953—2014年中国政府科技投入的规模和强度的变化态势,系统分析了政府科技投入与经济增长的弹性系数的变化情况。通过回归分析和协整检验,分析了1953—2014年中国政府的科技投入与经济增长的相关性。结果表明:1953—2014年中国政府科技投入的规模和强度不断加大,政府科技投入对经济增长的平均贡献率达到13.2%;政府科技投入与GDP增长之间存在较强的正相关关系和长期动态均衡关系。指出:为实施创新驱动发展战略、实现建设创新型国家的宏伟目标,应稳定增加政府科技投入、优化科技投入结构、完善和创新科技投入管理体制机制。     

Live and let die: A survival analysis of foreign R&D units in Swedish MNEs

This paper develops and tests a set of hypotheses regarding factors that influenced the longevity of foreign research and development units in Swedish multinational enterprises over the period 1992–2012. The results reveal an underexplored aspect of the R&D internationalization—the volatility of foreign R&D laboratories. During the investigated period, more than 40% of the R&D units in the sample had been terminated. The results substantiate earlier research regarding the negative effects of mergers and acquisitions on R&D in acquired units but show that these effects are not immediate. They appear – if at all – with a time lag of several years. The hazard of closure for an individual unit seems to be more strongly related to its role and position within the MNE than to local country characteristics. It was smaller for strongly locally embedded units and units with global mandates, but – contrary to expectations – the hazard was greater for units highly integrated with the rest of the MNE.     

What drives customer loyalty in grocery retail? Exploring shoppers' perceptions through associative networks

Mental associations play a key role in shaping customer-brand relationships and are critical to the development of favourable attitudes and emotional attachment towards a brand. By exploring shoppers’ knowledge structures, this study identifies what drivers of customer loyalty are more relevant to customers in the context of grocery retail. A mix-method study on shoppers’ perceptions and values associated to their most patronised grocery store is presented. Through focus group discussions, concept maps and associative network analysis, three types of associations are identified: functional, relational and premium store associations. Salience and relationships among these dimensions are also discussed.     

Interregional trade network analysis for road freight transport in Greece

This paper suggests a flexible decision support framework for the strategic planning of a freight transport hub network in Greece. The proposed methodology treats practical aspects related to the optimal number, location and geographical covering of hubs, through the network analysis of interregional trade, based on original survey data for road freight flows during 2004–2012. The results offer insights into the hierarchical structure of the network and related investment priorities, as the hub role of a prefecture is found to be strongly influenced by high population densities and manufacturing specialization, and its location along highway corridors.