Does retail type matter? Consumer responses to channel integration in omni-channel retailing

A critical issue faced by marketing practitioners today is orchestrating strategies that provide a smooth consumer experience in an omni-channel environment. The extant literature offers limited guidance on managing the consumer journey in an omni-channel environment across different retail types. Using the S–O-R framework as its basis, this study generates novel insights by examining how different types of retailers influence consumer perceptions of channel integration (CPCI) as well as consumer empowerment, trust, satisfaction, and patronage intention. Data from 736 consumers was collected using purposive sampling to target those who interact with retailers from high-end specialty stores, department stores, and hypermarkets. The data was then analysed using partial least squares structural equation modelling (PLS-SEM). We find that consumers from high-end specialty stores, hypermarkets, and department stores have different perceptions when patronising the omni-channel retail business. The implications of the study are discussed and suggestions for future research are presented.     

The trend of the Gini coefficient of China (1978–2010)

ABSTRACT

This study proposes a new approach to analyse the effects of an overlap term on the calculation of the overall Gini coefficient and estimates China’s Gini ratios since the adoption of the economic reform and open-door policies. A decomposition of the Chinese Gini coefficient for 1978–2010 reveals that the key factor contributing to income inequalities is the income disparity between rural and urban inhabitants. We further investigate the features of this income inequality between rural and urban areas and employ statistical approaches to evaluate the effects of urbanisation and rural-to-urban average income on nationwide income inequality. The results show that accelerating the pace of urbanisation is mainly responsible for decreasing China’s income disparity. Drawing on these results, we conclude with suggestions for related policies.     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

深入社会改革,加快建设和谐无锡——无锡“十二五”社会改革途径探讨

经过三十多年的改革开放以后,无锡和全国一样,经济社会有了巨大的发展,但是,社会发展滞后于经济发展的情况仍然存在,急需深入社会改革,推动社会发展。本文在回顾无锡在"十一五"期间社会改革取得的成就基础上,分析了无锡社会发展存在的问题和面临的挑战和机遇,提出了"十二五"期间无锡深化社会改革的目标以及在政府职能转换、社会管理模式创新、实现公共服务均等化和城乡协调发展等四个方面的改革建议,最后提出了保障改革的一些措施。     

Impacts of peer-to-peer accommodation on the hotel industry: Hoteliers’ perspectives

The sharing economy is a new phenomenon that has considerable implications for traditional industries in general and the hospitality sector in particular. Although some recent studies have investigated the effects of sharing economy on the hotel industry, they primarily focused on quantifying its effects which are not exploratory for a phenomenon. This study attempts to achieve two research objectives. First, an exploratory qualitative method via a semi-structured in-depth interview is employed to investigate the impacts of P2P accommodation on the industry from hoteliers’ perspectives in China. Second, the current study provides valuable insights about traditional hotel marketing and operations. A social science perspective is proposed because prior hospitality research, merely in its commercial sense, fails to capture the essence of hospitality. Results indicate that P2P accommodation has effects on the hotel industry in terms of host–guest interactions, product offerings, staff empowerment, and platform collaboration. The study also suggests that the extent to which P2P accommodation impacts the hotel industry is different in terms of hotel star ratings and operating model. P2P accommodation and the hotel industry in China have a supplementary relationship. This study contributes to social studies of the hospitality literature by gaining insights from hotel senior management level. It also has great implications for the hotel marketing and management practices within the sharing context.     

Agriculture–nutrition linkages with heterogeneous,unobserved returns and costs: Insights from Tajikistan

Agriculture–nutrition linkages (ANLs) have been increasingly investigated in the literature. However, nutritional returns and costs of household agricultural production practices (APPs) in semisubsistence settings are poorly understood. We fill these knowledge gaps using pooled cross-section data sets in Tajikistan, where semisubsistence farming and undernutrition coexist despite relatively good agricultural infrastructure and education systems. Agricultural diversification, yield enhancement, production expansion are positively associated with various nutritional outcomes, particularly in areas with poor food market access. Decomposition exercises suggest that nutritional returns and costs of these APPs vary across households, and the adoption of APPs is driven by the expected nutritional returns. In Tajikistan, improving nutrition through household ANLs requires growing the smallholder agricultural sector in multiple dimensions, including diversification, intensification, and expansion, while also understanding better the pathways of ANLs and addressing bottlenecks at appropriate stages of such pathways.     

Structural production layer decomposition: a new method to measure differences between MRIO databases for footprint assessments

Recent empirical assessments revealed that footprint indicators calculated with various multi-regional input–output (MRIO) databases deliver deviating results. In this paper, we propose a new method, called structural production layer decomposition (SPLD), which complements existing structural decomposition approaches. SPLD enables differentiating between effects stemming from specific parts in the technology matrix, e.g. trade blocks vs. domestic blocks, while still allowing to link the various effects to the total region footprint. Using the carbon footprint of the EU-28 in 2011 as an example, we analyse the differences between EXIOBASE, Eora, GTAP and WIOD. Identical environmental data are used across all MRIO databases. In all model comparisons, variations in domestic blocks have a more significant impact on the carbon footprint than variations in trade blocks. The results provide a wealth of information for MRIO developers and are relevant for policy makers designing climate policy measures targeted to specific stages along product supply chains.     

THE BIAS OF THE MULTIPLIER MATRIX WHEN SUPPLY AND USE TABLES ARE STOCHASTIC

The literature on stochastic input–output (I–O) analysis has paid considerable attention to the bias in the Leontief inverse. This paper extends previous studies by assuming supply and use tables (SUTs rather than I–O tables or input coefficients matrices) to be stochastic. This is a natural starting point because SUTs have become the basic data sources for I–O applications. In a Monte Carlo simulation experiment, a given SUT is randomized in two different ways and the effects are determined for eight different multiplier matrices. The analysis is carried out for Spain, Italy, the Netherlands, Germany and Finland, using their SUTs for 2006. The findings indicate that, in general, biases are statistically significant but negligibly small. This corroborates earlier findings obtained for stochastic I–O tables.     

Determinants of reverse marketing knowledge transfer potential from emerging market subsidiaries to multinational enterprises’ headquarters

Emerging markets (EM) are becoming increasingly important for multinational enterprises because of their high growth potential and future prospects. The unique circumstances in EM lead to increased pressure to offer creative marketing solutions that can be leveraged across the multinational network. Setting up subsidiaries to tap into these markets offers companies the opportunity to integrate in the local community and access its knowledge-base for local and global innovations. Literature, however, reveals that EM subsidiaries have been largely ignored concerning their potential for reverse knowledge transfer (RKT), and marketing initiatives are expected to be developed in mature, developed markets. Our paper fills this gap in research and contributes to extant literature by identifying factors at unit, relationship and knowledge levels influencing RKT potential specific to marketing knowledge from EM subsidiaries. The conceptual discussion leads to study propositions and conceptual framework.     

All consuming surveillance: surveillance as marketplace icon

With consumers and their activities routinely visible through online, mobile and social media, to both their peers and to corporations, this article examines surveillance as a marketplace icon. Surveillance is central to the construction of consumers and markets. Many contemporary marketing practices are surveillant as they rely on the collection, analysis and application of consumer data to place advertising, define market segments and to nudge consumer behaviours. Consumer surveillance is also an enactment of corporate power, attempting to align individual preferences with corporate goals. The historical origins of surveillance and the emergence of the surveillance–industrial–entertainment complex are explored, which highlights how surveillance, as well as a process for defining markets is also an object of consumption. The future sees a huge struggle for consumer data between two great centres of surveillance power – the state and the corporation – as they battle over data use for national security.