Channel strategy: Formulation and adaptation

Inspired by open systems theories like the structural contingency theory (Lawrence and Lorsch 1967), population ecology theory (Hannan and Freeman 1977), and resource dependence theory (Pfeffer and Salancik 1978), several marketing scholars have investigated how channels adapt and organize themselves to cope with their environments. Curiously, however, the implication of such adaptive behaviour (i.e., the better adapted firms are more profitable) has not been investigated in the marketing literature. This paper aims to probe that question. Moreover, unlike previous marketing studies, we articulate the manufacturer's rather than the distributor's point-of-view, because channel strategy decisions are usually in the manufacturer's domain. We scrutinize firms' adaptive responses from a channel structure and channel task perspective. Results show that the better adapted firms deliver superior performance, and that the adaptive responses often occur subtly at the specific channel task level even when the channel structure itself may appear seemingly unaltered.structural contingency theory; population ecology theory; resource dependence theory;

Photodetachment in combined static and dynamic electric fields

Through an exact solution of the time-dependent Schrödinger equation for an electron in a static electric field plus the time-dependent electric field of the detaching radiation, the photodetachment cross section of [Formula Presented] is calculated. Careful attention is paid to ensuring proper limiting behavior as the frequency of the time-dependent field goes to zero. We do not find observable effects of a cross term between the two fields on the detachment cross section. Our results point to possible gauge dependence and other difficulties of S-matrix formulations of multiphoton detachment and ionization. © 2000 The American Physical Society

Reply to “Comment on ‘Photodetachment in combined static and dynamic electric fields’”

While distortion of the initial negative-ion state by a strong static electric field can have observable effects, the effect attributed by the authors of the preceding Comment [Phys. Rev. A 64, 037401 (2001)] to a cross term between the detaching laser field and the static field is spurious, an artifact of their procedures. Other points of dispute are also clarified

Information hiding and retrieval in Rydberg wave packets using half-cycle pulses

We demonstrate an information hiding and retrieval scheme with the relative phases between states in a Rydberg wave packet acting as the bits of a data register. We use a terahertz half-cycle pulse (HCP) to transfer phase-encoded information from an optically accessible angular momentum manifold to another manifold which is not directly accessed by our laser pulses, effectively hiding the information from our optical interferometric measurement techniques. A subsequent HCP acting on these wave packets reintroduces the information back into the optically accessible data register manifold which can then be `read' out.Comment: 4 pages, 4 figure

Control of surface plasmon resonances in dielectrically coated proximate gold nanoparticles immobilized on a substrate

We present experimental and theoretical results for the changes in the optical-plasmon resonance of gold-nanoparticle dimers immobilized on a surface when coated with an organic dielectric material. The plasmon band of a nanoparticle dimer shifts to a higher wavelength when the distance between neighboring particles is decreased, and a well-separated second peak appears. This phenomenon is called cross-talk. We find that an organic coating lets cross-talk start at larger separation distances than for uncoated dimers by bridging the gap between immobilized nanoparticles (creating optical clusters). We study this optical clustering effect as a function of the polarization of the applied light, of the inter-particle distance, of the surrounding environment, and of the optical properties of the coating layer. Theoretical discrete-dipole approximation calculations support the experimental absorption spectroscopy results of gold nanoparticles on glass substrates and on optical waveguides

BREXIT Election:Forecasting a Conservative Party Victory through the Pound using ARIMA and Facebook\u27s Prophet

On the 30th October, 2019, the markets watched as British Prime Minister, Boris Johnson, took a massive political gamble to call a general election to break the Withdrawal Agreement stalemate in the House of Commons to “Get BREXIT Done”. The pound had been politically sensitive owing to BREXIT uncertainty. With the polls indicating a Conservative win on 4thDecember, 2019, the margin of victory could be observed through increases in the pound. The outcome of a Conservative party victory would benefit the pound by removing the current market turbulence. We look to provide a short-term forecast of the pound. Our approach focuses on modelling the GBP/EUR and GBP/USD Fx from the inception of BREXIT referendum talks from the 1stJanuary, 2016 to the conclusion of the BREXIT election on the 12thDecember, 2019, focusing on forecasted increases in the pound from the 4thDecember, 2019. We construct two machine learning models in the form of an Auto Regressive Integrated Moving Average (ARIMA) financial time series and an additive regression financial time series using Facebook’s Prophet to investigate the hypothesis that the polls prediction of a Conservative victory could be validated by forecasted increases in the pound. The efficiency of the forecasted models was then tested based on MAPE and MSE criteria. Our results found that the ARIMA and Prophet models were effective and proficient in forecasting the polls prediction on the 4thDecember, 2019 of a Conservative win by validation of forecasted increases in the pound. The ARIMA (4,1,0) model resulted in forecasts with the lowest MAPE and MAE

Технологические решения для строительства разведочной вертикальной скважины глубиной 2550 метров на нефтяном месторождении (Томская область)

Технический проект на сооружения разведочной вертикальной скважины 2550 метров на нефтяном месторождении (Томской области).Technical design for the construction of an exploration vertical well of 2,550 meters in an oil field (Tomsk region)

Does the source of oil price shocks matter for South African stock returns? A structural VAR approach

In this paper, we investigate the dynamic relationship between different oil price shocks and the South African stock market using a sign restriction structural vector autoregression (VAR) approach for the period 1973:01 to 2011:07. The results show that for an oil-importing country like South Africa, stock returns only increase with oil prices when global economic activity improves. In response to oil supply shocks and speculative demand shocks, stock returns and the real price of oil move in opposite directions. The analysis of the variance decomposition shows that the oil supply shock contributes more to the variability in real stock prices. The main conclusion is that different oil price shocks affect stock returns differently and policy makers and investors should always consider the source of the shock before implementing policy and making investment decisions.http://www.elsevier.com/locate/enecohb2016Economic

South African stock return predictability in the context data mining : the role of financial variables and international stock returns

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the t-statistic corresponding to the slope coefficient in a predictive regression model for in-sample predictions, while for the out-of-sample, the MSE-F and the ENC-NEW tests statistics with good power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the critical values of both the in-sample and out-of-sample test statistics. Furthermore, we use a procedure that combines in-sample general-to-specific model selection with out-ofsample tests of predictive ability to further analyse the predictive power of each financial variable. Our results show that, for the in-sample test statistic, only the stock returns for our major trading partners have predictive power at certain short and long run horizons. For the out-of-sample tests, the Treasury bill rate and the term spread together with the stock returns for our major trading partners show predictive power both at short and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data mining. The general-tospecific model shows that valuation ratios contain very useful information that explains the behaviour of stock returns, despite their inability to predict stock return at any horizon. The model also highlights the role of multiple variables in predicting stock returns at medium- to long-run horizons.http://www.elsevier.com/locate/ecmodnf201

Macroeconomic variables and South African stock return predictability

We examine both in-sample and out-of-sample predictability of South African stock return using macroeconomic variables. We base our analysis on a predictive regression framework, using monthly data covering the in-sample period between 1990:01 and 1996:12, and the out-of sample period commencing from 1997:01 to 2010:06. For the in-sample test, we use the t-statistic corresponding to the slope coefficient of the predictive regression model, and for the out-of-sample tests we employ the MSE-F and the ENC-NEW test statistics. When using multiple variables in a predictive regression model, the results become susceptible to data mining. To guard against this, we employ a bootstrap procedure to construct critical values that account for data mining. Further, we use a procedure that combines the in-sample general-to-specific model selection with tests of out-of-sample forecasting ability to examine the significance of each macro variable in explaining the stock returns behaviour. In addition, we use a diffusion index approach by extracting a principal component from the macro variables, and test the predictive power thereof. For the in-sample tests, our results show that different interest rate variables, world oil production growth, as well as, money supply have some predictive power at certain short-horizons. For the out-of-sample forecasts, only interest rates and money supply show short-horizon predictability. Further, the inflation rate shows very strong out-of-sample predictive power from 6-month-ahead horizons. A real time analysis based on a subset of variables that underwent revisions, resulted in deterioration of the predictive power of these variables compared to the fully revised data available for 2010:6. The diffusion index yields statistically significant results for only four specific months over the out-of-sample horizon. When accounting for data mining, both the in-sample and the out-of-sample test statistics for both the individual regressions and the diffusion index become insignificant at all horizons. The general-to-specific model confirms the importance of different interest rate variables in explaining the behaviour of stock returns, despite their inability to predict stock returns, when accounting for data mining.http://www.elsevier.com/locate/ecmodhb2013ff201