This paper investigates the competitive rationale for firms to invest in marketing activities aiming to enhance valuation and achieve differentiation and competitive advantage, while carrying the strategic risks of causing unintended negative consequences. We build a stylized theoretical model where firms offering similar (homogenous) products are competing by determining their marketing strategy and pricing. Each firm must choose between several marketing activities that have different potentials of enhancing consumers’ product valuations while carrying some risk of lowering consumer valuation if unintended negative outcomes occur. The stochastic nature of marketing implies that (1) even when both firms invest the same amount of money aiming to enhance product valuations by the same level, there will be a variety of (posterior) vertical differentiation scenarios where the consumers could value either firm’s product as better as or worse than the rival’s. (2) The firms may employ marketing activities that do not even lead to gains in consumer product valuation in expectation. The duopoly model analysis indicates that associated with strategic pricing, even such stochastic marketing activities may constitute desirable strategies for two a priori symmetric firms in order to avoid a Bertrand type competition as the benefit from differentiation is found to be significant enough to offset the unintended negative outcomes. The oligopoly model analysis indicates that there is an increased incentive to take marketing risk when there is a greater level of competitive intensity in the marketplace. Preliminary experimental evidence is presented to support the main findings from theoretical model analyses. The paper thus provides important managerial implications for firms contemplating investment in seemingly risky marketing activities.
There is no better place to explore the relationship of industry enclaves to urban life than China, where traditional danweis (work units) have coexisted with new foreign direct investment enclaves. Here we draw on original interviews with workers at Wuhan Iron and Steel Company (WISCO) and Foxconn in the city of Wuhan to examine industry enclaves old and new in terms of their spatial arrangement, work, institutions, and social life and identity. The article is one of the first to integrate urban and economic geographical perspectives on the subject of enclaves. It provides evidence of similarities and contrasts in the spatial arrangement of work, institutions, life and identity centred on industry enclaves old and new. These contrasts reflect wider relations between the state and the market and between social subject and commodified labour in China. In conclusion, we identify several research directions concerning the scale, diversity and reach of urban enclavism in China and beyond. 相似文献
Data Envelopment Analysis (DEA) window analysis with ideal window width is applied to evaluate the green technology innovation efficiency of 28 manufacturing industries in China during 2006–2014. The obtained results are compared with those calculated using the traditional DEA model, and convergence analysis of the efficiency is conducted. Five years is the obtained ideal window width and DEA window analysis with ideal window produces results closer to reality for China's manufacturing industry. The overall efficiency of the green technology innovation in the manufacturing sector is low following a wave-shaped curve – first decreasing, then increasing and decreasing again, with large inter-industrial differences. There are 8 high-, 14 medium- and 6 low-efficiency industries. A convergence trend in the green technology innovation efficiency within the 28 manufacturing industries exists, implying a catch-up effect between them. 相似文献
We introduce the Speculative Influence Network (SIN) to decipher the causal relationships between sectors (and/or firms) during financial bubbles. The SIN is constructed in two steps. First, we develop a Hidden Markov Model (HMM) of regime-switching between a normal market phase represented by a geometric Brownian motion and a bubble regime represented by the stochastic super-exponential Sornette and Andersen (Int J Mod Phys C 13(2):171–188, 2002) bubble model. The calibration of the HMM provides the probability at each time for a given security to be in the bubble regime. Conditional on two assets being qualified in the bubble regime, we then use the transfer entropy to quantify the influence of the returns of one asset i onto another asset j, from which we introduce the adjacency matrix of the SIN among securities. We apply our technology to the Chinese stock market during the period 2005–2008, during which a normal phase was followed by a spectacular bubble ending in a massive correction. We introduce the Net Speculative Influence Intensity variable as the difference between the transfer entropies from i to j and from j to i, which is used in a series of rank ordered regressions to predict the maximum loss (%MaxLoss) endured during the crash. The sectors that influenced other sectors the most are found to have the largest losses. There is some predictability obtained by using the transfer entropy involving industrial sectors to explain the %MaxLoss of financial institutions but not vice versa. We also show that the bubble state variable calibrated on the Chinese market data corresponds well to the regimes when the market exhibits a strong price acceleration followed by clear change of price regimes. Our results suggest that SIN may contribute significant skill to the development of general linkage-based systemic risks measures and early warning metrics. 相似文献
