How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis

In this empirical study, a five-stage methodology is used to examine the efficiency of 45 worldwide known airline companies from the financial, operation and marketing perspectives. Initially, the superefficient data envelopment model is run with inputs and outputs that are selected based on the literature review. However, because 21 out of 45 airline companies are found to be efficient based on this analysis, a stepwise regression-based mechanism is applied to four reduced models – one for each output variable – for better discrimination. The outputs are, namely, net profit margin (financial output), passengers carried, on-time departure performance (operational outputs), and customer satisfaction (marketing output). In this way, the significant input variables are found for each reduced model. In the third stage, in order to provide even more discrimination, social network-based eigenvector centrality values are used as the weights of the superefficiency scores, and the strengths and weaknesses of efficient airlines for each output are specified in terms of their related significant inputs. The results show that, when net profit margin is taken as an output, Vietnam Airlines has the top weighted superefficiency value and excels in terms of available seat kilometers and liquidity, but it should improve its debt level. Although Norwegian Airlines has the highest efficiency with respect to debt level, it is not the best role model because its eigenvector centrality value is relatively low. However, Norwegian airlines also has the highest weighted superefficiency and acts as a role model in terms of on-time departures with respect to this output. Its main strength is liquidity, and it has no significant weaknesses. On the other hand, in terms of overall satisfaction and passengers carried, Vietnam Airlines and Thai Airways are the leaders, respectively. Vietnam Airlines is the only superefficient company with respect to overall satisfaction, while the basic strengths of Thai Airways in terms of passengers carried are its employee and fleet, and it has no significant weakness. A final aggregation of the results is made by making pairwise comparisons of the relative importance of four outputs for 7 experts selected from different departments of airline companies. According to the results, Net Profit Margin has the highest priority, followed by On-time Departure and Overall Customer Satisfaction, while passengers carried has the lowest importance. Based on these relative priorities, it can be said that Vietnam Airlines can be accepted as the top performing airline company, followed by Norwegian Airlines.     

The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources

Big data analytics have transformed research in many fields, including the business areas of marketing, accounting and finance, and supply chain management. Yet, the discussion surrounding big data analytics in human resource management has primarily focused on job candidate screenings. In this article, we consider how significant strategic human capital questions can be addressed with big data analytics, enabling HR to enhance overall firm performance. We also examine how new data sources that help assess workforce performance in real time can assist in the identification and development of the knowledge stars that contribute to firm performance disproportionately as well as help reinforce firm capabilities. But in order for big data analytics to be successful in the HR field, regulatory and ethical challenges must also be addressed; these include privacy concerns and, in Europe, the General Data Protection Regulation (GDPR). We conclude by discussing how big data analytics can facilitate strategic change within HR and the organization as a whole.     

Assessing data quality: A managerial call to action

While awareness of data quality has increased in recent years, there have been very few studies on the actual level of data quality within organizations. This article outlines the analysis of 75 data quality assessments collected over the course of 2 years from a wide range of organizations, data sets, and business processes. The results reveal that data is in far worse shape than most managers realize. On average, 47% of recently created data records have at least one critical error. High-quality data is the exception, with only 3% of the DQ scores rated acceptable (≥97%). Indeed, the results suggest an unhealthy organizational tolerance of bad data and underscore the magnitude of improvement organizations need to make in order to be truly effective in the knowledge economy. By providing a unique insight and benchmark for data quality practitioners, this article serves as a call-to-action for all organizations—regardless of size and type—to determine their level of data quality. Finally, we set out a typology that presents a categorical scheme to promote preemptive actions against the most frequent types of data error.     

Shipping cost and development of the landlocked developing countries: Panel evidence from the common correlated effects approach

We estimate the impact of shipping cost on development for landlocked developing countries (LLDCs). Since container trade is important to them, we construct a country-specific measure of shipping cost, called HarpexCost, which combines the global cost of container shipping with information on how exposed to container shipping each LLDC is. We employ the common correlated effects (CCE) estimator of Pesaran (Econometrica, 2006; 55: 967) to first estimate the impact of HarpexCost on the LLDCs’ development, and then recover the actual impact of shipping cost from these estimates. Overall, we observe that shipping cost has large negative effects on the LLDCs. Building upon these results, we provide new estimates on the cost of landlockedness and how trade benefits their development.     

Trading activities,productivity and markups: Evidence for Spanish manufacturing

This work analyses the firms' internationalisation strategies of importing intermediates and exporting output, and the potential rewards of these activities in terms of total factor productivity (TFP), as a proxy for marginal costs, and markups. It further deepens into the study of the relationship between internationalisation strategies and markups by disentangling whether it operates through affecting firms' marginal costs and/or firms' prices. The panel database employed in this paper is the Spanish Survey on Business Strategies (ESEE) for the period 2006–14. Results in the paper distinguish between SMEs and large firms and indicate that there is high persistence in the performance of these activities and in firms' TFP and markups. For SMEs, we obtain rewards from importing inputs as well as exporting output in terms of TFP and markups. For large firms, we obtain rewards in TFP from the importing activity and rewards in markups from the exporting activity. Finally, we find evidence that the effects of internationalisation strategies on markups are due to both a price channel and a marginal cost channel.     

The Cinderella moment: Exploring consumers' motivations to engage with renting as collaborative luxury consumption mode

Past literature argued that the purchase of luxury goods is driven by people's motivation to conform or fit into our economic and social system. In this study, the authors focus on a new aspect of consumption, that is, renting instead of purchasing luxury goods, backed by the emerging opportunities of sharing economy platforms. Drawing upon the analysis of spontaneous consumers' online communications (in the form of tweets), this study aims to investigate the motivations to engage with luxury garment renting within a collaborative consumption context. To this end, a series of automatic content analyses, via two studies, were conducted using the tweets posted with respect to the Run the Runway collaborative consumption platform. Results demonstrate consumers' increased willingness to show their social status through renting rather than owning luxurious apparel based on five main motivators (need to wear new clothes for a special event, inspirations created by the products/brands, possibility to explore a new way of consuming luxury goods, need to make more sustainable choices, and to increase the life cycle of each luxury product). The implications of these findings are discussed, while they pave the way for future research in collaborative consumption of luxury retailing.     

林业产业结构升级对国有林区改革绩效的影响

基于2003—2016年东北、内蒙古重点国有林区87个林业局的面板数据,以林业总产值、森林管护面积、年末在岗职工人数作为衡量指标,采用面板数据固定效应模型分析林业产业结构升级对国有林区改革绩效的影响机制。结果表明:林业产业结构高级化对国有林区改革绩效具有促进效应,但产业结构升级速度过快也会在一定程度上对国有林区改革绩效产生抑制效应;林业财政投资额对林业总产值具有显著促进作用;年末在岗职工人均工资对森林管护面积和年末在岗职工人数具有显著促进作用;林业工作站数量对森林管护面积具有显著促进作用。因此为推动国有林区改革工作顺利进展,重点国有林区林业产业结构升级应与经济发展水平和生态环境状况相适应。     

Using paradata to collect better survey data: Evidence from a household survey in Tanzania

Data are a key component in the design, implementation, and evaluation of economic and social policies. Monitoring data quality is an essential part of any serious, large‐scale data collection process. The purpose of this article is to show how paradata should be used before, during, and after data collection to monitor and improve data quality. To do this we use timestamps, global positioning system (GPS) coordinates, and other paradata collected from an 800‐household survey conducted in Tanzania in 2016. We demonstrate how key paradata can be used during each phase of a research project to identify and prevent issues in the data and the methods used to collect it. Our results corroborate the importance of collecting and analyzing paradata to monitor fieldwork and ensuring data quality for micro data collection in developing countries. Based on these findings we also make recommendations as to how researchers can make better use of paradata in the future to manage and improve data quality. We argue for an expansion in the understanding and use of varied paradata among researchers, and a greater focus on its use for improving data quality.     

Duration of price promotion and product profit: An in-depth study based on point-of-sale data

Anecdotal evidence has shown that retail price promotions can help small and medium-sized retailers enhance their sales, and thus profits. However, most marketing managers usually stop a promotion after a certain duration. This study aims to explain why these retailers discontinue their price promotion. Our approach posits that overall contributions of a price promotion to the product profit progressively diminish with time. In this study, we present a theoretical framework to explain the relationship between duration and profit effects of price promotion and propose statistical models to empirically examine this framework using point-of-sale (POS) data. Our findings provide empirical support that the effect of price promotion on the product profit has a downward trend with elapsed time. The results are helpful for marketers to understand how price promotions dynamically influence product profit and when the promotion should be terminated.     

基于多源数据的国土空间高质量利用评价思路

研究目的：新时代国土空间规划背景下，提出利用多源数据评价国土空间高质量利用的思路，为辅助编制高质量的国土空间规划提供支撑。研究方法：文献分析法、归纳演绎法。研究结果：在国土空间规划新趋势下，以国土空间高质量利用内涵为引导，提出生态空间、农业空间和城镇空间的高质量利用目标与评价维度，并构建了基于多源数据的国土空间高质量利用的评价方法框架。研究结论：国土空间高质量利用评价应在统筹各类空间不同目标间关系的基础上，结合研究和实践需要，因地制宜进行评价，进而形成各空间的发展合力，推进国土空间的高质量利用。